# Patent

## Title
Dectection of AMACR cancer markers in urine

## Abstract

The present invention relates to compositions and methods for cancer diagnostics, including but not limited to, cancer markers. In particular, the present invention provides gene expression profiles associated with prostate cancers. The present invention also provides novel markers useful for the diagnosis, characterization, and treatment of prostate cancers. In particular, the present invention provides methods and compositions for the detection of α-methylacyl-CoA racemase (AMACR) in the urine as a marker for prostate cancer detection.

## Background
This application is a Continuation in Part of U.S. patent application Ser. No. 10/210,120 filed Aug. 01, 2002, now U.S. Pat. No. 7,229,774 which claims priority to U.S. Provisional Application Ser. No. 60/309,581 filed Aug, 02, 2001 and U.S. Provisional Application Ser. No. 60/334,468 filed Nov. 15, 2001; each of which is herein incorporated by reference in its entirety.


This invention was made with government support under National Cancer Institute Grant nos. P50CA69568, P50CA90381, and CA97063; Grant No. R01AG21404 awarded by the N. I. H, Grant no. RSG-02-179-MGO awarded by the American Cancer Society, and Grant No. DAMD17-03-1-0105 from ARMY/MRMC. The Government has certain rights in the invention.


FIELD OF THE INVENTION
The present invention relates to compositions and methods for cancer diagnostics, including but not limited to, cancer markers. In particular, the present invention provides gene expression profiles associated with prostate cancers. The present invention also provides novel markers useful for the diagnosis, characterization, and treatment of prostate cancers. In particular, the present invention provides methods and compositions for the use of α-methylacyl-CoA racemase (AMACR) as a marker for prostate cancer detection and prognosis.
BACKGROUND OF THE INVENTION
Afflicting one out of nine men over age 65, prostate cancer (PCA) is a leading cause of male cancer-related death, second only to lung cancer (Abate-Shen and Shen, Genes Dev 14:2410 [2000]; Ruijter et al., Endocr Rev, 20:22 [1999]). The American Cancer Society estimates that about 184,500 American men will be diagnosed with prostate cancer and 39,200 will die in 2001.
Prostate cancer is typically diagnosed with a digital rectal exam and/or prostate specific antigen (PSA) screening. An elevated serum PSA level can indicate the presence of PCA. PSA is used as a marker for prostate cancer because it is secreted only by prostate cells. A healthy prostate will produce a stable amount—typically below 4 nanograms per milliliter, or a PSA reading of “4” or less—whereas cancer cells produce escalating amounts that correspond with the severity of the cancer. A level between 4 and 10 may raise a doctor's suspicion that a patient has prostate cancer, while amounts above 50 may show that the tumor has spread elsewhere in the body.
When PSA or digital tests indicate a strong likelihood that cancer is present, a transrectal ultrasound (TRUS) is used to map the prostate and show any suspicious areas. Biopsies of various sectors of the prostate are used to determine if prostate cancer is present. Treatment options depend on the stage of the cancer. Men with a 10-year life expectancy or less who have a low Gleason number and whose tumor has not spread beyond the prostate are often treated with watchful waiting (no treatment). Treatment options for more aggressive cancers include surgical treatments such as radical prostatectomy (RP), in which the prostate is completely removed (with or without nerve sparing techniques) and radiation, applied through an external beam that directs the dose to the prostate from outside the body or via low-dose radioactive seeds that are implanted within the prostate to kill cancer cells locally. Anti-androgen hormone therapy is also used, alone or in conjunction with surgery or radiation. Hormone therapy uses luteinizing hormone-releasing hormones (LH-RH) analogs, which block the pituitary from producing hormones that stimulate testosterone production. Patients must have injections of LH-RH analogs for the rest of their lives.
While surgical and hormonal treatments are often effective for localized PCA, advanced disease remains essentially incurable. Androgen ablation is the most common therapy for advanced PCA, leading to massive apoptosis of androgen-dependent malignant cells and temporary tumor regression. In most cases, however, the tumor reemerges with a vengeance and can proliferate independent of androgen signals.
The advent of prostate specific antigen (PSA) screening has led to earlier detection of PCA and significantly reduced PCA-associated fatalities. However, the impact of PSA screening on cancer-specific mortality is still unknown pending the results of prospective randomized screening studies (Etzioni et al., J. Natl. Cancer Inst., 91:1033 [1999]; Maattanen et al., Br. J. Cancer 79:1210 [1999]; Schroder et al., J. Natl. Cancer Inst., 90:1817 [1998]). A major limitation of the serum PSA test is a lack of prostate cancer sensitivity and specificity especially in the intermediate range of PSA detection (4-10 ng/ml). Elevated serum PSA levels are often detected in patients with non-malignant conditions such as benign prostatic hyperplasia (BPH) and prostatitis, and provide little information about the aggressiveness of the cancer detected. Coincident with increased serum PSA testing, there has been a dramatic increase in the number of prostate needle biopsies performed (Jacobsen et al., JAMA 274:1445 [1995]). This has resulted in a surge of equivocal prostate needle biopsies (Epstein and Potter J. Urol., 166:402 [2001]). Thus, development of additional serum and tissue biomarkers to supplement PSA screening is needed.
SUMMARY OF THE INVENTION
The present invention relates to compositions and methods for cancer diagnostics, including but not limited to, cancer markers. In particular, the present invention provides gene expression profiles associated with prostate cancers. The present invention also provides novel markers useful for the diagnosis, characterization, and treatment of prostate cancers.
Accordingly, in some embodiments, the present invention provides a method for detecting the presence or absence of α-methylacyl-CoA racemase (AMACR) in urine, comprising providing urine from a subject and a reagent for detecting AMACR in the urine; and contacting the urine with the reagent under conditions such that the reagent detects the presence or absence of AMACR in the urine. In some embodiments, the level of AMACR in the urine is determined and assigned a score between 0 (absence of AMACR) and 4 (highest level AMACR expression) and a minimum threshold level is set to 1. In some embodiments, the presence of AMACR in the urine at a level above the minimum threshold level is indicative of a diagnosis of cancer in the subject. In some embodiments, the cancer is prostate cancer. In some embodiments, the reagent is an antibody (e.g., including, but not limited to, a single chain antibody, an Fab, and an epitope-binding fragment of an antibody). In some embodiments, the reagent comprises a label (e.g., including, but not limited to, a radioactive label, a fluorescent label, a chemiluminescent label, or a bioluminescent label).
The present invention additionally provides a kit for detecting the presence or absence of prostate cancer in a subject, comprising a reagent capable of specifically detecting the presence or absence of AMACR in urine and instructions for using the kit. In some embodiments, the reagent comprises an antibody that specifically binds to an AMACR polypeptide. In some embodiments, the reagent comprises a label (e.g., including, but not limited to, a radioactive label, a fluorescent label, a chemiluminescent label, or a bioluminescent label). In other embodiments, the kit instructions comprise instructions for determining whether the levels of AMACR in the urine are above a minimum threshold value.
The present invention further provides a method for determining risk of prostate cancer progression in a subject, comprising providing a prostate cancer tissue sample from the subject, detecting the presence or absence of AMACR in the sample, and determining that the subject is at increased risk for prostate cancer progression if the AMACR levels are below a maximum threshold value. In some embodiments, the prostate cancer tissue sample is obtained by surgical resection from the subject. In some embodiments, prostate cancer progression comprises prostate specific antigen failure. In other embodiments, prostate cancer progression comprises prostate cancer-specific death. In some embodiments, detection of AMACR comprises detecting an AMACR polypeptide. In some embodiments, detection of AMACR polypeptide comprises exposing the prostate cancer tissue sample to an antibody specific to AMACR polypeptide and detecting the binding of the antibody to the polypeptide. In some embodiments, the antibody is detectably labeled (e.g., including, but not limited to, a radioactive label, a fluorescent label, a chemiluminescent label, or a bioluminescent label). In certain embodiments, the AMACR polypeptide is detected and quantified by a semi-automated image analysis system. In some embodiments, the subject comprises a human subject.



DESCRIPTION OF THE FIGURES
FIG. 1 shows a gene expression profile of prostate cancer samples. FIG. 1a shows a dendrogram describing the relatedness of the samples. FIG. 1b shows a cluster diagram of the samples groups compared against normal adjacent prostate pool as a reference. FIG. 1c shows a cluster diagram of the samples groups compared against commercial prostate pool reference.
FIG. 2 shows functional clusters of genes differentially expressed in prostate cancer.
FIG. 3 shows the expression of hepsin in prostate cancer samples as determined by Northern blot analysis and immunohistochemistry. FIG. 3a shows Northern blot analysis of human hepsin (top) and normalization with GAPDH (bottom). NAT indicates normal adjacent prostate tissue and PCA indicates prostate cancer. FIG. 3b shows tissue microarrays used for hepsin analysis. FIG. 3c shows a histogram of hepsin protein expression by tissue type. Benign prostate hyperplasia (BPH). High-grade intraepithelial neoplasia (HG-PIN). Localized prostate cancer (PCA). Hormone-refractory prostate cancer (MET). FIG. 3d shows Kaplan Meier Analysis.
FIG. 4 shows the expression of pim-1 in prostate cancer samples as determined by Northern blot analysis and immunohistochemistry. FIG. 4a shows a histogram of pim-1 protein expression by tissue type as assessed from 810 tissue microarray elements. High-grade intraepithelial neoplasia (HG-PIN). Localized prostate cancer (PCA). FIG. 4b shows a Kaplan-Meier analysis. The tope line represents patients with strong Pim-1 staining. The bottom line represents patients with absent/weak Pim-1 expression.
FIG. 5 shows a comparison of gene expression profiles for normal adjacent prostate tissue and normal prostate tissue reference.
FIG. 6 shows a focused cluster of prostate cancer related genes.
FIG. 7 shows data for gene selection based on computed t-statistics for the NAP and CP pools.
FIG. 8 shows an overview of genes differentially expressed in prostate cancer.
FIG. 9 describes exemplary accession numbers and sequence ID Numbers for exemplary genes of the present invention.
FIG. 10 provides exemplary sequences of some genes of the present invention.
FIG. 11 an overview of the discovery and characterization of AMACR in prostate cancer utilized in some embodiments of the present invention.
FIG. 12 describes a DNA microanalysis of AMACR expression in prostate cancer.
FIG. 13 describes an analysis of AMACR transcript and protein levels in prostate cancer.
FIG. 14 describes an analysis of AMACR protein expression using prostate cancer tissue microarrays.
FIG. 15 shows relative gene expression of AMACR in several samples.
FIG. 16 shows AMACR protein expression PCA. FIG. 19A shows AMACR protein expression in localized hormone naive PCA. FIG. 19B shows strong AMACR expression in a naive lymph node metastasis. Error bars represent the 95% CI of the mean expression of the primary naive prostate cancer and corresponding lymph node metastases.
FIG. 17 shows the hormonal effect on AMACR expression. FIG. 17A shows PCA demonstrating strong hormonal effect due to anti-androgen treatment. FIG. 17B shows Western Blot analysis representing the baseline AMACR expression in different prostate cell lines (Left) and Western Blot analysis of LNCaP cells for AMACR and PSA expression after treatment with an androgen or an anti-androgen for 24 h and 48 hours (right).
FIG. 18 shows AMACR over-expression in multiple tumors. AMACR protein expression was evaluated by immunohistochemistry on a multi-tumor and a breast cancer tissue microarray. Percentage of cases with positive staining (moderate and strong staining intensity) is summarized on the Y-axis. The left bar represents negative or weak staining and the right bar represents moderate or strong staining.
FIG. 19 shows the results of laser capture microdissection (LCM) and RT-PCR amplification of AMACR in prostate cancer. LCM was used to isolate pure prostate cancer and benign glands and AMACR gene expression was characterized by RT-PCR in 2 radical prostatectomies. A constitutively expressed gene, GAPDH, was used as quantitative control of input mRNA. AMACR expression is barely detectable in benign glands, and is elevated in prostate cancer.
FIG. 20 describes the identification and validation of EZH2 over-expression in metastatic prostate cancer. FIG. 20a shows a cluster diagram depicting genes that molecularly distinguish metastatic prostate cancer (MET) from clinically localized prostate cancer (PCA). FIG. 20b shows a DNA microarray analysis of prostate cancer that reveals upregulation of EZH2 in metastatic prostate cancer. FIG. 20c shows RT-PCR analysis of the EZH2 transcript in prostate tissue and cell lines. FIG. 20d shows increased expression of EZH2 protein in prostate cancer.
FIG. 21 shows that EZH2 protein levels correlate with the lethal progression and aggressiveness of prostate cancer. FIG. 21a shows tissue microarray analysis of EZH2 expression. The mean EZH2 protein expression for the indicated prostate tissues is summarized using error bars with 95% confidence intervals. FIG. 21b shows a Kaplan-Meier analysis demonstrating that patients with clinically localized prostate cancers that have high EZH2 expression (Moderate/Strong staining) have a greater risk for prostate cancer recurrence after prostatectomy (log rank test, p=0.03).
FIG. 22 shows the role of EZH2 in prostate cell proliferation. FIG. 22a shows an immunoblot analysis of RNA interference using siRNA duplexes targeting the EZH2 sequence in prostate cells. FIG. 22b shows that RNA interference of EZH2 decreases cell proliferation as assessed by cell counting assay. FIG. 22c shows that RNA interference of EZH2 inhibits cell proliferation as assessed by WST assay. FIG. 22d shows that RNA interference of EZH2 induces G2/M arrest of prostate cells.
FIG. 23 shows that EZH2 functions as a transcriptional repressor in prostate cells. FIG. 23a shows a schematic diagram of EZH2 constructs used in transfection/transcriptome analysis. ER, modified ligand binding domain of estrogen receptor. H-1 and H-2, homology domains 1 and 2 which share similarity between EZH2 and E(z). CYS, cysteine-rich domain. SET, SET domain. TAG, myc-epitope tag. NLS, nuclear localization signal. FIG. 23b shows confirmation of expression of EZH2 constructs used in a. An anti-myc antibody was used. FIG. 23c shows a cluster diagram of genes that are significantly repressed by EZH2 overexpression. FIG. 23d shows SAM analysis of gene expression profiles of EZH2 transfected cells compared against EZH2 SET transfected cells. FIG. 23e shows a model for potential functional interactions of EZH2 as elucidated by transcriptome analysis and placed in the context of previously reported interactions. +, induction. −, repression.
FIG. 24 shows the detection of AMACR in PCA cell lines.
FIG. 25 shows the detection of AMACR protein in serum by quantitation of microarray data.
FIG. 26 shows an immunoblot analysis of serum from patients with either negative or positive PSA antigen.
FIG. 27 shows an immunoblot analysis of the presence of AMACR in urine samples from patients with bladder cancer (females) or bladder cancer and increased PSA (males).
FIG. 28 shows representative data of a humoral response by protein microarray analysis.
FIG. 29 shows immunoblot analysis of the humoral response of AMACR. FIG. 29a shows an immunoblot analysis of the humoral response to AMACR. FIG. 29b shows a control experiment where the humoral response was blocked.
FIG. 30 shows GP73 Transcript levels in prostate cancer. FIG. 30a shows the level of GP73 in individual samples after microarray analysis. FIG. 30b shows the result of GP73 transcripts determined by DNA microarray analysis from 76 prostate samples grouped according to sample type and averaged.
FIG. 31 shows that GP73 protein is upregulated in prostate cancer. FIG. 31a shows Western blot analysis of GP73 protein in prostate cancer. FIG. 31b shows an immunoblot analysis of the Golgi resident protein Golgin 97.
FIG. 32 shows immunoblot analysis of normal and prostate cancer epithelial cells.
FIG. 33 shows the cDNA expression of select annexin gene family members.
FIG. 34 shows a heat map representation of annexin family gene expression across four prostate cancer profiling studies. Over and under expression at the transcript level are represented by shades of red and green, respectively. Gray shading indicates that insufficient data was available. Each square represents an individual tissue sample.
FIG. 35 shows the expression of CtBP proteins in PCA specimens.
FIG. 36 shows tissue microarray analysis of CtBP in prostate cancer that suggests mis-localization during prostate cancer progression.
FIG. 37 shows the sub-cellular fractionation of LNCaP cells.
FIG. 38 shows a Kaplan-Meier Analysis of prostate cancer tissue microarray data.
FIG. 39 shows clinical and pathology data from patients with biopsy-proven clinically localized prostate cancer.
FIG. 40 shows evaluation of AMACR protein levels in serum, plasma and prostatic excretions. FIG. 40A shows Western blot analysis of sera from control subjects and prostate cancer patients probed with anti-AMACR antibody. FIG. 40B shows immunoblot analysis of plasma from prostate cancer patients and a control subject (CON). FIG. 40C shows immunoblot analysis of prostatic excretions from prostate cancer patients.
FIG. 41 shows data for the use of AMACR as a urine biomarker for the detection of prostate cancer. FIG. 41A shows concentrated urine samples from control subjects and prostate cancer patients immunoblotted with anti-AMACR antibody. FIG. 41B shows specificity of the AMACR immunoreactive band. FIG. 41C shows categorization of urine samples based on AMACR reactivity scores with 4 being the strongest reactivity and 0 being no reactivity. FIG. 41D shows a receiver operating characteristic (ROC) curve for detection of AMACR in urine as assessed by immunoblot analysis (n=110 sera from clinically localized prostate cancer patients and n=116 control subjects).
FIG. 42 shows AMACR expression analysis and correlation of low AMACR expression with higher risk of PSA biochemical recurrence. FIG. 42A shows two histograms demonstrating the distribution of scores for the raw (left, original scale) and normalized AMACR analysis. FIG. 42B shows that lower AMACR intensity was associated with prostate cancer progression as determined by PSA biochemical failure.
FIG. 43A shows AMACR levels and prostate cancer specific survival in a watchful waiting cohort with up to 20 years of clinical follow up using a cutpoint of 0.18. FIG. 43B shows lower AMACR expression in the 48 cases with a PSA biochemical failure versus the patients without disease progression (Error bars with 95% CI). FIG. 43C shows a Kaplan-Meier curve for patients whose tumors had higher and lower AMACR protein expression using the 0.18 cutpoint.
FIG. 44 illustrates the differing AMACR expression levels used as cutoff points for PSA biochemical failure versus cancer specific death.



GENERAL DESCRIPTION
Exploring the molecular circuitry that differentiates indolent PCA from aggressive PCA has the potential to lead to the discovery of prognostic markers and novel therapeutic targets. Insight into the mechanisms of prostate carcinogenesis is also gleaned by such a global molecular approach. Similar to breast cancer (Lopez-Otin and Diamandis, Endor. Rev., 19:365 [1998]), PCA develops in a complex milieu of genetic and environmental factors in which steroid hormone signaling plays a central role. The primary precursor lesion of PCA, high-grade prostatic intraepithelial neoplasia (HG-PIN), has several characteristics similar to other early invasive carcinomas (i.e., chromosomal abnormalities and cytologic features). Loss of specific chromosomal regions (e.g., 8p21, 10q, 13q, 17p) along with losses and mutations of tumor suppressor genes such as Nkx3.1, PTEN, Rb, and p53 have been implicated in the initiation and progression of prostate cancer (Abate-Shen and Shen, supra). With the emergence of global profiling strategies, a systematic analysis of genes involved in PCA is now possible. DNA microarray technology is revolutionizing the way fundamental biological questions are addressed in the post-genomic era. Rather than the traditional approach of focusing on one gene at a time, genomic-scale methodologies allow for a global perspective to be achieved. The power of this approach lies in its ability to comparatively analyze genome-wide patterns of mRNA expression (Brown and Botstein, Nat. Gent., 21:33 [1999]). Obtaining large-scale gene expression profiles of tumors allows for the identification of subsets of genes that function as prognostic disease markers or biologic predictors of therapeutic response (Emmert-Buck et al., Am. J. Pathol., 156:1109 [2000]). Golub et al. used DNA arrays in the molecular classification of acute leukemias (Golub et al., Science 286:531 [1999], demonstrating the feasibility of using microarrays for identifying new cancer classes (class discovery) and for assigning tumors to known classes (class prediction). Using a similar approach, Alizadeh et al. showed that diffuse large B-cell lymphoma could be dissected into two prognostic categories by gene expression profiling (Alizadeh et al., Nature 403:503 [2000]). They provided evidence that lymphomas possessing a gene expression signature characteristic of germinal center B cells had a more favorable prognosis than those expressing genes characteristic of activated peripheral B-cells. Similar large-scale classifications of breast cancer and melanoma have been undertaken, and as with the other studies, molecular classification was the primary focus (Alizadeh et al., supra).
Accordingly, the present invention provides an analysis of gene expression profiles in benign and malignant prostate tissue. Three candidate genes, AMACR, hepsin and pim-1, identified by DNA microarray analysis of PCA, were characterized at the protein level using PCA tissue microarrays. Analysis of the differential gene expression profiles of normal and neoplastic prostate has led to the identification of a select set of genes that define a molecular signature for PCA. The expression profiling experiments of the present invention demonstrate a role for multiple, collaborative gene expression alterations which ultimately manifest as the neoplastic phenotype. By making direct comparative hybridizations of normal and neoplastic tissues, genes that molecularly distinguish benign tissue from malignant are identified.
α-Methylacyl-CoA Racemase (AMACR) is an enzyme that plays an important role in bile acid biosynthesis and β-oxidation of branched-chain fatty acids (Ferdinandusse et al., J. Lipid Res., 41:1890 [2000]; Kotti et al., J. Biol. Chem., 275:20887 [2000]). Mutations of the AMACR gene have been shown to cause adult-onset sensory motor neuropathy (Ferdinandusse et al., Nat. Genet., 24:188 [2000]). In diagnostically challenging prostate biopsy cases, pathologists often employ the basal cell markers 34βE12 or p63, which stain the basal cell layer of benign glands that is not present in malignant glands. Thus, in many biopsy specimens, the pathologist must rely on absence of staining to make the final diagnosis of prostate cancer. Experiments conducted during the development of the present invention identified AMACR as a marker expressed in cancerous biopsy tissue. Thus, the clinical utility of AMACR in prostate needle biopsies is large. For example, at the University of Michigan Medical Center, approximately 400 prostate needle biopsies are performed per year and approximately 20% require the use of a basal-cell specific marker to evaluate difficult lesions, characterized by a small amount of atypical glands. Accordingly, it is contemplated that in combination with basal cell specific markers, such as 34βE12 or p63, screening for AMACR expression by the methods of the present invention results in fewer cases diagnosed as “atypical without a definitive diagnosis.”
Identification of the over-expression of AMACR in prostate cancer has clinical utility beyond diagnostic uses. Experiments conducted during the development of the present invention revealed that the only non-cancerous tissue to expresses significant levels of AMACR protein is the human liver. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism in not necessary to practice the present invention. Nonetheless, it is contemplated that AMACR activity is required for prostate cancer growth and by virtue of its specificity serves as a therapeutic target and a diagnostic marker.
Experiments conducted during the course of development of the present invention demonstrated that AMACR is present in the serum of prostate cancer patients. In addition, a humoral response to AMACR was identified based on the presence of antibodies to AMACR in the serum of prostate cancer patients.
The presence of AMACR was detected in very few prostate cancer patients' serum when compared to prostatic excretions obtained ex vivo from prostate cancer patients. Urine samples from prostate cancer patients were thus analyzed for the presence of AMACR (see Example 16). AMACR was detectable with high specificity and sensitivity in a large percentage of urine samples from prostate cancer patients, and the AMACR reactivity in the urine was not associated with PSA levels at time of diagnosis, Gleason score, pathologic stage, or prostate weight. Therefore, the present invention has utility for the non-invasive diagnosis or screening of prostate cancer.
Additional experiments conducted during the course of development of the present invention investigated AMACR expression in different groups of prostate cancer, including the aspect of neo-adjuvant hormonal withdrawal in localized disease. AMACR expression was found to be hormone independent in cell culture experiments. PSA, a gene known to be regulated by androgens, demonstrated hormone related alterations in expression under the same conditions. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that these findings provide evidence that AMACR is not regulated by the androgen pathway. It is further contemplated that the decreased AMACR expression in hormone refractory tissue allows the use of AMACR as a biomarker for hormone resistance. It is also contemplated that, given the fact that hormone treatment in the mean of hormonal withdrawal did not affect AMACR expression in the cell culture, that some other mechanism than the androgen pathway is responsible for AMACR downregulation in the integrity of cancer tissue.
The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that, alternatively, AMACR is over expressed in the development of cancer, perhaps playing an important role in providing energy for the neoplastic cells. However, as the tumors become de-differentiated, they no longer require these sources of energy. It is contemplated that poorly differentiated tumors may take over other pathways to accomplish this same activity of branched fatty acid oxidation. There is no association with the proliferative rate of the tumor cells and AMACR expression.
Further experiments conducted during the course of development of the present invention showed that decreased AMACR expression in localized prostate cancer is associated with biochemical recurrence and cancer specific death. Example 17 describes the analysis in detail. Briefly, a quantitative AMACR protein expression test was developed to determine prostate cancer risk progression for patients with clinically localized prostate cancer treated by radical prostatectomy. The cohort of men was followed long-term after prostatectomy, with cancer specific death or biochemical failure as the study endpoint. Therefore, the present invention has utility for the stratification of patients into risk groups for biochemical failure or prostate cancer specific death.
AMACR expression was also examined in other cancers. Examination of other tumors demonstrated that colon cancer has the highest AMACR expression. As colorectal cancers are not known to be hormonally regulated, the fact that de-differentiation and decreased AMACR expression were correlated in PCA further supports the hypothesis that de-differentiation leads to decreased AMACR expression in the hormone refractory metastatic PCA. Hormone treatment is also a front line therapy in metastatic prostate cancer but is known to loose efficacy, selecting out hormone insensitive clones. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that this phenomenon explains the observation that strong hormone treatment effect is consistent with decreased AMACR expression due to selection of potentially more de-differentiated cells.
The AMACR gene product is an enzyme, which plays an important role in bile acid biosynthesis and beta-oxidation of branched-chain fatty acids (Kotti et al., J. Biol. Chem. 275:20887 [2000]; Ferdinandusse et al., J Lipid Res 42:137 [2001]). AMACR over expression occurs in tumors with a high percentage of lipids such as PCA and colorectal cancer. The relationship between fatty acid consumption and cancer is a controversial subject in the development of PCA and colorectal cancer (Moyad, Curr Opin Urol 11:457 [2001]; Willett, Oncologist 5:393 [2000]). An essential role for AMACR in the oxidation of bile acid intermediates has been demonstrated. AMACR encodes an enzyme which catalyzes the racemization of alpha-methyl branched carboxylic coenzyme A thioesters and is localized in peroxisomes and mitochondria (Schmitz et al., Eur. J. Biochem. 231:815 [1995]). The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that, as AMACR is involved in the metabolism of lipids, that this leads to alterations in the oxidant balance of a cell. It is further contemplated that these changes are associated with DNA damage, malignant transformation, and other parameters of cell disturbance.
Additional experiments conducted during the course of development of the present invention demonstrated that AMACR mRNA and protein product are over expressed in a number of adenocarcinomas, including colorectal, prostate, breast, and ovarian and melanoma. Adenocarcinoma from the colorectum and prostate demonstrated consistent AMACR over expression (92% and 83% of tumor, respectively). Thus, AMACR is of use in the diagnosis of colonic neoplasia. For example, in some embodiments of the present invention, AMACR is used in the diagnosis of dysplasia. Specifically, in the setting of inflammatory bowel disease (IBD), where the identification of dysplasia may be diagnostically challenging, one evaluates putative lesions for their AMACR protein expression intensity. In some embodiments, this is performed in conjunction with the analysis of the adenomatous polyposis coli gene, since mutations in this gene are also believed to occur early in the development of colorectal neoplasia (Kinzler and Vogelstein, Cell 87:159 [1996]; Tsao and Shibata, Am J Pathol 145:531 [1994]).
Colonic adenomas (Kinzler and Vogelstein, supra; Tsao and Shibata, supra) and high-grade PIN (McNeal and Bostwick, Hum Pathol 17:64 [1986]; McNeal et al., Lancet 1:60 [1986]) are well known precursors of invasive colonic and prostate cancer, respectively. Experiments conducted during the course of development of the present invention demonstrated that AMACR is over expressed in colorectal adenomas (75%) and high-grade PIN (64%). Further supporting AMACR expression in early neoplastic lesions was the presence of focal AMACR expression in some atrophic prostate lesions. Some atrophic lesions (i.e., proliferative inflammatory atrophy and postatrophic hyperplasia) have recently been recognized as proliferative in nature with molecular alterations suggestive of early neoplastic changes (De Marzo et al., Am. J. Pathol. 155:1985 [1999]; Shah et al., Am. J. Pathol. 158:1767 [2001]). Some morphologically benign prostate glands were also observed to have focal moderate AMACR staining. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that AMACR may have a role in the early steps of cancer development.
Several cancers that are associated with AMACR over expression, including colorectal, prostate and breast cancer, have been linked to high-fat diet. The exact mechanism how high-fat diet contributes to tumorigenesis in these organ systems is unknown, but emerging evidence suggest that peroxisome proliferator activated receptor (PPAR) mediated pathway plays a critical role (Debril et al., J. Mol. Med. 79:30 [2001]). Diet fatty acids have been shown to function as peroxisome proliferators and bind to and activate PPARs (Zomer et al., J. Lipid Res. 41:1801 [2000]), a family of nuclear receptor transcriptional factors. Activation of PPAR mediated pathways in turn control cell proliferation and differentiation. In addition, it can also alter the cellular oxidant balance (Yeldandi et al., Mutat. Res. 448:159 [2000]). The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that these effects act in concert to contribute to the tumorigenesis of several cancers. This hypothesis is supported by the findings that peroxisome proliferators, when given to mice, enhance the development colon adenomatous polyps in mice (Saez et al., Nat. Med. 4:1058 [1998]). In addition, PPARs are expressed in several prostate cancer cell lines and their ligands, and peroxisome proliferators, when added to culture, affect the growth of these cell lines (Shappell et al., Cancer Res. 61:497 [2001]; Mueller et al., PNAS 97:10990 [2000]). A phase II clinical trial also showed that troglitazone, a PPARγ activator, could stabilize PSA level in patients with prostate cancer (Kubota et al., Cancer Res. 58:3344 [1998]; Hisatake et al., Cancer Res. 60:5494 [2000]).
AMACR is an involved in the β-oxidation of pristanic acid (Ferdinandusse et al., J. Lipid. Res. 41:1890 [2000]). Pristanic acid can function as a PPAR α activator and promote cell growth (Zomer et al., J. Lipid Res. 41:1801 [2000]). The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that hyperfunctioning of β-oxidation pathway leads to exhaustion of reducing molecules and alters the cellular oxidant status (Yeldandi et al., Mutat. Res. 448:159 [2000]).
The present invention further provides methods of targeting AMACR as a therapeutic target in cancer treatment. Over expressed in high percentage of colorectal, prostate, breast and melanoma, but not in adjacent normal tissues, AMACR is targeted using antibody or enzyme inhibitors. Toxicity is expected not to be a major concern because individuals with congenital absence of this enzyme have no or insignificant clinical manifestations (Clayton et al., Biochem. Soc. Trans. 29:298 [2001]).
Annexins are a group of structurally related calcium-binding proteins, which have a domain that binds to phospholipids and an amino terminal domain that determines specificity (Smith et al., Trends. Genet. 10:241 [1994]; Mailliard et al., J. Biol. Chem. 271:719 [1996]). The annexins are involved in regulation of membrane trafficking, cellular adhesion and possible tumorigenesis. Experiments conducted during the course of development of the present invention used cDNA microarrays to study the expression patterns of multiple annexin family members in a wide range of prostate tissue samples in order to determine their role in PCA progression. Meta-analysis of gene expression data was employed to help further validate the cDNA expression array findings. Finally, high-density tissue microarrays were used to assess annexin protein expression levels by immunohistochemistry.
Eight annexins were evaluated for their mRNA expression levels in benign prostatic tissue, localized hormone naïve PCA and metastatic hormone refractory PCA samples. Five annexins (1,2,4,7, and 11) demonstrated a progressive down regulation at the transcript level going from benign prostatic tissue to localized PCA to hormone refractory PCA. In order to validate the cDNA expression array finding of these 5 annexin family members, a meta-analysis was performed, which confirmed that when looking across 4 studies where at least two studies reported results, annexin 1,2,4, and 6 were significantly down regulated in localized PCA samples when compared to benign prostatic tissue. Therefore the meta-analysis confirmed results on annexin 1, 2, and 4. In these examples, summary statistics across all datasets found these annexins to be significantly down regulated at the cDNA level. However, not all of the 4 studies had significant down-regulation. Annexin 4, for example, was significantly down regulated in two of four studies but the resultant summary statistic, which also takes into account the number of samples evaluated, was statistically significant. Annexins 7,8, and 13 were not found to be significantly under expressed. As demonstrated in FIG. 1, annexin 7 does decrease significantly when comparing localized PCA and metastatic PCA.
The protein expression levels of all above five annexins tested were statistically significantly decreased in hormone refractory PCA samples when compared to either localized PCA or benign prostate tissue. Four of 5 annexins also demonstrated a decrease in protein expression in clinically localized PCA as compared to benign prostate tissue. However, in none of these cases was the protein expression found to be significantly decreased. This second validation method at the protein level confirmed the cDNA expression array data for annexin 1,2,4, 7, and 11.
Based on gene expression array data described herein, localized PCA cells down regulate their mRNA levels of annexins but maintained the corresponding protein expression levels. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that post-translational alteration may compensate for decrease mRNA, producing enough protein to maintain levels seen with benign samples. Since annexins play an important role in maintaining cellular adhesion, once the cells eventually lose this ability, tumor progression may occur. Therefore, as one might anticipate, annexin expression levels decreased significantly in the advanced hormone refractory PCA samples. This was confirmed at the protein level by significant decreases as demonstrated by immunohistochemistry.
A sequential down-regulation of annexins in both transcriptional and translational levels in metastatic PCA samples was observed. Annexin I, also called lipocortin, has been described as a phospholipase A2 inhibitor, and served as a substrate of epidermal growth factor receptor (Pepinsky et al., Nature 321:81 [1986]; Wallner et al., Nature 320:77 [1986]). The significant reduction of protein level has been shown in esophageal and prostate tumor cells (Paweletz et al., Cancer Res. 60:6293 [2000]). Annexin 2, also called p36, appears an efficient substrate of protein kinase C and Src pp60 (Hubaishy et al., Biochemistry 34:14527 [1995]). Annexin 4, called endonexin, regulates C1-flux by mediating calmodulin kinase II (CaMKII) activity (Chan et al., J. Biol. Chem. 269:32464 [1994]). Annexin 7, synexin, is involved in Duchenne's muscular dystrophy (Selbert et al. Exp. Cell. Res. 222:199 [1996]). Its gene is located on human chromosome 10q21, and its protein expression was decreased in hormone refractory tumor cells. In conclusion, the results of experiments conducted during the course of development of the present invention suggest that down regulation of several annexin family members may play a role in the development of the lethal PCA phenotype.
Additional experiments conducted during the course of development of the present invention identified additional markers that exhibited altered (e.g., increased or decreased) expression in prostate cancer. Additional markers include, but are not limited to, EZH2, Annexins 1, 2, 4, 7, and 11, CTBP 1 and 2, GP73, ABCC5 (MDR5), ASNS, TOP2A, and Vav2. In particular, EZH2 was identified as a marker that was overexpressed in prostate cancer, and in particular, in metastatic prostate cancer. EZH2 was further identified as being correlated with clinical failure (e.g., increased PSA levels). In addition, siRNA inhibition of EZH2 resulted in a decrease in cell proliferation of a prostate cancer cell line.
The present invention thus identifies markers and targets for diagnostic and therapeutic agents in a variety of cancers.
Definitions
To facilitate an understanding of the present invention, a number of terms and phrases are defined below:
The term “epitope” as used herein refers to that portion of an antigen that makes contact with a particular antibody.
When a protein or fragment of a protein is used to immunize a host animal, numerous regions of the protein may induce the production of antibodies which bind specifically to a given region or three-dimensional structure on the protein; these regions or structures are referred to as “antigenic determinants”. An antigenic determinant may compete with the intact antigen (i.e., the “immunogen” used to elicit the immune response) for binding to an antibody.
The terms “specific binding” or “specifically binding” when used in reference to the interaction of an antibody and a protein or peptide means that the interaction is dependent upon the presence of a particular structure (i.e., the antigenic determinant or epitope) on the protein; in other words the antibody is recognizing and binding to a specific protein structure rather than to proteins in general. For example, if an antibody is specific for epitope “A,” the presence of a protein containing epitope A (or free, unlabelled A) in a reaction containing labeled “A” and the antibody will reduce the amount of labeled A bound to the antibody.
As used herein, the terms “non-specific binding” and “background binding” when used in reference to the interaction of an antibody and a protein or peptide refer to an interaction that is not dependent on the presence of a particular structure (i.e., the antibody is binding to proteins in general rather that a particular structure such as an epitope).
The term “label” as used herein refers to any atom or molecule that can be used to provide a detectable (preferably quantifiable) effect, and that can be attached to a nucleic acid or protein. Labels include but are not limited to dyes; radiolabels such as 32P; binding moieties such as biotin; haptens such as digoxgenin; luminogenic, phosphorescent or fluorogenic moieties; mass tags; and fluorescent dyes alone or in combination with moieties that can suppress or shift emission spectra by fluorescence resonance energy transfer (FRET). Labels may provide signals detectable by fluorescence, radioactivity, colorimetry, gravimetry, X-ray diffraction or absorption, magnetism, enzymatic activity, characteristics of mass or behavior affected by mass (e.g., MALDI time-of-flight mass spectrometry), and the like. A label may be a charged moiety (positive or negative charge) or alternatively, may be charge neutral. Labels can include or consist of nucleic acid or protein sequence, so long as the sequence comprising the label is detectable.
As used herein, the term “subject” refers to any animal (e.g., a mammal), including, but not limited to, humans, non-human primates, rodents, and the like, which is to be the recipient of a particular treatment. Typically, the terms “subject” and “patient” are used interchangeably herein in reference to a human subject.
As used herein, the term “subject suspected of having cancer” refers to a subject that presents one or more symptoms indicative of a cancer (e.g., a noticeable lump or mass) or is being screened for a cancer (e.g., during a routine physical). A subject suspected of having cancer may also have one or more risk factors. A subject suspected of having cancer has generally not been tested for cancer. However, a “subject suspected of having cancer” encompasses an individual who has received an initial diagnosis (e.g., a CT scan showing a mass or increased PSA level) but for whom the stage of cancer is not known. The term further includes people who once had cancer (e.g., an individual in remission).
As used herein, the term “subject at risk for cancer” refers to a subject with one or more risk factors for developing a specific cancer. Risk factors include, but are not limited to, gender, age, genetic predisposition, environmental expose, previous incidents of cancer, preexisting non-cancer diseases, and lifestyle.
As used herein, the term “characterizing cancer in subject” refers to the identification of one or more properties of a cancer sample in a subject, including but not limited to, the presence of benign, pre-cancerous or cancerous tissue, the stage of the cancer, and the subject's prognosis. Cancers may be characterized by the identification of the expression of one or more cancer marker genes, including but not limited to, the cancer markers disclosed herein.
As used herein, the term “characterizing prostate tissue in a subject” refers to the identification of one or more properties of a prostate tissue sample (e.g., including but not limited to, the presence of cancerous tissue, the presence of pre-cancerous tissue that is likely to become cancerous, and the presence of cancerous tissue that is likely to metastasize). In some embodiments, tissues are characterized by the identification of the expression of one or more cancer marker genes, including but not limited to, the cancer markers disclosed herein.
As used herein, the term “prostate cancer tissue sample” refers to a sample consisting substantially (e.g., greater than 80%, preferably greater than 90%, and even more preferably greater than 99%) of prostate cells (e.g., that have been classified as cancerous by a pathologist or other qualified individual or instrument). Generally, the prostate is removed from a subject by surgery (e.g., radical prostatectomy) and a section of the prostate suspected of comprising cancerous cells is analyzed. Example 17 illustrates the detection of AMACR in prostate cancer tissue samples.
As used herein, the term “cancer marker genes” refers to a gene whose expression level, alone or in combination with other genes, is correlated with cancer or prognosis of cancer. The correlation may relate to either an increased or decreased expression of the gene. For example, the expression of the gene may be indicative of cancer, or lack of expression of the gene may be correlated with poor prognosis in a cancer patient. Cancer marker expression may be characterized using any suitable method, including but not limited to, those described in illustrative Examples 1-15 below.
As used herein, the term “a reagent that specifically detects expression levels” refers to reagents used to detect the expression of one or more genes (e.g., including but not limited to, the cancer markers of the present invention). Examples of suitable reagents include but are not limited to, nucleic acid probes capable of specifically hybridizing to the gene of interest, PCR primers capable of specifically amplifying the gene of interest, and antibodies capable of specifically binding to proteins expressed by the gene of interest. Other non-limiting examples can be found in the description and examples below.
As used herein, the term “detecting a decreased or increased expression relative to non-cancerous prostate control” refers to measuring the level of expression of a gene (e.g., the level of mRNA or protein) relative to the level in a non-cancerous prostate control sample. Gene expression can be measured using any suitable method, including but not limited to, those described herein.
As used herein, the term “threshold level” refers to a cutoff point or level of gene (e.g., AMACR) expression that has been established based on experimental or clinical data. In some embodiments, “threshold level” refers to the amount of a gene product (e.g., mRNA or protein) in a sample or a calculated numerical value based on multiple variables. The threshold level is a cutoff point above or below which certain characteristics or outcomes (e.g., cancer diagnosis, progression or death) are likely to occur. Generally, values above or below a defined threshold level correlate with some other characteristic or outcome, such as increased risk of death. Example 17 describes in detail the establishment of threshold levels of AMACR expression in prostate cancer tissue that correlate with risk of prostate cancer progression. Two end points of cancer progression, prostate specific antigen failure and prostate cancer-specific death, were correlated with threshold levels of normalized AMACR from multiple samples. This correlation allows distinct threshold values of AMACR in the prostate cancer samples to be used in predicting risk of prostate cancer progression. Threshold levels can be determined using any suitable method (e.g., statistical analysis of a group of samples with a known outcome). In some embodiments, threshold values are used by clinicians in the diagnosis and characterization of prostate cancer in a subject.
As used herein, the term “detecting a change in gene expression (e.g., hepsin, pim-1, EZH2, or AMACR) in said prostate cell sample in the presence of said test compound relative to the absence of said test compound” refers to measuring an altered level of expression (e.g., increased or decreased) in the presence of a test compound relative to the absence of the test compound. Gene expression can be measured using any suitable method, including but not limited to, those described in Examples 1-17 below.
As used herein, the term “reactivity score” refers to a value (e.g., numerical value) representing the amount of a given substance in a sample. In some embodiments, the sample of interest (e.g., urine) is contacted (“reacted”) with a reagent that allows for determination of the quantity of the substance of interest (e.g., the level of mRNA or protein) present in the sample. The amount of the given substance in the sample is compared to amounts of the substance in positive and negative control samples (e.g., samples with high reactivity and non-reactivity to the reagent), and a score is assigned to the sample based on that comparison. The reactivity score of the substance (e.g., protein) can be determined by quantitation with an instrument or by visual inspection; for example, an individual can visually examine band intensities on a gel or blot that contains the substance of interest that has been hybridized with labeled DNA, RNA, antibody or other detectable marker. The more substance of interest in the sample, the higher the reactivity score.
As used herein, the term “instructions for using said kit for detecting cancer in said subject” includes instructions for using the reagents contained in the kit for the detection and characterization of cancer in a sample from a subject. In some embodiments, the instructions further comprise the statement of intended use required by the U.S. Food and Drug Administration (FDA) in labeling in vitro diagnostic products. The FDA classifies in vitro diagnostics as medical devices and requires that they be approved through the 510(k) procedure. Information required in an application under 510(k) includes: 1) The in vitro diagnostic product name, including the trade or proprietary name, the common or usual name, and the classification name of the device; 2) The intended use of the product; 3) The establishment registration number, if applicable, of the owner or operator submitting the 510(k) submission; the class in which the in vitro diagnostic product was placed under section 513 of the FD&C Act, if known, its appropriate panel, or, if the owner or operator determines that the device has not been classified under such section, a statement of that determination and the basis for the determination that the in vitro diagnostic product is not so classified; 4) Proposed labels, labeling and advertisements sufficient to describe the in vitro diagnostic product, its intended use, and directions for use. Where applicable, photographs or engineering drawings should be supplied; 5) A statement indicating that the device is similar to and/or different from other in vitro diagnostic products of comparable type in commercial distribution in the U.S., accompanied by data to support the statement; 6) A 510(k) summary of the safety and effectiveness data upon which the substantial equivalence determination is based; or a statement that the 510(k) safety and effectiveness information supporting the FDA finding of substantial equivalence will be made available to any person within 30 days of a written request; 7) A statement that the submitter believes, to the best of their knowledge, that all data and information submitted in the premarket notification are truthful and accurate and that no material fact has been omitted; 8) Any additional information regarding the in vitro diagnostic product requested that is necessary for the FDA to make a substantial equivalency determination. Additional information is available at the Internet web page of the U.S. FDA.
As used herein, the term “prostate cancer expression profile map” refers to a presentation of expression levels of genes in a particular type of prostate tissue (e.g., primary, metastatic, and pre-cancerous prostate tissues). The map may be presented as a graphical representation (e.g., on paper or on a computer screen), a physical representation (e.g., a gel or array) or a digital representation stored in computer memory. Each map corresponds to a particular type of prostate tissue (e.g., primary, metastatic, and pre-cancerous) and thus provides a template for comparison to a patient sample. In preferred embodiments, maps are generated from pooled samples comprising tissue samples from a plurality of patients with the same type of tissue.
As used herein, the terms “computer memory” and “computer memory device” refer to any storage media readable by a computer processor. Examples of computer memory include, but are not limited to, RAM, ROM, computer chips, digital video disc (DVDs), compact discs (CDs), hard disk drives (HDD), and magnetic tape.
As used herein, the term “computer readable medium” refers to any device or system for storing and providing information (e.g., data and instructions) to a computer processor. Examples of computer readable media include, but are not limited to, DVDs, CDs, hard disk drives, magnetic tape and servers for streaming media over networks.
As used herein, the terms “processor” and “central processing unit” or “CPU” are used interchangeably and refer to a device that is able to read a program from a computer memory (e.g., ROM or other computer memory) and perform a set of steps according to the program.
As used herein, the term “stage of cancer” refers to a qualitative or quantitative assessment of the level of advancement of a cancer. Criteria used to determine the stage of a cancer include, but are not limited to, the size of the tumor, whether the tumor has spread to other parts of the body and where the cancer has spread (e.g., within the same organ or region of the body or to another organ).
As used herein, the term “providing a prognosis” refers to providing information regarding the impact of the presence of cancer (e.g., as determined by the diagnostic methods of the present invention) on a subject's future health (e.g., expected morbidity or mortality, the likelihood of getting cancer, and the risk of metastasis).
As used herein, the terms “prostate specific antigen failure” and “biochemical failure” refer to the development of high prostate specific antigen levels in a patient following prostate cancer therapy (e.g., surgery). See Examples 3 and 4 for examples of how prostate specific antigen failure is determined. As used herein, the term “risk of developing prostate specific antigen failure” refers to a subject's relative risk (e.g., the percent chance or a relative score) of developing prostate specific antigen failure following prostate cancer therapy.
As used herein, the term “post surgical tumor tissue” refers to cancerous tissue (e.g., prostate tissue) that has been removed from a subject (e.g., during surgery).
As used herein, the term “subject diagnosed with a cancer” refers to a subject who has been tested and found to have cancerous cells. The cancer may be diagnosed using any suitable method, including but not limited to, biopsy, x-ray, blood test, and the diagnostic methods of the present invention.
As used herein, the term “initial diagnosis” refers to results of initial cancer diagnosis (e.g. the presence or absence of cancerous cells). An initial diagnosis does not include information about the stage of the cancer of the risk of prostate specific antigen failure.
As used herein, the term “biopsy tissue” refers to a sample of tissue (e.g., prostate tissue) that is removed from a subject for the purpose of determining if the sample contains cancerous tissue. In some embodiment, biopsy tissue is obtained because a subject is suspected of having cancer. The biopsy tissue is then examined (e.g., by microscopy) for the presence or absence of cancer.
As used herein, the term “inconclusive biopsy tissue” refers to biopsy tissue for which histological examination has not determined the presence or absence of cancer.
As used herein, the term “basal cell marker” refers to a marker (e.g., an antibody) that binds to proteins present in the basal cell layer of benign prostate glands. Exemplary basal cell markers include, but are not limited to, 34βE12 and p63 (See e.g., O'Malley et al., Virchows Arch. Pathol. Anat. Histopathol., 417:191 [1990]; Wojno et al., Am. J. Surg. Pathol., 19:251 [1995]; Googe et al., Am. J. Clin. Pathol., 107:219 [1997]; Parsons et al., Urology 58:619; and Signoretti et al., Am. J. Pathol., 157:1769 [2000]).
As used herein, the term “non-human animals” refers to all non-human animals including, but are not limited to, vertebrates such as rodents, non-human primates, ovines, bovines, ruminants, lagomorphs, porcines, caprines, equines, canines, felines, aves, etc.
As used herein, the term “gene transfer system” refers to any means of delivering a composition comprising a nucleic acid sequence to a cell or tissue. For example, gene transfer systems include, but are not limited to, vectors (e.g., retroviral, adenoviral, adeno-associated viral, and other nucleic acid-based delivery systems), microinjection of naked nucleic acid, polymer-based delivery systems (e.g., liposome-based and metallic particle-based systems), biolistic injection, and the like. As used herein, the term “viral gene transfer system” refers to gene transfer systems comprising viral elements (e.g., intact viruses, modified viruses and viral components such as nucleic acids or proteins) to facilitate delivery of the sample to a desired cell or tissue. As used herein, the term “adenovirus gene transfer system” refers to gene transfer systems comprising intact or altered viruses belonging to the family Adenoviridae.
As used herein, the term “site-specific recombination target sequences” refers to nucleic acid sequences that provide recognition sequences for recombination factors and the location where recombination takes place.
As used herein, the term “nucleic acid molecule” refers to any nucleic acid containing molecule, including but not limited to, DNA or RNA. The term encompasses sequences that include any of the known base analogs of DNA and RNA including, but not limited to, 4-acetylcytosine, 8-hydroxy-N-6-methyladenosine, aziridinylcytosine, pseudoisocytosine, 5-(carboxyhydroxylmethyl) uracil, 5-fluorouracil, 5-bromouracil, 5-carboxymethylaminomethyl-2-thiouracil, 5-carboxymethylaminomethyluracil, dihydrouracil, inosine, N6-isopentenyladenine, 1-methyladenine, 1-methylpseudouracil, 1-methylguanine, 1-methylinosine, 2,2-dimethylguanine, 2-methyladenine, 2-methylguanine, 3-methylcytosine, 5-methylcytosine, N6-methyladenine, 7-methylguanine, 5-methylaminomethyluracil, 5-methoxyaminomethyl-2-thiouracil, beta-D-mannosylqueosine, 5′-methoxycarbonylmethyluracil, 5-methoxyuracil, 2-methylthio-N-6-isopentenyladenine, uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid, oxybutoxosine, pseudouracil, queosine, 2-thiocytosine, 5-methyl-2-thiouracil, 2-thiouracil, 4-thiouracil, 5-methyluracil, N-uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid, pseudouracil, queosine, 2-thiocytosine, and 2,6-diaminopurine.
The term “gene” refers to a nucleic acid (e.g., DNA) sequence that comprises coding sequences necessary for the production of a polypeptide, precursor, or RNA (e.g., rRNA, tRNA). The polypeptide can be encoded by a full length coding sequence or by any portion of the coding sequence so long as the desired activity or functional properties (e.g., enzymatic activity, ligand binding, signal transduction, immunogenicity, etc.) of the full-length or fragment are retained. The term also encompasses the coding region of a structural gene and the sequences located adjacent to the coding region on both the 5′ and 3′ ends for a distance of about 1 kb or more on either end such that the gene corresponds to the length of the full-length mRNA. Sequences located 5′ of the coding region and present on the mRNA are referred to as 5′ non-translated sequences. Sequences located 3′ or downstream of the coding region and present on the mRNA are referred to as 3′ non-translated sequences. The term “gene” encompasses both cDNA and genomic forms of a gene. A genomic form or clone of a gene contains the coding region interrupted with non-coding sequences termed “introns” or “intervening regions” or “intervening sequences.” Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements such as enhancers. Introns are removed or “spliced out” from the nuclear or primary transcript; introns therefore are absent in the messenger RNA (mRNA) transcript. The mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide.
As used herein, the term “heterologous gene” refers to a gene that is not in its natural environment. For example, a heterologous gene includes a gene from one species introduced into another species. A heterologous gene also includes a gene native to an organism that has been altered in some way (e.g., mutated, added in multiple copies, linked to non-native regulatory sequences, etc). Heterologous genes are distinguished from endogenous genes in that the heterologous gene sequences are typically joined to DNA sequences that are not found naturally associated with the gene sequences in the chromosome or are associated with portions of the chromosome not found in nature (e.g., genes expressed in loci where the gene is not normally expressed).
As used herein, the term “gene expression” refers to the process of converting genetic information encoded in a gene into RNA (e.g., mRNA, rRNA, tRNA, or snRNA) through “transcription” of the gene (i.e., via the enzymatic action of an RNA polymerase), and for protein encoding genes, into protein through “translation” of mRNA. Gene expression can be regulated at many stages in the process. “Up-regulation” or “activation” refers to regulation that increases the production of gene expression products (i.e., RNA or protein), while “down-regulation” or “repression” refers to regulation that decrease production. Molecules (e.g., transcription factors) that are involved in up-regulation or down-regulation are often called “activators” and “repressors,” respectively.
In addition to containing introns, genomic forms of a gene may also include sequences located on both the 5′ and 3′ end of the sequences that are present on the RNA transcript. These sequences are referred to as “flanking” sequences or regions (these flanking sequences are located 5′ or 3′ to the non-translated sequences present on the mRNA transcript). The 5′ flanking region may contain regulatory sequences such as promoters and enhancers that control or influence the transcription of the gene. The 3′ flanking region may contain sequences that direct the termination of transcription, post-transcriptional cleavage and polyadenylation.
The term “wild-type” refers to a gene or gene product isolated from a naturally occurring source. A wild-type gene is that which is most frequently observed in a population and is thus arbitrarily designed the “normal” or “wild-type” form of the gene. In contrast, the term “modified” or “mutant” refers to a gene or gene product that displays modifications in sequence and or functional properties (i.e., altered characteristics) when compared to the wild-type gene or gene product. It is noted that naturally occurring mutants can be isolated; these are identified by the fact that they have altered characteristics (including altered nucleic acid sequences) when compared to the wild-type gene or gene product.
As used herein, the terms “nucleic acid molecule encoding,” “DNA sequence encoding,” and “DNA encoding” refer to the order or sequence of deoxyribonucleotides along a strand of deoxyribonucleic acid. The order of these deoxyribonucleotides determines the order of amino acids along the polypeptide (protein) chain. The DNA sequence thus codes for the amino acid sequence.
As used herein, the terms “an oligonucleotide having a nucleotide sequence encoding a gene” and “polynucleotide having a nucleotide sequence encoding a gene,” means a nucleic acid sequence comprising the coding region of a gene or in other words the nucleic acid sequence that encodes a gene product. The coding region may be present in a cDNA, genomic DNA or RNA form. When present in a DNA form, the oligonucleotide or polynucleotide may be single-stranded (i.e., the sense strand) or double-stranded. Suitable control elements such as enhancers/promoters, splice junctions, polyadenylation signals, etc. may be placed in close proximity to the coding region of the gene if needed to permit proper initiation of transcription and/or correct processing of the primary RNA transcript. Alternatively, the coding region utilized in the expression vectors of the present invention may contain endogenous enhancers/promoters, splice junctions, intervening sequences, polyadenylation signals, etc. or a combination of both endogenous and exogenous control elements.
As used herein, the term “oligonucleotide,” refers to a short length of single-stranded polynucleotide chain. Oligonucleotides are typically less than 200 residues long (e.g., between 15 and 100), however, as used herein, the term is also intended to encompass longer polynucleotide chains. Oligonucleotides are often referred to by their length. For example a 24 residue oligonucleotide is referred to as a “24-mer”. Oligonucleotides can form secondary and tertiary structures by self-hybridizing or by hybridizing to other polynucleotides. Such structures can include, but are not limited to, duplexes, hairpins, cruciforms, bends, and triplexes.
As used herein, the terms “complementary” or “complementarity” are used in reference to polynucleotides (i.e., a sequence of nucleotides) related by the base-pairing rules. For example, for the sequence “A-G-T,” is complementary to the sequence “T-C-A.” Complementarity may be “partial,” in which only some of the nucleic acids' bases are matched according to the base pairing rules. Or, there may be “complete” or “total” complementarity between the nucleic acids. The degree of complementarity between nucleic acid strands has significant effects on the efficiency and strength of hybridization between nucleic acid strands. This is of particular importance in amplification reactions, as well as detection methods that depend upon binding between nucleic acids.
The term “homology” refers to a degree of complementarity. There may be partial homology or complete homology (i.e., identity). A partially complementary sequence is a nucleic acid molecule that at least partially inhibits a completely complementary nucleic acid molecule from hybridizing to a target nucleic acid is “substantially homologous.” The inhibition of hybridization of the completely complementary sequence to the target sequence may be examined using a hybridization assay (Southern or Northern blot, solution hybridization and the like) under conditions of low stringency. A substantially homologous sequence or probe will compete for and inhibit the binding (i.e., the hybridization) of a completely homologous nucleic acid molecule to a target under conditions of low stringency. This is not to say that conditions of low stringency are such that non-specific binding is permitted; low stringency conditions require that the binding of two sequences to one another be a specific (i.e., selective) interaction. The absence of non-specific binding may be tested by the use of a second target that is substantially non-complementary (e.g., less than about 30% identity); in the absence of non-specific binding the probe will not hybridize to the second non-complementary target.
When used in reference to a double-stranded nucleic acid sequence such as a cDNA or genomic clone, the term “substantially homologous” refers to any probe that can hybridize to either or both strands of the double-stranded nucleic acid sequence under conditions of low stringency as described above.
A gene may produce multiple RNA species that are generated by differential splicing of the primary RNA transcript. cDNAs that are splice variants of the same gene will contain regions of sequence identity or complete homology (representing the presence of the same exon or portion of the same exon on both cDNAs) and regions of complete non-identity (for example, representing the presence of exon “A” on cDNA 1 wherein cDNA 2 contains exon “B” instead). Because the two cDNAs contain regions of sequence identity they will both hybridize to a probe derived from the entire gene or portions of the gene containing sequences found on both cDNAs; the two splice variants are therefore substantially homologous to such a probe and to each other.
When used in reference to a single-stranded nucleic acid sequence, the term “substantially homologous” refers to any probe that can hybridize (i.e., it is the complement of) the single-stranded nucleic acid sequence under conditions of low stringency as described above.
As used herein, the term “hybridization” is used in reference to the pairing of complementary nucleic acids. Hybridization and the strength of hybridization (i.e., the strength of the association between the nucleic acids) is impacted by such factors as the degree of complementary between the nucleic acids, stringency of the conditions involved, the Tm of the formed hybrid, and the G:C ratio within the nucleic acids. A single molecule that contains pairing of complementary nucleic acids within its structure is said to be “self-hybridized.”
As used herein, the term “Tm” is used in reference to the “melting temperature.” The melting temperature is the temperature at which a population of double-stranded nucleic acid molecules becomes half dissociated into single strands. The equation for calculating the Tm of nucleic acids is well known in the art. As indicated by standard references, a simple estimate of the Tm value may be calculated by the equation: Tm=81.5+0.41(% G+C), when a nucleic acid is in aqueous solution at 1 M NaCl (See e.g., Anderson and Young, Quantitative Filter Hybridization, in Nucleic Acid Hybridization [1985]). Other references include more sophisticated computations that take structural as well as sequence characteristics into account for the calculation of Tm.
As used herein the term “stringency” is used in reference to the conditions of temperature, ionic strength, and the presence of other compounds such as organic solvents, under which nucleic acid hybridizations are conducted. Under “low stringency conditions” a nucleic acid sequence of interest will hybridize to its exact complement, sequences with single base mismatches, closely related sequences (e.g., sequences with 90% or greater homology), and sequences having only partial homology (e.g., sequences with 50-90% homology). Under “medium stringency conditions,” a nucleic acid sequence of interest will hybridize only to its exact complement, sequences with single base mismatches, and closely relation sequences (e.g., 90% or greater homology). Under “high stringency conditions,” a nucleic acid sequence of interest will hybridize only to its exact complement, and (depending on conditions such a temperature) sequences with single base mismatches. In other words, under conditions of high stringency the temperature can be raised so as to exclude hybridization to sequences with single base mismatches.
“High stringency conditions” when used in reference to nucleic acid hybridization comprise conditions equivalent to binding or hybridization at 42° C. in a solution consisting of 5×SSPE (43.8 g/l NaCl, 6.9 g/l NaH2PO4H2O and 1.85 g/l EDTA, pH adjusted to 7.4 with NaOH), 0.5% SDS, 5× Denhardt's reagent and 100 μg/ml denatured salmon sperm DNA followed by washing in a solution comprising 0.1×SSPE, 1.0% SDS at 42° C. when a probe of about 500 nucleotides in length is employed.
“Medium stringency conditions” when used in reference to nucleic acid hybridization comprise conditions equivalent to binding or hybridization at 42° C. in a solution consisting of 5×SSPE (43.8 g/l NaCl, 6.9 g/l NaH2PO4H2O and 1.85 g/l EDTA, pH adjusted to 7.4 with NaOH), 0.5% SDS, 5× Denhardt's reagent and 100 μg/ml denatured salmon sperm DNA followed by washing in a solution comprising 1.0×SSPE, 1.0% SDS at 42° C. when a probe of about 500 nucleotides in length is employed.
“Low stringency conditions” comprise conditions equivalent to binding or hybridization at 42° C. in a solution consisting of 5×SSPE (43.8 g/l NaCl, 6.9 g/l NaH2PO4H2O and 1.85 g/l EDTA, pH adjusted to 7.4 with NaOH), 0.1% SDS, 5× Denhardt's reagent [50× Denhardt's contains per 500 ml: 5 g Ficoll (Type 400, Pharamcia), 5 g BSA (Fraction V; Sigma)] and 100 μg/ml denatured salmon sperm DNA followed by washing in a solution comprising 5×SSPE, 0.1% SDS at 42° C. when a probe of about 500 nucleotides in length is employed.
The art knows well that numerous equivalent conditions may be employed to comprise low stringency conditions; factors such as the length and nature (DNA, RNA, base composition) of the probe and nature of the target (DNA, RNA, base composition, present in solution or immobilized, etc.) and the concentration of the salts and other components (e.g., the presence or absence of fommamide, dextran sulfate, polyethylene glycol) are considered and the hybridization solution may be varied to generate conditions of low stringency hybridization different from, but equivalent to, the above listed conditions. In addition, the art knows conditions that promote hybridization under conditions of high stringency (e.g., increasing the temperature of the hybridization and/or wash steps, the use of formamide in the hybridization solution, etc.) (see definition above for “stringency”).
“Amplification” is a special case of nucleic acid replication involving template specificity. It is to be contrasted with non-specific template replication (i.e., replication that is template-dependent but not dependent on a specific template). Template specificity is here distinguished from fidelity of replication (i.e., synthesis of the proper polynucleotide sequence) and nucleotide (ribo- or deoxyribo-) specificity. Template specificity is frequently described in terms of “target” specificity. Target sequences are “targets” in the sense that they are sought to be sorted out from other nucleic acid. Amplification techniques have been designed primarily for this sorting out.
Template specificity is achieved in most amplification techniques by the choice of enzyme. Amplification enzymes are enzymes that, under conditions they are used, will process only specific sequences of nucleic acid in a heterogeneous mixture of nucleic acid. For example, in the case of Qβ replicase, MDV-1 RNA is the specific template for the replicase (Kacian et al., Proc. Natl. Acad. Sci. USA 69:3038 [1972]). Other nucleic acids will not be replicated by this amplification enzyme. Similarly, in the case of T7 RNA polymerase, this amplification enzyme has a stringent specificity for its own promoters (Chamberlin et al., Nature 228:227 [1970]). In the case of T4 DNA ligase, the enzyme will not ligate the two oligonucleotides or polynucleotides, where there is a mismatch between the oligonucleotide or polynucleotide substrate and the template at the ligation junction (Wu and Wallace, Genomics 4:560 [1989]). Finally, Taq and Pfu polymerases, by virtue of their ability to function at high temperature, are found to display high specificity for the sequences bounded and thus defined by the primers; the high temperature results in thermodynamic conditions that favor primer hybridization with the target sequences and not hybridization with non-target sequences (H. A. Erlich (ed.), PCR Technology, Stockton Press [1989]).
As used herein, the term “amplifiable nucleic acid” is used in reference to nucleic acids that may be amplified by any amplification method. It is contemplated that “amplifiable nucleic acid” will usually comprise “sample template.”
As used herein, the term “sample template” refers to nucleic acid originating from a sample that is analyzed for the presence of “target.” In contrast, “background template” is used in reference to nucleic acid other than sample template that may or may not be present in a sample. Background template is most often inadvertent. It may be the result of carryover, or it may be due to the presence of nucleic acid contaminants sought to be purified away from the sample. For example, nucleic acids from organisms other than those to be detected may be present as background in a test sample.
As used herein, the term “primer” refers to an oligonucleotide, whether occurring naturally as in a purified restriction digest or produced synthetically, that is capable of acting as a point of initiation of synthesis when placed under conditions in which synthesis of a primer extension product that is complementary to a nucleic acid strand is induced, (i.e., in the presence of nucleotides and an inducing agent such as DNA polymerase and at a suitable temperature and pH). The primer is preferably single stranded for maximum efficiency in amplification, but may alternatively be double stranded. If double stranded, the primer is first treated to separate its strands before being used to prepare extension products. Preferably, the primer is an oligodeoxyribonucleotide. The primer must be sufficiently long to prime the synthesis of extension products in the presence of the inducing agent. The exact lengths of the primers will depend on many factors, including temperature, source of primer and the use of the method.
As used herein, the term “probe” refers to an oligonucleotide (i.e., a sequence of nucleotides), whether occurring naturally as in a purified restriction digest or produced synthetically, recombinantly or by PCR amplification, that is capable of hybridizing to at least a portion of another oligonucleotide of interest. A probe may be single-stranded or double-stranded. Probes are useful in the detection, identification and isolation of particular gene sequences. It is contemplated that any probe used in the present invention will be labeled with any “reporter molecule,” so that is detectable in any detection system, including, but not limited to enzyme (e.g., ELISA, as well as enzyme-based histochemical assays), fluorescent, radioactive, and luminescent systems. It is not intended that the present invention be limited to any particular detection system or label.
As used herein the term “portion” when in reference to a nucleotide sequence (as in “a portion of a given nucleotide sequence”) refers to fragments of that sequence. The fragments may range in size from four nucleotides to the entire nucleotide sequence minus one nucleotide (10 nucleotides, 20, 30, 40, 50, 100, 200, etc.).
As used herein, the term “target,” refers to the region of nucleic acid bounded by the primers. Thus, the “target” is sought to be sorted out from other nucleic acid sequences. A “segment” is defined as a region of nucleic acid within the target sequence.
As used herein, the term “polymerase chain reaction” (“PCR”) refers to the method of K. B. Mullis U.S. Pat. Nos. 4,683,195 4,683,202, and 4,965,188, hereby incorporated by reference, which describe a method for increasing the concentration of a segment of a target sequence in a mixture of genomic DNA without cloning or purification. This process for amplifying the target sequence consists of introducing a large excess of two oligonucleotide primers to the DNA mixture containing the desired target sequence, followed by a precise sequence of thermal cycling in the presence of a DNA polymerase. The two primers are complementary to their respective strands of the double stranded target sequence. To effect amplification, the mixture is denatured and the primers then annealed to their complementary sequences within the target molecule. Following annealing, the primers are extended with a polymerase so as to form a new pair of complementary strands. The steps of denaturation, primer annealing and polymerase extension can be repeated many times (i.e., denaturation, annealing and extension constitute one “cycle”; there can be numerous “cycles”) to obtain a high concentration of an amplified segment of the desired target sequence. The length of the amplified segment of the desired target sequence is determined by the relative positions of the primers with respect to each other, and therefore, this length is a controllable parameter. By virtue of the repeating aspect of the process, the method is referred to as the “polymerase chain reaction” (hereinafter “PCR”). Because the desired amplified segments of the target sequence become the predominant sequences (in terms of concentration) in the mixture, they are said to be “PCR amplified”.
With PCR, it is possible to amplify a single copy of a specific target sequence in genomic DNA to a level detectable by several different methodologies (e.g., hybridization with a labeled probe; incorporation of biotinylated primers followed by avidin-enzyme conjugate detection; incorporation of 32P-labeled deoxynucleotide triphosphates, such as dCTP or dATP, into the amplified segment). In addition to genomic DNA, any oligonucleotide or polynucleotide sequence can be amplified with the appropriate set of primer molecules. In particular, the amplified segments created by the PCR process are, themselves, efficient templates for subsequent PCR amplifications.
As used herein, the terms “PCR product,” “PCR fragment,” and “amplification product” refer to the resultant mixture of compounds after two or more cycles of the PCR steps of denaturation, annealing and extension are complete. These terms encompass the case where there has been amplification of one or more segments of one or more target sequences.
As used herein, the term “amplification reagents” refers to those reagents (deoxyribonucleotide triphosphates, buffer, etc.), needed for amplification except for primers, nucleic acid template and the amplification enzyme. Typically, amplification reagents along with other reaction components are placed and contained in a reaction vessel (test tube, microwell, etc.).
As used herein, the terms “restriction endonucleases” and “restriction enzymes” refer to bacterial enzymes, each of which cut double-stranded DNA at or near a specific nucleotide sequence.
The terms “in operable combination,” “in operable order,” and “operably linked” as used herein refer to the linkage of nucleic acid sequences in such a manner that a nucleic acid molecule capable of directing the transcription of a given gene and/or the synthesis of a desired protein molecule is produced. The term also refers to the linkage of amino acid sequences in such a manner so that a functional protein is produced.
The term “isolated” when used in relation to a nucleic acid, as in “an isolated oligonucleotide” or “isolated polynucleotide” refers to a nucleic acid sequence that is identified and separated from at least one component or contaminant with which it is ordinarily associated in its natural source. Isolated nucleic acid is such present in a form or setting that is different from that in which it is found in nature. In contrast, non-isolated nucleic acids as nucleic acids such as DNA and RNA found in the state they exist in nature. For example, a given DNA sequence (e.g., a gene) is found on the host cell chromosome in proximity to neighboring genes; RNA sequences, such as a specific mRNA sequence encoding a specific protein, are found in the cell as a mixture with numerous other mRNAs that encode a multitude of proteins. However, isolated nucleic acid encoding a given protein includes, by way of example, such nucleic acid in cells ordinarily expressing the given protein where the nucleic acid is in a chromosomal location different from that of natural cells, or is otherwise flanked by a different nucleic acid sequence than that found in nature. The isolated nucleic acid, oligonucleotide, or polynucleotide may be present in single-stranded or double-stranded form. When an isolated nucleic acid, oligonucleotide or polynucleotide is to be utilized to express a protein, the oligonucleotide or polynucleotide will contain at a minimum the sense or coding strand (i.e., the oligonucleotide or polynucleotide may be single-stranded), but may contain both the sense and anti-sense strands (i.e., the oligonucleotide or polynucleotide may be double-stranded).
As used herein, the term “purified” or “to purify” refers to the removal of components (e.g., contaminants) from a sample. For example, antibodies are purified by removal of contaminating non-immunoglobulin proteins; they are also purified by the removal of immunoglobulin that does not bind to the target molecule. The removal of non-immunoglobulin proteins and/or the removal of immunoglobulins that do not bind to the target molecule results in an increase in the percent of target-reactive immunoglobulins in the sample. In another example, recombinant polypeptides are expressed in bacterial host cells and the polypeptides are purified by the removal of host cell proteins; the percent of recombinant polypeptides is thereby increased in the sample.
“Amino acid sequence” and terms such as “polypeptide” or “protein” are not meant to limit the amino acid sequence to the complete, native amino acid sequence associated with the recited protein molecule.
The term “native protein” as used herein to indicate that a protein does not contain amino acid residues encoded by vector sequences; that is, the native protein contains only those amino acids found in the protein as it occurs in nature. A native protein may be produced by recombinant means or may be isolated from a naturally occurring source.
As used herein the term “portion” when in reference to a protein (as in “a portion of a given protein”) refers to fragments of that protein. The fragments may range in size from four amino acid residues to the entire amino acid sequence minus one amino acid.
The term “Southern blot,” refers to the analysis of DNA on agarose or acrylamide gels to fractionate the DNA according to size followed by transfer of the DNA from the gel to a solid support, such as nitrocellulose or a nylon membrane. The immobilized DNA is then probed with a labeled probe to detect DNA species complementary to the probe used. The DNA may be cleaved with restriction enzymes prior to electrophoresis. Following electrophoresis, the DNA may be partially depurinated and denatured prior to or during transfer to the solid support. Southern blots are a standard tool of molecular biologists (J. Sambrook et al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press, NY, pp 9.31-9.58 [1989]).
The term “Northern blot,” as used herein refers to the analysis of RNA by electrophoresis of RNA on agarose gels to fractionate the RNA according to size followed by transfer of the RNA from the gel to a solid support, such as nitrocellulose or a nylon membrane. The immobilized RNA is then probed with a labeled probe to detect RNA species complementary to the probe used. Northern blots are a standard tool of molecular biologists (J. Sambrook, et al., supra, pp 7.39-7.52 [1989]).
The term “Western blot” refers to the analysis of protein(s) (or polypeptides) immobilized onto a support such as nitrocellulose or a membrane. The proteins are run on acrylamide gels to separate the proteins, followed by transfer of the protein from the gel to a solid support, such as nitrocellulose or a nylon membrane. The immobilized proteins are then exposed to antibodies with reactivity against an antigen of interest. The binding of the antibodies may be detected by various methods, including the use of radiolabeled antibodies.
The term “transgene” as used herein refers to a foreign gene that is placed into an organism by, for example, introducing the foreign gene into newly fertilized eggs or early embryos. The term “foreign gene” refers to any nucleic acid (e.g., gene sequence) that is introduced into the genome of an animal by experimental manipulations and may include gene sequences found in that animal so long as the introduced gene does not reside in the same location as does the naturally occurring gene.
As used herein, the term “vector” is used in reference to nucleic acid molecules that transfer DNA segment(s) from one cell to another. The term “vehicle” is sometimes used interchangeably with “vector.” Vectors are often derived from plasmids, bacteriophages, or plant or animal viruses.
The term “expression vector” as used herein refers to a recombinant DNA molecule containing a desired coding sequence and appropriate nucleic acid sequences necessary for the expression of the operably linked coding sequence in a particular host organism. Nucleic acid sequences necessary for expression in prokaryotes usually include a promoter, an operator (optional), and a ribosome binding site, often along with other sequences. Eukaryotic cells are known to utilize promoters, enhancers, and termination and polyadenylation signals.
The terms “overexpression” and “overexpressing” and grammatical equivalents, are used in reference to levels of mRNA to indicate a level of expression approximately 3-fold higher (or greater) than that observed in a given tissue in a control or non-transgenic animal. Levels of mRNA are measured using any of a number of techniques known to those skilled in the art including, but not limited to Northern blot analysis. Appropriate controls are included on the Northern blot to control for differences in the amount of RNA loaded from each tissue analyzed (e.g., the amount of 28S rRNA, an abundant RNA transcript present at essentially the same amount in all tissues, present in each sample can be used as a means of normalizing or standardizing the mRNA-specific signal observed on Northern blots). The amount of mRNA present in the band corresponding in size to the correctly spliced transgene RNA is quantified; other minor species of RNA which hybridize to the transgene probe are not considered in the quantification of the expression of the transgenic mRNA.
The term “transfection” as used herein refers to the introduction of foreign DNA into eukaryotic cells. Transfection may be accomplished by a variety of means known to the art including calcium phosphate-DNA co-precipitation, DEAE-dextran-mediated transfection, polybrene-mediated transfection, electroporation, microinjection, liposome fusion, lipofection, protoplast fusion, retroviral infection, and biolistics.
The term “calcium phosphate co-precipitation” refers to a technique for the introduction of nucleic acids into a cell. The uptake of nucleic acids by cells is enhanced when the nucleic acid is presented as a calcium phosphate-nucleic acid co-precipitate. The original technique of Graham and van der Eb (Graham and van der Eb, Virol., 52:456 [1973]), has been modified by several groups to optimize conditions for particular types of cells. The art is well aware of these numerous modifications.
The term “stable transfection” or “stably transfected” refers to the introduction and integration of foreign DNA into the genome of the transfected cell. The term “stable transfectant” refers to a cell that has stably integrated foreign DNA into the genomic DNA.
The term “transient transfection” or “transiently transfected” refers to the introduction of foreign DNA into a cell where the foreign DNA fails to integrate into the genome of the transfected cell. The foreign DNA persists in the nucleus of the transfected cell for several days. During this time the foreign DNA is subject to the regulatory controls that govern the expression of endogenous genes in the chromosomes. The term “transient transfectant” refers to cells that have taken up foreign DNA but have failed to integrate this DNA.
As used herein, the term “selectable marker” refers to the use of a gene that encodes an enzymatic activity that confers the ability to grow in medium lacking what would otherwise be an essential nutrient (e.g. the HIS3 gene in yeast cells); in addition, a selectable marker may confer resistance to an antibiotic or drug upon the cell in which the selectable marker is expressed. Selectable markers may be “dominant”; a dominant selectable marker encodes an enzymatic activity that can be detected in any eukaryotic cell line. Examples of dominant selectable markers include the bacterial aminoglycoside 3′ phosphotransferase gene (also referred to as the neo gene) that confers resistance to the drug G418 in mammalian cells, the bacterial hygromycin G phosphotransferase (hyg) gene that confers resistance to the antibiotic hygromycin and the bacterial xanthine-guanine phosphoribosyl transferase gene (also referred to as the gpt gene) that confers the ability to grow in the presence of mycophenolic acid. Other selectable markers are not dominant in that their use must be in conjunction with a cell line that lacks the relevant enzyme activity. Examples of non-dominant selectable markers include the thymidine kinase (tk) gene that is used in conjunction with tk− cell lines, the CAD gene that is used in conjunction with CAD-deficient cells and the mammalian hypoxanthine-guanine phosphoribosyl transferase (hprt) gene that is used in conjunction with hprt− cell lines. A review of the use of selectable markers in mammalian cell lines is provided in Sambrook, J. et al., Molecular Cloning: A Laboratory Manual, 2nd ed., Cold Spring Harbor Laboratory Press, New York (1989) pp. 16.9-16.15.
As used herein, the term “cell culture” refers to any in vitro culture of cells. Included within this term are continuous cell lines (e.g., with an immortal phenotype), primary cell cultures, transformed cell lines, finite cell lines (e.g., non-transformed cells), and any other cell population maintained in vitro.
As used, the term “eukaryote” refers to organisms distinguishable from “prokaryotes.” It is intended that the term encompass all organisms with cells that exhibit the usual characteristics of eukaryotes, such as the presence of a true nucleus bounded by a nuclear membrane, within which lie the chromosomes, the presence of membrane-bound organelles, and other characteristics commonly observed in eukaryotic organisms. Thus, the term includes, but is not limited to such organisms as fungi, protozoa, and animals (e.g., humans).
As used herein, the term “in vitro” refers to an artificial environment and to processes or reactions that occur within an artificial environment. In vitro environments can consist of, but are not limited to, test tubes and cell culture. The term “in vivo” refers to the natural environment (e.g., an animal or a cell) and to processes or reaction that occur within a natural environment.
The terms “test compound” and “candidate compound” refer to any chemical entity, pharmaceutical, drug, and the like that is a candidate for use to treat or prevent a disease, illness, sickness, or disorder of bodily function (e.g., cancer). Test compounds comprise both known and potential therapeutic compounds. A test compound can be determined to be therapeutic by screening using the screening methods of the present invention. In some embodiments of the present invention, test compounds include antisense compounds.
As used herein, the term “sample” is used in its broadest sense. In one sense, it is meant to include a specimen or culture obtained from any source, as well as biological and environmental samples. Biological samples may be obtained from animals (including humans) and encompass fluids, solids, tissues, and gases. Biological samples include blood products, such as plasma, serum and the like. Environmental samples include environmental material such as surface matter, soil, water, crystals and industrial samples. Such examples are not however to be construed as limiting the sample types applicable to the present invention.
DETAILED DESCRIPTION OF THE INVENTION
The present invention relates to compositions and methods for cancer diagnostics, including but not limited to, cancer markers. In particular, the present invention provides gene expression profiles associated with prostate cancers. Accordingly, the present invention provides method of characterizing prostate tissues, kits for the detection of markers, as well as drug screening and therapeutic applications.
I. Markers for Prostate Cancer
The present invention provides markers whose expression is specifically altered in cancerous prostate tissues. Such markers find use in the diagnosis and characterization of prostate cancer.
A. Identification of Markers
Experiments conducted during the development of the present invention resulted in the identification of genes whose expression level was altered (e.g., increased or decreased) in PCA. The methods utilized glass slide cDNA microarrays that included approximately 5000 known, named genes, 4400 ESTs, and 500 control elements, as well as normal and cancerous prostate tissue. Differentially expressed genes were divided into functional clusters. The expression of relevant genes was confirmed using Western blot analysis. Protein expression in prostate tissues was measured for several genes of interest.
The methods of the present invention (See e.g., Example 2) were used to identify clusters of genes that were up or down regulated in PCA, benign prostate tissue, pre-cancerous tissue, and normal prostate. From these clusters, two genes, hepsin and pim-1 were identified as genes that were of particular relevance. Immunohistochemistry (See e.g., Example 4) was used to characterize the presence of hepsin and pim-1 proteins in prostate tissue. Hepsin was found to stain strongly in pre-cancerous tissue (HG-PIN). In addition, hepsin was found to stain less strongly in PCA tissues of men found to have an increased risk of metastasis as measured by PSA failure (increased PSA following surgery), thus confirming the diagnostic utility of hepsin. In addition, deceased expression of pim-1 in PCA tissue was also found to be associated with increased risk of PSA failure. Accordingly, in some embodiments, the present invention provides methods of detecting and characterizing prostate tissues.
The methods of the present invention identified a further gene, alpha-methyl-CoA racemase (AMACR), that was found to be expressed in PCA, but not benign prostate tissue (See e.g., Example 5). AMACR was found to be present in the serum and urine of prostate or bladder cancer patients (See e.g., Example 16). In addition, a humoral response to AMACR was identified. Further, an association between AMACR expression and disease prognosis was identified (See e.g. Example 17).
In still further embodiments, the methods of the present invention were used to characterize the EZH2 gene. EZH2 was found to be up-regulated in metastatic prostate cancer. The inhibition of EZH2 expression in prostate cells inhibited cell proliferation in vitro, as well as inducing transcriptional repression of a variety of genes. The methods of the present invention further identified CtBP1 and CTBP2, as well as that GP73 as being over-expressed in metastatic prostate cancer relative to localized prostate cancer and benign tissue.
In still further embodiments, the methods of the present invention identified annexins 1, 2, 4, 7 and 11 as being significantly decreased in hormone refractory PCA when compared to localized hormone naïve Pca. Tissue microarray analysis revealed a significant decrease in protein expression for annexins 1, 2, 4, 7 and 11 in hormone refractory PCA as compared to localized Pca. No significant differences were detected between the clinically localized PCA and non-cancerous prostate tissues.
B. Detection of Markers
In some embodiments, the present invention provides methods for detection of expression of cancer markers (e.g., prostate cancer markers). In preferred embodiments, expression is measured directly (e.g., at the RNA or protein level). In some embodiments, expression is detected in tissue samples (e.g., biopsy tissue). In other embodiments, expression is detected in bodily fluids (e.g., including but not limited to, plasma, serum, whole blood, mucus, prostatic secretions, and urine). The present invention further provides panels and kits for the detection of markers. In preferred embodiments, the presence of a cancer marker is used to provide a prognosis to a subject. For example, the detection of hepsin or pim-1 in prostate tissues is indicative of a cancer that is likely to metastasize and the expression of hepsin is indicative of a pre-cancerous tissue that is likely to become cancerous. In addition, the expression of AMACR is indicative of cancerous tissue. The information provided is also used to direct the course of treatment. For example, if a subject is found to have a marker indicative of a highly metastasizing tumor, additional therapies (e.g., hormonal or radiation therapies) can be started at a earlier point when they are more likely to be effective (e.g., before metastasis). In addition, if a subject is found to have a tumor that is not responsive to hormonal therapy, the expense and inconvenience of such therapies can be avoided.
The present invention is not limited to the markers described above. Any suitable marker that correlates with cancer or the progression of cancer may be utilized, including but not limited to, those described in the illustrative examples below (e.g., FKBP5, FASN, FOLH1, TNFSF10, PCM1, S100A11, IGFBP3, SLUG, GSTM3, ATF2, RAB5A, IL1R2, ITGB4, CCND2, EDNRB, APP, THROMBOSPONDIN 1, ANNEXIN A1, EPHA1, NCK1MAPK6, SGK, HEVIN, MEIS2, MYLK, FZD7, CAVEOLIN 2, TACC1, ARHB, PSG9, GSTM1KERATIN 5, TIMP2, GELSOLIN, ITM2C, GSTM5, VINCULIN, FHL1, GSTP1, MEIS1, ETS2, PPP2CB, CATHEPSIN B, CATHEPSIN H, COL1A2, RIG, VIMENTIN, MOESIN, MCAM, FIBRONECTIN 1, NBL1, ANNEXIN A4, ANEXIN A11, IL1R1, IGFBP5, CYSTATIN C, COL15A1, ADAMTS1, SKI, EGR1, FOSB, CFLAR, JUN, YWHAB, NRAS, C7, SCYA2, ITGA1LUMICAN, C1S, C4BPA, COL3A1, FAT, MMECD10, CLUSTERIN, PLA2G2A, MADh4, SEPP1RAB2, PP1CB, MPDZ, PRKCL2, CTBP1CTBP2, MAP3K10, TBXA2F, MTA1RAP2, TRAP1, TFCP2, E2EPF, UBCH10, TASTIN, EZH2, FLS353, MYBL2, LIMK1, GP73, VAV2, TOP2A, ASNS, CTBP, AMACR, ABCC5 (MDR5), and TRAF4. Additional markers are also contemplated to be within the scope of the present invention. Any suitable method may be utilized to identify and characterize cancer markers suitable for use in the methods of the present invention, including but not limited to, those described in illustrative Examples 1-17 below. For example, in some embodiments, markers identified as being up or down-regulated in PCA using the gene expression microarray methods of the present invention are further characterized using tissue microarray, immunohistochemistry, Northern blot analysis, siRNA or antisense RNA inhibition, mutation analysis, investigation of expression with clinical outcome, as well as other methods disclosed herein.
In some embodiments, the present invention provides a panel for the analysis of a plurality of markers. The panel allows for the simultaneous analysis of multiple markers correlating with carcinogenesis and/or metastasis. For example, a panel may include markers identified as correlating with cancerous tissue, metastatic cancer, localized cancer that is likely to metastasize, pre-cancerous tissue that is likely to become cancerous, and pre-cancerous tissue that is not likely to become cancerous. Depending on the subject, panels may be analyzed alone or in combination in order to provide the best possible diagnosis and prognosis. Markers for inclusion on a panel are selected by screening for their predictive value using any suitable method, including but not limited to, those described in the illustrative examples below.
In other embodiments, the present invention provides an expression profile map comprising expression profiles of cancers of various stages or prognoses (e.g., likelihood of future metastasis). Such maps can be used for comparison with patient samples. In some embodiments comparisons are made using the method described in Example 2. However, the present invention is not limited to the method described in Example 2. Any suitable method may be utilized, including but not limited to, by computer comparison of digitized data. The comparison data is used to provide diagnoses and/or prognoses to patients.
1. Detection of RNA
In some preferred embodiments, detection of prostate cancer markers (e.g., including but not limited to, those disclosed herein) is detected by measuring the expression of corresponding mRNA in a tissue sample (e.g., prostate tissue). mRNA expression may be measured by any suitable method, including but not limited to, those disclosed below.
In some embodiments, RNA is detection by Northern blot analysis. Northern blot analysis involves the separation of RNA and hybridization of a complementary labeled probe. An exemplary method for Northern blot analysis is provided in Example 3.
In other embodiments, RNA expression is detected by enzymatic cleavage of specific structures (INVADER assay, Third Wave Technologies; See e.g., U.S. Pat. Nos. 5,846,717, 6,090,543; 6,001,567; 5,985,557; and 5,994,069; each of which is herein incorporated by reference). The INVADER assay detects specific nucleic acid (e.g., RNA) sequences by using structure-specific enzymes to cleave a complex formed by the hybridization of overlapping oligonucleotide probes.
In still further embodiments, RNA (or corresponding cDNA) is detected by hybridization to a oligonucleotide probe). A variety of hybridization assays using a variety of technologies for hybridization and detection are available. For example, in some embodiments, TaqMan assay (PE Biosystems, Foster City, Calif.; See e.g., U.S. Pat. Nos. 5,962,233 and 5,538,848, each of which is herein incorporated by reference) is utilized. The assay is performed during a PCR reaction. The TaqMan assay exploits the 5′-3′ exonuclease activity of the AMPLITAQ GOLD DNA polymerase. A probe consisting of an oligonucleotide with a 5′-reporter dye (e.g., a fluorescent dye) and a 3′-quencher dye is included in the PCR reaction. During PCR, if the probe is bound to its target, the 5′-3′ nucleolytic activity of the AMPLITAQ GOLD polymerase cleaves the probe between the reporter and the quencher dye. The separation of the reporter dye from the quencher dye results in an increase of fluorescence. The signal accumulates with each cycle of PCR and can be monitored with a fluorimeter.
In yet other embodiments, reverse-transcriptase PCR (RT-PCR) is used to detect the expression of RNA. In RT-PCR, RNA is enzymatically converted to complementary DNA or “cDNA” using a reverse transcriptase enzyme. The cDNA is then used as a template for a PCR reaction. PCR products can be detected by any suitable method, including but not limited to, gel electrophoresis and staining with a DNA specific stain or hybridization to a labeled probe. In some embodiments, the quantitative reverse transcriptase PCR with standardized mixtures of competitive templates method described in U.S. Pat. Nos. 5,639,606, 5,643,765, and 5,876,978 (each of which is herein incorporated by reference) is utilized.
2. Detection of Protein
In other embodiments, gene expression of cancer markers is detected by measuring the expression of the corresponding protein or polypeptide. Protein expression may be detected by any suitable method. In some embodiments, proteins are detected by the immunohistochemistry method of Example 4. In other embodiments, proteins are detected by their binding to an antibody raised against the protein. The generation of antibodies is described below.
In some preferred embodiments, urine or prostate cancer samples are tested for levels of AMACR using AMACR-specific antibodies (Examples 16 and 17). Amounts of AMACR are normalized and compared to other samples, allowing for the determination of threshold AMACR levels that correlate with presence of prostate cancer or risk of cancer progression.
In some embodiments, AMACR levels in urine are scored by visual inspection of band intensity on Western blots, with 0 being no band and 4 being the highest band intensity. Associations are made between AMACR levels and presence of prostate cancer, and a minimum threshold level set to 1 allows for discrimination between presence (values greater than 1) and absence (values below 1) of prostate cancer (see Example 16).
Experiments conducted during the development of the present invention resulted in the discovery that AMACR expression decreases in metastatic prostate cancer, in contrast to increased AMACR expression in clinically localized prostate cancer. Thus, in some embodiments, AMACR levels are examined in prostate cancer tissue samples to determine risk of cancer progression and poor prognosis (Example 17). In some embodiments, the samples are scored by semi-automated quantitation of tissue hybridized with anti-AMACR antibodies. The values are normalized to background counterstain and AMACR levels in other prostate cancer samples. In one embodiment, a threshold level is established below which a correlation between AMACR levels and risk of prostate specific antigen failure exists. In another embodiment, a threshold level is established below which a correlation between AMACR levels and prostate cancer-specific death exists.
In some embodiments, levels of AMACR in new urine or prostate cancer samples are compared to the threshold levels established during the course of development of the present invention. In other embodiments, individual laboratories or clinics use urine or prostate cancer samples on site to define threshold levels of AMACR expression that correlate with presence of cancer or prognosis; in other embodiments, panels of data from urine or prostate cancer samples are available in an electronic format for use by researchers and clinicians in multiple locations. In other embodiments, a centralized database exists where data from samples are entered on an ongoing basis by clinicians and researchers, thereby reinforcing and refining AMACR threshold levels that correlate with prostate cancer or prognosis over time.
Antibody binding is detected by techniques known in the art (e.g., radioimmunoassay, ELISA (enzyme-linked immunosorbant assay), “sandwich” immunoassays, immunoradiometric assays, gel diffusion precipitation reactions, immunodiffusion assays, in situ immunoassays (e.g., using colloidal gold, enzyme or radioisotope labels, for example), Western blots, precipitation reactions, agglutination assays (e.g., gel agglutination assays, hemagglutination assays, etc.), complement fixation assays, immunofluorescence assays, protein A assays, and immunoelectrophoresis assays, etc.
In one embodiment, antibody binding is detected by detecting a label on the primary antibody. In another embodiment, the primary antibody is detected by detecting binding of a secondary antibody or reagent to the primary antibody. In a further embodiment, the secondary antibody is labeled. Many methods are known in the art for detecting binding in an immunoassay and are within the scope of the present invention.
In some embodiments, an automated detection assay is utilized. Methods for the automation of immunoassays include those described in U.S. Pat. Nos. 5,885,530, 4,981,785, 6,159,750, and 5,358,691, each of which is herein incorporated by reference. In some embodiments, the analysis and presentation of results is also automated. For example, in some embodiments, software that generates a prognosis based on the presence or absence of a series of proteins corresponding to cancer markers is utilized.
In other embodiments, the immunoassay described in U.S. Pat. Nos. 5,599,677 and 5,672,480; each of which is herein incorporated by reference.
3. Data Analysis
In some embodiments, a computer-based analysis program is used to translate the raw data generated by the detection assay (e.g., the presence, absence, or amount of a given marker or markers) into data of predictive value for a clinician. The clinician can access the predictive data using any suitable means. Thus, in some preferred embodiments, the present invention provides the further benefit that the clinician, who is not likely to be trained in genetics or molecular biology, need not understand the raw data. The data is presented directly to the clinician in its most useful form. The clinician is then able to immediately utilize the information in order to optimize the care of the subject.
The present invention contemplates any method capable of receiving, processing, and transmitting the information to and from laboratories conducting the assays, information provides, medical personal, and subjects. For example, in some embodiments of the present invention, a sample (e.g., a biopsy or a serum or urine sample) is obtained from a subject and submitted to a profiling service (e.g., clinical lab at a medical facility, genomic profiling business, etc.), located in any part of the world (e.g., in a country different than the country where the subject resides or where the information is ultimately used) to generate raw data. Where the sample comprises a tissue or other biological sample, the subject may visit a medical center to have the sample obtained and sent to the profiling center, or subjects may collect the sample themselves (e.g., a urine sample) and directly send it to a profiling center. Where the sample comprises previously determined biological information, the information may be directly sent to the profiling service by the subject (e.g., an information card containing the information may be scanned by a computer and the data transmitted to a computer of the profiling center using an electronic communication systems). Once received by the profiling service, the sample is processed and a profile is produced (i.e., expression data), specific for the diagnostic or prognostic information desired for the subject.
The profile data is then prepared in a format suitable for interpretation by a treating clinician. For example, rather than providing raw expression data, the prepared format may represent a diagnosis or risk assessment (e.g., likelihood of metastasis or PSA failure) for the subject, along with recommendations for particular treatment options. The data may be displayed to the clinician by any suitable method. For example, in some embodiments, the profiling service generates a report that can be printed for the clinician (e.g., at the point of care) or displayed to the clinician on a computer monitor.
In some embodiments, the information is first analyzed at the point of care or at a regional facility. The raw data is then sent to a central processing facility for further analysis and/or to convert the raw data to information useful for a clinician or patient. The central processing facility provides the advantage of privacy (all data is stored in a central facility with uniform security protocols), speed, and uniformity of data analysis. The central processing facility can then control the fate of the data following treatment of the subject. For example, using an electronic communication system, the central facility can provide data to the clinician, the subject, or researchers.
In some embodiments, the subject is able to directly access the data using the electronic communication system. The subject may chose further intervention or counseling based on the results. In some embodiments, the data is used for research use. For example, the data may be used to further optimize the inclusion or elimination of markers as useful indicators of a particular condition or stage of disease.
4. Kits
In yet other embodiments, the present invention provides kits for the detection and characterization of prostate cancer. In some embodiments, the kits contain antibodies specific for a cancer marker, in addition to detection reagents and buffers. In other embodiments, the kits contain reagents specific for the detection of mRNA or cDNA (e.g., oligonucleotide probes or primers). In preferred embodiments, the kits contain all of the components necessary to perform a detection assay, including all controls, directions for performing assays, and any necessary software for analysis and presentation of results.
5. In vivo Imaging
In some embodiments, in vivo imaging techniques are used to visualize the expression of cancer markers in an animal (e.g., a human or non-human mammal). For example, in some embodiments, cancer marker mRNA or protein is labeled using an labeled antibody specific for the cancer marker. A specifically bound and labeled antibody can be detected in an individual using an in vivo imaging method, including, but not limited to, radionuclide imaging, positron emission tomography, computerized axial tomography, X-ray or magnetic resonance imaging method, fluorescence detection, and chemiluminescent detection. Methods for generating antibodies to the cancer markers of the present invention are described below.
The in vivo imaging methods of the present invention are useful in the diagnosis of cancers that express the cancer markers of the present invention (e.g., prostate cancer). In vivo imaging is used to visualize the presence of a marker indicative of the cancer. Such techniques allow for diagnosis without the use of an unpleasant biopsy. The in vivo imaging methods of the present invention are also useful for providing prognoses to cancer patients. For example, the presence of a marker indicative of cancers likely to metastasize can be detected. The in vivo imaging methods of the present invention can further be used to detect metastatic cancers in other parts of the body.
In some embodiments, reagents (e.g., antibodies) specific for the cancer markers of the present invention are fluorescently labeled. The labeled antibodies are introduced into a subject (e.g., orally or parenterally). Fluorescently labeled antibodies are detected using any suitable method (e.g., using the apparatus described in U.S. Pat. No. 6,198,107, herein incorporated by reference).
In other embodiments, antibodies are radioactively labeled. The use of antibodies for in vivo diagnosis is well known in the art. Sumerdon et al., (Nucl. Med. Biol 17:247-254 [1990] have described an optimized antibody-chelator for the radioimmunoscintographic imaging of tumors using Indium-111 as the label. Griffin et al., (J Clin One 9:631-640 [1991]) have described the use of this agent in detecting tumors in patients suspected of having recurrent colorectal cancer. The use of similar agents with paramagnetic ions as labels for magnetic resonance imaging is known in the art (Lauffer, Magnetic Resonance in Medicine 22:339-342 [1991]). The label used will depend on the imaging modality chosen. Radioactive labels such as Indium-111, Technetium-99m, or Iodine-131 can be used for planar scans or single photon emission computed tomography (SPECT). Positron emitting labels such as Fluorine-19 can also be used for positron emission tomography (PET). For MRI, paramagnetic ions such as Gadolinium (III) or Manganese (II) can be used.
Radioactive metals with half-lives ranging from 1 hour to 3.5 days are available for conjugation to antibodies, such as scandium-47 (3.5 days) gallium-67 (2.8 days), gallium-68 (68 minutes), technetium-99m (6 hours), and indium-111 (3.2 days), of which gallium-67, technetium-99m, and indium-111 are preferable for gamma camera imaging, gallium-68 is preferable for positron emission tomography.
A useful method of labeling antibodies with such radiometals is by means of a bifunctional chelating agent, such as diethylenetriaminepentaacetic acid (DTPA), as described, for example, by Khaw et al. (Science 209:295 [1980]) for In-111 and Tc-99m, and by Scheinberg et al. (Science 215:1511 [1982]). Other chelating agents may also be used, but the 1-(p-carboxymethoxybenzyl) EDTA and the carboxycarbonic anhydride of DTPA are advantageous because their use permits conjugation without affecting the antibody's immunoreactivity substantially.
Another method for coupling DPTA to proteins is by use of the cyclic anhydride of DTPA, as described by Hnatowich et al. (Int. J. Appl. Radiat. Isot. 33:327 [1982]) for labeling of albumin with In-111, but which can be adapted for labeling of antibodies. A suitable method of labeling antibodies with Tc-99m which does not use chelation with DPTA is the pretinning method of Crockford et al., (U.S. Pat. No. 4,323,546, herein incorporated by reference).
A preferred method of labeling immunoglobulins with Tc-99m is that described by Wong et al. (Int. J. Appl. Radiat. Isot., 29:251 [1978]) for plasma protein, and recently applied successfully by Wong et al. (J. Nucl. Med., 23:229 [1981]) for labeling antibodies.
In the case of the radiometals conjugated to the specific antibody, it is likewise desirable to introduce as high a proportion of the radiolabel as possible into the antibody molecule without destroying its immunospecificity. A further improvement may be achieved by effecting radiolabeling in the presence of the specific cancer marker of the present invention, to insure that the antigen binding site on the antibody will be protected. The antigen is separated after labeling.
In still further embodiments, in vivo biophotonic imaging (Xenogen, Almeda, Calif.) is utilized for in vivo imaging. This real-time in vivo imaging utilizes luciferase. The luciferase gene is incorporated into cells, microorganisms, and animals (e.g., as a fusion protein with a cancer marker of the present invention). When active, it leads to a reaction that emits light. A CCD camera and software is used to capture the image and analyze it.
II. Antibodies
The present invention provides isolated antibodies. In preferred embodiments, the present invention provides monoclonal antibodies that specifically bind to an isolated polypeptide comprised of at least five amino acid residues of the cancer markers described herein (e.g., hepsin, pim-1, AMACR, EZH2, CTBP). These antibodies find use in the diagnostic methods described herein.
An antibody against a protein of the present invention may be any monoclonal or polyclonal antibody, as long as it can recognize the protein. Antibodies can be produced by using a protein of the present invention as the antigen according to a conventional antibody or antiserum preparation process.
The present invention contemplates the use of both monoclonal and polyclonal antibodies. Any suitable method may be used to generate the antibodies used in the methods and compositions of the present invention, including but not limited to, those disclosed herein. For example, for preparation of a monoclonal antibody, protein, as such, or together with a suitable carrier or diluent is administered to an animal (e.g., a mammal) under conditions that permit the production of antibodies. For enhancing the antibody production capability, complete or incomplete Freund's adjuvant may be administered. Normally, the protein is administered once every 2 weeks to 6 weeks, in total, about 2 times to about 10 times. Animals suitable for use in such methods include, but are not limited to, primates, rabbits, dogs, guinea pigs, mice, rats, sheep, goats, etc.
For preparing monoclonal antibody-producing cells, an individual animal whose antibody titer has been confirmed (e.g., a mouse) is selected, and 2 days to 5 days after the final immunization, its spleen or lymph node is harvested and antibody-producing cells contained therein are fused with myeloma cells to prepare the desired monoclonal antibody producer hybridoma. Measurement of the antibody titer in antiserum can be carried out, for example, by reacting the labeled protein, as described hereinafter and antiserum and then measuring the activity of the labeling agent bound to the antibody. The cell fusion can be carried out according to known methods, for example, the method described by Koehler and Milstein (Nature 256:495 [1975]). As a fusion promoter, for example, polyethylene glycol (PEG) or Sendai virus (HVJ), preferably PEG is used.
Examples of myeloma cells include NS-1, P3U1SP2/0, AP-1 and the like. The proportion of the number of antibody producer cells (spleen cells) and the number of myeloma cells to be used is preferably about 1:1 to about 20:1. PEG (preferably PEG 1000-PEG 6000) is preferably added in concentration of about 10% to about 80%. Cell fusion can be carried out efficiently by incubating a mixture of both cells at about 20° C. to about 40° C., preferably about 30° C. to about 37° C. for about 1 minute to 10 minutes.
Various methods may be used for screening for a hybridoma producing the antibody (e.g., against a tumor antigen or autoantibody of the present invention). For example, where a supernatant of the hybridoma is added to a solid phase (e.g., microplate) to which antibody is adsorbed directly or together with a carrier and then an anti-immunoglobulin antibody (if mouse cells are used in cell fusion, anti-mouse immunoglobulin antibody is used) or Protein A labeled with a radioactive substance or an enzyme is added to detect the monoclonal antibody against the protein bound to the solid phase. Alternately, a supernatant of the hybridoma is added to a solid phase to which an anti-immunoglobulin antibody or Protein A is adsorbed and then the protein labeled with a radioactive substance or an enzyme is added to detect the monoclonal antibody against the protein bound to the solid phase.
Selection of the monoclonal antibody can be carried out according to any known method or its modification. Normally, a medium for animal cells to which HAT (hypoxanthine, aminopterin, thymidine) are added is employed. Any selection and growth medium can be employed as long as the hybridoma can grow. For example, RPMI 1640 medium containing 1% to 20%, preferably 10% to 20% fetal bovine serum, GIT medium containing 1% to 10% fetal bovine serum, a serum free medium for cultivation of a hybridoma (SFM-101, Nissui Seiyaku) and the like can be used. Normally, the cultivation is carried out at 20° C. to 40° C., preferably 37° C. for about 5 days to 3 weeks, preferably 1 week to 2 weeks under about 5% CO2 gas. The antibody titer of the supernatant of a hybridoma culture can be measured according to the same manner as described above with respect to the antibody titer of the anti-protein in the antiserum.
Separation and purification of a monoclonal antibody (e.g., against a cancer marker of the present invention) can be carried out according to the same manner as those of conventional polyclonal antibodies such as separation and purification of immunoglobulins, for example, salting-out, alcoholic precipitation, isoelectric point precipitation, electrophoresis, adsorption and desorption with ion exchangers (e.g., DEAE), ultracentrifugation, gel filtration, or a specific purification method wherein only an antibody is collected with an active adsorbent such as an antigen-binding solid phase, Protein A or Protein G and dissociating the binding to obtain the antibody.
Polyclonal antibodies may be prepared by any known method or modifications of these methods including obtaining antibodies from patients. For example, a complex of an immunogen (an antigen against the protein) and a carrier protein is prepared and an animal is immunized by the complex according to the same manner as that described with respect to the above monoclonal antibody preparation. A material containing the antibody against is recovered from the immunized animal and the antibody is separated and purified.
As to the complex of the immunogen and the carrier protein to be used for immunization of an animal, any carrier protein and any mixing proportion of the carrier and a hapten can be employed as long as an antibody against the hapten, which is crosslinked on the carrier and used for immunization, is produced efficiently. For example, bovine serum albumin, bovine cycloglobulin, keyhole limpet hemocyanin, etc. may be coupled to an hapten in a weight ratio of about 0.1 part to about 20 parts, preferably, about 1 part to about 5 parts per 1 part of the hapten.
In addition, various condensing agents can be used for coupling of a hapten and a carrier. For example, glutaraldehyde, carbodiimide, maleimide activated ester, activated ester reagents containing thiol group or dithiopyridyl group, and the like find use with the present invention. The condensation product as such or together with a suitable carrier or diluent is administered to a site of an animal that permits the antibody production. For enhancing the antibody production capability, complete or incomplete Freund's adjuvant may be administered. Normally, the protein is administered once every 2 weeks to 6 weeks, in total, about 3 times to about 10 times.
The polyclonal antibody is recovered from blood, ascites and the like, of an animal immunized by the above method. The antibody titer in the antiserum can be measured according to the same manner as that described above with respect to the supernatant of the hybridoma culture. Separation and purification of the antibody can be carried out according to the same separation and purification method of immunoglobulin as that described with respect to the above monoclonal antibody.
The protein used herein as the immunogen is not limited to any particular type of immunogen. For example, a cancer marker of the present invention (further including a gene having a nucleotide sequence partly altered) can be used as the immunogen. Further, fragments of the protein may be used. Fragments may be obtained by any methods including, but not limited to expressing a fragment of the gene, enzymatic processing of the protein, chemical synthesis, and the like.
III. Drug Screening
In some embodiments, the present invention provides drug screening assays (e.g., to screen for anticancer drugs). The screening methods of the present invention utilize cancer markers identified using the methods of the present invention (e.g., including but not limited to, hepsin, pim-1, AMACR, EZH2, and CTBP). For example, in some embodiments, the present invention provides methods of screening for compound that alter (e.g., increase or decrease) the expression of cancer marker genes. In some embodiments, candidate compounds are antisense agents (e.g., oligonucleotides) directed against cancer markers. See Section IV below for a discussion of antisense therapy. In other embodiments, candidate compounds are antibodies that specifically bind to a cancer marker of the present invention.
In one screening method, candidate compounds are evaluated for their ability to alter cancer marker expression by contacting a compound with a cell expressing a cancer marker and then assaying for the effect of the candidate compounds on expression. In some embodiments, the effect of candidate compounds on expression of a cancer marker gene is assayed for by detecting the level of cancer marker mRNA expressed by the cell. mRNA expression can be detected by any suitable method. In other embodiments, the effect of candidate compounds on expression of cancer marker genes is assayed by measuring the level of polypeptide encoded by the cancer markers. The level of polypeptide expressed can be measured using any suitable method, including but not limited to, those disclosed herein.
Specifically, the present invention provides screening methods for identifying modulators, i.e., candidate or test compounds or agents (e.g., proteins, peptides, peptidomimetics, peptoids, small molecules or other drugs) which bind to cancer markers of the present invention, have an inhibitory (or stimulatory) effect on, for example, cancer marker expression or cancer markers activity, or have a stimulatory or inhibitory effect on, for example, the expression or activity of a cancer marker substrate. Compounds thus identified can be used to modulate the activity of target gene products (e.g., cancer marker genes) either directly or indirectly in a therapeutic protocol, to elaborate the biological function of the target gene product, or to identify compounds that disrupt normal target gene interactions. Compounds which inhibit the activity or expression of cancer markers are useful in the treatment of proliferative disorders, e.g., cancer, particularly metastatic (e.g., androgen independent) prostate cancer.
In one embodiment, the invention provides assays for screening candidate or test compounds that are substrates of a cancer markers protein or polypeptide or a biologically active portion thereof. In another embodiment, the invention provides assays for screening candidate or test compounds that bind to or modulate the activity of a cancer marker protein or polypeptide or a biologically active portion thereof.
The test compounds of the present invention can be obtained using any of the numerous approaches in combinatorial library methods known in the art, including biological libraries; peptoid libraries (libraries of molecules having the functionalities of peptides, but with a novel, non-peptide backbone, which are resistant to enzymatic degradation but which nevertheless remain bioactive; see, e.g., Zuckennann et al., J. Med. Chem. 37: 2678-85 [1994]); spatially addressable parallel solid phase or solution phase libraries; synthetic library methods requiring deconvolution; the ‘one-bead one-compound’library method; and synthetic library methods using affinity chromatography selection. The biological library and peptoid library approaches are preferred for use with peptide libraries, while the other four approaches are applicable to peptide, non-peptide oligomer or small molecule libraries of compounds (Lam (1997) Anticancer Drug Des. 12:145).
Examples of methods for the synthesis of molecular libraries can be found in the art, for example in: DeWitt et al., Proc. Natl. Acad. Sci. U.S.A. 90:6909 [1993]; Erb et al., Proc. Nad. Acad. Sci. USA 91:11422 [1994]; Zuckermann et al., J. Med. Chem. 37:2678 [1994]; Cho et al., Science 261:1303 [1993]; Carrell et al., Angew. Chem. Int. Ed. Engl. 33.2059 [1994]; Carell et al., Angew. Chem. Int. Ed. Engl. 33:2061 [1994]; and Gallop et al., J. Med. Chem. 37:1233 [1994].
Libraries of compounds may be presented in solution (e.g., Houghten, Biotechniques 13:412-421 [1992]), or on beads (Lam, Nature 354:82-84 [1991]), chips (Fodor, Nature 364:555-556 [1993]), bacteria or spores (U.S. Pat. No. 5,223,409; herein incorporated by reference), plasmids (Cull et al., Proc. Nad. Acad. Sci. USA 89:18651869 [1992]) or on phage (Scott and Smith, Science 249:386-390 [1990]; Devlin Science 249:404-406 [1990]; Cwirla et al., Proc. NatI. Acad. Sci. 87:6378-6382 [1990]; Felici, J. Mol. Biol. 222:301 [1991]).
In one embodiment, an assay is a cell-based assay in which a cell that expresses a cancer marker protein or biologically active portion thereof is contacted with a test compound, and the ability of the test compound to the modulate cancer marker's activity is determined. Determining the ability of the test compound to modulate cancer marker activity can be accomplished by monitoring, for example, changes in enzymatic activity. The cell, for example, can be of mammalian origin.
The ability of the test compound to modulate cancer marker binding to a compound, e.g., a cancer marker substrate, can also be evaluated. This can be accomplished, for example, by coupling the compound, e.g., the substrate, with a radioisotope or enzymatic label such that binding of the compound, e.g., the substrate, to a cancer marker can be determined by detecting the labeled compound, e.g., substrate, in a complex.
Alternatively, the cancer marker is coupled with a radioisotope or enzymatic label to monitor the ability of a test compound to modulate cancer marker binding to a cancer markers substrate in a complex. For example, compounds (e.g., substrates) can be labeled with 125I, 35S14C or 3H, either directly or indirectly, and the radioisotope detected by direct counting of radioemmission or by scintillation counting. Alternatively, compounds can be enzymatically labeled with, for example, horseradish peroxidase, alkaline phosphatase, or luciferase, and the enzymatic label detected by determination of conversion of an appropriate substrate to product.
The ability of a compound (e.g., a cancer marker substrate) to interact with a cancer marker with or without the labeling of any of the interactants can be evaluated. For example, a microphysiorneter can be used to detect the interaction of a compound with a cancer marker without the labeling of either the compound or the cancer marker (McConnell et al. Science 257:1906-1912 [1992]). As used herein, a “microphysiometer” (e.g., Cytosensor) is an analytical instrument that measures the rate at which a cell acidifies its environment using a light-addressable potentiometric sensor (LAPS). Changes in this acidification rate can be used as an indicator of the interaction between a compound and cancer markers.
In yet another embodiment, a cell-free assay is provided in which a cancer marker protein or biologically active portion thereof is contacted with a test compound and the ability of the test compound to bind to the cancer marker protein or biologically active portion thereof is evaluated. Preferred biologically active portions of the cancer markers proteins to be used in assays of the present invention include fragments that participate in interactions with substrates or other proteins, e.g., fragments with high surface probability scores.
Cell-free assays involve preparing a reaction mixture of the target gene protein and the test compound under conditions and for a time sufficient to allow the two components to interact and bind, thus forming a complex that can be removed and/or detected.
The interaction between two molecules can also be detected, e.g., using fluorescence energy transfer (FRET) (see, for example, Lakowicz et al., U.S. Pat. No. 5,631,169; Stavrianopoulos et al., U.S. Pat. No. 4,968,103; each of which is herein incorporated by reference). A fluorophore label is selected such that a first donor molecule's emitted fluorescent energy will be absorbed by a fluorescent label on a second, ‘acceptor’ molecule, which in turn is able to fluoresce due to the absorbed energy.
Alternately, the ‘donor’ protein molecule may simply utilize the natural fluorescent energy of tryptophan residues. Labels are chosen that emit different wavelengths of light, such that the ‘acceptor’ molecule label may be differentiated from that of the ‘donor’. Since the efficiency of energy transfer between the labels is related to the distance separating the molecules, the spatial relationship between the molecules can be assessed. In a situation in which binding occurs between the molecules, the fluorescent emission of the ‘acceptor’ molecule label in 15 the assay should be maximal. An FRET binding event can be conveniently measured through standard fluorometric detection means well known in the art (e.g., using a fluorimeter).
In another embodiment, determining the ability of the cancer markers protein to bind to a target molecule can be accomplished using real-time Biomolecular Interaction Analysis (BIA) (see, e.g., Sjolander and Urbaniczky, Anal. Chem. 63:2338-2345 [1991] and Szabo et al. Curr. Opin. Struct. Biol. 5:699-705 [1995]). “Surface plasmon resonance” or “BIA” detects biospecific interactions in real time, without labeling any of the interactants (e.g., BIAcore). Changes in the mass at the binding surface (indicative of a binding event) result in alterations of the refractive index of light near the surface (the optical phenomenon of surface plasmon resonance (SPR)), resulting in a detectable signal that can be used as an indication of real-time reactions between biological molecules.
In one embodiment, the target gene product or the test substance is anchored onto a solid phase. The target gene product/test compound complexes anchored on the solid phase can be detected at the end of the reaction. Preferably, the target gene product can be anchored onto a solid surface, and the test compound, (which is not anchored), can be labeled, either directly or indirectly, with detectable labels discussed herein.
It may be desirable to immobilize cancer markers, an anti-cancer marker antibody or its target molecule to facilitate separation of complexed from non-complexed forms of one or both of the proteins, as well as to accommodate automation of the assay. Binding of a test compound to a cancer marker protein, or interaction of a cancer marker protein with a target molecule in the presence and absence of a candidate compound, can be accomplished in any vessel suitable for containing the reactants. Examples of such vessels include microtiter plates, test tubes, and micro-centrifuge tubes. In one embodiment, a fusion protein can be provided which adds a domain that allows one or both of the proteins to be bound to a matrix. For example, glutathione-S-transferase-cancer marker fusion proteins or glutathione-S-transferase/target fusion proteins can be adsorbed onto glutathione Sepharose beads (Sigma Chemical, St. Louis, Mo.) or glutathione-derivatized microtiter plates, which are then combined with the test compound or the test compound and either the non-adsorbed target protein or cancer marker protein, and the mixture incubated under conditions conducive for complex formation (e.g., at physiological conditions for salt and pH). Following incubation, the beads or microtiter plate wells are washed to remove any unbound components, the matrix immobilized in the case of beads, complex determined either directly or indirectly, for example, as described above.
Alternatively, the complexes can be dissociated from the matrix, and the level of cancer markers binding or activity determined using standard techniques. Other techniques for immobilizing either cancer markers protein or a target molecule on matrices include using conjugation of biotin and streptavidin. Biotinylated cancer marker protein or target molecules can be prepared from biotin-NHS (N-hydroxy-succinimide) using techniques known in the art (e.g., biotinylation kit, Pierce Chemicals, Rockford, EL), and immobilized in the wells of streptavidin-coated 96 well plates (Pierce Chemical).
In order to conduct the assay, the non-immobilized component is added to the coated surface containing the anchored component. After the reaction is complete, unreacted components are removed (e.g., by washing) under conditions such that any complexes formed will remain immobilized on the solid surface. The detection of complexes anchored on the solid surface can be accomplished in a number of ways. Where the previously non-immobilized component is pre-labeled, the detection of label immobilized on the surface indicates that complexes were formed. Where the previously non-immobilized component is not pre-labeled, an indirect label can be used to detect complexes anchored on the surface; e.g., using a labeled antibody specific for the immobilized component (the antibody, in turn, can be directly labeled or indirectly labeled with, e.g., a labeled anti-IgG antibody).
This assay is performed utilizing antibodies reactive with cancer marker protein or target molecules but which do not interfere with binding of the cancer markers protein to its target molecule. Such antibodies can be derivatized to the wells of the plate, and unbound target or cancer markers protein trapped in the wells by antibody conjugation. Methods for detecting such complexes, in addition to those described above for the GST-immobilized complexes, include immunodetection of complexes using antibodies reactive with the cancer marker protein or target molecule, as well as enzyme-linked assays which rely on detecting an enzymatic activity associated with the cancer marker protein or target molecule.
Alternatively, cell free assays can be conducted in a liquid phase. In such an assay, the reaction products are separated from unreacted components, by any of a number of standard techniques, including, but not limited to: differential centrifugation (see, for example, Rivas and Minton, Trends Biochem Sci 18:284-7 [1993]); chromatography (gel filtration chromatography, ion-exchange chromatography); electrophoresis (see, e.g., Ausubel et al., eds. Current Protocols in Molecular Biology 1999, J. Wiley: New York.); and immunoprecipitation (see, for example, Ausubel et al., eds. Current Protocols in Molecular Biology 1999, J. Wiley: New York). Such resins and chromatographic techniques are known to one skilled in the art (See e.g., Heegaard J. Mol. Recognit 11:141-8 [1998]; Hageand Tweed J. Chromatogr. Biomed. Sci. Appl 699:499-525 [1997]). Further, fluorescence energy transfer may also be conveniently utilized, as described herein, to detect binding without further purification of the complex from solution.
The assay can include contacting the cancer markers protein or biologically active portion thereof with a known compound that binds the cancer marker to form an assay mixture, contacting the assay mixture with a test compound, and determining the ability of the test compound to interact with a cancer marker protein, wherein determining the ability of the test compound to interact with a cancer marker protein includes determining the ability of the test compound to preferentially bind to cancer markers or biologically active portion thereof, or to modulate the activity of a target molecule, as compared to the known compound.
To the extent that cancer markers can, in vivo, interact with one or more cellular or extracellular macromolecules, such as proteins, inhibitors of such an interaction are useful. A homogeneous assay can be used can be used to identify inhibitors.
For example, a preformed complex of the target gene product and the interactive cellular or extracellular binding partner product is prepared such that either the target gene products or their binding partners are labeled, but the signal generated by the label is quenched due to complex formation (see, e.g., U.S. Pat. No. 4,109,496, herein incorporated by reference, that utilizes this approach for immunoassays). The addition of a test substance that competes with and displaces one of the species from the preformed complex will result in the generation of a signal above background. In this way, test substances that disrupt target gene product-binding partner interaction can be identified. Alternatively, cancer markers protein can be used as a “bait protein” in a two-hybrid assay or three-hybrid assay (see, e.g., U.S. Pat. No. 5,283,317; Zervos et al., Cell 72:223-232 [1993]; Madura et al., J. Biol. Chem. 268.12046-12054 [1993]; Bartel et al., Biotechniques 14:920-924 [1993]; Iwabuchi et al., Oncogene 8:1693-1696 [1993]; and Brent WO 94/10300; each of which is herein incorporated by reference), to identify other proteins, that bind to or interact with cancer markers (“cancer marker-binding proteins” or “cancer marker-bp”) and are involved in cancer marker activity. Such cancer marker-bps can be activators or inhibitors of signals by the cancer marker proteins or targets as, for example, downstream elements of a cancer markers-mediated signaling pathway.
Modulators of cancer markers expression can also be identified. For example, a cell or cell free mixture is contacted with a candidate compound and the expression of cancer marker mRNA or protein evaluated relative to the level of expression of cancer marker mRNA or protein in the absence of the candidate compound. When expression of cancer marker mRNA or protein is greater in the presence of the candidate compound than in its absence, the candidate compound is identified as a stimulator of cancer marker mRNA or protein expression. Alternatively, when expression of cancer marker mRNA or protein is less (i.e., statistically significantly less) in the presence of the candidate compound than in its absence, the candidate compound is identified as an inhibitor of cancer marker mRNA or protein expression. The level of cancer markers mRNA or protein expression can be determined by methods described herein for detecting cancer markers mRNA or protein.
A modulating agent can be identified using a cell-based or a cell free assay, and the ability of the agent to modulate the activity of a cancer markers protein can be confirmed in vivo, e.g., in an animal such as an animal model for a disease (e.g., an animal with prostate cancer or metastatic prostate cancer; or an animal harboring a xenograft of a prostate cancer from an animal (e.g., human) or cells from a cancer resulting from metastasis of a prostate cancer (e.g., to a lymph node, bone, or liver), or cells from a prostate cancer cell line.
This invention further pertains to novel agents identified by the above-described screening assays (See e.g., below description of cancer therapies). Accordingly, it is within the scope of this invention to further use an agent identified as described herein (e.g., a cancer marker modulating agent, an antisense cancer marker nucleic acid molecule, a siRNA molecule, a cancer marker specific antibody, or a cancer marker-binding partner) in an appropriate animal model (such as those described herein) to determine the efficacy, toxicity, side effects, or mechanism of action, of treatment with such an agent. Furthermore, novel agents identified by the above-described screening assays can be, e.g., used for treatments as described herein.
IV. Cancer Therapies
In some embodiments, the present invention provides therapies for cancer (e.g., prostate cancer). In some embodiments, therapies target cancer markers (e.g., including but not limited to, hepsin, pim-1, AMACR, EZH2, and CTBP).
A. Antisense Therapies
In some embodiments, the present invention targets the expression of cancer markers. For example, in some embodiments, the present invention employs compositions comprising oligomeric antisense compounds, particularly oligonucleotides (e.g. those identified in the drug screening methods described above), for use in modulating the function of nucleic acid molecules encoding cancer markers of the present invention, ultimately modulating the amount of cancer marker expressed. This is accomplished by providing antisense compounds that specifically hybridize with one or more nucleic acids encoding cancer markers of the present invention. The specific hybridization of an oligomeric compound with its target nucleic acid interferes with the normal function of the nucleic acid. This modulation of function of a target nucleic acid by compounds that specifically hybridize to it is generally referred to as “antisense.” The functions of DNA to be interfered with include replication and transcription. The functions of RNA to be interfered with include all vital functions such as, for example, translocation of the RNA to the site of protein translation, translation of protein from the RNA, splicing of the RNA to yield one or more mRNA species, and catalytic activity that may be engaged in or facilitated by the RNA. The overall effect of such interference with target nucleic acid function is modulation of the expression of cancer markers of the present invention. In the context of the present invention, “modulation” means either an increase (stimulation) or a decrease (inhibition) in the expression of a gene. For example, expression may be inhibited to potentially prevent tumor proliferation.
It is preferred to target specific nucleic acids for antisense. “Targeting” an antisense compound to a particular nucleic acid, in the context of the present invention, is a multistep process. The process usually begins with the identification of a nucleic acid sequence whose function is to be modulated. This may be, for example, a cellular gene (or mRNA transcribed from the gene) whose expression is associated with a particular disorder or disease state, or a nucleic acid molecule from an infectious agent. In the present invention, the target is a nucleic acid molecule encoding a cancer marker of the present invention. The targeting process also includes determination of a site or sites within this gene for the antisense interaction to occur such that the desired effect, e.g., detection or modulation of expression of the protein, will result. Within the context of the present invention, a preferred intragenic site is the region encompassing the translation initiation or termination codon of the open reading frame (ORF) of the gene. Since the translation initiation codon is typically 5′-AUG (in transcribed mRNA molecules; 5′-ATG in the corresponding DNA molecule), the translation initiation codon is also referred to as the “AUG codon,” the “start codon” or the “AUG start codon”. A minority of genes have a translation initiation codon having the RNA sequence 5′-GUG, 5′-UUG or 5′-CUG, and 5′-AUA, 5′-ACG and 5′-CUG have been shown to function in vivo. Thus, the terms “translation initiation codon” and “start codon” can encompass many codon sequences, even though the initiator amino acid in each instance is typically methionine (in eukaryotes) or formylmethionine (in prokaryotes). Eukaryotic and prokaryotic genes may have two or more alternative start codons, any one of which may be preferentially utilized for translation initiation in a particular cell type or tissue, or under a particular set of conditions. In the context of the present invention, “start codon” and “translation initiation codon” refer to the codon or codons that are used in vivo to initiate translation of an mRNA molecule transcribed from a gene encoding a tumor antigen of the present invention, regardless of the sequence(s) of such codons.
Translation termination codon (or “stop codon”) of a gene may have one of three sequences (i.e., 5′-UAA, 5′-UAG and 5′-UGA; the corresponding DNA sequences are 5′-TAA, 5′-TAG and 5′-TGA, respectively). The terms “start codon region” and “translation initiation codon region” refer to a portion of such an mRNA or gene that encompasses from about 25 to about 50 contiguous nucleotides in either direction (i.e., 5′ or 3′) from a translation initiation codon. Similarly, the terms “stop codon region” and “translation termination codon region” refer to a portion of such an mRNA or gene that encompasses from about 25 to about 50 contiguous nucleotides in either direction (i.e., 5′ or 3′) from a translation termination codon.
The open reading frame (ORF) or “coding region,” which refers to the region between the translation initiation codon and the translation termination codon, is also a region that may be targeted effectively. Other target regions include the 5′ untranslated region (5′ UTR), referring to the portion of an mRNA in the 5′ direction from the translation initiation codon, and thus including nucleotides between the 5′ cap site and the translation initiation codon of an mRNA or corresponding nucleotides on the gene, and the 3′ untranslated region (3′ UTR), referring to the portion of an mRNA in the 3′ direction from the translation termination codon, and thus including nucleotides between the translation termination codon and 3′ end of an mRNA or corresponding nucleotides on the gene. The 5′ cap of an mRNA comprises an N7-methylated guanosine residue joined to the 5′-most residue of the mRNA via a 5′-5′ triphosphate linkage. The 5′ cap region of an mRNA is considered to include the 5′ cap structure itself as well as the first 50 nucleotides adjacent to the cap. The cap region may also be a preferred target region.
Although some eukaryotic mRNA transcripts are directly translated, many contain one or more regions, known as “introns,” that are excised from a transcript before it is translated. The remaining (and therefore translated) regions are known as “exons” and are spliced together to form a continuous mRNA sequence. mRNA splice sites (i.e., intron-exon junctions) may also be preferred target regions, and are particularly useful in situations where aberrant splicing is implicated in disease, or where an overproduction of a particular mRNA splice product is implicated in disease. Aberrant fusion junctions due to rearrangements or deletions are also preferred targets. It has also been found that introns can also be effective, and therefore preferred, target regions for antisense compounds targeted, for example, to DNA or pre-mRNA.
In some embodiments, target sites for antisense inhibition are identified using commercially available software programs (e.g., Biognostik, Gottingen, Germany; SysArris Software, Bangalore, India; Antisense Research Group, University of Liverpool, Liverpool, England; GeneTrove, Carlsbad, Calif.). In other embodiments, target sites for antisense inhibition are identified using the accessible site method described in U.S. patent WO0198537A2, herein incorporated by reference.
Once one or more target sites have been identified, oligonucleotides are chosen that are sufficiently complementary to the target (i.e., hybridize sufficiently well and with sufficient specificity) to give the desired effect. For example, in preferred embodiments of the present invention, antisense oligonucleotides are targeted to or near the start codon.
In the context of this invention, “hybridization,” with respect to antisense compositions and methods, means hydrogen bonding, which may be Watson-Crick, Hoogsteen or reversed Hoogsteen hydrogen bonding, between complementary nucleoside or nucleotide bases. For example, adenine and thymine are complementary nucleobases that pair through the formation of hydrogen bonds. It is understood that the sequence of an antisense compound need not be 100% complementary to that of its target nucleic acid to be specifically hybridizable. An antisense compound is specifically hybridizable when binding of the compound to the target DNA or RNA molecule interferes with the normal function of the target DNA or RNA to cause a loss of utility, and there is a sufficient degree of complementarity to avoid non-specific binding of the antisense compound to non-target sequences under conditions in which specific binding is desired (i.e., under physiological conditions in the case of in vivo assays or therapeutic treatment, and in the case of in vitro assays, under conditions in which the assays are performed).
Antisense compounds are commonly used as research reagents and diagnostics. For example, antisense oligonucleotides, which are able to inhibit gene expression with specificity, can be used to elucidate the function of particular genes. Antisense compounds are also used, for example, to distinguish between functions of various members of a biological pathway.
The specificity and sensitivity of antisense is also applied for therapeutic uses. For example, antisense oligonucleotides have been employed as therapeutic moieties in the treatment of disease states in animals and man. Antisense oligonucleotides have been safely and effectively administered to humans and numerous clinical trials are presently underway. It is thus established that oligonucleotides are useful therapeutic modalities that can be configured to be useful in treatment regimes for treatment of cells, tissues, and animals, especially humans.
While antisense oligonucleotides are a preferred form of antisense compound, the present invention comprehends other oligomeric antisense compounds, including but not limited to oligonucleotide mimetics such as are described below. The antisense compounds in accordance with this invention preferably comprise from about 8 to about 30 nucleobases (i.e., from about 8 to about 30 linked bases), although both longer and shorter sequences may find use with the present invention. Particularly preferred antisense compounds are antisense oligonucleotides, even more preferably those comprising from about 12 to about 25 nucleobases.
Specific examples of preferred antisense compounds useful with the present invention include oligonucleotides containing modified backbones or non-natural internucleoside linkages. As defined in this specification, oligonucleotides having modified backbones include those that retain a phosphorus atom in the backbone and those that do not have a phosphorus atom in the backbone. For the purposes of this specification, modified oligonucleotides that do not have a phosphorus atom in their internucleoside backbone can also be considered to be oligonucleosides.
Preferred modified oligonucleotide backbones include, for example, phosphorothioates, chiral phosphorothioates, phosphorodithioates, phosphotriesters, aminoalkylphosphotriesters, methyl and other alkyl phosphonates including 3′-alkylene phosphonates and chiral phosphonates, phosphinates, phosphoramidates including 3′-amino phosphoramidate and aminoalkylphosphoramidates, thionophosphoramidates, thionoalkylphosphonates, thionoalkylphosphotriesters, and boranophosphates having normal 3′-5′ linkages, 2′-5′ linked analogs of these, and those having inverted polarity wherein the adjacent pairs of nucleoside units are linked 3′-5′ to 5′-3′ or 2′-5′ to 5′-2′. Various salts, mixed salts and free acid forms are also included.
Preferred modified oligonucleotide backbones that do not include a phosphorus atom therein have backbones that are formed by short chain alkyl or cycloalkyl internucleoside linkages, mixed heteroatom and alkyl or cycloalkyl internucleoside linkages, or one or more short chain heteroatomic or heterocyclic internucleoside linkages. These include those having morpholino linkages (formed in part from the sugar portion of a nucleoside); siloxane backbones; sulfide, sulfoxide and sulfone backbones; formacetyl and thioformacetyl backbones; methylene formacetyl and thioformacetyl backbones; alkene containing backbones; sulfamate backbones; methyleneimino and methylenehydrazino backbones; sulfonate and sulfonamide backbones; amide backbones; and others having mixed N, O, S and CH2 component parts.
In other preferred oligonucleotide mimetics, both the sugar and the internucleoside linkage (i.e., the backbone) of the nucleotide units are replaced with novel groups. The base units are maintained for hybridization with an appropriate nucleic acid target compound. One such oligomeric compound, an oligonucleotide mimetic that has been shown to have excellent hybridization properties, is referred to as a peptide nucleic acid (PNA). In PNA compounds, the sugar-backbone of an oligonucleotide is replaced with an amide containing backbone, in particular an aminoethylglycine backbone. The nucleobases are retained and are bound directly or indirectly to aza nitrogen atoms of the amide portion of the backbone. Representative United States patents that teach the preparation of PNA compounds include, but are not limited to, U.S. Pat. Nos. 5,539,082; 5,714,331; and 5,719,262, each of which is herein incorporated by reference. Further teaching of PNA compounds can be found in Nielsen et al., Science 254:1497 (1991).
Most preferred embodiments of the invention are oligonucleotides with phosphorothioate backbones and oligonucleosides with heteroatom backbones, and in particular —CH2, —NH—O—CH2—, —CH2—N(CH3)—O—CH2— [known as a methylene (methylimino) or MMI backbone], —CH2—O—N(CH3)—CH2—, —CH2—N(CH3)—N(CH3)—CH2—, and —O—N(CH3)—CH2—CH2— [wherein the phosphodiester backbone is represented as —O—P—O—CH2—] of the above referenced U.S. Pat. No. 5,489,677, and the amide backbones of the above referenced U.S. Pat. No. 5,602,240. Also preferred are oligonucleotides having morpholino backbone structures of the above-referenced U.S. Pat. No. 5,034,506.
Modified oligonucleotides may also contain one or more substituted sugar moieties. Preferred oligonucleotides comprise one of the following at the 2′ position: OH; F; O-, S-, or N-alkyl; O-, S-, or N-alkenyl; O-, S- or N-alkynyl; or O-alkyl-O-alkyl, wherein the alkyl, alkenyl and alkynyl may be substituted or unsubstituted C1 to C10 alkyl or C2 to C10 alkenyl and alkynyl. Particularly preferred are O[(CH2)nO]mCH3, O(CH2)nOCH3, O(CH2)nNH2, O(CH2)nCH3, O(CH2)nONH2, and O(CH2)nON[(CH2)nCH3)]2, where n and m are from 1 to about 10. Other preferred oligonucleotides comprise one of the following at the 2′ position: C1 to C10 lower alkyl, substituted lower alkyl, alkaryl, aralkyl, O-alkaryl or O-aralkyl, SH, SCH3, OCN, Cl, Br, CN, CF3, OCF3, SOCH3, SO2CH3, ONO2, NO2, N3, NH2, heterocycloalkyl, heterocycloalkaryl, aminoalkylamino, polyalkylamino, substituted silyl, an RNA cleaving group, a reporter group, an intercalator, a group for improving the pharmacokinetic properties of an oligonucleotide, or a group for improving the pharmacodynamic properties of an oligonucleotide, and other substituents having similar properties. A preferred modification includes 2′-methoxyethoxy (2′-O—CH2CH2OCH3, also known as 2′-O-(2-methoxyethyl) or 2′-MOE) (Martin et al., Helv. Chim. Acta 78:486 [1995]) i.e., an alkoxyalkoxy group. A further preferred modification includes 2′-dimethylaminooxyethoxy (i.e., a O(CH2)2ON(CH3)2 group), also known as 2′-DMAOE, and 2′-dimethylaminoethoxyethoxy (also known in the art as 2′-O-dimethylaminoethoxyethyl or 2′-DMAEOE), i.e., 2′-O—CH2—O—CH2—N(CH2)2.
Other preferred modifications include 2′-methoxy(2′-O—CH3), 2′-aminopropoxy(2′-OCH2CH2CH2NH2) and 2′-fluoro (2′-F). Similar modifications may also be made at other positions on the oligonucleotide, particularly the 3′ position of the sugar on the 3′ terminal nucleotide or in 2′-5′ linked oligonucleotides and the 5′ position of 5′ terminal nucleotide. Oligonucleotides may also have sugar mimetics such as cyclobutyl moieties in place of the pentofuranosyl sugar.
Oligonucleotides may also include nucleobase (often referred to in the art simply as “base”) modifications or substitutions. As used herein, “unmodified” or “natural” nucleobases include the purine bases adenine (A) and guanine (G), and the pyrimidine bases thymine (T), cytosine (C) and uracil (U). Modified nucleobases include other synthetic and natural nucleobases such as 5-methylcytosine (5-me-C), 5-hydroxymethyl cytosine, xanthine, hypoxanthine, 2-aminoadenine, 6-methyl and other alkyl derivatives of adenine and guanine, 2-propyl and other alkyl derivatives of adenine and guanine, 2-thiouracil, 2-thiothymine and 2-thiocytosine, 5-halouracil and cytosine, 5-propynyl uracil and cytosine, 6-azo uracil, cytosine and thymine, 5-uracil (pseudouracil), 4-thiouracil, 8-halo, 8-amino, 8-thiol, 8-thioalkyl, 8-hydroxyl and other 8-substituted adenines and guanines, 5-halo particularly 5-bromo, 5-trifluoromethyl and other 5-substituted uracils and cytosines, 7-methylguanine and 7-methyladenine, 8-azaguanine and 8-azaadenine, 7-deazaguanine and 7-deazaadenine and 3-deazaguanine and 3-deazaadenine. Further nucleobases include those disclosed in U.S. Pat. No. 3,687,808. Certain of these nucleobases are particularly useful for increasing the binding affinity of the oligomeric compounds of the invention. These include 5-substituted pyrimidines, 6-azapyrimidines and N-2, N-6 and O-6 substituted purines, including 2-aminopropyladenine, 5-propynyluracil and 5-propynylcytosine. 5-methylcytosine substitutions have been shown to increase nucleic acid duplex stability by 0.6-1.2. degree ° C. and are presently preferred base substitutions, even more particularly when combined with 2′-O-methoxyethyl sugar modifications.
Another modification of the oligonucleotides of the present invention involves chemically linking to the oligonucleotide one or more moieties or conjugates that enhance the activity, cellular distribution or cellular uptake of the oligonucleotide. Such moieties include but are not limited to lipid moieties such as a cholesterol moiety, cholic acid, a thioether, (e.g., hexyl-S-tritylthiol), a thiocholesterol, an aliphatic chain, (e.g., dodecandiol or undecyl residues), a phospholipid, (e.g., di-hexadecyl-rac-glycerol or triethylammonium 1,2-di-O-hexadecyl-rac-glycero-3-H-phosphonate), a polyamine or a polyethylene glycol chain or adamantane acetic acid, a palmityl moiety, or an octadecylamine or hexylamino-carbonyl-oxycholesterol moiety.
One skilled in the relevant art knows well how to generate oligonucleotides containing the above-described modifications. The present invention is not limited to the antisensce oligonucleotides described above. Any suitable modification or substitution may be utilized.
It is not necessary for all positions in a given compound to be uniformly modified, and in fact more than one of the aforementioned modifications may be incorporated in a single compound or even at a single nucleoside within an oligonucleotide. The present invention also includes antisense compounds that are chimeric compounds. “Chimeric” antisense compounds or “chimeras,” in the context of the present invention, are antisense compounds, particularly oligonucleotides, which contain two or more chemically distinct regions, each made up of at least one monomer unit, i.e., a nucleotide in the case of an oligonucleotide compound. These oligonucleotides typically contain at least one region wherein the oligonucleotide is modified so as to confer upon the oligonucleotide increased resistance to nuclease degradation, increased cellular uptake, and/or increased binding affinity for the target nucleic acid. An additional region of the oligonucleotide may serve as a substrate for enzymes capable of cleaving RNA:DNA or RNA:RNA hybrids. By way of example, RNaseH is a cellular endonuclease that cleaves the RNA strand of an RNA:DNA duplex. Activation of RNase H, therefore, results in cleavage of the RNA target, thereby greatly enhancing the efficiency of oligonucleotide inhibition of gene expression. Consequently, comparable results can often be obtained with shorter oligonucleotides when chimeric oligonucleotides are used, compared to phosphorothioate deoxyoligonucleotides hybridizing to the same target region. Cleavage of the RNA target can be routinely detected by gel electrophoresis and, if necessary, associated nucleic acid hybridization techniques known in the art.
Chimeric antisense compounds of the present invention may be formed as composite structures of two or more oligonucleotides, modified oligonucleotides, oligonucleosides and/or oligonucleotide mimetics as described above.
The present invention also includes pharmaceutical compositions and formulations that include the antisense compounds of the present invention as described below.
B. Genetic Therapies
The present invention contemplates the use of any genetic manipulation for use in modulating the expression of cancer markers of the present invention. Examples of genetic manipulation include, but are not limited to, gene knockout (e.g., removing the cancer marker gene from the chromosome using, for example, recombination), expression of antisense constructs with or without inducible promoters, and the like. Delivery of nucleic acid construct to cells in vitro or in vivo may be conducted using any suitable method. A suitable method is one that introduces the nucleic acid construct into the cell such that the desired event occurs (e.g., expression of an antisense construct).
Introduction of molecules carrying genetic information into cells is achieved by any of various methods including, but not limited to, directed injection of naked DNA constructs, bombardment with gold particles loaded with said constructs, and macromolecule mediated gene transfer using, for example, liposomes, biopolymers, and the like. Preferred methods use gene delivery vehicles derived from viruses, including, but not limited to, adenoviruses, retroviruses, vaccinia viruses, and adeno-associated viruses. Because of the higher efficiency as compared to retroviruses, vectors derived from adenoviruses are the preferred gene delivery vehicles for transferring nucleic acid molecules into host cells in vivo. Adenoviral vectors have been shown to provide very efficient in vivo gene transfer into a variety of solid tumors in animal models and into human solid tumor xenografts in immune-deficient mice. Examples of adenoviral vectors and methods for gene transfer are described in PCT publications WO 00/12738 and WO 00/09675 and U.S. Pat. Nos. 6,033,908, 6,019,978, 6,001,557, 5,994,132, 5,994,128, 5,994,106, 5,981,225, 5,885,808, 5,872,154, 5,830,730, and 5,824,544, each of which is herein incorporated by reference in its entirety.
Vectors may be administered to subject in a variety of ways. For example, in some embodiments of the present invention, vectors are administered into tumors or tissue associated with tumors using direct injection. In other embodiments, administration is via the blood or lymphatic circulation (See e.g., PCT publication 99/02685 herein incorporated by reference in its entirety). Exemplary dose levels of adenoviral vector are preferably 108 to 1011 vector particles added to the perfusate.
C. Antibody Therapy
In some embodiments, the present invention provides antibodies that target prostate tumors that express a cancer marker of the present invention (e.g., hepsin, pim-1, EZH2, Annexin, CTBP, GP73, and AMACR). Any suitable antibody (e.g., monoclonal, polyclonal, or synthetic) may be utilized in the therapeutic methods disclosed herein. In preferred embodiments, the antibodies used for cancer therapy are humanized antibodies. Methods for humanizing antibodies are well known in the art (See e.g., U.S. Pat. Nos. 6,180,370, 5,585,089, 6,054,297, and 5,565,332; each of which is herein incorporated by reference).
In some embodiments, the therapeutic antibodies comprise an antibody generated against a cancer marker of the present invention (e.g., hepsin, pim-1, EZH2, Annexin, CTBP, GP73, and AMACR), wherein the antibody is conjugated to a cytotoxic agent. In such embodiments, a tumor specific therapeutic agent is generated that does not target normal cells, thus reducing many of the detrimental side effects of traditional chemotherapy. For certain applications, it is envisioned that the therapeutic agents will be pharmacologic agents that will serve as useful agents for attachment to antibodies, particularly cytotoxic or otherwise anticellular agents having the ability to kill or suppress the growth or cell division of endothelial cells. The present invention contemplates the use of any pharmacologic agent that can be conjugated to an antibody, and delivered in active form. Exemplary anticellular agents include chemotherapeutic agents, radioisotopes, and cytotoxins. The therapeutic antibodies of the present invention may include a variety of cytotoxic moieties, including but not limited to, radioactive isotopes (e.g., iodine-131, iodine-123, technicium-99m, indium-111, rhenium-188, rhenium-186, gallium-67, copper-67, yttrium-90, iodine-125 or astatine-211), hormones such as a steroid, antimetabolites such as cytosines (e.g., arabinoside, fluorouracil, methotrexate or aminopterin; an anthracycline; mitomycin C), vinca alkaloids (e.g., demecolcine; etoposide; mithramycin), and antitumor alkylating agent such as chlorambucil or melphalan. Other embodiments may include agents such as a coagulant, a cytokine, growth factor, bacterial endotoxin or the lipid A moiety of bacterial endotoxin. For example, in some embodiments, therapeutic agents will include plant-, fungus- or bacteria-derived toxin, such as an A chain toxins, a ribosome inactivating protein, α-sarcin, aspergillin, restrictocin, a ribonuclease, diphtheria toxin or pseudomonas exotoxin, to mention just a few examples. In some preferred embodiments, deglycosylated ricin A chain is utilized.
In any event, it is proposed that agents such as these may, if desired, be successfully conjugated to an antibody, in a manner that will allow their targeting, internalization, release or presentation to blood components at the site of the targeted tumor cells as required using known conjugation technology (See, e.g., Ghose et al., Methods Enzymol., 93:280 [1983]).
For example, in some embodiments the present invention provides immunotoxins targeted a cancer marker of the present invention (e.g., hepsin, pim-1, EZH2, Annexin, CTBP, GP73, and AMACR). Immunotoxins are conjugates of a specific targeting agent typically a tumor-directed antibody or fragment, with a cytotoxic agent, such as a toxin moiety. The targeting agent directs the toxin to, and thereby selectively kills, cells carrying the targeted antigen. In some embodiments, therapeutic antibodies employ crosslinkers that provide high in vivo stability (Thorpe et al., Cancer Res., 48:6396 [1988]).
In other embodiments, particularly those involving treatment of solid tumors, antibodies are designed to have a cytotoxic or otherwise anticellular effect against the tumor vasculature, by suppressing the growth or cell division of the vascular endothelial cells. This attack is intended to lead to a tumor-localized vascular collapse, depriving the tumor cells, particularly those tumor cells distal of the vasculature, of oxygen and nutrients, ultimately leading to cell death and tumor necrosis.
In preferred embodiments, antibody based therapeutics are formulated as pharmaceutical compositions as described below. In preferred embodiments, administration of an antibody composition of the present invention results in a measurable decrease in cancer (e.g., decrease or elimination of tumor).
D. Pharmaceutical Compositions
The present invention further provides pharmaceutical compositions (e.g., comprising the antisense or antibody compounds described above). The pharmaceutical compositions of the present invention may be administered in a number of ways depending upon whether local or systemic treatment is desired and upon the area to be treated. Administration may be topical (including ophthalmic and to mucous membranes including vaginal and rectal delivery), pulmonary (e.g., by inhalation or insufflation of powders or aerosols, including by nebulizer; intratracheal, intranasal, epidermal and transdermal), oral or parenteral. Parenteral administration includes intravenous, intraarterial, subcutaneous, intraperitoneal or intramuscular injection or infusion; or intracranial, e.g., intrathecal or intraventricular, administration.
Pharmaceutical compositions and formulations for topical administration may include transdermal patches, ointments, lotions, creams, gels, drops, suppositories, sprays, liquids and powders. Conventional pharmaceutical carriers, aqueous, powder or oily bases, thickeners and the like may be necessary or desirable.
Compositions and formulations for oral administration include powders or granules, suspensions or solutions in water or non-aqueous media, capsules, sachets or tablets. Thickeners, flavoring agents, diluents, emulsifiers, dispersing aids or binders may be desirable.
Compositions and formulations for parenteral, intrathecal or intraventricular administration may include sterile aqueous solutions that may also contain buffers, diluents and other suitable additives such as, but not limited to, penetration enhancers, carrier compounds and other pharmaceutically acceptable carriers or excipients.
Pharmaceutical compositions of the present invention include, but are not limited to, solutions, emulsions, and liposome-containing formulations. These compositions may be generated from a variety of components that include, but are not limited to, preformed liquids, self-emulsifying solids and self-emulsifying semisolids.
The pharmaceutical formulations of the present invention, which may conveniently be presented in unit dosage form, may be prepared according to conventional techniques well known in the pharmaceutical industry. Such techniques include the step of bringing into association the active ingredients with the pharmaceutical carrier(s) or excipient(s). In general the formulations are prepared by uniformly and intimately bringing into association the active ingredients with liquid carriers or finely divided solid carriers or both, and then, if necessary, shaping the product.
The compositions of the present invention may be formulated into any of many possible dosage forms such as, but not limited to, tablets, capsules, liquid syrups, soft gels, suppositories, and enemas. The compositions of the present invention may also be formulated as suspensions in aqueous, non-aqueous or mixed media. Aqueous suspensions may further contain substances that increase the viscosity of the suspension including, for example, sodium carboxymethylcellulose, sorbitol and/or dextran. The suspension may also contain stabilizers.
In one embodiment of the present invention the pharmaceutical compositions may be formulated and used as foams. Pharmaceutical foams include formulations such as, but not limited to, emulsions, microemulsions, creams, jellies and liposomes. While basically similar in nature these formulations vary in the components and the consistency of the final product.
Agents that enhance uptake of oligonucleotides at the cellular level may also be added to the pharmaceutical and other compositions of the present invention. For example, cationic lipids, such as lipofectin (U.S. Pat. No. 5,705,188), cationic glycerol derivatives, and polycationic molecules, such as polylysine (WO 97/30731), also enhance the cellular uptake of oligonucleotides.
The compositions of the present invention may additionally contain other adjunct components conventionally found in pharmaceutical compositions. Thus, for example, the compositions may contain additional, compatible, pharmaceutically-active materials such as, for example, antipruritics, astringents, local anesthetics or anti-inflammatory agents, or may contain additional materials useful in physically formulating various dosage forms of the compositions of the present invention, such as dyes, flavoring agents, preservatives, antioxidants, opacifiers, thickening agents and stabilizers. However, such materials, when added, should not unduly interfere with the biological activities of the components of the compositions of the present invention. The formulations can be sterilized and, if desired, mixed with auxiliary agents, e.g., lubricants, preservatives, stabilizers, wetting agents, emulsifiers, salts for influencing osmotic pressure, buffers, colorings, flavorings and/or aromatic substances and the like which do not deleteriously interact with the nucleic acid(s) of the formulation.
Certain embodiments of the invention provide pharmaceutical compositions containing (a) one or more antisense compounds and (b) one or more other chemotherapeutic agents that function by a non-antisense mechanism. Examples of such chemotherapeutic agents include, but are not limited to, anticancer drugs such as daunorubicin, dactinomycin, doxorubicin, bleomycin, mitomycin, nitrogen mustard, chlorambucil, melphalan, cyclophosphamide, 6-mercaptopurine, 6-thioguanine, cytarabine (CA), 5-fluorouracil (5-FU), floxuridine (5-FUdR), methotrexate (MTX), colchicine, vincristine, vinblastine, etoposide, teniposide, cisplatin and diethylstilbestrol (DES). Anti-inflammatory drugs, including but not limited to nonsteroidal anti-inflammatory drugs and corticosteroids, and antiviral drugs, including but not limited to ribivirin, vidarabine, acyclovir and ganciclovir, may also be combined in compositions of the invention. Other non-antisense chemotherapeutic agents are also within the scope of this invention. Two or more combined compounds may be used together or sequentially.
Dosing is dependent on severity and responsiveness of the disease state to be treated, with the course of treatment lasting from several days to several months, or until a cure is effected or a diminution of the disease state is achieved. Optimal dosing schedules can be calculated from measurements of drug accumulation in the body of the patient. The administering physician can easily determine optimum dosages, dosing methodologies and repetition rates. Optimum dosages may vary depending on the relative potency of individual oligonucleotides, and can generally be estimated based on EC50s found to be effective in in vitro and in vivo animal models or based on the examples described herein. In general, dosage is from 0.01 μg to 100 g per kg of body weight, and may be given once or more daily, weekly, monthly or yearly. The treating physician can estimate repetition rates for dosing based on measured residence times and concentrations of the drug in bodily fluids or tissues. Following successful treatment, it may be desirable to have the subject undergo maintenance therapy to prevent the recurrence of the disease state, wherein the oligonucleotide is administered in maintenance doses, ranging from 0.01 μg to 100 g per kg of body weight, once or more daily, to once every 20 years.
V. Transgenic Animals Expressing Cancer Marker Genes
The present invention contemplates the generation of transgenic animals comprising an exogenous cancer marker gene of the present invention or mutants and variants thereof (e.g., truncations or single nucleotide polymorphisms). In preferred embodiments, the transgenic animal displays an altered phenotype (e.g., increased or decreased presence of markers) as compared to wild-type animals. Methods for analyzing the presence or absence of such phenotypes include but are not limited to, those disclosed herein. In some preferred embodiments, the transgenic animals further display an increased or decreased growth of tumors or evidence of cancer.
The transgenic animals of the present invention find use in drug (e.g., cancer therapy) screens. In some embodiments, test compounds (e.g., a drug that is suspected of being useful to treat cancer) and control compounds (e.g., a placebo) are administered to the transgenic animals and the control animals and the effects evaluated.
The transgenic animals can be generated via a variety of methods. In some embodiments, embryonal cells at various developmental stages are used to introduce transgenes for the production of transgenic animals. Different methods are used depending on the stage of development of the embryonal cell. The zygote is the best target for micro-injection. In the mouse, the male pronucleus reaches the size of approximately 20 micrometers in diameter that allows reproducible injection of 1-2 picoliters (pl) of DNA solution. The use of zygotes as a target for gene transfer has a major advantage in that in most cases the injected DNA will be incorporated into the host genome before the first cleavage (Brinster et al., Proc. Natl. Acad. Sci. USA 82:4438-4442 [1985]). As a consequence, all cells of the transgenic non-human animal will carry the incorporated transgene. This will in general also be reflected in the efficient transmission of the transgene to offspring of the founder since 50% of the germ cells will harbor the transgene. U.S. Pat. No. 4,873,191 describes a method for the micro-injection of zygotes; the disclosure of this patent is incorporated herein in its entirety.
In other embodiments, retroviral infection is used to introduce transgenes into a non-human animal. In some embodiments, the retroviral vector is utilized to transfect oocytes by injecting the retroviral vector into the perivitelline space of the oocyte (U.S. Pat. No. 6,080,912, incorporated herein by reference). In other embodiments, the developing non-human embryo can be cultured in vitro to the blastocyst stage. During this time, the blastomeres can be targets for retroviral infection (Janenich, Proc. Natl. Acad. Sci. USA 73:1260 [1976]). Efficient infection of the blastomeres is obtained by enzymatic treatment to remove the zona pellucida (Hogan et al., in Manipulating the Mouse Embryo, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. [1986]). The viral vector system used to introduce the transgene is typically a replication-defective retrovirus carrying the transgene (Jahner et al., Proc. Natl. Acad. Sci. USA 82:6927 [1985]). Transfection is easily and efficiently obtained by culturing the blastomeres on a monolayer of virus-producing cells (Stewart, et al., EMBO J., 6:383 [1987]). Alternatively, infection can be performed at a later stage. Virus or virus-producing cells can be injected into the blastocoele (Jahner et al., Nature 298:623 [1982]). Most of the founders will be mosaic for the transgene since incorporation occurs only in a subset of cells that form the transgenic animal. Further, the founder may contain various retroviral insertions of the transgene at different positions in the genome that generally will segregate in the offspring. In addition, it is also possible to introduce transgenes into the germline, albeit with low efficiency, by intrauterine retroviral infection of the midgestation embryo (Jahner et al., supra [1982]). Additional means of using retroviruses or retroviral vectors to create transgenic animals known to the art involve the micro-injection of retroviral particles or mitomycin C-treated cells producing retrovirus into the perivitelline space of fertilized eggs or early embryos (PCT International Application WO 90/08832 [1990], and Haskell and Bowen, Mol. Reprod. Dev., 40:386 [1995]).
In other embodiments, the transgene is introduced into embryonic stem cells and the transfected stem cells are utilized to form an embryo. ES cells are obtained by culturing pre-implantation embryos in vitro under appropriate conditions (Evans et al., Nature 292:154 [1981]; Bradley et al., Nature 309:255 [1984]; Gossler et al., Proc. Acad. Sci. USA 83:9065 [1986]; and Robertson et al., Nature 322:445 [1986]). Transgenes can be efficiently introduced into the ES cells by DNA transfection by a variety of methods known to the art including calcium phosphate co-precipitation, protoplast or spheroplast fusion, lipofection and DEAE-dextran-mediated transfection. Transgenes may also be introduced into ES cells by retrovirus-mediated transduction or by micro-injection. Such transfected ES cells can thereafter colonize an embryo following their introduction into the blastocoel of a blastocyst-stage embryo and contribute to the germ line of the resulting chimeric animal (for review, See, Jaenisch, Science 240:1468 [1988]). Prior to the introduction of transfected ES cells into the blastocoel, the transfected ES cells may be subjected to various selection protocols to enrich for ES cells which have integrated the transgene assuming that the transgene provides a means for such selection. Alternatively, the polymerase chain reaction may be used to screen for ES cells that have integrated the transgene. This technique obviates the need for growth of the transfected ES cells under appropriate selective conditions prior to transfer into the blastocoel.
In still other embodiments, homologous recombination is utilized to knock-out gene function or create deletion mutants (e.g., truncation mutants). Methods for homologous recombination are described in U.S. Pat. No. 5,614,396, incorporated herein by reference.
Experimental
The following examples are provided in order to demonstrate and further illustrate certain preferred embodiments and aspects of the present invention and are not to be construed as limiting the scope thereof.
In the experimental disclosure which follows, the following abbreviations apply: N (normal); M (molar); mM (millimolar); μM (micromolar); mol (moles); mmol (millimoles); μmol (micromoles); nmol (nanomoles); pmol (picomoles); g (grams); mg (milligrams); μg (micrograms); ng (nanograms); 1 or L (liters); ml (milliliters); μl (microliters); cm (centimeters); mm (millimeters); μm (micrometers); nm (nanometers); and ° C. (degrees Centigrade).
EXAMPLE 1
Preparation of Total RNA and Reference Pools
The prostate surgical specimens were obtained from The University of Michigan Specialized Research Program in Prostate Cancer (S.P.O.R.E.) Tumor Bank with Institutional Review Board approval. Tumors samples were derived from patients with clinically localized and advanced hormone refractory prostate cancer. Table 1 shows the samples used in the present studies. All patients were operated on between 1993 and 1998 for clinically localized prostate cancer as determined by preoperative PSA, digital-rectal examination, and prostate needle biopsy. In addition, a subset of patients received bone and CAT scans to evaluate the possibility of metastatic spread. All patients received radical prostatectomy as a monotherapy (i.e., no hormonal or radiation therapy). The advanced prostate tumors were collected from a series of 12 rapid autopsies performed at the University of Michigan on men who died of hormone refractory prostate cancer. In brief, the majority of these patients had either widely metastatic prostate cancer which was treated with hormonal therapy followed by chemotherapy, or patients who presented with clinically localized disease which progressed and were then treated with both hormonal and chemotherapy. The majority of cases had multiple metastatic lesions to numerous sites. All autopsies were performed within 4-6 hours after death. The clinical and pathologic findings of these cases have recently been reported (Rubin et al., Clin. Cancer Res., 6:1038 [2000]). All samples used for the tissue microarray study were fixed in 10% formalin.
Tissues were homogenized using a polytron homogenizer (Brinkman Instruments) in Trizol (Gibco BRL) and the total RNA was isolated according to the standard Trizol protocol. The total RNA obtained was further subjected to an additional round of phenol chloroform extraction, precipitated and resuspended in RNAse free water. Total RNA was quantitated by spectrophotmetric (260/280 nm) absorbance and integrity judged by denaturing-formaldehyde agarose gel electrophoresis. Total RNA from four normal tissues was combined in equal concentrations to obtain the reference pool. The human prostate total RNA used in the commercial reference pool was obtained from Clontech, Inc.







TABLE 1







Prostate Samples












ID
PSA level
Tissue
Gleason Score
















BPH-201
6.2
Prostate
NA



BPH-202
3.9
Prostate
NA



BPH-203
3.9
Prostate
NA



BPH-204
4.6
Prostate
NA



BPH-205
4.6
Prostate
NA



BPH-206
4.6
Prostate
NA



BPH-207
4.8
Prostate
NA



BPH-208
13.6
Prostate
NA



BPH-209
9.8
Prostate
NA



BPH-210
4.6
Prostate
NA



BPH-211
2.6
Prostate
NA



BPH-212
7.1
Prostate
NA



BPH-214

Prostate
NA



BPH-215
5.4
Prostate
NA



Prostatitis
9.8
Prostate
NA



NAP-101
4.6
Prostate
NA



NAP-102
9.8
Prostate
NA



NAP-104
7
Prostate
NA



NAP-105
0.09
Prostate
NA



NAP-107
4.7
Prostate
NA



PCA-401
5.2
Prostate
4 + 4



PCA-402
22
Prostate
4 + 3



PCA-403
4.7
Prostate
3 + 3



PCA-404
8.5
Prostate
3 + 3



PCA-405
4.6
Prostate
3 + 3



PCA-406
7.8
Prostate
3 + 3



PCA-407
7.8
Prostate
3 + 3



PCA-408
5.4
Prostate
3 + 3



PCA-409
7
Prostate
3 + 3



PCA-410
44.6
Prostate
4 + 4



PCA-414

Prostate
3 + 4



PCA-416
24.1
Prostate
4 + 4



PCA-417
12.4
Prostate
4 + 4



PCA-420

Prostate
3 + 3



PCA-421
13.6
Prostate
3 + 4



MET-301

Lung
NA



MET-302

Liver
NA



MET-303

Liver
NA



MET-304

Stomach
NA



MET-305

Adrenal
NA



MET-306

Prostate
NA



MET-307

Lymph Node
NA



MET-308

Lymph Node
NA



MET-309

Lymph Node
NA



MET-310

Liver
NA



MET-311

Soft tissue
NA



MET-312

Liver
NA



MET-313

Soft tissue
NA



MET-314

Soft tissue
NA



MET-315

Soft tissue
NA



MET-316

Soft tissue
NA



MET-317

Liver
NA



MET-318

bone
NA



MET-319

bone
NA



MET-320

bone
NA










Table 1. Samples employed in the study. Designating PSA level in ng/mL, Organ sources and Gleason scores. Normal adjacent prostate (NAP), Benign prostatic hyperplasia (BPH), Localized prostate cancer (PCA) and Hormone refractory metastatic prostate cancer (MET). NA refers to “not applicable”.

EXAMPLE 2
Microarray Analysis
This example describes the use of microarray analysis to identify genes that demonstrate an altered level of expression in cancerous or benign prostate tissues.
A. Experimental Methods
Microarray analysis of gene expression was conducted essentially as described by the Brown and Derisi Labs. The sequence-verified cDNA clones on the human cDNA microarray are available from the web site of Research Genetics. Based on the latest Unigene build, the 10K human cDNA microarray used covers approximately 5520 known, named genes and 4464 ESTs. All chips have various control elements that include human, rat, and yeast genomic DNAs, SSC, yeast genes and “housekeeping genes,” among others. In addition, 500 cancer- and apoptosis-related cDNAs from Research Genetics were used to serve as independent controls for clone tracking and function as duplicates for quality control. Three metastatic prostate cancer cell lines: DU-145, LnCAP, and PC3 were also profiled for gene expression.
Fluorescently labeled (Cy5) cDNA was prepared from total RNA from each experimental sample. The two reference samples used in this study were labeled using a second distinguishable fluorescent dye (Cy3) and included a pool of normal adjacent prostate tissue (NAP) from four patients (distinct from those used in the experimental samples) and a commercial pool of normal prostate tissues (CP). In addition to minimizing patient-to-patient variation, comparisons against pools of normal prostate tissue facilitate the discovery of genes that molecularly distinguish prostate neoplasms. The two reference pools are different in that one is comprised of normal adjacent prostate tissue, which may be influenced by paracrine effects mediated by PCA, and furthermore is exposed to the same environmental and genetic factors as the adjacent PCA. By contrast, the CP pool is derived from 19 individuals with no known prostate pathology and also represents a renewable commercially available reference resource.
Purified PCR products, generated using the clone inserts as template, were spotted onto poly-L-lysine coated microscope slides using an Omnigrid robotic arrayer (GeneMachines, CA) equipped with quill-type pins (Majer Scientific, AZ). One full print run generated approximately 100 DNA microarrays. Protocols for printing and post-processing of arrays are well known in the art.
B. Data analysis
Primary analysis was done using the Genepix software package. Images of scanned microarrays were gridded and linked to a gene print list. Initially, data was viewed as a scatter plot of Cy3 versus Cy5 intensities. Cy3 to Cy5 ratios were determined for the individual genes along with various other quality control parameters (e.g., intensity over local background). The Genepix software analysis package flags spots as absent based on spot characteristics (refer to the web site of Axon Instruments, Inc.). Bad spots or areas of the array with obvious defects were manually flagged. Spots with small diameters (<50 microns) and spots with low signal strengths<350 fluorescence intensity units over local background in the more intense channel were discarded. Flagged spots were not included in subsequent analyses. Data were scaled such that the average median ratio value for all spots was normalized to 1.0 per array.
These files were then imported into a MICROSOFT ACCESS database. The data for the required experiments were extracted from the database in a single table format with each row representing an array element, each column a hybridization and each cell the observed normalized median of ratios for the array element of the appropriate hybridization. Prior to clustering, the normalized median of ratio values of the genes were log base 2 transformed and filtered for presence across arrays and selected for expression levels and patterns depending on the experimental set as stated. Average linkage hierarchial clustering of an uncentered Pearson correlation similarity matrix was applied using the program Cluster (Eisen et al., PNAS 95:14863 [1998]), and the results were analyzed and figures generated with the program TreeView. TreeView and Cluster are available from Michael Eisen's lab at the Lawrence Berkeley National Lab.
C. Results
Over forty 10K human cDNA microarrays were used to assess gene expression in four clinical states of prostate-derived tissues in relation to two distinct reference pools of normal specimens. FIG. 1 provides an overview of the variation in gene expression across the different tissue specimens analyzed. A hierarchical clustering algorithm was employed to group genes and experimental samples based on similarities of gene expression patterns over all the genes and samples tested, respectively.
1. Expression Dendrograms
Relationships between the experimental samples are summarized as dendrograms (FIG. 1a), in which the pattern and length of the branches reflect the relatedness of the samples. FIG. 1a shows dendrograms that reveal the variation in gene expression pattern between experimental samples with the two references employed. Individual samples in each group are indicated by the branches of the same color whereby METs are in dark blue, localized PCAs in orange, NAPs in light blue, BPHs in gray, and cell lines in pink. Asterisk (*) indicates a sample that was initially documented as BPH, but was later confirmed to have 5% cancer tissue. The details of metastatic samples used in this study are as follows: MET 301, from Lung; MET 302 and 303 from liver; MET 304, from stomach; MET 305 from adrenal gland; MET 306 from prostate; and MET 307 was from lymph node. Hierarchical clustering of the data identified distinct patterns of gene expression between the various groups analyzed. Each row represents a single gene with 1520 genes depicted in b, and 1006 genes depicted in c. The results represent the ratio of hybridization of fluorescent cDNA probes prepared from each experimental mRNA to the respective reference pools. These ratios are a measure of relative gene expression in each experimental sample and are depicted according to the color scale at the bottom left. Red and green colors in the matrix represent genes that are up- and down-regulated, respectively, relative to the reference pool employed. Black lines in the matrix represent transcript levels that are unchanged, while gray lines signify technically inadequate or missing data (NP, not present). Color saturation reflects the magnitude of the ratio relative to the median for each set of samples.
FIG. 1b shows a cluster diagram of the various sample groups compared against normal adjacent prostate pool as reference. Prior to hierarchical average-linkage clustering, the data was filtered for at least a 2-fold change in expression ratio and ratio measurements present in 50% of the samples. By this method, 1520 genes were selected from the NAP reference data set. Indicated by vertical bars on the left (b1 to b6) of FIG. 1b are regions identified with characteristic gene expression signatures. Clusters b1 and b5 show genes up-regulated in localized PCA but not in metastatic PCA. Clusters b2 and b4 highlight genes down-regulated in metastatic PCA and the cell lines DU145 and LnCAP. Cluster b3 identifies genes down-regulated in both localized PCA and metastatic PCA. Cluster b6 highlights genes that are primarily up-regulated in metastatic PCA alone. Portions of Clusters b4 and b6 are shown enlarged with selected genes shown using Human genome organization (HUGO) gene nomenclature.
FIG. 1c shows a cluster diagram of the various sample groups compared against the commercial prostate pool reference. Prior to hierarchical average-linkage clustering, the data was filtered for at least a 3-fold change in expression ratio and ratio measurements present in 75% of the samples resulting in a total of 1006 genes. Regions with distinct patterns (c1-c6) are indicated by vertical bars to the right of FIG. 1c. Cluster c1 depicts genes down-regulated in both localized PCA and metastatic PCA. Cluster c2 represents genes down-regulated only in metastatic PCA. Cluster c3 shows genes that are highly represented in the commercial pool. Cluster c4 highlights genes that are up-regulated in localized PCA and in metastatic PCA. Cluster c5 represent genes with a low representation in the commercial pool. Cluster c6, represents genes that are down-regulated in metastatic PCA but are up-regulated in all other samples used.
Benign conditions of the prostate such as BPH and NAP cluster separately from malignant PCA cell lines or tissues, regardless of the reference pool used. Within the PCA cluster, it is also evident that metastatic PCA and clinically localized PCA formed distinct subgroups. Similarly, in the “benign” grouping, BPH tended to distinguish itself from NAP. Interestingly, one of the “BPH” samples initially clustered with the localized PCA group. Upon further histopathologic review, however, it was discovered that this sample contained a small focus of neoplastic tissue ( ̃5%), thus accounting for its initial misclassification (now designated PCA+BPH in FIG. 1a).
Eisen matrix formats (Eisen et al., supra) of the variation in gene expression are also presented (FIG. 1b and 1c). With a global perspective of the data, it is apparent that metastatic PCA dominates the analysis and has the greatest variation in gene expression of the samples tested. Bars on the left or right of each matrix represent clusters of coordinately expressed genes highlighting interrelationships between specimens. For example, Clusters b3 and c1 represent genes down-regulated in both localized and metastatic PCA (FIGS. 1b and 1c). By contrast, Clusters b6 and b4 highlight genes that are specifically up- and down-regulated in metastatic PCA, respectively (FIG. 1b). IGFBP-5, DANI, FAT tumor suppressor and RAB5A are examples of genes that are down-regulated specifically in metastatic PCA and also have a proposed role in oncogenesis (“magnified” regions, FIG. 1b). Similarly, cancer-related genes that are up-regulated in metastatic PCA include MTA-1 (metastasis-associated 1), MYBL2, and FLS353 (preferentially expressed in colorectal cancer). Many genes in this “met-specific” cluster are shared by both the metastatic PCA tissue and the two PCA cell lines DU145 and LnCAP.
A total of 53 prostate specimens were profiled against the commercial pool. They include 4 normal adjacent prostate tissue (NAP), 14 benign prostatic hyperplasia (BPH), 1 prostatitis, 14 localized prostate cancer (PCA) and 20 hormone refractory metastatic PCA (MET). Prior to hierarchial average-linkage clustering, the data was filtered for at least 3-fold change in Cy5/Cy3 ratios and measurements present in 75% of the samples. By this method 1325 genes were selected. The data expands on FIG. 1c with an additional 40 samples, which include all from FIG. 1b, and also includes 28 additional prostate specimens.
2. Focused Clusters
Data was next assessed by examining functional groups of known, named genes. Cancer-related functional clusters were arbitrarily defined including cell growth/cell death, cell adhesion, anti-protease/protease, free radical scavengers, inflammation/immunity, phosphatase/kinase, transcription, and miscellaneous (FIGS. 2 and 6).
One of several available methods of gene selection was used to create a more limited set of genes for future exploration. In one method, t-statistics (based on MET/PCA vs. benign) were computed for each gene. The cell line samples were excluded from the analysis. Also, genes and ESTs that had data missing from 20% of samples were excluded from analysis. The t-statistics were ranked in two ways. First, they were ranked by absolute magnitude, which takes into account the inter-sample variability in expression ratios. Second, they were ranked by the magnitude of the numerator of the test statistic, which is based on the biological difference in expression ratios and designated as “effect size” (for MET/PCA vs. benign). A scatterplot of the genes with the 200 largest effect sizes and 200 largest t-statistics was then plotted (See FIG. 7). FIG. 7 shows gene selection based on computed t-statistics for each gene. Two groups were used in the analysis: PCA/MET and benign (NAP/BPH). FIG. 7a shows analysis of NAP pool data. FIG. 7b shows analysis of CP pool data. Selected genes are named and 200 genes for each data set are shown. Gene selection based on each method is shown. Selected gene names or symbols (as specified by Human genome organization (HUGO) gene nomenclature) are shown.
Genes that made both lists were also looked at separately in order to identify potential candidate genes. Implementing this methodology on both reference pool data sets (NAP and CP) yielded genes that included hepsin, pim-1, IM/ENIGMA, TIMP2, hevin, rig, and thrombospondin-1, among others. Several genes identified using gene selection methods are described in more detail in the context of “functional” clusters described in FIG. 2.
FIG. 2 shows the differential expression of functional clusters of select genes in prostate cancer. Gene names or symbols (as specified by Human genome organization (HUGO) gene nomenclature) are shown. The same convention for representing changes in transcript levels was used as in FIG. 1. The sample order from FIG. 1 was preserved for clarity.
FIG. 8 shows a focused cluster of PCA-related genes. The same convention for representing changes in transcript levels was used as in FIG. 1. This cluster of 231 genes was generated by selecting for a 3.5-fold variation in at least 2 of any class, and ratio measurements present in 75% of the samples. Classes included: PCA vs. NAP, MET vs. NAP, PCA vs. CP and MET vs. CP.
The reliability of the hierarchical clustering results was assessed using three separate methods: that of Calinski and Harabasz (1974), Hartigan (1975) and Krzanowski and Lai (1985). The number of “stable” clusters estimated by all these methods is two. In the CP pool data set, that would elicit a valid benign cluster (NAP and BPH) and a malignant cluster (PCA and MET).
Many of the genes identified in these “focused” clusters have been implicated directly or indirectly as cancer biomarkers or mediators of carcinogenesis. Several have been shown to be dysregulated in PCA. For example, the tumor suppressor gene PTEN was down-regulated, while the proto-oncogene myc was up-regulated in the microarray analysis of PCA (FIG. 2) (Abate-Shen and Shen, supra). Likewise, decreased expression of E-cadherin and increased expression of fatty acid synthase, both of which have been shown to be dysregulated in PCA were observed (Tomita et al., Cancer Res., 60:3650 [2000] and Shurbaji et al., Hum. Pathol., 27:917 [1996]). In addition to uncharacterized expressed sequence tags (ESTs), there are numerous genes that were identified by the screen but not previously known to be associated with PCA. It is contemplated that they find use as cancer markers.
Exemplary nucleic acid sequences for some of the genes identified in focused clusters are shown in FIGS. 9 and 10. The present invention is not limited to the particular nucleic acid sequences described in FIGS. 9 and 10. One skilled in the art recognizes that additional variants, homologs, and mutants of the described sequences find use in the practice of the present invention.
3. Comparison Between NAP and CP Pools
A direct comparison between the NAP and CP pool was also made and notable gene expression differences were readily apparent. FIG. 5 shows a comparison between the NAP and CP pools. The same convention for representing changes in transcript levels was used as in FIG. 1. The cluster was obtained by selecting for genes with at least a 2.5-fold variation in any two of the samples of each class, namely the normal tissues versus the NAP pool and normal tissue versus the CP pool at a 50% filter. Of the genes analyzed 59 were selected with this criteria. Genes that were found to be up-regulated in the NAP pool in comparison with CP pool included connective tissue growth factor, EGR-1 (Early Growth Response 1), matrilysin (MMP7), CFLAR/I-FLICE (caspase 8 and FADD-like apoptosis regulator), lumican, serum glucocorticoid regulated kinase, lens epithelium derived growth factor, PAI1 (plasminogen activator inhibitor type I), JUN and FOS B, among others. Vascular endothelial growth factor (VEGF), growth arrest specific (GAS1), cholecystokinin (CCK), amiloride binding protein (ABP1) were among the down-regulated genes in the normal adjacent prostate pool when compared to the commercial pool. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that the gene expression differences between normal prostate adjacent to PCA (NAP) and normal prostate tissue from individuals without prostate pathology (CP) may be attributable to a “field effect” induced by PCA itself.
EXAMPLE 3
Northern Blot Analysis
Thirty micrograms of total RNA was resolved by denaturing formaldehyde agarose gel and transferred onto Hybond membrane (Amersham) by a capillary transfer set up. Hybridizations were performed by the method described by Church and Gilbert, 1984. Signal was visualized and quantitated by phosphorimager. For relative fold estimation, the ratio between the signals obtained from hepsin and GAPDH probes was calculated.
Selected genes identified by microarray analysis were corroborated by Northern analysis. For example, hevin, 41⁄2 LIM domain protein and gelsolin were shown to be 3.2-, 3.2- and 1.9-fold down-regulated, respectively by microarray and 8.8-, 4.5-, and 3.5-fold down-regulated by Northern analysis. Similarly, hepsin was 4.3-fold up-regulated by microarray and 11.3-fold up-regulated by Northern analysis (FIG. 3a). As hepsin is a cell-surface serine protease with transcript expression precisely restricted to localized and metastatic PCA, its expression was examined in more detail at the protein level (See Example 4 below).
EXAMPLE 4
Tissue Analysis
This example describes the analysis of protein expression in normal and cancerous prostate tissues.
A. Tissue microarray construction.
Kononen et al. have described a method for evaluating tumor tissues in large numbers on a single glass slide (Kononen et al., Nat. Med., 4:844 [1998]). These high-density tissue microarrays allow for analysis of up to 1,000 tissue samples on a single slide. These slides can be evaluated by routine light microscopy on hematoxylin and eosin (H&E) prepared and immunohistochemically stained slides. Thus, candidate cancer biomarkers, identified by gene expression methodologies, can be evaluated at the protein level over a large number of clinically stratified tumor specimens.
Prostate tissues used in microarray analysis included 4 BPH, 8 NAP, 1 commercial pool of normal prostate tissue (from 19 individuals), 1 prostatitis, 11 localized PCA, and 7 metastatic PCA specimens. High-density tissue microarrays (TMA) were assembled using a manual tissue puncher/array (Beecher Instruments, Silver Springs, Md.) as previously described (Kononen et al., Nat. Med., 4:844 [1998]; Perrone et al., J. Natl. Cancer Inst., 92:937 [2000]). The instrument consists of thin-walled stainless steel needles with an inner diameter of approximately 600 μm and stylet used to transfer and empty the needle contents. The assembly is held in an X-Y position guide that is manually adjusted by digital micrometers. Small biopsies are retrieved from selected regions of donor tissue and are precisely arrayed in a new paraffin block. Tissue cores were 0.6 mm in diameter and ranged in length from 1.0 mm to 3.0 mm depending on the depth of tissue in the donor block. Multiple replicate core samples of normal, HGPIN, and PCA were acquired from each tissue block of each case. Cores were inserted into a 45×20×12 mm recipient bock and spaced at a distance of 0.8 mm apart. Prostate tumor grading was performed using the system described by Gleason (Gleason, Cancer Chemother Rep., 50:125 [1966]). Pathologic stages for the radical prostatectomies were determined using the TNM staging system (Schroder et al., Prostate Suppl., 4:129 [1992]). Surgical margins were assessed separately and are not included in tumor staging.
B. Immunohistochemistry
TMA sections were cut at five-micron thick intervals for immunohistochemistry. Initial sections were stained for hematoxylin and eosin to verify histology. TMA slides prepared from formalin-fixed paraffin embedded tissue were heated for 0.5-1 hours at 60° centigrade. All slides were placed in 10 millimolar citrate buffer (pH 6.0) and microwaved for 5 minutes. Standard biotin-avidin complex immunohistochemistry was performed. The affinity purified polyclonal Rabbit antibody against hHepsin was used at a 1:40 dilution (original concentration 0.2 mg/ml) for this study. Immunostaining intensity was scored by a dedicated genitourinary pathologist as absent, weak, moderate, or strong. Scoring was performed using a telepathology system in a blinded fashion without knowledge of overall Gleason score (e.g., tumor grade), tumor size, or clinical outcome (Perrone et al., supra). A total of 738 tissue samples from benign (n=205), high-grade PIN (n=38), localized prostate cancer (n=335) and hormone refractory prostate cancer (n=160) were examined.
Similarly, pim-1 was analyzed using two TMA blocks from a total of 810 PCA samples from 135 patients. Six PCA samples were evaluated from each case and a median score was calculated. In addition, a small number of samples with benign prostatic tissues (e.g., benign epithelium and atrophy) and HG-PIN were examined. Immunohistochemistry was performed as above, using a rabbit polyclonal antibody against the N-terminus of pim-1 (Santa Cruz Biotechnology) at a 1:100 dilution. Pim-1 demonstrated cytoplasmic staining and was graded as either negative, weak, moderate, or strong. All samples were reviewed blinded with respect to all related pathology and clinical data.
C. Statistical methods
A nonparametric ANOVA test (Mann-Whitney [two categories]) was employed to evaluate whether the prostate samples expressed hepsin and pim-1 at different levels based on various parameters (tissue type, Gleason score, and tumor size). Kaplan-Meier analysis was used to estimate the cumulative percentage of PSA free progression (“survival”). The log-rank test was employed to assess the differences in disease free progression hepsin immunostaining. Cox proportional-hazard regression was used for multivariate analysis. Commercial software from SPSS (Chicago, Ill.) was used for this study.
D. Results
1. Hepsin
Microarrays used in this study are shown in FIG. 3b. Over 700 benign and malignant prostate tissues were immunohistochemically profiled on tissue microarrays (FIG. 3c-e) using an affinity-purified hepsin-peptide antibody (Tsuji et al., J. Biol. Chem., 266:16948 [1991]). FIG. 3 shows the overexpression of Hepsin, a transmembrane serine protease, in prostate cancer. FIG. 3a shows a Northern blot analysis of human hepsin (top) and normalization with GAPDH (bottom). NAT indicates normal adjacent prostate tissue and PCA indicates prostate cancer. FIG. 3b shows tissue microarrays used for hepsin analysis. Staining was done with hemotoxylin and eosin to verify histology.
Immunohistochemical stains demonstrated absent or weak staining of benign prostate (c1), strong staining in localized prostate cancer (c2-6), and strong staining in a high-grade prostate tumor (magnification 100× was used for all images, samples measure 0.6 mm in diameter). Benign prostate glands demonstrate weak expression in the secretory, luminal cells and strong basal cell staining. In areas where prostate cancer and benign prostate glands are seen, significant hepsin staining differences are observed. Infiltrating prostate cancers (d3-4) demonstrate strong hepsin protein expression. Magnification for all images was 400×. FIG. 3c shows a histogram of hepsin protein expression by tissue type. Benign prostate hyperplasia (BPH). High-grade intraepithelial neoplasia (HG-PIN). Localized prostate cancer (PCA). Hormone-refractory prostate cancer (MET). Relative strength of hepsin staining was qualitatively assessed and categorized. Percentage of hepsin staining per category is shown on the y-axis. FIG. 3d shows Kaplan Meier Analysis. PSA-free survival was stratified by level of hepsin protein expression into two categories absent/low expression (circles) versus moderate/strong expression (squares).
Internal controls showed that liver tissue, as previously described, stained strongly for hepsin. Overall, hepsin exhibited predominantly membrane staining and was preferentially expressed in neoplastic prostate over benign prostate (Mann-Whitney test, p<0.0001). Importantly, the precursor lesion of PCA, HG-PIN, had the strongest expression of hepsin, and almost never had absent staining (Mann-Whitney, p<0.0001). Most cases of low or absent hepsin staining were seen in benign prostate specimens. In addition, hormone refractory metastatic cancers were intermediate in staining intensity between localized prostate tumors and benign prostate.
Men who develop elevated PSA levels following radical prostatectomy are at a high risk to develop distant metastases and die due to prostate cancer (Pound et al., JAMA, 281:1591 [1999]. Therefore, to assess the usefulness of hepsin as a potential PCA biomarker, PSA failure was defined as a PSA elevation of greater than 0.2 ng/ml following radical prostatectomy. Analysis was performed on 334 localized prostate cancer samples treating each as an independent sample. PSA elevation following radical prostatectomy was significantly associated with absent and low hepsin immunostaining with a 28% (46/119 samples) PSA failure rate, in contrast to 17% (28/141 samples) PSA failure rate for tumors with moderate to strong hepsin expression (FIG. 3d, Log Rank test P=0.03). Multivariate analysis was performed to examine if these results were independent of Gleason score, a well-established histologic grading system for PCA (Gleason, Hum. Pathol., 23:273 [1992]). Based on the results from fitting a Cox proportional hazards model, there is an association of weak or absent hepsin protein expression in PCA with increased risk of PSA elevation following prostatectomy, similar to high Gleason score (corresponding risk ratios were 2.9 (p=0.0004) and 1.65 (p=0.037), respectively). Weak or absent hepsin expression was also associated with large prostate cancers; the median tumor dimension for prostate tumors with moderate to strong expression was 1.3 cm but 1.5 cm for tumors with absent or weak staining (Mann-Whitney Rank test, P=0.043). Taken together, hepsin protein expression in PCA correlated inversely with measures of patient prognosis.
Hepsin is a 51 kDa transmembrane protein with highest expression in the liver, and like PSA, is a serine protease (Kurachi et al., Methods Enzymol., 244:100 [1994]). The protease domain of hepsin has access to the extracellular space and can potentially activate other proteases or degrade components of extracellular matrix. The function of hepsin is poorly understood. It has been proposed to have a role in controlling cell growth (Torres-Rosado et al., PNAS, 90:7181 [1993], cell morphology, and activating the extrinsic coagulation pathway on the cell surface, leading to thrombin formation (Kazama et al., J. Biol. Chem., 270:66 [1995]). Additionally, hepsin mRNA levels have been shown to be elevated in ovarian carcinomas (Tanimoto et al., Cancer Res., 57:2884 [1997]). The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that the high expression of hepsin in HG-PIN, and not benign prostate, suggests that hepsin plays a role in the establishment of PIN or in the transition from HG-PIN to carcinoma. Subsequent decreases in hepsin expression seen in large localized cancers and hormone-refractory cancers suggest a decreased requirement of this protease in later stages of PCA. Alternatively, patients with advanced PCA often develop disseminated intravascular coagulation (DIC) (Riddell et al., J. Nucl. Med., 37:401 [1996]) whereby hepsin may play an important role.
2. pim-1
Tumorigenic growth of the prostate depends on the evasion of normal homeostatic control mechanisms, where cell proliferation exceeds cell death (Bruckheimer and Kyprianou, Cell Tissue Res., 301: 153 [2000]). While it is well known that the oncogene myc is overexpressed in many PCAs (Buttyan et al., prostate 11:327-37 [1987]; Abate-Shen and Shen, supra), the present invention demonstrates that the proto-oncogene pim-1 kinase is similarly up-regulated (cell growth/cell death cluster, FIG. 2). Previous studies suggest that the cooperative interaction between pim-1 and myc may induce lymphoid cell transformation by promoting cell cycle progression and blocking apoptosis (Shirogane, et al., Immunity 11:709 [1999]). The present analysis supports a similar co-transcriptional regulation (or gene amplification) of pim-1 and myc possibly mediating a synergistic oncogenic effect in PCA.
Pim-1 kinase protein expression in PCA was also explored using high-denisty TMAs. FIG. 4 shows the overexpression of pim-1 in prostate cancer. Immunohistochemical stains demonstrated absent or weak staining of benign prostate, and strong cytoplasmic staining in localized prostate cancer. Benign prostate glands demonstrated absent or weak expression in the secretory, luminal cells. Infiltrating prostate cancers demonstrated strong pim-1 protein expression. Magnification for all images 1000×. FIG. 4a shows a histogram of pim-1 protein expression by tissue type as assessed from 810 tissue microarray elements. High-grade intraepithelial neoplasia (HG-PIN). Localized prostate cancer (PCA). Relative strength of pim-1 staining is represented in the included legend. The percentage of pim-1 staining per category shown on y-axis. FIG. 4b shows Kaplan-Meier analysis demonstrating that patients with PCA that have negative to weak pim-1 expression (bottom line) are at a greater risk of developing PSA-failure following prostatectomy (log rank p=0.04). PSA-free survival was stratified by level of pim-1 protein expression into two categories absent/weak expression (bottom line) versus moderate/strong expression (top line).
Pim-1 protein was found to be markedly overexpressed in PCA (FIG. 4). Negative to weak pim-1 protein expression was observed in the majority of benign prostatic epithelial (97%), prostatic atrophy (73%), and high-grade PIN (82%) samples (FIG. 4a). In contrast, moderate to strong pim-1 expression was observed in approximately half of the PCA samples (51%) (FIG. 4a). Kaplan-Meier analysis for PSA-free survival demonstrated positive extraprostatic extension, seminal vesicle invasion, Gleason score greater than 7 and decreased pim-1 expression to be associated with a higher cumulative rate of PSA failure (FIG. 4b). By univariate Cox models, it was found that Pim-1 expression is a strong predictor of PSA recurrence (hazard ratio (HR)=2.1 (95% CI 1.2-3.8, p=0.01)).
Among the variables examined, significant predictors of PSA recurrence were Gleason score (HR=1.8 (95% CI. 1.1-3.0), p=0.03), Gleason pattern 4/5 PCA (HR=3.9(95% CI 1.8-8.3), p<0.001), extraprostatic extension status (HR=2.6 (95% CI 1.6-4.2), p<0.0001), surgical margin status (HR=2.6 (95% CI 1.2-5.6), p=0.01), seminal vesicle status (HR=3.5 (95% CI 2.0-6.2), p<0.0001), the natural log of pre-operative PSA level (HR=2.5 (95% CI 1.6-3.8), p<0.001), HR=2.4, p<0.001), and maximum tumor dimension (HR=2.7 (95% CI 1.6-4.7), p<0.0001). Presence of Gleason pattern 4/5 PCA (HR=3.8 (95% CI 1.4-10.0), p<0.01), Ln(PSA) (HR=2.1 (95% CI 1.1-3.9), p=0.02), and decreased pim-1 protein expression (HR=4.5 (95% CI 1.6-15.2), p=0.01) were both found to be significant predictors of PSA recurrence by a multivariate Cox model. Thus, even more so than hepsin, decreased expression of pim-1 kinase in PCA correlated significantly with measures of poor patient outcome.
Pim-1 kinase is a proto-oncogene that is regulated by cytokine receptors (Matikainen et al., Blood 93:1980 [1999]). It was first described as a common site of proviral integration in murine retrovirus-induced T cell lymphomas (Cuypers et al., Cell 37:141 [1984]), and was previously thought to be involved exclusively in hematopoietic malignancies (Breuer et al., Nature 340:61 [1989]). Co-transcriptional regulation of pim-1 and myc was observed in the experiments described herein (FIG. 2 cell growth/cell death cluster). Chronic overexpression of myc in the ventral prostate of transgenic mice induced epithelial abnormalities similar to low-grade PIN, but progression to adenocarcinoma in this model was never observed (Zhang et al., Prostate 43:278 [2000]). The present invention is not limited to any one mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that pim-1 overexpression may potentiate myc-induced prostate carcinogenesis.
FIG. 8 provides a schematic overview of representative genes differentially expressed in PCA identified by DNA microarray analysis. Genes are grouped functionally and arrows represent up- or down-regulation in metastatic hormone-refractory PCA (MET) and/or localized PCA (PCA) relative to normal prostate epithelium. See FIG. 2 for gene expression levels.
EXAMPLE 5
AMACR Expression Analysis
The Example describes the analysis of the gene expression data described in Examples 1-4 above to identify AMACR as being consistently over-expressed in prostate cancer.
A. Tissue Samples
In order to examine the widest range of prostate cancer specimens, clinical samples were taken from the radical prostatectomy series at the University of Michigan and from the Rapid Autopsy Program. Both programs are part of the University of Michigan Prostate Cancer Specialized Program of Research Excellence (S.P.O.R.E.) Tissue Core.
Prostatectomy cases for the tissue microarray (TMA) outcomes array were selected from a cohort of 632 patients, who underwent radical retropubic prostatectomy at the University of Michigan as a monotherapy (i.e., no hormonal or radiation therapy) for clinically localized prostate cancer between the years of 1994 and 1998. Clinical and pathology data for all patients was acquired with approval from the Institutional Review Board at the University of Michigan. Detailed clinical, pathology, and TMA data is maintained on a secure relational database (Manley et al., Am. J. Pathol., 159:837 [2001]).
Processing of the prostate specimens began within approximately 15-20 minutes after surgical resection. The prostates were partially sampled and approximately 50% of the tissue was used for research. This protocol has been evaluated in a formal study to assure that partial sampling does not impair accurate staging and evaluation of the surgical margins (Hollenbeck et al., J. Urol., 164:1583 [2000]). Briefly, alternate sections of the prostate gland were submitted for histologic review. The remaining sections were frozen and stored in the SPORE Tissue Core. These samples were collected only from patients who had signed an IRB-approved informed consent. The samples were snap-frozen in OCT embedding media at −80° C. and stored in a holding area until the pathology report was finalized. These frozen samples were not available to researchers until adequate diagnosis and staging had been performed. The samples used for cDNA expression array analysis and RT-PCR were all evaluated by the study pathologists. All samples were grossly trimmed such that greater than 95% of the sample represented the desired lesion (e.g., prostate cancer, BPH, or benign prostate). Samples with prostate cancer were also assigned a Gleason score based on the sample used for molecular analysis.
In order to study hormone refractory prostate cancer, a Rapid Autopsy Protocol was used, which represents a valuable source of metastatic prostate tumors. Modeled after protocols developed at the University of Washington (Seattle, Wash.) and Johns Hopkins University (Baltimore, Md.), this program allows men with advanced prostate cancer to consent to an autopsy immediately after death. To date, 23 complete autopsies have been performed with a median time of 2 hours from death to autopsy. This procedure has previously been described in detail (Rubin et al., Clin. Cancer Res., 6:1038 [2000]). In brief, patients diagnosed with hormone refractory prostate cancer were asked to take part in a posthumous tissue donor program. The objectives and procedures for tissue donation were explained to the patient. Having agreed to participate in this IRB-approved tumor donor program, permission for autopsy is obtained before the death, with consent provided by the patient, or by next of kin. Hormone refractory primary and metastatic prostate cancer samples were collected using liquid nitrogen. Mirrored samples from the same lesion were placed in 10% buffered formalin. The fixed samples were embedded in paraffin and used for the development of TMAs. As with the prostatectomy samples, the study pathologist reviewed the glass slides, circled areas of viable prostate cancer, while avoiding areas of necrosis, and used these slides as a template for TMA construction.
B. Pathology and Evaluation
Prostates were inked before the assessment of surgical margins. Surgical margins from the apex and base were cut perpendicular to the prostatic urethral axis. The seminal vesicles were cut perpendicular to their entry into the prostate gland and submitted as the seminal vesicle margin. The prostates for this study were all partially embedded, taking alternate full sections from the apex, mid, and base. Detailed prostatectomy pathology reports included the presence or absence of surgical margin involvement by tumor (surgical margin status), the presence of extraprostatic extension, and seminal vesicle invasion. Tumors were staged using the TNM system, which includes extraprostatic extension and seminal vesicle invasion but does not take into account surgical margin status (Bostwick et al., Simin. Urol. Oncol., 17:222 [1999]). Tumors were graded using the Gleason grading system (Gleason, Cancer Chemother. Rep., 50:125 [1966]; Gleason, The Veterans Administration Cooperative Urological Research Group. Histologic Grading and Clinical Staging of Prostate Carcinoma. In: Tannenbaum M, editor. Urologic Pathology: The Prostate. Philadelphia: Lea & Febiger; 1977. p. 171-98).
As preparation for the construction of the TMAs, all glass slides were re-reviewed to identify areas of benign prostate, prostatic atrophy, high-grade prostatic intraepithelial neoplasia, and prostate cancer. To optimize the transfer of these designated tissues to the arrays, area of tumor involvement was encircled on the glass slide template as tightly around each lesion as possible. Areas with infiltrating tumor adjacent to benign glands were avoided.
C. RT-PCR
Total RNA integrity was judged by denaturing-formaldehyde agarose gel electrophoresis. cDNA was prepared using 1 μg of total RNA isolated from prostate tissue specimens. Primers used to amplify specific gene products were: AMACR sense, 5′CGTATGCCCCGCTGAATCTCGTG-3′ (SEQ ID NO:100); AMACR antisense, 5′-TGGCCAATCATCCGTGCTCATCTG-3′ (SEQ ID NO:101); GAPDH sense, 5′-CGGAGTCAACGGATTTGGTCGTAT-3′ (SEQ ID NO:102); and GAPDH antisense, 5′-AGCCTTCTCCATGGTGGTGAAGAC-3′ (SEQ ID NO: 103). PCR conditions for AMACR and GAPDH comprised 94° C. for 5 min, 28 cycles of 95° C. for 1 min, 60° C. for 1 min (annealing), and 72° C. for 1 min, and a final elongation step of 72° C. for 7 min. PCR reactions used a volume of 50 μl, with 1 unit of Taq DNA polymerase (Gibco BRL). Amplification products (5 μl) were separated by 2% agarose gel electrophoresis and visualized by ultraviolet light.
D. Immunoblot Analysis
Representative prostate tissue specimens were used for Western blot analysis. Tissues were homogenized in NP-40 lysis buffer containing 50 mmol/L Tris-HCl, pH 7.4, 1% Nonidet P-40 (Sigma, St. Louis. MO) and complete proteinase inhibitor cocktail (Roche, Ind., USA). Fifteen μg of protein extracts were mixed with SDS sample buffer and electrophoresed onto a 10% SDS-polyacrylamide gel under reducing conditions. The separated proteins were transferred onto nitrocellulose membranes (Amersham Pharmacia Biotech, Piscataway, N.J.). The membrane was incubated for 1 hour in blocking buffer (Tris-buffered saline with 0.1% Tween (TBS-T) and 5% nonfat dry milk). The AMACR antibody (Obtained from Dr. R Wanders, University of Amsterdam) was applied at 1:10,000 diluted in blocking buffer overnight at 4° C. After washing three times with TBS-T buffer, the membrane was incubated with horseradish peroxidase-linked donkey anti-rabbit IgG antibody (Amersham Pharmacia Biotech, Piscataway, N.J.) at 1:5000 for 1 hour at room temperature. The signals were visualized with the ECL detection system (Amersham Pharmacia biotech, Piscataway, N.J.) and autoradiography.
For β-tubulin western blots, the AMACR antibody probed membrane was stripped with Western Re-Probe buffer (Geno-tech, St. Louis, Mo.) and blocked in Tris-buffered saline with 0.1% Tween (TBS-T) with 5% nonfat dry milk and incubated with rabbit anti β-tubulin antibodies (Santa Cruz Biotechnologies, Santa Cruz, Calif.) at 1:500 for two hours. The western blot was then processed as described above.
E. Immunohistochemistry
Standard indirect immunohistochemistry (IHC) was performed to evaluate AMACR protein expression using a polyclonal anti-AMACR antibody. Protein expression was scored as negative (score=1), weak (score 2), moderate (3) and strong (4). In order to evaluate whether AMACR protein expression was associated with prostate cancer proliferation, a subset of samples were evaluated using the monoclonal mouse IgG Mib-1 antibody for Ki-67 (1:150 dilution, Coulter-Immunotech, Miami, Fla.). Microwave pretreatment (30 minutes at 100 C. in Tris EDTA Buffer) for antigen retrieval was performed using 3,3′ diaminobenzidine tetrahydrocloride as a chromogen. Lymph node tissue with known high Ki-67 positivity was used as a control.
F. Tissue Microarray Construction, Digital Image Capture, and Analysis
Five TMAs were used for this study. Three contained tissue from the prostatectomy series and two contained hormone refractory prostate cancer from the Rapid Autopsy Program. The TMAs were assembled using the manual tissue arrayer (Beecher Instruments, Silver Spring, Md.) as previously described (Kononen et al., Nat. Med., 4:844 [1998]; Perrone et al., J. Natl. Cancer Inst., 92:937 [2000]). Tissue cores from the circled areas (as described above) were targeted for transfer to the recipient array blocks. Five replicate tissue cores were sampled from each of the selected tissue types. The 0.6 mm diameter TMA cores were each spaced at 0.8 mm from core-center to core-center. After construction, 4 μm sections were cut and H&E staining was performed on the initial slide to verify the histology.
TMA H&E images were acquired using the BLISS Imaging System (Bacus Labs, Lombard, Ill.). AMACR protein expression was evaluated in a blinded manner. All images were scored for AMACR protein expression intensity. In addition, all TMA samples were assigned a diagnosis (i.e., benign, atrophy, high-grade prostatic intraepithelial neoplasia, and prostate cancer). This is recommended because the targeted tissues may not be what were actually transferred. Therefore, verification was performed at each step. TMA slides were evaluated for proliferation index using a CAS200 Cell Analysis System (Bacus Labs). Selected areas were evaluated under the 40× objective. Measurements were recorded as the percentage of total nuclear area that was positively stained. All positive nuclear staining, regardless of the intensity, was measured. Sites for analysis were selected to minimize the presence of stromal and basal cells; only tumor epithelium was evaluated. Specimens were evaluated for Ki-67 expression as previously described (Perrone et al., J. Natl. Cancer Inst. 92:937 [2000]). Each measurement was based on approximately 50-100 epithelial nuclei. Due to the fixed size of TMA samples, repeat non-overlapping measurement was the maximum attainable.
G. Analysis of Prostate Needle Biopsies
In order to evaluate the usefulness of AMACR expression in diagnostic 18 gauge needle biopsies, 100 consecutive biopsies with prostate cancer or atypia that required further work-up were tested for AMACR expression. All cases were immunostained using two basal cell specific markers (34βE12 and p63) and AMACR. Cases were evaluated for cancer sensitivity and specificity. Twenty-six of these cases were seen in consultation with a pathologist and were considered diagnostically difficult, requiring expert review and additional characterization.
H. Results
FIG. 11 shows a schematic of the DNA and tissue microarray paradigm that lead to the discovery and characterization of AMACR in prostate cancer. A) Prostate cancer progression as adapted from Abate-Shen and Shen, (Genes Dev., 14:2410 [2000]). Distinct molecular changes occur at each stage of prostate cancer progression that can be studied using DNA microarray or “chip” technology. B) cDNA generated from tumor (prostate cancer) and reference (benign prostate tissue) samples is labeled with distinguishable fluorescent dyes and interrogated with a DNA microarray that can monitor thousands of genes in one experiment. C) After hybridization, the DNA microarray is analyzed using a scanner and fluorescence ratios determined for each gene (in this case prostate cancer/benign tissue). D) The ratios are deposited into a computer database and subsequently analyzed using various statistical algorithms. One exemplary method of surveying the data (Eisen et al., PNAS 95:14863 [1998]) assigns color intensity to the ratios of gene expression. In this case, shades of red represent genes that are up-regulated in prostate cancer (e.g., a ratio of 4.0) and shades of green represent genes that a down-regulated (e.g., ratio of 0.1). Genes that are unchanged between tumor and benign tissues are represented by a black color and missing elements by a gray color. E) Genes that are identified by DNA microarray can then be validated at the transcript level (e.g., Northern blot, RT-PCR) or at the protein level (e.g., immunoblot). F) Construction of prostate cancer tissue microarrays facilitates the study of hundreds of patients (rather than hundreds of genes). G) Each tissue microarray slide contains hundreds of clinically stratified prostate cancer specimens linked to clinical and pathology databases (not shown). H) Tissue microarray slides can then be analyzed using various molecular or biochemical methods (in this case immunohistochemistry). I) Both DNA and tissue microarray data have clinical applications. Examples include, but are not limited to: 1. using gene expression profiles to predict patient prognosis, 2. identification of clinical markers and 3. development of novel therapeutic targets.
FIG. 12 summarizes AMACR transcript levels as determined by DNA microarray analysis over 57 prostate cancer specimens. Samples (Dhanasekaran et al., Nature 412: 822 [2001]) were grouped according to tissue type and averaged. The experimental sample was labeled in the Cy5 channel while the reference sample (pool of benign prostate tissue) was labeled in the Cy3 channel. The box-plot demonstrates the range of AMACR expression within each group. Tissues were grouped into the following classes benign (normal adjacent prostate tissue), benign prostatic hyperplasia (BPH), clinically localized prostate cancer, and metastatic prostate cancer. In relation to benign prostate tissues, localized prostate cancer and metastatic prostate cancer were 3.1 (Mann-Whitney test, p<0.0001) and 1.67 (Mann-Whitney test, p<0.004) fold up-regulated, respectively (represented as Cy5/Cy3 ratios).
DNA microarray results of AMACR mRNA levels were validated using an independent experimental methodology. AMACR-specific primers were generated and RT-PCR performed on the various RNA samples from 28 prostate tissue specimens and 6 prostate cell lines (FIG. 13A). GAPDH served as the loading control. Pool, refers to RNA from normal prostate tissues obtained from a commercial source. NAP, normal adjacent prostate tissue from a patient who has prostate cancer. 3+3, 3+4, 4+4, refers to the major and minor Gleason patterns of the clinically localized prostate cancer (PCA) examined. MET, metastatic prostate cancer. Various prostate cell lines are also examined. RT-PCR without enzyme served as a negative control. An RT-PCR product was clearly observed in the 20 localized prostate cancer samples but not in the benign samples examined. Metastatic prostate cancer and prostate cell lines displayed varying levels of AMACR transcript as compared to localized prostate cancer.
In order to gauge AMACR protein levels, immunoblot analysis was performed on selected prostate tissue extracts (FIG. 13B). β-tubulin served as a control for sample loading. Similar to AMACR transcript, over-expression of AMACR protein was observed in malignant prostate tissue relative to benign prostate tissue.
In order to validate protein expression of AMACR in situ, a separate cohort of prostate samples from those used in the cDNA expression array analysis was used. These prostate samples were taken from the University of Michigan Prostate SPORE Tissue Core and were assembled onto high-density tissue microarrays (schematically illustrated in FIG. 11F-H). Moderate to strong AMACR protein expression was seen in clinically localized prostate cancer samples with predominately cytoplasmic localization. A large contrast in levels of AMACR in malignant epithelia relative to adjacent benign epithelia was seen. Prostatic intraepithelial neoplasia (PIN) and some atrophic lesions, which are thought to be potentially pre-cancerous lesions (Putzi et al., Urology 56:828 [2000]; Shah et al., Am. J. Pathol., 158:1767 [2001]), demonstrated cytoplasmic staining of AMACR. High-grade prostate cancer also demonstrated strong cytoplasmic staining. However, no association was identified with AMACR staining intensity and Gleason (tumor) score. Many of the metastatic prostate cancer samples demonstrated only weak AMACR expression. The metastatic samples showed uniform PSA immunostaining, confirming the immunogenicity of these autopsy samples.
In order to assess AMACR protein expression over hundreds of prostate specimens, the tissue microarray data was quantitated. Benign prostate, atrophic prostate, PIN, localized prostate cancer, and metastatic prostate cancer demonstrated mean AMACR protein staining intensity of 1.0 (SE 0), 2.0 (SE 0.1), 2.5 (SE 0.1), 3.0 (SE 0), and 2.5 (SE 0.1), respectively (ANOVA p-value<0.0001). This data is graphically summarized using error bars representing the 95% confidence interval for each tissue category (FIG. 14).
The correlation of AMACR levels with tumor proliferation was next investigated using Ki-67 (Pyrrone et al., supra). There was no significant association between AMACR expression and Ki-67 expression with a correlation coefficient of 0.13 (p-value=0.22). In addition, no significant associations were identified between AMACR protein expression and pathology parameters such as radical prostatectomy, Gleason score, tumor stage, tumor size (cm), or surgical margin status. AMACR protein levels were next evaluated for association with PSA recurrence following surgery in 120 prostatectomy cases with a median follow-up time of 3 years. No statistically significant association was identified. AMACR demonstrated uniform moderate to strong expression in clinically localized prostate cancer with a high sensitivity for tumor and an equally high specificity. In addition, a preliminary survey of normal tissues including ovary, liver, lymph nodes, spleen, testis, stomach, thyroid, colon, pancreas, cerebrum, and striated muscle revealed significant AMACR protein expression in only normal liver.
The large difference in AMACR protein levels between normal secretory epithelial cells and malignant cells provides a clinical use for testing AMACR expression in prostate needle biopsy specimens. In diagnostically challenging cases, pathologists often employ the basal cell markers 34βE12 (O'Malley et al., Virchows Arch A Patho. Anat. Histopathol., 417:191 [1990]; Wojno et al., Am. J. Surg. Pathol., 19:251 [1995]; Googe et al., Am. J. Clin. Pathol., 107:219 [1997] or p63 (Parson et al., Urology 58:619 [2001]; Signoretti et al., Am. J. Pathol., 157:1769 [2000]), which stain the basal cell layer of benign glands. This second basal cell layer is absent in malignant glands. In many equivocal biopsy specimens, the surgical pathologist must rely on absence of staining to make the final diagnosis of prostate cancer. The clinical utility of AMACR immunostaining on 94 prostate needle biopsies was evaluated. The results are shown in Table 2. The sensitivity and specificity were calculated as 97% and 100%, respectively. These results included 26 cases where the final diagnosis required the use of a basal cell specific immunohistochemical marker (i.e., 34βE12 or p63).
This example demonstrated that AMACR is associated with PCA and that AMACR expression in prostate biopsies is useful for the diagnosis of cancer in inconclusive biopsy samples.







TABLE 2







Clinical utility of Assessing AMACR Protein in Prostate Needle


Biopsies (n = 94)












Positive
Negative


Sensitivity
Specificity
Predictive
Predictive


(TP/
(TN/
Value (TP/
Value (TN/


(TP + FN))
(TN + FP))
(TP + FP))
(TN + FN))





97% ((68/(2 + 68))
100% ((24/(24 + 0))
100%
92%




((68/(68 + 0))
((24/24 + 2))









EXAMPLE 6
Hormone Regulation of AMACR
This example describes studies that indicate that AMACR expression is hormone independent.
A. Sample Collection, cDNA Array and TMA Construction and Evaluation
Clinical samples were taken from the radical prostatectomy series and from the Rapid Autopsy Program at the University of Michigan. Both are part of the University of Michigan Prostate Cancer Specialized Program of Research Excellence (S.P.O.R.E.). Primary PCA of metastatic cases as well as lymph node metastases were contributed in collaboration from the University of Ulm, Germany. Detailed clinical and expression analysis as well as TMA data was acquired and maintained on a secure relational database according to the Institutional Review Board protocol of both institutions. Tissue procurement for expression analysis on the RNA level is described in the above examples. For the development of TMA, samples were embedded in paraffin. The study pathologist reviewed slides of all cases and circled areas of interest. These slides were used as a template for construction of the six TMAs used in this study. All TMAs were assembled using a manual tissue arrayer (Beecher Instruments, Silver Spring, Md.). At least three tissue cores were sampled from each donor block. Histologic diagnosis of the tissue cores was verified by standard haematoxylin and eosin (H&E) staining of the initial TMA slide. Standard biotin-avidin complex immunohistochemistry (IHC) was performed using a polyclonal anti-AMACR antibody (Ronald Wanders, University of Amsterdam). Digital images were acquired using the BLISS Imaging System (Bacus Lab, Lombard, Ill.). Staining intensity was scored as negative (score=1), weak (score 2), moderate (3) and strong (4). For exploration of the treatment effect by the means of hormonal withdrawal before radical prostatectomy, standard slides were used for regular H&E staining and consecutive sections for detection of AMACR expression. In order to test AMACR expression in poorly differentiated colon cancers, cases were used from a cohort of well-described colon tumors. In addition to well-differentiated colon cancers, a recently described subset of poorly differentiated colon carcinomas with a distinctive histopathological appearance, termed large cell minimally differentiated carcinomas, was used. These poorly differentiated colon carcinomas had a high frequency of the microsatellite instability phenotype.
B. Cell Culture and Immunoblot Analysis
Prostate cell lines (RWPE-1, LNCaP, PC3 and DU145) were obtained from the American Tissue Culture Collection. Cells were maintained in RPMI-1640 with 8% decomplemented fetal bovine serum, 0.1% glutamine and 0.1% penicillin and streptomycin (BioWhittaker, Walkersville, Md.). Cells were grown to 75% confluence and then treated for 24 and 48 with the antiandrogen bicalutamide (CASODEX, Zeneca Pharmaceuticals, Plankstadt, Germany) at a final concentration of 20 μM or with methyltrienolone (synthetic androgen (R1881); NEN, Life Science Products, Boston, Mass.) at a final concentration of 1 nM. Cells were harvested and lysed in NP-40 lysis buffer containing 50 mmol/L Tris-HCl, pH 7.4, 1% Nonidet P-40 (Sigma, St. Louis, Mo.) and complete proteinase inhibitor cocktail (Roche, Ind., USA). 15 μg of protein extracts were mixed with SDS sample buffer and electrophoresed onto a 10% SDS-polyacrylamide gel under reducing conditions. After transferring, the membranes (Amersham Pharmacia Biotech, Piscataway, N.J.) were incubated for 1 hour in blocking buffer (Tris-buffered saline with 0.1% Tween and 5% nonfat dry milk). The AMACR antibody was applied at 1:10.000 diluted blocking buffer overnight at 4° C. After three washes with TBS-T buffer, the membrane was incubated with horseradish peroxidase-linked donkey anti-rabbit IgG antibody (Amersham Pharmacia Biotech, Piscataway, N.J.) at 1:5000 for 1 hour at room temperature. The signals were visualized with the ECL detection system (Amersham Pharmacia biotech, Piscataway, N.J.). For β-tubulin blots, membranes were stripped with Western Re-Probe buffer (Geno-tech, St. Louis, Mo.) and blocked in Tris-buffered saline with 0.1% Tween with 5% nonfat dry milk and incubated with rabbit anti β-tubulin antibodies (Santa Cruz Biotechnologies, Santa Cruz, Calif.) at 1:500 for two hours. For PSA expression the membranes were reprobed in the described manner with PSA antibody (rabbit polyclonal; DAKO Corporation, Carpinteria, Calif.) at 1: 1000 dilution and further processed.
C. Statistical Analysis
Primary analysis of the cDNA expression data was done with the Genepix software. Cluster analysis with the program Cluster and generation of figures with TreeView was performed as described above. AMACR protein expression was statistically evaluated using the mean score result for each prostate tissue type (i.e., benign prostate, naive localized or advanced prostate cancer, hormone treated and hormone refractory prostate cancer). To test for significant differences in AMACR protein expression between all tissue types, a one-way ANOVA test was performed. To determine differences between all pairs, a post-hoc analysis using the Scheffé method was applied as described above. For comparison of naive primaries to their corresponding lymph node metastases with respect to AMACR protein expression, a non parametric analysis (Mann Whitney test) was performed. To compare AMACR expression intensity to the scored hormonal effect of the pretreated localized prostate cancer cases the Mantel-Haenszel Chi-Square test was applied. AMACR expression scores are presented in a graphical format using error-bars with 95% confidence intervals. P-values<0.05 were considered statistically significant.
D. Results
Hierarchical clustering of 76 prostate tissues including benign, BPH, localized PCA and metastatic PCA and filtering for only those genes with a 1.5 fold expression difference or greater, clustered the samples into histologically distinct groups as described above. As demonstrated by a TreeView presentation of this data (FIG. 15), AMACR was one of several genes that demonstrated over expression at the cDNA level of PCA samples with respect to benign pooled prostate tissue. The highest level of over expression by cDNA analysis was in the clinically localized PCA cases.
In order to further investigate the role of AMACR protein expression in samples with variable differentiation and exposure to anti-androgen treatment, several TMAs with a wide range of PCA were constructed: a total of 119 benign prostate samples, 365 primary hormone naive PCA samples, 37 naive prostate cancer lymph node metastases, and 41 hormone refractory metastatic PCA samples were evaluated. An additional 49 hormone treated primary prostate cancers (including 22 on standard slides) were examined for histologic changes associated with anti-androgen treatment and AMACR protein expression. The mean AMACR protein expression levels for each tissue category is presented in FIG. 16. Benign prostate, naive primary prostate cancer, hormone treated primary cancer, and hormone refractory metastatic tissue had a mean staining intensity of 1.28 (Standard Error SE 0.038, 95% Confidence Intervals CI 1.20-1.35), 3.11(SE 0.046, CI 3.02-3.20), 2.86 (SE 0.15, CI 2.56-3.15) and 2.52 (SE 0.15, CI 2.22-2.28), respectively). One-way ANOVA analysis revealed a p-value of <0.0001. To specifically examine the difference between different tissue types, a post-hoc pair-wise comparison was performed. Clinically localized PCA demonstrated a significantly stronger AMACR protein expression as compared to benign prostate tissue (post-hoc analysis using Scheffé method, mean difference=1.83, p<0.0001, CI 1.53-2.13). A significant decrease in AMACR protein expression was observed in the metastatic hormone refractory PCA samples with respect to clinically localized PCA (0.59, p=0.002, CI 0.15-1.03). Hormone treated primaries had a mean AMACR expression of 2.86, which was between the expression levels of naive primaries (3.11) and hormone refractory cases (2.52) (post-hoc analysis using Scheffé method, p=0.51, CI −0.66-0.16 and p=0.56, CI −0.23-0.91). There was no significant difference in AMACR expression in the 37 naive primary prostate samples and lymph node metastases derived from the same patient (Mann Whitney test, p=0.8). In other words, matched primaries and lymph node metastases showed similar AMACR expression pattern.
A subset of 22 PCA cases in which the patients received variable amount and types of anti-androgen treatment prior to surgery was examined. These cases were evaluated blindly with respect to treatment protocol for histological evidence of hormone treatment (H&E slide) and AMACR protein expression. The hormonal effect visible on the H&E slides was classified from 1 to 4 with 1 representing “no effect” and 4 showing a “very strong effect”. 13 cases demonstrated either no or moderate hormonal effect, and 9 cases had a very strong hormonal effect. Statistical analysis revealed a significant difference between these two groups with respect to AMACR expression intensity (FIG. 17, Mantel-Haenszel Chi-Square, p=0.009). FIG. 17 presents an example of a PCA case treated prior to surgery with anti-androgens that has a strong hormonal effect appreciated on H&E and decreased AMACR protein expression (FIG. 17A). In this dataset there was neither a correlation between treatment duration nor treatment type (monotherapy or complete hormonal withdrawal for hormone deprivation) and AMACR expression.
For further exploration of the hormonal effect on AMACR expression, primary cell culture experiments and Western blot analysis were performed. As demonstrated in FIG. 17 Panel B, LNCaP cells, derived from a metastatic lesion but considered hormone responsive, showed a higher baseline AMACR expression as compared to PC3 and DU-145 cells, which are both hormone independent cell lines derived from metastatic lesions. A benign cell line, RWPE-1 (Bello et al., Carcinogenesis 18:1215 [1997]), showed near absent AMACR expression, which is consistent with the in situ protein expression data. To simulate an anti-androgen treatment, the hormone responsive cell line LNCaP was treated with bicalutamide in a final concentration of 20 μM for a time period of 24 and 48 hours. AMACR expression in cell lysates of LNCaP cells did not change at either time point when exposed to anti-androgen therapy. Under the same conditions, PSA, a gene known to be regulated by the androgen receptor, showed decreased protein expression. In addition, when LNCaP cells were exposed to a synthetic androgen R1881, no increase in AMACR expression was observed (FIG. 17, Panel B). Therefore, these cell culture experiments provide evidence that AMACR expression is not regulated by the androgen pathway.
The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that another explanation for these observations was that AMACR over expression occurred in PCA, but as these tumors became poorly differentiated, as in the hormone refractory PCA, AMACR expression was down regulated either directly or indirectly due to the process of de-differentiation. To elucidate this potential correlation colon cancer samples were examined for AMACR expression (See Example 7). AMACR protein expression is also observed in some other tumor types, with the highest overall expression in colorectal cancers. Colorectal cancers are not known to be regulated by androgens and were therefore used as a control to test this hypothesis. Four well differentiated and seven anaplastic colon cancer samples were chosen. The poorly differentiated tumors have distinct molecular alterations distinguishing them from the common well to moderately differentiated colorectal tumors (Hinoi et al., Am. J. Pathol. 159:2239 [2001]). Strong AMACR protein expression in a moderately differentiated colon cancer was observed. This tumor still forms well defined glandular structures. The surrounding benign colonic tissue does not express AMACR. The anaplastic colon cancers demonstrated weak AMACR protein expression. Primarily data revealed positive AMACR expression in 4/4 well differentiated cases but only 4/7 anaplastic colonic cancers. Three of the anaplastic colon cancers had weak to moderate expression. Metastatic hormone refractory PCA demonstrated weak AMACR protein expression in tissue microarrays.
EXAMPLE 7
AMACR Expression in a Variety of Cancers
A. Analysis of Online EST and SAGE Database
The National Cancer Institute Cancer Genome Anatomy Project (CGAP) has several gene expression databases available online for comparing gene expression across multiple samples (See the Internet Web site of the National Cancer Institute). Both EST and SAGE databases offer Virtual Northern blots, which allow users to visualize and compare the expression level of a particular gene among multiple samples. The SAGE database includes over 5 million tags from 112 libraries of multiple benign and malignant tissues.
B. Selection of Study Cases
A total of 96 cases of cancers from different sites were selected for construction of a multi-tumor tissue microarray. The tissue microarray was constructed to perform a wide survey of multiple common tumor types. A minimum of three tissue cores (0.6 mm in diameter) was taken for each case. Tumors surveyed included colorectal adenocarcinoma (n=15 cases), renal cell carcinoma (6), prostatic adenocarcinoma (6), urothelial carcinoma (4), cervical squamous cell carcinoma (6), lung non-small cell carcinoma (4), lymphoma (15), melanoma (9) and several other cancer types. Normal adjacent tissue was taken when available. The prostate tissue microarray was constructed from selected patients who underwent radical prostatectomies as monotherapy for clinically localized prostate cancer. This tissue microarray contained a spectrum of prostatic tissue including prostatic atrophy, high-grade prostatic intraepithelial neoplasia (PIN), and clinically localized prostate cancer. In addition, standard slides were used to confirm results for colon cancer. Twenty-four cases of colorectal adenocarcinoma (16 well to moderately differentiated carcinoma and 8 large cell minimally differentiated carcinoma) and 8 endoscopically derived colorectal adenomas were selected for immunostaining for AMACR. For breast carcinoma, a TMA of 52 cases of invasive ductal carcinoma was used. Specimens were collected and analyzed in accordance with the Institutional Review Board guidelines.
C. Immunohistochemistry
Standard avidin-biotin complex immunohistochemistry was used. Pre-treatment was performed by steaming the slides for 10 minutes in sodium citrate buffer in a microwave oven. The slides were then incubated sequentially with primary antibody (1:2000 dilution, polyclonal rabbit anti-AMACR antibody), biotinylated secondary antibody, avidin-biotin complex and chromogenic substrate 3,3′-diaminobenzidine. Slides were evaluated for adequacy using a standard bright field microscope. Digital images were then acquired using the BLISS Imaging System (Bacus Lab, Lombard, Ill.) and evaluated by two pathologists. Protein expression was scored as negative, weak stain (faint cytoplasmic stain or granular apical staining), moderate (diffuse granular cytoplasmic stain) and strong (diffuse intense cytoplasmic stain). Only moderate and strong staining was considered as positive staining.
D. Laser Capture Microdissection
Sections of 2 radical prostatectomy samples were frozen in OCT in accordance with an Institutional Review Board protocol. Frozen sections (5 μm thick) were fixed in 70% alcohol for 10 minutes and then stained in hemotoxylin and eosin. Prostate cancer and benign prostate glands were dissected on a μCUT laser capture microdissector (MMI GmbH, Heidelberg, Germany). Approximately 6000 cells were harvested. Total RNA was isolated using Qiagen micro-isolation kit (Qiagen, San Diego, Calif.). Reverse transcription was performed using both oligo dT and random hexamer primers. Primers used to amplify specific gene products were: AMACR sense, 5′-CGTATGCCCCGCTGAATCTCGTG-3′ (SEQ ID NO:100); AMACR antisense, 5′-TGGCCAATCATCCGTGCTCATCTG-3′ (SEQ ID NO:105); GAPDH sense, 5′AGCCTTCTCCATGGTGGTGAAGAC-3′ (SEQ ID NO:106); and GAPDH antisense, 5′-AGCCTTCTCCATGGTGGTGAAGAC-3′ (SEQ ID NO:107). PCR conditions for AMACR and GAPDH were: heat denaturation at 94° C. for 5 mm, cycles of 940C for 1 mm 60° C. for 1 mm, and 72° C. for 1 mm (32 cycles for GAPDH, 40 cycles for AMACR), and a final extension step at 72° C. for 5 min. PCR products were then separated on 2% agarose gel and visualized by UV illumination.
E. Results
Using the Virtual Northern tool from the online CGAP program, AMACR expression was surveyed in two databases, EST and SAGE libraries. AMACR was found to be expressed in a wide range of tissues, including central and peripheral nervous system, colon, kidney, breast, pancreas, prostate and blood. Compared to their normal counterparts, a number of cancers have elevated AMACR expression, including tumors arising in bone marrow, breast, colon, genitourinary system, lung, lymph node, nervous system, pancreas, prostate, soft tissue and uterus.
To confirm the gene expression data, AMACR immunohistochemistry was performed on a multi-tumor tissue array that included some of the most common cancers from multiple sites. AMACR protein level was increased in many cancers, including colorectal, prostate, ovarian, lung cancers, lymphoma and melanoma (FIG. 18). In particular, AMACR over-expression was observed in 92% and 83% of colorectal and prostate cancer, respectively. Using a breast cancer tissue microarray, it was found that AMACR over-expression was present in 44% of invasive ductal carcinomas. AMACR over expression was not observed in female cervical squamous cell carcinoma (6 cases).
To further characterize AMACR expression in a spectrum of proliferative prostate lesions, a prostate tissue microarray, which included prostate cancer, high grade PIN and atrophic glands, was utilized. Positive AMACR staining (moderate and strong staining) was observed in 83% and 64% of clinically localized prostate cancer and high-grade PIN, respectively. Focal AMACR expression was observed in 36% of the atrophic lesions and in rare morphologically benign glands. To confirm that AMACR protein over-expression was the result of increased gene transcription, laser capture microdissection was used to isolate cancerous and benign prostatic glands. RT-PCR was performed to assess the AMACR mRNA expression. Benign glands had very low baseline expression (FIG. 19). In contrast, prostate cancer had much higher mRNA level, confirming that increased AMACR gene transcription leads to elevated protein over expression in prostate cancer.
AMACR expression was studied in 24 colorectal adenocarcinomas, including 16 well to moderately differentiated, and 8 poorly differentiated large cell adenocarcinomas. Overall, 83% (20/24) demonstrated positive AMACR protein expression. All (16/16, 100%) cases of well to moderately differentiated carcinoma had positive staining, compared to 64% (5/8) of poorly differentiated carcinoma. AMACR expression was examined in 8 colorectal adenoma biopsies obtained by colonoscopy. Moderate staining was present in 6 (75%) cases. Compared with well-differentiated adenocarcinomas, adenomas usually showed more focal (10-60% of cells) and less intense staining.
EXAMPLE 8
Characterization of EZH2 Expression in Prostate Cancer
A. SAM Analysis
SAM analysis was performed by comparing gene expression profiles of 7 metastatic prostate cancer samples against 10 clinically localized prostate cancer samples. Data was normalized per array by multiplication by a factor to adjust the aggregate ratio of medians to one, then log base 2 transformed and median centered. This normalized data was divided into two groups for comparison using a two-class, unpaired t-test. Critical values for the analysis include: Iterations=500, Random Number Seed 1234567, a fold change cutoff of 1.5 and a delta cutoff of 0.985, resulting in a final largest median False Discovery Rate of 0.898% for the 535 genes selected as significant (55 relatively up and 480 relatively down regulated between MET and PCA). These 535 genes were analyzed using Cluster (Eisen et al., PNAS 95:14863 [1998]) implementing average linkage hierarchical clustering of genes. The output was visualized by Treeview (Eisen et al., [1998], supra).
B. RT-PCR
Reverse transcription and PCR amplification were performed with 1 μg total RNA isolated from the indicated prostate tissues and cell lines. Human EZH2 forward (5′-GCCAGACTGGGAAGAAATCTG-3′ (SEQ ID NO:108)), reverse (5′-TGTGCTGGAAAATCCAAGTCA-3′ (SEQ ID NO:109)) and GAPDH sense (5′-CGGAGTCAACGGATTTGGTCGTAT-3′ (SEQ ID NO:110)), antisense 5′-AGCCTTCTCCATGGTGGTGAAGAC-3′ (SEQ ID NO:111)) primers were used. The amplified DNA was resolved on agarose gels and visualized with ethidium bromide.
C. Immunoblot Analysis
Prostate tissue extracts were separated by SDS-PAGE and blotted onto nitrocellulose membranes. Anti-EZH2 (Sewalt et al., Mol. Cell. Biol. 18:3586 [1998]), anti-EED (Sewalt et al., supra), and polyclonal anti-tubulin (Santa Cruz biotechnology) antibodies were used at 1:1000 dilution for immunoblot analysis. The primary antibodies were detected using horseradish peroxidase-conjugated secondary antibodies and visualized by enhanced chemiluminescence as described by the manufacturer (Amersham-Pharmacia).
D. Tissue Microarray Analysis
Clinically stratified prostate cancer tissue microarrays used in this study have been described previously (See above examples). Tissues utilized were from the radical prostatectomy series at the University of Michigan and from the Rapid Autopsy Program, which are both part of University of Michigan Prostate Cancer Specialized Program of Research Excellence (S.P.O.R.E.) Tissue Core. Institutional Review Board approval was obtained to procure and analyze the tissues used in this study.
EZH-2 protein expression was evaluated on a wide range of prostate tissue to determine the intensity and extent in situ. Immunohistochemistry was performed on three tissue microarrays (TMA) containing samples of benign prostate, prostatic atrophy, high-grade prostatic intraepithelial neoplasia (PIN), clinically localized prostate cancer (PCA), and metastatic hormone refractory prostate cancer (HR-METSs). Standard biotin-avidin complex immunohistochemistry (IHC) was performed to evaluate EZH2 protein expression using a polyclonal anti-EZH2 antibody. Protein expression was scored as negative (score=1), weak (score 2), moderate (3) and strong (4).
Approximately 700 TMA samples (0.6 mm diameter) were evaluated for this study (3-4 tissue cores per case). The TMAs were assembled using a manual tissue arrayer (Beecher Instruments, Silver Spring, Md.) as previously described (See above examples). Four replicate tissue cores were sampled from each of the selected tissue types. After construction, 4 μm sections were cut and hematoxylin and eosin staining was performed on the initial slide to verify the histologic diagnosis. TMA hematoxylin and eosin images were acquired using the BLISS Imaging System (Bacus Lab, Lombard, Ill.). EZH2 protein expression was evaluated in a blinded manner by the study pathologist using a validated web-based tool (Manley et al., Am. J. Pathol. 159:837 [2001]; Bova et al., Hum. Pathol. 32:417 [2001]) and the median value of all measurements from a single patient were used for subsequent analysis.
E. Clinical Outcomes Analysis
To assess individual variables for risk of recurrence, Kaplan-Meier survival analysis was performed and a univariate Cox proportional hazards model was generated. PSA-recurrence was defined as 0.2 ng/ml following radical prostatectomy. Covariates included Gleason sum, preoperative PSA, maximum tumor dimension, tumor stage, and surgical margin status. To assess the influence of several variables simultaneously including EZH2 protein expression, a final multivariate Cox proportional hazards model of statistically significant covariates was generated. Statistical significance in univariate and multivariate Cox models were determined by Wald's test. A p-value<0.05 was considered statistically significant.
F. EZH2 Constructs
Myc-tagged EZH2-pCMV was used. The Myc-EZH2 fragment was released with BamHI/XhoI double digest and was sub-cloned into the mammalian expression vector pcDNA3 (Invitrogen). An EZH2-ER in-frame fusion expression construct was generated by replacing the FADD fragment released by Kpn I/Not I double digest of the FADD-ER construct (originally derived from Myc-ER (Littlewood et al., Nuc. Acids. Res. 23:1686 [1995]) with the PCR amplified human EZH2 devoid of its stop codon. The EZH2.SET mutant DNA was amplified using the primers 5′GGGGTACCATGGGCGGCCGCGAACAAAAGTTGATT 3′ (SEQ ID NO:112) and 5′GGGGAATTCTCATGCCAGCAATAGATGCTTTTT3′ (SEQ ID NO:113) and subsequently sub-cloned into pcDNA3 utilizing the in built KpnI/EcoRI sites. Expression of these constructs was verified by immunoblot analysis of the expressed proteins using either anti-Myc HRP (Roche, Inc) or anti-EZH2 antibodies.
G. RNA interference
21-nucleotide sense and antisense RNA oligonucleotides were chemically synthesized (Dharmacon Research Inc.) and annealed to form duplexes. The siRNA employed in the study were targeted to the region corresponding from 85 to 106 of the reported human EZH2 (NM004456). Control siRNA duplexes targeted luciferase, lamin and AMACR (NM014324). The human transformed prostate cell line RWPE (Webber et al., Carcinogenesis 18:1225 [1997]) and PC3 were plated at 2×105 cells per well in a 12 well plate (for immunoblot analysis, cell counts, and fluorescence activated cell sorting (FACS) analysis) and 1.5×104 cell per well in a 96 well plate (for WST-1 proliferation assays). Twelve hours after plating, the cells were transfected with 60 picomoles of siRNA duplex, sense or antisense oligonucleotides (targeting EZH2) using oligofectamine (Invitrogen). A second identical transfection was performed 24 hours later. Forty-eight hours after the first transfection, the cells were lysed for immunoblot analysis and trypsinized for cell number estimation or FACS analysis. Cell viability was assessed 60 hours after the initial transfection.
H. Cell Proliferation Assays
Cell proliferation was determined with the colorimetric assay of cell viability, based on the cleavage of tetrazolium salt WST-1 by mitochondrial dehydrogenases as per manufacturers instructions (Roche, Inc.). The absorbance of the formazan dye formed, which directly correlates with the number of metabolically active cells in the culture, was measured at 450 nm (Bio-Tek instruments), an hour after the addition of the reagent. Cell counts were estimated by trypsinizing cells and analysis by coulter cell counter.
I. Flow Cytometric Analysis
Trypsinized cells were washed with phosphate buffered saline (PBS) and cell number was determined by using a coulter cell counter. For FACS analysis, the washed cells were fixed in 70% ethanol overnight. Before staining with propidium iodide, the cells were washed again with PBS and analyzed by flow cytometry (Becton Dickinson).
J. Microarray Analysis of EZH2 Transfected Cells
Initial testing of this transient transfection/transcriptome analysis system demonstrated that transient overexpression of TNFR1 (p55), a receptor for tumor necrosis factor, induced similar expression profiles as was observed with incubation of cells with TNF (Kumar-Smith et al., J. Biol. Chem. 24:24 [2001]). Other molecules have been similarly tested with this approach. Cells were transfected with different EZH2 constructs and transfection efficiency was monitored by beta-galactosidase assay and was approximately 30-50%. EZH2.SET mutant expressing samples were compared to EZH2 expressing samples using the SAM analysis package (Tusher et al., PNAS 98:5116 [2001]). Data was pre-processed by multiplication by a normalization factor to adjust the aggregate ratio of medians to one, log base 2 transformed and median centered each array, individually. This pre-processed data was divided into 2 groups for comparison using a two-class, unpaired t-test. Critical values for the analysis include: iterations=5000, (720 at convergence) random Number Seed 1234567, a fold change of 1.5 and a delta cutoff of 0.45205, resulting in a final largest median False Discovery Rate of 0.45% for the 161 genes selected as significant. These 161 genes were supplemented by the values for EZH2 and then analyzed using Cluster implementing average linkage hierarchical clustering of genes. The output was visualized in Treeview. Selected genes identified as being repressed by EZH2 (e.g., EPC and cdc27) were re-sequenced to confirm identity.
The molecular identity of a cell is determined by the genes it expresses (and represses). Embryogenesis and cell differentiation intimately depend upon keeping certain genes “on” and other genes “off”. When the transcriptional “memory” of a cell is perturbed this can lead to severe developmental defects (Jacobs et al., Semin. Cell Dev. Biol. 10:227 [1999]; Francis et al., Nat. Rev. Mol. Cell. Biol. 2:409 [2001]). Lack of differentiation, or anaplasia, is a hallmark of cancer, which results from normal cells “forgetting” their cellular identity. Thus, it is not surprising that dysregulation of the transcriptional maintenance system can lead to malignancy (Francis et al., supra; Jabobs et al., Nature 397:164 [1999]; Beuchle et al., Development 128:993 [2001]).
Studies in Drosophila melanogaster have been instrumental in the understanding of the proteins involved in transcriptional maintenance (Beuchle et al., [2001], supra; Strutt et al., Mol. Cell. Biol. 17:6773 [1997]; Tie et al., Development 128:275 [2001]). Two groups of proteins have been implicated in the maintenance of homeotic gene expression and include polycomb (PcG) and trithorax (trxG) group proteins (Mahmoudi et al., Oncogene 20:3055 [2001]; Lajeunesse et al., Development 122:2189 [1996]). PcG proteins act in large complexes and are thought to repress gene expression, while trxG proteins are operationally defined as antagonists of PcG proteins and thus activate gene expression (Francis et al., Nat. Rev. Mol. Cell. Biol. 2:409 [2001]; Mahmoudi et al., supra). There are at least twenty PcG and trxG proteins in Drosophila, and many have mammalian counterparts. In human malignancies, PcG and trxG proteins have primarily been found to be dysregulated in cells of hematopoietic origin (Yu et al., Nature 378:505 [1995]; Raaphorst et al., Am. J. Pathol., 157:709 [2000]; van Lohuizzen et al., Cell 65:737 [1991]). EZH2 is the human homolog of the Drosophila protein Enhancer of Zeste (E(z)) ((Laible et al., Embo. J. 16:3219 [1997]), for which genetic data defines as a PcG protein with additional trxG properties (LaJeunesse et al., supra). E(z) and EZH2 share homology in four regions including domain I, domain II, a cysteine-rich amino acid stretch, and a C-terminal SET domain (Laible et al., supra). The SET domain is a highly conserved domain found in chromatin-associated regulators of gene expression often modulating cell growth pathways (Jenuwein et al., Cell. Mol. Life Sci. 54:80 [1998]). EZH2 is thought to function in a PcG protein complex made up of EED, YY1 and HDAC2 (Satijn et al., Biochim. Biophys. Acta. 1447:1 [1999]). Disruption of the EZH2 gene in mice causes embryonic lethality suggesting a crucial role in development (O'Carroll et al., Mol. Cell. Biol. 21:4330 [2001]).
In previous studies (See e.g., Example 1), the gene at the top of the “list” of genes significantly up-regulated in metastatic prostate cancer was EZH2, which had a d-score (Tusher et al. PNAS 98:5116 [2001]) of 4.58 and a gene-specific FDR of 0.0012 (also called a “q-value” which is analogous to p-values, but adapted to multiple inference scenarios. FIG. 20a displays the 55 up-regulated genes identified by this approach. FIG. 20b summarizes the gene expression of EZH2 in 74 prostate tissue specimens analyzed on DNA microarrays made up of 10 K elements. The EZH2 transcript was significantly increased in metastatic prostate cancer with respect to clinically localized prostate cancer (Mann-Whitney test, p=0.001) and benign prostate (p=0.0001).
As independent experimental validation of DNA microarray results, RT-PCR was performed on 18 prostate samples and cell lines. As expected, EZH2 mRNA transcript levels were elevated in malignant prostate samples relative to benign (FIG. 20c). To determine whether EZH2 is up-regulated at the protein level in metastatic prostate cancer, tissue extracts were examined by immunoblotting. In the samples examined by immunoblot analysis, EZH2 protein was markedly elevated in metastatic prostate cancer relative to localized prostate cancer or benign prostate (FIG. 20d).
Importantly, EED, a PcG protein that forms a complex with EZH2 (vanLohuizen et al., supra; Sewalt et al., supra), along with an un-related protein, 3-tubulin, did not exhibit similar protein dysregulation. EZH2 protein expression was evaluated on a wide range of prostate tissues (over 700 tissue microarray elements) to determine the intensity and extent of expression in situ (FIG. 21a,b). When highly expressed, EZH2 expression was primarily observed in the nucleus as suggested previously (Raaphorst et al., supra). The staining intensity was increased from benign, prostatic atrophy, prostatic intraepithelial neoplasia (PIN), to clinically localized prostate cancer with median staining intensity of 1.7 (standard error [SE], 0.1; 95% confidence interval [CI], 1.5-1.9), 1.7 (SE, 0.2; 95% CI, 1.3-2.0), 2.3 (SE, 0.2.; 95% CI, 1.9-2.7), and 2.6 (SE, 0.1; 95% CI, 2.4-2.8), respectively (FIG. 24b). The strongest EZH2 protein expression was observed in hormone-refractory metastatic prostate cancer with a median staining intensity of 3.3 (SE, 0.3; 95% CI, 2.7-3.9). There was a statistically significant difference in EZH2 staining intensity between benign prostate tissue and localized prostate cancer (ANOVA post-hoc analysis mean difference 0.9, p<0.0001). Although metastatic prostate cancer had a higher mean expression level than localized prostate cancer, the difference did not reach statistical significance (ANOVA post-hoc analysis mean difference 0.7, p=0.3). These findings suggest that as prostate neoplasia progresses there was a trend towards increased EZH2 protein expression, mimicking that seen by DNA expression array analysis. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that this observation suggests that EZH2 levels may indicate how aggressive an individual's prostate cancer is given that the highest level of expression was observed in hormone-refractory, metastatic prostate cancer. Therefore, to test this hypothesis, the utility of EZH2 protein levels to predict clinical outcome in men treated with surgery for clinically localized prostate cancer was examined.
Two hundred and twenty-five (225) specimens from sixty-four patients (3-4 replicate samples per patient) with clinical follow up were interrogated on a single tissue microarray. These men had a median age of 61 years (range 43-76 years) and a 7.3 ng/ml median pre-operative serum prostate specific antigen (PSA) (range 0.8-21.0 ng/ml). Pathologic examination of their prostatectomy specimens indicated that 77% had organ-confined disease (pT2 stage) and 72% had negative surgical margins. The patient demographics and tumor stages were representative of the over 1500 radical prostatectomy patients. In order to test the utility of EZH2 as a potential tissue biomarker for prostate cancer, the clinical outcome of these 64 cases was examined, taking into account clinical and pathological parameters. Clinical failure was defined as either a 0.2 ng/ml PSA elevation or disease recurrence following prostatectomy (e.g., development of metastatic disease). By Kaplan-Meier analysis (FIG. 21c), EZH2 staining intensity of 3 and greater was significantly associated with clinical failure in 31% (10/32) of patients in contrast to 9% (3/32) of patients with an EZH2 protein levels below 3 (log rank p=0.03). There was no significant correlation between EZH2 levels and Gleason score (<7 versus=7), tumor stage (pT2 versus pT3), or surgical margin status (negative versus positive). There was a significant (p=0.048) albeit weak (Pearson coefficient=0.33) correlation between EZH2 protein levels and proliferation index in situ as assessed by Ki-67 labeling index. Multivariable Cox-Hazards regression analysis revealed that EZH2 protein expression (=3 versus <3) was the best predictor of clinical outcome with a recurrence ratio of 4.6 (95% CI 1.2-17.1, p=0.02), which was significantly better than surgical margin status, maximum tumor dimension, Gleason score, and pre-operative PSA. Thus, monitoring EZH2 protein levels in prostate specimens may provide additional prognostic information not discernible with current clinical and pathology parameters alone.
To shed light into the functional role of EZH2 in prostate cancer progression, EZH2 expression in transformed prostate cells in vitro was disrupted using RNA interference. T. Tuschl and colleagues recently reported that duplexes of 21-nucleotide RNA (siRNAs) mediate RNA interference in cultured mammalian cells in a gene-specific fashion (Elbashir et al., Nature 411:494 [2001]). RNA interference has been used effectively in insect cell lines to “knock-down” the expression of specific proteins, owing to sequence-specific, double stranded-RNA mediated RNA degradation (Hammond et al., Nature 404:293 [2000]). siRNAs are potent mediators of gene silencing, several orders of magnitude more potent than conventional antisense or ribozyme approaches (Macejak et al., Hepatology 31:769 [2000]). Thus, a 21-nucleotide stretch of the EZH2 molecule was targeted using criteria provided by Elbashir et al. (supra), and RNA oligonucleotides were synthesized commercially. After the RNA oligos were annealed to form siRNA duplexes, they were tested on the transformed androgen-responsive prostate cell line RWPE (Webber et al., Carcinogenesis 18:1225 [1997]; Bello et al., Carcinogenesis 18:1215 [1997]) as well as the metastatic prostate cancer cell line PC3. Forty-eight hours after transfection with siRNA duplexes, the levels of endogenous EZH2 protein were quntitated. When EZH2 protein was specifically down-regulated in prostate cell lines, the levels of the un-related control protein, β-tubulin, remained unchanged (FIG. 22a). The sense or anti-sense oligonucleotides comprising the EZH2 duplex, as well as un-related siRNA duplexes, did not affect EZH2 protein levels (FIG. 22a, middle and right panels), verifying the specificity of the siRNA approach in both prostate cell lines.
The phenotype of EZH2 “knock-down” prostate cells was next examined. By phase contrast microscopy, it was observed that siRNA directed against EZH2 markedly inhibited cell number/confluency relative to buffer control. Cell counts taken 48 hrs after transfection with siRNA showed a 62% inhibition of RWPE cell growth mediated by the EZH2 siRNA duplex, which is in contrast to the corresponding sense and anti-sense EZH2 oligonucleotides or control duplexes (targeting luciferase and lamin) which exhibited minimal inhibition (FIG. 22b). The prostate cancer cell line, PC3, demonstrated a similar growth inhibition mediated by EZH2 siRNA, suggesting that the findings are not a peculiarity of the RWPE cell line (FIG. 22b). Using a commercially available cell proliferation reagent WST-1, which measures mitochondrial dehydrogenase activity, a decrease in cell proliferation mediated by the EZH2 siRNA duplex, but not by un-related duplexes, was observed (FIG. 22c). In the time frame considered (48 hrs), RNA interference of EZH2 did not induce apoptosis as assessed by propidium idodide staining of nuclei or PARP cleavage. Consistent with this, the broad-spectrum caspase inhibitor, z-VAD-fmk, failed to attenuate EZH2 siRNA induced inhibition of cell proliferation (FIG. 22c). Thus, activation of the apoptosis pathway does not account for the decreases in cell number observed by RNA interference of EZH2.
Various PcG Group proteins have been suggested to play a role in cell cycle progression (Jacobs et al., Nature 397:164 [1999]; Visser et al., Br. J. Hematol. 112:950 [2001]; Borck et al. Curr. Opin. Genet. Dev. 11:175 [2001]). Flow cytometric analysis of EZH2 siRNA-treated prostate cells demonstrated cell cycle arrest in the G2/M phase (FIG. 22d). Un-related control siRNA duplexes failed to induce a similar cell cycle dysregulation. Few apoptotic cells (sub-G1 cells) were present in any of the experimental samples tested as assessed by flow cytometry (FIG. 22d). The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that these observations suggest that EZH2 plays a role in prostate cell proliferation by mitigating the G2/M transition.
To further understand the functional role of EZH2 in prostate cells, an epitope-tagged version of wild-type EZH2 and a deletion mutant of EZH2 missing the conserved SET domain in the eukaryotic expression vector pcDNA3 were generated (FIG. 23a). An “inducible”-version of EZH2 was also generated by creating a fusion protein with a modified murine estrogen receptor (ER) (FIG. 26a) (Littlewood et al., Nuc. Acid. Res. 23:1686 [1995]; Juin et al., Genes Dev. 13:1367 [1999]). EZH2-ER fusion was expressed in cells (FIG. 26b) and is inactivated, presumably by sequestration/binding to hsp90 and other proteins (Littlewood et al., supra). Upon treatment of cells with 4-hydroxytamoxifen, hsp90 dissociates from the ER fusion and liberates its activity. Expression of the epitope-tagged EZH2 constructs was confirmed by transfection in 293 (FIG. 23b), RWPE and in other mammalian cell lines.
PcG proteins have been proposed to mediate their functions by repression of target genes (Laible et al., supra; Jacobs et al., Semin Cell Dev. Biol. 10:227 [1999]). To begin to test this hypothesis, RWPE prostate cells were transiently transfected with wild-type EZH2 and global gene expression alterations were monitored using DNA microarrays. While RNA from the experimental (transfected) cell line was labeled with one fluorescent dye, the paired reference sample was labeled with a second distinguishable fluorescent dye. By making direct comparisons between “gene”-transfected cell lines and control vector-transfected cell lines the molecular differences between the samples were observed. When EZH2 was over-expressed in RWPE cells or SUM149 breast carcinoma cells, there was a consistent repression of a cohort of genes (FIG. 23c, d). This exclusive repression of genes was unique compared to other molecules tested in this system including c-myc and TNFR1, among others. When compared to vector-transfected cells the only gene that was significantly up-regulated in EZH2-transfected cells was EZH2 itself (FIG. 23c).
EZH2-mediated transcriptional repression was dependent on an intact SET domain (FIG. 23c), as deletion of this domain did not produce a repressive phenotype and in some cases “de-repressed” genes. EZH2 has been shown to interact with histone deacetylase 2 (HDAC2) via the EED protein (van der Vlag et al., Nat. Genet. 23:474 [1999]). In the experiments described above, EZH2-mediated gene silencing was dependent on HDAC activity, as the commonly used HDAC inhibitor, trichostatin A (TSA) completely abrogated the effects of EZH2 (FIG. 23c). Thus, EZH2 function requires both an intact SET domain as well as endogenous HDAC activity.
To identify genes that are significantly repressed by EZH2, wild-type EZH2-transfected cells were compared with EZH2 SET-transfected cells. Using this approach, 163 genes were consistently repressed while no genes were activated at an FDR of 0.0045 (FIG. 23d). Examination of the significant gene list identified the PcG group protein EPC, which is the human homolog of the drosophila protein Enhancer of Polycomb (E(Pc)) as being consistently repressed by EZH2 (FIG. 23c). Of the Drosophila PcG proteins, E(Pc) and E(z) are related in that they both act as suppressors of variegation (Su(var)) (Sinclair et al., Genetics 148:211 [1998]) and are the only PcG proteins to have yeast homologs, emphasizing the evolutionary conservation of this PcG pair. In addition to EPC, a host of other transcriptional regulators/activators were transcriptionally silenced by EZH2 including MDNA, RNF5, RNF15, ZNF42, ZNF262, ZNFN1A1, RBM5, SPIB, and FOXF2, among others (FIG. 23c). MDNA, also known as myeloid cell nuclear differentiation antigen, mediates transcriptional repression by interacting with the transcription factor YY1, which is a PcG homolog of Drosophila Pho and shown to be part of the EZH2/EED complex of proteins (Satijin et al., Mol. Cell. Biol. 21:1360 [2001]).
In addition to transcriptional repression in prostate cells, the results also support a role for EZH2 in regulating cell growth (FIG. 23). Transcriptional repression of cdc27 (two independent Unigene clones) was also observed. Cdc27 is part of the anaphase-promoting complex (APC) which mediates ubiquitination of cyclin B1, resulting in cyclinB/cdk complex degradation (Jorgensen et al., Mol. Cell. Biol. 18:468 [1998]). Another family of proteins that was repressed when EZH2 was targeted was the solute carriers. At least 5 distinct members were shown to be repressed (i.e., SSLC34A2, SLC25A16, SLC25A6, SLC16A2, and SLC4A3).
EXAMPLE 9
Expression of AMACR in Serum and Urine
This example describes the expression of AMACR in serum and urine. AMACR was detected by standard immunoblotting and by protein microarray using a polyclonal rabbit anti-AMACR antibody. The results are shown in FIGS. 24-27. FIG. 24 shows the detection of AMACR protein in PCA cell lines by quantitation of microarray data. DUCAP, DU145, and VCAP are prostate cancer cell lines. RWPE is a benign prostate cell line. PHINX is a human embryonic kidney cell line.
FIG. 25 shows the detection of AMACR protein in serum by quantitation of microarray data. P1-P7 represent serum from patients with prostate cancer. NS2 and NS3 represent serum from patients that do not have PCA. SNS2 and SNS3 represent serum from patients that do not have PCA that has been spiked with AMACR protein. FIG. 26 shows an immunoblot analysis of serum from patients with either negative or positive PSA antigen. FIG. 27 shows an immunoblot analysis of the presence of AMACR in urine samples from patients with bladder cancer (females) or bladder cancer and incidental prostate cancer (males). The results demonstrate that AMACR can be detected in the serum and urine of patients with bladder cancer or bladder cancer and prostate cancer.
EXAMPLE 10
AMACR as a Tumor Antigen
This example describes the presence of an immune response against AMACR in serum. FIG. 28 shows representative data of a humoral response by protein microarray analysis. Tumor antigens including AMACR, PSA, CEA, HSPs were spotted onto nitrocellulose coated slides. The slides were incubated with sera from different patients to detect a humoral response. The microarray was then washed. A Cy5 labeled goat anti-human IgG was used to detect the humoral response. The slide was then scanned using a microarray scanner (Axon). After data normalization, intensity of spots reflects the presence, absence or strength of humoral response to specific tumor antigen. A specific humoral response to AMACR was detected in cancer patients but not in controls. Cancer refers to sera from prostate cancer patients. BPH refers to sera from patients with benign prostate hyperplasia.
FIG. 29 shows immunoblot analysis of the humoral response to AMACR. FIG. 29A shows an SDS-PAGE gel containing recombinant MBP (control protein=M) and recombinant AMACR-MBP (A) that was run and transferred to nitrocellulose paper. Each strip blot was then incubated with human sera. A humoral response to the AMACR was detected using an HRP-conjugated anti-human antibody. Only AMACR and fragments of AMACR were detected in sera from prostate cancer patients and not in controls. FIG. 29B shows a control experiment whereby the humoral response is blocked with recombinant AMACR (quenched) and thus shows the specificity of the response.
This example demonstrates that AMACR functions as a tumor antigen in human serum of prostate cancer patients. A specific immune response was generated to AMACR in the serum of PCA patients, but not in controls.
EXAMPLE 11
Expression of GP73 in Prostate Cancer
This example describes the association of GP73 with prostate cancer.
A. Methods
Microarray analysis, RT-PCR, Western blotting, and immunohistochemistry were performed as described in the above examples.
B. Results
FIG. 30 shows GP73 Transcript levels in prostate cancer. FIG. 30a shows the level of GP73 in individual samples after microarray analysis. The graph shows the values of Cy5 versus Cy3 ratio wherein the prostate cancer tissue sample RNA were labeled with Cy5 fluorescent dye, while the reference sample (pool of benign tissue RNA) sample was labeled with Cy3 fluorescent dye. A total of 76 individual experiments from different prostate tissue are plotted and they are classified as benign, prostate cancer and metastatic cancer types. FIG. 30b shows the result of GP73 transcripts determined by DNA microarray analysis from 76 prostate samples grouped according to sample type and averaged. The experimental samples were labeled with Cy5 fluorescent dye, whereas the reference sample (pool of benign tissue sample) was labeled with Cy3 fluorescent dye. The box plot demonstrates the range of GP73 expression within each group. The middle horizontal bar indicates median values; the upper and lower limits of the boxes, interquartile ranges; and the error bars, 95% confidence intervals. FIG. 30c demonstrates that GP73 transcript levels are elevated in prostate cancer. RT-PCR was used to detect GP73 transcript levels in RNA preparations from prostate tissue extracts. GAPDH served as the loading control.
FIG. 31 shows that GP73 protein is upregulated in prostate cancer. FIG. 31a shows Western blot analysis of GP73 protein in prostate cancer. Total tissue proteins from benign, cancer and metastatic tissues (10 μg) were analyzed using anti-GP73 antiserum. β-Tubulin serves as control for sample loading. FIG. 3 lb shows an immunoblot analysis of the Golgi resident protein Golgin 97. The Golgin 97 protein levels were analyzed in the prostate tissue sample to indicate the level of Golgi structure in normal and cancerous prostate tissue. β-Tubulin serves as control for sample loading.
Tissue microarray analysis of GP73 protein in normal and cancerous prostate tissue was also performed. GP73 protein expression was analyzed by standard biotin-avidin immunohistochemical analysis using a polyclonal mouse antibody to GP73. Protein expression was evaluated on a wide range of prostate tissue using high-density tissue microarrays. High levels of staining were observed in prostate cancer tissue. Some normal epithelial cells did not stain for GP73 in a sub region of prostate cancer tissue.
FIG. 32 shows immunoblot analysis of normal and prostate cancer epithelial cells. The epithelial cells were isolated from normal prostate tissue and cancer tissue to specifically isolate the protein from epithelial cell for GP73 immunoblot analysis. For this purpose, laser capture microdissected samples were used. Actin western serves as control.
EXAMPLE 12
Lethal Markers and Targets
This example describes the identification of lethal markers. The markers serve as potential therapeutic targets. Markers were identified by correlating the number of samples with clinical parameters and gene expression. Specifically, the present study identified markers that have an expression profile similar to EZH2, which serves as a prototypic lethal biomarker of prostate cancer. These genes were identified by a scoring system that takes into account whether localized prostate cancer has recurred or not recurred. In addition, genes that have highly correlated expression with EZH2 were identified that may serve as markers to supplement EZH2.






















Total
16
13
16
6
20





mean
dev
High
bph_count
pca_count
pcau_count
pcar_count
met_count
score
UNIQID
NAME

























−0.024
0.3725
0.7206
0
4
5
6
16
18
5814
NULL ESTs Hs.30237


−0.306
0.1707
0.0351
0
0
3
3
14
17
2506
HN1


−0.348
0.2394
0.1312
0
2
1
4
14
16
5112
CSF2


0.0623
0.1578
0.3779
0
1
2
3
13
15
6053
ASNS


−0.246
0.1689
0.0921
0
2
0
2
15
15
1520
NULL ESTs Hs.16304


−0.212
0.1386
0.0648
0
2
0
2
15
15
8273
PRC1


−0.352
0.1458
−0.06
0
3
7
3
14
14
34
GPAA1


−0.292
0.2538
0.2153
0
0
1
3
10
13
5239
KIAA1691


−0.141
0.1572
0.1729
0
2
5
3
12
13
8562
NULL Human clone 23614


−0.21
0.1083
0.0067
0
4
4
2
15
13
3351
FLJ11715 hypothetical protein


−0.22
0.1846
0.1495
0
5
4
5
13
13
2715
NULL ESTs


−0.638
0.2696
−0.099
1
5
4
3
15
13
9556
FLJ12443 hypothetical protein


−0.142
0.1396
0.1371
0
0
2
2
10
12
1158
TGFBI


−0.124
0.1606
0.1967
0
1
1
3
10
12
5292
NULL ESTs


−0.444
0.2474
0.0504
0
1
2
2
11
12
3689
NUF2R hypothetical protein


−0.205
0.2362
0.2674
0
2
1
2
12
12
1219
ABCC5


−0.09
0.2214
0.3526
0
4
2
4
12
12
1360
MEN1


−0.241
0.1541
0.0673
0
5
3
2
15
12
8476
SARM and HEAT/












Armadillo motif


−0.874
0.3367
−0.201
0
1
4
2
10
11
3747
H2BFB


−0.196
0.254
0.3122
0
2
1
3
10
11
4941
VAV2


−0.166
0.1486
0.1307
0
2
4
2
11
11
8636
NULL ESTs Hs.23268


0.0255
0.1542
0.3338
0
3
3
3
11
11
280
TOP2A


−0.226
0.2536
0.2812
0
4
3
4
11
11
2156
EZH2


−0.031
0.1826
0.3346
0
4
4
2
13
11
1979
NULL ESTs Hs.268921


−0.48
0.2967
0.1131
0
2
0
2
10
10
906
MGC5627 hypothetical protein


−0.243
0.1421
0.0411
0
2
8
2
10
10
3728
NULL ESTs


−0.133
0.1806
0.2279
0
2
2
2
10
10
8759
RAB24


−0.192
0.1782
0.1645
0
3
2
2
11
10
2029
FLJ12876 hypothetical protein


−0.617
0
−0.617
0
3
2
2
10
9
3928
DGKD


0.1079
0.1132
0.3343
0
3
2
2
10
9
5372
ODF2


−0.288
0.1221
−0.043
0
4
3
3
10
9
7193
KIAA0602


−0.167
0.2278
0.2883
0
4
2
2
11
9
8535
EHM2


−0.95
0.3504
−0.249
0
4
2
2
11
9
9824
SLC19A1


−0.314
0.187
0.06
1
4
2
2
11
9
9447
LIG1


0.1366
0.1883
0.5132
1
4
3
2
10
8
327
NULL ESTs


−0.586
0.2952
0.0044
0
5
2
2
11
8
1269
DGKZ





mean: mean expression in BPH


Dev: standard deviation in BPH


High: 2 SD's above the mean (threshold)


Bph: # of BPH samples > thresh


PCA: # of PCA samples > thresh (>1 yr no recur)


Pcau: # of PCA samples > thresh (<1 yr followup)


Pcar: # of PCA samples > thresh (recur)


Met: # of metastatic samples > thresh


Score: = met + pcar − pca


Total: # of samples in category






Exemplary lethal markers identified using the above methods include ABCC5 (MDR5). This multi-drug resistance gene actively pumps cyclic nucleotides and other small molecules out of cells. An unrelated study found that this enzyme is potently Inhibited by phosphodiesterase inhibitors, including sildenafil (viagra). The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not required to practice the present invention. Nonetheless, it is contemplated that sildenafil may be useful in the treatment of aggressive PCA.
Another lethal marker identified is asparagine synthetase (ASNS). Current therapeutics for the inhibition of ASNS include asparaginase, an enzyme that destroys asparagine in the body. It has been shown that cancers expressing the synthetase are resistant. Analogs are being developed to inhibit the synthetase.
Top2A (topoisomerase 2) and the Vav2 Oncogene were also identified using the methods of the present invention. Vav2 is required for cell spreading, but is dependent on src. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not required to practice the present invention. Nonetheless, it is contemplated src inhibitors can stop vav2 mediated cell spreading.
This example describes the identification of cancer markers overexpressed in prostate cancers. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that therapeutic compounds that inhibit these lethal markers are useful in the treatment of prostate cancer.
EXAMPLE 13
Characterization of Annexin Expression in Prostate Cancer
This Example describes the expression of Annexins in prostate cancer.
A. Materials and Methods
Prostate Sample Collection
Prostate tissues were taken from the radical prostatectomy series and the rapid autopsy program available through the University of Michigan Prostate Cancer Specialized Program of Research Excellence (S.P.O.R.E.) Tissue Core. This program is approved by Institutional Review Board at the University of Michigan.
Hormone naïve, clinically localized PCA samples used for this study were taken from a cohort of men who underwent radical retropubic prostatectomy as a monotherapy (i.e., no hormonal or radiation therapy) for clinically localized PCA between the years 1994 and 1998. Processing of the prostatic tissues started within 20 minutes after surgical resection. The prostates were partially sampled and approximately 50% of the tissue was used for research. This protocol has been evaluated in a formal study to assure that partial sampling does not impair accurate staging and evaluation of the surgical margins (Hollenbeck et al., J. Urol. 164:1583 [2000]). The snap frozen samples used for cDNA expression array analysis were all evaluated by one of the study pathologists. All samples were grossly trimmed to ensure greater than 95% of the sample represented the desired lesion.
Hormone refractory PCA samples were collected from the rapid autopsy program (Rubin et al., [2000], supra). Snap frozen samples were used for cDNA expression array analysis. Mirrored samples from the same lesion were placed in 10% buffered formalin. The fixed samples are embedded in paraffin. As with the prostatectomy samples, the study pathologist reviewed the glass slides, circled areas of viable prostate cancer, avoiding areas of necrosis, and used these slides as a template for tissue microarray construction. In this study, twenty (20) hormone refractory metastatic PCAs were extracted from 15 rapid autopsy cases performed from 1997 to 2000. The patients' ages ranged from 53 to 84 and time from diagnosis to death ranged from 21 to 193 months. All 15 patients died with widely metastatic PCA after extensive treatment, which included antiandrogens and chemotherapy.
Prostatectomy samples were evaluated for the presence or absence of surgical margin involvement by tumor (surgical margin status), the presence of extraprostatic extension, and seminal vesicle invasion. Tumors were staged using the TNM system, which includes extraprostatic extension and seminal vesicle invasion but does not take into account surgical margin status (Bostwick et al., Semin. Urol. Oncol. 17:222 [1999]). Tumors were graded using the Gleason grading system (Gleason, [1966], supra).
Immunohistochemistry
After paraffin removal and hydration, the tissue microarray slides were immersed in 10 mM citrate buffer placed in a pressure cooker chamber and microwaved for 10 minutes for optimal antigen retrieval. Immunostaining was performed using a Dako autostainer (DAKO, Carpinteria, Calif.). The primary antibody was incubated for 45 minutes at room temperature and a secondary biotin-labeled antibody for 30 minutes. Streptavidin-LSA amplification method (DAKO K0679) was carried out for 30 minutes followed by peroxidase/diaminobenzidine substrate/Chromagen. The slides were counterstained with hematoxylin. Polyclonal antibodies directed against the N-terminus of annexin 1 (dilution 1:50), annexin 2 (dilution 1:100), annexin 4 (dilution 1:100), annexin 7 (dilution 1:500), and annexin 11 (dilution 1:100) were obtained from a signal source (Santa Cruz Biotechnology, Santa Cruz, Calif.). Protein expression as determined by two pathologists immunohistochemistry was scored as negative (score=1), weak (score 2), moderate (3) or strong (4), using the system described above.
Tissue Microarray Construction, Digital Image Capture, and Analysis
Tissue microarrays were constructed as previously described to evaluate protein expression in a wide range of samples ranging from benign prostate tissue taken from the prostatectomy samples to hormone refractory PCA. Three tissue microarrays were used for this study consisting of benign prostate, localized PCAs, and hormone refractory PCA. The tissue microarrays were assembled using the manual tissue arrayer (Beecher Instruments, Silver Spring, Md.) as previously described (Kononen et al., [1998], supra; Pyrrone et al., [2000], supra). Tissue cores from the circled areas of interest were targeted for transfer to the recipient array blocks. The 0.6 mm diameter tissue microarray cores were each spaced at 0.8 mm from core-center to core-center. Tissue microarray images were acquired using the BLISS Imaging System (Bacus Lab, Lombard, Ill.).
Statistical Analyses
To investigate the statistical significance associated with the differential expression of annexins across 4 independent gene expression studies, standard methods (Hedges et al., Statistical Methods for Meta-analysis meta-analysis. Orlando, Academic Press 1985, pp xxii, 369) were used to combine the results. For each of the studies, a t-statistic was computed (with the two groups being benign tissue compared against localized prostate cancer) and the associated p-values were transformed using a negative logarithmic transformation. These numbers were then doubled and added together to arrive at a summary measure of differential gene expression across the three studies. To assess the statistical significance associated with this summary measure, a permutation-based approach was adopted (Hedges et al., supra). Namely, the tissue types were permutated within studies, and the summary measure was computed for the permutated data. A p-value was computed using the permutation distribution of the summary measure. The issue then arises of whether or not the t-statistics from the three studies are comparable.
Annexin protein expression was statistically evaluated using the mean score results from each tissue microarray sample for each prostate tissue type (i.e., benign, localized PCA, and hormone refractory PCA). To determine differences between all pairs (e.g., localized prostate cancer versus benign), an ANOVA with a post-hoc analysis was performed using the Scheffé method (Scheffae et al., supra). The mean expression scores for all examined cases were presented in a graphical format by using error-bars with 95% confidence intervals.
B. Results
Expression array analysis revealed a significant dysregulation of annexin family members with PCA progression. The cDNA expression of annexins 1, 2, 4, 7 and 11 were significantly decreased in the hormone refractory PCA samples as compared to localized hormone sensitive PCA samples with 2.2, 1.5, 1.3, 1.4 and 1.8 fold decrease, respectively (all p-values<0.01) (Table 8 and FIG. 33). Annexins 1 and 4 showed significant decreases of mRNA expression in localized PCA samples as compared to the benign samples. There were no significant differences between localized hormone naive PCA and the benign samples for annexin 2, 7, and 11. No cDNA dysregulation between the tested prostate samples and annexins 8 and 13 was observed. Annexin 6 demonstrated a slight decrease in cDNA expression between localized PCA and benign samples, which was not statistically significant (Table 8).
In order to cross validate the cDNA expression results for these annexin family members, a meta-analysis of gene expression was performed. Annexin family members cDNA expression results were evaluated using a series of data sets (Welsh et al., Cancer Res. 61:5974 [2001]; Luo et al., Cancer Res. 61:4683 [2001]; Magee et al., Cancer Res. 61:5692 [2001]). The analysis evaluated annexins for each of the individual studies as well as performing a summary statistic, taking into account the significance of the gene expression across the 4 studies. The meta-analysis compared differences between clinically localized PCA and benign prostate tissue as not all of the studies had hormone refractory metastatic PCA. The meta-analysis (Table 9 and FIG. 34) demonstrated that annexins 1, 2, 4, and 6 were significantly down regulated across independent studies. Annexin 6 was down regulated to a significant level in 4 of 4 studies. Annexin 1 demonstrated down regulation in 3 of 4 studies. Annexins 2 and 4 were down regulated in 2 studies and overall considered to be significantly under expressed by the meta-analysis. Annexin 7 was not found to be significantly under expressed in any of the 4 studies at the transcript level.
Immunohistochemistry was performed to confirm these results at the protein level (Table 10). By immunohistochemistry, a significant decrease in protein expression for annexins 1, 2, 4, 7 and 11 in hormone refractory PCA samples as compared to localized PCA samples was identified with 2.5 (3.8 vs. 1.5 median expression), 2.4 (4 vs. 1.7 median expression), 3.6 (4 vs. 1.1 median expression) and 3.3 (4 vs. 1.2 median expression) fold decreases, respectively (Kruskal Wallis test, all p-values p<0.05). No statistically significant differences were seen between benign and localized PCA samples in any of the annexins tested.







TABLE 8







Gene Expression of Select Annexins.














Benign
BPH1
Loc-PCA2
Met-PCA3
Ratio
p

















Annexin
Count
Median
Count
Median
Count
Median
Count
Median
PCA/Met
Value*




















1
5
1.56
16
1.35
16
0.69
20
0.31
2.23
<0.001


2
5
0.79
16
0.69
16
0.74
20
0.49
1.51
0.009


4
5
0.91
16
0.97
16
0.9
20
0.69
1.30
0.001


6
5
1.2
16
1.29
16
1.05
20
1.15
0.91
0.377


7
5
0.8
16
0.88
16
0.88
20
0.62
1.42
<0.001


8
5
1.14
16
1.06
16
0.99
20
1.19
0.83
0.156


11
5
0.99
16
0.76
16
0.94
20
0.52
1.81
<0.001


13
5
1.08
16
1.35
16
1.03
20
0.94
1.10
0.393





*Kruskal Wallis Test.


1BPH, benign prostatic hyperplasia.


2Loc-PCA, localized prostate cancer.


3Met-PCA, metastatic hormone refractory prostatic cancer. Ratio PCA/Met, ratio of expression of localized PCA over hormone refractory PCA.













TABLE 9







Meta-Analysis of cDNA Prostate Gene Expression Studies for Annexin


Family Members













Present



Summary


Annexin
study
Welsh et al.
Luo et al.
Magee et al.
p-Value















6
0.024
0.0001
0.0001
0.026
0.0001


1
0.0001
0.031
0.0007
0.23
0.0001


2
NA
0.0001
NA
0.002
0.0001


11
NA
0.010
NA
0.6
0.17


7
0.25
0.48
0.38
0.088
0.20


4
0.33
0.023
0.0093
0.58
0.011


13
0.177
NA
1.00
NA
0.48


8
0.79
NA
0.104
NA
0.29
















TABLE 10







Tissue Microarray Protein Expression for Annexins by Tissue Type












Benign
Loc-PCA2
Met-PCA3
















Annexin
Count
Median
Count
Median
Count
Median
PCA/MET
p-value*


















1
37
2.59
360
2.45
162
1.46
1.68
<0.001


2
57
3.95
82
3.62
214
1.47
2.46
<0.001


4
23
3.65
357
3.96
141
1.57
2.52
<0.001


7
26
3.77
350
3.97
126
1.32
3.01
<0.001


11
23
4.00
360
3.99
163
1.30
3.01
<0.001





*Kruskal Wallis Test.


1 BPH, benign prostatic hyperplasia.


2Loc-PCA, localized prostate cancer.


3Met-PCA, metastatic hormone refractory prostatic cancer.






EXAMPLE 14
Association of CtBP with Prostate Cancer
This example describes the expression of C-terminal binding proteins 1 and 2 (CtBP 1 and CtBP2) in prostate cancer. Microarray analysis, Western Blots, immunohistochemistry, and statistical analysis were performed as described in the above examples.
The CtBP transcript was found to be up-regulated in metastatic prostate cancer (FIG. 38). Tissue extracts were used to validate this finding at the protein level using an antibody that recognizes CtBP1 and CtBP2 (Sewalt et al., Mol. Cell. Biol. 19:777 [1999]. The results are shown in FIG. 35. FIG. 35 shows the Expression of CtBP proteins in PCA specimens. Extracts from selected prostate specimens were assessed for expression of CtBP and PcG proteins by immunoblot analysis. Protein level was equalized in each extract before loading and blots were stained with Ponceau S to confirm equal loading. β-tubulin was used as a control protein.
Both CtBPs were over-expressed in metastatic prostate cancer relative to localized prostate cancer and benign tissue. EZH2 protein was also elevated in metastatic prostate cancer relative to localized prostate cancer or benign prostate (FIG. 35). EED, a PcG protein that forms a complex with EZH2, along with an un-related protein, β-tubulin, did not exhibit similar protein dysregulation. Thus, both transcriptional repressors (CtBP and EZH2) are mis-expressed in metastatic prostate cancer.
To determine in situ expression of CtBP, immunohistochemistry of prostate tissue sections were performed using prostate tissue microarrays. Benign prostatic epithelia exhibited exclusively nuclear staining consistent with CtBP's role as a transcriptional repressor. Both clinically localized and metastatic prostate cancer exhibited nuclear staining as well. Most of the metastatic prostate cancer cases and a fraction of the localized prostate cancer cases exhibited distinct cytoplasmic staining of CtBP.
FIG. 36 shows tissue microarray analysis of CtBP in prostate cancer that suggests mis-localization during prostate cancer progression. The mean CtBP protein expression for the indicated prostate tissues and sub-cellular compartment is summarized using error bars with 95% confidence intervals. FIG. 37 shows the sub-cellular fractionation of LNCaP cells. The results show an increased level of CtBP 1 in the cytoplasm relative to the nucleus. CtBP2 is weakly expressed in the cell lines and is not easily apparent. β-tubulin, which is not expressed in the nucleus, is provided as a control. FIG. 38 shows a Kaplan-Meier Analysis of prostate cancer tissue microarray data. The results demonstrate that the presence of cytoplasmic CtBP may be associated with a poorer clinical outcome. The median follow up time for all patients was 1 year (range 2 month to 6.5 years). Over this follow up time, 38% of the patients developed a recurrence or PSA elevation greater than 0.2 ng/ml. Prostate tumors from 97 patients demonstrated near uniform nuclear protein expression for CTBP. Cytoplasmic expression was variable with 85 of 97 cases (88%) demonstrating weak cytoplasmic staining and 12 (12%) with moderate to strong CTBP expression. There was a significant association with increased CTBP cytoplasmic staining intensity and PSA recurrence or presence of recurrent disease following prostatectomy with a relative risk of 1.7 (Cox regression analysis p=0.034). The data presented demonstrates a Kaplan-Meier Analysis of outcome stratified by negative/weak cytoplasmic CTBP staining and moderate/strong staining. CTBP cytoplasmic expression predicted recurrence even when Gleason score was taken into account in a multivariable model, suggesting that CTBP is a prognostic predictor of poor outcome [Gleason relative risk 1.4 (p=0.005) and cCTBP rr 1.6 (p=0.042)].
CtBP has been shown to bind nitric oxide synthase (NOS), which is thought to shift the localization of CtBP from the nuclear compartment to the cytoplasmic compartment (Riefler et al., J. Biol. Chem. 276:48262 [2001]). Weigert and colleagues have proposed a cytoplasmic role for CtBP in the induction of Golgi membrane fission (Weigart et al., Nature 402:429 [1999]). To further support the preliminary immunohistochemical findings, LNCaP (metastatic) prostate cancer cells were fractionated and it was found that CtBP levels were higher in the cytosol relative to the nucleus (FIG. 38).
EXAMPLE 15
Methods of Characterizing Cancer Markers
This example describes exemplary methods for the characterization of new cancer markers of the present invention. These methods, in combination with the methods described in the above examples, are used to characterized new cancer markers and identify new diagnostic and therapeutic targets.
A. Determination of Quantitative mRNA Transcript Levels of Cancer Markers in Prostate Cancer Specimens
In some embodiments, markers revealed to be over or under expressed in cancer microarrays (See e.g., Example 1 for a description of microarrays) are quantitated using real-time PCR (Wurmbach et al., J. Biol. Chem. 276:47195 [2001]).
In preferred embodiments, cDNA from over 100 prostate samples for archived cDNA samples and associated clinical data are available (See Example 1). The level of expression in the microarray is compared to those obtained by real-time PCR. To identify genes with dysregulation of expression, real-time PCR analysis of cDNA generated from laser-capture microdissected prostate cancer epithelia and benign epithelia is performed.
B. Detection of Mis-localized Transcripts
In some embodiments, in order to determine if a cancer marker normally present in the nucleus of a cell (e.g., a transcriptional repressor) is mis-localized to the cytoplasm (or other mis-locations) in cancer, the expression of the marker is examined in tissue extracts from preferably at least 20 benign prostate samples, 20 prostate cancer specimens, and 20 metastatic prostate specimens. Expression of the marker in benign prostate cell lines (RWPE), primary prostatic epithelial cells (Clonetics, Inc.) and a panel of prostate cancer cells including LNCaP, DU145, PC3, DUCaP, and VCaP cells is also examined. Once overall expression of prostate cell lines and tissues is established, the cellular localization of the marker is determined by 2 methods. In the first method, the cell and tissue extracts are fractionated into a nuclear fraction and a cytosolic fraction (NE-PER, Pierce-Endogen; Orth et al., J. Biol. Chem. 271:16443 [1996]). Quantitated protein is then analyzed by immunoblotting. Relative levels of cytosolic and nuclear cancer marker are determined by densitometry. To verify clean fractionation, antibodies to β-tubulin and PCNA (or lamin A) are used to assess cytosolic and nuclear fractions, respectively.
In the second method, cells are immunostained with antibodies to the cancer marker followed by detection using anti-rabbit FITC secondary antibody. Confocal microscopy (U of M Anatomy and Cell Biology Core Facility) is used to examine in situ localization of the cancer markers.
In some embodiments, mis-localization is further investigated by sequencing the gene in cells containing the mis-located transcript (e.g., metastatic cases) for mutations.
C. Correlation of Cancer Markers with Clinical Outcome
In some preferred embodiments, the association of expression or mis-localization of a cancer marker with clinical outcome is investigated. The ratio of total cancer marker to β-tubulin by immunoblot analysis of prostate cancer tissue extracts is first determined and associated with clinical outcome parameters. For markers suspected of being mis-localized in cancer (e.g., CtBP), the ratio of cytoplasmic marker to nuclear marker is next determined by immunoblot analysis of prostate cancer tissue extracts and associated with clinical outcome parameters. For example, it is contemplated that a high cytoplasmic/nuclear cancer marker ratio may portend a poor clinical outcome. In some embodiments (e.g., where a cancer marker is suspected of being mis-localized), immunohistochemistry of prostate cancer tissue microarrays is used to determine whether the presence of cytoplasmic marker correlates with poor clinical outcome. Tissue microarrays are prepared and performed as described in the above examples.
Briefly, high-density tissue microarrays (TMA) are constructed as previously described (Pyrrone et al, supra; Kononen et al., supra). Immunostaining intensity is scored by a genitourinary pathologist as absent, weak, moderate, or strong (or alternatively analyzed separately as for cytoplasmic and nuclear staining). Scoring is performed using a telepathology system in a blinded fashion without knowledge of overall Gleason score (e.g., tumor grade), tumor size, or clinical outcome (Pyrrone et al., supra). Tumor samples are derived from patients with clinically localized, advanced hormone refractory prostate cancer and naïve metastatic PCA. Cases of clinically localized prostate cancer are identified from the University of Michigan Prostate S.P.O.R.E. Tumor Bank. All patients were operated on between 1993 and 1998 for clinically localized prostate cancer as determined by preoperative PSA, digital-rectal examination, and prostate needle biopsy. All tissues used are collected with institutional review board approval. The advanced prostate tumors are collected from a series of 23 rapid autopsies performed at the University of Michigan on men who died of hormone refractory prostate cancer. The clinical and pathologic findings of these cases have been reported (Rubin et al., [2000], supra).
Statistical analysis of the array data is used to correlate the cancer marker protein measurements on the TMA with clinical outcomes, such as time to PSA recurrence and survival time. This analysis involves survival analysis methods for correlating the measurements with these censored response times. Kaplan-Meier curves are plotted for descriptive purposes. Univariate analyses is performed using the Cox model associating the biomarker with the survival time. In addition, multivariate Cox regression analysis is performed to test whether the biomarker adds any prognostic information over and above that available from known prognostic markers (i.e., Gleason score, tumor stage, margin status, PSA level before surgery).
D. RNA Interference
In some embodiments, RNA interference of cancer markers is used to investigate the role of the cancer marker in cell culture and well as for application as a therapeutic cancer treatment (See e.g., Example 8 for an example of RNA interference). 21-nucleotide RNAs (siACE-RNAi) are synthesized through a commercial vendor (Dharmacon Research, Inc.). RNA interference has been used in mammalian cells (Elbashir et al., Nature 411:494 [2001]). Several siRNA duplexes and controls are designed for each marker. The design of the siRNA duplexes uses criteria provided by Elbashir et al. (Elbashir et al., supra) and Dharmacon Research which include: starting approximately 75 bases downstream of the start codon, locating an adenine-adenine dimer, maintaining G/C content around 50%, and performing a BLAST-search against EST databases to ensure that only one gene is targeted. Multiple (e.g., two) siRNA duplexes are designed for each molecule of interest since whether the siRNA duplex is functional is a relatively empirical process. In addition, it is contemplated that using two siRNA duplexes may provide a combined “knock-down” effect. As a control, a “scrambled” siRNA, in which the order of nucleotides is randomized, is designed for each molecule of interest. Oligonucleotides are purchased deprotected and desalted. Upon arrival, the oligonucleotides are annealed to form a duplex using the manufacturer's provided protocol.
To test the efficacy of each siRNA duplex, prostate cell lines (RWPE, DU145, LnCAP, and PC3) are transfected with the OLIGOFECTAMINE reagent as described (Elbashir et al., supra). The cells are assayed for gene silencing 48 hrs post-transfection by immunoblotting with respective antibodies. A number of controls are included: buffer controls, sense siRNA oligo alone, anti-sense siRNA oligo alone, scrambled siRNA duplex, and siRNA duplexes directed against unrelated proteins. If significant silencing is not appreciated after single transfection, sequential transfection is performed and inhibition is monitored at later time points (i.e., 8 days later) as suggested by others (Breiling et al., Nature. 412: 51 [2001]). This may be necessary with proteins that have a long half-life.
In addition to the transient expression of siRNAs, a method for stable expression of siRNAs in mammalian cells is used (Brummelkamp et al., Science 296:550 [2002]). Prostate cancer cell lines are generated that express siRNA targeting cancer markers using the pSUPER system. Scrambled siRNA is used as a control. The cell lines facilitate downstream characterization of cancer markers that may be cumbersome using duplexes transiently. If inhibition of a specific cancer marker is found to be toxic to cells, the pSUPER cassette containing siRNA to the marker is cloned into an inducible vector system (e.g., Tet on/off).
E. Generation of Mutants
To study the function of cancer markers of the present invention, mutants of cancer markers are generated in eukaryotic expression vectors. myc-epitope tagged versions of cancer marker mutants are generated in both pcDNA3 and pcDNA3-ER (a modified estrogen receptor ligand binding domain). In the case of the ER constructs, the vectors produce an in-frame fusion protein with modified ER, thus generating a post-transcriptionally inducible vector (Littlewood et al., Nucleic Acids Res. 23: 686 [1995]). The ER-ligand domain is mutated and fails to bind endogenous estrogen, yet can be activated by 4-hydroxytamoxifen (Littlewood et al., supra). The ER-fusion proteins are inactivated in the absence of ligand presumably due to binding of proteins such as hsp90. In the presence of exogenously added 4-hydroxytamoxifen, ER-fusions become liberated. By using an inducible vector system, cell lines expressing a “toxic” or growth inhibitory version of a cancer marker can still be isolated.
Various N-terminal and C-terminal deletion mutants are generated that encompass function domains of the cancer marker (e.g., the PXDLS, dehydrogenase, and PDZ binding domains of CtBP; Chinnadurai, Mol Cell. 9: 213 [2002]). It is contemplated that some of the mutant versions of the cancer markers of the present invention act as dominant negative inhibitors of endogenous cancer marker function. Expression of epitope-tagged cancer markers and mutants is assessed by transient transfection of human embryonic kidney cells (using FUGENE) and subsequent Western blotting.
F. Establishing Stable Cell Lines Expressing Cancer Markers And Mutants
In some embodiments, cell lines stably expressing cancer markers of the present invention are generated for use in downstream analysis. FUGENE is used to transiently transfect prostate cell lines (RWPE, DU145, LnCAP, and PC3) with cancer markers and fusions or mutants using the above mentioned vectors and appropriate G418 selection. Prostate cell lines with varied expression levels of endogenous cancer marker protein are used. Both individual clones and pooled populations are derived and expression of cancer markers and mutants assessed by immunoblotting for the epitope tag. By also using an inducible system, clones expressing toxic versions of cancer markers or mutants can be isolated.
G. Cell Proliferation and Apoptosis Studies
In some embodiments, the role of cancer marker expression in prostate cell proliferation is investigated using a multi-faceted approach that includes 1. RNA interference, 2. transient transfection of cancer markers and potential dominant negative mutants, and 3. comparing stable transfectants of cancer markers and mutants. The following predictions are tested using these methods: 1. whether inhibition of cancer markers will block cell growth and 2. whether overexpression of cancer markers will enhance cell proliferation.
Cell proliferation is assessed by cell counting (Coulter counter) over a time course in culture by using the WST-1 reagent (Roche, Inc.), which is a non-radioactive alternative to [3H]-thymidine incorporation and analogous to the MTT assay. The rate of incorporation of the DNA labeling dye bromodeoxyuridine (BrdU) will also be measured as described previously (Jacobs et al., Nature. 397:164 [1999]). Potential cell cycle arrest induced by siRNA or dominant negative inhibitors of is determined by conventional flow cytometric methods. By using stable cell lines that “activate” cancer markers and mutants in a 4-hydroxytamoxifen-dependent fashion, cell proliferation and cell cycle alterations are monitored in a highly controlled in vitro system. To confirm that overexpression or inhibition of cancer markers does not activate the apoptosis pathway, several assays are used including propidium iodide staining of nuclei, TUNEL assay and caspase activation.
If a cancer marker is found to be a regulator of cell proliferation in prostate cells, studies are designed to address how components of cell cycle machinery are modulated by the cancer marker. Thus, in order to study cancer marker mediated effects on the cell cycle machinery of prostate cells, cancer marker functions are modulated with the above mentioned tools (i.e., siRNA, dominant negative inhibition, etc.) and the expression levels (transcript and protein) of cyclins (cyclin D1,E,A), cyclins-dependent kinases (cdk2, cdk4, cdk6) and cyclin-dependent kinase inhibitors (p21CIP1, p27KIP1, p45SKP2, p16INK4) are monitored.
H. Cell Adhesion and Invasion Assays
If a cancer marker is suspected of altering cell adhesion (e.g., the transcriptional repression of an epithelial gene program such as E-cadherin), the methods described above are used to investigate whether over-expression of the cancer marker causes increased or decreased cell adhesion. Adhesion to extracellular matrix components, human bone marrow endothelium (HBME) as well as to human umbilical vein endothelial cells (HUVEC) is tested. Cancer markers are further tested for their ability to modulate invasion of PCA.
Known methods are used in these studies (Cooper et al., Clin. Cancer Res. 6:4839 [2000]). Briefly, snap-apart 96-well tissue culture plates are coated with crude bone and kidney matrices. Plates are incubated overnight at room temperature under sterile conditions and stored at 4° C. until needed. Assay plates are also coated with extracellular matrix components (e.g., human collagen I, human fibronectin, mouse laminin I) and human transferrin at various concentrations according to the manufacturer's instruction (Collaborative Biomedical Products, Bedford, Mass.). Endothelial cells (HBME or HUVEC) are seeded onto bone matrices or plastic substrata at a concentration of 900 cells/μl and grown to confluence. Tumor cells are removed from the flask by a 15-20 minute treatment with 0.5 mM EDTA in Hank's balanced salt solution. Once the EDTA solution is removed, the cells are resuspended in adhesion medium (e.g., minimum essential medium (MEM) with 1% bovine serum albumin (BSA) supplemented with 10 uCi 51 Cr sodium salt (NEN, Boston, Mass.)) for 1 hour at 37° C. Cells are then washed three times in isotope free media and 1×105 radio-labeled tumor cells are resuspended in adhesion media and layered upon a confluent layer of endothelial cells for 30 min at 37° C. In addition, radiolabeled tumor cells are applied to crude bone matrices. Again, plates are washed three times in phosphate buffered saline and adhesion is determined by counting individual wells on a gamma counter. Cell adhesion is reported relative to the adhesion of controls (PC-3 cells on plastic), which are set to 100.
Cell invasion assays are performed using a classic Boyden chamber assay. Both strategies to inhibit and overexpress cancer markers are evaluated. Previous reports have correlated increased cell migration in a Boyden Chamber system with increased invasive properties in vivo (Klemke et al., J. Cell Biol. 140:61 [1998]). Commercially available 24-well invasion chambers are used (e.g., BD biosciences, Chemicon International).
I. Transcriptional Suppression in Prostate Cancer Cells
In some embodiments, the effect of cancer markers on gene silencing in prostate cells is assessed. Gene silencing is assayed in several ways. First, gene expression alterations induced by transient transfection of cancer markers and mutants in prostate cell lines (RWPE, DU145, LnCAP, and PC3) is assayed using FUGENE. Twelve to 48 hours after transfection, cells are harvested and a portion is processed to confirm expression of the transfectants by immunoblotting. Using vector-transfected cells as a reference sample, total RNA from transfected cells is then assessed on 20K cDNA microarrays.
In addition to transient transfections, stable cell lines overexpressing cancer markers and cancer marker mutants are generated. Patterns of gene expression from cancer marker and cancer marker mutant expressing cell lines are compared to vector-matched controls in order to identify a gene or group genes that is repressed by a given cancer marker. The present invention is not limited to a particular mechanism. Indeed, and understanding of the mechanism is not necessary to practice the present invention. Nonetheless, it is contemplated that genes identified as repressed by a given cancer marker will be increased (de-repressed) upon knock-down of the cancer marker (e.g., by siRNA inhibition).
EXAMPLE 16
AMACR as a Urine Biomarker for Non-Invasive Detection of Prostate Cancer
This example describes the investigation of AMACR as a diagnostic marker in biofluids.
A. Experimental Methods
Subjects and Samples
This study was approved by the Institutional Review Board (IRB) of the University of Michigan Medical School. At the time of diagnosis, serum (n=22), plasma (n=11) and urine (n=110) samples from biopsy-proven clinically localized prostate cancer patients were collected with written informed patient consent. The biofluids were stored in the University of Michigan Prostate S.P.O.R.E Tissue/Serum Bank. The average age of the prostate cancer patients in this study was 58.06±0.63. Clinical and pathology data from patients with biopsy-proven clinically localized prostate cancer used in this study is provided in FIG. 39 and the samples were obtained prior to prostatectomy at varying times after biopsy. As controls, urine samples from 116 control male subjects (average age 57.85±0.1) with no known history of prostate cancer were collected in the University of Michigan Clinical Pathology laboratories.
The urine samples were stored at 4° C. and concentrated within two days using a Biomax Ultrafree concentrator (5000 MW cutoff, Millipore Corporation, Bedford, Mass.) at 4° C. Multiple freeze-thaws of un-concentrated urine was avoided as a decrease in AMACR immunoreactivity of urine in these cases was observed. Protein content in each urine sample was estimated using Bradford reagent as per manufacturers instructions (Bio-Rad laboratories, Hercules, Calif.). The concentrated urine samples were frozen at −20° C. until use.
Prostatic fluids (n=13) were obtained ex vivo from resected prostates from prostate cancer patients in accordance with the IRB of Brigham and Women's Hospital. Within minutes of prostate removal, the gland was gently massaged ex vivo and the excretions collected from the prostatic urethra by aspiration using a 200 μl pipette. Care was taken not to damage the urethral lining or prostate tissue. The specimen (between 15 and 100 μl) was then snap-frozen in liquid nitrogen and stored at −20° C.
Antibody Production
Polyhistidine-tagged AMACR was purified from Escherichia coli containing HIS-AMACR plasmid in pET 28a(+) vector in a denatured state by using standard nickel affinity chromatography as per the manufacturer's instructions (Qiagen, Chatsworth, Calif.). The denatured protein was confirmed for purity by silver stain and antibodies were custom produced in rabbits (Proteintech Group Inc, Chicago, Ill.). The antiserum was obtained after four boosters, characterized by ELISA, and used for immunoblot analyses in this study.
Immunoblot Analysis
Serum, plasma, and prostatic secretions (each 1:10 diluted) or urine (20 μg total protein) were electrophoresed on a 10% pre-cast Bis-Tris gel (Invitrogen, Carlsbad, Calif.). The electrophoresis was carried out until the 39 kDa alcohol dehydrogenase (Seablue marker, Invitrogen, Carlsbad, Calif.) reached the end of the gel. The gel was then transferred onto nitrocellulose (in case of serum, plasma and prostatic fluid samples) or PVDF (urine samples) membranes using semi-dry transfer method (Bio-Rad, Hercules, Calif.). The blots were blocked in TBS (Bio-Rad, Hercules, Calif.) containing 5% non-fat milk, 5% normal goat serum (Sigma, St Louis, Mo.) and 0.1% Tween-20 (Sigma, St Louis, Mo.). The blots were probed with anti-AMACR antibodies at a dilution of 1:10,000. To test the specificity of the immunoreactivity, anti-AMACR antisera was quenched with either recombinant AMACR-MBP (Fusion protein of AMACR and Maltose Binding Protein) or MBP (New England BioLabs, Inc., Beverly, Mass.) at a final concentration of 10 g/ml and used as described above. Blots were washed for 30 minutes with TBS containing 0.1% tween-20 (Sigma, St Louis, Mo.) and then probed with 1:10,000 dilution of HRP-conjugated secondary antibody raised in goat (Southern Biotechnologies, Birmingham, Ala.) for 1 h at RT. The blots were washed as above and developed by ECL-Plus (Amersham Biosciences, Piscataway, N.J.).
Scoring of AMACR Reactivity
AMACR generally migrates at around 45 kDa. The intensity of this band in each sample was scored visually by a researcher who was unaware of the diagnosis of samples and the pattern of loading in the gels. An AMACR positive control sample (LNCaP total cell extract) was used for all immunoblot experiments. While scoring, the band in the sample lanes with highest reactivity was assigned a score of 4 (highest level of reactivity) while absence of a band was scored 0 (non reactivity). Intermediate band intensities were assigned as follows: weak (score=1), intermediate (score=2), and high (score=3). In all the immunoblots, the AMACR band in the LNCaP lane was scored as 4.
Statistical Analysis
All statistical analysis was performed with SPSS 11.1 (SPSS Inc. Chicago, Ill.). A graphical representation using bar graphs was used to show the distribution of AMACR-reactivity in both the control and prostate cancer sample from the urine cohort. Student's t test (two-sided) was used to test for statistically significant differences in AMACR reactivity between patients with prostate cancer and control subjects. No adjustment for multiple testing was made during the analysis. Associations between AMACR reactivity (as assessed by immunoblotting) and various clinical and pathology parameters were determined using Pearson's Correlation Test. The mean values for AMACR reactivity were presented with 95% confidence intervals. P values less than or equal to 0.05 were considered statistically significant. Receiver operating characteristic (ROC) curves were used to assess the sensitivity and specificity of urine-associated AMACR to detect prostate cancer. A cutoff point (AMACR reactivity>1.0) in the ROC curve was chosen at which urine-associated AMACR was best able to discriminate between prostate cancer and control groups.
B. Results
Several biofluids were examined for the presence of AMACR protein. As a pilot study, immunoblot analysis of sera and plasma samples from prostate cancer patients and control subjects was performed. AMACR was detected in only a small fraction of prostate cancer sera analyzed (2 out of 22, FIG. 40A). Similarly, only 1 out of 11 plasma samples from prostate cancer patients showed AMACR reactivity (FIG. 40B). Since AMACR was initially reported to be up-regulated in prostate cancer epithelia relative to benign epithelia, the presence of this protein in prostatic excretions was assessed. Thus, prostatic excretions obtained ex vivo from prostate glands that were resected from prostate cancer patients following radical prostatectomy were analyzed. A total of 13 prostatic excretions were analyzed by immunoblot analysis and, all exhibited AMACR immunoreactivity (FIG. 40C).
Having detected AMACR in prostatic excretions, the possibility of detecting this antigen in the voided urine of prostate cancer patients was explored. AMACR immunoblot analysis was performed on urine samples from 226 individuals including 110 biopsy-proven clinically localized prostate cancer patients and 116 control subjects by immunoblotting. FIG. 41A shows a representative AMACR immunoreactivity pattern where in 11 out of 13 prostate cancer urine and 3 out of 13 control urine samples showed AMACR reactivity. To confirm the specificity of the AMACR immunoreactive band, AMACR anti-sera was pre-saturated (or quenched) with excess of either recombinant AMACR-MBP or as a control, MBP alone.
By immunoblot analysis, levels of AMACR in urine were then scored in a blinded fashion based on band intensities. Scoring ranged from 0 to 4, with 0 representing no band present and 4 representing a very strong band (see Experimental Methods above). The mean score for urine-associated AMACR reactivity in prostate cancer patients (mean=2.48, 95% CI=2.21 to 2.75) was significantly greater (p<0.0001) than in the control subjects (mean=1.03, 95% CI=0.78 to 1.29). A significantly greater percentage of prostate cancer urine samples (73.7%) had AMACR reactivity scored in the range of 2-4 in contrast to controls (28.5%) (FIG. 41C). A receiver operator characteristic (ROC) curve was generated for AMACR reactivity and an optimum cutoff point was selected at the region where the slope of the curve had the highest value (FIG. 41D). At this cutoff point, AMACR had the best discriminatory power in distinguishing between urine from prostate cancer patients and control populations (AUC: 0.753, 95% CI=0.688 to 0.817, p<0.0001) representing a sensitivity and specificity of 73.6% and 71.6%, respectively (FIG. 41D). Overall, 81 out of 110 urine samples from patients with clinically localized prostate cancer and 33 out of 116 control samples were considered positive for AMACR reactivity. In subjects with an AMACR reactivity greater than 1.0, the odds ratio of having prostate cancer was 7.03 (95% CI=3.91 to 12.61; p<0.00001). No statistically significant associations were found between AMACR reactivity in the urine of prostate cancer patients and various clinical and pathologic parameters, including PSA level at time of diagnosis, Gleason grade, pathologic stage, or gland weight (Table 11).







TABLE 11







Association between AMACR reactivity and various clinical and


pathology parameters















Gleason
Pathological
Prostate


Variable
Analysis
PSA
Score
Stage
Weight















AMACR
Pearson
−0.105
−0.163
−0.155
0.099


reactivity
Correlation



p value
.325
.120
.178
.389





Note:


the correlation was considered significant if p value ≦0.05.






EXAMPLE 17
Decreased AMACR Expression in Localized Prostate Cancer is Associated with An Increased Rate of Biochemical Recurrence and Cancer Specific Death
This example describes using a semi-automated quantitative analysis of AMACR immunohistochemical staining that allows the determination of critical cutoffs to stratify patients into risk groups for biochemical failure or prostate cancer specific death.
A. Experimental Methods
Patient Cohorts
Surgical Cohort
This cohort consisted of 204 patients from the University of Michigan (Ann Arbor, Mich.), who underwent radical retro pubic prostatectomy as a primary therapy (i.e., no preceding hormonal or radiation therapy) for clinically localized prostate cancer between 1994 to 1998. Clinical and pathology data for all patients were acquired with approval from the Institutional Review Board at the University of Michigan. Clinical data regarding this cohort has been separately reported (Nelson et al., Urol. Oncol. 21:213-8 [2003]; Nelson et al., Urology 59:740-5; discussion 745-6 [2002]). A summary of the patient demographics is presented in Table 12. Disease progression was defined as a serum PSA increase greater than 0.2 ng./ml. after radical prostatectomy. Patients were considered censored if they have not had a PSA biochemical failure at the last follow up time evaluated for that individual.
Watchful Waiting Cohort
This cohort is the largest population-based watchful waiting cohort, and consists of patients from Örebro, Sweden with clinically localized prostate cancer, who underwent watchful waiting. This cohort, initially described in 1989 (Johansson et al., Lancet 1:799-803 [1989]), consists of all men who presented with voiding symptoms referred to the urology department to rule out the diagnosis of prostate carcinoma. From March 1977 through September 1991, 1,230 patients were diagnosed with prostate cancer in Örebro County. Among these, 253 were diagnosed through transurethral resection of the prostate (TURP) and these represent the study base for the watchful waiting cohort. None were diagnosed by PSA screening. For the current investigation, cases were excluded due to insufficient amount of tumor (N=39), inadequate immunohistochemistry (N=13), inability to confirm the original diagnosis of cancer (n=9), or initially presenting for cystoprostatectomy due to bladder cancer (n=1). Thus, data from 188 watchful waiting cases were included in this study.
The baseline evaluation of these patients at diagnosis included physical examination, chest radiography, intravenous pyelogram, bone scan and skeletal radiography (if needed). Lymph Node staging was not performed. In accordance with standard practices at that time in Örebro, these patients were initially followed expectantly (“watchful waiting”). Patients were treated with androgen deprivation therapy only if they exhibited symptoms. Patient follow up included clinical examinations, laboratory tests and bone scans every 6 months during the first 2 years following the initial prostate cancer diagnosis and subsequently every 2 years. Medical records of all deceased patients were reviewed to determine cause of death. As a validation, the classification of cause of death was compared with that recorded in the Swedish Death Register. Thus far, agreement on cause of death has been over 90%, with no evidence of systematic over- or under-estimation of prostate cancer as cause of death. As of March 2003, 36 (19.2%) of patients in this cohort died of prostate cancer. The remaining patients are considered censored having either died of other causes (126 or 67.0%) or were still alive without disease at time of last follow up (26 or 13.8%). No patients were lost to follow up.
In order to ensure a uniform review of the pathology, one of the study pathologists reviewed all cases from both series. Uniform pathology review included Gleason grading, an estimate of overall tumor involvement (tumor burden per tissue samples evaluated), and tumor type (peripheral zone versus transition zone). Although there are no strict criteria for distinguishing a transition zone tumor from a peripheral zone tumor that has invaded the transition zone, the transition zone tumors were defined for the sake of this analysis as tumors with Gleason score of 6 and below with a well-circumscribed growth pattern. For staging and grading of the tumors, the TNM-classification from 1992 (Barry et al., N. Engl. J. Med. 344:1373-7 [2001]) and the WHO classification (Kattan et al., J. Natl. Cancer Inst. 90:766-71 [1998]) were used. Of the 188 patients in the watchful waiting cohort, 75(39.9%) were stage T1a and 113 (60.1%) were found to have T1b. The mean age at diagnosis was 73 years.
Tissue Microarray Construction
The TMAs from both patient cohorts were assembled using the manual tissue arrayer (Beecher Instruments, Silver Spring, Md.) as previously described (Rubin et al., JAMA 287:1662-70 [2002]). Tissue cores from circled areas were targeted for transfer to the recipient array blocks. Three to five replicate tissue cores were sampled from each patient sample. In all cases, the dominant prostate cancer nodule or the nodule with the highest Gleason pattern was sampled for the tissue micorarray. The 0.6 mm diameter TMA cores were each spaced at 0.8 mm from core-center to core-center. Six tissue microarray blocks with an average of 480 cores per block were used for this study. All blocks contained benign prostate tissue as well as prostate cancer. Each block was assembled without prior knowledge of associated clinical or pathology staging information. After construction, 4 μm sections were cut and stained with hematoxylin and eosin on the initial slides to verify the histological diagnosis. All data is maintained on a relational database as previously described (Manley et al., Am. J. Pathol. 159:837-43 [2001]).
Immunohistochemistry
Pre-treatment conditions and incubations were worked out for AMACR immunostaining using the commercially available monoclonal antibody directed against AMACR (p504s, Zeta Co., CA). Pre-treatment included placing the slide in a 6.0 pH citrate buffer and microwaving for 30 minutes. Primary p504s antibody was incubated for 40 minutes at room temperature. Secondary anti-mouse antibodies applied for 30 minutes and the enzymatic reaction was completed using a streptavidin biotin detection kit (Dako developing system, Dako, Carpenteria, Calif.) for 5 minutes. Optimal primary antibody concentration was determined by serial dilutions, optimizing for maximal signal without background immunostaining.
Manual Scoring of AMACR
All TMA cores were assigned a diagnosis (i.e., benign, atrophy, PIN, or prostate cancer) by the two study pathologists. Prostate cancer samples were only included in the analysis if both reviewers agreed that it was cancer. All manual scoring was performed on an internet-based image evaluation tool that employs zoomable TMA images generated by the BLISS Imaging System (Bacus Lab, Lombard, Ill.). The AMACR protein expression was evaluated using a categorical scoring method ranging from negative to strong staining intensity as previously reported (Rubin et al., JAMA 287:1662-70 [2002]).
Semi-Automated Quantitative Image Analysis of AMACR
A semi-automated quantitative image analysis system, ACIS II (Chromavision, San Juan Capistrano, Calif.), was used to evaluate the same TMA slides from both cohorts. The ACIS II device consists of a microscope with a computer controlled mechanical stage. Software is used to detect the brown stain intensity of the chromogen used for the immunohistochemical analysis and compare this value to blue counterstain used as background. Theoretical intensity levels range from 0-255 chromogen intensity units (IU). In pilot experiments for this study, the reproducibility of the ACIS II system was tested and confirmed by scoring several TMAs on separate occasions. The correlation coefficient for these experiments was r2=0.973. Because of tissue heterogeneity, one of the study pathologists electronically circled the areas of histologically recognizable prostate cancer using the ACIS II software for each TMA core. This process ensured that AMACR intensity measurements were from prostate cancer tissue only and not the surrounding benign glands or stroma.
Statistical Analysis
AMACR intensity readings were obtained for each of the TMA slides separately and were then normalized within each array before combining the data for analysis. After several pilot studies, it was determined that normalization of the data was preferred. Experiment-to-experiment variation was observed. Therefore, the AMACR intensity readings were normalized for each TMA core on a given array prior to merging all of the data for the final analysis. Preferred for the normalization process was the presence of approximately equally distributed numbers of normal and cancer samples on each TMA. AMACR staining intensity readings for each TMA core from a given array were subtracted by the mean intensity for that same array and then divided by the standard deviation:




  
    
      Intensity
      ij
      Normalized
    
    =
    
      
        
          Intensity
          ij
        
        -
        
          mean
          ⁡
          
            (
            
              Intensity
              i
            
            )
          
        
      
      
        sd
        ⁡
        
          (
          
            Intensity
            i
          
          )
        
      
    
  
  ,




where j=1, . . . , ni (ni is the total number of cores on TMAi). As a result, each of the normalized arrays had mean score of 0 and standard deviation equal to 1. Data were then combined using this normalized scale.

In order to determine an optimal cutpoint for AMACR, a modification of the method of regression trees (Breiman et al., Kluwer Academic Publishers; p. 368 [1984]) applied to censored data was used (LeBlanc et al., Biometrics 48:411-425 [1992]). The regression tree method is an estimation procedure that selects a cutpoint for AMACR based on optimizing a discriminating measure using the censored failure time outcome. The method employs a likelihood criterion to optimize the cutpoint, and assumes that the cost of a false positive and false negative are equal. An adjusted analysis was performed for determining a cutpoint, which involved obtaining Martingale residuals (Themeau et al., Biometrika 77:147-160 [1990]) at the first stage by adjusting for potential confounders and then applying the regression tree algorithm to find a cutpoint. The adjusted method allowed for the cutpoint to be determined accounting for clinical parameters.
The cutpoints for the AMACR intensity scores had a theoretical range between 0 and 255 IU. Using the regression tree method, the cutpoint that best differentiated PSA biochemical failure in the 204 patients from the PSA screened surgical series was determined. A similar process was repeated for the Örebro watchful waiting cohort (n=188 cases) using cancer specific death as the endpoint.
Once the cutpoints were determined for each cohort, the cutpoint was then applied to the other cohort. For example, the optimal cutpoint derived using the surrogate endpoint (PSA failure) was tested on the watchful waiting cohort to determine if it would predict a true endpoint (prostate cancer specific death). The cutpoint derived using prostate cancer specific death as the endpoint was then tested on the surgical series to see if it would predict PSA biochemical failure. Cox proportional hazards regression analysis was further employed to examine the association between the AMACR cutpoint and time to prostate cancer outcome, taking into account other clinical parameters.
B. Results
A summary of the patient demographics of the testing cohort from the University of Michigan is presented in Table 12.







TABLE 12







Prostate Cancer Patient Demographics: Men with Clinically Localized


Prostate Cancer Treated by Radical Prostatectomy (n = 204)


Stratified by Prostate Specific Antigen Biochemical Recurrence Status









PSA Recurrence













Censored
Recurred




Parameter
(n = 156)
(n = 48)
p-value
















Age, years
60
  61
0.61



DRE, %



Negative
61.5
21 43.8
0.03



Positive
38.5
27 56.3



Mean PSA, ng/ml
7.2
  12.7
0.0002



RP Gleason Score, %


<0.0001



5
3.8
  12.1



6 (3 + 3)
44.2
  12.5



7 (3 + 4)
42.3
  47.9



7 (4 + 3)
7.7
  27.1



8 (4 + 4)
0.6
   6.3



9
1.3
   4.2



Tumor Size, %


0.0001



≦2 cm.
89.7
  66.7



>2 cm.
10.3
  33.3



EPE


<0.0001



Negative
84.6
  50



Positive
15.4
  50



SM Status


<0.0001



Negative
79.5
  41.7



Positive
20.5
  58.3



AMACR (−1.11 cutoff)


0.0002



Low
32.1
  62.5



High
67.9
  37.5







{circumflex over ( )} Prostate Specific Antigen (PSA) biochemical recurrence was defined as an elevation of serum PSA of greater than 0.2 ng./ml following surgery.



* P-value was calculated by Wilcoxon rank sum test for radical prostatectomy (RP) Gleason score and pathologic stage, by Chi-square test for surgical margin status (SM), tumor size (diameter), digital rectal examination results (DRE), and extraprostatic extension (EPE), by two-sample t-test for pre-treatment prostate specific antigen (PSA) serum levels, Age, and gland weight.






Manual Evaluation of AMACR

AMACR protein expression was evaluated manually by the study pathologist and graded on a 4-tiered scale. A significant difference was found in intensity between prostate cancer (mean score=3.14/4) and benign prostate epithelium (mean score=1.3/4) with a mean difference of 1.84 (ANOVA Post-hoc Scheffé Analysis p<0.00001). In the surgical series, no significant associations between AMACR intensity scores and biochemical failure were observed, consistent with previous observations (Rubin et al., JAMA 287(13):1662-70 [2002]).
Semi-Automated Quantitative AMACR Expression Analysis
In the surgical series, lower AMACR intensity was associated with a greater likelihood of PSA biochemical failure (Tables 13 and 14). Using the adjusted regression tree method, a dichotomous cutpoint was established for AMACR intensity of 1.11 SD (i.e. samples with minimum AMACR intensity of 1.11 SD below that of the mean), wherein 37.5% of patients with AMACR intensity scores below the cutpoint had PSA biochemical failure compared to 14.5% of patients with AMACR intensity scores above the cutpoint (P=0.0002). This univariate association is visually illustrated by Kaplan-Meier analysis (FIG. 42). Using this AMACR cutpoint in multivariate analysis, patients with AMACR expression levels below the threshold were at a significantly higher risk of developing PSA recurrence (P=0.03, HR=2.15 95% CI 1.07-4.32) after adjusting for pre-operative PSA, Gleason score and surgical margin status.







TABLE 13







Univariate Cox Regression Analysis for Associations with Prostate


Specific Biochemical Failure









Univariate










Parameters
Hazard Ratio
95% CI for HR
P-value













AMACR < 1.11: Low
2.89
1.47-5.68
0.002


AMACR ≧ −1.11: High
REF


Gleason Score 7+
4.36
1.96-9.73
0.0003


Gleason Score < 7
REF


SM status positive
3.61
2.26-5.76
<.0001


SM status negative
REF


pT Stage
3.01
2.09-4.34
<.0001



REF


Extra-prostatic extension
2.79
1.97-3.94
<.0001


No extension
REF


In(PSA), per unit increase
2.41
1.72-3.38
<.0001


Tumor size > 2 cm
3.49
1.91-6.37
<.0001


Tumor size ≦ 2 cm
REF


DRE positive
1.90
1.07-3.36
0.03


DRE negative
REF


Age, per year
1.01
0.97-1.05
0.61


Gland Weight, per gram
1.00
0.99-1.02
0.94





SM = surgical margin;


DRE = digital rectal examination;


In(PSA) = the natural logarithm of pre-treatment PSA













TABLE 14







Multivariate1 Cox Regression Model: Independent Associations


with PSA Recurrence for Men with Clinically Localized Prostate Cancer


Following Radical Prostatectomy









Multivariate adjusted












Parameter
HR
95% CI
pvalue
















AMACR < 1.11: Low
2.15
1.07-4.32
0.03



AMACR ≧ −1.11:
REF



High



Gleason Score 7+
3.50
 1.00-12.19
0.049



Gleason Score < 7
REF



SM Status positive
2.73
1.60-4.68
0.0002



SM Status negative
REF



Ln (PSA)
1.69
1.08-2.63
0.022







1Data in multivariate model are adjusted for AMACR cutpoint, Gleason score, SM status and natural log of PSA






Validation of the AMACR Cutpoint in the Watchful Waiting Cohort

After development of an optimal AMACR expression cutpoint to identify men at highest risk of developing PSA biochemical recurrence, this cutpoint developed with PSA relapses following radical prostatectomy was tested to determine if it also predicted cancer specific death among patients left without curative treatment. The −1.11 SD cutoff was then applied to the watchful waiting cohort. Using this cutpoint, AMACR intensity did not predict 5, 10, 15, and 20 years prostate cancer specific survival in univariate or multivariate analysis. For example, the multivariate adjusted hazard ratio for prostate cancer death after 20 years of follow-up was 1.09 (95% CI 0.33-3.60, p=0.89).
AMACR Cutpoint Using Cancer Specific Death as the Endpoint
Since the cutpoint developed for PSA failure did not predict cancer specific death, the optimal cutpoint for this latter endpoint was next determined. Using the adjusted regression tree method, the cutpoint was determined to be 0.18 SD. The patient demographics and AMACR staining intensity results for both cutpoints are presented in Table 15 stratifying the watchful waiting cohort by cancer specific death and censored patients. The univariate and multivariate analysis for the +0.18 SD cutpoint for 5, 10, 15, and 20-year prostate cancer specific survival are presented in Table 16. As demonstrated in Table 16 and FIG. 43, there was a significant association between the AMACR cutpoint and prostate cancer death in the multivariable analysis. For example, the hazard ratio for prostate cancer death after more than 20-years of follow-up was 3.04 (95% CI 1.43-6.49, p=0.004) comparing those with low AMACR levels to those with high levels. The effect of AMACR was independent of age at diagnosis, Gleason score, and tumor stage as evidenced in the multivariable analysis. The added value of AMACR in predicting prostate cancer death in this cohort over and beyond Gleason score and tumor stage was then examined. Among the 12 prostate cancer deaths with Gleason of 6 or less, using the AMACR cutpoint appropriately predicted 11 as deaths. Further, among the 4 prostate cancer deaths with Gleason 6 or less and tumor stage T1a, all were correctly predicted as death.







TABLE 15







Prostate Cancer (CaP) Patient Demographics by AMACR Expression


from the Watchful Waiting Cohort, Örebro 1977-2003










Censored



Parameter
(N = 152)
CaP Specific Death (N = 36)












Mean age, years
74.1
72.5


T Stage, %


T1a
46.1
13.9


T1b
53.9
86.1


Gleason score, %


4
0.2
0.0


5
2.6
8.3


6 (3 + 3)
59.9
25.0


7 (3 + 4)
18.4
22.2


7 (4 + 3)
8.5
11.1


8 (4 + 4)
7.2
30.6


9
1.3
2.8


AMACR Cutoff (−1.11), %


Low
12.8
8.3


High
87.2
91.7


AMACR Cutoff (0.18), %


Low
60.1
69.4


High
39.9
30.6





* AMACR intensity cutoffs were defined using either PSA biochemical failure as the endpoint (surrogate cutpoint equal −1.11) or prostate cancer specific death (true cutpoint equals 0.18)













TABLE 16







Univariate and Multivariate1 Cox Models: Association between AMACR and


Prostate Cancer Specific Death in Watchful Waiting Cohort, Örebro 1977-2003










Unadjusted
Multivariate Adjusted













Parameter
HR
95% CI
pvalue
HR
95% CI
pvalue










5 years of follow-up













AMACR < 0.18: Low
3.32
 0.74-14.98
0.12
7.36
 1.56-34.74
0.012


AMACR ≧ 0.18:
REF


REF


High


Age (per year)
1.04
0.97-1.11
0.30
1.03
0.95-1.12
0.51


Stage T1b
8.32
 1.08-63.97
0.042
5.50
 0.65-46.76
0.12


Stage T1a
REF


REF


Gleason Score 7+
5.01
 1.38-18.21
0.015
4.39
 1.12-17.15
0.034


Gleason Score < 7
REF


REF







10 years of follow-up













AMACR < 0.18: Low
1.59
0.67-3.79
0.29
3.23
1.32-7.90
0.010


AMACR ≧ 0.18:
REF


REF


High


Age (per year)
1.03
0.98-1.09
0.25
1.01
0.96-1.07
0.63


T stage T1b
10.25 
 2.42-43.48
0.0016
8.01
 1.78-36.08
0.0068


T stage T1a
REF


REF


Gleason 7+
4.09
1.77-9.43
0.001
2.84
1.17-6.93
0.022


Gleason < 7
REF


REF







15 years of follow-up













AMACR < 0.18: Low
1.91
0.86-4.25
0.11
3.97
1.71-9.17
0.0013


AMACR ≧ 0.18:
REF


REF


High


Age (per year)
1.04
0.99-1.09
0.12
1.03
0.98-1.08
0.30


T stage T1b
4.78
 1.84-12.41
0.0013
3.59
1.29-9.99
0.014


T stage T1a
REF


REF


Gleason 7+
3.63
1.77-7.44
0.0004
3.32
1.49-7.39
0.0033


Gleason < 7
REF


REF







20+ years of follow-up













AMACR < 0.18: Low
1.40
0.68-2.83
0.36
3.04
1.43-6.49
0.0039


AMACR ≧ 0.18:
REF


REF


High


Age (per year)
1.03
0.99-1.08
0.17
1.02
0.97-1.01
0.46


T stage T1b
5.12
 1.98-13.21
0.0007
3.45
1.25-9.56
0.017


T stage T1a
REF


REF


Gleason 7+
4.40
2.18-8.89
<0.0001
4.02
1.81-8.91
0.0006


Gleason < 7
REF


REF





1Data in multivariate model are adjusted for AMACR cutpoint, age, T stage and Gleason score






Application of AMACR Cutpoint for Cancer Specific Death on the Surgical Series

Using cancer specific death as the endpoint, the optimal normalized cutpoint was 0.18 (in contrast to −1.11 as determined by using PSA biochemical failure) (FIG. 43). It was then determined if this cutpoint could predict mean PSA biochemical failure following radical prostatectomy. Using the 0.18 cutpoint, 81% of the clinically localized tumors from the surgical series were below the AMACR cutpoint. There was evidence that AMACR levels below the cutpoint determined by prostate cancer death was significantly associated with time to PSA biochemical failure at the univariate level as demonstrated by the Kaplan-Meier analysis (FIG. 43). On multivariate analysis, low AMACR expression was a significant predictor of biochemical failure, independent of Gleason score, surgical margin status, and pre-treatment PSA, with a hazard ratio of 3.88 (95% CI=1.32-11.38, p<0.014) (Table 17).







TABLE 17







Multivariate1 Cox Model: Independent associations with PSA


Recurrence for Men with Clinically Localized Prostate Cancer Following


Radical Prostatectomy Using Cancer Specific Death Cutoff for AMACR









Multivariate adjusted












Parameter
HR
95% CI
pvalue
















AMACR < 0.18
3.88
 1.32-11.38
0.014



AMACR ≧ 0.18
REF



Gleason Score 7+
2.35
1.02-5.40
0.040



Gleason Score < 7
REF



SM Status positive
2.78
1.53-5.03
<0.001



SM Status negative
REF



Ln (PSA)
1.89
1.31-2.74
<0.001







AMACR intensity cutoffs were defined using prostate cancer specific death (true endpoint cutpoint equals 0.18).



1Data were adjusted for Gleason score; surgical margin status, and the natural log of pre-treatment serum PSA






The application of a biomarker in the clinical setting accommodates clinical characteristics of patients as well assessment of prostate cancer prognosis. In Table 18, the joint association between AMACR expression and Gleason score on prostate cancer outcome in the two cohorts was examined. For this analysis, the AMACR cutpoint of 0.18 SD was relied upon. Compared to those with “better” biomarker and clinical measures (i.e. high AMACR expression and low Gleason score), those with both low AMACR expression and high Gleason score had an almost 4 times higher risk of PSA biochemical failure. In the watchful waiting cohort, however, individuals with the “poorer” measures had an 18-fold higher risk of prostate cancer death (p=0.006). These data indicate that the AMACR biomarker, in combination with clinical parameters, can substantially predict prostate cancer mortality.







TABLE 18







Hazard ratio (95% CI) of prostate cancer outcome associated with


AMACR expression and Gleason score, cross classified










Surgical cohort
Watchful waiting cohort



PSA biochemical failure
Prostate cancer death












Low AMACR
High AMACR
Low AMACR
High AMACR





Gleason ≧ 7
3.9 (0.53-29.2)
1.7 (0.21-14.5)
18.0 (2.3-140.8)
4.9 (0.63-37.9)


Gleason < 7
1.2 (0.12-10.9)
REF
 6.4 (0.8-51.2)
REF





Data are adjusted for surgical margins and PSA (surgical cohort) or age and T stage (watchful waiting cohort).


AMACR cutpoint = 0.18.






Prostate cancer biomarker development requires selecting an endpoint for the study. Most studies have used PSA biochemical failure as a surrogate endpoint; however, this study indicates that PSA biochemical failure is not sufficient to define cutpoints for predicting cancer specific death. The AMACR cutpoint used to predict PSA biochemical failure did not predict cancer-specific death. The presence of two distinct cutpoints for the two distinct endpoints illustrates this principle (FIG. 44).
All publications and patents mentioned in the above specification are herein incorporated by reference. Various modifications and variations of the described method and system of the invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention which are obvious to those skilled in the relevant fields are intended to be within the scope of the following claims.

## Claims

1. A method of detecting the presence or absence of prostate cancer in a subject, comprising:
a) providing
i) urine from a subject;
ii) a reagent for detecting α-methylacyl-CoA racemase in said urine; and

b) contacting said urine with said reagent under conditions such that said reagent detects the presence or absence of α-methylacyl-CoA racemase in said urine;
c) determining the presence or absence of prostate cancer in said subject based on said presence or absence of α-methylacyl-CoA racemase in said urine.

2. The method of claim 1, wherein level of said α-methylacyl-CoA racemase in said urine is determined.

3. The method of claim 2, wherein a minimum threshold level of expression of α-methylacyl-CoA racemase is set to 1, where 0 is absence of α-methylacyl-CoA racemase and 4 is highest level expression.

4. The method of claim 3, wherein the presence of said α-methylacyl-CoA racemase in said urine at a level above said minimum threshold level is indicative of a diagnosis of prostate cancer in said subject.

5. The method of claim 1, wherein said reagent is an antibody.

6. The method of claim 5, wherein said antibody is selected from the group consisting of a single chain antibody, an Fab, and an epitope-binding fragment.

7. The method of claim 1, wherein said reagent comprises a label.

8. The method of claim 7, wherein said label is selected from the group consisting of a radioactive label, a fluorescent label, a chemiluminescent label, and a bioluminescent label.