Reanalysis of Cancer Drugs (2004)

Most cancer chemotherapy protocols in current use have been established empirically, and combination therapies have generally been designed based on single-agent activity and nonoverlapping toxicities. However, advances in our understanding of the molecular pathophysiology of human cancers indicate that certain molecular features of neoplastic cells can be associated with their sensitivity to chemotherapeutic agents and therefore can be used as the basis for rational drug selection and therapy design. In addition, the ability to discover markers that predict responsiveness to therapy is possible today as never before. Specimens (fixed tissues, immortalized cells, frozen specimens, body fluids, and so forth) obtained 5–10 years before the clinical outcome is known represent a major reservoir of information. Exploiting this resource can shorten the time necessary for retrospective trials and can then be used empirically when prospective trials are mounted. Furthermore, prognostic and predictive measures can be determined with microarrays (1).Identifying potential responders is critical to successful drug treatment and is potentially a major use of biomarkers. Such biomarker-based strategies can be key to the development and approval of new therapies. For instance, Koo et al. (2, 3) have observed a striking correlation between activating ras mutations in human tumor cells and enhanced sensitivity to deoxycytidine analogs as well as to topoisomerase (topo) II inhibitors. Compared with tumor cells with wild-type ras alleles, human tumor cell lines harboring or transformed with activated ras oncogenes display significantly enhanced cytotoxic sensitivity to deoxycytidine analogs, including 1-β-d-arabinofuranosylcytosine (cytarabine) and gemcitabine. Activated ras oncogenes similarly sensitize human tumor cells to topo II inhibitors and more prominently sensitize human tumor cells to epipodophyllotoxin-derived inhibitors such as etoposide and teniposide. Furthermore, these findings are supported by retrospective studies in patients with acute myeloid leukemia (AML) showing that the presence of ras oncogenes in leukemic cells is associated with increased complete remission rate, longer complete remission duration, and improved overall survival of the patients in response to treatment with cytarabine or the combination of cytarabine and a topo II inhibitor (4, 5). These results indicate that the ras oncogene plays a determinant role in rendering tumor cells sensitive to deoxycytidine analogs and topo II inhibitors and may provide a rationale for the design of potentially synergistic combination therapy (deoxycytidine analog + topo II inhibitor) for other cancers bearing frequent ras mutations. In Wilms' tumor, the most common pediatric cancer of the urinary tract, previous studies have identified topo IIα overexpression; the highly effective chemotherapeutic regimens are mainly constituted with topo II inhibitors (6, 7, 8). These results may provide a molecular basis for the success of topo II inhibitor-based treatment of Wilms' tumors and indicate that topo II overexpression is a biomarker for the choice of topo II inhibitor treatment.Strategies for selecting those most likely to respond to therapy have already proven beneficial to patients. For example, only patients with breast cancer expressing Her-2/neu respond to trastuzumab (Herceptin). Without identification of the susceptible subpopulation, Herceptin would not have been made available for treatment of this poor-prognosis breast cancer (9). The findings of Staudt (10) that gene expression profiles can be used prospectively to define lymphomas that respond to standard chemotherapy (Fig. 1) reaffirm that the thesis proposed herein has promise and that other examples of this utility will derive from the proposed analyses.This article proposes to explore the possibilities of analyzing (reanalysis) chemotherapeutic drugs and protocols in practice through conventional and newer molecular and/or imaging technologies to discover surrogate end point or other biomarkers predicting and measuring effectiveness of the therapies. These analyses should first be performed through clinical trials using approved drugs and established protocols. The studies can be prospectively designed or developed from retrospective studies, where appropriate patient material is available. The purpose of these studies will be severalfold: (a) first, to identify potential surrogate end point and other biomarkers markers that will be informative of patient outcome and response; and (b) second, to identify when a specific protocol should be used (e.g., as indicated by biomarkers and/or gene expression profiles). As candidate biomarker(s) are identified, they should be verified or validated against currently used standards or biomarkers. Efficacy in diagnosis, prognosis, or molecular classification for treatment must be demonstrated.Whereas the thrust of this paper is on evaluation of responses to approved cytotoxic therapies, other types of drugs and protocols should also be evaluated. It would be particularly beneficial to validate biomarkers of response to the newer molecular therapies that do not produce dramatic tumor shrinkage. Interestingly, modulation of expression of the molecular target might not always be a good predictor of response. For example, both epidermal growth factor receptor (EGFR)- and Her-2-overexpressing tumors are sensitive to the EGFR-selective tyrosine kinase inhibitor gefitinib (Iressa), and sensitivity to this agent is correlated with its ability to down-regulate Akt. However, EGFR-overexpressing MDA-468 cells, which lack PTEN function, are resistant to Iressa, and Iressa is unable to down-regulate Akt activity in these cells. This resistance to Iressa is attributable to EGFR-independent constitutive Akt activation caused by PTEN loss. Reconstitution of PTEN function through tetracycline-inducible expression restores Iressa sensitivity and reestablishes EGFR-stimulated Akt signaling (11). Gene or protein expression patterns such as these could be identified in other settings and with other drugs. Just as for the analysis of cytotoxic drugs, patients might be evaluated after a short treatment period with molecularly targeted agents; those who did not show the expression pattern could be spared further, possibly futile treatment.In the following sections, techniques and material sources for assessing and developing new biomarkers are delineated. Sample clinical settings for the conduct of research to identify and validate prognostic and predictive (drug effect and clinical outcome) markers are discussed. A separate section on AML provides data from completed and ongoing clinical trials as a prototype. The article concludes with specific recommendations for fostering research in this area. These include development of a collaborative initiative to facilitate access to both novel technologies as they become available (e.g., genomic, proteomic, functional imaging technologies, and so forth) and clinical trial samples (e.g., serum, biopsy tissue, DNA, imaging data, and so forth). The initiative could leverage existing National Cancer Institute (NCI) technology, clinical networks, and translational research programs. For example, the NCI's Specialized Programs of Research Excellence program has fostered multidisciplinary teams to address biomarker identification and validation.11 A bioinformatics system to aid in the collection and sharing of key data elements (e.g., outcome, demographic, and so forth) could be implemented in accord with the NCI's Cancer Bioinformatics Informatics Grid project.12 Patient and tissue access might best be achieved via established collaborative physician networks (e.g., Oncology Cooperative Groups). Finally, the initiative could also draw from other successful local, national, and international collaborations that support translational research and biomarker development, such as MdBIO,13 the NIH roadmap,14 the European Organization for the Treatment of Cancer,15 and the United Kingdom's National Cancer Research Institute.16 Together, these efforts will promote the discovery of surrogate end point or other biomarkers to predict and measure effectiveness of therapies.Technologies that could be used to develop biological markers to predict drug response or clinical outcomes for a cancer chemotherapeutic agent include the following: immunologically based assays for a given protein, peptide, or glycoprotein; PCR assays for quantitation of the expression of a specific gene product; genomic analysis; gene expression profiling to characterize the transcription level of multiple genes; proteomics; DNA methylation patterns; detection of circulating cancer cells; and functional imaging. Each of these is described below. Table 1 lists examples of data resources on potential biological markers that may be identified with these technologies.Conventional methods for detection of tumor markers in body fluids involving isolation of the marker (usually a protein or glycoprotein), developing a specific antibody to the marker, and developing an immunologically based assay using the antibody, such as an ELISA, will continue to be useful in evaluating biomarkers. ELISA is the standard assay for detection of well-known serum markers such as carcinoembryonic antigen, human chorionic gonadotrophin, α-fetoprotein, CA-125, and prostate-specific antigen (12).More recently, the development of the PCR technique has allowed determination of transcription levels of the above serum markers as well as of additional markers such as oncogenes in circulating cancer cells, serum, urine, and fecal samples (12, 13, 14).Comparative genomic hybridization and spectral karyotyping are two techniques used to measure tumor-associated chromosomal alterations. In comparative genomic hybridization, tumor DNA and normal reference DNA with different fluorescent labels are hybridized simultaneously to normal chromosome spreads. Regions of gain or loss of DNA sequences, such as deletions, duplications, or amplifications, are seen as changes in the ratio of the intensities of the two fluorophores along the target chromosomes (15). Spectral karyotyping allows visualization of all 23 pairs of human chromosomes by labeling each pair with a different fluorescent color (16).The Human Genome Project has revealed detailed information about the base sequence of human genes. This has allowed the development of DNA microarrays that enable the simultaneous detection of thousands of human genes displayed on a matrix as small as a slide coverslip. Two different kinds of target DNA sequences are widely used: (a) cDNA copies derived from a mRNA coding for a specific gene transcript; and (b) oligonucleotide sequences representing highly specific segments of the target genes. Data derived in this way can be used to systematically search for single genes whose over- or underexpression may be related to prognosis, disease progression, or drug response. Alternatively, an entire set of expressed genes can be used to subclassify tumor types, tumor stage, and/or tumor aggressiveness (17).In some tumor types, a minimal number of genes can be used to classify cancers. For example, a "lymphochip" representing a subset of genes expressed in B-lymphocytes can be used to characterize distinct types of diffuse large B-cell lymphomas that vary in aggressiveness and predict patient survival (18). Similarly, a gene expression profile has been identified that predicts survival of patients with breast cancer (19).Proteomics can be defined as the study of the protein expression profile of a tissue or specific cell type to define a set of functions. The term "proteome," coined in 1994 to provide an analogy to the concept of the genome, is used to define the complete set of proteins that is expressed by a cell, tissue, or whole organism. In the context of cancer, the term is used to describe a protein expression profile that reflects the phenotype of a malignant cell that differentiates it from normal cells of the tissue in which the tumor developed.Several techniques are available to determine protein expression profiles. These include the classic technique of two-dimensional gel electrophoresis; selective adsorption techniques to fractionate proteins based on size, hydrophobicity, ligand binding, and so forth; and mass spectrometer analysis (e.g., matrix-assisted laser desorption ionization time-of-flight and liquid chromatography tandem mass spectrometry). These techniques generate large data sets that require detailed bioinformatics analysis. Theoretically, 100,000 or more proteins may be expressed in a cell, if one considers all of the posttranslational modifications that can occur in the protein products of ≅30,000 human genes.Although characterization of the proteome that defines a cancer appears to be an overwhelming task, the determination of protein expression patterns based on pattern recognition of serum proteins has been used to diagnose ovarian cancer, even though the specific protein(s) present in each peak of the profile may not be known (20). It is hoped that algorithms based on assessments of protein patterns for other cancers can also be established. This could provide a way to use proteomics for cancer diagnosis, prognosis, and drug responsiveness.The methylation status of DNA in a cell type provides an indication of genome function. The sites of DNA methylation generally occur on CpG-rich base sequences, the so-called CpG islands. CpG islands are found in promoter regions of about half of all cellular genes, and intense methylation of these sequences is associated with gene silencing (21). Aberrant methylation of CpG islands in cancer tissue has been associated with inactivation of tumor suppressor genes (22). Aberrantly methylated DNA can be detected in body fluids such as serum, sputum, or breast ductal lavage from patients with lung (23, 24), liver (25), or breast (26) cancers.Epithelial cells are not normally found in blood, and their detection usually indicates the presence of a pathological state, frequently cancer. Circulating epithelial cells can be isolated from plasma, even against a huge background of blood cells, because they bear specific cell surface markers, called cytokeratins, not present on hematological cell types. Changes in circulating carcinoma cells have been found to correlate with disease status and drug response in patients with prostate (27) or breast (28) cancer, suggesting their use as biomarkers for drug response and disease progression.Viable and apoptotic circulating endothelial cell levels in peripheral blood may serve as a biomarker for tumor angiogenesis, and their detection and quantitation may reflect the effects of antiangiogenic therapy (29). Circulating endothelial cell levels have been shown to rise significantly in the peripheral blood of untreated lymphoma and breast cancer patients, returning to healthy control levels in patients who achieve complete remission after chemotherapy (30).In addition to fully differentiated endothelial cells, immature circulating endothelial progenitor cells derived from bone marrow also exhibit potential as a surrogate marker for tumor angiogenesis (31, 32). Although prognostic and therapeutic value has not been demonstrated, accumulating evidence in both mouse tumor models (33, 34) and cancer patients (30) suggests that malignant transformation is associated with increased numbers of circulating endothelial progenitor cells.Imaging technologies use energy-tissue interactions to noninvasively visualize internal tissues (35, 36, 37). Imaging modalities most commonly used in clinical settings include magnetic resonance imaging, X-ray computed tomography, positron emission tomography (PET), single photon emission computed tomography, and contrast and Doppler ultrasound. In the past, in vivo imaging methods revealed gross anatomy; diseases or treatment effects were mostly detected as anatomical structural abnormalities (structural or conventional imaging). Higher resolution detection and the use of imaging agents have enabled resolution on a finer scale and the evaluation of physiological parameters in live tissue (functional imaging). For drug development and evaluation, the main advantages of high-resolution imaging over other traditional biomarkers (such as those requiring tissue sampling, excision, and fluid analysis) are the direct visualization of disease processes and of tumor heterogeneity, the ability to quantitate changes over time, and the noninvasive nature of the tests. Optical technologies under development using fluorescence and bioluminescence may prove particularly useful in early drug development.More recently, imaging of specific drug and drug target molecules (molecular imaging) has evolved as a subset of functional imaging. Molecular imaging can be used to directly follow the path of an administered drug (e.g., the distribution and target binding of a labeled drug) or to monitor the drug's target (e.g., detection of receptor expression and modulation of downstream targets). Nuclear techniques, particularly quantitative PET imaging, are being used clinically for such evaluations. For example, many drugs can be labeled with the positron emitters 11C or 18F, and tissue distribution of these labeled drugs can be followed by PET imaging. Another PET technique is evaluation of target binding inhibition of a PET radioligand by unlabeled drug. Thus, molecular imaging techniques are particularly promising for drug distribution and pharmacokinetics and, when used for this purpose, may be able to explain responders and nonresponders to a given drug.Imaging (both anatomical and functional) can also play a key role in measuring response to therapy. The functional measurement of key biological parameters of neoplastic disease is possible: for example, angiogenesis and vascular responsiveness (using magnetic resonance imaging and ultrasound); cellular metabolism (e.g., 2-18F-2-deoxy-d-glucose-PET [FDG-PET]); cell proliferation and apoptosis (e.g., FLT and 99mTc-annexin imaging); and resistance to chemotherapy (99mTc-sestamibi imaging). Innovations in imaging devices allowing simultaneous combined modality measurements (e.g., PET/computed tomography or PET/magnetic resonance imaging) have great promise for increasing the utility of imaging in measuring the response to therapy.Two examples of functional/molecular imaging probes applicable to cancer drug development are FDG-PET and 99mTc-annexin. FDG-PET already is well established for use in the diagnosis and management of melanoma and lymphoma, as well as cancers of the lung, colon, breast, thyroid, esophagus, and head and neck. The apoptosis imaging probe 99mTc-annexin V has recently shown promise in predicting tumor response to apoptosis-inducing chemotherapeutics in a Phase I study (38).The techniques described above often have specific requirements regarding the material source. Particularly relevant material sources and their applications are described in the following paragraphs.This is the ideal source of material for all analyses described in this article and is required for certain types of analyses, particularly microarray-based gene expression profiling. With the introduction of laser capture microdissection it is to single cell types and separate normal tissues from tumor tissues to functional genomic and/or cell can also be established for assays and surrogate biomarker tissues are commonly used for to biomarker can be developed for biomarker between patients or between and patients, where appropriate samples are available. DNA and mass protein may be obtained from tissues, this material is not proven to be applicable for material sources can be used in analyses of DNA, and cancer cells from a of tissues isolated from or example, leukemic cells can be isolated directly from body to circulating carcinoma cells from are also available for a of tumors of circulating cancer and endothelial cells is described measurement of a candidate biomarker and provides the best evidence for evaluation of the biomarker and for correlation with clinical promising clinical where such measurements are possible is cancers in which serum biomarkers or anatomical are used to monitor patient response to therapy. A is where tissue samples or are available and after when of the cancer A is in which and or imaging is often available. for evaluation of biomarkers in these settings are in the following serum biomarkers are an of diagnosis, prognosis, and or even in tumors (e.g., in ovarian For example, in cancer, α-fetoprotein, human chorionic gonadotrophin, and may tumors small to be seen on and are for 1 after treatment These standard with computed tomography can be used to the presence or expression of specific new biomarkers is predictive or correlated clinical response to the standard therapy as well as disease Although therapy is successful in many patients, a in cancer is to identify those of patients likely to respond to therapy and/or to In support of the a study of additional biomarkers and used in combination with standard serum biomarkers could identify those with survival cancer patients samples are available both and patients treatment provide a in which to the expression of specific biomarkers is predictive of or correlated with responses to For instance, breast cancer often a to the the use of chemotherapy has been chemotherapy may the of disease and may enable breast therapy in patients because of the large of their tumors However, the success of this is under evaluation a Phase II study found that treatment associated with a clinical response in breast cancer patients Although it is that chemotherapy given in the after overall and it has not been proven that chemotherapy A potential trial design would include characterization and correlation of biomarker expression and response in and/or before and after treatment with as well as correlation with clinical response by imaging, clinical of progression, and This is by one study of the gene associated with in gene expression profiling of biopsy samples before identified a pattern of expression of genes a of genes that correlated with response The gene expression a and and predictive cancer is the of and the basis of chemotherapeutic in lung cancer is is a in the of standard therapy for lung cancer to the presence or expression of specific biomarkers in biopsy and/or is predictive of or correlated with clinical response. overall a of patients with small cell lung cancer respond to therapy with increased of the short of the disease and the of and imaging data with and small cell lung cancer provides a for trials understanding patient response to standard therapy. The trial would biomarker presence and expression before and after therapy and would correlate biomarker presence and response with clinical responses by imaging, clinical progression, and A can be used in cell lung cancer, which to standard therapy about of lung cancer It is already known that the presence of the mutations prognostic the prognostic potential of other markers (such as carcinoembryonic antigen, and is also being For example, a study used carcinoembryonic antigen and to identify a of I patients, in chemotherapy may be appropriate this the characterization of prognostic and treatment effect biomarkers in AML is and strategies for research are discussed. 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