# Patent

## Title
Biomarkers for head-and-neck cancers and precancers

## Abstract

The invention provides markers and methods for detecting head-and-neck precancers, (including OPLs), cancers and related disease conditions in a subject. The invention also provides localization and imaging methods for head-and-neck precancers (including OPLs) and cancers, along with kits for carrying out methods of the invention. The invention further provides therapeutic applications for head-and-neck precancers (including OPLs) and cancers which employ head-and-neck precancer and cancer markers, and binding agents for the markers. Methods of identifying a subject having oral dysplasia that is at high risk of malignant transformation are provided.

## Background
RELATED APPLICATIONS
This application is a continuation in part of U.S. application Ser. No. 12/866,567, filed Nov. 17, 2010, now U.S. Pat. No. 8,921,053, which is a national stage application of International Patent Application No. PCT/CA2009/000154, filed Feb. 6, 2009, which claims priority to Canadian Patent Application No. 2,643,611, filed Nov. 10, 2008 and Canadian Patent Application No. 2,618,163, filed on Feb. 7, 2008 all of which are incorporated herein by reference, as if set forth in their entirety.


FIELD OF THE INVENTION
The invention relates to markers for head-and-neck cancers, including oral cancers, and head-and-neck precancers, including, for example, oral leukoplakia with hyperplasia or dysplasia. The invention further relates to methods for assessing the status of head-and-neck tissue and oral tissue, and methods for the detection, diagnosis and prediction of head-and-neck disease. In one aspect, the invention relates to biomarkers of head-and-neck squamous cell carcinoma and biomarkers of head-and-neck precancers (including, but not limited to, oral leukoplakia with hyperplasia or dysplasia), and methods for detecting, diagnosing and predicting these and related conditions. In a further aspect, the invention relates to biomarkers of oral leukoplakia with hyperplasia or dysplasia, and methods for detecting, diagnosing and predicting same. In another aspect, the invention relates to a method for predicting risk of malignant transformation in oral lesions.
BACKGROUND OF THE INVENTION
Annually, about 500,000 cancer-related deaths are estimated in the United States alone. Of these, approximately 13,000 are attributed to head-and-neck including oral squamous-cell carcinoma (HNOSCC), making it the sixth most common cause of cancer deaths and the fourth most prevalent cancer in men worldwide (1).
A lack of biomarkers for early detection and risk assessment is clearly reflected by the fact that more than 50% of all patients with head-and-neck squamous-cell carcinoma (HNSCC) have advanced disease at the time of diagnosis (2). The five-year survival rate of HNSCC patients is less than 50%, and the prognosis of advanced HNSCC cases has not changed much over the past three decades, except in a few advanced centers (2). Conceivably, improvement in understanding of the steps leading to tumorigenesis will provide the ability to identify and predict malignant progression at an earlier stage of HNSCC lesions, in turn leading to more effective treatment and reduction of morbidity and mortality.
The precancerous lesions, potentially malignant lesions, premalignant lesions, and squamous intraepithelial lesions (SILs) of the head and neck (oral cavity, oropharynx, and larynx)—which are clinically usually defined as “leukoplakia”—remain the main controversial topic in head and neck pathology as regards classification, histological diagnosis, and treatment (3-5). The transition from a normal epithelium to squamous cell carcinoma (SCC) of the head and neck is a lengthy, comprehensive and multistage process, causally related to progressive accumulation of genetic changes leading to the selection of a clonal population of transformed epithelial cells (6). The whole spectrum of histological changes occurring in this process has been recently cumulatively designated potentially malignant lesions or SILs, ranging from squamous hyperplasia to carcinoma in situ (CIS) (3). In their evolution, some cases of potentially malignant lesions and SILs are self-limiting and reversible, some persist, and some progress to SCC in spite of careful follow-up and treatment.
Oral squamous-cell carcinoma (OSCC), the most common form of HNOSCC, is often preceded by clinically-well-defined lesions, such as leukoplakia, causally linked with chronic exposure of the oral mucosa to carcinogens or growth promoters in tobacco and alcohol; leukoplakias with dysplasia are termed “oral premalignant lesions” (OPLs) (3, 6).
Currently, there are no clinically-established biomarkers to facilitate the diagnosis or prognosis of head-and-neck cancer and/or oral leukoplakia. It is expected that identification of novel protein markers or therapeutic targets will ultimately improve patient care and survival. It is hoped that these biomarkers will transform clinical practice by including cancer screening and diagnosis based on molecular markers as a complement to histopathology.
In the post-genomics era, proteomics combined with mass spectrometry (MS) has become a powerful paradigm for the examination of proteins in a global manner, and the consequent discovery of cancer risk markers and drug targets. While transcriptomics provides a tool for unraveling gene-expression networks, proteomics links these networks to protein products and provides further insight into post-translational modifications that regulate cellular functions, thereby complementing genomic analyses (reviewed in Ralhan (8)). Identification of differentially expressed proteins in HNSCCs using proteomics revealed that expression patterns of proteins may have some predictive power for clinical outcome and personalized risk assessment (8-16)
Differential tagging with isotopic reagents, such as isotope-coded affinity tags (ICAT) (17) or the more recent variation that uses isobaric tagging reagents, iTRAQ (Applied Biosystems, Foster City, Calif.), followed by multidimensional liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis, is emerging as one of the more powerful methodologies in the search for disease biomarkers. Recent studies using iTRAQ reagents resulted in identification and relative quantification of proteins leading to a discovery of potential cancer markers (PCMs) for human cancers (17-23).
The presence of dysplastic areas in the oral epithelium is associated with a likely progression to cancer; however, it is not an accurate predictor of cancer risk (6, 7). The major challenge in oral tumorigenesis is the identification of proteins that may serve as markers to differentiate the high-risk leukoplakic lesions, including OPLs, from more benign lesions for early intervention to reduce the morbidity associated with this devastating disease. Rapid advances in treatment modalities and improvements in the early detection of head-and-neck cancers have not significantly impacted the overall survival rates of cancer patients. Thus, much effort has been focused on genomics- and proteomics-based identification of biomarkers that can detect the disease in early stages, predict the risk of malignant transformation in patients with oral leukoplakia, including OPLs, and/or predict the clinical outcome in HNOSCC patients after treatment of primary tumors.
Increased levels of S100A7 transcripts have been identified by microarray analysis in oral dysplasia relative to normal oral mucosa (63). Winter et al., (125) showed by RT-PCR S100A7 overexpression and DOC1 downregulation in 15 leukoplakia biopsies and proposed that the combined investigation of both genes may be a marker for estimating the risk of cancer development in intraoral lesions. However, major limitations of the Winter et al. study were the limited sample size and no data on correlation with clinical outcome in a follow up study or in a longitudinal study. Further, the majority of studies examining markers for oral lesions are cross-sectional analyses and do not provide data on these lesions over time, thus rendering them unsuitable for identifying patients with dysplasia that is at high risk of transformation. Longitudinal long term follow-up studies of OPLs are required to determine the robust signature of markers for predicting fate of dysplastic lesions.
SUMMARY OF THE INVENTION
As discussed herein, the inventors used iTRAQ labeling in combination with multidimensional LC-MS/MS analysis of head-and-neck cancer in order to compare protein profiles of HNSCC and non-cancerous head-and-neck tissues. The inventors also used iTRAQ labeling in combination with multidimensional LC-MS/MS analysis of oral leukoplakia with dysplasia (oral premalignant lesions, or OPLs) in order to compare protein profiles of OPLs and normal head-and-neck tissues. These studies were designed to identify potential biomarkers, and to identify, in a global fashion, molecular pathways that are deregulated in head-and-neck and oral cancer, thereby aiding in drug-target discovery.
The iTRAQ experiments were performed on resected HNSCC, excised OPLs, and non-cancerous tissue homogenates. The rationale for using whole tissue homogenates as opposed to laser-capture-microdissection (LCM)-procured tumor cells has been discussed previously (21, 23). There are at least two major advantages in the analysis of tissue homogenates: the relevant proteins are much more abundant in the tissues of interest than in bodily fluids, and there is an automatic link between a protein that is differentially expressed and the tumor itself. Such a link would need to be demonstrated if the differentially expressed proteins were to be discovered in a bodily fluid (e.g., blood), as every tissue or organ can potentially discharge into blood. Furthermore, the tumor microenvironment plays an important role in cancer progression (24); examination of protein expression in tissues from a homogenate of different cell types takes into account the contributions of the tumor microenvironment.
The protein expression profiles of HNSCCs and OPLs were compared with non-cancerous head-and-neck tissues (controls) using the iTRAQ-labelling technique in combination with multidimensional LC-MS/MS analysis. In the iTRAQ technology, primary amines are tagged, thereby potentially allowing the tagging of most tryptic peptides. The multiplexing ability afforded by the iTRAQ reagents, which are available in four different tags, was ideally suited for the present study, as it provided a means to perform a proteomic analysis of both paired and non-paired non-cancerous (histologically normal) head-and-neck tissues, while simultaneously comparing them against the cancer samples. This strategy helps to identify proteins that might be differentially expressed due to manifestation of field cancerization (25-27) in clinically normal mucosa, and may be useful in designing strategies for risk prediction of disease recurrence or second primary tumor development.
Some of the overexpressed proteins that were identified in the tissues by the iTRAQ technology and LC MS/MS analysis were confirmed by immunohistochemistry and Western blotting. These approaches ensured that the selected proteins demonstrated a consistent pattern of overexpression in HNSCCs and OPLs, and greatly increased confidence in the observations stemming from iTRAQ analysis. Apart from their potential utility as biomarkers for HNSCC and OPLs, these proteins also provide valuable insight into the previously unknown molecular networks and mechanisms that govern the normal-to-malignant conversion of epithelium.
Using the above techniques, the inventors identified markers associated with head-and-neck tissues, including oral tissues. Thus, the invention relates to novel markers for head-and-neck including oral tissues, including markers of head-and-neck including oral disease, and compositions comprising same.
In one aspect, the invention provides marker sets that distinguish head-and-neck cells, including oral cells, or tissue, diseases, or phases thereof. Also provided are uses of these marker sets. In specific aspects, the markers include at least 2, 3, 4, or 5 polypeptides listed in Table 5. In another aspect, the protein marker set includes protein clusters or proteins in pathways including markers listed in Table 5 and Table 2. In yet another aspect, the invention provides markers in Table 1 that are up-regulated or down-regulated or expressed in cancer samples as compared to the non-cancer samples. In yet another aspect, the invention provides markers in 5 and optionally Table 8 including 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, or 32 of the markers listed therein that are up-regulated or down-regulated or expressed in OPL samples as compared to the normal samples. In specific aspects, the OPL markers include at least 2, 3, 4, or 5 polypeptides listed in Table 6 and 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, or 32 listed in Table 5. In another aspect, the protein marker set includes protein clusters or proteins in pathways including markers listed in Table 5 (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, or 32).
Up-regulated markers identified in Table 1 (up-regulated in cancer samples versus non-cancer samples), and Table 6 (up-regulated in OPL samples versus non-cancer samples), including but not limited to native-sequence polypeptides, isoforms, chimeric polypeptides, all homologs, fragments, and precursors of the markers, including modified forms of the polypeptides and derivatives are referred to and defined herein as “head-and-neck cancer marker(s) and OPL marker(s)”.
Up-regulated head-and-neck cancer markers listed in Table 1 (in cancer sample versus non-cancer sample), those listed in Table 1 or 2, have application in the determination of the status of the head-and-neck cell or tissue and in the detection of a head-and-neck disease such as head-and-neck cancer. Thus, the markers can be used for diagnosis, monitoring (i.e., monitoring progression), prognosis, or classification of a head-and-neck disease (e.g., head-and-neck cancer), HNSCC or related conditions or as markers before surgery or after relapse. The invention also contemplates methods for assessing the status of a head-and-neck tissue.
Up-regulated OPL markers listed in Table 6 (in OPL sample versus normal sample), those listed in Table 6 or Table 7, have application in the determination of the status or phase of the head-and-neck/oral cell or tissue and in the detection of a head-and-neck disease such as oral leukoplakia with hyperplasia or dysplasia or head-and-neck cancer. Thus, the markers can be used for diagnosis, monitoring (i.e., monitoring progression), prognosis, or classification of a head-and-neck disease (e.g., oral leukoplakia with hyperplasia or dysplasia or OPLs), HNSCC or related conditions or as markers before surgery or after relapse. The invention also contemplates methods for assessing the status of a head-and-neck tissue.
In an aspect, a method is provided for characterizing a head-and-neck tissue by detecting OPL markers/head-and-neck cancer markers associated with a head-and-neck tissue stage or phase, or head-and-neck disease in a subject including:

    (a) obtaining a sample from a subject;
    (b) detecting or identifying in the sample OPL markers/head-and-neck cancer markers; and
    (c) comparing the detected amount with an amount detected for a standard.


In an embodiment of the invention, a method is provided for detecting OPL markers or head-and-neck cancer markers associated with OPL or head-and-neck cancer in a patient including:

    (a) obtaining a sample from a patient;
    (b) detecting in the sample OPL markers or head-and-neck cancer markers; and
    (c) comparing the detected amount with an amount detected for a standard.


The term “detect” or “detecting” includes assaying, imaging or otherwise establishing the presence or absence of the target OPL markers or head-and-neck cancer markers, subunits thereof, or combinations of reagent bound targets, and the like, or assaying for, imaging, ascertaining, establishing, or otherwise determining one or more factual characteristics of a head-and-neck tissue phase or head-and-neck disease including OPL, cancer, metastasis, stage, or similar conditions. The term encompasses diagnostic, prognostic, and monitoring applications for the OPL markers or head-and-neck cancer markers.
The invention also provides a method of assessing whether a patient is afflicted with or has a pre-disposition for head-and-neck disease, in particular OPL or head-and-neck cancer, the method including comparing:

    (a) levels of OPL or head-and-neck cancer markers
    (b) or head-and-neck cancer markers associated with the head-and-neck disease in a sample from the patient; and
    (c) normal levels of OPL or head-and-neck cancer markers
    (d) or head-and-neck cancer markers associated with the head-and-neck disease in samples of the same type obtained from control patients not afflicted with the disease, wherein altered levels of the OPL or head-and-neck cancer markers relative to the corresponding normal levels of OPL or head-and-neck cancer markers is an indication that the patient is afflicted with head-and-neck disease.


In an aspect of a method of the invention for assessing whether a patient is afflicted with or has a pre-disposition for head-and-neck cancer, higher levels of head-and-neck cancer markers (e.g., YWHAZ, stratifin, S100A7) in a sample relative to the corresponding normal levels is an indication that the patient is afflicted with head-and-neck cancer.
In an aspect of a method of the invention for assessing whether a patient is afflicted with or has a pre-disposition for OPL/head-and-neck cancer, higher levels of OPL markers (e.g., YWHAZ, stratifin, hnRNPK) in a sample relative to the corresponding normal levels is an indication that the patient is afflicted with OPL.
In another aspect of a method of the invention for assessing whether a patient is afflicted with or has a pre-disposition for head-and-neck cancer, lower levels of head-and-neck cancer markers (e.g., alpha-1-antitrypsin, KPSG lumican) in a sample relative to the corresponding normal levels is an indication that the patient is afflicted with head-and-neck cancer.
In another aspect of a method of the invention for assessing whether a patient is afflicted with or has a pre-disposition for OPL/head-and-neck cancer, lower levels of OPL/head-and-neck cancer markers (e.g., alpha-1-antitrypsin, peroxiredoxin 2) in a sample relative to the corresponding normal levels is an indication that the patient is afflicted with OPL (oral leukoplakia with dysplasia).
In a further aspect, a method for screening a subject for head-and-neck disease is provided including (a) obtaining a biological sample from a subject; (b) detecting the amount of OPL or head-and-neck cancer markers associated with the disease in said sample; and (c) comparing said amount of OPL or head-and-neck cancer markers detected to a predetermined standard, where detection of a level of OPL or head-and-neck cancer markers that differs significantly from the standard indicates head-and-neck disease.
In an embodiment, a significant difference between the levels of OPL or head-and-neck cancer marker levels in a patient and normal levels is an indication that the patient is afflicted with or has a predisposition to head-and-neck disease.
In a particular embodiment the amount of head-and-neck cancer marker(s) (e.g., prothymosin alpha, APC-binding protein EB1) detected is greater than that of a standard and is indicative of head-and-neck disease, in particular head-and-neck cancer. In another particular embodiment the amount of head-and-neck cancer marker(s) (e.g., alpha-1-antitrypsin, KPSG lumican) detected is lower than that of a standard and is indicative of head-and-neck disease, in particular head-and-neck cancer.
In a particular embodiment the amount of OPL/head-and-neck marker(s) (e.g., YWHAZ, stratifin, hnRNPK) detected is greater than that of a standard and is indicative of head-and-neck disease, in particular OPL (oral leukoplakia with hyperplasia or dysplasia)/head-and-neck cancer. In another particular embodiment the amount of OPL/head-and-neck marker(s) (e.g., alpha-1-antitrypsin, peroxiredoxin 2) detected is lower than that of a standard and is indicative of head-and-neck disease, in particular OPL/head-and-neck cancer.
In aspects of the methods of the invention, the methods are non-invasive for detecting head-and-neck disease which in turn allow for diagnosis of a variety of conditions or diseases associated with the head-and-neck.
In particular, the invention provides a non-invasive non-surgical method for detection, diagnosis or prediction of head-and-neck disease (e.g., OPL or oral leukoplakia with hyperplasia or dysplasia and head-and-neck cancer or HNSCC) in a subject including: obtaining a sample of blood, plasma, serum, urine or saliva or a tissue sample from the subject; subjecting the sample to a procedure to detect OPL markers and head-and-neck cancer markers in the blood, plasma, serum, urine, saliva or tissue; detecting, diagnosing, and predicting head-and-neck disease by comparing the levels of OPL markers and head-and-neck cancer markers to the levels of marker(s) obtained from a control subject with no head-and-neck disease.
In an embodiment, head-and-neck disease is detected, diagnosed, or predicted by determination of increased levels of markers (e.g., one or more Table 1 or 6 up-regulated markers, preferable Table 5 up-regulated markers and more preferably one or more Table 2 or 7 up-regulated markers) when compared to such levels obtained from the control.
In another embodiment, head-and-neck disease is detected, diagnosed, or predicted by determination of decreased levels of markers (e.g., one or more Table 1 or 6 down-regulated markers) when compared to such levels obtained from the control.
The invention also provides a method for assessing the aggressiveness or indolence of a head-and-neck disease in particular OPL (e.g., staging hyperplasia or dysplasia or degree of differentiation—mild dysplasia or severe dysplasia) or cancer (e.g., staging), the method including comparing:

    (a) levels of OPL or head-and-neck cancer markers or head-and-neck cancer markers associated with the head-and-neck disease in a patient sample; and
    (b) normal levels of the OPL or head-and-neck cancer markers in a control sample.


In an embodiment, a significant difference between the levels in the sample and the normal levels is an indication that the head-and-neck disease, in particular OPL or cancer, is aggressive or indolent. In a particular embodiment, the levels of OPL or head-and-neck cancer markers are higher than normal levels. In another particular embodiment, the levels of OPL or head-and-neck cancer markers are lower than normal levels.
In an embodiment, a method is provided for diagnosing and/or monitoring OPL and HNSCC including comparing:

    (a) levels of YWHAZ in a sample from the patient; and
    (b) normal levels of YWHAZ in samples of the same type obtained from control patients not afflicted with OPL or head-and-neck cancer or having a different stage of OPL or head-and-neck cancer, wherein altered levels of YWHAZ compared with the corresponding normal levels is an indication that the patient is afflicted with OPL or HNSCC.


In an embodiment, a method is provided for diagnosing and/or monitoring OPL or HNSCC including comparing:

    (a) levels of S100A7 in a sample from the patient; and
    (b) normal levels of S100A7 in samples of the same type obtained from control patients not afflicted with head-and-neck cancer or having a different stage of head-and-neck cancer, wherein altered levels of S100A7 compared with the corresponding normal levels is an indication that the patient is afflicted with HNSCC.


In an embodiment, a method is provided for diagnosing and/or monitoring oral leukoplakia with hyperplasia or dysplasia (OPL)/HNSCC including comparing:

    (a) levels of hnRNPK in a sample from the patient; and
    (b) normal levels of hnRNPK in samples of the same type obtained from control patients not afflicted with leukoplakia with hyperplasia or dysplasia (OPL)/head-and-neck cancer or having a different stage of leukoplakia with hyperplasia or dysplasia (OPL) or head-and-neck cancer, wherein altered levels of hnRNPK compared with the corresponding normal levels is an indication that the patient is afflicted with leukoplakia with hyperplasia or dysplasia (OPL)/HNSCC.


In an embodiment, a method is provided for diagnosing and/or monitoring HNSCC and leukoplakia with hyperplasia or dysplasia (OPL) including comparing

    (a) levels of stratifin in a sample from the patient; and
    (b) normal levels of stratifin in samples of the same type obtained from control patients not afflicted with head-and-neck cancer or leukoplakia with hyperplasia or dysplasia (OPL) or having a different stage of leukoplakia with hyperplasia or dysplasia (OPL) or head-and-neck cancer, wherein altered levels of stratifin compared with the corresponding normal levels is an indication that the patient is afflicted with HNSCC.


In an aspect, the invention provides a method for determining whether a cancer has metastasized or is likely to metastasize in the future, the method including comparing:

    (a) levels of OPL or head-and-neck cancer markers or head-and-neck cancer markers in a patient sample; and
    (b) normal levels (or non-metastatic levels) of the OPL or head-and-neck cancer markers in a control sample.


In an embodiment, a significant difference between the levels in the patient sample and the normal levels is an indication that the cancer has metastasized or is likely to metastasize in the future.
In another aspect, the invention provides a method for monitoring the progression of head-and-neck disease, in particular OPL or head-and-neck cancer in a patient the method including:

    (a) detecting OPL or head-and-neck cancer markers associated with the disease in a sample from the patient at a first time point;
    (b) repeating step (a) at a subsequent point in time; and
    (c) comparing the levels detected in (a) and (b), thereby monitoring the progression of the head-and-neck disease.


The invention contemplates a method for determining the effect of an environmental factor on the head-and-neck tissue, or head-and-neck disease including comparing OPL or head-and-neck cancer markers in the presence and absence of the environmental factor.
The invention also provides a method for assessing the potential efficacy of a test agent for inhibiting head-and-neck disease, and a method of selecting an agent for inhibiting head-and-neck disease.
The invention contemplates a method of assessing the potential of a test compound to contribute to a head-and-neck disease including:

    (a) maintaining separate aliquots of head-and-neck diseased cells in the presence and absence of the test compound; and
    (b) comparing the levels of OPL or head-and-neck cancer markers associated with the disease in each of the aliquots.


A significant difference between the levels of OPL or head-and-neck cancer markers in an aliquot maintained in the presence of (or exposed to) the test compound relative to the aliquot maintained in the absence of the test compound, indicates that the test compound potentially contributes to head-and-neck disease.
The invention further relates to a method of assessing the efficacy of a therapy for inhibiting head-and-neck disease in a patient. A method of the invention includes comparing: (a) levels of OPL or head-and-neck cancer markers associated with disease in a first sample from the patient obtained from the patient prior to providing at least a portion of the therapy to the patient; and (b) levels of OPL or head-and-neck cancer markers associated with disease in a second sample obtained from the patient following therapy.
In an embodiment, a significant difference between the levels of OPL or head-and-neck cancer markers in the second sample relative to the first sample is an indication that the therapy is efficacious for inhibiting head-and-neck disease.
In a particular embodiment, the method is used to assess the efficacy of a therapy for inhibiting head-and-neck disease (e.g., OPL or head-and-neck cancer), where lower levels of OPL or head-and-neck cancer markers in the second sample relative to the first sample, is an indication that the therapy is efficacious for inhibiting the disease.
The “therapy” may be any therapy for treating head-and-neck disease, in particular OPL or head-and-neck cancer, including but not limited to therapeutics, radiation, immunotherapy, gene therapy, and surgical removal of tissue. Therefore, the method can be used to evaluate a patient before, during, and after therapy.
Certain methods of the invention employ binding agents (e.g., antibodies) that specifically recognize OPL or head-and-neck cancer markers.
In an embodiment, the invention provides methods for determining the presence or absence of head-and-neck disease, in particular OPL or head-and-neck cancer, in a patient, including the steps of (a) contacting a biological sample obtained from a patient with one or more binding agent that specifically binds to one or more OPL or head-and-neck cancer markers associated with the disease; and (b) detecting in the sample an amount of marker that binds to the binding agent, relative to a predetermined standard or cut-off value (e.g., a control), thereby determining the presence or absence of head-and-neck disease in the patient.
In another embodiment, the invention relates to a method for diagnosing and monitoring a head-and-neck disease, in particular OPL or head-and-neck cancer, in a subject by quantifying one or more OPL or head-and-neck cancer markers associated with the disease in a biological sample from the subject including (a) reacting the biological sample with one or more binding agent specific for the OPL or head-and-neck cancer markers (e.g., an antibody) that are directly or indirectly labelled with a detectable substance; and (b) detecting the detectable substance.
In another aspect the invention provides a method of using an antibody to detect expression of one or more head-and-neck marker in a sample, the method including: (a) combining antibodies specific for one or more head-and-neck marker with a sample under conditions which allow the formation of antibody:marker complexes; and (b) detecting complex formation, wherein complex formation indicates expression of the marker in the sample. Expression may be compared with standards and is diagnostic of a head-and-neck disease, in particular OPL or HNSCC.
Embodiments of the methods of the invention involve (a) reacting a biological sample from a subject with antibodies specific for one or more OPL or head-and-neck cancer markers which are directly or indirectly labelled with an enzyme; (b) adding a substrate for the enzyme wherein the substrate is selected so that the substrate, or a reaction product of the enzyme and substrate forms fluorescent complexes; (c) quantifying one or more OPL or head-and-neck cancer markers in the sample by measuring fluorescence of the fluorescent complexes; and (d) comparing the quantified levels to levels obtained for other samples from the subject patient, or control subjects.
In another embodiment the quantified levels are compared to levels quantified for control subjects (e.g., normal or benign) without a head-and-neck disease (e.g., OPL or cancer) wherein an increase in head-and-neck marker levels compared with the control subjects is indicative of head-and-neck disease.
In a further embodiment the quantified levels are compared to levels quantified for control subjects (e.g., normal or benign) without a head-and-neck disease (e.g., OPL or cancer) wherein a decrease in head-and-neck marker levels compared with the control subjects is indicative of head-and-neck disease.
A particular embodiment of the invention includes the following steps

    (a) incubating a biological sample with first antibodies specific for one or more OPL or head-and-neck cancer markers which are directly or indirectly labelled with a detectable substance, and second antibodies specific for one or more head-and-neck cancer markers which are immobilized;
    (b) detecting the detectable substance thereby quantifying OPL or head-and-neck cancer markers in the biological sample; and
    (c) comparing the quantified OPL or head-and-neck cancer markers with levels for a predetermined standard.


The standard may correspond to levels quantified for samples from control subjects without OPL or head-and-neck cancer (normal or benign), with a different disease stage, or from other samples of the subject. In an embodiment, increased levels of OPL or head-and-neck cancer markers as compared to the standard may be indicative of head-and-neck precancer or cancer. In another embodiment, lower levels of OPL or head-and-neck cancer markers as compared to a standard may be indicative of head-and-neck precancer or cancer.
OPL or HNSCC marker levels can be determined by constructing an antibody microarray in which binding sites include immobilized, preferably monoclonal, antibodies specific to a substantial fraction of marker-derived OPL or HNSCC marker proteins of interest.
The invention also relates to kits for carrying out the methods of the invention. In an embodiment, a kit is for assessing whether a patient is afflicted with a head-and-neck disease (e.g., or leukoplakia with hyperplasia or dysplasia (OPL) or head-and-neck cancer or HNSCC or related conditions) and it includes reagents for assessing one or more head-and-neck cancer markers.
The invention also provides a diagnostic composition including an OPL or HNSCC marker. A composition is also provided including an antibody specific for OPL or HNSCC markers or a fragment thereof. The antibodies can be labeled with a detectable substance.
Still further the invention relates to therapeutic applications for head-and-neck diseases, in particular OPL or head-and-neck cancer, employing OPL or head-and-neck cancer markers, and/or binding agents for the markers.
In an aspect, the invention provides antibodies specific for OPL or HNSCC markers associated with a disease (e.g., leukoplakia with hyperplasia or dysplasia or HNSCC) that can be used therapeutically to destroy or inhibit the disease (e.g., the growth of OPL or HNSCC marker expressing cancer cells), or to block OPL or HNSCC marker activity associated with a disease. In an aspect, OPL or HNSCC markers may be used in various immunotherapeutic methods to promote immune-mediated destruction or growth inhibition of tumors expressing OPL or HNSCC markers.
The invention contemplates the methods and kits described herein using additional markers associated with a head-and-neck disease (e.g., OPL or head-and-neck cancer, HNSCCm or related conditions). The methods described herein may be modified by including reagents to detect the additional markers.
In particular, the invention contemplates the methods described herein using multiple markers for OPL or HNSCC cancer. Therefore, the invention contemplates a method for analyzing a biological sample for the presence of OPL or HNSCC markers, and other markers that are specific indicators of cancer, in particular head-and-neck cancer. The methods described herein may be modified by including reagents to detect the additional markers, or nucleic acids for the additional markers.
In embodiments of the invention the methods and kits use one or more of the markers listed in Table 5, in particular those listed in Table 2 and Table 7. In another embodiment, the method uses a panel of markers selected from the markers listed in Table 5, and in one embodiment of those listed in Table 2 and Table 7 in particular a panel including two, three or four or more of the markers in Table 5.
In an aspect, the present invention provides a method for diagnosing an increased risk for development of oral cancer in a subject having oral dysplasia. The method comprises measuring the level of S100A7 in a biological sample from the subject; and comparing the level of S100A7 in the biological sample with the level of S100A7 in a control, wherein a measured level of S100A7 higher than the control level is indicative of an increased risk for developing oral cancer. In some embodiments of this aspect, the biological sample comprises epithelial cells. In some embodiments, the biological sample is a cytosmear. In preferred embodiments, the epithelial cells are dysplastic.
In some embodiments of the invention, the control level is the level of S100A7 in a biological sample comprising dysplastic epithelial cells known not to progress to oral cancer for at least 3.5 years following measurement of the control level. In some embodiments, the biological sample known not to progress to cancer is known not to progress to cancer for at least 10 years following measurement of the control level.
In another aspect, the present invention provides a method for diagnosing an increased risk for development of oral cancer in a subject having oral dysplasia, the method comprising measuring the level of nuclear PTMA in a biological sample from the subject. In some embodiments, the measured level of nuclear PTMA is compared to the level of nuclear PTMA in a control. In some embodiments, a measured level of nuclear PTMA higher than the control level is indicative of an increased risk for developing oral cancer.
In some embodiments, the method further comprises measuring the level of cytoplasmic S100A7 in a biological sample from the subject; and comparing the level of cytoplasmic S100A7 in the biological sample with the level of cytoplasmic S100A7 in a control. In some embodiments, a measured level of cytoplasmic S100A7 higher than the control level is indicative of an increased risk for developing oral cancer.
In some embodiments of this aspect, the biological sample comprises epithelial cells. In some embodiments, the biological sample is a cytosmear. In some embodiments, the epithelial cells are dysplastic. In some embodiments, the control is a biological sample comprising dysplastic epithelial cells known not to progress to oral cancer for at least 3.5 years following measurement of the control level. In some embodiments, the biological sample known not to progress to cancer is known not to progress to cancer for at least 10 years following measurement of the control level.
In some embodiments of this aspect, the method further comprises measuring the degree of dysplasia in the biological sample obtained from the subject, wherein a moderate or severe degree of dysplasia is indicative of an increased risk for developing oral cancer relative to a corresponding control sample having a mild degree of dysplasia.
Other objects, features and advantages of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples while indicating preferred embodiments of the invention are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.
BRIEF DESCRIPTION OF THE TABLES AND DRAWINGS
Tables
Table 1. iTRAQ ratios for HNSCC and non-cancerous head-and-neck tissue samples. HNSCC samples (C1-05, cancer of the buccal mucosa; C6-C10, cancer of the tongue), non-paired non-cancerous samples (N1, N4, N5), and paired non-cancerous samples (N2, N3) versus the pooled non-paired non-cancerous control. Grey boxes, not detected; NQ, not quantified; 9999, no expression observed in the pooled sample
Table 2. Receiver-operating characteristics from the iTRAQ ratios of a panel of three best-performing biomarkers-YWHAZ, stratifin, and S100A7-individually and as a panel.
Table 3. Receiver-operating characteristics from the IHC scores of a panel of three best-performing biomarkers-YWHAZ, stratifin, and S100A7-individually and as a panel.
Table 4. Comparison of receiver-operating characteristics from the iTRAQ ratios of the panel of three best-performing biomarkers. Non-paired non-cancerous tissues give better sensitivity and specificity as comparators than do paired non-cancerous tissues.
Table 5. Differentially-expressed proteins not previously described in OPLs and head-and-neck malignancies and cancer.
Table 6. Average iTRAQ ratios for OPLs and histologically-normal control oral tissue samples. Ratios are from the comparison between OPLs (D1-D6) and the pooled normal sample, and the comparison between histologically-normal oral tissues (N1-N3) and the pooled normal sample. N4-N6 are histologically-normal oral tissues analyzed in an earlier iTRAQ analysis using the same pooled normal control to demonstrate consistent iTRAQ ratios in different experiments analyzed over different time periods. ND, not detected; NQ, not quantified
Table 7. Receiver-operating characteristics from (A) the iTRAQ ratios and (B) IHC scores of a panel of three best-performing biomarkers-YWHAZ, stratifin, and hnRNPK-individually and as a panel.
Table 8. Analysis of Stratifin and YWHAZ in HNOSCCs: correlation with clinicopathological parameters.
Table 9a. Analysis of overexpression of hnRNPK protein in oral lesions and correlation with clinicopathological parameters.
Table 9b. Biomarker analysis of hnRNPK (nuclear/cytoplasmic) in oral lesions.
Table 10. Alternate accession numbers for OPL proteins.
Table 11. Peptide sequences and coverage for HNSCC and OPL.
Table 12. Clinicopathological parameters of patients with oral premalignant lesions (OPLs).
Table 13. Antibodies used for immunohistochemistry and Western Blotting: sources and dilutions.
Table 14. RT-PCR analysis primers and PCR conditions.
Table 15. Molecules identified in the Networks and their cellular functions.
Table 16. Analysis of clinical parameters with transformation potential of Oral Dysplasia patients.
Table 17. Correlation of candidate protein markers expression with transformation in Oral Dysplasia patients.
Table 18. Evaluation of association of degree of dysplasia with candidate protein markers expression.
Table 19. Evaluation of correlation between p16 expression and protein markers.
Table 20. Evaluation of clinical parameters and S100A7 overexpression for determining oral cancer free survival (OCFS) in dysplasia patients.
Table 21: Multivariate Cox Regression analysis of cytoplasmic S100A7, nuclear PTMA and degree of dysplasia in patients having oral dysplastic lesions.



FIGURES
FIG. 1 provides a flow diagram for online 2D LC-MS/MS analysis. In position 1, ports 1-2, 3-4, 5-6, 7-8, and 9-10 are connected; in position 2, ports 2-3, 4-5, 6-7, 8-9, and 10-1 are connected. In the diagram, the valves are shown at the initial (Time=0 min) positions.
FIG. 2 shows a receiver-operating-characteristic curves of a panel of three best-performing biomarkers, YWHAZ, stratifin, and S100A7: (a) iTRAQ ratios, and (b) IHC scores.
FIG. 3 presents an immunohistochemical verification of iTRAQ-discovered potential cancer markers, YWHAZ, stratifin, and S100A7 in HNSCCs and non-cancerous head-and-neck tissues. Positive staining is brown and is intense in HNSCCs. The left panel shows the noncancerous (histologically normal) tissues and the right panel depicts the HNSCC tissue sections. Panel A: the HNSCC sample shows intense cytoplasmic and nuclear staining for YWHAZ, while the normal mucosa shows no detectable immunostaining. Panel B: the HNSCC tissue section shows cytoplasmic staining for stratifin in tumor cells, while the normal mucosa shows no detectable immunostaining. Panel C: the HNSCC tissue section shows intense cytoplasmic staining for S100A7 in tumor cells, while the normal mucosa shows no detectable immunoreactivity. All panels show ×200 magnifications.
FIG. 4 depicts Western blot analyses of YWHAZ, Stratifin and S100A7 in HNSCCs and paired noncancerous head-and-neck tissues. Equal amounts of protein lysates from HNSCCs and paired non-cancerous head-and-neck tissues were employed. See the text for details. The Panels show increased expression of (i) YWHAZ, (ii) stratifin, and (iii) S100A7 in HNSCCs (C1-C3) as compared to paired non-cancerous head-and-neck tissues (N1-N3). Alpha-tubulin (Panel 4) was used as the loading control.
FIG. 5 shows RT-PCR analyses of YWHAZ, stratifin, and S100A7 in HNSCCs and non-cancerous head-and-neck tissues: Panel (i) shows increased levels of YWHAZ transcripts in HNSCCs (C1-C3) as compared to the non-cancerous head-and-neck tissues that show basal levels (N2 and N3) and no detectable level (N1) of YWHAZ transcripts. Panel (ii) shows increased levels of stratifin transcripts in HNSCCs (C1-C3) as compared to the non-cancerous head-and-neck tissues that show basal level (N3) and no detectable level (N1 and N2) of stratifin transcripts. Panel (iii) shows increased levels of S100A7 transcripts in HNSCCs (C1-C3) as compared to the non-cancerous head-and-neck tissues that show basal level (N3) and no detectable level (N1 and N2) of S100A7 transcripts. β-Actin (Panel iv) was used as a control for normalizing the quantity of RNA used.
FIG. 6 provides receiver-operating-characteristic curves of a panel of three best-performing biomarkers, YWHAZ, stratifin, and hnRNPK: (A) iTRAQ ratios, and (B) IHC scores.
FIG. 7 presents an immunohistochemical verification of iTRAQ-discovered potential biomarkers, YWHAZ, stratifin, hnRNPK, S100A7, and PTHA in OPLs and histologically normal oral tissues. Verification of the panel of these 5 potential biomarkers was carried out using an independent set of 30 OPLs and 21 histological normal oral tissues. Representative photomicrographs are shown here. Positive staining is brown and is intense in OPLs. The upper panel shows the normal tissues and the lower panel the OPL tissue sections. Panel A: the OPL sample shows intense cytoplasmic and nuclear staining for YWHAZ, while the normal mucosa shows no detectable immunostaining. Panel B: the OPL tissue section exhibits cytoplasmic staining for stratifin in epithelial cells, while the normal mucosa shows no detectable immunostaining. Panel C: the OPL tissue section shows nuclear staining for hnRNPK in epithelial cells, while no detectable immunostaining is evident in the normal mucosa. Panel D: the OPL sample shows intense cytoplasmic staining for S100A7 in epithelial cells, while the normal mucosa displays no detectable immunoreactivity. Panel E: the OPL sample exhibits intense nuclear staining for PTHA in epithelial cells, while no detectable immunostaining is evident in the normal sample. All panels show ×100 magnifications.
FIG. 8A illustrates Western blot analyses of YWHAZ, stratifin, hnRNPK, S100A7 and PTHA in representative OPLs and histologically normal oral tissues. The OPLs and histologically normal oral tissues (n=3) were selected randomly from the same cohort of tissues as used for IHC analysis and the results shown are representative of 3 independent experiments. Equal amounts of protein lysates from OPLs (D1-D3) and histologically normal oral tissues (N1-N3) were used. The panels show increased expression of (i) YWHAZ, (ii) stratifin, (iii) hnRNPK, (iv) S100A7, and (v) PTHA in OPLs (D1-D3) as compared to the histologically normal oral tissues (N1-N3). α-tubulin (Panel (vi)) was used as the loading control.
FIG. 8B depicts RT-PCR analyses of YWHAZ, stratifin, hnRNPK, S100A7, and PTHA in representative OPLs and histologically normal oral tissues selected randomly, as used for IHC and Western blot analysis and the results shown are representative of 3 independent experiments: Panel (i) shows increased levels of YWHAZ transcripts in OPLs (D1-D3) as compared to the histologically normal oral tissues (N1-N3) that did not show detectable levels of YWHAZ transcripts. Panel (ii) demonstrates increased levels of stratifin transcripts in OPLs (D1-D3) as compared to the histologically normal oral tissues (N1-N3) that show basal level (N1) and no detectable level (N2 and N3) of stratifin transcripts. Panel (iii) shows increased levels of hnRNPK transcripts in OPLs (D1-D3) as compared to the histologically normal oral tissues (N1-N3), in which no detectable levels of hnRNPK transcripts are evident. Panel (iv) exhibits increased levels of S100A7 transcripts in OPLs (D1-D3) as compared to no detectable levels in the histologically normal oral tissues (N1-N3). Panel (v) shows increased levels of PTHA transcripts in OPLs (D1-D3) as compared to the histologically normal oral tissues (N1-N3) in which no detectable levels of PTHA transcripts are evident. β-Actin (Panel iv) was used as a control for normalizing the quantity of RNA used.
FIG. 8C shows network analysis using ingenuity pathways analysis (IPA) software. Differentially expressed proteins identified in OPLs in comparison with normal oral tissues were analyzed using the IPA software. Network analysis classified proteins into 2 networks on the basis of function cited previously in literature. Above panel shows merged network of the pathways identified using IPA software. Bold lines (—) show direct interactions/regulation while dashed lines (---) show indirect interactions/regulation of proteins at the ends of line. Proteins shown in red color are upregulated and in green color are down-regulated in OPLs in comparison with normal tissues.
FIGS. 9A and 9B illustrate identification of stratifin (9A) and YWHAZ (9B) in HNOSCCs by mass spectrometry. The peptides for which MS/MS spectra are shown are colored red and in a larger font. Those that are common between stratifin and YWHAZ are shown in purple. Other peptides observed are in blue. The matched b ions are shown in green, and the matched y ions in red.
FIG. 10 provides an immunohistochemical analysis of stratifin in head-and-neck cancer tissues. Paraffin-embedded HNOSCC tissue sections and non-malignant mucosa were stained using anti-stratifin antibody (all ×100 magnifications): Panel a shows normal oral mucosa with no detectable stratifin immunostaining; Panel b shows HNOSCC with strong cytoplasmic and nuclear stratifin immunostaining in the tumor cells; Panel c shows HNOSCC negative control with lack of staining in the tumor cells.
FIG. 11 shows a box-plot analysis. The box plot shows distribution of total scores of stratifin in HNOSCCs and non-malignant head-and-neck tissues.
FIG. 12 sets forth a co-immunoprecipitation assay and Western blot analysis. Immunoprecipitation assays of stratifin, YWHAZ, NFκB, Bcl-2, and β-catenin proteins were carried out using specific antibodies in head-and-neck cancer cells, HSC2. FIG. 12a shows immunoblot analysis for stratifin, demonstrating the binding of stratifin with YWHAZ, NFκB, Bcl-2, and β-catenin, and the lack of binding in the negative control. Similarly, reverse immunoprecipitation assays were carried out using specific antibodies for YWHAZ, NFκB, Bcl-2, and β-catenin. FIG. 12b shows immunoblot analysis for: (i) YWHAZ, (ii) NFκB, (iii) Bcl-2, and (iv) β-catenin confirming the binding of these proteins with stratifin.
FIG. 13 illustrates a Kaplan-Meier estimation of cumulative proportion of disease-free survival: 13a, stratifin protein expression; the median time for disease-free survival (no recurrence/metastasis) in patients with stratifin-positive tumors was 19 months, whereas in those with stratifin-negative tumors it was 38 months (p=0.06). 13b, YWHAZ protein expression; the median time for disease-free survival (no recurrence/metastasis) in patients with YWHAZ-positive tumors was 23 months, whereas in those with YWHAZ-negative tumors it was 35 months (p=0.08). 13c, concomitant stratifin and YWHAZ expressions; the median time for disease-free survival of patients with HNOSCCs showing concomitant expressions of stratifin and YWHAZ (Stratifin+/YWHAZ+) was 13 months, as compared to patients with tumors that did not show increased expression of either of these proteins with the median time for disease-free survival being 38 months (p=0.019).
FIG. 14 shows an immunohistochemical analysis of hnRNPK in head-and-neck cancer tissues. Paraffin-embedded sections of histologically normal mucosa, leukoplakia with no evidence of dysplasia or with dysplasia and HNOSCCs were stained using anti-hnRNPK monoclonal antibody as described herein. (a) Normal oral mucosa with no detectable hnRNPK immunostaining. (b) Leukoplakic lesion with no dysplasia showing nuclear hnRNPK immunostaining. (c) Leukoplakic lesion with no dysplasia showing nuclear and cytoplasmic hnRNPK immunostaining. (d) Dysplasia depicting nuclear hnRNPK immunostaining in epithelial cells. (e) Dysplasia depicting nuclear and cytoplasmic hnRNPK immunostaining in epithelial cells. (f) HNOSCC section illustrating only nuclear hnRNPK immunostaining in the tumor cells. (g) HNOSCC section showing both cytoplasmic and nuclear staining in tumor cells. (h) HNOSCC section showing no immunostaining in tumor cells for hnRNPK protein serving as a negative control. Arrow shows nuclear staining of hnRNPK in panels b, d, and f, and nuclear and cytoplasmic staining in panel c, e, and g. a-h, original magnification×200
FIG. 15 presents receiver-operating characteristic curves of hnRNPK (nuclear/cytoplasmic) in (a) normal vs. leukoplakia with no evidence of dysplasia; (b) normal vs. dysplasia; and (c) normal vs. HNOSCCs. Bold line shows ROC analysis for nuclear hnRNPK. Dashed line shows ROC analysis for cytoplasmic hnRNPK.
FIG. 16 depicts an evaluation of hnRNPK expression (nuclear/cytoplasmic) as a biomarker for risk prediction of oral leukoplakia and prognosis of HNOSCCs. The figure shows estimated (a) positive predictive value (PPV) and (b) negative predictive value (NPV) for nuclear/cytoplasmic hnRNPK expression as prognostic biomarkers for disease progression of leukoplakia. Panels c and d show PPV and NPV for recurrence in HNOSCC patients, respectively.
FIG. 17 illustrates a Kaplan-Meier estimation of cumulative proportion of disease-free survival showing: (a) significantly reduced time for disease progression (p<0.001; median time=17 months) in leukoplakia patients showing increased cytoplasmic expression of hnRNPK as compared to median time of 35 months in the patients showing no/faint immunostaining of hnRNPK in cytoplasm; (b) median time for disease progression (34 months) was observed in leukoplakia patients showing intense nuclear expression of hnRNPK (n=78) as compared to patients who did not show increased nuclear hnRNPK; and (c) Median time for disease-free survival (no recurrence/metastasis) in HNOSCC patients showing cytoplasmic immunostaining of hnRNPK was 11 months, whereas in those patients showing no/faint hnRNPK-immunostaining in cytoplasm it was 41 months (p=0.004). In patients showing increased nuclear expression disease (d), free survival was 14 months as compared to HNOSCCs that showed mild or moderate nuclear immunostaining (median disease-free survival=57 months, p=0.07).
FIG. 18 depicts validation of hnRNPK expression in oral lesions. (a) Western blot analysis of hnRNPK in normal mucosa, leukoplakia and HNOSCC tissues. Equal amount of protein lysates from these tissues were electrophoresced on 12% SDS-PAGE and transferred to PVDF membrane. The membrane was incubated with respective primary antibodies and secondary antibodies as described herein, and the signal detected by enhanced chemiluminescence method. Panel (a) shows increased expression of hnRNPK in leukoplakia (L) and HNOSCCs (T) as compared to paired non-malignant head-and-neck tissues (N). Actin was used as control for equal loading of protein in SDS-PAGE (lower panel). (b) RT-PCR analysis of hnRNPK in normal mucosa, leukoplakia and HNOSCC tissues. Panel shows increased levels of hnRNPK transcripts in leukoplakia (L) and HNOSCCs (T) as compared to the non-malignant head-and-neck tissues that showed basal levels (N) of hnRNPK transcripts. β-actin, used as a control to normalize the quantity of RNA used for each RT-PCR reaction, is shown in the lower panel.
FIG. 19A-E presents CID spectra of the single-peptide identifications in the HNSCC and OPL.
FIG. 20 illustrates negative and positive controls for IHC in OPLs.
FIGS. 21A and 21B depict CID spectra of two peptides, A: DLAGSIIGK (SEQ ID NO: 368) and B: IDEPLEGSEDR (SEQ ID NO: 369), identified from hnRNPK in iTRAQ-labeled oral leukoplakia with dysplasia.
FIG. 22 sets forth a Kaplan-Meier analysis of OPLs with no evidence of dysplasia showing overexpression of hnRNPK.
FIG. 23 depicts immunohistochemical analysis of five candidate markers in oral lesions with dysplasia. Immunohistochemistry was carried out in tissue sections from oral lesions with dysplasia using specific antibodies for S100A7, prothymosin alpha (PTMA), 14-3-3ζ, 14-3-3σ and heterogeneous nuclear ribonucleoprotein K (hnRNP K) as described in Materials and Methods. Panel shows cytoplasmic and/or nuclear immunostaining of (i) S100A7; (ii) PTMA; (iii) 14-3-3ζ and (iv) 14-3-3σ in (a) mild; (b) moderate and (c) severe dysplasia. Panel (v) shows nuclear hnRNP K in (a) mild; (b) moderate and (c) severe dysplasia; No detectable cytoplasmic expression of hnRNPK was observed in dysplasia sections used in this study. Arrows show cytoplasmic (C) or nuclear (N) staining in cells (Original magnification×200).
FIG. 24 depicts analysis of p16 and HPV 16/18 status in oral lesions with dysplasia. (A) Nuclear immunostaining of nuclear p16 in (i) mild; (ii) moderate and (iii) severe dysplasia; No detectable cytoplasmic expression of p16 was observed in dysplasia sections used in this study. Arrows show nuclear (N) staining in cells (original magnification×200); (B) (i) a representative dysplasia section showing no staining for HPV 16/18; (ii) dysplasia section used as a negative control; (iii) cervical cancer tissue section showing positive staining for HPV16/18 in epithelial cells and (iv) dysplasia section used as positive control showing integrity of genomic DNA in tissue sections Arrow shows presence of HPV 16/18 in epithelial cells in cervical cancer section (original magnification×200).
FIG. 25 depicts Kaplan-Meier survival analysis for evaluation of oral cancer-free survival (OCFS). Kaplan-Meier survival curves for (A) cytoplasmic S100A7 expression showing reduced OCFS (p=0.007) and (B) nuclear S100A7 expression (p=0.041).
FIG. 26 depicts Kaplan-Meier survival analysis for evaluation of oral cancer-free survival (OCFS). Kaplan-Meier survival curves for mild, moderate and severe dysplasia. Patients with moderate dysplasia demonstrated low mean OCFS=58.59 months (p=0.004) while in severe dysplasia cases, patients showed mean OCFS=38.9 months, (p<0.001) as compared to mild dysplasia (mean OCFS=116.25 months).
FIG. 27 depicts Kaplan-Meier survival analysis for evaluation of S100A7 overexpression with degree of dysplasia. Kaplan-Meier survival curves for S100A7 overexpression in (i) cytoplasm and (ii) nucleus in (a) mild dysplasia, (b) moderate dysplasia and (c) severe dysplasia.
FIG. 28 depicts positive and negative predictive values for time to malignant transformation. (a) Positive Predictive Values [PPV(t)] for time to malignant transformation for 39 oral dysplasia patients with S100A7 expression and for all 110 dysplasia patients with survival data (overall); (b) Negative Predictive Values [NPV(t)] for time to malignant transformation for 39 patients with S100A7 overexpression, and for all 110 patients (overall).
FIG. 29 depicts representative photomicrographs of S100A7 immunostaining in cytosmears. (a) stained oral epithelial cells obtained by scraping a patient's oral lesion; (b) stained oral cancer cells (positive control); (c) stained oral cancer cells (negative control); and (d) stained oral squamous cell carcinoma cells, depicting S100A7 immunostaining in both cytoplasm and nuclei.
FIG. 30 depicts Kaplan-Meier survival analysis for evaluation of PTMA and S100A7 intensity scores with oral cancer free survival time in months. A. Kaplan-Meier survival curves for PTMA nuclear intensity scores (low and high). B. Kaplan-Meier survival curves for PTMA nuclear intensity scores (low and high) in combination with S100A7 cytoplasmic intensity scores.
FIGS. 31a and b depict Kaplan-Meier survival analyses of combination of cytoplasmic S100A7, nuclear PTMA and degree of dysplasia.



DETAILED DESCRIPTION OF THE INVENTION
Multidimensional liquid chromatography-mass spectrometry (LC-MS/MS) has been used for the analysis of biological samples labeled with isobaric mass tags (iTRAQ) to identify proteins that are differentially expressed in human head-and-neck squamous-cell carcinomas (HNSCCs) in relation to non-cancerous head-and-neck tissues (control) for cancer biomarker discovery. Fifteen individual samples (cancer and non-cancerous tissues) were compared against a pooled non-cancerous control (prepared by pooling equal amounts of proteins from six noncancerous tissues) in five sets by online and offline separation. Eight hundred and eleven (811) non-redundant proteins in HNSCCs were identified, including structural proteins, signaling components, enzymes, receptors, transcription factors and chaperones.
A panel of proteins showing consistent differential expression in HNSCC relative to the non-cancerous controls was discovered. Some of the proteins include stratifin (14-3-3 sigma), YWHAZ (14-3-3 zeta), three calcium-binding proteins of the 5100 family, S100A 2, S100A 7 (psoriasin) and S100A 11 (calgizarrin), prothymosin alpha (PTMA or PTHA), L-lactate dehydrogenase A chain (LDH-A), glutathione S transferase-Pi, APC binding protein EB1, and fascin. Peroxiredoxin2, carbonic anhydrase I, flavin reductase, histone H3, and polybromo-1D (BAF180) were underexpressed in HNSCCs.
A panel of the three best performing biomarkers—YWHAZ, stratifin, and S100A7—achieved a sensitivity of 0.92 and a specificity of 0.91 in discriminating cancerous from non-cancerous head-and-neck tissues (Table 7A). Verification of differential expression of YWHAZ, stratifin and S100A7 proteins in clinical samples of HNSCCs and paired and non-paired non-cancerous tissues by immunohistochemistry (Table 7B), immunoblotting, and RT-PCR confirmed their overexpression in head-and-neck cancer. Verification of YWHAZ, stratifin and S100A7 in an independent set of HNSCCs achieved a sensitivity of 0.92 and a specificity of 0.87 in discriminating cancerous from non-cancerous head-and-neck tissues, thereby confirming their overexpressions and utility as credible cancer biomarkers.
The inventors also used iTRAQ labeling in combination with multidimensional LC-MS/MS analysis of oral leukoplakia with dysplasia (oral premalignant lesions, or OPLs) in order to compare protein profiles of OPLs and normal head-and-neck tissues. Nine individual samples (6 OPLs and 3 normal tissues) were compared against a pooled normal control (prepared by pooling equal amounts of proteins from six noncancerous tissues) in five sets by online and offline separation.
The LC-MS/MS analyses collectively resulted in identification of 459 non-redundant proteins; 216 were identified as single hits with more than 95% confidence. Of all the proteins identified, only 17 were differentially expressed in OPLs relative to normal control (observed in ≧3 out of the 6 samples and with >50% showing differential expression). Of these, 15 proteins were confidently identified with a minimum of two peptide matches in each case. Two proteins, parathymosin and DLC1 were identified by single peptides. All these 17 proteins are given in Table 6, along with two structural proteins: β-actin and gelsolin precursor as controls. The heat map in Table 6 also depicts the variations in the levels of overexpressed and underexpressed proteins in individual OPL and histological normal tissues versus the pooled normal control. These differential expression levels were averages of the replicate analyses: 56.4% of the ratios varied by less than 10% from their respective averages shown, and 82.0% varied by less than 20%.
Thirteen proteins that did not meet the aforementioned initial criteria—IGL2, P37AUF1 (HNRPD), SOD2, PKM2, ROA1HNRNPA1, HSP27, cofilin, glyceraldehyde-3-phosphate dehydrogenase, NDP kinase B, elongation factor 2, CALM3, PEBP, and S100A7—were also included in Table 5 for further analysis, as these proteins are of biological relevance in cancer development. Of these, 11 proteins were confidently identified with a minimum of two peptide matches in each case. p37AUF1 (hnRNP D) was identified by a single peptide with a confidence of 99%. SOD2 was identified by more than one unique peptides, however, the best matching peptide was identified with a confidence of 93%. Although, individually this peptide did not meet the inventors' stipulated criteria for acceptance, manual verification of the spectrum showed good sequence coverage for this peptide. Furthermore, the cumulative score which included the lower confidence peptide matches was >2.0 and corresponded with a confidence of 99%.
The best-performing proteins that can differentiate between OPLs and normal tissues were identified by determining the individual receiver-operating characteristic (ROC) curves of the proteins in Table 7. The three proteins with the highest AUC values—YWHAZ, stratifin and hnRNPK—are listed in Table 7A together with their individual and collective figures-of-merit, including sensitivity and specificity. As a panel, these three biomarkers achieved a sensitivity of 0.83 and a specificity of 0.74 in discriminating OPLs from histological normal oral tissues (Table 7A and FIG. 6A).
The panel of three potential biomarkers, YWHAZ, stratifin and hnRNPK, and two other proteins with high AUC values, S100A7 (0.56) and PTHA (0.56), were chosen for verification in an independent set of OPLs (30 cases) and normal tissues (21 cases) by IHC. Representative levels of expression and subcellular localizations of all the five proteins in oral dysplastic tissues in comparison with normal tissues are shown in FIG. 7A-E. These data were further verified by Western blot analysis (FIG. 8A) at the protein level, as well as RT-PCR analysis at the mRNA level (FIG. 8B). The differential expression suggested by iTRAQ ratios tended to be moderate, while the results of Western and RT-PCR analyses tended to show more extreme differential expression. Thus, Western and RT-PCR analyses, verified the differential expression reported by the iTRAQ analysis in trend but not in scale. This discrepancy of scale has also been noted in other studies ascribed to compression of the dynamic range of iTRAQ ratios (21). Importantly, in IHC analysis, the biomarker panel of YWHAZ, stratifin, and hnRNPK achieved a sensitivity of 0.91, specificity of 0.95, and predictive value of 0.96 (Table 7B and FIG. 7B) in discriminating OPLs from histological normal oral tissues.
To gain insight into the plausible biological processes in which these proteins might be involved, the inventors used the Ingenuity pathway analysis tools (Ingenuity Systems, Inc. software) and discovered two major networks in OPLs (FIG. 8C). The network comprised of 23 proteins identified in this study that are primarily involved in inflammation, molecular transport, cellular movement, cellular signaling, proliferation, gene expression and cancer. To the best of the inventors' knowledge, this is the first study reporting differential expressions of p37AUF1 (HNRPD) and histone H2B.1 in OPLs.
Accordingly, the inventors describe herein methods for detecting the presence of a head-and-neck disease (e.g., OPL or head-and-neck cancer) in a sample, the absence of a disease (e.g., OPL or head-and-neck cancer) in a sample, the stage or grade of the disease, and other characteristics of head-and-neck diseases that are relevant to prevention, diagnosis, characterization, and therapy of head-and-neck diseases such as OPL or cancer in a patient, for example, the benign, premalignant or malignant nature of a head-and-neck cancer, the metastatic potential of a head-and-neck cancer, assessing the histological type of neoplasm associated with a head-and-neck cancer, the indolence or aggressiveness of a leukoplakia with hyperplasia or dysplasia or head-and-neck cancer, and other characteristics of head-and-neck diseases that are relevant to prevention, diagnosis, characterization, and therapy of head-and-neck diseases such as OPL or cancer in a patient. Methods are also provided for assessing the efficacy of one or more test agents for inhibiting a head-and-neck disease, assessing the efficacy of a therapy for a head-and-neck disease, monitoring the progression of a head-and-neck disease, selecting an agent or therapy for inhibiting a head-and-neck disease, and assessing the disease (e.g., carcinogenic) potential of a test compound.
In some embodiments of the present invention, a method for diagnosing an increased risk for development of oral cancer in a subject having oral dysplasia is provided. In such a method, the level of S100A7 protein in a biological sample from the subject is measured using an assay suitable for protein detection, as set forth above.
The measured level of S100A7 in the biological sample is then compared with the level of S100A7 in a control, wherein a measured level of S100A7 higher than the control level is indicative of an increased risk or a “high” or “higher” risk for developing oral cancer. In some embodiments, the biological sample from the subject comprises oral epithelial cells. In some embodiments, the biological sample is a cytosmear. In preferred embodiments, at least some of the oral epithelial cells in the biological sample are dysplastic.
In some embodiments, the control is a biological sample comprising dysplastic epithelial cells that are known not to progress to oral cancer for at least 3.5 years following measurement of S100A7 in the control biological sample. In preferred embodiments, the biological sample known not to progress to cancer is known not to progress to cancer for at least 10 years following measurement of S100A7 in the control biological sample.
As is apparent from the foregoing embodiments, the presently disclosed methods are useful for managing the treatment of patients with potential oral cancer or with known oral cancer. For example, in some embodiments, S100A7 can be useful for screening patients to identify patients at high risk or higher risk for oral cancer. Other known methods of identifying oral cancer might not identify the same patients as being at high or higher risk for oral cancer. In this manner, only those patients with a test result indicating a high or higher probability of malignant transformation of an oral lesion can be sent on to have one or more anti-cancer therapies. Patients whose test results suggest a low probability of cancer can be re-evaluated using S100A7 during their routine follow-up.
In some aspects of the present invention, a method for diagnosing an increased risk for development of oral cancer in a subject having oral dysplasia comprising measuring the level of nuclear PTMA in a biological sample from the subject is provided. The measured level of nuclear PTMA is then compared with the level of nuclear PTMA in a control, wherein a measured level of nuclear PTMA higher than the control level is indicative of an increased risk for developing oral cancer.
In some embodiments of this aspect, the method further comprises measuring the level of cytoplasmic S100A7 in a biological sample from the subject; and comparing the level of cytoplasmic S100A7 in the biological sample with the level of cytoplasmic S100A7 in a control, wherein a measured level of cytoplasmic S100A7 higher than the control level is indicative of an increased risk for developing oral cancer.
In some embodiments of this aspect, the biological sample comprises epithelial cells. In some embodiments, the biological sample is a cytosmear. In some embodiments, the epithelial cells are dysplastic.
In some embodiments of this aspect, the control is a biological sample comprising dysplastic epithelial cells known not to progress to oral cancer for at least 3.5 years following measurement of the control level. In some embodiments, the biological sample known not to progress to cancer is known not to progress to cancer for at least 10 years following measurement of the control level.
In some embodiments of this aspect, the method further comprises measuring the degree of dysplasis in the sample obtained from the subject. In some embodiments a moderate or severe degree of dysplasia is indicative of an increased risk for developing oral cancer relative to a corresponding control sample having a mild degree of dysplasia.
In some embodiments, the presently disclosed methods comprise detecting a level of S100A7 expression in epithelial cells. In some embodiments of these methods, cytosmear can be used to obtain the epithelial cells. The cytosmear can be stained, as described herein, and examined by light microscopy to determine cytopathology and S100A7 expression levels.
Abbreviation Index.
For convenience, certain abbreviations used in the description, tables, figures, and appended claims are defined here: iTRAQ, isobaric tags for relative and absolute quantification; LC, liquid chromatography; MS/MS, tandem mass spectrometry; PCM, potential cancer marker; HNSCC, head-and-neck squamous cell carcinoma; LCM, laser capture microdissection; PBS, phosphate-buffered saline; SCX, strong cation exchange; ID, internal diameter; RP, reverse phase; IDA, information-dependent acquisition; TBS, tris-buffered saline; SFN, stratifin or 14-3-3 sigma; YWHAZ, 14-3-3 zeta; LDH-A, L-lactate dehydrogenase A; SD, standard deviation; ROC, receiver-operating characteristics; PPIA, peptidyl prolyl isomerase A; PV, predictive values; PPV, positive predictive values; PTHA, prothymosin alpha; PTMA, prothymosin appha; PKM2, pyruvate kinase isozyme M2; AUC, area under the curve; RSD, relative standard deviation; TMA, tissue microarray.
Glossary.
For convenience, certain terms employed in the specification, examples, and appended claims are collected here.
The recitation of numerical ranges by endpoints herein includes all numbers and fractions subsumed within that range (e.g., 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.90, 4, and 5). It is also to be understood that all numbers and fractions thereof are presumed to be modified by the term “about.” Furthermore, it is to be understood that “a”, “an,” and “the” include plural referents unless the content clearly dictates otherwise. Thus, for example, reference to a method comprising “a head-and-neck marker” includes two or more OPL or head-and-neck cancer markers. The term “about” means plus or minus 0.1 to 50%, 5-50%, or 10-40%, preferably 10-20%, more preferably 10% or 15%, of the number to which reference is being made.
“Head-and-neck disease” refers to any disorder, disease, condition, syndrome or combination of manifestations or symptoms recognized or diagnosed as a disorder of the head and neck, including but not limited to hyperplasia, dysplasia and cancer precursors, head-and-neck cancer or carcinoma.
“Head-and-neck cancer” or “head-and-neck carcinoma” includes malignant head-and-neck disease including but not limited to squamous cell and adenocarcinomas.
Biomarkers of head-and-neck precancers includes OPL markers including but not limited to oral leukoplakia with hyperplasia or dysplasia.
The terms “sample”, “biological sample”, and the like mean a material known or suspected of expressing or containing one or more OPL or head-and-neck cancer markers. A test sample can be used directly as obtained from the source or following a pretreatment to modify the character of the sample. The sample can be derived from any biological source, such as tissues, extracts, or cell cultures, including cells (e.g., tumor cells), cell lysates, and physiological fluids, such as, for example, whole blood, plasma, serum, saliva, ocular lens fluid, cerebral spinal fluid, sweat, urine, milk, ascites fluid, synovial fluid, peritoneal fluid, lavage fluid, and the like. The sample can be obtained from animals, preferably mammals, most preferably humans. The sample can be treated prior to use, such as preparing plasma from blood, diluting viscous fluids, and the like. Methods of treatment can involve filtration, distillation, extraction, concentration, inactivation of interfering components, the addition of reagents, and the like.
In embodiments of the invention the sample is a mammalian tissue sample. In a particular embodiment, the tissue is head-and-neck tissue. In some embodiments, the sample comprises oral dysplastic epithelial cells.
In another embodiment the sample is a human physiological fluid. In a particular embodiment, the sample is human serum.
The terms “subject”, “individual”, and “patient” refer to a mammal. In particular, the terms refer to a human. A subject, individual or patient may be afflicted with or suspected of having or being pre-disposed to head-and-neck disease or a condition as described herein.
The term “head-and-neck marker” refers to a marker associated with normal or diseased head-and-neck tissue and includes or consists of one or more of the polypeptides that are up-regulated in cancer samples as compared to normal samples in Table 1 and Table 7, those listed in Table 5, in particular The term includes native-sequence polypeptides, isoforms, chimeric polypeptides, complexes, all homologs, fragments, precursors, and modified forms and derivatives of the markers.
A head-and-neck marker may be associated with a head-and-neck disease, in particular it may be an OPL or head-and-neck cancer marker. The term “OPL or head-and-neck cancer marker” includes a marker associated with OPL or head-and-neck cancer, in particular a marker listed in Table 5.
The terms “YWHAZ”, “YWHAZ polypeptide”, and “YWHAZ protein” include human YWHAZ, in particular the native-sequence polypeptide, isoforms, chimeric polypeptides, all homologs, fragments, precursors, complexes, and modified forms and derivatives of human YWHAZ. The amino acid sequence for native human YWHAZ includes the amino acid sequences referenced in NCBI Gene ID: Q86V33, including GenBank Accession Nos. P29213, P29312, Q32P43, Q5XJ08, Q6GPI2, Q6IN74, Q6NUR9, Q6P3U9, and the exemplary sequences shown in SEQ ID NO: 24 (GenBank Accession No. P63104). Corresponding terms for “S100A7”, “stratifin”, and “hnRNPK” have similar meanings. The amino acid sequence for native human S100A7 includes the amino acid sequences referenced in NCBI Gene ID: P31151, including GenBank Accession Nos. Q6FGE3, Q9H1E2, and the exemplary sequences shown in SEQ ID NO: 13 (GenBank Accession No. P31151). The amino acid sequence for native human stratifin includes the amino acid sequences referenced in NCBI Gene ID: P31947, including GenBank Accession Nos. Q6FH30, Q6FH51, Q96DH0, and the exemplary sequences shown in SEQ ID NO: 23 (GenBank Accession No. P31947). The amino acid sequence for native human hnRNPK includes the amino acid sequences referenced in NCBI Gene ID: gi|48429103, NP_002131.2, P61978.1 including GenBank Accession Nos. S74678.1, NP_112552.1, AAB20770.1, NP_112553.1, X72727.1, 1J5K_A, CAA51267.1, 1KHM_A, AB209562.1, IZZI_A, BAD92799.1, IZZI_B, BC000355.2, IZZJ_A, AAH00355.1, IZZJ_B, BC014980.1, IZZJ_C, AAH14980.1, 1ZZK_A, and the exemplary sequences shown in SEQ ID NO: 25 (GenBank Accession No. P61978.1).
A “native-sequence polypeptide” includes a polypeptide having the same amino acid sequence of a polypeptide derived from nature. Such native-sequence polypeptides can be isolated from nature or can be produced by recombinant or synthetic means. The term specifically encompasses naturally occurring truncated or secreted forms of a polypeptide, polypeptide variants including naturally occurring variant forms (e.g., alternatively spliced forms or splice variants), and naturally occurring allelic variants.
The term “polypeptide variant” means a polypeptide having at least about 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 97%, 98%, or 99% amino acid sequence identity, particularly at least about 70-80%, more particularly at least about 85%, still more particularly at least about 90%, most particularly at least about 95% amino acid sequence identity with a native-sequence polypeptide. Particular polypeptide variants have at least 70-80%, 85%, 90%, 95% amino acid sequence identity to the sequences identified in Table 5 or 2 or 7. Such variants include, for instance, polypeptides wherein one or more amino acid residues are added to, or deleted from, the N- or C-terminus of the full-length or mature sequences of the polypeptide, including variants from other species, but excludes a native-sequence polypeptide. In aspects of the invention variants retain the immunogenic activity of the corresponding native-sequence polypeptide.
Percent identity of two amino acid sequences, or of two nucleic acid sequences is defined as the percentage of amino acid residues or nucleotides in a candidate sequence that are identical with the amino acid residues in a polypeptide or nucleic acid sequence, after aligning the sequences and introducing gaps, if necessary, to achieve the maximum percent sequence identity, and not considering any conservative substitutions as part of the sequence identity. Skilled artisans can determine appropriate parameters for measuring alignment, including any algorithms needed to achieve maximal alignment over the full length of the sequences being compared. Methods to determine identity and similarity are codified in publicly-available computer programs.
An allelic variant may also be created by introducing substitutions, additions, or deletions into a polynucleotide encoding a native polypeptide sequence such that one or more amino acid substitutions, additions, or deletions are introduced into the encoded protein. Mutations may be introduced by standard methods, such as site-directed mutagenesis and PCR-mediated mutagenesis. In an embodiment, conservative substitutions are made at one or more predicted non-essential amino acid residues. A “conservative amino acid substitution” is one in which an amino acid residue is replaced with an amino acid residue with a similar side chain. Amino acids with similar side chains are known in the art and include amino acids with basic side chains (e.g., Lys, Arg, His), acidic side chains (e.g., Asp, Glu), uncharged polar side chains (e.g., Gly, Asp, Glu, Ser, Thr, Tyr, and Cys), non-polar side chains (e.g., Ala, Val, Leu, Iso, Pro, Trp), beta-branched side chains (e.g., Thr, Val, Iso), and aromatic side chains (e.g., Tyr, Phe, Trp, His). Mutations can also be introduced randomly along part or all of the native sequence, for example, by saturation mutagenesis. Following mutagenesis the variant polypeptide can be recombinantly expressed and the activity of the polypeptide may be determined.
Polypeptide variants include polypeptides comprising amino acid sequences sufficiently identical to or derived from the amino acid sequence of a native polypeptide which include fewer amino acids than the full length polypeptides. A portion of a polypeptide can be a polypeptide which is for example, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100 or more amino acids in length. Portions in which regions of a polypeptide are deleted can be prepared by recombinant techniques and can be evaluated for one or more functional activities such as the ability to form antibodies specific for a polypeptide.
A naturally occurring allelic variant may contain conservative amino acid substitutions from the native polypeptide sequence or it may contain a substitution of an amino acid from a corresponding position in a polypeptide homolog, for example, a murine polypeptide.
A modified form of a polypeptide referenced herein includes modified forms of the polypeptides and derivatives of the polypeptides, including post-translationally modified forms such as glycosylated, phosphorylated, acetylated, methylated or lapidated forms of the polypeptides. For example, an N-terminal methionine may be cleaved from a polypeptide, and a new N-terminal residue may or may not be acetylated. In particular, for chaperonin 10 the first residue, methionine, can be cleaved and the second first residue, alanine can be N-acetylated.
Oral premalignant lesions (OPL) or head-and-neck cancer markers may be prepared by recombinant or synthetic methods, or isolated from a variety of sources, or by any combination of these and similar techniques.
“Statistically different levels”, “significantly altered levels”, or “significant difference” in levels of markers in a patient sample compared to a control or standard (e.g., normal levels or levels in other samples from a patient) may represent levels that are higher or lower than the standard error of the detection assay. In particular embodiments, the levels may be 1.5, 2, 3, 4, 5, or 6 times higher or lower than the control or standard.
“Microarray” and “array” refer to nucleic acid or nucleotide arrays or protein or peptide arrays that can be used to detect biomolecules associated with head and neck cell or tissue phase and head-and-neck disease, for instance to measure gene or protein expression. A variety of arrays are made in research and manufacturing facilities worldwide, some of which are available commercially.
“Binding agent” refers to a substance such as a polypeptide or antibody that specifically binds to one or more OPL or head-and-neck cancer markers. A substance “specifically binds” to one or more OPL or head-and-neck cancer markers if is reacts at a detectable level with one or more OPL or head-and-neck cancer markers, and does not react detectably with peptides containing an unrelated or different sequence. Binding properties may be assessed using an ELISA, which may be readily performed by those skilled in the art (see, for example, Newton et al., Develop. Dynamics 197: 1-13, 1993).
A binding agent may be a ribosome, with or without a peptide component, an aptamer, an RNA molecule, or a polypeptide. A binding agent may be a polypeptide that includes one or more OPL or head-and-neck marker sequence, a peptide variant thereof, or a non-peptide mimetic of such a sequence. By way of example, a YWHAZ sequence may be a peptide portion of a YWHAZ that is capable of modulating a function mediated by YWHAZ.
Antibodies for use in the present invention include but are not limited to monoclonal or polyclonal antibodies, immunologically active fragments (e.g., a Fab or (Fab)2 fragments), antibody heavy chains, humanized antibodies, antibody light chains, genetically engineered single chain Fv molecules (Ladner et al., U.S. Pat. No. 4,946,778), chimeric antibodies, for example, antibodies which contain the binding specificity of murine antibodies, but in which the remaining portions are of human origin, or derivatives, such as enzyme conjugates or labeled derivatives.
Antibodies, including monoclonal and polyclonal antibodies, fragments and chimeras, may be prepared using methods known to those skilled in the art. Isolated native or recombinant OPL or head-and-neck cancer markers may be utilized to prepare antibodies. Antibodies specific for an OPL or head-and-neck marker may also be obtained from scientific or commercial sources.
In an embodiment of the invention, antibodies are reactive against an OPL or head-and-neck marker if they bind with a Ka of greater than or equal to 10-7 M.
Markers.
The invention provides a set of markers correlated with head-and-neck disease. In an aspect, the invention provides a set of markers identified as useful for detection, diagnosis, prevention and therapy of head-and-neck disease including or consisting of one or more of the markers listed in Table 5. In another aspect, the invention provides the head-and-neck or OPL cancer markers in Table 2 and Table 7 for detection, diagnosis and prognosis of a head-and-neck disease. The invention also provides a method of using OPL or head-and-neck cancer markers listed in Table 5 or Table 2 or Table 7, to distinguish head-and-neck disease.
In an embodiment, the markers include or consist of 1, 2, 3, 4 or more other markers listed in Table 5, Table 2, and Table 7.
In embodiments of the invention, a marker is provided which is selected from the group consisting of the polypeptides set forth in Table 5 which polypeptides are up-regulated biomarkers in OPL or head-and-neck cancer and optionally at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 polypeptides set forth in Table 5 and/or 2 or polypeptides in Table 1 and Table 5 and/or 6 or polypeptides in Table 7 that are up-regulated biomarkers in OPL or head-and-neck cancer.
In embodiments of the invention, a marker is provided which is selected from the group consisting of at least one marker of Table 2 or 7 and at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 polypeptides set forth in Table 5.
The invention provides marker sets that distinguish head-and-neck disease and uses therefor. In an aspect, the invention provides a method for classifying a head-and-neck disease including detecting a difference in the expression of a first plurality of OPL or head-and-neck cancer markers relative to a control, the first plurality of OPL or head-and-neck cancer markers or OPL. In specific aspects, the plurality of markers consists of the markers listed in Table 2 and optionally at least 5 to 10 of the markers listed in Table 5. In specific aspects, the plurality of markers consists of the markers listed in Table 7 and optionally at least 5 to 10 of the markers listed in Table 5. In specific aspects, a control includes markers derived from a pool of samples from individual patients with no head-and-neck disease.
Any of the markers provided herein may be used alone or with other markers of head-and-neck disease, or with markers for other phenotypes or conditions. Additionally, all of the sequences provided herein are representative only; there may be other sequences for particular protein or coding sequences or related sequences. The invention is not intended to be limited to the sequences herein provided.
Detection Methods.
A variety of methods can be employed for the diagnostic and prognostic evaluation of head-and-neck disease or head-and-neck status involving one or more OPL or head-and-neck cancer markers, and the identification of subjects with a predisposition to head-and-neck diseases or that are receptive to in vitro fertilization and embryo transfer procedures. Such methods may, for example, utilize head-and-neck cancer markers, and fragments thereof, and binding agents (e.g., antibodies) against one or more OPL or head-and-neck cancer markers, including peptide fragments. In particular, the antibodies may be used, for example, for the detection of either an over- or an under-abundance of one or more OPL or head-and-neck cancer markers relative to a non-disorder state or a different head and neck cell or tissue phase or the presence of a modified (e.g., less than full length) OPL or head-and-neck marker which correlates with a disorder state or a progression toward a disorder state.
The invention contemplates a method for detecting the phase of a head-and-neck tissue, in particular a secretory head-and-neck tissue, including producing a profile of levels of one or more OPL or head-and-neck marker associated with a known head and/or neck cell or tissue phase and/, and optionally other markers associated with the phase in cells from a patient, and comparing the profile with a reference to identify a profile for the test cells indicative of the phase. In an aspect, the head-and-neck cancer markers include those of Table 5, preferably Table 2 or fragments thereof. In an aspect, the OPL markers include those of Table 5, preferably Table 7 or fragments thereof.
The invention also contemplates a method for detecting a head-and-neck disease, in particular an OPL or head-and-neck cancer, including producing a profile of levels of one or more head-and-neck marker associated with a head-and-neck disease and/, and other markers associated with head-and-neck disease in cells from a patient, and comparing the profile with a reference to identify a profile for the test cells indicative of disease. In an aspect, the head-and-neck cancer markers are one or more of those listed in Table 5 or Table 2. In an aspect, the OPL markers are one or more of those listed in Table 5 or Table 7.
The methods described herein may be used to evaluate the probability of the presence of malignant or pre-malignant cells, for example, in a group of cells freshly removed from a host. Such methods can be used to detect tumors, quantify their growth, and help in the diagnosis and prognosis of head-and-neck disease. The methods can be used to detect the presence of cancer metastasis, as well as confirm the absence or removal of all tumor tissue following surgery, cancer chemotherapy, and/or radiation therapy. They can further be used to monitor cancer chemotherapy and tumor reappearance.
The methods described herein can be adapted for diagnosing and monitoring head-and-neck tissue status or a head-and-neck disease by detecting one or more OPL or head-and-neck cancer markers in biological samples from a subject. These applications require that the amount of markers quantified in a sample from a subject being tested be compared to a predetermined standard or cut-off value. The standard may correspond to levels quantified for another sample or an earlier sample from the subject, or levels quantified for a control sample. Levels for control samples from healthy subjects, different head-and-neck tissue phases, or subjects with a head-and-neck disease may be established by prospective and/or retrospective statistical studies. Healthy subjects who have no clinically evident disease or abnormalities may be selected for statistical studies. Diagnosis may be made by a finding of statistically different levels of detected head-and-neck cancer markers associated with disease, compared to a control sample or previous levels quantified for the same subject.
The methods described herein may also use multiple markers for a head-and-neck disease, in particular OPL and head-and-neck cancer. The methods described herein may be modified by including reagents to detect the additional markers.
Oral premalignant lesion (OPL) or head-and-neck cancer marker-positive samples or alternatively higher levels in patients compared to a control (e.g., non-cancerous tissue) may be indicative of late stage disease, and/or that the patient is not responsive to chemotherapy. Alternatively, negative samples or lower levels compared to a control (e.g., non-cancerous tissue or negative samples) may be indicative of progressive disease and shorter overall survival.
Protein Methods.
Binding agents may be used for a variety of diagnostic and assay applications. There are a variety of assay formats known to the skilled artisan for using a binding agent to detect a target molecule in a sample. In general, the presence or absence of a head-and-neck disease (e.g., cancer) in a subject may be determined by (a) contacting a sample from the subject with a binding agent; (b) detecting in the sample a level of polypeptide that binds to the binding agent; and (c) comparing the level of polypeptide with a predetermined standard or cut-off value.
In particular embodiments of the invention, the binding agent is an antibody. Antibodies specifically reactive with one or more head-and-neck marker, or derivatives, such as enzyme conjugates or labeled derivatives, may be used to detect one or more head-and-neck marker in various samples (e.g., biological materials). They may be used as diagnostic or prognostic reagents and they may be used to detect abnormalities in the level of expression of one or more head-and-neck marker, or abnormalities in the structure, and/or temporal, tissue, cellular, or subcellular location of one or more head-and-neck marker. Antibodies may also be used to screen potentially therapeutic compounds in vitro to determine their effects on disorders (e.g., OPL or head-and-neck cancer) involving one or more OPL or head-and-neck cancer markers, and other conditions. In vitro immunoassays may also be used to assess or monitor the efficacy of particular therapies.
In an aspect, the invention provides a method for monitoring or diagnosing a head-and-neck disease (e.g., OPL or cancer) in a subject by quantifying one or more OPL or head-and-neck cancer markers in a biological sample from the subject including reacting the sample with antibodies specific for one or more OPL or head-and-neck cancer markers, which are directly or indirectly labeled with detectable substances and detecting the detectable substances. In a particular embodiment of the invention, OPL or head-and-neck cancer markers are quantified or measured.
In an aspect of the invention, a method for detecting a head-and-neck disease (e.g., OPL or cancer) is provided including:

    (a) obtaining a sample suspected of containing one or more OPL or head-and-neck cancer markers associated with a head-and-neck disease;
    (b) contacting said sample with antibodies that specifically bind to the OPL or head-and-neck cancer markers under conditions effective to bind the antibodies and form complexes;
    (c) measuring the amount of OPL or head-and-neck cancer markers present in the sample by quantifying the amount of the complexes; and
    (d) comparing the amount of OPL or head-and-neck cancer markers present in the samples with the amount of OPL or head-and-neck cancer markers in a control, wherein a change or significant difference in the amount of OPL or head-and-neck cancer markers in the sample compared with the amount in the control is indicative of a head-and-neck disease.


In an embodiment, the invention contemplates a method for monitoring the progression of a head-and-neck disease (e.g., OPL or cancer) in an individual, including:

    (a) contacting antibodies which bind to one or more OPL or head-and-neck cancer markers with a sample from the individual so as to form complexes including the antibodies and one or more OPL or head-and-neck cancer markers in the sample;
    (b) determining or detecting the presence or amount of complex formation in the sample;
    (c) repeating steps (a) and (b) at a point later in time; and
    (d) comparing the result of step (b) with the result of step (c), wherein a difference in the amount of complex formation is indicative of disease, disease stage, and/or progression of the disease in said individual.


The amount of complexes may also be compared to a value representative of the amount of the complexes from an individual not at risk of, or afflicted with, a head-and-neck disease at different stages. A significant difference in complex formation may be indicative of advanced disease (e.g., advanced head-and-neck cancer, or an unfavourable prognosis).
In aspects of the invention for diagnosis and monitoring of OPL or head-and-neck cancer, the OPL or head-and-neck cancer markers are one or more of those upregulated in cancer samples as compared to normal samples in Table 1, those listed in Table 5, and/or YWHAZ, S100A7, and/or stratifin, and/or hnRNPK.
In embodiments of the methods of the invention, YWHAZ, S100A7, hnRNPK and/or stratifin is detected in samples and higher levels, in particular significantly higher levels compared to a control (normal or benign) is indicative of the prognosis of OPL or head-and-neck cancer patient outcome.
In aspects of the invention for characterizing head-and-neck disease the OPL or head-and-neck cancer markers include YWHAZ, S100A7, hnRNPK and/or stratifin and fragments thereof.
Antibodies may be used in any known immunoassays that rely on the binding interaction between antigenic determinants of one or more head-and-neck marker and the antibodies. Examples of immunoassays are radioimmunoassays (RIA), enzyme immunoassays (e.g., ELISA), munofluorescence, immunoprecipitation, latex agglutination, hemagglutination, histochemical tests, and sandwich (immunometric) assays.
According to an embodiment of the invention, an immunoassay for detecting one or more OPL or head-and-neck cancer markers in a biological sample includes contacting binding agents that specifically bind to OPL or head-and-neck cancer markers in the sample under conditions that allow the formation of first complexes including a binding agent and OPL or head-and-neck cancer markers and determining the presence or amount of the complexes as a measure of the amount of OPL or head-and-neck cancer markers contained in the sample. In a particular embodiment, the binding agents are labeled differently or are capable of binding to different labels.
Antibodies may be used to detect and quantify one or more OPL or head-and-neck cancer markers in a sample in order to diagnose pathological states. In particular, the antibodies may be used in immunohistochemical analyses, for example, at the cellular and sub-subcellular level, to detect one or more OPL or head-and-neck cancer markers, to localize them to particular head-and-neck cells and tissues (e.g., tumor cells and tissues), and to specific subcellular locations, and to quantify the level of expression.
Immunohistochemical methods for the detection of antigens in tissue samples are well known in the art. Briefly, in the context of the present invention, a tissue sample obtained from a subject suspected of having a head-and-neck-related problem is contacted with antibodies, preferably monoclonal antibodies recognizing one or more head-and-neck cancer markers. The site at which the antibodies are bound is determined by selective staining of the sample by standard immunohistochemical procedures. The same procedure may be repeated on the same sample using other antibodies that recognize one or more OPL or head-and-neck cancer markers. Alternatively, a sample may be contacted with antibodies against one or more OPL or head-and-neck cancer markers simultaneously, provided that the antibodies are labeled differently or are able to bind to a different label. The tissue sample may be normal head-and-neck tissue, an OPL, or a cancer tissue or a benign tissue.
An antibody microarray in which binding sites include immobilized, preferably monoclonal, antibodies specific to a substantial fraction of marker-derived OPL or head-and-neck cancer markers of interest can be utilized in the present invention. Antibody arrays can be prepared using methods known in the art (see, for example, Zhu et al., Science 293:2101 (2001) and reference 20).
Antibodies specific for one or more OPL or head-and-neck marker may be labelled with a detectable substance and localised in biological samples based upon the presence of the detectable substance. Examples of detectable substances include, but are not limited to, the following: radioisotopes (e.g., 3H, 14C, 35s, 125I, 131I), fluorescent labels (e.g., FITC, rhodamine, lanthanide phosphors), luminescent labels such as luminol; enzymatic labels (e.g., horseradish peroxidase, beta-galactosidase, luciferase, alkaline phosphatase, acetylcholinesterase), biotinyl groups (which can be detected by marked avidin (e.g., streptavidin containing a fluorescent marker or enzymatic activity that can be detected by optical or colorimetric methods)), predetermined polypeptide epitopes recognized by a secondary reporter (e.g., leucine zipper pair sequences, binding sites for secondary antibodies, metal binding domains, epitope tags). In some embodiments, labels are attached via spacer arms of various lengths to reduce potential steric hindrance. Antibodies may also be coupled to electron dense substances, such as ferritin or colloidal gold, which are readily visualised by electron microscopy.
One of the ways an antibody can be detectably labeled is to link it directly to an enzyme. The enzyme when later exposed to its substrate will produce a product that can be detected. Examples of detectable substances that are enzymes are horseradish peroxidase, beta-galactosidase, luciferase, alkaline phosphatase, acetylcholinesterase, malate dehydrogenase, ribonuclease, urease, catalase, glucose-6-phosphate, staphylococcal nuclease, delta-5-steroid isomerase, yeast alcohol dehydrogenase, alpha-glycerophosphate, triose phosphate isomerase, asparaginase, glucose oxidase, and acetylcholine esterase.
For increased sensitivity in an immunoassay system a fluorescence-emitting metal atom such as Eu (europium) and other lanthanides can be used. These can be attached to the desired molecule by means of metal-chelating groups such as DTPA or EDTA.
A bioluminescent compound may also be used as a detectable substance. Examples of bioluminescent detectable substances are luciferin, luciferase and aequorin.
Indirect methods may also be employed in which the primary antigen-antibody reaction is amplified by the introduction of a second antibody, having specificity for the antibody reactive against one or more head-and-neck cancer markers. By way of example, if the antibody having specificity against one or more OPL or head-and-neck marker is a rabbit IgG antibody, the second antibody may be goat anti-rabbit gamma-globulin labelled with a detectable substance as described herein.
Methods for conjugating or labelling the antibodies discussed above may be readily accomplished by one of ordinary skill in the art.
Cytochemical techniques known in the art for localizing antigens using light and electron microscopy may be used to detect one or more head-and-neck cancer markers. Generally, antibodies may be labeled with detectable substances and one or more head-and-neck cancer markers may be localised in tissues and cells based upon the presence of the detectable substances.
In the context of the methods of the invention, the sample, binding agents (e.g., antibodies specific for one or more OPL or head-and-neck cancer markers), or one or more OPL or head-and-neck cancer markers may be immobilized on a carrier or support. Examples of suitable carriers or supports are agarose, cellulose, nitrocellulose, dextran, Sephadex, Sepharose, liposomes, carboxymethyl cellulose, polyacrylamides, polystyrene, gabbros, filter paper, magnetite, ion-exchange resin, plastic film, plastic tube, glass, polyamine-methyl vinyl-ether-maleic acid copolymer, amino acid copolymer, ethylene-maleic acid copolymer, nylon, silk, etc. The support material may have any possible configuration including spherical (e.g., bead), cylindrical (e.g., inside surface of a test tube or well, or the external surface of a rod), or flat (e.g., sheet, test strip). Thus, the carrier may be in the shape of, for example, a tube, test plate, well, beads, disc, sphere, etc. The immobilized antibody may be prepared by reacting the material with a suitable insoluble carrier using known chemical or physical methods, for example, cyanogen bromide coupling. An antibody may be indirectly immobilized using a second antibody specific for the antibody. For example, mouse antibody specific for a head-and-neck marker may be immobilized using sheep anti-mouse IgG Fc fragment specific antibody coated on the carrier or support.
Where a radioactive label is used as a detectable substance, one or more OPL or head-and-neck marker may be localized by radioautography. The results of radioautography may be quantified by determining the density of particles in the radioautographs by various optical methods, or by counting the grains.
Time-resolved fluorometry may be used to detect a signal. For example, the method described by Christopoulos T K and Diamandis E P in Anal Chem 1992:64:342-346 may be used with a conventional time-resolved fluorometer.
In accordance with an embodiment of the invention, a method is provided wherein one or more OPL or head-and-neck marker antibodies are directly or indirectly labelled with enzymes, substrates for the enzymes are added wherein the substrates are selected so that the substrates, or a reaction product of an enzyme and substrate, form fluorescent complexes with a lanthanide metal (e.g., europium, terbium, samarium, and dysprosium, preferably europium and terbium). A lanthanide metal is added and one or more OPL or head-and-neck cancer markers are quantified in the sample by measuring fluorescence of the fluorescent complexes. Enzymes are selected based on the ability of a substrate of the enzyme, or a reaction product of the enzyme and substrate, to complex with lanthanide metals such as europium and terbium. Suitable enzymes and substrates that provide fluorescent complexes are described in U.S. Pat. No. 5,312,922 to Diamandis. Examples of suitable enzymes include alkaline phosphatase and β-galactosidase. Preferably, the enzyme is alkaline phosphatase.
One or more OPL or head-and-neck marker antibodies may also be indirectly labelled with an enzyme. For example, the antibodies may be conjugated to one partner of a ligand binding pair, and the enzyme may be coupled to the other partner of the ligand binding pair. Representative examples include avidin-biotin, and riboflavin-riboflavin binding protein. In an embodiment, the antibodies are biotinylated, and the enzyme is coupled to streptavidin. In another embodiment, an antibody specific for OPL or head-and-neck marker antibody is labeled with an enzyme.
In accordance with an embodiment, the present invention provides means for determining one or more OPL or head-and-neck cancer markers in a sample by measuring one or more head-and-neck cancer markers by immunoassay. It will be evident to a skilled artisan that a variety of immunoassay methods can be used to measure one or more head-and-neck cancer markers. In general, an immunoassay method may be competitive or non-competitive. Competitive methods typically employ an immobilized or immobilizable antibody to one or more OPL or head-and-neck marker and a labeled form of one or more OPL or head-and-neck marker. Sample OPL or head-and-neck cancer markers and labeled OPL or head-and-neck cancer markers compete for binding to antibodies to OPL or head-and-neck cancer markers. After separation of the resulting labeled OPL or head-and-neck cancer markers that have become bound to antibodies (bound fraction) from that which has remained unbound (unbound fraction), the amount of the label in either bound or unbound fraction is measured and may be correlated with the amount of OPL or head-and-neck cancer markers in the test sample in any conventional manner (e.g., by comparison to a standard curve).
In an aspect, a non-competitive method is used for the determination of one or more OPL or head-and-neck cancer markers, with the most common method being the “sandwich” method. In this assay, two antibodies to OPL or head-and-neck cancer markers are employed. One of the antibodies to OPL or head-and-neck cancer markers is directly or indirectly labeled (sometimes referred to as the “detection antibody”) and the other is immobilized or immobilizable (sometimes referred to as the “capture antibody”). The capture and detection antibodies can be contacted simultaneously or sequentially with the test sample. Sequential methods can be accomplished by incubating the capture antibody with the sample, and adding the detection antibody at a predetermined time thereafter (sometimes referred to as the “forward” method); or the detection antibody can be incubated with the sample first and then the capture antibody added (sometimes referred to as the “reverse” method). After the necessary incubation(s) have occurred, to complete the assay, the capture antibody is separated from the liquid test mixture, and the label is measured in at least a portion of the separated capture antibody phase or the remainder of the liquid test mixture. Generally, it is measured in the capture antibody phase since it includes OPL or head-and-neck cancer markers bound by (“sandwiched” between) the capture and detection antibodies. In an embodiment, the label may be measured without separating the capture antibodies and liquid test mixture.
In a typical two-site immunometric assay for OPL or head-and-neck cancer markers, one or both of the capture and detection antibodies are polyclonal antibodies or one or both of the capture and detection antibodies are monoclonal antibodies (i.e. polyclonal/polyclonal, monoclonal/monoclonal, or monoclonal/polyclonal). The label used in the detection antibody can be selected from any of those known conventionally in the art. The label may be an enzyme or a chemiluminescent moiety, but it can also be a radioactive isotope, a fluorophor, a detectable ligand (e.g., detectable by a secondary binding by a labeled binding partner for the ligand), and the like. In a particular aspect, the antibody is labelled with an enzyme which is detected by adding a substrate that is selected so that a reaction product of the enzyme and substrate forms fluorescent complexes. The capture antibody may be selected so that it provides a means for being separated from the remainder of the test mixture. Accordingly, the capture antibody can be introduced to the assay in an already immobilized or insoluble form, or can be in an immobilizable form, that is, a form which enables immobilization to be accomplished subsequent to introduction of the capture antibody to the assay. An immobilized capture antibody may include an antibody covalently or non-covalently attached to a solid phase such as a magnetic particle, a latex particle, a microtiter plate well, a bead, a cuvette, or other reaction vessel. An example of an immobilizable capture antibody is antibody which has been chemically modified with a ligand moiety, e.g., a hapten, biotin, or the like, and which can be subsequently immobilized by contact with an immobilized form of a binding partner for the ligand, e.g., an antibody, avidin, or the like. In an embodiment, the capture antibody may be immobilized using a species specific antibody for the capture antibody that is bound to the solid phase.
The above-described immunoassay methods and formats are intended to be exemplary and are not limiting.
Screening Methods.
The invention also contemplates methods for evaluating test agents or compounds for their ability to inhibit a head-and-neck disease (e.g., OPL or cancer), potentially contribute to a head-and-neck disease (e.g., OPL or cancer). Test agents and compounds include but are not limited to peptides such as soluble peptides including Ig-tailed fusion peptides, members of random peptide libraries and combinatorial chemistry-derived molecular libraries made of D- and/or L-configuration amino acids, phosphopeptides (including members of random or partially degenerate, directed phosphopeptide libraries), antibodies (e.g., polyclonal, monoclonal, humanized, anti-idiotypic, chimeric, single chain antibodies, fragments (e.g., Fab, F(ab)2, and Fab expression library fragments, and epitope-binding fragments thereof), and small organic or inorganic molecules. The agents or compounds may be endogenous physiological compounds or natural or synthetic compounds.
The invention provides a method for assessing the potential efficacy of a test agent for inhibiting a head-and-neck disease (e.g., OPL or cancer) in a patient, the method including comparing:

    (a) levels of one or more OPL or head-and-neck cancer markers, and optionally other markers in a first sample obtained from a patient and exposed to the test agent; and
    (b) levels of one or more OPL or head-and-neck cancer markers, and optionally other markers, in a second sample obtained from the patient, wherein the sample is not exposed to the test agent, wherein a significant difference in the levels of expression of one or more head-and-neck cancer markers, and optionally the other markers, in the first sample, relative to the second sample, is an indication that the test agent is potentially efficacious for inhibiting a head-and-neck disease (e.g., OPL or cancer) in the patient.


The first and second samples may be portions of a single sample obtained from a patient or portions of pooled samples obtained from a patient.
In an aspect, the invention provides a method of selecting an agent for inhibiting a head-and-neck disease (e.g., OPL or cancer) in a patient including:

    (a) obtaining a sample from the patient;
    (b) separately maintaining aliquots of the sample in the presence of a plurality of test agents;
    (c) comparing one or more OPL or head-and-neck cancer markers, and optionally other markers, in each of the aliquots; and
    (d) selecting one of the test agents which alters the levels of one or more OPL or head-and-neck cancer markers and optionally other markers in the aliquot containing that test agent, relative to other test agents.


In a further aspect, the invention provides a method of selecting an agent for inhibiting or enhancing a OPL or head and neck cell or tissue phase in a patient including:

    (a) obtaining a sample of OPL or head and neck cell or tissue in a selected phase;
    (b) separately maintaining aliquots of the sample in the presence of a plurality of test agents;
    (c) comparing one or more OPL or head-and-neck cancer markers, and optionally other markers, in each of the aliquots; and
    (d) selecting one of the test agents which alters the levels of one or more OPL or head-and-neck cancer markers, and optionally other markers in the aliquot containing that test agent, relative to other test agents.


Still another aspect of the present invention provides a method of conducting a drug discovery business including:

    (a) providing one or more methods or assay systems for identifying agents that inhibit a head-and-neck disease (e.g., OPL or head-and-neck cancer) or affect a OPL or head and neck cell or tissues phase in a patient;
    (b) conducting therapeutic profiling of agents identified in step (a), or further analogs thereof, for efficacy and toxicity in animals; and
    (c) formulating a pharmaceutical preparation including one or more agents identified in step (b) as having an acceptable therapeutic profile.


In certain embodiments, the subject method can also include a step of establishing a distribution system for distributing the pharmaceutical preparation for sale, and may optionally include establishing a sales group for marketing the pharmaceutical preparation.
The invention also contemplates a method of assessing the potential of a test compound to contribute to a head-and-neck disease (e.g., OPL or head-and-neck cancer) including:

    (a) maintaining separate aliquots of cells or tissues from a patient with a head-and-neck disease (e.g., OPL or cancer) in the presence and absence of the test compound; and
    (b) comparing one or more OPL or head-and-neck cancer markers, and optionally other markers in each of the aliquots.


A significant difference between the levels of the markers in the aliquot maintained in the presence of (or exposed to) the test compound relative to the aliquot maintained in the absence of the test compound, indicates that the test compound possesses the potential to contribute to a head-and-neck disease (e.g., OPL or head-and-neck cancer).
Kits.
The invention also contemplates kits for carrying out the methods of the invention. Kits may typically include two or more components required for performing a diagnostic assay. Components include but are not limited to compounds, reagents, containers, and/or equipment.
The methods described herein may be performed by utilizing pre-packaged diagnostic kits including one or more specific OPL or head-and-neck marker antibody described herein, which may be conveniently used, e.g., in clinical settings to screen and diagnose patients and to screen and identify those individuals exhibiting a predisposition to developing a head-and-neck disease.
In an embodiment, a container with a kit includes a binding agent as described herein. By way of example, the kit may contain antibodies or antibody fragments which bind specifically to epitopes of one or more OPL or head-and-neck cancer markers and optionally other markers, antibodies against the antibodies labelled with an enzyme; and a substrate for the enzyme. The kit may also contain microtiter plate wells, standards, assay diluent, wash buffer, adhesive plate covers, and/or instructions for carrying out a method of the invention using the kit.
In an aspect of the invention, the kit includes antibodies or fragments of antibodies which bind specifically to an epitope of one or more polypeptide listed in Table 1 that is upregulated in cancer samples as compared to normal samples, or those listed in Table 5 or Table 2 and means for detecting binding of the antibodies to their epitope associated with tumor cells, either as concentrates (including lyophilized compositions), which may be further diluted prior to use or at the concentration of use, where the vials may include one or more dosages. Where the kits are intended for in vivo use, single dosages may be provided in sterilized containers, having the desired amount and concentration of agents. Containers that provide a formulation for direct use, usually do not require other reagents, as for example, where the kit contains a radiolabelled antibody preparation for in vivo imaging.
In an aspect of the invention, the kit includes antibodies or fragments of antibodies which bind specifically to an epitope of one or more polypeptide listed in Table 6 that is upregulated in OPL samples as compared to normal samples, or those listed in Table 5 or Table 7 and means for detecting binding of the antibodies to their epitope associated with OPL cells, either as concentrates (including lyophilized compositions), which may be further diluted prior to use or at the concentration of use, where the vials may include one or more dosages. Where the kits are intended for in vivo use, single dosages may be provided in sterilized containers, having the desired amount and concentration of agents. Containers that provide a formulation for direct use, usually do not require other reagents, as for example, where the kit contains a radiolabelled antibody preparation for in vivo imaging.
The reagents suitable for applying the screening methods of the invention to evaluate compounds may be packaged into convenient kits described herein providing the necessary materials packaged into suitable containers.
The invention contemplates a kit for assessing the presence of head-and-neck cells, wherein the kit includes antibodies specific for one or more OPL or head-and-neck cancer markers, and optionally antibodies specific for other markers associated with a head-and-neck disease (e.g., OPL or cancer).
The invention relates to a kit for assessing the suitability of each of a plurality of test compounds for inhibiting a head-and-neck disease (e.g., OPL or head-and-neck cancer) in a patient. The kit includes reagents for assessing one or more OPL or head-and-neck cancer markers, and optionally a plurality of test agents or compounds.
Additionally the invention provides a kit for assessing the potential of a test compound to contribute to a head-and-neck disease (e.g., OPL or cancer). The kit includes head-and-neck diseased cells (e.g., OPL or cancer cells) and reagents for assessing one or more OPL or head-and-neck cancer markers and optionally other markers associated with a head-and-neck disease.
The inventors' study lays a major thrust on determining the clinical impact of a proteomics based biomarkers in predicting the high risk leukoplakia, as early as hyperplasia, and clinical outcome in HNOSCC patients after treatment of primary tumors. The unique features of the inventors' study are its prospective nature, the large number of patients in this type of disease setting, and the length of follow-up of leukoplakia and HNOSCC patients. Furthermore, in support of the proposed role of hnRNPK, S100A7 and nuclear PTMA as malignant transformation-related proteins, their overexpression in early oral lesions is a very important unique finding of this study and herein the inventors present clinical evidence to establish its link with progression potential of leukoplakia. To the inventors' knowledge, this is the first investigation to demonstrate the clinical application of a candidate biomarker identified using MS-based tissue proteomics in identifying early oral premalignant lesions that may be at high risk of disease progression.
Most studies on leukoplakia focus on dysplastic lesions, while knowledge of molecular alterations in oral hyperplasias is meager. As per the existing literature, the malignant transformation potential is often linked to the severity of dysplasia; in comparison the hyperplastic lesions have received less attention, primarily because lesions undergo spontaneous regression. However, the lesions that do not regress need identification and biomarkers to predict the risk of malignant transformation. In this context the inventors' study assumes importance, because not only does it show aberrant hnRNPK expression as early as in hyperplasia, but the follow-up study also points to the relevance of cytoplasmic hnRNPK in predicting the risk of disease progression in leukoplakia patients with hyperplasia and HNOSCCs. Further, S100A7 and/or nuclear PTMA overexpression in oral dysplastic lesions are shown to predict a high risk of malignant transformation.
It is noteworthy that studies on molecular analysis of leukoplakia with hyperplasia are very limited, because these patients often do not come to the clinics since their lesions are small and do not pose any overt clinical problem. However, it is extremely important to target this patient population for risk assessment and early intervention for cancer prevention in high risk cases. Hence, the inventors' findings are important and warrant further validation in larger independent studies on oral hyperplastic lesions. Furthermore, the cytoplasmic expression of hnRNPK protein observed in epithelial cells of a subset of hyperplastic and dysplastic lesions points to a potential role in development and progression during early stages of oral tumorigenesis, while the overexpression in HNOSCCs and association with poor prognosis suggests a sustained involvement in frank malignancy as well.
The present invention is described in the following non-limiting Examples, which are set forth to illustrate and to aid in an understanding of the invention, and should not be construed to limit in any way the scope of the invention as defined in the claims which follow thereafter.
EXAMPLES
In Examples 1-13, the inventors demonstrate the identification of a consistently increased expression of a panel of proteins, including stratifin (14-3-3σ) and YWHAZ (14-3-3ζ), that may serve as cancer biomarkers. In Examples 14-20, the prognostic utility of these two candidate biomarkers for head-and-neck/oral squamous cell carcinoma (HNOSCC) is described. In Examples 21-27, the clinical significance and utility of one of the OPL markers, hnRNPK, in early premalignant stages and in development, progression, and prognosis of premalignant lesions and confirmed/frank head-and-neck malignancies, is described. In Example 28, the inventors demonstrate that S100A7 is a biomarker that can be used to predict the malignant transformation in oral dysplastic lesions.
Example 1—Samples and Reagents
Head-and-neck cancer and oral leukoplakia tissues were retrieved from an in-house, dedicated, research head-and-neck tissue bank, with approval from the Human Ethics Committee of All India Institute of Medical Sciences, New Delhi, India. With patient consent, biopsies/excised tissue specimens of oral leukoplakia and surgically resected specimens of HNSCCs, and paired non-cancerous tissues (each taken from a distant site) were collected and banked from patients undergoing treatment at the Department of Otorhinolaryngology, All India Institute of Medical Sciences. Normal tissues with no evidence of cancer (non-paired noncancerous controls) were collected from patients attending the Dental Outpatient Department of All India Institute of Medical Sciences for tooth extraction, after consent of the patients. After excision, tissues were flash-frozen in liquid nitrogen within 20 min of devitalization and stored at −80° C. until further use; one tissue piece was collected in 10% formalin and embedded in paraffin for histopathological analysis. The clinical and pathological data were recorded in a pre-designed proforma. These included clinical TNM staging (tumor, node, metastasis based on International Union Against Cancer's classification of malignant tumors, 1988), site of the lesion, histopathological differentiation, age, and gender of the patients.
The histologic diagnosis (dysplasia for OPLs and histological normal oral epithelium for controls) was rendered using microscopic examination of hematoxylin-and-eosin-stained frozen section of each research tissue block. The histologic diagnosis for each HNSCC sample was reconfirmed using microscopic examination of a hematoxylin-and-eosin-stained frozen section of each research tissue block. The tissue from the mirror face of the histologic section was then washed three times in approximately 1 ml of phosphate-buffered saline (PBS) with a cocktail of protease inhibitors as described previously (1 mM 4-(2-aminoethyl)benzenesulfonyl fluoride, 10 μM leupeptin, 1 μg/ml aprotinin, and 1 μM pepstatin) (21). The washed tissue was then homogenized in 0.5 ml PBS with protease inhibitors, using a handheld homogenizer. These homogenates were then flash frozen in liquid nitrogen and stored at −80° C. until use. Samples were thawed and clarified by centrifugation and the protein concentration determined by a Bradford-type assay using Bio-Rad protein quantification reagent (Bio-Rad, Mississauga, ON, Canada).
The iTRAQ experiments were performed in five sets of four samples each for the HNSCC samples. A pool of non-paired non-cancerous head-and-neck tissue homogenates was used as a control in each set of experiments: equal amounts of total protein from the lysates of six non-cancerous samples (non-paired controls) were pooled to generate a common reference “control sample” against which all the HNSCC samples were compared. Each sample contained 200 μg of proteins. Trypsin digestion and labeling were performed according to the manufacturer's (Applied Biosystems′) protocol; however, as double the manufacturer's recommended amounts were used, two individual vials of each reagent were used for labeling each sample. iTRAQ labeling was performed as follows: control (non-paired non-cancerous pool), iTRAQ reagent 114; two cancer samples, iTRAQ 115 and 117; individual non-cancerous tissue sample (paired or non-paired sample), iTRAQ 116. A total of five iTRAQ sets were analyzed resulting in ten cancer (five buccal mucosa and five tongue) samples and two paired non-cancerous plus three non-paired noncancerous samples being compared to the control sample. The paired non-cancerous samples originated from patients with cancer that were resected from sites a minimum of 2 cm away from the advancing edge of the cancer. Each iTRAQ set was analyzed with one run each of online 2D LC-MS/MS and offline 2D LC-MS/MS analyses.
The experiments with OPLs were performed in three sets of four samples; the same pool of non-cancerous oral-tissue homogenates was used as a control in each set of experiments. Each analytical set comprised 4×100 μg of each sample labeled as follows: control (normal pool) was labeled with one iTRAQ tag; two OPL samples were labeled with two other iTRAQ tags; and an individual histological normal tissue sample was labeled with the fourth iTRAQ tag. Thus a total of six OPLs and three histological normal samples were compared to the control sample in three iTRAQ sets. The order in which the samples were labeled within each of these three sets was randomized to minimize any systematic error and bias. The iTRAQ analysis of these samples was performed with one run of online reverse phase LC-MS/MS for preliminary examinations, and three replicate runs per set of online two-dimensional LC-MS/MS analyses.
Example 2—Strong Cation Exchange (SCX) Separation Conditions
For the offline 2D LC-MS/MS analysis, each set of labeled samples was first separated by SCX fractionation using an HP1050 high-performance liquid chromatograph (Agilent, Palo Alto, Calif., U.S.) with a 2.1-mm internal diameter (ID)×100-mm length polysulfoethyl A column packed with 5-μm beads with 300 Å pores (The Nest Group, Southborough, Mass.) as described previously (21). A 2.1-mm ID×10-mm length guard column of the same material was fitted immediately upstream of the analytical column. Separation was performed as previously described (21). Briefly, each pooled sample set was diluted with the loading buffer (15 mM KH2PO4 in 25% acetonitrile, pH 3.0) to a total volume of 2 ml and the pH adjusted to 3.0 with phosphoric acid. Samples were then filtered using a 0.45-μm syringe filter (Millipore, Cambridge, ON, Canada) before loading onto the column. Separation was performed using a linear binary gradient over one hour. Buffer A was identical in composition to the loading buffer, while Buffer B was Buffer A containing 350 mM KCl. Fractions were collected every two minutes using an SF-2120 Super Fraction Collector (Advantec MFs, Dublin, Calif.), after an initial wait of 2 minutes to accommodate the void volume. This resulted in a total of 30 SCX fractions per sample set. These fractions were dried by speed vacuuming (Thermo Savant SC110 A, Holbrook, N.Y.) and resuspended in 30 μl of 0.1% formic acid each.
For the online 2D LC-MS/MS analysis, an SCX cartridge (BioX-SCX, LC Packings, The Netherlands) was plumbed upstream of the reverse phase (RP) desalting cartridge and analytical column. This SCX cartridge was connected through a second valve on the Switchos unit as shown in FIG. 1. Samples were separated on this SCX cartridge using 10 μl step elutions with increasing concentration of ammonium acetate (10 mM, 50 mM, 100 mM, 150 mM, 200 mM, 250 mM, 300 mM, 350 mM, 500 mM and 1M). Each step elution was loaded onto the RP desalting column using the switching program as shown in FIG. 1, where the eluting peptides were desalted before loading onto the analytical column that was subsequently brought inline with the desalting column. The flow path used for these steps was designed to ensure that there was never any flow reversal through either of the cartridges (SCX or RP). Separation on the RP analytical column was effected as described for the second stage of the offline LC-MS/MS analysis described below.
Example 3—LC-MS/MS Run Conditions
The SCX fractions from 6 to 30 were analyzed by nanoLC-MS/MS using the LC Packings Ultimate instrument (Amsterdam, The Netherlands) fitted with a 10-μl sample loop. Samples were loaded, using a μl pick-up mode, onto a 5-mm RP C18 precolumn (LC Packings) at 50 μl/min and washed for 4 min before switching the precolumn inline with the separation column. The separation column used was either a 75-μm ID×150-mm length PepMap RP column from LC Packings packed with 3 μm C18 beads with 100 Å pores, or an in-house equivalent packed with similar beads (Kromasil; The Nest Group, Southborough, Mass.). The flow rate used for separation on the RP column was 200 nl/min with the following gradient:



















Time (min)
0
10
15
125
145
150
160
162
188







% B
5
5
15
35
60
80
80
5
Stop









Samples were analyzed on a QSTAR Pulsar i mass spectrometer (Applied Biosystems/MDS SCIEX, Foster City, Calif.) in information-dependent acquisition (IDA) mode with the scan cycles set up to perform a 1-s MS scan followed by five MS/MS scans of the five most abundant peaks for 2 s each. Every fourth scan the peak that was closest in intensity to the threshold of 10 counts was selected for MS/MS. Data acquisition was performed without any repetitions and with a dynamic exclusion of 30 s. Relative protein abundances were determined using the MS/MS scans of iTRAQ-labeled peptides (17). The iTRAQ-labeled peptides fragmented under collision-induced dissociation (CID) conditions to give reporter ions at 114.1, 115.1, 116.1, and 117.1 Th.
The ratios of peak areas of the iTRAQ reporter ions reflect the relative abundances of the peptides and, consequently, the proteins in the samples. Larger, sequence-information-rich fragment ions were also produced under these conditions and gave the identity of the protein from which the peptide was derived.
The OPL samples were analyzed on a Q-STAR Pulsar-i hybrid quadrupole/time-of-flight tandem mass spectrometer (Applied Biosystems/MDS SCIEX, Foster City, Calif.) in information-dependent acquisition (IDA) mode with the scan cycles set up to perform a 1-s MS scan followed by five MS/MS scans of the five most abundant ions for 2 s each. The method was also set up to select the least abundant ions in the MS scan that are nearest to a threshold of 10 counts on every fourth scan. Data acquisition was performed without any repetitions and with a dynamic exclusion of 30 s. Relative protein abundances were determined using the 114.1, 115.1, 116.1 and 117.1 Th reporter ions in the MS/MS scans of the iTRAQ-labeled peptides (23). The ratios of the peak areas of the iTRAQ reporter ions reflect the relative abundances of the peptides and the relative concentrations of the proteins in the samples. Larger, sequence-information-rich fragment ions were also produced under these MS/MS conditions and gave the identity of the protein from which the peptide originated.
Example 4—Data Analysis
The software used for data acquisition was Analyst QS 1.1 (Applied Biosystems/MDS SCIEX). Data were analyzed using ProteinPilot (21, 28) and the database searched was the Celera human database (human KBMS 20041109) with a total of 178, 243 entries, both provided by Applied Biosystems Inc. Identified proteins were grouped by the software to minimize redundancy. All peptides used for the calculation of protein ratios were unique to the given protein or proteins within the group; peptides that were common to other isoforms or proteins of the same family that were reported separately were ignored. The ProteinPilot cutoff score used was 1.3, which corresponds to a confidence limit of 95%.
Example 5—Statistical Analysis
The average iTRAQ ratios from different runs were calculated for each protein in the offline and online analyses. Thereafter, the iTRAQ ratios for each protein in the two analyses were averaged. Proteins that were selected for further analysis met the following criteria: (1) detection in ≧6 out of the 10 cancer samples, ≧50% of which showed differential expression≧1.5-fold relative to the control sample, and/or (2) known to be of interest from other studies. These proteins are listed in Table 1 along with two housekeeping proteins (to contrast the performance of the potential biomarkers).
For the OPL samples, the average iTRAQ ratios from the replicates were calculated for each protein. Proteins selected for further statistical analysis met the following criteria: (1) detection in ≧3 of 6 OPLs, and ≧50% of which showed differential expression≧50% higher than the control sample, and/or (2) known to be of interest based on their biological functions or associations with tumorigenesis. These proteins are listed in Table 6 along with two housekeeping proteins (to contrast the performance of the potential biomarkers).
Example 6—Biomarker Panel Analysis
To identify a panel of best-performing proteins that can distinguish between HNSCC and non-cancerous tissues, each protein in Table 1 was individually assessed for its ability to discriminate between normal and cancer samples by evaluating its receiver operator characteristic (ROC) curve based on the iTRAQ ratios. Plotting ROC curves and calculating the area-under-the-curve (AUC) and other attributes were performed using the ROCR package within the R statistical computing environment (29). Proteins giving the highest AUC values were selected for biomarker panel analysis and used as input variables into a Naïve Bayes model, implemented in JAVA (30) using the WEKA package (31). Given a sample i that has iTRAQ ratios (or IHC scores, see later) in the vector x(i), the Naïve Bayes model has the form:

P(i=cancer|x(i))=P(cancer)×P(x(i))|i=cancer)/P(x(i))

where P(i=cancer|x(i)) is the probability that i is a cancer sample given its x(i) values. This is the posterior probability and is calculated using Bayes theorem. A value≧0.5 is considered a positive hit. P(x(i)|i=cancer) is the probability that within the cancer samples, x(i) exists within them. P(cancer) is the probability of i being a cancer sample; this is the prior probability. P(x(i)) is the probability of i occurring and is a normalization factor. Nine trials of three-fold cross validation were used for each biomarker panel input into the Naïve Bayes model. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each trial.
To identify a panel of best-performing proteins that can distinguish between OPL and normal tissues, each protein in Table 6 was individually assessed for its ability to discriminate between histological normal and OPL samples by evaluating its receiver-operating characteristic (ROC) performance based on the iTRAQ ratio values in terms of sensitivity and specificity using the ROCR package within the R statistical computing environment (29, 30). Proteins giving the highest AUC values were selected for biomarker panel analysis and used as input variables into a Naïve Bayes model, implemented in JAVA (30) using the WEKA package (31). Nine trials of three-fold cross-validation were used for each biomarker panel input into the Naïve Bayes model. Sensitivity, specificity, PPV, and NPV were calculated for each trial and the averages are shown in Table 7A. The ROC curve for the panel of the three-best biomarkers—stratifin, YWHAZ, and hnRNPK—is depicted in FIG. 6A.
Example 7—Verification of Candidate Potential Cancer Markers (PCMS) by Immunohistochemistry
The three best-performing proteins from the above biomarker panel analysis were selected for immunohistochemical verification using an independent, larger sample set (Table 12). Antibodies against these three biomarkers were available commercially (Santa Cruz Biotechnology Inc., Santa Cruz, Calif., Table 13). Each antibody was first optimized with respect to dilution and the use of microwave heating in citrate buffer (0.01 M, pH 6.0) to expose the antigen (“antigen retrieval”). Paraffin-embedded sections (5 μm) of human HNSCCs (25 cases) and paired head-and-neck non-cancerous tissues from these patients (25 samples), as well as non-paired non-cancerous head-and-neck tissues (10 samples) were collected on gelatin-coated slides. For histopathological analysis, representative sections were stained with hematoxylin and eosin; immunostaining was done on serial sections as previously described (32). Following the application of a protein blocker for 10 min, deparaffinized tissue sections were first incubated with the primary antibodies for 1 h at room temperature or for 16 h at 4° C., followed by the respective secondary antibody conjugated with biotin. The primary antibody was detected using the streptavidin-biotin complex (DAKO LSAB plus kit, DAKO Cytomation, Denmark) and diaminobenzidine as chromogen. Slides were washed with 3× Tris-buffered saline (TBS, 0.1 M, pH=7.4) after every step. Finally, the sections were counterstained with Mayer's hematoxylin and mounted with DPX mountant. In the negative controls, the primary antibody was replaced by non-immune mouse IgG of the same isotype to ensure specificity. HNSCC tissue sections with known immunopositivity for specific proteins were used as positive controls in each batch of sections analyzed (32).
Example 8—Evaluation of Immunohistochemical Staining
The immunopositive staining was evaluated in five areas. Sections were scored as positive if epithelial cells showed immunopositivity in the cytoplasm, plasma membrane and/or nucleus when judged independently by two scorers who were blinded to the clinical outcome, i.e., the slides were coded and the pathologists did not have prior knowledge of the local tumor burden, lymphonodular spread, and grading of the tissue samples, while scoring the immunoreactivity. First, a quantitative score was performed by estimating the percentage of immunopositive-stained cells: 0<10% cells, 1=10-30% cells, 2=30-50% cells, 3=50-70% cells, and 4=>70% cells. Second, the intensity of staining was scored by evaluating the average staining intensity of the positive cells (0, none; 1, weak; 2, intermediate; and 3, strong). Finally, a total score (ranging from 0 to 7) was obtained by adding the quantitative score and the intensity score for each of the 60 sections. The immunohistochemical data were subjected to statistical analysis as described above for the MS results.
Example 9—Western Blot Analysis of Proteins in HNSCCS and Normal Tissues
Whole-cell lysates were prepared from five HNSCCs and five non-cancerous head-and-neck tissues. Frozen tissue samples were homogenized and lysed in a buffer containing 50 mM Tris-Cl (pH 7.5), 150 mM NaCl, 10 mM MgCl2, 1 mM ethylenediamine tetraacetate (pH 8.0), 1% Nonidet P-40, 100 mM sodium fluoride, 1 mM phenylmethylenesulfonyl fluoride, and 2 μl/ml protease inhibitor cocktail (Sigma). Protein concentrations were determined using the Bradford reagent (Sigma), and equal amounts of proteins (80 μg/lane) from the HNSCCs and non-cancerous tissues were resolved on 12% sodium dodecyl sulphate (SDS)-polyacrylamide gel. The proteins were then electro-transferred onto polyvinylidene-difluoride (PVDF) membranes. After blocking with 5% non-fat powdered milk in TBS (0.1 M, pH=7.4), blots were incubated with the respective primary antibodies (1:200 dilution) at 4° C. overnight. The protein abundance of alpha-tubulin was used as a control for protein loading, and was determined with mouse monoclonal anti-alpha-tubulin antibody (Clone B7, Santa Cruz Biotechnology Inc.). Membranes were incubated with the respective secondary antibody, HRP-conjugated rabbit/goat/mouse anti-IgG (goat anti-rabbit IgG, 1:5000; rabbit anti-goat IgG, 1:4000; or rabbit anti-mouse IgG, 1:2000, DAKO Cytomation, Denmark), and diluted with 1% bovine serum albumin for 2 h at room temperature. After each step, blots were washed three times with Tween (0.2%)-TBS. Protein bands were detected by the enhanced chemiluminescence method (Santa Cruz Biotechnology Inc.) on XO-MAT film.
The panel of the three-best biomarkers for OPLs-stratifin, YWHAZ and hnRNPK-together with two additionally promising proteins-S100A7 and PTHA-were evaluated for their performances using IHC on an independent set of 30 OPLs and 21 histological normal oral tissues. The inventors included S100A7 because it had high individual AUC value and was identified as one of the best-performing PCMs in the inventors' earlier iTRAQ analysis of HNOSCCs (23); it is important to determine whether overexpression of S100A7 occurs in early stages in the development of HNOSCC. PTHA was included because it also had high individual AUC value and had been reported to be important in other cancers (33-36). The sources of the antibodies and dilutions used for IHC are given in Table 13. After histological confirmations of dysplasia in OPLs and normal oral mucosa in the control tissues, paraffin-embedded tissue sections were processed for immunohistochemistry (23).
Briefly, after antigen retrieval, tissue sections were incubated with the primary antibodies (See Table 13 for details) for 16 h at 4° C., followed by the respective biotin conjugated secondary antibodies and detected using streptavidin-biotin complex (DAKO LSAB plus kit, DAKO Cytomation, Glostrup, Denmark) and diaminobenzidine as the chromogen. In the negative controls, the primary antibody was replaced by isotype specific non-immune mouse IgG to ensure specificity. HNOSCC sections with known immunopositivity for respective proteins as reported earlier (23) were used as positive control in each batch of sections analyzed (FIG. 20).
Example 10—Evaluation of Immunohistochemical Staining
Immunopositive staining was evaluated in five areas of the tissue sections as described (32). Sections were scored as positive if epithelial cells showed immunopositivity in the cytoplasm, plasma membrane, and/or nucleus when observed by two evaluators who were blinded to the clinical outcome. These sections were scored as follows: 0, <10% cells; 1, 10-30% cells; 2, 30-50% cells; 3, 50-70% cells; and 4, >70% cells showed immunoreactivity. Sections were also scored semi-quantitatively on the basis of intensity as follows: 0, none; 1, mild; 2, moderate; and 3, intense. Finally, a total score (ranging from 0 to 7) was obtained by adding the scores of percentage positivity and intensity for each of the 51 sections (30 OPLs and 21 histologically normal tissues). The immunohistochemical data were subjected to statistical analysis as described above for the iTRAQ ratios.
Example 11—Western Blot Analysis of 14-3-3 Proteins in OPLS and Normal Tissues
Whole-cell lysates were prepared from 3 OPLs and 3 normal oral tissues using lysis buffer containing 50 mM Tris-Cl (pH 7.5), 150 mM sodium chloride, 10 mM magnesium chloride, 1 mM EDTA (pH 8.0), 1% Nonidet P-40, 100 mM sodium fluoride, 1 mM phenylmethylene sulphonylfluoride, and 2 μl/ml protease inhibitor cocktail (23). Equal amounts of proteins (80 μg/lane) from OPLs and normal tissues were resolved on 12% SDS-polyacrylamide gels. The proteins were then electro-transferred onto polyvinylidene difluoride (PVDF) membranes. After blocking with 5% non-fat milk in TBS (0.1 M, pH 7.4), blots were incubated at 4° C. overnight with the respective antibodies (details given in Table 13). The sources of the antibodies and dilutions used for IHC for OPL markers are given in Table 13. Protein abundance of α-tubulin served as a control for protein loading. Membranes were incubated with the respective secondary antibodies, horseradish peroxidase-conjugated rabbit/goat/mouse anti-IgG diluted at the appropriate dilution in 1% BSA for 2 h at room temperature. After each step, blots were washed three times with Tween (0.2%)-Tris-buffer saline (TTBS). Protein bands were detected by the enhanced chemiluminescence method (ECL, Santa Cruz Biotechnology Inc.) on XO-MAT film.
Example 12—Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Analysis
To determine if overexpression of the five proteins in OPLs were due to increase in the transcript levels, RT-PCR analysis was performed using total RNA isolated from OPLs and normal oral mucosa (3 each), using gene-specific primers for YWHAZ, stratifin, hnRNPK, S100A7 and PTHA, and beta actin as a control (See Table 14 for gene-specific primer sequences (synthesized by Microsynth, Switzerland) and PCR conditions used). Synthesis of complementary DNAs (cDNAs) were carried out by reverse transcription of 2.0 μg of total RNA using MMLV reverse transcriptase. PCR amplification was carried out in a total volume of 20 μl containing 3 μl reverse transcribed cDNA, 10×PCR buffer, 10 mM dNTPs, 20 μM of each primer and 1 U of Taq polymerase. After 5 min of initial denaturation, 32 amplification cycles of 1 min at 94° C.—1 min at specific annealing temperature and 1 min at 72° C.—were carried out, followed by a 10-min elongation at 72° C. β-actin was used as a control to optimize the amounts of cDNAs generated. PCR products were separated on 1.5% agarose gel, stained with ethidium bromide, and visualized with Chemilmager IS-4400 (Alpha Innotech Corp., CA) (23).
Example 13—Network Analysis
The 30 proteins listed in Table 6 were used for network analysis. HUGO or SwissProt accession numbers were imported into the Ingenuity Pathway Analysis (IPA) Software (Ingenuity Systems, Mountain View, Calif.). The IPA database consists of proprietary ontology representing 300 000 biologic objects ranging from genes, proteins, and molecular and cellular processes. More than 11 200 human genes are currently represented in the database. The proteins were categorized based on location, cellular components, and reported or suggested biochemical, biologic, and molecular functions using the software. The identified proteins were mapped to networks that were generated based on evidence from existing literature available in the Ingenuity database and then ranked by score. A score of 3 or higher has a 99.9% confidence level of not being generated by random chance alone and was used as the cutoff for identifying protein networks. The molecules identified in the networks and their cellular functions are given in Table 15.
Provided below is a summary of the results obtained by the inventors in connection with the experiments of Examples 1-13:
The offline and online 2D LC-MS/MS analyses collectively resulted in the identification of a total of 811 non-redundant proteins. Only a few of these proteins displayed consistent differential expression in the HNSCC samples (measured in ≧6 out of the 10 samples and with ≧50% showing ≧1.5-fold differential expression relative to the control sample) that warranted further analysis. These proteins, all confidently identified with ≧two peptide matches (except APC-binding protein EB1 and superoxide dismutase [Mn]) are given in Table 1 along with two structural proteins, actin and β-2-tubulin, as controls. (See Table 11 for peptide sequences and coverage, and FIG. 19A for the CID spectra of the single-peptide identifications.) As the nanoLC analyses were performed on 25 SCX fractions, the acquired data files were searched in two groups out of necessity (the version of ProteinPilot software available at that time was incapable of handling a large number of data files each with a large amount of data). Fractions 6-15 were, therefore, searched in one group, while fractions 16-30 were searched in a second group.
The ProteinPilot result files from these two halves were then exported into an Excel spreadsheet where the proteins of interest from the two searches were combined by averaging the ratios for the protein in each sample. It is noteworthy that each of the ratios reported by searching either half of the fractions is itself comprised of the ratios from multiple peptides identified in the given protein. ProteinPilot automatically only includes unique and high-confidence matches of peptides for any particular protein in the ratios reported (i.e., it excludes those that are shared between different isoforms of any protein or low-confidence matches to peptides). These averaged ratios from the offline and online analyses were then again averaged and reported in Table 1. Of all the individual expression ratios (two offline and two online), 56.4% varied by less than 10% from their respective average shown, and 82.0% varied by less than 20%. It is reassuring that the expression ratios from different analyses and separate handling were comparable.
Nine proteins that did not meet the cutoff criteria stated above—cytokeratin 14, polybromo 1D, PKM2, annexin A1, nucleophosmin 1, Hsp27, cystatin B, GRP 94, and MARCKS—were also included in Table 1 for further analysis, as these had been reported in head-and-neck cancer or are of biological relevance in cancer. The HNSCCs analyzed included five squamous-cell carcinomas (SCCs) of buccal mucosa and five SCCs of the tongue. The rationale for the choice of these two SCC types was to determine if there are site-specific protein expressions or not. The best-performing proteins that can differentiate between HNSCC and non-cancerous tissues were identified by determining the individual ROC curves of the proteins in Table 1 (as described in the Experimental section). The three proteins with the highest AUC values-YWHAZ, stratifin and S100A7—are listed in Table 2 together with their individual and collective figures-of-merit, including sensitivity (cancer samples correctly identified as cancer samples) and specificity (normal samples correctly identified as normal samples). As a panel, the three best-performing biomarkers achieved a sensitivity of 0.92 and a specificity of 0.91 in discriminating HNSCC from non-cancerous head-and-neck tissues (Table 2 and FIG. 2a).
A number of proteins, e.g., prothymosin alpha and APC-binding protein EB1, were predominantly overexpressed in SCCs of buccal mucosa (Table 1) and showed some promise in differentiating between SCCs of buccal mucosa and the tongue; however, as the number of samples are small, this possibility will need to be fully investigated in a future study involving more samples of both types.
Verification of candidate protein biomarkers is a necessary step in moving from the initial discovery to possible application. The panel of three best-performing biomarkers identified by MS analysis—YWHAZ, stratifin and S100A7—were chosen for verification in a different and larger set of HNSCCs and non-cancerous head-and-neck tissues. Verification exercises included immunohistochemical (FIG. 3) and Western blot analyses (FIG. 4) at the protein level, as well as RT-PCR analysis (FIG. 5) at the mRNA level. All verification results support the above MS findings. In the immunohistochemical analysis, the biomarker panel of YWHAZ, stratifin and S100A7 achieved a sensitivity of 0.92 and a specificity of 0.87 (Table 3 and FIG. 2b) in discriminating HNSCCs from non-cancerous head-and-neck tissues. The paired non-cancerous head-and-neck tissues obtained from HNSCC patients might have altered protein expressions prior to histological changes.
To investigate this possibility, the noncancerous tissues were segregated into paired and non-paired groups and evaluated separately with the HNSCCs. Significantly, the panel of the three biomarkers—YWHAZ, Stratifin and S100A7—appears to perform better in discriminating HNSCC tissues against the non-paired non-cancerous head-and-neck tissues (sensitivity, 0.96; specificity, 0.96) than against the paired non-cancerous tissues (sensitivity, 0.92; specificity, 0.83) (see Table 4). These results appear to support the notion of protein-expression alterations prior to histological changes and caution the use of only paired samples.
The LC-MS/MS analyses of OPLs collectively resulted in identification of 439 non-redundant proteins; 216 were identified as single hits with more than 95% confidence. Of all the proteins identified, only 17 passed the inventors' criteria for further statistical analysis (vide supra). Of this subset, 15 proteins were confidently identified with a minimum of two peptide matches in each case (See Table 11 for peptide sequences and coverage). Two proteins, parathymosin and DLC1 were identified by single peptides (See FIG. 19B-E for the CID spectra of the single-peptide identifications). These 17 proteins are given in Table 6, along with two structural proteins, β-actin and gelsolin precursor, as controls. Table 6 also depicts the variations in the levels of overexpressed and underexpressed proteins in individual OPL and histological normal tissues versus the pooled normal control. These differential expression levels were averages of the replicate injections: 56.4% of the ratios varied by less than 10% from their respective averages shown, and 82.0% varied by less than 20%.
Thirteen proteins that did not meet the aforementioned initial criteria—IGL2, p37AUF1 (hnRNPD), SOD2, PKM2, hnRNPA1, HSP27, cofilin, glyceraldehyde-3-phosphate dehydrogenase, NDP kinase B, elongation factor 2, CALM3, PEBP and S100A7—were also included in Table 6 for further analysis, as they are of biological relevance in cancer development. Of these, 11 proteins were confidently identified with a minimum of two peptide matches in each case (see Table 11B-E for peptide sequences and coverage). p37AUF1 (hnRNPD) was identified by a single peptide with a confidence of 99% (see FIG. 19D for the CID spectra of the single-peptide identification). SOD2 was identified by more than one unique peptide; however, the best-matching peptide was identified with a confidence of only 93%. Although this peptide did not meet the inventors' stipulated criteria for acceptance, manual verification of the spectrum showed good sequence coverage for this peptide (FIG. 19E). Furthermore, the cumulative score, which included the lower confidence peptide matches, was >2.0 and corresponded to a confidence of 99%.
The best-performing proteins that can differentiate between OPLs and normal tissues were identified by determining the individual ROC curves of the proteins in Table 7. The three proteins with the highest AUC values-YWHAZ, stratifin and hnRNPK—are listed in Table 7A together with their individual and collective figures-of-merit, including sensitivity and specificity. As a panel, these three biomarkers achieved a sensitivity of 0.83 and a specificity of 0.74 in discriminating OPLs from histological normal oral tissues (Table 7A and FIG. 6A).
Verification of Candidate Biomarkers by Immunohistochemistry, Western Blot, and RT-PCR Analyses.
The panel of three potential biomarkers, YWHAZ, stratifin and hnRNPK, and two other proteins with high AUC values, S100A7 (0.56) and PTHA (0.56), were chosen for verification in an independent set of OPLs (30 cases) and normal tissues (21 cases) by IHC. Representative levels of expression and subcellular localizations of all five proteins in oral dysplastic tissues in comparison with normal tissues are shown in FIG. 7A-E. (FIG. 20 depicts the positive and negative controls used for each protein analyzed by IHC.) These data were further verified by Western blot analysis (FIG. 8A) at the protein level, as well as RT-PCR analysis at the mRNA level (FIG. 8B).
The differential expression suggested by iTRAQ ratios tended to be moderate, whereas the results of Western and RT-PCR analyses tended to show more extreme differential expression. Thus, Western and RT-PCR analyses, verified the differential expression reported by the iTRAQ analysis in trend, but not in scale. This discrepancy of scale has also been noted in other studies and has been ascribed to compression of the dynamic range of iTRAQ ratios (21). Specifically, in that study the inventors determined that a two-fold differential expression as determined by iTRAQ analysis was in reality closer to a four-fold differential expression in an absolute quantification study that was performed on the same samples. Importantly, in IHC analysis, the biomarker panel of YWHAZ, stratifin, and hnRNPK achieved a sensitivity of 0.91 and a specificity of 0.95 (Table 8B and FIG. 6B) in discriminating OPLs from histological normal oral tissues.
Network Analysis.
To gain insight into the plausible biological processes in which these proteins might be involved, the inventors used the Ingenuity Pathway Analysis tools (Ingenuity Systems, Inc. software) and discovered two major networks (Table 15) in OPLs (the merged network is shown in FIG. 8C). To the best of the inventors' knowledge, ours is the first study reporting differential expressions of p37AUF1 and histone H2B.1 in OPLs. These proteins and their cellular functions are listed in Table 11.
Without being bound by theory, the results obtained in the experiments of Examples 1-13 are discussed below:
Multidimensional LC-MS/MS has been used for the analysis of clinical samples of HNSCCs labeled with isobaric mass tags (iTRAQ) to identify proteins that are differentially expressed in head-and-neck cancer in relation to non-cancerous head-and-neck tissues. The expression ratios were consistent between the online and offline 2D LC-MS/MS methods used, demonstrating that the methodologies were rugged and reproducible, even though the conditions and details used in peptide elution from the SCX columns in the two methods were different. Expectedly, the numbers of proteins identified by the online analysis (431) was lower than those identified by the offline analysis (580), due to the lower capacity of the SCX cartridge used in the former (50 ng of total peptides versus up to 1 mg in the latter). However, the online analysis was advantageous in terms of shorter data acquisition time and lower amounts of total sample required.
Development of HNSCC is a multistep process that often involves field cancerization, a phenomenon in which not only the site of the primary tumor, but the entire mucosa of the upper aerodigestive tract, is prone to undergoing malignant transformation or progression at multiple sites (37). It is now evident that molecular changes underlying field cancerization are not localized to areas with altered histology, but may persist beyond the histological border of precancerous lesions; a large fraction of the carcinogen-exposed field may harbor molecular aberrations without presenting clinical or morphological symptoms (6 and references therein). Identification of proteins with altered expression as a manifestation of field cancerization is important in identification of biomarkers for prediction of risk of recurrence, as well as for development of second primary tumors in patients treated for HNSCC. Thus, the selection of normal controls for HNSCCs in a differential expression analysis, including the current study, is non-straightforward and requires careful planning.
To address this issue, the inventors have included two types of non-cancerous histologically confirmed normal tissues in the inventors' analysis: (1) noncancerous tissues obtained from HNSCC patients from a site distant to the tumor, and (2) normal tissues obtained from individuals with no evidence of cancer or pre-cancerous lesions. In a recent proteomic study, Roesch-Ely et al. (12) investigated changes in protein expressions occurring in different stages of tumorigenesis and field cancerization in HNSCCs. A number of reported differentially expressed proteins, including calgizarrin, stratifin, histone H4, and cystatin A, are also identified in this current study. This study appears to be the first reporting differential expression of calmodulin-like protein 5, polybromo-1D, APC-binding protein EB1, α-1-antitrypsin precursor, carbonic anhydrase I, mast cell tryptase β-III, histone H2B.1, L-plastin, and peptidylprolyl isomerase A (PPIA) in HNSCC.
Among the differentially expressed proteins identified, no single protein emerged as a unique marker for HNSCC. However, a panel of three best-performing biomarkers YWHAZ, Stratifin and S100A7 performed satisfactorily, as determined by both MS and immunohistochemistry on independent sets of samples. Significantly, YWHAZ has previously been identified by the inventors to be overexpressed in oral cancer at the mRNA level and has subsequently been verified using immunohistochemical analysis (38, 39). This serves as an independent validation of and complements the current results. Furthermore, YWHAZ has also been reported to be overexpressed in stomach cancer (40), and in breast and prostate tumor model systems (41, 42). More importantly, YWHAZ is not overexpressed in lung-cancer tissue samples (43), thus illustrating the fact that this protein can provide some selectivity in discriminating among different cancer types.
Stratifin has been reported to be overexpressed in HNSCC. A recent proteomic study reported a 3.6-fold straffin overexpression (44), thus corroborating the results obtained in this study. A second independent study also showed stratifin overexpression in the range of 2.8-9.1-fold in cancer samples (45). In addition, a study of 300 patients with pancreatic ductal adenocarcinoma showed stratifin overexpression in 82% of primary infiltrating adenocarcinomas, while another 15% showed weak immunopositivity. Overexpression of stratifin correlated with poor prognosis (46). Interestingly and significantly, stratifin was reported to be down-regulated in HNSCCs by Roesch-Ely et al. (12), whereas the inventors observed consistent overexpression of stratifin in iTRAQ and in IHC verification analysis. The HNSCCs in the study of Roesch-Ely et al. (12) are from the German population with tobacco smoking and alcohol consumption being the major risk factors, while the clinical samples in this study, and in Lo et al. (15, 44) and Chen et al. (45) are from Asian populations, where in addition, chewing tobacco and/or betel quid, and bidi smoking are important risk factors. These differences in the risk factors may account for the observed variations in stratifin expression and warrant in-depth investigation in a larger study.
14-3-3 proteins recognize phosphoserine/threonine (pS/T)-containing motifs used by a variety of signal transduction pathways to bind over 200 target proteins that play important roles in the regulation of various cellular processes, including mitogenic and cell-survival signaling, cell-cycle control and apoptotic cell death, epithelial-mesenchymal transition, and cell adhesion, invasion and metastasis (46). The involvement of 14-3-3 proteins in the regulation of oncogenes and tumor suppressor genes points to a potential role in tumorigenesis (47); multiple pathways can be targeted by modulation of these proteins, underscoring their potential as candidate drug targets. Although it might be argued that 14-3-3 proteins are, therefore, too pleiotropic to be targets for therapeutic inhibition, it has been shown that simultaneous inactivation of all 14-3-3 proteins sensitizes cancer cells to DNA-damaging agents. Selective inactivation of stratifin leads to an increased sensitivity towards cancer chemotherapeutic agents. Recent studies have shown that stratifin forms homodimers, while YWHAZ forms homodimers and also heterodimers with other isoforms (48-50). Stratifin has been extensively investigated; by contrast, YWHAZ remains largely unexplored. It is noteworthy that the potential success of strategies aimed at modulating 14-3-3 availability in the cell for cancer therapy is provided in studies showing that reducing cellular 14-3-3 increases chemosensitivity (51, 52).
Cytokeratin 14 has also been demonstrated to be overexpressed in many squamous cell carcinomas. A study using immunohistochemical analysis demonstrated that 67 of 74 cases of squamous cell carcinomas showed immunoreactivity regardless of origin, suggesting cytokeratin to be a useful marker for squamous cell carcinoma (53). Another study, comparing mRNA levels of cytokeratin 14 between oral squamous cell carcinoma and leukoplakia samples reported that the former showed a higher amount of cytokeratin 14 (54).
Prothymosin alpha, found to be overexpressed here in HNSCC, has recently been proposed to be a potential marker of proliferation in patients with thyroid cancer (55). This protein was implicated in various other cancers, including gastric, lung, liver, colon, and breast cancers (33-36, 56, 57). Prothymosin alpha was proposed to be a surrogate marker for the diagnosis of estrogen-negative breast-cancer cases (56), and a urinary marker for the detection and monitoring of bladder cancer (58). Prothymosin alpha expression has been observed in lymph nodes and tonsils (59). This expression in lymph nodes of HNSCC patients would correlate with locoregional spread of the disease and may be a determinant of disease prognosis. Prothymosin alpha is a small, highly acidic, nuclear protein that has been proposed to play a role in cell proliferation and immune regulation (60).
Protein changes related to cytoskeletal reorganization, cellular metabolism, and protein-protein interactions have been observed, based on which a model for its immunological mode of action has been proposed (60). Interestingly, some of the proteins identified in that study, such as L-plastin, HSP90, vinculin, aldolaseA, meosin, and galectin 3 are found to be overexpressed in the present study as well, although not all of them are included in Table 1.
L-plastin is expressed by hematopoetic cells and by most human cancer cell lines, including human submandibular gland cell lines (61, 62); yet, its functional importance in tumor tissues is controversial: its expression correlates with tumor progression in colon cancer, but not in breast cancer; in melanoma, L-plastin phosphorylation promotes tumor cell invasion (reviewed in 61). Intriguingly, L-plastin has also been proposed to represent a novel target for cancer therapy, and the constitutive activity of its promoter in non-hematopoetic tumors presents novel perspectives for cancer gene therapy using L-plastin promoter-driven viral vectors (61).
S100A7, a small calcium-binding protein of the S100 protein family, originally identified in psoriatic keratinocytes, is up-regulated in abnormally differentiating keratinocytes, squamous carcinomas of different organs, and in a subset of breast tumors (62-66). Incidentally, S100A7 was also identified in oral premalignant epithelia by microarray analysis and proposed to be a marker for invasion (63). It has been hypothesized to play a role in breast-tumor progression by promoting angiogenesis and enhancing the selection of cells that overcome their anti-invasive function (64). This hypothesis has also been suggested to explain why S100A7 expression is high in high-grade or estrogen-receptor negative tumors, as these are associated with increased hypoxia and reactive oxygen species (ROS), a scenario in which the angiogenic effects of S100A7 are most important.
It is noteworthy that increased hypoxia and ROS also occur in head-and-neck tumors and might explain the observed changes in S100A7 expression here. Another study in breast cancer showed that BRCA1 is a transcriptional repressor of S100A7. BRCA1 and c-Myc form a complex on S100A7 promoter, and BRCA1-mediated repression is dependent on a functional c-Myc (68). Furthermore, BRCA1 mutations in tumors abrogate the repression of S100A7. In the absence of BRCA1, S100A7 is induced by topoisomerase II poison and etoposide, as well as increases the cellular sensitivity to etoposide, suggesting a mechanism for BRCA1-mediated resistance to etoposide (68). Incidentally, BRCA1 alterations have been reported in head-and-neck cancer (69, 70). However, a correlation, if any, between BRCA1 alterations and S100A7 expression in head-and-neck cancer remains to be demonstrated.
Calgizzarin (S100 A11) has also been previously linked with cancer and was reported as a potential marker for head-and-neck cancer (18). Likewise, S100 A2, which shows overexpression in HNSCC is also known to be overexpressed in other forms of cancer, such as non-small cell lung cancer and uterine leiomyoma (71, 72). It has been demonstrated that calgizzarin plays an anti-apoptotic role in uterine leiomyosarcoma cell line (72). Fascin has been discovered to be an early marker for esophageal squamous cell carcinoma (73). The inventors have previously reported pyruvate kinase M2 to be overexpressed in head-and-neck cancers (17, 21). Several studies suggest that PKM2 is present primarily in a dimeric form in tumors, and is useful as a biomarker in their early detection (74-78). PKM2 overexpression in tumor cells is explained on the basis of its key role in the generation of ATP in the glycolytic pathway. Under hypoxic conditions that are typical for tumors, this pathway is a critical route by which tumors satisfy the higher energy requirements needed for proliferation (reviewed in 79, 80).
Two of the more interesting proteins discovered in this current HNSCC study are the APC-binding protein EB1 and polybromo-1D. End-binding protein 1 (EB1) was initially discovered as a protein that binds adenomatous polyposis coli protein (APC) at its C-terminal region (81). More recently, however, it has also been shown to bind tubulin and has been detected to associate with the microtubules that form the mitotic spindle during mitosis (82).
The EB1 interaction with APC is of particular interest as APC is a tumor suppressor whose inactivation leads to a significantly enhanced level of susceptibility for malignant transformation in colorectal cancer (82). Among others, APC binds to β-catenin and possibly controls β-catenin's availability in the cytoplasm (82). By virtue of APC's binding to tubulin, EB1 participates in microtubule-dependent processes, including intracellular vesicle trafficking, organization of organelles within the cell, and even cell migration (82).
One possible proposed explanation for the mechanism of action of EB1, is that overexpression of EB1, at least in esophageal squamous cell carcinoma, affects the interaction between APC and β-catenin, and that this overexpression correlates with the nuclear accumulation of β-catenin (82). Normally, APC in combination with glycogen synthase kinase 3β (GSK 3β) and axin forms a destruction complex that phosphorylates free β-catenin in the cytoplasm, which in turn targets it for ubiquitination and degradation (82). Disruption of APC interaction with β-catenin by EB1 overexpression leads to increased levels of β-catenin in the nucleus, which in turn binds to T-cell factor/lymphoid-enhancing factor (TCF/LEF) and activates transcription of target genes such as c-myc and cyclin D1. Thus, the overexpression of EB1 is thought to play a role in the development of esophageal squamous cell carcinoma by indirectly causing the activation of the β-catenin/TCF pathway (83). It is, therefore, possible that overexpression of EB1 in this study could be the first evidence for the same process occurring in HNSCC.
Polybromo 1D (PB1), also known as BRG1-associated factor 180 (BAF180), is a relatively new member of the SWI/SNF-B (PBAF) chromatin remodeling complex that is a homolog of the yeast rsc protein complex, which is required for progression through mitosis (84). In fact, antibodies against BAF180 localize to the kinetochores during mitosis (84). The fact that both PB1 and EB1 are known to be involved with mitosis is also noteworthy, but requires further investigation to ascertain if a direct relationship between the two exists. Other studies have shown that in yeast, rsc can act as an activator as well as a suppressor of transcription, and that it can be functionally linked with the PKC pathway (85, 86).
Additionally, it was shown that temperature-sensitive mutants of one of the proteins (nps1) in the rsc complex, when placed at the restrictive temperature, can be rescued by the overexpression of not only the yeast homolog of PKC, PKC1 (as well as other proteins downstream of the PKC1 signal pathway), but also by Bim1p, which is the yeast homolog of EB1 (85). It was further demonstrated that there is no direct interaction between Pkc1p and Bim1p, or any activation of BIM1 transcription or post-transcriptional regulation by Pkc1p, but that suppression of the activity of overexpressed Pkc1p requires a functional Bim1p (85).
In addition to the possibility of this potentially significant link between PB1 and EB1, there is also independent evidence suggesting that PB1 is a tumor suppressor and that this activity is found in lung cancer but not in breast cancer (86). This was verified when transfection of BAF180 gene into breast tumor cell lines, possessing a truncated version of the same gene, resulted in growth inhibition (86). Other members of this complex that have been associated with cancer include hSNF5/INI1 and BRG1 itself. HSNF5/INI1 mutations have been found in malignant rhabdoid tumors, while mutations in BRG1 have been noted in various cell lines including carcinomas of the breast, lung, pancreas and prostate. Implication of other members of the PBAF complex in suppression of various cancers, in addition to the above evidence which suggests that PB1 may be a tumor suppressor itself, makes PB1 an exciting discovery in the inventors' study. In light of PB1's suggested tumor suppressor role, the presently observed lower expression of this protein in the HNSCC samples is consistent with expectations and warrants in-depth investigation of its role in head-and-neck tumorigenesis.
Thus, the use of iTRAQ-labeling of head-and-neck cancers combined with LCMS/MS has led to the discovery of several novel, differentially expressed proteins in these tumors. A panel of the three best-performing biomarkers achieved a sensitivity of 0.92 and a specificity of 0.91. This performance was verified using immunohistochemistry on a larger, independent set of clinical samples of HNSCCs.
The unique features of the OPL study are its prospective nature, the large number of patients in this type of disease setting, and the length of follow-up of leukoplakia and HNOSCC patients. Table 7 also shows the analysis of three histological normal samples used in a previous exercise to demonstrate consistency and validity over a period of six months (23). The number of OPLs examined in this study—six for the LC-MS/MS and 30 for subsequent verifications—was relatively modest, but was necessitated by the small number and size of OPL samples available. Nevertheless, the inventors successfully demonstrated the utility of iTRAQ-labeling of small OPL biopsy specimens and detection of a large number of expressed proteins that led to the discovery of a panel of candidate OPL biomarkers.
Replicate analyses demonstrated that the expression ratios were reproducible-82% were within 20% of the averages shown in Table 6. Differential expressions analyses of the proteomes between OPLs and histological normal oral tissues revealed 30 proteins that merit further examination and verification. A panel of three potential biomarkers selected by ROC analyses and two other biologically relevant proteins that had high AUC values were successfully verified to be overexpressed using an independent and larger set of OPLs and histological normal tissues by IHC and Western analyses, thus confirming findings of the iTRAQ analyses. In addition, RT-PCR analyses showed increased levels of transcripts for all five proteins, suggesting that the increased protein expressions were due to upregulation at the transcriptional level.
The inventors' approach enabled identifying in oral premalignant lesions a large number of proteins, including mediators of inflammatory response, redox system, proteases, chaperones, transcriptional regulators, calcium binding proteins, metabolic enzymes, and proteins involved in cell proliferation and growth, intermediary metabolism, signal transduction, cell cycle regulation, cell death, cell motility and cell morphology. Pathway analyses unraveled important novel links between inflammation and cancer. Importantly, it showed direct interaction between all the three proteins-YWHAZ, stratifin and hnRNPK—that constitute the panel of OPL biomarkers (87). The mechanism involved in upregulation of YWHAZ and stratifin in OPLs remains unknown.
hnRNPK is an RNA-binding protein that regulates gene expression at both transcriptional and translational levels (88, 89). Therefore, the inventors speculate that hnRNPK may be involved in regulation of YWHAZ and stratifin in OPLs. The data analysis also suggests that hnRNPK directly regulates the expression of COX2, enzyme implicated in the synthesis of prostaglandins, which are mediators of the inflammatory response. The inventors' earlier in vitro and in vivo studies demonstrated that COX-2 activation and NF-kB overexpression are parallel events occurring in early precancerous stages of tobacco-associated oral carcinogenesis and these events remain elevated down the tumorigenic pathway (90), while others demonstrated a role for 14-3-3 proteins in the nuclear export of p65-Iκβ-alpha complexes (91) and the role of 14-3-3 in phosphorylation of beta-catenin by AKT that promotes beta-catenin transcriptional activity (92) as well as in apoptosis and cell adhesion emphasizing the oncogenic character of 14-3-3 zeta (YWHAZ) (93). Tobacco carcinogens, including tobacco specific nitrosamines (TSNA), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), appear to activate these proteins involved in the inflammatory response of epithelial cells and initiation of the carcinogenic cascade.
The other important links identified are regulation of NF-kB by SERPINA1 and phosphatidyl ethanolamine binding protein 1 (PEBP1). SERPINA1 has been shown to reduce the activation of NF-kB; decrease in SERPINA1 levels in OPLs may partly account for activated NF-kB in OPLs. Pathway analyses also showed, for the first time, that deregulation of calcium-associated proteins (cystatin B, FABP5, and S100A7) and mitochondrial dysfunction (SOD2) may play an important role in the development of OPLs. Importantly, YWHAZ was found to directly interact with nucleophosmin (NPM1), an important protein involved in increased cellular proliferation, and with HSP90B1, which has been reported to increase the activity of ERK. HSP90B1, YWHAZ, nucleophosmin1, parathymosin (PTMS), SOD2, and PEBP1 are all involved in the inhibition of apoptosis.
Furthermore, HSP90B1, SOD2, and stratifin are associated with increased cell viability. Increased expressions of hnRNPK, PTHA, stratifin, SOD2 and nucleophosmin1, and reduced expression of DLC1, play a role in hyperproliferation of cells. Increased cell proliferation and inhibition of apoptosis are two hallmarks of cancer, and the inventors' data suggest that both events are occurring in early, premalignant stages. Alterations in cytoskeleton are important events in tumorigenesis; deregulation of YWHAZ and its interaction with MARCKs, beta actin and tubulin identified herein suggest the implication of cytoskeletal reorganization in development of oral dysplasias.
It is noteworthy that invasion is an important event in the progression of dysplasia as well as of cancer, and five proteins identified in the inventors' study—underexpressions of DLC1, IGHG1 and FABP5, and overexpressions of S100A7 and PEBP1—are all involved in cell invasion. Significantly, this is the first report of p37AUF1 (hnRNPD) expression in OPLs, and pathway analyses suggest its potential interaction with stratifin and scaffold protein b (SAFB). PEBP1 is oncogenic, while FABP5 and SERPINA1 are metastatic. Taken together, the discovery of these alterations in OPLs suggests that these proteins may be associated with the potential of malignant transformation. The findings herein certainly warrant additional validation; elucidation of functional significance in future studies will provide further insight into the biology of development and progression of OPLs.
None of the aforementioned proteins can be classified individually as specific biomarkers for OPLs. However, a panel of the three best-performing biomarkers: YWHAZ, stratifin, and hnRNPK confer satisfactory performance. The current study clearly demonstrates overexpression of YWHAZ in OPLs, suggesting its involvement in early stages of oral carcinogenesis. Mechanistically, YWHAZ overexpression increases p53 protein degradation via hyperactivation of the phosphoinositide 3-kinase (PI3K)-Akt signaling pathway that phosphorylates MDM2 (92-95). Replacement of p53 leads to luminal cell apoptosis. YWHAZ is known to be involved in diverse cellular processes, many of which are deregulated in HNOSCCs (39). The inventors' ongoing studies on functional analysis of YWHAZ in oral cancer cells have also shown its involvement in the activation of PI3K-Akt signaling pathway and cytoskeletal reorganization (data not shown).
Stratifin, another member of the 14-3-3 protein family, was overexpressed in OPLs and emerged as one of the best-performing potential biomarkers. The inventors' present data suggest that the increase in stratifin expression is an early event in the development of cancer. Importantly, their recent proteomic analysis showed overexpression of stratifin in HNOSCCs (23); underscoring its importance in head-and-neck tumorigenesis (87). Interestingly and significantly, stratifin was reported to be down-regulated in HNSCCs by Roesch-Ely et al., (12), whereas the inventors observed consistent overexpression of stratifin in iTRAQ and in IHC verification analyses. The HNSCCs in the study of Roesch-Ely et al. (12) were from the German population with tobacco smoking and alcohol consumption being the major risk factors; while the clinical samples in this study, and in Lo et al. (44), were from Asian populations, where in addition, chewing tobacco and/or betel quid, bidi smoking and HPV infection are important risk factors. In support of these observations, Bhawal et al., (96) reported that hypermethylation of stratifin promoter is not a frequent event in HNSCC. Moreover, IKK alpha, a catalytic subunit of the IKK complex, has been shown to protect the stratifin locus from hypermethylation; this function serves to maintain genomic stability in keratinocytes.
Heterogeneous nuclear ribonucleoprotein K protein (hnRNPK), identified by iTRAQ analysis and verified by IHC in OPLs, is an interesting protein that has been strongly implicated as a key player of tumorigenesis (87). hnRNPK is overexpressed, aberrantly localized, and associated with poor prognosis in colorectal cancer (88), while its transcriptional upregulation was reported in OSCC (89). In view of a role of hnRNPK as a transformation-related protein, its overexpression in OPLs is an important finding; in-depth studies are warranted to establish its link, if any, with transformation potential of OPLs.
Prothymosin alpha, overexpressed in a subset of OPLs, has been proposed to be a proliferation marker in patients with thyroid cancer (55). This protein was implicated in various other cancers, including gastric, lung, liver, colon, and breast cancers (33-36, 55-60). S100A7, a small calcium-binding protein, is upregulated in abnormally differentiating keratinocytes, squamous carcinomas of different organs, and in a subset of breast tumors (65, 67). S100A7 has been identified in oral premalignant epithelia by microarray analysis and proposed to be a marker for invasion (66). It is postulated to play a role in breast-tumor progression in association with increased hypoxia and ROS by promoting angiogenesis (67). Increased hypoxia and ROS also occur in OPLs and HNOSCCs, and might explain the observed changes in S100A7 expression here. Reciprocal negative regulation between S100A7 and β-catenin signaling has been shown to play an important role in tumor progression of OSCC.
Thus, proteomic analyses of OPLs revealed the integrated importance of alterations in multiple cellular processes and suggested novel links between inflammation and premalignancy, some of which may serve as potential chemopreventive/therapeutic targets. Validation of the panel of OPL biomarkers in larger studies will ascertain its clinical utility and long-term patient follow up will evaluate the potential of these biomarkers for predicting the risk of malignant transformation in OPLs.
Example 14—Tissues
Following institutional human ethics committee approval, 51 anonymized HNOSCCs and 39 non-malignant head-and-neck tissues dating from 2002 and 2006 were retrieved from the Research Tissue Bank at All India Institute of Medical Sciences, New Delhi, India. The tissue specimens, surgically resected human HNOSCCs and non-malignant tissues (taken from a distant site) had been collected from patients undergoing curative surgery (with prior written patient consents). After excision, tissues were immediately snap-frozen in liquid nitrogen and stored at −80° C. in the Research Tissue Bank. One piece from each patient was collected in 10% formalin and embedded in paraffin for histopathological analysis; the rest was banked. Clinical and pathological data were recorded in a pre-designed performa; these included clinical TNM staging (tumor, node, and metastasis classification of malignant tumors of the International Union Against Cancer (UICC)) (97), site of the lesion, histopathological differentiation, age, and gender.
Example 15—Follow-Up Study
Fifty-one HNOSCC patients who underwent treatment of primary HNOSCC between 2002 and 2006 were investigated and evaluated in the head-and-neck cancer follow-up clinic. Survival status of the patients was verified and regularly updated from the records of the Tumor Registry, Institute Rotary Cancer Hospital, as of May, 2007. Patients were monitored for a maximum period of 42 months. As per the hospital protocol, HNOSCC patients with T1 and T2 tumors were treated with radical radiotherapy or surgery alone, whereas the majority of patients with T3 and T4 diseases were treated using a combination of radical surgery followed by postoperative radical radiotherapy. The patients were revisited clinically on a regular basis and the time to recurrence was recorded. If a patient died, the survival time was censored at the time of death; the medical history, clinical examination, and radiological evaluation were used to determine whether the death had resulted from recurrent cancer (relapsing patients) or from any other cause.
Disease-free survivors were defined as patients free from clinical and radiological evidence of local, regional, or distant relapse at the time of the last follow-up. Loco-regional relapse/death was observed in 17 of 51 (30%) patients monitored in this study. Thirty-four patients who did not show recurrence were alive until the end of the follow-up period. Only disease-free survival was evaluated in the present study, as the number of deaths due to disease progression did not allow a reliable statistical analysis. Disease-free survival was expressed as the number of months from the date of surgery to the loco-regional relapse.
Example 16—Immunohistochemistry
Paraffin-embedded sections (5 μm thick) of human oral normal tissues (n=39) and HNOSCCs (n=51) were collected on gelatin-coated slides. For histopathological analysis, representative sections were stained with hematoxylin and eosin, whereas immunostaining was performed on serial sections as described previously (23, 98). Briefly, the sections were deparaffinized in xylene, hydrated, and pretreated in a microwave oven in citrate buffer (0.01 M (pH=6.0)) for antigen retrieval. The sections were incubated with hydrogen peroxide (0.3% v/v) in methanol for 20 min to quench the endogenous peroxidase activity. Non-specific binding was blocked with 1% bovine serum albumin (BSA) in phosphate-buffered saline (PBS, 0.01 M, pH=7.2) for 1 h. Thereafter, slides were incubated with the primary antibody, (1 μg/ml) (anti-14-3-3a, goat polyclonal antibody, Santa Cruz Biotechnology Inc., Santa Cruz, Calif.) for 16 h at 4° C. and washed with PBS. The primary antibody was detected using the streptavidin-biotin complex (Dako LSAB plus kit, Dako, Copenhagen, Denmark) and diaminobenzidine as the chromogen. All incubations were performed at room temperature in a moist chamber. Slides were washed with 3× Tris-buffered saline (TBS, 0.1 M, pH=7.4) after every step. Finally, the sections were counterstained with Mayer's hematoxylin and mounted with DPX mountant. In negative controls, the primary antibody was replaced by non-immune mouse IgG of the same isotype to ensure specificity.
Example 17—Positive Criteria for Immunohistochemical Staining
Immunopositive staining was evaluated in five areas of the tissue section. For stratifin expression, sections were scored as positive if epithelial cells showed immunopositivity in the cytoplasm, plasma membrane, and/or nucleus as evaluated by two independent scorers blinded to the clinical outcome (the slides were coded and the scorers did not have prior knowledge of the local tumor burden, lymphonodular spread, and grading of the tissue samples). These sections were rated based on the percentage of cells showing immunopositivity as follows: 0, <10%; 1, 10-30%; 2, 30-50%; 3, 50-70%; and 4, >70%. Sections were also rated on the basis of stain intensity as follows: 0, none; 1, mild; 2, moderate; 3, intense, as described by Perathoner et al. (99). Finally, a total score (ranging from 0 to 7) was obtained by adding the scores of percentage positivity and intensity. The sections were considered positive if the total score was ≧5 (23).
Example 18—Cell Culture
Human oral squamous carcinoma cell line, HSC2, was used in this study. Cells were grown in monolayer cultures in Dulbecco's modified eagle medium (DMEM-F12) supplemented with 10% fetal bovine serum (FBS, Sigma-Aldrich, MO), 100 g/ml streptomycin and 100 U/ml Penicillin in a humidified incubator (5% carbon-dioxide, 95% air) at 37° C. as described (23).
Example 19—Co-Immunoprecipitation
Co-immunoprecipitation (Co-IP) assays were carried out as described earlier (100). Briefly, oral cancer cells, HSC2, were rinsed in ice-cold PBS and lysed in lysis buffer. Lysates were incubated on ice for 30 min and cell debris was removed by centrifugation. Lysates were pre-cleared by adding 20:1 of Protein A-Sepharose (GE Healthcare Biosciences, Sweden), followed by overnight incubation with polyclonal stratifin, YWHAZ, and NFκB antibodies, or monoclonal β-catenin and Bcl-2 antibodies (1:200 dilution) (Santa Cruz Biotechnology, CA) on a rocker at 4° C. Immunocomplexes were pulled down by incubating with Protein A-Sepharose for 2 h at 4° C., followed by washing with 4× ice-cold lysis buffer to eliminate non-specific interactions. In negative controls, the primary antibody was replaced by non-immune mouse IgG of the same isotype to ensure specificity. Protein A-Sepharose-bound immunocomplexes were then resuspended in Laemelli sample buffer (10 mM Tris, 10% v/v glycerol, 2% w/v SDS, 5 mM EDTA, 0.02% bromophenol blue, and 6% β-mercaptoethanol, pH=7.4), boiled for 5 min, and analyzed by Western blotting using specific antibodies.
The proteins were electro-transferred onto polyvinylidenedifluoride (PVDF) membrane. After blocking with 5% non-fat powdered milk in TBS (0.1 M, pH=7.4), blots were incubated with anti-14-3-3σ antibody (1:200 dilution) at 4° C. overnight. alpha-Tubulin served as a control for protein loading and was determined with mouse monoclonal anti-alpha-tubulin antibody (Santa Cruz Biotechnology, Santa Cruz, Calif.). Membranes were incubated with secondary antibody, HRP-conjugated goat/mouse anti-IgG (Dako CYTOMATION, Denmark), diluted at an appropriate dilution in 1% BSA, for 2 h at room temperature. After each step, blots were washed with 3× Tween (0.2%)-TBS (TTBS). Protein bands were detected by the enhanced chemiluminescence method (Santa Cruz Biotechnology, CA) on XO-MAT film.
Example 20—Statistical Analysis
The immunohistochemical data were subjected to statistical analysis using SPSS 10.0 software. The relationship between the protein expression and clinicopathological parameters were tested by Chi-Square and Fischer's exact test. Two sided p-values were calculated and p≦0.05 was considered to be significant. Box plots were prepared to determine the distribution of total score of stratifin expression in HNOSCCs and non-malignant tissues. The correlation of stratifin and or YWHAZ staining with patient survival was evaluated using life tables constructed from survival data with Kaplan-Meier plots.
Provided below is a summary of the results obtained by the inventors in connection with the experiments of Examples 14-20:
To determine the clinical significance of stratifin and YWHAZ in head-and-neck tumorigenesis, their expressions were analyzed in HNOSCCs (51 cases) and non-malignant tissues (39 cases) using immunohistochemistry. Significant increase in stratifin expression was observed in the HNOSCCs as compared to the non-malignant mucosa (p=0.03, Odd's Ratio (OR)=3.8, 95% CI=1.6-9.2). Kaplan-Meier survival analysis reveals correlation of stratifin overexpression with reduced disease-free survival of HNOSCC patients (p=0.06). The most intriguing finding is the significant decrease in median disease-free survival (13 months) in HNOSCC patients showing overexpression of both stratifin and YWHAZ proteins, as compared to patients that did not show overexpression of these proteins (median disease-free survival=38 months, p=0.019), underscoring their utility as adverse prognosticators for HNOSCCs. Co-immunoprecipitation assays show the formation of stratifin-YWHAZ heterodimers in HNOSCC and interactions with NFκB, β-catenin, and Bcl-2 proteins. These results indicate the involvement of these proteins in the development of head-and-neck cancer and their association with adverse disease outcome. The amino acid sequences of stratifin and YWHAZ with peptides identified by MS and MS/MS are given in FIGS. 9A and 9B, respectively.
Immunohistochemical Analysis of Stratifin in HNOSCCs and Non-Malignant Tissues.
Results of the immunohistochemical analysis of stratifin expression in HNOSCCs and non-malignant mucosa, and the relationship with clinicopathological parameters are summarized in Table 8. Chi-Square analysis shows significant increase in stratifin expression in HNOSCCs as compared to non-malignant mucosa (p=0.03, OR=3.8, 95% CI=1.6-9.2). In histologically normal oral tissues, 31% of the cases show weak immunostaining of stratifin (FIG. 10a). Increased stratifin expression was observed in 63% of HNOSCCs. Intense nuclear/membranous staining, in addition to cytoplasmic staining, was observed in the epithelial cells of HNOSCCs (FIG. 10b). No immunostaining was observed in tissue sections used as negative controls where the primary antibody was replaced by isotype specific IgG (FIG. 10c). No significant correlation was observed between stratifin overexpression and clinicopathological parameters including age, gender, histological differentiation, tumor stage, and nodal status of HNOSCCs (Table 8). Increased expressions of stratifin were observed in HNOSCCs with a median score of 6 (range 4-7) as compared to non-malignant (histologically normal) oral tissues median score of 5 (range 4-6) shown in the box plot analysis in FIG. 11.
Co-Immunoprecipitation.
To determine the functional significance of stratifin in head-and-neck carcinogenesis, the inventors identified its binding partners in oral cancer cells, HSC2, using co-IP assays followed by Western blotting. IP of stratifin reveals its binding to YWHAZ NFκB, β-catenin, and Bcl-2 proteins as shown in FIG. 12a. Reverse IP assay using specific antibodies for these proteins followed by Western blotting confirmed their binding to stratifin (FIG. 12b). No band was observed in the immunoblot analysis of the negative controls. It is noteworthy that all these proteins—stratifin, YWHAZ, NFκB, β-catenin and Bcl-2—have 14-3-3 binding motif, Mode 1, as previously reported by the inventors (39).
Association of Stratifin and YWHAZ Expression with Disease Outcome.
Kaplan-Meier Survival analysis reveals reduced disease-free survival for HNOSCC patients overexpressing stratifin (p=0.06, FIG. 13a). The median disease-free survival was 19 months in HNOSCC patients showing stratifin overexpression as compared to 38 months in HNOSCC patients who did not. Patients with YWHAZ-positive tumors had a shorter disease-free survival (median=23 months) than YWHAZ-negative tumors (median=35 months; p=0.08, FIG. 13b). Most remarkably, HNOSCC patients showing overexpressions of both stratifin and YWHAZ have a significantly decreased median disease-free survival of 13 months (p=0.019, FIG. 13c) in HNOSCCs, as compared to patients showing no overexpression of these two proteins (median=38 months), underscoring the utility of these proteins as adverse prognosticators for HNOSCCs.
Without being bound by theory, the results obtained in the experiments of Examples 14-20 are discussed below:
This investigation is one of the very few studies that demonstrate the prognostic utility of candidate biomarkers identified using MS-based proteomics. Recently, a comparison of protein profiles in tumor-distant head-and-neck tissues with clinical outcomes was reported to reveal a significant association between aberrant profiles and tumor-relapse events, suggesting that proteomic profiling in conjunction with protein identification may have significant predictive power for clinical outcome (12). The concept of using a panel of biomarkers for the purpose of improved diagnostics has taken hold in recent years. For example, DeSouza et al. (21) and Dubé et al. (101) demonstrated that the use of a panel of three biomarkers-chaperonin 10, pyruvate kinase M2, and α-1-antitrypsin-markedly increases the sensitivity and specificity for differentiating between endometrial carcinoma and non-malignant endometrial tissues. For head-and-neck cancers, Example 1 determined that a panel of biomarkers-stratifin, YWHAZ, and S100A7-performs better than any of the individual biomarkers for the detection of HNOSCC (23). In this current study, it is found that a panel of two biomarkers-stratifin and YWHAZ-shows promise as prognostic markers for HNOSCCs. Although not wishing to be bound by any particular theory, the enhanced performance of the combination of stratifin and YWHAZ versus either protein individually, in prognosing the clinical outcome of HNOSCCs, can be understood on the basis of their biological functions detailed below.
Results of in vitro studies demonstrate the formation of stratifin-YWHAZ heterodimers and binding of stratifin to NFκB, β-catenin, and Bcl-2, implicating stratifin's involvement in many cellular processes associated with tumorigenesis. Similar to the present invention, Bhawal et al. (96) have very recently reported increased expression of the stratifin transcript and protein in OSCCs. These results are in accordance with findings of Chen et al. (45) and Lo et al. (15, 44) who reported overexpression of stratifin in OSCCs. In addition, Lo et al. (15) demonstrated ten-fold increases in stratifin expression in HPV18-positive OSCCs in comparison with HPV18-negative OSCCs. It is of note that all these studies are on Asian populations. By contrast, studies on European populations reported decreased expression of stratifin in HNSCCs (12). If this geographical difference stands up to further scrutiny, it points to the importance of genetic and/or risk factors in developing HNOSCCs. Furthermore, epigenetic inactivation of stratifin has been shown to be associated with p16 gene silencing and HPV negativity in OSCCs (102). Thus these results suggest different mechanisms at work in HNOSCC tumorigenesis exhibiting overexpression of stratifin and tumorigenesis that does not. Whether these different mechanisms can be attributed to the presence or absence of HPV infection and/or differences in risk factors, such as smoking and drinking in the European and Western populations, and chewing of betel quid and/or tobacco in the Asian population, remains to be determined.
Overexpression of stratifin has been observed in other human cancers. Perathoner et al. (99) suggested that stratifin overexpression promotes tumor proliferation and/or prevents apoptotic signal transduction in colorectal carcinoma. Samuel et al. (103) demonstrated the role of stratifin in prevention of apoptosis by influencing the sub-cellular distribution of the pro-apoptotic protein, Bax, in colorectal cancer cells. Deletion of stratifin has been correlated with increased sensitivity of colorectal cells to doxorubicin. Similarly, Guweidhi et al. (104) proposed an anti-apoptotic role for stratifin in pancreatic cancer cells by inhibiting bad-mediated apoptosis. Liu et al. (105) showed that elevated stratifin expression contributes considerably to the observed drug resistance in MCF7/AdVp3000 cells. Stratifin has been shown to be a pivotal MDM2 regulator, involved in blocking a variety of MDM2 activities, including MDM2-mediated cytoplasmic localization of p53. Stratifin overexpression leads to destabilization of MDM2 by enhancing its self-ubiquitination and, thereby, stabilizing the cellular p53 (106). In previous studies, the inventors reported that p53 mutations are infrequent in OSCCs in the Indian population, despite stratifin overexpression; a currently unknown mechanism must be involved in stabilizing p53 in these OSCC patients (107, 108). The present inventors have also reported overexpression of MDM2 and cyclinD1 in OSCCs (109). Investigation of the relationship between stratifin overexpression, p53 stabilization, MDM2 and cyclinD1 expressions in HNOSCCs is currently underway.
The inventors, in a recent study aimed at delineation of early changes in expression of proteins in hyperplasia, demonstrated increased expressions of NFκB and COX-2 in early pre-malignant stages of the development of oral cancer and sustained elevation along the tumorigenic pathway (90). Furthermore, increased expression of YWHAZ in different stages of the development of OSCC and YWHAZ's involvement in cell signaling pathways involved in inflammation, cell proliferation and abrogation of apoptosis during oral carcinogenesis (39) was shown. Herein the inventors extend these findings by demonstrating the binding of stratifin with YWHAZ, thus suggesting the formation of stratifin-YWHAZ heterodimers and binding to NF-kB in oral cancer. These findings are supported by the study of Aguilera et al. (91) which showed the requirement of 14-3-3 proteins for efficient export of the p65 sub-unit of NF-kB. Taken together with the inventors' earlier findings of YWHAZ it is hypothesized that 14-3-3 proteins may be an important link between chronic inflammation and cancer that warrants further investigation.
The Co-IP results show stratifin binding also with β-catenin and Bcl-2 proteins. Earlier, the inventors showed that these proteins interact with YWHAZ thereby supporting the hypothesis that these complexes may be responsible for altered functions of stratifin. Fang et al. (92) recently showed that AKT, which is activated downstream from epidermal growth factor receptor signaling, phosphorylates β-catenin at Ser-552 in vitro and in vivo, causing its dissociation from cell-cell contacts and accumulation in both the cytosol and nucleus, and enhancing its interaction with YWHAZ via a binding motif containing Ser-552. This phosphorylation of β-catenin by AKT increases β-catenin's transcriptional activity and promotes tumor cell invasion, indicating that AKT-dependent regulation of β-catenin plays a critical role in tumor invasion and development. The oncogenic role of YWHAZ has been proposed in a recent study using siRNA for knocking down its expression in cancer cells (93). Down-regulation of YWHAZ sensitizes cells to stress-induced apoptosis and JNK/p38 signaling; in addition, it enforces cell-cell contacts and expression of adhesion proteins. YWHAZ's oncogenic properties is also supported by a Web-based meta-analysis (Onco-mine) that reveals its overexpression in various types of carcinomas (39, 93). To unravel the functional significance of 14-3-3 proteins in tumor development, the present inventors have investigated the functional significance of the interactions between stratifin and YWHAZ, and their respective roles in the development and progression of HNOSCC. All indications are that targeting specific 14-3-3 isoforms may serve as a plausible strategy for cancer therapy.
Hence, stratifin is overexpressed in HNOSCCs relative to normal tissues. Increased concomitant expression of stratifin and YWHAZ serves as adverse prognosticator in HNOSCCs and underscores the importance of these proteins in head-and-neck tumorigenesis. Increased expression of stratifin forming stratifin-YWHAZ heterodimers and binding to NFκB, β-catenin, and Bcl-2 proteins suggest the implication of these complexes in diverse cellular processes in head-and-neck carcinogenesis. It is submitted that targeting the stratifin-YWHAZ heterodimer, using small molecule modulator/peptide inhibitor that intervenes with 14-3-3 client protein interactions, would serve as a plausible therapeutic strategy for head-and-neck cancer.
Example 21—Patients and Clinicopathological Data Collection and Tumor and Biopsy Specimens
The Institutional Human Ethics Committee of the All India Institute of Medical Sciences (AIIMS), New Delhi, India, approved this study prior to its commencement. Tissue specimens were obtained from diagnostic or therapeutic procedures from 199 patients with oral leukoplakia (with no dysplasia (n=115) or with dysplasia (n=84) (Table 9A)) attending the Outpatient Clinic of the Departments of Surgical Disciplines and Otolaryngology, AIIMs, and from 100 HNOSCC patients undergoing curative cancer surgery during the period 2002-2007, after obtaining patient consents. Wherever possible non-malignant tissues (n=30) were taken from a site distant from the surgically resected HNOSCC patients. Non-malignant normal oral tissues (n=25) were also collected from the patients attending the Outpatient Department of Dental Surgery for tooth extraction. Taken together, these 55 non-malignant oral tissues with histological evidence of normal epithelium constituted the normal group. After excision, tissues were immediately snap-frozen in liquid nitrogen and stored at −80° C. in the Research Tissue Bank till further use; one part of the tissue was collected in 10% formalin and embedded in paraffin for histopathological and immunohistochemical analyses.
The histopathological assessment scoring was based on the architectural and cytological changes of grading epithelial dysplasia described in the WHO classification and recently reviewed (3). For each case, the pathologist recorded the grade and details of the criteria on which the decision was based. Leukoplakic lesions were classified into two groups: (a) lesions with no dysplasia, (b) lesions with dysplasia.
Histologically confirmed oral normal epithelia, leukoplakia with evidence of no dysplasia or with dysplasia, and HNOSCCs as revealed by H&E staining were used for immunohistochemistry (32). Patient demographic, clinical, and pathological data were recorded in a pre-designed form as described previously (32). The information documented included clinical TNM staging (tumor, node, metastasis based on the Union International Center le Cancer TNM classification of malignant tumors 1998), site of the lesion, histopathological differentiation, age, gender, and tobacco consumption habits.
Example 22—Follow-Up Study
One hundred patients with oral leukoplakia who underwent treatment between 2002-2005 were followed up in the head-and-neck follow-up clinic at regular time intervals with the maximum follow-up period included in this study being 36 months. All small leukoplakic lesions (size< or =4×4 cm) were completely excised, while incisional biopsy was done for the large diffuse lesions (size>4×4 cm). The patients were followed every six months, and the status of each lesion was defined and recorded using following the criteria: (a) static: if it was within ±2 mm size on the largest diameter; (B) progressed: if it had grown more than 2 mm from the original (size of the residuam, if partially excised); and (c) regressed: if it was reduced in size by more than 2 mm from the original residuam. For the lesions that were excised completely-disease progression was defined as development of a new lesion after excision of the primary lesion at the same site, or at another site in the oral cavity. The lesions that had progressed as per the above mentioned criteria were re-biopsied and leukoplakic lesions with dysplasia were excised.
Seventy-seven HNOSCC patients who underwent treatment from 2002-2007 were also investigated and evaluated in the head-and-neck cancer follow-up clinic at regular time intervals. Survival status of the HNOSCC patients was verified and updated from the records of the Tumor Registry, Institute Rotary Cancer Hospital, AIIMs, as of May 2008. HNOSCC patients were monitored for a maximum period of 76 months. As per the hospital protocol, HNOSCC patients with T1 and T2 tumors were treated with radical radiotherapy or surgery alone, whereas the majority of patients with T3 and T4 diseases were treated by radical surgery followed by postoperative radical radiotherapy. The patients were revisited clinically on a regular basis and the time to recurrence was recorded.
If a patient died, the survival time was censored at the time of death; the medical history, clinical examination, and radiological evaluation were used to determine whether the death had resulted from recurrent cancer (relapsing patients) or from any other causes. Disease-free survivors were defined as patients free from clinical and radiological evidence of local, regional, or distant relapse at the time of the last follow-up. Loco-regional relapse/death was observed in 61 of 77 (79%) patients monitored during the follow-up. Sixteen patients who did not show recurrence were alive until the end of the follow-up period. Only disease-free survival was evaluated in the present study, as the number of deaths due to disease progression did not allow a reliable statistical analysis. Disease-free survival was expressed as the number of months from the date of surgery to loco-regional relapse.
Example 23—Immunohistochemistry
Paraffin-embedded sections (5 μm) of human oral non-malignant tissues (n=55), leukoplakic lesions (with no dysplasia (n=115) or with dysplasia (n=84)) and HNOSCCs (n=100) were collected on gelatin-coated slides. Immunohistochemistry conditions were optimized and evaluated by three of the inventors. In brief, the sections were deparaffinized in xylene, hydrated in gradient alcohol, and pretreated in a microwave oven for 10 min in Tris-EDTA buffer (0.01 M, pH=9) for antigen retrieval. The sections were incubated with hydrogen peroxide (0.3% v/v) in methanol for 30 min to quench the endogenous peroxidase activity, followed by blocking with 1% bovine serum albumin (BSA) to preclude nonspecific binding. Thereafter, the slides were incubated with mouse monoclonal anti-hnRNPK antibody (1 μg/ml, ab23644, Abcam Inc., Cambridge, Mass.) for 16 h at 4° C. The primary antibody was detected using the streptavidin-biotin complex with the Dako LSAB plus kit (Dako CYTOMATION, Glostrup, Denmark) and diaminobenzidine as the chromogen (25). All procedures were carried out at room temperature unless otherwise specified. Slides were washed with Tris-buffered saline (TBS, 0.1 M, pH=7.4), 3-5 times after every step. Finally, the sections were counterstained with Mayer's hematoxylin and mounted with D.P.X. mountant. In the negative control tissue sections, the primary antibody was replaced by isotype-specific non-immune mouse IgG. A section from colorectal cancer tissue was used as a positive control in each batch of immunohistochemistry. The sections were evaluated by light microscopic examination.
Example 24—Evaluation of Immunohistochemical Staining
Each slide was evaluated for hnRNPK immunoreactivity using a semiquantitative scoring system for both staining intensity and the percentage of positive epithelial cells. Immunopositive staining was evaluated in randomly selected five areas of the tissue section. For hnRNPK protein expression, sections were scored as positive if epithelial cells showed immunopositivity in the nucleus/cytoplasm when observed independently by three of the inventors, who were blinded to the clinical outcome. (The slides were coded and the scorers did not have prior knowledge of the local tumor burden, lymphonodular spread, and grading of the tissue samples.) The tissue sections were scored based on the % of immunostained cells as: 0-10%=0; 10-30%=1; 30-50%=2; 50-70%=3 and 70-100%=4. Sections were also scored semi-quantitatively on the basis of staining intensity as negative=0; mild=1; moderate=2; intense=3 (17). Finally, a total score was obtained by adding the score of percentage positivity and intensity.
Example 25—Statistical Analyses
The immunohistochemical data were subjected to statistical analyses using the SPSS 10.0 software (Chicago). Sensitivity and specificity were calculated and quantified using ROC analyses. The PV describes the proportion of correctly classified cases. Based on sensitivity and specificity values for hnRNPK, a cutoff≧5 was defined as positive criterion for hnRNPK immunopositivity for statistical analyses. The relationships between hnRNPK protein expression and clinicopathologic parameters were tested using Chi-Square and Fischer's exact test. Two-sided p values were calculated and p<0.05 was considered to be significant.
For the follow-up study of 100 leukoplakia cases, let T denote the failure time, i.e., the first time the progression is diagnosed after excision of the leukoplakic lesions. For these data, the positive and negative predictive values as functions of time are defined as follows:

PVnuclear(t)=Prob(T≦t AND Progression|hnRNPK(nuclear)≧5);

PVnuclear(t)=Prob(T>t OR No Progression|hnRNPK(nuclear)<5);

0≦t≦36,

and, analogously, for cytoplasmic hnRNPK. Similarly, PPV and NPV were calculated for recurrence in HNOSCCs (where t runs from 0 to 76 months). These probabilities are estimated from the observed accumulated incidences over the respective time periods. The correlation of hnRNPK staining with patient survival was evaluated using life tables constructed from survival data with Kaplan-Meier plots.

Example 26—Immunoblot Analysis of HNRNPK in Oral Tissues
Whole-cell lysates were prepared from oral non-malignant, leukoplakia and HNOSCC tissues by homogenization in lysis buffer containing 50 mM Tris-Cl (pH=7.5), 150 mM NaCl, 10 mM MgCl2, 1 mM ethylenediamine tetraacetate (EDTA, pH=8.0), 1% Nonidet P-40, 100 mM sodium fluoride, 1 mM phenylmethylene sulfonylfluoride (PMSF) and 2 μl/ml protease inhibitor cocktail (Sigma) as previously described (32). Protein concentration was determined using the Bradford reagent (Sigma) and equal amounts of proteins (80 μg/lane) were resolved on 10% sodium dodecyl sulfate (SDS)-polyacrylamide gel. The proteins were then electro-transferred onto polyvinylidenedifluoride (PVDF) membrane. After blocking with 5% non-fat powdered milk in Tris-buffered saline (TBS, 0.1 M, pH=7.4), blots were incubated with anti-hnRNPK monoclonal antibody (1 μl/ml, Abcam Inc., Cambridge, Mass.) at 4° C. overnight. Protein abundance of actin (goat polyclonal antibody, Santa Cruz Biotechnology, CA) served as a control for protein loading in each lane. Membranes were incubated with HRP-conjugated anti-mouse/goat secondary antibody, G (DAKO Cytomation, Glostrup, Denmark), diluted at an appropriate dilution in 1% BSA, for 2 h at room temperature. After each step, blots were washed three times with Tween (0.1%)-Tris-buffer saline (TTBS). Protein bands were detected by the enhanced chemiluminescence method (ECL, Santa Cruz Biotechnology, CA) on XO-MAT film.
Example 27—Reverse Transcription—PCT
Representative frozen tissue specimens of histologically confirmed oral normal tissues, leukoplakia and HNOSCCs were used for extraction of total RNA using the TRI reagent (Sigma, MO) as previously described (29). First-strand cDNA was synthesized using 2 μg RNA with oligo dT as the primer with MMLV reverse transcriptase. PCR was carried out using hnRNPK specific primers forward-(5′AGCAGAGCTCGGAATCTTCCTCTT3′ SEQ ID NO: 749) and reverse-(5′ATCAGCACTGAAACC AAC CA TGCC3′ SEQ ID NO: 750) (Accession No. NM_002140). 20 μl of each PCR product was used for electrophoresis on a 1.2% agarose gel stained with ethidium bromide. The gel was visualized with UV light and photographed.
Provided below is a summary of the results obtained by the inventors in connection with the experiments of Examples 21-27:
Identification of hnRNP K in Oral Premalignant Lesions by Mass Spectrometry.
The tandem MS spectra for the two peptides, A: DLAGSIIGK (SEQ ID NO: 368) and B: IDEPLEGSEDR (SEQ ID NO: 369), identified from hnRNPK in iTRAQ-labeled oral leukoplakia with dysplasia by LC-MS are given in FIGS. 21A and 21B, respectively. In each case, the topmost panel shows the confidence and score for each peptide, the sequence, theoretical mass, theoretical mass/charge ratio, charge state and difference between experimental and theoretical mass of the peptide. The expected product ion masses highlighted in the table in the middle are matched with the detected peaks in each spectrum. The lowermost panel in each case shows the location of the peptide within the context of the intact protein sequence.
Immunohistochemical Analysis of hnRNP K Expression in Oral Lesions.
To determine the clinical significance of hnRNPK protein in head-and-neck tumorigenesis, its expression was analyzed in different stages of HNOSCC development by means of immunohistochemistry using a specific monoclonal antibody. Of the 55 normal tissues analyzed, 51 cases (93%) showed faint or no detectable hnRNPK immunostaining in the nucleus/cytoplasm of the epithelial cells (Table 9a, FIG. 14a). However, four normal tissues showed nuclear expression of hnRNPK, as per positivity criteria defined in the Methods section; all these four tissues were obtained from a site adjacent to the tumor from HNOSCC patients, and thus the increased hnRNPK expression in these histological normal tissues may be a manifestation of field cancerization.
Chi square trend analysis showed significant increase in nuclear staining of hnRNPK in different stages of head-and-neck/oral tumorigenesis (normal, leukoplakia and HNOSCCs; Table 9a, ptrend<0.001). Of the 199 leukoplakias analyzed, 141 cases (71%) showed significant increase in nuclear hnRNPK immunostaining in comparison with the normal tissues (p<0.001, Odds ratio (OR)=30.9, 95% CI=10.7-89.7, Table 9a). Oral leukoplakia is a clinical terminology and histologically these lesions are classified into leukoplakia with no dysplasia or with dysplasia for disease management. Of the 199 leukoplakias, 115 cases showed no histological evidence of dysplasia; 78/115 (68%) cases showed significant increase in nuclear hnRNPK immunoreactivity in comparison with the normal tissues (p<0.001, OR=26.8, 95% CI=9.1-79.9, Table 1a and FIG. 14b). Importantly, progressive increase in nuclear expression of hnRNPK was observed in 75% dysplasias (63 of 84 cases, FIG. 14d) in comparison with normal tissues (p<0.001, OR=38.2, 95% CI=11.7-113.1).
It is noteworthy that 26 of 199 leukoplakia cases showed cytoplasmic localization of hnRNPK, in addition to its nuclear expression, as shown in FIGS. 14c and 14e, respectively. Chi square analysis revealed that leukoplakias showing cytoplasmic hnRNPK staining are at 4.3-fold higher risk for cancer development (p<0.001, 95% CI=2.2-7.2, Table 9a). The majority of HNOSCCs (78%) showed nuclear localization of hnRNPK in tumor cells (FIG. 14f). In addition to nuclear staining, intense hnRNPK staining was also observed in the cytoplasm of tumors cells in 38 of 100 HNOSCCs analyzed (FIG. 14g).
The clinicopathological parameters of HNOSCCs patients and their correlation with nuclear/cytoplasmic expression of hnRNPK are shown in Table 9a. Increased cytoplasmic staining of hnRNPK showed a significant association with de-differentiation of HNOSCCs (p=0.001). Furthermore, no significant correlation between nuclear/cytoplasmic hnRNPK and other clinicopathological parameter, including gender, tumor size, nodal status or tobacco consumption of HNOSCC patients was found. No immunostaining was observed in tissue sections used as negative controls where the primary antibody was replaced by isotype specific IgG (FIG. 14h), while the positive control (colorectal cancer) showed nuclear expression of hnRNPK protein (data not shown).
Evaluation of hnRNP K as Potential Biomarker for Diagnosis and/or Prognosis.
Receiver-operating characteristic (ROC) curve analysis was used to determine the potential of hnRNPK as a biomarker to distinguish leukoplakia and HNOSCCs from normal oral epithelium. The values for AUC were 0.822, 0.872 and 0.869 for leukoplakia without dysplasia (FIG. 15a), with dysplasia (FIG. 15b), and cancer (FIG. 15c), respectively, with respect to normal oral tissues based on the total score for nuclear immunostaining (Table 9b). The PPVs were 92.7, 92.3, and 92.3, respectively, for nuclear immunostaining in the three groups. Similarly, ROC analysis was used for determination of AUC and PPV for cytoplasmic hnRNPK staining in all these three groups as shown in Table 9b and FIG. 16a-c. 
hnRNP K Expression as a Predictor of Disease Progression and Prognosis.
Significantly, the follow-up data sets of 100 leukoplakia patients for three years and 77 HNOSCC cases for seven years were used to assess the prognostic value of hnRNPK for predicting disease progression in patients with leukoplakia and cancer recurrence in HNOSCC patients after completion of primary treatment. Both PPVs NPVs of the prognostic test are of paramount importance in this context, with the former to correctly identify cases that need early intervention, and with the latter to gauge, in the most accurate way, where such intervention with its monumental personal impacts can and should be avoided.
FIG. 16 shows the estimated PPVs and NPVs for nuclear and cytoplasmic hnRNPK expression as prognostic biomarkers. FIGS. 16a and 16b for disease progression of leukoplakia; and for cancer recurrence in HNOSCC patients (FIGS. 16c and 16d). Even though the absolute numbers that give rise to these estimates are only moderate (23 cases), cytoplasmic hnRNPK expression in leukoplakias (12 cases) appears to be a promising biomarker for disease progression, with PPVcyto (18 months)=44.4 and PPVcyto (36 months)=66.7 (12 disease progressions). These values are compared with the PPVs of overall hnRNPK expression (both nuclear and cytoplasmic immunopositivity−PPVoverall), PPVoverall (18 months)=15.0 and PPVoverall (36 months)=23.0. These result in estimated ratios or relative positive predictive values of cytoplasmic hnRNPK expression for disease progression of 2.96 and 2.90 for 18 and 36 months, respectively.
On the other hand, high nuclear hnRNPK expression (22 cases) appears not, by itself, to define a biomarker of high prognostic value (PPV nuc (36 months)=28.2, compared with PPVoverall (36 months)=23). Of note, the negative predictive value of cytoplasmic hnRNPK expression in leukoplakias is very high (NPVcyto (36 months)=86.6). Based on the inventors' data, the additional prognostic value which hnRNPK, in either its nuclear or cytoplasmic expression, provides for predicting (PPV) or excluding (NPV) cancer recurrence in HNOSCC patients is: PPVnuc (76 months)/PPVoverall(76 months)=68.9/61.0; PPVcyto (76 months)/PPVoverall(76 months)=81.3/61.0; NPVnuc (76 months)/NPVoverall (76 months)=68.9/39.0; and NPVcyto (76 months)/NPVoverall (76 months)=53.3/39.0. Based on these analyses, the most significant improvement over clinicopathological criteria that cytoplasmic hnRNPK appears to offer as a marker is in predicting disease progression in leukoplakia patients and prognosis of HNOSCCs.
While PPVs. and NPVs. quantify the estimated predictive power of the marker, the strength of the statistical association of hnRNPK expression with poor prognosis was assessed by Kaplan-Meier survival analysis. Log-rank test showed significantly reduced time for disease progression (p<0.001; median time=17 months) in leukoplakia patients showing increased cytoplasmic expression of hnRNPK (18 cases), as compared to the median time of 35 months in the patients showing no/faint immunostaining of hnRNPK in the cytoplasm (FIG. 17a). Leukoplakia patients showing intense nuclear hnRNPK expression (78 cases) had poor prognosis, as compared to patients who did not show increased nuclear hnRNPK (p=0.004, FIG. 17b), though there was no significant difference in median time for disease progression. The inventors' findings clearly underscore the potential of cytoplasmic hnRNPK as a marker for predicting disease progression in leukoplakia patients. Of the 100 leukoplakia patients, 83 cases showed no histological evidence of dysplasia and similar correlations of cytoplasmic and nuclear expression were observed with disease progression for these leukoplakias (FIGS. 4a and 4b, respectively). However, similar statistical analysis could not be carried out for dysplasias due to the small number of cases in this group (17 cases).
In addition, Kaplan-Meier survival analysis showed significantly reduced disease free survival (p=0.004; median survival 11 months) in HNOSCC patients harboring increased cytoplasmic expression of hnRNPK, as compared to median disease-free survival of 41 months in the patients showing no/faint cytoplasmic hnRNPK immunostaining (FIG. 17c). Similarly, reduced disease-free survival of 14 months was observed in HNOSCC patients showing intense nuclear expression of hnRNPK, as compared to patients who did not show increased nuclear hnRNPK (median survival of 57 months); although this could not reach a statistically significant value of p≦0.05 (FIG. 17d). These findings clearly demonstrate the potential of nuclear hnRNPK as a biomarker for diagnosis, and cytoplasmic hnRNPK as a potential marker for predicting poor prognosis of HNOSCCs.
Immunoblotting and RT-PCR.
The overexpression of hnRNPK in oral lesions was further validated by immunoblotting and RT-PCR analyses in the same tissue samples as used for immunohistochemical analysis. Immunoblot analysis showed a single intense band of 64 kDa, confirming the increased expression of hnRNPK in oral leukoplakias and HNOSCCs, as compared to the normal tissues (FIG. 18A). RT-PCR analysis demonstrated increased levels of hnRNPK transcripts in the same tissue specimens of leukoplakias and HNOSCCs in comparison with normal tissues (FIG. 18B), thus supporting the immunohistochemical findings and suggesting transcriptional upregulation of hnRNPK in these tissues.
Without being bound by theory, the results obtained in the experiments of Examples 21-27 are discussed below:
hnRNPK overexpression in early oral lesions is a very important unique finding of this study, providing clinical evidence to establish its link with progression potential of leukoplakia in support of its proposed role as a transformation-related protein. To the inventors' knowledge, this is the first investigation to demonstrate the clinical application of a candidate biomarker identified using MS-based tissue proteomics in identifying early oral premalignant lesions that may be at high risk of disease progression. The salient findings of the inventors' study are: i) nuclear hnRNPK expression increases progressively from oral normal tissues to hyperplasia, dysplasia and frank malignancy and may serve as a plausible diagnostic marker for HNOSCCs; ii) cytoplasmic accumulation of hnRNPK is significantly increased from leukoplakia to cancer; (iii) aberrant subcellular localization (cytoplasmic accumulation) of hnRNPK is a predictor of disease progression in leukoplakia patients and disease recurrence in HNOSCC patients; iv) cytoplasmic hnRNPK is associated with poor prognosis of HNOSCCs; and v) hnRNPK is transcriptionally upregulated in head and neck tumorigenesis.
Expression profiling of different cancer types and mechanistic studies have strongly implicated hnRNPK as a key player in human cancers. To the inventors' knowledge, this study is the first report demonstrating increased expression of hnRNPK in oral leukoplakia by immunohistochemistry. The significantly increased nuclear expression of hnRNPK in oral hyperplastic lesions points to this alteration being an early event in the development of premalignant lesions and is in accord with its role as a transcriptional regulator of growth promoting genes such as myc and src and promoter of cell proliferation (111-117).
The major challenge in oral tumorigenesis is the identification of proteins that may serve as markers to predict high risk leukoplakias for early intervention. Most studies on leukoplakia focus on dysplastic lesions, while knowledge of molecular alterations in oral hyperplasia is meager. As per the existing literature, the malignant transformation potential is often linked to the severity of dysplasia; in comparison the hyperplastic lesions have received less attention, primarily because these lesions often undergo spontaneous regression. However, the lesions that do not regress need identification and biomarkers to predict the risk of malignant transformation.
In this context, the study assumes importance, because not only does it show aberrant hnRNPK expression as early as in hyperplasia, but the follow-up study also points to the relevance of cytoplasmic hnRNPK in predicting the risk of disease progression in leukoplakia patients with hyperplasia and HNOSCCs. It is noteworthy that studies on molecular analysis of leukoplakia with hyperplasia are very limited, because these patients often do not come to the clinics since their lesions are small and do not pose any overt clinical problem. However, it is extremely important to target this patient population for risk assessment and early intervention for cancer prevention in high risk cases. Hence, the inventors' findings are important and warrant further validation in larger independent studies on oral hyperplastic lesions. Furthermore, the cytoplasmic expression of hnRNPK protein observed in epithelial cells of a subset of hyperplastic and dysplastic lesions points to a potential role in development and progression during early stages of oral tumorigenesis, while the overexpression in HNOSCCs and association with poor prognosis suggests a sustained involvement in frank malignancy as well.
In this context, the aberrant cytoplasmic accumulation of hnRNPK protein in a small subset of leukoplakias (26/199, 13% cases) and larger proportion of HNOSCCs (38%) and its potential of risk prediction is noteworthy. The cumulative risk of leukoplakia to transform into OSCC range from 3.6 to 19.8%, 0.4 to 38%, 3 to 33%, and 0 to 20% in different studies; the calculated average amounted to 3% to 8.1% (35). Based on meta-analysis of several follow-up studies of leukoplakia patients an overall rate of 5% transformations in 5 years, resulting in an average annual transformation rate of 1% has been reported by Hunter et al. (2). This 3 year follow-up study showed disease progression in 23/100 leukoplakia patients, 12/23 showed cytoplasmic accumulation of hnRNPK. Long-term follow-up of these leukoplakia patients is needed to establish the link between cytoplasmic hnRNPK and risk of cancer development.
Kaplan-Meier survival analysis revealed association of cytoplasmic hnRNPK with disease progression of leukoplakia and poor prognosis of HNOSCC. Furthermore, analysis of the predictive potential of hnRNPK revealed its utility as a marker to identify high risk leukoplakia and aggressive HNOSCCs, supporting the association observed by Kaplan Meier analysis. These findings also suggest that leukoplakic lesions with cytoplasmic hnRNPK protein expression are at high risk of disease progression and warrant early intervention as well. The potential mechanistic link between cytoplasmic hnRNPK expression and potential of malignant transformation remains to be established. Efforts are currently underway to demonstrate the role of hnRNPK in malignant transformation of cell cultures established from oral hyperplastic lesions in vitro.
The poor prognosis of HNOSCC patients showing aberrant cytoplasmic hnRNPK protein expression also supports a role for this protein in progression of HNOSCCs. Interestingly, aberrant cytoplasmic hnRNPK protein expression has also been observed in colorectal cancers (88). Importantly, nasopharyngeal carcinoma patients showing cytoplasmic hnRNPK were reported to have significantly reduced distant metastasis free survival (118). The cytoplasmic hnRNPK expression may be attributed to the presence of a N-terminal bipartite nuclear localization signal and a hnRNPK-specific nuclear shuttling signal that confer the capacity for bidirectional transport across the nuclear envelope (114). Recently, the K nuclear shuttling (KNS) domain, a well-known signal for nuclear import and export, has also been shown to be responsible for the transactivation activity of hnRNPK protein (119). The cytoplasmic accumulation of hnRNPK is controlled by extracellular signal-regulated kinase (ERK)-dependent serine phosphorylation (Ser284 and Ser353) (120). In the cytoplasm, hnRNPK functions as a translational regulator of specific mRNAs, such as c-myc mRNA, renin mRNA, human papillomavirus type 16 L2 capsid protein mRNA, and reticulocyte-15-lipoxygenase (r15-LOX) mRNA (121-124). HPV 16 and 18 have been associated with a large proportion of HNOSCCs, especially among non-consumers of tobacco, though the molecular mechanisms underlying the development of HPV associated HNOSCCS are under intense investigation. Recent proteomic analysis of HPV positive and HPV negative OSCCs have revealed differences in protein expression patterns; whether hnRNPK plays different roles in these tumor subtypes remains to be investigated (15). In the cytoplasm, hnRNPK functions as a specific activator of c-Src and is a substrate of this tyrosine kinase. c-Src-dependent phosphorylation modulates the r15-LOX mRNA-binding activity of hnRNPK and its function in the control of mRNA translation during erythroid cell maturation (113, 114, 124). Taken together with the diverse influence of hnRNPK on gene expression and mechanisms regulating hnRNPK subcellular localization, it is speculated that gene dysregulation resulting from cytoplasmic accumulation of hnRNPK may play an important role in tumorigenesis.
Hence, hnRNPK has herein been shown to be over-expressed in oral lesions—early premalignant stages of tumorigenesis and in frank tumors in comparison with normal oral tissues both at protein and transcript levels. Furthermore, its subcellular localization—predominantly nuclear in hyperplasias, but present in both cytoplasm and nucleus in a subset of hyperplasias and dysplasias and increasing cytoplasmic expression in tumor cells, suggests that nuclear-cytoplasmic translocation may have an important role in malignant transformation of oral cancer cells. The most important finding is that cytoplasmic hnRNPK is a predictor of disease progression in leukoplakia patients and poor prognostic marker for HNOSCCs, hence targeting hnRNPK might be a new chemopreventive/therapeutic strategy in head and neck/oral cancer. Large scale studies are warranted to further evaluate hnRNPK's potential as an indicator of risk of progression of leukoplakia and role in development and progression during early stages of head and neck/oral tumorigenesis.
Example 28—S100A7 Overexpression is a Predictive Marker for High Risk of Malignant Transformation in Oral Dysplasia
In this example, 5 candidate protein biomarkers were evaluated for their potential use in assessing the risk of cancer development from oral dysplasias. In particular, the results of this example support the use of S100A7 overexpression as a biomarker for identifying oral dysplastic lesions at high risk of cancer development.
Materials and Methods.
Study Population Characteristics and Criteria.
This study was approved by the research ethics board of Mount Sinai Hospital, Toronto, Canada, prior to commencement. Patient charts from 2000 to 2010 containing clinico-pathological diagnosis of dysplasia were retrospectively reviewed in the Department of Pathology at Mount Sinai Hospital to obtain clinical information and follow-up data. Information regarding gender, age, site of lesions at the time of initial dysplasia diagnosis and smoking history was documented in a clinical database. Patients with oral lesions having histopathological evidence of dysplasia and a known clinical outcome were included in this study. Patients with oral lesions with dysplasia but with no available follow-up data and patients diagnosed with oral lesions with dysplasia concomitant with OSCC at the first visit were excluded from this study.
Based on the aforementioned inclusion/exclusion criteria, an independent set of 110 patients with dysplasia were selected for further analysis. There was no overlap of dysplasia cases used in the present study with the samples used in the discovery set published previously (87). In cases where patients with oral lesions underwent multiple biopsies, the first biopsy section with histological evidence of dysplasia was used for immunostaining.
All patients with oral lesions had an initial biopsy. The patients with histopathological evidence of mild dysplasia were monitored at six-month intervals. A repeat biopsy was performed if the lesion changed in appearance. Patients with moderate or higher grades of dysplasia had excision of the lesions wherever feasible clinically. When excision was not feasible, the patient was continually monitored with repeat biopsies for clinically suspicious areas for cancer development.
Histopathology.
The histopathologic diagnosis in all cases was re-examined and confirmed by oral pathologists at Mount Sinai Hospital according to the World Health Organization (WHO) criteria. Dysplastic areas were selected from a hematoxylin and eosin (H&E) stained section of each tissue sample. Dysplastic lesions were classified as mild, moderate or severe dysplasia based on WHO standard criteria (3). These cases included mild (n=58), moderate (n=39) and severe (n=13) dysplasia. Of 110 tissue blocks reviewed for inclusion in this study, 86 dysplasia cases were used for construction of tissue microarrays (TMAs) and 24 cases were used for immunohistochemistry using whole tissue sections.
Construction of Tissue Microarrays (TMAs).
The TMA blocks were constructed by relocating small cylindrical tissue cores (2 cores per tissue block representing the dysplasia sections) from individual donor blocks and placing them in a recipient block with defined array coordinates. Arrays were constructed from formalin-fixed paraffin embedded (FFPE) tissues by the removal of 0.6 mm diameter tissue cores from donor blocks. A total of two morphologically representative areas of interest from each donor block were identified under the microscope by a pathologist using a stained H&E section as a guide. Using a precise spacing pattern on a manual TMA instrument, 150-200 cores could be transferred to the recipient paraffin block in a grid like fashion, retaining a link to the original block and its pathology. Consecutive 4 μm sections were cut from the recipient block and used for immunohistochemical staining for p16, five candidate protein biomarkers and HPV 16/18 status using chromogenic in situ hybridization (cISH) as described below.
Immunhistochemistry (IHC) of Candidate Markers in Oral Lesions Using TMA.
TMA slides were immunostained using Vectastain Elite ABC kit (PK-6100) rapid protocol as described by the manufacturers (Vectastain Laboratories, CA). Antigen retrieval was performed using microwave in Tris-EDTA buffer pH=9.0 containing 0.05% Tween-20 for 15 minutes at 450 watts followed by 5 minutes at 900 watts. Slides were immunostained with the respective mouse monoclonal antibodies; anti-p16 (sc-1661, Santa Cruz Biotechnology, CA) at 1:100 dilution, anti-S100A7 (sc-52948, Santa Cruz Biotechnology, CA) at 1:500 dilution; anti-PTMA (LS-B2322, Lifespan Biosciences, WA) at 1:3500 dilution; anti-hnRNPK (ab23644, Abcam, MA) at 1:5000 dilution; anti-14-3-3σ (ab14116-50, Abcam, MA) at 1:2500 dilution; 14-3-3ζ (IMG-6664A, Imgenex, CA) at 1:100 dilution. Tissue sections of liver were used as positive control in the TMA slides. The sections were evaluated by light microscopic examination. Images were captured using the Visiopharm Integrator System (Horsholm, Denmark).
Evaluation of Immunohistochemical Staining.
Immunopositive staining was evaluated in five areas of the tissue sections as previously described (87, 100, 126, 127, 128). Sections were scored as positive if epithelial cells showed immunopositivity in the cytoplasm, and/or nucleus when observed by evaluators who were blinded to the clinical outcome. These sections were scored as follows: 0, <10% cells; 1, 11-30% cells; 2, 31-50% cells; 3, 51-70% cells; and 4, >70% cells showed immunoreactivity. Sections were also scored semi-quantitatively on the basis of intensity as follows: 0, none; 1, mild; 2, moderate; and 3, intense. Finally, a total score (ranging from 0 to 7) was obtained by adding the scores of percentage positivity and intensity for each of the tissue sections. The immunohistochemical data were subjected to statistical analysis as described below. Scoring by 2 observers was discrepant in about 2% of cases, wherein a consensus on the final result was reached by re-evaluation of these slides and discussion. An inter-rater reliability analysis using the K-statistic was performed to determine consistency among evaluators. The inter-rater reliability for the evaluators was found to be K=0.921 (p<0.001, 95% C.I.=0.83-1.01).
cISH for HPV16/18 Detection.
HPV 16/18 status was determined in formalin-fixed oral dysplasia tissue sections in TMA using a known cISH protocol. Briefly, formalin-fixed paraffin embedded oral dysplasia tissue sections in TMA were deparaffinized in xylene. Sections were treated by digestion with proteinase K, followed by hybridization with biotinylated DNA probes for HR-HPV genotypes 16/18 or human embryonic DNA used as a control for determining genomic DNA integrity as previously described (129). Cervical cancer tissue section was used as a positive control for detection of HPV 16/18 infection. For determining HPV 16/18 status, diffuse nuclear staining was considered as indicative of episomal HPV, while point-form nuclear staining was characteristic of integrated HPV16/18 DNA (129).
Follow-Up Data and Statistical Analysis.
Statistical analysis was performed using the software packages SPSS version 20.0 for Windows (SPSS Inc., Chicago Ill.) and R-statistical software version 2.12.2 (R Foundation, Vienna, Austria). Malignant transformation versus no transformation of oral dysplastic lesions was considered to be the clinical outcome of the patients in this study. A descriptive analysis was performed on clinical and pathological factors. Based on our earlier studies, a pre-defined cut-off value for each candidate protein biomarker was chosen for defining positivity (low/high score). The χ2 test and Fischer exact test were used to assess associations among categorical variables. Significance of our null hypothesis was verified using the Mann-Whitney test.
Follow-up period of dysplasia patients for oral cancer free survival (OCFS) was defined as the interval from the date when the patient underwent first biopsy to the date of malignant transformation (i.e. events) or no transformation at last consultation (for censored observations). Dysplasia patients were monitored for a maximum period of 150 months (mean 43 months and median 36.5 months). Notably, malignant transformation of oral dysplasia was observed in 39 of 110 (35.4%) patients. However, seventy-one patients (64.5%) showed no histological evidence of malignant transformation until the end of the follow-up period. Life tables were created to determine the median OCFS among patients with mild, moderate and severe dysplasia. Oral cancer free survival was determined using time-to-event analysis, the Kaplan-Meier method and the log-rank test. Cox proportional hazards models were utilized to evaluate clinicopathological factors including age, gender, degree of dysplasia, smoking habits, p16 immunostaining and overexpression of candidate markers in predicting risk of cancer development. Hazard ratios (H.R.) with 95% confidence intervals (95% C.I.) and significant p-values were reported. All tests were two-sided, and p-values<0.05 were considered statistically significant. The systematic and rigorous assessment of PPVs and NPVs for prognostic markers was carried out as previously described earlier (100, 126, 1727, 128).
Results.
Patient Characteristics.
Of the 110 patients with dysplasia included in the current study, follow-up data were available for up to a maximum of 150 months with a mean follow-up period of 43 months. 39 patients (35.4%) developed invasive squamous cell carcinoma of the oral cavity with a mean time for malignant transformation of 27.9 months (range 2-118 months). The baseline clinico-pathological characteristics of patients with dysplastic lesions including age, site of lesion, histopathological grade and smoking history are presented in Table 1. The average age at diagnosis was 59 years (range, 30 years-88 years). On the basis of histopathological characteristics, these lesions were sub-classified as mild (58 cases, 52.7%), moderate (39 cases, 35.4%) or severe dysplasia (13 cases, 11.8%). No significant differences were observed in age, gender, site of lesion or smoking history between patients with dysplasia that showed malignant transformation (i.e. developed oral cancer) relative to those with untransformed dysplasia (Table 16). Notably, 12 of 58 (20.7%) cases with mild dysplasia, 18 of 39 (46.1%) cases with moderate dysplasia (p=0.008, odd's ratio, O.R.=3.286, 95% C.I.=1.3-8.1, Table 16) and 9 of 13 (69.2%) severe dysplasia developed malignancy (p=0.001, O.R.=8.625, 95% C.I.=2.3-32.8, Table 16).
Analysis of Candidate Marker Overexpression and Clinicopathological Parameters.
Our immunohistochemical analysis revealed 79.1% (87 of 110) dysplastic lesions exhibited increased expression of S100A7 protein in either the cytoplasm and/or nucleus of epithelial cells (FIG. 23(i, a-c); Table 17). The intensity of S100A7 expression in dysplasia sections ranged from weak to strongly positive among different grades of dysplasia (FIG. 23(i, a-c)). Thirty four of 58 (58.6%) cases with mild dysplasia, 26 of 39 (66.7%) cases with moderate dysplasia and 10 of 13 (76.9%) cases with severe dysplasia exhibited cytoplasmic S100A7 overexpression (Table 18). Notably, 32 of the 70 dysplasia cases (45.7%) exhibiting S100A7 overexpression in cytoplasm transformed to cancer (p=0.003, O.R.=3.97, 95% C.I.=1.5-10.2, Table 17). Nuclear S100A7 expression was observed in 40 of 58 cases with mild dysplasia (68.9%), 33 of 39 (84.6%) cases with moderate dysplasia and 11 of 13 (84.6%) cases with severe dysplasia (Table 18). Thirty five of the 84 (41.6%) dysplasia cases exhibiting nuclear S100A7 developed malignancy (p=0.018, O.R.=3.929, 95% C.I.=1.2-12.4, Table 17). However, no significant correlation was observed between S100A7 overexpression (cytoplasm/nucleus) and degree of dysplasia (p>0.05, Table 18).
IHC analysis showed PTMA expression in either cytoplasm (25 of 39 cases, 64.1%) or nuclei (36 of 39 cases, 92.3%) of epithelial cells of dysplasia that progressed to cancer (FIG. 23(ii, a-c); Table 2). Similarly, increased expression of both the 14-3-3ζ and 14-3-3σ isoforms were observed in cytoplasm and/or nuclei of epithelial cells in mild, moderate and severe dysplasia cases (FIGS. 23(iii, a-c) and (iv, a-c); Table 17). Among dysplasia cases that transformed to cancer, 79.5% (31 of 39 cases) exhibited cytoplasmic expression of 14-3-3ζ, while 21 cases (53.8%) exhibited 14-3-3ζ expression in nuclei of epithelial cells (Table 17). 64.1% of dysplasia cases exhibited 14-3-3a expression in cytoplasm while 46.2% of dysplasia cases exhibited nuclear expression in addition to cytoplasmic staining (Table 17). Nuclear hnRNP K was observed in tissue samples obtained from all dysplasia patients studied, but no detectable expression of nuclear hnRNPK was observed in cytoplasm (FIG. 23(v, a-c); Table 17). No significant difference was observed for expression of cytoplasmic or nuclear PTMA, 14-3-3ζ, 14-3-3a and hnRNP K in dysplasia that transformed to cancer as compared to those that did not progress to cancer (Table 17). Mann-Whitney tests also showed significant association of S100A7 overexpression in cytoplasm (p=0.002) and nucleus (p=0.008) in dysplasia cells among patients with oral lesions who progressed to cancer relative to patients who did not progress to cancer, thereby providing an independent evaluation of association of protein markers with dysplasia.
Evaluation of p16 Expression and HPV 16/18 Status.
Expression of p16 was evaluated in all oral dysplasia cases analyzed in this study. Nuclear p16 was observed in 85 of 110 cases (77.3%), while 25 cases (22.7%) exhibited low or no detectable expression of nuclear p16 in oral dysplasia cells (FIG. 24). Thirty two of 39 (82.1%) dysplasia cases that transformed to cancer exhibited nuclear p16 expression (Table 17). Nuclear p16 expression was observed in 49 of 58 (84.4%) mild, 28 of 39 (71.7%) moderate, and 8 of 13 (61.3%) severe dysplasia (Table 18). However, no significant correlation was observed between nuclear p16 and any of the five candidate protein biomarkers exhibiting overexpression in oral dysplasia cases analyzed in this study (Table 19).
Our study revealed no detectable levels of HPV 16/18 in the dysplasia cases analyzed, irrespective of their p16 status (positive/negative) (FIG. 24, i, Table 17). Oral dysplasia tissue sections used as negative controls showed no detectable levels of HPV 16/18 (FIG. 24, ii). Cervical cancer tissue sections used as positive controls showed strong positivity for HPV 16/18 (FIG. 24, iii). TMA tissue sections used as control to determine genomic DNA integrity showed strong positive staining (FIG. 24, iv). No significant correlation was observed between nuclear p16 and HPV16/18 in oral dysplasia cases. Together, these data clearly suggest lack of association of p16 or HPV 16/18 with S100A7 expression and transformation of oral dysplasia.
Evaluation of S100A7 Overexpression as a Marker for Oral Cancer Free Survival (OCFS).
Among the five candidate protein biomarkers analyzed in our study, S100A7 overexpression in cytoplasm or nuclei showed significant association with malignant transformation of dysplastic lesions (Table 17). Hence, we further determined the potential of S100A7 overexpression in identifying patients having OLs with dysplasia at high risk of cancer development using Kaplan-Meier survival analysis to determine the probability of OCFS for these dysplasia patients. The association between S100A7 overexpression in cytoplasm or nuclei of dysplasia, loss of p16 expression and other potential risk factors including dysplasia grade (mild, moderate & severe), smoking history, age, gender and site of lesion with OCFS was analyzed by univariate analysis (Table 20). Notably, dysplasia patients showing cytoplasmic S100A7 had significantly reduced OCFS (mean OCFS=68.6 months, p=0.007) as compared to patients with weak or no cytoplasmic S100A7 immunostaining (mean OCFS=122.8 months; FIG. 25a; Table 20). Similarly, dysplasia patients showing nuclear S100A7 had reduced OCFS (mean OCFS=81.5 months, p=0.041) in comparison with patients with weak or no nuclear S100A7 immunostaining (mean OCFS=117.2 months; FIG. 25b; Table 20). Among clinical parameters, degree of dysplasia (moderate or severe) showed a significant correlation with OCFS (p<0.05, Table 3). Patients with moderate dysplasia demonstrated a low mean OCFS of 58.59 months (p=0.004) while in severe dysplasia cases, patients showed a mean OCFS of 38.9 months, (p<0.001, FIG. 26) compared to mild dysplasia (mean OCFS=116.25 months; FIG. 26). None of the other clinical parameters including age, gender, site of lesion or smoking history showed any significant correlation with OCFS (p>0.05, Table 3).
The life table and Kaplan Meier analysis clearly showed the low mean OCFS in moderate and severe dysplasia patients exhibiting S100A7 overexpression in cytoplasm or nuclei of dysplasia cells. 13 of 18 (72.2%) moderate dysplasia cases and 9 of 9 (100%) severe dysplasia cases that developed oral carcinoma exhibited cytoplasmic S100A7 overexpression, while 17 of 18 (94.4%) moderate and 8 of 9 (88.8%) severe dysplasia cases exhibited nuclear overexpression of S100A7. However, no significant correlation was observed for differences in OCFS in moderate/severe dysplasia patients exhibiting S100A7 overexpression in cytoplasm or nuclei (p>0.05) as revealed by Kaplan Meier analysis (FIG. 27a-c).
Analysis of risk factors for transformation of dysplasia into cancer was performed using the Cox proportional hazards model (Table 20). Cytoplasmic S100A7 overexpression (p=0.041, H.R.=2.36) and degree of dysplasia (moderate dysplasia, p=0.013 and severe dysplasia, p<0.001) emerged as an independent factor for identifying high risk dysplasia (Table 20). This clearly demonstrated the significance of cytoplasmic S100A7 overexpression in predicting malignant transformation of dysplasia.
Based on these data, the additional prognostic value that S100A7 overexpression in cytoplasm provided for predicting (Positive Predictive Value, PPV) or excluding (Negative Predictive Value, NPV) malignant transformation in oral dysplasia patients was measured by the ratios: PPVtransformation/dysplasia (118 months|S100A7 cyto+)/PPVtransformation/dysplasia (118 months)=75.6/60.0; NPVtransformation/dysplasia (118 months|S100A7 cyto+)/NPVtransformation/dysplasia (118 months)=78.5/40.0 (FIGS. 24a and 24b). Increase in PPV and NPV for S100A7 in comparison to dysplasia grade underscores the potential of S100A7 as a marker for predicting malignant transformation in dysplastic lesions.
Discussion of Results.
Early prediction for malignant potential of oral epithelial dysplasia is desired for clinical management of patients with the disease. In the present study, the expression of five candidate protein biomarkers, namely, S100A7, PTMA, 14-3-3ζ, 14-3-3σ and hnRNP K was verified in oral dysplasia and correlated with p16 expression as well as HPV 16/18 status. The majority of the dysplasia (mild/moderate/severe) that progressed to malignancy exhibited S100A7 overexpression (cytoplasm/nuclear). These data support the potential of S100A7 overexpression for use in distinguishing dysplasia patients at higher risk of cancer development. Of the five candidate protein biomarkers analyzed, S100A7 overexpression in cytoplasm emerged as the most significant risk factor of cancer development in patients having oral lesions with dysplasia with PPV (75.6%) and NPV (78.5%), regardless of age, gender, site of lesion, smoking habits and grade of dysplasia. Unlike S100A7, there was no significant difference in the expression of nuclear p16 among dysplasia patients who transformed to cancer relative to those who did not transform to cancer. Moreover, HPV 16/18 was not detected in any of the dysplasia cases analyzed in this study using cISH, irrespective of their p16 status or transformation to malignancy. Reports regarding the use of p16 expression as a surrogate marker for high risk (HR)-HPV infection or as a marker for progression in dysplasia are controversial (130-136). Moreover, involvement of both p16 and HR-HPV in development of oral epithelial dysplasia and their roles in transformation to malignancy have not been shown unequivocally as demonstrated in squamous cell carcinomas of pharynx (137-139).
Example 29—Combined Cytoplasmic S100A7 and Nuclear PTMA Overexpression is a Predictive Marker for High Risk of Malignant Transformation in Oral Dysplasia
In this example, PTMA was further evaluated for its potential use in assessing the risk of cancer development from oral dysplasias. In particular, the results of this example support the use of cytoplasmic S100A7 overexpression combined with nuclear PTMA overexpression as a biomarker for identifying oral dysplastic lesions at high risk of cancer development.
Materials and Methods.
Study population characteristics and criteria, histopathology, IHC and statistical analyses were consistent with those described in Example 28. Tissue sections analyzed were serial sections used for S100A7 immunostaining in Example 28.
Results.
Immunohistochemical analysis revealed that 78.2% (86 of 110) of dysplastic lesions exhibited increased nuclear expression of PTMA (FIG. 30). Thirty eight of 39 cases (92.3%) that transformed into cancer exhibited a high nuclear PTMA score relative to 50 of 71 (70.4%) cases that did not transform into cancer and had low nuclear PTMA scores (p=0.008). Kaplan Meier survival analysis demonstrated a significant correlation between high nuclear PTMA intensity score and poor prognosis in oral dysplasia patients (i.e., a high nuclear PTMA score indicated a high likelihood of malignant transformation). Oral dysplasia patients exhibiting increased nuclear PTMA had a mean oral cancer free survival (OCFS)=79.8 months. In contrast, patients exhibiting low expression of nuclear PTMA had a mean OCFS=122.5 months (p=0.029, FIG. 30a). Combination of cytoplasmic S100A7 and nuclear PTMA intensity scores emerged also as an indicator of poor prognosis in oral dysplasia patients (p=0.002, FIG. 30b).
Further, in Cox multivariate regression analysis, subjects having cytoplasmic S100A7 positive, nuclear PTMA positive moderate to severe dysplastic lesions are at higher risk for cancer development relative to other groups (Table 21).
Patients having cytoplasmic S100A7 positive, nuclear PTMA positive, moderate or severe grade oral dysplasia had significantly reduced disease free survival (mean DFS=50.5 months) compared to patients having S100A7 positive, nuclear PTMA positive, mild grade oral dysplasia (mean DFS=112 months; p<0.001; FIG. 31a).
Patients having cytoplasmic S100A7 positive, nuclear PTMA positive moderate or severe grade oral dysplasia had significantly reduced disease free survival (mean DFS=50.5 months) compared to any two of these markers being positive (mean DFS=85.9 months) or any one of these markers being positive (mean DFS=133.2 months; p<0.001; FIG. 31b).
Example 30—Oral Cytosmears can be Used to Assess S100A7 Expression Levels in Oral Epithelial Cells
In this example, cytosmear samples were evaluated for their potential use in assessing S100A7 expression in oral lesions. In particular, the results of this example support the use of cytosmear samples in methods that comprise detecting S100A7 overexpression as a biomarker for i) identifying oral dysplastic lesions at high risk of cancer development and ii) diagnosing and prognosing head and neck cancers, as set forth herein above.
Materials and Methods.
Oral cytosmears (n=20) were obtained from patients with oral lesions in the Dentistry Clinic at MSH, Toronto. To obtain the smear of exfoliated cells from the oral cavity of patients, a wooden spatula was used for scraping over the oral lesion. Cells collected were spread over a glass slide and fixed with a cytofixative. These cytomears were used for S100A7 immunostaining as described above. Briefly, cytomears were hydrated by dipping in Tris-buffered saline (TBS, 0.1M, pH=7.2), permeabilized with 0.025% of Triton-X 100 followed by blocking with 5% bovine serum albumin for 30 min. at room temperature in a moist chamber. Thereafter, slides were incubated with mouse monoclonal S100A7 antibody (sc-52948, Santa Cruz Biotechnology, CA) for 1 h at room temperature in a moist chamber. Slides will be washed with Tris-buffered saline (TBS, 0.1M, pH=7.2) followed by incubation with biotinylated secondary antibodies for 20 minutes. The sections were then incubated with VECTASTAIN Elite ABC Reagent (Vector labs, Burlingame, Calif.) and diaminobenzidine, which was used as the chromogen. Finally, the sections were counterstained with Mayer's hematoxylin and mounted with D.P.X mountant. Cytosmears prepared from oral cancer cells were used as controls. In negative controls, primary antibody was replaced by isotype-specific non-immune mouse IgG. The sections were evaluated by light microscopy using a Nanozoomer Scanner for cytopathology and scored for S100A7 immunostaining.
Results.
Cytosmears obtained from patients with oral lesions exhibited weak or no immunostaining for S100A7 in cytoplasm or nuclei of oral epithelial cells (FIG. 29a). Cytosmears prepared from oral cancer cells, which were used as a positive control, exhibited moderate S100A7 immunostaining in both cytoplasm and nuclei (FIG. 29b). No immunostaining was observed in negative control cytosmear samples (FIG. 29c). Cytosmears prepared from subjects having oral squamous cell carcinoma exhibited S100A7 immunostaining in both cytoplasm and nuclei (FIG. 29d).
While the foregoing invention has been described in some detail for purposes of clarity and understanding, it will be appreciated by one skilled in the art, from a reading of the disclosure, that various changes in form and detail can be made without departing from the true scope of the invention in the appended claims The present invention is not to be limited in scope by the specific embodiments described herein, since such embodiments are intended as but single illustrations of one aspect of the invention, and any functionally equivalent embodiments are within the scope of thereof. Indeed, various modifications of the invention, in addition to those shown and described herein, will become apparent to those skilled in the art from the foregoing description and accompanying drawings. Such modifications are intended to fall within the scope of the appended claims.
All publications, patents, and patent applications referred to herein are incorporated by reference in their entirety to the same extent as if each individual publication, patent, or patent application were specifically and individually indicated to be incorporated by reference in its entirety. Nothing herein is to be construed as an admission that the invention is not entitled to antedate the cited references by virtue of prior invention.
Set out below are full citations for the references cited herein.

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TABLE 1





iTRAQ ratios for HNSCC and non-cancerous head-and-neck tissue samples
























Accession #
Protein name
C1
C2
C3
C4
C5
C6
C7
C8





spt|P31947
Stratifin
3.6
2.48
1.73
2.23
2.09
3.44
3.15
2.05


trm|Q86V33
YWHAZ
2.58
2.34
1.45
1.54
1.23
1.85
10.27
1.58


spt|P29034
S100A 2
4.1
3.48
1.85
1.5
3.58
1.95
32.17
4.8


spt|P31151
S100A 7
2.35
2.33
3.04
2.9
3.78
2.65
NQ
2.82


spt|P06454
Prothymosin 
2.72
3.63
2.85
2.37
1.43
1.05
NQ
1.25



Alpha










trm|Q96IH1
Fascin
3.51
2.35
NQ
0.85
2.33
1.89
12.1
NQ


spt|P31949
Calgizzarin
2.38
NQ
2.35
2.75
2.13
1.83
NQ
2.37


spt|P36952
Maspin Precursor
2.03
NQ
1.76
1.76
1.02
2.2
NQ
1.98


spt|P13928
Annexin A8
1.3
NQ
NQ
1.58
1.6
1.33
NQ
NQ


spt|Q9NZT1
Calmodulin-like 
1.61
1.19
NQ
1.72
0.76
1.54
1.77
NQ



protein 5










gb|AAC13869.1
Glutathione S 
1.99
1.68
1.23
1.1
1.73
1.71
0.92
1.38



Transferase-P










spt|P00338
LDH A
2.07
1.74
1.27
1.02
1.36
1.77
2.33
1.56


spt|P62937
PPIA
1.69
1.89
1.18
0.99
1.76
1.34
2.86
1.65


spt|Q15691
APC-binding 
2.15
2.62
3.02
3.45
9999
1.39
NQ
2.02



protein EB1










gb|AAH16934
Superoxide 
2.38
1.81
NQ
1
0.81
7.96
NQ
NQ



dismutase [Mn]










trm|Q86YI6
L Plastin
1.78
1
NQ
0.88
1.36
1.68
NQ
NQ


spt|P60709
Beta Actin
1.11
1.04
1.06
0.86
1.14
0.86
0.82
1.3


trm|Q81Z29
Tubulin beta2
1.2
0.91
1.02
0.88
1.18
1.13
NQ
1.05


trm|Q8WU39
PACAP
0.3
0.72
0.65
0.71
0.61
0.48
0.13
0.52


trm|Q71DI3
Histone H3
0.38
NQ
0.57
0.58
0.69
0.36
NQ
0.6


spt|P62805
Histone H4
0.66
0.69
0.52
0.69
NQ
0.68
0.67
0.54


spt|P01009
Alpha 1 Anti- 
0.97
0.29
0.35
0.65
0.5
0.62
0.22
0.35



Trypsin











Precursor










spt|P51884
KSPG Lumican
0.51
0.65
0.7
0.71
0.51
0.53
0.65
0.65


trm|Q96RZ7
Mast cell tryptase 
0.51
0.76
0.7
0.76
0.64
0.54
0.62
0.65



beta III










trm|Q9UE88
Histone H2B.1
0.58
0.6
0.61
0.87
0.62
0.58
1.9
0.48


spt|P08670
Vimentin
0.26
0.4
0.62
0.61
0.55
0.33
0.38
0.45


spt|P32119
Peroxiredoxin 2
0.43
0.85
0.56
0.66
0.71
0.46
0.55
0.89


spt|P00915
Carbonic 
0.34
0.78
0.48
0.57
0.37
0.37
0.88
0.67



Anhydrase I










spt|P30043
Flavin reductase
0.54
0.74
0.54
NQ
0.8
0.59
0.1
0.86


pir|KRHUE
Cytokeratin 14
1.27
1.31
1.84
3.83
1.46
1.29
0.24
2.06


trm|Q86U86
Polybromo-1D
NQ
NQ
0.54
NQ
0.58
NQ
NQ
NQ


spt|P14618
PK M2
1.51
1.48
1.18
1.04
1.18
1.34
2.26
1.61


spt|P04083
Annexin A1
0.96
1.63
1.2
2.36
1.4
1.68
0.63
1.24


gb|AAH16768.1
Nucleophosmin 1
1.37
NQ
1.69
1.46
1.4
1.8
NQ
1.19


sptIP04792
Hsp27
1.2
1.3
1.25
1.68
1.25
1.49
1.69
1.82


spt|P04080
Cystatin B
1.04
0.75
0.58
0.77
0.76
1.21
0.67
0.76


spt|P14625
GRP 94
0.5
0.86
NQ
0.8
0.77
0.55
0.59
NQ


gb|AAA59555
MARCKS
0.86
1.57
1.26
9999
0.54
1.09
5.47
1.3






Accession #
Protein name
C9
C10
N2
N3
N1
N4
N5






spt|P31947
Stratifin
1.93
1.04
0.84
0.52
0.82
0.86
1.06



trm|Q86V33
YWHAZ
1.58
1.02
0.95
0.81
0.98
0.93
0.93



spt|P29034
S100A 2
2.34
2.27
1.37
1.28
0.95
1.35
1.88



spt|P31151
S100A 7
1.71
1.44
0.69
1.01
0.81
1.08
1.26



spt|P06454
Prothymosin 
1.79
1.29
0.88
1.53
1.04
1.16
1.66




Alpha










trm|Q96IH1
Fascin
1.43
1.76
1.16
NQ
1.14
1.02
1.01



spt|P31949
Calgizzarin
2.5
2.23
NQ
1
1.59
1.3
1.19



spt|P36952
Maspin Precursor
1.98
0.94
NQ
1.09
0.86
1.09
0.88



spt|P13928
Annexin A8
1.71
1.53
0.83
NQ
1.84
1.18
1.12



spt|Q9NZT1
Calmodulin-like 
1.17
0.98
0.92
NQ
0.88
0.58
1.06




protein 5










gb|AAC13869.1
Glutathione S 
1.73
1.13
1.08
0.97
0.59
1.01
0.92




Transferase-P










spt|P00338
LDH A
1.84
1.26
1.03
0.75
0.96
0.94
0.93



spt|P62937
PPIA
1.17
1.06
0.86
0.48
0.86
0.92
0.97



spt|Q15691
APC-binding 
1.94
NQ
0.93
0.87
1.36
1.40
NQ




protein EB1










gb|AAH16934
Superoxide 
NQ
0.91
NQ
NQ
NQ
0.81
1.13




dismutase [Mn]










trm|Q86YI6
L Plastin
1.25
1.52
NQ
NQ
0.98
0.68
1.08



spt|P60709
Beta Actin
1.06
0.87
0.83
0.71
1.07
0.81
1.1



trm|Q81Z29
Tubulin beta2
1.2
1.02
0.99
0.88
1.18
1
NQ



trm|Q8WU39
PACAP
0.72
0.62
0.39
0.31
1.66
1.44
1.02



trm|Q71DI3
Histone H3
0.62
2.47
NQ
1.86
1.73
1.24
1.84



spt|P62805
Histone H4
1.24
NQ
1.2
2.36
1.89
2.72
NQ



spt|P01009
Alpha 1 Anti- 
0.71
0.28
1
0.31
0.73
0.85
0.82




Trypsin











Precursor










spt|P51884
KSPG Lumican
0.6
0.93
2.03
1.84
0.68
1.02
0.8



trm|Q96RZ7
Mast cell tryptase 
0.7
0.83
1.36
1.84
0.93
0.92
0.79




beta III










trm|Q9UE88
Histone H2B.1
0.43
1.09
2
1.3
1.45
1.38
1.79



spt|P08670
Vimentin
0.43
0.73
0.91
0.77
1.03
0.55
0.78



spt|P32119
Peroxiredoxin 2
0.63
0.51
0.94
0.43
0.64
0.55
0.77



spt|P00915
Carbonic 
0.59
0.56
0.63
0.36
0.51
0.67
0.93




Anhydrase I










spt|P30043
Flavin reductase
NQ
0.72
0.67
0.5
0.64
NQ
0.81



pir|KRHUE
Cytokeratin 14
1.01
1.7
0.61
0.98
0.91
1.04
1.18



trm|Q86U86
Polybromo-1D
NQ
0.58
1.69
NQ
NQ
1.07
NQ



spt|P14618
PK M2
1.4
1.21
0.9
0.84
0.95
0.94
0.97



spt|P04083
Annexin A1
0.91
1.52
0.86
0.94
1.05
1.27
1.4



gb|AAH16768.1
Nucleophosmin 1
1.15
1.36
NQ
0.84
1.19
1.48
0.98



sptIP04792
Hsp27
1.42
1.01
1.21
1.01
0.9
1.32
1.12



spt|P04080
Cystatin B
0.78
0.52
0.95
0.37
0.72
0.83
0.72



spt|P14625
GRP 94
0.8
0.73
0.68
NQ
1.17
0.81
0.77



gb|AAA59555
MARCKS
0.56
0.54
1.19
1.1
0.98
0.54
0.83





NQ—Not Quantifiable.













TABLE 2







Receiver-operating characteristics from the iTRAQ ratios


of a panel of three best-performing biomarkers - YWHAZ,


stratifin, and S100A7 - individually and as a panel.












BIOMARKER PANEL
SENS
SPEC
PPV
NPV
AUC





YWHAZ
0.30
1.00
1.00
0.42
1.00


SFN
0.80
1.00
1.00
0.71
0.98


S100 CBP A7
0.70
1.00
1.00
0.63
0.90


YWHAZ, STRATIFIN,
0.92
0.91
0.95
0.85
0.96


S100A7
















TABLE 3







Receiver-operating characteristics from the IHC scores


of a panel of three best-performing biomarkers - YWHAZ,


stratifin, and S100A7 - individually and as a panel.












BIOMARKER PANEL
SENS
SPEC
PPV
NPV
AUC





YWHAZ
1.00
0.71
0.71
1.00
0.90


SFN
0.92
0.60
0.62
0.91
0.85


S100 CBP A7
0.96
0.71
0.71
0.96
0.90


YWHAZ, STRATIFIN,
0.92
0.87
0.83
0.94
0.91


S100A7
















TABLE 4







Comparison of receiver-operating characteristics from the iTRAQ


ratios of the panel of three best-performing biomarkers.












COMPARISON
SENS
SPEC
PPV
NPV
AUC





Cancer vs.
0.92
0.83
0.85
0.92
0.89


Paired Normal







Cancer vs.
0.96
0.96
0.98
0.90
0.97


Non-Paired Normal
















TABLE 5







Differentially-expressed proteins not previously described in OPLs and head-and-neck malignancies and cancer.
















Expression



SEQ



in Head-and-
Expression


ID. No.
Protein Name
Gene Name
Accession No.
Neck Cancer
in OPLs















1.
Calmodulin-like
CALML5
Peptide: spt|Q9NZT1
Up-regulated




protein 5

mRNA/DNA coding: NM_017422




2.
Polybromo-1D
PBRM1
Peptide: trm|Q86U86
Down-regulated






mRNA/DNA coding: NM_181042




3.
APC-binding protein
MAPRE1
Peptide: spt|Q15691
Up-regulated




EB1

mRNA/DNA coding: NM_012325




4.
Carbonic anhydrase I
CA1
Peptide: spt|P00915
Down-regulated






mRNA/DNA coding: NM_001738




5.
Mast cell tryptase
tryptaseB
Peptide: trm|Q96RZ7
Down-regulated




beta III

mRNA/DNA coding: NM_024164




6.
Histone H3
HIST2H3A
Peptide: trm|Q71DI3
Down-regulated






mRNA/DNA coding: NM_021059




7.
Plastin 3
PLS3
Peptide: spt|P13797
Up-regulated






mRNA/DNA coding: NM_005032




8.
Histone H4
HIST1H4A
Peptide: spt|P62805
Down-regulated






mRNA/DNA coding: NM_003495




9.
Cyclophilin A
PPIA
Peptide: trm|Q6NTE9
Up-regulated






mRNA/DNA coding: NM_021130




10.
PACAP
MGC29506
Peptide: trm|Q8WU39
Down-regulated




(proapoptotic caspase

mRNA/DNA coding: NM_016459





adaptor protein)






11.
LDH A
LDHA
Peptide: spt|P00338
Up-regulated






mRNA/DNA coding: NM_005566




12.
KSPG Luminican
LUM
Peptide: spt|P51884
Down-regulated






mRNA/DNA coding: NM_002345




13.
S100 CBP A7
S100A7
Peptide: spt|P31151
Up-regulated
*Up-regulated





mRNA/DNA coding: NM_002963.3




14.
Peroxiredoxin 2
PRDX2
Peptide: spt|P32119
Down-regulated
Down-regulated





mRNA/DNA coding: NM_181738




15.
Superoxide dismutase
SOD2
Peptide: trm|AAH16934
Up-regulated
*Up-regulated



2 (SOD2 protein)

mRNA/DNA coding: BC016934




16.
Alpha 1 Anti-Trypsin
SERPINA1 or
Peptide: spt|P01009
Down-regulated
Down-regulated



Precursor
AAT
mRNA/DNA coding: NM_001002236




17.
MARCKS
MACS
Peptide: gb|AAA59555.1
Up-regulated
Down-regulated





mRNA/DNA coding: M68956




18.
GRP-94
HSP90B1
Peptide: spt|P14625
Down-regulated
Up-regulated





mRNA/DNA coding: NM_003299




19.
Prothymosin Alpha
PTMA (also referred
Peptide: spt|P06454
Up-regulated
Up-regulated




to as PTHA)
mRNA/DNA coding: NM_001099285




20.
Histone H2B.1
HIST2H2BE
Peptide: spt|Q16778
Down-regulated
Up-regulated





mRNA/DNA coding: NM_003528




21.
Nucleophosmin 1
NPM1
Peptide: gb|AAH16768.1
Up-regulated
Up-regulated





mRNA/DNA coding: BC016768




22.
PK M2
PKM2
Peptide: spt|P14618

Up-regulated





mRNA/DNA coding: NM_182471




23.
Stratifin
SFN
spt|P31947

Up-regulated





mRNA/DNA coding:




24.
YWHAZ

trm|Q86V33

Up-regulated





mRNA/DNA coding:




25.
hnRNPK

spt|P61978

Up-regulated





mRNA/DNA coding:




18.
HSP90B1

spt|P14625

Up-regulated





mRNA/DNA coding:




26.
Parathymosin
PTHM
trm|O15256

Up-regulated





mRNA/DNA coding:




27.
Cystatin B

spt|P04080

Down-regulated





mRNA/DNA coding: P04080




28.
DLC1

trm|Q6NSB4

Down-regulated





mRNA/DNA coding:




29.
FABP5

spt|Q01469

Down-regulated





mRNA/DNA coding:




30.
IGHG1 protein

gb|AAH25314.1

Down-regulated





mRNA/DNA coding:




31.
Calgizzarin

spt|P31949

Down-regulated





mRNA/DNA coding:




32.
IGL 2*

trm|Q8N5F4

Up-regulated





mRNA/DNA coding:




33.
P37AUF1*

trm|Q12771

Up-regulated





mRNA/DNA coding:




22.
PKM2*

spt|P14618

Up-regulated





mRNA/DNA coding:




34.
ROA1HNRNPA1*

sptIP09651

Up-regulated





mRNA/DNA coding:




35.
Hsp27*

sptIP04792

Up-regulated





mRNA/DNA coding: P04792




36.
Cofilin*

spt|P23528

Up-regulated





mRNA/DNA coding:




37.
Glyceraldehyde-3-

emb|CAA25833.1

Up-regulated



phosphate Dehydrogenase*

mRNA/DNA coding:




38.
NDP Kinase B*

spt|P22392

Up-regulated





mRNA/DNA coding:




39.
Elongation Factor 2*

spt|P13639

Up-regulated





mRNA/DNA coding:




40.
PE Binding protein*

spt|P30086

Up-regulated





mRNA/DNA coding:




41.
CALM 3*

spt|P27482

Up-regulated





mRNA/DNA coding:
















TABLE 6





Average iTRAQ ratios for OPLs aNQ histologically-normal control oral tissue samples






















Accession #
Protein Name
D1
D2
D3
D4
D5
D6





spt|P31947
Stratifin
0.74
2.15
1.94
1.53
1.77
1.63


trm|Q86V33
YWHAZ
1.02
3.07
1.19
1.88
0.81
1.5


spt|P61978
hnRNPK
9.86
1.14
1.13
1.71
1.25
1.5


spt|P06454
PTHA
0.64
0.61
1.19
1.53
3.91
3.54


spt|P14625
HSP90B1
2.86
1.65
1.46
3.38
0.8
0.99


trm|O15256
Parathymosin
NQ
NQ
NQ
3.97
2.35
2.89


trm|Q9UE88
Histone H2B.1
2.97
1.25
1.73
0.87
1.96
1.52


spt|P14625
GRP 94
2.86
1.65
1.19
3.38
0.8
0.99


gb|AAH16768.1
Nucleophosmin 1
1.2
0.96
1.56
1.66
NQ
NQ


spt|P04080
Cystatin B
0.78
1.14
0.36
0.39
0.54
0.78


gb|AAA59555.1
MARCKS
0.67
0.5
0.57
0.61
0.72
0.6


trm|Q6NSB4
DLC1
1.63
0.29
NQ
NQ
0.5
0.53


spt|P01009
Alpha 1 Anti-
0.45
0.57
0.67
0.85
1.36
0.99



Trypsin Precursor








spt|P32119
Peroxiredoxin 2
0.89
0.72
0.62
0.63
0.64
0.47


spt|Q01469
FABP5
0.78
1.43
0.79
0.67
0.58
0.66


gb|AAH25314.1
IGHG1 protein
1.13
0.58
1.15
0.67
NQ
NQ


spt|P31949
Calgizzarin
0.48
0.45
NQ
NQ
0.84
1.18


trm|Q8N5F4
IGL 2*
NQ
NQ
NQ
NQ
4.09
1.77


trm|Q12771
p37AUF1*
7.77
4.35
NQ
NQ
NQ
NQ


prf|0904262A
SOD2*
NQ
NQ
NQ
NQ
1.34
1.51


spt|P14618
PKM2*
1.04
1.37
1.26
1.66
1.09
1.12


sptIP09651
ROA1HNRNPA1*
1.3
1.7
1.16
1.25
0.9
1.87


sptIP04792
Hsp27*
1.17
1.88
0.78
1.27
1.13
2.35


spt|P23528
Cofilin*
1.13
1.27
1.45
2.06
1.17
1.17


emb|CAA25833.1
Glyceraldehyde-3-
1.37
1.55
0.75
1.5
1.13
1.12



phosphate









Dehydrogenase








spt|P13639
Elongation Factor 2*
1.26
1.47
NQ
NQ
1.35
1.28


spt|P31151
S100 A7*
NQ
NQ
1.3
1.4
NQ
NQ


spt|P30086
PE BiNQing protein
NQ
NQ
NQ
NQ
1.4
1.57


spt|P27482
CALM 3*
1.25
0.97
1.15
1.15
4.55
1.08


spt|P06396
Gelsolin Precursor
1.04
1
0.95
1.03
1.04
1.15





Accession #
Protein Name
N1
N2
N3
N4
N5
N6





spt|P31947
Stratifin
0.88
0.74
0.75
0.84
0.78
1.03


trm|Q86V33
YWHAZ
1.18
0.84
0.99
1
0.8
0.97


spt|P61978
hnRNPK
1.04
1.24
1.1
1.23
0.9
NQ


spt|P06454
PTHA
0.69
0.91
1.57
0.88
1.16
1.66


spt|P14625
HSP90B1
1.16
1.19
0.61
0.98
1.05
1.02


trm|O15256
Parathymosin
NQ
NQ
0.81
NQ
NQ
NQ


trm|Q9UE88
Histone H2B.1
1.2
0.82
1.83
1.2
1.38
1.5


spt|P14625
GRP 94
1.16
0.61
1.46
1
0.81
0.85


gb|AAH16768.1
Nucleophosmin 1
0.77
0.97
NQ
1.17
1.05
NQ


spt|P04080
Cystatin B
0.96
0.29
0.82
0.87
0.77
0.73


gb|AAA59555.1
MARCKS
0.56
0.57
0.83
NQ
0.54
0.83


trm|Q6NSB4
DLC1
0.43
NQ
0.75
0.68
NQ
0.99


spt|P01009
Alpha 1 Anti-
0.92
0.77
0.79
0.81
0.69
1.06



Trypsin Precursor








spt|P32119
Peroxiredoxin 2
0.99
0.7
0.69
0.6
0.75
NQ


spt|Q01469
FABP5
0.89
0.97
0.87
0.83
0.93
0.93


gb|AAH25314.1
IGHG1 protein
1.11
1.24
NQ
NQ
NQ
NQ


spt|P31949
Calgizzarin
0.51
NQ
1.19
1.23
NQ
1.19


trm|Q8N5F4
IGL 2*
NQ
NQ
0.95
NQ
NQ
NQ


trm|Q12771
p37AUF1*
0.97
NQ
NQ
NQ
NQ
NQ


prf|0904262A
SOD2*
NQ
NQ
1.23
NQ
0.81
1.13


spt|P14618
PKM2*
1.12
0.94
1.09
1.01
0.87
0.97


spt|P09651
ROA1HNRNPA1*
0.81
1.33
1.04
1.23
0.88
1.07


spt|P04792
Hsp27*
0.96
1.17
0.83
0.89
1.23
0.95


spt|P23528
Cofilin*
0.73
0.93
1.05
1.04
0.9
NQ


emb|CAA25833.1
Glyceraldehyde-3-
1.39
0.62
1.36
1.17
0.71
0.97



phosphate









Dehydrogenase








spt|P13639
Elongation Factor 2*
1.03
NQ
1.34
1.22
1.07
0.93


spt|P31151
S100 A7*
NQ
0.88
NQ
0.81
1.03
1.09


spt|P30086
PE BiNQing protein
NQ
NQ
1.05
NQ
NQ
NQ


spt|P27482
CALM 3*
0.89
1
0.89
0.51
1.02
1.06


spt|P06396
Gelsolin Precursor
0.9
1.05
1.02
0.91
1.05
1.02





NQ—Not Quantifiable.













TABLE 7







Receiver-operating characteristics from (A) the iTRAQ ratios and


(B) IHC scores of a panel of three best-performing biomarkers -


YWHAZ, stratifin, and hnRNPK - individually and as a panel.












Biomarker
Sensitivity
Specificity
PPV
NPV
AUC















A. iTRAQ analysis







YWHAZ
0.33
1.0
1.0
0.43
0.78


Stratifin
0.81
1.0
1.0
0.75
0.82


hnRNPK
0.17
1.0
1.0
0.38
0.78


Panel of the three
0.83
0.74
0.87
0.69
0.85


B. IHC analysis







YWHAZ
0.90
0.95
0.96
0.87
0.93


Stratifin
0.77
0.95
0.96
0.74
0.93


hnRNPK
0.80
0.91
0.92
0.76
0.89


Panel of the three
0.91
0.95
0.96
0.88
0.97
















TABLE 8







Analysis of Stratifin and YWHAZ in HNOSCCs: correlation


with clinicopathological parameters.












Total





Clinicopathological
Cases
STRATIFIN+
STRATIFIN+-YWHAZ+
STRATIFIN+/YWHAZ+














Features
N
n
(%)
n
(%)
n
(%)

















Non-malignant tissue
39
12
(31)
8
(20)
25
(64)


HNOSCC#
51
32
(63)
28
(55)
43
(84)


Differentiation*









WDSCC
29
18
(62)
16
(55)
26
(90)


MDSCC
19
12
(63)
10
(53)
15
(79)


PDSCC
3
2
(67)
2
(67)
2
(67)


Tumor Stage









T1
6
5
(83)
5
(83)
6
(100) 


T2
15
6
(40)
4
(27)
11
(73)


T3
13
9
(69)
8
(61)
12
(92)


T4
17
12
(71)
11
(65)
14
(82)


Nodal Status









N−
28
17
(61)
15
(54)
23
(82)


N+
23
15
(65)
13
(56)
20
(87)





*WDSCC, well differentiated squamous cell carcinoma; MDSCC, moderately differentiated squamous cell carcinoma; PDSCC, poorly differentiated squamous cell carcinoma


#For HNOSCCs vs. Non-malignant tissues:


a) Stratifin+ (p = 0.03, OR = 3.8, 95% CI = 1.6-9.2);


b) YWHAZ+ (p = 0.024, OR = 2.8, 95% CI = 1.2-6.8);


c) Stratifin+-YWHAZ+ (p = 0.001, OR = 4.7, 95% CI = 1.8-12.2);


d) SFN+/YWHAZ+ (p = 0.027, OR = 3.1, 95% CI = 1.1-8.2).













TABLE 9a







Analysis of overexpression of hnRNP K protein in oral lesions and correlation with clinicopathological parameters.
















Clinicopathological
Total
Nuclear
Positivity


Cytoplasmic
Positivity




Features
Cases
N
(%)
p-value
OR (95% CI)
N
(%)
p-value
OR (95% CI)



















NORMAL
55
4
 (7)


—
—




LEUKOPLAKIA
199
141
(71)
<0.001a
30.9 (10.7-89.7) 
26
(13)
<0.001b
4.3 (2.2-7.2)


NO DYSPLASIA
115
78
(68)
<0.001c
26.8 (9.1-79.9) 
18
(16)
<0.001d
4.3 (1.8-6.3)


DYSPLASIA
84
63
(75)
<0.001e
38.2 (11.7-113.1)
8
(10)
<0.001f
 5.8 (2.5-13.4)


HNOSCC
100
78
(78)
<0.001g
45.2 (14.7-138.8)
38
(38)




Age (Median, 53 yrs)











<53
49
34
(69)
0.05
2.7 (1.1-7.5) 
16
(33)
0.28
—


≧53
51
44
(86)


22
(43)




Gender











Male
75
59
(78)
0.78
—
28
(37)
0.81
—


Female
25
19
(76)


10
(40)




Differentiation







0.001



WDSCC
45
33
(73)
0.31
—
9
(20)

—


MDSCC
49
39
(79)


24
(49)




PDSCC
6
6
(100) 


5
(83)




Tumor Stage







0.19



T1
4
4
(100) 
0.42
—
3
(75)

—


T2
35
28
(80)


15
(43)




T3
25
17
(68)


6
(24)




T4
36
29
(81)


14
(39)




Nodal Status







0.52



N0
33
24
(73)
0.37
—
14
(42)

—


N1-4
67
54
(81)


24
(36)




Habits







0.41



Non consumer
22
19
(86)
0.28
—
10
(45)

—


Tobacco consumer
78
59
(75)


28
(36)





# Nuclear staining:


aNormal vs. Leukoplakia;


cNormal vs. Leukoplakia with no evidence of dysplasia;


eNormal vs. Dysplasia;


gNormal vs. HNOSCCs; N/L/HNOSCCs: p < 0.001;


## Cytoplasmic staining:


bLeukoplakia vs. HNOSCCs;


dLeukoplakia with no evidence of dysplasia vs. HNOSCCs;


fDysplasia vs. HNOSCCs; N/L/HNOSCCs: p < 0.001













TABLE 9b







Biomarker analysis of hnRNP K (nuclear/cytoplasmic)


in oral lesions.











hnRNP K
Sensitivity
Specificity
PPV
AUC














I) Nuclear staining






Normal vs. Leukoplakia
67.0
92.7
94.8
0.822


(No Dysplasia)






Normal vs. Leukoplakia
74.1
92.3
93.7
0.872


(Dysplasia)






Normal vs. OSCCs
78.0
92.3
95.1
0.869


II) Cytoplasmic staining






Normal vs. Leukoplakia
15.3
100
100
0.577


(No Dysplasia)






Normal vs. Leukoplakia
8.3
100
100
0.543


(Dysplasia)






Normal vs. OSCCs
38.1
100
100
0.709
















TABLE 10







Alternate accession numbers for OPL proteins.









Accession #
Protein Name
Alternate Accession #s





spt|P61978
hnRNPK
gi|48429103, NP_002131.2,




S74678.1, NP_112552.1,




AAB20770.1, NP_112553.1,




X72727.1, 1J5K_A,




CAA51267.1, 1KHM_A,




AB209562.1, 1ZZI_A,




BAD92799.1, 1ZZI_B,




BC000355.2, 1ZZJ_A,




AAH00355.1, 1ZZJ_B,




BC014980.1, 1ZZJ_C,




AAH14980.1, 1ZZK_A,




S43363


spt|P14625
HSP90B1
gi|119360, AAH66656.1,




X15187.1, M26596.1,




CAA33261.1, AAA58621.1,




M33716.1, AY040226.1,




AAA68201.1, AAK74072.1,




BC066656.1, NP_003290.1


trm|O15256
Parathymosin
gi|74705500, Y13586.1,




CAA73913.1


trm|Q6NSB4
DLC1
gi|74758095, BC070299.1,




AAH70299.1


spt|Q01469
FABP5
gi|232081, AAH70303.1,




M94856.1, I56326,




AAA58467.1, NP_001435.1,




BT007449.1, XP_001127657.1,




AAP36117.1, XP_001128089.1,




BC019385.2, XP_001718427.1,




AAH19385.1, 1B56_A,




BC070303.1, 1JJJ_A


gb|AAH25314.1
IGHG1 protein
gi|19263707


trm|Q8N5F4
IGL 2*
gi|74728989, BC032452.1,




AAH32452.1


trm|Q12771
P37AUF1*
gi|74754454, U02019.1,




AAC50056.1, A54601


prf|0904262A
SOD2*
gi|223632


spt|P14618
PKM2*
gi|20178296, BC007952.2,




M23725.1, AAH07952.3,




AAA36449.1, BC012811.2,




M26252.1, AAH12811.3,




AAA36672.1, BC035198.1,




X56494.1, AAH35198.1,




CAA39849.1, AF025439.1,




AY352517.1, AAC39559.1,




AAQ15274.1, S30038,




AK222927.1, S64635,




BAD96647.1, NP_002645.3,




AC020779.10, NP_872270.1,




CH471082.1, 1T5A_A,




EAW77884.1, 1T5A_B,




BC000481.2, 1T5A_C,




AAH00481.3, 1T5A_D,




BC007640.1, 1ZJH_A,




AAH07640.1


sptIP09651
ROA1HNRNPA1*
gi|133254, AAH74502.1,




X12671.1, BC103707.1,




CAA31191.1, AAI03708.1,




X06747.1, NZ_SHDD041214211,




CAA29922.1, NP_002127.1,




X04347.1, 1HA1_A,




CAA27874.1, 1L3K_A,




X79536.1, 1PGZ_A,




CAA56072.1, 1PO6_A,




BC002355.2, 1U1K_A,




AAH02355.1, 1U1L_A,




BC009600.1, 1U1M_A,




AAH09600.1, 1U1N_A,




BC012158.1, 1U1O_A,




AAH12158.1, 1U1P_A,




BC033714.1, 1U1Q_A,




AAH33714.1, 1U1R_A,




BC052296.1, 1UP1_A,




AAH52296.1, 2H4M_C,




BC070315.1, 2H4M_D,




AAH70315.1, 2UP1_A,




BC074502.1


spt|P23528
Cofilin*
gi|116848, AAH11005.1,




D00682.1, BC012265.1,




BAA00589.1, AAH12265.1,




U21909.1, BC012318.1,




AAA64501.1, AAH12318.1,




X95404.1, BC018256.2,




CAA64685.1, AAH18256.1,




BT006846.1, NP_005498.1,




AAP35492.1, 1Q8G_A,




BC011005.2, 1Q8X_A


emb|CAA25833.1
Glyceraldehyde-3-
gi|31645, 1U8F,



Phosphate Dehydrogenase*
1ZNQ


spt|P22392
NDP Kinase B*
gi|127983, NP_002503.1,




X58965.1, 1NSK_L,




CAB37870.1, 1NSK_N,




M36981.1, 1NSK_O,




AAA36369.1, 1NSK_R,




L16785.1, 1NSK_T,




AAA60228.1, 1NSK_U,




BC002476.2, 1NUE_A,




AAH02476.1, 1NUE_B,




A49798, 1NUE_C,




NP_001018146.1, 1NUE_D,




NP_001018147.1, 1NUE_E,




NP_001018148.1, 1NUE_F,




NP_001018149.1


spt|P13639
Elongation Factor 2*
gi|119172, BC126259.1,




X51466.1, AAI26260.1,




CAA35829.1, M19997.1,




Z11692.1, AAA50388.1,




CAA77750.1, EFHU2,




AY942181.1, NP_001952.1,




AAX34409.1


spt|P30086
PE Binding protein
gi|1352726, BC031102.1,




D16111.1, AAH31102.1,




BAA03684.1, S76773.1,




X75252.1, AAD14234.1,




CAA53031.1, I53745,




X85033.1, NP_002558.1,




CAA59404.1, 1BD9_A,




BC008714.2, 1BD9_B,




AAH08714.1, 1BEH_A,




BC017396.1, 1BEH_B,




AAH17396.1


spt|P27482
CALM 3*
gi|115502, CAI11029.1,




M58026.1, BC031889.1,




AAA36356.1, AAH31889.1,




X13461.1, AAA21893.1,




CAA31809.1, NP_005176.1,




AL732437.12, 1GGZ_A




















TABLE 11









SEQUENCE
#



ACCESSION
PROTEIN
COVERAGE
PEPTIDES
PEPTIDE





gb|AAC13869.1
Glutathione S 
38.27751279
6
AFLASPEYVNLPINGNGKQ



Transferase-P


DQQEAALVDMVNDGVEDLR






FQDGDLTLYQSNTILR






MLLADQGQSWK






PPYTVVYFPVR






TLGLYGKDQQEAALVDMVNDGVEDLR


 


spt|P00338
LDH A
20.54380625
7
DQLIYNLLK






FIIPNVVK






GEMMDLQHGSLFLR






LVIITAGAR






QVVESAYEVIK






VIGSGCNLDSAR






VTLTSEEEAR


 


spt|P01009
Alpha 1 Anti-
29.90430593
9
AVLTIDEK



Trypsin Precursor


DTEEEDFHVDQVTTVK






FLENEDRR






GTEAAGAMFLEAIPM






GTEAAGAMFLEAIPMSIPPEVK






LQHLENELTHDIITK






SVLGQLGITK






TDTSHHDQDHPTFNK






VFSNGADLSGVTEEAPLK


 


spt|P04080
Cystatin B
54.08163071
6
CGAPSATQPATAETQHIADQVR






GAPSATQPATAETQHIADQVR






MMCGAPSATQPATAETQHIADQVR






PSATQPATAETQHIADQVR






SQVVAGTNYFIK






VHVGDEDFVHLR


 


spt|P04083
Annexin A1
34.49275494
9
ALYEAGER






DITSDTSGDFR






GLGTDEDTLIEILASR






GTDVNVFNTILTTR






GVDEATIIDILTK






KGTDVNVFNTILTTR






NALLSLAK






QAWFIENEEQEYVQTVK






TPAQFDADELR


 


spt|P06454
Prothymosin 
35.45454443
5
AAEDDEDDDVDTK



Alpha


AAEDDEDDDVDTKK






EVVEEAENGR






KEVVEEAENGR






SDAAVDTSSEITTK


 


spt|P07585
Decorin Precursor
5.013927445
4
DFEPSLGPVCPFR






DLPPDTTLLDNLQNNK






ELHLDNNK






VSPGAFTPLVK


 


spt|P08670
Vimentin
58.81057382
28
ADLSEAANR






DGQVINETSQHHDDLE






DNLAEDIMR






EEAENTLQSFR






EKLQEEMLQR






EMEENFAVEAANYQDTIGR






ETNLDSLPLVDTHSK






EYQDLLNVK






FADLSEAANR






ILLAELEQLK






ISLPLPNFSSLNLR






KLLEGEESR






LGDLYEEEMR






LLEGEESR






LLQDSVDFSLADAINTEFK






LQDEIQNMK






LQDEIQNMKEEMAR






LQEEMLQR






NLDSLPLVDTHSK






NLQEAEEWYK






ODVDNASLAR






QQYESVAAK






QVDQLTNDK






QVQSLTCEVDALK






RQVDQLTNDK






TNEKVELQELNDR






VELQELNDR






VEVERDNLAEDIMR


 


spt|P13928
Annexin A8
17.4311921
6
AYEEDYGSSLEEDIQADTSGYLER






EGVIIEILASR






GIGTNEQAIIDVLTK






NALLSLVGSDP






SSSHFNPDPDAETLYK






TLSSMIMEDTSGDYK


 


spt|P14618
PK M2
39.81132209
18
AEGSDVANAVLDGADCIMLSGETAK






APIIAVTR






EAEAAIYHLQLFEELR






EAEAAIYHLQLFEELRR






FDEILEASDGIMVAR






GADFLVTEVENGGSLGSK






GDLGIEPAEK






GDYPLEAVR






GSGTAEVELK






GVNLPGAAVDLPAVSEK






IYVDDGLISLQVK






KASDVHEVR






LAPITSDPTEATAVGAVEASFK






LDIDSPPITAR






NTGIICTIGPASR






RFDEILEASDGIMVAR






TATESFASDPILYRPVAVALDTK






VNFAMNVGK


 


spt|P14625
GRP 94
16.31382257
6
FAFQAEVNR






GVVDSDDLPLNVSR






IYMAGSSR






LGVIEDHSNR






LISLTDENALSGNEELTVK






NLLHVTDTGVGMTR


 


spt|P26038
Meosin
31.25
17
ALELEQER






ALTSELANAR






APDFVFYAPR






AQQELEEQTR






EALLQASR






EKEELMER






FYPEDVSEELIQDITQR






IGFPWSEIR






IQVWHEEHR






ISQLEMAR






KAQQELEEQTR






KTQEQLALEMAELTAR






QLFDQVVK






TAMSTPHVAEPAENEQDEQDENGAEAS






TANDMIHAENMR






TQEQLALEMAELTAR






VTTMDAELEFAIQPNTTGK


 


spt|P29034
S100A 2
17.52577275
2
ELPSFVGEK






ELPSFVGEKVDEEGLK


 


spt|P31151
S100A 7
33.00000131
3
GTNYLADVFEK






GTNYLADVFEKK






SIIGMIDMFHK


 


spt|P31947
SFN
75.4629612
16
ADLHTLSEDSYK






DNLTLWTADNAGEEGGEAPQEPQS






DSTLIMQLLR






EEKGPEVR






EMPPTNPIR






GAVEKGEELSCEER






GEELSCEER






LAEQAER






NLLSVAYK






SAYQEAMDISK






SAYQEAMDISKK






SNEEGSEEKGPEVR






TTFDEAMADLHTLSEDSYK






VLSSIEQK






YEDMAAFMK






YLAEVATGDDK


 


spt|P31949
Calgizzarin
36.19047701
2
ISSPTETER






TEFLSFMNTELAAFTK


 


spt|P36952
Maspin Precursor
11.4666631
2
GDTANEIGQVLHFENVK






VCLEITEDGGDSIEVPGAR


 


spt|P51884
KSPG Lumican
23.66863936
6
FNALQYLR






ISNIPDEYFK






NIPTVMENLENYYLEVNQLEK






NNQIDHIDEK






SLEDLQLTHNK






SLEYLDLSFNQIAR


 


spt|P60709
Beta Actin
72.5333333
34
AALVVDNGSGMCK






AGFAGDDAPR






ALDFEQEMATAASSSSLEK






AVRPSIVGR






AVRPSIVGRPR






DDDIAALVVDNGSGMCK






DESGPSIVHR






DLTDYLMK






DLYANTVLSGGTTMYPGIADR






DSYVGDEAQSK






DSYVGDEAQSKR






EITALAPSTMK






GFAGDDAPR






GYSFTTTAER






HQGVMVGMGQK






IWHHTFYNELR






KDLYANTVLSGGTTMYPGIADR






LCYVALDFEQEMATAASSSSLEK






LLTEAPLNPK






QEYDESGPSIVHR






SGGTTMYPGIADR






SYELPDGQVIYIGNER






TALAPSTMK






TEAPLNPK






TTGIVMDSGDGVTHTVPIYEGY






TTGIVMDSGDGVTHTVPIYEGYALPH






TTGIVMDSGDGVTHTVPIYEGYALPHAIL






VALDFEQEMATAASSSSLEK






VAPEEHPV






VAPEEHPVL






VAPEEHPVLL






VAPEEHPVLLTEAPLNPK






VLSGGTTMYPGIADR






YPIEHGIVTNWDDMEK


 


spt|P62805
Histone H4
48.0392158
5
DAVTYTEHAK






DNIQGITKPAIR






ISGLIYEETR






TVTAMDVVYALK






VFLENVIR


 


spt|Q9NZT1
Calmodulin-
58.21917653
6
AFDQDGDGHITVDELR



like protein 5


AFSAVDTDGNGTINAQELGAALK






AGLEDLQVAFR






AMAGLGQPLPQEELDAMIR






NLSEAQLR






VNYEEFAR


 


trm|O60744
Thioredoxin 
39.28571343
3
EKLEATINELV



Delta 3


TAFQEALDAAGDK






VGEFSGANK


 


trm|Q6NTE9
PPIA
52.38095522
8
EGMNIVEAMER






FEDENFILK






IIPGFMCQGGDFTR






ITIADCGQLE






KITIADCGQLE






SIYGEKFEDENFILK






VNPTVFFDIAVDGEPLGR






VSFELFADK


 


trm|Q71DI3
Histone H3
30.14705777
2
EIAQDFKTDLR






SAPATGGVK


 


trm|Q86V33
YWHAZ
39.37500119
13
DNLTLWTSDTQGDEAEAGEGGEN






DSTLIMQLLR






EMQPTHPIR






GIVDQSQQAYQEAFEISK






GIVDQSQQAYQEAFEISKK






LAEQAER






MDKNELVQK






NLLSVAYK






SVTEQGAELSNEER






TAFDEAIAELDTLSEESYK






VVSSIEQK






YDDMAACMK






YLAEVAAGDDKK


 


trm|Q8WU39
PACAP
26.98412836
3
ELSELVYTDVLDR






NWQDYGVR






TCLHYLGEFGEDQIYEAHQQGR


 


trm|Q96IH1
FSCN1
5.200000107
5
ASAETVDPASLWEY






DVPWGVDSLITLAFQDQR






FLIVAHDDGR






KVTGTLDANR






YLAADKDGNVTCER


 


trm|Q96RZ7
Mast cell
18.02575141
5
DDMLCAGNTR



tryptase beta


EQHLYYQDQLLPVSR



III


IVGGQEAPR






VPIMENHICDAK






YHLGAYTGDDVR


 


trm|Q9UE88
Histone H2B.1
19.80198026
3
AMGIMNSFVNDIFER






LLLPGELAK






QVHPDTGISSK


 







OPLs











spt|P29966
MARCKS
9.64
2
AAEEPSKVEEK






EAPAEGEAAEPGSPTAAEGEAASAASS


 


spt|P06748
Nucleophosmin 1
6.18
2
GPSSVEDIK






VTLATLK


 


gb|AAH25314.1
IGHG1 protein
21.49
12
ALPAPIEK






DYFPEPVTV






FNWYVDGVEVHNAK






GFYPSDIAVEWESNGQPENNYK






GPSVFPLAPSSK






NQVSLTCLVK






QVQLVQSGAEVK






STSGGTAALGCLVK






THTCPPCPAPELLGGPSVFLFPPKPK






TPEVTCVVVDVSHEDPEVK






TTPPVLDSDGSFFLYSK






VVSVLTVLHQDWLNGK


 


spt|P01009
Alpha 1 Anti-
8.13
3
AVLTIDEK



Trypsin Precursor


DTEEEDFHVDQVTTVK






LSITGTYDLK


 


spt|P04080
Cystatin B
36.73
4
GAPSATQPATAETQHIADQVR






MMCGAPSATQPATAETQHIADQVR






SQVVAGTNYFIK






VFQSLPHENKPLTLSNYQTNK


 


spt|P06454
PTHA
25.45
5
AAEDDEDDDVDTK






AAEDDEDDDVDTKK






EVVEEAENGR






RAAEDDEDDDVDTK






SDAAVDTSSEITTK


 


spt|P14625
GRP 94
3.74
10
DDEVDVDGTVEEDLGK






EFEPLLNWMK






EVEEDEYK






FAFQAEVNR






KEASESSPFVER






LGVIEDHSNR






LISLTDENALSGNEELTVK






TDDEVVQREEEAIQLDGLNASQIR






TVLDLAVVLFETATLR






VFITDDFHDMMPK


 


spt|P27482
Calmodulin
20.27
5
AADTDGDGQVNYEEFVR



related


ADQLTEEQVTEFK



protein-NB1


LSDEEVDEMIR



CALM3


SLGQNPTEAELR






VFDKDGNGFVSAAELR


 


spt|P30086
PE Binding 
15.05
3
GNDISSGTVLSDYVGSGPPK



protein PEBP


LYTLVLTDPDAPSR






VLTPTQVK


 


spt|P31151
S100A7
24.00
4
GTNYLADVFEK






KIDFSEFLSLLGDIATDYHK






QSHGAAPCSGGSQ






SIIGMIDMFHK


 


spt|P31947
Stratifin
28.24
16
DSTLIMQLLR






EKVETELQGCDTVLGLLDSHLIK






EKVETELQGCDTVLGLLDSHLIKEAGD






EMPPTNPIR






GAVEKGEELSCEER






GEELSCEER






GSEEKGPEVR






LAEQAER






NLLSVAYK






SAYQEAMDISKK






SNEEGSEEKGPEVR






TTFDEAMADLHTLSEDSYK






VETELQGVCDTVLGLLDSHLIK






VLSSIEQK






YEDMAAFMK






YLAEVATGDDK


 


spt|P60709
Beta Actin
27.47
21
AGFAGDDAPR






AVFPSIVGR






AVFPSIVGRPR






DDDIAALVVDNGSGMCK






DLYANTVLSGGTTMYPGIADR






DSYVGDEAQSK






DSYVGDEAQSKR






EITALAPSTMK






GYSFTTTAER






HQGVMVGMGQK






IIAPPER






IWHHYFYNELR






LCYVALDFEQEMATAASSSSLEK






LDLAGRDLTDYLMKILTERGYSFTTTAER






QEYDEYGPSIVHR






SYELPDGQVITIGNER






TEAPLNPK






TTGIVMDSGDGVTHTVPIYEGYALPHAIL






VAPEEHPVLL






VAPEEHPVLLTEAPLNPK






YPIEHGIVTNWDDMEK


 


spt|P61978
heterogeneous 
2.38
3
DLAGSIIGK



nuclear protein


IDEPLEGSEDR



K


ILSISADIETIGEILK


 


spt|Q01469
FABP5
28.15
5
ATVQQLEGR






ELGVGIALR






FEETTADGR






GFDEYMK






TTQFSCTLGEKFEETTADGR


 


trm|O15256
Parathymosin
19.05
1
AAEEEDEADPKR


 


trm|Q12771
P37AUF1*
2.80
1
GFGFVLFK


 


trm|Q6NSB4
Hp Protein, DLC1
3.20
1
VGYVSGWGR


 


spt|P63104
YWHAZ
13.75
8
DSTLIMQLLR






GIVDQSQQAYQEAFEISK






LAEQAER






NLLSVYK






SVTEQGAELSNEER






TAFDEAIAELDTLSEESYK






VVSSIEQK






YLAEVAAGDDKK


 


trm|Q8N5F4
IGL2*
23.61
4
AGVETTTPSK






DTERPSGIPER






SYELTQPPSVSVSPGQTAR






SYSCQVTHEGSTVEK


 


spt|P06396
Gelsolin Precursor
2.30
2
AQPVQVAEGSEPDGFWEALGGK






TPSAAYLWVGTGASEAEK


 


emb|CAA25833.1
eraldehyde3-
16.72
8
AGAHLQGGAK



phosphate


GALQNIIPASTGAAK



Dehydrogen


LTGMAFR






QASEGPLK






TVDGPSGK






VIPELDGK






VPTANVSVVDLTCR






VVDLMAHMASKE


 


spt|P14618
PKM2*
9.04
8
APIIAVTR






GADFLVTEVENGGSLGSK






GDLGIEPAEK






GDYPLEAVR






IENHEGVR






KASDVHEVR






LDIDSPPITAR






NTGIICTIGPASR


 


spt|P04792
Hsp27*
18.85
5
AQLGGPEAAK






LATQSNEITIPVTFESR






QDEHGYISR






QLSSGVSEIR






VSLDVNHFAPDELTVK


 


spt|P09651
ROA1HNRNPA1*
7.50
2
EDSQRPGAHLTVK






SESPKEPEQLR


 


spt|P13639
Elongation Factor
1.17
2
GEGQLGPAER



2*


SDPVVSYR


 


spt|P14625
HSP90B1
3.74
10
DDEVDVDGTVEEDLGK






EFEPLLNWMK






EVEEDEYK






FAFQAEVNR






KEAESSPFVER






LGVIEDHSNR






LISLTDENALSGNEELTVK






TDDEVVQREEEAIQLDGLNASQIR






TVLDLAVVLFETATLR






VFITDDFHDMMPK


 


spt|P22392
NDP Kinase B*
11.84
2
GLVGEIIK






NIIHGSDSVK


 


spt|P23528
Cohlin*
4.82
4
ASGVAVSDGVIK


 


spt|P31949
Calgizzanin
8.57
2
ISSPTETER






NQKDPGVLDR


 


spt|P32119
Peroxiredoxin 2
4.04
6
ATAVVDGAFK






GLFIIDGK






KEGGLGPLNIPLLADVTR






LSEDYGVLK






QITVNDLPVGR






TDEGIAYR


pf|0904262A
SOD2*
13.73
1
TLVVHEK


 


spt|Q16778
Histone H2B.1
15.87
3
AMGIMNSFVNDIFER






LLLPGELAK






QVHPDTGISSK










OFFLINE













SEQUENCE
#



ACCESSION
PROTEIN
COVERAGE
PEPTIDES
PEPTIDE





gb|AAA59555.1
MARCKS
59.33734775
11
AAEEPSKVEEK






AEDGATPSPSNETPK






AEDGATPSPSNETPKK






AVAPEKPPASDETK






EAGEGGEAEAPAAEGGK






EAPAEGEAAEPGSPTAAEGEAASAASS






EELQANGSAPAADKEEPAAAGSGAASP






GEAAAERPGEAAVASSPSK






GEPAAAAAPEAGASPVEK






GSAPAADKEEPAAGSGAASPSAAEK






VNGDASPAAAESGAK


 


gb|AAC13869.1
Glutathione S
61.90476418
4
AFLASPEYVNLPINGNGKQ



Transferase-P


ALPGQLKPFETLLSQNQGGK






ASCLYGQLPK






FQDGDLTLYQSNTILR


 


gb|AAH16768.1
Nucleophosmin 1
12.24489808
3
GPSSVEDIK






MSVQPTVSLGGFEITPPVVLR






MTDQEAIQDLWQWR


 


pir|KRHUE
Cytokeratin 14
69.4915235
5
ASLENSLEETK






DAEEWFFTK






ILTATVDNANVLLQIDNAR






KVVSTHEQVLR






VVSTHEQVLR


 


spt|P00338
LDH A
52.56797671
14
ATLKDQLITNLLKEEQTPQNIK






DQLIYNLLK






DQLIYNLLKEEQTPQNK






FIIPNVVK






GEMMDLQHGSLFLR






KSADTLWGIQK






LVIITAGAR






QVVESAYEVIK






RVHPVSTMIK






SADTLWGIQK






TLHPDLGTDKDKEQWK






VHPVSTMIK






VIGSGCNLDSAR






VTLTSEEEAR


 


spt|P00915
Carbonic 
66.15384817
13
ASPDWGYDDK



anhydrasel


ASPDWGYDDKNGPEQWSK






EIINVGHSFHVNFEDNDNR






GGPFSDSYR






HDTSLKPISV






HDTSLKPISVSYNPATAK






LYPIANGNNQSPVDIK






SAELHVAHWNSAK






SLLSNVEGDNAVPMQHNNRPTQPLK






SSEQLAQFR






VLDALQAIK






YSAELHVAHWNSAK






YSSLAEAASK


 


spt|P01009
Alpha 1 Anti-
55.74162602
9
DTEEEDFHVDQVTTVK



Trypsin Precursor


EDPQGDAAQK






GTEAAGAMFLEAIPM






KLSSWVLLMK






LGMFNIQHCK






LQHLENELTHDIITK






LSITGTYDLK






LVDKFLEDVK






VFSNGADLSGVTEEAPLK


 


spt|P04083
Annexin A1
75.36231875
14
AAYLQETGKPLDETLK






AAYLQETGKPLDETLKK






ALYEAGER






CATSKPAFFAEK






DITSDTSGDFR






GGPGSAVSPYPTFNPSSDVAALHK






GLGTDEDTLIEILASR






GTDVNVFNTILTTR






GVDEATIIDILTK






KGTDVNVFNTIKTTR






NALLSLAK






SEDFGVNEDLADSDAR






SEIDMNDIK






TPAQFDADELR


 


spt|P04792
Hsp27
34.55497324
7
DGVVEITGK






KYTLPPGVDPTQVSSSLSPEGTLTVEAP






LATQSNEITIPVTFESR






QDEHGYISR






QLSSGVSEIR






TKDGVVEITGK






VSLDVNHFAPDELTVK


 


spt|P06454
Prothymosin alpha
23.63636345
6
AAEDDEDDDVDTK






AAEDDEDDDVDTKK






EVVEEAENGR






EVVEEAENGRDAPAN






KEVVEEAENGR






SDAAVDTSSEITTK


 


spt|P07585
Deconin Precursor
38.16156089
5
DLPPDTTLLDLQNNK






NLHALILVNNK






SSGIENGAFQGMK






VSPGAFTPLVK






VVQCSDLGLDKVPK


 


spt|P08670
Vimentin
63.21585774
29
ADLSEAANR






DGQVINETSQHHDDLE






DNLAEDIMR






EEAENTLQSFR






EKLQEEMLQR






EMEENFAVEAANYQDTIGR






ETNLDSLPLVDTHSK






EYQDLLNVK






FADLSEAANR






ILLAELEQLK






ILLAELEQLKGQGK






ISLPLPNFSSLNLR






KLLEGEESR






KVESLQEEIAFLK






KVESLQEEIAFLKK






LGDLYEEEMR






LLQDSVDFSLADAINTEFK






LQDEIQNMKEEMAR






LQEEMLQR






NLDSLPLVDTHSK






NLQEAEEWYK






QDVDNASLAR






QQYESVAAK






QVDQLTNDK






QVQSLTCEVDALK






RQVDQLTNDK






TVETRDGQVINETSQHHDDLE






VELQELNDR






VEVERDNLAEDIMR


 


spt|P14625
GRP 94
26.40099525
14
DDEVDVDGTVEEDLGK






EFEPLLNWMK






EGVKFDESEK






ELISNASDALDK






FQSSHHPTDITSLDQYVER






GLFDEYGSK






GVVDSDDLPLNVSR






KIADDKYNDTFWK






LGVIEDHSNR






LISTDENALSGNEELTVK






NLLHVTDTGVGMTR






RVFITDDFHDMMPK






SILFVPTSAPR






VFITDDFHDMMPK


 


spt|P29034
S100A 2
27.83505023
6
ELPSFVGEK






ELPSFVGEKVDEEGLK






ELPSFVGEKVDEEGLKK






GEKVDEEGLK






VDEEGLKK






YSCQEGDKFK


 


spt|P30043
Flavin reductase
39.51219618
7
CLTTDEYDGHSTYPSHQYQ






HDLGHFMLR






LPSEGPRPAHVVVGDVLQAADVDK






LQAVTDDHIR






NDLSPTTVMSEGAR






PAHVVVGDVLQAADVDK






TVAGQDAVIVLLGTR


 


spt|P31151
S100A 7
98.00000191
7
ENFPNFLSACDKK






GTNYLADVFEK






GTNYLADVFEKK






IDKPSLLTMMK






KGTNYLADVFEKK






QSHGAAPCSGGSQ






SIIGMIDMFHK


 


spt|P31947
SFN
89.35185075
22
ADNAGEEGGEAPQEPQS






DNLTLWTADNAGEEGGEAPQEPQ






DNLTLWTADNAGEEGGEAPQEPQS






DSTLIMQLLR






EMPPTNPIR






GAVEKGEELSCEER






GEELSCEER






LAEQAER






NLLSVAYK






RYLAEVATGDDK






SAYQEAMDISK






SAYQEAMDISKK






SNEEGSEEKGPEVR






STLIMQLLR






SVFHYEIANSPEEAISLAK






TADNAGEEGGEAPQEPQS






TTFDEAMADLHTLSEDS






TTFDEAMADLHTLSEDSYK






VLSSIEQK






YEDMAAFMK






YLAEVATGDDK






YLAEVATGDDKK


 


spt|P31949
Calgizzarin
23.80952388
3
DGYNYTLSK






ISSPTETER






TEFLSFMNTELAAFTK


 


spt|P32119
Peroxiredoxin 2
64.64646459
11
ATAVVDGAFK






EGGLGPLNIPLLADVTR






GLFIIDGK






IGKPAPDFK






KEGGLGPLNIPLLADVTR






LSEDYGVLK






LVQAFQYTDEHGEVCPAGWKPGSDTIK






QITVNDLPVGR






QYTDEHGEVCPAGWKPGSDTIKPNVDC






RLSEDYGVLK






TDEGIAYR


 


spt|P51884
KSPG Lumican
56.80473447
13
FNALQYLR






ILGPLSYSK






ISETSLPPDMYECLR






ISNIPDEYFK






LKEDAVSAAFK






LPSGLPVSLLTLYLDNNK






NIPTVNENLENYYLEVNQLEK






NNQIDHIDEK






RFNALQYLR






SLEDLQLTHNK






SLEYLDLSFNQIAR






SVPMVPPGIK






VANEVTLN


 


spt|P60709
Beta Actin
83.46656694
49
AGFAGDDAPR






ALDFEQEMATAASSSSLEK






AVFPSIVGR






AVFPSIVGRPR






CPEALFQPSFLGMESCGIHETTFNSIMK






DDDIAALVVDNGSGMCK






DDIAALVVDNGSGMCK






DLTDYLMK






DLYANTVLSGGTTMYPGIADR






DSYVGDEAQSK






DSYVGDEAQSKR






EITALAPSTMK






GFAGDDAPR






GIHETTFNSIMK






GIVTNWDDMEK






GQKDSYVGDEAQSK






GYSFTTTAER






HQGVMVGMGQK






HQGVMVGMGQKDSYVGDEAQSK






IIAPPER






IIAPPERK






IWHHTFYNELR






KDLYANTVLSGGTTMYPGIADR






KQEYDESGPSIVHR






KYPIEHGIVTNWDDMEK






LCYVALDFEQEMATAASSSSLEK






LLTEAPLNPK






PIEHGIVTNWDDMEK






QEYDESGPSIVHR






RVAPEEHPVLLTEAPLNPK






SGGTTMYPGIADR






SKQEYDESGPSIVHR






SYELPDGQVI






SYELPDGQVITI






SYELPDGQVITIGNER






TTGIVMDSGDGVTH






TTGIVMDSGDGVTHTVPIYEGY






TTGIVMDSGDGVTHTVPIYEGYALPH






TTGIVMDSGDGVTHTVPIYEGYALPHAIL






TVLSGGTTMYPGIADR






VAPEEHPV






VAPEEHPVL






VAPEEHPVLL






VAPEEHPVLLTEA






VAPEEHPVLLTEAPLN






VAPEEHPVLLTEAPLNPK






VAPEEHPVLLTEAPLNPKANR






YPIEHGIVTNWDDMEK






YVALDFEQEMATAASSSSLEK


 


spt|Q15691
APC-binding
8.955223858
1
KPLTSSSAAPQRPISTQR



protein EB1





 


trm|Q86U86
Polybromo-1D
29.01124954
2
AAQQQQPSASPR






RPNETFHLATRK


 


trm|Q86V33
YWHAZ
77.49999762
15
DNLTLWTSDTQGDEAEAGEGGEN






DSTLIMQLLR






EKIETELR






GIVDQSQQAYQEAFEISK






GIVDQSQQAYQEAFEISKK






LAEQAER






MDKNELVQK






NLLSVAYK






SDTQGDEAEAGEGGEN






STLIMQLLR






SVTEQGAELSNEER






TAFDEAIAELDTLSEESYK






VVSSIEQK






YDDMAACMK






YLAEVAAGDDKK


 


trm|Q86YI6
L Plastin
52.53968239
9
AESMLQQADK






HVIPMNPNTDDLFK






IDINMSGFNETDDLKR






IKPVDWSK






MINLSVPDTIDER






SGNLTEDDKHNNAK






TISSSLAVVDLIDAIQPGCINYDLVK






VNKPPYPK






VYALPEDLVEVKPK


 


trm|Q8IZ29
Tubulin, beta, 2
40.67415595
10
ALTVPELTQQMFDAK






AVLVDLEPGTMDSVR






EIVHLQAGQCGNQIGAK






GHYTEGAELVDSVLDVVR






IMNTFSVVPSPK






IREEYPDR






LHFFMPGFAPLTSR






LTTPTYGDLNHLVSATMSGVTTCLR






SGPFGQOFRPDNFVFGQSGAGNNWAK






TAVCDIPPR


 


trm|Q96AM7
Superoxide
52.85714269
1
HHAAYVNNLNVTEEK



dismutase [Mn]





 


trm|Q96IH1
FSCN1
66.60000086
8
ASAETVDPASLWEY






DVPWGVDSLITLAFQDQR






EVPGPDCR






FLIVAHDDGR






KVTGTLDANR






LVARPEPATGYTLEFR






WSLQSEAHR






YLAADKDGNVTCER


















#




MAX
Seq
Times



ACCESSION
Confidence
ID
Seen






gb|AAC13869.1
98.99999499
42
17



  
98.99999499
43
17




98.99999499
44
11




98.99999499
45
2




98.99999499
46
1




98.99999499
47
2


 



spt|P00338
98.99999499
48
2




98.99999499
49
3




98.99999499
50
2




98.99999499
51
11




98.99999499
52
5




98.99999499
53
7




98.99999499
54
12


 



spt|P01009
98.99999499
55
2



  
98.99999499
56
2




97.99999595
57
1




98.99999499
58
3




98.99999499
59
1




98.99999499
60
1




98.99999499
61
2




98.99999499
62
1




98.99999499
63
5


 



spt|P04080
98.99999499
64
2




98.99999499
65
2




98.99999499
66
21




98.99999499
67
4




98.99999499
68
14




98.99999499
69
10


 



spt|P04083
98.99999499
70
7




98.99999499
71
6




98.99999499
72
50




98.99999499
73
9




98.99999499
74
4




98.99999499
75
8




98.99999499
76
6




98.99999499
77
1




98.99999499
78
6


 



spt|P06454
98.99999499
79
1



  
98.99999499
80
2




98.99999499
81
3




98.99999499
82
5




98.99999499
83
6


 



spt|P07585
94.99999881
84
1




98.99999499
85
1




97.99999499
86
1




98.99999499
87
1


 



spt|P08670
98.99999499
88
2




98.99999499
89
5




98.99999499
90
10




98.99999499
91
4




98.99999499
92
6




98.99999499
93
17




98.99999499
94
8




98.99999499
95
2




98.99999499
96
10




98.99999499
97
3




98.99999499
98
5




98.99999499
99
7




98.99999499
100
13




94.99999881
101
1




98.99999499
102
2




98.99999499
103
3




98.99999499
104
9




98.99999499
105
10




98.99999499
106
1




98.99999499
107
3




98.99999499
108
1




98.99999499
109
5




98.99999499
110
2




98.99999499
111
7




96.9999969
112
1




98.99999499
113
5




98.99999499
114
7




98.99999499
115
2


 



spt|P13928
98.99999499
116
1




97.99999595
117
1




97.99999595
118
1




96.9999969
119
1




98.99999499
120
1




98.99999499
121
2


 



spt|P14618
98.99999499
122
14




98.99999499
123
17




98.99999499
124
3




98.99999499
125
1




98.99999499
126
3




98.99999499
127
17




98.99999499
128
3




98.99999499
129
10




98.99999499
130
1




98.99999499
131
5




98.99999499
132
7




98.99999499
133
1




98.99999499
134
3




98.99999499
135
21




98.99999499
136
10




98.99999499
137
17




98.99999499
138
6




98.99999499
139
2


 



spt|P14625
98.99999499
140
1




98.99999499
141
2




98.99999499
142
1




98.99999499
143
4




98.99999499
144
1




98.99999499
145
11


 



spt|P26038
98.99999499
146
5




98.99999499
147
8




98.99999499
148
5




98.99999499
149
3




96.9999969
150
4




98.99999499
151
4




98.99999499
152
2




96.9999969
153
1




98.99999499
154
3




98.99999499
155
6




98.99999499
156
10




98.99999499
157
1




96.9999969
158
1




96.9999969
159
1




98.99999499
160
3




98.99999499
161
1




98.99999499
162
2


 



spt|P29034
98.99999499
163
13




98.99999499
164
1


 



spt|P31151
98.99999499
165
4




98.99999499
166
2




98.99999499
167
32


 



spt|P31947
96.9999969
168
1




98.99999499
169
4




98.99999499
170
180




97.99999595
171
1




98.99999499
172
9




98.99999499
173
20




98.99999499
174
10




98.99999499
175
3




98.99999499
176
56




98.99999499
177
4




98.99999499
178
10




98.99999499
179
56




98.99999499
180
50




98.99999499
181
47




98.99999499
182
9




98.99999499
183
9


 



spt|P31949
98.99999499
184
6




98.99999499
185
6


 



spt|P36952
98.99999499
186
1




98.99999881
187
1


 



spt|P51884
97.99999595
188
1




96.9999969
189
1




98.99999499
190
3




98.99999499
191
13




98.99999499
192
11




98.99999499
193
10


 



spt|P60709
98.99999499
194
5




98.99999499
195
66




98.99999499
196
6




98.99999499
197
36




98.99999499
198
68




98.99999499
199
88




98.99999499
200
2




98.99999499
201
24




98.99999499
202
16




98.99999499
203
32




98.99999499
204
8




98.99999499
205
38




98.99999499
206
1




98.99999499
207
10




98.99999499
208
1




98.99999499
209
4




98.99999499
210
7




98.99999499
211
1




98.99999499
212
2




98.99999499
213
6




98.99999499
214
2




98.99999499
215
101




98.99999499
216
3




98.99999499
217
16




98.99999499
218
6




98.99999499
219
1




98.99999499
220
15




98.99999499
221
2




97.99999595
222
2




95.99999785
223
2




98.99999499
224
5




96.9999969
225
1




98.99999499
226
3




98.99999499
227
33


 



spt|P62805
98.99999499
228
15




98.99999499
229
2




98.99999499
230
10




98.99999499
231
1




97.99999595
232
7


 



spt|Q9NZT1
98.99999499
233
3



  
98.99999499
234
1




98.99999499
235
4




98.99999499
236
2




98.99999499
237
1




98.99999499
238
1


 



trm|O60744
98.99999499
239
1



 







98.99999499
240
4




98.99999499
241
10


 



trm|Q6NTE9
98.99999499
242
14




98.99999499
243
3




98.99999499
244
21




96.9999969
245
1




98.99999499
246
2




98.99999499
247
8




98.99999499
248
54




98.99999499
249
1


 



trm|Q71DI3
94.99999481
250
1




98.99999499
251
4


 



trm|Q86V33
98.99999499
252
3




98.99999499
253
180




98.99999499
254
8




98.99999499
255
6




98.99999499
256
2




98.99999499
257
3




98.99999499
258
4




98.99999499
259
56




98.99999499
260
8




98.99999499
261
45




98.99999499
262
9




98.99999499
263
7




98.99999499
264
9


 



trm|Q8WU39
98.99999499
265
11




98.99999499
266
5




98.99999499
267
1


 



trm|Q96IH1
98.99999499
268
1




98.99999499
269
1




98.99999499
270
7




98.99999499
271
3




98.99999499
272
2


 



trm|Q96RZ7
96.9999969
273
1



  
98.99999499
274
2



  
98.99999499
275
9




98.99999499
276
2




98.99999499
277
6


 



trm|Q9UE88
98.99999499
278
4




98.99999499
279
2




98.99999499
280
11


 









OPLs












spt|P29966
99.00
281
2




99.00
282
1


 



spt|P06748
99.00
283
5




96.00
284
1


 



gb|AAH25314.1
99.00
285
12




98.00
286
1




99.00
287
5




99.00
288
4




99.00
289
2




99.00
290
1




99.00
291
3




99.00
292
2




98.00
293
2




99.00
294
3




99.00
295
24




99.00
296
2


 



spt|P01009
99.00
297
4



  
99.00
298
2




99.00
299
1


 



spt|P04080
99.00
300
1




99.00
301
12




99.00
302
3




99.00
303
2


 



spt|P06454
99.00
304
9




99.00
305
14




99.00
306
6




99.00
307
1




99.00
308
17


 



spt|P14625
99.00
309
5




99.00
310
4




99.00
311
3




99.00
312
1




99.00
313
4




99.00
314
3




99.00
315
4




99.00
316
1




96.00
317
1




99.00
318
2


 



spt|P27482
99.00
319
3



  
99.00
320
4




99.00
321
1




99.00
322
2




99.00
323
5


 



spt|P30086
99.00
324
1



  
99.00
325
1




99.00
326
1


 



spt|P31151
99.00
327
1




99.00
328
3




99.00
329
1




99.00
330
2


 



spt|P31947
99.00
331
52




99.00
332
13




99.00
333
2




99.00
334
4




99.00
335
38




99.00
336
7




97.00
337
1




98.00
338
2




99.00
339
62




99.00
340
1




99.00
341
42




99.00
342
4




99.00
343
2




99.00
344
26




98.00
345
2




99.00
346
9


 



spt|P60709
99.00
347
83




99.00
348
14




99.00
349
73




99.00
350
20




99.00
351
8




99.00
352
29




99.00
353
36




99.00
354
34




99.00
355
5




99.00
356
4




97.00
357
7




98.00
358
4




99.00
359
12




97.00
360
2




99.00
361
1




99.00
362
199




99.00
363
37




99.00
364
3




99.00
365
2




99.00
366
48




99.00
367
7


 



spt|P61978
99.00
368
2



  
99.00
369
1



  
96.00
370
2


 



spt|Q01469
99.00
371
7




99.00
372
17




99.00
373
3




96.00
374
4




99.00
375
1


 



trm|O15256
99.00
376
8


 



trm|Q12771
99.00
377
5


 



trm|Q6NSB4
99.00
378
2


 



spt|P63104
99.00
379
50




99.00
380
1




98.00
381
2




99.00
382
59




99.00
383
7




99.00
384
4




99.00
385
10




99.00
386
2


 



trm|Q8N5F4
99.00
387
21




98.00
388
1




99.00
389
2




99.00
390
17


 



spt|P06396
99.00
391
1




99.00
392
6


 



emb|CAA25833.1
99.00
393
11



  
99.00
394
19




98.00
395
3




99.00
396
9




99.00
397
4




99.00
398
16




99.00
399
10




99.00
400
2


 



spt|P14618
99.00
401
10




99.00
402
1




99.00
403
6




99.00
404
2




99.00
405
5




99.00
406
1




99.00
407
9




99.00
408
4


 



spt|P04792
99.00
409
21




99.00
410
9




99.00
411
6




99.00
412
1




99.00
413
8


 



spt|P09651
99.00
414
3




99.00
415
4


 



spt|P13639
99.00
416
1




99.00
417
1


 



spt|P14625
99.00
418
5




99.00
419
4




99.00
420
3




99.00
421
1




99.00
422
4




99.00
423
3




99.00
424
4




99.00
425
1




96.00
426
1




99.00
427
2


 



spt|P22392
99.00
428
4




99.00
429
1


 



spt|P23528
99.00
430
24


 



spt|P31949
98.00
431
1




99.00
432
2


 



spt|P32119
99.00
433
18




99.00
434
2




99.00
435
2




99.00
436
1




99.00
437
10




99.00
438
6


 



pf|0904262A
93.00
439
1


 



spt|Q16778
99.00
440
4




99.00
441
7




99.00
442
68









#



OFFLINE
MAX
Seq
Times



ACCESSION
Confidence
ID
Seen






gb|AAA59555.1
98.99999499
443
2




99.00000095
444
3




94.99999881
445
1




99.00000095
446
1




99.00000095
447
1




98.99999499
448
3




99.00000095
449
3




99.00000095
450
6




99.00000095
451
9




98.99999499
452
1




99.00000095
453
7


 



gb|AAC13869.1
99.00000095
454
2



  
99.00000095
455
27




99.00000095
456
1




98.00000191
457
1


 



gb|AAH16768.1
99.00000095
458
1




98.99999499
459
1




98.99999499
460
2


 



pir|KRHUE
99.00000095
461
2




99.00000095
462
2




98.99999499
463
2




99.00000095
464
2




99.00000095
465
6


 



spt|P00338
98.99999499
466
8




98.99999499
467
2




99.00000095
468
2




94.99999881
469
2




98.99999499
470
2




97.99999595
471
2




99.00000095
472
20




99.00000095
473
32




99.00000095
474
8




99.00000095
475
3




98.99999499
476
2




99.00000095
477
2




99.00000095
478
31




99.00000095
479
55


 



spt|P00915
99.00000095
480
2




99.00000095
481
3




99.00000095
482
71




99.00000095
483
2




99.00000095
484
1




99.00000095
485
49




99.00000095
486
31




99.00000095
487
3




99.00000095
488
73




99.00000095
489
2




99.00000095
490
6




99.00000095
491
22




99.00000095
492
3


 



spt|P01009
99.00000095
493
7



  
98.00000191
494
1




95.99999785
495
1




96.9999969
496
1




99.00000095
497
1




98.99999499
498
3




99.00000095
499
2




98.99999499
500
1




99.00000095
501
15


 



spt|P04083
99.00000095
502
10




99.00000095
503
35




99.00000095
504
8




99.00000095
505
4




99.00000095
506
40




99.00000095
507
14




99.00000095
508
427




99.00000095
509
25




99.00000095
510
75




99.00000095
511
14




98.00000191
512
2




99.00000095
513
25




99.00000095
514
1




99.00000095
515
12


 



spt|P04792
99.00000095
516
4




99.00000095
517
5




98.99999499
518
14




95.99999785
519
2




98.99999499
520
2




99.00000095
521
6




99.00000095
522
15


 



spt|P06454
98.00000191
523
1




98.99999499
524
1




99.00000095
525
13




98.99999499
526
1




99.00000095
527
1




99.00000095
528
54


 



spt|P07585
99.00000095
529
7




99.00000095
530
3




99.00000095
531
3




99.00000095
532
3




99.00000095
533
3


 



spt|P08670
98.00000191
534
1




98.99999499
535
6




99.00000095
536
9




99.00000095
537
6




98.99999499
538
1




98.99999499
539
16




98.99999499
540
4




98.99999499
541
2




99.00000095
542
7




98.99999499
543
18




98.99999499
544
14




98.99999499
545
55




98.99999499
546
1




98.99999499
547
15




98.99999499
548
1




99.00000095
549
7




98.99999499
550
18




98.99999499
551
4




99.00000095
552
4




98.99999499
553
2




98.99999499
554
4




99.00000095
555
78




97.99999595
556
2




98.00000191
557
2




98.99999499
558
6




97.99999595
559
1




98.99999499
560
2




98.99999499
561
5




98.99999499
562
2


 



spt|P14625
98.99999499
563
2




96.9999969
564
2




98.99999499
565
2




99.00000095
566
1




99.00000095
567
2




99.00000095
568
1




99.00000095
569
21




98.99999499
570
2




99.00000095
571
1




98.99999499
572
6




98.99999499
573
6




99.00000095
574
3




98.99999499
575
9




98.99999499
576
2


 



spt|P29034
99.00000095
577
6




99.00000095
578
14




99.00000095
579
13




94.99999881
580
1




98.99999499
581
6




99.00000095
582
7


 



spt|P30043
99.00000095
583
1




99.00000095
584
2




99.00000095
585
9




99.00000095
586
1




99.00000095
587
14




98.99999499
588
4




98.99999499
589
4


 



spt|P31151
99.00000095
590
9




99.00000095
591
22




99.00000095
592
7




99.00000095
593
2




95.99999785
594
2




99.00000095
595
3




99.00000095
596
300


 



spt|P31947
99.00000095
597
13




96.9999969
598
2




99.00000095
599
53




99.00000095
600
515




99.00000095
601
14




99.00000095
602
26




99.00000095
603
16




99.00000095
604
9




99.00000095
605
35




98.00000191
606
1




99.00000095
607
9




99.00000095
608
29




99.00000095
609
9




98.99999499
610
1




98.99999499
611
1




98.99999499
612
6




98.99999499
613
1




99.00000095
614
396




99.00000095
615
6




99.00000095
616
12




99.00000095
617
19




98.99999499
618
2


 



spt|P31949
99.00000095
619
1




99.00000095
620
13




99.00000095
621
15


 



spt|P32119
99.00000095
622
3




99.00000095
623
4




99.00000095
624
14




99.00000095
625
22




99.00000095
626
21




99.00000095
627
7




99.00000095
628
52




99.00000095
629
41




97.00000286
630
1




99.00000095
631
5




99.00000095
632
13


 



spt|P51884
99.00000095
633
7




99.00000095
634
3




99.00000095
635
4




99.00000095
636
4




99.00000095
637
8




99.00000095
638
17




99.00000095
639
5




99.00000095
640
2




99.00000095
641
2




99.00000095
642
10




99.00000095
643
8




99.99999881
644
1




95.99999785
645
1


 



spt|P60709
99.00000095
646
77




99.00000095
647
13




99.00000095
648
61




99.00000095
649
303




98.99999499
650
30




99.00000095
651
172




99.00000095
652
3




99.00000095
653
29




99.00000095
654
64




99.00000095
655
39




99.00000095
656
3




99.00000095
657
46




99.00000095
658
1




99.00000095
659
3




99.00000095
660
1




99.00000095
661
8




99.00000095
662
33




98.99999499
663
14




98.00000191
664
1




97.00000286
665
8




99.00000095
666
3




99.00000095
667
512




99.00000095
668
99




99.00000095
669
2




99.00000095
670
1




98.99999499
671
12




99.00000095
672
2




98.99999499
673
2




99.00000095
674
36




98.99999499
675
2




99.00000095
676
6




99.00000095
677
2




99.00000095
678
5




98.99999499
679
6




99.00000095
680
702




98.99999499
681
4




99.00000095
682
5




99.00000095
683
1




99.00000095
684
69




99.00000095
685
3




99.00000095
686
9




97.00000286
687
4




99.00000095
688
8




98.99999499
689
4




98.99999499
690
8




99.00000095
691
509




99.00000095
692
3




99.00000095
693
120




94.99999881
694
2


 



spt|Q15691
99.00000095
695
12



  





 



trm|Q86U86
98.00000191
696
2




99.00000095
697
1


 



trm|Q86V33
99.00000095
698
10




99.00000095
699
753




96.9999969
700
1




99.00000095
701
21




99.00000095
702
32




99.00000095
703
10




98.00000191
704
1




99.00000095
705
38




99.00000095
706
3




98.99999499
707
2




99.00000095
708
113




99.00000095
709
899




99.00000095
710
7




99.00000095
711
3




99.00000095
712
11


 



trm|Q86YI6
99.00000095
713
1




98.99999499
714
2




98.99999499
715
2




98.99999499
716
2




94.99999881
717
1




99.00000095
718
4




98.99999499
719
2




99.00000095
720
1




95.99999785
721
2


 



trm|Q8IZ29
98.99999499
722
1




98.99999499
723
6




98.99999499
724
2




98.99999499
725
4




98.99999499
726
1




97.99999595
727
1




98.99999499
728
7




98.99999499
729
4




98.99999499
730
34




98.99999499
731
2


 



trm|Q96AM7
99.00000095
732
1



  





 



trm|Q96IH1
99.00000095
733
3




98.99999499
734
4




99.00000095
735
1




99.00000095
736
3




98.99999499
737
1




98.99999499
738
2




94.99999881
739
1




99.00000095
740
5
















TABLE 12







Clinicopathological parameters of patients with Oral Premalignant Lesions (OPLs)













Age/Gender
Site
Tissue
Histopathology
Tobacco habits










A) ITRAQ Analysis: Discovery of Biomarkers












1.
35/F
GBS
Leukoplakia
Dysplasia
Areca nut chewing (×5-6 yrs)


2.
42/M
BM
Leukoplakia
Dysplasia
Bidi smoking (×10 yrs)


3.
50/M
BM
Leukoplakia
Dysplasia
Pan masala and bidi smoking (×15-18 yrs)


4.
42/M
GBS
Leukoplakia
Dysplasia
Gutkha chewing (×20 yrs) and Bidi smoking (×6 yrs)


5.
42/M
T
Leukoplakia
Dysplasia
Gutkha chewing and bidi smoking (×5 yrs)


6.
50/M
SP
Leukoplakia
Dysplasia
Gutkha chewing and bidi smoking (×35 yrs)







B) Immunohistochemical Analysis: Verification of Biomarkers












1.
23/M
BM
Leukoplakia
Dysplasia
Khaini chewing (×4 yrs)


2.
36/M
LIP
Leukoplakia
Dysplasia
Khaini chewing (×10-12 yrs)


3.
40/F
GBS
Leukoplakia
Dysplasia
Khaini chewing (×14 yrs)


4.
22/M
GBS
Leukoplakia
Dysplasia
Khaini chewing (×5 yrs)


5.
45/F
BM
Leukoplakia
Dysplasia
Gutkha chewing (×8 yrs)


6.
22/M
BM
Leukoplakia
Dysplasia
Gutkha chewing (×3-4 yrs)


7.
50/F
GBS
Leukoplakia
Dysplasia
Gutkha chewing (×5 yrs)


8.
18/M
GBS
Leukoplakia
Dysplasia
Gutkha and khaini chewing (×5 yrs)


9.
35/M
BM
Leukoplakia
Dysplasia
Gutkha and khaini chewing (×10 yrs)


10.
40/F
T
Leukoplakia
Dysplasia
Gutkha and khaini chewing (×6 yrs)


11.
31/M
BM
Leukoplakia
Dysplasia
Betel quid with khaini chewing (×8 yrs)


12.
42/M
BM
Leukoplakia
Dysplasia
Bidi smoking (×18 yrs)


13.
50/M
BM
Leukoplakia
Dysplasia
Bidi smoking (×30 yrs)


14.
46/M
BM
Leukoplakia
Dysplasia
Bidi smoking (×18 yrs)


15.
54/M
BM
Leukoplakia
Dysplasia
Bidi smoking (×27 yrs)


16.
45/M
BM
Leukoplakia
Dysplasia
Bidi smoking (×12 yrs)


17.
50/M
BM
Leukoplakia
Dysplasia
Bidi smoking (×20 yrs)


18.
35/M
T
Leukoplakia
Dysplasia
Bidi smoking (×8 yrs)


19.
55/M
T
Leukoplakia
Dysplasia
Bidi smoking (×45 yrs)


20.
43/M
BM
Leukoplakia
Dysplasia
Cigarette smoking (×21 yrs)


21.
50/M
BM
Leukoplakia
Dysplasia
Cigarette smoking (×11 yrs)


22.
27/M
BM
Leukoplakia
Dysplasia
Gutkha chewing (×2 yrs) and cigarette smoking (×5 yrs)


23.
35/M
BM
Leukoplakia
Dysplasia
Gutkha and cigarette smoking (×10 yrs)


24.
24/M
BM
Leukoplakia
Dysplasia
Gutkha chewing (×3 yrs) and cigarette smoking (×1 yrs)


25.
54/M
BM
Leukoplakia
Dysplasia
Ghutka, khaini chewing (×15-16 yrs) and hookah smoking (×15-16 yrs)


26.
36/M
BM
Leukoplakia
Dysplasia
Gutkha and pan masala chewing (×8 yrs); bidi smoking (×10-12 yrs)


27.
66/M
BM
Leukoplakia
Dysplasia
Gutkha and khaini (×8 yrs) and bidi smoking (5 yrs)


28.
39/M
BM
Leukoplakia
Dysplasia
Betel quid with khaini (×2 yrs) and cigarette smoking (×5 yrs)


29.
45/M
A
Leukoplakia
Dysplasia
Betel quid with khaini (×20 yrs) and cigarette smoking (×25 yrs)


30.
70/M
BM
Leukoplakia
Dysplasia
No habit of addiction (NHA)





All the patients were from India. Abbreviations: M: Male; F: Female; Site: A; Alvcolus, BM: Buccal Mucosa, GBS: Gigivo-buccal sulcus, T: Tongue; SP: Soft palate; ‘Khaini’ is a mixture of tobacco, lime and menthol or aromatic spices; ‘Gutkha’ usually contains powdered tobacco, betel nut, catechu, lime and flavors; Pan masala is a mixture of spices such as cardamom, lime, menthol, catechu and betel nuts; ‘Bidi’ is tobacco hand rolled in Temburini leaf.













TABLE 13







Antibodies used for immunohistochemistry and


Western Blotting: sources and dilutions.















Dilution





Dilution
used for





used for
Western



Company
Clone ID
IHC
Blot





Antibody






Anti-14-3-3ζ
Santa Cruz
C-16
1:200
1:500


(YWHAZ) Rabbit






polyclonal antibody






Anti-14-3-3σ (Stratifin)
Santa Cruz
N-14
1:200
1:200


Goat polyclonal antibody






Anti-Psoriasin (S100A7)
Santa Cruz
47C1068
1:100
1:200


mouse monoclonal antibody






Anti-Pro-thymosinα
Santa Cruz
N-18
1:75 
1:100


(PTHA) Goat polyclonal






antibody






Anti-hnRNPK mouse
Abcam
ab23644
1:400
1:400


monoclonal antibody






Anti-Tubulin α mouse
Santa Cruz
B7
—
1:200


monoclonal antibody






Secondary Antibody:






Goat Anti-rabbit IgG
DAKO
—
 1:5000
 1:5000


Rabbit Anti-Goat IgG
DAKO
—
 1:4000
 1:4000


Rabbit Anti-Mouse IgG
DAKO
—
 1:2000
 1:2000
















TABLE 14







RT-PCR Analysis Primers and PCR conditions:













Annealing
No. of
Product


Gene

Temperature
amplification
size


(Accession #)
Primer Sequence (SEQ ID NO:)
(° C.)
cycles
(bp)





14-3-3ζ
5′-ATGTACTTGGAAAAAGGCCG-3′
54
32
400


(NM_001135699)
(SEQ ID NO: 741)






5′-CCCTGCTCTTGAGGAGCTTA-3′






(SEQ ID NO: 742)





 


Stratifin
5′-AGAGACACAGAGTCCGGCATTGG-3′
57
32
396


(NM_006142)
(SEQ ID NO: 743)






5′-TCCACCTTCTCCCGGTACTCACGC-3′






(SEQ ID NO: 744)





 


S100A7
5′-CTTCCTTAGTGCCTGTGACAAAAA-3′
57
32
121


(Psoriasin)
(SEQ ID NO: 745)





(NM_002963)
5′-AAGGACAGAAACTCAGAAAAATC






AATCT-3′ (SEQ ID NO: 746)





 


Prothymosin
5′-ATGTCAGACGCAGCCGTAGACACC
65
32
326


Alpha
A-3′ (SEQ ID NO: 747)





(NP_001092755.1)
5′CTAGTCATCCTCGTCGGTCTTCTG-3′






(SEQ ID NO: 748)





 


HnRNPK
5′AGCAGAGCTCGGAATCTTCCTCT
54
32
123


(NM_002140)
T-3′ (SEQ ID NO: 749)






5'ATCAGCACTGAAACCAACCATGC






C-3′ (SEQ ID NO: 750)





 


Beta actin
5′-CAGCCATGTACGTTGCTATCCAG-3′
62
32
421


(NM_001101.3)
(SEQ ID NO: 751)






5′-GTTTCGTGGATGCCACAGGAC-3′






(SEQ ID NO: 752)
















TABLE 15







Molecules identified in the Networks and their cellular functions











ID
Molecules in Network
Score
Focus genes
Top Functions














1
↑ACTB, Actin, ADRA2C, ALOX15, ANG, COX2, ↓CSTB,
39
15
Molecular



DDX1, ERK, ↓ FABP5, ↑HNRPD, ↑ HNRPK, ↑ HSP90B1,


Transport,



KIF1C, LIMA1, LOX, ↓ MARCKS, MLXIP, NFkB, ↑ NPM1


Cancer, Cellular



(includes EG: 4869), PCBP2, PCBP1 (includes


Movement



EG: 29371), ↑PEBP1, PHACTR1, REM1, ↑S100A7, SAFB,






↓SERPINA1, ↑ SFN, ↑ SOD2, SYNPO2, ↑TUBB, WTAP,






YWHAD, ↑YWHAZ





2
AKAP13, AKT1, AKT2, ↑ CALML3, COX2, ↓ DLC1,
15
7
Cancer, Cell-To-



ERRFI1, HMG1L1, ↑HNRPD, IGH-1A, ↓IGHG1, IGHG3,


Cell Signalling



IGKV1-117, IL33, KRT19, KRT72, LCK, LOX, ↑NPM1


and Interaction,



(includes EG: 4869), NR3C1, PCAF, PRKDC, ↑PTMS,


Hematological



RELA, retinoic acid, RGS3, SLC25A4, SLC2A1,


System Development



SUMO1, TAT, TCL1B, ↑TLR1, TPD52, VAV1, YBX1


and Function
















TABLE 16







Analysis of clinical parameters with transformation


potential of Oral Dysplasia patients.











Transformed
Untransformed














Characteristics
N
(%)
N
(%)
p-value
O.R. (95% C.I.)¶


















Dysplasia

39
(35.4)
71
(64.5)





(110 cases)










Age (Years)
≦59
15
(38.5)
37
(52.1)






>59
24
(61.5)
34
(47.9)
0.170
1.741
 (0.7-3.85)


Gender
Female
21
(53.8)
30
(42.2)






Male
18
(46.2)
41
(57.8)
0.243
0.627
(0.3-1.4)


Site
Tongue
26
(66.7)
53
(74.6)






Others§
13
(33.3)
18
(25.4)
0.373
0.679
(0.3-1.6)














Histopathological
Mild
12
(30.8)
46
(64.8)

















Grade
Moderate
18
(46.2)
21
(29.6)
0.008*
3.286
(1.3-8.1)



Severe
9
(23.1)
4
 (5.6)
0.001**
8.625
 (2.3-32.8)


Smoking
Yes
15
(51.7)
31
(52.5)





history§§











No
14
(48.3)
28
(47.5)
0.942
0.968
(0.4-2.4)





¶O.R. Odd's ratio, 95% C.I., 95% Confidence Interval


§Others included buccal mucosa (n = 18), floor of mouth (n = 12) and lip (n = 1)


§§Smoking history available for 88 cases only;


*p-value obtained from Chi-square analysis for Mild vs. Moderate dysplasia


**p-value obtained from Chi-square analysis for Mild vs. Severe dysplasia













TABLE 17







Correlation of candidate protein markers expression


with transformation in Oral Dysplasia patients.











Transformed
Untransformed















Characteristics
N
(%)
N
(%)
p-value
O.R.¶
(95% C.I.)¶


















Dysplasia

39

71

—
—
—


(n = 110)










p16 expression
Nuclear positive
32
(82.1)
53
(74.6)
0.375
1.553
(0.5-4.1)


HPV 16/18+

0
—
0
—
—
—
—


S100A7+
Overexpression
36
(92.3)
51
(71.8)
0.014
4.706
 (1.3-17.1)



(cytoplasm/nuclear)










Cytoplasm
32
(82.1)
38
(53.5)
0.003
3.970
 (1.5-10.2)



Nuclear
35
(89.7)
49
(69.0)
0.018
3.929
 (1.2-12.4)


PTMA+
Overexpression
37
(94.9)
67
(94.4)
0.911
1.104
(0.2-6.3)



(cytoplasm/nuclear)










Cytoplasm
25
(64.1)
36
(50.7)
0.176
1.736
(0.8-3.8)



Nuclear
36
(92.3)
63
(88.7)
0.743
1.524
(0.4-6.1)


14-3-3ζ+
Overexpression
37
(94.9)
69
(97.2)
0.536
0.536
(0.1-5.3)



(cytoplasm/nuclear)










Cytoplasm
31
(79.5)
62
(87.3)
0.277
0.563
(0.2-1.6)



Nuclear
21
(53.8)
38
(53.5)
0.974
1.013
(0.4-2.2)


14-3-3σ+
Overexpression
27
(69.2)
62
(87.3)
0.040
0.327
(0.1-0.8)



(cytoplasm/nuclear)










Cytoplasm
25
(64.1)
57
(80.3)
0.062
0.439
(0.2-1.1)



Nuclear
18
(46.2)
46
(64.8)
0.071
0.466
(0.2-1.1)


hnRNP K+
*Nuclear
39
(100)  
70
(98.6)
1.000
0.986
(0.9-1.1)





¶O.R. Odd's ratio, 95% C.I., 95% Confidence Interval


*No cytoplasmic staining was observed for p16 and hnRNP K in tissue sections used in this study













TABLE 18







Evaluation of association of degree of dysplasia


with candidate protein markers expression.












Mild
Moderate
Severe




dysplasia
dysplasia
dysplasia















Characteristics
N
(%)
N
(%)
N
(%)
p-value


















Dysplasia

58
(52.7)
39
(35.4)
13
(11.8)



(n = 110)










Disease Outcome
Transformed
12
(20.7)
18
(46.2)
9
(69.2)




Untransformed
46
(79.3)
21
(53.8)
4
(30.8)
0.001


p16 expression
*Nuclear
49
(84.4)
28
(71.7)
8
(61.3)
0.121


S100A7+
Cytoplasm
34
(58.6)
26
(66.7)
10
(76.9)
0.411



Nuclear
40
(68.9)
33
(84.6)
11
(84.6)
0.156


PTMA+
Cytoplasm
30
(51.7)
22
(56.4)
9
(69.2)
0.512



Nuclear
53
(91.4)
34
(87.2)
12
(92.3)
0.762


14-3-3ζ+
Cytoplasm
47
(81.0)
34
(87.2)
12
(92.3)
0.508



Nuclear
24
(41.4)
26
(66.7)
9
(69.2)
0.024


14-3-3σ+
Cytoplasm
46
(79.3)
27
(69.2)
9
(69.2)
0.480



Nuclear
38
(65.5)
18
(46.2)
8
(61.5)
0.160


hnRNP K+
*Nuclear
58
(100)  
38
(97.4)
13
(100)  
0.399





*No cytoplasmic staining was observed for p16 and hnRNP K in tissue sections used in this study.













TABLE 19







Evaluation of correlation between


p16 expression and protein markers.












p16





expression



Characteristics

N (%)
p-value





Dysplasia(n = 110)

85 (77.3)



Untransformed

53 (74.3)



Dysplasia





Transformed

32 (82.1)
0.375


Dysplasia





S100A7+
Overexpression
67 (78.8)
0.899



(cytoplasm/nuclear)





Cytoplasm
55 (64.7)
0.667



Nuclear
66 (77.6)
0.559


PTMA+
Overexpression
82 (96.5)
0.101



(cytoplasm/nuclear)





Cytoplasm
51 (60.0)
0.077



Nuclear
79 (92.9)
0.058


14-3-3ζ+
Overexpression
81 (95.3)
0.572



(cytoplasm/nuclear)





Cytoplasm
70 (82.4)
0.241



Nuclear
44 (51.8)
0.468


14-3-3σ+
Overexpression
66 (77.6)
0.108



(cytoplasm/nuclear)





Cytoplasm
62 (72.9)
0.476



Nuclear
47 (55.3)
0.258


hnRNPK+
*Nuclear
84 (98.8)
0.586





*No cytoplasmic staining was observed for hnRNP K in tissue sections used in this study.













TABLE 20







Evaluation of clinical parameters and S100A7 overexpression


for determining OCFS in dysplasia patients.













Multi-





Kaplan Meier
variate Cox





Survival
regression





analysis
analysis
Hazard's




Un-adjusted
Adjusted
Ratio
95%



p-value
p-value
(H.R.)
C.I.





Age
0.411
0.771
—
—


Gender
0.391
0.612
—
—


Site
0.740
0.284
—
—


Smoking
0.755
0.124
—
—


history






Dysplasia






Grade






Mild*
—
—
—
—


Moderate
0.004
0.013
2.54
(1.6-10.8)


Severe
<0.001 
<0.001 
5.42
(2.6-23.2)


p16 expression
0.995
0.892
—
—


S100A7






overexpression






Cytoplasm+
0.007
0.041
2.36
(0.9-8.4) 


Nuclear+
0.041
0.570
—
—
















TABLE 21







Multivariate Cox regression analysis indicating that patients


with cytoplasmic S100A7 positive, nuclear PTMA positive


and moderate or severe grade of dysplasia are at at higher


risk of cancer development compared to other patients exhibiting


0, 1 or 2 of the same variables.













Multi-





Kaplan Meier
variate Cox





Survival
regression





analysis
analysis
Hazard's




Un-adjusted
Adjusted
Ratio
95%



p-value
p-value
(HR)
C.I.














S100A7
0.007
0.269
—
—


Cytoplasm+






PTMA
0.690
0.618
—
—


Nuclear+






S100A7 Cyto+ +
0.006
0.295
—
—


PTMA Nuc+






Degree of
<0.001
0.127
—
—


Dysplasia






S100A7 Cyto+ +
0.368
0.295
—
—


PTMA Nuc+ +






Mild Dysplasia






S100A7 Cyto+ +
<0.001
<0.001
3.47
1.85-6.53


PTMA Nuc+ +






Moderate/Severe






Dysplasia

## Claims

1. A method of concurrently detecting levels of nuclear prothymosin alpha, PTMA, and cytoplasmic psoriasin, S100A7, in a biological sample obtained from a subject having moderate or severe grade oral dysplasia, the method comprising:
concurrently contacting the biological sample with a first binding agent that specifically binds to prothymosin alpha, PTMA, and a second binding agent that specifically binds to psoriasin, S100A7, wherein the biological sample is an oral tissue sample, a cytosmear, saliva or a combination thereof; and,
detecting the level of nuclear PTMA and the level of cytoplasmic S100A7 in the sample by measuring the amount of PTMA and S100A7 bound to the first and second binding agents, respectively.

2. The method of claim 1, wherein the biological sample comprises epithelial cells.

3. The method of claim 2, wherein the epithelial cells are dysplastic.

4. The method of claim 3, wherein at least one of the first binding agent and the second binding agent is an antibody.

5. The method of claim 1, wherein the step of detecting the level of nuclear PTMA and the level of cytoplasmic S100A7 is conducted using immunohistochemistry (IHC).

6. The method of claim 4, wherein the step of detecting the level of nuclear PTMA and the level of cytoplasmic S100A7 is conducted using immunohistochemistry (IHC).