Patent Publication Number: US-2007122856-A1

Title: Tissue diagnostics for ovarian cancer

Description:
This Application claims the benefit of priority to U.S. Provisional Application No. 60/735,450, filed Nov. 10, 2005 and to U.S. Provisional Application No. 60/802,084, filed May 18, 2006, the specifications of which are incorporated by reference in their entirety. 
    
    
     FIELD OF THE INVENTION  
      The present invention relates generally to the field of medicine. More specifically, the invention pertains to methods and devices for detecting the development of cancer in cell samples isolated from a subject.  
     BACKGROUND OF THE INVENTION  
      Cancer is one of the deadliest illnesses in the United States. It accounts for nearly 600,000 deaths annually in the United States, and costs billions of dollars for those who suffer from the disease. This disease is in fact a diverse group of disorders, which can originate in almost any tissue of the body. In addition, cancers may be generated by multiple mechanisms including pathogenic infections, mutations, and environmental insults (see, e.g., Pratt et al. (2005)  Hum Pathol.  36(8): 861-70). The variety of cancer types and mechanisms of tumorigenesis add to the difficulty associated with treating a tumor, increasing the risk posed by the cancer to the patient&#39;s life and wellbeing.  
      Cancers manifest abnormal growth and the ability to move from an original site of growth to other tissues in the body (hereinafter termed “metastasis”), unlike most non-cancerous cells. These clinical manifestations are therefore used to diagnose cancer because they are applicable to all cancers. Additionally, a cancer diagnosis is made based on identifying cancer cells by their gross pathology through histological and microscopic inspection of the cells. Although the gross pathology of the cells can provide accurate diagnoses of the cells, the techniques used for such analysis are hampered by the time necessary to process the tissues and the skill of the technician analyzing the samples. These methodologies can lead to unnecessary delay in treating a growing tumor, thereby increasing the likelihood that a benign tumor will acquire metastatic characteristics. It is thus necessary to accurately diagnose potentially cancerous growths as quickly as possible to avoid the development of a potentially life threatening illness.  
      One potential method of increasing the speed and accuracy of cancer diagnoses is the examination of genes as markers for neoplastic potential. Recent advances in molecular biology have identified genes involved in cell cycle control, apoptosis, and metabolic regulation (see, e.g., Isoldi et al. (2005)  Mini Rev. Med. Chem.  5(7): 685-95). Mutations in many of these genes have also been shown to increase the likelihood that a normal cell will progress to a malignant state (see, e.g., Soejima et al. (2005)  Biochem. Cell Biol.  83(4): 429-37). For example, mutations in p53, which is a well-known tumor suppressor gene, have been associated with aberrant cell growth leading to neoplastic potential (see Li et al. (2005)  World J. Gastroenterol.  11 (19): 2998-3001). Many mutations can affect the levels of expression of certain genes in the neoplastic cells as compared to normal cells.  
      There remains a need to identify an accurate and rapid means for diagnosing cancer in patients. Treatment efficacy would be improved by more efficient diagnoses of tissue samples. Furthermore, rapid diagnoses of cancerous tissues would allow clinicians to treat potential tumors prior to the metastasis of the cancer to other tissues of the body. Finally, a test that did not rely upon a particular technician&#39;s skill at identifying abnormal histological characteristics would improve the reliability of cancer diagnoses. There is, therefore, a need for new methods of diagnoses for cancer that are accurate, fast, and relatively easy to interpret.  
     SUMMARY OF THE INVENTION  
      The present invention is based in part upon the discovery that differential expression of certain genes at the protein level occurs when a cell progresses to a neoplastic state. These protein expression patterns are therefore diagnostic for the presence of cancer in a cell sample. This discovery has been exploited to provide an invention that uses such patterns of expression to diagnose the presence of neoplastic cells in the cell sample.  
      In one aspect, the invention provides a method of diagnosing cancer in a subject. The method comprises the step of selecting at least one protein marker from cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase. Once the protein marker(s) is/are selected, a level of expression of the selected protein marker(s) in a cell sample (e.g., a biological fluid sample or a cell sample) is detected by contacting protein-targeting agents that bind to the protein markers isolated from the sample. The level of expression of the selected protein marker(s) in the sample is compared to a level of expression of the same protein marker(s) detected in a control sample of the same tissue type as the sample. The presence of cancer is indicated if the level of expression of one or more protein markers in the sample is greater than the level of expression for the same protein markers in the control sample of the same tissue type.  
      In another aspect, the invention provides a method of diagnosing ovarian cancer in a subject. The method comprises the selection of at least one protein marker from cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, calveolin-1, and glyceraldehyde-3-phosphate dehydrogenase. The level of expression of the selected protein marker(s) in a potentially cancerous ovarian cell sample is detected by contacting the cell sample with a targeting agent or agents specific for the selected cell marker(s). Additionally, the level of expression of the same selected protein marker(s) is detected in a normal ovarian control cell sample by contacting the control cell sample with a targeting agent or agents specific for the selected cell marker(s). The level of expression of the selected protein marker in the potentially cancerous ovarian cell sample is compared to the level of expression of the same protein marker(s) in the normal ovarian control cell sample. The presence of ovarian cancer is indicated if the level of expression of the selected protein marker(s), excluding calveolin-1, in the potentially cancerous ovarian cell sample is greater than the level of expression for the same cell marker(s) in the normal ovarian control cell sample, and/or the level of expression of caveolin-1 in the potentially cancerous ovarian cell sample is less than the level of expression of caveolin-1 in the normal ovarian control cell sample.  
      In certain embodiments, at least two protein markers are selected, and an increased level of expression of at least one of the selected protein markers in the potentially cancerous ovarian cell sample compared to their level of expression in the normal ovarian control cell sample indicates the presence of ovarian cancer. In further embodiments, at least three protein markers are selected and an increased level of expression of at least two of the selected protein markers in potentially cancerous ovarian cell sample compared to their level of expression in the normal ovarian control cell sample indicates the presence of ovarian cancer. In still other embodiments, at least four protein markers are selected and an increased level of expression of at least three of the selected protein markers in the potentially cancerous ovarian cell sample compared to the level of expression in the normal ovarian control cell sample indicates the presence of ovarian cancer. In particular embodiments, the selected protein markers comprise cytokeratin 19, cytokeratin 18, ACRABPII, cytokeratin 7, and caveolin-1. In certain embodiments, the protein targeting agents are selected from the group consisting of ligands, inhibitors, peptidomimetic compounds, peptides, proteins, antibodies, antigen-binding fragments, and combinations thereof. In other embodiments, the level of expression of protein markers is detected by protein capture probes attached to a solid support.  
      In particular embodiments, the ovarian cancer is an ovarian adenocarcinoma, an epithelial adenocarcinoma, or a mucinous carcinoma. In certain embodiments, the subject is a human. In still more particular embodiments, the presence of cancer is indicated if the level of expression in the potentially cancerous ovarian cell sample of at least one of the selected markers is increased or decreased by at least two times when compared to the level of expression of the same protein markers in the normal ovarian control cell sample.  
      In further embodiments, the protein markers are from the group consisting of cytokeratin 19, cytokeratin 18, ACRABPII, and cytokeratin 7. In particular embodiments, the presence of cancer is indicated if the level of expression in the potentially cancerous ovarian cell sample of at least one of the selected protein markers is at least two times the level of expression of the same protein markers in the normal ovarian cell control sample.  
      In some embodiments, the protein markers are cytokeratin 19, cytokeratin 18, ACRABPII, cytokeratin 7, and caveolin-1. In a particular embodiment, the presence of cancer is indicated if the level of expression in the potentially cancerous ovarian cell sample of at least one of the selected protein markers is increased or decreased by at least three times when compared to the level of expression of the same protein markers in the normal ovarian control cell sample.  
      In some embodiments, the step of comparing the level of expression of the selected protein markers further comprises using a class prediction algorithm to differentiate the level of expression of the selected protein markers in the cell sample from the level of expression of the same protein markers in the normal cell sample. In certain embodiments, the level of expression of protein markers is determined using protein microarray, ELISA, Western blotting, and dipstick assays. In certain embodiments, the detection means is selected from the group consisting of fluorophores, chemical dyes, radiolabels, chemiluminescent compounds, colorimetric enzymatic reactions, chemiluminescent enzymatic reactions, magnetic compounds, and paramagnetic compounds.  
      In another aspect, the invention provides a method of diagnosing ovarian cancer in a subject. The method comprises the selection of at least one protein marker from cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, calveolin-1, and glyceraldehyde-3-phosphate dehydrogenase. The level of expression of the selected protein marker(s) in a biological fluid sample isolated from the subject is detected by contacting the biological fluid sample with a targeting agent or agents specific for the selected cell marker(s). Additionally, the level of expression of the same selected protein marker(s) is detected in a control sample by contacting the control sample with a targeting agent or agents specific for the selected cell marker(s). The level of expression of the selected protein marker in the biological fluid sample is compared to the level of expression of the same protein marker(s) in the control sample. The presence of ovarian cancer is indicated if the level of expression of the selected protein marker(s), excluding calveolin-1, in the biological fluid sample is greater than the level of expression for the same cell marker(s) in the control sample, and/or the level of expression of caveolin- 1 in the biological fluid sample is less than the level of expression of caveolin-1 in the control sample.  
      In certain embodiments, at least two protein markers are selected, and an increased level of expression of at least one of the selected protein markers in the biological fluid sample compared to their level of expression in the control sample indicates the presence of ovarian cancer. In further embodiments, at least three protein markers are selected and an increased level of expression of at least two of the selected protein markers in the biological fluid sample compared to their level of expression in the control sample indicates the presence of ovarian cancer. In still other embodiments, at least four protein markers are selected and an increased level of expression of at least three of the selected protein markers in the biological fluid sample compared to the level of expression in the control sample indicates the presence of ovarian cancer. In particular embodiments, the selected protein markers comprise cytokeratin 19, cytokeratin 18, ACRABPII, cytokeratin 7, and caveolin-1. In certain embodiments, the protein targeting agents are selected from the group consisting of ligands, inhibitors, peptidomimetic compounds, peptides, proteins, antibodies, antigen-binding fragments, and combinations thereof. In other embodiments, the level of expression of protein markers is detected by protein capture probes attached to a solid support.  
      In particular embodiments, the ovarian cancer is an ovarian adenocarcinoma, an epithelial adenocarcinoma, or a mucinous carcinoma. In certain embodiments, the subject is a human. In still more particular embodiments, the presence of cancer is indicated if the level of expression in the biological fluid sample of at least one of the selected markers is increased or decreased by at least two times when compared to the level of expression of the same protein markers in the control sample. In other embodiments, the level of expression of the selected protein markers is increased or decreased by at least 1.1 to 1.5 times when compared to the level of expression of the same protein marker in the control sample.  
      In further embodiments, the protein markers are from the group consisting of cytokeratin 19, cytokeratin 18, ACRABPII, and cytokeratin 7. In particular embodiments, the presence of cancer is indicated if the level of expression in the biological fluid sample of at least one of the selected protein markers is at least two times the level of expression of the same protein markers in the control sample. In some embodiments, the biological fluid sample includes blood, bile, serum, sweat, urine, mucosal secretions, saliva, seminal fluid, cerebrospinal fluid, tears, and sebaceous secretions. In certain embodiments, the biological fluid sample is blood or serum.  
      In some embodiments, the protein markers are cytokeratin 19, cytokeratin 18, ACRABPII, cytokeratin 7, and caveolin-1. In a particular embodiment, the presence of cancer is indicated if the level of expression in the biological fluid sample of at least one of the selected protein markers is increased or decreased by at least three times when compared to the level of expression of the same protein markers in the control sample. In other embodiments, the level of expression of the selected protein markers is increased or decreased by at least 1.1 to 1.5 times when compared to the level of expression of the same protein marker in the control sample.  
      In some embodiments, the step of comparing the level of expression of the selected protein markers further comprises using a class prediction algorithm to differentiate the level of expression of the selected protein markers in the biological fluid sample from the level of expression of the same protein markers in the control sample. In certain embodiments, the level of expression of protein markers is determined using protein microarray, ELISA, Western blotting, and dipstick assays. In certain embodiments, the detection means is selected from the group consisting of fluorophores, chemical dyes, radiolabels, chemiluminescent compounds, colorimetric enzymatic reactions, chemiluminescent enzymatic reactions, magnetic compounds, and paramagnetic compounds.  
      In another aspect, the invention provides a focused microarray for diagnosing a neoplasm. The focused microarray comprises a first set of protein capture probes that bind specifically to a protein marker selected from the group consisting of cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase, and caveolin-1. The first set comprises at least two different protein capture probes. The focused microarray further contains a second set of protein capture probes, each of which binds to an endogenous housekeeping protein. Also, a solid support is provided to which the first and second set of protein capture probes are attached at predetermined positions.  
      In certain embodiments, the first set of capture probes binds to at least three of the protein markers from the group consisting of cytokeratin 19, cytokeratin 18, ACRABPII, cytokeratin 7, and caveolin-1. In other embodiments, the first set of capture probes binds to at least four of the protein markers from the group consisting of cytokeratin 19, cytokeratin 18, ACRABPII, cytokeratin 7, and caveolin-1. In still other embodiments, the first set of capture probes binds to the protein markers consisting of cytokeratin 19, cytokeratin 18, ACRABPII, cytokeratin 7, and caveolin-1. In some embodiments, the protein capture probes are from the group consisting of ligands, inhibitors, peptidomimetic compounds, peptides, proteins, antibodies, antigen-binding fragments of antibodies, and combinations thereof.  
      In yet another aspect, the invention provides a kit for diagnosing cancer in a subject. The kit provides a first set of probes for the detection of one or more protein markers selected from the group consisting of cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase, and caveolin-1. The kit also provides a second set of probes for the detection of one or more endogenous housekeeping proteins. Furthermore, the kit contains a detection means for identifying a probe binding to a target protein marker.  
      In certain embodiments, the second set of protein targeting agents is specific for proteins markers that do not vary statistically significantly in their level of expression between potentially cancerous cell samples and normal control cell samples.  
      In certain embodiments, the detection means is selected from the group consisting of fluorophores, chemical dyes, radiolabels, chemiluminescent compounds, colorimetric enzymatic reactions, chemiluminescent enzymatic reactions, magnetic compounds, and paramagnetic compounds. In particular embodiments, the first set and second sets of protein targeting agents are attached to a solid support at predetermined positions. In more particular embodiments, the cancer being detected using the kit is an ovarian adenocarcinoma, an ovarian epithelial adenocarcinoma, or a mucinous carcinoma.  
      In another aspect, the invention provides a method of diagnosing ovarian cancer in a subject. The method comprises selecting a first group protein markers including cytokeratin 19, cytokeratin 18, ACRABPII, and cytokeratin 7. The method also comprises selecting the protein marker caveolin-1. Next, a level of expression for the protein markers is detected in a potentially cancerous ovarian cell sample by binding targeting agents with the protein markers isolated from that sample. The level of expression of the same protein markers is detected in a normal ovarian control cell sample by binding targeting agents with the protein markers isolated from the normal ovarian control cell sample. The level of expression of the protein markers in the potentially cancerous ovarian cell sample is then compared to the level of expression of the same protein markers in the normal ovarian control cell sample. The presence of ovarian cancer is indicated if the level of expression of the first group of protein markers, not including caveolin-1, in the potentially cancerous ovarian cell sample is greater than the level of expression of the same protein markers in the ovarian normal control cell sample, and the level of expression of caveolin-1 in the potentially cancerous ovarian cell sample is less than the level of expression of caveolin-1 in the normal ovarian control cell sample  
    
    
     BRIEF DESCRIPTION OF THE FIGURES  
      The foregoing and other objects of the present invention, the various features thereof, as well as the invention itself may be more fully understood from the following description, when read together with the accompanying drawings in which:  
       FIG. 1A  is a tabular representation showing the patient profiles of the 55 tumor tissue samples used in the western blot and ELISA studies.  
       FIG. 1B  is a tabular representation showing the individual profiles of the 58 normal tissue samples used in the western blot and ELISA studies.  
       FIG. 2A  is a photographic representation of 10 different immunoblots probed with anti-cytokeratin 18 antibody that shows the level of expression of cytokeratin 18 in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 2B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of cytokeratin 18 in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 3A  is a photographic representation of 10 different immunoblots probed with anti-cytokeratin 19 antibody that shows the level of expression of cytokeratin 19 in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 3B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of cytokeratin 19 in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 4A  is a photographic representation of 10 different immunoblots probed with anti-cytokeratin 7 antibody that shows the level of expression of cytokeratin 7 in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 4B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of cytokeratin 7 in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 5A  is a photographic representation of 10 different immunoblots probed with anti-caveolin-1 antibody that shows the level of expression of caveolin-1 in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 5B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of caveolin-1 in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 6  is a photographic representation of 10 different immunoblots probed with anti-ACRABPII antibody that shows the level of expression of ACRABPII in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 7A  is a photographic representation of 10 different immunoblots probed with anti-hepatoma-derived growth factor antibody that shows the level of expression of hepatoma-derived growth factor in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 7B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of hepatoma-derived growth factor in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 8A  is a photographic representation of 10 different immunoblots probed with anti-enolase-l antibody that shows the level of expression of enolase-1 in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 8B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of enolase-1 in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 9A  is a photographic representation of 10 different immunoblots probed with anti-triosephosphate isomerase-1 antibody that shows the level of expression of triosephosphate isomerase-l in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 9B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of triosephosphate isomerase-1 in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 10A  is a photographic representation of 10 different immunoblots probed with anti-glyceraldehyde-3-phosphate dehydrogenase antibody that shows the level of expression of glyceraldehyde-3-phosphate dehydrogenase in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 10B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of glyceraldehyde-3-phosphate dehydrogenase in normal ovarian tissue subjects and ovarian cancer patients.  
       FIG. 11A  is a photographic representation of 10 different immunoblots probed with anti-vinculin antibody that shows the level of expression of vinculin in tissue samples from normal subjects (“Normals”) and ovarian cancer patients (“Tumors”), normal and tumor samples are identified by the BR number provided.  
       FIG. 11B  is a graphic representation showing a scatter plot of the results of an ELISA analysis comparing the levels of expression of vinculin in normal ovarian tissue subjects and ovarian cancer patients.  
    
    
     DETAILED DESCRIPTION OF THE INVENTION  
      Patent and scientific literature referred to herein establishes knowledge that is available to those of skill in the art. The issued US patents, allowed applications, published foreign applications, and references, including GenBank database sequences, that are cited herein are hereby incorporated by reference to the same extent as if each was specifically and individually indicated to be incorporated by reference.  
      1.1. General  
      The present invention provides, in part, methods and kits for diagnosing, detecting, or screening a cell sample for tumorigenic potential and neoplastic characteristics such as aberrant growth. The invention also allows for the improved clinical management of tumors by providing a device that detects the expression level of genes identified as markers for cancer.  
      Typically, a gene will affect the phenotype of the cell through its expression at the protein level. Mutations in the coding sequence of the gene can alter its protein product in such a way that the protein does not perform its intended function appropriately. Some mutations, however, affect the levels of protein expressed in the cell without altering the functionality of the protein, itself. Such mutations directly affect the phenotype of a cell by changing the delicate balance of protein expression in a cell. Therefore, an alteration in a gene&#39;s overall activity can be measured by determining the level of expression of the protein product of the gene in a cell.  
      Accordingly, one aspect of the invention provides a method for diagnosing cancer in a cell. The method utilizes protein-targeting agents to identify proteins in a potentially cancerous cell sample or potentially cancerous serum sample. Increased levels of expression of particular protein markers in a cell or serum sample and a decreased expression level of other protein markers in a cell or serum sample indicate the presence of a neoplasm.  
      As used herein, the term “protein-targeting agent” means a molecule capable of binding or interacting with a protein or a portion of a protein. Such binding or interactions can include ionic bonds, van der Waals interactions, London forces, covalent bonds, and hydrogen bonds. The target protein can be bound in a receptor binding pocket, on its surface, or any other portion of the protein that is accessible to binding or interactions with a molecule. Protein-targeting agents include, but are not limited to, proteins, peptides, ligands, peptidomimetic compounds, inhibitors, organic molecules, aptamers, or combinations thereof.  
      As used herein, the term “tumorigenic potential” means ability to give rise to either benign or malignant tumors. Tumorigenic potential may occur through genetic mechanisms such as mutation or through infection with vectors such as viruses and bacteria.  
      The term “cancer” refers herein to a disease condition in which a tissue or cells exhibit aberrant, uncontrolled growth and/or lack of contact inhibition. A cancer can be a single cell or a tumor composed of hyperplastic cells. In addition, cancers can be malignant and metastatic, spreading from an original tumor site to other tissues in the body. In contrast, some cancers are localized to a single tissue of the body.  
      As used herein, a “cancer cell” is a cell that shows aberrant cell growth, such as increased, uncontrolled cell proliferation and/or lack of contact inhibition. A cancer cell can be a hyperplastic cell, a cell from a cell line that shows a lack of contact inhibition when grown in vitro, or a cancer cell that is capable of metastasis in vivo. In addition, cancer cells include cells isolated from a tumor or tumors. As used herein, a “tumor” is a collection of cells that exhibit the characteristics of cancer cells. Non-limiting examples of cancer cells include melanoma, ovarian cancer, ovarian cancer, prostate cancer, sarcoma, leukemic retinoblastoma, hepatoma, myeloma, glioma, mesothelioma, carcinoma, leukemia, lymphoma, Hodgkin lymphoma, Non-Hodgkin lymphoma, promyelocytic leukemia, lymphoblastoma, and thymoma, and lymphoma cells, melanoma cells, sarcoma cells, leukemia cells, retinoblastoma cells, hepatoma cells, myeloma cells, glioma cells, mesothelioma cells, and carcinoma cells.  
      As used herein, the term “inhibitor” means a compound that prevents a biomolecule, e.g., a protein, nucleic acid, or ribozyme, from completing or initiating a reaction. An inhibitor can inhibit a reaction by competitive, uncompetitive, or non-competitive means. Exemplary inhibitors include, but are not limited to, nucleic acids, proteins, small molecules, chemicals, peptides, peptidomimetic compounds, and analogs that mimic the binding site of an enzyme. In some embodiments, the inhibitor can be nucleic acid molecules including, but not limited to, siRNA that reduce the amount of functional protein in a cell.  
      The term “protein markers” as used herein means any protein, peptide, polypeptides, group of peptides, polypeptides or proteins expressed from a gene, whether chromosomal, extrachromosomal, endogenous, or exogenous, which may produce a cancerous or non-cancerous phenotype in the cell or the organism. As used herein, “gene” means any deoxyribonucleic acid sequence capable of being translated into a protein or peptide sequence. The gene is a DNA sequence that may be transcribed into a mRNA and then translated into a peptide or protein sequence. Extrachromosomal sources of nucleic acid sequences can include double-strand DNA viral genomes, single-stranded DNA viral genomes, double-stranded RNA viral genomes, single-stranded RNA viral genomes, bacterial DNA, mitochondrial genomic DNA, cDNA or any other foreign source of nucleic acid that is capable of generating a gene product.  
      Protein markers can have any structure or configuration, and can be in any location within a cell, on the cell surface. Protein markers can also be secreted from the cell into an extracellular matrix or directly into the blood or other biological fluid. Protein markers can be a single polypeptide chain or peptide fragments of a polypeptide. Moreover, protein markers can also be combinations of nucleic acids and polypeptides as in the case of a ribosome. Protein markers can have any secondary structure combination, any tertiary structure, and come in quaternary structures as well.  
      As used herein, the term “normal control cell sample” refers to a cell or group of cells that is exhibiting common characteristics for the particular cell type from which the cell or group of cells was isolated. A normal control cell sample does not exhibit tumorigenic potential, metastatic potential, or aberrant growth in vivo or in vitro. A normal control cell sample can be isolated from tissues in a subject that is not suffering from cancer. It may not be necessary to isolate a normal control cell sample each time a cell sample is tested for cancer as long as the nucleic acids isolated from the normal control cell sample allow for probing against the focused microarray during the testing procedure.  
      In another aspect, the invention provides methods for diagnosing cancer in a cell sample using a protein microarray. The methods can be practiced using a microarray composed of capture probes affixed to a derivatized solid support such as, but not limited to, glass, nylon, metal alloy, or silicon. Non-limiting examples of derivatizing substances include aldehydes, gelatin-based substrates, epoxies, poly-lysine, amines and silanes. Techniques for applying these substances to solid surfaces are well known in the art. In useful embodiments, the solid support can be comprised of nylon.  
      For purposes of the invention, the term “capture probe” is intended to mean any agent capable of binding a gene product in a complex cell sample. Capture probes can be disposed on the derivatized solid support utilizing methods practiced by those of ordinary skill in the art through a process called “printing” (see, e.g., Schena et. al., (1995)  Science,  270(5235): 467-470). The term “printing”, as used herein, refers to the placement of spots onto the solid support in such close proximity as to allow a maximum number of spots to be disposed onto a solid support. The printing process can be carried out by, e.g., a robotic printer. The VersArray CHIP Writer Prosystem (BioRad Laboratories) using Stealth Micro Spotting Pins (Telechem International, Inc, Sunnyvale, Calif.) is a non-limiting example of a chip-printing device that can be used to produce the focused microarray for this aspect. In certain embodiments, capture probes are antibodies or any other molecule, which are attached to a solid support at predetermined positions, capable of binding a protein (herein termed “protein capture probes”).  
      In some embodiments, the levels of expression of the protein markers in the potentially cancerous cell sample are compared to the levels of expression of the protein markers in a normal control cell sample of the same tissue type. If the expression of at least one protein marker in the potentially cancerous cell sample is greater than the expression of the protein marker or genes in the normal control cell sample, then cancer is indicated. In some embodiments, the cell sample is tumorigenic if the level of expression of at least two or more of the plurality of protein markers in the potentially cancerous cell sample is greater than the level of expression of the same protein marker(s) in the normal control cell sample of the same tissue type. Certain markers, however, will have a lower level of expression in a potentially cancerous cell sample than in a normal control cell sample. An example of such a marker is caveolin-1.  
      Furthermore, cell samples can be isolated from human tumor tissues using means that are known in the art (see, e.g., Vara et al. (2005)  Biomaterials  26(18):3987-93; Iyer et al. (1998)  J. Biol. Chem.  273(5):2692-7). For example, the cell sample can be isolated from the ovary of a human patient with ovarian cancer. Ovarian cancer cells can be obtained from other tissues as well, as in the case of metastatic ovarian cancer. Non-limiting sites of ovarian cancer-derived metastases can include, but are not limited to, ovarian, bone, blood, lung, skin, brain, adipose tissue, muscle, gastrointestinal tissues, hepatic tissues, and kidney. Alternatively, cell samples can be obtained commercially from cell line sources as well (e.g., American Type Culture Collections, Mannassas, Va.).  
      As used herein, the term “ovarian cell sample” is intended to mean a cell that is isolated from ovarian tissue. Ovarian cell samples can be isolated from several non-limiting types of ovarian tissue including glandular, ductal, stromal, fibrous and lymphatic tissue. In addition, the cell sample can be a metastatic cell isolated from bone, lymphatic tissue, blood, brain, lung, muscle, and skin. Ovarian or ovarian cell samples can be isolated from a mammal such as a human, mouse, rat, horse, pig, guinea pig, or chinchilla. The methods of the invention can be used to detect different types of neoplastic cells from ovarian tissue. Exemplary non-limiting ovarian cancer cells include ovarian adenocarcinoma, epithelial adenocarcinoma, sex cord-stromal carcinoma, endometrioid tumors, mucinous carcinoma, germ cell tumors, and clear cell tumors. Ovarian cancer cell lines are also available from common sources, such as the ATCC cell biology collections (American Type Culture Collections, Mannassas, Va.).  
      The present invention allows for the detection of cancer in tissues that are of mixed cellular populations such as a mixture of cancer cells and normal cells. In such cases, cancer cells can represent as little as 40% of the tissue isolated for the present invention to determine that the cell sample is tumorigenic. In certain embodiments, the cell sample can be composed of 50% cancer cells for the present invention to detect tumorigenic potential. Cell samples composed of greater than 50% tumorigenic cells can also be used in the present invention. It should be noted that cell samples can be isolated from tissues that are less than 40% tumorigenic cells as long as the cell sample contains a portion of cells that are at least 40% tumorigenic.  
      In the present invention, levels of expression of housekeeping proteins are used to normalize the signal obtained between patients. As used herein, the term “housekeeping proteins” refers to any protein that has relatively stable or steady expression at the protein level during the life of a cell. Housekeeping proteins can be protein markers that show little difference in expression between cancer cells and normal cells in a particular tissue type. Examples of housekeeping proteins are well known in the art, and include, but are not limited to, isocitrate lyase, acyltransferase, creatine kinase, TATA-binding protein, hypoxanthine phosphoribosyl transferase 1, and guanine nucleotide binding protein, beta polypeptide 2-like 1 (see, e.g., Pandey et al. (2004)  Bioinformatics  20(17): 2904-2910). In addition, the housekeeping proteins are used to identify the proper signal level by which to compare the cell sample signals between protein microarray experiments.  
      Another aspect of the invention provides a method of diagnosing cancer in a cell sample. In this method, expression of a protein marker in the potentially cancerous cell is measured. Expression levels for the protein markers can be determined using any techniques known in the art. Useful ways to determine such expression levels include, but not limited to, Western blot, protein microarrays, and Enzyme-Linked Immunosorbent Assays (“ELISA”) (see, e.g., U.S. Pat. No. 6,955,896; U.S. Pat. No. 6,087,012; U.S. Pat. No. 3,791,932; U.S. Pat. No. 3,850,752; U.S. Pat. No. 4,034,074). Such examples are not intended to limit the potential means for determining the expression of a protein marker in a cell sample. Expression levels of markers in or by potentially cancerous cell samples and normal control cell samples can be compared using standard statistical techniques known to those of skill in the art (see, e.g., Ma et al., (2002)  Methods Mol. Biol.  196:139-45).  
      The cancer cell sample can be isolated from a human patient by a physician and tested for expression of protein markers using a focused microarray. In addition, the cancer cell sample can be isolated from an organism that develops a tumor or cancer cells including, but not limited to, mouse, rat, horse, pig, guinea pig, or chinchilla. Cell samples can be stored for extended periods prior to testing or tested immediately upon isolation of the cell sample from the subject. Cell samples can be isolated by non-limiting methods such as surgical excision, aspiration from soft tissues such as adipose tissue or lymphatic tissue, biopsy, or removed from the blood. These methods are known to those of skill in the art.  
      1.2. Protein-Targeting Agents  
      Protein marker expression is used to identify tumorigenic potential. Protein markers can be obtained by isolation from a cell sample using any techniques available to one of ordinary skill in the art (see, e.g., Ausubel et. al.,  Current Protocols in Molecular Biology,  Wiley and Sons, New York, N.Y., 1999). Isolation of protein markers from the potentially tumorigenic cell sample allows for the generation of target molecules, providing a means for determining the expression level of the protein markers in the potentially tumorigenic cell sample as described below. The protein markers can be isolated from a tissue sample isolated from a human patient. The markers can be isolated from a cytoplasmic fraction or a membrane fraction of the sample. Protein isolation techniques known in the art include, but are not limited to, column chromatography, spin column chromatography, and protein precipitation. Protein markers can be isolated using methods that are taught in, for example, Ausubel et al.,  Current Protocols in Molecular Biology,  Vol. 1, John Wiley &amp; Sons, Inc., (1993).  
      In particular embodiments, the invention provides protein-targeting agents that comprise of antibodies or antigen binding fragments thereof. These embodiments are described in detail below. Other potential protein targeting agents include, but are not limited to, peptidomimetic compounds, peptides directed to the active sites of an enzyme, nucleic acids, nucleic acid aptamers.  
      In addition, inhibitors can be used as protein targeting agents to bind to protein markers. Useful inhibitors are compounds that bind to a target protein, and normally reduce the “effective activity” of the target protein in the cell or cell sample. Inhibitors include, but are not limited to, antibodies, antibody fragments such as “Fv,” “F(ab′)2,” “F(ab),” “Dab” and single chains representing the reactive portion of an antibody (“SC-Mab”), peptides, peptidomimetic compounds, and small molecules (see, e.g., Lopez-Alemany et al. (2003)  Am. J. Hematol.  72(4): 234-42; Miles et al. (1991)  Biochem.  30(6): 1682-91). Inhibitors can perform their functions through a variety of means including, but not limited to, non-competitive, uncompetitive, and competitive mechanisms. For instance, the triosephosphate isomerase 1 inhibitor N-hydroxy-4-phosphono-butanamide has been described previously (see, e.g., Verlinde et al. (1989)  Protein Sci.  1(12): 1578-84).  
      Protein-targeting agents, including antibodies can also be conjugated to non-limiting materials such as magnetic compounds, paramagnetic compounds, proteins, nucleic acids, antibody fragments, or combinations thereof. Furthermore, antibodies can be disposed on an NPV membrane and placed into a dipstick. Antibodies can also be immobilized on a solid support at pre-determined positions such as in the case of a microarray.  
      Protein-targeting agents can be detectably labeled. As used herein, “detectably labeled” means that a targeting agent is operably linked to a moiety that is detectable. By “operably linked” is meant that the moiety is attached to the protein-targeting agent by either a covalent or non-covalent (e.g., ionic) bond. Methods for creating covalent bonds are known (see, e.g., Wong, S. S.,  Chemistry of Protein Conjugation and Cross - Linking,  CRC Press 1991; Burkhart et al.,  The Chemistry and Application of Amino Crosslinking Agents or Aminoplasts , John Wiley &amp; Sons Inc., New York City, N.Y., 1999).  
      According to the invention, a “detectable label” is a moiety that can be sensed. Such labels can be, without limitation, fluorophores (e.g., fluorescein (FITC), phycoerythrin, rhodamine), chemical dyes, or compounds that are radioactive, chemoluminescent, magnetic, paramagnetic, promagnetic, or enzymes that yield a product that may be colored, chemoluminescent, or magnetic. The signal is detectable by any suitable means, including spectroscopic, photochemical, biochemical, immunochemical, electrical, optical or chemical means. In certain cases, the signal is detectable by two or more means. In certain embodiments, protein targeting agents include fluorescent dyes, radiolabels, and chemiluminescent labels, which are examples that are not intended to limit the scope of the invention (see, e.g., Gruber et al. (2000)  Bioconjug. Chem.  11(5): 696-704).  
      For example, protein-targeting agents may be conjugated to Cy5/Cy3 fluorescent dyes. These dyes are frequently used in the art (see, e.g., Gruber et al. (2000)  Bioconjug. Chem.  11(5): 696-704). The fluorescent labels can be selected from a variety of structural classes, including the non-limiting examples such as 1- and 2-aminonaphthalene, p,p′diaminostilbenes, pyrenes, quaternary phenanthridine salts, 9-aminoacridines, p,p′-diaminobenzophenone imines, anthracenes, oxacarbocyanine, marocyanine, 3-aminoequilenin, perylene, bisbenzoxazole, bis-p-oxazolyl benzene, 1,2-benzophenazin, retinol, bis-3-aminopridinium salts, hellebrigenin, tetracycline, sterophenol, benzimidazolyl phenylamine, 2-oxo-3-chromen, indole, xanthen, 7-hydroxycoumarin, phenoxazine, salicylate, strophanthidin, porphyrins, triarylmethanes, flavin, xanthene dyes (e.g., fluorescein and rhodamine dyes); cyanine dyes; 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene dyes and fluorescent proteins (e.g., green fluorescent protein, phycobiliprotein).  
      1.3. Antibodies for Detection of Protein Markers  
      Aspects of the present invention utilize monoclonal and polyclonal antibodies as protein targeting agents directed specifically against certain protein markers. Useful markers include cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3 -phosphate dehydrogenase. Anti-protein marker antibodies, both monoclonal and polyclonal, for use in the invention are available from several commercial sources (e.g., Santa Cruz Biotechnology, Santa Cruz, Calif.; and Biogenesis, Inc., Kingston, N.H.). cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase antibodies can be administered to a patient orally, subcutaneously, intramuscularly, intravenously, or interperitoneally.  
      As used herein, the term “polyclonal antibodies” means a population of antibodies that can bind to multiple epitopes on an antigenic molecule. A polyclonal antibody is specific to a particular epitope on an antigen, while the entire pool of polyclonal antibodies can recognize different epitopes. In addition, polyclonal antibodies developed against the same antigen can recognize the same epitope on an antigen, but with varying degrees of specificity. Polyclonal antibodies can be isolated from multiple organisms including, but not limited to, rabbit, goat, horse, mouse, rat, and primates. Polyclonal antibodies can also be purified from crude serums using techniques known in the art (see, e.g., Ausubel, et al.,  Current Protocols in Molecular Biology , Vol. 1, pp. 4.2.1-4.2.9, John Wiley &amp; Sons, Inc., 1996).  
      The term “monoclonal antibody”, as used herein, refers to an antibody obtained from a population of substantially homogenous antibodies, i.e., the individual antibodies comprising the population are identical except for possible naturally occurring mutations that may be present in minor amounts. Monoclonal antibodies are highly specific, being directed against a single antigenic site. By their nature, monoclonal antibody preparations are directed to a single specific determinant on the target. Novel monoclonal antibodies or fragments thereof mean in principle all immunoglobulin classes such as IgM, IgG, IgD, IgE, IgA, or their subclasses or mixtures thereof. Non-limiting examples of subclasses include the IgG subclasses IgG1, IgG2, IgG3, IgG2a, IgG2b, IgG3, or IgGM. The IgG subtypes IgG1/κ and IgG2b/κ are also included within the scope of the present invention. Antibodies can be obtained commercially from, e.g., BioMol International LP (Plymouth Meeting, Pa.), BD Biosciences Pharmingen (San Diego, Calif.), and Cell Sciences, Inc. (Canton, Mass.).  
      The monoclonal antibodies herein include hybrid and recombinant antibodies produced by splicing a variable (including hypervariable) domain of an anti-protein marker antibody with a constant domain (e.g., “humanized” antibodies), or a light chain with a heavy chain, or a chain from one species with a chain from another species, or fusions with heterologous proteins, regardless of species of origin or immunoglobulin class or subclass designation, as well as antibody fragments (e.g., Fab, F(ab) 2 , and Fv), so long as they exhibit the desired biological activity. (See, e.g., U.S. Pat. No. 4,816,567; Mage and Lamoyi, in  Monoclonal Antibody Production Techniques and Applications,  (Marcel Dekker, Inc., New York 1987, pp.79-97). Thus, the modified “monoclonal” indicates the character of the antibody as being obtained from a substantially homogeneous population of antibodies, and is not to be construed as requiring production of the antibody by any particular method. For example, the monoclonal antibodies to be used in accordance with the present invention can be made by the hybridoma method (see, e.g., Kohler and Milstein (1975)  Nature  256:495) or can be made by recombinant DNA methods (U.S. Pat. No. 4,816,567). The monoclonal antibodies can also be isolated from phage libraries generated using the techniques described in the art (see, e.g., McCafferty et al. (1990)  Nature  348:552-554).  
      Alternative methods for producing antibodies can be used to obtain high affinity antibodies. Antibodies can be obtained from human sources such as serum. Additionally, monoclonal antibodies can be obtained from mouse-human heteromyeloma cell lines by techniques known in the art (see, e.g., Kozbor (1984)  J. Immunol.  133, 3001; Boerner et al., (1991)  J. Immunol.  147:86-95). Methods for the generation of human monoclonal antibodies using phage display, transgenic mouse technologies, and in vitro display technologies are known in the art and have been described previously (see, e.g., Osbourn et al. (2003)  Drug Discov. Today  8: 845-51; Maynard and Georgiou (2000)  Ann. Rev. Biomed. Eng.  2: 339-76; U.S. Pat. Nos. 4,833,077; 5,811,524; 5,958,765; 6,413,771; and 6,537,809).  
      Aspects of the invention also utilize polyclonal antibodies for the detection of cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase.  
      1.4. Detection of Protein Markers From Biological Fluids  
      An aspect of the present invention includes an assay for the detection of any protein marker using a protein-targeting agent to bind to the protein marker. The protein marker typically is a peptide, polypeptide, protein, glycoprotein, or protiolipid. The protein-targeting agent can comprise antigens and antibodies thereto; haptens and antibodies thereto; and hormones, ligands, vitamins, metabolites and pharmacological agents, and their receptors and binding substances. The protein-targeting agent may be an immunologically-active polypeptide or protein or molecular weight between 1,000 Daltons and 10,000,000 Daltons, such as an antibody or antigenic polypeptide or protein, or a hapten of molecular weight between 100 Daltons and 1,500 Daltons. Protein-targeting agents can bind to protein markers that are obtained from biological fluids. As used herein, the term “biological fluids” means aqueous or semi-aqueous liquids isolated from an organism in which biological macromolecules may be identified or isolated. Biological fluids may be disposed internally as in the case of blood serum, bile, or cerebrospinal fluid. Biological fluids can be excreted as in the non-limiting cases of urine, saliva, sweat, tears, mucosal secretions, lacrimal secretions, seminal fluid, sperm, and sebaceous secretions.  
      For detection of markers in biological fluids, detection devices can be used that are in the form of a “dipstick.” Such devices are known in the art, and have been applied to detecting protein markers in serum and other biological fluids (see, e.g. U.S. Pat. No. 4,390,343). In some instances, a dipstick-type device can be comprised of analytical elements where protein-targeting agents, such as antibodies, inhibitors, organic molecules, peptidomimetic compounds, ligands, organic compounds, or combinations thereof, are incorporated into a gel. The gel can be comprised of non-limiting substances such as agarose, gelatin or PVP (see, e.g., U.S. Pat. No. 4,390,343). The gel can be contained within an analytical region for reaction with a protein marker.  
      The “dipstick” format (exemplified in U.S. Pat. Nos. 5,275,785, 5,504,013, 5,602,040, 5,622,871 and 5,656,503) typically consists of a strip of porous material having a biological fluid sample-receiving end, a reagent zone and a reaction zone. As used herein, the term “reagent zone” means the area within the dipstick in which the protein-targeting agent and the protein markers in the biological sample come into contact. By the term “reaction zone”, is meant the area within the dipstick in which an immobilized binding agent captures the protein-targeting agent/protein marker complex. As used herein, the term “binding agent” refers to any molecule or group of molecules that can bind, interact, or associate with a protein-targeting agent/protein marker complex.  
      In certain embodiments, the biological fluid sample is wicked along the assay device starting at the sample-receiving end and moving into the reagent zone. The protein marker(s) to be detected binds to a protein-targeting agent incorporated into the reagent zone, such as a labeled protein-targeting agent, to form a complex. For example, a labeled antibody can be the protein-targeting agent, which complexes specifically with the protein marker. In other examples, the protein-targeting agent can be a receptor that binds to a protein marker in a receptor:ligand complex. In yet other examples, an inhibitor is used to bind to a protein marker, thereby forming a complex with the protein marker targeted by the particular inhibitor. In some examples, peptidomimetic compounds are used to bind to protein markers to mimic the interaction of a protein marker with a normal peptide. In other examples, the protein-targeting agent can be an organic molecule capable of associating with the protein marker. In all cases, the protein-targeting agent has a label. The labeled protein-targeting agent-protein marker complex then migrates into the reaction zone, where the complex is captured by another specific binding partner firmly immobilized in the reaction zone. Retention of the labeled complex within the reaction zone thus results in a visible readout.  
      A number of different types of other useful assays that measure the presence of a protein market are well known in the art. One such assay is an immunoassay. Immunoassays may be homogeneous, i.e. performed in a single phase, or heterogeneous, where antigen or antibody is linked to an insoluble solid support upon which the assay is performed. Sandwich or competitive assays may be performed. The reaction steps may be performed simultaneously or sequentially. Threshold assays may be performed, where a predetermined amount of analyte is removed from the sample using a capture reagent before the assay is performed, and only analyte levels of above the specified concentration are detected. Assay formats include, but are not limited to, for example, assays performed in test tubes, wells or on immunochromatographic test strips, as well as dipstick, lateral flow or migratory format immunoassays.  
      In certain embodiments, a lateral flow test immunoassay device is used. In such devices, a membrane system forms a single fluid flow pathway along the test strip. The membrane system includes components that act as a solid support for immunoreactions. For example, porous or bibulous or absorbent materials can be placed on a strip such that they partially overlap, or a single material can be used, in order to conduct liquid along the strip. The membrane materials can be supported on a backing, such as a plastic backing. The test strip includes a glass fiber pad, a nitrocellulose strip and an absorbent cellulose paper strip supported on a plastic backing.  
      Antibodies that specifically bind with the target protein marker are immobilized on the solid support. The antibodies can be bound to the test strip by adsorption, ionic binding, van der Waals adsorption, electrostatic binding, or by covalent binding, by using a coupling agent, such as glutaraldehyde. For example, the antibodies can be applied to the conjugate pad and nitrocellulose strip using standard dispensing methods, such as a syringe pump, airbrush, ceramic piston pump or drop-on-demand dispenser. A volumetric ceramic piston pump dispenser can be used to stripe antibodies that bind the analyte of interest, including a labeled antibody conjugate, onto a glass fiber conjugate pad and a nitrocellulose strip.  
      The test strip can be treated, for example, with sugar to facilitate mobility along the test strip or with water-soluble non-immune animal proteins, such as albumins, including bovine (BSA), other animal proteins, water-soluble polyamino acids, or casein to block non-specific binding sites.  
      1.5. Cancer Diagnosis and Prediction Analysis  
      Cancer diagnoses can be performed by comparing the levels of expression of a protein marker or a set of protein markers in a potentially neoplastic cell sample to the levels of expression for a protein marker or a set of protein markers in a normal control cell sample of the same tissue type. Alternatively, the level of expression of a protein marker or a set of protein markers in a potentially cancerous cell sample is compared to a reference pool of protein markers that represents the level of expression for a protein marker or a set of protein markers in a normal control population (herein termed “training set”). The training set also includes the data for a population that has a known tumor or class of tumors. This data represents the average level of expression that has been determined for the neoplastic cells isolated from the tumor or class of tumors. It also has data related to the average level of expression for a protein marker or set of protein markers for normal cells of the same cell type within a population. In these embodiments, the algorithm compares newly generated expression data for a particular protein marker or set of protein markers from a cell sample isolated from a patient containing potentially neoplastic cells to the levels of expression for the same protein marker or set of protein markers in the training set. The algorithm determines whether a cell sample is neoplastic or normal by aligning the level of expression for a protein marker or set of protein markers with the appropriate group in the training set. In certain embodiments, software for performing the statistical manipulations described herein can be provided on a computer connected by data link to a data generating device, such as a microarray reader.  
      Class prediction algorithms can be utilized to differentiate between the levels of expression of markers in a cell sample and the levels of expression of markers in a normal cell sample (Vapnik,  The Nature of Statistical Learning Theory,  Springer Publishing, 1995). Exemplary, non-limiting algorithms include, but are not limited to, compound covariate predictor, diagonal linear discriminant analysis, nearest neighbor predictor, nearest centroid predictor, and support vector machine predictor (Simon et al.,  Design and Analysis of DNA Microarray Investigations: An Artificial Intelligence Milestone.,  Springer Publishing, 2003). These statistical tests are well known in the art, and can be applied to ELISA or data generated using other protein expression determination techniques such as dot blotting, Western Blotting, and protein microarrays (see, e.g., U.S. Patent Application No. 2005/0239079).  
      It should be recognized that statistical analysis of the levels of expression of protein markers in a cell sample to determine cancer state does not require a particular algorithm or set of particular algorithms. Any algorithm can be used in the present invention so long as it can discriminate between statistically significant and statistically insignificant differences in the levels of expression of protein markers in a cell sample as compared to the levels of expression of the same protein markers in a normal cell sample of the same tissue type.  
      In some embodiments, an increased level of expression in the potentially cancerous cell sample indicates that cancer cells exist in the cell sample. In such cancerous samples, protein markers showing increased levels of expression include, but are not limited to cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase. The algorithm makes the class prediction based upon the overall levels of expression found in the cell sample as compared to the levels of expression in the training set. It should be noted that, in some instances, one protein marker can be used to classify a gene as either neoplastic or normal. Two or more protein markers can also be used to properly classify a cell sample as neoplastic or normal. In particular, three protein markers can be used for classification purposes. Four protein markers can be used to identify neoplastic cells within a cell sample. Five protein markers can be used to identify neoplastic cells in a cell sample. Furthermore, six or more protein markers can be used to properly classify cell samples into either the neoplastic cell class or the non-neoplastic cell class.  
      The type of analysis detailed above compares the level of expression for the protein marker(s) in the cell sample to a training set containing reference pools of protein that are representative of a normal population and a neoplastic population. In certain embodiments, the training set can be obtained with kits that can be used to determine the level of expression of protein marker(s) in a patient cell sample. Alternatively, an investigator can generate new training sets using protein expression reference pools that can be obtained from commercial sources such as Asterand, Inc. (Detroit, Mich.). Comparisons between the training sets and the cell samples are performed using standard statistical techniques that are well known in the art, and include, but are not limited to, the ArrayStat 1.0 program (Imaging Research, Inc.). Statistically significant increased levels of expression in the cell sample of protein marker(s) indicate that the cell sample contains a cancer cell or cells with tumorigenic potential. Also, standard statistical techniques such as the Student T test are well known in the art, and can be used to determine statistically significant differences in the levels of expression for protein markers in a patient cell sample (see, e.g., Piedra et al. (1996)  Ped. Infect. Dis. J.  15:1). In particular, the Student T test is used to identify statistically significant changes in expression using protein microarray analysis or ELISA analysis (see, e.g., Piedra et al. (1996)  Ped. Infect. Dis. J.  15:1).  
      1.6 Focused Microarray  
      The invention allows for protein-targeting agents to be immobilized on a solid support. In certain embodiments, the support can be a bead or flat surface similar to a slide. Such a microarray can determine the protein expression of certain markers in a chemotherapeutic drug-resistant cancer cell sample and the protein expression of a multi-drug-sensitive control cell of the same tissue type. The microarray can also be used to determine the presence of a non-MDR-neoplastic cell in a cell sample. Protein microarrays can be prepared by methods disclosed in, e.g., U.S. Pat. Nos. 6,087,102, 6,139,831, and 6,087,103.  
      Protein-targeting agents conjugated to the surface of the protein microarray can be bound by detectably labeled protein markers isolated from a cell sample. This method of detection can be termed “direct labeling” because the protein marker, which is the target, is labeled. In other embodiments, protein markers can be bound by protein-targeting agents, and then subsequently bound by a detectably labeled antibody specific for the protein marker. These methods are termed “indirect labeling” because the detectable label is associated with a secondary antibody or other protein-targeting agent. An overview of protein microarray technology in general can be found in Mitchell,  Nature Biotech.  (2002), 20:225-229, the contents of which are incorporated herein by reference.  
      1.7 Kits  
      Aspects of the invention additionally provide kits for detecting neoplasms such as ovarian cancer in a cell sample. The kits include targeting agents for the detection of cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase. The kits also can include targeting agents for the detection of vimentin, HSC70, and nucleophosmin. A patient that potentially has a tumor or the potential to develop a tumor (“in need thereof”) can be tested for the presence of a tumor or tumor potential by determining the level of expression of targeting agents in a cell sample derived from the patient.  
      The kit comprises labeled binding agents capable of detecting cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, or glyceraldehyde-3-phosphate dehydrogenase in a biological sample, as well as means for determining the amount of these protein markers in the sample, and means for comparing the amount of the protein markers in the potentially cancerous sample with a standard (e.g., normal non-neoplastic control cells). The binding agents can be packaged in a suitable container. The kit can further comprise instructions for using the compounds or agents to detect the protein markers, as well as other neoplasm-associated markers. Such a kit can comprise, e.g., one or more antibodies, or fragments thereof as binding agents, that bind specifically to at least a portion of a protein marker.  
      The kit can also contain a probe for detection of housekeeping protein expression. These probes advantageously allow health care professionals to obtain an additional data point to determine whether chemotherapeutic drug resistance exists. The probes can be any binding agents such as labeled antibodies, or fragments thereof, specific for the housekeeping proteins. Alternatively or additionally, the probes can be inhibitors, peptidomimetic compounds, peptides and/or small molecules.  
      Data related to the levels of expression of the selected protein markers in normal tissues and neoplasms can be supplied in a kit or individually in the form of a pamphlet, document, floppy disk, or computer CD. The data can represent patient pools developed for a particular population (e.g., Caucasian, Asian, etc.) and is tailored to a particular cancer type. Such data can be distributed to clinicians for testing patients for the presence of a neoplasm such as an ovarian cancer. A clinician obtains the levels of expression for a protein marker or set of protein markers in a particular patient. The clinician then compares the expression information obtained from the patient to the levels of expression for the same protein marker or set of protein markers that had been determined previously for both normal control and cancer patient pools. A finding that the level of expression for the protein marker or the set of protein markers is similar to the normal patient pool data indicates that the cell sample obtained from the patient is not neoplastic. A finding that the level of expression for the protein marker or the set of protein markers is similar to the cancer patient pool data indicates that the cell sample obtained from the patient is neoplastic.  
      1.8. Testing  
      The diagnostic methods according to the invention were tested for their ability to diagnose cancer in cell samples isolated from human subjects suffering from ovarian cancers.  
      Sample materials were obtained from Asterand, Inc. (Detroit, Mich.), Cytomix LLC (Lexington, Mass.), and Biochain Institute, Inc. (Hayward, Calif.). Standard clinical and pathological reports were available for each cancer patient included in this study. For the ovarian panel, 55 tumors and 58 normal tissues were used.  
      The expression levels of 9 proteins-of-interest were analyzed for differential expression in ovarian samples from 55 tumor patients and 58 healthy controls by Western blotting and ELISA assays.  FIG. 1A  shows the tumor content, diagnosis, age, and menopausal status of each patient in the study.  FIG. 1B  shows the age, race, and menopausal status of all individuals who donated normal tissues to the study. The proteins were cytokeratin 18, cytokeratin 19, caveolin-1, ACRABPII, cytokeratin 7, hepatoma-derived growth factor, enolase-1, triosephosphate isomerase-1, and glyceradehyde-3-phosphate dehydrogenase. As shown in  FIGS. 2-10 , these proteins showed differential expression between normal and neoplastic ovarian tissues. Therefore, these proteins were biomarkers for ovarian cancer.  
      Cytokeratin 18 was found to be up-regulated in ovarian tumors when compared to normal tissues ( FIG. 2A ). Western blot analysis showed that, in most cases, protein expression was up-regulated in the tumor tissues. To confirm these results, ELISA analysis was performed ( FIG. 2B ). Quantification of cytokeratin 18 expression by ELISA showed that its expression levels were increased by 18-fold in tumors as compared to normal tissues. Therefore, cytokeratin 18 appeared to be a reliable predictor of ovarian neoplasms in human subjects.  
      In addition, cytokeratin 19 showed a 19-fold increase in tumors as compared to normal tissues ( FIG. 3A ). These results were confirmed by ELISA, which showed that the majority of neoplastic tissues had increased expression of cytokeratin 19 marker in the cell samples ( FIG. 3B ). In addition to cytokeratin 19, cytokeratin 7 showed increased levels of expression in neoplastic tissues as compared to normal subject tissues ( FIG. 4A ). Western blot analysis established that few normal subjects showed increased levels of expression of cytokeratin 7. These results were confirmed by ELISA techniques, which showed that most ovarian cancer patients had higher levels of cytokeratin 7 expression than their normal counterparts ( FIG. 4B ).  
      Alternatively, caveolin-1 protein levels were found to be significantly decreased in tumor patient samples as compared to normal subject samples ( FIG. 5A ). ELISA and Western blot analysis established that most individuals containing tumor tissues had 2.5-fold lower levels of caveolin-1 expression at the protein level than their normal counterparts ( FIGS. 5A and 5B ).  
      ACRABPII protein expression levels were also increased in tumor patients as compared to normal subjects ( FIG. 6 ). Ovarian cancer patients showed consistently higher levels of ACRABPII in tumor tissues than normal subjects. Western analysis showed that normal subjects had almost no detectable ACRABPII in their tissue samples, whereas at least half of tumor samples isolated showed some level of ACRABPII expression.  
      Hepatoma-derived growth factor showed increased protein expression levels in tumor samples as compared to normal samples ( FIGS. 7A and 7B ). ELISA analysis established that this growth factor was expressed at 2.0-fold higher levels in tumor tissues as compared to normal tissues. Western blot analysis showed that overlap existed in protein expression between normal subjects and cancer patients ( FIG. 7A ). However, the general result was that higher expression of hepatoma-derived growth factor was indicative of cancer.  
      The glycolytic protein enolase-1 showed a 2.0-fold increased level of protein expression in ovarian tumor samples as compared to normal tissue samples ( FIG. 8B ). ELISA analysis showed that some tumor patients had similar levels of enolase-1 expression to their normal counterparts ( FIG. 8B ). Western blot analysis showed that tumor patients had higher levels of enolase-1 than normal subjects ( FIG. 8A ).  
      In addition, ELISA and Western blot analysis was performed to determine the levels of expression of triosephosphate isomerase-1 in normal ovarian tissues and ovarian tumor samples ( FIGS. 9A and 9B ). The results showed that triosephosphate isomerase-1 was 1.2-fold increased in expression in tumor tissues as compared to normal tissues. The levels of protein expression for glyceraldehyde-3-phosphate dehydrogenase was also determined by ELISA and Western blot ( FIGS. 10A and 10B ).  
      A summary of the protein targets analyzed in this study is shown below in Table 1.  
                   TABLE 1                       Fold Increase           Expression in Tumors   Protein marker                                        18   cytokeratin 18       12   cytokeratin 7       19   cytokeratin 19       2.0   enolase-1       N/A   A-CRABP II       2.0   hepatoma-derived growth factor       1.2   triosephosphate isomerase-1       −2.5   caveolin-1       1.6   GAPDH                  
 
      Depending on the classifiers used, 85% to 88% of the patients were classified in their respective classes with a protein classifier composed of 4 different proteins.  
      Table 2 shows the performance of all classifiers for the ovarian training set (113 cases).  
                               TABLE 2                                       Two Fold   Three Fold           Classifiers   Expression Increase   Expression Increase                          CCP   88%   88%           LDA   88%   85%           1-NN   86%   80%           3-NN   87%   88%           NC   88%   88%           SVM   85%   83%                      
 
      The 1-Nearest Neighbor (1-NN) was the best classifier method for that ovarian training set (Table 2). The other classifier methods used included compound covariate predictor (CCP), diagonal linear discriminant analysis (LD), 3-nearest neighbor predictor (3-NN), nearest centroid predictor (NC), and support vector machine predictor (SVM). Sensitivity toward the normal class was approximately 95% with a specificity of approximately 81%. The PPV was about 84%, while the NPV was approximately 94%. For the tumor class, a sensitivity of approximately 81% was calculated for the classifier method with a specificity of approximately 95%, while a PPV of approximately 94% and a NPV of approximately 84%. Percentages represent accurate tumor classification of patient when protein markers have greater than a two-fold or three-fold increase in expression in tumor tissues as compared to normal tissues.  
     EXAMPLES  
      Those skilled in the art will recognize, or be able to ascertain, using no more than routine experimentation, numerous equivalents to the specific substances and procedures described herein. Such equivalents are intended to be encompassed in the scope of the claims that follow the examples below.  
     Example 1  
     Classification of Cell Samples Isolated from Ovarian Cancer Patients and Normal Ovarian Subjects  
      1. Patient Samples and Normal Samples  
      Patient material was obtained from Asterand, Inc. (Detroit, Mich.), Clinomics Biosciences, Inc (Watervliet, N.Y.) and Biochain Institute, Inc. (Hayward, Calif.). For the ovarian cancer groups, only patients with greater than 70% tumor cell content in the tumor mass were included in the studies. Each patient included in the study was screened against the same normal total RNA pool in order to compare them together. The tumor pool composed of 55 cases. The ovarian normal pool was composed of 58 cases.  
      2. Western Blot Analysis of Protein Markers in Ovarian Cancer and Ovarian Normal Tissues  
      Human ovarian tissues were homogenized using a Polytron PT10-35 (Brinkmann, Mississauga, Canada) for 30 seconds at speed setting of 4 in the presence of 300 μl of 10 mM HEPES-Tris, pH 7.4, 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholic acid, 0.1% SDS, 1 mM EDTA and a cocktail of protease inhibitors from Roche Corp. (Laval, Qc, Canada).  
      For ovarian tissues, 40 μg of proteins from homogenates and from human ovarian cell lines were used in SDS-PAGE gels. Samples were mixed with Laemmli buffer (250 mM Tris-HCl, pH 8.0, 25% (v/v) b-mercaptoethanol, 50% (v/v) glycerol, 10% (w/v) SDS, 0.005% (w/v) bromophenol blue), heated for 5 minutes at 95° C. and resolved in 12% SDS-polyacrylamide gels (SDS-PAGE). Proteins were then electro-transferred onto Hybond-ECL nitrocellulose membranes (Amersham Biosciences, Baie d&#39;Urfé, Canada) for 90 minutes at 100 volts at room temperature. Membranes were blocked for 1 hour at room temperature in blocking solution (PBS containing 5% fat-free dry milk). Membranes were washed with PBS and incubated with the primary antibodies at the appropriate dilutions in blocking solution containing 0.02% sodium azide for 2 hours at room temperature. PBS washing was performed, and the membranes were subsequently incubated for 1 hour at room temperature with secondary anti-mouse, anti-rabbit or anti-goat antibodies labeled with horseradish peroxydase (Bio-Rad, Mississauga, Canada) diluted 1/3000 in PBS. Chemiluminescence detection was performed using the SuperSignal West Pico Chemiluminescent Substrate (Pierce, Rockford, Ill., USA) following the manufacturer&#39;s recommendations.  
      Proteins and the source from which they were obtained are shown in Table 3.  
                       TABLE 3                       Target   Source   Company and Product Number                  Calveolin-1   Immunogen peptide   Santa Cruz Biotech, Inc.               (SE199-0025)       ACRABPII   Human recombinant   Produced inhouse       Cytokeratin 7   Immunogen peptide   Santa Cruz Biotech, Inc.               (sc-17118P)       Cytokeratin 18   Human recombinant   Cedarlane (CLPRO349)       Cytokeratin 19   Human recombinant   Cedarlane (CLPRO349)       Enolase-1   Human recombinant   Produced inhouse       GAPDH   Purified from   Advanced Immunochemical, Inc.           human heart       HDGF   Human recombinant   R&amp;D Systems (CUSTOM02)       TPI   Purified from   Sigma-Aldrich Corp. (T-6258)           rabbit muscle       Vinculin   Human recombinant   Abnova Corp. (H00007414-P01)                  
 
      The results of expression analyses for the protein markers are shown in  FIGS. 1-6 .  
      3. ELISA Analysis of Protein Markers in Ovarian Cancer and Ovarian Normal Tissues  
      To quantify the amount of each target of interest and to confirm the results obtained by Western blot, an ELISA technique was performed on ovarian samples for all protein markers being analyzed in the present study. These markers included cytokeratin 19, cytokeratin 18, cytokeratin 7, ACRABPII, hepatoma-derived factor, enolase-1, triosephosphate isomerase 1, and glyceraldehyde-3-phosphate dehydrogenase. Prior to screening all samples, an optimization of the conditions was performed using normal and tumor samples to determined the linearity of the assay (dose-dependant curve, time of development of the assay) for each target to be analyzed in this assay. Once conditions were optimized, 96-well plates ((Maxisorp plates, NUNC, (Rochester, N.Y., USA)) were coated with the appropriate amount of samples and incubated overnight at 4° C. Wells were washed 3 times with PBS and then blocked with 3% bovine serum albumin (BSA)/PBS for 1 hour at room temperature. Primary antibodies (40 ng/well) were added to the wells and incubated for 2 hours at room temperature. Plates were washed 3 times with PBS and the secondary anti-mouse, anti-rabbit or anti-goat antibodies labeled with horseradish peroxidase (Bio-Rad, Mississauga, Canada), diluted 1:3000 in 3% BSA/PBS, was incubated for 1 hour at room temperature. Wells were washed 3 times with PBS and developed with 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) as the substrate (Sigma Corp., St. Louis, Mo.). The intensity of the signal was assessed by reading the plates at a 405 nm wavelength using a microplate reader. For each of the target, a standard curve was established with a recombinant or purified protein at the same time to quantify the target in each sample. Results were expressed as concentrations of a target in 1 μg of total protein extract. All samples were quantified in the same assay. Differences among normal and tumor groups were analyzed using Student&#39;s two-tailed t test with significance level defined as P&lt;0.05. ELISA results are shown in  FIGS. 1-6  as scatter plots showing the levels of protein expression for each protein marker. Results are shown as μg/mg of protein marker in each normal subject versus μg/mg of protein marker in each ovarian cancer patient.  
      4. Classification of Ovarian Cancer Patients Using Classification Algorithms  
      Class prediction analyses were performed using the BRB ArrayTools developed by Dr. Richard Simon (NIH/NCI) and Amy Peng. Briefly, class prediction analyses were done on the results obtained for each patient in the study. Patients were divided into two classes following their malignancy: normal class and tumor class. These classes became the training sets by which patients were compared for purposes of classification. The classification algorithms used the expression data from the training sets to make all patient classifications during the tests. Class determination was done based on the clinical data associated to each patient. There were six different classification algorithms used in the studies: compound covariate predictor, diagonal linear discriminant analysis, nearest neighbor predictor (1-NN and 3-NN), nearest centroid predictor and support vector machine predictor. Those analyses permitted the development of a multi-gene classifier to predict the class for a new sample and estimate the misclassification rates. Cross-validation of the class prediction classifiers were done by the leave one-out study and permutation tests (n=2000) were conducted to address significance of the cross-validation test error rate.  
      To evaluate the performances of these ELISA and Western Blot assays in predicting accurately a diagnostic for ovarian cancer, the sensitivity, the specificity, the positive predicting value (PPV) and the negative predicting value (NPV) were determined for multiple protein markers. An ovarian training set data was composed of 113 cases divided as follow: 55 normal and 58 tumors. The results are shown in Table 4.  
                       TABLE 4                       Markers with   Patients with   Percent of       Increased Expression*   Increased Expression**   Total Patients                                            5/5   19   35       4/5   15   27       3/5   7   13       2/5   4   7       1/5   1   2       0/5   9   16       Total   58   100                 *total markers with increased expression in the tumor sample.            **number of patients with tumors showing markers with increased expression.             
 
      A high accuracy was obtained when we compare ELISA protein profile obtained for both ovarian groups. These parameters were determined by two different methods: 1) by visual assessment of the signal from Western blot data, and 2) by analyzing the ELISA data. All results were analyzed by using a Student&#39;s two-tailed t test with the significance level defined as P&lt;0.05 and/or the BRB-array Tools software designed for microarray data analysis.  
       FIGS. 2-10  show the levels of expression for each marker in tumor samples and normal tissue samples.  FIGS. 2-5  show western blot and ELISA assays (scatter plots showing individual patients) that establish that the markers cytokeratin 18, cytokeratin 19, cytokeratin 7, and caveolin-1 show significantly different levels of expression in tumor tissues as compared to normal tissues. Cytokeratin 18, cytokeratin 19, cytokeratin 7 were expressed at higher levels in tumor tissues as compared to normal tissues ( FIGS. 2-4 ). Calveolin-1 was down-regulated in tumor tissues ( FIGS. 5A and 5B ). Western blot analysis also showed that ACRABPII was expressed at far higher levels in tumor tissues as compared to normal tissues ( FIG. 6 ). The fold increase of cytokeratin 18, cytokeratin 19, and cytokeratin 7 expression in tumor tissues over normal tissues was 12-19 times (Table 1). Calveolin-1 had a 2.5 times decreased level of expression (Table 1). Western results for ACRABPII appeared to be similar to cytokeratin 18, cytokeratin 19, and cytokeratin 7.  
      Hepatoma-derived factor, enolase, triosephosphate isomerase, and glyceraldehydes-3-phosphate dehydrogenase also showed increased levels of expression in tumor tissues as compared to normal tissues, but to a lesser extent than the markers described above ( FIGS. 7-10 ). Fold increases in expression were between 1.2 and 2.0 fold. The increases were, therefore, measurable and showed that these markers are also useful in ovarian cancer detection.  
      In addition, vinculin expression was measured to provide an internal control ( FIGS. 11A and 11B ). Vinculin is a ubiquitously expressed protein involved in cytoskeletal attachment to the plasma membrane. Western blot analysis showed that expression in normal subjects and cancer patients was similar ( FIG. 11A ). ELISA analysis confirmed the western results, showing that cancer patients and normal subjects had nearly equal levels of expression ( FIG. 11B ). Therefore, vinculin analysis confirmed that the assays were not identifying artifactual increases in protein expression between tumors and normal tissues.  
      The analyses using six different algorithms to make predictions indicated that the assays were able to discriminate between cancerous tissues and normal tissues. Western blot assays were 78.2% sensitive at identifying an ovarian neoplasm, and 89.7% specific for individuals with no evidence of cancer (i.e., the test did not identify normal tissues as being cancerous). Furthermore, the positive predicting value for western blot assays was 87.8%, indicating that the assay was accurate at identifying ovarian tumors. The negative predicting value was 84.1%, which established that the assay was accurate at properly categorizing normal tissues.  
      The results for ELISA assays were similar. The ELISA assay using the combination of markers was 81.8% sensitive in identifying ovarian tumors. The assay also showed a specificity of 98.3% for individuals with no evidence of cancer. As used herein, the term “specificity” means the ability of a particular marker or combination of markers to properly identify normal tissues without falsely identifying normal tissues as being tumors. The positive predicting value for the ELISA assay was 97.8%. The negative predicting value was 85.1%.  
     Equivalents  
      Those skilled in the art will recognize, or be able to ascertain, using no more than routine experimentation, numerous equivalents to the specific compositions and procedures described herein. Such equivalents are considered to be within the scope of this invention, and are covered by the following claims.