WO2017214189A1

WO2017214189A1 - Methods and compositions for detection and diagnosis of bladder cancer

Info

Publication number: WO2017214189A1
Application number: PCT/US2017/036209
Authority: WO
Inventors: Karen B. Chapman; Ljubomir BUTUROVIC; Liqun QIU; Jennifer L. KIDD; Damjan KRSTAJIC
Original assignee: Oncocyte Corporation
Priority date: 2016-06-06
Filing date: 2017-06-06
Publication date: 2017-12-14

Abstract

The present disclosure provides methods, compositions and kits for the detection and diagnosis of bladder cancer.

Description

METHODS AND COMPOSITIONS FOR DETECTION AND DIAGNOSIS

OF BLADDER CANCER

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to, and the benefit of, U.S. provisional patent application serial number 62/346,546 filed on June 6, 2016, incorporated herein by reference in its entirety.

FIELD

[0002] The present disclosure relates to cancer and the diagnosis and detection of cancer.

BACKGROUND

[0003] Bladder cancer is the fifth most common cancer in the United States and the seventh most common cancer in men worldwide [1,2]. An estimated 74,000 new cases of bladder cancer were diagnosed in the US in 2015 [3]. Urothelial carcinoma (UC) is the most common histological type of bladder cancer, constituting more than 90% of bladder cancers in the Americas, Europe and Asia [4]. It is estimated that there are currently more than 560,000 people living with bladder cancer in the U.S. alone [5]. Since the disease has a recurrence rate of nearly 70% and can progress to invasive, metastatic, and lethal disease, regular surveillance and treatment of recurrent disease from the time of diagnosis for the remainder of a patient's life makes bladder cancer the most costly malignancy on a per patient basis [6].

[0004] The two standard methods for the surveillance of bladder cancer recurrence - microscopic assessment of urinary cytology specimens and bladder cystoscopy - both have inherent drawbacks. Cystoscopy is considered the gold standard for diagnosing bladder cancer and can yield a valuable biopsy, but is invasive and expensive and may be limited in its ability to detect flat lesions or carcinomas in situ [7]. Voided urine cytology is inexpensive, readily available and has a high level of specificity for high-grade tumors, but lacks the desired level of sensitivity [8], particularly with respect to low-grade tumors [9]. Furthermore, up to 20% of urine cytology specimens fall into one of two indeterminate categories [10-13] that require follow-up testing, typically in the form of an invasive cystoscopy procedure. [0005] In addition to the above-mentioned issues with surveillance for bladder cancer recurrence, there is an unmet need for a non-invasive diagnostic test for bladder cancer for patients without a prior history of bladder cancer presenting with hematuria. Although hematuria is the most common symptom of bladder cancer, the majority of patients with hematuria do not have bladder cancer. Reported malignancy rates in this population range from 1.9% [14] to 13% [15,16]. Even though the probability of bladder cancer is relatively low, most patients with hematuria undergo urine cytology or cystoscopy as part of routine diagnostic workup.

[0006] Previously described urine-based bladder cancer markers include Aurora A Kinase (AURKA) mRNA expression [17], cell-free urinary microRNAs [18], survivin [19], telomerase activity [20] and UroVysion™, a FISH-based assay that detects a chromosomal rearrangement common in bladder cancer [21,22]. Low adoption of these biomarker tests may reflect poor performance statistics, insufficient studies demonstrating clinical utility, or lack of specialized equipment and/or training necessary to perform the biomarker assays. Thus, there is an unmet need for a validated, non-invasive bladder cancer diagnostic test with performance that matches or exceeds cystoscopy, particularly with respect to the accurate and sensitive detection of low-grade as well as high-grade tumors. The present disclosure meets this need and other needs in the field.

SUMMARY

[0007] Disclosed herein are, inter alia, simple liquid-biopsy-based tests for bladder cancer. The procedures are non-invasive, consisting of acquisition of a bodily fluid (e.g. voided urine) and do not require sample purification and/or nucleic acid amplification. The methods and compositions disclosed herein accurately discriminate between malignant and benign lesions of the bladder, potentially reducing the need for costly and invasive cystoscopy procedures.

[0008] Embodiments of the disclosure provide methods of diagnosis, prognosis and treatment of cancer. Other embodiments provide compositions relating to the diagnosis, prognosis and treatment of cancer. The methods and compositions of the present disclosure may be used for diagnosis, detection and/or treatment of cancers, for example, bladder cancer, including Transitional Cell Carcinoma (TCC) (also known as urothelial carcinoma) of the bladder and the subtypes of TCC such as papillary carcinoma and flat carcinomas of the bladder, papillary urothelial neoplasm of low malignant potential, squamous cell carcinoma, adenocarcinoma, small- cell carcinoma, and sarcoma of the bladder.

[0009] The methods and compositions disclosed herein are based on the identification of biomarkers that are specific to bladder cancer. Accordingly, panels of biomarkers, whose presence and levels can be measured in patient samples, are provided. The biomarkers provided in the panels disclosed herein represent genes whose products are detected at different (higher or lower) levels in samples (e.g. urine samples) obtained from subjects with bladder cancer vs. subjects with benign bladder pathologies/no cancer.

[0010] In some embodiments, the present disclosure provides a method for detecting bladder cancer in a subject comprising: a) obtaining a sample from a subject (i.e., a "subject sample"); b) measuring expression of one or more markers in the sample from the subject, wherein the one or more markers are selected from any one or more markers encoded by one or more genes identified in Table 3; c) measuring expression of the one or more markers of step b) in a control sample; and d) comparing expression level of the one or more markers in the subject sample relative to the expression level of the same one or more markers in the control sample, wherein a differential expression (overexpression or underexpression) of the one or more markers in the subject sample relative to the control sample indicates the subject has bladder cancer. In certain embodiments, the one or more markers may be gene products (i.e. mRNA or polypeptides) encoded by any one or more genes identified in Table 3. In some embodiments, the one or more markers are mRNA. In some embodiments, the one or more markers are polypeptides.

[0011] In some embodiments, the present disclosure provides a method for detecting bladder cancer in a subject comprising: a) obtaining a sample from a subject (i.e., a "subject sample"); b) measuring expression of a panel of markers in the sample from the subject, wherein the panel of markers are selected from a plurality of markers encoded by a plurality of genes identified in Table 3; c) measuring expression of the panel of markers of step b) in a control sample; and d) comparing expression level of the panel of markers in the subject sample relative to the expression level of the panel of markers in the control sample, wherein a differential expression of the panel of markers indicates the subject has bladder cancer. In certain embodiments, the panel of markers comprises the 171 markers identified in Table 3. In other embodiments, the panel comprises between 2-170 markers selected from Table 3. In other embodiments, the panel comprises between 2-10, between 10-20, between 10-50, or between 10-100 markers selected from Table 3.

[0012] In certain embodiments, the present disclosure provides a method for detecting bladder cancer in a subject comprising: a) obtaining a sample from a subject (i.e., a "subject sample"); b) contacting the subject sample with one or more agents that detect one or more markers identified in Table 3, thereby measuring the level of one or more markers in the subject sample; c) contacting a control sample with one or more agents from b), thereby measuring the level of one or more markers in the control sample; and d) comparing the level of the one or more markers between the sample obtained from the subject and the control sample, wherein a presence of the one or more markers at a higher or lower level in the subject sample relative to the control sample indicates that the subject has bladder cancer.

[0013] In certain embodiments, the present disclosure provides a method for detecting bladder cancer in a subject comprising: a) obtaining a sample from a subject (i.e., a "subject sample"); b) contacting the subject sample with one or more agents that bind to one or more markers identified in Table 3, and measuring binding to determine the level of the one or more markers in the subject sample; c) contacting a control sample with the one or more agents from b), and measuring binding to determine the level of the one or more markers in the control sample; and d) comparing the level of the one or more markers between the subject sample and the control sample, wherein a presence of the one or more markers at a higher or lower level in the subject sample relative to the control sample indicates that the subject has bladder cancer. In certain embodiments, the one or more markers are polynucleotides (e.g. mRNA or cDNA). In other embodiments, the one or more markers are polypeptides.

[0014] In addition to a comparison between a subject and control sample, differential expression (i.e., overexpression or underexpression) of the bladder cancer markers identified infra can be determined based upon a cutoff or reference value, wherein a value higher or lower than the cutoff or reference value indicates the subject has bladder cancer. In some embodiments, whether the subject has bladder cancer can be determined by measuring the expression of the upregulated genes vs. downregulated genes within a single sample, followed by obtaining a simple ratio of: i)the sum total of the expression values of the upregulated genes within a single sample, to ii) the sum total of the expression values of the downregulated genes within the single sample, or an inverse ratio thereof, wherein a ratio larger or smaller than a selected cutoff value indicates the subject has bladder cancer.

[0015] In some embodiments, the present disclosure provides a method for detecting bladder cancer in a subject comprising: a) obtaining a sample from a subject (i.e., a "subject sample"); b) measuring expression of one or more markers in the subject sample, wherein the one or more markers are selected from any one or more markers encoded by one or more genes identified in Table 3; and c) comparing the expression level of the one or more markers in the subject sample relative to a corresponding reference or cutoff value for the same one or more markers, wherein differential expression (overexpression or underexpression) of the one or more markers in the subject sample relative to the corresponding reference or cutoff values indicates the subject has bladder cancer.

[0016] In some embodiments, the present disclosure provides a method for detecting bladder cancer in a subject comprising: a) obtaining a sample from a subject (i.e., a "subject sample"); b) measuring expression of a panel of markers in the subject sample, wherein the panel of markers are selected from a plurality of markers encoded by a plurality of genes identified in Table 3; and c) comparing the expression levels of the panel of markers in the subject sample relative to corresponding reference or cutoff values for the same panel of markers, wherein differential expression (overexpression or underexpression) of the panel of markers in the subject sample relative to the corresponding reference or cutoff values indicates the subject has bladder cancer. In certain embodiments, the panel of markers comprises the 171 markers identified in Table 3. In other embodiments, the panel comprises between 2-170 markers selected from Table 3. In other embodiments, the panel comprises between 2-10, between 10-20, between 10-50 or between 10-100 markers selected from Table 3.

[0017] In certain embodiments, measuring the expression level of a gene is accomplished by measuring levels of the nucleic acid product of the gene (e.g., mRNA, cDNA). Such can be achieved using agents that specifically bind to the nucleic acid of interest (for example, labeled nucleic acid probes), and testing for binding of the agent to a nucleic acid in the sample. Nucleic acid probes can be labeled using any label known in the art, including but not limited to radioactive, colorimetric, enzymatic, fluorometric and magnetic labels.

[0018] In certain embodiments, measuring the expression level of a gene is accomplished by measuring levels of the protein product of the gene. Such can be achieved using agents that specifically bind to the protein of interest, for example, antibodies (e.g. , monoclonal antibodies, humanized antibodies) or aptamers (e.g., nucleic acid aptamers, peptide aptamers) and testing for binding of the agent to a polypeptide in the sample.

[0019] With regard to the embodiments described in the preceding paragraphs, the sample may be any sample as described infra, for example, a bodily fluid, such as urine, blood, plasma or serum. The sample may be a cellular sample or the extract of a cellular sample. The sample may be a tissue sample. Nucleic acids and/or proteins may be isolated from the sample. Nucleic acids such as RNA (e.g. , mRNA) may be transcribed into cDNA. The agent may be one or more molecules that bind specifically to one or more proteins expressed by the cancer cell, or the agent may be one or more molecules that bind specifically to one or more nucleic acids expressed by the cancer cell. For example, the agent may be one or more nucleic acids that hybridize to a nucleic acid expressed by the cancer cell. The agent may be a protein (e.g. , an antibody), or an aptamer, that binds specifically to the protein expressed by one of the marker genes identified infra. The nucleic acid expressed by the cancer cell may be an RNA molecule, e.g. , an mRNA.

[0020] In certain embodiments the present disclosure provides compositions of matter useful in distinguishing a bladder cancer cell from a non-cancerous cell comprising one or more molecules that specifically bind to a molecule expressed at higher levels by a bladder cancer cell compared to a non-cancer cell. In certain embodiments, the composition comprises a protein or an aptamer that binds to one or more molecules expressed by the bladder cancer cell at higher levels compared to the non-cancer cell. In certain embodiments, the protein or an aptamer binds to one or more molecules present at higher levels in the cancerous sample as compared to the benign sample. In other embodiments, the protein or an aptamer binds to one or more molecules present at higher levels in the benign sample as compared to the cancerous sample. In certain embodiments, the composition comprises a nucleic acid that binds to one or more molecules expressed by the bladder cancer cell at higher levels compared to the non-cancer cell. In certain embodiments, the nucleic acid binds to one or more molecules present at higher levels in the cancerous sample as compared to the benign sample. In other embodiments, the nucleic acid binds to one or more molecules present at higher levels in the benign sample as compared to the cancerous sample. [0021] In some embodiments, the present disclosure provides a composition of matter comprising one or more proteins, such as an antibody, or one or more aptamers, that specifically binds to a bladder cancer marker chosen from any one or more of the markers listed in Table 3. In some embodiments, the marker may be expressed by the bladder cancer cell either at a level that is higher or lower than the level of the same marker expressed by a non-cancerous cell. In other embodiments, the marker may be present at elevated (or alternatively, reduced) levels in biological fluids obtained from a subject, such as urine, blood, plasma or serum.

[0022] In further embodiments the present disclosure provides a composition of matter comprising a plurality of reagents, such as a plurality of oligonucleotide probes, or a plurality of antibodies, or a plurality of aptamers, that specifically bind to a panel of markers wherein the panel of markers comprises two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, sixteen or more, seventeen or more, eighteen or more, nineteen or more, twenty or more, twenty-one or more, twenty-two or more, twenty-three or more, twenty-four or more, twenty-five or more, or twenty- six or more molecules (e.g., mRNA or proteins) encoded by the genes chosen from the genes listed in Table 3.

[0023] In still further embodiments the present disclosure provides a method of determining if a bladder cancer in a subject is advancing comprising a) measuring the expression level of one or more markers associated with bladder cancer at a first time point; b) measuring the expression level of the one or more markers measured in a) at a second time point, wherein the second time point is subsequent to the first time point; and c) comparing the expression level measured in a) and b), wherein an increase or decrease in the expression level of the one or more markers in b) compared to a) indicates that the subject' s bladder cancer is advancing. Suitable markers include those markers encoded by any one or more genes listed in Table 3.

[0024] In some embodiments, the present disclosure provides a method of determining whether a subject has high-grade urothelial carcinoma, comprising: a) obtaining a sample from a subject (i.e. , a "subject sample"); b) contacting the sample from the subject with one or more agents that detect one or more markers differentially expressed in high-grade urothelial carcinoma; c) contacting a control sample with one or more agents from b); and d) comparing the expression levels of the one or more markers between the sample obtained from the subject and the control sample, wherein a differential expression (i.e., overexpression or underexpression) of the one or more markers in the subject sample relative to the control sample indicates that the subject has high-grade urothelial carcinoma. Suitable markers include gene products (i.e. , mRNAs and/or polypeptides) corresponding to one or more markers listed in Table 3.

[0025] In some embodiments, the present disclosure provides a method of determining whether a subject has low-grade urothelial carcinoma, comprising a) obtaining a sample from a subject (i.e., a "subject sample"); b) contacting the sample from the subject with one or more agents that detect one or more markers differentially expressed in low-grade urothelial carcinoma; c) contacting a control sample with one or more agents from b); and d) comparing the expression levels of the one or more markers between the sample obtained from the subject and the control sample, wherein a differential expression (i.e., overexpression or underexpression) of the one or more markers in the subject sample relative to the control sample indicates that the subject has low-grade urothelial carcinoma. Suitable markers include gene products (i.e., mRNAs and/or polypeptides) corresponding to one or more markers listed in Table 3.

[0026] In yet other embodiments the present disclosure provides a method of eliciting an immune response to a bladder cancer cell comprising contacting a subject with a protein or protein fragment that is expressed by a bladder cancer cell thereby eliciting an immune response to the bladder cancer cell. As an example, the subject may be contacted intravenously or intramuscularly with protein or protein fragment.

[0027] In yet other embodiments present disclosure provides a kit for detecting bladder cancer cells in a sample. The kit may comprise one or more agents that detect expression of any of the cancer associated markers (e.g. , polypeptides, nucleic acids) disclosed infra. The agents may bind to one or more of the cancer associated markers disclosed infra. The kit may include agents that are proteins and/or nucleic acids for example. In one embodiment, the kit provides a plurality of agents.

[0028] In other embodiments, the present disclosure provides a kit for detection of bladder cancer in a sample obtained from a subject. The kit may comprise one or more agents that bind specifically to one or more of the markers encoded for by one or more of the genes listed in Table 3. The kit may comprise one or more containers and instructions for determining if the sample is positive for cancer. The kit may optionally contain one or more multiwell plates, a detectable substance such as a dye, a radioactively labeled molecule, a chemiluminescently labeled molecule and the like. The detectible substance may be linked to the agent that specifically binds to a molecule expressed by a bladder cancer cell. The kit may further contain a positive control (e.g., one or more bladder cancer cells; or specific known quantities of the molecule expressed by the bladder cancer cell) and/or a negative control (e.g. , a tissue or cell sample that is noncancerous).

BRIEF DESCRIPTION OF THE DRAWINGS

[0029] For a fuller understanding of the nature and advantages of the present invention, reference should be had to the following detailed description taken in connection with the accompanying drawings, in which:

[0030] FIGURE 1 is a schematic of NanoString® bladder cancer assay from urine sediment lysates using the methods and markers of the present disclosure.

[0031] FIGURE 2 shows Small Vector Machine (SVM) model of 133 Lasso markers in the microarray dataset, yielding an AUROC of 0.88.

[0032] FIGURE 3A shows the best performing model on the NanoString data set, SVM with RBF kernel, achieving an AUROC of 0.85. A distinct model, defined by a clinically favorable criterion of maximum specificity for sensitivity at least 90%, is shown, using 27 probes (sensitivity = 90.1%, specificity = 54%).

[0033] FIGURE 3B depicts the accuracy of the model described in FIG. 3A for the hematuria and recurrence surveillance cohorts. For both the hematuria and recurrence cohorts, the accuracy for detecting high-grade lesions was 100%. The accuracy for the detection of low- grade lesions was 77% for the hematuria cohort and 75% for the recurrence cohort.

[0034] FIGURE 4 is a schematic illustrating development of sequential classifiers distinguishing between high grade and low grade urothelial carcinoma.

[0035] FIGURES 5A-5B and FIGURES 6A-6B depict results using the four-classifier strategy stratifying patient cohort and tumor grade.

[0036] FIGURE 5A: Hematuria high-grade malignant versus low grade malignant, AUROC = 0.93.

[0037] FIGURE 5B : Hematuria low-grade versus benign, AUROC = 0.81.

[0038] FIGURE 6A: Recurrence high-grade malignant versus low grade malignant plus benign, AUROC = 0.81.

[0039] FIGURE 6B: Recurrence low-grade malignant versus benign, AUROC = 0.64. DETAILED DESCRIPTION

[0040] Before the compositions and methods of the present disclosure are described, it is to be understood that the invention or inventions disclosed herein are not limited to the particular processes, compositions, or methodologies described, as these may vary. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only, and is not intended to limit the scope of the present invention which will be limited only by the appended claims. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the preferred methods, devices, and materials are now described. Nothing herein is to be construed as an admission that the invention is not entitled to antedate such disclosure by virtue of prior invention.

[0041] As used herein, the singular forms "a," "an," and "the" include plural reference unless the context clearly dictates otherwise. Thus, for example, reference to a "therapeutic" is a reference to one or more therapeutics and equivalents thereof known to those skilled in the art, and so forth.

[0042] As used herein, the term "about" means plus or minus 10% of the numerical value of the number with which it is being used. Therefore, about 50% means in the range of 45% to 55%.

[0043] "Administering," when used in conjunction with a therapeutic, means to administer a therapeutic directly into or onto a target tissue or to administer a therapeutic to a patient whereby the therapeutic treats the tissue to which it is targeted. Thus, as used herein, the term "administering," when used in conjunction with a therapeutic, can include, but is not limited to, providing the therapeutic into or onto the target tissue; providing the therapeutic systemically to a patient by, e.g., intravenous injection whereby the therapeutic reaches the target tissue; providing the therapeutic in the form of the encoding sequence thereof to the target tissue (e.g., by so-called gene-therapy techniques). "Administering" a composition may be accomplished by oral administration, intravenous injection, intraperitoneal injection, intramuscular injection, subcutaneous injection, transdermal diffusion or electrophoresis, local injection, extended release delivery devices including locally implanted extended release devices such as bioerodible or reservoir-based implants, as protein therapeutics or as nucleic acid therapeutic via gene therapy vectors, topical administration, or by any of these methods in combination with other known techniques. Such combination techniques include, without limitation, heating, radiation and ultrasound.

[0044] "Agent" as used herein refers to a molecule that specifically binds to a cancer associated sequence or a molecule encoded by a cancer associated sequence or a receptor that binds to a molecule encoded by a cancer associated sequence. Examples of agents include nucleic acid molecules (such as DNA), proteins (such as antibodies) and aptamers. The agent may be linked with a label or detectible substance as described infra. The agent may be linked with a therapeutic agent or a toxin.

[0045] The term "amplify" as used herein means creating an amplification product which may include, for example, additional target molecules, or target-like molecules or molecules complementary to the target molecule, which molecules are created by virtue of the presence of the target molecule in the sample. In the situation where the target is a nucleic acid, an amplification product can be made enzymatically with DNA or RNA polymerases or reverse transcriptases, or any combination thereof.

[0046] The terms "animal," "patient" or "subject" as used herein include, but are not limited to, humans, non-human primates and non-human vertebrates such as wild, domestic and farm animals including any mammal, such as cats, dogs, cows, sheep, pigs, horses, rabbits, rodents such as mice and rats. In some embodiments, the term "subject," "patient" or "animal" refers to a male. In some embodiments, the term "subject," "patient" or "animal" refers to a female.

[0047] The term "antibody", as used herein, means an immunoglobulin or a part thereof, and encompasses any polypeptide comprising an antigen binding site regardless of the source, method of production, or other characteristics. The term includes for example, polyclonal, monoclonal, monospecific, polyspecific, humanized, single chain, chimeric, synthetic, recombinant, hybrid, mutated, and CDR grafted antibodies. A part of an antibody can include any fragment which can bind antigen, for example, an Fab, F (ab')2, Fv, scFv.

[0048] The term "biological sources" as used herein refers to the sources from which the target polynucleotides or proteins or peptide fragments may be derived. The source can be of any form of "sample" as described infra, including but not limited to, cell, tissue or fluid. "Different biological sources" can refer to different cells/tissues/organs of the same individual, or cells/tissues/organs from different individuals of the same species, or cells/tissues/organs from different species.

[0049] The term "capture reagent" refers to a reagent, for example an antibody or antigen binding protein, capable of binding a target molecule or analyte to be detected in a sample.

[0050] The term "gene expression result" refers to a qualitative and/or quantitative result regarding the expression of a gene or gene product. Any method known in the art may be used to quantitate a gene expression result. The gene expression result can be an amount or copy number of the gene, the RNA encoded by the gene, the mRNA encoded by the gene, the protein product encoded by the gene, or any combination thereof. The gene expression result can also be normalized or compared to a standard. The gene expression result can be used, for example, to determine if a gene is expressed, overexpressed, or differentially expressed in two or more samples by comparing the gene expression results from 2 or more samples or one or more samples with a standard or a control.

[0051] The term "homology," as used herein, refers to a degree of complementarity. There may be partial homology or complete homology. The word "identity" may substitute for the word "homology." A partially complementary nucleic acid sequence that at least partially inhibits an identical sequence from hybridizing to a target nucleic acid is referred to as "substantially homologous." The inhibition of hybridization of the completely complementary nucleic acid sequence to the target sequence may be examined using a hybridization assay (Southern or northern blot, solution hybridization, and the like) under conditions of reduced stringency. A substantially homologous sequence or hybridization probe will compete for and inhibit the binding of a completely homologous sequence to the target sequence under conditions of reduced stringency. This is not to say that conditions of reduced stringency are such that nonspecific binding is permitted, as reduced stringency conditions require that the binding of two sequences to one another be a specific (i.e., a selective) interaction. The absence of non-specific binding may be tested by the use of a second target sequence which lacks even a partial degree of complementarity (e.g., less than about 30% homology or identity). In the absence of non-specific binding, the substantially homologous sequence or probe will not hybridize to the second non- complementary target sequence.

[0052] As used herein, the term "hybridization" or "hybridizing" refers to hydrogen bonding, which may be Watson-Crick, Hoogsteen or reversed Hoogsteen hydrogen bonding between complementary nucleoside or nucleotide bases. For example, adenine and thymine are complementary nucleobases which pair through the formation of hydrogen bonds. "Complementary," as used herein in reference to nucleic acid molecules, refers to the capacity for precise pairing between two nucleotides. For example, if a nucleotide at a certain position of an oligonucleotide is capable of hydrogen bonding with a nucleotide at the same position of a DNA or RNA molecule, then the oligonucleotide and the DNA or RNA are considered to be complementary to each other at that position. The oligonucleotide and the DNA or RNA are complementary to each other when a sufficient number of corresponding positions in each molecule are occupied by nucleotides which can hydrogen bond with each other. Thus, "specifically hybridizable" and "complementary" are terms which are used to indicate a sufficient degree of complementarity or precise pairing such that stable and specific binding occurs between the oligonucleotide and the DNA or RNA target. It is understood in the art that a nucleic acid sequence need not be 100% complementary to that of its target nucleic acid to be specifically hybridizable. A nucleic acid compound is specifically hybridizable when there is binding of the molecule to the target, and there is a sufficient degree of complementarity to avoid non-specific binding of the molecule to non-target sequences under conditions in which specific binding is desired, i.e., under physiological conditions in the case of in vivo assays or therapeutic treatment, and in the case of in vitro assays, under conditions in which the assays are performed.

[0053] The term "inhibiting" includes the administration of a compound of the present disclosure to prevent the onset of the symptoms, alleviating the symptoms, or eliminating the disease, condition or disorder. The term "inhibiting" may also refer to lowering the expression level of gene, such as a gene encoding a cancer associated sequence. Expression level of RNA and/or protein may be lowered.

[0054] The terms "label" and/or "detectable substance" refer to a composition capable of producing a detectable signal indicative of the presence of the target polynucleotide or a polypeptide or protein in an assay sample. Suitable labels include radioisotopes, nucleotide chromophores, enzymes, substrates, fluorescent molecules, chemiluminescent moieties, magnetic particles, bioluminescent moieties, and the like. As such, a label is any composition detectable by a device or method, such as, but not limited to, a spectroscopic, photochemical, biochemical, immunochemical, electrical, optical, chemical detection device or any other appropriate device. In some embodiments, the label may be detectable visually without the aid of a device. The term "label" is used to refer to any chemical group or moiety having a detectable physical property or any compound capable of causing a chemical group or moiety to exhibit a detectable physical property, such as an enzyme that catalyzes conversion of a substrate into a detectable product. The term "label" also encompasses compounds that inhibit the expression of a particular physical property. The label may also be a compound that is a member of a binding pair, the other member of which bears a detectable physical property.

[0055] A "microarray" is a linear or two-dimensional array of, for example, discrete regions, each having a defined area, each optionally containing a polynucleotide of defined sequence, formed on the surface of a solid support. The density of the discrete regions on a microarray is determined by the total numbers of target polynucleotides to be detected on the surface of a single solid phase support, preferably at least about 50/cm² more preferably at least about 100/cm², even more preferably at least about 500/cm², and still more preferably at least about 1,000/cm². As used herein, a DNA microarray is an array of oligonucleotide primers placed on a chip or other surfaces used to identify, amplify, detect, or clone target polynucleotides. Since the position of each particular group of oligonucleotides in the array is known, the identities of the target polynucleotides can be determined based on their binding to a particular position in the microarray.

[0056] As used herein, the term "naturally occurring" refers to sequences or structures that may be in a form normally found in nature, or to phenomena that inevitably occur in nature in all circumstances. "Naturally occurring" may include sequences in a form normally found in any animal.

[0057] The use of "nucleic acid," "polynucleotide" or "oligonucleotide" or equivalents herein means at least two nucleotides covalently linked together. In some embodiments, an oligonucleotide is an oligomer of 6, 8, 10, 12, 20, 30 or up to 100 nucleotides. In some embodiments, an oligonucleotide is an oligomer of at least 6, 8, 10, 12, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 300, 400, or 500 nucleotides. A "polynucleotide" or "oligonucleotide" may comprise DNA, RNA, PNA (peptide nucleic acid) or a polymer of nucleotides linked by phosphodiester and/or any alternate bonds.

[0058] As used herein, the term "optional" or "optionally" refers to embodiments where the subsequently described structure, event or circumstance may or may not occur, and that the description includes instances where the event occurs and instances where it does not. [0059] The phrases "percent homology," "% homology," "percent identity," or "% identity" refer to the percentage of sequence similarity found in a comparison of two or more amino acid or nucleic acid sequences. Percent identity can be determined electronically, e.g., by using the MEGALIGN program (LASERGENE software package, DNASTAR). The MEGALIGN program can create alignments between two or more sequences according to different methods, e.g., the Clustal Method. (Higgins, D. G. and P. M. Sharp (1988) Gene 73:237- 244.) The Clustal algorithm groups sequences into clusters by examining the distances between all pairs. The clusters are aligned pairwise and then in groups. The percentage similarity between two amino acid sequences, e.g., sequence A and sequence B, is calculated by dividing the length of sequence A, minus the number of gap residues in sequence A, minus the number of gap residues in sequence B, into the sum of the residue matches between sequence A and sequence B, times one hundred. Gaps of low or of no homology between the two amino acid sequences are not included in determining percentage similarity. Percent identity between nucleic acid sequences can also be calculated by the Clustal Method, or by other methods known in the art, such as the Jotun Hein Method. (See, e.g., Hein, J. (1990) Methods Enzymol. 183:626-645.) Identity between sequences can also be determined by other methods known in the art, e.g., by varying hybridization conditions.

[0060] By "pharmaceutically acceptable", it is meant the carrier, diluent or excipient must be compatible with the other ingredients of the formulation and not deleterious to the recipient thereof.

[0061] "Recombinant protein," as used herein, means a protein made using recombinant techniques, for example, but not limited to, through the expression of a recombinant nucleic acid as described infra. A recombinant protein may be distinguished from naturally occurring protein by at least one or more characteristics. For example, the protein may be isolated or purified away from some or all of the proteins and compounds with which it is normally associated in its wild type host, and thus may be substantially pure. For example, an isolated protein is unaccompanied by at least some of the material with which it is normally associated in its natural state, preferably constituting at least about 0.5%, more preferably at least about 5% by weight of the total protein in a given sample. A substantially pure protein comprises about 50-75%, about 80%, or about 90%. In some embodiments, a substantially pure protein comprises about 80-99%, 85-99%, 90- 99%, 95-99%, or 97-99% by weight of the total protein. A recombinant protein can also include the production of a cancer associated protein from one organism (e.g. human) in a different organism (e.g. yeast, E. coli, or the like) or host cell. Alternatively, the protein may be made at a significantly higher concentration than is normally seen, through the use of an inducible promoter or high expression promoter, such that the protein is made at increased concentration levels. Alternatively, the protein may be in a form not normally found in nature, as in the addition of an epitope tag or amino acid substitutions, insertions and deletions, as discussed herein. Recombinant proteins may also differ from naturally-occurring proteins with respect to one or more post- translational modifications such as, for example, phosphorylation, glycosylation or ubiquitination.

[0062] The abbreviation "ROC" as used herein refers to "receiver operating characteristic". A receiver operating characteristic graph is used in the statistical analysis of binary classifiers. The ROC curve is created by plotting the sensitivity (true positive rate) versus 1- specificity (false positive rate). The area under the ROC curve ("AUROC") is the probability that a classifier will rank a randomly chosen positive instance higher than a randomly chosen negative one. In simple terms, the AUROC provides a means of reducing classifier ROC performance to a single value. Random classification yields an AUROC of 0.5 whereas perfect classification (no classification errors) yields an AUROC of 1.

[0063] As used herein, the term "sample" refers to composition that is being tested or treated with a reagent, agent, capture reagent, binding partner and the like. Samples may be obtained from subjects. In some embodiments, the sample may be blood, plasma, serum, urine or any combination thereof. A sample may be derived from blood, plasma, serum, urine or any combination thereof. Other typical samples include, but are not limited to, any bodily fluid obtained from a mammalian subject, tissue biopsy, sputum, lymphatic fluid, blood cells (e.g., peripheral blood mononuclear cells), tissue or fine needle biopsy samples, peritoneal fluid, colostrum, breast milk, fetal fluid, fecal material, tears, pleural fluid, or cells therefrom. The sample may be processed in some manner before being used in a method described herein, for example a particular component to be analyzed or tested according to any of the methods described infra. One or more molecules (e.g. , nucleic acids, proteins) may be isolated from a sample.

[0064] The terms "specific binding," "specifically binds," and the like, refer to instances where two or more molecules form a complex that is measurable under physiologic or assay conditions and is selective. An antibody or antigen binding protein or other molecule is said to "specifically bind" to a protein, antigen, or epitope if, under appropriately selected conditions, such binding is not substantially inhibited, while at the same time non-specific binding is inhibited. Specific binding is characterized by a high affinity and is selective for the compound, protein, epitope, or antigen. Nonspecific binding usually has a low affinity. Examples of specific binding include the binding of enzyme and substrate, an antibody and its antigenic epitope, a cellular signaling molecule and its respective cell receptor.

[0065] As used herein, a polynucleotide "derived from" a designated sequence refers to a polynucleotide sequence which is comprised of a sequence of approximately at least about 6 nucleotides, preferably at least about 8 nucleotides, more preferably at least about 10-12 nucleotides, and even more preferably at least about 15-20 nucleotides corresponding to a region of the designated nucleotide sequence. "Corresponding" means homologous to or complementary to the designated sequence. Preferably, the sequence of the region from which the polynucleotide is derived is homologous to or complementary to a sequence that is unique to a cancer associated gene.

[0066] As used herein, the term "tag," "sequence tag" or "primer tag sequence" refers to an oligonucleotide with a specific nucleic acid sequence that serves to identify a batch of polynucleotides bearing such tags therein. Polynucleotides from the same biological source are covalently tagged with a specific sequence tag so that in subsequent analysis the polynucleotide can be identified according to its source of origin. The sequence tags also serve as primers for nucleic acid amplification reactions.

[0067] The term "support" refers to conventional supports such as beads, particles, dipsticks, fibers, filters, membranes, and silane or silicate supports such as glass slides.

[0068] As used herein, the term "therapeutic" or "therapeutic agent" means an agent that can be used to treat, combat, ameliorate, prevent or improve an unwanted condition or disease of a patient. In part, embodiments of the present disclosure are directed to the treatment of cancer or the decrease in proliferation of cells. In some embodiments, the term "therapeutic" or "therapeutic agent" may refer to any molecule that associates with or affects the target marker or cancer associated sequence disclosed infra, its expression or its function. In various embodiments, such therapeutics may include molecules such as, for example, a therapeutic cell, a therapeutic peptide, a therapeutic gene, a therapeutic compound, or the like, that associates with or affects the target marker or cancer associated sequence disclosed infra, its expression or its function. [0069] A "therapeutically effective amount" or "effective amount" of a composition is a predetermined amount calculated to achieve the desired effect, i.e., to inhibit, block, or reverse the activation, migration, metastasis, or proliferation of cells. In some embodiments, the effective amount is a prophylactic amount. In some embodiments, the effective amount is an amount used to medically treat the disease or condition. The specific dose of a composition administered according to this invention to obtain therapeutic and/or prophylactic effects will, of course, be determined by the particular circumstances surrounding the case, including, for example, the composition administered, the route of administration, and the condition being treated. It will be understood that the effective amount administered will be determined by the physician in the light of the relevant circumstances including the condition to be treated, the choice of composition to be administered, and the chosen route of administration. A therapeutically effective amount of composition of this invention is typically an amount such that when it is administered in a physiologically tolerable excipient composition, it is sufficient to achieve an effective systemic concentration or local concentration in the targeted tissue.

[0070] The terms "treat," "treated," or "treating" as used herein can refer to both therapeutic treatment or prophylactic or preventative measures, wherein the object is to prevent or slow down (lessen) an undesired physiological condition, symptom, disorder or disease, or to obtain beneficial or desired clinical results. In some embodiments, the term may refer to both treating and preventing. For the purposes of this disclosure, beneficial or desired clinical results include, but are not limited to, alleviation of symptoms; diminishment of the extent of the condition, disorder or disease; stabilization (i.e., not worsening) of the state of the condition, disorder or disease; delay in onset or slowing of the progression of the condition, disorder or disease; amelioration of the condition, disorder or disease state; and remission (whether partial or total), whether detectable or undetectable, or enhancement or improvement of the condition, disorder or disease. Treatment includes eliciting a clinically significant response without excessive levels of side effects. Treatment also includes prolonging survival as compared to expected survival if not receiving treatment.

[0071] The term "tissue" refers to any aggregation of similarly specialized cells that are united in the performance of a particular function.

Cancer Associated Sequences [0072] In some embodiments, the present disclosure provides for nucleic acid and protein sequences that are associated with cancer, herein termed "cancer associated" or "CA" sequences. Some embodiments described herein are directed to the use of cancer associated sequences for diagnosis and treatment of bladder cancer. In some embodiments, the cancer associated sequence is selected from any one or more genes (or the complement thereof) listed in Table 3. In some embodiments, these cancer associated sequences may be associated with bladder cancer, including, without limitation, Transitional Cell Carcinoma (TCC) (also known as urothelial carcinoma) of the bladder and the subtypes of TCC such as papillary carcinoma and flat carcinomas of the bladder, papillary urothelial neoplasm of low malignant potential, squamous cell carcinoma, adenocarcinoma, small-cell carcinoma, and sarcoma of the bladder. However, as will be appreciated by those skilled in the art, sequences that are identified in one type of cancer may have a strong likelihood of being involved in other types of cancers as well. Thus, while the sequences outlined herein may be initially identified as correlated with one or more types of cancers, they may also be found in other types of cancers as well. The method of diagnosing may comprise measuring the level of expression of a cancer associated marker disclosed herein. The method may further comprise comparing the expression level of the cancer associated sequence with a standard and/or a control. The standard may be from a sample known to contain bladder cancer cells. The control may include known bladder cancer cells and/or non-cancerous cells, such as non-cancer cells derived from bladder tissue.

[0073] Cancer associated sequences may include those that are up-regulated (i.e., expressed at a higher level), as well as those that are down-regulated (i.e., expressed at a lower level), in cancers. Cancer associated sequences can also include sequences that have been altered (i.e., translocations, truncated sequences or sequences with substitutions, deletions or insertions, including, but not limited to, point mutations) and show either the same expression profile or an altered profile. In some embodiments, the cancer associated sequences are from humans; however, as will be appreciated by those in the art, cancer associated sequences from other organisms may be useful in animal models of disease and drug evaluation; thus, other cancer associated sequences may be useful, including those obtained from any subject, such as, without limitation, sequences from vertebrates, including mammals, such as rodents (rats, mice, hamsters, guinea pigs, etc.), primates, and farm animals (including sheep, goats, pigs, cows, horses, etc.). Cancer associated sequences from other organisms may be obtained using the techniques outlined herein. [0074] Examples of cancer associated sequences include the nucleic acid and amino acid sequences encoded by the genes listed in Table 3.

[0075] In some embodiments, the cancer associated sequences are nucleic acids. As will be appreciated by those skilled in the art and as described herein, cancer associated sequences of embodiments herein may be useful in a variety of applications including diagnostic applications to detect nucleic acids or their expression levels in a subject, therapeutic applications or a combination thereof. Further, the cancer associated sequences of embodiments herein may be used in screening applications; for example, generation of biochips (e.g., microarrays) comprising nucleic acid probes that specifically bind to the cancer associated sequences.

[0076] A nucleic acid of the present disclosure may include phosphodiester bonds, although in some cases, as outlined below (for example, in antisense applications or when a nucleic acid is a candidate drug agent), nucleic acid analogues may have alternate backbones, comprising, for example, phosphoramidate (Beaucage et al., Tetrahedron 49(10): 1925 (1993) and references therein); Letsinger, J. Org. Chem. 35:3800 (1970); Sprinzl et al., Eur. J. Biochem. 81 :579 (1977); Letsinger et al., Nucl. Acids Res. 14:3487 (1986); Sawai et al, Chem. Lett. 805 (1984), Letsinger et al., J. Am. Chem. Soc. 110:4470 (1988); and Pauwels et al., Chemica Scripta 26: 141 91986)); phosphorothioate (Mag et al., Nucleic Acids Res. 19: 1437 (1991) and U.S. Pat. No. 5,644,048); phosphorodithioate (Briu et al., J. Am. Chem. Soc. 111 :2321 (1989); O-methylphosphoroamidite linkages (see Eckstein, Oligonucleotides and Analogues: A Practical Approach, Oxford University Press), and/or peptide nucleic acid backbones and linkages (see Egholm, J. Am. Chem. Soc. 114: 1895 (1992); Meier et al., Chem. Int. Ed. Engl. 31 : 1008 (1992); Nielsen, Nature, 365:566 (1993); Carlsson et al., Nature 380:207 (1996),). Other nucleic acid analogues include those with positively-charged backbones (Denpcy et al., Proc. Natl. Acad. Sci. USA 92:6097 (1995); non- ionic backbones (U.S. Pat. Nos. 5,386,023, 5,637,684, 5,602,240, 5,216,141 and 4,469,863; Kiedrowshi et al., Angew. Chem. Intl. Ed. English 30:423 (1991); Letsinger et al., J. Am. Chem. Soc. 110:4470 (1988); Letsinger et al., Nucleoside & Nucleotide 13: 1597 (1994); Chapters 2 and 3, ASC Symposium Series 580, "Carbohydrate Modifications in Antisense Research", Ed. Y. S. Sanghui and P. Dan Cook; Mesmaeker et al., Bioorganic & Medicinal Chem. Lett. 4:395 (1994); Jeffs et al., J. Biomolecular NMR 34: 17 (1994); Tetrahedron Lett. 37:743 (1996)) and non-ribose backbones, including those described in U.S. Pat. Nos. 5,235,033 and 5,034,506, and Chapters 6 and 7, ASC Symposium Series 580, "Carbohydrate Modifications in Antisense Research", Ed. Y. S. Sanghui and P. Dan Cook. Nucleic acids containing one or more carbocyclic sugars are also included within one definition of nucleic acids (see Jenkins et al., Chem. Soc. Rev. (1995) pp. 169-176). Several nucleic acid analogues are described in Rawls, C & E News Jun. 2, 1997 page 35. These modifications of the ribose-phosphate backbone may be made for a variety of reasons, for example to increase the stability and half-life of such molecules in physiological environments for use in anti-sense applications or as probes on a biochip.

[0077] As will be appreciated by those skilled in the art, such nucleic acid analogues may be used in some embodiments of the present disclosure. In addition, mixtures of naturally occurring nucleic acids and nucleic acid analogues can be made; alternatively, mixtures of different nucleic acid analogues, and mixtures of naturally occurring nucleic acids and analogues may be made.

[0078] In some embodiments, the nucleic acids may be single stranded or double stranded or may contain portions of both double stranded or single stranded sequence. As will be appreciated by those skilled in the art, the depiction of a single strand also defines the sequence of the other (complementary) strand; thus the sequences described herein also includes the complement of the sequence. The nucleic acid may be DNA, both genomic and cDNA, RNA, or a hybrid, where the nucleic acid contains any combination of deoxyribo- and ribo-nucleotides, and any combination of bases, including uracil, adenine, thymine, cytosine, guanine, inosine, xanthine, hypoxanthine, isocytosine, isoguanine, etc. As used herein, the term "nucleoside" includes nucleotides and nucleoside and nucleotide analogs, and modified nucleosides such as amino- modified nucleosides. In addition, "nucleoside" includes non-naturally occurring analogue structures. Thus, for example, the subject units of a peptide nucleic acid, each containing a base, are referred to herein as a nucleoside.

[0079] In some embodiments, cancer associated sequences may include both nucleic acid and amino acid sequences. In some embodiments, the cancer associated sequences may include sequences having at least about 60% homology with the disclosed sequences. In some embodiments, the cancer associated sequences may have at least about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95%, about 97%, about 99%, about 99.8% homology with the disclosed sequences. In some embodiments, the cancer associated sequences may be "mutant nucleic acids". As used herein, "mutant nucleic acids" refers to, for example, deletion mutants, insertions, point mutations, substitutions, and translocations. [0080] In some embodiments, the cancer associated sequences may be recombinant nucleic acids. The term "recombinant nucleic acid," as used herein, refers to nucleic acid molecules, originally formed in vitro, in general, by the manipulation of nucleic acid by polymerases, ligases, kinases and/or endonucleases, in a form not normally found in nature. Thus a recombinant nucleic acid may be an isolated nucleic acid, in a linear form, or cloned in a vector formed in vitro by ligating DNA molecules that are not normally joined, both of which are considered recombinant for the purposes of this invention. It is understood that once a recombinant nucleic acid is made and reintroduced into a host cell or organism, it can replicate using the in vivo cellular machinery of the host cell rather than by in vitro manipulation; however, such nucleic acids, once produced recombinantly, although subsequently replicated in vivo, are still considered recombinant or isolated for the purposes of the invention. As used herein, a "polynucleotide" or "nucleic acid" is a polymeric form of nucleotides of any length, either ribonucleotides or deoxyribonucleotides or a mixture thereof. This term includes double- and single- stranded DNA and RNA. It also includes known types of modifications, for example, labels which are known in the art, methylation, "caps", substitution of one or more of the naturally occurring nucleotides with a nucleotide analogue, internucleotide modifications-such as, for example, those with uncharged linkages (e.g., phosphorothioates, phosphorodithioates, etc.), those containing pendant moieties, such as, for example proteins (including e.g., nucleases, toxins, antibodies, signal peptides, poly- L-lysine, etc.), those with intercalators (e.g., acridine, psoralen, etc.), those containing chelators (e.g., metals, radioactive metals, etc.), those containing alkylators, those with modified linkages (e.g., alpha anomeric nucleic acids, etc.), as well as unmodified forms of the polynucleotide.

[0081] The use of microarray analysis of gene expression allows the identification of host sequences associated with bladder cancer. These sequences may then be used in a number of different ways, including diagnosis, prognosis, screening for modulators (including both agonists and antagonists), antibody generation (for immunotherapy and imaging), etc. However, as will be appreciated by those skilled in the art, sequences that are identified in one type of cancer may have a strong likelihood of being involved in other types of cancers as well. Thus, while the sequences outlined herein are initially identified as correlated with bladder cancer, they may also be found in other types of cancers as well.

[0082] Some embodiments described herein are directed to the use of cancer associated sequences for diagnosis and treatment of bladder cancer. In some embodiments, the cancer associated sequence is selected from any one or more genes (or the complement thereof) listed in Table 3. In some embodiments, these cancer associated sequences may be associated with bladder cancer, including, without limitation, Transitional Cell Carcinoma (TCC) (also known as urothelial carcinoma) of the bladder and the subtypes of TCC such as papillary carcinoma and flat carcinomas of the bladder, papillary urothelial neoplasm of low malignant potential, squamous cell carcinoma, adenocarcinoma, small-cell carcinoma, and sarcoma of the bladder.

[0083] In some embodiments, the cancer associated sequences are DNA sequences encoding mRNA encoded by any one or more of the genes listed in Table 3. Alternatively, a cancer associated sequence can be a cancer-associated associated protein or cancer associated polypeptide expressed by the aforementioned mRNAs or homologues thereof. In some embodiments, the cancer associated sequence may be a nucleic acid that is a mutant version of the above disclosed sequences. In some embodiments, the homologue may have at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 97%, at least about 98%, at least about 99%, at least about 99.5% identity with the disclosed polypeptide sequence.

[0084] In some embodiments, an isolated nucleic acid comprises at least 10, 12, 15, 20 or 30 contiguous nucleotides of a sequence (or complement thereof) selected from the group consisting of the cancer associated polynucleotide sequences corresponding to any one or more genes listed in Table 3.

[0085] In some embodiments, the polynucleotide, or its complement or a fragment thereof, further comprises a detectable label, is attached to a solid support, is prepared at least in part by chemical synthesis, is an antisense fragment, is single stranded, is double stranded or is comprised in a microarray.

[0086] In some embodiments, the present disclosure provides an isolated polypeptide, encoded within an open reading frame of a cancer associated sequence selected from the polynucleotide sequences (or complements thereof) corresponding to any one or more of the genes listed in Table 3. In some embodiments, the present disclosure provides an isolated polypeptide, wherein said polypeptide comprises the amino acid sequence encoded by a polynucleotide selected from the group consisting of sequences (or complements thereof) corresponding to any one or more gene(s) listed in Table 3. In some embodiments, the invention provides an isolated polypeptide, wherein said polypeptide comprises the amino acid sequence encoded by a cancer associated polypeptide as described herein.

[0087] In some embodiments, the present disclosure further provides an isolated polypeptide, comprising the amino acid sequence of an epitope of the amino acid sequence of a cancer associated polypeptide disclosed herein. The polypeptide or fragment thereof may be attached to a solid support. In some embodiments the present disclosure provides an isolated antibody (monoclonal or polyclonal) or antigen binding fragment thereof, that binds to such a polypeptide. The isolated antibody or antigen binding fragment thereof may be attached to a solid support. The isolated antibody or antigen binding fragment thereof may further comprise a detectable substance.

[0088] Some embodiments also provide for antigens (e.g., cancer-associated polypeptides) associated with a variety of cancers as targets for diagnostic and/or therapeutic antibodies, e.g. bladder cancer antigens. These antigens may also be useful for drug discovery (e.g., small molecules) and for further characterization of cellular regulation, growth, and differentiation.

Methods of Detecting and Diagnosing Bladder Cancer

[0089] In some embodiments, a method of detecting or diagnosing bladder cancer may comprise assaying gene expression in a subject in need of said diagnosis. Any method known in the art may be used to assay gene expression of one or more markers disclosed herein. In some embodiments, detecting a level of a cancer associated sequence may comprise techniques such as, but not limited to, polymerase chain reaction (PCR), mass spectroscopy, microarray, gel electrophoresis, and/or hybridization using one more probes that specifically bind a nucleic acid encoding a cancer associated sequence disclosed herein. Information relating to expression of a receptor can also be useful in determining therapies aimed at up- or down-regulating the cancer associated sequence's signaling using agonists or antagonists.

[0090] In some embodiments, a method of diagnosing bladder cancer may comprise detecting a level of the cancer associated protein in a subject. In some embodiments, a method of screening for cancer may comprise detecting a level of the cancer associated protein. In some embodiments, the cancer associated protein is encoded by a nucleotide sequence (or fragment thereof, or complement thereof) selected from a sequence corresponding to any one or more of the genes listed in Table 3. In some embodiments, a method of detecting cancer in a sample may comprise contacting the sample obtained from a subject with an antibody that specifically binds a cancer-associated protein as disclosed herein. In some embodiments, the antibody may be a monoclonal antibody or a polyclonal antibody. In some embodiments, the antibody may be a humanized or a recombinant antibody. In some embodiments, an antibody specifically binds to one or more of a molecule, such as protein or peptide, encoded by one or more cancer associated sequences disclosed herein.

[0091] In some embodiments, the antibody binds to an epitope from a protein encoded by any one or more of the genes listed in Table 3. In some embodiments, the epitope is a fragment of a protein sequence encoded by the nucleotide sequence of any of the cancer associated sequences disclosed herein. In some embodiments, the epitope comprises about 1- 10, 1-20, 1-30, 3-10, or 3-15 residues of the cancer associated sequence. In some embodiments, the epitope is not linear. In some embodiments, the epitope is discontinuous.

[0092] In some embodiments, the antibody binds to the regions described herein or a peptide with at least 90, 95, or 99% homology or identity to the region. In some embodiments, the fragment of the regions described herein is 5- 10 residues in length. In some embodiments, the fragment of the regions (e.g. , epitope) described herein are 3-5 residues in length. The fragments are described based upon the length provided. In some embodiments, the epitope is about 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 20 residues in length.

[0093] In some embodiments, the sequence to which the antibody binds may include both nucleic acid and amino acid sequences. In some embodiments, the sequence to which the antibody binds may include sequences having at least about 60% homology with the disclosed sequences. In some embodiments, the sequence to which the antibody binds may have at least about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95%, about 97%, about 99%, or about 99.8% homology with the disclosed sequences. In some embodiments, the sequences may be referred to as "mutant nucleic acids" or "mutant peptide sequences."

[0094] In some embodiments, a subject can be diagnosed with bladder cancer by detecting the presence, in a sample obtained from the subject, of a cancer associated sequence, or a fragment or complement thereof, e.g. , a sequence corresponding to any one or more of the genes listed in Table 3. As discussed, cancer associated sequences may be detected in any type of sample, including, but not limited to, serum, blood, tumor and the like. The sample may be any type of sample as described herein.

[0095] Any assay known in the art may be used to screen for the presence, absence or expression level of one or more proteins encoded for by a cancer associated sequence described infra. In some embodiments the assay may be, for example, an ELISA, a radio-immuno assay, a western blot, a flow cytometry assay and the like.

[0096] In certain embodiments, a cancer-associated protein is detected by using an aptamer that specifically binds to the protein of interest. Aptamers are unique short nucleic acid (e.g., DNA, RNA) or peptide sequences that can be obtained by randomized synthesis followed by multiple rounds of selection for binding to a target. Certain aptamers, known as slow off-rate modified aptamers, or SOMAmers^®, comprise unique short DNA sequences that incorporate several bases that have been modified to include "protein-like" side chains, and a 5'-linker. Aptamers are high-affinity binding reagents which are very specific for their targets (e.g. , polypeptides, nucleic acids, small organic molecules) and allow for extremely high multiplexing of protein measurements in a high throughput and reproducible manner with very small sample volume requirements.

[0097] In some embodiments, the present disclosure provides a method of diagnosing bladder cancer or a neoplastic condition in a subject, the method comprising obtaining, from a sample derived from the subject, a gene expression result for one or more cancer associated sequences selected from sequences corresponding to any one or more of the genes listed in Table 3; and diagnosing bladder cancer or a neoplastic condition in the subject based on the cancer associated sequence gene expression result, wherein the subject is diagnosed as having bladder cancer or a neoplastic condition if the cancer associated sequence is expressed at a level that is 1) higher than its expression level in a negative control such a non-cancerous bladder tissue or cell sample and/or 2) higher than or equivalent to its expression level in a standard or positive control wherein the standard or positive control is known to contain bladder cancer cells.

[0098] Some embodiments are directed to a biochip (e.g. , a microarray) comprising one or more nucleic acid sequences which encode one or more cancer associated proteins. In some embodiments, a biochip comprises a nucleic acid molecule which encodes at least a portion of a cancer associated protein. In some embodiments, the cancer associated protein is encoded by a sequence selected from sequence corresponding to any one or more of the genes listed in Table 3; or a fragment thereof, or a complement thereof, or a homologues thereof, or combinations thereof. In some embodiments, the nucleic acid molecule specifically hybridizes with a nucleic acid sequence selected from a sequence corresponding to any one or more of the genes listed in Table 3, a fragment thereof, or a complement thereof. In some embodiments, the biochip comprises first and second nucleic molecules wherein the first nucleic acid molecule specifically hybridizes with a first sequence selected from a cancer associated sequence disclosed herein and the second nucleic acid molecule specifically hybridizes with a second sequence selected from a cancer associated sequences disclosed herein, wherein the first and second sequences are not the same sequence. In some embodiments, the present disclosure provides methods of detecting or diagnosing cancer, such as bladder cancer, comprising detecting the expression of a nucleic acid sequence selected from sequences corresponding to any one or more of the genes listed in Table 3, or a fragment or a complement thereof, wherein a sample is contacted with a biochip comprising a sequence selected from sequences corresponding to any one or more of the genes listed in Table 3 or a fragment or a complement thereof.

[0099] Also provided herein is a method for diagnosing or determining the propensity to cancers, for example bladder cancer, by measuring the expression level of one or more of the sequences upregulated in bladder cancer, disclosed herein, in a sample and comparing the expression level of the one or more cancer associated sequences in the sample with expression level of the same cancer associated sequences in a non-cancerous cell. A higher level of expression of one or more of the cancer associated sequences disclosed herein in the sample compared to the non-cancerous cell indicates a propensity for the development of cancer, e.g., bladder cancer.

[00100] In some embodiments, the present disclosure provides a method for detecting a cancer associated sequence by expression of a polypeptide in a test sample, comprising detecting a level of expression of at least one polypeptide such as, without limitation, a cancer associated protein encoded by a sequence disclosed herein, or a fragment thereof. In some embodiments, the method comprises comparing the level of expression of the polypeptide in the test sample with a level of expression of polypeptide in a normal sample, i.e., a non-cancerous sample, wherein a higher level of expression of the polypeptide in the test sample relative to the level of polypeptide expression in the normal sample is indicative of the presence of cancer in the test sample. In some embodiments, the polypeptide expression is compared to a cancer sample, wherein a level of expression in the test sample that is at least as high as the level of expression in the cancer sample is indicative of the presence of cancer in the test sample. In some embodiments, the sample is a cell sample. In some embodiments the sample is a tissue sample. In some embodiments the sample is a bodily fluid. Examples of suitable bodily fluids, include, but are not limited to, blood, serum, plasma, saliva and urine. In some embodiments the sample is a blood sample. In some embodiments the sample is a serum sample. In some embodiments the sample is a urine sample.

[00101] In some embodiments, the present disclosure provides a method for detecting cancer by detecting the presence of an antibody in a test serum sample. In some embodiments, the antibody recognizes a polypeptide or an epitope of a cancer associated sequence disclosed herein. In some embodiments, the method comprises detecting a level of an antibody against an antigenic polypeptide such as, without limitation, a cancer associated protein such as a protein encoded by a cancer associated sequence disclosed herein, or an antigenic fragment thereof. In some embodiments, the method comprises comparing the level of the antibody in the test sample with a level of the antibody in the control sample, wherein an altered level of antibody in said test sample relative to the level of antibody in the control sample is indicative of the presence of cancer in the test sample. In some embodiments, the control sample is a sample derived from a non-cancerous sample, e.g., blood or serum obtained from a subject that is cancer free. In these cases, a higher level of antibody in the test sample, compared to the non-cancerous control sample, indicates the presence of cancer in the test sample. In some embodiments, the control is derived from a cancer sample, and, in these cases, levels or amount of antibody that are the same or greater in the test sample compared to the cancer control sample are indicative of the presence of cancer in the test sample.

[00102] In some embodiments, a method for diagnosing cancer or a neoplastic condition comprises a) determining the expression of one or more genes comprising a nucleic acid sequence (or a fragment thereof or a complement thereof) selected from the group consisting of the human genomic and mRNA sequences corresponding to any one or more of the genes listed in Table 3, in a first sample type (e.g. tissue, bodily fluid, etc.) of a first individual; and b) comparing said expression of said gene(s) with their expression in a second normal sample type from said first individual or a sample from a second unaffected individual; wherein an increase in said expression in the first sample, compared to either the (i) second normal sample from the first individual or (ii) the sample from the second unaffected individual indicates that the first individual has cancer. [00103] In some embodiments, the present disclosure also provides a method for detecting presence or absence of cancer cells in a subject. In some embodiments, the method comprises contacting one or more cells from the subject with an antibody as described herein. The antibody may be conjugated to a detectible substance. In some embodiments the antibody that binds to a protein encoded by a cancer associated sequence disclosed herein may bind to a second antibody wherein the second antibody is conjugated to a detectable substance. In some embodiments the antibody that binds to a protein encoded for by a cancer associated sequence disclosed herein is bound to a solid support. In some embodiments, the method comprises detecting a complex of a cancer associated protein and the antibody, wherein detection of the complex indicates with the presence of cancer cells in the subject. The complex may include a detectable substance as described herein. The complex may include a solid support, such as bead, a chip, a magnet, a multiwell plate and the like.

[00104] In some embodiments, the present disclosure provides methods of detecting cancer in a test sample, comprising: (i) detecting a level of activity of at least one polypeptide that is a gene product; and (ii) comparing the level of activity of the polypeptide in the test sample with a level of activity of polypeptide in a normal sample, wherein an increased level of activity of the polypeptide in the test sample relative to the level of polypeptide activity in the normal sample is indicative of the presence of cancer in the test sample, wherein said gene product is a product of a gene selected from one or more of the cancer associated sequences provided herein.

Capture Reagents and Specific Binding Partners

[00105] The present disclosure provides for specific binding partners and capture reagents that bind specifically to cancer associated sequences disclosed herein and the polypeptides or proteins encoded by those sequences. The capture reagents and specific binding partners may be used in diagnostic assays as disclosed herein and/or in therapeutic methods described herein, as well as in drug screening assays disclosed infra. Capture reagents include for example nucleic acids and proteins. Suitable proteins include antibodies. Capture reagents and binding partners can also include aptamers.

[00106] As used herein, the term "specifically binds" or "specifically binding" means binding that is measurably different from a non-specific interaction. Specific binding can be measured, for example, by determining binding of a molecule compared to binding of a control molecule, which generally is a molecule of similar structure that does not have binding activity. For example, specific binding is indicated if the molecule has measurably higher affinity for cells expressing a protein encoded by a cancer associated sequence disclosed herein than for cells that do not express the same protein encoded by the cancer associated sequences disclosed herein. Specificity of binding can be determined, for example, by competitive inhibition of a known binding molecule.

[00107] The term "specifically binding," as used herein, includes both low and high affinity specific binding. Specific binding can be exhibited, for example, by a low affinity homing molecule having a Kd of at least about 10^"4M. Specific binding also can be exhibited by a high affinity homing molecule, for example, a homing molecule having a Kd of at least about 10^"5 M. Such a molecule can have, for example, a Kd of at least about 10^"6 M, at least about 10^"7 M, at least about 10^"8 M, at least about 10^"9 M, at least about 10^"10 M, or can have a Kd of at least about 10^"11 M or 10^"12 M or greater. Both low and high affinity homing molecules are useful and are encompassed by the present disclosure. Low affinity homing molecules are useful in targeting, for example, multivalent conjugates. High affinity homing molecules are useful in targeting, for example, multivalent and univalent conjugates.

[00108] In some embodiments the specific binding partner or capture reagent is an antibody. Binding in IgG antibodies, for example, is generally characterized by an affinity of at least about 10^"7 M or higher, such as at least about 10 ^s M or higher, or at least about 10^"9 M or higher, or at least about 10^"10M or higher, or at least about 10^"11 M or higher, or at least about 10^" ¹² M or higher. The term is also applicable where, e.g., an antigen-binding domain is specific for a particular epitope that is not carried by numerous antigens, in which case the antibody or antigen binding protein carrying the antigen-binding domain will generally not bind other antigens. In some embodiments, the capture reagent has a Kd equal or less than 10^"9 M, 10^"10 M, or 10^"11 M for its binding partner (e.g. antigen). In some embodiments, the capture reagent has a Ka greater than or equal to 10⁹ M^"1 for its binding partner. Capture reagent can also refer to, for example, antibodies. Intact antibodies, also known as immunoglobulins, are typically tetrameric glycosylated proteins composed of two light (L) chains of approximately 25 kDa each, and two heavy (H) chains of approximately 50 kDa each. Two types of light chain, termed lambda and kappa, exist in antibodies. Depending on the amino acid sequence of the constant domain of heavy chains, immunoglobulins are assigned to five major classes: A, D, E, G, and M, and several of these may be further divided into subclasses (isotypes), e.g., IgGl, IgG2, IgG3, IgG4, IgAl, and IgA2. Each light chain is composed of an N-terminal variable (V) domain (VL) and a constant (C) domain (CL). Each heavy chain is composed of an N-terminal V domain (VH), three or four C domains (CHs), and a hinge region. The CH domain most proximal to VH is designated CHI. The VH and VL domains consist of four regions of relatively conserved sequences named framework regions (FRl, FR2, FR3, and FR4), which form a scaffold for three regions of hypervariable sequences (complementarity determining regions, CDRs). The CDRs contain most of the residues responsible for specific interactions of the antibody or antigen binding protein with the antigen. CDRs are referred to as CDR1, CDR2, and CDR3. Accordingly, CDR constituents on the heavy chain are referred to as HI, H2, and H3, while CDR constituents on the light chain are referred to as LI, L2, and L3. CDR3 is the greatest source of molecular diversity within the antibody or antigen binding protein-binding site. H3, for example, can be as short as two amino acid residues or greater than 26 amino acids. The subunit structures and three-dimensional configurations of different classes of immunoglobulins are well known in the art. For a review of antibody structure, see Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory, Eds. Harlow et al., 1988. One of skill in the art will recognize that each subunit structure, e.g., a CH, VH, CL, VL, CDR, and/or FR structure, comprises active fragments. For example, active fragments may consist of the portion of the VH, VL, or CDR subunit that binds the antigen, i.e., the antigen-binding fragment, or the portion of the CH subunit that binds to and/or activates an Fc receptor and/or complement.

[00109] Non-limiting examples of binding fragments encompassed within the term "antigen- specific antibody" used herein include: (i) an Fab fragment, a monovalent fragment consisting of the VL, VH, CL and CHI domains; (ii) an F(ab')2 fragment, a bivalent fragment comprising two Fab fragments linked by a disulfide bridge at the hinge region; (iii) an Fd fragment consisting of the VH and CHI domains; (iv) an Fv fragment consisting of the VL and VH domains of a single arm of an antibody, (v) a dAb fragment, which consists of a VH domain; and (vi) an isolated CDR. Furthermore, although the two domains of the Fv fragment, VL and VH, are coded for by separate genes, they may be recombinantly joined by a synthetic linker, creating a single protein chain in which the VL and VH domains pair to form monovalent molecules (known as single chain Fv (scFv)). The most commonly used linker is a 15-residue (Gly₄Ser)3 peptide, but other linkers are also known in the art. Single chain antibodies are also intended to be encompassed within the terms "antibody or antigen binding protein," or "antigen-binding fragment" of an antibody. The antibody can also be a polyclonal antibody, monoclonal antibody, chimeric antibody, antigen-binding fragment, Fc fragment, single chain antibody, or any derivatives thereof.

[00110] Antibodies can be obtained using conventional techniques known to those skilled in the art, and the fragments are screened for utility in the same manner as intact antibodies. Antibody diversity is created by multiple germline genes encoding variable domains and a variety of somatic events. The somatic events include recombination of variable gene segments with diversity (D) and joining (J) gene segments to make a complete VH domain, and the recombination of variable and joining gene segments to make a complete VL domain. The recombination process itself is imprecise, resulting in the loss or addition of amino acids at the V (D) J junctions. These mechanisms of diversity occur in the developing B cell prior to antigen exposure. After antigenic stimulation, the expressed antibody genes in B cells undergo somatic mutation. Based on the estimated number of germline gene segments, the random recombination of these segments, and random VH-VL pairing, up to 1.6X10⁷ different antibodies may be produced (Fundamental Immunology, 3rd ed. (1993), ed. Paul, Raven Press, New York, N.Y.). When other processes that contribute to antibody diversity (such as somatic mutation) are taken into account, it is thought that upwards of 1X10¹⁰ different antibodies may be generated (Immunoglobulin Genes, 2nd ed. (1995), eds. Jonio et al., Academic Press, San Diego, Calif.). Because of the many processes involved in generating antibody diversity, it is unlikely that independently derived monoclonal antibodies with the same antigen specificity will have identical amino acid sequences.

[00111] Antibodies, or antigen binding protein molecules, capable of specifically interacting with the antigens, epitopes, or other molecules described herein may be produced by methods well known to those skilled in the art. For example, monoclonal antibodies can be produced by generation of hybridomas in accordance with known methods. Hybridomas formed in this manner can then be screened using standard methods, such as enzyme-linked immunosorbent assay (ELISA) and Biacore analysis, to identify one or more hybridomas that produce an antibody that specifically interacts with a molecule or compound of interest. As an alternative to preparing monoclonal antibody-secreting hybridomas, a monoclonal antibody to a polypeptide of the present disclosure may be identified and isolated by screening a recombinant combinatorial immunoglobulin library (e.g., an antibody phage display library) with a polypeptide of the present disclosure to thereby isolate immunoglobulin library members that bind to the polypeptide. Techniques and commercially available kits for generating and screening phage display libraries are well known to those skilled in the art. Additionally, examples of methods and reagents particularly amenable for use in generating and screening antibody or antigen binding protein display libraries can be found in the literature.

[00112] Examples of chimeric antibodies include, but are not limited to, humanized antibodies. The antibodies described herein can also be human antibodies. In some embodiments, the capture reagent comprises a detection reagent. The detection reagent can be any reagent that can be used to detect the presence of the capture reagent binding to its specific binding partner. The capture reagent can comprise a detection reagent directly or the capture reagent can comprise a particle that comprises the detection reagent. In some embodiments, the capture reagent and/or particle comprises a color, colloidal gold, radioactive tag, fluorescent tag, or a chemiluminescent substrate. The particle can be, for example, a viral particle, a latex particle, a lipid particle, or a fluorescent particle.

[00113] The capture reagents (e.g. antibody) of the present disclosure can also include an anti-antibody, i.e. an antibody that recognizes another antibody but is not specific to an antigen, such as, but not limited to, anti-IgG, anti-IgM, or ant-IgE antibody. This non-specific antibody can be used as a positive control to detect whether the antigen specific antibody is present in a sample.

[00114] Nucleic acid capture reagents include DNA, RNA and PNA molecules for example. The nucleic acid may be about 5 nucleotides long, about 10 nucleotides long, about 15 nucleotides long, about 20 nucleotides long, about 25 nucleotides long, about 30 nucleotides long, about 35 nucleotides long about 40 nucleotides long. The nucleic acid may be greater than 30 nucleotides long. The nucleic acid may be less than 30 nucleotides long.

Treatment of Bladder Cancer

[00115] In some embodiments, bladder cancers expressing one or more of the cancer associated sequences disclosed herein may be treated by antagonizing the cancer associated sequence's activity. In some embodiments, a method of treating bladder cancer may comprise administering a therapeutic such as, without limitation, antibodies that antagonize the ligand binding to the cancer associated sequence, small molecules that inhibit the cancer associated sequence's expression or activity, siRNAs directed towards the cancer associated sequence, or the like.

[00116] In some embodiments, a method of treating cancer (e.g. bladder or other types of cancer) comprises detecting the presence of a cancer associated sequence's receptor and administering a cancer treatment. The treatment may specifically bind to the cancer associated sequence's receptor. The cancer treatment may be any cancer treatment or one that specifically inhibits the action of a cancer associated sequence. For example, various cancers are tested to determine if a specific molecule is present before giving a cancer treatment. In some embodiments, therefore, a sample is obtained from the patient and tested for the presence of a cancer associated sequence or the overexpression of a cancer associated sequence as described herein. In some embodiments, if a cancer associated sequence is found to be overexpressed then a bladder cancer treatment or therapeutic is administered to the subject. The bladder cancer treatment may be a conventional non-specific treatment, such as chemotherapy, or the treatment may comprise a specific treatment that only targets the activity of the cancer associated sequence or the receptor to which the cancer associated sequence binds. These treatments can be, for example, an antibody that specifically binds to the cancer associated sequence and inhibits its activity. The treatment may be a nucleic acid that downregulates or silences the expression of the cancer associated sequence.

[00117] Some embodiments herein describe methods of treating cancer or a neoplastic condition comprising administering, to a subject, an antibody that binds to the cancer associated sequence. In some embodiments, the antibody may be monoclonal or polyclonal. In some embodiments, the antibody may be humanized or recombinant. In some embodiments, the antibody may neutralize biological activity of the cancer associated sequence by binding to and/or interfering with the cancer associated sequence's receptor. In some embodiments the antibody may bind to a site on the protein encoded by the cancer associated DNA sequence that is not the receptor. In some embodiments, administering the antibody may be to a biological fluid or tissue, such as, without limitation, blood, urine, serum, plasma, tumor tissue, or the like.

[00118] In some embodiments, a method of treating cancer may comprise administering an agent that interferes with the synthesis, secretion, receptor binding or receptor signaling of cancer associated proteins or its receptors. In some embodiments, the cancer may be selected from Transitional Cell Carcinoma (TCC) (also known as urothelial carcinoma) of the bladder and the subtypes of TCC such as papillary carcinoma and flat carcinomas of the bladder, papillary urothelial neoplasm of low malignant potential, squamous cell carcinoma, adenocarcinoma, small- cell carcinoma, and sarcoma of the bladder.

[00119] In some embodiments, the cancer cell may be targeted specifically with a therapeutic based upon the differentially expressed gene or gene product. For example, in some embodiments, the differentially expressed gene product may be an enzyme, which can convert an anti-cancer prodrug into its active form. Therefore, in normal cells, where the differentially expressed gene product is not expressed or expressed at significantly lower levels, the prodrug may be either not activated or activated in a lesser amount, and may be, therefore less toxic to normal cells. Therefore, the cancer prodrug may, in some embodiments, be given in a higher dosage so that the cancer cells can metabolize the prodrug, which will, for example, kill the cancer cell, and the normal cells will not metabolize the prodrug or not as well, and, therefore, the prodrug will be less toxic to the patient. An example of the use of this type of treatment is for tumor cells that overexpress a metalloprotease, which is described in Atkinson et al., British Journal of Pharmacology (2008) 153, 1344-1352. Using proteases to target cancer cells is also described in Carl et al., PNAS, Vol. 77, No. 4, pp. 2224-2228, April 1980. For example, doxorubicin or other types of chemotherapeutic can be linked to a peptide sequence that is specifically cleaved or recognized by the differentially expressed gene product. The doxorubicin or other type of chemotherapeutic is then cleaved from the peptide sequence and is activated such that it can kill or inhibit the growth of the cancer cell whereas in the normal cell the chemotherapeutic is never internalized into the cell or is not metabolized as efficiently, and is, therefore, less toxic.

[00120] In some embodiments, a method of treating bladder cancer may comprise gene knockdown of one or more cancer associated sequences described herein. Gene knockdown refers to techniques by which the expression of one or more of an organism's genes is reduced, either through genetic modification (a change in the DNA of one of the organism's chromosomes such as, without limitation, chromosomes encoding cancer associated sequences) or by treatment with a reagent such as a short DNA or RNA oligonucleotide with a sequence complementary to either an mPvNA transcript or a gene. In some embodiments, the oligonucleotide used may be selected from RNase-H competent antisense, such as, without limitation, ssDNA oligonucleotides, ssRNA oligonucleotides, phosphorothioate oligonucleotides, or chimeric oligonucleotides; RNase- independent antisense, such as morpholino oligonucleotides, 2'-0-methyl phosphorothioate oligonucleotides, locked nucleic acid oligonucleotides, or peptide nucleic acid oligonucleotides; RNAi oligonucleotides, such as, without limitation, siRNA duplex oligonucleotides, or shRNA oligonucleotides; or any combination thereof. In some embodiments, a plasmid may be introduced into a cell, wherein the plasmid expresses either an antisense RNA transcript or an shRNA transcript. The oligonucleotide introduced or transcript expressed may interact with the target mRNA by complementary base pairing (a sense-antisense interaction).

[00121] The specific mechanism of silencing may vary with the oligonucleotide chemistry. In some embodiments, the binding of a oligonucleotide described herein to the active gene or its transcripts may cause decreased expression through blocking of transcription, degradation of the mRNA transcript (e.g. by small interfering RNA (siRNA) or RNase-H dependent antisense) or blocking either mRNA translation, pre-mRNA splicing sites or nuclease cleavage sites used for maturation of other functional RNAs such as miRNA (e.g. by morpholino oligonucleotides or other RNase-H independent antisense). For example, RNase-H competent antisense oligonucleotides (and antisense RNA transcripts) may form duplexes with RNA that are recognized by the enzyme RNase-H, which cleaves the RNA strand. As another example, RNase- independent oligonucleotides may bind to the mRNA and block the translation process. In some embodiments, the oligonucleotides may bind in the 5'-UTR and halt the initiation complex as it travels from the 5'-cap to the start codon, preventing ribosome assembly. A single strand of RNAi oligonucleotides may be loaded into the RISC complex, which catalytically cleaves complementary sequences and inhibits translation of some mRNAs bearing partially- complementary sequences. The oligonucleotides may be introduced into a cell by any technique including, without limitation, electroporation, microinjection, salt-shock methods such as, for example, CaCl₂ shock; transfection of anionic oligonucleotides by cationic lipids such as, for example, Lipofectamine^®; transfection of uncharged oligonucleotides by endosomal release agents such as, for example, Endo-Porter; or any combination thereof. In some embodiments, the oligonucleotides may be delivered from the blood to the cytosol using techniques selected from nanoparticle complexes, virally-mediated transfection, oligonucleotides linked to octaguanidinium dendrimers (morpholino oligonucleotides), or any combination thereof.

[00122] In additional embodiments, all or a portion of the sequence of any of the cancer- associated genes listed in Table 3 can be deleted, so as to prevent expression of the cancer- associated sequence. Methods for targeted deletion of cellular sequences are known in the art and include zinc finger nucleases, TALENs and the CRISPR-Cas9 system. Delivery of the aforementioned reagents to tumor cells can be accomplished, e.g., with viral vectors (e.g., adenovirus, AAV).

[00123] In some embodiments, a method of treating bladder cancer comprises treating a subject with a suitable reagent to knockdown or inhibit expression of a gene encoding the mRNA disclosed in sequences corresponding to any one or more of the genes listed in Table 3, a fragment thereof, a complement thereof, or a combination thereof. In other embodiments the present disclosure provide for the in vitro knockdown of the expression of one or more of the genes disclosed in sequences corresponding to any one or more of the genes listed in Table 3, or a fragment thereof or a complement thereof.

[00124] In some embodiments, bladder cancers are treated by modulating the activity or expression of sequences corresponding to any one or more of the genes listed in Table 3 or a fragment thereof or a complement thereof, or the gene product thereof.

[00125] In some embodiments, a method of treating bladder cancer comprises administering an antibody (e.g. monoclonal antibody, human antibody, humanized antibody, recombinant antibody, chimeric antibody, and the like) that specifically binds to a cancer associated protein that is expressed on a cell surface. In some embodiments, the antibody binds to an extracellular domain of the cancer associated protein. In some embodiments, the antibody binds to a cancer associated protein differentially expressed on a cancer cell surface relative to a normal cell surface, or, in some embodiments, to at least one human cancer cell line. In some embodiments, the antibody is linked to a therapeutic agent or a toxin.

[00126] In some embodiments, implementation of an immunotherapy strategy for treating, reducing the symptoms of, or preventing cancer or neoplasms, (e.g., a vaccine) may be achieved using many different techniques available to the skilled artisan.

[00127] Immunotherapy or the use of antibodies for therapeutic purposes has been used in recent years to treat cancer. Passive immunotherapy involves the use of monoclonal antibodies in cancer treatments. See, for example, Cancer: Principles and Practice of Oncology, 6th Edition (2001) Chapter 20 pp. 495-508. Inherent therapeutic biological activity of these antibodies include direct inhibition of tumor cell growth or survival, and the ability to recruit the natural cell killing activity of the body's immune system. These agents may be administered alone or in conjunction with radiation or chemotherapeutic agents. Alternatively, antibodies may be used to make antibody conjugates in which the antibody is linked to a toxic agent and directs that agent to the tumor by specifically binding to the tumor.

Screening for Cancer Therapeutics

[00128] The present disclosure provides for screening assays to determine if a candidate molecule has an inhibitory effect on the growth and or metastasis of bladder cancer cells. Suitable candidates include proteins, peptides, nucleic acids such as DNA, RNA shRNA smRNA and the like, small molecules including small organic molecules and small inorganic molecules. A small molecule may include molecules less than 50 kd, less than 25 kD, less than 10 kD, less than 5 kD, less than 2.5 kD, or less than 1 kD.

[00129] In some embodiments, a method of identifying an anti-cancer agent is provided, wherein the method comprises contacting a candidate agent with a sample; and determining the cancer associated sequence's activity in the sample. In some embodiments, the candidate agent is identified as an anti-cancer agent if the cancer associated sequence's activity is reduced in the sample after the contacting. In other embodiments the candidate agent reduces the expression level of one or more cancer associated sequences disclosed infra.

[00130] In some embodiments, the candidate agent is an antibody. In some embodiments, the method comprises contacting a candidate antibody that binds to the cancer associated sequence with a sample, and assaying for the cancer associated sequence's activity, wherein the candidate antibody is identified as an anti-cancer agent if the activity of the cancer associated sequence is reduced in the sample after the contacting. A cancer associated sequence's activity can be any activity of the cancer associated sequence. An example of an activity may include enzymatic activity either of the cancer associated sequence itself or of an enzyme that interacts with or is modulated by the cancer associated sequence either at the nucleic acid level or the protein level.

[00131] In some embodiments, the present disclosure provides methods of identifying an anti-cancer (e.g. bladder cancer) agent comprising contacting a candidate agent to a cell sample; and determining activity of a cancer associated sequence, wherein the candidate agent is identified as an anti-cancer agent if the cancer associated sequence's activity is reduced in the cell sample after the contacting. In some embodiments, the present disclosure provides methods of identifying an anti-cancer agent, the method comprising contacting a cell sample with a candidate agent that binds to a cancer associated sequence (or a fragment thereof, a complement thereof, or combination thereof) selected from any one or more of the genes listed in Table 3, and assaying for the cancer associated sequence's activity or expression level, wherein the candidate agent is identified as an anti-cancer agent if the cancer associated sequence's activity is modulated in the cell sample after the contacting.

[00132] In some embodiments, a method of screening drug candidates includes comparing the level of expression of the cancer-associated sequence in the absence of the drug candidate to the level of expression in the presence of the drug candidate.

[00133] Some embodiments are directed to a method of screening for a therapeutic agent capable of binding to a cancer-associated sequence (nucleic acid or protein), the method comprising combining the cancer-associated sequence and a candidate therapeutic agent, and determining the binding of the candidate agent to the cancer-associated sequence.

[00134] Further provided herein is a method for screening for a therapeutic agent capable of modulating the activity of a cancer-associated sequence. In some embodiments, the method comprises combining the cancer-associated sequence and a candidate therapeutic agent, and determining the effect of the candidate agent on the bioactivity of the cancer-associated sequence. An agent that modulates the bioactivity of a cancer associated sequence may be used as a therapeutic agent capable of modulating the activity of a cancer-associated sequence.

[00135] In certain embodiments the present disclosure provides a method of screening for anticancer activity comprising: (a) contacting a cell that expresses a cancer associated gene selected from one or more cancer associated sequences disclosed in any of Table 3, homologues thereof, combinations thereof, or fragments thereof with an anticancer drug candidate; (b) detecting an effect of the anticancer drug candidate on an expression of the cancer associated sequence in the cell (either at the nucleic acid or protein level); and (c) comparing the level of expression in the absence of the drug candidate to the level of expression in the presence of the drug candidate; wherein an effect on the expression of the cancer associate gene indicates that the candidate has anticancer activity. For example the drug candidate may lower the expression level of the cancer associated sequence in the cell.

[00136] In some embodiments, a method of evaluating the effect of a candidate cancer drug may comprise administering the drug to a patient and removing a cell sample from the patient. The expression profile of the cell is then determined. In some embodiments, the method may further comprise comparing the expression profile of the patient to an expression profile of a healthy individual. In some embodiments, the expression profile comprises measuring the expression of one or more or any combination thereof of the genes disclosed in Table 3. In some embodiments, if the expression profile of one or more or any combination thereof of the sequences disclosed in Table 3 is modified (increased or decreased) the candidate cancer drug is said to be effective.

[00137] In some embodiments, the present disclosure provides a method of screening for anticancer activity comprising: (a) providing a cell that expresses a cancer associated gene (or a fragment thereof or a complement thereof) that encodes a nucleic acid sequence selected from the group consisting of the cancer associated sequences chosen from sequences corresponding to any one or more of the genes listed in Table 3, (b) contacting the cell, which can be derived from a cancer cell, with an anticancer drug candidate; (c) monitoring an effect of the anticancer drug candidate on expression of the cancer associated sequence in the cell sample, and optionally (d) comparing the level of expression in the absence of said drug candidate to the level of expression in the presence of the drug candidate; wherein, if expression in the presence of said anticancer drug candidate is less than expression in the absence of said anticancer drug candidate, the anticancer drug candidate has anti-cancer activity.

[00138] Suitable drug candidates include, but are not limited to an inhibitor of transcription, a G-protein coupled receptor antagonist, a growth factor antagonist, a serine- threonine kinase antagonist, and/or a tyrosine kinase antagonist. In some embodiments, in which the candidate modulates (e.g. , inhibits) the expression of the cancer associated sequence, the candidate is said to have anticancer activity. In some embodiments, the anticancer activity is determined by measuring cell growth. In some embodiments, the candidate inhibits or retards cell growth and is said to have anticancer activity. In some embodiments, the candidate causes the cell to die, and thus, the candidate is said to have anticancer activity.

[00139] In some embodiments, the present disclosure provides a method of screening for activity against bladder cancer. In some embodiments, the method comprises contacting a cell that overexpresses a cancer associated gene which is complementary to a cancer associated sequence selected from cancer associated sequences disclosed in Table 3, homologues thereof, combinations thereof, or fragments thereof with a bladder cancer drug candidate. In some embodiments, the method comprises detecting an effect of the bladder cancer drug candidate on an expression of the cancer associated polynucleotide in the cell or an effect on the cell's growth or viability. In some embodiments, the method comprises comparing the level of expression, cell growth, or viability in the absence of the drug candidate to the level of expression, cell growth, or viability in the presence of the drug candidate; wherein an effect on the expression of the cancer associated polynucleotide, cell growth, or viability indicates that the candidate has activity against a bladder cancer cell that differentially expresses (e.g. , overexpresses) a cancer associated gene, wherein said gene is selected from any one or more of the genes listed in Table 3, complements thereof, homologues thereof, combinations thereof, or fragments thereof. In some embodiments, the drug candidate may include, for example, a transcription inhibitor, a G-protein coupled receptor antagonist, a growth factor antagonist, a serine-threonine kinase antagonist, or a tyrosine kinase antagonist.

Methods of Identifying Bladder Cancer Markers

[00140] The pattern of gene expression in a particular living cell may be characteristic of its current state. Nearly all differences in the state or type of a cell are reflected in the differences in RNA levels of one or more genes. Comparing expression patterns of uncharacterized genes may provide clues to their function. High throughput analysis of expression of hundreds or thousands of genes can help in (a) identification of complex genetic diseases, (b) analysis of differential gene expression over time, between tissues and disease states, and (c) drug discovery and toxicology studies. Increase or decrease in the levels of expression of certain genes correlate with cancer biology. For example, oncogenes are positive regulators of tumorigenesis, while tumor suppressor genes are negative regulators of tumorigenesis. (Marshall, Cell, 64: 313-406 (1991); Weinberg, Science, 254: 1138- 1146 (1991)). Accordingly, some embodiments herein provide for polynucleotide and polypeptide sequences involved in cancer and, in particular, in oncogenesis.

[00141] Oncogenes are genes that can cause cancer. Carcinogenesis can occur by a wide variety of mechanisms, including infection of cells by viruses containing oncogenes, activation of protooncogenes in the host genome, and mutations of protooncogenes and tumor suppressor genes. Carcinogenesis is fundamentally driven by somatic cell evolution (i.e. mutation and natural selection of variants with progressive loss of growth control). The genes that serve as targets for these somatic mutations are classified as either protooncogenes or tumor suppressor genes, depending on whether their mutant phenotypes are dominant or recessive, respectively.

[00142] Some embodiments of the present disclosure are directed to cancer associated sequences ("target markers"). Some embodiments are directed to methods of identifying novel target markers useful in the diagnosis and treatment of cancer wherein expression levels of mRNAs, miRNAs, proteins, or protein post translational modifications including but not limited to phosphorylation and sumoylation are compared between five categories of cell types: (1) immortal pluripotent stem cells (such as embryonic stem ("ES") cells, induced pluripotent stem ("iPS") cells, and germ-line cells such as embryonal carcinoma ("EC") cells) or gonadal tissues; (2) ES, iPS, or EC-derived clonal embryonic progenitor ("EP") cell lines, (3) nucleated blood cells including but not limited to CD34+ cells and CD133+ cells; (4) normal mortal somatic adult- derived tissues and cultured cells including: skin fibroblasts, vascular endothelial cells, normal non-lymphoid and non-cancerous tissues, and the like, and (5) malignant cancer cells including cultured cancer cell lines or human tumor tissue. mRNAs, miRNAs, or proteins that are generally expressed (or not expressed) in categories 1, 3, and 5, or categories 1 and 5 but not expressed (or expressed) in categories 2 and 4 are candidate targets for cancer diagnosis and therapy. Some embodiments herein are directed to human applications, non-human veterinary applications, or a combination thereof.

[00143] Another method of identifying cancer-associated sequences (i.e., cancer- associated markers, cancer-associated genes) is to compare gene expression in cancerous cells to gene expression in non-cancerous cells and identify genes whose expression is greater in cancerous cells. Gene expression can be measured as either mRNA or protein. The Examples provided herein describe application of such a method to identify the cancer-associated sequences.

[00144] Once expression is determined, the gene sequence results may be further filtered by considering fold-change in cancer cell lines vs. normal tissue; general specificity; whether the gene product is secreted or not, level of expression in cancer cell lines; and signal to noise ratio.

[00145] It will be appreciated that there are various methods of obtaining expression data and uses of the expression data. For example, the expression data that can be used to detect or diagnose a subject with cancer can be obtained experimentally. In some embodiments, obtaining the expression data comprises obtaining the sample and processing the sample to experimentally determine the expression data. The expression data can comprise expression data for one or more of the cancer associated sequences described herein. The expression data can be experimentally determined by, for example, using a microarray or quantitative amplification method such as, but not limited to, those described herein. In some embodiments, obtaining expression data associated with a sample comprises receiving the expression data from a third party that has processed the sample to experimentally determine the expression data.

[00146] Detecting a level of expression or similar steps that are described herein may be done experimentally or provided by a third-party as is described herein. Therefore, for example, "detecting a level of expression" may refer to experimentally measuring the data and/or having the data provided by another party who has processed a sample to determine and detect a level of expression data.

Techniques for Analyzing Samples

[00147] Any technique known in the art may be used to analyze a sample according to the methods disclosed infra such as methods of detecting or diagnosing cancer in a sample or identifying a new cancer associated sequence. Exemplary techniques are provided below.

[00148] Gene Expression Assays: Measurement of the gene expression levels may be performed by any known methods in the art, including but not limited to quantitative PCR, or microarray gene expression analysis, bead array gene expression analysis and RNA blot (Northern) analysis. The gene expression levels may be represented as relative expression normalized to the ADPRT gene (Accession number NM_001618.2), GAPD gene (Accession number NM_002046.2), or other housekeeping genes known in the art. In the case of microarrayed probes of mRNA expression, the gene expression data may also be normalized by a median of medians method. In this method, each array gives a different total intensity.

[00149] Isolation of total RNA and miRNA: RNA may be harvested according to the vendor's instructions using Qiagen RNEasy kits to isolate total RNA or Ambion mirVana kits to isolate RNA enriched for small RNA species. The RNA concentrations may be determined by spectrophotometry and RNA quality may be determined by denaturing agarose gel electrophoresis to visualize 28S and 18S RNA. Samples with clearly visible 28S and 18S bands without signs of degradation and at a ratio of approximately 2: 1, 28S: 18S may be used for subsequent miRNA analysis.

[00150] Assay for miRNA in samples isolated from human cells: The miRNAs may be quantitated using a Human Panel TaqMan^® MicroRNA Assay from Applied Biosystems, Inc. This is a two-step assay that uses stem-loop primers for reverse transcription (RT) followed by realtime TaqMan^®. The assay includes two steps, reverse transcription (RT) and quantitative PCR. Real-time PCR may be performed on an Applied Biosystems 7500 Real-Time PCR System. The copy number per cell may be estimated based on the standard curve of synthetic mir-16 miRNA and assuming a total RNA mass of approximately 15pg/cell.

[00151] The reverse transcription reaction may be performed using lx cDNA archiving buffer, 3.35 units MMLV reverse transcriptase, 5mM each dNTP, 1.3 units AB RNase inhibitor, 2.5 nM 330-plex reverse primer (RP), and 3 ng of cellular RNA in a final volume of 5 ul. The reverse transcription reaction may be performed on a BioRad or MJ thermocycler with a cycling profile of 20 °C for 30 sec; 42 °C for 30 sec; 50 °C for 1 sec, for 60 cycles followed by one cycle of 85 °C for 5 min.

[00152] Real-time PCR. Two microliters of 1:400 diluted Pre-PCR product may be used for a 20 ul reaction. All reactions may be duplicated. Because the method is very robust, duplicate samples may be sufficient and accurate enough to obtain values for miRNA expression levels. TaqMan^® universal PCR master mix of ABI may be used according to manufacturer's suggestion. Briefly, lx TaqMan^® Universal Master Mix (ABI), 1 uM Forward Primer, 1 uM Universal Reverse Primer and 0.2 uM TaqMan^® Probe may be used for each real-time PCR. The conditions used may be as follows: 95°C for 10 min, followed by 40 cycles at 95°C for 15 s, and 60°C for 1 min. All the reactions may be run on ABI Prism 7000 Sequence Detection System.

[00153] Microarray hybridization and data processing. cDNA samples and total RNA (5 μg in each of eight individual tubes) may be subjected to the One-Cycle Target Labeling procedure for biotin labeling by in vitro transcription (IVT) (Affymetrix, Santa Clara, CA) or using the Illumina Total Prep RNA Labelling kit. For analysis on Affymetrix gene chips, the cRNA may be subsequently fragmented and hybridized to the Human Genome U133 Plus 2.0 Array (Affymetrix) according to the manufacturer's instructions. The microarray image data may be processed with the GeneChip Scanner 3000 (Affymetrix) to generate CEL data. The CEL data may be then subjected to analysis with dChip software, which has the advantage of normalizing and processing multiple datasets simultaneously. The expression levels of only the Present probes may be considered for all quantitative analyses described below. For analysis on Illumina Human HT-12 v4 Expression Bead Chips, labeled cRNA may be hybridized according to the manufacturer's instructions.

Generating an Immune Response Against Bladder Cancer

[00154] In some embodiments, antigen presenting cells (APCs) may be used to activate T lymphocytes in vivo or ex vivo, to elicit an immune response against cells expressing a cancer associated sequence. APCs are highly specialized cells and may include, without limitation, macrophages, monocytes, and dendritic cells (DCs). APCs may process antigens and display their peptide fragments on the cell surface together with molecules required for lymphocyte activation. In some embodiments, the APCs may be dendritic cells. DCs may be classified into subgroups, including, e.g., follicular dendritic cells, Langerhans dendritic cells, and epidermal dendritic cells. In other embodiments the present disclosure provides a method of eliciting an antibody response to one or more of the cancer associated sequences disclosed infra. The method may comprise administering a protein or a peptide fragment encoded by one or more of the cancer associated sequences disclosed infra to a subject.

[00155] Some embodiments are directed to the use of cancer associated polypeptides and polynucleotides encoding a cancer associated sequence, a fragment thereof, or a mutant thereof, and antigen presenting cells (such as, without limitation, dendritic cells), to elicit an immune response against cells expressing a cancer-associated polypeptide sequence, such as, without limitation, cancer cells, in a subject. In some embodiments, the method of eliciting an immune response against cells expressing a cancer associated sequence comprises (1) isolating a hematopoietic stem cell, (2) genetically modifying the cell to express a cancer associated sequence, (3) differentiating the cell into DCs; and (4) administering the DCs to the subject (e.g., human patient). In some embodiments, the method of eliciting an immune response includes (1) isolating DCs (or isolation and differentiation of DC precursor cells), (2) pulsing the cells with a cancer associated sequence, and; (3) administering the DCs to the subject. These approaches are discussed in greater detail, infra. In some embodiments, the pulsed or expressing DCs may be used to activate T lymphocytes ex vivo. These general techniques and variations thereof are within the skill of those in the art (see, e.g., W097/29182; WO 97/04802; WO 97/22349; WO 96/23060; WO 98/01538; Hsu et al., 1996, Nature Med. 2:52-58), and still other variations may be discovered in the future. In some embodiments, the cancer associated sequence is contacted with a subject to stimulate an immune response. In some embodiments, the immune response is a therapeutic immune response so as to treat a subject as described infra. In some embodiments, the immune response is a prophylactic immune response. For example, the cancer associated sequence can be contacted with a subject under conditions effective to stimulate an immune response. The cancer associated sequence can be administered as, for example, a DNA molecule {e.g. DNA vaccine), RNA molecule, or polypeptide, or any combination thereof. The identity of particular sequences useful in stimulating an immune response against bladder cancer cells {e.g., sequences of the markers disclosed in Table 3) was not known prior to the present disclosure. Any sequence or combination of sequences disclosed herein or a homologue thereof can be administered to a subject to stimulate an immune response.

[00156] In some embodiments, dendritic cell precursor cells are isolated for transduction with a cancer associated sequence, and induced to differentiate into dendritic cells. The genetically modified DCs express the cancer associated sequence, and may display peptide fragments on the cell surface.

[00157] In some embodiments, the cancer associated sequence expressed comprises a sequence of a naturally occurring protein. In some embodiments, the cancer associate sequence does not comprise a naturally occurring sequence. As already noted, fragments of naturally occurring proteins may be used; in addition, the expressed polypeptide may comprise mutations such as deletions, insertions, or amino acid substitutions when compared to a naturally occurring polypeptide, so long as at least one peptide epitope can be processed by the DC and presented on a MHC class I or II surface molecule. In some embodiments, it may be desirable to use sequences other than "wild type," in order to, for example, increase antigenicity of the peptide or to increase peptide expression levels. In some embodiments, the introduced cancer associated sequences may encode variants such as polymorphic variants (e.g., a variant expressed by a particular human patient) or variants characteristic of a particular cancer (e.g., a cancer in a particular subject).

[00158] In some embodiments, a cancer associated sequence may be introduced (transduced) into DCs or stem cells in any of a variety of standard methods, including transfection, recombinant vaccinia viruses, adeno-associated viruses (AAVs), retroviruses, etc. [00159] In some embodiments, the transformed DCs of the present disclosure may be introduced into the subject (e.g., without limitation, a human patient) where the DCs may induce an immune response. Typically, the immune response includes a cytotoxic T-lymphocyte (CTL) response against target cells bearing antigenic peptides (e.g., in a MHC class I/peptide complex). These target cells are typically cancer cells.

[00160] In some embodiments, when the DCs are to be administered to a subject, they may preferably isolated from, or derived from precursor cells from, that subject (i.e., the DCs may administered to an autologous subject). However, the cells may be infused into HLA-matched allogeneic or HLA-mismatched allogeneic subject. In the latter case, immunosuppressive drugs may be administered to the subject.

[00161] In some embodiments, the cells may be administered in any suitable manner. In some embodiments, the cell may be administered with a pharmaceutically acceptable carrier (e.g., saline). In some embodiments, the cells may be administered through intravenous, intra- articular, intramuscular, intradermal, intraperitoneal, or subcutaneous routes. Administration (i.e., immunization) may be repeated at time intervals. Infusions of DC may be combined with administration of cytokines that act to maintain DC number and activity (e.g., GM-CSF, IL-12).

[00162] In some embodiments, the dose administered to a subject may be a dose sufficient to induce an immune response as detected by assays which measure T cell proliferation, T lymphocyte cytotoxicity, and/or effect a beneficial therapeutic response in the patient over time, e.g., to inhibit growth of cancer cells or result in reduction in the number of cancer cells or the size of a tumor.

[00163] In some embodiments, DCs are obtained (either from a patient or by in vitro differentiation of precursor cells) and pulsed with antigenic peptides having a cancer associated sequence. The pulsing results in the presentation of peptides onto the surface MHC molecules of the cells. The peptide/MHC complexes displayed on the cell surface may be capable of inducing a MHC-restricted cytotoxic T-lymphocyte response against target cells expressing cancer associated polypeptides (e.g., without limitations, cancer cells).

[00164] In some embodiments, cancer associated sequences used for pulsing may have a length of at least about 6 or 8 amino acids and fewer than about 30 amino acids or fewer than about 50 amino acid residues. In some embodiments, an immunogenic peptide sequence may have from about 8 to about 12 amino acids. In some embodiments, a mixture of human protein fragments may be used; alternatively a particular peptide of defined sequence may be used. The peptide antigens may be produced by de novo peptide synthesis, enzymatic digestion of purified or recombinant human peptides, by purification of the peptide sequence from a natural source (e.g., a subject or tumor cells from a subject), or expression of a recombinant polynucleotide encoding a human peptide fragment.

[00165] In some embodiments, the amount of peptide used for pulsing DC may depend on the nature, size and purity of the peptide or polypeptide. In some embodiments, an amount of from about 0.05 ug/ml to about 1 mg/ml, from about 0.05 ug/ml to about 500 ug/ml, from about 0.05 ug/ml to about 250 ug/ml, from about 0.5 ug/ml to about 1 mg/ml, from about 0.5 ug/ml to about 500 ug/ml, from about 0.5 ug/ml to about 250 ug/ml, or from about 1 ug/ml to about 100 ug/ml of peptide may be used. After adding the peptide antigen(s) to the cultured DC, the cells may then be allowed sufficient time to take up and process the antigen and express antigen peptides on the cell surface in association with either class I or class II MHC. In some embodiments, the time to take up and process the antigen may be about 18 to about 30 hours, about 20 to about 30 hours, or about 24 hours.

[00166] Numerous examples of systems and methods for predicting peptide binding motifs for different MHC Class I and II molecules have been described. Such prediction could be used for predicting peptide motifs that will bind to the desired MHC Class I or II molecules. Examples of such methods, systems, and databases that those of ordinary skill in the art might consult for such purpose include:

[00167] 1. Peptide Binding Motifs for MHC Class I and II Molecules; William E. Biddison, Roland Martin, Current Protocols in Immunology, Unit II (DOI: 10.1002/0471142735.ima01is36; Online Posting Date: May, 2001).

[00168] Reference 1 above provides an overview of the use of peptide-binding motifs to predict interaction with a specific MHC class I or II allele, and gives examples for the use of MHC binding motifs to predict T-cell recognition.

[00169] One skilled in the art of peptide-based vaccination may determine which peptides would work best in individuals based on their HLA alleles (e.g., due to "MHC restriction"). Different HLA alleles will bind particular peptide motifs (usually 2 or 3 highly conserved positions out of 8-10) with different affinities which can be predicted theoretically or measured as dissociation rates. Thus, a skilled artisan may be able to tailor the peptides to a subject's HLA profile.

[00170] In some embodiments, the present disclosure provides methods of eliciting an immune response against cells expressing a cancer associated sequence comprising contacting a subject with a cancer associated sequence under conditions effective to elicit an immune response in the subject, wherein said cancer associated sequence comprises a sequence or fragment thereof of a gene selected from one or more of the cancer associated sequences disclosed herein.

Transfecting Cells With Cancer Associated Sequences

[00171] Cells may be transfected with one or more of the cancer associated sequences disclosed herein. Transfected cells may be useful in screening assays, diagnosis and detection assays. Transfected cells expressing one or more cancer associated sequences as disclosed herein may be used to obtain isolated nucleic acids encoding cancer associated sequences and/or isolated proteins or peptide fragments encoded by one or more cancer associated sequences.

[00172] Electroporation may be used to introduce the cancer associated nucleic acids described herein into mammalian cells (Neumann, E. et al. (1982) EMBO J. 1, 841-845), plant and bacterial cells, and may also be used to introduce proteins (Marrero, M.B. et al. (1995) J. Biol. Chem. 270, 15734-15738; Nolkrantz, K. et al. (2002) Anal. Chem. 74, 4300-4305; Rui, M. et al. (2002) Life Sci. 71, 1771-1778). Cells suspended in a buffered solution of the purified protein of interest are placed in a pulsed electrical field. Briefly, high-voltage electric pulses result in the formation of small (nanometer- sized) pores in the cell membrane. Proteins enter the cell via these small pores or during the process of membrane reorganization as the pores close and the cell returns to its normal state. The efficiency of delivery may be dependent upon the strength of the applied electrical field, the length of the pulses, the temperature and the composition of the buffered medium. Electroporation is successful with a variety of cell types, even some cell lines that are resistant to other delivery methods, although the overall efficiency is often quite low. Some cell lines may remain refractory even to electroporation unless partially activated.

[00173] Microinjection may be used to introduce femtoliter volumes of DNA directly into the nucleus of a cell (Capecchi, M.R. (1980) Cell 22, 470-488) where it can be integrated directly into the host cell genome, thus creating an established cell line bearing the sequence of interest. Proteins such as antibodies (Abarzua, P. et al. (1995) Cancer Res. 55, 3490-3494; Theiss, C. and Meller, K. (2002) Exp. Cell Res. 281, 197-204) and mutant proteins (Naryanan, A. et al. (2003) J. Cell Sci. 116, 177-186) can also be directly delivered into cells via microinjection to determine their effects on cellular processes firsthand. Microinjection has the advantage of introducing macromolecules directly into the cell, thereby bypassing exposure to potentially undesirable cellular compartments such as low-pH endosomes.

[00174] Several proteins and small peptides have the ability to transduce or travel through biological membranes independent of classical receptor-mediated or endocytosis-mediated pathways. Examples of these proteins include the HIV-1 TAT protein, the herpes simplex virus 1 (HSV-1) DNA-binding protein VP22, and the Drosophila Antennapedia (Antp) homeotic transcription factor. In some embodiments, protein transduction domains (PTDs) from these proteins may be fused to other macromolecules, peptides or proteins such as, without limitation, a cancer associated polypeptide or fragment thereof, to successfully transport the polypeptide into a cell (Schwarze, S.R. et al. (2000) Trends Cell Biol. 10, 290-295). Exemplary advantages of using fusions of these transduction domains is that protein entry is rapid, concentration-dependent and appears to work with cell types that are difficult to transduce using other methods (Fenton, M. et al. (1998) J. Immunol. Methods 212, 41-48).

[00175] In some embodiments, liposomes may be used as vehicles to deliver oligonucleotides, DNA (gene) constructs and small drug molecules into cells (Zabner, J. et al. (1995) J. Biol. Chem. 270, 18997-19007; Feigner, P.L. et al. (1987) Proc. Natl. Acad. Sci. USA 84, 7413-7417). Certain lipids, when placed in an aqueous solution and sonicated, form closed vesicles consisting of a circularized lipid bilayer surrounding an aqueous compartment. The vesicles or liposomes of embodiments herein may be formed in a solution containing the molecule to be delivered. In addition to encapsulating DNA in an aqueous solution, cationic liposomes may spontaneously and efficiently form complexes with DNA, with the positively charged head groups on the lipids interacting with the negatively charged backbone of the DNA. The exact composition and/or mixture of cationic lipids used can be altered, depending upon the macromolecule of interest and the cell type used (Feigner, J.H. et al. (1994) J. Biol. Chem. 269, 2550-2561). The cationic liposome strategy has also been applied successfully to protein delivery (Zelphati, O. et al. (2001) J. Biol. Chem. 276, 35103-35110). Because proteins are more heterogeneous than DNA, the physical characteristics of the protein, such as its charge and hydrophobicity, may influence the extent of its interaction with the cationic lipids. Kits

[00176] Also provided by the invention are kits and systems for practicing the subject methods, as described above, such components configured to diagnose cancer in a subject, treat cancer in a subject, detect cancer in a sample, or perform basic research experiments on cancer cells (e.g., either derived directly from a subject, grown in vitro or ex vivo, or from an animal model of cancer. The various components of the kits may be present in separate containers or certain compatible components may be pre-combined into a single container, as desired.

[00177] In some embodiments, the present disclosure provides a kit for diagnosing the presence of cancer in a test sample, said kit comprising at least one polynucleotide that selectively hybridizes to a cancer associated polynucleotide sequence chosen from any one or more of the genes listed in Table 3, or a fragment or a complement thereof. In another embodiment the invention provides an electronic library comprising a cancer associated polynucleotide, a cancer associated polypeptide, or fragment thereof, disclosed infra. In some embodiments the kit may include one or more capture reagents or specific binding partners of one or more cancer associated sequences disclosed infra.

[00178] The subject systems and kits may also include one or more other reagents for performing any of the subject methods. The reagents may include one or more matrices, solvents, sample preparation reagents, buffers, desalting reagents, enzymatic reagents, denaturing reagents, probes, polynucleotides, vectors (e.g., plasmid or viral vectors), etc., where calibration standards such as positive and negative controls may be provided as well. As such, the kits may include one or more containers such as vials or bottles, with each container containing a separate component for carrying out a sample processing or preparing step and/or for carrying out one or more steps for producing a normalized sample according to the present disclosure.

[00179] In addition to above-mentioned components, the subject kits typically further include instructions for using the components of the kit to practice the subject methods. The instructions for practicing the subject methods are generally recorded on a suitable recording medium. For example, the instructions may be printed on a substrate, such as paper or plastic, etc. As such, the instructions may be present in the kits as a package insert, in the labeling of the container of the kit or components thereof (i.e., associated with the packaging or sub-packaging) etc. In other embodiments, the instructions are present as an electronic storage data file present on a suitable computer readable storage medium, e.g. CD-ROM, diskette, etc. In yet other embodiments, the actual instructions are not present in the kit, but means for obtaining the instructions from a remote source, e.g. via the internet, are provided. An example of this embodiment is a kit that includes a web address where the instructions can be viewed and/or from which the instructions can be downloaded. As with the instructions, this means for obtaining the instructions is recorded on a suitable substrate.

[00180] In addition to the subject database, programming and instructions, the kits may also include one or more control samples and reagents, e.g., two or more control samples for use in testing the kit.

EXAMPLES

[00181] The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the present invention, and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed.

Example 1: Identification of bladder cancer mRNA biomarkers via microarray

analysis of patient urine samples

[00182] In order to evaluate the feasibility of using urine-based mRNA biomarkers to distinguish bladder cancer from benign conditions, and to identify most robust biomarkers for the development of a gene expression classifier for use in diagnosis and detection of bladder cancer, mRNA biomarkers were examined in urine samples from patients undergoing cystoscopy for hematuria or bladder cancer recurrence surveillance. Biomarker identification was carried out via microarray analysis of patient urine samples collected at 9 independent sites in a training set consisting of 241 samples. The microarray data were subjected to different feature selection algorithms, one of which (Lasso [23]) was used to select a total of 125 markers for follow-up analysis. Additional data analysis based on differential marker expression between high grade urothelial carcinoma and benign samples identified additional 46 markers. The combined 125 plus 46 markers were selected to form a single 171-gene expression classifier combining the hematuria and recurrence surveillance cohorts. The 171-marker classifier was transferred to a custom Nanostring nCounter Elements platform for a streamlined assay for bladder cancer detection from urine specimens.

[00183] Sample collection. All patient urine samples were collected with informed patient consent and under an Institutional Review Board-approved protocol at 9 independent sites, all community practices in the United States. Voided urine samples were collected from two different patient groups: (1) Hematuria: patients presenting with hematuria with no prior history of bladder cancer and (2) Recurrence: patients with a history of bladder cancer undergoing routine surveillance for recurrence. All patients were undergoing cystoscopy to rule out/diagnose bladder cancer and a voided urine sample was collected just prior to the cystoscopy procedure. Patients without any visible tumor or suspicious growth as determined by cystoscopy were designated as "benign" for this analysis while assignment of the "malignant" designation required pathology confirmation. Additionally, some malignant samples were collected from patients prior to surgery with subsequent pathology confirmation.

[00184] Microarray analysis for the biomarker selection set. Two hundred forty one patient urine samples were used for mRNA biomarker discovery (Table 1): 62 diagnosed with urothelial carcinoma and 179 diagnosed with benign conditions. Samples were collected from patients undergoing bladder cystoscopy for potential bladder cancer either because they presented with hematuria, a common symptom of bladder cancer, or because they were undergoing surveillance for a possible recurrence of urothelial carcinoma. Malignant samples were analyzed consecutively; benign samples were randomly selected to be representative of all of the collection sites and patient cohorts (recurrence and hematuria).

Table 1. Samples in the microarray dataset.

[00185] Voided urine samples (45 mL) were centrifuged at 600-800 x g and the supernatant discarded. Remaining liquid and pellet was transferred to a 1.5 mL microfuge tube and centrifuged for 5 minutes at room temperature. The supernatant was removed and the pellet resuspended in 50 μΐ_^ of lysis Solution from the SurePrep™ Urine Exfoliated Cell RNA Purification Kit (Thermo Fischer Scientific, Waltham, MA). The sample lysate was stored at - 80°C before NanoString analysis.

[00186] Total RNA was quantified using the ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE), amplified using the TargetAmp™-Pico Labeling Kit (Epicentre Technologies, Madison, WI) and purified using RNeasy Mini Kit columns (Qiagen, Valencia, CA). Samples with insufficient RNA yield (less than 100 ng/μΕ) were eliminated from further analysis. The remaining samples were processed for microarray analysis using the HumanHT-12 v4 Expression BeadChip (Illumina, San Diego, CA) and BeadArray Reader (Illumina, San Diego, CA). A quality control threshold for the microarray data was set based on the number of present calls detected. The final microarray dataset contained 241 samples comprised of 62 malignant and 179 benign samples (Table 1).

[00187] Marker Selection and classifier development on the microarray dataset. The microarray dataset was used to select a subset of microarray markers for transfer to Nanostring platform using machine learning analysis. Our approach was to run cross-validation using different combinations of marker selection and classification algorithms. The combination which produced the best performance was selected for the final marker selection step, which entailed running the marker selection on the entire training set.

[00188] The data was split in two classes, malignant and benign. No attempt was made to distinguish high vs. low grade cancers, due to available samples at the time of the microarray analyses. (High vs. low grade classification was performed later on using the Nanostring dataset.)

[00189] The following feature selection algorithms were applied to select the markers:

[00190] Pearson's univariate ranking: the Pearson's correlation coefficient was calculated between each microarray marker and the output category (benign or malignant). The absolute values of the coefficients were sorted in descending order and the first N markers were selected.

[00191] Lasso: Lasso (least absolute shrinkage and selection operator, [23]) creates linear models where the residual sum of squares subject to the sum of the absolute value of the coefficients is less than a constant. Due to the nature of this constraint the lasso method tends to produce some coefficients to be exactly zero and, therefore, in effect performs feature selection. [00192] Random Forest Importance: Random Forest [24] [ML-2] utilizes multiple classification trees trained on bootstrap subsets of the training dataset. The prediction of a random forest is the majority vote the classification trees. For each marker it is possible to calculate its frequency (importance) in the classification trees. The frequencies are sorted in descending order and the first N markers are selected.

[00193] We combined Support Vector Machine (SVM, [25]) and Random Forest classifiers with all three feature selection methods. In addition, for Lasso we used its selected markers with a logistic regression.

[00194] The area under receiver operating curve (AUROC) of a classifier was chosen as the measure for selecting best markers. AUROC is a common rank measure used in selection of probabilistic classifiers, defined as probability that classifier will give higher probabilities to positive (malignant) samples than to negative (benign) samples. The AUROC was estimated using 50 repeats of 10-fold pooled cross-validation [26].

[00195] In order to assess the "information loss" induced by choosing a subset of all available microarray markers, we also applied Support Vector Machine, Random Forest and ElasticNet [27] on all microarray markers.

[00196] Marker selection from the microarray dataset based on classifier analysis. The models achieving the highest AUROC values are shown in Table 2. The Lasso, ElasticNet and Pearson correlation feature selection methodologies followed by linear SVM all yielded similar performances with AUROC values in a narrow range from 0.86 - 0.88. However, the number of gene probes necessary to achieve this performance varied widely: 1850 probes for Pearson correlation, 257 for Elastic Net and 133 for Lasso.

Table 2.

[00197] While the ElasticNet feature selection followed by linear SVM yielded the highest AUROC at 0.88, the Lasso methodology performed similarly (AUROC = 0.87) with far fewer probes. Of the 133 markers selected by Lasso, 125 markers were selected to be transferred to the NanoString platform.

[00198] Additional marker selection. An additional 46 markers were selected for the 171-marker classifier panel (to be transferred to the NanoString platform) using an independent method based on differential gene expression between malignant high grade urothelial carcinoma (HGUC) and benign samples. Raw data was imported into GeneSpring GX software (Agilent Technologies, Santa Clara, CA) and normalized using the percentile shift normalization algorithm. An unpaired t-test was performed comparing HGUC samples to benign samples. The p-values were computed asymptotically using a fold change cutoff of >2.0 and a p-value cutoff of <0.05. Entities passing the cutoff criteria were ranked by p-value and the top 44 markers (plus two housekeeping genes) were selected to be included in the final panel of 171 genes. The 171 markers included in the 171-gene expression classifier and transferred into the NanoString platform are listed in Table 3.

Table 3. 171-marker bladder cancer classifier distinguishing between malignant bladder cancer and benign samples.

Differential

Number ProbelD Symbol Lasso Housekeeping expression

1 50440 ZBTB2 X #N/A #N/A

2 110324 MAP2K6 X #N/A #N/A

LOC1001324

3 240386 39 X #N/A #N/A

4 450615 MT2A X #N/A #N/A

5 460010 TSPAN7 X #N/A #N/A

6 460220 ITGA1 X #N/A #N/A

LOC1001297

7 540598 58 X #N/A #N/A

8 670278 NES X #N/A #N/A

9 770564 Clorfl l5 X #N/A #N/A

10 840554 RYBP X #N/A #N/A

11 940750 DA645971 X #N/A #N/A

12 1010082 AV737317 X #N/A #N/A 1030433 CALML4 X #N/A #N/A

1190703 ID02 X #N/A #N/A

1230017 PHCA X #N/A #N/A

1300397 CRISP 1 X #N/A #N/A

1300470 MAMDC2 X #N/A #N/A

1400044 HSPA12A X #N/A #N/A

1410100 BM979825 X #N/A #N/A

1410470 FAM71E1 X #N/A #N/A

1450273 CLUAP1 X X #N/A

1450504 AI349750 X #N/A #N/A

1510424 S 100P X #N/A #N/A

1580397 ISCA2 X #N/A #N/A

1690053 TTYH2 X #N/A #N/A

1690056 LYZ X #N/A #N/A

1850037 CB999335 X #N/A #N/A

1940414 CSTL1 X #N/A #N/A

1980706 ATP6V0D2 X #N/A #N/A

2000148 IFIT1 X #N/A #N/A

2030180 BI836710 X #N/A #N/A

2140279 HINT3 X #N/A #N/A

2190154 UPK2 X #N/A #N/A

2230475 C21orfl30 X #N/A #N/A

2230538 LRRN3 X #N/A #N/A

2370341 LOC91561 X #N/A #N/A

2450647 KRT1 X #N/A #N/A

2480717 FCGR2B X #N/A #N/A

2680056 CES 1 X #N/A #N/A

2750196 CSF2 X #N/A #N/A

2850458 CACNB2 X #N/A #N/A

2900360 KIR2DL4 X #N/A #N/A

2940747 KCNK4 X #N/A #N/A

3060477 RPL8 X #N/A #N/A

3060523 NAMPT X #N/A #N/A

3170598 SNORA74B X #N/A #N/A

3390376 ZNF134 X #N/A #N/A

3400019 RGS2 X #N/A #N/A

3400240 PRDM16 X #N/A #N/A

3420528 GPR63 X #N/A #N/A

3440133 RNF150 X #N/A #N/A 3460070 SPP1 X #N/A #N/A

3460349 MT1JP X #N/A #N/A

3460452 LOC648394 X #N/A #N/A

3710168 KRT34 X #N/A #N/A

3710554 FGD5 X #N/A #N/A

LOC1001296

3800592 97 X #N/A #N/A

3840519 DPEP3 X #N/A #N/A

LOC1001278

3870132 86 X #N/A #N/A

3990341 FAM176A X #N/A #N/A

4010634 CRYBB2 X #N/A #N/A

4040398 MAL X #N/A #N/A

4050561 PLA2G2F X #N/A #N/A

4050647 CD5L X #N/A #N/A

4150608 LOC644619 X #N/A #N/A

4180768 ALAS 2 X #N/A #N/A

4200044 DIOl X #N/A #N/A

4200209 RBKS X #N/A #N/A

4220437 UCN2 X #N/A #N/A

4220541 ZNF431 X #N/A #N/A

4260044 SQSTM1 X #N/A #N/A

4260435 ERCC2 X #N/A #N/A

4290040 NPPB X #N/A #N/A

4390768 PCDHA1 X #N/A #N/A

4480079 AQP2 X #N/A #N/A

4480437 PIM3 X #N/A #N/A

4490411 KRTAP9-4 X #N/A #N/A

4490671 MIF X #N/A #N/A

4540692 LOC730284 X #N/A #N/A

4560468 CLDN10 X #N/A #N/A

4560497 ETNK2 X #N/A #N/A

4610424 RBP4 X #N/A #N/A

4640039 FER1L4 X #N/A #N/A

4640133 PSORS 1C2 X #N/A #N/A

4810575 ADAMTSL2 X #N/A #N/A

4850092 ACSM5 X #N/A #N/A

4860719 ROCK2 X #N/A #N/A

4900341 GBA3 X #N/A #N/A 89 4920767 FTL X #N/A #N/A

90 5050347 CD5 X #N/A #N/A

91 5090630 AW967735 X #N/A #N/A

92 5260551 C8B X #N/A #N/A

93 5310739 SEMA5B X #N/A #N/A

94 5420600 BEST1 X #N/A #N/A

95 5490446 HLA-DPB2 X #N/A #N/A

96 5550414 RPRM X #N/A #N/A

97 5570711 IDOl X #N/A #N/A

98 5720725 ARG2 X #N/A #N/A

99 5860470 TRIM 15 X #N/A #N/A

100 5890400 SPRR2E X #N/A #N/A

101 5900050 LOC653800 X #N/A #N/A

102 5900189 PDE1A X #N/A #N/A

103 5910079 LOC728226 X #N/A #N/A

104 5960102 CLDN16 X #N/A #N/A

105 5960133 NFIB X #N/A #N/A

LOC1001281

106 6040576 63 X #N/A #N/A

107 6060678 LOC401317 X #N/A #N/A

108 6130047 CCDC151 X #N/A #N/A

109 6200402 MT1A X #N/A #N/A

110 6370414 CLECL1 X #N/A #N/A

111 6370541 CST1 X #N/A #N/A

112 6450148 KRT33B X #N/A #N/A

113 6520215 ANXA1 X #N/A #N/A

114 6560195 PRAMEF13 X #N/A #N/A

115 6560279 VAV3 X #N/A #N/A

116 6960246 FLJ46230 X #N/A #N/A

117 7100040 FXYD4 X #N/A #N/A

118 7100484 PMFBP1 X #N/A #N/A

119 7150368 LOC653244 X #N/A #N/A

120 7210059 LRCH3 X #N/A #N/A

121 7320129 RAB36 X #N/A #N/A

122 7330184 SPRR1A X #N/A #N/A

123 7380343 P2RY2 X #N/A #N/A

124 7570095 PPFIA4 X #N/A #N/A

125 7570408 CCL5 X #N/A #N/A

126 2030148 WDR54 #N/A #N/A X 127 5340632 UMOD #N/A #N/A X

128 2320168 TMPRSS l lD #N/A #N/A X

129 4610131 SPRR3 #N/A #N/A X

130 6770187 SPRR2A #N/A #N/A X

131 6380707 SPINK5 #N/A #N/A X

132 7610433 SLC1A5 #N/A #N/A X

133 5050270 SALL4 #N/A #N/A X

134 6180039 RPS3 #N/A #N/A X

135 2140753 RPL14 #N/A #N/A X

136 4010296 RNASE1 #N/A #N/A X

137 5050193 RLTPR #N/A #N/A X

138 1030142 RHCG #N/A #N/A X

139 2650564 RARRES3 #N/A #N/A X

140 60092 PUS 1 #N/A #N/A X

141 5570445 PRR5 #N/A #N/A X

142 10543 PNCK #N/A #N/A X

143 4860152 PLA2G2A #N/A #N/A X

144 2000373 ΡΓΓΧ1 #N/A #N/A X

145 50600 PIGR #N/A #N/A X

146 1820196 OVGP1 #N/A #N/A X

147 3840148 NCCRP1 #N/A #N/A X

148 150750 LOC347292 #N/A #N/A X

LOC1001330

149 1450059 08 #N/A #N/A X

150 1980309 IL8 #N/A #N/A X

151 6980458 HSD17B2 #N/A #N/A X

152 4610520 GCNT3 #N/A #N/A X

153 4730204 FCRLB #N/A #N/A X

154 4830685 FBLN1 #N/A #N/A X

155 4880360 FBL #N/A #N/A X

156 4120333 ERP29 #N/A #N/A X

157 3450719 EEF1A1 #N/A #N/A X

158 3450521 ECM1 #N/A #N/A X

159 6580408 CTSW #N/A #N/A X

160 5890451 CTNNA1 #N/A #N/A X

161 6110079 CRYAB #N/A #N/A X

162 2100132 CRNN #N/A #N/A X

163 2260445 CRH #N/A #N/A X

164 3400296 CRABP2 #N/A #N/A X 165 7400377 CEACAM6 #N/A #N/A X

166 1580411 CD3D #N/A #N/A X

167 4730356 C19orf31 #N/A 4730356 #N/A

168 20440 BHMT2 #N/A #N/A X

169 4180452 ATP1B 1 #N/A #N/A X

170 4890494 ANXA2P2 #N/A #N/A X

171 4920148 ALDH1A3 #N/A #N/A X

Example 2 - Gene Expression Classifier Combining Hematuria and Recurrence Cohorts on NanoString® dataset

[00199] Because microarray methodology is not particularly well suited for clinical applications, markers identified in Table 3 were transferred to the NanoString® nCounter Elements™ platform to develop an assay better suited for clinical laboratories and applications. The NanoString® nCounter Elements™ platform has a limit of 200 probes and cost of goods goes up incrementally with the number of probes. Accordingly, we strove to seek a reasonable balance between maximizing performance and minimizing the number of probes. The 171 selected markers included 125 probes/markers identified by Lasso analysis as well as additional 46 genes that were either: i) differentially expressed based on p-value or ii) housekeeping reference genes, as indicated in Table 3.

[00200] NanoString® assay. The NanoString® nCounter Analysis System (NanoString Technologies, Seattle, WA) was used with a custom designed 171-gene NanoString Elements™ panel to quantitate gene expression levels in 5 μΐ_^ of sample lysate. An nCounter Elements™ panel was designed using unlabeled oligonucleotides to target genes of interest and General Purpose Reagent (GPR) color-coded molecular barcodes and capture tags that allow for the direct digital counting of RNA molecules. A quality control threshold of raw mean counts >10 was set empirically and was based on classifier performance in earlier feasibility studies. Implementation of this quality control threshold did not result in the elimination of any of the analyzed samples.

[00201] The NanoString® platform allows for the direct digital counting of RNAs in cell lysates, eliminating the need to purify and amplify RNA. Urine samples are processed by centrifugation; the cell pellet is resuspended in lysis buffer and then a small fraction of this crude lysate is loaded directly into the NanoString® hybridization reaction, minimizing sample handling and resulting in a simplified workflow. [00202] Results. The 171-marker NanoString® panel was tested on an expanded sample set (n = 262) of urine sediment lysates. 202 samples overlapped with the microarray dataset and 60 samples were previously untested. A machine learning strategy was used on the NanoString® dataset with the goal of developing a single overarching gene expression classifier that distinguishes between malignant and benign samples, without separating out hematuria or recurrence cohorts or high-grade or low-grade malignancies. A variety of algorithms were evaluated (data not shown); the best performing model by AUROC was an SVM with RBF kernel, achieving an AUROC of 0.85. A distinct model, defined by a clinically favorable criterion of maximum specificity for sensitivity at least 90%, is shown in Figure 3 A. It achieved AUROC of 0.85 using 27 probes/markers. The similarity in performance level between the highest AUROC model on the microarray dataset (AUROC = 0.87) and the highest AUROC model on the NanoString dataset (AUROC = 0.85) indicated that the transition from the microarray platform to the NanoString platform was achieved without significantly compromising performance.

[00203] This model was derived from a heterogeneous dataset comprised of samples from hematuria and recurrence cohorts and both high and low-grade malignancies. The performance of this overarching model in these individual subgroups is shown in Figure 3B. For both the hematuria and recurrence cohorts, the accuracy for detecting high-grade lesions was 100%. The accuracy for the detection of low-grade lesions was lower: 77% for the hematuria cohort and 75% for the recurrence cohort.

Example 3 - Further classifier development on the NanoString® dataset.

[00204] We sought to develop a classifier(s) which accurately detect the presence of high grade and low grade bladder cancer in the hematuria and recurrence populations. With the goal of maximizing performance in these patient populations, we examined the performance of classifiers developed on the whole dataset versus separate classifiers developed on the hematuria and recurrence subsets. Additionally, since the high-grade and low-grade are morphologically distinct, we also evaluated the performance of separate classifiers for high and low grade as well as for the hematuria and recurrence patient cohorts.

[00205] We developed binary classifiers for the following four scenarios: 1) high-grade hematuria (n = 23) vs. other (low-grade + benign) (n = 77); 2) low-grade hematuria (n = 23) vs. benign (n = 77); 3) high-grade recurrence (n = 23) vs. other (low-grade + benign) (n = 74); and 4) low-grade recurrence (n = 23) vs. benign (n = 74). The raw Nanostring data (n=215) was normalized using quantile normalization [28].

[00206] We required that the classifier must report probability of disease and not just a binary yes/no answer. This is critical for at least two reasons: 1) tests which report probability provide an intuitive aid to diagnosis and leave the decision making in the hands of a clinician 2) such tests facilitate optimization of sensitivity and specificity of the resulting classifier by adjusting decision threshold. We focused our attention on four state-of-the-art types of probabilistic classifiers, chosen due to established track record in molecular clinical and other applications, and because they utilize different approaches to estimating probabilities: 1) ElasticNet; 2) Multi-layer perceptron neural network [29]; Random Forest; and Support Vector Machine. We again chose AUROC as the measure for selecting best classifiers and applied repeated 10-fold cross-validation for model selection.

[00207] Results. Results for the four-classifier approach are depicted in Figures 5A-5B (hematuria cohort) and 6A-6B (recurrence cohort). The best performing gene expression classifier developed for the detection of high-grade urothelial carcinoma in patients presenting with hematuria (n=123) performed with a cross-validated AUROC of 0.93, while the gene expression classifier for low-grade urothelial carcinoma in patients presenting with hematuria performed with an AUROC of 0.81. In the recurrence surveillance cohort (n=120) the gene expression classifier developed for the detection of high-grade urothelial carcinoma performed with an AUC = 0.81 and the gene expression classifier developed for detection of low-grade urothelial carcinoma performed with an AUROC = 0.64.

References:

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Organization/International Society of Urological Pathology consensus classification of urothelial (transitional cell) neoplasms of the urinary bladder. Bladder Consensus Conference Committee. Am J Surg Pathol 22: 1435-1448.

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bladder cancer management: present and future. Am J Clin Exp Urol 2: 1-14. man MF, Pashos CL, Redaelli A, Laskin B, Hauser R (2003) The health economics of bladder cancer: a comprehensive review of the published literature. Pharmacoeconomics 21: 1315-1330.

D, Karl A, Knuchel R, Stepp H, Hartmann A, et al. (2005) Diagnosis of urothelial carcinoma of the bladder using fluorescence endoscopy. BJU Int 96: 217-222.

HE, Omar AA, Elgammal MA, Ibrahim GH (2014) Utility of urine cytology in evaluating hematuria with sonographically suspected bladder lesion in patients older than 50 years. Urol Ann 6: 212-217.

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(2013) The Johns Hopkins Hospital template for urologic cytology samples: parts II and III: improving the predictability of indeterminate results in urinary cytologic samples: an outcomes and cytomorphologic study. Cancer Cytopathol 121: 21-28.

RK, Lieberman SF, Slezak JM, Landa HM, Mariani AJ, et al. (2013) Stratifying risk of urinary tract malignant tumors in patients with asymptomatic microscopic hematuria. Mayo Clin Proc 88: 129-138.

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JAMA 241: 149-150.

artino M, Shariat SF, Hofbauer SL, Lucca I, Taus C, et al. (2014) Aurora A Kinase as a diagnostic urinary marker for urothelial bladder cancer. World J Urol.

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microRNA-99a and microRNA-125b are diagnostic markers for the non-invasive screening of bladder cancer. PLoS One 9: el00793.

El-Hakim TF, El-Shafie MK, Abdou AG, Azmy RM, El-Naidany SS, et al. (2014)

Value of urinary survivin as a diagnostic marker in bladder cancer. Anal Quant

Cytopathol Histpathol 36: 121-127.

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endorf L, Grilli B, Sauter G, Mihatsch MJ, Gasser TC, et al. (2001) Multiprobe FISH for enhanced detection of bladder cancer in voided urine specimens and bladder washings. Am J Clin Pathol 116: 79-86.

endorf L, Grilli B (2004) UroVysion multiprobe FISH in urinary cytology. Methods Mol

Med 97: 117-131.

shirani R (1996) Regression shrinkage and selection via the lasso. Journal of the Royal

Statistical Society Series B (Methodological): 267-288. 24. Breiman L (2001) Random forests. Machine Learning 45: 5-32.

25. Chang C, Lin C (2011) LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST) 2: 27.

26. Krstajic D, Buturovic LJ, Leahy DE, Thomas S (2014) Cross-validation pitfalls when

selecting and assessing regression and classification models. J Cheminform 6: 10.

27. Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67: 301-320.

28. Bolstad BM, Irizarry RA, Astrand M, Speed TP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.

Bioinformatics 19: 185-193.

29. Ripley BD (2007) Pattern recognition and neural networks. Cambridge University Press.

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[ML-1] Tibshirani R. Regression shrinkage and selection via the lasso. Journal of the Royal

Statistical Society. Series B (Methodological). 1996 Jan 1:267-88.

[ML-2] Breiman L. Random forests. Machine learning. 2001 Oct l;45(l):5-32.

[ML-3] Chang CC, Lin CJ. LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST). 2011 Apr 1;2(3):27.

[ML-4] Zou H, Hastie T. Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (Statistical Methodology). 2005 Apr l;67(2):301-20.

[ML-5] Krstajic D, Buturovic LJ, Leahy DE, Thomas S. Cross-validation pitfalls when selecting and assessing regression and classification models. Journal of cheminformatics. 2014 Dec l;6(l): l-5.

References for Nanostring machine learning section

[ML-6] Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003 Jan 22; 19(2): 185-93.

[ML-7] Ripley BD. Pattern recognition and neural networks. Cambridge university press; 2007.

Claims

CLAIMS What is claimed is:

1. A method for diagnosing bladder cancer in a subject by analyzing a subject sample for the differential expression of one or more markers encoded by one or more genes listed in Table 3, wherein the subject is diagnosed with bladder cancer if one or more markers from Table 3 is differentially expressed.

2. The method of claim 1, wherein the one or more makers comprises a nucleic acid.

3. The method of claim 1, wherein the one or more markers comprises a peptide.

4. The method of claim 1, wherein analyzing a subject sample comprises contacting the subject sample with one or more agents that specifically bind to proteins encoded by one or more of the genes listed in Table 3 and detecting binding to determine whether the protein is differentially expressed.

5. The method of claim 4, wherein the agent is selected from the group consisting of an antibody and an aptamer.

6. The method of claim 5, wherein the aptamer comprises an oligonucleotide, optionally further comprising one or more modified bases.

7. The method of claim 5, wherein the aptamer comprises a peptide.

8. The method of claim 1, wherein the subject sample is a bodily fluid selected from the group consisting of blood, plasma, serum and urine.

9. The method of claim 1, wherein the subject sample is a cell or tissue sample.

10. The method of claim 1, wherein the subject is a human.

11. The method of claim 1, wherein the subject is diagnosed with high-grade urothelial carcinoma.

12. The method of claim 1, wherein the subject is diagnosed with low-grade urothelial carcinoma.

13. The method of claim 1, wherein analyzing a subject sample comprises contacting the subject sample with one or more agents that specifically bind to nucleic acids encoded by one or more of the genes listed in Table 3, and testing for binding to determine whether the nucleic acids are differentially expressed.

14. The method of claim 13, wherein the sample comprises a mRNA or cDNA preparation form the subject.

15. The method of claim 13, wherein the agent is a labeled nucleic acid probe.

16. The method of claim 15, wherein the label is selected from the group consisting of radioactive, colorimetric, enzymatic, fluorometric, chemiluminescent and magnetic.

17. The method of claim 1, wherein the one or more genes comprises, RNASE1, RSP3, Intercept, CRABP2, CRNN, SPINK5, ERP29, TMPRSS l lD, Age, RBP4, ALDH1A3, MIF, CRH, FTL, PLA2G2F, and SLC1A5.

18. The method of claim 1, wherein the one or more genes comprises, TMPRSS 1 ID, RNASE1, SLC1A5, and Intercept.

19. The method of claim 1, wherein the one or more genes comprises, RBP4, Intercept, TMPRSS l lD, RNASE1, FTL, Age, CRH, ERP29, and SLC1A5.

20. The method of claim 1, wherein the one or more genes comprises, Intercept, RNASEl, CRH, HSD17B2, and RBP4.

21. The method of claim 1, wherein the one or more genes comprises, Intercept, ALDH1A3, CRH, CRNN, MIF, RNASEl, SPINK5, TMPRSS l lD, FTL, RBP4, SLC1A5, and Age.

22. The method of claim 1, wherein the one or more genes comprises, Intercept, RNASEl, Age, MIF, RBP4, FTL, CRNN, TMPRSS l lD, ALDH1A3, RPS3, SPINK5, ERP29, CRH, SLC1A5, and PLA2G2F.

23. The method of claim 1, wherein the one or more genes comprises, Intercept, RNASEl, Age, HSD17B2, RBP4, ALDH1A3, FTL, CRH, MIF, TMPRSSl lD, and ERP29.

24. A method for detecting differential expression of one or more bladder cancer markers in a subject, the method comprising, contacting a sample from a subject with one or more agents that specifically bind to proteins encoded by one or more of the genes listed in Table 3 and detecting binding between the one or more agents and the proteins encoded by one or more of the genes listed in Table 3 to determine whether the proteins are differentially expressed.

25. The method of claim 24, wherein the agent is selected from the group consisting of an antibody and an aptamer.

26. The method of claim 25, wherein the aptamer comprises an oligonucleotide, optionally further comprising one or more modified bases.

27. The method of claim 25, wherein the aptamer comprises a peptide.

28. The method of claim 24, wherein the one or more genes comprises, RNASEl, RSP3, Intercept, CRABP2, CRNN, SPINK5, ERP29, TMPRSS l lD, Age, RBP4, ALDH1A3, MIF, CRH, FTL, PLA2G2F, and SLC1A5.

29. The method of claim 24, wherein the one or more genes comprises, TMPRSS l lD, RNASEl, SLC1A5, and Intercept.

30. The method of claim 24, wherein the one or more genes comprises, RBP4, Intercept, TMPRSS l lD, RNASEl, FTL, Age, CRH, ERP29, and SLC1A5.

31. The method of claim 24, wherein the one or more genes comprises, Intercept, RNASEl, CRH, HSD17B2, and RBP4.

32. The method of claim 24, wherein the one or more genes comprises, Intercept, ALDH1A3, CRH, CRNN, MIF, RNASEl, SPINK5, TMPRSS l lD, FTL, RBP4, SLC1A5, and Age.

33. The method of claim 24, wherein the one or more genes comprises, Intercept, RNASEl, Age, MIF, RBP4, FTL, CRNN, TMPRSS l lD, ALDH1A3, RPS3, SPINK5, ERP29, CRH, SLC1A5, and PLA2G2F.

34. The method of claim 24, wherein the one or more genes comprises, Intercept, RNASEl, Age, HSD17B2, RBP4, ALDH1A3, FTL, CRH, MIF, TMPRSSl lD, and ERP29.

35. A method for detecting differential expression of one or more bladder cancer markers in a subject, the method comprising, contacting a sample from a subject with one or more agents that specifically bind to nucleic acids encoded by one or more of the genes listed in Table 3 and detecting binding between the one or more agents and the nucleic acids encoded by one or more of the genes listed in Table 3 to determine whether the nucleic acids are differentially expressed.

36. The method of claim 35, wherein the sample comprises a mRNA or cDNA preparation form the subject.

37. The method of claim 35, wherein the agent is a labeled nucleic acid probe.

38. The method of claim 37, wherein the label is selected from the group consisting of radioactive, colorimetric, enzymatic, fluorometric, chemiluminescent and magnetic.

39. The method of claim 35, wherein the detection of differential expression of one or more bladder cancer markers is used to diagnose bladder cancer.

40. The method of claim 39, wherein the bladder cancer is selected from the group consisting of high-grade urothelial carcinoma and low-grade urothelial carcinoma.

41. The method of claim 35, wherein the one or more genes comprises, RNASEl, RSP3, Intercept, CRABP2, CRNN, SPINK5, ERP29, TMPRSS l lD, Age, RBP4, ALDH1A3, MIF, CRH, FTL, PLA2G2F, and SLC1A5.

42. The method of claim 35, wherein the one or more genes comprises,

TMPRSS l lD, RNASEl, SLC1A5, and Intercept.

43. The method of claim 35, wherein the one or more genes comprises, RBP4, Intercept, TMPRSS l lD, RNASEl, FTL, Age, CRH, ERP29, and SLC1A5.

44. The method of claim 35, wherein the one or more genes comprises, Intercept, RNASEl, CRH, HSD17B2, and RBP4.

45. The method of claim 35, wherein the one or more genes comprises, Intercept, ALDH1A3, CRH, CRNN, MIF, RNASEl, SPINK5, TMPRSS l lD, FTL, RBP4, SLC1A5, and Age.

46. The method of claim 35, wherein the one or more genes comprises, Intercept, RNASEl, Age, MIF, RBP4, FTL, CRNN, TMPRSS l lD, ALDH1A3, RPS3, SPINK5, ERP29, CRH, SLC1A5, and PLA2G2F.

47. The method of claim 35, wherein the one or more genes comprises, Intercept, RNASE1, Age, HSD17B2, RBP4, ALDH1A3, FTL, CRH, MIF, TMPRSSl lD, and ERP29.

48. A method for treating bladder cancer in a subject, the method comprising, requesting a test providing the results of an analysis to determine whether the subject differentially expresses one or more markers listed in Table 3, wherein the differential expression of the one or more markers indicates bladder cancer, and administering a treatment.

49. The method of claim 48, wherein the treatment comprises eliciting an immune response in the subject against cells expressing one or more cancer associated sequences.

50. The method of claim 48, wherein the treatment comprises inhibiting the action of one or more cancer associated sequences.

51. A kit for detecting bladder cancer in a subject sample, the kit comprising one or more agents that specifically bind to a marker encoded by one or more genes listed in Table 3.

52. The kit of claim 51, wherein the one or more genes comprises, RNASE1, RSP3, Intercept, CRABP2, CRNN, SPINK5, ERP29, TMPRSS l lD, Age, RBP4, ALDH1A3, MIF, CRH, FTL, PLA2G2F, and SLC1A5.

53. The kit of claim 51 , wherein the one or more genes comprises, TMPRSS 1 ID, RNASE1, SLC1A5, and Intercept.

54. The kit of claim 51, wherein the one or more genes comprises, RBP4, Intercept, TMPRSS l lD, RNASE1, FTL, Age, CRH, ERP29, and SLC1A5.

55. The kit of claim 51, wherein the one or more genes comprises, Intercept,

RNASE1, CRH, HSD17B2, and RBP4.

56. The kit of claim 51, wherein the one or more genes comprises, Intercept, ALDH1A3, CRH, CRNN, MIF, RNASEl, SPINK5, TMPRSS l lD, FTL, RBP4, SLC1A5, and Age.

57. The kit of claim 51, wherein the one or more genes comprises, Intercept, RNASEl, Age, MIF, RBP4, FTL, CRNN, TMPRSS l lD, ALDH1A3, RPS3, SPINK5, ERP29, CRH, SLC1A5, and PLA2G2F.

58. The kit of claim 51, wherein the one or more genes comprises, Intercept, RNASEl, Age, HSD17B2, RBP4, ALDH1A3, FTL, CRH, MIF, TMPRSSl lD, and ERP29.