GENDER-SPECIFIC MARKERS FOR DIAGNOSING PROGNOSIS AND DETERMINING TREATMENT STRATEGY FOR RENAL CANCER PATIENTS

Description

TECHNICAL FIELD

The present invention relates to a marker for diagnosing prognosis of a patient with kidney cancer, a kit for diagnosing prognosis of a patient with kidney cancer including the same, and a method of providing information required to diagnose the prognosis of kidney cancer and determine a therapeutic strategy for kidney cancer using the kit for diagnosing prognosis of a patient with kidney cancer.

BACKGROUND ART

The kidney is an important urinary organ that serves to excrete waste materials from the body by filtering blood to generate urine. Also, the kidney is an important endocrine organ that produces hormones such as angiotensin that controls the blood pressure, erythropoietin as a haemopoietic factor, and the like.

Tumors occurring in the kidney include renal cell carcinoma arising from the adults, Wilms' tumor arising from the children, sarcoma as a rare tumor, and the like. Later on, the renal cell carcinoma as a malignant tumor having the highest incidence rate is referred to as kidney cancer. In Japan, the kidney cancer develops at an incidence frequency of approximately 2.5 per every 100,000 persons. In this case, the kidney cancer tends to occur at a higher frequency for men, that is, the proportion of men and women is 2 to 3:1. Among the urological malignant tumors, the kidney cancer is the most common tumor following prostate cancer and bladder cancer. The kidney cancer refers to renal cell carcinoma that develops mostly in the parenchyma (including medulla and cortex in which cells producing urine in the kidney are held together) of the kidney.

A genetic factor is known to be one of risk factors for kidney cancer, but such risk factors generally include smoking, excessive fat intake, and the like. Also, it has been know that the incidence rate of tumor is high in patients receiving dialysis for a long time.

In the case of kidney cancer, patients rarely have any observable symptoms when a tumor has the maximum diameter of 5 cm or less. Generally, the kidney cancer is often found when patients take a medical examination through a CT scan, and the like. Hematuria, celioncus, pain, and the like appear as the symptoms of large tumors. Also, pyrexy, weight loss, anaemia, and the like are often caused as the systemic symptoms, and erythrocytosis, hypertension, hypercalcemia, and the like are rarely caused by endocrine factors. Meanwhile, development of phlebismus or varicocele in the abdominal wall often occurs by tremors in the inferior vena cava of the kidney. Approximately 20% of the kidney cancers are found from the metastasis to the lungs or bone. Because tumor has a strong tendency to spread into the vein in the case of kidney cancer, the kidney cancer easily metastasizes into other organs.

Kidney cancer has few symptoms when it has a small tumor size, but has symptoms only when the tumor grows to push organs. Therefore, because the diagnosis of the kidney cancer is often delayed, the metastasis of kidney cancer into other organs is found in approximately 30% of patients, compared to when the kidney cancer is diagnosed at an early stage. The most common symptom is hematuria, but is found only in 60% of the patients. On the contrary, because patients have symptoms such as dyspnoea, cough, headaches, and the like depending on the metastasized sites, the patients who are diagnosed with kidney cancer due to such metastatic symptoms also account for 30% of the entire patients. Because hypertension, hypercalcemia, hepatic dysfunction, and the like may be caused by certain hormones especially produced by cancer cells, tumors may be often found while checking these other symptoms in kidney cancer. However, there are many current cases in which tumors are found by chance in imaging tests while patients receive medical checkups without any symptoms. In this case, because the tumors are generally found at early stages, the results of tumor treatment have been relatively successful. Therefore, it has been known that it is very important to diagnose such kidney cancer.

In U.S., patients with kidney cancer account for approximately 3% of adult cancer patients, and approximately 32,000 cancer patients are newly reported every year. Also, approximately 12,000 cases are assumed to die from kidney cancer, with an increasing incidence frequency worldwide every year. In Korea, the incidence frequency of kidney cancer is reported to be lower than that in U.S. Therefore, the National Cancer Registry data (2012) reported that 1,578 new cases of cancer patients are registered so that it accounts for 1.6% of the total number of cancer occurrences. Kidney cancer occurs commonly in people between 40 to 60 years old, and the current state of cancer incidence by gender (National Cancer Registry data on 2012) reports that kidney cancer occurs most commonly in people in their 60s (479 cases, 30.2%), followed by 50s (412 cases, 26.0%), and 40s (268 cases, 16.9%) in the corresponding order thereof When patients with kidney cancer undergo surgery to remove the tumor after the onset of kidney cancer, the patients have a high survival rate. However, because the patients have no clear symptoms at an early stage, it is difficult to diagnose kidney cancer at this stage. For these reasons, there is a need for development of a marker capable of diagnosing kidney cancer at an early stage and checking the patients' remaining lives after the onset of cancer.

Transglutaminase 2 (Registered Korean Patent No. 1267580) is disclosed as a marker used to detect or diagnose kidney cancer in humans. Although markers for diagnosing cancers including kidney cancer have been developed, there is no research on markers capable of determining the prognosis of patients with kidney cancer, particularly the relationship between the gender of patients with kidney cancer and the mutation of a certain gene.

To develop a therapeutic agent for diagnosing kidney cancer or healing patients with kidney cancer so as to determine a therapeutic strategy, the present inventors have conducted research on the relationship between the gene mutation and the gender of the patients found in the patients with kidney cancer on the basis of the need for development of the markers capable of diagnosing the prognosis of the patients with kidney cancer.

DISCLOSURE

Technical Problem

To apply a suitable therapeutic strategy to patients with kidney cancer, a development of markers which aid in predicting the prognosis of patients with kidney cancer and determining a therapeutic strategy thereof is needed. Therefore, it is an object of the present invention to provide a marker which aids in predicting the prognosis of patients with kidney cancer and determining a therapeutic strategy thereof based on the gender of the patients with kidney cancer.

Technical Solution

To solve the above problems, according to an aspect of the present invention, there is provided a kit for providing information required to predict a therapeutic effect against kidney cancer or diagnose prognosis of a patient with kidney cancer according to the gender of the patient with kidney cancer, wherein the kit is able to detect a gender-specific marker that is a mutation of a gene coding for at least one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1.

According to another aspect of the present invention, there is provided a method of providing information required to verify a difference in therapeutic effect against kidney cancer according to the gender of patients with kidney cancer. In this case, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer whose gender is identified; amplifying the DNA test sample using the kit; determining whether or not there is a gender-specific marker specific to a gender group of target patients from the results of amplification; treating the patient with kidney cancer, in which the gender-specific marker is identified, with any candidate material for treating kidney cancer or healing the patient with kidney cancer using any method; and choosing any candidate material for treating kidney cancer or any method of treating kidney cancer as a therapeutic candidate material or a therapeutic method, which is suitable for the gender group of patients with kidney cancer in which the gender-specific marker is identified, when the any candidate material or the any method is used to treat kidney cancer.

According to still another aspect of the present invention, there is provided a method of providing information required to diagnose prognosis of kidney cancer according to the gender of a patient with kidney cancer. In this case, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer; amplifying the DNA test sample using the kit; and determining whether or not there is a gender-specific marker from the results of amplification.

Advantageous Effects

Because there is a relationship between the gender of a patient with kidney cancer and a mutation of a gene selected from a gene group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1, all genes of which are found in the present invention, the presence of the mutation of the gene can be checked to predict a difference in therapeutic effect against kidney cancer and a difference in survival rate of the patient with kidney cancer according to the gender of the patient with kidney cancer.

In addition, because there is a relationship between a survival rate of the patient with kidney cancer who has a certain gender and a mutation of one gene selected from a gene group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1, all genes of which are found in the present invention, or a relationship between the mutation of the gene and a relapse rate of kidney cancer, mutations of the genes according to the present invention can be used as the marker to predict the prognosis of the patient with kidney cancer.

However, the effects of the present invention are not limited to the effects as described above, and other effects not disclosed herein will be clearly understood from the following detailed description by those skilled in the art.

DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram showing gender-specific mutant genes specifically shown from candidate genes when patients with kidney cancer who are classified according to the gender thereof are compared with each other. Each of numerical values represents the number of the patients with kidney cancer in which mutated genes are identified.

FIGS. 2 to 10 are graphs plotted for an overall survival rate or a disease-free survival rate of patients with kidney cancer (red) who have mutations in respective ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes and patients with kidney cancer (blue) who have no mutations in the corresponding genes.

BEST MODE

Unless defined otherwise in this specification, all the technical and scientific terms used herein have the same meanings as what are generally understood by a person skilled in the related art to which the present invention belongs. In general, the nomenclatures used in this specification and the experimental methods described below are widely known and generally used in the related art.

Hereinafter, the present invention will be described in detail.

1. Gender-Specific Mutant Genes in Patient with Kidney Cancer and Primer Sets Capable of Detecting the Mutant Genes

One aspect of the present invention provides a kit for providing information required to predict a difference in therapeutic effect against kidney cancer or diagnose prognosis of a patient with kidney cancer according to the gender of the patient with kidney cancer, wherein the kit may detect a gender-specific marker that is a mutation of at least one gene selected from a gene group consisting of ACSS3 (Gene Bank Accession Number: NM_024560.3), ADAM21 (Gene Bank Accession Number: NM_003813.3), AFF2 (Gene Bank Accession Number: NM_002025.3), ALG13 (Gene Bank Accession Number: NM_001099922.2), ARSF (Gene Bank Accession Number: NM_001201538.1), BAP1 (Gene Bank Accession Number: NM_004656.3), BRWD3 (Gene Bank Accession Number: NM_153252.4), CFP (Gene Bank Accession Number: NM_001145252.1), COL4A5 (Gene Bank Accession Number: NM_000495.4), CPEB1 (Gene Bank Accession Number: NM_030594.4), ERBB2 (Gene Bank Accession Number: NM_004448.3), FAM47A (Gene Bank Accession Number: NM_203408.3), HSP90AA1 (Gene Bank Accession Number: NM_001017963.2), IRAK1 (Gene Bank Accession Number: NM_001569.3), KDMSC (Gene Bank Accession Number: NM_004187.3), KDM6A (Gene Bank Accession Number: NM_021140.3), LRP12 (Gene Bank Accession Number: NM_013437.4), NCOA6 (Gene Bank Accession Number: NM_001242539.2), NHS (Gene Bank Accession Number: NM_198270.3), PHF16(JADE3) (Gene Bank Accession Number: NM_001077445.2), RGAG1 (Gene Bank Accession Number: NM_020769.2), SCAF1 (Gene Bank Accession Number: NM_021228.2), SCRN1 (Gene Bank Accession Number: NM_001145514.1), SH3TC1 (Gene Bank Accession Number: NM_018986.4), TBC1D8B (Gene Bank Accession Number: NM_017752.2), TET2 (Gene Bank Accession Number: NM_001127208.2), TEX13A (Gene Bank Accession Number: NM_001291277.1), ULK3 (Gene Bank Accession Number: NM_001099436.3), WNK3 (Gene Bank Accession Number: NM_001002838.3), and ZNF449 (Gene Bank Accession Number: NM_152695.5).

The full names of abbreviations for the genes may be ACSS3 (Homo sapiens acyl-CoA synthetase short chain family member 3), ADAM21 (Homo sapiens ADAM metallopeptidase domain 21), AFF2 (Homo sapiens AF4/FMR2 family member 2), ALG13 (UDP-N-acetylglucosaminyltransferase subunit), BAP1 (BRCA1-associated protein 1), BRWD3 (bromodomain and WD repeat domain containing 3), COL4A5 (collagen type IV alpha 5 chain), CPEB1 (cytoplasmic polyadenylation element binding protein 1), ERBB2 (erb-b2 receptor tyrosine kinase 2), HSP90AA1 (heat shock protein 90 alpha family class A member 1), IRAK1 (interleukin 1 receptor associated kinase 1), KDMSC (lysine demethylase 5C), KDM6A (lysine demethylase 6A), LRP12 (LDL receptor related protein 12), NCOA6 (nuclear receptor coactivator 6), NHS (NHS actin remodeling regulator), RGAG1 (retrotransposon Gag like 9), SCAF1 (SR-related CTD associated factor 1), SH3TC1 (SH3 domain and tetratricopeptide repeats 1), TBC1D8B (TBC1 domain family member 8B), TET2 (tet methylcytosine dioxygenase 2), TEX13A (testis-expressed 13A), ULK3 (unc-51 like kinase 3), WNK3 (WNK lysine-deficient protein kinase 3), ARSF (arylsulfatase F), CFP (complement factor properdin), FAM47A (family with sequence similarity 47 member A), PHF16 (jade family PHD finger 3), ZNF449 (zinc finger protein 449), and SCRN1 (secernin 1).

According to one exemplary embodiment of the present invention, there is provided a kit for providing information required to predict a difference in therapeutic effect against kidney cancer or diagnose prognosis of a patient with kidney cancer according to the gender of the patient with kidney cancer, wherein the kit may detect a mutation of at least one gene selected from the following genes: a mutation of a gene coding for at least one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1.

In the present invention, the term ‘diagnosis’ refers to a process in which the presence or nature of a pathologic status is determined, that is, a process in which a difference in therapeutic effect against cancer according to the gender of a cancer patient is verified for the objects of the present invention and a process in which the relapse and metastasis of cancer, drug response and resistance, and the like in the corresponding subject after cancer treatment are judged. Preferably, when the mutations of the genes of the present invention are used, it is also possible to predict a difference in survival rate by checking whether there are mutations in a test sample of a patient with kidney cancer. In this case, a difference in therapeutic effect against kidney cancer and the prognosis of the corresponding patient in the future according to the gender of the corresponding patient with kidney cancer may be determined from the difference in survival rate.

In the present invention, the term ‘prognosis’ refers to the prediction of the progress and cure of a disease having a probability of cancer-attributable death or progression, including, for example, the relapse and metastatic spread of a neoplastic disease such as cancer, and drug resistance. The prognosis may refer to a prediction of the prognosis of kidney cancer for the objects of the present invention. Preferably, the prognosis may refer to a prediction of a disease-free survival rate or survival rate of the patient with kidney cancer.

In the present invention, the term ‘cancer’ includes any members belonging to a class of diseases characterized by the uncontrolled growth of abnormal cells. The term includes all stages and grades of cancers, including all types of known cancers and neoplastic conditions, cancers before/after metastasis, regardless whether the cancer is characterized by any one malignant, benign, soft tissue, or solid cancer.

In the present invention, the term ‘gene’ and modified products thereof include DNA fragments associated with the synthesis of polypeptide chains; each of the DNA fragments includes regions upstream and downstream from a coding region, for example, a promoter and a 3′-untranslated region, respectively, and also includes intervening sequences (introns) between respective coding fragments (exons).

The mutation of the gene may include any one or more mutations, and may, for example, have at least one mutation selected from the group consisting of truncating mutation, missense mutation, nonsense mutation, frameshift mutation, in-frame mutation, splice mutation, and splice_region mutation. The frameshift mutation may be at least one selected from a frameshift insertion (FS ins) mutation and a frameshift deletion (FS del) mutation. The in-frame mutation may be at least one selected from an in-frame insertion (IF ins) mutation and an in-frame deletion (IF del) mutation.

In conjunction with mutations in a polypeptide sequence, the term “X#Y” is obviously recognized in the related art. Here, the sign “#” represents a mutation position with respect to the amino acid number of a polypeptide, “X” represents an amino acid found at the position of a wild-type amino acid sequence, and “Y” represents a mutant amino acid found at the same position. For example, the sign “G1717V” with respect to a BAZ2B polypeptide means that there is a glycine residue at amino acid number 1,717 of a wild-type BAZ2B sequence, and the glycine residue is replaced with valine in a mutant BAZ2B sequence.

The mutations of the genes are as follows:

The mutation of the gene coding for ACSS3 is a nonsense mutation ‘R634*’, a splice mutation A152_splice' (where T is substituted with C at position 81503485 on the chromosome), or a missense mutation ‘G268D’, wherein the sign in a notation of the nonsense mutation means that the synthesis of amino acids is terminated at the corresponding amino acid position (a description thereof is omitted hereinafter), in an amino acid sequence set forth in SEQ ID NO: 1; the mutation of the gene coding for ADAM21 is at least one mutation selected from the group consisting of N265Y, R408C, T589S, and I161V in an amino acid sequence set forth in SEQ ID NO: 2; the mutation of the gene coding for AFF2 is at least one missense mutation selected from the group consisting of S770F, P513H, T640N, and 1149K in an amino acid sequence set forth in SEQ ID NO: 3; the mutation of the gene coding for ALG13 is at least one missense mutation selected from P925T and V456E, or a frameshift deletion (FS del) mutation ‘L195Pfs*23’, where a notation of the frameshift mutation is based on the amino acid type (an amino acid position) and the amino acid type fs* (the number of nucleotides downstream from the amino acid position to a stop codon) (both the FS ins mutation and FS del mutation are denoted by the same notation, and a description thereof is omitted hereinafter), in an amino acid sequence set forth in SEQ ID NO: 4; the mutation of the gene coding for BAP1 is a nonstart mutation ‘M1?’ (where T is substituted with C at position 52443894 and C is substituted with T at position 52443892 on the chromosome), at least one nonsense mutation selected from the group consisting of G128*, E402*, Q253*, Q267*, S460*, Y627*, S279*, R60*, Q40*, Q156*, and K626*, at least one FS del mutation selected from the group consisting of E283Gfs*52, V335Efs*56, K711Sfs*25, R700Gfs*36, D74Efs*4, and D407Vfs*23, at least one missense mutation selected from the group consisting of F170V, F170C, E31A, N78S, L49V, D75G, SlOT, N229H, G109V, L17P, A145G, and A1061T, at least one splice mutation selected from the group consisting of X23_splice (where C is substituted with T at position 52443729 on the chromosome), X41_splice (where A is substituted with G at position 52443568 on the chromosome), X41_splice (where A is substituted with T at position 52443568 on the chromosome), X23_splice (where ACCTGCGATGAGGAAAGGAAAGCAG at positions 52443623 to 52443647 are deleted from the chromosome), and X311_splice (where C is substituted with A at position 52439311 on the chromosome), or an in-frame deletion (IF del) mutation ‘K659del’, where the sign ‘del’ in a notation of the IF del mutation represents a deletion of the corresponding amino acid at the corresponding amino acid position (a description thereof is omitted hereinafter), in an amino acid sequence set forth in SEQ ID NO: 5; the mutation of the gene coding for BRWD3 is at least one missense mutation selected from G287A and I1747N in an amino acid sequence set forth in SEQ ID NO: 6; the mutation of the gene coding for COL4A5 is at least one missense mutation selected from the group consisting of P1184L, P756S, P1365S, G1427V, and A1656T, or a splice mutation ‘X1510_splice’ (where G is substituted with T at position 107935977 on the chromosome) in an amino acid sequence set forth in SEQ ID NO: 7; the mutation of the gene coding for CPEB1 is at least one missense mutation selected from S393R and G136V, or a splice mutation ‘X499_splice’ (where C is substituted with A at position 83215272 on the chromosome) in an amino acid sequence set forth in SEQ ID NO: 8; the mutation of the gene coding for ERBB2 is at least one missense mutation selected from the group consisting of E1114G, S649T, and V2191, or an FS ins mutation ‘N388Qfs*14’ in an amino acid sequence set forth in SEQ ID NO: 9; the mutation of the gene coding for HSP90AA1 is at least one missense mutation selected from the group consisting of D512N, H806R, I325T, and L167V in an amino acid sequence set forth in SEQ ID NO: 10; the mutation of the gene coding for IRAK1 is a nonsense mutation ‘Q280*’, or at least one missense mutation selected from V548M and Q584K in an amino acid sequence set forth in SEQ ID NO: 11; the mutation of the gene coding for KDMSC is at least one nonsense mutation selected from the group consisting of R681*, Q813*, E284*, E798*, Y639*, S1110*, K459*, and R215*, at least one missense mutation selected from the group consisting of E1152K, R1458W, G536W, C730R, E592V, C512W, C730F, and H733P, a splice mutation ‘X321_splice’ (where A is substituted with G at position 53244975 on the chromosome), or at least one FS del mutation selected from the group consisting of T471Vfs*5, Q1427Pfs*50, E122Vfs*14, E1131Sfs*16, H988Tfs*18, P27Lfs*46, F56Cfs*18, D1414Efs*54, and G845Rfs*2 in an amino acid sequence set forth in SEQ ID NO: 12; the mutation of the gene coding for KDM6A is a missense mutation ‘A30V’, an FS mutation ‘A1246Pfs*19’, or an IF del mutation ‘V156del’ in an amino acid sequence set forth in SEQ ID NO: 13; the mutation of the gene coding for LRP12 is at least one missense mutation selected from the group consisting of S622L, E639K, and V6711 in an amino acid sequence set forth in SEQ ID NO: 14; the mutation of the gene coding for NCOA6 is at least one missense mutation selected from the group consisting of G164E, N8771, N864Y, and V1444A, or an FS ins mutation ‘H832Sfs*47’ in an amino acid sequence set forth in SEQ ID NO: 15; the mutation of the gene coding for NHS is at least one missense mutation selected from the group consisting of C360R, P1107A, and D1069H in an amino acid sequence set forth in SEQ ID NO: 16; the mutation of the gene coding for RGAG1 is at least one missense mutation selected from the group consisting of A1015G, M858V, and G1053R in an amino acid sequence set forth in SEQ ID NO: 17; the mutation of the gene coding for SCAF1 is at least one FS ins mutation selected from the group consisting of A219Sfs*11, P211Tfs*19, P211Tfs*19, and A216Pfs*94, or an FS del mutation ‘A216Pfs*94’ in an amino acid sequence set forth in SEQ ID NO: 18; the mutation of the gene coding for SH3TC1 is at least one missense mutation selected from A375V and L180F or an FS del mutation ‘R2238Sfs*38’ in an amino acid sequence set forth in SEQ ID NO: 19; the mutation of the gene coding for TBC1D8B is at least one missense mutation selected from the group consisting of G1059V, A614T, and Y815F, or a nonsense mutation ‘S861*’ in an amino acid sequence set forth in SEQ ID NO: 20; the mutation of the gene coding for TET2 is at least one missense mutation selected from the group consisting of Q317K, L757V, V449E, N1714K, D194E, N1390H, R1451Q, M600I, and P554S, or a nonsense mutation ‘1(326*’ in an amino acid sequence set forth in SEQ ID NO: 21; the mutation of the gene coding for TEX13A is at least one missense mutation selected from R393S and Y257D, or a splice mutation ‘X199_splice’ (where C at position 104464282 is deleted from the chromosome) in an amino acid sequence set forth in SEQ ID NO: 22; the mutation of the gene coding for ULK3 is an FS del mutation ‘Q81Sfs*41’ and at least one missense mutation selected from D79H and L77V in an amino acid sequence set forth in SEQ ID NO: 23; the mutation of the gene coding for WNK3 is at least one nonsense mutation selected from S865* and Y589* and a missense mutation ‘E537G’ in an amino acid sequence set forth in SEQ ID NO: 24; the mutation of the gene coding for ARSF is a missense mutation ‘I42F’ in an amino acid sequence set forth in SEQ ID NO: 25; the mutation of the gene coding for CFP is at least one missense mutation selected from the group consisting of S27L, R359Q, and E135K, or an FS ins mutation ‘E323Gfs*34’ in an amino acid sequence set forth in SEQ ID NO: 26; the mutation of the gene coding for FAM47A is at least one missense mutation selected from R505H and E507Q, or at least one IF del mutation selected from L235_H246del and L235_H246del in an amino acid sequence set forth in SEQ ID NO: 27; the mutation of the gene coding for PHF16 is at least one missense mutation selected from K656Q and R207W in an amino acid sequence set forth in SEQ ID NO: 28; the mutation of the gene coding for ZNF449 is a missense mutation ‘F183I’ in an amino acid sequence set forth in SEQ ID NO: 29; and the mutation of the gene coding for SCRN1 is a missense mutation ‘D427Y’ or an FS ins mutation ‘A257Cfs*34’ in an amino acid sequence set forth in SEQ ID NO: 30.

An analytical method for diagnosing the prognosis of kidney cancer using the mutation of the gene, a next-generation sequencing (NGS) method, RT-PCR, a direct nucleic acid sequencing method, a microarray, and the like may be used. In this case, any methods may be used without limitation as long as the methods can be used to determine the presence of mutations using the mutation of the gene according to the present invention. According to one exemplary embodiment, the presence of mutations is determined using an anti-antibody (a mutant antibody against each gene) or nucleic acid probe that hybridizes with a mutant polynucleotide of each of the gene under a stringent condition. According to another exemplary embodiment, the anti-antibody or nucleic acid probe is detectably labeled. According to still another exemplary embodiment, a label is selected from the group consisting of an immunofluorescent label, a chemiluminescent label, a phosphorescent label, an enzyme label, a radioactive label, avidin/biotin, colloidal gold particles, coloring particles, and magnetic particles. According to yet another exemplary embodiment, the presence of mutations is determined using an radioimmunoassay, a Western blot assay, an immunofluorescence assay, an enzyme immunoassay, an immunoprecipitation assay, a chemiluminescence assay, an immunohistochemical assay, a dot-blot assay, a slot-blot assay, or a flow cytometric assay. According to yet another exemplary embodiment, the presence of mutations is determined by RT-PCR. According to yet another exemplary embodiment, the presence of mutations is determined by nucleic acid sequencing.

In the present invention, the term ‘polynucleotide’ generally refers to any polyribonucleotide or polydeoxyribonucleotide that may be unmodified RNA or DNA or modified RNA or DNA. Therefore, non-limiting examples of the polynucleotide as defined herein include single- and double-stranded DNAs, DNAs including single- and double-stranded regions, single- and double-stranded RNAs, and RNAs including single- and double-stranded regions, and hybrid molecules including DNAs and RNAs that may be single-stranded or more typically double-stranded or may include single- and double-stranded regions. Therefore, the DNA or RNA having a modified backbone due to its stability or other reasons is a ‘polynucleotide’ as described in the terms intended herein. Also, the DNA or RNA containing unusual bases such as inosine or modified bases such as a tritiated base is encompassed in the term ‘polynucleotide’ as defined herein. Generally, the term ‘polynucleotide’ includes all chemically, enzymatically and/or metabolically modified forms of an unmodified polynucleotide. The polynucleotide may be prepared by various methods including an in vitro recombinant DNA-mediated technology, and prepared by expression of DNA in cells and organisms.

Primer sets capable of detecting the mutation of the gene, that is, primer sets for diagnosing prognosis of kidney cancer are as follows: at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 31 and SEQ ID NO: 32, SEQ ID NO: 33 and SEQ ID NO: 34, and SEQ ID NO: 35 and SEQ ID NO: 36 to detect the mutation of ACSS3; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 37 and SEQ ID NO: 38, SEQ ID NO: 39 and SEQ ID NO: 40, SEQ ID NO: 41 and SEQ ID NO: 42, and SEQ ID NO: 43 and SEQ ID NO: 44 to detect the mutation of ADAM21; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 45 and SEQ ID NO: 46, SEQ ID NO: 47 and SEQ ID NO: 48, SEQ ID NO: 49 and SEQ ID NO: 50, and SEQ ID NO: 51 and SEQ ID NO: 52 to detect the mutation of AFF2; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 53 and SEQ ID NO: 54, SEQ ID NO: 55 and SEQ ID NO: 56, and SEQ ID NO: 57 and SEQ ID NO: 58 to detect the mutation of ALG13; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 59 and SEQ ID NO: 60, SEQ ID NO: 61 and SEQ ID NO: 62, SEQ ID NO: 63 and SEQ ID NO: 64, SEQ ID NO: 65 and SEQ ID NO: 66, SEQ ID NO: 67 and SEQ ID NO: 68, SEQ ID NO: 69 and SEQ ID NO: 70, SEQ ID NO: 71 and SEQ ID NO: 72, SEQ ID NO: 73 and SEQ ID NO: 74, SEQ ID NO: 75 and SEQ ID NO: 76, SEQ ID NO: 77 and SEQ ID NO: 78, SEQ ID NO: 79 and SEQ ID NO: 80, SEQ ID NO: 81 and SEQ ID NO: 82, SEQ ID NO: 83 and SEQ ID NO: 84, SEQ ID NO: 85 and SEQ ID NO: 86, SEQ ID NO: 87 and SEQ ID NO: 88, SEQ ID NO: 89 and SEQ ID NO: 90, SEQ ID NO: 91 and SEQ ID NO: 92, and SEQ ID NO: 93 and SEQ ID NO: 94 to detect the mutation of BAP1; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 95 and SEQ ID NO: 96, and SEQ ID NO: 97 and SEQ ID NO: 98 to detect the mutation of BRWD3; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 99 and SEQ ID NO: 100, SEQ ID NO: 101 and SEQ ID NO: 102, SEQ ID NO: 103 and SEQ ID NO: 104, SEQ ID NO: 105 and SEQ ID NO: 106, SEQ ID NO: 107 and SEQ ID NO: 108, and SEQ ID NO: 109 and SEQ ID NO: 110 to detect the mutation of COL4A5; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 111 and SEQ ID NO: 112, SEQ ID NO: 113 and SEQ ID NO: 114, and SEQ ID NO: 115 and SEQ ID NO: 116 to detect the mutation of CPEB1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 117 and SEQ ID NO: 118, SEQ ID NO: 119 and SEQ ID NO: 120, and SEQ ID NO: 121 and SEQ ID NO: 122 to detect the mutation of ERBB2; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 123 and SEQ ID NO: 124, SEQ ID NO: 125 and SEQ ID NO: 126, SEQ ID NO: 127 and SEQ ID NO: 128, and SEQ ID NO: 129 and SEQ ID NO: 130 to detect the mutation of HSP90AA1; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 131 and SEQ ID NO: 132, and SEQ ID NO: 133 and SEQ ID NO: 134 to detect the mutation of IRAK1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 135 and SEQ ID NO: 136, SEQ ID NO: 137 and SEQ ID NO: 138, SEQ ID NO: 139 and SEQ ID NO: 140, SEQ ID NO: 141 and SEQ ID NO: 142, SEQ ID NO: 143 and SEQ ID NO: 144, SEQ ID NO: 145 and SEQ ID NO: 146, SEQ ID NO: 147 and SEQ ID NO: 148, SEQ ID NO: 149 and SEQ ID NO: 150, SEQ ID NO: 151 and SEQ ID NO: 152, SEQ ID NO: 153 and SEQ ID NO: 154, SEQ ID NO: 155 and SEQ ID NO: 156, SEQ ID NO: 157 and SEQ ID NO: 158, SEQ ID NO: 159 and SEQ ID NO: 160, SEQ ID NO: 161 and SEQ ID NO: 162, SEQ ID NO: 163 and SEQ ID NO: 164, SEQ ID NO: 165 and SEQ ID NO: 166, SEQ ID NO: 167 and SEQ ID NO: 168, SEQ ID NO: 169 and SEQ ID NO: 170, SEQ ID NO: 171 and SEQ ID NO: 172, SEQ ID NO: 173 and SEQ ID NO: 174, and SEQ ID NO: 175 and SEQ ID NO: 176 to detect the mutation of KDMSC; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 177 and SEQ ID NO: 178, and SEQ ID NO: 179 and SEQ ID NO: 180 to detect the mutation of KDM6A; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 181 and SEQ ID NO: 182, and SEQ ID NO: 183 and SEQ ID NO: 184 to detect the mutation of LRP12; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 185 and SEQ ID NO: 186, SEQ ID NO: 187 and SEQ ID NO: 188, SEQ ID NO: 189 and SEQ ID NO: 190, and SEQ ID NO: 191 and SEQ ID NO: 192 to detect the mutation of NCOA6; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 193 and SEQ ID NO: 194, SEQ ID NO: 195 and SEQ ID NO: 196, and SEQ ID NO: 197 and SEQ ID NO: 198 to detect the mutation of NHS; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 199 and SEQ ID NO: 200, SEQ ID NO: 201 and SEQ ID NO: 202, and SEQ ID NO: 203 and SEQ ID NO: 204 to detect the mutation of RGAG1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 205 and SEQ ID NO: 206, SEQ ID NO: 207 and SEQ ID NO: 208, SEQ ID NO: 209 and SEQ ID NO: 210, SEQ ID NO: 211 and SEQ ID NO: 212, and SEQ ID NO: 213 and SEQ ID NO: 214 to detect the mutation of SCAF1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 215 and SEQ ID NO: 216, SEQ ID NO: 217 and SEQ ID NO: 218, and SEQ ID NO: 219 and SEQ ID NO: 220 to detect the mutation of SH3TC1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 221 and SEQ ID NO: 222, SEQ ID NO: 223 and SEQ ID NO: 224, SEQ ID NO: 225 and SEQ ID NO: 226, and SEQ ID NO: 227 and SEQ ID NO: 228 to detect the mutation of TBC1D8B; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 229 and SEQ ID NO: 230, SEQ ID NO: 231 and SEQ ID NO: 232, SEQ ID NO: 233 and SEQ ID NO: 234, SEQ ID NO: 235 and SEQ ID NO: 236, SEQ ID NO: 237 and SEQ ID NO: 238, SEQ ID NO: 239 and SEQ ID NO: 240, SEQ ID NO: 241 and SEQ ID NO: 242, SEQ ID NO: 243 and SEQ ID NO: 244, and SEQ ID NO: 245 and SEQ ID NO: 246 to detect the mutation of TET2; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 247 and SEQ ID NO: 248, SEQ ID NO: 249 and SEQ ID NO: 250, and SEQ ID NO: 251 and SEQ ID NO: 252 to detect the mutation of TEX13A; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 253 and SEQ ID NO: 254 to detect the mutation of ULK3; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 255 and SEQ ID NO: 256, SEQ ID NO: 257 and SEQ ID NO: 258, and SEQ ID NO: 259 and SEQ ID NO: 260 to detect the mutation of WNK3; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 261 and SEQ ID NO: 262 to detect the mutation of ARSF; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 263 and SEQ ID NO: 264, SEQ ID NO: 265 and SEQ ID NO: 266, SEQ ID NO: 267 and SEQ ID NO: 268, and SEQ ID NO: 269 and SEQ ID NO: 270 to detect the mutation of CFP; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 271 and SEQ ID NO: 272 to detect the mutation of FAM47A; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 273 and SEQ ID NO: 274, and SEQ ID NO: 275 and SEQ ID NO: 276 to detect the mutation of PHF16; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 277 and SEQ ID NO: 278 to detect the mutation of ZNF449; and at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 279 and SEQ ID NO: 280, and SEQ ID NO: 281 and SEQ ID NO: 282 to detect the mutation of SCRN1.

The kit of the present invention thus manufactured is very economical because a lot of time and cost may be save, compared to typical gene mutation search methods known in the art. Several days or Several months are averagely taken to search for one gene thoroughly using the conventional gene mutation search methods such as single strand conformational polymorphism (SSCP), a protein truncation test (PTT), cloning, direct sequencing, and the like. Also, the gene mutation may be rapidly and simply examined accurately using the next-generation sequencing (NGS) method. When the mutation is checked using conventional analytical methods such as SSCP, cloning, direct sequencing, restriction fragment length polymorphism (RFLP), and the like, approximately one month is taken to complete the check. On the other hand, when the kit of the present invention is used and a DNA test sample is prepared, results may be obtained within approximately 10 to 11 hours. Because a primer set capable of detecting the mutation of the gene is stacked in one chip, the time and cost may be saved compared to the conventional methods. Because less than half the reagents' cost per experiment is averagely consumed compared to the conventional methods, a higher cost saving effect may be expected in consideration of the researchers' labor costs.

2. Method of Providing Information Required to Diagnose Prognosis of Kidney Cancer Using Survival-Specific Mutant Gene

According to another aspect of the present invention, there is provided a method of providing information required to verify a difference in therapeutic effect against kidney cancer according to the gender of a patient with kidney cancer. Here, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer whose gender is identified; amplifying the DNA test sample using the kit; determining whether or not there is a gender-specific marker specific to a gender group of target patients from the results of amplification; treating the patient with kidney cancer, in which the gender-specific marker is identified, with any candidate material for treating kidney cancer or healing the patient with kidney cancer using any method; and choosing any candidate material for treating kidney cancer or any method of treating kidney cancer as a therapeutic candidate material or a therapeutic method, which is suitable for the gender group of patients with kidney cancer in which the gender-specific marker is identified, when the any candidate material or the any method is used to treat kidney cancer.

According to still another aspect of the present invention, there is provided a method of providing information required to diagnose prognosis of kidney cancer according to the gender of a patient with kidney cancer. Here, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer; amplifying the DNA test sample using the kit; and determining whether or not there is a gender-specific marker from the results of amplification.

The ‘kit for diagnosing prognosis of kidney cancer’ is as described in ‘1. gender-specific mutant genes in patient with kidney cancer and primer sets capable of detecting the mutant genes’, and thus a specific description thereof is omitted.

The any candidate material for treating kidney cancer may be a therapeutic agent generally used to treat kidney cancer, or a novel material whose therapeutic effect against kidney cancer is not known, but the present invention is not limited thereto. It may be determined whether or not the any therapeutic candidate material has a therapeutic effect on a certain group of patients by treating a patient with kidney cancer having a gender-specific marker with the therapeutic candidate material to check the therapeutic effect. When the therapeutic candidate material has a therapeutic effect against kidney cancer, it may be predicted that the therapeutic candidate material has a high therapeutic effect when the therapeutic candidate material is applied to a group of patients having the same gender-specific marker, thereby providing useful information to determine a therapeutic strategy. Also, when a therapeutic effect is not exerted by the use of the any therapeutic candidate material, the unnecessary treatment needs not to be performed by suspending the therapy on the group of patients having the same gender-specific marker. Therefore, a therapeutic strategy may be effectively designed.

Any method of treating kidney cancer may also be applied instead of the any therapeutic candidate material. After verifying a therapeutic effect in a group of patients having a certain gender-specific marker, it may be determined whether or not the method is applied to the group of patients having the same gender-specific marker. When the therapeutic effect is verified in the group of patients having the gender-specific marker, the any therapeutic candidate material and the any method of treating kidney cancer may be used together.

The term ‘sample’ used herein includes any biological specimen obtained from a patient. The sample includes whole blood, plasma, serum, red blood cells, white blood cells (for example, peripheral blood mononuclear cells), a ductal fluid, hydrops abdominis, a pleural efflux, a nipple aspirate, a lymph fluid (for example, disseminated tumor cells of lymph nodes), a bone marrow aspirate, saliva, urine, feces (that is, stool), phlegm, a bronchial lavage fluid, tear, a fine needle aspirate (for example, collected by random mammary fine needle aspiration), any other bodily fluids, a tissue sample (for example, a tumor tissue), for example, a tumor biopsy (for example, an aspiration biopsy) or a lymph node (for example, a sentinel lymph node biopsy), a tissue sample (for example, a tumor tissue), for example, a surgical resection of tumor, and cell extracts thereof. In some embodiments, the sample is whole blood or some components thereof, for example, plasma, serum or cell pellets. In another embodiment, the sample is obtained by isolating circulating cells of a solid tumor from the whole blood or cell fractions thereof using any techniques known in the related art. In still another embodiment, the sample is, for example, a formalin-fixed paraffin-embedded (FFPE) tumor tissue sample from a solid tumor such as colon cancer.

In certain embodiments, the sample is a tumor lysate or extract prepared from a frozen tissue obtained from a target having colon cancer.

The term ‘patient’ generally includes a human, and may also include other animals, for example, other primates, rodents, dogs, cats, horses, sheep, pigs, and the like.

The term ‘subject’ includes targets excluding a human, which are diagnosed with kidney cancer or suspected to have kidney cancer.

The method may be used to predict an overall survival rate or disease-free survival rate of the patient with kidney cancer.

In the present invention, the term ‘overall survival rate’ includes clinical endpoints recorded for patients who are diagnosed with a disease, for example, cancer or alive for a predetermined period after treatment of the disease, and refers to a survival probability of the patients regardless of the relapse of cancer.

In the present invention, the term ‘disease-free survival rate (DFS)’ includes a survival period of a patient without the relapse of cancer after treatment of a certain disease (for example, cancer).

According to the present invention, the presence of mutations of the gene of the present invention in a sample of a patient with kidney cancer may be analyzed to verify what the prognosis of a subject having a target test sample is for cancer. Also, such a method may be established by comparing overall survival rates or disease-free survival rates of control subjects who are known to have a good prognosis and have no mutations. In the present invention, the subject known to have a good prognosis refers to a subject who has no family histories such as metastasis, relapse, death, and the like after the onset of cancer.

The sample of the subject suspected to have cancer refers to a test sample of a subject or a tissue which already develops cancer or tumor or is expected to develop cancer or tumor, that is, a target test sample used to diagnose the prognosis of cancer or tumor.

The gender-specific marker may be a mutation of a gene coding for one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1. In females of the patients with kidney cancer, the gender-specific marker may be a mutation of a gene coding for one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1. In males of the patients with kidney cancer, the gender-specific marker may be a mutation of a gene coding for TET2.

The method of providing information required to diagnose the prognosis of kidney cancer according to the gender of the patient with kidney cancer may be used to predict the overall survival rate or disease-free survival rate of the patient with kidney cancer. For example, the method may further include judging that the survival rate of the patient with kidney cancer is not good or that a relapse rate of kidney cancer in the patient with kidney cancer is high when the mutation is identified in the gene coding for one selected from the group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1, and the patient with kidney cancer is female.

The method of providing information required to diagnose the prognosis of kidney cancer according to the gender of the patient with kidney cancer may further include judging that the survival rate of the patient with kidney cancer is not good when the gender of the patient with kidney cancer is female and the mutation is identified in the gene coding for one selected from the group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, and ZNF449, and the patient with kidney cancer is male.

The method of providing information required to diagnose the prognosis of kidney cancer according to the gender of the patient with kidney cancer may further include judging that the relapse rate of kidney cancer in the patient with kidney cancer is high when the gender of the patient with kidney cancer is female and the mutation is identified in the gene coding for one selected from the group consisting of ACSS3, ARSF, CFP, FAM47A, ZNF449, and SCRN1.

As described above, the mutation of at least one gene selected from a gene group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1 is used as the mutation of the gene of the present invention to verify that there is a difference in gene mutations according to the gender of a patient who develops cancer, particularly kidney cancer, but this fact is still unknown. Also, the mutation of at least one gene selected from a gene group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 may be used to diagnose the prognosis of cancer, particularly kidney cancer, in a patient having a certain gender, but this fact is also still unknown. Further, there is no report on the fact that the overall survival rate or disease-free survival rate may be different in each of the genes. The present inventors have first found that the mutation of the genes may be used as a diagnostic marker capable of predicting a difference in therapeutic effect against kidney cancer or diagnosing the prognosis of the patient with kidney cancer according to the gender of the patient with kidney cancer.

The method for providing information required to predict a difference in therapeutic effect against kidney cancer according to the gender of the patient with kidney cancer according to the present invention may be used to diagnose a gene mutation in kidney cancer based on the gender, increase the survival rate of the patient with kidney cancer, or reduce the relapse rate of kidney cancer. Because the therapeutic effect against kidney cancer may be predicted and the survival rate of the patient with kidney cancer or the relapse rate of kidney cancer may be predicted using the information on the gene mutation which varies depending on the gender of the patient who develops kidney cancer, the method for diagnosing the prognosis of kidney cancer according to the present invention may be used to screen therapeutic agents suitable for each patient and select therapeutic methods so as to provide information, thereby effectively designing a therapeutic strategy for kidney cancer.

MODE FOR INVENTION

Hereinafter, the present invention will be described in further detail with reference to examples and experimental examples thereof.

However, it should be understood that the following examples are just preferred examples for the purpose of illustration only and is not intended to limit or define the scope of the invention.

Example 1

Acquisition of Genetic Information and Clinical Information

To check whether the genes of (ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1) may be used as a kidney cancer marker according to the gender of a patient with kidney cancer, the data on the relapse, metastasis, death, and observation time of 417 patients with clear cell renal cell carcinoma whose genetic information and clinical information were all secured were obtained from The Cancer Genome Atlas (TCGA), and used for analyses. The following Table 1 lists the data on the relapse, metastasis, and death of the patients with clear cell renal cell carcinoma.

	TABLE 1
	Total

Gender

Number of

Ratio

	Male	Female	patients	(%)

Relapse	0	148	(54.6%)	81	(55.5%)	229	55.2%
	1	77	(28.4%)	32	(21.9%)	109	26.1%
	Not	46	(17.0%)	33	(22.6%)	79	18.7%
	detected
Metas-	0	224	(82.7%)	127	(87.0%)	351	84.2%
tasis	1	47	(17.3%)	19	(13.0%)	66	15.8%
Death	0	181	(66.8%)	89	(61.0%)	270	65.0%
	1	90	(33.2%)	57	(39.0%)	147	35.0%

Total number	271	146	417
of patients

Example 2

Confirmation of Usability as Gender-Specific Marker

417 patients were divided into two groups based on the gender thereof to check a correlation between of the gender and the mutations of the candidate genes in Example 1 using three feature selection methods (Information Gain, Chi-Square, and MR). Mutation positions of the genes are listed in the following Tables 2 to 6.

TABLE 2
	Accession	AA		Copy		Mutation		Start	End
Gene	No.	change	Type	#	COSMIC	Assessor	Chr	Pos	Pos	Ref	Var

ACSS3	NM_024560.3	R634*	Nonsense	Diploid	4		chr12	81647354	81647354	C	T
		X152_splice	Splice	Gain			chr12	81503485	81503485	T	C
		G268D	Missense	Gain	1	Low	chr12	81536908	81536908	G	A
ADAM21	NM_003813.3	N265Y	Missense	ShallowDel	2	Medium	chr14	70925009	70925009	A	T
		R408C	Missense	Diploid	3	Medium	chr14	70925438	70925438	C	T
		T589S	Missense	Diploid	1	Low	chr14	70925981	70925981	A	T
		I161V	Missense	Diploid	3	Low	chr14	70924697	70924697	A	G
AFF2	NM_002025.3	S770F	Missense	DeepDel	1	Low	chr23	148037884	148037884	C	T
		P513H	Missense	Diploid	1	Medium	chr23	148035250	148035250	C	A
		T640N	Missense	Gain	1	Low	chr23	148037494	148037494	C	A
		I149K	Missense	Diploid	1	Neutral	chr23	147743694	147743694	T	A
		I149K	Missense	Diploid	1	Neutral	chr23	147743694	147743694	T	A
		I149K	Missense	Diploid	1	Neutral	chr23	147743694	147743694	T	A
ALG13	NM_001099922.2	P925T	Missense	Diploid		Low	chr23	110987973	110987973	C	A
		L195Pfs*23	FS del	Diploid			chr23	110951455	110951455	T	—
		V456E	Missense	Diploid		Medium	chr23	110964871	110964871	T	A
BAP1	NM_004656.3	M1?	Nonstart	ShallowDel	6		chr3	52443894	52443894	T	C
		G128*	Nonsense	ShallowDel	2		chr3	52441470	52441470	C	A
		E402*	Nonsense	ShallowDel			chr3	52438515	52438515	C	A
		E283Gfs*52	FS del	ShallowDel	1		chr3	52439864	52439864	T	—
		V335Efs*56	FS del	ShallowDel	1		chr3	52439219	52439238	GCTG	—
										CCTG
										GAGG
										CTTC
										ACCA
		Q253*	Nonsense	ShallowDel	2		chr3	52440295	52440295	G	A
		Q267*	Nonsense	ShallowDel	1		chr3	52439913	52439913	G	A

TABLE 3
	Accession	AA		Copy		Mutation		Start	End
Gene	No.	change	Type	#	COSMIC	Assessor	Chr	Pos	Pos	Ref	Var

BAP1	NM_004656.3	S460*	Nonsense	ShallowDel	3		chr3	52437782	52437782	G	C
		F170V	Missense	ShallowDel	4	High	chr3	52441262	52441262	A	C
		K711Sfs*25	FS del	ShallowDel	1		chr3	52436362	52436362	T	—
		Y627*	Nonsense	ShallowDel	1		chr3	52437163	52437163	G	C
		R717Gfs*19	FS del	ShallowDel	1		chr3	52436345	52436345	G	—
		X23_splice	Splice	ShallowDel			chr3	52443729	52443729	C	T
		S279*	Nonsense	ShallowDel	1		chr3	52439876	52439876	G	T
BAP1	NM_004656.3	R60*	Nonsense	DeepDel	4		chr3	52442567	52442567	G	A
		M1?	Nonstart	ShallowDel	6		chr3	52443892	52443892	C	T
		M1?	Nonstart	ShallowDel	6		chr3	52443892	52443892	C	T
		R700Gfs*36	FS del	ShallowDel	1		chr3	52436397	52436397	C	—
		X41_splice	Splice	ShallowDel			chr3	52443568	52443568	A	G
		Q40*	Nonsense	ShallowDel	2		chr3	52443574	52443574	G	A
		Q156*	Nonsense	ShallowDel	1		chr3	52441304	52441304	G	A
		K626*	Nonsense	ShallowDel	1		chr3	52437168	52437168	T	A
		D74Efs*4	FS del	ShallowDel	1		chr3	52442523	52442523	A	—
		X41_splice	Splice	ShallowDel			chr3	52443568	52443568	A	T
		D407Vfs*23	FS del	ShallowDel	2		chr3	52438499	52438499	T	—
		F170C	Missense	ShallowDel	4	High	chr3	52441261	52441261	A	C
		X23_splice	Splice	ShallowDel			chr3	52443623	52443647	ACCT	—
										GCGA
										TGAG
										GAAA
										GGAA
										AGCA
										G
		X311_splice	Splice	ShallowDel			chr3	52439311	52439311	C	A
		E31A	Missense	ShallowDel	5	High	chr3	52443600	52443600	T	G
		N78S	Missense	ShallowDel	2	Neutral	chr3	52442512	52442512	T	C
		N78S	Missense	ShallowDel	2	Neutral	chr3	52442512	52442512	T	C
		L49V	Missense	ShallowDel	2	High	chr3	52442600	52442600	G	C
		D75G	Missense	ShallowDel	1	Neutral	chr3	52442521	52442521	T	C
		S10T	Missense	ShallowDel	4	High	chr3	52443866	52443866	C	G
		N229H	Missense	ShallowDel	1	Medium	chr3	52440367	52440367	T	G
		G109V	Missense	ShallowDel	1	High	chr3	52442023	52442023	C	A
		L17P	Missense	ShallowDel	1	Medium	chr3	52443747	52443747	A	G
		A145G	Missense	ShallowDel	1	Medium	chr3	52441418	52441418	G	C
		K659Del	IF del	DeepDel			chr3	52436801	52436803	CTT	—
		A1061T	Missense	Diploid	2	Medium	chr23	79948521	79948521	C	T

TABLE 4
	Accession	AA		Copy
Gene	No.	change	Type	#	COSMIC
BRWD3	NM_153252.4	G287A	Missense	Diploid	1
		I1747N	Missense	Diploid	1
COL4A5	NM_000495.4	P1184L	Missense	Diploid	1
		P756S	Missense	Diploid	1
		P1365S	Missense	Diploid
		G1427V	Missense	Diploid
		X1510_splice	Splice	Diploid
		A1656T	Missense	Diploid
CPEB1	NM_030594.4	S393R	Missense	Diploid
		G136V	Missense	Diploid
		X499_splice	Splice	Diploid
ERBB2	NM_004448.3	E1114G	Missense	Diploid	1
		S649T	Missense	Diploid	1
		V219I	Missense	Diploid	1
		N388Qfs*14	FS ins	Diploid
HSP90AA1	NM_001017963.2	D512N	Missense	ShallowDel	2
		H806R	Missense	Diploid	1
		I325T	Missense	ShallowDel	1
		L167V	Missense	ShallowDel	1

		Mutation		Start	End
	Gene	Assessor	Chr	Pos	Pos	Ref	Var
	BRWD3	Neutral	chr23	79991541	79991541	C	G
		Neutral	chr23	79932277	79932277	A	T
	COL4A5	Medium	chr23	107909822	107909822	C	T
		Medium	chr23	107849993	107849993	C	T
		Medium	chr23	107924995	107924995	C	T
		High	chr23	107929324	107929324	G	T
			chr23	107935977	107935977	G	T
		Neutral	chr23	107938641	107938641	G	A
	CPEB1	Medium	chr15	83221251	83221251	G	C
		Neutral	chr15	83226709	83226709	C	A
			chr15	83215272	83215272	C	A
	ERBB2	Low	chr17	37883729	37883729	A	G
		Low	chr17	37876087	37876087	G	C
		Neutral	chr17	37866350	37866350	G	A
			chr17	37871549	37871550	—	C
	HSP90AA1	High	chr14	102550300	102550300	C	T
		High	chr14	102548486	102548486	T	C
		High	chr14	102551690	102551690	A	G
		Medium	chr14	102552583	102552583	G	C

TABLE 5
	Accession	AA		Copy
Gene	No.	change	Type	#	COSMIC
IRAK1	NM_001569.3	Q280*	Nonsense	Diploid	1
		V548M	Missense	Diploid	1
		Q584K	Missense	Diploid	1
KDM5C	NM_004187.3	R681*	Nonsense	Diploid	3
		Q813*	Nonsense	Diploid	2
		E1152K	Missense	Diploid	1
		X321_splice	Splice	Diploid
		T471Vfs*5	FS del	Diploid
		R1458W	Missense	Diploid	1
		G536W	Missense	Diploid	1
		E284*	Nonsense	Diploid	1
		Q1427Pfs*50	FS del	Diploid	1
		C730R	Missense	Diploid	2
		E592V	Missense	Diploid	1
		E798*	Nonsense	Diploid	1
		C512W	Missense	Diploid	1
		Y639*	Nonsense	Diploid	1
		S1110*	Nonsense	Diploid	1
		E122Vfs*14	FS del	Diploid	1
		K459*	Nonsense	Diploid	1
		E1131Sfs*16	FS del	Diploid	1
		C730F	Missense	Diploid	2
		H988Tfs*18	FS del	Diploid	1
		H733P	Missense	Diploid	1
		P27Lfs*46	FS del	Diploid	1
		F56Cfs*18	FS del	Diploid	1
		D1414Efs*54	FS del	Diploid	1
		R215*	Nonsense	Diploid	1
		G845Rfs*2	FS del	ShallowDel

		Mutation		Start	End
	Gene	Assessor	Chr	Pos	Pos	Ref	Var
	IRAK1		chr23	153283528	153283528	G	A
		Neutral	chr23	153278782	153278782	C	T
		Low	chr23	153278674	153278674	G	T
	KDM5C		chr23	53230752	53230752	G	A
			chr23	53227751	53227751	G	A
		Medium	chr23	53223905	53223905	C	T
			chr23	53244975	53244975	A	G
			chr23	53240028	53240031	GGTA	—
		Low	chr23	53222460	53222460	G	A
		High	chr23	53239736	53239736	C	A
			chr23	53245090	53245090	C	A
			chr23	53222653	53222656	GGCT	—
		Medium	chr23	53228214	53228214	A	G
		High	chr23	53231127	53231127	T	A
			chr23	53227796	53227796	C	A
		High	chr23	53239905	53239905	G	C
			chr23	53230876	53230877	—	T
			chr23	53224222	53224222	G	C
			chr23	53247129	53247135	CCAC	—
						CTT
			chr23	53240705	53240705	T	A
			chr23	53224160	53224160	C	—
		Medium	chr23	53228213	53228213	C	A
			chr23	53225887	53225887	G	—
		Medium	chr23	53228204	53228204	T	G
			chr23	53253992	53253992	G	—
			chr23	53250081	53250082	AA	—
			chr23	53222684	53222694	TGTG	—
						GTTC
						TCA
			chr23	53246339	53246339	T	A
			chr23	53227036	53227042	GTAGACC	—

TABLE 6
	Accession	AA		Copy
Gene	No.	change	Type	#	COSMIC
KDM6A	NM_021140.3	A30V	Missense	Diploid	1
		A1246Pfs*19	FS del	Diploid
		V156Del	IF del	ShallowDel
LRP12	NM_013437.4	S622L	Missense	Diploid	1
		E639K	Missense	Diploid	2
		V671I	Missense	Gain	1
NCOA6	NM_001242539.2	G164E	Missense	Diploid	1
		N877I	Missense	Gain	1
		N864Y	Missense	Gain	1
		V1444A	Missense	Diploid	1
		H832Sfs*47	FS ins	Gain
NHS	NM_198270.3	C360R	Missense	Diploid
		P1107A	Missense	Diploid	1
		D1069H	Missense	Diploid	2
RGAG1	NM_020769.2	A1015G	Missense	Diploid	1
		M858V	Missense	Diploid	1
		G1053R	Missense	Diploid	1
SCAF1	NM_021228.2	A219Sfs*11	FS ins	ShallowDel
		P211Tfs*19	FS ins	Diploid
		P211Tfs*19	FS ins	Diploid
		A216Pfs*94	FS del	Diploid

		Mutation		Start	End
	Gene	Assessor	Chr	Pos	Pos	Ref	Var
	KDM6A	Medium	chr23	44732886	44732886	C	T
			chr23	44949174	44949174	A	—
			chr23	44879876	44879878	GGT	—
	LRP12	Low	chr8	105503616	105503616	G	A
		Neutral	chr8	105503566	105503566	C	T
		Neutral	chr8	105503470	105503470	C	T
	NCOA6	Low	chr20	33356290	33356290	C	T
		Low	chr20	33337368	33337368	T	A
		Neutral	chr20	33337408	33337408	T	A
		Neutral	chr20	33329729	33329729	A	G
			chr20	33337505	33337506	—	G
	NHS	Low	chr23	17742451	17742451	T	C
		Low	chr23	17745608	17745608	C	G
		Medium	chr23	17745494	17745494	G	C
	RGAG1	Low	chr23	109696889	109696889	C	G
		Neutral	chr23	109696417	109696417	A	G
		Low	chr23	109697002	109697002	G	C
	SCAF1		chr19	50154294	50154295	—	C
			chr19	50154270	50154271	—	C
			chr19	50154270	50154271	—	C
			chr19	50154291	50154294	TGCA	—

TABLE 7
	Accession	AA		Copy		Mutation		Start	End
Gene	No.	change	Type	#	COSMIC	Assessor	Chr	Pos	Pos	Ref	Var

SH3TC1	NM_018986.4	A375V	Missense	Diploid	1	Neutral	chr4	8224578	8224578	C	T
		R238Sfs*38	FS del	Diploid			chr4	8218768	8218768	G	—
		L180F	Missense	Diploid	1	Neutral	chr4	8217896	8217896	G	T
TBC1D8B	NM_017752.2	G1059V	Missense	Diploid	2	Neutral	chr23	106117008	106117008	G	T
		A614T	Missense	ShallowDel	1	Medium	chr23	106093257	106093257	G	A
		S861*	Nonsense	Gain	1		chr23	106109183	106109183	C	G
		Y815F	Missense	Diploid	J	Medium	chr23	106109045	106109045	A	T
		Y815F	Missense	Diploid	3	Medium	chr23	106109045	106109045	A	T
		Y815F	Missense	ShallowDel	3	Medium	chr23	106109045	106109045	A	T
TET2	NM_001127208.2	Q317K	Missense	ShallowDel	1	Low	chr4	106156048	106156048	C	A
		K326*	Nonsense	Diploid	1		chr4	106156075	106156075	A	T
		L757V	Missense	Diploid		Neutral	chr4	106157368	106157368	C	G
		V449E	Missense	Diploid		Low	chr4	106156445	106156445	T	A
		N1714K	Missense	Diploid	1	Medium	chr4	106196809	106196809	T	G
		D194E	Missense	Diploid	1	Low	chr4	106155681	106155681	C	A
		N1390H	Missense	Diploid	1	Medium	chr4	106190890	106190890	A	C
		R1451Q	Missense	Diploid	2	Medium	chr4	106193890	106193890	G	A
		M600I	Missense	ShallowDel	1	Neutral	chr4	106156899	106156899	G	A
		P554S	Missense	ShallowDel	1	Neutral	chr4	106156759	106156759	C	T
TEX13A	NM_001291277.1	R393S	Missense	Diploid		Medium	chr23	104463697	104463697	C	A
		X199_splice	Splice	Diploid	2		chr23	104464282	104464282	C	—
		X199_splice	Splice	Diploid	2		chr23	104464282	104464282	C	—
		Y257D	Missense	Diploid		Low	chr23	104464107	104464107	A	C
ULK3	NM_001099436.3	Q81Sfs*41	FS del	Diploid			chr15	75134624	75134624	A	—
		D79H	Missense	Diploid		Medium	chr15	75134629	75134629	C	G
		L77V	Missense	Diploid		Low	chr15	75134635	75134635	G	C
WNK3	NM_001002838.3	S865*	Nonsense	Diploid	1		chr23	54276546	54276546	G	T
		E537G	Missense	Diploid	1	Low	chr23	54321069	54321069	T	C
		Y589*	Nonsense	Diploid	1		chr23	54319687	54319687	A	T

The correlation between the mutagenesis of the candidate genes and the gender of the patients with kidney cancer was confirmed with respect to each the gender groups. A P-value of less than 0.05 was considered to be statistically significant. The following Tables 8 and 11 list information on the related candidate genes (M0: No distant metastasis, and M1: Distant metastasis).

	TABLE 8
	Total
	No. of
	patients
	with

identified

Fisher's

Mutation type

Gender

gene

Exact

Missense

Missense

In-

Metastasis

Metastasis

M

F

mutations

(P-value)

Mutation(%)

Truncating

(P)

(D)

frame

Cytoband

M0

M1

(%)

ACSS3	0	3	3	0.042	0.72%	2	1	0	0	12q21.31	1	2	66.70%
ADAM21	0	4	4	0.015	0.96%	0	4	0	0	14q24.1	4	0	0.00%
AFF2	1	5	6	0.022	1.44%	0	6	0	0	Xq28	5	1	16.70%
ALG13	0	3	3	0.042	0.72%	1	2	0	0	Xq23	3	0	0.00%
AOC2	2	2	4	0.614	0.96%	3	1	0	0	17q21	4	0	0.00%
AR	0	1	1	0.35	0.24%	0	1	0	0	Xq12	1	0	0.00%
ARSF	0	1	1	0.35	0.24%	0	1	0	0	Xp22.3	1	0	0.00%
ASUN	1	2	3	0.281	0.72%	1	2	0	0	12p11.23	2	1	33.30%
ASXL2	2	4	6	0.19	1.44%	4	1	0	1	2p24.1	4	2	33.30%
ASXL3	7	0	7	0.102	1.68%	0	7	0	0	18q12.1	4	3	42.90%
AVPR2	0	2	2	0.122	0.48%	0	2	0	0	Xq28	2	0	0.00%
BAP1	12	25	37	<0.001	8.87%	25	8	3	1	3p21.1	26	11	29.70%
BCOR	2	0	2	0.544	0.48%	1	1	0	0	Xq25-q26.1	1	1	50.00%
BHLHB9	3	0	3	0.555	0.72%	0	3	0	0	Xq23	3	0	0.00%
BRWD3	0	3	3	0.042	0.72%	0	3	0	0	Xq21.1	3	0	0.00%
CDCA7	0	2	2	0.122	0.48%	0	2	0	0	2q31.1	2	0	0.00%
CELSR1	7	0	7	0.102	1.68%	3	4	0	0	22q13.31	5	2	28.60%
CFP	1	3	4	0.126	0.96%	1	3	0	0	Xp11.4	3	1	25.00%
CLN8	0	2	2	0.122	0.48%	0	2	0	0	8p23	2	0	0.00%

	TABLE 9
	Total
	No. of
	patients
	with

identified

Fisher's

Mutation type

Gender

gene

Exact

Mutation

Missense

Missense

In-

Metastasis

Metastasis

M

F

mutations

(P-value)

(%)

Truncating

(P)

(D)

frame

Cytoband

M0

M1

(%)

COL4A5	1	5	6	0.022	1.44%	1	5	0	0	Xq22	5	1	16.70%
CPEB1	0	3	3	0.042	0.72%	1	2	0	0	15q25.2	2	1	33.30%
CYLC1	0	2	2	0.122	0.48%	0	2	0	0	Xq21.1	2	0	0.00%
DYSF	2	4	6	0.19	1.44%	2	3	0	1	2p13.2	4	2	33.30%
ERBB2	0	4	4	0.015	0.96%	1	3	0	0	17q12	4	0	0.00%
FAM47A	1	3	4	0.126	0.96%	0	2	0	2	Xp21.1	3	1	25.00%
FRMD7	4	0	4	0.302	0.96%	2	2	0	0	Xp22.2	3	1	25.00%
FRMPD4	4	0	4	0.302	0.96%	3	1	0	0	Xp22.2	4	0	0.00%
GABRQ	2	4	6	0.19	1.44%	2	4	0	0	Xq28	5	1	16.70%
GPR45	0	3	3	0.042	0.72%	1	2	0	0	2q12.1	2	1	33.30%
HAUS7	2	0	2	0.544	0.48%	0	2	0	0	Xq28	1	1	50.00%
HSP90AA1	0	4	4	0.015	0.96%	0	4	0	0	14q32.31	4	0	0.00%
IRAK1	0	3	3	0.042	0.72%	1	2	0	0	Xq28	3	0	0.00%
ITIH6	0	1	1	0.35	0.24%	0	1	0	0	Xp11.22-	1	0	0.00%
										p11.21
KDM5C	3	23	26	<0.001	6.24%	18	8	0	0	Xp11.22-	22	4	15.40%
										p11.21
KDM6A	0	3	3	0.042	0.72%	1	1	0	1	Xp11.2	3	0	0.00%
LPAR4	0	2	2	0.122	0.48%	1	1	0	0	Xq21.1	2	0	0.00%
LRP12	0	3	3	0.042	0.72%	0	3	0	0	8q22.2	3	0	0.00%
MAGEB10	0	2	2	0.122	0.48%	0	2	0	0	Xp21.1	2	0	0.00%

TABLE 10
			Total
			No. of
			patients
			with
			identified	Fisher's

Gender

gene

Exact

Mutation type

	M	F	mutations	(P-value)	Mutation(%)	Truncating
MAGEB16	0	2	2	0.122	0.48%	0
MAGED1	2	0	2	0.544	0.48%	0
MAP3K15	1	3	4	0.126	0.96%	2
MED14	4	1	5	0.661	1.20%	1
NBPF10	4	4	8	0.459	1.92%	2
NCOA6	0	4	4	0.015	0.96%	1
NCOR1P1	Null	20p11.1	Null
NHS	0	3	3	0.042	0.72%	0
NOX1	2	2	4	0.614	0.96%	2
PABPC3	9	1	10	0.176	2.40%	1
PHF16(JADE3)	0	2	2	0.122	0.48%	0
POTEH-AS1	Null	22q11.1	Null
PRRG3	0	2	2	0.122	0.48%	0
RGAG1	0	3	3	0.042	0.72%	0
SCAF1	0	4	4	0.015	0.96%	4
SCRN1	0	2	2	0.122	0.48%	1
SH3TC1	0	3	3	0.042	0.72%	1
SMC1A	0	2	2	0.122	0.48%	1
SYTL4	0	1	1	0.35	0.24%	0

Mutation type

Missense

Missense

In-

Metastasis

Metastasis

		(P)	(D)	frame	Cytoband	M0	M1	(%)
	MAGEB16	2	0	0	Xp21.1	2	0	0.00%
	MAGED1	2	0	0	Xp11.23	2	0	0.00%
	MAP3K15	2	0	0	Xp22.12	3	1	25.00%
	MED14	4	0	0	Xp11.4	5	0	0.00%
	NBPF10	6	0	0	1q21.1	6	2	25.00%
	NCOA6	3	0	0	20q11.22	4	0	0.00%
	NCOR1P1
	NHS	3	0	0	Xp22.13	3	0	0.00%
	NOX1	2	0	0	Xq22	4	0	0.00%
	PABPC3	9	0	0	13q12-ql3	10	0	0.00%
	PHF16(JADE3)	2	0	0	Xp11.23	2	0	0.00%
	POTEH-AS1
	PRRG3	2	0	0	Xq28	2	0	0.00%
	RGAG1	3	0	0	Xq23	3	0	0.00%
	SCAF1	0	0	0	19q13.33	3	1	25.00%
	SCRN1	1	0	0	7p14.3	1	1	50.00%
	SH3TC1	2	0	0	4p16.1	3	0	0.00%
	SMC1A	1	0	0	Xp11.22-	2	0	0.00%
					p11.21
	SYTL4	1	0	0	Xq21.33	1	0	0.00%

	TABLE 11
	Total
	No. of
	patients
	with

identified

Fisher's

Mutation type

Gender

gene

Exact

Mutation

Missense

Missense

In-

Metastasis

Metastasis

M

F

mutations

(P-value)

(%)

Truncating

(P)

(D)

frame

Cytoband

M0

M1

(%)

TBC1D8B	1	5	6	0.022	1.44%	1	5	0	0	Xq22.3	6	0	0.00%
TET2	9	0	9	0.03	2.16%	1	8	0	0	4q24	3	6	66.70%
TEX13A	0	4	4	0.015	0.96%	2	2	0	0	Xq22.3	4	0	0.00%
TFDP3	1	2	3	0.281	0.72%	0	3	0	0	Xq26.2	3	0	0.00%
TRO	0	2	2	0.122	0.48%	1	1	0	0	Xp11.22-	2	0	0.00%
										p11.21
ULK3	0	3	3	0.042	0.72%	1	2	0	0	15q24.1	3	0	0.00%
USP51	1	4	5	0.53	1.20%	1	4	0	0	Xp11.21	3	2	40.00%
WNK3	0	3	3	0.042	0.72%	2	1	0	0	Xp11.22	2	1	33.30%
ZMYM3	1	1	2	1	0.48%	0	2	0	0	Xq13.1	2	0	0.00%
ZNF318	2	5	7	0.054	1.68%	2	5	0	0	6p21.1	6	1	14.30%
ZNF449	0	1	1	0.35	0.24%	0	1	0	0	Xq26.3	1	0	0.00%

From the analysis results, it was confirmed that there were the genes whose P-values were shown to be greater than or equal to 0.05 compared to the other groups even when the genes had mutations in each of the gender groups, and also confirmed that there were the genes whose P-values were shown to be less than 0.05 while the genes had the mutations. Because the mutant genes whose P-values were less than 0.05 compared to the other groups correlated with the certain gender group compared to the other groups, the mutant genes were defined as gender-specific genes. For example, it can be seen that there were a large total number of patients in which AOC2, AR, and ARSF were mutated, but the AOC2, AR, and ARSF mutants had a high P-value of 0.05 or more, there was no correlation between the gender of the patients and the mutations of these genes. On the other hand, it was confirmed that, because the ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, and WNK3 genes has a P-value of less than 0.05 in comparison between the groups, there was a correlation between the gender of the patients and the mutagenesis of these genes.

FIG. 1 shows the results of analyzing the correlation between the gender of patients and the mutations of genes. As shown in FIG. 1, it was confirmed that there were a larger number of patients having the mutant genes in the female groups than in the male groups in the case of the ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TEX13A, ULK3, and WNK3 genes, and there were a larger number of patients having the mutant gene in the male groups than in the female groups in the case of the TET2 gene.

From the results, it can be seen that the mutations of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TEX13A, ULK3, and WNK3 were able to be used as the markers specific to the female groups, and that the mutation of TET2 was able to be used as the marker specific to the male groups.

Example 3

Confirmation of Applicability as Survival-Specific Markers According to Gender

It was confirmed whether there were survival-specific mutant genes among the candidate genes according to the gender. The analyses were performed in the same manner as in Example 2. Mutation positions of the respective genes are listed in Table 12.

TABLE 12
	Accession	AA		Copy
Gene	No.	change	Type	#	COSMIC
ACSS3	NM_024560.3	R634*	Nonsense	Diploid	4
		X152_splice	Splice	Gain
		G268D	Missense	Gain	1
ALG13	NM_001099922.2	P925T	Missense	Diploid
		L195Pfs*23	FS del	Diploid
		V456E	Missense	Diploid
ARSF	NM_001201538.1	I42F	Missense	Diploid	1
CFP	NM_001145252.1	S27L	Missense	Diploid	2
		R359Q	Missense	Diploid	1
		E135K	Missense	Diploid	1
		E323Gfs*34	FS ins	Gain	1
FAM47A	NM_203408.3	R505H	Missense	ShallowDel	3
		E507Q	Missense	ShallowDel	6
		L235_H246Del	IF del	Diploid
		L235_H246Del	IF del	Diploid
KDM6A	NM_021140.3	A30V	Missense	Diploid	1
		A1246Pfs*19	FS del	Diploid
		V156Del	IF del	ShallowDel
PHF16(JADE3)	NM_001077445.2	K656Q	Missense	Diploid
		R207W	Missense	ShallowDel
ZNF449	NM_152695.5	F183I	Missense	Diploid	1
SCRN1	NM_001145514.1	D427Y	Missense	Gain
		A257Cfs*34	FS ins	Diploid

		Mutation		Start	End
	Gene	Assessor	Chr	Pos	Pos	Ref	Var
	ACSS3		chr12	81647354	81647354	C	T
			chr12	81503485	81503485	T	C
		Low	chr12	81536908	81536908	G	A
	ALG13	Low	chr23	110987973	110987973	C	A
			chr23	110951455	110951455	T	—
		Medium	chr23	110964871	110964871	T	A
	ARSF	Medium	chr23	2990179	2990179	A	T
	CFP	Medium	chr23	47489070	47489070	G	A
		Low	chr23	47485783	47485783	C	T
		Low	chr23	47487501	47487501	C	T
			chr23	47485891	47485892	—	C
	FAM47A	Neutral	chr23	34148882	34148882	C	T
		Low	chr23	34148877	34148877	C	G
			chr23	34149658	34149693	ATGG	—
						GACA
						CTCC
						AGTC
						TCTG
						GAGG
						CTCC
						GGGC
						GGAG
			chr23	34149658	34149693	ATGG	—
						GACA
						CTCC
						AGTC
						TCTG
						GAGG
						CTCC
						GGGC
						GGAG
	KDM6A	Medium	chr23	44732886	44732886	C	T
			chr23	44949174	44949174	A	—
			chr23	44879876	44879878	GGT	—
	PHF16(JADE3)	Low	chr23	46917973	46917973	A	C
		Medium	chr23	46887437	46887437	C	T
	ZNF449	Low	chr23	134483227	134483227	T	A
	SCRN1	Medium	chr7	29963599	29963599	C	A
			chr7	29980329	29980330	—	C

An overall survival Kaplan-Meier estimate and a disease-free survival Kaplan-Meier estimate were calculated using a Kaplan-Meier survival analysis method (Spss 21). The 417 target patients volunteered in Example 1 were divided into surviving patients (270) and dead patients (147), and comparative analyses thereof were performed. The overall survival Kaplan-Meier estimate or the disease-free survival Kaplan-Meier estimate was calculated based on the clinical information (occurrence of events (death or relapse), and observation time) on the patients volunteered in Example 1 using the Kaplan-Meier survival analysis method. The event was defined as ‘death’ for the overall survival Kaplan-Meier estimate, and the event was defined as ‘relapse’ for the disease-free survival Kaplan-Meier estimate. To verify whether the mutagenesis in each of the genes correlated with the death of the patients from kidney cancer or the relapse of kidney cancer, the correlation between the mutagenesis and the overall survival Kaplan-Meier estimate, and the correlation between the mutagenesis and the disease-free survival Kaplan-Meier estimate were confirmed, based on the event times of the respective groups obtained in the Kaplan-Meier survival analysis method, using a log rank test. A P-value of less than 0.05 was considered to be statistically significant. Cases with alterations in the query genes of the present invention were used as the experimental groups, and a case without alterations in the query genes of the present invention was used as the control. A median months survival refers to a median value when the survival estimates of the patients from the corresponding groups were listed. A gradient of the survival curve obtained by the Kaplan-Meier survival analysis method was determined by the survival estimates.

To check whether the mutagenesis in each of the candidate genes correlated with the survival rate of the patients with kidney cancer, who had a certain gender, the genetic information on the 417 patient with kidney cancer obtained in Example 1 was analyzed. The gender of the patients in which the mutations of the ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes were identified was listed in Table 13.

	TABLE 13
	Gender group	Total number of patients with

	M	F	identified gene mutations

	ACSS3	0	3	3
	ALG13	0	3	3
	ARSF	0	1	1
	CFP	1	3	4
	FAM47A	1	3	4
	KDM6A	0	3	3
	PHF16	0	2	2
	ZNF449	0	1	1
	SCRN1	0	2	2

As shown in FIGS. 2 to 10, it can be seen that, because the probability of the null hypothesis being true was shown to be greater than or equal to 99.5% when it is assumed that the mutagenesis of the ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes correlated with the survival rates of the females of the patients with kidney cancer in comparison between the groups, that is, the probability of the null hypothesis being false was shown to be less than 0.5%, there was the correlation between the mutagenesis of the ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes and the survival rate of the female patients of the patients with kidney cancer (see information on ‘Gender group’ and information on ‘Total number of patients with identified gene mutations’ listed in Table 13).

Some mutant genes whose P-values were shown to be greater than or equal to 0.05, the value of which was considered to be insignificant, when only the correlation between the mutagenesis and the gender was verified in Example 1 had a P-value of less than 0.05, the value of which was considered to be significant, when the correlation between the mutagenesis and the survival rates of the patients with kidney cancer who had a certain gender. For example, the P-value of ARSF was considered to be insignificant only when the correlation between the mutagenesis and the gender was verified in Example 1, but considered to be significant when the correlation between the mutation of ARSF and the survival rates of the patients was compared between the gender groups in this example (see information on ‘Gender group’ of Table 13 and the P-values shown in FIGS. 2 to 15).

The analysis results of survival of the patients with kidney cancer who had the mutant genes are shown in FIGS. 2 to 15.

From the analysis results, as shown in FIG. 2(A), it was confirmed that at least 50% of the patients with kidney cancer in which the ACSS3 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ACSS3 gene was mutated died within 20 months, the patients with kidney cancer in which the ACSS3 gene was mutated had a survival rate lower than the patients with kidney cancer in which the ACSS3 gene was not mutated (red). Referring to FIG. 2(B), it was revealed that at least 50% of the patients with kidney cancer in which the ACSS3 gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 40 months when the ACSS3 gene was mutated (red). Therefore, it can be seen that the mutation of the ACSS3 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the ACSS3 gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 3, it was confirmed that at least 50% of the patients with kidney cancer in which the ALG13 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ALG13 gene was mutated died within 20 months, the patients with kidney cancer in which the ALG13 gene was mutated had a survival rate lower than the patients with kidney cancer in which the ALG13 gene was not mutated (red). Therefore, it can be seen that the mutation of the ALG13 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer because the patients had a high probability of dying from kidney cancer when the ALG13 gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 4(A), it was confirmed that at least 50% of the patients with kidney cancer in which the ARSF gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ARSF gene was mutated died within 20 months, the patients with kidney cancer in which the ARSF gene was mutated had a survival rate lower than the patients with kidney cancer in which the ARSF gene was not mutated (red). Referring to FIG. 4(B), it was revealed that at least 50% of the patients with kidney cancer in which the ARSF gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 20 months when the ARSF gene was mutated (red). Therefore, it can be seen that the mutation of the ARSF gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the ARSF gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 5(A), it was confirmed that at least 50% of the patients with kidney cancer in which the CFP gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the CFP gene was mutated died within 20 months, the patients with kidney cancer in which the CFP gene was mutated had a survival rate lower than the patients with kidney cancer in which the CFP gene was not mutated (red). Referring to FIG. 5(B), it was revealed that at least 50% of the patients with kidney cancer in which the CFP gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 40 months when the CFP gene was mutated (red). Therefore, it can be seen that the mutation of the CFP gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the CFP gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 6(A), it was confirmed that at least 50% of the patients with kidney cancer in which the FAM47A gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the FAM47A gene was mutated died within 20 months, the patients with kidney cancer in which the FAM47A gene was mutated had a survival rate lower than the patients with kidney cancer in which the FAM47A gene was not mutated (red). Referring to FIG. 6(B), it was revealed that at least 50% of the patients with kidney cancer in which the FAM47A gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 40 months when the FAM47A gene was mutated (red). Therefore, it can be seen that the mutation of the FAM47A gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the FAM47A gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 7, it was confirmed that at least 50% of the patients with kidney cancer in which the KDM6A gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the KDM6A gene was mutated died within 20 months, the patients with kidney cancer in which the KDM6A gene was mutated had a survival rate lower than the patients with kidney cancer in which the KDM6A gene was not mutated (red). Therefore, it can be seen that the mutation of the KDM6A gene was useful as the marker for predicting the survival rate of the patients with kidney cancer because the patients had a high probability of dying from kidney cancer when the KDM6A gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 8, it was confirmed that at least 50% of the patients with kidney cancer in which the PHF16 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the PHF16 gene was mutated died within 40 months, the patients with kidney cancer in which the PHF16 gene was mutated had a survival rate lower than the patients with kidney cancer in which the PHF16 gene was not mutated (red). Therefore, it can be seen that the mutation of the PHF16 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer because the patients had a high probability of dying from kidney cancer when the PHF16 gene was mutated and the gender of the patients with kidney cancer was female.

Referring to FIG. 9, it was revealed that at least 50% of the patients with kidney cancer in which the SCRN1 gene did not relapsed into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 20 months when the SCRN1 gene was mutated (red). Therefore, it can be seen that the mutation of the SCRN1 gene was useful as the marker for predicting the relapse of kidney cancer because the patients had a high probability of relapsing into kidney cancer when the SCRN1 gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 10(A), it was confirmed that at least 50% of the patients with kidney cancer in which the ZNF449 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ZNF449 gene was mutated died within 10 months, the patients with kidney cancer in which the ZNF449 gene was mutated had a survival rate lower than the patients with kidney cancer in which the ZNF449 gene was not mutated (red). Referring to FIG. 10(B), it was revealed that at least 50% of the patients with kidney cancer in which the ZNF449 gene did not relapsed into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 20 months when the ZNF449 gene was mutated (red). Therefore, it can be seen that the mutation of the ZNF449 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer or the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the ZNF449 gene was mutated and the gender of the patients with kidney cancer was female.

From the above results, it can be seen that the survival rate of the patients with kidney cancer who had a certain gender was significantly reduced, or the relapse rate of kidney cancer in the patients with kidney cancer was increased when any one gene selected from the group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 was mutated. Therefore, it can be seen that the prognoses of kidney cancer, particularly the survival of the patients with kidney cancer or the relapse of kidney cancer, were able to be predicted by comparing the gender of the patients to check whether the genes of the present invention were mutated.

Example 4

Manufacture of Chips Capable of Detecting Genes of Examples 2 and 3

Primer sets for detecting mutations of the genes of Examples 2 and 3 were constructed using Ion AmpliSeq Custom and Community Panels (commercially available from Thermo fisher) with reference to https://tools.thermofishercom/content/sfs/manuals/MAN0006735_AmpliSeq_DNA_R NA_LibPrep_UG.pdf. To easily detect the mutations, types of chips were selected and the depth of the chips was enhanced. Specifically, information on a panel to be manufactured was input into Ampliseq.com, and the input information was fed back. Thereafter, the related items were discussed to manufacture a panel equipped with a primer set capable of detecting the mutation. Tables 14 to 21 list the primer sets capable of detecting the mutations of the genes of the present invention.

TABLE 14
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop

ACSS3	chr12	31	GGGATAAGATTG	32	GAAGGCTCTAC	8150	8150	8150	8150
			CTATCATCTATG		AATGAGAATGTA	3404	3433	3537	3566
			ACAGT		TGCTAT
ACSS3	chr12	33	TTCAGTCAGATG	34	ACAGTCATGTG	8153	8153	8153	8153
			CTCAGACTTAAA		ACTGGGCTTTT	6787	6817	6938	6960
			TAGATT
ACSS3	chr12	35	CTCTAGATATAA	36	CCATTGACAATG	8164	8164	8164	8164
			ATGCAACAGAG		GCAGATAAAGC	7268	7297	7411	7436
			GAGCAA		TG
ADAM21	chr14	37	GGGCTTTCGAG	38	TGCTACTTCCTT	7092	7092	7092	7092
			GAGTATTAAAAA		CTCTGTTAAGCC	4606	4634	4735	4759
			TAAGT
ADAM21	chr14	39	GTATTTCTTGTT	40	ATGCTGTAGCTG	7092	7092	7092	7092
			GTCAACATAGTG		GGAAAGACTG	4919	4949	5070	5092
			GATTCC
ADAM21	chr14	41	CTTAAACCAGG	42	GTCTTGTTCACA	7092	7092	7092	7092
			GATCATGTCTGC		CTGCTGTACG	5377	5402	5487	5509
			AT
ADAM21	chr14	43	GATGTCTTTTGT	44	GGCCACACACA	7092	7092	7092	7092
			GGGAGAGTTCA		GTACCATCTTT	5885	5911	6037	6059
			ATG
AFF2	chrX	45	TCACCAGGATAA	46	AGTCTGCATCTT	1477	1477	1477	1477
			TACCCATCCTTC		GTTTGGCTGA	4362	4364	4377	4379
			A			3	8	5	7
AFF2	chrX	47	TCGGAGAGCAG	48	CTGTGGGACAG	1480	1480	1480	1480
			CTCTGAGT		GCAGATCAT	3518	3519	3529	3531
						0	9	6	6
AFF2	chrX	49	GGCTTTGAAGC	50	GGGTCATGAAG	1480	1480	1480	1480
			ATAAGTTGTCAA		CTCCACACTTT	3739	3742	3755	3757
			CA			9	4	0	2
AFF2	chrX	51	GCCAAATCCAA	52	AGAGGTTTTTC	1480	1480	1480	1480
			GGAAATCTGTG		AGGTTCTCATGA	3780	3782	3795	3797
			GT		TCTC	5	9	2	9
ALG13	chrX	53	TCCGGATACCTG	54	CATCCATTGATG	1109	1109	1109	1109
			CATAAGCAAG		CCTCATTCAAA	5136	5138	5151	5154
			GAC			7	9	5	1
ALG13	chrX	55	GAAGACTAAGG	56	TCCTGTTGATAT	1109	1109	1109	1109
			ATTGTGAGTTTG		TTCTTTACCTTT	6478	6481	6492	6495
			TAGCA		TCTGCT	5	3	9	9
ALG13	chrX	57	TCTTTGTTAGTG	58	AGTCTCTCCCA	1109	1109	1109	1109
			ATTGCCTCACCA		CATCAAGAGCA	8788	8791	8803	8805
			T			6	1	4	6

TABLE 15
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop
BAP1	chr3	59	GTAGGAGAGAA	60	GTGGAGGCTGA	5243	5243	5243	5243
			GAAGACTGAGA		GATTGCAAACT	6693	6720	6840	6863
			GCACT		A
BAP1	chr3	61	TTCCAATCAAG	62	GTCGTGGAAGC	5243	5243	5243	5243
			AACTTGGCACC		CACGGACA	7065	7088	7218	7237
			T
BAP1	chr3	63	GCCGTGTCTGTA	64	CCATCAACGTC	5243	5243	5243	5243
			CTCTCATTGC		TTGGCTGAGAA	7674	7696	7808	7830
BAP1	chr3	65	AACCTGGTAGC	66	TTGTCCCAGGA	5243	5243	5243	5243
			CTTAGAAAGCT		GGAAGAAGACC	8439	8462	8588	8611
			G		T
BAP1	chr3	67	GGGACTTGGCA	68	ATCCCACAGCC	5243	5243	5243	5243
			TAATTGTGATTG		CTCCCAACAAA	9134	9158	9248	9270
			T
BAP1	chr3	69	GCTTCACCACTA	70	GGGAGACTGTG	5243	5243	5243	5243
			GCTTGGGTTT		AGCTTTTCTTGG	9230	9252	9353	9376
BAP1	chr3	71	GGACTTGTTGCT	72	GGGTCTACCCT	5243	5243	5243	5243
			GGCTGACTT		TTCTCCTCTGA	9836	9857	9948	9970
BAP1	chr3	73	GTATGTTCACGA	74	CGACCGCAGGA	5244	5244	5244	5244
			ATCAGAGACAA		TCAAGTATGAG	0173	0200	0325	0347
			ATGC
BAP1	chr3	75	CAGCCTGGCCT	76	CAGGATATCTGC	5244	5244	5244	5244
			CATACTTGATC		CTCAACCTGAT	0317	0339	0440	0464
					G
BAP1	chr3	77	CATGGTGCCTAC	78	CCTGAGAAGCA	5244	5244	5244	5244
			CATGGTCAAT		GAATGGCCTTA	1178	1200	1291	1313
BAP1	chr3	79	CGCACTGCACT	80	GCCAAGGCCCA	5244	5244	5244	5244
			AAGGCCATT		TAATAGCCATG	1282	1302	1418	1440
BAP1	chr3	81	CACACACCTGG	82	CCCATAGTCCTA	5244	5244	5244	5244
			CATGGCTATTA		CCTGAGGAGAA	1408	1430	1510	1534
					A
BAP1	chr3	83	CTGAAACCCTT	84	TTGGTTTCACA	5244	5244	5244	5244
			GGTGAAGTCCT		GCTGATACCCA	1981	2003	2082	2105
					A
BAP1	chr3	85	ATCCCACCCTCC	86	CCCAGCCCTGT	5244	5244	5244	5244
			AAACAAAGCA		ATATGGATTTAT	2453	2475	2601	2627
					CTT
BAP1	chr3	87	GCTGCTGCTTTC	88	GGGTGCAAGTG	5244	5244	5244	5244
			TGTGAGATTTT		GAGGAGATCTA	3443	3466	3593	3615
BAP1	chr3	89	CCCTGACATTTG	90	TCGGTAAGAGC	5244	5244	5244	5244
			CTCTGAAGGT		CTTTTCTCCCT	3570	3592	3710	3732
BAP1	chr3	91	TCTTACCGAAAT	92	AAGATGAATAA	5244	5244	5244	5244
			CTTCCACGAGC		GGGCTGGCTGG	3724	3747	3875	3897
BAP1	chrX	93	CTTACTGAACA	94	GTGGGAACAGA	7994	7994	7994	7994
			CTGTAACACTG		GCTAATATTCTC	8434	8462	8580	8608
			GAAAGA		AAGAG

TABLE 16
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop

BRWD3	chrX	95	AGAGGATCCTC	96	CTAGAGGAGCT	7993	7993	7993	7993
			AGTGGACACAA		ACCAGAGCCAA	2193	2215	2343	2367
					AC
BRWD3	chrX	97	ATTGTTTTTACA	98	TTGATGTTAGGC	7999	7999	7999	7999
			TGCCATTGCCAG		TGAACATGAAA	1496	1522	1615	1645
			AA		ACTTTTT
COL4A5	chrX	99	ATTAAATTCTCT	100	TGGGAAACCAC	1078	1078	1078	1078
			GTGGCAAACAA		GATCACCTTTT	4989	4992	5004	5006
			TAAGGAC			3	3	5	7
COL4A5	chrX	101	CAGCTGGACAG	102	GTGTGTGGTAG	1079	1079	1079	1079
			AAGGGTGAA		CTTAGTAAGAA	0980	0982	0991	0993
					AGAAGAT	1	1	0	9
COL4A5	chrX	103	CAAAAACTGGT	104	TGGAGGACCAG	1079	1079	1079	1079
			TTCTCTCACACC		CATCTCCTTTA	2488	2490	2503	2505
			AAT			0	6	2	4
COL4A5	chrX	105	CCTCATTCTTTT	106	TCTCTCAGACTC	1079	1079	1079	1079
			CCTGTAGGTCCA		AAAGACTTTCC	2924	2926	2938	2941
			A		CT	2	7	8	3
COL4A5	chrX	107	CCTTGAAAGGC	108	TCTTGAAGCAA	1079	1079	1079	1079
			TGTTTGCTATTG		AGTTGCAAACA	3588	3591	3603	3606
			T		TTATTGA	9	3	4	3
COL4A5	chrX	109	CTGCTTGGAAG	110	CCCTAGCATCTC	1079	1079	1079	1079
			AGTTTCGTTCAG		TGAAGGAAGCT	3855	3857	3870	3872
						0	3	1	4
CPEB1	chr15	111	CCCACCTGATCT	112	TGGCCAATAATG	8321	8321	8321	8321
			CGACAGAAGA		TGCCCTTCTT	5186	5208	5335	5357
CPEB1	chr15	113	CACAAGAAAAT	114	AAGTCTGTCCG	8322	8322	8322	8322
			CCAGTGCCTCA		ATCCTTGCTTC	1163	1186	1315	1337
			A
CPEB1	chr15	115	CTAACTGAGGG	116	GCTGTTGGCTG	8322	8322	8322	8322
			TGCTGGAAACT		CAAAGAAAACT	6619	6641	6770	6793
					A
ERBB2	chr17	117	GTTTGAGTGAA	118	GATCTCTTCCAG	3787	3787	3787	3787
			GGCATTCATGGT		AGTCTCAAACA	1434	1457	1582	1608
					CTT
ERBB2	chr17	119	CAAGAGGGTGG	120	GAGTGAAGGGC	3787	3787	3787	3787
			TTCCCAGAATT		AATGAAGGGTA	5993	6015	6108	6130
ERBB2	chr17	121	GGCTGGCTCCG	122	CAACGTAGCCA	3788	3788	3788	3788
			ATGTATTTGAT		TCAGTCTCAGA	3628	3650	3751	3773

TABLE 17
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop

HSP90AA1	chr14	123	ATTACATAGTAT	124	CGACAAGTCTG	1025	1025	1025	1025
			AAGGCTTACCC		TGAAGGATCTG	4842	4845	4854	4857
			AGACCA		G	7	6	9	2
HSP90AA1	chr14	125	CCTGATAACTTT	126	GTCCTTGGAATG	1025	1025	1025	1025
			CAAAATTTTGCT		ACTCAGTGCAT	5022	5026	5034	5036
			TTGTTGC			9	0	0	3
HSP90AA1	chr14	127	CAGACAGAAAT	128	CAGGTGAACCT	1025	1025	1025	1025
			TCACTCTGCAAT		ATGGGTCGT	5159	5162	5175	5177
			TACATAAAA			7	9	1	1
HSP90AA1	chr14	129	CCCAAGAAGTT	130	TGAGACGTTCG	1025	1025	1025	1025
			CACACTGAAAC		CCTTTCAGG	5249	5252	5264	5266
			C			9	2	5	5
IRAK1	chrX	131	CGCCTAGGCTCT	132	CCCGCAGGAGA	1532	1532	1532	1532
			CGTCACT		ACTCCTAC	7864	7866	7878	7880
						4	3	2	1
IRAK1	chrX	133	CCAGGTGTCAG	134	ACAGGTTTCGT	1532	1532	1532	1532
			GAGTGCTTT		CACCCAAACA	8340	8342	8355	8357
						1	1	4	5
KDM5C	chrX	135	TCCGTACCCTCT	136	TGTCTTTCTGCC	5322	5322	5322	5322
			TTGGCTCTAG		TGTCTGTAATCA	2382	2404	2516	2541
					C
KDM5C	chrX	137	CCAGAAGTGTG	138	AGTTGACTGGC	5322	5322	5322	5322
			CGGATCCTC		CCTGTGTTG	2621	2641	2768	2788
KDM5C	chrX	139	CCCACACACAC	140	CTGTCCTGGGTA	5322	5322	5322	5322
			AGATAGAGGTT		TGGCAGATC	3786	3809	3917	3938
			G
KDM5C	chrX	141	CCATCTGTGTCG	142	GTTCTCTGCCCA	5322	5322	5322	5322
			AAGCTCCTT		TGTGCAGAT	4090	4111	4229	4250
KDM5C	chrX	143	CTCTTCTGGGTC	144	CCTAGCCCTGCT	5322	5322	5322	5322
			TCCACTCAAC		GTGGATAAAG	5798	5820	5943	5965
KDM5C	chrX	145	CAGGTTGTTCAT	146	AGTCTTAGCATA	5322	5322	5322	5322
			CTGGTCCAGAA		GACATGGAGGG	6986	7009	7102	7127
					AA
KDM5C	chrX	147	GCCTCACTCAG	148	CCTCTGCCTCTA	5322	5322	5322	5322
			GCAGTTCTTTA		TTCAATACTGCC	7723	7745	7847	7873
					TA
KDM5C	chrX	149	CTACTGGAGCA	150	GATGATGAGCG	5322	5322	5322	5322
			CTTGCAGAGAT		CCAGTGTATCA	8174	8196	8276	8298

TABLE 18
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop

KDM5C	chrX	151	CCCGAACTTCC	152	CCAGAGAAGCT	5323	5323	5323	5323
			ACCAGAATAGG		AGACCTGAACC	0683	0705	0807	0830
					T
KDM5C	chrX	153	CCATCTTGCAGA	154	GAAGCAGGAGG	5323	5323	5323	5323
			TAAGCTCCTCA		GTTGTAGAGAA	0839	0862	0981	1004
					G
KDM5C	chrX	155	GCAAAGTTGTA	156	CAGGAAAATCT	5323	5323	5323	5323
			GCCTTGGTTGA		CTATCTCAACAG	1067	1089	1174	1201
					CCAT
KDM5C	chrX	157	GAGGTCAGGCT	158	CCTGCATGACC	5323	5323	5323	5323
			GGCTATCAAAT		AAGGTGTGATT	9653	9675	9789	9811
KDM5C	chrX	159	GGAGCCCACAC	160	GTACTGTGCCA	5323	5323	5323	5323
			TGACTTGATTC		CATCAATGCAG	9811	9833	9963	9985
KDM5C	chrX	161	ATGCCAGAGATA	162	GTTCCCTAGGCT	5323	5323	5324	5324
			TCTGCATTGATG		AAAGAAAATGA	9951	9976	0094	0124
			T		CTTAAGA
KDM5C	chrX	163	AGATACTAAATG	164	TAGCATTGAGG	5324	5324	5324	5324
			ATTTGCCTAAGC		AAGATGTGACT	0617	0646	0764	0790
			TCACA		GTTG
KDM5C	chrX	165	GGGAATGCTTAT	166	CCTAAGACCTT	5324	5324	5324	5324
			TGAAGGGACAA		CCTGGAGAGCA	4917	4942	5055	5078
			GA		A
KDM5C	chrX	167	GTAGCCTCATGG	168	CCATTTTTCTCT	5324	5324	5324	5324
			TCATCTTGGT		CTCCCAGATAA	5003	5025	5151	5177
					GGA
KDM5C	chrX	169	TCCCTCCACCTC	170	TAATGAGGAGA	5324	5324	5324	5324
			AAAGCTCTAA		AGGACAAGGAA	6280	6302	6406	6436
					TACAAACC
KDM5C	chrX	171	GCAAGGAGCCA	172	CTACAGGCCTA	5324	5324	5324	5324
			ATATTTTTGCCT		CTCCCTCACATA	7043	7066	7194	7217
KDM5C	chrX	173	ACCACCAGCTC	174	CTTTTGGTGACT	5324	5325	5325	5325
			CTAGTCTTCTC		TCCGGTCTTACA	9997	0019	0144	0168
KDM5C	chrX	175	CGATGGGCCTGA	176	GCGCCATGAGT	5325	5325	5325	5325
			TTTTCGC		CCTTAAGG	3960	3979	4115	4134
KDM6A	chrX	177	CCAAGCAAGAA	178	AGACTCATAGT	4487	4487	4487	4487
			TTCATGCACGT		CTGTGTTCACTT	9794	9816	9938	9966
					TGAAC
KDM6A	chrX	179	CACTGTTCATTG	180	AAAAAGGAACA	4494	4494	4494	4494
			GGTTCAGGCTA		GTCCTATTGGAT	9108	9131	9215	9245
					ATAATCC

TABLE 19
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop

LRP12	chr8	181	ACCTCGGGTACT	182	AAGTTTGTTTTC	1055	1055	1055	1055
			CTGAGTTGAG		CGTGGAGTCTG	0337	0339	0352	0354
					A	5	7	2	6
LRP12	chr8	183	TCCACGGAAAA	184	TTCCTATGGCAG	1055	1055	1055	1055
			CAAACTTCTGTG		GCAGATCAAG	0352	0355	0368	0370
			A			9	3	1	3
NCOA6	chr20	185	CTGGGAAGTTT	186	CAAGGAGAGCT	3332	3332	3332	3332
			GTTAGGATCCGA		TGAATGTGCCT	9645	9669	9793	9815
			A
NCOA6	chr20	187	CCCAAAATGGC	188	GGCCATGGGAT	3333	3333	3333	3333
			CTGCAGATATG		GTCTTTCAATG	7295	7317	7434	7456
NCOA6	chr20	189	CTCCACTGAAA	190	GGTGATCCTGCT	3333	3333	3333	3333
			GGTGCATTGAA		ACTACAGCAAAT	7420	7443	7568	7594
			A		AA
NCOA6	chr20	191	GCAGGGCTCAA	192	TTGGCTCAGAA	3335	3335	3335	3335
			ATGATCAAATAA		CCGAAGCCAAG	6193	6218	6343	6366
			GC		A
NHS	chrX	193	TCCAAGTAAATG	194	GGGATACCCGA	1774	1774	1774	1774
			AAAATTTGTTTG		GATGGTTTTCC	2356	2386	2505	2527
			CCATTT
NHS	chrX	195	ACAGCAACCCT	196	TCTCCTACTGTG	1774	1774	1774	1774
			CTTTAAAAGATG		TTCTGCTTATTAT	5415	5441	5558	5588
			GAA		GAGTA
NHS	chrX	197	ACCGTCATCCAC	198	CTTAACTTCTTC	1774	1774	1774	1774
			TGCATGTTTT		AGACTTGTTGAT	5537	5559	5657	5685
					GGAC
RGAG1	chrX	199	GAATGATGTCAT	200	AGTGTGCACAT	1096	1096	1096	1096
			CCATGCCACAA		GTCTCCAGAAG	9633	9635	9648	9650
						1	4	3	5
RGAG1	chrX	201	GTCCACATTGCA	202	CATGGGCATCGA	1096	1096	1096	1096
			AACCAGTGTT		TCCAGAAACT	9680	9683	9694	9697
						9	1	9	1
RGAG1	chrX	203	CCACATCATTTA	204	TGTGGTGTGGA	1096	1096	1096	1096
			TGAGAGCCTCA		CATTGTTCCAG	9692	9695	9708	9710
			GTT			8	4	0	2

TABLE 20
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop

SCAF1	chr19	205	CCATGTGTCCCA	206	GGGTTCGTGAG	5014	5014	5014	5014
			TTGGCTTCT		CAAAGGAGG	5305	5326	5424	5444
SCAF1	chr19	207	CGCTTTAGCTCC	208	ACTAGCGACCC	5014	5014	5014	5014
			GCCTCTC		AACTCCGC	5405	5424	5555	5574
SCAF1	chr19	209	GGGACCTCCAC	210	CTCACCAGGAT	5014	5014	5014	5014
			TCCAAACTCT		AAAGGCAGAAG	8240	8261	8372	8396
					GA
SCAF1	chr19	211	ATGGTCCGCCA	212	GTGCTTCAAGG	5014	5014	5014	5014
			GACAGAGA		GAGCCAAGAGT	8342	8361	8484	8506
SCAF1	chr19	213	GCACTTGAGTCT	214	CCGCCATACCTT	5014	5014	5014	5014
			AGCTGTCAGT		TATCATTGGG	8503	8525	8655	8677
SH3TC1	chr4	215	CCACAGGCTTC	216	CAACGCTCACC	8217	8217	8217	8217
			ACTCATCACTG		TTCTTGGATGA	832	854	972	994
SH3TC1	chr4	217	CAGTGACCACC	218	GGCGGTGAAGA	8218	8218	8218	8218
			TCCATCCTTTT		GTCTGTTTCC	658	680	804	825
SH3TC1	chr4	219	TCTGTCTGTCAA	220	CCTGGCATCCTC	8224	8224	8224	8224
			ATCAAGGAATG		CTCAGAAAAG	473	500	623	645
			GAAA
TBC1D8	chrX	221	ATGAGATACATC	222	CATATCAGTCAT	1060	1060	1060	1060
			AGCATGCTAATA		GTGTTCTGTCA	9316	9319	9330	9333
			GAAGTG		GCT	0	0	8	4
TBC1D8B	chrX	223	AGCAGACATGG	224	CAGTCAATCTG	1061	1061	1061	1061
			TTTTTAAAATCT		ATACTGTTCCAA	0894	0897	0909	0912
			TCCAAA		ATATGG	6	5	1	0
TBC1D8B	chrX	225	CCATATTTGGAA	226	TACCAATTGCA	1061	1061	1061	1061
			CAGTATCAGATT		GAGGAGAATTC	0909	0912	0923	0926
			GACTG		TTTGAA	2	1	8	6
TBC1D8B	chrX	227	TGGAAGGAAAC	228	CAACAGCGATG	1061	1061	1061	1061
			TACATAGCCCTA		CAAGAATCTGT	1691	1694	1707	1709
			CA		T	9	4	0	3
TET2	chr4	229	TAACTGCAGTG	230	AGTTCACCATG	1061	1061	1061	1061
			GGCCTGAAAAT		TGTGTGTTCCA	5560	5562	5575	5577
						6	8	1	3
TET2	chr4	231	CCTGTGATGCTG	232	AATTCTTCACCA	1061	1061	1061	1061
			ATGATGCTGATA		GACGCTAGCTT	5598	5600	5613	5615
						3	7	1	4
TET2	chr4	233	GGAAAAAGCAC	234	GCCTTTCAGAA	1061	1061	1061	1061
			TCTGAATGGTG		AGCATCGGAGA	5636	5638	5651	5653
			GA		A	3	7	4	7

TABLE 21
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_Primer*	NO	Rev_Primer*	Start	Start	Stop	Stop

TET2	chr4	235	AACTGCCAGCA	236	TTACGTTTTAGA	1061	1061	1061	1061
			GTTGATGAGAA		TGGGATTCCGCT	5668	5670	5681	5684
					T	1	3	9	4
TET2	chr4	237	CACCAAGCGGA	238	AGCTGTGTTGTT	1061	1061	1061	1061
			ATCCCATCTAA		TTCTGGGTGTA	5681	5683	5695	5697
						6	8	6	9
TET2	chr4	239	AAACACAACCA	240	CCATGAAAACA	1061	1061	1061	1061
			TCCCAGAGTTC		TTCTTCCACTTT	5728	5730	5743	5745
			A		AGTCTG	5	8	0	9
TET2	chr4	241	GGGTCACTGCAT	242	GCAGTGTGAGA	1061	1061	1061	1061
			GTTTGGACTT		ACAGACTCAAC	9083	9085	9093	9095
					AG	1	3	2	6
TET2	chr4	243	AAGTCTCTGAC	244	GAAAGCTTTTC	1061	1061	1061	1061
			GTGGATGAGTTT		AGCTGCAGCTT	9380	9382	9395	9397
			G			3	7	5	7
TET2	chr4	245	AGGTTTGGAAAT	246	ATCTAGAGGTG	1061	1061	1061	1061
			AGCCAGAGTTTT		GCTCCCATGAA	9671	9673	9686	9688
			ACA			1	8	3	5
TEX13A	chrX	247	TCGAGATATACA	248	CTCATCAGCAA	1044	1044	1044	1044
			TGCTTCGGTTCT		AGACCTCCAGT	6360	6363	6375	6377
			ATTTTG		A	5	5	6	9
TEX13A	chrX	249	GGGTTCGTGGTT	250	CCTCCATGGAG	1044	1044	1044	1044
			CCAGAGAAAT		ACCACAGAGAA	6402	6405	6415	6417
						8	0	6	8
TEX13A	chrX	251	TCTCTCCAGCTT	252	CTGCTGGAGGA	1044	1044	1044	1044
			CTCTGTGGT		AAAGGAGCAGA	6414	6416	6429	6431
						7	8	6	8
ULK3	chr15	253	GCCTGAAGAGA	254	CCAAGAAAAGT	7513	7513	7513	7513
			GTGTCCCTTCT		CTGAACAAGGC	4560	4582	4700	4724
					AT
WNK3	chrX	255	GCTGAAGAGAA	256	CCTGGCTTCTTC	5427	5427	5427	5427
			GGAGGAGACTG		AGTCAATAAGG	6466	6489	6610	6640
			A		TAAATAA
WNK3	chrX	257	GAAACTTGCTG	258	GGCAGGAGCTG	5431	5431	5431	5431
			GTAATGTCCTAC		CATCAGTTATA	9571	9598	9722	9744
			TAGT
WNK3	chrX	259	GTGCTGCTGTG	260	GGGATTCTCAG	5432	5432	5432	5432
			GTTTTCTTTGTA		TGCAAGTCTATG	1002	1025	1135	1159
					G

TABLE 22
		SEQ		SEQ
Lineitem_		ID	Ion_AmpliSeq_	ID	Ion_AmpliSeq_	Amplicon_	Insert_	Insert_	Amplicon_
Name	Chr	NO	Fwd_ Primer*	NO	Rev_Primer*	Start	Stop	Start	Stop

ARSF	chrX	261	GTGCATGACGA	262	ACGACTGACGA	2990	2990	2990	2990
			CAAGCCTAATAT		ACGTATGACTG	128	153	234	256
			TG
CFPX	chrX	263	GCTGTAGCAGT	264	ACATGAAGTCC	4748	4748	4748	4748
			GCCGGATAT		ATCAGCTGTCA	5743	5763	5843	5867
					AG
CFP	chrX	265	CCGGGATTTCTT	266	TGATTCCCTGCT	4748	4748	4748	4748
			GACAGCTGAT		TTGGTCCAATC	5835	5857	5940	5963
CFP	chrX	267	CCCACTCTGAG	268	GAATGGGCAGT	4748	4748	4748	4748
			GACCTCTGTA		GCTCTGGAA	7417	7438	7563	7583
CFP	chrX	269	GGCAAAGGCAG	270	GTGTCCAGGCC	4748	4748	4748	4748
			TGTTGAGAC		CACCACAT	8961	8981	9116	9135
FAM47A	chrX	271	ACTGGATCTCCG	272	GAGACTGGAGT	3414	3414	3414	3414
			ACGAGTGAT		GTCCCATCTAAG	9619	9640	9760	9783
JADE3	chrX	273	ACGCCATTGCCA	274	TCCACTCTCACT	4688	4688	4688	4688
			TGAAAATATGAA		AACCTGATGCA	7346	7371	7497	7520
			C
JADE3	chrX	275	CCATTCTAGGAG	276	GCCATTGGATTT	4691	4691	4691	4691
			TGAAGCAAAGG		GGCAAACTTG	7837	7861	7989	8011
			A
ZNF449	chrX	277	GGAGCTGAACT	278	CATTGAGTAATT	1344	1344	1344	1344
			ATGGTGCTACT		GGTGTTTCTAAC	8319	8321	8330	8333
					CCAAC	0	2	7	6
SCRN1	chr7	279	TTTTGCTGGTAA	280	CCTGGAAGCCA	2996	2996	2996	2996
			TTTAGTAAGGTG		TGGAAGAAATC	3511	3539	3658	3681
			GGAA		C
SCRN1	chr7	281	AGGGTATGAGA	282	GAACTCAGGAG	2998	2998	2998	2998
			AGGAGAATCGT		TTACGCTCAGA	0257	0281	0408	0430
			GA

To verify whether the mutations of the genes were detected using the constructed primer sets, the gene mutations verified in Example 2 and a DNA test samples derived from wild-type kidney cancer cells were amplified. Specifically, each of the gene mutations and the DNA test samples used as the test sample was amplified using a primer set corresponding to each of the test samples, respectively. Thereafter, the amplified chips were scanned using a scanner and application program, and analyzed using quantitative analysis software.

As a result, it can be seen that the mutations of the genes of Examples 2 and 3 were detected using the primer sets constructed in Example 4. On the other hand, the mutations were not detected in the test samples derived from the kidney cancer cells as the control. As described above, because the mutations of genes selected from a gene group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1 were detectable using the primer sets listed in Tables 14 to 22, it was possible to predict the overall survival Kaplan-Meier estimates and disease-free survival Kaplan-Meier estimates of the patients with kidney cancer in which the genes were mutated, thereby effectively designing a therapeutic strategy for kidney cancer.

Although preferred embodiments of the present invention have been shown and described for the purpose of illustration only, it would be appreciated by those skilled in the art that various modifications and changes may be made in these embodiments without departing from the scope of the present invention.