Patent Application
20220229060
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.
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.
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.
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.
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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
As shown in
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
The analysis results of survival of the patients with kidney cancer who had the mutant genes are shown in
From the analysis results, as shown in
As shown in
As shown in
As shown in
As shown in
As shown in
As shown in
Referring to
As shown in
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.
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.
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.
| Number | Date | Country | Kind |
|---|---|---|---|
| 10-2016-0124785 | Sep 2016 | KR | national |
| 10-2017-0123572 | Sep 2017 | KR | national |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15779108 | May 2018 | US |
| Child | 17646179 | US |
