KR20240173306A - Composition And Kit For Diagnosing Prognosis Of Kidney Cancer According To Gender - Google Patents

Abstract

The present invention provides a composition for prognosis diagnosis according to the gender of a kidney cancer patient, a kit for prognosis diagnosis of kidney cancer, and a method for providing information necessary for prognosis diagnosis of kidney cancer using the same. By using the composition and kit for prognosis diagnosis of kidney cancer of the present invention, it is possible to diagnose and predict the prognosis, such as the possibility of survival or recurrence after treatment, of a kidney cancer patient according to the gender, thereby helping to establish a treatment strategy for the kidney cancer patient.

Description

Composition And Kit For Diagnosing Prognosis Of Kidney Cancer According To Gender

The present invention relates to a composition for diagnosing the prognosis of kidney cancer according to the gender of the kidney cancer patient, a kit for diagnosing the prognosis of kidney cancer, and a method for providing information necessary for diagnosing the prognosis of a kidney cancer patient using the same.

The kidneys are important urinary organs that filter blood to produce urine and excrete waste products from the body. They are also important endocrine organs that produce hormones such as angiotensin, which regulates blood pressure, and erythropoietin, which is a red blood cell hematopoietic factor.

Tumors that occur in the kidney include renal cell carcinoma (RCC) that occurs in adults, Wilms tumor that occurs in children, and sarcoma, which is a rare tumor. Most kidney cancers are renal cell cancers that occur in the kidney parenchyma (the part where the cells that make urine in the kidney are gathered, consisting of the medulla and cortex). Genetic factors are known as risk factors for kidney cancer, but smoking and excessive fat intake are generally included. It is also known that the incidence of tumors is high in patients receiving long-term dialysis.

70-85% of kidney cancers are renal cell carcinomas. Renal cell carcinomas are classified into clear cell RCC, papillary RCC, chromophobe RCC, medullary RCC, and unclassified RCC. Clear cell RCC, the most common type of renal cell carcinoma, occurs more than twice as often in men than in women worldwide, and the prognosis is reported to be worse in men.

Kidney cancer rarely has symptoms when the tumor is small, and symptoms only appear when the tumor grows to a certain size and pushes the organs. Therefore, diagnosis is often delayed, and about 30% of patients are diagnosed with metastasis when they are first diagnosed. The most common symptom is hematuria, but this only occurs in 60% of patients. Rather, depending on the metastatic site, symptoms such as shortness of breath, coughing, and headaches may appear, and up to 30% of all patients are diagnosed with kidney cancer due to these metastatic symptoms. Because kidney cancer can cause high blood pressure, hypercalcemia, and liver dysfunction due to specific hormones produced by cancer cells, the tumor is sometimes found while examining other symptoms. Recently, it is often found accidentally during imaging tests during health checkups without any symptoms, and in these cases, the treatment results are relatively good because it is usually found early.

Kidney cancer has a high survival rate after tumor removal, but it is difficult to diagnose in the early stages because there are no clear symptoms. For this reason, early diagnosis of kidney cancer and development of markers that can check the remaining lifespan after cancer onset are necessary.

Patent Document 1 discloses transglutaminase 2 as a marker used for detecting or diagnosing human renal cancer. Markers for diagnosing cancers including renal cancer are being developed, but research has not yet been conducted on markers that can measure the prognosis of renal cancer patients, particularly on the correlation between the gender of renal cancer patients and mutations of specific genes.

The inventors of the present invention studied the relationship between genetic mutations found in patients with clear cell renal cell cancer and the patient's gender, in view of the need for the development of markers capable of diagnosing the prognosis of patients with renal cancer in order to diagnose renal cancer or to discover treatments for patients with renal cancer and determine treatment strategies.

Korean Patent Publication No. 1267580

In order to apply a therapeutic strategy suitable for renal cancer patients, it is necessary to develop a marker that can provide information for predicting the prognosis of renal cancer patients and determining a treatment strategy. The present invention aims to provide a marker that helps in diagnosing the prognosis of renal cancer patients and determining a treatment strategy for renal cancer patients based on the sex of the renal cancer patients.

One aspect of the present invention provides a composition for diagnosing the prognosis of renal cancer according to gender, comprising a reagent capable of detecting a gender-dependent survival specific marker of a renal cancer patient, wherein the marker comprises at least one selected from the group consisting of a mutation in the ARHGEF5 gene, a mutation in the ASB15 gene, a mutation in the BAP1 gene, a mutation in the EPB41L5 gene, a mutation in the KIAA1614 gene, a mutation in the LOXL3 gene, a mutation in the LRCH1 gene, a mutation in the OR10AG1 gene, a mutation in the PDE4C gene, a mutation in the PRSS38 gene, a mutation in the RTN3 gene, a mutation in the TENM4 gene, a mutation in the TINAGL1 gene, and a mutation in the ZFAND2B gene.

Another aspect of the present invention provides a kit for diagnosing the prognosis of renal cancer according to gender, comprising a reagent capable of detecting a gender-dependent survival specific marker of a renal cancer patient, wherein the marker comprises at least one selected from the group consisting of a mutation in the ARHGEF5 gene, a mutation in the ASB15 gene, a mutation in the BAP1 gene, a mutation in the EPB41L5 gene, a mutation in the KIAA1614 gene, a mutation in the LOXL3 gene, a mutation in the LRCH1 gene, a mutation in the OR10AG1 gene, a mutation in the PDE4C gene, a mutation in the PRSS38 gene, a mutation in the RTN3 gene, a mutation in the TENM4 gene, a mutation in the TINAGL1 gene, and a mutation in the ZFAND2B gene.

Another aspect of the present invention provides a method for providing information necessary for prognostic diagnosis of a renal cancer patient, comprising the steps of: preparing a sample DNA from a sample of a renal cancer patient; amplifying the sample DNA using a composition or kit for prognostic diagnosis of renal cancer; and confirming the presence or absence of a gender-dependent survival-specific marker from the amplification result.

By using the composition for prognosis diagnosis of renal cancer of the present invention and the kit for prognosis diagnosis of renal cancer comprising the same, the prognosis, such as the possibility of survival or recurrence after treatment, can be diagnosed and predicted based on the sex of the renal cancer patient. This can be helpful in establishing a treatment strategy for the renal cancer patient.

Figure 1 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the ARHGEF5 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 2 shows a graph of overall survival rate and disease-free survival rate by sex (female/male) for the ARHGEF5 gene.
Figure 3 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the ASB15 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 4 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the ASB15 gene.
Figure 5 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the BAP1 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 6 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the BAP1 gene.
Figure 7 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the EPB41L5 gene (red) and kidney cancer patients without a mutation in the EPB41L5 gene (blue).
Figure 8 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the EPB41L5 gene.
Figure 9 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the KIAA1614 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 10 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the KIAA1614 gene.
Figure 11 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the LOXL3 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 12 shows a graph of overall survival rate and disease-free survival rate by gender (female/male) for the LOXL3 gene.
Figure 13 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the LRCH1 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 14 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the LRCH1 gene.
Figure 15 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the OR10AG1 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 16 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the OR10AG1 gene.
Figure 17 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the PDE4C gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 18 shows a graph of overall survival and disease-free survival rates by gender (female/male) for the PDE4C gene.
Figure 19 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the PRSS38 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 20 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the PRSS38 gene.
Figure 21 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the RTN3 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 22 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the RTN3 gene.
Figure 23 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the TENM4 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 24 shows a graph of overall survival rate and disease-free survival rate by gender (female/male) for the TENM4 gene.
Figure 25 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the TINAGL1 gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 26 shows a graph of the overall survival rate and disease-free survival rate by gender (female/male) for the TINAGL1 gene.
Figure 27 shows a graph of the overall survival rate and disease-free survival rate of kidney cancer patients with a mutation in the ZFAND2B gene (red) and kidney cancer patients without a mutation in the gene (blue).
Figure 28 shows a graph of overall survival rate and disease-free survival rate by gender (female/male) for the ZFAND2B gene.
Figure 29A is a table summarizing the p values obtained by the Kaplan Meier analysis method performed in Example 2 on 417 patients with clear cell renal cell carcinoma obtained from TCGA (The Cancer Genome Atlas), and Figure 29B is a table summarizing the p values obtained by confirming the data of 120 Korean patients with renal cell carcinoma using the NGS (Next Generation Sequencing) analysis method.
Figure 30 shows a graph of the overall survival rate and disease-free survival rate by sex (female/male) as a result of performing Kaplan Meier analysis on 11 genes (ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1) identified as male-dependent survival-specific in Examples 2 and 3.
Figure 31 shows a graph of the overall survival rate and disease-free survival rate by sex (female/male) as a result of performing Kaplan Meier analysis on three genes (BAP1, OR10AG1, ZFAND2B) identified as female-dependent survival-specific in Examples 2 and 3.

In this specification, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In general, the nomenclature used herein and the experimental methods described below are well known and commonly used in the art.

The term 'gene' and its variants in the present invention include a DNA segment involved in the production of a polypeptide chain; this includes regions before and after a coding region, for example, a promoter and a 3'-untranslated region, respectively, as well as intervening sequences (introns) between individual coding segments (exons).

The term 'cancer' in this invention includes any member of the class of diseases characterized by the uncontrolled growth of abnormal cells. The term includes all known cancers and neoplastic states, whether characterized as malignant, benign, soft tissue or solid, and cancers of all stages and grades, including cancers before and after metastasis.

In the present invention, the term 'prognosis' refers to the course of a disease and whether it is cured, such as the possibility of cancer-induced death or progression, including recurrence, metastatic spread, and drug resistance, for example, in a neoplastic disease such as cancer. For the purpose of the present invention, it may be to predict the prognosis of renal cancer, and preferably to predict the disease-free survival rate or survival rate of a renal cancer patient.

In the present invention, the term 'diagnosis' means confirming the existence or characteristics of a pathological condition, and for the purpose of the present invention, it means not only confirming whether cancer has occurred, but also determining whether the subject has recurrence, metastasis, drug responsiveness, resistance, etc. after cancer treatment. Preferably, when utilizing a mutation in the gene of the present invention, by confirming whether there is a mutation in a sample of the subject, it is possible to predict not only whether the subject has cancer, but also whether the subject will have a good prognosis in the future.

In the present invention, the term 'gender-dependent survival-specific marker' may mean a mutation of a gene or mutations of genes that may be an indicator for predicting the prognosis of renal cancer in a patient after treatment based on the sex of the patient. In addition, in the present invention, 'marker gene' may be used to mean each gene mutation included in the gender-dependent survival-specific marker.

1. Composition and kit for prognostic diagnosis of renal cancer

One aspect of the present invention provides a composition for the prognosis and diagnosis of renal cancer, comprising a reagent capable of detecting a sex-dependent survival-specific marker of a renal cancer patient. The sex-dependent survival-specific marker of the composition for the prognosis and diagnosis of renal cancer of the present invention can be an indicator for predicting the prognosis of renal cancer in a subject after treatment, depending on the sex of the renal cancer patient.

For example, if the sex-dependent survival-specific marker is identified and the renal cancer patient is male, the survival rate of the individual may be determined to be lower or the recurrence rate higher than that of a person for whom the sex-dependent survival-specific marker is not identified, or if the sex-dependent survival-specific marker is identified and the renal cancer patient is female, the survival rate of the individual may be determined to be lower or the recurrence rate higher than that of a person for whom the sex-dependent survival-specific marker is not identified.

Specifically, the sex-dependent survival-specific markers include mutations in the ARHGEF5 gene (Gene bank accession number: NM_005435.3), mutations in the ASB15 gene (Gene bank accession number: NM_001290258.1), mutations in the BAP1 gene (Gene bank accession number: NM_004656.3), mutations in the EPB41L5 gene (Gene bank accession number: NM_001184937.1), mutations in the KIAA1614 gene (Gene bank accession number: NM_020950.1), mutations in the LOXL3 gene (Gene bank accession number: NM_032603.4), mutations in the LRCH1 gene (Gene bank accession number: NM_001164211.1), and mutations in the OR10AG1 gene (Gene bank accession number: The present invention may include at least one selected from the group consisting of a mutation in the NM_001005491.1 gene, a mutation in the PDE4C gene (Gene bank accession number: NM_000923.5), a mutation in the PRSS38 gene (Gene bank accession number: NM_183062.2), a mutation in the RTN3 gene (Gene bank accession number: NM_001265589.1), a mutation in the TENM4 gene (Gene bank accession number: NM_001098816.2), a mutation in the TINAGL1 gene (Gene bank accession number: NM_022164.2), and a mutation in the ZFAND2B gene (Gene bank accession number: NM_001270998.1).

Specifically, the sex-dependent survival-specific marker may be a mutation in at least one of the ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1 genes, or a mutation in at least one of the BAP1, OR10AG1, ZFAND2B genes. For example, if a mutation in at least one of the ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1 genes is detected as the sex-dependent survival-specific marker and the renal cancer patient is male, it can be determined that the individual has a lower survival rate and a higher recurrence rate than a person in whom the sex-dependent survival-specific marker is not identified. In addition, if a mutation in at least one of the BAP1, OR10AG1, and ZFAND2B genes is detected as the sex-dependent survival-specific marker and the renal cancer patient is a woman, it can be determined that the individual has a lower survival rate and a higher recurrence rate than a person in whom the sex-dependent survival-specific marker is not identified.

The full names of the abbreviations of the above genes are ARHGEF5 (Rho guanine nucleotide exchange factor 5), ASB15 (ankyrin repeat and SOCS box containing 15), BAP1 (BRCA1 associated protein 1), EPB41L5 (erythrocyte membrane protein band 4.1 like 5), and KIAA1614, respectively. (KIAA1614), LOXL3 (lysyl oxidase like 3), LRCH1 (leucine rich repeats and calponin homology domain containing 1), OR10AG1 (olfactory receptor family 10 subfamily AG member 1), PDE4C (phosphodiesterase 4C), PRSS38 (serine protease 38), RTN3 (reticulon 3), TENM4 (teneurin transmembrane protein 4) ), TINAGL1 (tubulointerstitial nephritis antigen like 1), ZFAND2B (zinc finger It may be AN1-type containing 2B).

In the present invention, the reagent capable of detecting the sex-dependent survival specific marker may include at least one selected from the group consisting of a primer, a probe, an antibody, and an aptamer for the sex-dependent survival specific marker. The primer, probe, antibody, or aptamer can be produced using a known technique, and the primer, probe, antibody, or aptamer capable of detecting a mutation in the gene of the present invention is included in the scope of the present invention.

In the present invention, the term 'primer' means a short nucleic acid sequence having a short free 3' hydroxyl group, which can form base pairs with a complementary template and functions as a starting point for copying the template strand. The primer can initiate DNA synthesis in the presence of a reagent for polymerization reaction (i.e., DNA polymerase or reverse transcriptase) and four different nucleoside triphosphates in an appropriate buffer solution and temperature. In the present invention, the presence or absence of the corresponding genetic marker can be determined through whether or not the desired product is generated by performing PCR amplification using the forward and reverse primers of the mutant gene, and this can be utilized for diagnosis. For example, in the case of a forward primer, a primer corresponding to a mutant in which a deletion, substitution or insertion has occurred is designed, and a reverse primer corresponding to a position in which a mutation has not occurred is designed, and when PCR is performed, if it is a mutant of the gene of the present invention, an amplification product will be generated by PCR, but if it is not a mutant of the gene of the present invention, no amplification product will be generated. PCR conditions, and the lengths of the forward and reverse primers can be modified based on those known in the art.

In the present invention, the term 'probe' means a nucleic acid fragment such as RNA or DNA that can specifically bind to DNA, and is composed of a few bases at the shortest and hundreds of bases at the longest. The probe is labeled so that the presence or absence of a specific DNA can be confirmed. The probe can be produced in the form of an oligonucleotide probe, a single-stranded DNA probe, a double-stranded DNA probe, an RNA probe, etc. In the present invention, hybridization is performed using a probe complementary to a mutation in a gene, and the recurrence of renal cancer can be diagnosed through hybridization. For example, if a probe corresponding to a mutant in which deletion, substitution, or insertion has occurred is synthesized and the genomic DNA of a renal cancer patient is hybridized with the probe, hybridization will occur if it is a mutant of the gene of the present invention, but hybridization will not occur if it is not a mutant of the gene of the present invention. The selection of an appropriate probe and the hybridization conditions can be modified based on what is known in the art.

In the present invention, the term 'antibody' is a term known in the art and refers to a specific protein molecule directed to an antigenic site. In the present invention, the antibody may refer to an antibody that specifically binds to each marker gene. Such an antibody may be produced by cloning each marker gene into an expression vector according to a conventional method to obtain a protein encoded by the marker gene, and then producing the obtained protein by a conventional method. This also includes a partial peptide that can be produced from the protein, and the partial peptide of the present invention includes at least 7 amino acids, preferably 9 amino acids, and more preferably 12 or more amino acids. The form of the antibody of the present invention is not particularly limited, and a polyclonal antibody, a monoclonal antibody, or a part thereof that has antigen binding properties is also included in the antibody of the present invention, and all immunoglobulin antibodies are included. Furthermore, the antibody of the present invention also includes special antibodies such as humanized antibodies. The antibody used for detecting the marker gene of the present invention includes a complete form having two full-length light chains and two full-length heavy chains, as well as a functional fragment of an antibody molecule. A functional fragment of an antibody molecule is a fragment that possesses at least an antigen-binding function, and includes Fab, F(ab'), F(ab') ₂ , and Fv.

The term 'aptamer' used herein refers to a single-stranded nucleic acid (DNA, RNA or modified nucleic acid) that has a stable tertiary structure in itself and has the characteristics of being able to bind to a target molecule with high affinity and specificity. Aptamers can be synthesized by known chemical methods, and for example, aptamers for various desired target substances (proteins, sugars, dyes, DNA, metal ions, cells, etc.) can be developed by a method called SELEX (Systematic Evolution of Ligands of Exponential enrichment).

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

The term "X#Y" in relation to a mutation in a polypeptide sequence is well-recognized in the art, where "#" indicates the position of the mutation with respect to the amino acid number of the polypeptide, "X" indicates the amino acid found at that position in the wild-type amino acid sequence, and "Y" indicates the mutant amino acid at that position. For example, the notation "E487G" in relation to an ARHGEF5 polypeptide indicates that a glutamic acid is present at amino acid number 487 in the wild-type ARHGEF5 sequence, and that the glutamic acid is replaced by glycine in the mutant ARHGEF5 sequence. Mutations in the above genes are as follows:

The mutation of the above ARHGEF5 gene is a missense mutation of at least one of E487G and V1574F in the amino acid sequence of SEQ ID NO: 1;

The mutation in the above ASB15 gene is a nonsense mutation, E105*, or a missense mutation, V246L, in the amino acid sequence of sequence number 2;

The mutation of the above BAP1 gene is a non-start mutation in the amino acid sequence of SEQ ID NO: 3, M1? (substitution of T to C at chromosomal position 52443894, substitution of C to T at 52443892), or at least one nonsense mutation selected from the group consisting of G128*, E402*, Q253*, Q267*, S460*, Y627*, S279*, R60*, Q40*, Q156* and K626*, or at least one FS del mutation selected from the group consisting of E283Gfs*52, V335Efs*56, K711Sfs*25, R717Gfs*19, R700Gfs*36, D74Efs*4 and D407Vfs*23, or F170V, F170C, At least one missense mutation selected from the group consisting of E31A, N78S, L49V, D75G, S10T, N229H, G109V, L17P, A145G and A1061T, or at least one splice mutation selected from the group consisting of X23_splice (C to T substitution at chromosomal position 52443729), X41_splice (A to G substitution at chromosomal position 52443568), X41_splice (A to T substitution at chromosomal position 52443568), X23_splice (deletion of ACCTGCGATGAGGAAAGGAAAGCAG at chromosomal positions 52443623 to 52443647), and X311_splice (C to A substitution at chromosomal position 52439311), or K659del In the notation of in-frame deletion (IF del) mutations and in-frame insertion mutations, del indicates that the corresponding amino acid is deleted at the corresponding amino acid sequence position (an explanation is omitted below);

The mutation in the above EPB41L5 gene is an IF del mutation, L303_P306del in the amino acid sequence of sequence number 4;

The mutation of the above KIAA1614 gene is at least one missense mutation selected from the group consisting of E592A, G1014S, and P1037S in the amino acid sequence of SEQ ID NO: 5;

The mutation of the above LOXL3 gene is at least one missense mutation among C376Y and H398Q in the amino acid sequence of SEQ ID NO: 6;

The mutation of the above LRCH1 gene is at least one missense mutation among L468S and H653Y in the amino acid sequence of SEQ ID NO: 7;

The mutation of the above OR10AG1 gene is a missense mutation of at least one of L204F and L156F in the amino acid sequence of SEQ ID NO: 8;

The mutation of the above PDE4C gene is at least one missense mutation selected from the group consisting of S254F, D429N, T561M, L488Q, and N437K in the amino acid sequence of SEQ ID NO: 9, or a frame shift insertion mutation of Y557Lfs*21;

The mutation of the above PRSS38 gene is an FS ins mutation of S314Qfs*21 in the amino acid sequence of SEQ ID NO: 10, a missense mutation of V315I, or a splice mutation of X104_splice (G to T substitution at position 228004909 of chromosome);

The mutation of the above RTN3 gene is at least one missense mutation selected from the group consisting of E260D, S312N, and E622K in the amino acid sequence of SEQ ID NO: 11;

The mutation of the above TENM4 gene is at least one missense mutation selected from the group consisting of V2177L, L697F, and M2761T in the amino acid sequence of SEQ ID NO: 12, or a frame shift insertion mutation of K619Efs*4;

The mutation of the above TINAGL1 gene is a missense mutation of at least one of G45D and C226F in the amino acid sequence of SEQ ID NO: 13, or a frame shift deletion mutation of C309Vfs*2;

The mutation in the above ZFAND2B gene is a missense mutation of at least one of I149T and S159G in the amino acid sequence of SEQ ID NO: 14.

Next generation sequencing (NGS), RT-PCR, direct nucleic acid sequence analysis, and microarray can be used as analysis methods for diagnosing the prognosis of renal cancer using mutations in the above genes, and any method capable of confirming the presence of a mutation using the mutations in the genes of the present invention can be applied without limitation. In one embodiment, the presence of a mutation is determined using an anti-(mutation of each gene) antibody or nucleic acid probe that hybridizes to a polynucleotide of a mutation of each gene under stringent conditions. In another embodiment, the antibody or nucleic acid probe is detectably labeled. In another embodiment, the label is selected from the group consisting of an immunofluorescent label, a chemiluminescent label, a phosphorescent label, an enzymatic label, a radioactive label, avidin/biotin, colloidal gold particles, colored particles, and magnetic particles. In another embodiment, the presence of the mutation is determined by a radioimmunoassay, a western blot assay, an immunofluorescence assay, an enzyme-linked immunosorbent assay, an immunoprecipitation assay, a chemiluminescence assay, an immunohistochemical assay, a dot blot assay, a slot blot assay, or a flow cytometry assay. In another embodiment, the presence of the mutation is determined by RT-PCR. In another embodiment, the presence of the mutation is determined by nucleic acid sequencing.

The term 'polynucleotide' as used herein generally refers to any polyribonucleotide or polydeoxyribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA. Thus, for example, polynucleotides as defined herein include, but are not limited to, single- and double-stranded DNA, DNA comprising single- and double-stranded regions, single- and double-stranded RNA, and RNA comprising single- and double-stranded regions, hybrid molecules comprising DNA and RNA, which may be single-stranded or, more typically, double-stranded or may comprise single- and double-stranded regions. Thus, DNA or RNA having a backbone that has been modified for stability or other reasons is a 'polynucleotide' as the term is intended herein. Also included within the term 'polynucleotide' as defined herein are DNA or RNA comprising an unusual base such as inosine or a modified base such as a tritiated base. In general, the term 'polynucleotide' includes all chemically, enzymatically and/or metabolically modified forms of an unmodified polynucleotide. Polynucleotides can be prepared by a variety of methods, including in vitro recombinant DNA-mediated techniques, and by expression of DNA in cells and organisms.

Another aspect of the present invention provides a kit for diagnosing the prognosis of renal cancer, comprising a reagent capable of detecting a gender-dependent survival specific marker of a renal cancer patient, wherein the marker comprises at least one selected from the group consisting of a mutation in the ARHGEF5 gene, a mutation in the ASB15 gene, a mutation in the BAP1 gene, a mutation in the EPB41L5 gene, a mutation in the KIAA1614 gene, a mutation in the LOXL3 gene, a mutation in the LRCH1 gene, a mutation in the OR10AG1 gene, a mutation in the PDE4C gene, a mutation in the PRSS38 gene, a mutation in the RTN3 gene, a mutation in the TENM4 gene, a mutation in the TINAGL1 gene, and a mutation in the ZFAND2B gene.

Specifically, the sex-dependent survival-specific marker may be a mutation in at least one of the ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1 genes, or a mutation in at least one of the BAP1, OR10AG1, ZFAND2B genes. For example, if a mutation in at least one of the ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1 genes is detected as the sex-dependent survival-specific marker and the renal cancer patient is male, it can be determined that the individual has a lower survival rate and a higher recurrence rate than a person in whom the sex-dependent survival-specific marker is not identified. In addition, if a mutation in at least one of the BAP1, OR10AG1, and ZFAND2B genes is detected as the sex-dependent survival-specific marker and the renal cancer patient is a woman, it can be determined that the individual has a lower survival rate and a higher recurrence rate than a person in whom the sex-dependent survival-specific marker is not identified.

The reagent capable of detecting the above sex-dependent survival specific marker may include at least one selected from the group consisting of a primer, a probe, an antibody, and an aptamer, and since the specific details are as described above, a specific description is omitted.

The kit of the present invention may be a RT-PCR kit, a DNA chip kit, or a protein chip kit. As an example, the RT-PCR kit for measuring the mRNA expression level of the marker gene of the present invention may be a kit including essential elements required for performing RT-PCR. In addition to each primer pair specific for the marker gene, the RT-PCR kit may include a test tube or other appropriate container, a reaction buffer (having various pH and magnesium concentrations), deoxynucleotides (dNTPs), enzymes such as Taq polymerase and reverse transcriptase, DNase, RNAse inhibitor, DEPC-water, sterile water, and the like. In addition, it may include a primer pair specific for a gene used as a quantitative control.

As another example, the DNA chip kit of the present invention may include essential elements necessary for performing a DNA chip analysis method. The DNA chip kit may include a substrate to which a cDNA corresponding to a marker gene or a fragment thereof is attached as a probe, and reagents, agents, enzymes, etc. for producing a fluorescent label probe. In addition, the substrate may include a cDNA corresponding to a quantitative control gene or a fragment thereof.

As another example, the kit of the present invention is a protein chip kit for measuring the level of a protein expressed from the marker gene, and the kit may include, but is not particularly limited to, a substrate for immunological detection of an antibody, a suitable buffer solution, a secondary antibody labeled with a chromogenic enzyme or fluorescent substance, a chromogenic substrate, etc. The above description is not particularly limited thereto, but a nitrocellulose membrane, a 96-well plate synthesized with polyvinyl resin, a 96-well plate synthesized with polystyrene resin, and a glass slide glass can be used, and the chromogenic enzyme is not particularly limited thereto, but peroxidase and alkaline phosphatase can be used, and the fluorescent substance is not particularly limited thereto, but FITC, RITC, etc., and the chromogenic substrate solution is not particularly limited thereto, but ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) or OPD (o-phenylenediamine), TMB (tetramethyl benzidine).

Additionally, the kit of the present invention may additionally include a buffer, an indicator, or a combination thereof as a reagent.

The kit for prognosis and diagnosis of renal cancer of the present invention is very economical because it saves time and cost compared to the conventional general gene mutation search method. It takes several days to several months on average to test all genes using the conventional gene mutation search method such as SSCP (Single Strand Conformational Polymorphism), PTT (Protein Truncation Test), cloning, and direct sequencing. In addition, gene mutations can be tested quickly and precisely using next generation sequencing (NGS). If mutations are tested using the conventional analysis method such as SSCP, cloning, direct sequencing, and RFLP (Restriction Fragment Length Polymorphism), it takes about a month to complete the test, whereas using the kit of the present invention, if the sample DNA is prepared, the results can be obtained in about 10 to 11 hours, and since a set of primers capable of detecting mutations is integrated into one chip, not only time but also cost can be saved compared to the conventional method. Since the average reagent cost per experiment is less than half that of conventional methods, even greater cost savings can be expected when considering the researcher's labor costs.

2. How to provide information necessary for prognostic diagnosis of kidney cancer

Another aspect of the present invention provides a method for providing information necessary for prognostic diagnosis of a renal cancer patient, comprising the steps of: preparing a sample DNA from a sample of a renal cancer patient; and confirming the presence or absence of a gender-dependent survival-specific marker in the sample DNA using the composition or kit for prognostic diagnosis of renal cancer.

The method may further include a step of amplifying a sample DNA prepared from a sample of the renal cancer patient using the composition or kit for prognostic diagnosis of renal cancer.

The description of the above 'Composition and kit for diagnosing the prognosis of renal cancer' is the same as that described in ' 1. Composition and kit for diagnosing the prognosis of renal cancer ', so a detailed description is omitted.

The term 'patient' usually includes humans, but may also include other animals, such as other primates, rodents, dogs, cats, horses, sheep, pigs, etc.

The term 'sample' refers to a sample of an entity or tissue in which cancer or a tumor has already developed or is expected to develop, and the target sample for diagnosing the prognosis thereof. Specifically, it may refer to a tumor lysate or extract prepared from frozen tissue obtained from a patient with renal cancer.

The term 'subject' includes any subject diagnosed with or suspected of having renal cell carcinoma.

The above method can predict the overall survival rate or disease-free survival rate of patients with renal cancer.

The term 'overall survival (OS)' in the present invention includes a clinical endpoint that describes a patient who is alive for a limited period of time after being diagnosed with or treated for a disease, such as cancer, and means the possibility of surviving regardless of whether the cancer relapses.

In the present invention, the term 'disease-free survival (DFS)' includes the period of time that a patient survives without recurrence of cancer after treatment for a specific disease (e.g., cancer).

The present invention can predict what prognosis an individual having a target sample has for cancer by confirming the presence of a mutation in the gene of the present invention in a sample of a renal cancer patient. In addition, this method can be achieved by comparing the total survival rate or disease-free survival rate of an individual in a control group that does not have a mutation known to have a good prognosis. In the present invention, an individual known to have a good prognosis means an individual who has no history of metastasis, recurrence, death, etc. after the onset of cancer.

The above sex-dependent survival specific marker may include at least one selected from the group consisting of a mutation in the ARHGEF5 gene, a mutation in the ASB15 gene, a mutation in the BAP1 gene, a mutation in the EPB41L5 gene, a mutation in the KIAA1614 gene, a mutation in the LOXL3 gene, a mutation in the LRCH1 gene, a mutation in the OR10AG1 gene, a mutation in the PDE4C gene, a mutation in the PRSS38 gene, a mutation in the RTN3 gene, a mutation in the TENM4 gene, a mutation in the TINAGL1 gene, and a mutation in the ZFAND2B gene.

The method for providing information necessary for prognostic diagnosis of the above renal cancer patient can predict the overall survival rate or disease-free survival rate of the renal cancer patient. For example, the method can include a step of determining that, if the sex-dependent survival-specific marker is identified and the renal cancer patient is male, the survival rate is lower than that of a person for whom the sex-dependent survival-specific marker is not identified, or a step of determining that, if the sex-dependent survival-specific marker is identified and the renal cancer patient is female, the survival rate is lower than that of a person for whom the sex-dependent survival-specific marker is not identified.

Additionally, the method may include a step of determining that, if the gender-dependent survival-specific marker is identified and the renal cancer patient is male, the recurrence rate of renal cancer is higher than that of a person in whom the gender-dependent survival-specific marker is not identified, or, if the gender-dependent survival-specific marker is identified and the renal cancer patient is female, the recurrence rate of renal cancer is higher than that of a person in whom the gender-dependent survival-specific marker is not identified.

Specifically, the sex-dependent survival-specific marker may be a mutation in at least one of the ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1 genes, or a mutation in at least one of the BAP1, OR10AG1, ZFAND2B genes. For example, if a mutation in at least one of the ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1 genes is detected as the sex-dependent survival-specific marker and the renal cancer patient is male, it may be determined that the individual has a lower survival rate and a higher recurrence rate than a person in whom the sex-dependent survival-specific marker is not identified, and in this case, the sex-dependent survival-specific marker may be referred to as a male-dependent survival-specific marker. In addition, if a mutation in at least one of the BAP1, OR10AG1, and ZFAND2B genes is detected as the sex-dependent survival-specific marker and the renal cancer patient is a female, the individual may be judged to have a lower survival rate and a higher recurrence rate than a person in whom the sex-dependent survival-specific marker is not identified, and in this case, the sex-dependent survival-specific marker may be referred to as a female-dependent survival-specific marker.

Thus, it has not yet been revealed that the prognosis, such as the possibility of survival or recurrence, of renal cancer can be diagnosed according to the sex of a renal cancer patient by using a mutation in at least one gene selected from the group of genes consisting of ARHGEF5, ASB15, BAP1, EPB41L5, KIAA1614, LOXL3, LRCH1, OR10AG1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1, and ZFAND2B, which are mutations in the genes of the present invention. In addition, it has not been reported that the overall survival rate or disease-free survival rate may be different for each gene. The present inventors have first clarified that the mutations in the above genes can be used as diagnostic markers to predict the difference in treatment effect according to the sex of a renal cancer patient or to diagnose the prognosis of a renal cancer patient.

The method of the present invention for providing information necessary for predicting differences in the treatment effects of renal cancer patients can be used to diagnose genetic mutations of renal cancer, increase the survival rate of renal cancer patients, or reduce the recurrence rate. Through the method for diagnosing the prognosis of renal cancer patients of the present invention, it is possible to predict the treatment effects according to the gender of renal cancer patients, or to predict the survival rate or recurrence rate of renal cancer patients, using the mutation occurrence information of genes of renal cancer. Therefore, it is possible to provide information for not only discovering a treatment agent suitable for each patient, but also selecting a treatment agent, so that a therapeutic strategy for renal cancer can be efficiently designed.

Hereinafter, the present invention will be described in detail through examples and experimental examples.

However, the following examples and experimental examples are only intended to illustrate the present invention, and the content of the present invention is not limited by the following examples and experimental examples.

Example

Obtaining genetic and clinical information

In order to derive sex-dependent survival-specific markers that can diagnose the prognosis of patients with renal cell carcinoma after treatment, data on recurrence, metastasis, death, and observation time of 417 patients with clear cell renal cell carcinoma for whom both genetic and clinical information were secured were obtained from The Cancer Genome Atlas (TCGA) and used for analysis.

Number of patients ratio(%) gender male 271 65 female 146 35 Survival status O 270 65 X 147 35 total 417 100

years Number of patients (%) ≤50 88(21%) 51~60 119(29%) 61~70 107(25%) ≥71 103(25%)

ordnance Number of patients (%) Step I 197(47.2%) Step II 40(9.6%) Step III 112(26.9%) Step IV 68(16.3%)

gender count male female Number of patients ratio(%) relapse 0 148(54.6%) 81(55.5%) 229 55.2% 1 77(28.4%) 32(21.9%) 109 26.1% Not observed 46(17.0%) 33(22.6%) 79 18.7% transition 0 224(82.7%) 127(87.0%) 351 84.2% 1 47(17.3%) 19(13.0%) 66 15.8% dying 0 181(66.8%) 89(61.0%) 270 65.0% 1 90(33.2%) 57(39.0%) 147 35.0% Total number of patients 271 146 417

Selection of genes associated with sex

In the above data, 417 data for which gender could be confirmed were divided into two groups, male (M0)/female (M1), according to gender, and machine learning was performed using three feature selection methods (Information Gain, Chi-Square, MRMR) to derive the following 14 genes related to gender:

ARHGEF5, ASB15, BAP1, EPB41L5, KIAA1614, LOXL3, LRCH1, OR10AG1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1, ZFAND2B

Screening and review of sex-dependent survival-specific markers for prognosis prediction

To confirm the possibility of using these genes as sex-dependent survival-specific markers for prognosis prediction, a comparative analysis was performed on the data of the 417 target patients, and missing values and outliers were excluded.

Based on the clinical information of the above patients (whether an event (death or recurrence) and observation time), the overall survival or disease-free survival was calculated using the Kaplan Meier survival analysis using SPSS. In the overall survival, an event was defined as death, and in the disease-free survival, an event was defined as the recurrence of renal cancer. In order to confirm whether the occurrence of mutations in each of the above genes was correlated with death or recurrence of renal cancer, the association between the occurrence of mutations and overall survival and the association between the occurrence of mutations and disease-free survival were confirmed using the log-rank test based on the event time of each group obtained from the Kaplan Meier survival analysis. A p value less than 0.05 was considered statistically significant.

The experimental group consisted of cases with mutations in the genes of the present invention (cases with alterations in query genes), and the control group consisted of cases without mutations in the genes of the present invention (cases without alterations in query genes). The median months survival refers to the value at the center when the survival periods of the patients in the group are listed. The slope of the survival curve by Kaplan Meier survival analysis is determined by the survival period.

As a result of the above analysis, the results for the p value of overall survival or disease-free survival were confirmed, and the following 14 genes with a p value of less than 0.05 are considered to be genes highly related to survival rate or recurrence rate, and specifically, it is judged that when there is a mutation in the corresponding gene, the survival rate is low or the recurrence rate is high. Therefore, the following 14 genes are confirmed to be gender-dependent and survival-specific genes.

ARHGEF5, ASB15, BAP1, EPB41L5, KIAA1614, LOXL3, LRCH1, OR10AG1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1, ZFAND2B

Figures 1 to 28 represent graphs of the total survival rate and disease-free survival rate of kidney cancer patients with mutations in the respective genes (red) and kidney cancer patients without mutations in the respective genes (blue), for each of the 14 sex-dependent survival-specific genes, as well as the total survival rate and disease-free survival rate by each sex (female/male).

Looking specifically at the data in Figures 1 to 28, the data is as follows:

As can be seen in (B) of Fig. 1, in the case of kidney cancer patients who do not have a mutation in the ARHGEF5 gene, more than 50% did not have a recurrence for more than 100 months (blue), but in the case of patients with a mutation in the ARHGEF5 gene, more than 50% of the kidney cancer patients relapsed in less than 30 months (red). In addition, as can be seen in (B) of Fig. 2, in the case of male kidney cancer patients who do not have a mutation in the ARHGEF5 gene, more than 50% did not have a recurrence for more than 80 months (blue), but in the case of male patients with a mutation in the ARHGEF5 gene, more than 50% of the kidney cancer patients relapsed in less than 30 months (red). Therefore, since the probability of recurrence due to kidney cancer increases when there is a mutation in the ARHGEF5 gene and the kidney cancer patient is male, it can be seen that a mutation in the ARHGEF5 gene is significant as a survival rate or recurrence prediction marker for kidney cancer in male kidney cancer patients.

As can be seen in (A) of Fig. 3, in the case of kidney cancer patients without mutations in the ASB15 gene, more than 50% survived for more than 80 months (blue), whereas in the case of kidney cancer patients with mutations in the ASB15 gene, more than 50% of the kidney cancer patients died before 80 months, confirming a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 3, in the case of kidney cancer patients without mutations in the ASB15 gene, more than 50% did not have a recurrence for more than 100 months (blue), whereas in the case of kidney cancer patients with mutations in the ASB15 gene, more than 60% of the kidney cancer patients recurred before 80 months (red). In addition, as can be seen in (A) of Fig. 4, in the case of male kidney cancer patients without mutations in the ASB15 gene, more than 50% survived for more than 90 months (blue), whereas in the case of male kidney cancer patients with mutations in the ASB15 gene, more than 50% of the kidney cancer patients died before 80 months, confirming a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 4, in the case of male kidney cancer patients without mutations in the ASB15 gene, more than 50% did not have a recurrence for more than 80 months (blue), whereas in the case of male kidney cancer patients with mutations in the ASB15 gene, more than 50% of the kidney cancer patients recurred in less than 30 months (red). Therefore, since there is a mutation in the ASB15 gene and the probability of death or recurrence due to kidney cancer is higher when the kidney cancer patient is male, it can be seen that the mutation in the ASB15 gene is significant as a survival rate or recurrence prediction marker for male kidney cancer patients.

As can be seen in Fig. 5 (A), in the case of kidney cancer patients without mutations in the BAP1 gene, more than 50% survived for more than 80 months (blue), whereas in the case of kidney cancer patients with mutations in the BAP1 gene, more than 50% survived for up to 150 months (red). According to Fig. 5 (B), in the case of kidney cancer patients without mutations in the BAP1 gene, more than 50% did not have a recurrence for more than 100 months (blue), whereas in the case of kidney cancer patients with mutations in the BAP1 gene, more than 50% did not have a recurrence for up to 130 months (red). In addition, as can be seen in (C) of Fig. 6, in the case of female kidney cancer patients who did not have a mutation in the BAP1 gene, more than 50% survived for more than 90 months (blue), whereas in the case of female kidney cancer patients who had a mutation in the BAP1 gene, more than 50% of the kidney cancer patients died before 60 months, indicating a lower survival rate than the kidney cancer patients who did not have a mutation (red). According to (D) of Fig. 6, in the case of female kidney cancer patients who did not have a mutation in the BAP1 gene, more than 50% of the kidney cancer patients did not have a recurrence for more than 130 months (blue), whereas in the case of female kidney cancer patients who had a mutation in the BAP1 gene, more than 50% of the kidney cancer patients recurred in less than 60 months (red). Therefore, since the probability of death or recurrence due to kidney cancer is higher in cases where there is a mutation in the BAP1 gene and the kidney cancer patient is female, it can be seen that the mutation in the BAP1 gene is significant as a survival rate or recurrence prediction marker of kidney cancer in female kidney cancer patients.

As can be seen in (B) of Fig. 7, in the case of kidney cancer patients without mutations in the EPB41L5 gene, more than 50% did not have a recurrence for more than 100 months (blue), but in the case of mutations in the EPB41L5 gene, 100% of the kidney cancer patients relapsed in less than 10 months (red). In addition, as can be seen in (B) of Fig. 8, in the case of male kidney cancer patients without mutations in the EPB41L5 gene, more than 50% did not have a recurrence for more than 80 months (blue), but in the case of male patients with mutations in the EPB41L5 gene, 100% of the kidney cancer patients relapsed in less than 10 months (red). Therefore, since there is a mutation in the EPB41L5 gene and the probability of recurrence of kidney cancer increases when the kidney cancer patient is male, it can be seen that the mutation in the EPB41L5 gene is significant as a survival rate or recurrence prediction marker for kidney cancer patients who are male.

As can be seen in (A) of Fig. 9, in the case of kidney cancer patients without mutations in the KIAA1614 gene, more than 50% survived for more than 80 months (blue), whereas in the case of kidney cancer patients with mutations in the KIAA1614 gene, more than 50% of the kidney cancer patients died before 50 months, indicating a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 9, in the case of kidney cancer patients without mutations in the KIAA1614 gene, more than 50% did not experience a recurrence for more than 100 months (blue), whereas in the case of patients with mutations in the KIAA1614 gene, more than 50% of the kidney cancer patients relapsed in less than 40 months (red). In addition, as can be seen in (A) of Fig. 10, in the case of male kidney cancer patients without mutations in the KIAA1614 gene, more than 50% survived for more than 80 months (blue), whereas in the case of male kidney cancer patients with mutations in the KIAA1614 gene, more than 50% of the kidney cancer patients died before 50 months, indicating a lower survival rate than in kidney cancer patients without mutations (red). According to (B) of Fig. 10, in the case of male kidney cancer patients without mutations in the KIAA1614 gene, more than 50% did not experience a recurrence for more than 80 months (blue), whereas in the case of male kidney cancer patients with mutations in the KIAA1614 gene, more than 50% of the kidney cancer patients relapsed in less than 40 months (red). Therefore, since there is a mutation in the KIAA1614 gene and the probability of death or recurrence due to kidney cancer is higher when the kidney cancer patient is male, it can be seen that the mutation in the KIAA1614 gene is significant as a survival rate or recurrence prediction marker for male kidney cancer patients.

As can be seen in (A) of Fig. 11, in the case of kidney cancer patients without mutations in the LOXL3 gene, more than 50% survived for more than 80 months (blue), whereas 100% of kidney cancer patients with mutations in the LOXL3 gene died before 20 months, confirming a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 11, in the case of kidney cancer patients without mutations in the LOXL3 gene, more than 50% did not have a recurrence for more than 100 months (blue), whereas in the case of kidney cancer patients with mutations in the LOXL3 gene, 100% of the kidney cancer patients relapsed in less than 10 months (red). In addition, as can be seen in (A) of Fig. 12, in the case of male kidney cancer patients who did not have a mutation in the LOXL3 gene, more than 50% survived for more than 80 months (blue), whereas 100% of male kidney cancer patients who had a mutation in the LOXL3 gene died before 20 months, confirming a lower survival rate than kidney cancer patients who did not have a mutation (red). According to (B) of Fig. 12, in the case of male kidney cancer patients who did not have a mutation in the LOXL3 gene, more than 50% did not have a recurrence for more than 70 months (blue), whereas in the case of male kidney cancer patients who had a mutation in the LOXL3 gene, 100% of the kidney cancer patients recurred in less than 10 months (red). Therefore, since the probability of death or recurrence due to kidney cancer is higher in cases where there is a mutation in the LOXL3 gene and the kidney cancer patient is male, it can be seen that a mutation in the LOXL3 gene is significant as a survival rate or a predictive marker for kidney cancer recurrence in male kidney cancer patients.

As can be seen in (B) of Fig. 13, in the case of renal cancer patients who do not have a mutation in the LRCH1 gene, more than 50% did not have a recurrence for more than 100 months (blue), but in the case of patients with a mutation in the LRCH1 gene, more than 50% of the renal cancer patients relapsed in less than 20 months (red). In addition, as can be seen in (B) of Fig. 14, in the case of male renal cancer patients who do not have a mutation in the LRCH1 gene, more than 50% did not have a recurrence for more than 80 months (blue), but in the case of male patients with a mutation in the LRCH1 gene, more than 50% of the renal cancer patients relapsed in less than 20 months (red). Therefore, since the probability of recurrence due to renal cancer increases when there is a mutation in the LRCH1 gene and the renal cancer patient is male, it can be seen that a mutation in the LRCH1 gene is significant as a survival rate or recurrence prediction marker for male renal cancer patients.

As can be seen in (A) of Fig. 15, in the case of kidney cancer patients without mutations in the OR10AG1 gene, more than 50% survived for more than 80 months (blue), whereas in the case of kidney cancer patients with mutations in the OR10AG1 gene, more than 50% of the kidney cancer patients died before 40 months, indicating a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 15, in the case of kidney cancer patients without mutations in the OR10AG1 gene, more than 50% did not experience a recurrence for more than 100 months (blue), whereas in the case of patients with mutations in the OR10AG1 gene, more than 50% of the kidney cancer patients relapsed in less than 20 months (red). In addition, as can be seen in (A) of Fig. 16, in the case of female kidney cancer patients without mutations in the OR10AG1 gene, more than 50% survived for more than 80 months (blue), whereas in the case of female kidney cancer patients with mutations in the OR10AG1 gene, more than 50% of the kidney cancer patients died before 40 months, indicating a lower survival rate than in kidney cancer patients without mutations (red). According to (B) of Fig. 16, in the case of female kidney cancer patients without mutations in the OR10AG1 gene, more than 50% did not experience a recurrence for up to 130 months (blue), whereas in the case of female kidney cancer patients with mutations in the OR10AG1 gene, more than 50% of the kidney cancer patients relapsed in less than 20 months (red). Therefore, since the OR10AG1 gene has a mutation and the probability of death or recurrence due to kidney cancer is higher when the patient is a female, it can be seen that the mutation in the OR10AG1 gene is significant as a survival rate or recurrence prediction marker for female kidney cancer patients.

As can be seen in (A) of Fig. 17, in the case of kidney cancer patients without mutations in the PDE4C gene, more than 50% survived for more than 80 months (blue), whereas in the case of kidney cancer patients with mutations in the PDE4C gene, more than 50% of the kidney cancer patients died before 60 months, indicating a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 17, in the case of kidney cancer patients without mutations in the PDE4C gene, more than 50% did not have a recurrence for more than 100 months (blue), whereas in the case of patients with mutations in the PDE4C gene, more than 50% of the kidney cancer patients relapsed in less than 20 months (red). In addition, as can be seen in (A) of Fig. 18, in the case of male kidney cancer patients without mutations in the PDE4C gene, more than 50% survived for more than 80 months (blue), whereas in the case of male kidney cancer patients with mutations in the PDE4C gene, more than 50% of the kidney cancer patients died before 50 months, confirming a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 18, in the case of male kidney cancer patients without mutations in the PDE4C gene, more than 50% did not have a recurrence for more than 80 months (blue), whereas in the case of male kidney cancer patients with mutations in the PDE4C gene, more than 50% of the kidney cancer patients recurred in less than 20 months (red). Therefore, since there is a mutation in the PDE4C gene and the probability of death or recurrence due to kidney cancer is higher when the kidney cancer patient is male, it can be seen that the mutation in the PDE4C gene is significant as a survival rate or kidney cancer recurrence prediction marker for male kidney cancer patients.

As can be seen in (B) of Fig. 19, in the case of kidney cancer patients who do not have a mutation in the PRSS38 gene, more than 50% did not have a recurrence for more than 100 months (blue), but in the case of patients with a mutation in the PRSS38 gene, more than 50% of the kidney cancer patients relapsed in less than 60 months (red). In addition, as can be seen in (B) of Fig. 20, in the case of male kidney cancer patients who do not have a mutation in the PRSS38 gene, more than 50% did not have a recurrence for more than 80 months (blue), but in the case of male patients with a mutation in the PRSS38 gene, more than 50% of the kidney cancer patients relapsed in less than 30 months (red). Therefore, since the probability of recurrence due to kidney cancer increases when there is a mutation in the PRSS38 gene and the kidney cancer patient is male, it can be seen that a mutation in the PRSS38 gene is significant as a survival rate or recurrence prediction marker for kidney cancer in male kidney cancer patients.

As can be seen in (A) of Fig. 22, in the case of male kidney cancer patients who did not have a mutation in the RTN3 gene, more than 50% survived for more than 80 months (blue), whereas in the case of male kidney cancer patients who had a mutation in the RTN3 gene, more than 50% of the kidney cancer patients died before 50 months, indicating a lower survival rate than kidney cancer patients who did not have a mutation (red). According to (B) of Fig. 22, in the case of male kidney cancer patients who did not have a mutation in the RTN3 gene, more than 50% of the kidney cancer patients did not have a recurrence for more than 80 months (blue), whereas in the case of male kidney cancer patients who had a mutation in the RTN3 gene, more than 50% of the kidney cancer patients recurred in less than 10 months (red). Therefore, since the probability of death or recurrence due to kidney cancer is higher in cases where there is a mutation in the RTN3 gene and the kidney cancer patient is male, it can be seen that a mutation in the RTN3 gene is significant as a survival rate or kidney cancer recurrence prediction marker in male kidney cancer patients.

As can be seen in (A) of Fig. 23, in the case of kidney cancer patients without mutations in the TENM4 gene, more than 50% survived for more than 80 months (blue), whereas in the case of kidney cancer patients with mutations in the TENM4 gene, more than 50% of the kidney cancer patients died before 20 months, indicating a lower survival rate than kidney cancer patients without mutations (red). According to (B) of Fig. 23, in the case of kidney cancer patients without mutations in the TENM4 gene, more than 50% did not have a recurrence for more than 100 months (blue), whereas in the case of patients with mutations in the TENM4 gene, more than 50% of the kidney cancer patients relapsed in less than 10 months (red). In addition, as can be seen in (A) of Fig. 24, in the case of male kidney cancer patients who did not have a mutation in the TENM4 gene, more than 50% survived for more than 80 months (blue), whereas in the case of male kidney cancer patients who had a mutation in the TENM4 gene, more than 50% of the kidney cancer patients died before 20 months, indicating a lower survival rate than kidney cancer patients who did not have a mutation (red). According to (B) of Fig. 24, in the case of male kidney cancer patients who did not have a mutation in the TENM4 gene, more than 50% did not have a recurrence for more than 80 months (blue), whereas in the case of male kidney cancer patients who had a mutation in the TENM4 gene, more than 50% of the kidney cancer patients recurred in less than 10 months (red). Therefore, since there is a mutation in the TENM4 gene and the patient with kidney cancer is male, the probability of death or recurrence due to kidney cancer is higher, and it can be seen that the mutation in the TENM4 gene is significant as a survival rate or recurrence prediction marker for male kidney cancer patients.

As can be seen in (B) of Fig. 25, in the case of kidney cancer patients who do not have a mutation in the TINAGL1 gene, more than 50% did not have a recurrence for more than 100 months (blue), but in the case of patients with a mutation in the TINAGL1 gene, more than 50% of the kidney cancer patients relapsed in less than 60 months (red). In addition, as can be seen in (B) of Fig. 26, in the case of male kidney cancer patients who do not have a mutation in the TINAGL1 gene, more than 50% did not have a recurrence for more than 80 months (blue), but in the case of male patients with a mutation in the TINAGL1 gene, more than 50% of the kidney cancer patients relapsed in less than 60 months (red). Therefore, since the probability of recurrence due to kidney cancer increases when there is a mutation in the TINAGL1 gene and the kidney cancer patient is male, it can be seen that a mutation in the TINAGL1 gene is significant as a survival rate or recurrence prediction marker for kidney cancer in male kidney cancer patients.

As can be seen in (D) of FIG. 28, in the case of female renal cancer patients who did not have a mutation in the ZFAND2B gene, more than 50% did not have a recurrence for up to 130 months (blue), but in the case of female patients who had a mutation in the ZFAND2B gene, more than 50% of the renal cancer patients recurred in less than 30 months (red). Therefore, since the probability of recurrence due to renal cancer increases when there is a mutation in the ZFAND2B gene and the renal cancer patient is female, it can be seen that a mutation in the ZFAND2B gene is significant as a survival rate or recurrence prediction marker for female renal cancer patients.

The p values obtained by performing the Kaplan Meier analysis in Figures 1 to 28 above are organized into a table and shown in Figure 29A.

The results of checking the total survival period or disease-free survival period by gender (female/male) of renal cancer patients with mutations in the 11 genes identified as male-dependent survival-specific genes above, namely ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, and TINAGL1 (red) and renal cancer patients without mutations in the corresponding genes (blue) are shown in Fig. 30. From this, the probability that the null hypothesis that the occurrence of mutations in the above 11 genes is related to the survival rate or recurrence rate of male renal cancer patients is correct is 99.5% or higher, i.e., the probability that the null hypothesis is false is less than 0.5%, so it can be seen that the occurrence of mutations in the above 11 genes is related to the survival rate or recurrence rate of male renal cancer patients.

The results of checking the total survival period or disease-free survival period by gender (female/male) of renal cancer patients with mutations in the three genes identified as female-dependent survival-specific genes, namely BAP1, OR10AG1, and ZFAND2B (red) and renal cancer patients without mutations in the corresponding genes (blue) are shown in Figure 31. The probability that the null hypothesis that the occurrence of mutations in the three genes is associated with the survival rate or recurrence rate of female renal cancer patients is correct is 99.5% or higher, i.e., the probability that the null hypothesis is false is less than 0.5%. Therefore, it can be seen that there is a correlation between the occurrence of mutations in the three genes and the survival rate or recurrence rate of female renal cancer patients.

Validation using real kidney cancer patient data

To verify whether the 14 genetic mutations identified as sex-dependent survival-specific genetic markers in Example 2 above are applicable as prognostic diagnostic biomarkers for actual renal cancer patients, the corresponding genetic mutations were analyzed using the Next Generation Sequencing (NGS) analysis method for 120 Korean renal cancer patients for whom survival data were available.

(1) Experimental method

Patient group

A genetic validation was performed on a cohort of 120 patients diagnosed with clear cell renal cell carcinoma (ccRCC) at Seoul St. Mary's Hospital. The gene pool was comprised of 14 ccRCC-survival specific genes extracted through machine learning, excluding synonymous and benign variants. Machine learning techniques included feature selection techniques such as Information Gain, Chi-squared test, and Minimum Redundancy Maximum Relevance (MRMR), and classification machine learning models such as Naive Bayes, K-Nearest Neighbor (K-NN), and Support Vector Machine (SVM). Specifically, all renal cell carcinoma patients were diagnosed with renal cell carcinoma after radical nephrectomy, and a pathologist performed a pathological analysis on each tumor, and the analysis was conducted on patients diagnosed with renal cell carcinoma (ccRCC).

Manufacturing of target libraries

Genomic DNA was extracted from paraffin-embedded slides obtained from patients and fragmented to approximately 250 bp using a Bioruptor Pico Sonication System (Diagenode, Belgium). Pre-PCR was performed on end-repair, dA-tailing, adapter ligation, and indexed next generation sequencing (NGS) library for Illumina sequencing. The gDNA library and capture probes prepared using the Celemics target enrichment kit (Celemics, Seoul, Republic of Korea) were hybridized to capture the target region. Customized capture probes were designed and chemically synthesized to hybridize to the target region. The captured region was amplified by a post-PCR method to enrich the sample quantity. Subsequently, the target-captured library was sequenced on an Illumina NextSeq550 instrument (Illumina, San Diego, CA, USA) with a read layout of 2 x 150 bp.

Bioinformatics analysis

Samples were sequenced on an Illumina Nextseq 550 platform and BCL2FASTQ version 2.19.1.403 (Illumina) was used to demultiplex the base-call image files into individual sequence read files (FASTQ format). All options and parameters were set to default, and sequencing adapters were removed using AdapterRemoval version 2. 2. 2. All sequencing reads were aligned to the GRCh37 human genome using BWA-MEM (Burrows-Wheeler Aligner) software. All programs used the Burrows-Wheeler Transform algorithm to index the human genome sequence to calculate the constant complexity of each sequencing read. Post-align and recalibration processes were performed using Picard version 1.115 (http://broadinstitute.github.io/picard) and GATK version 4.0.4.0.

(2) Analysis results

Survival-specific genetic mutations

Among the data of the above 120 renal cell carcinoma patients, the overall survival or disease-free survival was calculated for the 14 sex-dependent survival-specific genes using Kaplan Meier survival analysis using SPSS. In the overall survival, an event was defined as death, and in the disease-free survival, an event was defined as the recurrence of renal cell carcinoma. In order to confirm whether the occurrence of mutations in each of the above genes was correlated with death or recurrence of renal cell carcinoma, the association between the occurrence of mutations and overall survival and the association between the occurrence of mutations and disease-free survival were confirmed by the log-rank test based on the event times of each group obtained from the Kaplan Meier survival analysis. A p value less than 0.05 was considered statistically significant.

As a result of the above analysis, the total survival rate and disease-free survival rate verified for each of the 14 sex-dependent survival-specific genes, and the p-values resulting from the total survival rate and disease-free survival rate according to each sex (female/male) are summarized and shown in Figure 29B.

Comparing this result with the result of Example 2 shown in Fig. 29A, it can be confirmed that the same gender dependency and survival specificity results were shown when verified using actual renal cell carcinoma patient data in Example 3, similar to the gender dependency (whether male-specific or female-specific) and survival specificity results confirmed in Example 2 for the above 14 genes.

Through the above results, it can be seen that when there is a mutation in any one gene selected from the group consisting of ARHGEF5, ASB15, BAP1, EPB41L5, KIAA1614, LOXL3, LRCH1, OR10AG1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1, and ZFAND2B, the survival rate of patients with renal cell carcinoma of a specific gender is significantly lowered or the recurrence rate is increased. Therefore, it can be seen that the presence or absence of a mutation in the genes of the present invention can be used to predict the prognosis of renal cell carcinoma, particularly survival or recurrence, by contrasting the patient's gender.

Mutation location information

The mutated positions of the 14 sex-dependent survival-specific genes are shown below.

Gene Accession no. AA change Type Copy # COSMIC Mutation Assessor
Prediction Score Chromosome Start Pos End Pos Reference Variant ARHGEF5 NM_005435.3 E487G Missense Diploid 7 7 144061222 144061222 A G E487G Missense Gain 7 7 144061222 144061222 A G V1574F Missense Diploid 1 7 144077075 144077075 G T ASB15 NM_001290258.1 E105* Nonsense Diploid 1 　 7 123257653 123257653 G T V246L Missense AMP 　 Neutral 7 123267202 123267202 G T BAP1 NM_004656.3 M1? Nonstart ShallowDel 6 　 3 52443894 52443894 T C G128* Nonsense ShallowDel 2 　 3 52441470 52441470 C A E402* Nonsense ShallowDel 　 　 3 52438515 52438515 C A E283Gfs*52 FS del ShallowDel 1 　 3 52439864 52439864 T - V335Efs*56 FS del ShallowDel 1 　 3 52439219 52439238 GCTGCCTG
GAGGCTTCACCA - Q253* Nonsense ShallowDel 2 　 3 52440295 52440295 G A Q267* Nonsense ShallowDel 1 　 3 52439913 52439913 G A S460* Nonsense ShallowDel 3 　 3 52437782 52437782 G C F170V Missense ShallowDel 4 High 3 52441262 52441262 A C K711Sfs*25 FS del ShallowDel 1 　 3 52436362 52436362 T - Y627* Nonsense ShallowDel 1 　 3 52437163 52437163 G C R717Gfs*19 FS del ShallowDel 1 　 3 52436345 52436345 G - X23_splice Splice ShallowDel 　 　 3 52443729 52443729 C T S279* Nonsense ShallowDel 1 　 3 52439876 52439876 G T R60* Nonsense DeepDel 4 　 3 52442567 52442567 G A M1? Nonstart ShallowDel 6 　 3 52443892 52443892 C T M1? Nonstart ShallowDel 6 　 3 52443892 52443892 C T R700Gfs*36 FS del ShallowDel 1 　 3 52436397 52436397 C - X41_splice Splice ShallowDel 　 　 3 52443568 52443568 A G Q40* Nonsense ShallowDel 2 　 3 52443574 52443574 G A Q156* Nonsense ShallowDel 1 　 3 52441304 52441304 G A K626* Nonsense ShallowDel 1 　 3 52437168 52437168 T A D74Efs*4 FS del ShallowDel 1 　 3 52442523 52442523 A - X41_splice Splice ShallowDel 　 　 3 52443568 52443568 A T D407Vfs*23 FS del ShallowDel 2 　 3 52438499 52438499 T - F170C Missense ShallowDel 4 High 3 52441261 52441261 A C X23_splice Splice ShallowDel 　 　 3 52443623 52443647 ACCTGCG
ATGAGGAAAGGAAAGCAG - X311_splice Splice ShallowDel 　 　 3 52439311 52439311 C A E31A Missense ShallowDel 5 High 3 52443600 52443600 T G N78S Missense ShallowDel 2 Neutral 3 52442512 52442512 T C N78S Missense ShallowDel 2 Neutral 3 52442512 52442512 T C L49V Missense ShallowDel 2 High 3 52442600 52442600 G C D75G Missense ShallowDel 1 Neutral 3 52442521 52442521 T C S10T Missense ShallowDel 4 High 3 52443866 52443866 C G N229H Missense ShallowDel 1 Medium 3 52440367 52440367 T G G109V Missense ShallowDel 1 High 3 52442023 52442023 C A L17P Missense ShallowDel 1 Medium 3 52443747 52443747 A G A145G Missense ShallowDel 1 Medium 3 52441418 52441418 G C K659del IF del DeepDel 　 　 3 52436801 52436803 CTT - A1061T Missense Diploid 2 Medium 23 79948521 79948521 C T EPB41L5 NM_001184937.1 L303_P306del IF del Gain 　 　 2 120847955 120847966 ACTGGATCATCC - KIAA1614 NM_020950.1 E592A Missense Diploid 1 1 180904820 180904820 A C G1014S Missense Diploid 1 1 180910302 180910302 G A P1037S Missense Diploid 1 1 180910371 180910371 C T LOXL3 NM_032603.4 C376Y Missense Diploid 1 High 2 74763244 74763244 C T H398Q Missense Diploid 1 Medium 2 74763177 74763177 A C LRCH1 NM_001164211.1 L468S Missense Gain 1 Medium 13 47279205 47279205 T C H653Y Missense Diploid 　 Medium 13 47303069 47303069 C T OR10AG1 NM_001005491.1 L156F Missense Diploid 2 Neutral 11 55735474 55735474 G A L204F Missense Diploid 2 Low 11 55735328 55735328 C A PDE4C NM_000923.5 S254F Missense Diploid 2 Medium 19 18331077 18331077 G A D429N Missense Diploid 1 High 19 18329004 18329004 C T T561M Missense Gain 3 Low 19 18322678 18322678 G A L488Q Missense Diploid 2 Medium 19 18327573 18327573 A T N437K Missense Diploid 1 High 19 18328978 18328978 G T Y557Lfs*21 FS ins Gain 　 　 19 18322690 18322691 - A PRSS38 NM_183062.2 S314Qfs*21 FS ins Diploid 1 228033865 228033866 - T V315I Missense Diploid 1 1 228033871 228033871 G A X104_splice Splice Diploid 1 228004909 228004909 G T RTN3 NM_001265589.1 E260D Missense Diploid 　 Low 11 63486754 63486754 A C S312N Missense Diploid 　 Neutral 11 63486909 63486909 G A E622K Missense Diploid 　 Low 11 63487838 63487838 G A TENM4 NM_001098816.2 V2177L Missense Diploid 　 Low 11 78380861 78380861 C G K619Efs*4 FS ins Diploid 　 　 11 78523290 78523291 - C L697F Missense Diploid 　 Neutral 11 78516425 78516425 T G M2761T Missense Diploid 　 Low 11 78369131 78369131 A G TINAGL1 NM_001204414.1 G45D Missense Diploid 1 1 32042883 32042883 G A C226F Missense ShallowDel 1 1 32050373 32050373 G T C309Vfs*2 FS del ShallowDel 　 　 1 32050813 32050813 C - ZFAND2B NM_001270998.1 I149T Missense Diploid 2 2 220072989 220072989 T C S159G Missense Diploid 1 2 220073018 220073018 A G

Fabrication of a chip capable of detecting mutations in genes of examples 2 and 3

Primer sets for mutation detection of genes of Examples 2 and 3 were produced using Thermo fisher's Ion AmpliSeq™ Custom and Community Panels with reference to https://tools.thermofisher.com/content/sfs/manuals/MAN0006735_AmpliSeq_DNA_RNA_LibPrep_UG.pdf. In order to easily detect mutations, the chip type was selected and the Depth was increased. Specifically, the panel information to be produced was input into Ampliseq.com, and after receiving feedback on the input information, related matters were discussed to produce a panel equipped with a primer set capable of detecting mutations. Table 6 shows primer sets capable of detecting mutations of the genes of the present invention.

Lineitem_Name Chr Sequence number Ion_AmpliSeq_Fwd_Primer* Sequence number Ion_AmpliSeq_Rev_Primer* Amplicon_Start Insert_Start Insert_Stop Amplicon_Stop ARHGEF5 chr7 15 AGGAACTGTCCCCCGCAGCTCTGT 16 ATGACCCATCTCCCTGTGGGA 144061198 144061218 144061545 144061561 ARHGEF5 chr7 17 ACCTGTTCCGACTCTTTCTGC 18 TCTCAGACGGGGAGCGAGGCT 144071048 144071065 144071296 144071318 ASB15 chr7 19 CAACTTTTCAACATAATGCTTTCATGTCAC 20 GCCACACTCCCTTTTCTAATAAAGTTCTTA 123257601 123257631 123257719 123257749 ASB15 chr7 21 GGGATTGTTTAAACAATACCATCCAGTT 22 GGTACATTTCCGCTTCCTCCAT 123267108 123267136 123267259 123267281 BAP1 chr3 23 GTAGGAGAGAAGAAGACTGAGAGCACT 24 GTGGAGGCTGAGATTGCAAACTA 52436693 52436720 52436840 52436863 BAP1 chr3 25 TTCCAATCAAGAACTTGGCACCT 26 GTCGTGGAAGCCACGGACA 52437065 52437088 52437218 52437237 BAP1 chr3 27 GCCGTGTCTGTACTCTCATTGC 28 CCATCAACGTCTTGGCTGAGAA 52437674 52437696 52437808 52437830 BAP1 chr3 29 AACCTGGTAGCCTTAGAAAGCTG 30 TTGTCCCAGGAGGAAGAAGACCT 52438439 52438462 52438588 52438611 BAP1 chr3 31 GGGACTTGGCATAATTGTGATTGT 32 ATCCCACAGCCCTCCCAACAAA 52439134 52439158 52439248 52439270 BAP1 chr3 33 GCTTCACCACTAGCTTGGGTTT 34 GGGAGACTGTGAGCTTTTCTTGG 52439230 52439252 52439353 52439376 BAP1 chr3 35 GGACTTGTTGCTGGCTGACTT 36 GGGTCTACCCTTTCTCCTCTGA 52439836 52439857 52439948 52439970 BAP1 chr3 37 GTATGTTCACGAATCAGAGACAAATGC 38 CGACCGCAGGATCAAGTATGAG 52440173 52440200 52440325 52440347 BAP1 chr3 39 CAGCCTGGCCTCATACTTGATC 40 CAGGATATCTGCCTCAACCTGATG 52440317 52440339 52440440 52440464 BAP1 chr3 41 CATGGTGCCTACCATGGTCAAT 42 CCTGAGAAGCAGAATGGCCTTA 52441178 52441200 52441291 52441313 BAP1 chr3 43 CGCACTGCACTAAGGCCATT 44 GCCAAGGCCCATAATAGCCATG 52441282 52441302 52441418 52441440 BAP1 chr3 45 CACACACCTGGCATGGCTATTA 46 CCCATAGTCCTACCTGAGGAGAAA 52441408 52441430 52441510 52441534 BAP1 chr3 47 CTGAAACCCTTGGTGAAGTCCT 48 TTGGTTTCACAGCTGATACCCAA 52441981 52442003 52442082 52442105 BAP1 chr3 49 ATCCCACCCTCCAAACAAAGCA 50 CCCAGCCCTGTATATGGATTTATCTT 52442453 52442475 52442601 52442627 BAP1 chr3 51 GCTGCTGCTTTCTGTGAGATTTT 52 GGGTGCAAGTGGAGGAGATCTA 52443443 52443466 52443593 52443615 BAP1 chr3 53 CCCTGACATTTGCTCTGAAGGT 54 TCGGTAAGAGCCTTTTCTCCCT 52443570 52443592 52443710 52443732 BAP1 chr3 55 TCTTACCGAAATCTTCCACGAGC 56 AAGATGAATAAGGGCTGGCTGG 52443724 52443747 52443875 52443897 BAP1 chrX 57 CTTACTGAACACTGTAACACTGGAAAGA 58 GTGGGAACAGAGCTAATATTCTCAAGAG 79948434 79948462 79948580 79948608 EPB41L5 chr2 59 ATCTCAGAAATAGGAGATAGGACTGTTTGA 60 CTCGAAGGCGGAAGAAAGCATG 120847854 120847884 120848006 120848028 KIAA1614 chr1 61 GGGCACACGAGCGATTCCTCC 62 GCAGAGCCCCGGCTCCACATG
180904664 180904687 180905124 180905144 KIAA1614 chr1 63 CATGCAGAGCCTTCTGCCCCA 64 CCCTCGGCTGCCCCTTTGGAC 180909960 180909986 180910546 180910560 LOXL3 chr2 65 GGGCCATTGGACTGTAGATTGG 66 CCCACAAGAACATCACAGCTGA 74763044 74763066 74763189 74763211 LOXL3 chr2 67 GTCCAGAGCAGCGAACTTCACT 68 CATATTCCTTCGGAAGGTTAGGTGT 74763236 74763258 74763337 74763362 LOXL3 chr2 69 GGCATCCTGGCTATGTGAACAA 70 TTAATTACAACTTCCTGATCTTTTGCCATCT 74763165 74763187 74763285 74763315 LRCH1 chr13 71 GCATTGAGATGAGATTGAAGGTCAGT 72 TGTTTTATGTCAGTTAGTTTCCCTTTGGT 47302983 47303009 47303128 47303157 OR10AG1 Chr11 73 GGTGGAGAAGGCTTTAGCCTTTC 74 CTCAAGCTTGCTTGTGGAAACATATTT 55735247 55735270 55735387 55735414 OR10AG1 Chr11 75 AAATATGTTTCCACAAGCAAGCTTGAG 76 GATGAACCACAAAGTCTGCATTCAG 55735388 55735415 55735537 55735562 PDE4C chr19 77 TGTCACACATGGGACTGATGTC 78 CCAAGCCTCGATCTCTGTAGGT 18322598 18322620 18322749 18322771 PDE4C chr19 79 TGGCCTCACCATGTCAATGAC 80 CTGGCGCTTATGTACAACGAC 18327542 18327563 18327676 18327697 PDE4C chr19 81 ACCCACTTCCCACTCCTACTTA 82 TCAGGCTGTGTTCACAGACTTG 18328936 18328958 18329040 18329062 PDE4C chr19 83 GGCAGTGACTCAACAAAGCTCA 84 TCATCACGGTCTTCACCTTCTCT 18331013 18331035 18331138 18331161 PRSS38 chr1 85 CAGGAAGAAACTGGCTTTTCAATCC 86 TGAGGTTTACGAGGCCTACGTA 228004785 228004810 228004937 228004959 PRSS38 chr1 87 GCCAGTGTTTCCTATTTCTCAAAATGG 88 GAGAATCCTAGAGTGGGTATCCTGA 228033763 228033790 228033911 228033936 RTN3 chr11 89 ATCCAAAGTTTCAGGAGATGATGTTATTGA 90 TGAAATGTCTTCGGATGATTCTTTATCAGT 63486664 63486694 63486808 63486838 RTN3 chr11 91 GACATTTCAGAGACTAATGACAAGCTTTTT 92 GATCCCAAGTCAGTATTTCGTTAGTAAAGT 63486830 63486860 63486974 63487004 RTN3 chr11 93 GATACGAATGTCTCCTTAGAAGATGTGA 94 GTTTAACATTTTTCCCATGTAATGACTCCA 63487733 63487761 63487877 63487907 TENM4 chr11 95 GGCCACAAAAGAGTAGCTGTCT 96 CTACGACGGCTTTTTCGTGATC 78369054 78369076 78369183 78369205 TENM4 chr11 97 GGCCGTCAGCATCATACTCATA 98 GAAGGAAGTGCAGTATGAGATCTTCC 78380789 78380811 78380911 78380937 TENM4 chr11 99 GCATTTACCGATAGAACAGTCGTGT 100 GTCTGCGTGAGAGGCGAAT 78516329 78516354 78516483 78516502 TENM4 chr11 101 CCACATCGATACACTGGTTGGT 102 TGGACATTGATTCATGCCAGACT 78523245 78523267 78523379 78523402 TINAGL1 chr1 103 GGCCATGATGCACTGAGTCTT 104 GCTCGGCTGTGCATCATACA 32050699 32050720 32050818 32050838 TINAGL1 chr1 105 TGATTCATGAGCCTCTTGACCAAG 106 GAATGGATTGAGACACGATCGGAT 32050343 32050367 32050493 32050517 ZFAND2B Chr2 107 TGACCTGTGAACGCTGTAGC 108 ACCATGCCTTCCTGTACCTC 220072962 220072984 220073020 220073141

In order to verify whether mutation detection is possible with the developed primer set, the genetic mutations identified in Examples 2 and 3 and samples derived from wild-type renal cancer cells were used as samples, and each genetic mutation was amplified with the primer set corresponding to each sample. After the reaction was completed, the chip was scanned using a scanner and an application program, and analyzed using quantitative analysis software.

As a result, the mutations in the genes of Examples 2 and 3 could be detected with the primer set produced in Example 5. On the other hand, no mutations were detected in the samples derived from renal cancer cells as the control group. Thus, since the primer pairs in Table 5 can be used to detect mutations in genes selected from the gene group consisting of ARHGEF5, ASB15, BAP1, EPB41L5, KIAA1614, LOXL3, LRCH1, OR10AG1, PDE4C, PRSS38, RTN3, TENM4, TINAGL1, and ZFAND2B, the overall survival period and disease-free survival period of renal cancer patients showing mutations in the above genes can be predicted, and a treatment strategy can be efficiently designed accordingly.

Although the preferred embodiments of the present invention have been described above as examples, the scope of the present invention is not limited to the specific embodiments described above, and those skilled in the art will be able to make appropriate changes within the scope described in the claims of the present invention.

Attach electronic file of sequence list

Claims (12)

A composition for diagnosing the prognosis of renal cancer according to gender, comprising a reagent capable of detecting a gender-dependent survival specific marker of a renal cancer patient, wherein the marker comprises at least one selected from the group consisting of a mutation in the ARHGEF5 gene, a mutation in the ASB15 gene, a mutation in the BAP1 gene, a mutation in the EPB41L5 gene, a mutation in the KIAA1614 gene, a mutation in the LOXL3 gene, a mutation in the LRCH1 gene, a mutation in the OR10AG1 gene, a mutation in the PDE4C gene, a mutation in the PRSS38 gene, a mutation in the RTN3 gene, a mutation in the TENM4 gene, a mutation in the TINAGL1 gene, and a mutation in the ZFAND2B gene. In claim 1,
The above reagent is a composition comprising at least one selected from the group consisting of a primer, a probe, an aptamer, and an antibody. In claim 1,
A composition comprising a mutation in one or more genes selected from the group consisting of ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, and TINAGL1, among the above sex-dependent survival-specific markers. In claim 1,
A composition comprising a mutation in one or more genes selected from the group consisting of BAP1, OR10AG1, and ZFAND2B, wherein the female-dependent survival-specific marker among the above sex-dependent survival-specific markers. A kit for diagnosing the prognosis of renal cancer according to gender, comprising a reagent capable of detecting a gender-dependent survival specific marker of a renal cancer patient, wherein the marker comprises at least one selected from the group consisting of a mutation in the ARHGEF5 gene, a mutation in the ASB15 gene, a mutation in the BAP1 gene, a mutation in the EPB41L5 gene, a mutation in the KIAA1614 gene, a mutation in the LOXL3 gene, a mutation in the LRCH1 gene, a mutation in the OR10AG1 gene, a mutation in the PDE4C gene, a mutation in the PRSS38 gene, a mutation in the RTN3 gene, a mutation in the TENM4 gene, a mutation in the TINAGL1 gene, and a mutation in the ZFAND2B gene. In claim 5,
A kit comprising at least one reagent selected from the group consisting of a primer, a probe, an aptamer, and an antibody. In claim 5,
A kit comprising a mutation in one or more genes selected from the group consisting of ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, and TINAGL1, among the above sex-dependent survival-specific markers. In claim 5,
A kit comprising a mutation in one or more genes selected from the group consisting of BAP1, OR10AG1, and ZFAND2B, among the above sex-dependent survival-specific markers, the female-dependent survival-specific marker. Step of preparing sample DNA from a sample of a kidney cancer patient;
A method for providing information necessary for the prognostic diagnosis of a renal cancer patient, comprising: a step of confirming the presence or absence of a gender-dependent survival specific marker using a composition for prognostic diagnosis of renal cancer according to any one of claims 1 to 4 or a kit for prognostic diagnosis of renal cancer according to any one of claims 5 to 8 for the sample DNA; In claim 9,
A method further comprising the step of amplifying a sample DNA prepared from a sample of the renal cancer patient. In claim 9,
A method further comprising a step of determining that, when a mutation in one or more genes selected from the group consisting of ARHGEF5, ASB15, EPB41L5, KIAA1614, LOXL3, LRCH1, PDE4C, PRSS38, RTN3, TENM4, and TINAGL1 is identified as the sex-dependent survival-specific marker and the renal cancer patient is male, the survival rate is lower or the recurrence rate is higher than that of a person in whom the sex-dependent survival-specific marker is not identified. In claim 9,
A method further comprising a step of determining that, when a mutation in one or more genes selected from the group consisting of BAP1, OR10AG1, and ZFAND2B as the sex-dependent survival-specific marker is identified and the patient with renal cancer is a woman, the survival rate is lower or the recurrence rate is higher than that of a person in whom the sex-dependent survival-specific marker is not identified.