WO2022014991A1 - Pathological grade-specific marker for making prognosis of and determining treatment strategy for prostate cancer patient - Google Patents

Abstract

The present invention relates to a marker for predicting a difference in the effects of prostate cancer treatments and making a prognosis in accordance with the pathological grade of a prostate cancer patient. Since a genetic mutation of the present invention is respectively correlated with a survival rate and a recurrence rate of a prostate cancer patient of a particular pathological grade, the mutated gene of the present invention can be used as a marker for predicting a difference in the effects of prostate cancer treatments or a prognosis of the prostate cancer patient, on the basis of the pathological grade.

Description

Pathology-grade-specific markers for prognostic diagnosis and treatment strategy determination of prostate cancer patients

The present invention provides a method for providing information necessary for prognostic diagnosis of prostate cancer and determining a treatment strategy using a marker for prognosis diagnosis of a prostate cancer patient, a kit for prognosis diagnosis of a prostate cancer patient including the same, and a prognostic diagnosis marker for a prostate cancer patient is about

As one of the male reproductive organs, the prostate is a body organ that makes and secretes a part of the liquid component of semen. It is composed of a middle lobe and two lateral lobes, a part consists of glandular tissue, and a part consists of muscle fibers and surrounds the urethra. When the prostate enlarges, the urethra becomes narrow, making it difficult for urine to pass through. Prostate cancer is also found with the same symptoms.

Prostate cancer is a malignant tumor that occurs in the prostate. Age, race, and family history are considered to be the most important causes, and hormones, dietary habits, and chemicals are also known to act as important factors in the pathogenesis. According to data from the Central Cancer Registry in 2019, prostate cancer ranked 7th among all cancers and 4th among cancers occurring in men, and the incidence rate in Korea is increasing.

The diagnosis of prostate cancer is made by combining all findings after performing digital rectal examination, blood prostate-specific antigen (PSA) test, transrectal ultrasound, and imaging. In the early stages of prostate cancer, the cancer does not spread to the surrounding area, so treatment is effective, but it becomes an incurable disease after it progresses, so early diagnosis is very important.

Treatment methods for prostate cancer include observational therapy, curative surgery, radiation therapy, hormone therapy, and chemotherapy, and are determined by considering related factors such as stage, tumor differentiation, and patient's age and health status. When prostate cancer is diagnosed at the local cancer stage, the cure rate is high, but when it is detected after the advanced stage, the cure rate drops significantly. If the level of prostate-specific antigen (PSA) in the blood increases in the follow-up test after treatment even after a cure, it is found to be a biochemical recurrence of prostate cancer. Years later, clinical relapse occurs. However, biochemical recurrence does not necessarily lead to clinical recurrence, and even if clinical recurrence occurs, the timing varies greatly. In addition, the clinical course after curative treatment for localized prostate cancer has not been clearly clarified, so a treatment policy for biochemical recurrence has not been established.

The pathology grade of prostate cancer patients will influence the choice of treatment method. Although several biomarkers for the diagnosis of prostate cancer have been disclosed (Registration Patent No. 10-1778036), markers that can measure the prognosis of patients with prostate cancer, in particular, genetic mutations found in prostate cancer and the survival rate of patients and The relationship with pathology grade has not been studied yet.

In order to apply an appropriate therapeutic strategy for prostate cancer patients, it is necessary to develop markers that predict the prognosis of prostate cancer patients and help determine treatment strategies.

An object of the present invention is to provide a marker that helps in prognostic diagnosis and treatment strategy determination of prostate cancer patients based on the pathology grade of the prostate cancer patients.

In order to achieve the above object, one aspect of the present invention includes an agent capable of detecting a mutation of a gene encoding ALMS1, NRXN3, NTRK1 and TRIOBP, according to the pathological grade of a prostate cancer patient predicting or prognosis of the treatment effect A diagnostic composition is provided.

Another aspect of the present invention provides a kit for diagnosing the therapeutic effect or prognosis according to the pathological grade of a prostate cancer patient comprising the composition.

Another aspect of the present invention comprises the steps of preparing a sample DNA from a sample of a prostate cancer patient with known pathology;

amplifying the sample DNA using the kit;

confirming the presence or absence of a pathology grade-specific marker from the amplification result;

Treating a prostate cancer patient whose pathology grade-specific marker has been identified with any prostate cancer treatment candidate or by any method; and

When any prostate cancer treatment candidate material or any treatment method improves or treats prostate cancer, adopting it as a treatment candidate or treatment method suitable for the pathology grade group of prostate cancer patients whose pathology grade-specific markers have been identified; It provides a method for providing information necessary to determine the difference in the treatment effect of prostate cancer according to the pathological grade of the prostate cancer patient, including.

Another aspect of the present invention comprises the steps of preparing a sample DNA from a sample of a prostate cancer patient;

amplifying the sample DNA using the kit; and

It provides a method of providing information necessary for prognostic diagnosis of prostate cancer according to the pathology grade of a prostate cancer patient, including the step of confirming the presence or absence of a pathology grade-specific marker from the amplification result.

Mutations of genes encoding ALMS1, NRXN3, NTRK1 and TRIOBP, which are the mutant genes discovered in the present invention, or COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, Since the mutation of at least one gene selected from the gene group consisting of NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD3, STRN3, TP53 and ZNF24 and the pathology grade of prostate cancer patients are related, by checking whether the gene is mutated It is possible to predict the difference in prostate cancer treatment effect and survival rate according to the pathology grade of prostate cancer patients.

In addition, mutations of genes encoding ALMS1, NRXN3, NTRK1 and TRIOBP, which are the mutant genes discovered in the present invention, or COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4 in addition to the mutated genes , NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD3, STRN3, TP53, and a mutation in one gene selected from the group consisting of ZNF24 and the survival rate of patients with prostate cancer of a specific pathological grade, or mutation of the gene and prostate cancer Since the recurrence rate of each is correlated, the mutation of the genes of the present invention can be used as a marker to predict the prognosis of a prostate cancer patient.

However, the effects of the present invention are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 shows the number and percentage of patients classified by pathology grade for 491 data used in the present invention.

FIG. 2 shows 52 pathology grade-specific mutant genes identified through comparative analysis between pathology grades of stage II, III and IV.

3 shows 27 pathology grade-specific mutant genes identified through comparative analysis between stage II and III + IV pathology grades.

FIG. 4 shows 80 pathology grade-specific mutant genes identified through comparative analysis between stage II + III and IV pathology grades.

5 to 28 show the total survival rate or disease-free of a prostate cancer patient with a mutation in the corresponding gene (red) and a prostate cancer patient without a mutation in the corresponding gene (blue) for each of the pathology grade-specific and survival-specific genes. It is a graph about the survival rate.

Prostate adenocarcinoma (Prostate adenocarcinoma (TCGA) reported to The Cancer Genome Atlas (TCGA) in order to discover pathology grade-specific markers for differential diagnosis, treatment strategy determination, or prognosis of prostate cancer based on the difference in pathology grades of prostate cancer patients. PRAD) data were used for machine learning. As a result, a pathology-grade-specific mutant gene and a survival-specific mutant gene for prostate cancer were found, respectively, and through this, 24 prostate cancer pathology-grade-specific and survival-specific markers were discovered.

Hereinafter, the present invention will be described in detail.

1. Pathology-grade-specific mutant gene in prostate cancer patients

One aspect of the present invention is to provide a composition for predicting treatment effect or prognosis diagnosis according to the pathology grade of a prostate cancer patient, comprising an agent capable of detecting mutations in genes encoding ALMS1, NRXN3, NTRK1 and TRIOBP.

In one embodiment of the present invention, the diagnostic composition is COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD3, STRN3, TP53 It may be a composition for predicting treatment effect or prognosis diagnosis according to the pathological grade of a prostate cancer patient, further comprising an agent capable of detecting a mutation of a gene encoding at least one selected from the group consisting of ZNF24.

In another embodiment of the present invention, the mutation of the gene encoding ALMS1 is at least one missense mutation selected from the group consisting of T196A, P1387L, T2308M, A1618V and A1157V in the amino acid sequence of SEQ ID NO: 1, or Y2936* is a nonsense mutation, or a frame shift insert (FS ins) mutation that is R4154Efs*40;

The mutation of the gene encoding NRXN3 is at least one missense mutation selected from the group consisting of L309I, A228S, R654H, R654C, D166Y, A85T, D308A and F23I in the amino acid sequence of SEQ ID NO: 2;

The mutation of the gene encoding NTRK1 is, in the amino acid sequence of SEQ ID NO: 3, at least one missense mutation selected from the group consisting of R342Q, R507C, P63S, P695S, G714S, A612V, R574H and R599H, or Q730_L731del in-frame deletion (in-frame delete, IF del) mutation;

The mutation of the gene encoding TRIOBP is at least one missense mutation selected from the group consisting of P1125L, S1252F, R2259H and Q702R in the amino acid sequence of SEQ ID NO: 4, or Q2245*, Q350*, R1554* and R448* at least one nonsense mutation selected from the group consisting of; It may be a composition for predicting treatment effect or prognosis diagnosis according to the pathological grade of a prostate cancer patient.

In another embodiment of the present invention, the mutation of the gene encoding COL22A1 is at least one missense mutation selected from the group consisting of N1115D, R210W, T117M, G490D, L1427M and D1133G in the amino acid sequence of SEQ ID NO: 5, or , a nonsense mutation that is R592*, or a frame shift delete (FS del) mutation of at least one of K529Rfs*21 (diploid) and K529Rfs*21 (amp);

The mutation of the gene encoding FHOD3 is at least one missense mutation selected from the group consisting of T1328P, R188H, G120R, A1330T and A1051T in the amino acid sequence of SEQ ID NO: 6, or R461Afs*31 A frame shift deletion (frame shift) delete, FS del) mutation;

The mutation of the gene encoding MYH11 is at least one missense mutation selected from the group consisting of A815T, E1888K, T975M, A732V, A1259V and A334V in the amino acid sequence of SEQ ID NO: 7, or a nonsense mutation that is R1609*;

The mutation of the gene encoding ACY3 is a missense mutation of R233C in the amino acid sequence of SEQ ID NO: 8;

The mutation of the gene encoding C8orf74 is a missense mutation that is A273T in the amino acid sequence of SEQ ID NO: 9;

The mutation of the gene encoding CPT1A is a missense mutation that is A577V in the amino acid sequence of SEQ ID NO: 10;

The mutation in the gene encoding DDX39A is a missense mutation that is A96V in the amino acid sequence of SEQ ID NO: 11;

The mutation in the gene encoding FBXL4 is a missense mutation that is D550A in the amino acid sequence of SEQ ID NO: 12;

The mutation of the gene encoding ICAM1 is a missense mutation of P63L in the amino acid sequence of SEQ ID NO: 13;

The mutation in the gene encoding KIFAP3 is a nonsense mutation that is Q492* in the amino acid sequence of SEQ ID NO: 14;

The mutation of the gene encoding IPO4 is R916* innonsense mutation in the amino acid sequence of SEQ ID NO: 15;

The mutation in the gene encoding NAT2 is a missense mutation that is L52F in the amino acid sequence of SEQ ID NO: 16;

The mutation in the gene encoding NFIX is a missense mutation that is R343H in the amino acid sequence of SEQ ID NO: 17;

The mutation in the gene encoding PLIN4 is a missense mutation that is A646T in the amino acid sequence of SEQ ID NO: 18;

The mutation in the gene encoding SCRIB is a missense mutation that is P422S in the amino acid sequence of SEQ ID NO: 19;

The mutation of the gene encoding SHC4 is a missense mutation of P80L in the amino acid sequence of SEQ ID NO: 20;

The mutation of the gene encoding SOD3 is a missense mutation of D54N in the amino acid sequence of SEQ ID NO: 21;

The mutation in the gene encoding STRN3 is a missense mutation that is at least one of L206I and L792I in the amino acid sequence of SEQ ID NO: 22;

The mutation of the gene encoding TP53 is, in the amino acid sequence of SEQ ID NO: 23, R273C, R248Q, E285K, R282W, R248W, R175H, G245D, H193R, M237I, G245S, C135F, C135Y, C135W, V157F, R181C, Y163H, V173M , at least one missense mutation selected from the group consisting of N239D, R337C, R249G, C176R, C141G, E271V, H193N, G266V, G279E, P177R, G199V, T256I, A74T and P82L, or at least one of R342* and E298* a nonsense mutation, or a frame shift insert (FS ins) mutation that is at least one of Q165Hfs*17 and C124Wfs*25, or A86Vfs*55, R209Kfs*6, V203Wfs*44, K319Rfs*26, S90Ffs*53, At least one frame shift delete (FS del) mutation selected from the group consisting of S149Pfs*21 and Q144Gfs*24, or at least one selected from the group consisting of X126_splice, X307_splice, X33_splice, X331_splice, X126_splice and X126_splice splice mutation;

The mutation of the gene encoding ZNF24 is a missense mutation that is Y344C in the amino acid sequence of SEQ ID NO: 24; It may be a composition for predicting treatment effect or prognosis diagnosis according to the pathological grade of a prostate cancer patient.

Gene bank accession numbers of the genes are ALMS1 (Gene bank accession number: NM_015120.4), NRXN3 (Gene bank accession number: NM_001272020.2), NTRK1 (Gene bank accession number: NM_002529.3), TRIOBP (Gene bank accession number), respectively. number: NM_001039141.3), COL22A1 (Gene bank accession number: NM_152888.3), FHOD3 (Gene bank accession number: NM_001281739.3), MYH11 (Gene bank accession number: NM_002474.3), ACY3 (Gene bank accession number: NM_080658.2), C8orf74 (Gene bank accession number: NM_001040032.2), CPT1A (Gene bank accession number: NM_001876.4), DDX39A (Gene bank accession number: NM_005804.4), FBXL4 (Gene bank accession number: NM_001278716). 2), ICAM1 (Gene bank accession number: NM_000201.3), KIFAP3 (Gene bank accession number: NM_014970.4), IPO4 (Gene bank accession number: NM_024658.4), NAT2 (Gene bank accession number: NM_000015.3) , NFIX (Gene bank accession number: NM_001365902.2), PLIN4 (Gene bank accession number: NM_001080400.1), SCRIB (Gene bank accession number: NM_015356.5), SHC4 (Gene bank accession number: NM_203349.4), SOD3 (Gene bank accession number: NM_003102.3), STRN3 (Gene bank accession number: NM_001083893.2), TP53 (Gene bank accession number: NM_000546). 5) and ZNF24 (Gene bank accession number: NM_006965.4).

The full names of the abbreviations of the genes are ALMS1 (ALMS1 centrosome and basal body associated protein), NRXN3 (neurexin 3), NTRK1 (neurotrophic receptor tyrosine kinase 1), TRIOBP (TRIO and F-actin binding protein), COL22A1 (collagen type), respectively. XXII alpha 1 chain), FHOD3 (formin homology 2 domain containing 3), MYH11 (myosin heavy chain 11), ACY3 (aminoacylase 3), C8orf74 (chromosome 8 open reading frame 74), CPT1A (carnitine palmitoyltransferase 1A), DDX39A (DExD -box helicase 39A), FBXL4 (F-box and leucine rich repeat protein 4), ICAM1 (intercellular adhesion molecule 1), KIFAP3 (kinesin associated protein 3), IPO4 (Homo sapiens importin 4), NAT2 (N-acetyltransferase 2) , NFIX (nuclear factor IX), PLIN4 (perilipin 4), SCRIB (scribble planar cell polarity protein), SHC4 (SHC adapter protein 4), SOD3 (superoxide dismutase 3), STRN3 (striatin 3), TP53 (tumor protein p53) and zinc finger protein 24 (ZNF24).

In another embodiment of the present invention, the agent may be a composition for predicting treatment effect or prognostic diagnosis according to the pathology grade of a prostate cancer patient, which includes a primer set, a probe or an antibody for the mutation of the gene.

In the present invention, the term 'diagnosis' refers to confirming the presence or characteristics of a pathological state, and for the purpose of the present invention, not only confirming the difference in the cancer treatment effect depending on whether the cancer patient has metastasized, but also confirming the difference in the cancer treatment effect after the cancer treatment. means to judge whether recurrence, drug reactivity, resistance, etc. Preferably, when the mutation of the gene of the present invention is used, the difference in the treatment effect of prostate cancer according to the pathological grade of the prostate cancer patient and the difference in the survival rate that can determine the prognosis of the patient in the future by confirming whether the mutation is present from the sample of the patient with prostate cancer can also be predicted.

In the present invention, the term 'prognosis' refers to the progress and cure of neoplastic diseases such as cancer, such as the possibility of cancer-caused death or progression, including recurrence, metastatic spread, and drug resistance, for example. For the purpose of the present invention, it may be to predict the prognosis of prostate cancer, preferably to predict the disease-free or survival rate of prostate cancer patients.

As used herein, the term 'cancer' includes any member of a class of diseases characterized by the uncontrolled growth of abnormal cells. The term includes all known cancers and neoplastic conditions, 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 'gene' and its variants include a DNA fragment involved in the generation of a polypeptide chain; It includes regions before and after the coding region, eg promoters and 3'-untranslated regions, respectively, as well as intervening sequences (introns) between individual coding fragments (exons).

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

In the present invention, the term 'missense mutation' refers to a mutation in which one base in a DNA base sequence is substituted with another base to change the codon of an amino acid to another codon.

In the present invention, the term 'nonsense mutation' refers to a mutation in which a part of a specific nucleotide sequence of a gene is converted to a stop codon so that protein synthesis is no longer made.

In the present invention, the term 'frame shift insertion' refers to a mutation that occurs when one or more nucleotides are added to DNA to shift the decoding frame of the genetic code.

In the present invention, the term 'frame shift deletion' refers to a mutation in which one or more nucleotides are deleted in DNA and the reading frame of the genetic code is shifted and shifted.

In the present invention, the term 'in-frame deletion' refers to a mutation in which a specific nucleotide sequence of a gene is deleted, but there is no change in the other amino acids except for the amino acid due to the deleted nucleotide sequence.

As used herein, the term 'splice mutation' refers to a gene mutation in which a nucleotide at a specific position of a gene is substituted.

The term “X#Y” with respect to mutations in a polypeptide sequence is self-recognized in the art, where “#” denotes the mutation site with respect to the amino acid number of the polypeptide, and “X” denotes that of the wild-type amino acid sequence. indicates the amino acid found at that position, and "Y" indicates the mutant amino acid at that position. For example, the designation "G1717V" with respect to a BAZ2B polypeptide indicates that glycine is present at amino acid number 1717 of the wild-type BAZ2B sequence and that glycine has been replaced by valine in the mutant BAZ2B sequence.

The term “*” in reference to mutations in polypeptide sequences is readily recognized in the art where “*” may be used to indicate translation stop codons in the one and three amino acid codes, e.g., nonsense mutations In *, indicates that the amino acid synthesis at the corresponding amino acid position is terminated.

The term "_" with respect to a mutation in a polypeptide sequence is clearly recognized in the art, where "_" indicates a range and, for example, when A200_C240 is used, the alanine of the 200 amino acid sequence of the polypeptide. ) to cysteine located in the amino acid sequence at number 240 indicates the range.

The term “del” with respect to a mutation in a polypeptide sequence is self-recognized in the art, where “del” denotes a deletion, for example, when used as V7del, the 7th position of a specific sequence is valine. , and when used as V76_S79del, it means a mutation in which a deletion from valine located at position 76 to serine located at position 79 in a specific sequence has occurred.

The term “ins” in reference to a mutation in a polypeptide sequence is art-recognized as is self-evident in the art where “ins” denotes an insertion, e.g., when used as V76_S77insV, from valine 76 to 77 in a particular sequence. It refers to a mutation in which valine is inserted between the serine located at the bun.

The term “fs” in reference to a mutation in a polypeptide sequence is readily recognized in the art where “fs” stands for a frame shift, e.g., the 97th position in a particular sequence when used as V97SfsTer23 or V97Sfs*23 It indicates that the located valine is changed to serine and there is a termination codon (Termination, Ter) at the position 23 (120th amino acid sequence) after it, and when V76_S79*? , means a mutation in which a new stop codon does not appear.

Next generation sequencing (NGS), RT-PCR, direct nucleic acid sequencing method, and microarray can be used as an analysis method for diagnosing the prognosis of prostate cancer using the mutation of the gene. Any method that can confirm the existence of a mutation using a mutation of a gene can be applied without limitation.

In one embodiment, the presence of a mutation is determined using an anti-(mutant of each gene) antibody or nucleic acid probe that hybridizes under stringent conditions to the polynucleotide of the mutant of each gene.

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 radioimmunoassay, western blot assay, immunofluorescence assay, enzymeimmunoassay, immunoprecipitation assay, chemiluminescence assay, immunohistochemical assay, dot blot assay, slot blot assay, or flow cytometry. determined by the 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.

As used herein, the term 'polynucleotide' 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 single- and double-stranded DNA. - RNA comprising a region, single-stranded or more typically double-stranded, or hybrid molecule comprising DNA and RNA, which may contain 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 in the term 'polynucleotide' as defined herein is DNA or RNA comprising an unconventional 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 unmodified polynucleotides. 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 is to provide a kit for predicting treatment effect or prognosis diagnosis according to the pathological grade of a prostate cancer patient, comprising the composition.

The kit of the present invention prepared as described above is very economical because it saves time and money compared to the existing general gene mutation search method. Using existing gene mutation detection methods such as SSCP (Single Strand Conformational Polymorphism), PTT (Protein Truncation Test), cloning, and direct sequencing to test all one gene, on average, it takes several days to several months. This takes In addition, gene mutations can be precisely tested quickly and simply through next generation sequencing (NGS). In the case of testing mutations by existing analysis methods 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, the sample DNA is prepared If it is done, results can be obtained within about 10 to 11 hours, and since a primer set capable of detecting mutations is integrated on one chip, not only time but also cost can be reduced compared to the conventional method. Compared to the conventional method, the average cost of reagents is less than half per experiment, so even greater cost savings can be expected when considering the researcher's labor costs.

2. Method of providing information necessary for prognostic diagnosis of prostate cancer using survival-specific mutant gene

Another aspect of the present invention comprises the steps of preparing a sample DNA from a sample of a prostate cancer patient with known pathology; amplifying the sample DNA using the kit; confirming the presence or absence of a pathology grade-specific marker from the amplification result; Treating a prostate cancer patient whose pathology grade-specific marker has been identified with any prostate cancer treatment candidate or by any method; And any prostate cancer treatment candidate material or any treatment method improves or treats prostate cancer, selecting a treatment candidate or treatment method suitable for a prostate cancer patient whose pathology grade-specific marker has been identified. Prostate comprising a; Provided is a method for providing information necessary to determine the difference in cancer treatment effect according to the pathology grade of cancer patients.

In one embodiment of the present invention, the pathology grade-specific marker is ALMS1, NRXN3, NTRK1, TRIOBP, COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, NAT2, NFIX, PLIN4, NFIX, , SCRIB, SHC4, SOD3, STRN3, TP53 and ZNF24 may be a mutation of a gene encoding one selected from the group consisting of.

In another embodiment of the present invention, the pathology grade-specific markers for pathology grade IV among prostate cancer patients are ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, IPO4, KIFAP3, NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD3, The method may be a mutation of a gene encoding one selected from the group consisting of STRN3 and ZNF24.

Another aspect of the present invention comprises the steps of preparing a sample DNA from a sample of a prostate cancer patient; amplifying the sample DNA using the kit; and confirming the presence or absence of a pathology grade-specific marker from the amplification result; provides a method of providing information necessary for prognostic diagnosis of prostate cancer according to the pathology grade of a prostate cancer patient, including.

For the description of the kit for prognostic diagnosis of prostate cancer, see '1. Since it is the same as described in 'Pathology grade-specific mutant gene in prostate cancer patients', a detailed description will be omitted.

Any of the therapeutic candidate substances may be a therapeutic agent commonly used for the treatment of prostate cancer or a novel substance whose therapeutic effect on prostate cancer is unknown, but is not limited thereto. Whether the treatment candidate material is effective in a specific patient group can be determined by checking the therapeutic effect after treating any of the above treatment candidates with a prostate cancer patient having a recurrence-specific marker. If there is a treatment effect for prostate cancer, it can be predicted that the treatment effect will be high when applied to a patient group having the same pathology grade-specific marker, so it can provide useful information for determining a treatment strategy. In addition, if a therapeutic effect does not appear when any treatment candidate is used, treatment strategy can be efficiently designed because unnecessary treatment is not required by not proceeding with treatment to the patient group having the same recurrence-specific marker. have.

Any prostate cancer treatment method instead of any of the above treatment candidates is also applicable, and by confirming the therapeutic effect in a patient group having a specific pathology grade-specific marker, it can be determined whether to apply to a patient group having the same pathology grade-specific marker. have. When confirming the therapeutic effect in the patient group having the pathology grade-specific marker, any treatment candidate substance and any prostate cancer treatment method may be combined.

As used herein, the term 'sample' includes any biological sample obtained from a patient. Samples include whole blood, plasma, serum, red blood cells, white blood cells (eg peripheral blood mononuclear cells), ductal fluid, ascites, pleural efflux, nipple aspirate, lymphatic fluid (eg disseminated tumors of lymph nodes) cells), bone marrow aspirate, saliva, urine, feces (ie feces), sputum, bronchial lavage fluid, tears, fine needle aspirate (eg harvested by random mammary fine needle aspiration), any other bodily fluid, tissue A sample (eg tumor tissue) such as a tumor biopsy (eg puncture biopsy) or lymph node (eg sentinel lymph node biopsy), a tissue sample (eg tumor tissue), eg surgical resection of a tumor and cell extracts thereof. In some embodiments, the sample is whole blood or some component thereof, such as plasma, serum or cell pellet. In another embodiment, the sample is obtained by isolating circulating cells of a solid tumor from whole blood or a cell fraction thereof using any technique known in the art. In another embodiment, the sample is a formalin-fixed paraffin-embedded (FFPE) tumor tissue sample from a solid tumor, eg, colorectal cancer.

In certain embodiments, the sample is a tumor lysate or extract prepared from frozen tissue obtained from a subject with colorectal cancer.

The term 'patient' usually includes humans as well as other animals, such as other primates, rodents, dogs, cats, horses, sheep, pigs, and the like.

The term 'subject' includes subjects other than humans diagnosed with or suspected of having prostate cancer.

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

In the present invention, the term 'overall survival' includes a clinical endpoint describing a patient who is alive for a limited time after being diagnosed with or treated for a disease, such as cancer, and the survival rate with or without cancer recurrence. means possibility.

In the present invention, the term 'disease-free survival (DFS)' includes a period in which a patient survives without cancer recurrence after treatment for a specific disease (eg, cancer).

In the present invention, by analyzing the presence of a mutation in a gene of the present invention in a sample of a prostate cancer patient, it is possible to determine what prognosis an individual having the target sample has for cancer. Also, this method can be achieved by comparing the total survival or disease-free survival of subjects 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 sample of an individual suspected of cancer refers to a sample of an individual or tissue in which cancer or tumor has already occurred or is expected to occur, and is a target sample for diagnosing the prognosis.

The method of providing information necessary for prognostic diagnosis of prostate cancer according to the pathology grade of the prostate cancer patient can predict the total survival rate or disease-free survival rate of the prostate cancer patient. For example, in the method, mutations are identified in genes encoding ALMS1, NRXN3, NTRK1, and TRIOBP, and in the case of a patient with prostate cancer, the survival rate of the prostate cancer patient is lower than that of a person whose mutation is not identified in the gene. Or, determining that the recurrence rate of prostate cancer in the prostate cancer patient is higher than the recurrence rate of prostate cancer in a person whose mutation is not identified in the gene; may further include.

The method of providing information necessary for prognostic diagnosis of prostate cancer according to the recurrence of the prostate cancer patient is COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, NAT2, NFIX, PLIN4, When a mutation is identified in a gene encoding at least one selected from the group consisting of SCRIB, SHC4, SOD3, STRN3, TP53 and ZNF24, the survival rate of prostate cancer patients is lower than the survival rate of those whose mutations are not identified in the gene, or , determining that the recurrence rate of prostate cancer in the prostate cancer patient is higher than the recurrence rate of prostate cancer in a person whose mutation is not identified in the gene.

As such, mutations of the genes of the present invention are ALMS1, NRXN3, NTRK1, TRIOBP, COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, SIPO4, NAT2, NFIX, PLIN4, SCRIB, PLIN4, SCRIB Using mutations in at least one gene selected from the gene group consisting of SOD3, STRN3, TP53, and ZNF24, there has been no clarification on the content that there is a difference in gene mutations according to the pathological grade of cancer, particularly prostate cancer. In addition, to ALMS1, NRXN3, NTRK1, TRIOBP, COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD24 It has not yet been revealed that the prognosis for prostate cancer can be diagnosed in a specific pathological grade using a mutation of at least one gene selected from the constituting gene group. In addition, it has not been reported that the total survival rate or disease-free survival rate may be different for each gene. The present inventors have identified for the first time that mutations of the above genes can be used as diagnostic markers for predicting the difference in the treatment effect of prostate cancer according to the pathological grade of the prostate cancer patient or diagnosing the prognosis of the prostate cancer patient.

The method of providing information necessary for predicting the difference in the treatment effect of prostate cancer according to the pathology grade of the prostate cancer patient of the present invention is to diagnose the genetic mutation of the prostate cancer based on the pathology grade, increase the survival rate of the prostate cancer patient, or , or to lower the recurrence rate. Through the method for prognostic diagnosis of prostate cancer of the present invention, it is possible to predict the therapeutic effect of prostate cancer or predict the survival rate or recurrence rate of prostate cancer patients by using gene mutation information according to the pathological grade of the prostate cancer, It can provide information on the selection of treatments as well as the discovery of suitable treatments for each patient, so that it is possible to efficiently design a therapeutic strategy for prostate cancer.

Hereinafter, the present invention will be described in detail by way of Examples and Experimental Examples.

However, the following Examples and Experimental Examples are only for illustrating the present invention, and the content of the present invention is not limited by the following Examples and Experimental Examples.

[Example]

Example 1. Securing genetic information and clinical information

Genes of the present invention (ALMS1, NRXN3, NTRK1, TRIOBP, COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, NAT2, NFIX, PLIN4, SCRIB, SHC4, SCRIB, STRN3 In order to check whether TP53 and ZNF24 (hereinafter also referred to as 'candidate genes') can be used as prostate cancer markers according to pathology grade, both genetic information and clinical information are secured from The Cancer Genome Atlas (TCGA). Data on recurrence, metastasis, death, and observation time of 498 patients with clear prostate cancer were obtained and used for analysis. Table 1 below shows data on recurrence, metastasis, and death of prostate cancer patients. The above candidate genes are genes that have been mutated in prostate cancer patients according to the pathology grade.

		Sum
		Number of patients (persons)	ratio (%)
survival or not	survival	488/498	98%
	Dead	10/498	2%
relapse	disease free	401/488	82.2%
	recurrence/progression	87/488	17.8%
transition	None (M0)	456/459	99.4%
	Yes (M1a)	1/459	0.2%
	Yes (M1b)	1/459	0.2%
	Yes (M1c)	1/459	0.2%
total number of patients		498 people

Example 2. Confirmation of utility as a pathology grade-specific marker

Among the 498 TCGA-reported prostate cancer patients, 491 data that can confirm the pathological grade were classified into three groups as shown in Table 2, and the correlation between the mutation and the pathological grade of the candidate genes of Example 1 was analyzed by three Feature Selections. (Information Gain, Chi-Square, MRMR) method was confirmed. The mutated positions of the genes are shown in the table below.

Comparison between pathological grade groups
test set type	Detail	note
test set 1	Stage Ⅱ vs Ⅲ vs Ⅳ	Comparative analysis between pathology grades
test set 2	Stage Ⅱ vs Ⅲ + Ⅳ	Comparative analysis before and after Stage II
test set 3	Stage Ⅱ + Ⅲ vs Ⅳ	Comparative analysis before and after Stage III
Results of comparative analysis between age groups
test set type	pathology grade specific gene
test set 1	ACY3,C8orf74,CPT1A,DDX39A,FBXL4,ICAM1,IPO4,KIFAP3,SOD3,ZNF24
test set 2	ALMS1,COL22A1,FHOD3,MYH11,NRXN3,NTRK1,TP53,TRIOBP
test set 3	NAT2,NFIX,PLIN4,SCRIB,SHC4, STRN3

2-1. Comparative analysis between each group (test set 1 - Stage Ⅰ vs Ⅱ vs Ⅲ vs Ⅳ)

In Table 2, for each of the three pathological grade groups divided by group, the association between the occurrence of mutations in candidate genes and the pathology grade of prostate cancer patients was confirmed. A P-value of less than 0.05 was considered statistically significant. Information on candidate genes related to test set 1 is shown in Tables 3 to 5 below.

gene	pathology grade			mutation Number	Mutation (%)	Mutation type				Saito band	Pathology grade (%)			Fisher (p-value)
	II	Ⅲ	IV			cut	missense	in-frame	Etc		II	Ⅲ	IV
ACY3	0	0	One	One	0.20	0	One	0	0	11q13.2	0	0	100	0.02037
ADA	0	0	One	One	0.20	0	One	0	0	20q13.12	0	0	100	0.02037
AGPAT2	0	0	One	One	0.20	0	One	0	0	9q34.3	0	0	100	0.02037
AOC1	0	0	One	One	0.20	0	One	0	0	7q36.1	0	0	100	0.02037
APOBEC2	0	0	One	One	0.20	One	0	0	0	6p21.1	0	0	100	0.02037
ARHGAP39	0	0	One	One	0.20	0	One	0	0	8q24.3	0	0	100	0.02037
ARHGEF28	0	0	One	One	0.20	One	0	0	0	5q13.2	0	0	100	0.02037
BPIFB2	0	0	One	One	0.20	0	One	0	0	20q11.21	0	0	100	0.02037
C19orf26	0	0	One	One	0.20	0	One	0	0	19p13.3	0	0	100	0.02037
C8orf74	0	0	One	2	0.40	0	2	0	0	8p23.1	0	0	100	0.02037
CD40	0	0	One	One	0.20	0	One	0	0	20q13.12	0	0	100	0.02037
CDK2AP2	0	0	One	One	0.20	One	0	0	0	11q13.2	0	0	100	0.02037
CEP97	0	0	One	One	0.20	0	One	0	0	3q12.3	0	0	100	0.02037
CHP2	0	0	One	One	0.20	0	One	0	0	16p12.2	0	0	100	0.02037
CLDN12	0	0	One	One	0.20	0	One	0	0	7q21.13	0	0	100	0.02037
CPT1A	0	0	One	2	0.40	0	2	0	0	11q13.3	0	0	100	0.02037
DAK	0	0	One	One	0.20	One	0	0	0	11q12.2	0	0	100	0.02037
DAPP1	0	0	One	One	0.20	0	One	0	0	4q23	0	0	100	0.02037
DDX39A	0	0	One	One	0.20	0	One	0	0	20p13	0	0	100	0.02037
DDX39A	0	0	One	One	0.20	0	One	0	0	19p13.12	0	0	100	0.02037

gene	pathology grade			mutation Number	Mutation (%)	type of mutation				Saito band Pathology grade (%)	Fisher (p-value)
	II	Ⅲ	IV			cut	missense	in-frame	Etc		II	Ⅲ	IV
DYNC2H1	0	0	One	One	0.20	0	One	0	0	11q22.3	0	0	100	0.02037
E2F8	0	0	One	One	0.20	0	One	0	0	11p15.1	0	0	100	0.02037
EDA	0	0	One	One	0.20	0	One	0	0	Xq13.1	0	0	100	0.02037
FAM78B	0	0	One	One	0.20	0	One	0	0	1q24.1	0	0	100	0.02037
FBXL4	0	0	One	One	0.20	0	One	0	0	6q16.1-q16.2	0	0	100	0.02037
GALT	0	0	One	One	0.20	0	One	0	0	9p13.3	0	0	100	0.02037
GEMIN2	One	0	One	2	0.40	2	0	0	0	14q21.1	50	0	50	0.016
GLP2R	0	0	One	One	0.20	0	One	0	0	17p13.1	0	0	100	0.02037
GSTM3	0	0	One	One	0.20	0	One	0	0	1p13.3	0	0	100	0.02037
HDHD3	0	0	One	One	0.20	0	One	0	0	9q32	0	0	100	0.02037
HEXIM1	0	0	One	One	0.20	0	0	One	0	17q21.31	0	0	100	0.02037
HSD17B2	0	0	One	One	0.20	0	One	0	0	16q23.3	0	0	100	0.02037
ICAM1	0	0	One	2	0.40	0	2	0	0	19p13.2	0	0	100	0.02037
IPO4	0	0	One	2	0.40	2	0	0	0	14q12	0	0	100	0.02037
ISCU	0	0	One	One	0.20	0	One	0	0	12q23.3	0	0	100	0.02037
KIFAP3	0	0	One	2	0.40	2	0	0	0	1q24.2	0	0	100	0.02037
KLK2	0	0	One	One	0.20	One	0	0	0	19q13.33	0	0	100	0.02037
LRRC17	0	0	One	One	0.20	0	One	0	0	7q22.1	0	0	100	0.02037
MELK	0	0	One	One	0.20	0	One	0	0	9p13.2	0	0	100	0.02037
MT-CO2	0	0	One	One	0.20	0	One	0	0	NA	0	0	100	0.02037

gene	pathology grade			mutation Number	Mutation (%)	Mutation type				Saito band	Pathology grade (%)			Fisher (p-value)
	II	Ⅲ	IV			cut	missense	in-frame	Etc		II	Ⅲ	IV
NBL1	0	0	One	One	0.20	One	0	0	0	1p36.13	0	0	100	0.02037
NUMB	0	0	One	One	0.20	0	One	0	0	14q24.2-q24.3	0	0	100	0.02037
OR52J3	One	0	One	2	0.40	0	2	0	0	11p15.4	50	0	50	0.016
PLRG1	0	0	One	One	0.20	One	0	0	0	4q31.3	0	0	100	0.02037
PRKAG3	0	0	One	One	0.20	0	One	0	0	2q35	0	0	100	0.02037
PTPLA	0	0	One	One	0.20	One	0	0	0	10p12.33	0	0	100	0.02037
RWDD2A	0	0	One	One	0.20	0	One	0	0	6q14.1	0	0	100	0.02037
S100A7L2	0	0	One	One	0.20	0	One	0	0	1q21.3	0	0	100	0.02037
SOD3	0	0	One	One	0.20	0	One	0	0	4p15.2	0	0	100	0.02037
TNFAIP3	0	0	One	One	0.20	0	One	0	0	6q23.3	0	0	100	0.02037
TPX2	0	0	One	One	0.20	One	0	0	0	20q11.21	0	0	100	0.02037
ZNF24	0	0	One	One	0.20	0	One	0	0	18q12.2	0	0	100	0.02037

As a result of the analysis, in each pathology grade group, even if the gene had a mutation, there were genes with a P-value of 0.05 or higher compared to other groups, while genes with a mutation and a P-value of less than 0.05 were identified. Mutant genes with a P-value of less than 0.05 compared to other groups were selected as pathology grade-specific genes because they were correlated with a specific pathology grade group compared to other groups. When comparing between groups, the P-value of SMO was less than 0.05, confirming that there was a correlation between the occurrence of mutations in these genes and the pathology grade. 2 shows the results according to test set 1. 2, ACY3, ADA, AGPAT2, AOC1, APOBEC2, ARHGEF28, BPIFB2, C19ORF26, C8orf74, CD40, CDK2AP2, CEP97, CHP2, CPT1A, DAK, DAPP1, DDX39A, DDX39A, E2F8H1, E2F2H1 FBXL4, GALT, GLP2R, GSTM3, HDHD3, HEXM1, HSD17B2, ICAM1, IPO4, ISCU, KIFAP3, KLK2, LRRC17, MELK, MT-CO2, NBL1, NUMB, PLRG1, PRKAG3, PTPLA, RWIPDD2A, TNFA100ADD2A It was confirmed that TPX2 and ZNF24 showed more mutations in group IV than other groups, and GEMIN2 and OR52J3 showed more mutations in group II and IV than other groups. From the above results, ACY3, ADA, AGPAT2, AOC1, APOBEC2, ARHGEF28, BPIFB2, C19ORF26, C8orf74, CD40, CDK2AP2, CEP97, CHP2, CPT1A, DAK, DAPP1, DDX39A, DDX39A, DYNC2H1, F78B, F8, EDA, FAM GALT, GLP2R, GSTM3, HDHD3, HEXM1, HSD17B2, ICAM1, IPO4, ISCU, KIFAP3, KLK2, LRRC17, MELK, MT-CO2, NBL1, NUMB, PLRG1, PRKAG3, PTPLA, RWDD2A, SOD37L2, SOD37L TNF, SOD37L2 It can be seen that 52 mutations of ZNF24, GEMIN2 and OR52J3 can be used as markers specific to group II or group IV.

2-2. Comparative analysis before and after Stage Ⅱ (Test set 2 - Stage Ⅱ vs Ⅲ + Ⅳ)

Among the three pathology grade groups divided by group in Table 2, for low pathology grades (II) and high pathology grades (III and IV), the association between the occurrence of mutations in candidate genes and the pathology grade of prostate cancer patients was confirmed. . A P-value of less than 0.05 was considered statistically significant. Information on candidate genes related to test set 2 is shown in Tables 6 to 12 below.

gene	mutation Number	Mutation (%)	Saito band	type of mutation				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II	Stage III+IV	Stage III+IV (%)
ACACA	8	1.7	17q12	2	6	0	0	2	6	75.0	0.355
ADAM23	5	1.1	2q33.3	0	5	0	0	0	5	100.0	0.091
ALMS1	7	1.5	2p13.1	2	5	0	0	0	7	100.0	0.035
ALPK2	9	2.0	18q21.31-q21.32	2	7	0	0	One	8	88.9	0.088
ANK3	8	1.7	10q21.2	4	4	0	0	0	8	100.0	0.022
ANKRD36C	35	7.6	2q11.1	One	34	0	0	21	14	40.0	0.01
ATOH1	3	0.7	4q22.2	0	3	0	0	3	0	0.0	0.057
BRWD1	6	1.3	21q22.2	2	4	0	0	0	6	100.0	0.057
COL22A1	9	2.0	8q24.23-q24.3	3	6	0	0	0	9	100.0	0.014
CPSF7	2	0.4	11q12.2	0	2	0	0	2	0	0.0	0.148
CYFIP2	6	1.3	5q33.3	One	5	0	0	0	6	100.0	0.057
DBR1	7	1.5	3q22.3	0	0	7	0	One	6	85.7	0.185
DCC	6	1.3	18q21.2	0	6	0	0	0	6	100.0	0.057
DDX23	6	1.3	12q13.12	One	5	0	0	0	6	100.0	0.057
DNASE2B	3	0.7	1p31.1-p22.3	3	0	0	0	3	0	0.0	0.057

gene	mutation Number	Mutation (%)	Saito band	Mutation type				pathology grade			Fisher’s exact (P-Value)
				cut	missense	in-frame	Etc	Stage II	Stage III+IV	Stage III+IV (%)
DUSP27	5	1.1	1q24.1	0	3	2	0	0	5	100.0	0.091
EIF4G3	6	1.3	1p36.12	4	2	0	0	0	6	100.0	0.057
EP300	7	1.5	22q13.2	0	7	0	0	0	7	100.0	0.035
FAM83C	6	1.3	20q11.22	One	5	0	0	0	6	100.0	0.057
FBN3	14	3.1	19p13.2	0	14	0	0	One	13	92.9	0.012
FEM1A	7	1.5	19p13.3	One	6	0	0	5	2	28.6	0.083
FHOD3	7	1.5	18q12.2	2	5	0	0	0	7	100.0	0.035
FRAS1	6	1.3	4q21.21	0	6	0	0	0	6	100.0	0.057
GNAZ	3	0.7	22q11.22-q11.23	0	2	One	0	2	0	0.0	0.33
GRIK3	6	1.3	1p34.3	0	6	0	0	5	One	16.7	0.035
GRIP1	5	1.1	12q14.3	0	5	0	0	0	5	100.0	0.091
HSPG2	12	2.6	1p36.12	2	10	0	0	One	11	91.7	0.027
INO80	5	1.1	15q15.1	One	4	0	0	0	5	100.0	0.091
IRS2	3	0.7	13q34	2	One	0	0	3	0	0.0	0.057
ITPR3	6	1.3	6p21.31	0	6	0	0	0	6	100.0	0.057

gene	mutation Number	Mutation (%)	Saito band	type of mutation				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II	Stage III+IV	Stage III+IV (%)
ITPRIP	5	1.1	10q25.1	0	5	0	0	0	5	100.0	0.091
KAL1	5	1.1	Xp22.31	3	2	0	0	0	5	100.0	0.091
KCNV1	5	1.1	8q23.2	One	4	0	0	0	5	100.0	0.091
KDM6A	14	3.1	Xp11.3	10	4	0	0	9	5	35.7	0.047
KIAA1109	6	1.3	4q27	One	5	0	0	One	5	83.3	0.264
KIAA1244	5	1.1	6q23.3-q24.1	0	5	0	0	0	5	100.0	0.091
KMT2D	36	7.8	12q13.12	18	17	One	0	6	30	83.3	0.006
KRTAP4-6	6	1.3	17q21.2	0	6	0	0	5	One	16.7	0.035
KRTAP4-7	5	1.1	17q21.2	0	5	0	0	0	5	100.0	0.091
KSR1	3	0.7	17q11.2	0	3	0	0	3	0	0.0	0.057
LCT	6	1.3	2q21.3	0	6	0	0	0	6	100.0	0.057
LRRC15	5	1.1	3q29	0	5	0	0	0	5	100.0	0.091
LRRC66	5	1.1	4q12	One	4	0	0	0	5	100.0	0.091
LTBP1	5	1.1	2p22.3	One	4	0	0	0	5	100.0	0.091
MAP1A	5	1.1	15q15.3	One	4	0	0	0	5	100.0	0.091

gene	mutation Number	Mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II	Stage III+IV	Stage III+IV (%)
MDN1	9	2.0	6q15	0	9	0	0	One	8	88.9	0.088
MGAT4C	3	0.7	12q21.31-q21.32	0	3	0	0	3	0	0.0	0.057
MT-CO1	3	0.7	NA	One	2	0	0	3	0	0.0	0.057
MUC2	6	1.3	11p15.5	0	6	0	0	0	6	100.0	0.057
MYH11	7	1.5	16p13.11	One	6	0	0	0	7	100.0	0.035
MYOT	5	1.1	5q31.2	0	5	0	0	0	5	100.0	0.091
NALCN	12	2.6	13q32.3-q33.1	0	12	0	0	One	11	91.7	0.027
NIPBL	7	1.5	5p13.2	0	7	0	0	0	7	100.0	0.035
NLRP4	5	1.1	19q13.43	0	5	0	0	0	5	100.0	0.091
NOS1	3	0.7	12q24.22	0	3	0	0	3	0	0.0	0.057
NRXN3	8	1.7	14q24.3-q31.1	0	8	0	0	0	8	100.0	0.022
NTRK1	9	2.0	1q23.1	0	8	One	0	0	9	100.0	0.014
NUTM2F	3	0.7	9q22.32	0	0	3	0	3	0	0.0	0.057
PCDH11X	5	1.1	Xq21.31	0	5	0	0	0	5	100.0	0.091
PCDHA7	4	0.9	5q31.3	0	4	0	0	3	One	25.0	0.162

gene	number of mutations	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II	Stage III+IV	Stage III+IV (%)
PCDHA8	6	1.3	5q31.3	One	5	0	0	0	6	100.0	0.057
PIK3CD	5	1.1	1p36.22	One	4	0	0	0	5	100.0	0.091
POM121L12	6	1.3	7p12.1	0	6	0	0	0	6	100.0	0.057
PPP2R2B	4	0.9	5q32	One	3	0	0	3	0	0.0	0.162
PRRC2C	3	0.7	1q24.3	One	2	0	0	3	0	0.0	0.057
RBP3	4	0.9	10q11.22	0	4	0	0	4	0	0.0	0.022
RP1	16	3.5	8q11.23-q12.1	One	15	0	0	11	5	31.3	0.015
SECISBP2L	3	0.7	15q21.1	0	3	0	0	3	0	0.0	0.057
SHROOM3	3	0.7	4q21.1	One	2	0	0	3	0	0.0	0.057
SIGLEC1	8	1.7	20p13	One	7	0	0	0	8	100.0	0.022
SMC2	5	1.1	9q31.1	0	5	0	0	0	5	100.0	0.091
SMG7	8	1.7	1q25.3	4	4	0	0	One	7	87.5	0.128
SORCS2	3	0.7	4p16.1	0	3	0	0	3	0	0.0	0.057
SPTA1	28	6.1	1q23.1	3	25	0	0	3	23	88.5	0.002
STRC	5	1.1	15q15.3	2	3	0	0	0	5	100.0	0.091

gene	number of mutations	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II	Stage III+IV	Stage III+IV (%)
TACC2	6	1.3	10q26.13	One	5	0	0	0	6	100.0	0.057
TAF1D	4	0.9	11q21	2	2	0	0	3	0	0.0	0.162
TBXA2R	5	1.1	19p13.3	2	3	0	0	0	5	100.0	0.091
TENM2	10	2.2	5q34	One	9	0	0	One	9	90.0	0.06
TGM6	5	1.1	20p13	0	5	0	0	0	5	100.0	0.091
TMEM184A	5	1.1	7p22.3	One	One	3	0	0	5	100.0	0.091
TMPRSS2	5	1.1	21q22.3	2	2	One	0	5	0	0.0	0.009
TNS1	6	1.3	2q35	0	6	0	0	One	5	83.3	0.264
TP53	64	13.9	17p13.1	18	46	0	0	11	52	82.5	0.001
TP53BP1	10	2.2	15q15.3	5	5	0	0	One	9	90.0	0.06
TPTE2	8	1.7	13q12.11	2	6	0	0	6	2	25.0	0.042
TRIOBP	9	2.0	22q13.1	5	4	0	0	0	9	100.0	0.014
UACA	8	1.7	15q23	0	8	0	0	One	6	85.7	0.128
UTP20	6	1.3	12q23.2	One	5	0	0	0	6	100.0	0.057
VPS13C	7	1.5	15q22.2	0	6	One	0	One	6	85.7	0.185

gene	number of mutations	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II	Stage III+IV	Stage III+IV (%)
ZMYM3	13	2.8	Xq13.1	7	6	0	0	One	12	92.3	0.018
ZNF208	13	2.8	19p12	One	12	0	0	2	11	84.6	0.077
ZNF845	12	2.6	19q13.42	One	11	0	0	8	4	33.3	0.047
ZNF99	10	2.2	19p12	0	10	0	0	One	9	90.0	0.06

As a result of the analysis, in each pathology grade group, even if the gene had a mutation, there were genes with a P-value of 0.05 or higher compared to other groups, while genes with a mutation and a P-value of less than 0.05 were identified. Mutant genes with a P-value of less than 0.05 compared to other groups were selected as pathology grade-specific genes because they were correlated with a specific pathology grade group compared to other groups. For example, ZNF208 had a large total number of mutated patients, but the P-value was as high as 0.05 or higher, suggesting that there was no correlation between mutations in these genes and the pathology grade. 3 shows the results of analyzing the correlation between mutations in genes and pathology grades. As can be seen from Figure 3, ANKRD36C, GRIK3, KDM6A, KRTAP4-6, RBP3, TPTE2 and ZNF24 were found to have a higher number of patients with mutated genes in low pathology grade (II) than high pathology grade (III + IV). , ALMS1, ANK3, COL22A1, EP300, FHOD3, HSPG2, KMT2D, MYH11, NALCN, NIPBL, NRXN3, NTRK1, SIGLEC1, SPTA1, TP53, TRIOBP and ZMYM3 have higher pathology than low pathology class (Ⅱ) (Ⅲ + Ⅳ). It was confirmed that the number of patients with mutated genes in

From the above results, ANKRD36C, GRIK3, KDM6A, KRTAP4-6, RBP3, TPTE2, ZNF24, ALMS1, ANK3, COL22A1, EP300, FHOD3, HSPG2, KMT2D, MYH11, NALCN, NIPBL, NRXN3, NTRK1, SPTA1, TP53, NTRK1, TP It can be seen that TRIOBP and ZMYM3 mutations can be used as specific markers before and after stage II.

2-3. Comparative analysis before and after Stage Ⅲ (Test set 3 - Stage Ⅱ+ Ⅲ vs Ⅳ)

Among the three pathology grade groups divided by group in Table 2, for pathology grade II + III and pathology grade IV, the association between the occurrence of mutations in candidate genes and the pathology grade of prostate cancer patients was confirmed. A P-value of less than 0.05 was considered statistically significant. Tables 13 to 18 below show information of candidate genes related to test set 3.

gene	mutation Number	Mutation (%)	Saito band	type of mutation				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II+III	Stage IV	Stage IV (%)
ACY3	One	0.2	11q13.2	0	One	0	0	0	One	100.0	0.022
ADA	One	0.2	20q13.12	0	One	0	0	0	One	100.0	0.022
AGPAT2	One	0.2	9q34.3	0	One	0	0	0	One	100.0	0.022
AOC1	One	0.2	7q36.1	0	One	0	0	0	One	100.0	0.022
APOBEC2	One	0.2	6p21.1	One	0	0	0	0	One	100.0	0.022
ARHGAP39	One	0.2	8q24.3	0	One	0	0	0	One	100.0	0.022
ARHGEF28	One	0.2	5q13.2	One	0	0	0	0	One	100.0	0.022
BPIFB2	One	0.2	20q11.21	0	One	0	0	0	One	100.0	0.022
C19orf26	One	0.2	19p13.3	0	One	0	0	0	One	100.0	0.022
C8orf74	2	0.4	8p23.1	0	2	0	0	0	One	100.0	0.022
CD40	One	0.2	20q13.12	0	One	0	0	0	One	100.0	0.022
CDK2AP2	One	0.2	11q13.2	One	0	0	0	0	One	100.0	0.022
CEP97	One	0.2	3q12.3	0	One	0	0	0	One	100.0	0.022
CHP2	One	0.2	16p12.2	0	One	0	0	0	One	100.0	0.022
CLASRP	4	0.8	19q13.32	0	One	3	0	2	2	50.0	0.003

gene	mutation Number	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II+III	Stage IV	Stage IV (%)
CLDN12	One	0.2	7q21.13	0	One	0	0	0	One	100.0	0.022
CPT1A	2	0.4	11q13.3	0	2	0	0	0	One	100.0	0.022
DAK	One	0.2	11q12.2	One	0	0	0	0	One	100.0	0.022
DAPP1	One	0.2	4q23	0	One	0	0	0	One	100.0	0.022
DDX39A	One	0.2	20p13	0	One	0	0	0	One	100.0	0.022
DDX39A	One	0.2	19p13.12	0	One	0	0	0	One	100.0	0.022
DYNC2H1	One	0.2	11q22.3	0	One	0	0	0	One	100.0	0.022
E2F8	One	0.2	11p15.1	0	One	0	0	0	One	100.0	0.022
EDA	One	0.2	Xq13.1	0	One	0	0	0	One	100.0	0.022
FAM78B	One	0.2	1q24.1	0	One	0	0	0	One	100.0	0.022
FBXL4	One	0.2	6q16.1-q16.2	0	One	0	0	0	One	100.0	0.022
GALT	One	0.2	9p13.3	0	One	0	0	0	One	100.0	0.022
GEMIN2	2	0.4	14q21.1	2	0	0	0	One	One	50.0	0.044
GLP2R	One	0.2	17p13.1	0	One	0	0	0	One	100.0	0.022
GSTM3	One	0.2	1p13.3	0	One	0	0	0	One	100.0	0.022

gene	mutation Number	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II+III	Stage IV	Stage IV (%)
HDHD3	One	0.2	9q32	0	One	0	0	0	One	100.0	0.022
HEXIM1	One	0.2	17q21.31	0	0	One	0	0	One	100.0	0.022
HNRNPA1	One	0.2	12q13.13	0	One	0	0	0	One	100.0	0.022
HS6ST2	One	0.2	Xq26.2	One	0	0	0	0	One	100.0	0.022
HSD17B2	One	0.2	16q23.3	0	One	0	0	0	One	100.0	0.022
HSPBP1	One	0.2	19q13.42	0	One	0	0	0	One	100.0	0.022
ICAM1	2	0.4	19p13.2	0	2	0	0	0	One	100.0	0.022
IPO4	2	0.4	14q12	2	0	0	0	0	One	100.0	0.022
ISCU	One	0.2	12q23.3	0	One	0	0	0	One	100.0	0.022
JMJD4	One	0.2	1q42.13	0	One	0	0	0	One	100.0	0.022
KIFAP3	2	0.4	1q24.2	2	0	0	0	0	One	100.0	0.022
KLK2	One	0.2	19q13.33	One	0	0	0	0	One	100.0	0.022
LRRC17	One	0.2	7q22.1	0	One	0	0	0	One	100.0	0.022
MACC1	One	0.2	7p21.1	0	One	0	0	0	One	100.0	0.022
MELK	One	0.2	9p13.2	0	One	0	0	0	One	100.0	0.022

gene	mutation Number	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II+III	Stage IV	Stage IV (%)
MT-CO2	One	0.2	NA	0	One	0	0	0	One	100.0	0.022
NANOS1	One	0.2	10q26.11	0	0	One	0	0	One	100.0	0.022
NAT2	2	0.4	8p22	0	2	0	0	0	One	100.0	0.022
NBL1	One	0.2	1p36.13	One	0	0	0	0	One	100.0	0.022
NFIX	One	0.2	19p13.13	0	One	0	0	0	One	100.0	0.022
NUMB	One	0.2	14q24.2-q24.3	0	One	0	0	0	One	100.0	0.022
OR10H2	2	0.4	19p13.12	0	2	0	0	One	One	50.0	0.044
OR52J3	2	0.4	11p15.4	0	2	0	0	One	One	50.0	0.044
PAX6	One	0.2	11p13	One	0	0	0	0	One	100.0	0.022
PLIN4	2	0.4	19p13.3	0	2	0	0	0	One	100.0	0.022
PLRG1	One	0.2	4q31.3	0	One	0	0	0	One	100.0	0.022
PRKAG3	One	0.2	2q35	0	One	0	0	0	One	100.0	0.022
PTER	One	0.2	10p13	0	One	0	0	0	One	100.0	0.022
PTPLA	One	0.2	10p12.33	One	0	0	0	0	One	100.0	0.022
RAB8B	One	0.2	15q22.2	0	One	0	0	0	One	100.0	0.022

gene	mutation Number	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II+III	Stage IV	Stage IV (%)
RASL10A	One	0.2	22q12.2	0	One	0	0	0	One	100.0	0.022
RPS4Y2	One	0.2	Yq11.223	0	One	0	0	0	One	100.0	0.022
RWDD2A	One	0.2	6q14.1	0	One	0	0	0	One	100.0	0.022
S100A7L2	One	0.2	1q21.3	0	One	0	0	0	One	100.0	0.022
SCAMP1	One	0.2	5q14.1	One	0	0	0	0	One	100.0	0.022
SCRIB	2	0.4	8q24.3	0	2	0	0	0	One	100.0	0.022
SHC4	One	0.2	15q21.1	0	One	0	0	0	One	100.0	0.022
SLC2A12	One	0.2	6q23.2	0	One	0	0	0	One	100.0	0.022
SOD3	One	0.2	4p15.2	0	One	0	0	0	One	100.0	0.022
ST6GALNAC1	One	0.2	17q25.1	0	One	0	0	0	One	100.0	0.022
STMN2	One	0.2	8q21.13	0	One	0	0	0	One	100.0	0.022
STRN3	3	0.6	14q12	0	3	0	0	One	One	50.0	0.044
TAB2	One	0.2	6q25.1	0	One	0	0	0	One	100.0	0.022
TFPT	One	0.2	19q13.42	0	One	0	0	0	One	100.0	0.022
TNFAIP3	One	0.2	6q23.3	0	One	0	0	0	One	100.0	0.022

gene	mutation Number	mutation (%)	Saito band	Mutation type				pathology grade			Fisher's exact (P-Value)
				cut	missense	in-frame	Etc	Stage II+III	Stage IV	Stage IV (%)
TPX2	One	0.2	20q11.21	One	0	0	0	0	One	100.0	0.022
TROAP	One	0.2	12q13.12	0	One	0	0	0	One	100.0	0.022
TSHR	One	0.2	14q31.1	0	One	0	0	0	One	100.0	0.022
UBL7	One	0.2	15q24.1	One	0	0	0	0	One	100.0	0.022
ZNF24	One	0.2	18q12.2	0	One	0	0	0	One	100.0	0.022

As a result of analysis, when comparing between groups, ACY3, ADA, AGPAT2, AOC1, APOBEC2, ARHGAP39, ARHGEF28, BPIFB2, C19orf26, C8orf74, CD40, CDK2AP2, CEP97, CHP2, CLASRP, CLDN12, CPT1A, DDX39A, DAPP1, DDX39A, DAPP1, DYNC2H1, E2F8, EDA, FAM78B, FBXL4, GALT, GEMIN2, GLP2R, GSTM3, HDHD3, HEXIM1, HNRNPA1, HS6ST2, HSD17B2, HSPBP1, HSPG2, ICAM1, IPO, KLK2, LRRC17K, MACC1, KELIFAP, JMJD4, MELIFAP MT-CO2, NANOS1, NAT2, NBL1, NFIX, NUMB, OR10H2, OR52J3, PAX6, PLIN4, PLRG1, PRKAG3, PTER, PTPLA, RAB8B, RASL10A, RPS4Y2, RWDD2A, S100A7L2, SCOD3, SCRIB, SLC2, SCRIB ST6GALNAC1, STMN2, STRN3, TAB2, TFPT, TNFAIP3, TPX2, TROAP, TSHR, UBL7, and ZNF24 had a P-value of less than 0.05, which was confirmed to correlate with the mutagenesis of these genes and their pathology grade. Shows the results of analyzing the correlation between gene mutations and pathology grades. 4, CLASRP, GEMININ2, OR10H2, OR52J3, STRN3, ACY3, ADA, AGPAT2, AOC1, APOBEC2, ARHGAP39, ARHGEF28, BPIFB2, C19orf26, C8orf74, CD40, CDK2AP2, CEPDN12, CHP2, DAK, CEP97, CHP2 DAPP1, DDX39A, DDX39A, DYNC2H1, E2F8, EDA, FAM78B, FBXL4, GALT, GLP2R, GSTM3, HDHD3, HEXIM1, HNRNPA1, HS6ST2, HSD17B2, HSPBP1, HSPG2, KSPBP1, HSPG2, ICAM3, JIPOMJD IS CULR, JIPOMJD IS CULR, JIPOMJ MACC1, MELK, MT-CO2, NANOS1, NAT2, NBL1, NFIX, NUMB, PAX6, PLIN4, PLRG1, PRKAG3, PTER, PTPLA, RAB8B, RASL10A, RPS4Y2, RWDD2A, S100A7L2, SCAMP1, SCRIB, SHCAMP1, SCRIB ST6GALNAC1, STMN2, TAB2, TFPT, TNFAIP3, TPX2, TROAP, TSHR, UBL7, and ZNF24 were identified in a large number of patients with mutated genes in pathology grade IV.

From the above results, ARHGAP39, ARHGEF28, BPIFB2, C19orf26, C8orf74, CD40, CDK2AP2, CEP97, CHP2, CLDN12, CPT1A, DAK, DAPP1, DDX39A, DDX39A, DYNC2H1, E2F8, EDA, FGSTM78B, GLP2R, FBXL4, GALT, FB HDHD3, HEXIM1, HNRNPA1, HS6ST2, HSD17B2, HSPBP1, HSPG2, ICAM1, IPO4, ISCU, JMJD4, KIFAP3, KLK2, LRRC17, MACC1, MELK, MT-CO2, NANOS1, PNFIX, NBL1, PNFIX, NBL1, NFIX Mutations of PLRG1, PRKAG3, PTER, PTPLA, RAB8B, RASL10A, RPS4Y2, RWDD2A, S100A7L2, SCAMP1, SCRIB, SHC4, SLC2A12, SOD3, ST6GALNAC1, STMN2, TBLAB2, TSTFPT, TNFAIP3, TPXHR, UBL7, TROAP It can be seen that can be used as a specific marker for the distinction between pathology grades II + Ⅲ and pathology grade IV.

Example 3. Confirmation of availability as a survival-specific marker according to pathology grade

Among the candidate genes of Example 1, it was confirmed whether there was a survival-specific mutant gene. The 498 target patients obtained in Example 1 were classified into surviving patients (488 patients) and deceased patients (10 patients), and based on the clinical information (event (death or recurrence), observation time) obtained in Example 1 Overall survival kaplan-meier estimate and disease free survival kaplan-meier estimate were obtained using the Kaplan Meier survival assay (Spss 21). In the total survival period, death was determined as an event, and in the disease-free survival period, prostate cancer recurrence was determined as an event. In order to determine whether the occurrence of mutations in each of the above genes is correlated with the death or recurrence of prostate cancer in patients with recurrent prostate cancer, the event time (event time) for each group obtained in the Kaplan Meier survival assay time), the association between the occurrence of mutations and the total survival period, and the association between the occurrence of mutations and the disease-free survival period were confirmed by a log rank test. A P-value of less than 0.05 was considered statistically significant. The experimental group was the case with alterations in query gene, and the control group was the case without alterations in query gene. The median months survival means a value located at the center when the survival period of patients in the corresponding group is listed. The median disease-free survival period (median months desease free) means a value located at the center when the survival period of patients in the relevant group is listed. The slope in the survival curve by the Kaplan Meier survival assay is determined by the duration of survival.

In order to determine whether the occurrence of mutations in each of the candidate genes is associated with the survival rate of prostate cancer patients with known pathology (null hypothesis), the prognosis of 498 prostate cancer patients obtained in Example 1 was analyzed.

3-1. Comparative analysis between each pathology grade (Test set 1 - Stage Ⅱ vs Ⅲ vs Ⅳ)

For each of the three pathological grade groups divided by group in Table 2, the correlation between the occurrence of mutations in candidate genes and the survival rate of prostate cancer patients of a specific pathological grade was confirmed. A P-value of less than 0.05 was considered statistically significant. Table 19 shows the P-values of total survival and disease-free survival between pathological grades.

gene	total survival	disease free survival
ACY3	0.9	0.0004
C8orf74	0.852	7.77E-16
CPT1A	0.852	7.77E-16
DDX39A	0.852	7.77E-16
FBXL4	0.9	0.0004
ICAM1	0.852	7.77E-16
IPO4	0.852	7.77E-16
KIFAP3	0.852	7.77E-16
SOD3	0.9	0.0004
ZNF24	0.9	0.0004

As shown in FIGS. 5 to 14 , when comparing between groups, mutations in ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, IPO4, KIFAP3, SOD3 and ZNF24 genes showed the survival rate of the pathological grade IV group among prostate cancer patients. Since the probability that the null hypothesis is correct is 99.5% or more, that is, the probability that the null hypothesis is false is less than 0.5%, It can be seen that there is a correlation between the occurrence of mutations and the survival rate of patients with pathological grade IV among prostate cancer patients3-2. Comparative analysis before and after Stage Ⅱ (Test set 2 - Stage Ⅱ vs Ⅲ + Ⅳ)

For each of the three pathological grade groups divided by group in Table 2, the correlation between the occurrence of mutations in candidate genes and the survival rate of prostate cancer patients of a specific pathological grade was confirmed. A P-value of less than 0.05 was considered statistically significant. Table 20 shows the P-values of total survival and disease-free survival before and after Stage II.

gene	total survival	disease free survival
ALMS1	0.077	0.01
COL22A1	0.028	0.469
FHOD3	0.0045	0.0507
MYH11	0.015	0.00035
NRXN3	0.707	0.019
NTRK1	0.823	0.031
TP53	0.313	0.0018
TRIOBP	0.744	0.045

15 to 22 , when comparing between groups, mutations in ALMS1, COL22A1, FHOD3, MYH11, NRXN3, NTRK1, TP53, and TRIOBP genes are correlated with the survival rate of pathological grade III + IV group among prostate cancer patients. Mutations in ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, IPO4, KIFAP3, SOD3 and ZNF24 genes occur because the probability that the null hypothesis of It can be seen that there is a correlation with the survival rate of patients with pathological grade Ⅲ + Ⅳ among prostate cancer patients.3-3. Comparative analysis before and after Stage Ⅲ (Test set 3 - Stage Ⅱ + Ⅲ vs Ⅳ)

For each of the three pathological grade groups divided by group in Table 2, the correlation between the occurrence of mutations in candidate genes and the survival rate of prostate cancer patients of a specific pathological grade was confirmed. A P-value of less than 0.05 was considered statistically significant. Table 21 shows the P-values of total survival and disease-free survival before and after Stage III.

gene	total survival	disease free survival
ACY3	0.9	0.0004
C8orf74	0.852	7.77E-16
CPT1A	0.852	7.77E-16
DDX39A	0.852	7.77E-16
FBXL4	0.9	0.0004
ICAM1	0.852	7.77E-16
IPO4	0.852	7.77E-16
KIFAP3	0.852	7.77E-16
NAT2	0.852	7.77E-16
NFIX	0.852	7.77E-16
PLIN4	0.852	7.77E-16
SCRIB	0.852	7.77E-16
SHC4	0.852	7.77E-16
SOD3	0.9	0.0004
STRN3	0.791	0.00015
ZNF24	0.9	0.00042

As shown in FIGS. 23 to 28, when comparing between groups, the null hypothesis that mutations in NAT2, NFIX, PLIN4, SCRIB, SHC4, and STRN3 genes are associated with the survival rate of the pathological grade IV group among prostate cancer patients Since the probability of being correct is more than 99.5%, that is, the probability that the null hypothesis is incorrect is less than 0.5%, mutations in NAT2, NFIX, PLIN4, SCRIB, SHC4 and STRN3 genes and the survival rate of patients with pathological grade IV among prostate cancer patients and It can be seen that there is a correlation.3-4. Disease-free survival-specific genes

Among the candidate genes of Example 1, with respect to the genes identified in Examples 3-1, 3-2 and 3-3 as survival-specific mutant genes, ACY3, ALMS1, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, IPO4, KIFAP3, NAT2, NFIX, NRXN3, NTRK1, PLIN4, SCRIB, SHC4, SOD3, STRN3, TP53, TRIOBP and ZNF24 were identified. The corresponding results for each gene are shown below.

As can be seen from FIG. 5 , ACY3 in the case of prostate cancer patients in which the mutation in the ACY3 gene does not occur, more than 50% survive for more than 80 months (blue), whereas in the case of prostate cancer patients in which the mutation in the ACY3 gene occurs, Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the ACY3 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 6 , in the case of C8orf74 gene mutation, more than 50% of patients with prostate cancer in which the C8orf74 gene survived for more than 80 months (blue), whereas the C8orf74 gene mutation occurred in prostate cancer patients Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the C8orf74 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen in FIG. 7 , CPT1A in the case of prostate cancer patients in which the CPT1A gene mutation did not occur, 50% or more survived for more than 80 months (blue), whereas the CPT1A gene mutation occurred in prostate cancer patients. Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the CPT1A gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 8, DDX39A survives more than 50% of patients with prostate cancer in which the CPT1A gene is not mutated (blue), whereas prostate cancer patients in which the mutation in the DDX39A gene survives. Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the DDX39A gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 9 , FBXL4 survives more than 50% of patients with prostate cancer in which the FBXL4 gene is not mutated for more than 80 months (blue), whereas the FBXL4 gene mutation in prostate cancer patients Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the FBXL4 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 10 , ICAM1 in the case of prostate cancer patients in which the ICAM1 gene mutation did not occur, 50% or more survived for more than 80 months (blue), whereas the ICAM1 gene mutation occurred in the prostate cancer patients Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the ICAM1 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 11 , IPO4 in the case of prostate cancer patients in which the mutation in the IPO4 gene did not occur, 50% or more survived for more than 80 months (blue), whereas in the case of prostate cancer patients in which the mutation in the IPO4 gene was generated, Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the IPO4 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 12 , KIFAP3 in the case of prostate cancer patients in which the mutation in the KIFAP3 gene did not occur, 50% or more survived for more than 80 months (blue), whereas in the case of prostate cancer patients in which the mutation in the KIFAP3 gene was generated, Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the KIFAP3 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 13, SOD3 is a prostate cancer patient with a mutation in the SOD3 gene, whereas 50% or more of the prostate cancer patients with no mutation in the SOD3 gene survive for more than 80 months (blue). Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the SOD3 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 14 , ZNF24 is a prostate cancer patient with a mutation in the ZNF24 gene, whereas 50% or more of the prostate cancer patients in which the ZNF24 gene mutation does not occur survive for more than 80 months (blue). Since more than 50% of prostate cancer patients died before 20 months of age, it was confirmed that the survival rate was lower than that of non-mutagenic prostate cancer patients (red). Therefore, if there is a mutation in the ZNF24 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 15 , in ALMS1, more than 50% of prostate cancer patients in which the ALMS1 gene mutation did not occur survived for more than 80 months (blue), whereas the ALMS1 gene mutation in the prostate cancer patients Since more than 50% of prostate cancer patients died before 20 months of age, it was confirmed that the survival rate was lower than that of non-mutagenic prostate cancer patients (red). Therefore, if there is a mutation in the ALMS1 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen in FIG. 19 , in the case of prostate cancer patients in which the NRXN3 gene mutation does not occur, NRXN3 survives for more than 80 months (blue), whereas the NRXN3 gene mutation occurs in prostate cancer patients. Since more than 50% of prostate cancer patients died before 30 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the NRXN3 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 20, NTRK1 is more than 50% of patients with prostate cancer in which the NTRK1 gene is not mutated survive for more than 80 months (blue), whereas the NTRK1 gene mutation in prostate cancer patients is Since more than 50% of prostate cancer patients died before 20 months of age, it was confirmed that the survival rate was lower than that of non-mutagenic prostate cancer patients (red). Therefore, if there is a mutation in the NTRK1 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 21 , TP53 in the case of prostate cancer patients in which the mutation in the TP53 gene did not occur, 50% or more survived for more than 80 months (blue), whereas in the case of prostate cancer patients in which the mutation in the TP53 gene occurred, Since more than 50% of prostate cancer patients died before 60 months of age, it was confirmed that the survival rate was lower than that of prostate cancer patients without mutation (red). Therefore, if there is a mutation in the TP53 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

TRIOBP, as can be seen in FIG. 22, in the case of prostate cancer patients in which the TRIOBP gene mutation does not occur, 50% or more survives for more than 80 months (blue), whereas the TRIOBP gene mutation occurs in prostate cancer patients Since more than 50% of prostate cancer patients died before 30 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the TRIOBP gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen in FIG. 23, NAT2 is a prostate cancer patient with a mutation in the NAT2 gene, whereas 50% or more of the prostate cancer patients in which the NAT2 gene mutation does not occur survive for more than 80 months (blue). Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the NAT2 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death due to prostate cancer increases. can

NFIX, as can be seen in FIG. 24, in the case of prostate cancer patients in which the mutation in the NFIX gene does not occur, more than 50% survive for more than 80 months (blue), whereas the prostate cancer patients in which the mutation in the NFIX gene occurs Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the NFIX gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 25 , PLIN4 in the case of prostate cancer patients in which the mutation in the PLIN4 gene did not occur, 50% or more survived for more than 80 months (blue), whereas in the case of prostate cancer patients in which the mutation in the PLIN4 gene was generated, Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the PLIN4 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death due to prostate cancer increases. can

As can be seen from FIG. 26 , in SCRIB, more than 50% of prostate cancer patients in which the SCRIB gene mutation did not occur survived for more than 80 months (blue), whereas the prostate cancer patients in which the SCRIB gene mutation occurred were Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the SCRIB gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

As can be seen from FIG. 27 , in the case of prostate cancer patients in which the SHC4 gene is not mutated, 50% or more survived over 80 months (blue), whereas in the case of prostate cancer patients in which the SHC4 gene is mutated, the SHC4 gene is mutated. Since more than 50% of prostate cancer patients died before 10 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the SHC4 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. Able to know.

As can be seen from FIG. 28, STRN3 is a prostate cancer patient with a mutation in the STRN3 gene, whereas 50% or more of the patients with prostate cancer in which the mutation in the STRN3 gene has not occurred survive for more than 80 months (blue). Since more than 50% of prostate cancer patients died before 40 months of age, it was confirmed that the survival rate was lower than that of non-mutated prostate cancer patients (red). Therefore, if there is a mutation in the STRN3 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death from prostate cancer increases. can

3-5. Genes specific for total survival and disease-free survival

MYH11 was identified as a gene specific for total survival and disease-free survival. The results corresponding to the following are shown.

As can be seen from (A) of FIG. 18 , in the case of prostate cancer patients in which the MYH11 gene is not mutated, 50% or more of MYH11 survived for more than 100 months (blue), whereas the MYH11 gene was mutated. Since more than 50% of prostate cancer patients died before the age of 80 months, it was confirmed that the survival rate of prostate cancer patients was lower than that of prostate cancer patients without mutation (red). According to (B) of FIG. 18 , in the case of prostate cancer patients in which the MYH11 gene mutation did not occur, more than 50% of the patients had no recurrence for more than 80 months (blue). Prostate cancer was found to recur in more than 50% of patients (red). Therefore, if there is a mutation in the MYH11 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death or recurrence due to prostate cancer increases. It can be seen that it is significant as a predictive marker.

3-6. Total Survival Specific Genes

COL22A1 and FHOD3 were identified as total survival-specific genes. The results are shown below.

As can be seen from (A) of FIG. 16, COL22A1 survived more than 50% of patients with prostate cancer in which the COL22A1 gene did not occur for more than 160 months (blue), whereas the COL22A1 gene had a mutation. Since more than 50% of prostate cancer patients died before the age of 120 months, it was confirmed that the survival rate of prostate cancer patients was lower than that of prostate cancer patients without mutation (red). According to FIG. 16 (B), in the case of prostate cancer patients in which the COL22A1 gene mutation did not occur, more than 50% of the patients had no recurrence for more than 160 months (blue). Prostate cancer was found to recur in more than 50% of patients (red). Therefore, if there is a mutation in the COL22A1 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death or recurrence due to prostate cancer increases. It can be seen that it is significant as a predictive marker.

As can be seen from (A) of FIG. 17 , in the case of prostate cancer patients in which the FHOD3 gene is not mutated, 50% or more of FHOD3 survived for more than 120 months (blue), whereas the FHOD3 gene was mutated. Since more than 50% of prostate cancer patients died before the age of 60 months, it was confirmed that the survival rate of prostate cancer patients was lower than that of prostate cancer patients without mutation (red). According to (B) of Figure 17, in the case of prostate cancer patients in which the mutation in the FHOD3 gene did not occur, more than 50% of the patients had no recurrence for more than 80 months (blue), but if the FHOD3 gene had a mutation, it was less than 50 months, so prostate cancer patients Prostate cancer was found to recur in more than 50% of patients (red). Therefore, if there is a mutation in the FHOD3 gene and the pathology grade of the prostate cancer patient is group IV, the probability of death or recurrence due to prostate cancer increases. It can be seen that it is significant as a predictive marker. Through the above results, ACY3, ALMS1, C8orf74, COL22A1, CPT1A, DDX39A, FBXL4, FHOD3, ICAM1, IPO4, KIFAP3, MYH11, NAT2, NFIX, NRXN3, NTRK1, PLIN4, SCRIB, SHC4, SOD3, STRN3, SOD3, STRN3 If there is a mutation in any one gene selected from the group consisting of ZNF24, it can be seen that the survival rate of patients with recurrent prostate cancer is significantly lowered or the recurrence rate is increased. In contrast, it can be seen that the prognosis of prostate cancer, particularly survival or recurrence, can be predicted.

In the above, preferred embodiments of the present invention have been exemplarily described, but the scope of the present invention is not limited to the specific embodiments as described above, and those of ordinary skill in the art will It will be possible to change it appropriately.

Mutations of genes encoding ALMS1, NRXN3, NTRK1 and TRIOBP, which are the mutant genes discovered in the present invention, or COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, Since the mutation of at least one gene selected from the gene group consisting of NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD3, STRN3, TP53 and ZNF24 and the pathology grade of prostate cancer patients are related, by checking whether the gene is mutated It is possible to predict the difference in prostate cancer treatment effect, survival rate, and recurrence rate according to the pathology grade of prostate cancer patients. Therefore, the mutant genes can be widely used in fields related to the establishment of a diagnosis and treatment strategy for prostate cancer.

Claims (11)

1. A composition for predicting treatment effect or prognostic diagnosis according to the pathological grade of a prostate cancer patient, comprising an agent capable of detecting mutations in genes encoding ALMS1, NRXN3, NTRK1 and TRIOBP
2. The method of claim 1,

   The diagnostic composition is at least selected from the group consisting of COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD3, STRN3, TP53 and ZNF24. A composition for predicting treatment effect or prognosis diagnosis according to the pathology grade of a prostate cancer patient, further comprising an agent capable of detecting a mutation in a gene encoding one.
3. The method of claim 1,

   The mutation of the gene encoding ALMS1 is at least one missense mutation selected from the group consisting of T196A, P1387L, T2308M, A1618V and A1157V in the amino acid sequence of SEQ ID NO: 1, or a nonsense mutation that is Y2936*, or R4154Efs*40 an in frame shift insert (FS ins) mutation;

   The mutation of the gene encoding NRXN3 is at least one missense mutation selected from the group consisting of L309I, A228S, R654H, R654C, D166Y, A85T, D308A and F23I in the amino acid sequence of SEQ ID NO: 2;

   The mutation of the gene encoding NTRK1 is at least one missense mutation selected from the group consisting of R342Q, R507C, P63S, P695S, G714S, A612V, R574H and R599H in the amino acid sequence of SEQ ID NO: 3, or Q730_L731del in- an in-frame delete (IF del) mutation;

   The mutation of the gene encoding TRIOBP is at least one missense mutation selected from the group consisting of P1125L, S1252F, R2259H and Q702R in the amino acid sequence of SEQ ID NO: 4, or Q2245*, Q350*, R1554* and R448* at least one nonsense mutation selected from the group consisting of; A composition for predicting treatment effect or prognostic diagnosis according to the pathological grade of a prostate cancer patient.
4. 3. The method of claim 2,

   The mutation of the gene encoding COL22A1 is, in the amino acid sequence of SEQ ID NO: 5, at least one missense mutation selected from the group consisting of N1115D, R210W, T117M, G490D, L1427M and D1133G, R592*, a nonsense mutation, or K529Rfs *21 (diploid) and at least one of K529Rfs*21 (amp) is a frame shift delete (FS del) mutation;

   The mutation of the gene encoding FHOD3 is at least one missense mutation selected from the group consisting of T1328P, R188H, G120R, A1330T and A1051T in the amino acid sequence of SEQ ID NO: 6, or R461Afs*31 A frame shift deletion (frame shift) delete, FS del) mutation;

   The mutation of the gene encoding MYH11 is at least one missense mutation selected from the group consisting of A815T, E1888K, T975M, A732V, A1259V and A334V in the amino acid sequence of SEQ ID NO: 7, or a nonsense mutation that is R1609*;

   The mutation of the gene encoding ACY3 is a missense mutation of R233C in the amino acid sequence of SEQ ID NO: 8;

   The mutation of the gene encoding C8orf74 is a missense mutation that is A273T in the amino acid sequence of SEQ ID NO: 9;

   The mutation of the gene encoding CPT1A is a missense mutation that is A577V in the amino acid sequence of SEQ ID NO: 10;

   The mutation in the gene encoding DDX39A is a missense mutation that is A96V in the amino acid sequence of SEQ ID NO: 11;

   The mutation in the gene encoding FBXL4 is a missense mutation that is D550A in the amino acid sequence of SEQ ID NO: 12;

   The mutation of the gene encoding ICAM1 is a missense mutation of P63L in the amino acid sequence of SEQ ID NO: 13;

   The mutation in the gene encoding KIFAP3 is a nonsense mutation that is Q492* in the amino acid sequence of SEQ ID NO: 14;

   The mutation of the gene encoding IPO4 is a nonsense mutation that is R916* in the amino acid sequence of SEQ ID NO: 15;

   The mutation in the gene encoding NAT2 is a missense mutation that is L52F in the amino acid sequence of SEQ ID NO: 16;

   The mutation in the gene encoding NFIX is a missense mutation that is R343H in the amino acid sequence of SEQ ID NO: 17;

   The mutation of the gene encoding PLIN4 is a missense mutation that is A646T in the amino acid sequence of SEQ ID NO: 18;

   The mutation in the gene encoding SCRIB is a missense mutation that is P422S in the amino acid sequence of SEQ ID NO: 19;

   The mutation of the gene encoding SHC4 is a missense mutation of P80L in the amino acid sequence of SEQ ID NO: 20;

   The mutation of the gene encoding SOD3 is a missense mutation of D54N in the amino acid sequence of SEQ ID NO: 21;

   The mutation in the gene encoding STRN3 is a missense mutation that is at least one of L206I and L792I in the amino acid sequence of SEQ ID NO: 22;

   The mutation of the gene encoding TP53 is, in the amino acid sequence of SEQ ID NO: 23, R273C, R248Q, E285K, R282W, R248W, R175H, G245D, H193R, M237I, G245S, C135F, C135Y, C135W, V157F, R181C, Y163H, V173M , at least one missense mutation selected from the group consisting of N239D, R337C, R249G, C176R, C141G, E271V, H193N, G266V, G279E, P177R, G199V, T256I, A74T and P82L, or at least one of R342* and E298* a nonsense mutation, or a frame shift insert (FS ins) mutation that is at least one of Q165Hfs*17 and C124Wfs*25, or A86Vfs*55, R209Kfs*6, V203Wfs*44, K319Rfs*26, S90Ffs*53, At least one frame shift delete (FS del) mutation selected from the group consisting of S149Pfs*21 and Q144Gfs*24, or at least one selected from the group consisting of X126_splice, X307_splice, X33_splice, X331_splice, X126_splice and X126_splice splice mutation;

   The mutation of the gene encoding ZNF24 is a missense mutation of Y344C in the amino acid sequence of SEQ ID NO: 24; A composition for predicting treatment effect or prognostic diagnosis according to the pathological grade of a prostate cancer patient.
5. 3. The method of claim 1 or 2,

   Wherein the agent comprises a primer set, a probe or an antibody for the mutation of the gene, a composition for predicting treatment effect or prognosis diagnosis according to the pathological grade of a prostate cancer patient.
6. A kit for predicting treatment effect or prognosis diagnosis according to the pathological grade of a prostate cancer patient, comprising the composition of claim 1 or 2.
7. preparing sample DNA from a sample of a prostate cancer patient;

   amplifying the sample DNA using the kit of claim 6; and

   A method of providing information necessary for prognostic diagnosis of prostate cancer according to the pathology grade of a prostate cancer patient, comprising: confirming the presence or absence of a pathology grade-specific marker from the amplification result.
8. 8. The method of claim 7,

   The method is a method of predicting the overall survival rate or disease-free survival rate of a prostate cancer patient.
9. 9. The method of claim 8,

   A mutation is identified in the genes encoding ALMS1, NRXN3, NTRK1, and TRIOBP, and if the patient is a patient with prostate cancer, the survival rate of the prostate cancer patient is lower than that of a person in which the mutation is not identified in the gene, or The method further comprising; determining that the recurrence rate of prostate cancer is higher than the recurrence rate of prostate cancer in a person whose mutation is not confirmed in the gene.
10. 10. The method of claim 9,

    At least one selected from the group consisting of encoding at least one selected from the group consisting of COL22A1, FHOD3, MYH11, ACY3, C8orf74, CPT1A, DDX39A, FBXL4, ICAM1, KIFAP3, IPO4, NAT2, NFIX, PLIN4, SCRIB, SHC4, SOD3, STRN3, TP53 and ZNF24. When a mutation is identified in a gene, the survival rate of patients with prostate cancer is lower than that of a person whose mutation is not confirmed in the gene, or the recurrence rate of prostate cancer in the prostate cancer patient is the prostate of a person whose mutation is not identified in the gene. Method comprising further; determining that the cancer recurrence rate is higher than the.
11. The use of the composition of claim 1 for diagnosing prostate cancer, predicting the therapeutic effect according to the pathology grade, and diagnosing the prognosis.

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