WO2020101432A1 - Biomarker for predicting onset of hereditary ovarian cancer and use thereof - Google Patents

Abstract

The present invention relates to a biomarker for predicting the onset of hereditary ovarian cancer and a use thereof and, more particularly, to a marker composition for predicting the onset of hereditary ovarian cancer, a composition and kit for predicting the onset of hereditary ovarian cancer, and a method for providing information for predicting the onset of hereditary ovarian cancer. By measuring the mRNA or protein level of a biomarker gene according to the present invention, the onset of hereditary ovarian cancer accompanied by BRCA mutations can be predicted early, and the biomarker can be effectively used as a target for developing a therapeutic agent for hereditary ovarian cancer.

Description

Biomarker for predicting the development of hereditary ovarian cancer and use thereof

The present invention relates to a biomarker for predicting the development of hereditary ovarian cancer, and more specifically, a marker composition for predicting the development of hereditary ovarian cancer, a composition for predicting the development of hereditary ovarian cancer, and a kit for predicting the development, and hereditary ovarian cancer It relates to a method of predicting the outbreak of.

Ovarian cancer is a cancer that is the cause and death of teenagers in domestic women. More than 60% of ovarian cancer patients are diagnosed after the cancer has spread, and the 5-year survival rate is less than 30%. The symptoms of ovarian cancer are not clear, and it is ambiguous to recognize abdominal distension, indigestion, diarrhea, and constipation as symptoms of ovarian cancer. Also, most importantly, there is no effective method to detect ovarian cancer early. Thus, effective means for the prevention and early detection of ovarian cancer are important medical needs that have not yet been met.

About 25% of the most common types of ovarian cancer, high grade serous ovarian cancer, are associated with the BRCA1 gene. The BRCA1 gene is located on chromosome 17 and was first validated as a gene that increases the risk of developing breast and ovarian cancer, and BRCA2 is also reported to increase the risk of developing the carcinoma following BRCA1. The probability of developing ovarian cancer in people with the BRCA1 mutation reaches 44% before the age of 70, and the mutated BRCA gene may be inherited from the mother as well as from the father. It is known that approximately 10% of ovarian cancers are related to mutations in the BRCA1 and BRCA2 genes, and if there are mutations in these two genes, the incidence of ovarian cancer is increased by 10 times or more compared to normal people, and the recurrence rate of ovarian cancer is also increased. . In addition, among Korean ovarian cancer patients, BRCA1 (23.8%) and BRCA2 (25.7%) are reported to be accompanied by BRCA mutations regardless of family history (Choi et al. JGO. 2016).

However, despite this effect by the BRCA mutation, there is currently only a method for preventing ovarian cancer caused by preventive bilateral ovarian resection (risk-reducing salpingo-oophoerctomy; RRSO), and other methods have not yet been established. It is not. In women of childbearing age, “prophylactic bilateral ovarian resection” causes premature menopause, leading to a decline in quality of life, and the proportion of elderly women (birth> 35 years old) in Korea ranged from 11% in 1999 to 28.6% in 2009, 17.6% in 10 years. Is increasing, and among the carriers of BRCA1, there are fewer targets for RRSO to be implemented at an appropriate time. Accordingly, there is an urgent need to develop a method capable of preventing and preventing the development of ovarian cancer other than preventive ovarian resection (RRSO).

In a recent study related to breast cancer and BRCA genes, it was suggested that RANKL / RANK inhibitor (e.g. denosumab) may serve as a preventive drug for breast cancer in BRCA-positive subjects. Based on this, it is considered that it is necessary to develop a biomarker capable of predicting this even in hereditary ovarian cancer, and further develop a therapeutic agent for hereditary ovarian cancer using a target inhibitor of a selective biomarker as a treatment method other than preventive ovarian resection.

As described above, the present inventors predicted whether or not the onset of hereditary ovarian cancer accompanied by a BRCA gene mutation, and further tried to present a target for the development of a therapeutic agent for the disease, as a result, the BRCA mutation compared to a normal person with a BRCA mutation The present invention was completed by discovering 11 types of markers whose expression was significantly changed in patients with ovarian cancer, and verifying their effectiveness.

Accordingly, an object of the present invention is to provide a marker composition for predicting the development of hereditary ovarian cancer.

Another object of the present invention is to provide a composition for predicting the development of hereditary ovarian cancer and a kit for predicting the development of hereditary ovarian cancer comprising the composition.

In addition, another object of the present invention is to provide an information providing method for predicting the development of hereditary ovarian cancer.

However, the technical problem to be achieved by the present invention is not limited to the above-mentioned problems, and other problems that are not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the object of the present invention as described above, the present invention is ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth growth) factor beta-binding protein 1; NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323 , NM_001323518, NM_006744), SPARC (secreted protein acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052) SE F member 2; NM_000934, NM_001165920, NM_001165921), and THBS1 (Thrombospondin 1; NM_003246) at least one gene selected from the group or a protein encoding the gene, providing a marker composition for predicting the development of hereditary ovarian cancer do.

In addition, the present invention is ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth factor beta-binding protein 1; NM_000627, NM_001166264 , NM_001166265, NM_001166266, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323518, NM_006744), SPARC (secreted protein) acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052), SERPINF2 (serpin family F member 2; NM_000920, NM_000934, NM_000934, NM_000934, NM_000934, NM_000920 And a preparation for measuring the level of mRNA of one or more genes selected from the group consisting of THBS1 (Thrombospondin 1; NM_003246) or a protein encoded by the gene, and a composition for predicting the development of hereditary ovarian cancer, and the composition A kit for predicting the development of hereditary ovarian cancer is provided.

In one embodiment of the present invention, the hereditary ovarian cancer may be accompanied by mutation of the BRCA1 or BRCA2 gene.

In another embodiment of the present invention, the agent measuring the mRNA level of the gene may be a sense and antisense primer, or a probe that complementarily binds to the mRNA of the gene.

In another embodiment of the present invention, the agent measuring the protein level may be an antibody that specifically binds to a protein encoded by the gene.

In addition, the present invention is ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth factor beta-binding) in biological samples derived from a subject protein 1; NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323517, NM_001323517, NM_001323517 ), SPARC (secreted protein acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052), SERPINF2 (serpin family F member 2; NM_000934, NM_001165920, NM_001165921), and THBS1 (Thrombospondin 1; NM_003246), one or more genes selected from the group consisting of measuring the level of protein or the protein encoding the gene, for predicting the development of hereditary ovarian cancer Provides information provision method.

In one embodiment of the present invention, the subject may carry a mutation of the BRCA1 or BRCA2 gene.

In another embodiment of the present invention, when the mRNA level of one or more genes selected from the group consisting of RBP4, SERPINA5, SERPINC1 and SERPINF2 or the protein level encoded by the gene is reduced compared to a healthy normal control group, hereditary ovarian cancer develops It can be expected to do.

In another embodiment of the present invention, the mRNA of one or more genes selected from the group consisting of ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC and THBS1 or the protein level encoded by the gene is increased compared to a healthy normal control group. If present, it can be predicted that hereditary ovarian cancer will develop.

In another embodiment of the present invention, the mRNA expression level is in situ hybridization, polymerase chain reaction (PCR), reverse transcriptase chain reaction (RT-PCR), real-time polymerase chain reaction ( Real-time PCR), RNase protection assay (RNase protection assay; RPA), microarray (microarray) and Northern blotting (northern blotting) can be measured by one or more methods selected from the group consisting of.

In another embodiment of the present invention, the expression level of the protein is Western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme immunoassay (ELISA), immunoprecipitation ( One or more methods selected from the group consisting of immunoprecipitation, flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip. It can be measured through.

In the present invention, 11 types of biomarkers capable of predicting the development of hereditary ovarian cancer in a subject who has a BRCA gene mutation can be predicted early, and the BRCA mutation is measured by measuring the mRNA or protein level of the biomarker gene according to the present invention. It can be predicted early whether or not the onset of hereditary ovarian cancer is accompanied, it can be usefully used to develop a therapeutic agent for hereditary ovarian cancer by targeting the biomarker.

1A is an experimental scenario for discovering proteins whose expression is specifically changed in a BRCA gene mutant positive (BRCA +) ovarian cancer patient, in order to derive a candidate marker protein for predicting the development of hereditary ovarian cancer accompanied by a mutation in the BRCA gene. It is shown as a picture.

Figure 1b is a result of analyzing the differentially expressed protein with a volcano plot using plasma samples obtained from normal and ovarian cancer patients who are positive for BRCA mutations.

FIG. 1C shows the analysis of the functions of the proteins in the analysis of FIG. 1B through the network analysis of 19 proteins with reduced expression and 61 proteins with increased expression in the ovarian cancer patient.

Figure 1d is a BRCA mutation positive normal group (BRCA + subjects: HC), normal group (HC), BRCA mutation positive ovarian cancer patients (BRCA + subjects: OC), ovarian cancer patients (OC) significantly increased the number of proteins in each group The results are shown by comparing.

Figure 1e is a comparative analysis of the proteins identified in the four groups of Figure 1d, the results are shown in a van diagram, from which a specific expression of reduced or increased BRCA mutant-positive ovarian cancer patients only 24 kinds of proteins were derived Is the result.

Figure 2a is a group of nine proteins specifically reduced expression in patients with BRCA mutation-positive ovarian cancer, SERPINA5 and IGFBP5 for each of 4 groups (BRCA mutant negative normal group (HN), BRCA mutant positive normal group (HP) , BRCA mutation negative ovarian cancer patient group (ON), and BRCA mutation positive ovarian cancer patient group (OP) is the result of analyzing the statistical significance of the difference in protein expression level.

FIG. 2b analyzes the presence or absence of statistical significance for the difference in protein expression level between the same four groups in F2 and TFRC among the nine proteins whose expression was specifically decreased in BRCA mutant-positive ovarian cancer patients. Is the result.

Figure 2c analyzed the presence or absence of statistical significance for the difference in protein expression level between the same four groups in SELL and APOC3 among the nine proteins whose expression was specifically reduced in BRCA mutant-positive ovarian cancer patients. Is the result.

FIG. 2D analyzes the presence or absence of statistical significance for the difference in protein expression level between the same four groups as in FIG. 2A for each of SERPINF2 and SERPINC1 among nine proteins whose expression is specifically decreased in patients with BRCA mutant positive ovarian cancer. Is the result.

Figure 2e is a result of analyzing the presence or absence of statistical significance for the difference in protein expression level between the same four groups in FIG. 2a for RBP4 among nine proteins whose expression is specifically decreased in patients with BRCA mutant positive ovarian cancer.

Figure 3a is a group of 15 proteins specifically increased expression in patients with BRCA mutation-positive ovarian cancer, 4 groups for each of VNN1 and PPBP (BRCA mutation-negative normal group (HN), BRCA mutation-positive normal group (HP) , BRCA mutation negative ovarian cancer patient group (ON), and BRCA mutation positive ovarian cancer patient group (OP) is the result of analyzing the statistical significance of the difference in protein expression level.

Figure 3b analyzed the presence or absence of statistical significance for the difference in protein expression level between the same four groups as in Figure 3a for ALDOA and VWF among 15 types of proteins specifically increased expression in patients with BRCA mutant-positive ovarian cancer. Is the result.

FIG. 3c analyzes the presence or absence of statistical significance for differences in protein expression levels between the same four groups as in FIG. 3a for SERPINE1 and GPI, respectively, among 15 types of proteins specifically increased in BRCA mutant-positive ovarian cancer patients. Is the result.

FIG. 3D analyzes the presence or absence of statistical significance for the difference in protein expression level between the same four groups as in FIG. 3A for each of the 15 proteins specifically expressed in BRCA mutant-positive ovarian cancer patients with increased expression of PSAP and HEXB. Is the result.

FIG. 3e analyzes the presence or absence of statistical significance for the difference in protein expression level between the same four groups as in FIG. 3a for each of THBS1 and SPARC among 15 proteins specifically increased in BRCA mutant positive ovarian cancer patients. Is the result.

Figure 3f analyzes the presence or absence of statistical significance for the difference in protein expression level between the same four groups as in Figure 3a for each of CDH2 and MRC1 among 15 proteins specifically increased in BRCA mutant-positive ovarian cancer patients. Is the result.

Figure 3g analyzed the presence or absence of statistical significance for differences in protein expression levels between the same four groups as in Figure 3a for HSPA4 and RELN, respectively, among 15 proteins specifically expressed in BRCA mutant positive ovarian cancer patients. Is the result.

Figure 3h is a result of analyzing the presence or absence of statistical significance for the difference in protein expression level between the same four groups as in Figure 3a for LTBP1 among 15 proteins specifically increased expression in BRCA mutant positive ovarian cancer patients.

FIG. 4A shows an analysis of ROC curves and AUC values to investigate the accuracy of SERPINA5 (Uniprot ID: P5154) and IGFBP5 (P24593) among 9 proteins with specific expression reduction in BRCA mutant positive ovarian cancer patients. It is the result that is drawn and shown.

Figure 4b is a BRCA mutant-positive ovarian cancer patients specifically expressed in the reduced expression of the F2 (P00734) and TFRC (P02786) of the nine proteins, ROC curve analysis was performed to investigate the accuracy and derive the AUC value Is the result.

Figure 4c is a BRCA mutant-positive ovarian cancer patients in the nine specifically reduced expression of the protein SELL (P14151.2) and APOC3 (P02656) ROC curve analysis to investigate the accuracy and derive the AUC value The results are shown.

Figure 4d is a BRCA mutant-positive ovarian cancer patients specifically expressed in the nine proteins with reduced expression of SELL (P08697) and APOC3 (P01008), respectively, to investigate the accuracy of the ROC curve analysis and deriving the AUC value Is the result.

Figure 4e is a result of performing a ROC curve analysis and deriving the AUC value to investigate the accuracy of RBP4 (P02753) among nine proteins whose expression is specifically decreased in patients with BRCA mutant positive ovarian cancer.

Figure 5a is a BRCA mutant-positive ovarian cancer patients in the expression of 15 specifically increased protein VNN1 (Uniprot ID: O95497) and PPBP (P02775) to investigate the accuracy of each of the ROC curve analysis to perform AUC value This is the result.

Figure 5b is a BRCA mutant-positive ovarian cancer patients to express the AUC value by performing an ROC curve analysis to investigate the accuracy of each of the ALDOA (P04075.2) and VWF (P04275) among 15 proteins specifically increased expression One result.

Figure 5c is a BRCA mutant-positive ovarian cancer patients to express the AUC value by performing an ROC curve analysis to investigate the accuracy of SERPINE1 (P05121) and GPI (P06744.2) among 15 types of proteins specifically increased expression One result.

Figure 5d is a BRCA mutant-positive ovarian cancer patients to express the AUC value by performing an ROC curve analysis to investigate the accuracy of each of the PSAP (P07602.3) and HEXB (P07686) of 15 proteins specifically increased expression One result.

Figure 5e is a result of deriving the AUC value by performing an ROC curve analysis to investigate the accuracy of each of the THBS1 (P07996) and SPARC (P09486) among 15 types of proteins specifically increased expression in BRCA mutant positive ovarian cancer patients to be.

Figure 5f is a result of deriving the AUC value by performing an analysis of the ROC curve to investigate the accuracy of each of the CDH2 (P19022) and MRC1 (P22897) among 15 proteins specifically increased expression in BRCA mutant positive ovarian cancer patients to be.

Figure 5g is a result of deriving the AUC value by performing an ROC curve analysis to investigate the accuracy of each of HSPA4 (P34932) and RELN (P78509) among 15 proteins specifically increased expression in BRCA mutant positive ovarian cancer patients to be.

Figure 5h is a result of deriving the AUC value by performing an analysis of the ROC curve to investigate the accuracy of LTBP1 (Q14766.4) among 15 kinds of proteins specifically increased expression in BRCA mutant positive ovarian cancer patients.

Figure 6 shows a schematic diagram for 2 fold cross validation to verify the validity of the 24 marker candidates.

The present inventors predicted hereditary ovarian cancer with a BRCA gene mutation in advance and furthermore, tried to present a target for the development of a therapeutic agent for the disease, and as a result, expressed in patients with ovarian cancer with a BRCA mutation compared to a normal person with a BRCA mutation The present invention was completed by excavating the 11 kinds of markers that have changed significantly and verifying their effectiveness.

Accordingly, the present invention is ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth factor beta-binding protein 1; NM_000627, NM_001166264 , NM_001166265, NM_001166266, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323518, NM_006744), SPARC (secreted protein) acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052), SERPINF2 (serpin family F member 2; NM_000920, NM_000934, NM_000934, NM_000934, NM_000934, NM_000920 And, THBS1 (Thrombospondin 1; NM_003246) provides a marker composition for predicting the development of hereditary ovarian cancer, comprising at least one gene selected from the group consisting of or a protein encoded by the gene.

In addition, the present invention is ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth factor beta-binding protein 1; NM_000627, NM_001166264 , NM_001166265, NM_001166266, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323518, NM_006744), SPARC (secreted protein) acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052), SERPINF2 (serpin family F member 2; NM_000920, NM_000934, NM_000934, NM_000934, NM_000934, NM_000920 And, THBS1 (Thrombospondin 1; NM_003246) comprising at least one gene selected from the group consisting of mRNA or an agent that measures the level of the protein encoding the gene, provides a composition for predicting the development of hereditary ovarian cancer.

In addition, the present invention provides a kit for predicting the development of hereditary ovarian cancer comprising the composition.

The present inventors discovered 11 types of biomarkers capable of predicting the onset of hereditary ovarian cancer through specific examples and verified their effectiveness.

In one embodiment of the present invention, plasma samples of the BRCA mutant-positive normal group and the BRCA-mutant-positive ovarian cancer patient group were significantly reduced in 19 ovarian cancer patients and 61 increased in expression compared to the normal group. Proteins were identified, and among the proteins, the expressions were significantly changed in the BRCA mutant-positive ovarian cancer patient group, except for those that overlap with the proteins with increased expression in the entire normal group and the ovarian cancer patient group, respectively, which are not related to the BRCA mutation. Species marker candidate proteins were derived (see Example 2).

In another embodiment of the present invention, for each of the 24 types of proteins, 4 groups (BRCA-negative normal group (HN), BRCA-positive normal group (HP), BRCA-negative ovarian cancer patient group (ON), and BRCA-positive group) Statistical significance was analyzed for differences in protein expression levels between ovarian cancer patient groups (OP), and it was confirmed that all 24 proteins had statistical significance between the BRCA positive normal group (HP) and the ovarian cancer patient group (OP). See example 3).

In another embodiment of the present invention, in order to investigate the accuracy of each of the 24 types of proteins, ROC curve analysis was performed and AUC values were derived to confirm sensitivity and specificity (see Example 4).

In another embodiment of the present invention, 2 fold cross validation was repeated 50 times to verify the effectiveness as a marker for the 24 proteins, and various results were synthesized to derive the final 11 biomarkers (Examples) 5).

As used in the present invention, the term “hereditary ovarian cancer” refers to an ovarian cancer that develops due to a mutation gene or a gene defect inherited from at least one of the parents. In the present invention, the genetic ovarian cancer is a mutation of the BRCA1 or BRCA2 gene It may be accompanied by, it does not necessarily mean that ovarian cancer is caused by mutation of the gene.

As used in the present invention, the term “prediction” is used to determine whether a specific individual is likely to develop hereditary ovarian cancer, is relatively likely to develop hereditary ovarian cancer, or whether hereditary ovarian cancer has already developed. Speak. The method of the present invention can be used to predict an individual with a high risk of developing hereditary ovarian cancer in an individual who has a BRCA gene mutation and to prevent or delay the onset of the disease through special and appropriate management.

In the present invention, the agent for measuring the mRNA level of the gene may be sense and antisense primers or probes that complementarily bind to the mRNA of the gene.

The term “primer” used in the present invention is a short gene sequence serving as a starting point for DNA synthesis, and means an oligonucleotide synthesized for the purpose of diagnosis, DNA sequencing, and the like. The primers can be generally synthesized to a length of 15 to 30 base pairs, but may vary depending on the purpose of use, and can be modified by methylation, capping, or the like by a known method.

As used in the present invention, the term "probe (probe)" refers to a nucleic acid capable of specifically binding to mRNAs of several bases to hundreds of bases in length produced through enzymatic chemical separation or synthesis. The presence or absence of mRNA can be confirmed by labeling radioactive isotopes, enzymes, or phosphors, and can be designed and modified in a known manner.

The agent for measuring the protein level may be an antibody that specifically binds to a protein encoded by a gene, but is not limited thereto.

As used in the present invention, the term “antibody” includes immunoglobulin molecules that are immunologically reactive with a specific antigen, and includes both monoclonal and polyclonal antibodies. In addition, the antibodies include forms produced by genetic engineering such as chimeric antibodies (eg, humanized murine antibodies) and heterologous antibodies (eg, bispecific antibodies).

The anti-cancer agent reactivity prediction kit of the present invention may be composed of one or more other component compositions, solutions, or devices suitable for analytical methods.

In another aspect of the present invention, the present invention is an ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming) growth factor beta-binding protein 1; NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323518, NM_006744), SPARC (secreted protein acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_0042 family F member 2; NM_000934, NM_001165920, NM_001165921), and THBS1 (Thrombospondin 1; NM_003246) selected from the group consisting of mRNA of one or more genes or measuring the level of protein encoded by the gene, hereditary ovarian cancer Provides information providing method for predicting the outbreak.

The term “method for providing information for predicting the development of hereditary ovarian cancer” used in the present invention provides objective basic information necessary to predict whether or not the development of hereditary ovarian cancer is a preliminary step for predicting the onset of disease, and the clinical judgment of a doctor Or findings are excluded.

In one embodiment of the present invention, the subject may have a BRCA1 or BRCA2 gene mutation.

In the present invention, if the mRNA level of one or more genes selected from the group consisting of RBP4, SERPINA5, SERPINC1 and SERPINF2 or the protein level encoded by the gene is reduced compared to a healthy normal control group, it is predicted that hereditary ovarian cancer will develop. Can be.

In the present invention, when the mRNA level of one or more genes selected from the group consisting of ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC and THBS1 or the protein level encoded by the gene is increased compared to a healthy normal control group, hereditary ovaries It can be predicted that cancer will develop.

The biological sample derived from the patient may include whole blood, blood, saliva, tissue, cells, sputum, cerebrospinal fluid, and urine, but is not limited thereto.

The expression level of the mRNA is a polymerase chain reaction (PCR), reverse transcriptase chain reaction (RT-PCR), real-time polymerase chain reaction (Real-time PCR), RNase protection assay (RNase) by conventional methods known in the art. protection assay (RPA), microarray (microarray) and Northern blotting (northern blotting) may be measured through one or more methods selected from the group consisting of, but is not limited to.

The protein expression level is Western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzymatic immunoassay (ELISA), immunoprecipitation, by conventional methods known in the art. , Through flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip. It can be measured, but is not limited thereto.

Hereinafter, preferred embodiments are provided to help understanding of the present invention. However, the following examples are only provided to more easily understand the present invention, and the contents of the present invention are not limited by the following examples.

[Example]

Example 1. Experimental method

1-1. Recruiting subjects and securing samples

All samples in this example were processed after obtaining the appropriate consent and approval from the Clinical Trial Review Committee of the Seoul St. Mary's Hospital, Catholic University College of Medicine. Plasma samples were obtained from 20 ovarian cancer patients before surgery and 20 healthy normal groups. Plasma samples derived from patients with ovarian cancer were provided by Seoul St. Mary's Hospital and Korean Gynecologic Cancer Bank (KGCB), and healthy normal control-derived plasma samples were obtained from subjects undergoing medical examination at Seoul St. Mary's Hospital in the case of BRCA mutant negative subjects. In the case of positive subjects, they were obtained from those who agreed to visit Seoul St. Mary's Hospital and consent to blood collection. All samples were frozen with liquid nitrogen and stored at -80 ° C until use.

1-2. Preparation of plasma samples

Plasma samples obtained from 20 normal groups (10 BRCA1 / 2 gene mutations, 10 non-variables) and 20 ovarian cancer patients (10 BRCA1 / 2 gene mutations, 10 non-variables) were pretreated according to the following procedure. Did. More specifically, 14 proteins (albumin, immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), alpha1-antitrypsin (α1) present in high concentration using 40 μl of the plasma sample) -antitrypsin), alpha1-acid glycoprotein, apolipoprotein A1, apolipoprotein A2, complement C3, transferrin, alpha2-macroglobulin (α2-marcoglobulin), haptoglobin (haptoglobin), fibrinogen (fibrinogen), transthyretin (transthyretin) was removed into the HPLC MARS14 (Multiple Affinity Removal System 14, agilent, Inc.) column was injected. Next, after lyophilizing the low concentration plasma protein, reabsorbed with 5% SDS, 50 mM of 1M triethylammonium bicarbonate, dithiothreitol was added to make 20 mM, and at 95 ° C. It was reacted for 10 minutes to reduce disulfide bonds. Thereafter, iodoacetamide was added to be 40 mM for alkylation, and the mixture was reacted for 30 minutes at room temperature under dark conditions, and this was dissolved in a lysis buffer using an S-trap filter (S-TRAPTM, Protifi). ) And the solution was passed out of the filter, the protein was confined in the filter, and then centrifuged to wash. Subsequently, the mixture was filled with a digestion buffer, and plasma protein and Lys-C / trypsin mixed enzyme (promega) were added at a mass ratio of 25: 1, and reacted at 37 ° C for 16 hours. Next, after dissolving 100 μl of 0.1% formic acid in the dried sample, 5 μl was taken and used for LC-MS / MS analysis.

1-3. LC-MS / MS analysis

Nano LC-Q-Exactive plus mass spectrometry performed in Example 1-2 was performed according to the following method.

i) first fractionated with 50 cm C18 capillary column (OD 360 μm, ID 75 μm) for 200 min; ii) fractionated for 150 minutes with a gradient (5 ~ 45% acetonitrile and 0.1% formic acid solution); iii) after collecting data in DDA (data dependent acquisition) mode for the top 20 intensity precursors; iv) The collected data was compared with the human SWISSPROT sequence database using the Proteome discoverer 2.2 program to identify peptides and proteins, and the LFQ (Lable-Free Quantification) value of the proteins was parsimony using the MS1 peak intensity of the identified peptides. : Maximum information using minimum data) was analyzed to discover biomarkers through quantitative results.

1-4. Data analysis

In order to compare the amount of the target protein in the plasma sample, six new plasma proteins were found as a correctable normalization factor without showing differences between groups among endogenouse plasma proteins. The six proteins include thyroxine-binding globulin (TBG), complement factor I (CFI), complement component C6 (C6), and plastin-2 (PLS2), Complement C2 (C2), Complement factor H (CFH). The LFQ value for the representative peptide of the 6 proteins was divided by the median value of the LFQ value of each peptide from the raw value of plasma from 40 subjects, and the median value of 6 peptides per sample was defined as the final normalization factor. The LFQ value of other proteins was divided by the final normalization factor.

P values were obtained through Mann-whitney test using normalized values during statistical analysis. Quantitative differences between the two groups were obtained with a P value less than 0.05 / 374 through Bonferonni correction by post-test. More than twice, I discovered protein.

Example 2. Identification of candidate proteins whose expression is specifically changed in patients with hereditary ovarian cancer

In order to discover biomarkers capable of predicting the development of hereditary ovarian cancer, the present inventors discover proteins differentially expressed in plasma samples according to two scenarios as shown in FIG. 1A and comprehensively analyze them. The purpose of this study was to derive markers whose expression changes specifically in patients with hereditary ovarian cancer accompanied by mutations in the BRCA gene.

2-1. Identification of differentially expressed proteins among BRCA mutant positive subjects (Scenario I)

First, the plasma samples obtained from normal and ovarian cancer patients who are BRCA mutant positive (BRCA +) are analyzed through the methods described in Examples 1-2 and 1-3, and statistical analysis criteria of Examples 1-4 are used. The differentially expressed protein was analyzed by volcano plot. As a result, as shown in FIG. 1B, 19 types of proteins with significantly decreased expression were found in patients with BRCA mutant-positive ovarian cancer, and 61 types of proteins with increased expression were found.

Furthermore, the protein was classified based on the function of the protein through network analysis of the protein with reduced expression and the protein with increased expression, respectively. As a result, as shown in Fig. 1c, it was confirmed that 19 types of proteins with decreased expression in BRCA-positive ovarian cancer patients are involved in regulating the catabolic process of triglycerides, acute-phase reactions, and blood clotting fibrin thrombus, 61 proteins with increased expression in benign ovarian cancer patients are typically hydrogen peroxide metabolism, NADH metabolism, interleukin-8 production regulation and interleukin-12 mediated signaling pathway, regulation of cell death by oxidative stress, platelet aggregation And positive regulation by the host of the viral process.

2-2. Identification of differentially expressed proteins in normal and ovarian cancer patients (Scenario Ⅱ)

In this example, the subjects were all normal and ovarian cancer patients regardless of whether the BRCA gene was mutated or not, and differentially expressed in plasma samples derived from all normal and ovarian cancer patients in a similar manner to Example 2-1. Protein was derived. As a result, it was confirmed that 13 kinds of proteins were significantly increased in the normal group and 48 kinds of proteins were significantly increased in the ovarian cancer patient group.

2-3. Identification of proteins with specific expression changes in patients with hereditary ovarian cancer

Then, the results obtained in Examples 2-1 and 2-2 were comprehensively analyzed. 1D shows the number of proteins with increased expression in each group of the BRCA mutant positive normal group (BRCA + subjects: HC), the normal group (HC), the BRCA mutant positive ovarian cancer patient group (BRCA + subjects: OC), and the ovarian cancer patient group (OC). For comparison, in FIG. 1E, a common protein among proteins with increased expression in each group and a protein with increased expression in each group are distinguished by a van diagram. As a result, 10 proteins are common among the proteins with increased expression in the BRCA mutant-positive normal group and the whole normal group, and 46 of the proteins with increased expression in the BRCA mutant-positive ovarian cancer patients and the whole ovarian cancer patients are common. I could see that.

From the above results, except for proteins in which expression was increased in common, expression increased only in the BRCA mutant-positive normal group, i.e., 9 proteins whose expression decreased only in the BRCA-mutant-positive ovarian cancer patient group and expression in the BRCA-mutant-positive ovarian cancer patient group. The increased 15 proteins were isolated, and the 24 proteins were derived as candidate markers for predicting the development of hereditary ovarian cancer. Information on the 9 and 15 proteins and genes encoding them are shown in Tables 1 and 2, respectively.

Index	Uniprot ID	Gene	Protein Name
One	P05154	SERPINA5	Plasma serine protease inhibitor
2	P24593	IGFBP5	Insulin-like growth factor-binding protein 5
3	P00734	F2		Prothrombin
4	P02786	TFRC	Transferrin receptor protein 1
5	P14151-2	SELL	L-selectin
6	P02656	APOC3	Apolipoprotein C-III
7	P08697	SERPINF2	Alpha-2-antiplasmin
8	P01008	SERPINC1	Antithrombin-III
9	P02753	RBP4	Retinol-binding protein 4

Index	UniprotID	Gene	Protein Name
One	O95497	VNN1		Pantetheinase
2	P02775	PPBP	Platelet basic protein
3	P04075-2	ALDOA	Fructose-bisphosphate aldolase A
4	P04275	VWF	von Willebrand factor
5	P05121	SERPINE1	Plasminogen activator inhibitor 1
6	P06744-2	GPI	Glucose-6-phosphate isomerase
7	P07602-3	PSAP		Prosaposin
8	P07686	HEXB	Beta-hexosaminidase subunit beta
9	P07996	THBS1	Thrombospondin-1
10	P09486	SPARC	Osteonectin
11	P19022	CDH2	Cadherin-2
12	P22897	MRC1	Macrophage mannose receptor 1
13	P34932	HSPA4	Heat shock 70 kDa protein 4
14	P78509	RELN		Reelin
15	Q14766-4	LTBP1	Latent-transforming growth factor beta-binding protein 1

Example 3. Analysis of the presence or absence of statistical significance of proteins with specific expression changes in patients with hereditary ovarian cancer

The present inventors are four groups (BRCA negative normal group (HN), BRCA positive normal group (HP)) for each of the 24 kinds of proteins whose expression is specifically changed in the BRCA mutant positive ovarian cancer patients derived through Example 2 above. , The analysis of the statistical significance of protein expression difference between BRCA-negative ovarian cancer patient group (ON) and BRCA-positive ovarian cancer patient group (OP) was analyzed.

Results for 9 proteins with decreased expression in patients with ovarian cancer with BRCA mutations are shown in FIGS. 2A to 2E, and results for 15 proteins with increased expression are shown in FIGS. 3A to 3H. As a result of the analysis, it was confirmed that all 24 proteins had a significant difference in the expression level between the normal group, which is positive for BRCA mutation, and the patient group, which is positive for BRCA mutation. Table 3 below summarizes the average expression level and standard deviation of 24 proteins in the normal group with a positive BRCA mutation and the group with ovarian cancer with a positive BRCA mutation.

Accession	Description	HC vs OC	Healthy- BRCA + (n = 20)	OC- BRCA +  (n = 20)	Healthy- BRCA + (n = 20)	OC- BRCA +  (n = 20)
P00734	Prothrombin	HC ↑	38.49	37.11	0.17	0.40
P01008	Antithrombin-III	HC ↑	38.14	36.81	0.16	0.52
P02656	Apolipoprotein C-III	HC ↑	34.20	33.06	0.71	0.97
P02753	Retinol-binding protein 4	HC ↑	35.50	34.42	0.23	0.60
P02786	Transferrin receptor protein 1	HC ↑	28.61	26.83	0.58	1.10
P05154	Plasma serine protease inhibitor	HC ↑	33.17	32.01	0.22	0.48
P08697	Alpha-2-antiplasmin	HC ↑	36.17	35.04	0.13	0.32
P14151-2	Isoform 2 of L-selectin	HC ↑	30.13	29.11	0.55	0.65
P24593	Insulin-like growth factor-binding protein 5	HC ↑	26.71	25.70	0.85	0.61
O95497	Pantetheinase	OC ↑	26.38	27.95	1.17	1.15
P02775	Platelet basic protein	OC ↑	32.11	35.11	0.88	0.49
P04075-2	Isoform 2 of Fructose-bisphosphate aldolase A	OC ↑	27.80	28.92	0.36	0.87
P04275	von Willebrand factor	OC ↑	32.04	33.73	0.4	0.44
P05121	Plasminogen activator inhibitor 1	OC ↑	26.20	27.64	0.6	0.65
P06744-2	Isoform 2 of Glucose-6-phosphate isomerase	OC ↑	27.68	28.77	0.48	0.63
P07602-3	Isoform Sap-mu-9 of Prosaposin	OC ↑	25.26	26.74	0.62	0.64
P07686	Beta-hexosaminidase subunit beta	OC ↑	24.20	25.46	0.88	0.57
P07996	Thrombospondin-1	OC ↑	29.82	32.88	1.11	0.78
P09486	SPARC	OC ↑	25.67	30.19	0.82	1.15
P19022	Cadherin-2	OC ↑	26.58	27.73	0.59	0.65
P22897	Macrophage mannose receptor 1	OC ↑	26.35	27.36	0.61	0.56
P34932	Heat shock 70 kDa protein 4	OC ↑	26.01	27.43	0.49	0.85
P78509	Reelin	OC ↑	25.69	27.36	1.24	0.60
Q14766-4	Isoform 4 of Latent-transforming growth factor beta-binding protein 1	OC ↑	25.73	28.82	0.84	0.58

Example 4. Analysis of sensitivity and specificity of 24 markers

The present inventors tried to analyze the sensitivity and specificity to determine the accuracy of 24 markers whose expression was significantly changed in the BRCA mutant-positive ovarian cancer patient group, for which ROC curve analysis was performed. Did. Sensitivity and specificity were evaluated by calculating the area under the ROC curve (AUC).

Results for nine proteins with decreased expression in patients with ovarian cancer with BRCA mutations are shown in FIGS. 4A to 4E and Table 4, and results for 15 proteins with increased expression are shown in FIGS. 5A to 5H and It is shown in Table 5. When Area = 1, it was judged to have perfect accuracy for the test dataset, and when Area = 0.5, it was judged to have inaccurate (worthless) accuracy. Accuracy criteria according to AUC values are as follows: 0.9 ~ 1 = excellent, 0.8 ~ 0.9 = good, 0.7 ~ 0.8 = Fair (C), 0.6-0.7 = poor (D), 0.5-0.6 = Fail (F).

Index	Uniprot ID	Gene	Protein Name	AUC value
One	P05154	SERPINA5	Plasma serine protease inhibitor	0.951
2	P24593	IGFBP5	Insulin-like growth factor-binding protein 5	0.839
3	P00734	F2	Prothrombin	0.868
4	P02786	TFRC	Transferrin receptor protein 1	0.753
5	P14151-2	SELL	L-selectin	0.864
6	P02656	APOC3	Apolipoprotein C-III	0.633
7	P08697	SERPINF2	Alpha-2-antiplasmin	0.914
8	P01008	SERPINC1	Antithrombin-III	0.927
9	P02753	RBP4	Retinol-binding protein 4	0.981

Index	Uniprot ID	Gene	Protein Name	AUC value
One	O95497	VNN1	Pantetheinase	0.533
2	P02775	PPBP	Platelet basic protein	0.534
3	P04075.2	ALDOA	Fructose-bisphosphate aldolase A	0.844
4	P04275	VWF	von Willebrand factor	0.792
5	P05121	SERPINE1	Plasminogen activator inhibitor 1	0.642
6	P06744.2	GPI	Glucose-6-phosphate isomerase	0.774
7	P07602.3	PSAP	Prosaposin	0.771
8	P07686	HEXB	Beta-hexosaminidase subunit beta	0.755
9	P07996	THBS1	Thrombospondin-1	0.667
10	P09486	SPARC	Osteonectin	0.664
11	P19022	CDH2	Cadherin-2	0.868
12	P22897	MRC1	Macrophage mannose receptor 1	0.816
13	P34932	HSPA4	Heat shock 70 kDa protein 4	0.826
14	P78509	RELN	Reelin	0.760
15	Q14766.4	LTBP1	Latent-transforming growth factor beta-binding protein 1	0.674

Example 5. Validation of 24 markers

The present inventors tried to verify the effectiveness as a specific biomarker capable of predicting the development of hereditary ovarian cancer against 24 markers whose expression was significantly changed in the group of 24 BRCA mutant positive ovarian cancer patients. To this end, 2 fold cross validations were repeated 50 times for each of the 24 types of proteins, and FIG. 6 shows a schematic diagram of the verification process.

Through the above analysis, 15 proteins with optimal K value of 15 selected from 24 candidate proteins, AUC value of cross validation of 0.983 or more, and Probability (probability) of 0.70 or more (selected K = 7) were selected. 7 proteins were selected through literature. In addition, additionally, PPBP, SPARC, THBS1, and LTBP1 proteins showing significant difference in expression between BRCA mutation-positive normal group and ovarian cancer patients in 24 candidate group proteins, and also showing significant difference in expression between BRCA mutation-positive and negative groups Did.

Thus, through the above examples, the following 11 types were finally discovered as biomarkers for predicting the development of ovarian cancer after BRCA mutation, and the information on the 11 types of biomarkers is shown in Table 6 below.

Information			Significant sample group	Univariate ROC analysis
Accession	Description	Gene	HC vs OC	AUC
P01008	Antithrombin-III	SERPINC1	HC ↑	0.927
P02753	Retinol-binding protein 4	RBP4	HC ↑	0.981
P05154	Plasma serine protease inhibitor	SERPINA5	HC ↑	0.951
P08697	Alpha-2-antiplasmin	SERPINF2	HC ↑	0.914
P04075-2	Isoform 2 of Fructose-bisphosphate aldolase A	ALDOA	OC ↑	0.844
P19022	Cadherin-2	CDH2	OC ↑	0.868
P22897	Macrophage mannose receptor 1	MRC1	OC ↑	0.816
P02775	Platelet basic protein	PPBP	OC ↑	0.534
P09486	Osteonectin, SPARC	SPARC	OC ↑	0.664
P07996	Thrombospondin-1	THBS1	OC ↑	0.667
Q14766.4	Latent-transforming growth factor beta-binding protein 1	LTBP1	OC ↑	0.674

According to the present invention, 11 biomarkers having specific expression changes in ovarian cancer patients with mutations in the BRCA gene were identified and their effectiveness was verified. As a result, the above 11 types were obtained from subjects with mutations in the BRCA gene clinically. By measuring the mRNA or protein level of the biomarker gene, it is possible to provide early information on whether or not ovarian cancer is occurring, thereby preventing the disease, and the biomarker is a hereditary ovarian cancer accompanied by a BRCA gene mutation. It may be usefully used as a target molecule in developing a targeted therapeutic agent for.

Claims (14)

1. ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth factor beta-binding protein 1; NM_000627, NM_001166264, NM_001166265, NM_001166265, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323518, NM_006744), SPARC (secreted protein acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052), SERPINF2 (serpin family F member 2; NM_000934, NM_001165920, NM_TH165 1; NM_003246) comprising at least one gene selected from the group or a protein encoded by the gene, a marker composition for predicting the development of hereditary ovarian cancer.
2. According to claim 1,

   The hereditary ovarian cancer is characterized by accompanying a mutation in the BRCA1 or BRCA2 gene, marker composition.
3. ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth factor beta-binding protein 1; NM_000627, NM_001166264, NM_001166265, NM_001166265, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323518, NM_006744), SPARC (secreted protein acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052), SERPINF2 (serpin family F member 2; NM_000934, NM_001165920, NM_TH165 1; NM_003246) composition for predicting the development of hereditary ovarian cancer, comprising an agent for measuring the mRNA level of one or more genes selected from the group consisting of the protein encoded by the gene.
4. According to claim 3,

   The hereditary ovarian cancer is characterized in that it is accompanied by a mutation in the BRCA1 or BRCA2 gene, composition.
5. According to claim 3,

   The agent for measuring the mRNA level of the gene is characterized in that the sense and antisense primers, or probes that complementarily bind to the mRNA of the gene, the composition.
6. According to claim 3,

   The agent for measuring the protein level is characterized in that the antibody that specifically binds to the protein encoded by the gene.
7. A kit for predicting the development of hereditary ovarian cancer, comprising the composition of claim 3.
8. ALDOA (aldolase, fructose-bisphosphate A; GenBank accession number: NM_001243177), CDH2 (Cadherin 2; NM_001792, NM_001308176), LTBP1 (Latent-transforming growth factor beta-binding protein 1; NM_000627, in biological samples from subjects) NM_001166264, NM_001166265, NM_001166266, NM_206943), MRC1 (mannose receptor C-type 1; NM_002438), PPBP (pro-platelet basic protein; NM_002704), RBP4 (Retinol-binding protein 4; NM_001323517, NM_001323518, NM_006744) protein acidic and cysteine rich; NM_003118, NM_001309443, NM_001309444), SERPINA5 (serpin family A member 5; NM_000624), SERPINC1 (serpin family C member 1; NM_000488, NM_001365052), SERPINF2 (serpin family F member 2; NM_000165, NM_000934, N ), And measuring the mRNA level of one or more genes selected from the group consisting of THBS1 (Thrombospondin 1; NM_003246) or the protein level encoded by the gene, a method for predicting the development of hereditary ovarian cancer.
9. The method of claim 8,

   Hereditary ovarian cancer is a predictive method characterized in that it is accompanied by a mutation in the BRCA1 or BRCA2 gene.
10. The method of claim 8,

    The subject is characterized in that it carries a mutation in the BRCA1 or BRCA2 gene, prediction method.
11. The method of claim 8,

    The mRNA of one or more genes selected from the group consisting of RBP4, SERPINA5, SERPINC1 and SERPINF2 or protein levels encoded by the gene are predicted to develop hereditary ovarian cancer when the level of the protein is reduced compared to a healthy normal control group. , Prediction method.
12. The method of claim 8,

    Genetic ovarian cancer will develop if the mRNA level of one or more genes selected from the group consisting of ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC and THBS1 or the protein level encoded by the gene is increased compared to a healthy normal control group A prediction method characterized by predicting.
13. The method of claim 8,

    The expression level of the mRNA is in situ hybridization (in situ hybridization), polymerase chain reaction (PCR), reverse transcriptase chain reaction (RT-PCR), real-time polymerase chain reaction (real-time PCR), RNase protection assay (RNase protection assay; RPA), a microarray (microarray) and Northern blotting (northern blotting), a prediction method characterized by being measured by at least one method selected from the group consisting of.
14. The method of claim 8,

    The expression level of the protein is western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzymatic immunoassay (ELISA), immunoprecipitation, flow cytometry. , Characterized by being measured through one or more methods selected from the group consisting of immunofluorescence, ouchterlony, complement fixation assay and protein chip, Prediction method.

Images