Biomarkers for predicting the occurrence of hereditary ovarian cancer and their uses

Abstract

The present disclosure relates to biomarkers for predicting the occurrence of hereditary ovarian cancer and their uses, and more specifically, to a marker composition for predicting the occurrence of hereditary ovarian cancer, a composition and a kit for predicting the occurrence of hereditary ovarian cancer, and a method for providing information for predicting the occurrence of hereditary ovarian cancer. The presence or absence of hereditary ovarian cancer with BRCA mutation can be predicted early by measuring the mRNA or protein level of the biomarker gene according to the present disclosure, and the biomarker can be effectively used to develop a therapeutic agent for hereditary ovarian cancer targeting the biomarker.

Description

Technical Field

[0001] The present disclosure relates to biomarkers for predicting the occurrence of hereditary ovarian cancer and uses thereof, and more specifically, to a marker composition for predicting the occurrence of hereditary ovarian cancer, a composition and kit for predicting the occurrence of hereditary ovarian cancer, and a method for predicting the occurrence of hereditary ovarian cancer. Background Art

[0002] Ovarian cancer is one of the top ten cancers and causes of death among Korean women, and more than 60% of ovarian cancer patients are diagnosed at an advanced stage, and the 5-year survival rate at this time is less than 30%. The symptoms of ovarian cancer are not obvious, and bloating, indigestion, diarrhea, and constipation are difficult to identify as symptoms of ovarian cancer. And, most importantly, there is no effective test method that can detect ovarian cancer at an early stage. Therefore, effective means of preventing and early detecting ovarian cancer are important unmet medical needs.

[0003] It is known that about 25% of high-grade serous ovarian cancer (which is the most common type of ovarian cancer) is associated with the BRCA1 gene. The BRCA1 gene is located on chromosome 17 and has been initially confirmed as a gene that increases the risk of breast cancer and ovarian cancer, and after BRCA1, BRCA2 has also been reported to increase the risk of the above cancer types. The probability of ovarian cancer in people with BRCA1 mutations reaches 44% before the age of 70, and the mutated BRCA genes can be inherited not only from the maternal line, but also from the paternal line. It is known that about 10% of ovarian cancer is related to mutations in the BRCA1 and BRCA2 genes. When mutations are present in these two genes, the incidence of ovarian cancer increases by 10 times or more compared to normal people, and the recurrence rate of ovarian cancer also increases. In addition, it is reported that in Korean ovarian cancer patients, regardless of family history, BRCA1 (23.8%) and BRCA2 (25.7%) are accompanied by BRCA mutations (Choi et al., JGO.2016).

[0004] However, despite these effects of BRCA mutations, prophylactic risk-reducing salpingo-oophorectomy (RRSO) is the only method for preventing ovarian cancer caused by BRCA mutations, and other methods have not been established. In women of childbearing age, "prophylactic risk-reducing salpingo-oophorectomy" causes early menopause, resulting in a decrease in quality of life, and the proportion of older mothers (>35 years old giving birth) in Korea increased from 11% in 1999 to 28.6% in 2009, which means an increase of 17.6% in 10 years, resulting in a decrease in the number of BRCA1 carriers who can undergo RRSO at an appropriate time. Therefore, there is an urgent need to develop a method other than RRSO that can predict and prevent the occurrence of ovarian cancer.

[0005] In recent studies on breast cancer and BRCA genes, it has been suggested that RANKL / RANK inhibitors (e.g., denosumab) may function as preventive drugs for breast cancer in BRCA-positive subjects. Based on this, it is judged necessary to discover biomarkers that can predict hereditary ovarian cancer, and furthermore, to develop hereditary ovarian cancer therapeutic agents using target inhibitors of selective biomarkers as a therapy other than RRSO.

[0006] Public Content

[0007] Technical issues

[0008] As described above, as a result of research work to predict the presence or absence of hereditary ovarian cancer occurrence accompanied by BRCA gene mutations and further present targets for the development of therapeutic agents for the disease, the inventors of the present application discovered 11 types of markers whose expressions are significantly changed in ovarian cancer patients with BRCA mutations compared to normal persons with BRCA mutations, thereby completing the present disclosure.

[0009] Therefore, the present disclosure is directed to providing a marker composition for predicting the occurrence of hereditary ovarian cancer.

[0010] In addition, the present disclosure relates to providing a composition for predicting the occurrence of hereditary ovarian cancer and a kit for predicting the occurrence of hereditary ovarian cancer, which comprises the composition.

[0011] Additionally, the present disclosure relates to methods of providing information for predicting the development of hereditary ovarian cancer.

[0012] However, technical problems to be achieved by the present disclosure are not limited to the above-mentioned problems, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

[0013] Technical Solution

[0014] In order to achieve the purpose of the present disclosure as described above, one aspect of the present disclosure provides a marker composition for predicting the occurrence of hereditary ovarian cancer, wherein the marker composition comprises at least one gene or a protein encoded by the at least one gene, wherein the at least one gene is selected from: aldolase, fructose-bisphosphate A (ALDOA) ​​(GenBank accession number: NM_001243177), cadherin 2 (CDH2) (NM_001792, NM_001308176), latent transforming growth factor β-binding protein 1 (LTBP1) (NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), mannose receptor C-1 type (MRC1) (NM_002438), proplatelet basic protein ( PPBP)(NM_002704), retinol binding protein 4 (RBP4) (NM_001323517, NM_001323518, NM_006744), secreted acidic protein rich in cysteine ​​(SPARC) (NM_003118, NM_001309443, NM_001309444), serpin family A member 5 (SERPINA5) (NM_000624), serpin family C member 1 (SERPINC1) (NM_000488, NM_001365052), serpin family F member 2 (SERPINF2) (NM_000934, NM_001165920, NM_001165921) and thrombospondin 1 (THBS1) (NM_003246).

[0015] In addition, another aspect of the present disclosure provides a composition for predicting the occurrence of hereditary ovarian cancer and a kit for predicting the occurrence of hereditary ovarian cancer, the kit comprising the composition, the composition comprising an agent for measuring the mRNA level of at least one gene or the protein level encoded by the at least one gene, the at least one gene being selected from: aldolase, fructose-bisphosphate A (ALDOA) ​​(GenBank Accession No.: NM_001243177), cadherin 2 (CDH2) (NM_001792, NM_001308176), latent transforming growth factor β-binding protein 1 (LTBP1) (NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), mannose receptor C-1 type (MRC1) (NM_00243177). 38), proplatelet basic protein (PPBP) (NM_002704), retinol binding protein 4 (RBP4) (NM_001323517, NM_001323518, NM_006744), secreted acidic protein rich in cysteine ​​(SPARC) (NM_003118, NM_001309443, NM_001309444), serpin family A member 5 ( SERPINA5) (NM_000624), serpin family C member 1 (SERPINC1) (NM_000488, NM_001365052), serpin family F member 2 (SERPINF2) (NM_000934, NM_001165920, NM_001165921) and thrombospondin 1 (THBS1) (NM_003246).

[0016] In an embodiment of the present disclosure, the hereditary ovarian cancer may be accompanied by a mutation in the BRCA1 or BRCA2 gene.

[0017] In another embodiment of the present disclosure, the reagents for measuring the mRNA level of at least one gene may be sense and antisense primers or probes, each complementarily binding to the mRNA of the at least one gene.

[0018] In another embodiment of the present disclosure, the reagent for measuring protein levels may be an antibody that specifically binds to a protein encoded by the at least one gene.

[0019] In addition, another aspect of the present disclosure provides a method for providing information for predicting the occurrence of hereditary ovarian cancer, the method comprising measuring the mRNA level of at least one gene in a biological sample derived from a subject or the protein level encoded by the at least one gene, the at least one gene being selected from: aldolase, fructose-bisphosphate A (ALDOA) ​​(GenBank Accession No.: NM_001243177), cadherin 2 (CDH2) (NM_001792, NM_001308176), latent transforming growth factor β-binding protein 1 (LTBP1) (NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), mannose receptor C-1 type (MRC1) (NM_002438), proplatelet basic protein white (PPBP) (NM_002704), retinol binding protein 4 (RBP4) (NM_001323517, NM_001323518, NM_006744), secreted acidic protein rich in cysteine ​​(SPARC) (NM_003118, NM_001309443, NM_001309444), serpin family A member 5 (SERPINA5) (NM_000624), serpin family C member 1 (SERPINC1) (NM_000488, NM_001365052), serpin family F member 2 (SERPINF2) (NM_000934, NM_001165920, NM_001165921) and thrombospondin 1 (THBS1) (NM_003246).

[0020] In embodiments of the present disclosure, the subject may have a mutation in the BRCA1 or BRCA2 gene.

[0021] In another embodiment of the present disclosure, when the mRNA level of at least one gene selected from RBP4, SERPINA5, SERPINC1 and SERPINF2 or the protein level encoded by the at least one gene is reduced compared with a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.

[0022] In another embodiment of the present disclosure, when the mRNA level of at least one gene selected from ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC and THBS1 or the protein level encoded by the at least one gene is increased compared with a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.

[0023] In another embodiment of the present disclosure, the expression level of mRNA can be measured by at least one method selected from the group consisting of in situ hybridization, polymerase chain reaction (PCR), reverse transcription (RT)-PCR, real-time PCR, RNase protection assay (RPA), microarray, and northern blot.

[0024] In another embodiment of the present disclosure, the expression level of a protein can be measured by at least one method selected from the group consisting of Western blot, radioimmunoassay (RIA), radial immunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, Ouchterlony two-way immunodiffusion, complement fixation assay, and protein chip.

[0025] Beneficial Effects

[0026] In the present disclosure, since 11 types of biomarkers capable of early predicting the occurrence of hereditary ovarian cancer in subjects with BRCA gene mutations have been discovered, the occurrence of hereditary ovarian cancer accompanied by BRCA mutations can be early predicted by measuring the mRNA or protein levels of the biomarker genes according to the present disclosure, and the biomarkers can be effectively used to develop therapeutic agents for hereditary ovarian cancer by targeting the biomarkers. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] FIG. 1A is an experimental scheme for discovering proteins whose expression is specifically altered in BRCA gene mutation-positive (BRCA+) ovarian cancer patients to obtain candidate marker proteins for predicting the occurrence of hereditary ovarian cancer associated with BRCA gene mutation.

[0028] FIG. 1B shows the results of analyzing differentially expressed proteins using a volcano plot using plasma samples obtained from a BRCA mutation-positive normal group and ovarian cancer patients.

[0029] FIG. 1C shows analysis of the functions of the corresponding proteins of 19 types of proteins whose expressions were decreased and 61 types of proteins whose expressions were increased in ovarian cancer patients as a result of the analysis in FIG. 1B , by network analysis.

[0030] FIG. 1D is a result of comparing the number of proteins whose expression was significantly increased in each group among the BRCA mutation-positive normal group (BRCA+ subjects: HC), the normal group (HC), the BRCA mutation-positive ovarian cancer patients (BRCA+ subjects: OC), and the ovarian cancer patients (OC).

[0031] FIG. 1E is a result of a Venn diagram after comparative analysis of proteins identified in the four groups of FIG. 1D , and results obtained therefrom of 24 types of proteins whose expression was specifically decreased or increased only in the BRCA mutation-positive ovarian cancer patient group.

[0032] Figure 2A is the result of analyzing whether there is a statistically significant difference in protein expression levels among four groups (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)) for each of SERPINA5 and IGFBP5 among the 9 types of proteins whose expression is specifically reduced in BRCA mutation-positive ovarian cancer patients.

[0033] FIG. 2B is the result of analyzing whether there is a statistically significant difference in protein expression level between the same four groups as shown in FIG. 2A for each of F2 and TFRC among 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0034] FIG. 2C is the result of analyzing whether there is a statistically significant difference in protein expression level between the four same groups as shown in FIG. 2A for each of SELL and APOC3 among the 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0035] FIG. 2D is the result of analyzing whether there is a statistically significant difference in protein expression level between the same four groups as shown in FIG. 2A for each of SERPINF2 and SERPINC1 among 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0036] FIG. 2E is a result of analyzing whether there is a statistically significant difference in the protein expression level of RBP4 among the 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients among the same four groups as shown in FIG. 2A .

[0037] Figure 3A is the result of analyzing whether there is a statistically significant difference in protein expression levels among four groups (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)) for each of VNN1 and PPBP among the 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0038] FIG. 3B is the result of analyzing whether there is a statistically significant difference in the protein expression level of each of ALDOA and VWF among the 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients between the same four groups as shown in FIG. 3A .

[0039] FIG. 3C is the result of analyzing whether there is a statistically significant difference in protein expression level between the same four groups as shown in FIG. 3A for each of SERPINE1 and GPI among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0040] FIG. 3D is the result of analyzing whether there is a statistically significant difference in protein expression level between the same four groups as shown in FIG. 3A for each of PSAP and HEXB among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0041] FIG. 3E is the result of analyzing whether there is a statistically significant difference in protein expression level between the same four groups as shown in FIG. 3A for each of THBS1 and SPARC among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0042] FIG. 3F is the result of analyzing whether there is a statistically significant difference in protein expression level between the same four groups as shown in FIG. 3A for each of CDH2 and MRC1 among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0043] FIG. 3G is the result of analyzing whether there is a statistically significant difference in protein expression level between the same four groups as shown in FIG. 3A for each of HSPA4 and RELN among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0044] FIG. 3H is the result of analyzing whether there is a statistically significant difference in the protein expression level of LTBP1 among the 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients among the same four groups as shown in FIG. 3A .

[0045] FIG. 4A is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of SERPINA5 (Uniprot ID: P5154) and IGFBP5 (P24593) among 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0046] FIG. 4B is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of F2 (P00734) and TFRC (P02786) among 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0047] FIG. 4C is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of SELL (P14151.2) and APOC3 (P02656) among 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0048] FIG. 4D is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of SELL (P08697) and APOC3 (P01008) among 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0049] FIG. 4E is a result of performing ROC curve analysis and deriving AUC values ​​to study the accuracy of RBP4 (P02753) among 9 types of proteins whose expression is specifically decreased in BRCA mutation-positive ovarian cancer patients.

[0050] FIG. 5A is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of one of VNN1 (Uniprot ID: O95497) and PPBP (P02775) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0051] FIG. 5B is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of ALDOA (P04075.2) and VWF (P04275) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0052] FIG. 5C is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of SERPINE1 (P05121) and GPI (P06744.2) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0053] FIG. 5D is a result of performing ROC curve analysis and deriving AUC values ​​to study the accuracy of each of PSAP (P07602.3) and HEXB (P07686) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0054] FIG. 5E is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of THBS1 (P07996) and SPARC (P09486) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0055] FIG. 5F is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of CDH2 (P19022) and MRC1 (P22897) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0056] FIG. 5G is a result of performing ROC curve analysis and deriving AUC values ​​to investigate the accuracy of each of HSPA4 (P34932) and RELN (P78509) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0057] FIG. 5H is a result of performing ROC curve analysis and deriving an AUC value to study the accuracy of LTBP1 (Q14766.4) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.

[0058] Figure 6 A schematic diagram of 2-fold cross validation to verify the effectiveness of 24 types of marker candidate panels is shown.

[0059] Best Mode for Carrying Out the Invention

[0060] As a result of research work to predict hereditary ovarian cancer accompanied by BRCA gene mutations and further present targets for developing therapeutic agents for the disease, the inventors of the present application discovered 11 types of markers whose expressions are significantly changed in ovarian cancer patients with BRCA mutations compared to normal persons with BRCA mutations and verified their effectiveness, thereby completing the present disclosure.

[0061] Therefore, a marker composition for predicting the occurrence of hereditary ovarian cancer is provided, wherein the marker composition comprises at least one gene or a protein encoded by the at least one gene, wherein the at least one gene is selected from: aldolase, fructose-bisphosphate A (ALDOA) ​​(GenBank accession number: NM_001243177), cadherin 2 (CDH2) (NM_001792, NM_001308176), latent transforming growth factor β-binding protein 1 (LTBP1) (NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), mannose receptor C-1 type (MRC1) (NM_002438), proplatelet basic protein (PPBP) (NM_002792). 04), retinol binding protein 4 (RBP4) (NM_001323517, NM_001323518, NM_006744), secreted acidic protein rich in cysteine ​​(SPARC) (NM_003118, NM_001309443, NM_001309444), serpin family A member 5 (SERPINA5) (NM_000624), serpin family C member 1 (SERPINC1) (NM_000488, NM_001365052), serpin family F member 2 (SERPINF2) (NM_000934, NM_001165920, NM_001165921) and thrombospondin 1 (THBS1) (NM_003246).

[0062] In addition, a composition for predicting the occurrence of hereditary ovarian cancer is provided, the composition comprising an agent for measuring the mRNA level of at least one gene or the protein level encoded by the at least one gene, the at least one gene being selected from: aldolase, fructose-bisphosphate A (ALDOA) ​​(GenBank accession number: NM_001243177), cadherin 2 (CDH2) (NM_001792, NM_001308176), latent transforming growth factor β-binding protein 1 (LTBP1) (NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), mannose receptor C-1 type (MRC1) (NM_002438), proplatelet basic protein (PPBP) (NM_001243177), pro-platelet basic protein (PPBP) (NM_001243178), pro-platelet basic protein (PPBP) (NM_001243179), pro-platelet basic protein (P ... _002704), retinol binding protein 4 (RBP4) (NM_001323517, NM_001323518, NM_006744), secreted acidic protein rich in cysteine ​​(SPARC) (NM_003118, NM_001309443, NM_001309444), serpin family A member 5 (SERPINA5) (NM_000624), serpin family C member 1 (SERPINC1) (NM_000488, NM_001365052), serpin family F member 2 (SERPINF2) (NM_000934, NM_001165920, NM_001165921) and thrombospondin 1 (THBS1) (NM_003246).

[0063] In addition, a kit for predicting the occurrence of hereditary ovarian cancer is provided, which comprises the composition.

[0064] The inventors of the present application discovered 11 types of biomarkers that can predict the occurrence of hereditary ovarian cancer through specific embodiments and confirmed their effectiveness.

[0065] In an embodiment of the present disclosure, plasma samples of a BRCA mutation-positive normal group and a BRCA mutation-positive ovarian cancer patient group are used to identify 19 types of proteins whose expression is significantly decreased and 61 types of proteins whose expression is significantly increased in the ovarian cancer patient group compared with the normal group, and those proteins overlapping with proteins whose expression is increased in all normal groups and ovarian cancer patient groups, respectively, and which are not related to BRCA mutation are excluded from the above proteins to obtain 24 types of marker candidate group proteins whose expression is specifically and significantly changed in the BRCA mutation-positive ovarian cancer patient group (see Example 2).

[0066] In another embodiment of the present disclosure, whether there is a statistically significant difference in protein expression levels of each of the 24 types of proteins between four groups (BRCA-negative normal group (HN), BRCA-positive normal group (HP), BRCA-negative ovarian cancer patient group (ON), and BRCA-positive ovarian cancer patient group (OP)) was analyzed, and each of the 24 types of proteins was identified to have statistical significance between the BRCA-positive normal group (HP) and the BRCA-positive ovarian cancer patient group (OP) (see Example 3).

[0067] In another embodiment of the present disclosure, ROC curve analysis was performed and AUC values ​​were derived to investigate the accuracy of each of the 24 types of proteins to identify sensitivity and specificity (see Example 4).

[0068] In another embodiment of the present disclosure, 2-fold cross validation was repeated 50 times to verify the effectiveness of 24 types of proteins as markers, and multiple results were collected to obtain the final 11 types of biomarkers (see Example 5).

[0069] The term "hereditary ovarian cancer" used in the present disclosure refers to ovarian cancer that occurs due to a mutation or defective gene inherited from at least one parent, and in the present disclosure, hereditary ovarian cancer may be accompanied by a mutation in the BRCA1 or BRCA2 gene and does not necessarily mean that ovarian cancer is caused by a gene mutation.

[0070] The term "prediction" as used in the present disclosure refers to determining whether there is a possibility of developing hereditary ovarian cancer in a particular individual, whether the possibility of developing hereditary ovarian cancer is relatively high, or whether hereditary ovarian cancer has already occurred. The method of the present disclosure can be used to predict individuals with BRCA gene mutations as individuals with a high risk of developing hereditary ovarian cancer, and can be used to delay or prevent the development of the disease through special and appropriate management of these individuals.

[0071] In the present disclosure, the reagents for measuring the mRNA level of at least one gene may be sense and antisense primers or probes, each complementarily binding to the mRNA of the at least one gene.

[0072] The term "primer" used in the present disclosure is a short gene sequence that serves as a starting point for DNA synthesis, and refers to an oligonucleotide synthesized for diagnosis, DNA sequencing, etc. Primers can generally be synthesized to a length of 15-30 base pairs, but can vary depending on the purpose of use, and can be modified by methylation, capping, etc. by known methods.

[0073] The term "probe" used in the present disclosure refers to a nucleic acid capable of specifically binding to mRNA of a few bases to several hundred bases in length, which is produced by enzymatic chemical separation, purification or synthesis. Radioactive isotopes, enzymes or phosphors can be labeled to identify the presence or absence of mRNA, and can be designed and modified by known methods.

[0074] The reagent for measuring the protein level may be an antibody that specifically binds to a protein encoded by at least one gene, but is not limited thereto.

[0075] The term "antibody" used in the present disclosure includes immunoglobulin molecules that are immunoreactive with specific antigens, and includes monoclonal antibodies and polyclonal antibodies. In addition, antibodies include forms produced by genetic engineering, such as chimeric antibodies (e.g., humanized mouse antibodies) and heterologous antibodies (e.g., bispecific antibodies).

[0076] The kit for predicting the responsiveness of the anticancer agents of the present disclosure may comprise one or more other composition, solution or device suitable for the analytical method.

[0077] According to another aspect of the present disclosure, a method for providing information for predicting the occurrence of hereditary ovarian cancer is provided, the method comprising measuring the mRNA level of at least one gene in a biological sample derived from a subject or the protein level encoded by the at least one gene, the at least one gene being selected from the group consisting of: aldolase, fructose-bisphosphate A (ALDOA) ​​(GenBank Accession No.: NM_001243177), cadherin 2 (CDH2) (NM_001792, NM_001308176), latent transforming growth factor β-binding protein 1 (LTBP1) (NM_000627, NM_001166264, NM_001166265, NM_001166266, NM_206943), mannose receptor C-1 type (MRC1) (NM_002438), proplatelet basic protein white (PPBP) (NM_002704), retinol binding protein 4 (RBP4) (NM_001323517, NM_001323518, NM_006744), secreted acidic protein rich in cysteine ​​(SPARC) (NM_003118, NM_001309443, NM_001309444), serpin family A member 5 (SERPINA5) (NM_000624), serpin family C member 1 (SERPINC1) (NM_000488, NM_001365052), serpin family F member 2 (SERPINF2) (NM_000934, NM_001165920, NM_001165921) and thrombospondin 1 (THBS1) (NM_003246).

[0078] The term "method for providing information for predicting the occurrence of hereditary ovarian cancer" used in the present disclosure includes providing objective basic information necessary for predicting the occurrence of hereditary ovarian cancer as a preliminary step for predicting the occurrence of the disease, and excluding the clinical judgment or opinion of the doctor.

[0079] In embodiments of the present disclosure, the subject may have a mutation in the BRCA1 or BRCA2 gene.

[0080] In the present disclosure, when the mRNA level of at least one gene selected from RBP4, SERPINA5, SERPINC1 and SERPINF2 or the protein level encoded by the at least one gene is reduced compared with a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.

[0081] In the present disclosure, when the mRNA level of at least one gene selected from ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC and THBS1 or the protein level encoded by the at least one gene is increased compared with a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.

[0082] Biological samples derived from a patient may include, but are not limited to, whole blood, blood, saliva, tissue, cells, saliva, cerebrospinal fluid, and urine.

[0083] The expression level of mRNA can be measured by at least one selected from polymerase chain reaction (PCR), reverse transcription (RT)-PCR, real-time PCR, RNase protection assay (RPA), microarray and northern blotting, which are conventional methods known in the art, but are not limited thereto.

[0084] The expression level of the protein can be measured by at least one method selected from Western blotting, radioimmunoassay (RIA), radial immunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, Ouchterlony two-way immunodiffusion, complement fixation assay and protein chip, which are conventional methods known in the art, but are not limited thereto.

[0085] Hereinafter, preferred embodiments are presented to help understand the present disclosure. However, the following embodiments are provided to more easily understand the present disclosure, and the present disclosure is not limited to the following embodiments. Example

[0086] Example 1: Experimental method

[0087] 1-1. Recruitment and sample acquisition

[0088] All samples in this embodiment were processed after obtaining appropriate consent and approval from the Clinical Research Review Committee of Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea. Plasma samples were obtained from 20 ovarian cancer patients and 20 healthy normal groups before surgery. Plasma samples derived from ovarian cancer patients were provided by Seoul St. Mary's Hospital and the Korean Gynecologic Cancer Bank (KGCB), and plasma samples derived from healthy normal controls were obtained from subjects who underwent medical examinations at Seoul St. Mary's Hospital in the case of BRCA mutation-negative subjects, and from subjects who visited Seoul St. Mary's Hospital and agreed to blood sampling in the case of BRCA mutation-positive subjects. All samples were frozen with liquid nitrogen and stored at -80°C until use.

[0089] 1-2. Pretreatment of plasma samples

[0090] Plasma samples obtained from a normal group of 20 people (10 BRCA1 / 2 gene mutations, 10 non-mutations) and 20 ovarian cancer patients (10 BRCA1 / 2 gene mutations, 10 non-mutations) were pretreated according to the following procedure. More specifically, 40 μL of the plasma sample was injected into an HPLC multiple affinity removal system 14 (MARS14; Agilent Technologies, Inc.) column, and 14 proteins (albumin, immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), α1-antitrypsin, α1-acid glycoprotein, apolipoprotein A1, apolipoprotein A2, complement C3, transferrin, α2-macroglobulin, haptoglobin, fibrinogen, and transthyretin) present in high concentrations were removed from the column. Next, the low-concentration plasma protein was lyophilized and reabsorbed with 5% SDS and 50 mM of 1 M triethylammonium bicarbonate, dithiothreitol was added thereto to 20 mM, and the mixture was reacted at 95° C. for 10 minutes to reduce the disulfide bond. Then, for alkylation, iodoacetamide was added thereto to 40 mM, the mixture was reacted at room temperature in the dark for 30 minutes, and the mixture was filtered using an S-trap filter (S-TRAP TM, ProtiFi) drains the lysis buffer and solution to the outside of the filter, and then only the protein is confined in the filter, which is then centrifuged and washed. Subsequently, the filter is filled with digestion buffer, and then plasma protein and Lys-C / trypsin mixed enzyme (Promega) are added thereto at a mass ratio of 25:1, and then reacted at 37°C for 16 hours. Next, 100 μL of 0.1% formic acid is dissolved in the dried sample, and 5 μL of it is used for LC-MS / MS analysis.

[0091] 1-3. LC-MS / MS analysis

[0092] The Nano LC-Q-Exactive+ mass spectrometry analysis performed in Examples 1-2 was performed according to the following method.

[0093] i) First, fractionation was performed using a 50 cm C18 capillary column (OD 360Fm, ID 75Fm) for 200 min; ii) fractionation was performed in a gradient (5-45% acetonitrile and 0.1% formic acid) for 150 min; iii) data on the top 20 intensity precursors were collected in data dependent acquisition (DDA) mode; then iv) the collected data were compared with the human SWISSPROT sequence database using the Proteome discoverer 2.2 program to identify peptides and proteins, and analyzed for biomarker discovery by quantifying the results of label-free quantification (LFQ) values ​​of proteins using the MS1 peak intensity of the identified peptides by the parsimony (maximum information using minimum data) method.

[0094] 1-4. Data Analysis

[0095] In order to compare the amount of target protein in plasma samples, six new plasma proteins were found as correctable normalization factors without showing intergroup differences between endogenous plasma proteins. The six proteins were thyroxine binding globulin (TBG), complement factor I (CFI), complement component C6 (C6), plastin-2 (PLS2), complement C2 (C2), and complement factor H (CFH). The LFQ values ​​of representative peptides of the six proteins were divided by the median LFQ value of each peptide from the original values ​​in plasma of a total of 40 subjects.

[0096] During statistical analysis, normalized values ​​were used to obtain P values ​​by Mann-Whitney test, and proteins with quantitative differences of two-fold or more between the two groups and P values ​​less than 0.05 / 374 by Bonferonni correction as a post-test were found.

[0097] Example 2: Discovery of candidate proteins with specific expression changes in hereditary ovarian cancer patients

[0098] In order to discover biomarkers that can predict the occurrence of hereditary ovarian cancer, the inventors of the present application attempted to discover proteins that are differentially expressed in plasma samples according to the two schemes shown in Figure 1A, and conducted a comprehensive analysis of them to obtain markers with specific expression changes in hereditary ovarian cancer patients with BRCA gene mutations.

[0099] 2-1. Identification of differentially expressed proteins between BRCA mutation-positive subjects (Scheme I)

[0100] First, the plasma samples obtained from the BRCA mutation-positive (BRCA+) normal group and ovarian cancer patients were used for analysis by the methods described in Examples 1-2 and 1-3, and the proteins differentially expressed according to the statistical analysis criteria of Example 1-4 were analyzed using a volcano plot. As a result, as shown in FIG1B , 19 types of proteins whose expression was significantly decreased and 61 types of proteins whose expression was significantly increased were found in BRCA mutation-positive ovarian cancer patients.

[0101] In addition, each protein whose expression was decreased and each protein whose expression was increased were distinguished by network analysis based on the function of the protein. As a result, as shown in FIG1C , 19 types of proteins whose expression was decreased in BRCA-positive ovarian cancer patients were confirmed to be related to triglyceride catabolism, acute phase reaction, and coagulation fibrin thrombus formation, and 61 types of proteins whose expression was increased in BRCA-positive ovarian cancer patients were confirmed to be representatively related to hydrogen peroxide metabolism, NADH metabolism, regulation of interleukin-8 production, interleukin-12-mediated signaling pathway, apoptosis regulation by oxidative stress, platelet aggregation, and positive regulation of viral processes by the host.

[0102] 2-2. Identification of differentially expressed proteins between normal controls and ovarian cancer patients (Scheme II)

[0103] In this example, regardless of whether the BRCA gene is mutated, all normal groups and ovarian cancer patients are targeted, and differentially expressed proteins in plasma samples derived from all normal groups and ovarian cancer patients are obtained in a manner similar to Example 2-1. The results confirmed that the expression of 13 types of proteins in the normal group was significantly increased, and the expression of 48 types of proteins in ovarian cancer patients was significantly increased.

[0104] 2-3. Identification of proteins with specific altered expression in patients with hereditary ovarian cancer

[0105] Then, the results obtained in Examples 2-1 and 2-2 were comprehensively analyzed. FIG. 1D shows a comparison between the number of proteins whose expression increased in each group of the BRCA mutation-positive normal group (BRCA+ subject: HC), the normal group (HC), the BRCA mutation-positive ovarian cancer patient group (BRCA+ subject: OC), and the ovarian cancer patient group (OC), and in FIG. 1E , a Venn diagram is used to distinguish common proteins among proteins whose expression increased in each group and proteins whose expression increased only in one group. As a result, it was confirmed that among the proteins whose expression increased in each of the BRCA mutation-positive normal group and all normal groups, 10 proteins were common, and among the proteins whose expression increased in each of the BRCA mutation-positive ovarian cancer patients and all ovarian cancer patients, 46 proteins were common.

[0106] According to the above results, in addition to proteins whose expression is commonly increased, proteins whose expression is decreased or increased only in the BRCA mutation-positive normal group, that is, 9 types of proteins whose expression is decreased only in the BRCA mutation-positive ovarian cancer patient group and 15 types of proteins whose expression is increased only in the BRCA mutation-positive ovarian cancer patient group were separated, and these 24 types of proteins were obtained as a candidate group of markers for predicting the occurrence of hereditary ovarian cancer. Information on the 9 types and 15 types of proteins and the genes encoding them are shown in Tables 1 and 2, respectively.

[0107] [Table 1]

[0108] index Uniprot ID Gene Protein name 1 P05154 SERPINA5 Serine protease inhibitors 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

[0109] [Table 2]

[0110] index UniprotID Gene Protein name 1 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 β-Hexosaminidase subunit β 9 P07996 THBS1 Thrombospondin-1 10 P09486 SPARC Osteonectin 11 P19022 CDH2 E-cadherin-2 12 P22897 MRC1 Macrophage mannose receptor 1 13 P34932 HSPA4 70kDa heat shock protein 4 14 P78509 RELN Reelin 15 Q14766-4 LTBP1 Latent transforming growth factor-β binding protein 1

[0111] Example 3: Is there a statistically significant difference in the expression of specific altered proteins in patients with hereditary ovarian cancer? Sexual Analysis

[0112] The inventors of the present application analyzed whether there was statistical significance in the difference in protein expression levels among the four groups (BRCA-negative normal group (HN), BRCA-positive normal group (HP), BRCA-negative ovarian cancer patient group (ON), and BRCA-positive ovarian cancer patient group (OP)) for each of the 24 types of proteins whose expression was specifically changed in BRCA mutation-positive ovarian cancer patients obtained by Example 2.

[0113] The results of 9 types of proteins whose expression was decreased in ovarian cancer patients with BRCA mutations are shown in Figures 2A to 2E, and the results of 15 types of proteins whose expression was increased are shown in Figures 3A to 3H. As a result of the analysis, it was confirmed that all 24 types of proteins had significant differences in expression levels between the BRCA mutation-positive normal group and the BRCA mutation-positive ovarian cancer patient group. In Table 3 below, the average expression levels and standard deviations of 24 types of proteins in the BRCA mutation-positive normal group and the BRCA mutation-positive ovarian cancer patient group are shown.

[0114] [Table 3]

[0115]

[0116]

[0117] Example 4: Sensitivity and specificity analysis of 24 types of markers

[0118] The inventors of the present application attempted to analyze sensitivity and specificity, and therefore performed ROC curve analysis to identify the accuracy of 24 types of markers whose expression was significantly changed in the BRCA mutation-positive ovarian cancer patient group. Sensitivity and specificity were evaluated by calculating the area under the ROC curve (AUC).

[0119] The results for 9 types of proteins whose expression is decreased in ovarian cancer patients with BRCA mutations are shown in Figures 4A-4E and Table 4, and the results for 15 types of proteins whose expression is increased are shown in Figures 5A-5H and Table 5. When area = 1, the test data set is judged to have perfect accuracy, and when area = 0.5, it is judged to have worthless accuracy. The accuracy criteria according to the AUC value 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 = failure (F).

[0120] [Table 4]

[0121]

[0122]

[0123] [Table 5]

[0124] index UniProt ID Gene Protein name AUC value 1 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 β-Hexosaminidase subunit β 0.755 9 P07996 THBS1 Thrombospondin-1 0.667 10 P09486 SPARC Osteonectin 0.664 11 P19022 CDH2 E-cadherin-2 0.868 12 P22897 MRC1 Macrophage mannose receptor 1 0.816 13 P34932 HSPA4 70kDa heat shock protein 4 0.826 14 P78509 RELN Reelin 0.760 15 Q14766.4 LTBP1 Latent transforming growth factor-β binding protein 1 0.674

[0125] Example 5: Verification of the effectiveness of 24 types of markers

[0126] The inventors of the present application attempted to verify the effectiveness of 24 types of markers whose expression was significantly changed in the BRCA mutation-positive ovarian cancer patient group as specific biomarkers that can predict the occurrence of hereditary ovarian cancer. To this end, 2-fold cross validation was repeated 50 times for each of the 24 types of proteins. Figure 6 A schematic diagram of the validation process is shown.

[0127] Through analysis, the optimal K value (which is a variable selected from the 24 types of candidate histones) was 15, the cross-validated AUC value was 0.983 or higher, 15 proteins with a probability of 0.70 or higher were selected (selected K = 7), and 7 proteins were selected through literature, etc. In addition, among the 24 types of candidate histones, PPBP, SPARC, THBS1, and LTBP1 proteins were added, and their expressions showed significant differences between the BRCA mutation-positive normal group and ovarian cancer patients, and their expressions showed significant differences between the BRCA mutation-positive group and the BRCA mutation-negative group.

[0128] Therefore, through the above examples, the following 11 types were finally found as biomarkers for predicting the occurrence of ovarian cancer after BRCA mutation, and information about these 11 types of biomarkers is shown in the following Table 6.

[0129] [Table 6]

[0130]

[0131]

[0132] Industrial Applicability

[0133] According to the present disclosure, 11 types of biomarkers whose expression is specifically altered in ovarian cancer patients with BRCA gene mutations were discovered, and their effectiveness was verified, because in clinical practice, by measuring the levels of mRNA or protein of 11 types of biomarker genes from subjects with BRCA gene mutations, information on whether ovarian cancer occurs can be provided at an early stage, the disease can be prevented, and the biomarkers can be effectively used as target molecules to develop targeted therapeutics for hereditary ovarian cancer accompanied by BRCA gene mutations.

Claims

1. Use of a reagent in preparing a kit for predicting the occurrence of hereditary ovarian cancer, wherein the reagent is used to measure the mRNA level of the retinol binding protein 4 (RBP4) gene or the protein level encoded by the gene, and the mRNA level of at least one gene selected from the following or the protein level encoded by the at least one gene: aldolase, fructose-bisphosphate A (ALDOA), cadherin 2 (CDH2), mannose receptor C-1 type (MRC1), proplatelet basic protein (PPBP), serpin family A member 5 (SERPINA5), serpin family C member 1 (SERPINC1), and thrombospondin 1 (THBS1), and The hereditary ovarian cancer is accompanied by a mutation in the BRCA1 or BRCA2 gene.

2. The use according to claim 1, wherein the kit further comprises a reagent for measuring at least one gene selected from the group consisting of latent transforming growth factor β-binding protein 1 (LTBP1), secreted acidic protein rich in cysteine ​​(SPARC) and serpin family F member 2 (SERPINF2) or a protein encoded by the at least one gene.

3. Use of a reagent in preparing a composition for predicting the occurrence of hereditary ovarian cancer, wherein the reagent is used to measure the mRNA level of the retinol binding protein 4 (RBP4) gene or the protein level encoded by the gene, and the mRNA level of at least one gene selected from the group consisting of aldolase, fructose-bisphosphate A (ALDOA), cadherin 2 (CDH2), mannose receptor C-1 type (MRC1), proplatelet basic protein (PPBP), serpin family A member 5 (SERPINA5), serpin family C member 1 (SERPINC1), and thrombospondin 1 (THBS1), The hereditary ovarian cancer is accompanied by a mutation in the BRCA1 or BRCA2 gene.

4. The use according to claim 3, wherein the composition further comprises an agent for measuring at least one gene selected from the group consisting of latent transforming growth factor β-binding protein 1 (LTBP1), secreted acidic protein rich in cysteine ​​(SPARC) and serpin family F member 2 (SERPINF2) or a protein encoded by the at least one gene.

5. The use according to claim 1 or 3, wherein the reagent for measuring the mRNA level of at least one gene is a sense and antisense primer, or a probe, each of which complementarily binds to the mRNA of the at least one gene.

6. The use according to claim 1 or 3, wherein the reagent for measuring protein levels is an antibody that specifically binds to the protein encoded by the at least one gene.

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