CN113286898A - Biomarkers for predicting genetic ovarian carcinogenesis and uses thereof - Google Patents

Biomarkers for predicting genetic ovarian carcinogenesis and uses thereof Download PDF

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CN113286898A
CN113286898A CN201980088377.8A CN201980088377A CN113286898A CN 113286898 A CN113286898 A CN 113286898A CN 201980088377 A CN201980088377 A CN 201980088377A CN 113286898 A CN113286898 A CN 113286898A
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崔伦瞋
扈净允
金敬坤
许修荣
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Industry Academic Cooperation Foundation of Catholic University of Korea
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Abstract

The present disclosure relates to biomarkers for predicting genetic ovarian carcinogenesis and uses thereof, and more particularly, to marker compositions for predicting genetic ovarian carcinogenesis, compositions and kits for predicting genetic ovarian carcinogenesis, and methods of providing information for predicting genetic ovarian carcinogenesis. The presence or absence of genetic ovarian carcinogenesis accompanied by BRCA mutation 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 genetic ovarian cancer targeting the biomarkers.

Description

Biomarkers for predicting genetic ovarian carcinogenesis and uses thereof
Technical Field
The present disclosure relates to biomarkers for predicting genetic ovarian carcinogenesis and uses thereof, and more particularly, to marker compositions for predicting genetic ovarian carcinogenesis, compositions and kits for predicting genetic ovarian carcinogenesis, and methods of predicting genetic ovarian carcinogenesis.
Background
Ovarian cancer is one of the first ten cancers and causes of death that occur in korean women, and over 60% of ovarian cancer patients are diagnosed as advanced stage, and the 5-year survival rate at this time is less than 30%. Symptoms of ovarian cancer are not obvious and abdominal distension, dyspepsia, diarrhea, and constipation are difficult to identify as symptoms of ovarian cancer. Moreover, and most importantly, there is no effective detection method that can detect ovarian cancer at an early stage. Therefore, effective means for prevention and early detection of ovarian cancer is an unmet important medical need.
It is known that about 25% of high-grade serous ovarian cancers (which are the most common type of ovarian cancer) are associated with the BRCA1 gene. The BRCA1 gene is located on chromosome 17, has been primarily demonstrated as a gene that increases the risk of developing breast and ovarian cancer, and after BRCA1, BRCA2 has also been reported to increase the risk of developing the above cancer types. The probability of ovarian carcinogenesis in humans with the BRCA1 mutation reaches 44% before the age of 70 years, and the mutated BRCA gene can be inherited not only from the maternal line, but also from the paternal line. It is known that approximately 10% of ovarian cancers are associated with mutations in the genes BRCA1 and BRCA2, and when there are mutations in both genes, the incidence of ovarian cancer increases by 10-fold or more compared to normal persons, and the recurrence rate of ovarian cancer also increases. Furthermore, BRCA1 (23.8%) and BRCA2 (25.7%) were reported to be accompanied by BRCA mutations (Choi et al, jgo.2016) in korean ovarian cancer patients regardless of family history.
However, despite these effects of BRCA mutation, salpingo-oophorectomy (RRSO), which prophylactically reduces the risk, is the only method of preventing ovarian cancer caused by BRCA mutations, and no other methods have been established. In women of childbearing age, "prophylactic reduced risk salpingo-oophorectomy" causes menopause to advance, resulting in a reduced quality of life, and the proportion of korean elderly mothers (>35 year old children) increases from 11% in 1999 to 28.6% in 2009, which means a 17.6% increase in 10 years, resulting in a reduction in the number of BRCA1 carriers who can practice RRSO at the right time. Therefore, there is an urgent need to develop a method other than RRSO that it can predict and prevent the occurrence of ovarian cancer.
In recent studies on breast cancer and BRCA genes, it has been suggested that RANKL/RANK inhibitors, such as denosumab, may act as prophylactic agents for breast cancer in BRCA positive subjects. Based on this, it was judged that there is a need to find biomarkers that can predict hereditary ovarian cancer, and further to develop hereditary ovarian cancer therapeutics that use target inhibitors of selective biomarkers as therapies other than RRSO.
BRIEF SUMMARY OF THE PRESENT DISCLOSURE
Technical problem
As described above, as a result of research work predicting whether there is genetic ovarian carcinogenesis accompanied by a mutation in the BRCA gene and also presenting a target for development of a therapeutic agent for the disease, the inventors of the present application found 11 types of markers, the expression of which is significantly changed in ovarian cancer patients having a BRCA mutation compared to normal persons having a BRCA mutation, thereby completing the present disclosure.
Accordingly, the present disclosure relates to providing marker compositions for predicting the occurrence of hereditary ovarian cancer.
In addition, the present disclosure relates to providing a composition for predicting genetic ovarian carcinogenesis and a kit for predicting genetic ovarian carcinogenesis, which includes the composition.
In addition, the present disclosure relates to methods of providing information for predicting the occurrence of hereditary ovarian cancer.
However, the 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 from the following description by those skilled in the art.
Technical scheme
To achieve the object of the present disclosure as described above, one aspect of the present disclosure provides a marker composition for predicting genetic ovarian carcinogenesis, the marker composition comprising at least one gene or a protein encoded by the at least one gene 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
Furthermore, another aspect of the present disclosure provides a composition for predicting genetic ovarian carcinogenesis comprising the composition comprising a reagent for measuring the mRNA level of at least one gene 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
In embodiments of the disclosure, the hereditary ovarian cancer may be accompanied by a mutation in BRCA1 or BRCA2 gene.
In another embodiment of the disclosure, the agent for measuring the mRNA level of at least one gene may be sense and antisense primers or probes, each complementary to bind the mRNA of the at least one gene.
In another embodiment of the present disclosure, the reagent for measuring the level of protein may be an antibody that specifically binds to the protein encoded by the at least one gene.
Furthermore, a further 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 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
In embodiments of the present disclosure, the subject may have a mutation in BRCA1 or BRCA2 gene.
In another embodiment of the present disclosure, when the mRNA level of at least one gene selected from RBP4, SERPINA5, serpinac 1 and serpinaf 2, or the protein level encoded by said at least one gene, is decreased compared to a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.
In another embodiment of the present disclosure, when the mRNA level of at least one gene selected from the group consisting of ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC, and THBS1, or the protein level encoded by the at least one gene is increased as compared to a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.
In another embodiment of the present disclosure, the expression level of mRNA may 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.
In another embodiment of the present disclosure, the expression level of the protein may be measured by at least one method selected from the group consisting of: western blotting, Radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, Ouchterlony double immunodiffusion, complement fixation assay, and protein chips.
Advantageous effects
In the present disclosure, since 11 types of biomarkers capable of early predicting the occurrence of hereditary ovarian cancer in a subject having a mutation in the BRCA gene were found, the occurrence of hereditary ovarian cancer accompanied by a mutation in BRCA can be early predicted by measuring the mRNA or protein level of the biomarker gene according to the present disclosure, and the biomarkers can be effectively used for developing a therapeutic agent for hereditary ovarian cancer by targeting the biomarkers.
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FIG. 1A is an experimental protocol for the discovery of 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 accompanied by a BRCA gene mutation.
Fig. 1B shows the results of analyzing differentially expressed proteins using volcano plots (volcano plot) using plasma samples obtained from BRCA mutation-positive normal group and ovarian cancer patients.
FIG. 1C shows an analysis of the function of the 19 types of proteins with reduced expression and the corresponding proteins with increased expression of 61 types of proteins in ovarian cancer patients as a result of the analysis of FIG. 1B by a network analysis.
FIG. 1D is a result of comparing the amount of protein expressed significantly increased in each of BRCA mutation-positive normal group (BRCA + subject: HC), normal group (HC), BRCA mutation-positive ovarian cancer patient (BRCA + subject: OC), and ovarian cancer patient (OC).
Fig. 1E is the results of the venn diagram after comparative analysis of the proteins identified in the four groups of fig. 1D, and the results of the 24 types of proteins obtained therefrom, the expression of which is specifically reduced or increased only in the BRCA mutation-positive ovarian cancer patient group.
Fig. 2A is a result of analyzing whether there was a statistical significance in the difference in the protein expression level between 4 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 9 types of proteins whose expression specificity was reduced in BRCA mutation-positive ovarian cancer patients.
Fig. 2B is a result of analyzing whether there was a statistical significance in the 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 specificity was decreased in BRCA mutation-positive ovarian cancer patients.
Fig. 2C is a result of analyzing whether there was a statistical significance in the differences in protein expression levels between the four identical groups as shown in fig. 2A for each of SELL and APOC3 among the 9 types of proteins whose expression specificity was reduced in BRCA mutation-positive ovarian cancer patients.
Fig. 2D is a result of analyzing whether there was a statistical significance in the differences in protein expression levels between the same four groups as shown in fig. 2A for each of SERPINF2 and SERPINC1 among 9 types of proteins whose expression specificity was decreased in BRCA mutation-positive ovarian cancer patients.
FIG. 2E is a result of analyzing whether there was a statistical significance in the differences in protein expression levels between the same four groups as shown in FIG. 2A for RBP4 among 9 types of proteins whose expression specificity was decreased in BRCA mutation-positive ovarian cancer patients.
Fig. 3A is a result of analyzing whether there was a statistical significance in the difference in protein expression level between 4 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 15 types of proteins whose expression was specifically increased in BRCA mutation-positive ovarian cancer patients.
Fig. 3B is a result of analyzing whether there was a statistical significance in the difference in protein expression level between the same four groups as shown in fig. 3A for each of ALDOA and VWF among 15 types of proteins whose expression specificity was increased in BRCA mutation-positive ovarian cancer patients.
Fig. 3C is a result of analyzing whether there was a statistical significance in the 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 specificity was increased in BRCA mutation-positive ovarian cancer patients.
Fig. 3D is a result of analyzing whether there was a statistical significance in the differences in protein expression levels between the same four groups as shown in fig. 3A for each of PSAP and HEXB among the 15 types of proteins whose expression specificity was increased in BRCA mutation-positive ovarian cancer patients.
Fig. 3E is a result of analyzing whether there was a statistical significance in the 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 specificity was increased in BRCA mutation-positive ovarian cancer patients.
Fig. 3F is a result of analyzing whether there was a statistical significance in the 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 was specifically increased in BRCA mutation-positive ovarian cancer patients.
Fig. 3G is a result of analyzing whether there was a statistical significance in the differences in protein expression levels between the same four groups as shown in fig. 3A for each of HSPA4 and RELN among the 15 types of proteins whose expression was specifically increased in BRCA mutation-positive ovarian cancer patients.
FIG. 3H is a result of analyzing whether there was a statistical significance in the differences in protein expression levels between the same four groups as shown in FIG. 3A for LTBP1 among 15 types of proteins whose expression was specifically increased in BRCA mutation-positive ovarian cancer patients.
FIG. 4A is a result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of each of SERPINA5 (Unit ID: P5154) and IGFBP5 (P2493) in 9 types of proteins whose expression specificity was decreased in BRCA mutation-positive ovarian cancer patients.
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) in 9 types of proteins whose expression specificity was decreased in BRCA mutation-positive ovarian cancer patients.
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) in 9 types of proteins with reduced expression specificity in BRCA mutation-positive ovarian cancer patients.
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) in 9 types of proteins whose expression specificity was reduced in BRCA mutation-positive ovarian cancer patients.
Fig. 4E is a result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of RBP4(P02753) among 9 types of proteins whose expression specificity was reduced in BRCA mutation-positive ovarian cancer patients.
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.
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) in 15 types of proteins whose expression specificity was increased in BRCA mutation-positive ovarian cancer patients.
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) in 15 types of proteins whose expression was specifically increased in BRCA mutation-positive ovarian cancer patients.
Fig. 5D is a result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of each of PSAP (P07602.3) and HEXB (P07686) among 15 types of proteins whose expression specificity was increased in BRCA mutation-positive ovarian cancer patients.
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 specificity was increased in BRCA mutation-positive ovarian cancer patients.
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 was specifically increased in BRCA mutation-positive ovarian cancer patients.
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) of the 15 types of proteins whose expression specificity was increased in BRCA mutation-positive ovarian cancer patients.
FIG. 5H is a result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of LTBP1(Q14766.4) among 15 types of proteins whose expression is specifically increased in BRCA mutation-positive ovarian cancer patients.
Figure 6 shows a schematic of a 2-fold cross-validation to validate the effectiveness of 24 types of marker candidate sets.
Best mode for carrying out the invention
As a result of research work predicting hereditary ovarian cancer accompanied by BRCA gene mutation and also presenting a target for developing a therapeutic agent for the disease, the inventors of the present application discovered 11 types of markers and verified their effectiveness, thereby completing the present disclosure, the expression of which is significantly altered in ovarian cancer patients having BRCA mutation compared to normal persons having BRCA mutation.
Accordingly, there is provided a marker composition for predicting the occurrence of hereditary ovarian cancer, the marker composition comprising at least one gene or a protein 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
Further, there is provided a composition for predicting the occurrence of hereditary ovarian cancer, the composition comprising an agent for measuring the mRNA level of at least one gene 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
In addition, a kit for predicting the occurrence of hereditary ovarian cancer is provided, which comprises the composition.
The inventors of the present application found 11 types of biomarkers that can predict the occurrence of hereditary ovarian cancer through specific embodiments and confirmed the effectiveness thereof.
In an embodiment of the present disclosure, plasma samples of the BRCA mutation-positive normal group and the BRCA mutation-positive ovarian cancer patient group are used to identify 19 types of proteins whose expression is significantly reduced and 61 types of proteins whose expression is significantly increased in the ovarian cancer patient group as compared to the normal group, and to exclude from the above proteins those proteins that overlap with proteins whose expression is increased in all normal and ovarian cancer patient groups, respectively, and are unrelated to the BRCA mutation, to obtain 24 types of marker candidate histones whose expression is specifically significantly altered in the BRCA mutation-positive ovarian cancer patient group (see example 2).
In another embodiment of the present disclosure, each of the 24 types of proteins was analyzed for the presence or absence of statistical significance of the difference in protein expression level between 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), and each of the 24 types of proteins was identified as statistically significant between the BRCA-positive normal group (HP) and the BRCA-positive ovarian cancer patient group (OP) (see example 3).
In another embodiment of the present disclosure, ROC curve analysis is performed and AUC values are derived to investigate the accuracy of each of the 24 types of proteins to identify sensitivity and specificity (see example 4).
In another embodiment of the present disclosure, 2-fold cross-validation is repeated 50 times to validate the 24 types of proteins as markers and multiple results are collected to obtain the final 11 types of biomarkers (see example 5).
The term "hereditary ovarian cancer" as used in the present disclosure refers to ovarian cancer that occurs as a result of 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 the ovarian cancer is caused by a genetic mutation.
The term "predicting" as used in this disclosure refers to determining whether there is a likelihood of developing hereditary ovarian cancer, whether there is a relatively high likelihood of developing hereditary ovarian cancer, or whether hereditary ovarian cancer has already developed in a particular individual. The methods of the present disclosure can be used to predict individuals with mutations in the BRCA gene as individuals at high risk of developing hereditary ovarian cancer, and can be used to delay or prevent the progression of disease through specific and appropriate management of these individuals.
In the present disclosure, the agent for measuring the mRNA level of at least one gene may be sense and antisense primers or probes, each complementary binding to the mRNA of the at least one gene.
The term "primer" as used in the present disclosure is a short gene sequence that serves as an origin of DNA synthesis, and refers to an oligonucleotide that is synthesized for diagnosis, DNA sequencing, and the like. The primer may be generally synthesized to a length of 15 to 30 base pairs, but may vary depending on the purpose of use, and may be modified by methylation, capping, or the like by a known method.
The term "probe" as used in the present disclosure refers to a nucleic acid capable of specifically binding to an mRNA of several bases to several hundred bases in length, which is produced by enzymatic chemical isolation purification or synthesis. Radioisotopes, enzymes, or phosphors may be labeled to identify the presence of mRNA, and may be designed and modified by known methods.
The reagent for measuring the protein level may be an antibody that specifically binds to the protein encoded by at least one gene, but is not limited thereto.
The term "antibody" as used in the present disclosure includes immunoglobulin molecules that are immunoreactive with a particular antigen, and includes monoclonal and polyclonal antibodies. In addition, antibodies include forms produced by genetic engineering, such as chimeric antibodies (e.g., humanized murine antibodies) and heterologous antibodies (e.g., bispecific antibodies).
Kits for predicting the responsiveness of an anti-cancer agent of the present disclosure may comprise one or more other compositions of compositions, solutions, or devices suitable for the assay method.
According to another aspect of the present disclosure, there is provided a method of providing information for predicting the occurrence of hereditary ovarian cancer, the method comprising measuring the mRNA level of at least one gene 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
The term "method for providing information for predicting the occurrence of hereditary ovarian cancer" as used in the present disclosure includes, as a preliminary step for predicting the occurrence of a disease, providing objective basic information necessary for predicting the occurrence of hereditary ovarian cancer and excluding the clinical judgment or opinion of a doctor.
In embodiments of the present disclosure, the subject may have a mutation of the BRCA1 or BRCA2 gene.
In the present disclosure, when the mRNA level of at least one gene selected from RBP4, SERPINA5, serpinac 1, and serpinaf 2, or the protein level encoded by the at least one gene is decreased as compared to a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.
In the present disclosure, when the mRNA level of at least one gene selected from the group consisting of ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC, and THBS1, or the protein level encoded by the at least one gene is increased as compared to a healthy normal control group, the occurrence of hereditary ovarian cancer can be predicted.
Biological samples derived from a patient may include, but are not limited to, whole blood, saliva, tissue, cells, saliva, cerebrospinal fluid, and urine.
The expression level of mRNA may be measured by at least one selected from the group consisting of Polymerase Chain Reaction (PCR), Reverse Transcription (RT) -PCR, real-time PCR, Rnase Protection Assay (RPA), microarray, and northern blot, which are conventional methods known in the art, but is not limited thereto.
The expression level of the protein may be measured by at least one method selected from the group consisting of western blot, Radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, Ouchterlony double immunodiffusion, complement fixation assay, and protein chip, which are conventional methods known in the art, but is not limited thereto.
In the following, preferred embodiments are presented to aid in understanding the present disclosure. However, the following examples are provided for easier understanding of the present disclosure, and the present disclosure is not limited by the following examples.
Examples
Example 1: experimental methods
1-1 recruiting subjects and obtaining samples
All samples in this example were processed after appropriate approval and approval by The clinical research review board of The Seoul St. Plasma samples were obtained from 20 ovarian cancer patients and a healthy normal group of 20 individuals prior to surgery. Plasma samples derived from patients with ovarian Cancer were provided by seoul saint hospital and the Korean Gynecological Cancer Bank (KGCB), and plasma samples derived from healthy normal control groups were obtained from subjects who were medically examined at seoul saint hospital in the case of BRCA mutation-negative subjects, and from subjects who visited seoul saint hospital and were blood-collected identically in the case of BRCA mutation-positive subjects. All samples were frozen with liquid nitrogen and stored at-80 ℃ until use.
1-2 pretreatment of plasma samples
Plasma samples obtained from a normal group of 20 persons (10 BRCA1/2 gene mutations, 10 non-mutated) and 20 ovarian cancer patients (10 BRCA1/2 gene mutations, 10 non-mutated) were pretreated according to the following procedure. More specifically, 40 μ L of plasma sample was used for injection into an HPLC multiple affinity removal System 14(MARS 14; Agilent Technologies, Inc.) column from which 14 proteins (albumin, immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), α 1-antitrypsin, α 1-acid glycoprotein, apolipoprotein A1, apolipoprotein A2, complement C3, transferrin, α 2-macroglobulin, haptoglobin, fibrinogen and transthyretin) present in high concentrations were removed. Next, low concentration plasma protein was lyophilized and reabsorbed with 5% SDS and 50mM of 1M triethylammonium bicarbonate, dithiothreitol was added thereto to 20mM, and then the mixture was reacted at 95 ℃ for 10 minutes, thereby reducing disulfide bonds. Then, for alkylation, iodoacetamide was added thereto to 40mM, and the mixture was reacted at room temperature for 30 minutes under dark conditions using a S-TRAP filter (S-TRAP)TMProtiFi) drained the lysis buffer and solution outside the filter, then only the proteins were confined in the filter, then centrifuged and washed. Subsequently, the filter was filled with digestion buffer, and then plasma protein and Lys-C/trypsin cocktail (Promega) were added thereto at a mass ratio of 25:1, followed by reaction at 37 ℃ for 16 hours. Next, 100. mu.L of 0.1% formic acid was dissolved in the dried sample, and 5. mu.L thereof was used for LC-MS/MS analysis.
LC-MS/MS analysis
The Nano LC-Q-active + mass spectrometry analysis performed in example 1-2 was performed according to the following method.
i) First, fractionation was performed for 200 minutes using a 50cm C18 capillary column (OD 360Fm, ID 75 Fm); ii) fractionation in a gradient (5-45% acetonitrile and 0.1% formic acid) for 150 minutes; iii) collecting data on the first 20 intensity precursors in a Data Dependent Acquisition (DDA) mode; then iv) the collected data were compared to the human SWISSPROT sequence database using the protome resolver 2.2 program to identify peptides and proteins and analyzed for biomarkers by the reduced (maximum information using minimal data) method using MS1 peak intensity of the identified peptides by quantifying the results of label-free quantification (LFQ) values of proteins.
1-4. analysis of data
To compare the amount of target protein in plasma samples, six new plasma proteins were found as correctable normalization factors, and no inter-group differences between endogenous plasma proteins were shown. The six proteins are thyroxine-binding globulin (TBG), Complement Factor I (CFI), complement component C6(C6), plastin-2 (PLS 2), complement C2(C2) and Complement Factor H (CFH). LFQ values for representative peptides of six proteins were divided by the median LFQ value for each peptide from the original values in plasma for a total of 40 subjects.
During the statistical analysis, P-values were obtained by the mann-whitney test using normalized values, and it was found that the quantitative difference between the two groups was two or more times, while protein having P-values less than 0.05/374 was post-tested by Bonferonni correction.
Example 2: in thatCandidate proteins with altered expression specificity found in patients with hereditary ovarian cancer
In order to find biomarkers that can predict the occurrence of hereditary ovarian cancer, the inventors of the present application tried to find proteins differentially expressed in plasma samples according to the two protocols shown in fig. 1A and comprehensively analyzed them to obtain markers whose expression is specifically changed in hereditary ovarian cancer patients accompanied by mutations in the BRCA gene.
Identification of proteins differentially expressed between BRCA mutation-positive subjects (scheme I)
First, analysis was performed by the methods described in examples 1-2 and 1-3 using plasma samples obtained from BRCA mutation positive (BRCA +) normal groups and ovarian cancer patients, and analysis of the proteins differentially expressed according to the statistical analysis criteria of examples 1-4 using volcano plots. As a result, as shown in fig. 1B, 19 types of proteins whose expression was significantly reduced and 61 types of proteins whose expression was significantly increased were found in BRCA mutation-positive ovarian cancer patients.
In addition, each protein with reduced expression is distinguished from each protein with increased expression by network analysis based on the function of the protein. As a result, as shown in fig. 1C, it was confirmed that 19 types of proteins whose expression was decreased in BRCA-positive ovarian cancer patients were associated with triglyceride catabolism, acute phase reaction, and thrombopoiesis, and that 61 types of proteins whose expression was increased in BRCA-positive ovarian cancer patients were representatively associated with hydrogen peroxide metabolism, NADH metabolism, regulation of interleukin-8 production, interleukin-12-mediated signaling pathway, apoptotic regulation by oxidative stress, platelet aggregation, and positive regulation of viral processes by the host.
2-2 identification of proteins differentially expressed in Normal group and ovarian cancer patients (scheme II)
In this example, proteins that are differentially expressed in plasma samples targeted to and derived from all normal groups and ovarian cancer patients, regardless of whether the BRCA gene is mutated, were obtained in a manner similar to example 2-1. The results confirmed a significant increase in the expression of 13 types of proteins in the normal group, and a significant increase in the expression of 48 types of proteins in ovarian cancer patients.
2-3 identification of proteins with altered expression specificity in patients with hereditary ovarian cancer
Then, the results obtained in examples 2-1 and 2-2 were analyzed in combination. FIG. 1D shows a comparison between the amounts of proteins whose expression is increased in each 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 the proteins whose expression is increased in each group from the common proteins in the proteins whose expression is increased in only one group. As a result, it was confirmed that 10 proteins were common among the proteins whose expression was increased in each of the BRCA mutation-positive normal group and all normal groups, and 46 proteins were common among the proteins whose expression was increased in each of the BRCA mutation-positive ovarian cancer patients and all ovarian cancer patients.
According to the above results, in addition to the proteins whose expression is increased in common, 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 isolated, and these 24 types of proteins were obtained as a marker candidate group for predicting the occurrence of hereditary ovarian cancer. Information on the 9 and 15 types of proteins and the genes encoding them are shown in tables 1 and 2, respectively.
[ Table 1]
Index Uniprot ID Gene Name of protein
1 P05154 SERPINA5 Plasma 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
[ Table 2]
Index UniprotID Gene Name of protein
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 Prosphingolipid activator (Prosaposin)
8 P07686 HEXB Beta-hexosaminidase subunit beta
9 P07996 THBS1 Thrombospondin-1
10 P09486 SPARC Osteonectins
11 P19022 CDH2 Cadherin-2
12 P22897 MRC1 Macrophage mannose receptor 1
13 P34932 HSPA4 70kDa heat shock protein 4
14 P78509 RELN Fibrillation proteins (Reelin)
15 Q14766-4 LTBP1 Latent transforming growth factor beta binding protein 1
Example 3: statistically significant presence or absence of protein with altered expression specificity in patients with hereditary ovarian cancer Analysis of sex
The inventors of the present application analyzed whether there was a statistical significance in the difference between the protein expression levels between 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)) with respect to each of the 24 types of proteins whose expression was specifically altered in the BRCA mutation-positive ovarian cancer patients obtained by example 2.
The results for 9 types of proteins with reduced expression in ovarian cancer patients with BRCA mutations are shown in figures 2A-2E, and the results for 15 types of proteins with increased expression therein 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 mean expression levels and standard deviations of the 24 types of proteins in the BRCA mutation-positive normal group and the BRCA mutation-positive ovarian cancer patient group are shown.
[ Table 3]
Figure BDA0003153801030000191
Figure BDA0003153801030000201
Example 4: sensitivity and specificity analysis of 24 types of markers
The inventors of the present application tried to analyze sensitivity and specificity, and therefore performed ROC curve analysis to identify the accuracy of 24 types of markers that expressed significant changes in a BRCA mutation-positive ovarian cancer patient group. Sensitivity and specificity were assessed by calculating the area under the ROC curve (AUC).
The results for 9 types of proteins with reduced expression in ovarian cancer patients with BRCA mutations are shown in figures 4A-4E and table 4, and the results for 15 types of proteins with increased expression therein are shown in figures 5A-5H and table 5. The test data set is judged to have perfect accuracy when the area is 1, and worthless accuracy is judged when the area is 0.5. The accuracy criteria according to AUC values are as follows: excellent 0.9-1, good 0.8-0.9, general (C) 0.7-0.8, poor (D) 0.6-0.7, and failure (F) 0.5-0.6.
[ Table 4]
Figure BDA0003153801030000202
Figure BDA0003153801030000211
[ Table 5]
Index UniProt ID Gene Name of protein 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 Prosphingolipid activator 0.771
8 P07686 HEXB Beta-hexosaminidase subunit beta 0.755
9 P07996 THBS1 Thrombospondin-1 0.667
10 P09486 SPARC Osteonectins 0.664
11 P19022 CDH2 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 Fibrillation proteins (Reelin) 0.760
15 Q14766.4 LTBP1 Latent transforming growth factor beta binding protein 1 0.674
Example 5: validation of the effectiveness of 24 types of markers
The inventors of the present application attempted to validate the effectiveness of 24 types of markers expressing significant alterations in a BRCA mutation-positive ovarian cancer patient group as specific biomarkers capable of predicting 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, and a schematic representation of the validation process is shown in fig. 6.
By the analysis, the optimal K value (which is a variable selected from 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 by literature or the like. In addition, among the 24 types of candidate histones, PPBP, SPARC, THBS1, and LTBP1 proteins were added, the expression of which showed significant differences between the BRCA mutation-positive normal group and ovarian cancer patients, and the expression of which showed significant differences between the BRCA mutation-positive group and the BRCA mutation-negative group.
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 on these 11 types of biomarkers is shown in the following table 6.
[ Table 6]
Figure BDA0003153801030000221
Figure BDA0003153801030000231
Industrial applicability
According to the present disclosure, 11 types of biomarkers specifically altered in expression in ovarian cancer patients having BRCA gene mutation were found, and the effectiveness thereof was verified, because information on the presence or absence of ovarian carcinogenesis can be provided early in clinical practice by measuring the levels of mRNA or protein of the 11 types of biomarker genes from subjects having BRCA gene mutation, the disease can be prevented, and the biomarkers can be effectively used as target molecules to develop targeted therapeutics against hereditary ovarian cancer accompanied by BRCA gene mutation.

Claims (14)

1. A marker composition for predicting the occurrence of hereditary ovarian cancer, the marker composition comprising at least one gene or a protein 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
2. The marker composition of claim 1, wherein the hereditary ovarian cancer is accompanied by a mutation in the BRCA1 or BRCA2 gene.
3. A composition for predicting the occurrence of hereditary ovarian cancer, the composition comprising an agent for measuring the mRNA level of at least one gene 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
4. The composition of claim 3, wherein the hereditary ovarian cancer is accompanied by a mutation in the BRCA1 or BRCA2 gene.
5. The composition of claim 3, wherein the agents for measuring the mRNA level of at least one gene are sense and antisense primers or probes, each of which complementarily binds the mRNA of the at least one gene.
6. The composition of claim 3, wherein the reagent for measuring protein levels is an antibody that specifically binds to the protein encoded by the at least one gene.
7. A kit for predicting genetic ovarian carcinogenesis comprising the composition of claim 3.
8. A method of predicting the occurrence of hereditary ovarian cancer, the method comprising measuring in a biological sample derived from a subject the mRNA level of at least one gene 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, mannose receptor C-type 1 (MRC 001166264) (NM _ 001166264), preproplastin (PPBP) (NM _ 001166264), retinol-binding protein 4(RBP 001166264) (NM _001166264 ), secreted cysteine-rich acidic protein (SPARC) (NM _001166264 ), serpin family a member 5(serpin 001166264) (NM _ 001166264), serpin family C member 1(serpin nc 001166264) (NM _001166264 ), serpin family 2(serpin family a) (thp 001166264 ) (thp 001166264, serpin 001166264), and platelet response protein 001166264).
9. The method of claim 8, wherein the hereditary ovarian cancer is accompanied by a mutation in the BRCA1 or BRCA2 gene.
10. The method of claim 8, wherein the subject has a mutation in the BRCA1 or BRCA2 gene.
11. The method of claim 8, wherein the occurrence of hereditary ovarian cancer is predicted when the level of mRNA of or the level of protein encoded by at least one gene selected from RBP4, SERPINA5, SERPINC1 and SERPINF2 is decreased compared to a healthy normal control group.
12. The method of claim 8, wherein the occurrence of hereditary ovarian cancer is predicted when the level of mRNA of or the level of protein encoded by at least one gene selected from ALDOA, CDH2, LTBP1, MRC1, PPBP, SPARC, and THBS1 is increased as compared to a healthy normal control group.
13. The method of claim 8, wherein the expression level of the mRNA is 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.
14. The method of claim 8, wherein the expression level of the protein is measured by at least one method selected from the group consisting of: western blotting, Radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, Ouchterlony double immunodiffusion, complement fixation assay, and protein chips.
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