KR101539104B1 - Composition for predicting the response to anti-cancer drug of ovarian cancer using CpG methylation status in promoter region of PARP4 gene and uses thereof - Google Patents

Abstract

The present invention relates to a composition, a kit and a method for predicting reaction of anti-cancer drug treatment of an ovarian cancer patient by detecting methylation status of a CpG portion of a poly (ADP-ribose) polymerase family, member 4 (PARP4) gene promotor.

Description

TECHNICAL FIELD The present invention relates to a composition for predicting the anticancer drug response of ovarian cancer using CpG methylation of a PARP4 gene promoter and a use thereof, and a composition for predicting the response of an anticancer drug to ovarian cancer using PARP4 gene promoter,

The present invention relates to a composition, a kit and a method for predicting an anticancer drug therapeutic response of an ovarian cancer patient by detecting a methylation level of a CpG region of a poly (ADP-ribose) polymerase family member 4 gene of PARP4.

Ovarian cancer has the highest mortality rate among women with cancer, and its frequency is steadily increasing as the recent lifestyle is westernized, hormone replacement therapy is spreading and the elderly population is increasing. Because ovarian cancer does not show any obvious symptoms at the beginning, more than 70% of patients are initially diagnosed as advanced ovarian cancer with more than 3 cases, and more than 75% of patients have reported recurrence and metastasis within 2 years after initial treatment.

Ovarian cancer is found in only 15% of all patients in the early stages, and more than 65% of all patients are found to have metastasized to other tissues. The treatment of ovarian cancer is often accompanied by paclitaxel or platinum-based chemotherapy combined with surgical operations to remove metastatic lesions and metastatic lesions such as uterus, ovary, and lymph nodes. However, 80-90% of the current therapies show good response at the initial stage, but only 10-15% reach complete remission, and 65-75% of the relapsed patients do not respond to chemotherapy And the subsequent treatment is very difficult. Furthermore, among patients with similar clinical characteristics, the response to chemotherapy varies widely, and even patients with the same stage have significant differences in patient survival.

Thus, there is a need for a biomarker that can better predict the response of a tumor to treatment and select patients that are effective for a particular therapy. The development of these biomarkers is expected to contribute greatly to improve patient survival rate and treatment efficiency.

Korean Patent Publication No. 2011-0043097 (disclosed on April 27, 2011)

Thus, in the present invention, genomic DNA and RNA were extracted from a cell line showing sensitivity to an anticancer drug and a cell line showing resistance to an anticancer drug, and a DNA methylation microarray and gene expression microarray analysis were performed. In the ovarian cancer cell lines, IC ₅₀ values and the degree of DNA methylation of promoter CpG were analyzed by Pearson correlation and Spearman correlation. These results were subjected to an integration analysis to finally select a gene whose expression was regulated by DNA methylation among genes involved in chemotherapeutic resistance, thereby identifying a specific CpG site that affected the gene expression. In addition, the present inventors completed the present invention by confirming that the reactivity of cancer patients with ovarian cancer can be predicted by measuring the degree of methylation occurring at a specific CpG position of the gene.

Therefore, one object of the present invention is to provide a method for inhibiting the expression of anthraquinolone (ANXA4), CD302 (CD302 molecule), CDC42EP2 (Rho GTPase binding 2), EFTUD1 (elongation factor Tu GTP binding domain containing 1), KCNE4 (ADP-ribose) polymerase family, member 4 (MUC2), MUC2 (microtubule associated monoxygenase, calponin and LIM domain containing 2), PARP4 ], SPSB1 (splA / ryanodine receptor domain and SOCS box containing 1), and SYCP2 (synaptonemal complex protein 2). And to provide a composition for predicting the reactivity of a cancer patient to an anticancer agent.

It is another object of the present invention to provide a kit for predicting the reactivity of an ovarian cancer patient to an anticancer agent, which comprises the above composition.

It is another object of the present invention to provide a method of detecting the methylation level of the CpG region of at least one gene promoter selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2, And to provide a method for predicting the responsiveness of a patient to an anticancer drug.

Another object of the present invention is to provide a method for predicting the response of an ovarian cancer patient to an anticancer agent, comprising the step of administering to the patient a sample comprising ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 The present invention provides a method for detecting methylation of a CpG region of at least one gene promoter selected from the group consisting of:

The present invention is based on the finding that the specific CpG site of the ANXA4, CD302, CDC42EP2, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 gene promoters is specifically methylated in anticancer drug resistant cells, , It has been found for the first time that the specific CpG site of the EFTUD1 gene promoter is specifically hypermethylated in the anticancer-resistant cells, whereby the expression of the gene is specifically reduced, and the degree of methylation of the promoter of the genes is used as a biomarker To provide a technique for predicting the responsiveness of ovarian cancer patients to anticancer agents.

Since CpG of the ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 gene promoters show specific methylation changes in anticancer drug resistant cells, Or two or more of them may be used as a complex biomarker.

Accordingly, the present invention provides a method for measuring the methylation level of a CpG site of a promoter of at least one gene selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1, and SYCP2 To a composition for predicting the reactivity of an ovarian cancer patient to an anticancer agent, and a kit containing the same.

In one embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent and a kit comprising the same, which comprises an agent for measuring the methylation level of the CpG region of the promoter of the ANXA4 gene.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent comprising a preparation for measuring the methylation level of a CpG site of a promoter of CD302 gene, and a kit comprising the same.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent and a kit comprising the same, which comprises an agent for measuring the methylation level of the CpG region of the promoter of CDC42EP2 gene.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent and a kit comprising the same, which comprises an agent for measuring the methylation level of the CpG region of the promoter of the EFTUD1 gene.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent and a kit comprising the same, which comprises an agent for measuring the methylation level of the CpG region of the promoter of the KCNE4 gene.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent and a kit comprising the same, the kit comprising the agent for measuring the methylation level of the CpG region of the promoter of the MBNL2 gene.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MICAL2, PARP4, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent and a kit comprising the same, which comprises an agent for measuring the methylation level of a CpG region of a promoter of MICAL2 gene.

In this case, more preferably, the composition and kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, PARP4, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent, comprising a preparation for measuring the methylation level of the CpG region of the promoter of the PARP4 gene, and a kit comprising the same.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, SPSB1 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent, and a kit comprising the same, which comprises an agent for measuring the methylation level of a CpG region of a promoter of SPSB1 gene.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4 and SYCP2 . ≪ / RTI >

In another embodiment, the present invention relates to a composition for predicting the responsiveness of an ovarian cancer patient to an anticancer agent and a kit comprising the same, which comprises an agent for measuring the methylation level of the CpG region of the promoter of SYCP2 gene.

In this case, more preferably, the composition and the kit are those which measure the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4 and SPSB1 . ≪ / RTI >

In the present invention, the sequence information of the ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 genes can be confirmed in a known gene database. For example, the nucleic acid sequence of the human ANXA4 gene can be found in Genbank Accession No. NM_001153, the nucleic acid sequence of the human CD302 gene can be found in Genbank Accession No. NM_014880, and the nucleic acid sequence of the human CDC42EP2 gene can be found in Genbank Accession No. NM_006779 The nucleic acid sequence of human EFTUD1 gene can be confirmed by Genbank registration number NM_024580, the nucleic acid sequence of human KCNE4 gene can be confirmed by Genbank registration number NM_080671, the nucleic acid sequence of human MBNL2 gene can be confirmed by Genbank registration number NM_144778, Nucleic acid sequence of human MICAL2 gene can be confirmed by Genbank registration number NM_014632, nucleic acid sequence of human PARP4 gene can be confirmed by Genbank registration number NM_006437, nucleic acid sequence of human SPSB1 gene can be confirmed by Genbank registration number NM_025106, human SYCP2 The nucleic acid sequence of the gene is < RTI ID = Bank registration number NM_014258.

The term "methylation" or "methylation" in the present invention means that a methyl group is attached to a base constituting DNA. Preferably, the methylation status in the present invention means whether methylation occurs in the cytosine of a specific CpG site in the promoter region of a specific gene. When methylation occurs, the binding of transcription factors is hindered and the expression of a specific gene is inhibited. On the other hand, when unmethylated or hypomethylated, the expression of a specific gene is increased.

Genomic DNA of mammalian cells contains 5th methyl-cytosine (5-methylcytosine, 5-mC) base with a methyl group attached to the fifth carbon of the cytosine ring in addition to A, C, G and T do. Methylation of 5-methylcytosine occurs only in C of a CG dinucleotide (5'-mCG-3 ') called CpG, and methylation of CpG inhibits expression of repeated sequences of alu or transposon and genome. Further, since 5-mC of the CpG is naturally deaminated and is likely to become a thymine (T), CpG is a site where most of the epigenetic changes occur frequently in mammalian cells.

The term "measurement of the methylation level" in the present invention refers to a measurement of the methylation level of the CpG region of a promoter of a gene, and includes methylation-specific PCR such as methylation-specific polymerase chain reaction (MSP) PCR using real-time methylation-specific polymerase chain reaction (PCR), methylated DNA-specific binding protein, or quantitative PCR. Or by automated base analysis such as pyrosequencing and bisulfite sequencing, but are not limited thereto.

Preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the ANXA4 gene may mean measuring the methylation level of the cytosine at the CpG site that appears in the 69770033 to 69770154 base of chromosome 2. In the present invention, the 69770033 to 69770154 base of the chromosome 2 is represented by SEQ ID NO: 1.

More preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the ANXA4 gene may mean measuring the methylation level of cytosine located at position 69770093 (SEQ ID NO: 1, 61) of chromosome 2 .

Preferably, in the present invention, the methylation level of the CpG region of the promoter of the CD302 gene is measured by measuring the level of methylation of the CpG region appearing in the 159798495 to 159798616 base, 159798510 to 159798631 base, or 159798465 to 159798586 base of the chromosome 2 This may mean measuring the level of methylation of the god. In the present invention, the nucleotide sequences of the CpG region are represented by SEQ ID NO: 2, SEQ ID NO: 3 and SEQ ID NO: 4, respectively.

More preferably, in the present invention, the methylation level of the CpG region of the promoter of the CD302 gene can be measured by measuring the methylation level of 159798555 (61st in SEQ ID NO: 2), 159798570 (61st in SEQ ID NO: 3) or 159798525 (Position 61 of SEQ ID NO: 4) of the cytosine.

Also preferably, in the present invention, the methylation level of the CpG region of the promoter of the CDC42EP2 gene is measured by measuring the methylation level of the cytosine of the CpG region appearing in the 65316855 to 65316976 base of the 11th chromosome, or the 65316443 to 65316564th base It can mean something. In the present invention, the nucleotide sequences of the CpG region are represented by SEQ ID NO: 5 and SEQ ID NO: 6, respectively.

More preferably, in the present invention, the methylation level of the CpG region of the promoter of the CDC42EP2 gene is measured by determining the methylation level of the CDC42EP2 gene located at 65316915th (61st in SEQ ID NO: 5) or 65316503 (61st in SEQ ID NO: 6) May mean measuring the methylation level of cytosine.

Also preferably, measuring the methylation level of the CpG region of the promoter of the EFTUD1 gene in the present invention may mean measuring the methylation level of cytosine at the CpG site appearing in the 82262935 to 82263056 base of chromosome 15. In the present invention, the 82262935 to 82263056 base of the above chromosome 15 is represented by SEQ ID NO: 7.

More preferably, measuring the methylation level of the CpG region of the promoter of the EFTUD1 gene in the present invention may mean measuring the methylation level of cytosine located at 82262995 th (position 61 of SEQ ID NO: 7) of chromosome 15 .

Preferably, in the present invention, the methylation level of the CpG region of the promoter of the KCNE4 gene is measured by measuring the level of the 223051909 to 223052030 base, 223051844 to 223051965 base, 223052042 to 223052163 base, 223051814 to 223051935 base, Or measuring the methylation level of cytosine at the CpG site that appears in the 223051724 to 223051845 base. In the present invention, the nucleotide sequences of the CpG region are represented by SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11 and SEQ ID NO: 12, respectively.

More preferably, in the present invention, the methylation level of the CpG region of the promoter of the KCNE4 gene can be measured by measuring the level of the 223051969th (61st in SEQ ID NO: 8), 223051904 (61st in SEQ ID NO: 9) May mean measuring the methylation level of the cytosine located at 223052102 (61st of SEQ ID NO: 10), 223051874th (61st of SEQ ID NO: 11) or 223051784 (61st of SEQ ID NO: 12) of the chromosome.

Preferably, in the present invention, the methylation level of the CpG region of the promoter of the MBNL2 gene is measured by measuring the level of methylation of the CpG region of 97257602 to 97257723 base, 97225103 to 97225224 base, or 97260256 to 97260377 base of the chromosome 13 This may mean measuring the level of methylation of the god. In the present invention, the nucleotide sequences of the CpG region are represented by SEQ ID NO: 13, SEQ ID NO: 14 and SEQ ID NO: 15, respectively.

More preferably, in the present invention, the methylation level of the CpG region of the promoter of the MBNL2 gene can be measured by measuring the level of 97257662 (61st in SEQ ID NO: 13), 97225163 (61st in SEQ ID NO: 14) or 97260316 (Position 61 of SEQ ID NO: 15) of the cytosine.

Also, preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the MICAL2 gene may mean measuring the methylation level of cytosine at the CpG site appearing in the 12138155 to 12138276 base of chromosome 11. In the present invention, the nucleotides 12138155 to 12138276 of the chromosome 11 are represented by SEQ ID NO: 16.

More preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the MICAL2 gene may mean measuring the methylation level of the cytosine located at position 12138215 (SEQ ID NO: 16, 61) of chromosome 11 .

Also, preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the PARP4 gene may mean measuring the methylation level of cytosine at the CpG site occurring in the 24511103 to 24511224 base of chromosome 13. In the present invention, the bases 24511103 to 24511224 of the above chromosome 13 are represented by SEQ ID NO: 17.

More preferably, measuring the methylation level of the CpG region of the promoter of the PARP4 gene in the present invention may mean measuring the methylation level of the cytosine located at 24511163 th (chromosome 61 of SEQ ID NO: 17) of chromosome 13 .

Also preferably, measuring the methylation level of the CpG region of the promoter of the SPSB1 gene in the present invention may mean measuring the methylation level of cytosine at the CpG site in the 9315508 to 9315629 base of chromosome 1. In the present invention, the 9315508 to 9315629 base of the above chromosome 1 is represented by SEQ ID NO: 18.

More preferably, measuring the methylation level of the CpG region of the promoter of the SPSBl gene in the present invention may mean measuring the methylation level of the cytosine located at 9315568th (position 61 of SEQ ID NO: 18) of chromosome 1 .

Also, preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of SYCP2 gene may mean measuring the methylation level of cytosine at the CpG site appearing in the 59933471 to 59933592 base of chromosome 20. In the present invention, the nucleotides 59933471 to 59933592 of the chromosome 20 are shown in SEQ ID NO: 19.

More preferably, measuring the methylation level of the CpG region of the promoter of the SYCP2 gene in the present invention may mean measuring the methylation level of cytosine located at 59933531 th (position 61 of SEQ ID NO: 19) of chromosome 20 .

In the present invention, the nucleotide sequence of the human genome chromosome region is expressed according to the latest version of The December 2013 Human reference sequence (GRCh38) The specific sequence of the human genome chromosome region may be changed somewhat as the result of the genome sequence study is updated, and the expression of the human genome chromosome region of the present invention may be different according to the modification. Accordingly, the human genome chromosome region expressed in accordance with the December 2013 Human reference sequence (GRCh38) of the present invention is updated after the filing date of the present invention, so that the human genome chromosome region expression is updated It will be obvious that the scope of the present invention is extended to the modified human genome chromosome region even if it is otherwise changed. Such modifications are readily apparent to those skilled in the art to which the present invention pertains.

In the present invention, eleven kinds of ovarian cancer cell lines were classified into an anticancer drug sensitive cell line and an anticancer drug resistant cell line by examining the degree of tolerance to cisplatin anticancer drug. Genomic DNA and RNA were extracted from these cell lines, and then the cells were treated with Illumina Human Methylation 450 Bead Chip DNA methylation microarray and Affymetrix Human Gene 1.0 ST were used to analyze gene expression microarray. The IC ₅₀ values for anticancer drugs and gene expression and the degree of DNA methylation change of promoter CpG in ovarian cancer cell lines were analyzed by Pearson correlation Spearman correlation. These results were analyzed by integration analysis, and the gene whose expression was regulated by DNA methylation among the genes involved in chemotherapeutic resistance was finally selected. In addition, it was confirmed that the specific CpG site that affected the expression of the gene was identified and the reactivity of the ovarian cancer patient to the anticancer agent can be predicted by measuring the degree of methylation occurring at a specific CpG site of the gene.

Among the selected genes, ANXA4 showed a 5.6-fold increase in gene expression and a low methylation level in the promoter CpG region in the resistant cell line of the anticancer sensitive cell line, and the IC ₅₀ value and the IC ₅₀ value of the cisplatin anticancer drug in 11 ovarian cancer cell lines Expression and DNA methylation of promoter CpG showed significant difference in Spearman correlation. Therefore, the change of DNA methylation in the promoter CpG region of ANXA4 gene was selected as an anticancer drug response prediction marker.

CD302 is a cancer sensitive cells was the gene expressed in the resistant cell master, with respect to the master, is that methylation at increased 7.8 times and at the same time the promoter CpG sites, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and gene expression, and promoter CpG The degree of DNA methylation in the CD302 gene was significantly correlated with Pearson correlation and Spearman correlation. Therefore, the change in DNA methylation at the promoter CpG region of the CD302 gene was selected as an anticancer drug response prediction marker.

CDC42EP2 has had the gene expression is increased 1.59-fold in the resistant cell master, with respect to an anticancer agent sensitivity cells week group, the IC ₅₀ value and the gene expression and level of promoter CpG DNA methylation changes to cisplatin chemotherapy in ovarian cancer cell lines of 11 Pearson correlation and Spearman correlation, the change in DNA methylation at the promoter CpG site of the CDC42EP2 gene was selected as a predictive marker for chemotherapy response.

EFTUD1 has had the gene expression decreases 2.36 times the resistant cell master, with respect to an anticancer agent sensitivity cells week group, the IC ₅₀ value and the gene expression and level of promoter CpG DNA methylation changes to cisplatin chemotherapy in ovarian cancer cell lines of 11 Pearson correlation and Spearman correlation, the DNA methylation changes in the promoter CpG region of the EFTUD1 gene were selected as predictors of anticancer drug response.

KCNE4 showed 3.63 fold increase in gene expression in the resistant cell line of the anticancer sensitive cell line and hypomethylation in the promoter CpG region. In the 11 ovarian cancer cell lines, IC ₅₀ value and gene expression and cpm The DNA methylation changes in the promoter CpG region of the KCNE4 gene were selected as predictors of anticancer drug response.

The MBNL2 gene was 3.83 times more potent in the resistant cell line than that in the cancer cell line, and was hypomethylated at the promoter CpG site. In the 11 ovarian cancer cell lines, the IC ₅₀ value and the gene expression and promoter CpG The DNA methylation change in the promoter CpG region of the MBNL2 gene was selected as the predictive marker for anticancer drug response.

MICAL2 the anticancer sensitive cells was the gene expression in the resistant cell master, with respect to the master, is that methylation at and at the same time the promoter CpG sites increased 7.73 times, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and gene expression, and promoter CpG The DNA methylation changes in the promoter CpG region of the MICAL2 gene were selected as predictors of anticancer drug response.

PARP4 has had the gene expression is increased 1.62-fold in the resistant cell master, with respect to an anticancer agent sensitivity cells week group, the IC ₅₀ value and the gene expression and level of promoter CpG DNA methylation changes to cisplatin chemotherapy in ovarian cancer cell lines of 11 Pearson correlation and Spearman correlation, the change in DNA methylation in the promoter CpG region of the PARP4 gene was selected as a predictor of anticancer drug response.

In SPSB1, the gene expression in the resistant cell line was increased 2.4-fold and the methylation level was low in the promoter CpG region. In the ovarian cancer cell lines, the IC ₅₀ value and the gene expression and promoter CpG The DNA methylation change in the promoter CpG region of the SPSB1 gene was selected as an anticancer drug response prediction marker since the degree of DNA methylation change in the SPSB1 gene was significant in Pearson correlation and Spearman correlation.

SYCP2 the anticancer sensitive cells showed gene expression in the resistant cell master, with respect to the master, is that methylation at and at the same time the promoter CpG sites increased 5.43 times, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and gene expression, and promoter CpG The DNA methylation changes in the promoter CpG region of the SYCP2 gene were selected as predictors of anticancer drug response, as the degree of DNA methylation change was significant in Pearson correlation and Spearman correlation.

Thus, hypomethylation or hypermethylation of DNA methylation at specific CpG positions of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and / or SYCP2 can predict reactivity to chemotherapeutic agents in ovarian cancer patients Can be used as a biomarker.

In the present invention, the patient refers to a patient who has developed ovarian cancer. A gene sample is obtained from tissues, cells, whole blood, serum, plasma, saliva, sputum, cerebrospinal fluid or urine obtained from these ovarian cancer patients. The gene sample includes cDNA synthesized from DNA, mRNA or mRNA.

In the present invention, the term "prediction of reactivity to an anticancer agent" means predicting whether the patient will preferentially or non-preferentially respond to the anticancer agent treatment, or anticipating the risk of resistance or resistance to the anticancer agent. The predictive methods of the present invention can be used clinically to make treatment decisions by selecting the most appropriate treatment regimen for patients with ovarian cancer. Preferably, the anticancer agent may be a platinum-based anticancer agent, for example, cisplatin.

In general, ovarian cancer is treated with chemotherapy, especially platinum-based chemotherapy combined with cisplatin. However, among patients with similar clinical features or similar stages, chemotherapy There is a wide range of responses and significant differences in survival. By using the method of the present invention, the responsiveness to chemotherapy can be easily predicted, the survival prognosis of the chemotherapy can be determined, and a patient group suitable for chemotherapy can be selected to improve the treatment efficiency. In addition, the survival rate after the onset of ovarian cancer can be increased.

In addition, since the abnormal methylation change of cancer-resistant cancer cells exhibits significant similarity to the methylation change of genomic DNA obtained from a biological sample such as tissue, whole blood, serum, plasma, saliva, sputum, cerebrospinal fluid or urine, When using the marker, it is possible to easily diagnose the reactivity of the patient to the anticancer drug through blood or body fluids.

In the present invention, the agent for measuring the methylation level of the CpG region is a compound that modifies an unmethylated cytosine base or a methylation-sensitive restriction enzyme, ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and / A primer specific for the methylated allele sequence of the gene promoter, and a primer specific for the unmethylated allele sequence.

The compound capable of modifying the unmethylated cytosine base may be bisulfite or a salt thereof, but is not limited thereto, preferably sodium bisulfite. Methods for detecting the methylation of a CpG site by modifying an unmethylated cytosine residue using such a bisulfite are well known in the art (WO01 / 26536; US2003 / 0148326A1).

In addition, the methylation sensitive restriction enzyme may be a restriction enzyme capable of specifically detecting the methylation of the CpG site, and may be a restriction enzyme containing CG as a recognition site of the restriction enzyme. For example, Sma I, Sac II, Eag I, Hpa II, Msp I, Bss HII, Bst UI, Not I, and the like. The methylation or non-methylation of the restriction enzyme recognition site at C may or may not be cleaved by restriction enzymes and may be detected by PCR or Southern blot analysis. Other methylation sensitive restriction enzymes than the above restriction enzymes are well known in the art.

Genomic DNA is obtained from a biological sample of a patient as a representative method for measuring the level of methylation at the CpG site of the patient's ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and / or SYCP2 gene promoters, The DNA thus obtained is subjected to amplification by PCR using a primer and the presence or absence of the amplified product after the treatment of the methylation-sensitive restriction enzyme or a compound that modifies a cytosine base which is not methylated in the obtained DNA can do.

Thus, the preparations of the present invention can be used as primers specific for the methylated allele sequence of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and / or SYCP2 genes and primers specific for unmethylated allele sequences . ≪ / RTI > In the present invention, the term "primer" means a short nucleic acid sequence capable of forming a base pair with a complementary template with a nucleic acid sequence having a short free 3-terminal hydroxyl group and serving as a starting point for template strand copying. The primer can initiate DNA synthesis in the presence of reagents and four different nucleoside triphosphates for polymerization reactions (i. E., DNA polymerase or reverse transcriptase) at appropriate buffer solutions and temperatures. In addition, primers can incorporate additional features that do not alter the primer properties of primers that serve as a starting point for DNA synthesis, as sense and antisense nucleic acids with 7 to 50 nucleotide sequences. The sequence of the primer does not necessarily have to be exactly the same as the sequence of the template, but is sufficiently complementary that it can hybridize with the template. The position of the primer or the primer binding site refers to a target DNA fragment to which the primer hybridizes.

The primer of the present invention can be preferably designed according to the sequence of a specific CpG site to be subjected to methylation analysis and includes a pair of primers capable of specifically amplifying cytosine that has been methylated and not modified by bisulfite, And a primer pair that is not methylated and can specifically amplify cytosine modified by bisulfite.

In addition to the above preparation, the composition and kit may further contain a polymerase agarose, a buffer solution necessary for electrophoresis, and the like.

In another aspect, the present invention provides a method of detecting the methylation level of CpG region of at least one gene promoter selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1, To a method for predicting the response of a cancer patient to an anticancer agent.

In order to provide information necessary for predicting the responsiveness of an ovarian cancer patient to an anticancer agent, a sample selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 The methylation of the CpG region of the at least one gene promoter is detected.

For example, the present invention provides a method for detecting the methylation level of the CpG region of an ANXA4 gene promoter from a sample of a patient with ovarian cancer; And comparing the methylation level with a methylation level of CpG of a corresponding gene promoter of a control sample. The present invention also relates to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent. The control sample may be an anticancer sensitive control sample.

In this case, more preferably, the method further comprises detecting the methylation level of the CpG region of at least one gene promoter selected from the group consisting of CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSBl, ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the control sample. The control sample may be an anticancer sensitive control sample.

In another aspect, the present invention provides a method for detecting a CD302 gene, comprising: measuring the methylation level of a CpG region of a CD302 gene promoter from a sample of an ovarian cancer patient; And comparing the methylation level with a methylation level of CpG of a corresponding gene promoter of a control sample. The present invention also relates to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent. The control sample may be an anticancer sensitive control sample.

More preferably, the method further comprises measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of ANXA4, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 of the patient ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another aspect, the present invention provides a method for detecting a CDC42EP2 gene, comprising: measuring the methylation level of a CpG region of a CDC42EP2 gene promoter from a sample of an ovarian cancer patient; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

More preferably, the method further comprises comparing the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 from the patient sample ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another embodiment, the present invention provides a method for detecting the methylation level of a CpG region of an EFTUD1 gene promoter from a sample of an ovarian cancer patient; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

More preferably, the method further comprises measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of ANXA4, CD302, CDC42EP2, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 of the patient ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another embodiment, the present invention provides a method for detecting a CpG region of a KCNE4 gene promoter, comprising: measuring a methylation level of a CpG region of a KCNE4 gene promoter from a sample of an ovarian cancer patient; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

More preferably, the method further comprises comparing the methylation level of the CpG region of the at least one gene promoter selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 from the patient sample ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another embodiment, the present invention provides a method for detecting the methylation level of a CpG region of a MBNL2 gene promoter from a sample of a patient suffering from ovarian cancer; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

More preferably, the method further comprises comparing the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MICAL2, PARP4, SPSB1 and SYCP2 from the patient sample ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another embodiment, the present invention provides a method for detecting the methylation level of a CpG region of a MICAL2 gene promoter from a sample of an ovarian cancer patient; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

More preferably, the method further comprises comparing the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, PARP4, SPSB1 and SYCP2 from the patient sample ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another aspect, the present invention provides a method for detecting the level of methylation of a CpG region of a PARP4 gene promoter from a sample of an ovarian cancer patient; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

More preferably, the method further comprises comparing the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, SPSB1 and SYCP2 from the patient sample ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another aspect, the present invention provides a method for detecting the methylation level of a CpG region of an SPSB1 gene promoter from a sample of an ovarian cancer patient; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

In this case, more preferably, the method further comprises determining the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4 and SYCP2 from the patient sample ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

In another embodiment, the present invention provides a method for detecting the methylation level of a CpG region of a SYCP2 gene promoter from a sample of a patient suffering from ovarian cancer; And comparing the level of methylation with the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample, to a method for providing information for predicting the responsiveness of an ovarian cancer patient to an anticancer agent.

In this case, more preferably, the method further comprises determining the methylation level of the CpG region of one or more gene promoters selected from the group consisting of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4 and SPSB1 from the patient sample ; And comparing the methylation level to the methylation level of CpG of the corresponding gene promoter of the anticancer sensitive control sample.

The term "patient sample" in the present invention refers to a tissue, a cell, a whole blood, a serum, a blood sample, or the like which have different methylation levels of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and / Plasma, saliva, sputum, cerebrospinal fluid or urine, and the like.

First, to obtain genomic DNA from a patient and measure the methylation level, the genomic DNA can be obtained by the phenol / chloroform extraction method, SDS extraction method (Tai et al., Plant Mol. Biol. Reporter, 8: 297-303, 1990), Cetyl Trimethyl Ammonium Bromide (Murray et al., Nuc. Res., 4321-4325, 1980) or commercially available DNA extraction kits.

The step of measuring the methylation level of the CpG region of the gene promoter comprises, more particularly, (a) treating the genomic DNA in the obtained sample with a compound that modifies the unmethylated cytosine base or a methylation-sensitive restriction enzyme; And (b) amplifying the treated DNA by PCR using a primer capable of amplifying a specific CpG region of the gene.

The compound that modifies the unmethylated cytosine base in step (a) may be bisulfite, preferably sodium bisulfite. Methods for detecting the methylation of a particular CpG site by modifying an unmethylated cytosine residue using such a bisulfite are well known in the art.

In addition, as described above, the methylation-sensitive restriction enzyme in step (a) may be a restriction enzyme capable of specifically detecting methylation of a specific CpG site and may be a restriction enzyme containing CG as a recognition site of a restriction enzyme For example, Sma I, Sac II, Eag I, Hpa II, Msp I, Bss HII, Bst UI, Not I, and the like.

In the step (b), the amplification may be performed by a conventional PCR method. As described above, the primers used herein can be desirably designed according to the sequence of a specific CpG site to be subjected to methylation analysis, and can be specifically amplified by specifically amplifying cytosine which has been methylated and not modified by bisulfite And a primer pair capable of specifically amplifying cytosine modified by bisulfite without being methylated.

The step of measuring the methylation level of the CpG region of the gene promoter may further include the step of (c) confirming the presence or absence of the result amplified in step (b). The presence or absence of the amplified product in the step (c) may be performed according to a method known in the art, for example, electrophoresis to detect a band at a desired position. For example, in the case of using a compound for modifying an unmethylated cytosine residue, two kinds of primer pairs used in the step (a), that is, a primer capable of specifically amplifying cytosine that has been methylated and not modified by bisulfite The degree of methylation can be determined according to the presence or absence of the PCR product amplified by the pair of primers that can specifically amplify cytosine modified by bisulfite and methylation, respectively. Preferably, the methylation can be determined by treating the sample genomic DNA with bisulfite, amplifying the CpG region of the gene promoter of interest by PCR, and analyzing the base sequence of the amplified region using a bisulfite genomic sequencing method have.

In the case where restriction enzymes are used, it is judged that the CpG region has been methylated in the case where there is a PCR result in DNAs treated with restriction enzymes in a state known in the art, for example, mock DNA, If there is no PCR result in the DNA treated with the restriction enzyme, the methylation can be judged by judging that the CpG site is unmethylated, which is obvious to a person skilled in the art. In the above, mock DNA refers to a sample DNA that has been separated from the sample and has not undergone any treatment.

According to this method, specific CpG sites of the ANXA4, CD302, CDC42EP2, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 gene promoters in the patient sample are measured in a low methylation state or the specific CpG site of the EFTUD1 gene promoter is hypermethylated , It can be predicted that the patient will show reactivity to the anticancer drug.

Therefore, according to the present invention, it is possible to effectively confirm the methylation of CpG in the promoters of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and / or SYCP2 gene, Can be predicted.

According to the present invention, the degree of methylation of a specific gene promoter region of a genomic DNA obtained from a biological sample of a patient is measured by a PCR-based MSP (methylation-specific PCR) Since the reactivity can be predicted, a diagnostic kit with high accuracy and convenience can be developed.

FIG. 1 shows a process of selecting an anti-cancer drug therapeutic marker in ovarian cancer patients.
2, OV-90, PA-1, MDAH 2774, A2780, A2780cp, SK-OV-3) RTI ID = 0.0 > IC50 < _{/ RTI} > And the results are shown in Table 1. The results are shown in Table 1. The results are shown in Table 1. The results are shown in Table 1.
FIG. 3 shows the results of confirming the expression of ANXA4 gene after treating 5-aza-2'-deoxycytidine with ovarian cancer cell lines (OV-90, TOV-112D, A2780, PA-1 and ES-2).
FIG. 4 shows the results of treatment of 5-aza-2'-deoxycytidine with ovarian cancer cell line (OV-90, TOV-112D, TOV-21G, A2780, Caov-3, MDAH2774, PA- . The results are shown in Fig.
FIG. 5 shows the results of treatment of 5-aza-2'-deoxycytidine with ovarian cancer cell lines (OV-90, TOV-112D, TOV-21G, A2780, Caov-3, MDAH2774, OVCAR-3 ES-2 and SKOV- And the expression of CDC42EP2 gene was confirmed.
FIG. 6 shows the results of treatment of 5-aza-2'-deoxycytidine with ovarian cancer cell line (OV-90, TOV-112D, TOV-21G, A2780, A2780cis, MDAH2774, PA1, OVCAR-3, ES-2 and SKOV- And the expression of EFTUD1 gene was examined.
FIG. 7 shows the results of treatment of 5-aza-2'-deoxycytidine with ovarian cancer cell lines (OV-90, TOV-112D, TOV-21G, A2780, Caov-3, PA1, OVCAR-3, ES-2 and SKOV- And the expression of KCNE4 gene was confirmed.
8 shows the results of treatment of 5-aza-2'-deoxycytidine with ovarian cancer cell lines (OV-90, TOV-112D, A2780, Caov-3, MDAH2774, PA1, OVCAR-3, ES-2 and SKOV- The expression of MBNL2 gene was confirmed.
FIG. 9 is a graph showing the effect of 5-aza-2'-deoxycytidine (OV-90, TOV-112D, TOV- And the expression of MICAL2 gene was confirmed.
Fig. 10 is a graph showing the effect of 5-aza-2 'on ovarian cancer cell lines (OV-90, TOV-112D, TOV-21G, A2780, A2780cis, Caov-3, MDAH2774, PA1, OVCAR-3, ES- -deoxycytidine and the expression of PARP4 gene was confirmed.
Fig. 11 is a graph showing the activity of 5-aza-2'-deoxycytidine (OV-90, TOV-112D, TOV-21G, A2780, A2780cis, Caov-3, MDAH2774, OVCAR-3, ES-2 and SKOV- And the expression of SPSB1 gene was confirmed.
Fig. 12 is a graph showing the effect of 5-aza-2 'on the ovarian cancer cell lines (OV-90, TOV-112D, TOV-21G, A2780, A2780cis, Caov-3, MDAH2774, PA1, OVCAR-3, ES-2 and SKOV- -deoxycytidine, and the expression of SYCP2 gene was confirmed.

Hereinafter, the present invention will be described in detail with reference to examples. However, the following examples are illustrative of the present invention, and the present invention is not limited by the following examples.

Example  1. Cell culture

To determine the resistance of cisplatin to the anticancer drug, the following 11 ovarian cancer cell lines were used (Table 1). The cell lines were purchased from American Type Culture Collection (ATCC), SK-OV-3 and ES-2 cell lines were used for McCoy's 5a, PA-1 cells were used for MEM alpha, Caov- MCDB 105 and medium 199 (1: 1 mix), OVCAR-3, MDAH2774, A2780 and A2780cis cell lines were cultured in RPMI 1640 supplemented with 10% fetal bovine serum, 100 U / mL penicillin and 100 [mu] g / mL streptomycin. For the A2780cis cell line, 1 [mu] M cisplatin was added to the culture medium to maintain cisplatin resistance.

Cat. (cell) Cell line Cell-derived / related diseases morphology badge Badge availability HTB-77 SKOV-3 Derived from human / adenocarcinoma / metastatic state epithelial McCoy's 5a + 10% FBS + 1% P / S (REF) 16600-082 (Gibco) CRL-1978 ES-2 Human / carcinoma fibroblast McCoy's 5a + 10% FBS + 1% P / S (REF) 16600-082 (Gibco) CRL-1572 PA-1 Human / teratocarcinoma epithelial MEM alpha + 10% FBS + 1% P / S 41061-029 (Gibco) HTB-75 Caov-3 Human / adenocarcinoma epithelial DMEM (1.5 g / L sodium bicarbonate) + 10% FBS + 1% P / S LM001-51 (welgene) CRL-11730 TOV-21G Human / adenocarcinoma epithelial MCDB 105 (1.5 g / L sodium bicarbonate) & Medium 199 (2.2 g / L sodium bicarbonate) 1: 1 mix 11150-059 (Gibco, Medium 199) CRL-11731 TOV-112D Human / adenocarcinoma epithelial MCDB 105 (1.5 g / L sodium bicarbonate) & Medium 199 (2.2 g / L sodium bicarbonate) 1: 1 mix 11150-059 (Gibco, Medium 199) CRL-11732 OV-90 Human / plural epithelial MCDB 105 (1.5 g / L sodium bicarbonate) & Medium 199 (2.2 g / L sodium bicarbonate) 1: 1 mix 11150-059 (Gibco, Medium 199) HTB-161 OVCAR-3 Human / adenocarcinoma epithelial RPMI 1640 (25 mM HEPES) + 10% FBS + 1% P / S LM011-03 (welgene) CRL-10303 MDAH 2774 Human / adenocarcinoma mucinous RPMI 1640 (25 mM HEPES) + 10% FBS + 1% P / S LM011-03 (welgene) 93112519 A2780 (parent) Human / carcinoma epithelial RPMI 1640 (25 mM HEPES) + 10% FBS + 1% P / S LM011-03 (welgene) 93112517 A2780cis Human / carcinoma epithelial RPMI 1640 (25 mM HEPES) + 10% FBS + 1% P / S LM011-03 (welgene)

Example  2. Cisplatin  Anti-cancer drug resistance measurement

Antitumor resistance was measured by tetrazolium salt (3-4,5-dimethylthiazol-2-yl) -2,5-diphenyltetrazolium bromide (MTT) method. 96-well plate in 2 × 10 ⁵ / ㎖ 37 ℃ divides by 100 ㎕ a density of _{cells, 95% 0 2/5%} CO 2 And stabilized in the incubator for 16 to 18 hours. Cisplatin was treated with concentration (0-100 μM) for 48 hours, and then added with 20 μl / well of 2.5 mg / ml MTT solution for 2 hours. 100 μl / well of dimethyl sulfoxide (DMSO) was added and the absorbance was measured at a wavelength of 540 nm after 1 hour. Antitumor resistance of cisplatin to cells measured by MTT assay was expressed as a percentage of the control group of each cancer cell, and the concentration at which the cell viability decreased to 50% was determined by IC ₅₀ (50% inhibitory concentration) Respectively. Eleven cell lines were treated with IC _{50 <} RTI ID = 0.0 > (Sensitive) and resistant (resistant) to the anticancer agent, and intermediate cells with intermediate tolerance between the sensitive cell line and the resistant cell line.

Example  3. Total RNA Wow genomic DNA  extraction

Total RNA and genomic DNA were extracted from each cell line using RNeasy mini kit (Qiagen) and QIAmp mini kit (Qiagen). The extraction method was carried out according to the manufacturer's manual. Extracted total RNA and genomic DNA were quantified using spectrophotometer. RNA and DNA status were electrophoresed on 1% agarose gel to confirm degradation.

Example  4. Bisulfite ( Bisulfite ) process

When bisulfite is treated with genomic DNA, cytosine at the 5'-CpG-3 'site in the DNA sequence is retained as it is, but when it is unmethylated, it is converted to uracil to measure the degree of methylation . Therefore, genomic DNA was treated with bisulfite to distinguish methylated cytosine from unmethylated cytosine. First, 2 μg of genomic DNA was treated with EpiTech Bisulfite kit (Qiagen) according to the manufacturer's manual, and the bisulfite-treated DNA thus prepared was dissolved in 20 μL of H ₂ O and stored at -20 ° C. until use Respectively. The bisulfite-treated DNA was amplified by PCR (polymerase chain reaction).

Example  5. Quantitative real time ( Quantitative real - time ) PCR  ( qRT - PCR )

Superscript II reverse transcriptase (Invitrogen) was used for cDNA synthesis. 1 μg of total RNA and 50 ng of oligo dT were denatured at 70 ° C for 10 min. Then, 4 μl of 5 × RT buffer, 2 μl of 0.1 mM DTT, 4 μl of 2.5 mM dNTP mixture, 200 units of Superscript II reverse transcriptase, units were reacted at 25 ° C for 10 minutes, 42 ° C for 50 minutes, and 95 ° C for 5 minutes to synthesize cDNA, diluted 1: 4, and 2 μl of the reaction mixture was reacted with qRT -PCR as a template. For qRT-PCR, 20 μl of the reaction solution containing 2 μl of cDNA, 10 μl of SYBR Premix EX Taq (Takara Bio), 0.4 μl of Rox reference dye (50 × Takara Bio) and 200 nM of each gene was amplified using ABI 7500fast sequence detection system (Applied Biosystems) For 30 seconds at 95 ° C, and then amplified by repeating 40 cycles (95 ° C for 3 seconds, 60 ° C for 30 seconds). The specificity of the PCR product was confirmed by reacting at 95 ° C for 15 seconds, at 60 ° C for 1 minute, and at 95 ° C for 15 seconds. GAPDH expression was used as an internal control and the expression of ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 genes was corrected by the ΔΔCT method with GAPDH expression level. The oligonucleotide primer sequences used are as follows (Table 2).

order SEQ ID NO: human ANXA4 (forward) 5'-CTGCTGGCTATAGTAAAGTGCATGA-3 ' 20 human ANXA4 (reverse) 5'-TGCCCGGATATCCAACATGT-3 ' 21 human CD302 (forward) 5'-CCACACCCAGCTAACTTTTTGTATT-3 ' 22 human CD302 (reverse) 5'-GTAAATGACGGTAGAGGAATAAGAGAAAA-3 ' 23 human CDC42EP2 (forward) 5'-GCCTTGCCCTCAAGAACGT-3 ' 24 human CDC42EP2 (reverse) 5'-TGCCAAACATCTGAATCAATGTC-3 ' 25 human EFTUD1 (forward) 5'-CTGCCTGTTGCTGAAAGCTTT-3 ' 26 human EFTUD1 (reverse) 5'-GAATGATCTCCCAATGGCTGAA-3 ' 27 human KCNE4 (forward) 5'-AAAATGCTCTGCATGGATTGG-3 ' 28 human KCNE4 (reverse) 5'-GCTGTATGTCAAAGCGGACTGA-3 ' 29 human MBNL2 (forward) 5'-GCCAGACTTCATCCAGCTTGA-3 ' 30 human MBNL2 (reverse) 5'-TCTGTAACAGGCAACTGGATGGT-3 ' 31 human MICAL2 (forward) 5'-CTCACACGACACCTGGACCTA-3 ' 32 human MICAL2 (reverse) 5'-CCACGCTTATCCAATTTGTACCA-3 ' 33 human PARP4 (forward) 5'-GCCACAATGCTGGTACTACAGTTT-3 ' 34 human PARP4 (reverse) 5'-TCTTACCCATTCACTTGCTTGCT-3 ' 35 human SPSB1 (forward) 5'-TTTTAAAGATTTTCCTCCCTCCTGTT-3 ' 36 human SPSB1 (reverse) 5'-TGAGGACGGCTGGGTCAA-3 ' 37 human SYCP2 (forward) 5'-TGGCTAAAAGTGTCTTCTGTAATACTGAT-3 ' 38 human SYCP2 (reverse) 5'-GCTCCTCTTCTAGCATGTCCTTAAG-3 ' 39 human GAPDH (forward) 5'-AATCCCATCACCATCTTCCA-3 ' 40 human GAPDH (reverse) 5'-TGGACTCCACGACGTACTCA-3 ' 41

Example  6. 5- aza -2'- 도 옥시티디디  (5- aza - dC ) process

Each ovarian cancer cell line was treated with a methylation inhibitor 5-aza-2'-deoxycytidine (Sigma-Aldrich) at a concentration of 10 μM for 3 days and then treated with ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 and SYCP2 Changes in expression were measured using qRT-PCR.

Example  7. Analysis of gene expression changes in anticancer drug-sensitive ovarian cancer cell line and anticancer drug resistant ovarian cancer cell line

RNA was extracted from 11 ovarian cancer cell lines and mRNA microarray was performed using Affymetrix Human Gene 1.0 ST. The expression values of each gene obtained after scanning are used as background correction, RMA normalization (Biostatistics. 2003 Apr; 4 (2): 249-64. Exploration, normalization, and summaries of high density oligonucleotide array probe level data), and log2 transformation (log2 transformation), and finally used for statistical analysis. The following three analyzes were performed to find genes whose expression was significantly changed in relation to cisplatin resistance by comparing the degree of gene expression in the cisplatin-sensitive cell line and the resistant cell line, and the following genes were significantly Differentially expressed genes (DEGs) were selected for the group:

a. Eleven types of ovarian cancer cell lines were classified into cisplatin-sensitive group and resistant group, and the expression changes between the two groups were analyzed to show that the expression level of the resistant cell line was significantly changed by more than 1.5 times in the resistant cell line (p <0.05) (Maximum log2 expression ≥ 7), and a gene whose expression level was 1 or more (Δlog2 expression in 11 cell lines ≥ 1.0) in 11 cell lines.

b. The IC ₅₀ values of 11 ovarian cancer cell lines and the Pearson correlation coefficient of each gene expression were significant (p <0.05), the highest expression level was 7 or more, and the gene expression level was 1 or more in 11 cell lines found.

c. The IC ₅₀ values of the 11 ovarian cancer cell lines and the Spearman correlation coefficient of each gene expression were significant (p <0.05), the highest expression level was 7 or more, and the expression level of the gene was 11 or more in 11 cell lines found.

Example  8. Anti-cancer drug-sensitive ovarian cancer cell line and anti-cancer drug resistant ovarian cancer cell line DNA 메틸레이션  Change analysis

DNA was extracted from eleven ovarian cancer cell lines and bisulfite conversion was performed to convert unmethylated cytosine to uracil. Using human methylation 450 bead chip (illumina), about 485,000 CpG sites The degree of methylation was measured. The degree of DNA methylation is expressed as a value having a value of 0 to 1, and a value of 0 means that the corresponding CpG site is completely unmethylated and 1 means completely methylated. The following three analyzes were performed to find CpG sites with significantly different degrees of methylation in relation to cisplatin resistance, and the CpG sites found in the results of each analysis were found in comparison with the degree of methylation in the cisplatin sensitive cell group and the resistant cell group , And these were selected as differential methylated genes (DMGs) in the two groups:

a. Eleven kinds of ovarian cancer cell lines were classified into cisplatin-sensitive group and resistant group, and the DNA methylation changes between the two groups were analyzed to find a CpG region with a significant change in β value of 0.25 or more in the resistant cell line to the sensitive cell line (β &Gt; 0.25 < 0.05)

b. The IC ₅₀ values of 11 ovarian cancer cell lines and the Pearson correlation coefficient of β value of each CpG site were found to be significant CpG sites (p <0.05)

c. IC ₅₀ values of 11 ovarian cancer cell lines and Spearman correlation coefficient of β value of each CpG site were found to be significant CpG site (p <0.05)

Example  9. Anticancer drug-sensitive ovarian cancer cell line and anticancer drug resistant ovarian cancer cell line DNA 메틸레이션  Analysis of change and gene expression integration

DNA methylation analysis data and gene expression analysis data were integrated analysis to identify the gene whose expression is regulated by methylation among the genes involved in the chemoresistance to cancer treatment, and each DNA methylation analysis data and gene Among the three analysis methods used in the expression analysis data, two or more analysis results showed that DNA methylation, hypomethylation-up_regulation, DNA methylation and hypermethylation-down_regulation (Fig. 1).

Experiment result

1. Classification of anticancer drug-sensitive ovarian cancer cell line and anti-cancer drug resistant ovarian cancer cell line

(OVCAR-3, TOV-21G, TOV-112D, CaOV-3, ES-2, OV-90, PA-1, MDAH 2774, A2780, A2780cp and SK- IC ₅₀ in response to (Sensitivity) and resistant (resistant) to the anticancer agent, and intermediate cells with intermediate resistance between the sensitive cell line and the resistant cell line, and the results were as follows: 2.

2. Promoter CpG Methylation  Prediction of anticancer therapy response using change Marker  selection

Table 3 shows the results of gene expression changes in anticancer-sensitive ovarian cancer cell lines and anticancer drug-resistant ovarian cancer cell lines. In the case of ANXA4, CD302, CDC42EP2, KCNE4, MBNL2, MICAL2, SPSB1 and SYCP2 genes, gene expression was increased in the resistant cell lineage compared to the cisplatin-sensitive ovarian cancer cell line and the gene expression in the resistant cell line was decreased in the EFTUD1 gene there was. In addition, results in ovarian cancer cell lines of 11 examined the significance of the IC ₅₀ value and the gene expression of the cisplatin chemotherapy, ANXA4 gene showed significantly from Spearman correlation CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, PARP4, SPSB1 And SYCP2 gene were significant in both Pearson correlation and Spearman correlation.

gene symbol Resistant vs Sensitive Pearson Correlation Spearman correlation Average expression ^{One )} Range of expression ^{2 )} log2  Fold change p value Pearson rho p value Spearman rho p value ANXA4 2.48 0.01 0.54 0.085 0.63 0.044 10.76 3.8 CD302 2.96 0.002 0.86 0.001 0.85 0.002 10.01 4.67 CDC42EP2 0.67 0.034 0.76 0.006 0.81 0.004 9.48 1.47 EFTUD1 -1.24 0.001 -0.72 0.013 -0.69 0.023 8.03 2.06 KCNE4 1.86 0.009 0.65 0.029 0.65 0.037 7.19 3.8 MBNL2 1.94 0.018 0.61 0.047 0.63 0.044 10.67 3.92 MICAL2 2.95 0.007 0.74 0.009 0.68 0.025 9.19 4.76 PARP4 0.7 0.005 0.73 0.011 0.75 0.012 11.38 1.19 SPSB1 1.27 0.003 0.75 0.008 0.72 0.017 8.73 1.86 SYCP2 2.44 0.017 0.73 0.011 0.74 0.013 6.49 4.2

1) associated with maximum log2 expression

2) associated with changes in expression level in 11 cell lines (Δlog2 expression in 11 cell lines)

Table 4 shows the results of analysis of DNA methylation changes in anticancer drug-sensitive ovarian cancer cell lines and anticancer drug-resistant ovarian cancer cell lines. In the case of ANXA4, CD302, CDC42EP2, KCNE4, MBNL2, MICAL2, SPSB1 and SYCP2 genes, the DNA methylation of the promoter CpG region was decreased in the anticancer-resistant ovarian cancer cell line. In the case of EFTUD1, The increase in the number of In addition, the IC ₅₀ values for the cisplatin anticancer drugs and the degree of change in the promoter CpG methylation were found to be significant in the 11 ovarian cancer cell lines. KCNE4 and MBNL2 genes were significant in Spearman correlation and MICAL2 gene was significant in Pearson correlation And ANXA4, CD302, CDC42EP2, EFTUD1, PARP4, SPSB1 and SYCP2 genes were significant in both Pearson correlation and Spearman correlation.

gene symbol Location of  CpG site Resistant vs Sensitive Pearson  Correlation Spearman  correlation Range of 메틸레이션 ^{One )} difference in  beta value p value Pearson rho p value Spearman rho p value ANXA4 5'UTR -0.56 0.017 -0.65 0.037 -0.63 0.036 0.81 CD302 TSS1500 -0.47 0.002 -0.77 0.008 -0.74 0.009 0.77 TSS1500 -0.38 0.01 -0.91 0 -0.64 0.035 0.79 TSS1500 -0.55 0.001 -0.79 0.006 -0.84 0.001 0.83 CDC42EP2 5'UTR -0.34 0.051 -0.66 0.031 -0.77 0.006 0.78 5'UTR -0.2 0.154 -0.67 0.028 -0.63 0.039 0.8 EFTUD1 TSS1500 0.27 0.094 0.64 0.04 0.61 0.047 0.54 KCNE4 TSS200 -0.35 0.015 -0.84 0.003 -0.68 0.021 0.77 TSS1500 -0.39 0.029 -0.62 0.048 -0.63 0.038 0.81 TSS200 -0.31 0.04 -0.6 0.056 -0.66 0.027 0.72 TSS1500 -0.41 0.036 -0.58 0.066 -0.63 0.038 0.81 TSS1500 -0.43 0.012 -0.82 0.004 -0.71 0.014 0.81 MBNL2 5'UTR -0.46 0.016 -0.66 0.031 -0.73 0.011 0.72 5'UTR -0.57 0.003 -0.52 0.107 -0.62 0.041 0.78 5'UTR -0.43 0.007 -0.84 0.003 -0.65 0.031 0.79 MICAL2 5'UTR -0.5 0.021 -0.7 0.021 -0.54 0.088 0.76 PARP4 5'UTR -0.42 0.138 -0.85 0.004 -0.63 0.049 0.92 SPSB1 5'UTR -0.28 0.013 -0.63 0.044 -0.73 0.011 0.57 SYCP2 TSS1500 -0.66 0.001 -0.7 0.021 -0.82 0.002 0.8

1) means the value obtained by subtracting the minimum β value from the maximum β value of 11 cell lines

Table 5 shows the positions of CpG sites showing significant DNA methylation expression changes in cancer-resistant ovarian cancer cell lines and cancer-resistant ovarian cancer cell lines. Chromosomal location is indicated in accordance with The December 2013 Human reference sequence (GRCh38).

gene order Chromosome location ANXA4 CTGGCCAAAATATGGACAAAAGATCGTCCGTAAGTTACTAGCTGGGTGCTAGGCTGGAAT [ CG ] ATTCTTATTTAAGATGGCCTAGTAGGCAGGCCTCCAAATTTGTTTTCATTCCTTTACCTT (SEQ ID NO: 1) ch2: 69770033-69770154 CD302 AGCTTCTCTAAATATTGACATTGTATATAACGCCAGTGCAGTGATCAAACACAGGGCACT [ CG ] CACTGGGATAATGCGATTAGCTAATCTACAGCACTTACCACATTTCATTAATTGCCCCTC (SEQ ID NO: 2) ch2: 159798495-159798616 TGACATTGTATATAACGCCAGTGCAGTGATCAAACACAGGGCACTCGCACTGGGATAATG [ CG ] ATTAGCTAATCTACAGCACTTACCACATTTCATTAATTGCCCCTCTAAGGGTCCTTTTCT (SEQ ID NO: 3) ch2: 159798510-159798631 AGCACAAGAGATTTCCGTAACCCTTCAGCCAGCTTCTCTAAATATTGACATTGTATATAA [ CG ] CCAGTGCAGTGATCAAACACAGGGCACTCGCACTGGGATAATGCGATTAGCTAATCTACA (SEQ ID NO: 4) ch2: 159798465-159798586 CDC42EP2 GTGAGTGAGACAGCTGTCAGGGACGCCCAATTTGTTGTGGAAACACTCAGGCTGTCTTGG [ CG ] CTGCCGTGTGATGGGTTGGGGGTGCGGGGAGGACCTGGCCCAGGCTCTGGGTACATCCC (SEQ ID NO: 5) ch11: 65316855-65316976 TAGATGGAGGAGATCTGGGGACCCACTGTTCCCAGCCTAGCTGTGAGCCCCTTTCTCTCC [ CG ] CTCCCCAAACATATTATGGAAGTAGGCGTGGCCCACTGCATGGGAACCACGTGGACCAGG (SEQ ID NO: 6) ch11: 65316443-65316564 EFTUD1 AAGAAACGGCTGGTGTAGCGGCGGGCCCGGGCTTGGGAGCCGACCTAGGGCCTAGGTGCA [ CG ] GAGCCGGCTCCTCGGGAACCCTGAGAGTGGCCGTCCCCCGGAGATGAAGGGACGAGGGCG (SEQ ID NO: 7) ch15: 82262935-82263056 KCNE4 ACTTTGGGGTAACGGTTCCAGCACAGCACATCCCTTTCTCCTCTTTTCACTCATCGTCAC [ CG ] CTACCTGAAAACCCTGGCCGGGTGCTGGGGCTTGAGGAGCAGTTCCCACTTCCCAGTCTT (SEQ ID NO: 8) ch2: 223051909-223052030 GTAGCCCAATAATGGTTATTCCCCAGGAGCCGCGCGAAGCATGAGCTAATTTTCAGTGAG [ CG ] CGGACTTTGGGGTAACGGTTCCAGCACAGCACATCCCTTTCTCCTCTTTTCACTCATCGT (SEQ ID NO: 9) ch2: 223051844-223051965 ACAGCTGCAAAGTTCAGGGAGTTGAACTGCAGTGCTTTCAGTTCACTGCTCACTCTGCCA [ CG ] ATCAATCTCTGTTGTAAATTTTCCTCCCAGAGCACGTGACGATGCACTTCTTGACTATAT (SEQ ID NO: 10) ch2: 223052042-223052163 ATTATGGGATTCAGCTGCCTCTGAAAACCTGTAGCCCAATAATGGTTATTCCCCAGGAGC [ CG ] CGCGAAGCATGAGCTAATTTTCAGTGAGCGCGGACTTTGGGGTAACGGTTCCAGCACAGC (SEQ ID NO: 11) ch2: 223051814-223051935 TTATTTGCATAAGGAGTGGAAGAACTGAAACCGAAGCCCCAGTTCCTTGACTGTAAATCC [ CG ] CACTTGCTTCCAACTGTCTTTCATCCAGATTATGGGATTCAGCTGCCTCTGAAAACCTGT (SEQ ID NO: 12) ch2: 223051724-223051845 MBNL2 GTCGATGTCTCAAGATTTCTTGGTTCATCTTTATGATGCCAAAGCACACACCCTCTACCT [ CG ] TTTGTTTCAGTCACCCTGGGTTCTTGTTGGAATGGCCCAGGGAGCTCCATGTAAATCATG (SEQ ID NO: 13) ch13: 97257602-97257723 TTTCAATTTGCTGTTGCTATGGTGAAAACAAATCAATATCACATGGCTACCAGCCAGTCC [ CG ] CGCTCAGGGAGTGCCATAGAAATTCAAGATCAGGTACTCAAGATTCCAAGCAAGAATTGG (SEQ ID NO: 14) ch13: 97225103-97225224 TGAAGGAGCAGTCAAAGGCCAGGATGGTTGGGGGGAGTCAGAAAGTATGGGGCCAGTCAC [ CG ] AGGTCAGTGTAGGCCGTCAGAAGACTCTTGACAGTCCCGCTCTGTGAGGTGGGGAGCCAT (SEQ ID NO: 15) ch13: 97260256-97260377 MICAL2 GGTGCCCTGACTGCAGCCAACAATAGAATTTGTTTAGCCATCTTGCTATTCCTTTCTTCA [ CG ] TGCAAAACTTGTTGGAGGCCAGGGAGAGATTCTCTGTCCATTTCCTCTTGCTGGGTGAAG (SEQ ID NO: 16) ch11: 12138155-12138276 PARP4 TTAAACATAAATCTGCGGTCTGTTCTTAGCACCTGCGGCTGCGTGGGAGGTATGGAAAGG [ CG ] CACTTTGGGTTTCGTGAAATCTCAAGTCAGGTCTTGACTTCTCTCTTTCCACAGATTCAT (SEQ ID NO: 17) ch13: 24511103-24511224 SPSB1 TCACATGACGGGGTGGGAGCTGAATGTGAATGTGACTCCTGAGCTGCAGCTTCTAACCAT [ CG ] AGTGATGCACACTCTGAGGCCCACAGTGACATGTGCATGGCACCCTTGGCCTGATGCCAG (SEQ ID NO: 18) ch1: 9315508-9315629 SYCP2 CGTTCTCGCCTGCCGGCTTGAAAGGCCAAGCCGAAGCCCCACCCTCCCTCCGCGCCCCGC [ CG ] TGGGGGAAGCCCACCCAGGCACTCTGCTCAACCTGCCTGCGGCAGGAGGCGTCCGCGTAG (SEQ ID NO: 19) ch20: 59933471-59933592

DNA methylation changes and gene expression in cancer-sensitive ovarian cancer cell lines and anticancer-resistant ovarian cancer cell lines were analyzed by DNA methylation, DNA methylation and hypermethylation-up_regulation, (10, 10, 20, 30, 40, 50, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, and 60 days) were selected as anticancer drug response prediction markers.

ANXA4 is an anticancer agent sensitivity cells had the gene expression in the resistant cell master, with respect to the master, is that methylation at increased 5.6 times and at the same time the promoter CpG sites, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and gene expression, and promoter CpG The DNA methylation changes in the promoter CpG region of the ANXA4 gene were selected as predictors of anticancer drug response.

CD302 is a cancer sensitive cells was the gene expressed in the resistant cell master, with respect to the master, is that methylation at increased 7.8 times and at the same time the promoter CpG sites, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and gene expression, and promoter CpG The degree of DNA methylation in the CD302 gene was significantly correlated with Pearson correlation and Spearman correlation. Therefore, the change in DNA methylation at the promoter CpG region of the CD302 gene was selected as an anticancer drug response prediction marker.

CDC42EP2 has had the gene expression is increased 1.59-fold in the resistant cell master, with respect to an anticancer agent sensitivity cells week group, the IC ₅₀ value and the gene expression and level of promoter CpG DNA methylation changes to cisplatin chemotherapy in ovarian cancer cell lines of 11 Pearson correlation and Spearman correlation, the change in DNA methylation at the promoter CpG site of the CDC42EP2 gene was selected as a predictive marker for chemotherapy response.

EFTUD1 has had the gene expression decreases 2.36 times the resistant cell master, with respect to an anticancer agent sensitivity cells week group, the IC ₅₀ value and the gene expression and level of promoter CpG DNA methylation changes to cisplatin chemotherapy in ovarian cancer cell lines of 11 Pearson correlation and Spearman correlation, the DNA methylation changes in the promoter CpG region of the EFTUD1 gene were selected as predictors of anticancer drug response.

KCNE4 showed 3.63 fold increase in gene expression in the resistant cell line of the anticancer sensitive cell line and hypomethylation in the promoter CpG region. In the 11 ovarian cancer cell lines, IC ₅₀ value and gene expression and cpm The DNA methylation changes in the promoter CpG region of the KCNE4 gene were selected as predictors of anticancer drug response.

The MBNL2 gene was 3.83 times more potent in the resistant cell line than that in the cancer cell line, and was hypomethylated at the promoter CpG site. In the 11 ovarian cancer cell lines, the IC ₅₀ value and the gene expression and promoter CpG The DNA methylation change in the promoter CpG region of the MBNL2 gene was selected as the predictive marker for anticancer drug response.

MICAL2 the anticancer sensitive cells was the gene expression in the resistant cell master, with respect to the master, is that methylation at and at the same time the promoter CpG sites increased 7.73 times, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and gene expression, and promoter CpG The DNA methylation changes in the promoter CpG region of the MICAL2 gene were selected as predictors of anticancer drug response.

PARP4 has had the gene expression is increased 1.62-fold in the resistant cell master, with respect to an anticancer agent sensitivity cells week group, the IC ₅₀ value and the gene expression and level of promoter CpG DNA methylation changes to cisplatin chemotherapy in ovarian cancer cell lines of 11 Pearson correlation and Spearman correlation, the change in DNA methylation in the promoter CpG region of the PARP4 gene was selected as a predictor of anticancer drug response.

In SPSB1, the gene expression in the resistant cell line was increased 2.4-fold and the methylation level was low in the promoter CpG region. In the ovarian cancer cell lines, the IC ₅₀ value and the gene expression and promoter CpG The DNA methylation change in the promoter CpG region of the SPSB1 gene was selected as an anticancer drug response prediction marker since the degree of DNA methylation change in the SPSB1 gene was significant in Pearson correlation and Spearman correlation.

SYCP2 the anticancer sensitive cells showed gene expression in the resistant cell master, with respect to the master, is that methylation at and at the same time the promoter CpG sites increased 5.43 times, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and gene expression, and promoter CpG The DNA methylation changes in the promoter CpG region of the SYCP2 gene were selected as predictors of anticancer drug response, as the degree of DNA methylation change was significant in Pearson correlation and Spearman correlation.

3. Promoter of gene in ovarian cancer cell line CpG Methylation  Identification of regulation of gene expression by changes

Each ovarian cancer cell line was treated with 5-aza-2'-deoxycytidine, a DNA methylation agent, for 3 days. Ten genes (ANXA4, CD302, CDC42EP2, EFTUD1, KCNE4, MBNL2, MICAL2, SPSB1 and SYCP2) And the expression of these genes was found to be increased. This means that expression of the above genes is regulated by DNA methylation (Figures 3-12).

These results indicate that 10 genes expressing significant expression changes in anticancer drug resistant ovarian cancer cell lines are regulated by hypomethylation and / or hypermethylation of specific CpG sites in the promoter region of each gene, This means that the marker can be used as a marker.

<110> Ewha University - Industry Collaboration Foundation <120> Composition for predicting the response to anti-cancer drug of          ovarian cancer using CpG methylation status in promoter region of          PARP4 gene and uses thereof <130> DPP20145435KR <160> 41 <170> Kopatentin 1.71 <210> 1 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of ANXA4 gene (Chr2: 69770033-69770154) <400> 1 ctggccaaaa tatggacaaa agaccgtccg taagttacta gctgggtgct aggctggaat 60 cgattcttat ttaagatggc ctagtaggca ggcctccaaa tttgttttca ttcctttacc 120 tt 122 <210> 2 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) &Lt; 223 > CpG in promoter region of CD302 gene (Chr2: 159798495-159798616) <400> 2 agcttctcta aatattgaca ttgtatataa cgccagtgca gtgatcaaac acagggcact 60 cgcactggga taatgcgatt agctaatcta cagcacttac cacatttcat taattgcccc 120 tc 122 <210> 3 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of CD302 gene (Chr2: 159798510-159798631) <400> 3 tgacattgta tataacgcca gtgcagtgat caaacacagg gcactcgcac tgggataatg 60 cgattagcta atctacagca cttaccacat ttcattaatt gcccctctaa gggtcctttt 120 ct 122 <210> 4 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of CD302 gene (Chr2: 159798465-159798586) <400> 4 agcacaagag atttccgtaa cccttcagcc agcttctcta aatattgaca ttgtatataa 60 cgccagtgca gtgatcaaac acagggcact cgcactggga taatgcgatt agctaatcta 120 ca 122 <210> 5 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of CDC42EP gene (Chr11: 65316855-65316976) <400> 5 gtgagtgaga cagctgtcag ggacgcccaa tttgttgtgg aaacactcag gctgtcttgg 60 cgctgccgtg tgatggggtt gggggtgcgg ggaggacctg gcccaggctc tgggtacatc 120 cc 122 <210> 6 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of CDC42EP gene (Chr11: 65316443-65316564) <400> 6 tagatggagg agatctgggg acccactgtt cccagcctag ctgtgagccc ctttctctcc 60 cgctccccaa acatattatg gaagtaggcg tggcccactg catgggaacc acgtggacca 120 gg 122 <210> 7 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of EFTUD1 gene (Chr15: 82262935-82263056) <400> 7 aagaaacggc tggtgtagcg gcgggcccgg gcttgggagc cgacctaggg cctaggtgca 60 cggagccggc tcctcgggaa ccctgagagt ggccgtcccc cggagatgaa gggacgaggg 120 cg 122 <210> 8 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of KCNE4 gene (Chr2: 223051909-223052030) <400> 8 actttggggt aacggttcca gcacagcaca tccctttctc ctcttttcac tcatcgtcac 60 cgctacctga aaaccctggc cgggtgctgg ggcttgagga gcagttccca cttcccagtc 120 tt 122 <210> 9 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of KCNE4 gene (Chr2: 223051844-223051965) <400> 9 gtagcccaat aatggttatt ccccaggagc cgcgcgaagc atgagctaat tttcagtgag 60 cgcggacttt ggggtaacgg ttccagcaca gcacatccct ttctcctctt ttcactcatc 120 gt 122 <210> 10 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of KCNE4 gene (Chr2: 223052042-223052163) <400> 10 acagctgcaa agttcaggga gttgaactgc agtgctttca gttcactgct cactctgcca 60 cgatcaatct ctgttgtaaa ttttcctccc agagcacgtg acgatgcact tcttgactat 120 at 122 <210> 11 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of KCNE4 gene (Chr2: 223051814-223051935) <400> 11 attatgggat tcagctgcct ctgaaaacct gtagcccaat aatggttatt ccccaggagc 60 cgcgcgaagc atgagctaat tttcagtgag cgcggacttt ggggtaacgg ttccagcaca 120 gc 122 <210> 12 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of KCNE4 gene (Chr2: 223051724-223051845) <400> 12 ttatttgcat aaggagtgga agaactgaaa ccgaagcccc agttccttga ctgtaaatcc 60 cgcacttgct tccaactgtc tttcatccag attatgggat tcagctgcct ctgaaaacct 120 gt 122 <210> 13 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of MBNL2 gene (Chr13: 97257602-97257723) <400> 13 gtcgatgtct caagatttct tggttcatct ttatgatgcc aaagcacaca ccctctacct 60 cgtttgtttc agtcaccctg ggttcttgtt ggaatggccc agggagctcc atgtaaatca 120 tg 122 <210> 14 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of MBNL2 gene (Chr13: 97225103-97225224) <400> 14 tttcaatttg ctgttgctat ggtgaaaaca aatcaatatc acatggctac cagccagtcc 60 cgcgctcagg gagtgccata gaaattcaag atcaggtact caagattcca agcaagaatt 120 gg 122 <210> 15 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of MBNL2 gene (Chr13: 97260256-97260377) <400> 15 tgaaggagca gtcaaaggcc aggatggttg gggggagtca gaaagtatgg ggccagtcac 60 cgaggtcagt gtaggccgtc agaagactct tgacagtccc gctctgtgag gtggggagcc 120 at 122 <210> 16 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of MICAL2 gene (Chr11: 12138155-12138276) <400> 16 ggtgccctga ctgcagccaa caatagaatt tgtttagcca tcttgctatt cctttcttca 60 cgtgcaaaac ttgttggagg ccagggagag attctctgtc catttcctct tgctgggtga 120 ag 122 <210> 17 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of PARP4 gene (Chr13: 24511103-24511224) <400> 17 ttaaacataa atctgcggtc tgttcttagc acctgcggct gcgtgggagg tatggaaagg 60 cgcactttgg gtttcgtgaa atctcaagtc aggtcttgac ttctctcttt ccacagattc 120 at 122 <210> 18 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of SPSB1 gene (Chr1: 9315508-9315629) <400> 18 tcacatgacg gggtgggagc tgaatgtgaa tgtgactcct gagctgcagc ttctaaccat 60 cgagtgatgc acactctgag gcccacagtg acatgtgcat ggcacccttg gcctgatgcc 120 ag 122 <210> 19 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> CpG in promoter region of SYCP2 gene (Chr20: 59933471-59933592) <400> 19 gcttctcgcc tgccggcttg aaaggccaag ccgaagcccc accctccctc cgcgccccgc 60 cgtgggggaa gcccacccag gcactctgct caacctgcct gcggcaggag gcgtccgcgt 120 ag 122 <210> 20 <211> 25 <212> DNA <213> Artificial Sequence <220> <223> human ANXA4 (forward) primer <400> 20 ctgctggcta tagtaaagtg catga 25 <210> 21 <211> 20 <212> DNA <213> Artificial Sequence <220> Human ANXA4 (reverse) primer <400> 21 tgcccggata tccaacatgt 20 <210> 22 <211> 25 <212> DNA <213> Artificial Sequence <220> Human CD302 (forward) primer <400> 22 ccacacccag ctaacttttt gtatt 25 <210> 23 <211> 29 <212> DNA <213> Artificial Sequence <220> Human CD302 (reverse) primer <400> 23 gtaaatgacg gtagaggaat aagagaaaa 29 <210> 24 <211> 19 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > human CDC42EP2 (forward) primer <400> 24 gccttgccct caagaacgt 19 <210> 25 <211> 23 <212> DNA <213> Artificial Sequence <220> Human CDC42EP2 (reverse) primer <400> 25 tgccaaacat ctgaatcaat gtc 23 <210> 26 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> human EFTUD1 (forward) primer <400> 26 ctgcctgttg ctgaaagctt t 21 <210> 27 <211> 22 <212> DNA <213> Artificial Sequence <220> Human EFTUD1 (reverse) primer <400> 27 gaatgatctc ccaatggctg aa 22 <210> 28 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> human KCNE4 (forward) primer <400> 28 aaaatgctct gcatggattg g 21 <210> 29 <211> 22 <212> DNA <213> Artificial Sequence <220> <223> human KCNE4 (reverse) primer <400> 29 gctgtatgtc aaagcggact ga 22 <210> 30 <211> 21 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > human MBNL2 (forward) primer <400> 30 gccagacttc atccagcttg a 21 <210> 31 <211> 23 <212> DNA <213> Artificial Sequence <220> Human MBNL2 (reverse) primer <400> 31 tctgtaacag gcaactggat ggt 23 <210> 32 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> human MICAL2 (forward) primer <400> 32 ctcacacgac acctggacct a 21 <210> 33 <211> 23 <212> DNA <213> Artificial Sequence <220> Human MICAL2 (reverse) primer <400> 33 ccacgcttat ccaatttgta cca 23 <210> 34 <211> 24 <212> DNA <213> Artificial Sequence <220> Human PARP4 (forward) primer <400> 34 gccacaatgc tggtactaca gttt 24 <210> 35 <211> 23 <212> DNA <213> Artificial Sequence <220> Human PARP4 (reverse) primer <400> 35 tcttacccat tcacttgctt gct 23 <210> 36 <211> 26 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > human SPSB1 (forward) primer <400> 36 ttttaaagat tttcctccct cctgtt 26 <210> 37 <211> 18 <212> DNA <213> Artificial Sequence <220> Human SPSB1 (reverse) primer <400> 37 tgaggacggc tgggtcaa 18 <210> 38 <211> 29 <212> DNA <213> Artificial Sequence <220> <223> human SYCP2 (forward) primer <400> 38 tggctaaaag tgtcttctgt aatactgat 29 <210> 39 <211> 25 <212> DNA <213> Artificial Sequence <220> Human SYCP2 (reverse) primer <400> 39 gctcctcttc tagcatgtcc ttaag 25 <210> 40 <211> 20 <212> DNA <213> Artificial Sequence <220> <223> human GAPDH (forward) primer <400> 40 aatcccatca ccatcttcca 20 <210> 41 <211> 20 <212> DNA <213> Artificial Sequence <220> Human GAPDH (reverse) primer <400> 41 tggactccac gacgtactca 20

Claims (11)

A composition for predicting responsiveness to a platinum-based anticancer agent in an ovarian cancer patient, comprising an agent for measuring the methylation level of the CpG region of a poly (ADP-ribose) polymerase family, member 4 gene promoter.
2. The method according to claim 1, wherein the agent for measuring the methylation level of the CpG region of the gene promoter comprises
Compounds or methylation sensitive restriction enzymes that modify unmethylated cytosine bases;
A primer specific to the methylated sequence of the CpG region of the gene promoter; And
Wherein the primer comprises a primer specific for the unmethylated sequence.
3. The composition of claim 2, wherein the compound that modifies the unmethylated cytosine base is bisulfite or a salt thereof.
3. The composition of claim 2, wherein the methylation sensitive restriction enzyme is Sma I, Sac II, Eag I, Hpa II, Msp I, Bss HII, Bst UI or Not I.
The composition according to claim 1, wherein the CpG site of the gene promoter comprises CpG which appears in the nucleotide sequence of SEQ ID NO: 17 (24511103 to 24511224 th of chromosome 13).
A kit for predicting the response of a platinum-based anticancer agent to ovarian cancer patients, comprising the composition of any one of claims 1 to 5.
(a) treating the genomic DNA in the obtained sample with a compound or methylation-sensitive restriction enzyme that transforms the unmethylated cytosine base; And
(b) amplifying the treated DNA by PCR using a primer capable of amplifying the CpG region of the PARP4 (poly (ADP-ribose) polymerase family, member 4) gene promoter.
METHODS OF DETECTING THE Methylation Levels of the CpG Region of the PARP4 Gene Promoter from Patient Samples to Provide the Information Needed to Predict Responses to Platinum-Based Anticancer Agents in Ovarian Cancer Patients.
delete 8. The method according to claim 7, wherein the CpG site of the gene promoter comprises CpG which appears in the nucleotide sequence of SEQ ID NO: 17 (24511103 to 24511224-th of chromosome 13).
8. The method of claim 7, wherein the compound that modifies the unmethylated cytosine base is bisulfite or a salt thereof.
8. The method according to claim 7, wherein the methylation level is detected by a methylation-specific polymerase chain reaction, a real-time methylation-specific polymerase chain reaction, Wherein the method is selected from the group consisting of PCR using affinity binding proteins, quantitative PCR, pyrosequencing and bisulfite sequencing.

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