KR101597811B1 - Gene relating to anti-cancer drug resistance and use thereof - Google Patents

Abstract

The present invention relates to a composition for predicting the reactivity of a platinum-based anticancer drug therapy in a patient with ovarian cancer by detecting a level of methylation in a CpG region on a promoter of a synaptopodin (SYNPO) gene. The present invention further relates to a kit and a method thereof. To this end, the composition of the present invention comprises a formulation for measuring the level of methylation in the CpG region on the promoter of the SYNPO gene.

Description

Anticancer drug resistance-related genes and their use {Gene relating to anti-cancer drug resistance and use thereof}

The present invention relates to compositions, kits, and methods for predicting platinum-based chemotherapeutic response in ovarian cancer patients by detecting the methylation level of the CpG region of the SYNPO (synaptopodin) gene promoter.

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 pharmaceutical composition for preventing or treating an epidermal growth factor receptor pathway substrate 8-like 3 (EPS8L3), HSPA2 (heat shock 70kDa protein 2), SYNPO (synaptopodin), ZNF93 (zinc finger protein 93), ADD2 , H1F0 (H1 histone family, member 0), LRRC8B (leucine rich repeat containing 8 family, member B), SHC3 (Src homology 2 domain containing transforming protein 3) and ZFP37 (zinc finger protein 37 homolog) The present invention provides a composition for predicting the reactivity of an ovarian cancer patient against an anticancer agent, comprising a preparation for measuring the methylation level of a CpG site of a promoter of one or more genes.

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 for detecting the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37, And to provide a method for predicting the reactivity to an anticancer agent.

Another object of the present invention is to provide a method for predicting the response of an ovarian cancer patient to an anticancer agent in a group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 And a method for detecting methylation of the CpG region of one or more selected gene promoters.

The present invention is based on the finding that specific CpG sites of the EPS8L3, HSPA2, SYNPO and ZNF93 gene promoters are specifically under-methylated in anticancer-resistant cells, thereby specifically increasing the expression of the gene and ADD2, H1F0, LRRC8B, SHC3 and ZFP37 Specific CpG sites of the gene promoter are specifically hypermethylated in anticancer-resistant cells, and thereby the expression of the gene is specifically reduced. The degree of methylation of the promoter of the genes is used as a biomarker, And provides a technique for predicting the responsiveness of cancer patients to anticancer drugs.

CpG of the EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 gene promoters showed specific methylation changes in the anticancer drug resistant cells. Therefore, Or two or more of them may be used as a complex biomarker.

Accordingly, the present invention includes an agent for measuring the methylation level of the CpG region of the promoter of at least one gene selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 To an anticancer agent for ovarian cancer patients, 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 EPS8L3 gene.

In this case, more preferably, the composition and the kit include a preparation for measuring the methylation level of the CpG region of one or more gene promoters selected from the group consisting of HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 As shown in FIG.

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 HSPA2 gene.

In this case, more preferably, the composition and kit include a preparation for measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 As shown in FIG.

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 a promoter of the SYNPO gene.

In this case, more preferably, the composition and kit include a preparation for measuring the methylation level of the CpG region of one or more gene promoters selected from the group consisting of EPS8L3, HSPA2, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 As shown in FIG.

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 a methylation level of a CpG region of a promoter of ZNF93 gene.

In this case, more preferably, the composition and kit include a preparation for measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 As shown in FIG.

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 ADD2 gene.

In this case, more preferably, the composition and kit include a preparation for measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, H1F0, LRRC8B, SHC3 and ZFP37 As shown in FIG.

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 H1F0 gene.

In this case, more preferably, the composition and kit include a preparation for measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, LRRC8B, SHC3 and ZFP37 As shown in FIG.

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 LRRC8B gene.

In this case, more preferably, the composition and the kit include a preparation for measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, SHC3 and ZFP37 As shown in FIG.

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 SHC3 gene.

In this case, more preferably, the composition and the kit further comprise a preparation for measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B and ZFP37 As shown in FIG.

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 ZFP37 gene.

In this case, more preferably, the composition and kit include a preparation for measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B and SHC3 As shown in FIG.

In the present invention, the EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 genes can be identified in the known gene database.

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 methylation level" as used herein refers to a measurement of the methylation level of the CpG region of the promoter of the EPS8L3 gene, including 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 EPS8L3 gene may mean measuring the methylation level of the cytosine of the CpG region present in the 109763825 to 109763946 base of chromosome 1. In the present invention, the nucleotide sequence of the CpG site is represented by SEQ ID NO: 1.

More preferably, measuring the methylation level of the CpG region of the promoter of the EPS8L3 gene in the present invention may mean measuring the methylation level of cytosine located at 109763885th (position 61 of SEQ ID NO: 1) of chromosome 1 .

Also preferably, in the present invention, the methylation level of the CpG region of the promoter of the HSPA2 gene is determined by measuring the 64540187 to 64540308 base, 64540272 to 64540393 base, 64540659 to 64540780 base, 64539999 to 64540120 base, 64540164 to 64540670 base, 64540549 to 64540670 base, 64540318 to 64540439 base, 64540324 to 64540439 base, 64540324 to 64542444 base, 64540734 to 64540855 base, 64540045 to 64540166 base, 64542487 to 64542608 base, or 64542929 to 64540670 base, Lt; RTI ID = 0.0 > CpG < / RTI > site. In the present invention, the nucleotide sequences of the CpG region are represented by SEQ ID NOS: 2 to 13, respectively.

More preferably, in the present invention, the methylation level of the CpG region of the promoter of the HSPA2 gene is measured by comparing the 64540247th (61st in SEQ ID NO: 2), 64540332 (61st in SEQ ID NO: 3) or 64540719 (61st in SEQ ID NO: 4), 64540059 (61st in SEQ ID NO: 5), 64540225 (61st in SEQ ID NO: 6), 64540609 (61st in SEQ ID NO: 7), 64540378 (61st of SEQ ID NO: 10), 64540594 (61st of SEQ ID NO: 9), 645403894 (61st of SEQ ID NO: The 61 th position of SEQ ID NO: 13).

Also preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the SYNPO gene may mean measuring the methylation level of cytosine at the CpG site appearing in the 150639874 to 150639995 base of chromosome 5. In the present invention, the nucleotide sequence of the CpG site is represented by SEQ ID NO: 14.

More preferably, measuring the methylation level of the CpG region of the promoter of the SYNPO gene in the present invention may mean measuring the methylation level of cytosine located at position 150639934 (SEQ ID NO: 61) of chromosome 5 have.

Also preferably, measuring the methylation level of the CpG region of the promoter of the ZNF93 gene in the present invention may mean measuring the methylation level of cytosine at the CpG site appearing in 19900852 to 19900973 base of chromosome 19. In the present invention, the nucleotide sequence of the CpG site is represented by SEQ ID NO: 15.

More preferably, measuring the methylation level of the CpG region of the promoter of the ZNF93 gene in the present invention may mean measuring the methylation level of cytosine located at position 19900912 (61st position of SEQ ID NO: 15) of chromosome 19 .

Also preferably, measuring the methylation level of the CpG region of the promoter of the ADD2 gene in the present invention may mean measuring the methylation level of the cytosine at the CpG site appearing in the 70768415 to 70768536 base of chromosome 2. In the present invention, the nucleotide sequence of the CpG site is represented by SEQ ID NO: 16.

More preferably, measuring the methylation level of the CpG region of the promoter of the ADD2 gene in the present invention may mean measuring the methylation level of the cytosine located at 70768475 th (position 61 of SEQ ID NO: 16) of chromosome 2 have.

Preferably, in the present invention, the methylation level of the CpG region of the promoter of the H1F0 gene is measured by measuring the methylation level of the chromosome 22 of 37805527 to 37805648 base, 37805781 to 37805902 base, 37805623 to 37805744 base, 37804154 to 37804275 base, May refer to measuring the methylation level of the cytosine at the CpG site appearing in the 37805429 to 37805550 base, 37805070 to 37805191 base, 37806592 to 37806713 base or 37805075 to 37805196 base. In the present invention, the nucleotide sequences of the CpG site are represented by SEQ ID NO: 17 to SEQ ID NO: 24, respectively.

More preferably, in the present invention, the methylation level of the CpG region of the promoter of the H1F0 gene can be measured by comparing the 37th, (61st in SEQ ID NO: 19), 37804214 (61st in SEQ ID NO: 20), 37805489 (61st in SEQ ID NO: 21), 37805130 (61st in SEQ ID NO: 22), 37806652 Th >) or 37805135 (position 61 of SEQ ID NO: 24).

Also, preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the LRRC8B gene may mean measuring the methylation level of the cytosine of the CpG region appearing in the 89524306 to 89524427 base of chromosome 1. In the present invention, the nucleotide sequence of the CpG site is represented by SEQ ID NO: 25.

More preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the LRRC8B gene may mean measuring the methylation level of cytosine located at position 89524366 (61st position in SEQ ID NO: 25) of chromosome 1 .

Also preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the SHC3 gene may mean measuring the methylation level of cytosine at the CpG site that appears in the 89178746 to 89178867 base of chromosome 9. In the present invention, the nucleotide sequence of the CpG site is represented by SEQ ID NO: 26.

More preferably, measuring the methylation level of the CpG region of the promoter of the SHC3 gene in the present invention may mean measuring the methylation level of cytosine located at position 89178806 (position 61 of SEQ ID NO: 26) of chromosome 9 .

Also, preferably, in the present invention, measuring the methylation level of the CpG region of the promoter of the ZFP37 gene may mean measuring the methylation level of cytosine at the CpG site appearing in the 113056818 to 113056939 base of chromosome 9. In the present invention, the nucleotide sequence of the CpG site is represented by SEQ ID NO: 27.

More preferably, measuring the methylation level of the CpG region of the promoter of the ZFP37 gene in the present invention may mean measuring the methylation level of cytosine at position 113056878 (61st position in SEQ ID NO: 27) of chromosome 9 .

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. (EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37), whose expression is regulated by DNA methylation, among the genes involved in resistance to chemotherapy And 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.

Therefore, the hypomethylation or hypermethylation of DNA methylation occurring at specific CpG positions of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and / or ZFP37 is a biologic agent for predicting the response to anticancer drugs in ovarian cancer patients It can be used as a marker.

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 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 a significant similarity to the methylation change of genomic DNA obtained from a biological sample such as tissue, whole blood, serum, plasma, saliva, sputum or urine, 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, EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and / A primer specific for the methylated allele sequence of the non-methylated allele sequence, 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 by a representative method for measuring the level of methylation at the CpG site of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and / or ZFP37 gene promoters of a patient, By treating a compound that modifies a cytosine base that is not methylated to DNA or a methylation-sensitive restriction enzyme, amplifying the treated DNA by PCR using a primer, and confirming presence or absence of the amplified product have.

Thus, the preparations of the present invention include primers specific for methylated allele sequences of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and / or ZFP37 genes and primers specific for unmethylated allele sequences can do. 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. Also, 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 EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37, To an anticancer agent.

In order to provide information necessary for predicting the reactivity of an ovarian cancer patient to an anticancer agent, a sample of a patient selected from the group consisting of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 And more particularly, to a method for detecting methylation of a CpG region of a gene promoter or more.

For example, the present invention relates to a method for detecting methylation of a CpG region of an EPS8L3 gene promoter from a sample of a patient suffering from 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.

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 HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 from the patient sample ; 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 the methylation level of a CpG region of an HSPA2 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 the step of measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 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 the methylation level of a CpG region of a SYNPO 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 EPS8L3, HSPA2, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 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 a CpG region of a ZNF93 gene promoter, comprising: measuring the methylation level of a CpG region of a ZNF93 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 the step of measuring the methylation level of the CpG region of at least one gene promoter selected from the group consisting of EPS8L3, HSPA2, SYNPO, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 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 the level of methylation of a CpG region of an ADD2 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 EPS8L3, HSPA2, SYNPO, ZNF93, H1F0, LRRC8B, SHC3 and ZFP37 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 a CpG gene, comprising: measuring the methylation level of CpG region of H1F0 gene promoter from a sample of 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 EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, LRRC8B, SHC3 and ZFP37 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 level of methylation of a CpG region of an LRRC8B 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 EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, SHC3 and ZFP37 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 a CpG region of a SHC3 gene promoter, comprising: measuring the methylation level of a CpG region of a SHC3 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 EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B and ZFP37 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 ZFP37 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 EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B and SHC3 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 sample, a cell, a whole blood, a serum, a plasma, a blood sample, or the like which have different methylation levels of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and / Saliva, sputum 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, the specific CpG region of the EPS8L3, HSPA2, SYNPO and ZNF93 gene promoters in the patient sample is measured in a low methylation state or the specific CpG region of the ADD2, H1F0, LRRC8B, SHC3 and ZFP37 gene promoters is hypermethylated If measured, it can be predicted that the patient will show reactivity to the anticancer agent.

Therefore, according to the present invention, the methylation of CpG in the EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and / or ZFP37 gene promoters can be effectively confirmed, have.

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) Sensitive and anti-cancerous (Resistant), and a cell lineage with an intermediate resistance level between the sensitive cell line and the resistant cell line, in order from the IC ₅₀ in response to the cisplatin anticancer drug, ), Respectively.
FIG. 3 shows the results of confirming the expression of EPS8L3 gene after treatment with 5-aza-2'-deoxycytidine in ovarian cancer cell lines.
FIG. 4 shows the results of confirming the expression of the HSPA2 gene after treatment with 5-aza-2'-deoxycytidine in ovarian cancer cell lines.
FIG. 5 shows the results of confirming the expression of SYNPO gene after treatment of 5-aza-2'-deoxycytidine with ovarian cancer cell lines.
FIG. 6 shows the results of confirming the expression of ZNF93 gene after treatment of 5-aza-2'-deoxycytidine in ovarian cancer cell lines.
FIG. 7 shows the results of confirming the expression of ADD2 gene after treatment of 5-aza-2'-deoxycytidine in ovarian cancer cell lines.
FIG. 8 shows the results of examining the expression of H1F0 gene after 5-aza-2'-deoxycytidine was treated in ovarian cancer cell lines.
FIG. 9 shows the results of confirming the expression of LRRC8B gene after treatment of 5-aza-2'-deoxycytidine with ovarian cancer cell lines.
FIG. 10 shows the results of confirming the expression of SHC3 gene after treatment of 5-aza-2'-deoxycytidine in ovarian cancer cell lines.
FIG. 11 shows the results of confirming the expression of ZFP37 gene after 5-aza-2'-deoxycytidine treatment in ovarian cancer cell line.

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

Cell line Cell-derived / related diseases morphology badge Badge availability SKOV-3 Derived from human / adenocarcinoma / metastatic state epithelial McCoy's 5a + 10% FBS + 1% P / S (REF) 16600-082 (Gibco) ES-2 Human / carcinoma fibroblast McCoy's 5a + 10% FBS + 1% P / S (REF) 16600-082 (Gibco) PA-1 Human / teratocarcinoma epithelial MEM alpha + 10% FBS + 1% P / S 41061-029 (Gibco) Caov-3 Human / adenocarcinoma epithelial DMEM (1.5 g / L sodium bicarbonate) + 10% FBS + 1% P / S LM001-51 (welgene) 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) 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) 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) OVCAR-3 Human / adenocarcinoma epithelial RPMI 1640 (25 mM HEPES) + 10% FBS + 1% P / S LM011-03 (welgene) MDAH 2774 Human / adenocarcinoma mucinous RPMI 1640 (25 mM HEPES) + 10% FBS + 1% P / S LM011-03 (welgene) A2780 (parent) Human / carcinoma epithelial RPMI 1640 (25 mM HEPES) + 10% FBS + 1% P / S LM011-03 (welgene) 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 / ㎖ stabilized in density frequency division by _{37 ℃, 95% 0 2/} 5% CO 2 culture per 100 ㎕ tank to the cells for 16 ~ 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. Having a medium resistance level between the cell lines of 11 cisplatin group and listed in sequence according to the IC ₅₀ in response to an anticancer agent which has the sensitive group (Sensitive) and resistance to anticancer agents (Resistant), and sensitive cell master, and the resistant cells lord And divided into cell groups (Intermediate).

Example  3. Total RNA and 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 state 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. Expression of EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 genes was corrected by the ΔΔCT method with GAPDH expression level. The oligonucleotide primer sequences used are as follows (Table 2).

primer order SEQ ID NO: human EPS8L3 (forward) 5'-TCTTACCGCCTAGACAGCATC -3 ' 28 Human EPS8L3 (reverse) 5'-GGCTGGTCTTCAGTCGCTC -3 ' 29 human HSPA2 (forward) 5'-GGTCCCGGCCTATTTCAACG -3 ' 30 Human HSPA2 (reverse) 5'-GGACACGTCGAAAGTGCCA -3 ' 31 human SYNPO (forward) 5'-ATGGAGGGGTACTCAGAGGAG -3 ' 32 human SYNPO (reverse) 5'-CTCTCGGTTTTGGGACAGGTG -3 ' 33 human ZNF93 (forward) 5'-GCCAAAACATGCCCTAGTGT-3 ' 34 human ZNF93 (reverse) 5'-TCCACCTTTAGCTGGCTTGT -3 ' 35 human ADD2 (forward) 5'-CCATGATGACGCCTATCAATGA-3 ' 36 human ADD2 (reverse) 5'-GTCCAGGAGTCGGTAGACAC-3 ' 37 human H1F0 (forward) 5'-ACTCGCAGATCAAGTTGTCCA -3 ' 38 human H1F0 (reverse) 5'-GGTTCGTCGCTCTTGGCTA -3 ' 39 human LRRC8B (forward) 5'-TTTATGCTCAACGGTCTTCCAG-3 ' 40 human LRRC8B (reverse) 5'-GGTCTACGACCAGAGATGAATGG -3 ' 41 human SHC3 (forward) 5'-AACCTCCAGTTTGCGGGAATG -3 ' 42 human SHC3 (reverse) 5'-GTGGTGATTCGCTATGATCTGTT -3 ' 43 human ZFP37 (forward) 5'-GGCGTCCAGATTCTGACAAAG -3 ' 44 human ZFP37 (reverse) 5'-GCTCGGACACAGCCATCTC -3 ' 45 human GAPDH (forward) 5'-AATCCCATCACCATCTTCCA-3 ' 46 human GAPDH (reverse) 5'-TGGACTCCACGACGTACTCA-3 ' 47

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

HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37 gene expression were measured after treatment of each ovarian cancer cell line with 5-aza-2'-deoxycytidine (Sigma-Aldrich) Changes 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. 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 gene expression level was 1 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-OV- group and listed in accordance with the IC ₅₀ turn in response to having a sensitive group (sensitive) and resistance to anticancer agents (resistant), and sensitive cell division by master, and the resistant cells lord cell master, (intermediate) having a degree of intermediate resistance between The results are shown in Fig.

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 EPS8L3, HSPA2, SYNPO, and ZNF93 genes, gene expression was increased in the resistant cell line compared to the cisplatin-sensitive ovarian cancer cell line. In the case of ADD2, H1F0, LRRC8B, SHC3 and ZFP37 genes, there was. In addition, the result, EPS8L3, SYNPO, SHC3 gene in ovarian cancer cell lines of 11 examined the significance of the IC ₅₀ value and the gene expression of the cisplatin chemotherapy is showed significance at the Spearman correlation ZNF93, LRRC8B gene beam significance in Pearson correlation , And HSPA2, ADD2, H1F0, and ZFP37 genes were significant in both Pearson and Spearman correlations.

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 EPS8L3 1.16 0.041 0.48 0.134 0.67 0.028 7.87 2.63 HSPA2 2.56 0.039 0.63 0.037 0.65 0.037 8.62 5.03 SYNPO 0.75 0.036 0.59 0.056 0.63 0.044 8.35 1.80 ZNF93 1.25 0.047 0.61 0.046 0.59 0.061 6.66 3.19 ADD2 -1.90 0.028 -0.72 0.012 -0.76 0.009 8.17 4.09 H1F0 -2.54 0.000 -0.85 0.001 -0.79 0.006 11.43 3.43 LRRC8B -1.43 0.018 -0.62 0.043 -0.46 0.154 8.80 2.85 SHC3 -1.11 0.057 -0.57 0.067 -0.67 0.028 7.81 2.35 ZFP37 -1.68 0.007 -0.60 0.049 -0.62 0.048 7.41 3.29

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 EPS8L3, HSPA2, SYNPO and ZNF93 genes, the DNA methylation of the promoter CpG region was decreased in the anticancer-resistant ovarian cancer cell line. In the case of ADD2, H1F0, LRRC8B, SHC3 and ZFP37 genes, DNA of the promoter CpG region Methylation increased. In addition, IC ₅₀ values for cisplatin chemotherapy in ovarian cancer cell lines of 11 and a promoter, the significance of the change degree of CpG methylation examined results, EPS8L3, SYNPO, ZNF93, ADD2 , LRRC8B and SHC3 gene in both Pearson correlation and Spearman correlation ZFP37 gene was significant in Spearman correlation, and HSPA2 and H1F0 genes were significant in Pearson correlation or Spearman correlation.

gene  symbol Methylation  Chip ID Resistant vs  Sensitive Pearson  Correlation Spearman  correlation Range of  methylanthone ^One) difference in  β value p value Pearson rho p value Spearman rho p value EPS8L3 cg00515905 -0.54 0.000 -0.62 0.048 -0.71 0.014 0.82 HSPA2 cg00880494 -0.50 0.070 -0.63 0.044 -0.60 0.049 0.80 cg01141043 -0.51 0.053 -0.64 0.040 -0.63 0.036 0.81 cg01786715 -0.53 0.036 -0.68 0.025 -0.68 0.021 0.82 cg08161617 -0.59 0.042 -0.47 0.146 -0.66 0.028 0.87 cg08317373 -0.52 0.046 -0.40 0.225 -0.64 0.033 0.77 cg14057961 -0.52 0.038 -0.49 0.129 -0.66 0.028 0.75 cg14060296 -0.61 0.068 -0.64 0.040 -0.61 0.045 0.96 cg15802091 -0.51 0.000 -0.48 0.137 -0.67 0.025 0.72 cg16319578 -0.29 0.060 -0.75 0.012 -0.66 0.028 0.61 cg22947154 -0.52 0.059 -0.73 0.015 -0.63 0.037 0.85 cg24642523 -0.40 0.000 -0.44 0.183 -0.64 0.034 0.57 cg25581090 -0.27 0.000 -0.56 0.076 -0.72 0.012 0.42 SYNPO cg13590277 -0.30 0.009 -0.85 0.002 -0.79 0.004 0.60 ZNF93 cg05661139 -0.64 0.022 -0.66 0.031 -0.69 0.019 0.87 ADD2 cg22370480 0.29 0.036 0.74 0.013 0.65 0.032 0.59 H1F0 cg01443426 0.73 0.000 0.83 0.003 0.83 0.002 0.83 cg01883777 0.78 0.002 0.71 0.019 0.75 0.007 0.89 cg07141002 0.74 0.011 0.66 0.044 0.69 0.029 0.86 cg10999992 0.39 0.030 0.79 0.006 0.74 0.010 0.81 cg14910534 0.36 0.001 0.74 0.013 0.82 0.002 0.47 cg24292323 0.37 0.001 0.46 0.154 0.61 0.048 0.55 cg25043629 0.34 0.001 0.66 0.031 0.76 0.006 0.44 cg27424226 0.34 0.009 0.65 0.037 0.56 0.075 0.62 LRRC8B cg08128789 0.29 0.035 0.76 0.009 0.69 0.018 0.52 SHC3 cg26493353 0.35 0.039 0.66 0.031 0.67 0.023 0.76 ZFP37 cg14633455 0.36 0.009 0.39 0.237 0.61 0.046 0.55

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 EPS8L3 GGTGCCAGTGAAGGCCGGGTGCCTGGTCCCCCCAGGAGGCTGGTCTTGGAGCAGGTGGTC [CG] GTGCTGGTGGTGGAAGGACAGCAGCTTCTCTGCTAGTGGCCACAGGCAGAGCCTGCCTTT (SEQ ID NO: 1) ch1: 109763825-
109763946 HSPA2 TTATTTCTTCGGTGCAACCAACTCAGAATGAATTCCTCCGCCCCTGCGTGCTCAGTGAGT [CG] GCACCCTAGCAGTGAACTGCATTTAAAACCTCAGGAATTGAGCGAACTCTCCCAGTGGCT (SEQ ID NO: 2) ch14: 64540187-
64540308 TAAAACCTCAGGAATTGAGCGAACTCTCCCAGTGGCTCTCCTCACCGGGATCCCCTTCCA [CG] CCTCCTCCCCGTGCCGCGCCTCAGTCCGCACTGCTCATTGGCCGCGTGCCCTGCCAATCC (SEQ ID NO: 3) ch14: 64540272-
64540393 TGTGAGGGCGGTCCCGGGAGCGGATTGGGTCTGGGAGTTCCCAGAGGCGGCTATAAGAAC [CG] GGAACTGGGCGCGGGGAGCTGAGTTGCTGGTAGTGCCCGTGGTGCTTGGTTCGAGGTGGC (SEQ ID NO: 4) ch14: 64540659-
64540780 GAGCGCTCACAACCACTGAGACGCAGTGAAGCACCCACCATAAAATCCCAGGAGGCCGAC [CG] CCGGTTCAGACTTTTTCTTTTCTTTAATCCCCGTCCAAGGGATCCGCCCTCACCCCCCAC (SEQ ID NO: 5) ch14: 64539999-
64540120 GGGAAAACAAGCTGCTCGAGCTTTATTTCTTCGGTGCAACCAACTCAGAATGAATTCCTC [CG] CCCCTGCGTGCTCAGTGAGTCGGCACCCTAGCAGTGAACTGCATTTAAAACCTCAGGAAT (SEQ ID NO: 6) ch14: 64540165-
64540286 CGTGTCTCCTGGCGGGGGCCGGAGTCCCGCCCCTCGTCCAACTTGAAATCTGTTGGGTCA [CG] GGCCAGTCACTCCGACCTAGGCAAGCCTGTGGTGGAGCTGGAAGAGTTTGTGAGGGCGGT (SEQ ID NO: 7) ch14: 64540549-
64540670 GGGATCCCCTTCCACGCCTCCTCCCCGTGCCGCGCCTCAGTCCGCACTGCTCATTGGCCG [CG] TGCCCTGCCAATCCGATGCACGTCGGCTAGGGCAAAGACCGCGAAAAAGCGCGTACACCT (SEQ ID NO: 8) ch14: 64540318-
64540439 ACCGCCGCCGACAAGAGCACCGGTAAGGAAAACAAAATCACCATCACCAATGACAAAGGT [CG] TCTGAGCAAGGACGACATTGACCGGATGGTGCAGGAGGCGGAGCGGTACAAATCGGAAGA (SEQ ID NO: 9) ch14: 64542323-
64542444 GGGAGCTGAGTTGCTGGTAGTGCCCGTGGTGCTTGGTTCGAGGTGGCCGTTAGTTGACTC [CG] CGGAGTTCATCTCCCTGGTTTTCCCGTCCTAACGTCGCTCGCCTTTCAGTCAGGATGTCT (SEQ ID NO: 10) ch14: 64540734-
64540855 CCCAGGAGGCCGACCGCCGGTTCAGACTTTTTCTTTTCTTTAATCCCCGTCCAAGGGATC [CG] CCCTCACCCCCCACCCCAGCCACCCCAATTCCCTATTCCCTCCCCTTGGACGGCGCCGGG (SEQ ID NO: 11) ch14: 64540045-
64540166 GTCCTATACCTACAACATCAAGCAGACGGTGGAAGACGAGAAACTGAGGGGCAAGATTAG [CG] AGCAGGACAAAAACAAGATCCTCGACAAGTGTCAGGAGGTGATCAACTGGCTCGACCGAA (SEQ ID NO: 12) ch14: 64542487-
64542608 AAAAGTTCCAAAGTTTGTTTTTTAAAAACATTATTCGAGGTTTCTCTTTAATGCATTTTG [CG] TGTTTGCTGACTTGAGCATTTTTGATTAGTTCGTGCATGGAGATTTGTTTGAGATGAGAA (SEQ ID NO: 13) ch14: 64542929-
64543050 SYNPO AATAGGGCCCAGACCCTCATTGCTACAAAGCAAAACACTGGGAGGGGGCAGCATGGCCCA [CG] TGACTGGCCCTGCACTGGGCATTAGGCCAACCTGGGCTTGAATTTCAGCTCTTCCTCTGG (SEQ ID NO: 14) Ch5: 150639874-
150639995 ZNF93 TAAGAATTATCCAATCAGGGACGCTGGCTGGAAACGTCCAATCAGGCAAGCAGCCGGAC [CG] AACAGGGCGGCTTCTGGTTTGGCGGGTCCTTTGTCTCTCGGTGCAGCCGGAGCTCCAGGT (SEQ ID NO: 15) Ch19: 19900852-
19900973 ADD2 CAGACCCCCCTAGCCAGGCTTCCAGCCCCCTTCCACCCCCGCCCCGCACCACTCACTACC [CG] GGATGGCCAGAGCTAAGCAGGGGAGTCTGTTACTAGGGAGAAAATCTGAAACAGAGCTCC (SEQ ID NO: 16) Ch2: 70768415-
70768536 H1F0 CGGACCAGACAGGCCACCATGACCGAGAATTCCACGTCCGCCCCTGCGGCCAAGCCCAAG [CG] GGCCAAGGCCTCCAAGAAGTCCACAGACCACCCCAAGTATTCAGACATGATCGTGGCTGC (SEQ ID NO: 17) Ch22: 37805527-
37805648 TGTCCTCAAGCAGACCAAAGGGGTGGGGGCCTCGGGGTCCTTCCGGCTAGCCAAGAGCGA [CG] AACCCAAGAAGTCAGTGGCCTTCAAGAAGACCAAGAAGGAAATCAAGAAGGTAGCCACGC (SEQ ID NO: 18) Ch22: 37805781-
37805902 AAGTATTCAGACATGATCGTGGCTGCCATCCAGGCCGAGAAGAACCGCGCTGGCTCCTCG [CG] CCAGTCCATTCAGAAGTATATCAAGAGCCACTACAAGGTGGGTGAGAACGCTGACTCGCA (SEQ ID NO: 19) Ch22: 37805623-
37805744 GCGCCCCGCTTTCCCAAGTCCCCAAAGCACTCAGGGCCTCTCCTCATTACAGGGGCCCCC [CG] GACCGTCCCTGGTTAGAGCTTCTGGGGCAGCTTCTCCATTGTGGACCGCCCTCCCCCGCC (SEQ ID NO: 20) Ch22: 37804154-
37804275 AGACTGGCCCGGTAGTCAGGGGCTCAGGAGCAGATCCCGAGGCAGGCTTTGCTCAGCCTC [CG] ACGAGGGCTGGCCCTTTGGAAGGCGCCTTCAACAGCCGGACCAGACAGGCCACCATGACC (SEQ ID NO: 21) Ch22: 37805429-
37805550 AGGCCCGGGCCGGGGGGAAAGGTCGGATTTGCTCGGCGGAAGAAACACAGATGGCGGCGG [CG] CAGCGCCATTCCGGGCCGGGAGCAGGCAGCCAGCAGCCCTGTCCTCACCGCGGTCCGCCC (SEQ ID NO: 22) Ch22: 37805070-
37805191 GGAGAGAGGTGGTAGGGAGCAGCCAGCCGGCAAAGGAAGGAGGGGGAAAAAAACCGCCAC [CG] GGCTGACTTCCACCTCCCAGTGGTGAGCAGTGGGGGCCCAAACCCAGTTTCCTTCTCATT (SEQ ID NO: 23) Ch22: 37806592-
37806713 CGGGCCGGGGGGAAAGGTCGGTTTGCTCGGCGGAAGAAACACAGATGGCGGCGGCGCAG [CG] CCATTCCGGGCCGGGAGCAGGCAGCCAGCAGCCCTGTCCTCACCGCGGTCCGCCCGCCGC (SEQ ID NO: 24) Ch22: 37805075-
37805196 LRRC8B & Lt ; / RTI & Ch1: 89524306-
89524427 SHC3 GGGGCTGCTCACAGCAAAAGCATGACTCACTCTGAGAGGAGACCCTTCTCAACAAAGGCT [CG] GTGAGCACTGCAAATCACTTCCTGTAGCAGAAGAAAAAAAAGGAAAAAAAAAAAAAAAA (SEQ ID NO: 26) Ch9: 89178746-
89178867 ZFP37 ACAATTAGATCGGGAGGTGGAAGCTGGCGAGGGCGTTACTTGCAGGATGCAGGAGTGATG [CG] ATCAGAGCCAGCCGGAACCGAGTTCCGTTACGCACTACAGGACTGACCTGGGCCTGACAA (SEQ ID NO: 27) Ch9: 113056818-
113056939

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, (HSPA2, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37) were selected as anticancer drug response predictive markers.

EPS8L3 the anticancer sensitive cells was the gene expression in the resistant cell master, with respect to the master, is that methylation at the 2.2-fold increase, 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 change in the promoter CpG region of the EPS8L3 gene was selected as an anticancer drug response prediction marker.

HSPA2 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 5.9 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 change in the promoter CpG region of the HSPA2 gene was selected as the anticipation marker for the anticancer drug response because the degree of DNA methylation change in the HSPA2 gene was significant in Pearson correlation or Spearman correlation.

SYNPO was down-regulated in the promoter CpG region with a 1.7-fold increase in gene expression in the resistant cell line to the anticancer-sensitive cell line. In the 11 ovarian cancer cell lines, the IC ₅₀ value and the gene expression and promoter CpG , The DNA methylation changes in the promoter CpG region of the SYNPO gene were selected as anticipatory marker for anticancer therapy.

ZNF93 was hypomethylated in the promoter CpG region at the same time that the gene expression was increased 2.4 times in the resistant cell line to the anticancer drug sensitive cell line. In the 11 ovarian cancer cell lines, IC ₅₀ value, gene expression and promoter CpG The DNA methylation change in the promoter CpG region of the ZNF93 gene was selected as an anticancer drug response prediction marker since the degree of DNA methylation change in the ZNF93 gene was significant in the Pearson correlation.

ADD2 was highly methylated at the promoter CpG site while the gene expression was decreased 3.7 fold in the resistant cell line to the anticancer drug sensitive cell line. In the 11 ovarian cancer cell lines, the IC ₅₀ value and the gene expression and promoter CpG The DNA methylation changes in the promoter CpG region of the ADD2 gene were selected as predictors of response to anticancer therapy because the degree of DNA methylation change in the CpG region of the ADD2 gene was significant in Pearson correlation and Spearman correlation.

H1F0 the anticancer sensitive cells was the gene expression in the resistant cell master, with respect to the master, the high methylation in 5.8-fold reduction, 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 change in the promoter CpG region of the H1F0 gene was selected as the anticipation marker for the anticancer drug response, since the degree of DNA methylation change in the H1F0 gene was significant in Pearson correlation or Spearman correlation.

LRRC8B was found to be highly methylated in the promoter CpG region while 2.7 times decrease in gene expression in the resistant cell line to the anticancer drug sensitive cell line. 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 LRRC8B gene was selected as the predictive marker for anticancer drug response.

SHC3 was highly methylated in the promoter CpG region at the same time that the gene expression was reduced 2.2 fold in the resistant cell line to the anticancer sensitive cell line and the IC ₅₀ value and the gene expression and the promoter CpG for the cisplatin anticancer drug in 11 ovarian cancer cell lines The DNA methylation change in the promoter CpG region of the SHC3 gene was selected as the predictive marker for anticancer drug response.

ZFP37 was highly methylated in the promoter CpG region at the same time that the gene expression was reduced 3.2 fold in the resistant cell line to the anticancer drug sensitive cell line. 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 ZFP37 gene was selected as a predictive marker for anticancer drug response.

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

Each of the ovarian cancer cell lines was treated with 5-aza-2'-deoxycytidine, a DNA methylation agent, for 3 days, and then 9 selected genes (EPS8L3, HSPA2, SYNPO, ZNF93, ADD2, H1F0, LRRC8B, SHC3 and ZFP37) And the expression of these genes was found to be increased. This means that expression of the above genes is regulated by DNA methylation (Figs. 3 to 11).

The results of these experiments show that nine genes expressing significant expression changes in anticancer drug resistant ovarian cancer cell lines are regulated by hypomethylation or hypermethylation of specific CpG sites in the promoter region of each gene, It can be used as a marker.

<110> Ewha University - Industry Collaboration Foundation <120> Gene related to anti-cancer drug resistance and use thereof <130> DPP20154335KR <160> 47 <170> Kopatentin 1.71 <210> 1 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch1: 109763825- 109763946 <400> 1 ggtgccagtg aaggccgggt gcctggtccc cccaggaggc tggtcttgga gcaggtggtc 60 cggtgctggt ggtggaagga cagcagcttc tctgctagtg gccacaggca gagcctgcct 120 tt 122 <210> 2 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540187- 64540308 <400> 2 ttatttcttc ggtgcaacca actcagaatg aattcctccg cccctgcgtg ctcagtgagt 60 cggcacccta gcagtgaact gcatttaaaa cctcaggaat tgagcgaact ctcccagtgg 120 ct 122 <210> 3 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540272- 64540393 <400> 3 taaaacctca ggaattgagc gaactctccc agtggctctc ctcaccggga tccccttcca 60 cgcctcctcc ccgtgccgcg cctcagtccg cactgctcat tggccgcgtg ccctgccaat 120 cc 122 <210> 4 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540659- 64540780 <400> 4 tgtgagggcg gtcccgggag cggattgggt ctgggagttc ccagaggcgg ctataagaac 60 cgggaactgg gcgcggggag ctgagttgct ggtagtgccc gtggtgcttg gttcgaggtg 120 gc 122 <210> 5 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64539999- 64540120 <400> 5 gagcgctcac aaccactgag acgcagtgaa gcacccacca taaaatccca ggaggccgac 60 cgccggttc gctttttct tttctttaat ccccgtccaa gggatccgcc ctcacccccc 120 ac 122 <210> 6 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540165- 64540286 <400> 6 gggaaaacaa gctgctcgag ctttatttct tcggtgcaac caactcagaa tgaattcctc 60 cgcccctgcg tgctcagtga gtcggcaccc tagcagtgaa ctgcatttaa aacctcagga 120 at 122 <210> 7 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540549- 64540670 <400> 7 tctgtctcct ggcgggggcc ggagtcccgc ccctcgtcca acttgaaatc tgttgggtca 60 cgggccagtc actccgacct aggcaagcct gtggtggagc tggaagagtt tgtgagggcg 120 gt 122 <210> 8 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540318- 64540439 <400> 8 gggatcccct tccacgcctc ctccccgtgc cgcgcctcag tccgcactgc tcattggccg 60 cgtgccctgc caatccgatg cacgtcggct agggcaaaga ccgcgaaaaa gcgcgtacac 120 ct 122 <210> 9 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64542323- 64542444 <400> 9 accgccgccg acaagagcac cggtaaggaa aacaaaatca ccatcaccaa tgacaaaggt 60 cgtctgagca aggacgacat tgaccggatg gtgcaggagg cggagcggta caaatcggaa 120 ga 122 <210> 10 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540734- 64540855 <400> 10 gggagctgag ttgctggtag tgcccgtggt gcttggttcg aggtggccgt tagttgactc 60 cgcggagttc atctccctgg ttttcccgtc ctaacgtcgc tcgcctttca gtcaggatgt 120 ct 122 <210> 11 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64540045- 64540166 <400> 11 cccaggaggc cgaccgccgg ttcagacttt ttcttttctt taatccccgt ccaagggatc 60 cgccctcacc ccccacccca gccaccccaa ttccctattc cctccccttg gacggcgccg 120 gg 122 <210> 12 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64542487- 64542608 <400> 12 gtcctatacc tacaacatca agcagacggt ggaagacgag aaactgaggg gcaagattag 60 cgagcaggac aaaaacaaga tcctcgacaa gtgtcaggag gtgatcaact ggctcgaccg 120 aa 122 <210> 13 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch14: 64542929- 64543050 <400> 13 aaaagttcca aagtttgttt tttaaaaaca ttattcgagg tttctcttta atgcattttg 60 cgtgtttgct gacttgagca tttttgatta gttcgtgcat ggagatttgt ttgagatgag 120 aa 122 <210> 14 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch5: 150639874- 150639995 <400> 14 aatagggccc agaccctcat tgctacaaag caaaacactg ggagggggca gcatggccca 60 cgtgactggc cctgcactgg gcattaggcc aacctgggct tgaatttcag ctcttcctct 120 gg 122 <210> 15 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch19: 19900852-19900973 <400> 15 taagaattat ccaatcaggg acgctgggct ggaaacgtcc aatcaggcaa gcagccggac 60 cgaacagggc ggcttctggt ttggcgggtc ctttgtctct cggtgcagcc ggagctccag 120 gt 122 <210> 16 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch2: 70768415- 70768536 <400> 16 cagacccccc tagccaggct tccagccccc ttccaccccc gccccgcacc actcactacc 60 cgggatggcc agagctaagc aggggagtct gttactaggg agaaaatctg aaacagagct 120 cc 122 <210> 17 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37805527-37805648 <400> 17 cggaccagac aggccaccat gaccgagaat tccacgtccg cccctgcggc caagcccaag 60 cgggccaagg cctccaagaa gtccacagac caccccaagt attcagacat gatcgtggct 120 gc 122 <210> 18 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37805781-37805902 <400> 18 tgtcctcaag cagaccaaag gggtgggggc ctcggggtcc ttccggctag ccaagagcga 60 cgaacccaag aagtcagtgg ccttcaagaa gaccaagaag gaaatcaaga aggtagccac 120 gc 122 <210> 19 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37805623- 37805744 <400> 19 aagtattcag acatgatcgt ggctgccatc caggccgaga agaaccgcgc tggctcctcg 60 cgccagtcca ttcagaagta tatcaagagc cactacaagg tgggtgagaa cgctgactcg 120 ca 122 <210> 20 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37804154- 37804275 <400> 20 gcgccccgct ttcccaagtc cccaaagcac tcagggcctc tcctcattac aggggccccc 60 cggaccgtcc ctggttagag cttctggggc agcttctcca ttgtggaccg ccctcccccg 120 cc 122 <210> 21 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37805429- 37805550 <400> 21 agactggccc ggtagtcagg ggctcaggag cagatcccga ggcaggcttt gctcagcctc 60 cgacgagggc tggccctttg gaaggcgcct tcaacagccg gaccagacag gccaccatga 120 cc 122 <210> 22 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37805070- 37805191 <400> 22 aggcccgggc cggggggaaa ggtcggattt gctcggcgga agaaacacag atggcggcgg 60 cgcagcgcca ttccgggccg ggagcaggca gccagcagcc ctgtcctcac cgcggtccgc 120 cc 122 <210> 23 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37806592-37806713 <400> 23 ggagagaggt ggtagggagc agccagccgg caaaggaagg agggggaaaa aaaccgccac 60 cgggctgact tccacctccc agtggtgagc agtgggggcc caaacccagt ttccttctca 120 tt 122 <210> 24 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch22: 37805075-37805196 <400> 24 cgggccgggg ggaaaggtcg gatttgctcg gcggaagaaa cacagatggc ggcggcgcag 60 cgccattccg ggccgggagc aggcagccag cagccctgtc ctcaccgcgg tccgcccgcc 120 gc 122 <210> 25 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch1: 89524306-89524427 <400> 25 cgttatataa atgccaagtt actcagggac gcacacgtga gaaggctggg gcccgacaca 60 cgcggtgtag tgccgaagtc accggtgtgg cgcgcctggg ggacacgccg aagcccattt 120 cc 122 <210> 26 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch9: 89178746- 89178867 <400> 26 ggggctgctc acagcaaaag catgactcac tctgagagga gacccttctc aacaaaggct 60 cggtgagcac tgcaaatcac ttcctgtagc agaagaaaaa aaaggaaaaa aagaagaaaa 120 aa 122 <210> 27 <211> 122 <212> DNA <213> Homo sapiens <220> <221> promoter &Lt; 222 > (1) .. (122) <223> ch9: 113056818- 113056939 <400> 27 acaattagat cgggaggtgg aagctggcga gggcgttact tgcaggatgc aggagtgatg 60 cgatcagagc cagccggaac cgagttccgt tacgcactac aggactgacc tgggcctgac 120 aa 122 <210> 28 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> human EPS8L3 (forward) <400> 28 tcttaccgcc tagacagcat c 21 <210> 29 <211> 19 <212> DNA <213> Artificial Sequence <220> <223> Human EPS8L3 (reverse) <400> 29 ggctggtctt cagtcgctc 19 <210> 30 <211> 20 <212> DNA <213> Artificial Sequence <220> Human HSPA2 (forward) <400> 30 ggtcccggcc tatttcaacg 20 <210> 31 <211> 19 <212> DNA <213> Artificial Sequence <220> <223> Human HSPA2 (reverse) <400> 31 ggacacgtcg aaagtgcca 19 <210> 32 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> human SYNPO (forward) <400> 32 atggaggggt actcagagga g 21 <210> 33 <211> 21 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > human SYNPO (reverse) <400> 33 ctctcggttt tgggacaggt g 21 <210> 34 <211> 20 <212> DNA <213> Artificial Sequence <220> <223> human ZNF93 (forward) <400> 34 gccaaaacat gccctagtgt 20 <210> 35 <211> 20 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > human ZNF93 (reverse) <400> 35 tccaccttta gctggcttgt 20 <210> 36 <211> 22 <212> DNA <213> Artificial Sequence <220> <223> human ADD2 (forward) <400> 36 ccatgatgac gcctatcaat ga 22 <210> 37 <211> 20 <212> DNA <213> Artificial Sequence <220> <223> human ADD2 (reverse) <400> 37 gtccaggagt cggtagacac 20 <210> 38 <211> 21 <212> DNA <213> Artificial Sequence <220> Human H1F0 (forward) <400> 38 actcgcagat caagttgtcc a 21 <210> 39 <211> 19 <212> DNA <213> Artificial Sequence <220> Human H1F0 (reverse) <400> 39 ggttcgtcgc tcttggcta 19 <210> 40 <211> 22 <212> DNA <213> Artificial Sequence <220> Human LRRC8B (forward) <400> 40 tttatgctca acggtcttcc ag 22 <210> 41 <211> 23 <212> DNA <213> Artificial Sequence <220> Human LRRC8B (reverse) <400> 41 ggtctacgac cagagatgaa tgg 23 <210> 42 <211> 21 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > human SHC3 (forward) <400> 42 aacctccagt ttgcgggaat g 21 <210> 43 <211> 23 <212> DNA <213> Artificial Sequence <220> Human SHC3 (reverse) <400> 43 gtggtgattc gctatgatct gtt 23 <210> 44 <211> 21 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > human ZFP37 (forward) <400> 44 ggcgtccaga ttctgacaaa g 21 <210> 45 <211> 19 <212> DNA <213> Artificial Sequence <220> Human ZFP37 (reverse) <400> 45 gctcggacac agccatctc 19 <210> 46 <211> 20 <212> DNA <213> Artificial Sequence <220> <223> human GAPDH (forward) <400> 46 aatcccatca ccatcttcca 20 <210> 47 <211> 20 <212> DNA <213> Artificial Sequence <220> Human GAPDH (reverse) <400> 47 tggactccac gacgtactca 20

Claims (11)

A composition for predicting responsiveness to a platinum-based anticancer agent in a patient suffering from ovarian cancer, comprising an agent for measuring the methylation level of a CpG region of a SYNPO (synaptopodin) 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 that appears in the nucleotide sequence of SEQ ID NO: 14 (150639874 to 150639995 th of chromosome 5).
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 method for detecting the methylation level of the CpG region of the SYNPO (synaptopodin) gene promoter from a patient sample in order to provide information necessary for predicting responsiveness to platinum-based anticancer drugs in ovarian cancer patients.
8. The method according to claim 7, wherein the method for detecting the methylation level of the CpG region of the gene promoter comprises:
(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 gene promoter.
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: 14 (150639874 to 150639995 th of chromosome 5).
9. The method of claim 8, 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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