초록 ▼

오믹스 데이터 통합과 네트워크 분석을 통해 난소암 혈액 바이오마커 후보군을 발굴하기 위하여 TCGA로부터 난소암에 대한 네 종류의 오믹스 데이터 (Mutation, DNA methylation, CGV, mRNA expression)를 확보하고, 통계 분석 및 네트워크 분석으로 난소암 바이오마커 후보군을 발굴하였다, 혈청에서 검증 가능한 N-glycoprotein을 선별하고 high-throughput으로 검증하기 위하여, 이들 후보군 중 약 30%를 혈청에서 검증 가능한 N-glycoprotein으로 선별하였다. 검증을 위하여 난

오믹스 데이터 통합과 네트워크 분석을 통해 난소암 혈액 바이오마커 후보군을 발굴하기 위하여 TCGA로부터 난소암에 대한 네 종류의 오믹스 데이터 (Mutation, DNA methylation, CGV, mRNA expression)를 확보하고, 통계 분석 및 네트워크 분석으로 난소암 바이오마커 후보군을 발굴하였다, 혈청에서 검증 가능한 N-glycoprotein을 선별하고 high-throughput으로 검증하기 위하여, 이들 후보군 중 약 30%를 혈청에서 검증 가능한 N-glycoprotein으로 선별하였다. 검증을 위하여 난소암 환자 40명과 비환자군 20명의 혈청 샘플을 확보하고 SWAH-MS 질량분석을 위한 N-glycoproteome enrichment를 완료하였다.

Abstract ▼

The goal of the project is network-based identification of biomarker candidates of high-grade serous ovarian cancer through integration of multi-level genomic datasets and verification of network-based biomarker candidates in serum samples. In this work, 4 different types of ovarian cancer omics dat

The goal of the project is network-based identification of biomarker candidates of high-grade serous ovarian cancer through integration of multi-level genomic datasets and verification of network-based biomarker candidates in serum samples. In this work, 4 different types of ovarian cancer omics data (Mutation, messenger RNA expression, DNA methylation and DNA copy number variation data) were obtained from TCGA. These data from large number of samples (247 patients) were integrated and re-evaluated for each gene by considering their interacting partners in protein-protein interactions. The network modules significantly enriched with integrated data were identified and proposed to biomarker candidates for high-grade serous ovarian cancers. Among them, serum N-glycoproteins were prioritized. To verify these candidates, independent serum samples were obtained from 40 ovarian cancer patients and 20 normal. N-glycoproteome of serum samples were enriched for all 60 samples. Verification of these candidates in indep endent serum samples using SWATH-MS will be conducted in Mar/2013.