Deciphering MicroRNA-mediated Regulatory Networks in Ovarian Cancer Using Omics and Systems Biology Approaches

• Main Authors: Huang, Ya-Rong, 黃雅蓉
• Other Authors: Huang, Hsien-Da
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/vx6rnd

碩士 === 國立交通大學 === 生物資訊及系統生物研究所 === 105 === Ovarian cancer ranks fifth in cancer deaths among women. It also has the highest mortality rate among all gynecologic cancers, mainly because most patients are diagnosed at late stage and the development of drug resistance. The standard treatment of ovarian cancer is the combination of debulking surgery and platinum-based chemotherapy. However, drug resistance exists and leads to recurrence of tumors and poor prognosis of patients. Previous studies have confirmed that microRNAs, genes and DNA methylation play important roles in cancer. Several mechanisms have been demonstrated to affect chemotherapy response, but the exact mechanisms are not fully investigated. This research aims to identify the relation between microRNAs, genes, DNA methylation and chemotherapy response. In order to clarify the exact mechanism affected chemotherapy response, we attempted to construct the microRNA and target-gene interaction network and epigenetic regulatory network in ovarian cancer by using The Cancer Genome Atlas (TCGA) data. We identified 19 significantly differentially expressed miRNAs and 21 hypermethylated genes between two groups of patients with different chemotherapy response. We also constructed the miRNA and target gene interaction network which included 8 miRNAs and 12 genes. One miRNA (miR-363-3p) and 41 genes were associated with overall survival. Two miRNAs (miR-181a-5p and miR-30e-5p) and 21 genes were associated with disease-free survival. We expect to apply this computational method to the other types of human cancer. This study provides a novel prognostic biomarker for ovarian cancer patients and our findings may identify patients who will fail to chemotherapy.