文献类型：会议论文

英文题名：Differential networking meta-analysis of gastric cancer across Asian and American racial groups

作者：Dai, Wentao[1,4,5];Li, Quanxue[1,2];Liu, Bing-Ya[3];Li, Yi-Xue[1,2,4,5,6];Li, Yuan-Yuan[1,2,4,5,6]

机构：[1]Shanghai Ctr Bioinformat Technol, 1278 Keyuan Rd, Shanghai 201203, Peoples R China;[2]East China Univ Sci & Technol, Sch Biotechnol, Shanghai 200237, Peoples R China;[3]Shanghai Jiao Tong Univ, Ruijin Hosp, Shanghai Key Lab Gastr Neoplasms, Shanghai Inst Digest Surg,Sch Med, Shanghai 200025, Peoples R China;[4]Shanghai Engn Res Ctr Pharmaceut Translat, 1278 Keyuan Rd, Shanghai 201203, Peoples R China;[5]Shanghai Ind Technol Inst, 1278 Keyuan Rd, Shanghai 201203, Peoples R China;[6]Chinese Acad Sci, Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol, Key Lab Computat Biol, Shanghai 200031, Peoples R China

会议论文集：International Conference on Systems Biology (ISB)

会议日期：AUG 18-21, 2017

会议地点：Shenzhen, PEOPLES R CHINA

语种：英文

外文关键词：Gastric carcinoma (GC); Differential networking meta-analysis; Cross-racial; Conditional gene regulatory networks (GRN); Dysfunctional regulation mechanisms

摘要：Background: Gastric Carcinoma is one of the most lethal cancer around the world, and is also the most common cancers in Eastern Asia. A lot of differentially expressed genes have been detected as being associated with Gastric Carcinoma (GC) progression, however, little is known about the underlying dysfunctional regulation mechanisms. To address this problem, we previously developed a differential networking approach that is characterized by involving differential coexpression analysis (DCEA), stage-specific gene regulatory network (GRN) modelling and differential regulation networking (DRN) analysis. Result: In order to implement differential networking meta-analysis, we developed a novel framework which integrated the following steps. Considering the complexity and diversity of gastric carcinogenesis, we first collected three datasets (GSE54129, GSE24375 and TCGA-STAD) for Chinese, Korean and American, and aimed to investigate the common dysregulation mechanisms of gastric carcinogenesis across racial groups. Then, we constructed conditional GRNs for gastric cancer corresponding to normal and carcinoma, and prioritized differentially regulated genes (DRGs) and gene links (DRLs) from three datasets separately by using our previously developed differential networking method. Based on our integrated differential regulation information from three datasets and prior knowledge (e.g., transcription factor (TF)-target regulatory relationships and known signaling pathways), we eventually generated testable hypotheses on the regulation mechanisms of two genes, XBP1 and GIF, out of 16 common cross-racial DRGs in gastric carcinogenesis. Conclusion: The current cross-racial integrative study from the viewpoint of differential regulation networking provided useful clues for understanding the common dysfunctional regulation mechanisms of gastric cancer progression and discovering new universal drug targets or biomarkers for gastric cancer.