title: Differential network analysis reveals dysfunctional regulatory networks in gastric carcinogenesis.
abstract: Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing disease-related genes on the dataset we considered. We propose this extendable differential networking framework as a promising way to gain insights into gene regulatory mechanisms underlying cancer progression and other phenotypic changes.
authors.affiliation: School of Life Science and Technology, Tongji University Shanghai 200092, P. R. China ; Shanghai Center for Bioinformation Technology Shanghai 200235, P. R. China ; Shanghai Industrial Technology Institute 1278 Keyuan Road, Shanghai 201203, P. R. China.
authors.forename: Mu-Shui
authors.initials: MS
authors.lastname: Cao
authors.affiliation: Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine Shanghai 200025, P. R. China.
authors.forename: Bing-Ya
authors.initials: BY
authors.lastname: Liu
authors.affiliation: Shanghai Center for Bioinformation Technology Shanghai 200235, P. R. China ; Shanghai Industrial Technology Institute 1278 Keyuan Road, Shanghai 201203, P. R. China.
authors.forename: Wen-Tao
authors.initials: WT
authors.lastname: Dai
authors.affiliation: Shanghai Center for Bioinformation Technology Shanghai 200235, P. R. China ; Shanghai Industrial Technology Institute 1278 Keyuan Road, Shanghai 201203, P. R. China ; Shanghai Engineering Research Center of Pharmaceutical Translation 1278 Keyuan Road, Shanghai 201203, P. R. China.
authors.forename: Wei-Xin
authors.initials: WX
authors.lastname: Zhou
authors.affiliation: School of Life Science and Technology, Tongji University Shanghai 200092, P. R. China ; Shanghai Center for Bioinformation Technology Shanghai 200235, P. R. China ; Shanghai Industrial Technology Institute 1278 Keyuan Road, Shanghai 201203, P. R. China ; Shanghai Engineering Research Center of Pharmaceutical Translation 1278 Keyuan Road, Shanghai 201203, P. R. China.
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
authors.affiliation: Shanghai Center for Bioinformation Technology Shanghai 200235, P. R. China ; Shanghai Industrial Technology Institute 1278 Keyuan Road, Shanghai 201203, P. R. China ; Shanghai Engineering Research Center of Pharmaceutical Translation 1278 Keyuan Road, Shanghai 201203, P. R. China.
authors.forename: Yuan-Yuan
authors.initials: YY
authors.lastname: Li
keywords: Gastric cancer (GC); carcinogenesis; differential coexpression analysis (DCEA); differential network analysis; differentially regulated genes (DRGs); gene regulation network (GRN); gene regulatory mechanisms