Multiscale network analysis reveals molecular mechanisms and key regulators of the tumor microenvironment in gastric cancer. Issue 5 (11th October 2019)

• Record Type: Journal Article
• Authors: Song, Won‐Min; Lin, Xiandong; Liao, Xuehong; Hu, Dan; Lin, Jieqiong; Sarpel, Umut; Ye, Yunbin; Feferman, Yael; Labow, Daniel M.; Walsh, Martin J.; Zheng, Xiongwei; Zhang, Bin
• Is Part Of: International journal of cancer. Volume 146:Issue 5(2020)
• Page Start: 1268
• Page End: 1280
• Publication Date: 2019-10-11
• Subjects: gastric cancer -- tumor microenvironment -- gene coexpression network -- network module -- key driver -- DNA methylation -- somatic mutations; Cancer -- Periodicals; Cancer -- Prevention -- Periodicals; 616.994
• DOI: 10.1002/ijc.32643
• Languages: English
• ISSNs: 0020-7136

Abstract

Abstract : Gastric cancer (GC) is the third leading cause of cancer deaths and the fourth most prevalent malignancy worldwide. The high incidence and mortality rates of gastric cancer result from multiple factors such as ineffective screening, diagnosis, and limited treatment options. In our study, we sought to systematically identify predictive molecular networks and key regulators to elucidate complex interacting signaling pathways in GC. We performed an integrative network analysis of the transcriptomic data in The Cancer Genome Atlas (TCGA) gastric cancer cohort and then comprehensively characterized the predictive subnetworks and key regulators by the matched genetic and epigenetic data. We identified 221 gene subnetworks (modules) in GC. The most prognostic subnetworks captured multiple aspects of the tumor microenvironment in GC involving interactions among stromal, epithelial and immune cells. We revealed the genetic and epigenetic underpinnings of those subnetworks and their key transcriptional regulators. We computationally predicted and experimentally validated specific mechanisms of anticancer effects of GKN2 in gastric cancer proliferation and invasion in vitro . The network models and the key regulators of the tumor microenvironment in GC identified here pave a way for developing novel therapeutic strategies for GC. Abstract : What's new? Gene signatures have been identified for diagnosis and classification of gastric cancer (GC) as well as prediction of therapeutic response. However, key molecular mechanisms underlying prognosis remain to be revealed. Our study systematically identifies and characterizes predictive molecular networks and key regulators. The most prognostic subnetworks capture multiple aspects of the tumor microenvironment in GC involving interactions among stromal, epithelial, and immune cells. The authors computationally predicted and experimentally validated specific mechanisms of anti‐cancer effects of GKN2 in GC proliferation and invasion in vitro . These network models and key regulators pave the way for developing novel therapeutic strategies for GC.