Bioinformatic approaches to augment study of epithelial-to-mesenchymal transition in lung cancer

摘要: Bioinformatic approaches are intended to provide systems level insight into the complex biological processes that underlie serious diseases such as cancer. In this review we describe current bioinformatic resources, and illustrate how they have been used study a clinically important example: epithelial-to-mesenchymal transition (EMT) in lung Lung cancer is leading cause of cancer-related deaths often diagnosed at advanced stages, limited therapeutic success. While EMT essential during development wound healing, pathological reactivation program by cells contributes metastasis drug resistance, both major causes death from Challenges studying include its transient nature, molecular phenotypic heterogeneity, complicated networks rewired signaling cascades. Given biology role EMT, it critical better align two order advance impact precision oncology. This task relies heavily on application resources. Besides summarizing recent work area, use four EMT-associated genes, TGF-β (TGFB1), NEDD9/HEF1, β-catenin (CTNNB1) E-cadherin (CDH1), exemplars demonstrate capacities limitations probing resources inform hypothesis-driven studies with goals.