ECGene: A Literature‐Based Knowledgebase of Endometrial Cancer Genes. Issue 4 (13th January 2016)

• Record Type: Journal Article
• Authors: Zhao, Min; Liu, Yining; O'Mara, Tracy A
• Is Part Of: Human mutation. Volume 37:Issue 4(2016)
• Page Start: 337
• Page End: 343
• Publication Date: 2016-01-13
• Subjects: endometrial cancer -- database -- cancer genomics -- network analysis -- systems biology -- long noncoding RNA; Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.22950
• Languages: English
• ISSNs: 1059-7794

Abstract

Abstract : The most comprehensive computational system about endometrial cancer, ECGene, contains 458 human genes extracting from literature. We annotated the genes with extensive bioinformatics information and pre‐compute useful regulatory information such as the co‐expression pattern of mRNA and long non‐coding RNAs. This integrative systems‐based approach will help users to conduct network‐based functional analyses. Our ECGene validated "core" genes, gene networks and signaling pathways that previously had been associated with the disease and identified some new ones. ABSTRACT: Endometrial cancer (EC) ranks as the sixth common cancer for women worldwide. To better distinguish cancer subtypes and identify effective early diagnostic biomarkers, we need improved understanding of the biological mechanisms associated with EC dysregulated genes. Although there is a wealth of clinical and molecular information relevant to EC in the literature, there has been no systematic summary of EC‐implicated genes. In this study, we developed a literature‐based database ECGene (Endometrial Cancer Gene database) with comprehensive annotations. ECGene features manual curation of 414 genes from thousands of publications, results from eight EC gene expression datasets, precomputation of coexpressed long noncoding RNAs, and an EC‐implicated gene interactome. In the current release, we generated and comprehensively annotated a list of 458 EC‐implicated genes. We found the top‐ranked EC‐implicated genes are frequently mutated in The Cancer Genome Atlas (TCGA) tumor samples. Furthermore, systematic analysis of coexpressed lncRNAs provided insight into the important roles of lncRNA in EC development. ECGene has a user‐friendly Web interface and is freely available athttp://ecgene.bioinfo‐minzhao.org/ . As the first literature‐based online resource for EC, ECGene serves as a useful gateway for researchers to explore EC genetics.