title: ECGene: A Literature-Based Knowledgebase of Endometrial Cancer Genes.
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 at http://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.
authors.affiliation: School of Engineering, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Queensland, 4558, Australia.
authors.forename: Min
authors.initials: M
authors.lastname: Zhao
authors.affiliation: School of Engineering, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Queensland, 4558, Australia.
authors.forename: Yining
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.
authors.forename: Tracy A
authors.initials: TA
authors.lastname: O'Mara
mesh_terms: D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D030561:Databases, Nucleic Acid; D016889:Endometrial Neoplasms / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods; D006801:Humans; D051188:Knowledge Bases; D009154:Mutation; D009857:Oncogenes; D016366:Open Reading Frames; D062085:RNA, Long Noncoding / Q000235:genetics; D014584:User-Computer Interface; D064878:Web Browser
chemical_list: D062085:RNA, Long Noncoding
keywords: cancer genomics; database; endometrial cancer; long noncoding RNA; network analysis; systems biology