Identification of hub genes and construction of transcriptional regulatory network for the progression of colon adenocarcinoma hub genes and TF regulatory network of colon adenocarcinoma.
Journal: 2019/October - Journal of Cellular Physiology
ISSN: 1097-4652
Abstract:
The aim of this study was to identify key genes related to the progression of colon adenocarcinoma (COAD), and to investigate the regulatory network of hub genes and transcription factors (TFs). Dataset GSE20916 including 44 normal colon, 55 adenoma, and 36 adenocarcinoma tissue samples was used to construct co-expression networks via weighted gene co-expression network. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis for the objective module were performed using the online Database for Annotation, Visualization and Integrated Discovery. Hub genes were identified by taking the intersection of differentially expressed genes between dataset GSE20916 and GSE39582 and validated using The Cancer Genome Atlas (TCGA) database. The correlations between microRNA (miRNA) and hub genes were analyzed using the online website StarBase. Cytoscape was used to establish a regulatory network of TF-miRNA-target gene. We found that the orange module was a key module related to the tumor progression in COAD. In datasets GSE20916 and GSE39582, a total of eight genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) were selected, which were closely related with patients' survivals in TCGA database and dataset GSE20916. COAD patients with higher expressions of each hub gene had a worse prognosis than those with lower expressions. A regulatory network of TF-miRNA-target gene with 144 TFs, 26 miRNAs, and 7 hub genes was established, including model KLF11-miR149-BGN, TCEAL6-miR29B2-COL1A1, and TCEAL6-miR29B2-COL1A2. In conclusion, during the progression of COAD, eight core genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) play vital roles. Regulatory networks of TF-miRNA-target gene can help to understand the disease progression and optimize treatment strategy.
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