Backgrounds: Colorectal cancer (CRC) is one of the most fatal cancers in the world, and itsdevelopment poses a significant therapeutic challenge. The factors involved in determining therisk of
CRC advancement must be identified to develop targeted therapy for
CRC patients.Materials and Methods: In the present study, employing by systems biology approach, the coexpressionnetwork of
CRC was reconstructed by combining differential expression analysis andweighted gene co-expression network analysis (WGCNA). Firstly, we analyzed the GSE۱۵۶۴۵۱dataset from the GEO database. Genes with considerable variation were identified by screeningof differentially expressed genes (DEGs). Then, gene co-expression networks were applied toreconstruct and explore the biological function of identified genes. In the next stage, geneontology and KEGG pathway analysis and module networks were performed using Cytoscape.Finally, to validate the results of the study, online database analyses through XenaBrowser andGEIPA were performed to estimate hub-gene expression and discover their prognostic value.Results: As a result, a total of ۱۷۳ genes were discovered to be abnormally expressed in CRC(۱۸ up-regulated and ۱۵۴ down-regulated). In addition, among the ۸ modules, the brown modulewas significantly related to tumor progression (r=۰.۹۳, p-value=۶e-۵۳). Based on the Venndiagram created between the brown module and DEGs, four genes were identified as DEG hubgenes.Based on gene enrichment analysis, we propped
BEST۴ and
CA۷ as two novel targets inCRC. The genes in this module are involved in the mitotic cell cycle process, DNA replication,and negative regulation of mitotic nuclear division.Conclusion: Our findings can help better understand the association between the transcriptomeand clinical data in CRC, moreover they will also allow determining targeted molecular therapiesfor the disease.