Hub genes identification and association of key pathways with hypoxia in cancer cells: A bioinformatics analysis

Three human cancer cell lines (A549, HCT116, and HeLa) were used to investigate the molecular mechanisms and potential prognostic biomarkers associated with hypoxia. We obtained gene expression data from Gene Expression Omnibus (GEO) datasets GSE11704, GSE147384, and GSE38061, which included 5 hypoxic and 8 control samples. Using the GEO2R tool and Venn diagram software, we identified common differentially expressed genes (cDEGs). The cDEGs were then subjected to Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis by employing DAVID. The hub genes were identified from critical PPI subnetworks through CytoHuba plugin and these genes' prognostic significance and expression were verified using Kaplan-Meier analysis and Gene Expression Profiling Interactive Analysis (GEPIA), respectively. The research showed 676 common DEGs (cDEGs), with 207 upregulated and 469 downregulated genes. The STRING analysis showed 673 nodes and 1446 edges in the PPI network. We identified 4 significant modules and 19 downregulated hub genes. GO analysis revealed all of them were majorly involved in ribosomal large subunit assembly and biogenesis, rRNA processing, ribosome biogenesis, translation, RNA & protein binding frequently at the sites of nucleolus and nucleoplasm while 11 were significantly associated with a better prognosis of hypoxic tumors. Our research sheds light on the molecular mechanisms that underpin hypoxia in human cancer cell lines and identifies potential prognostic biomarkers for hypoxic tumors.