Identification and Interaction Analysis of Molecular Markers in Colorectal Cancer by Integrated Bioinformatics...

BACKGROUND Colorectal cancer (CRC) is an extremely common gastrointestinal malignancy. MATERIAL AND METHODS Three mRNA and 2 microRNA microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and microRNAs (DEMs) were obtained. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) program was utilized to perform gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Protein-protein interaction (PPI) network analysis was performed with the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape and Molecular Complex Detection (MCODE). Kaplan-Meier curves were plotted to determine overall survival (OS) estimates. DEMs targets were predicted by miRWalk. Quantitative reverse transcription polymerase chain reaction (QRT-PCR) was utilized to detect the expression of genes and microRNAs. RESULTS A total of 264 DEGs and 8 DEMs were obtained. GO analysis revealed that the DEGs were enriched in terms of cell structure, digestion, receptor binding, and extracellular material (ECM). KEGG pathway analysis showed that the DEGs were enriched in ECM interaction and mineral absorption. Additionally, a PPI network consisting of 181 nodes and 450 edges was established. Three modules with 38 high-degree hubs were extracted from the PPI network and found to be involved in pathways such as chemokine signaling. Five DEGs located in the network of DEM-DEG pairs were associated with the overall survival of CRC patients. Furthermore, hsa-miR-551b was demonstrated to be significantly down-regulated in CRC tissues. CONCLUSIONS The key biomarkers could provide new clues for CRC.