Colorectal cancer (CRC) is one of the most common malignancies, giving rise to serious financial burden globally. This study was designed to explore the potential mechanisms implicated with CRC and identify some key biomarkers. CRC-associated gene expression dataset (GSE32323) was downloaded from GEO database. The differentially expressed genes (DEGs) were selected out based on the GEO2R tool. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to search the enriched pathways of these DEGs. Additionally, a protein-protein interaction (PPI) network was also constructed to visualize interactions between these DEGs. Quantitative Real-time PCR (qPCR) was further performed to valid the top5 up-regulated and top5 down-regulated genes in patients with CRC. Finally, the survival analysis of the top5 up-regulated and top5 down-regulated genes was conducted using GEPIA, aiming to clarify their potential effects on CRC. In this study, a total of 451 DEGs were captured (306 down-regulated genes and 145 up-regulated genes). Among these DEGs, the top5 up-regulated genes were DPEP1, KRT23, CLDN1, LGR5 and FOXQ1 while the top5 down-regulated genes were CLCA4, ZG16, SLC4A4, ADH1B and GCG. GO analysis revealed that these DEGs were mainly enriched in cell adhesion, cell proliferation, RNA polymerase II promoter and chemokine activity. KEGG analysis disclosed that the enriched pathway included mineral absorption, chemokine signaling pathway, transcriptional misregulation in cancer, pathways in cancer and PPAR signaling pathway. Survival analysis showed that the expression level of ZG16 may correlate with the prognosis of CRC patients. Furthermore, according to the connectivity degree of these DEGs, we selected out the top15 hub genes, namely MYC, CXCR1, TOP2A, CXCL12, SST, TIMP1, SPP1, PPBP, CDK1, THBS1, CXCL1, PYY, LPAR1, BMP2 and MMP3, which were expected to be promising therapeutic target in CRC. Collectively, our analysis unveiled potential biomarkers and candidate targets in CRC, which could be helpful to the diagnosis and treatment of CRC.
Keywords: Quantitative Real-time PCR (qPCR); bioinformatics analysis; biomarkers; colorectal cancer; differentially expressed genes (DEGs).