Journal
ONCOLOGY REPORTS
Volume 38, Issue 4, Pages 2043-2050Publisher
SPANDIDOS PUBL LTD
DOI: 10.3892/or.2017.5930
Keywords
bioinformatics analysis; colorectal cancer; differentially expressed gene; protein-protein interaction; microRNA regulatory network
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Colorectal cancer (CRC) is the most common cancer of the digestive system. The aim of the present study was to identify the potential biomarkers and uncover the underlying mechanisms. The gene and miRNA expression profiles were obtained from GEO database. The differentially expressed genes (DEGs) and miRNAs (DE miRNAs) were identified by GEO2R. The gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by KOBAS 3.0. The protein-protein interaction (PPI) network and miRNA-gene network were constructed by Cytoscape software. Then, the identified genes were verified by quantitative real-time PCR in both CRC tissue samples and cell lines. A total of 600 upregulated DEGs, 283 downregulated DEGs, 13 upregulated DE miRNAs and 7 downregulated DE miRNAs were identified. GO analysis results showed that upregulated DEGs were significantly enriched in binding, organelle and cellular process. Downregulated DEGs were enriched in binding, extracellular region and chemical homeostasis. KEGG analysis showed that the DEGs were mostly enriched in cell cycle and pathways in cancer. A total of eight genes were identified as biomarkers, including CAD, ITGA2, E2F3, BCL2, PRKACB, IGF1, SGK1 and NR3C1. Experimental validation showed that seven of the eight identified genes had the same expression trend as predicted, except for ITGA2. Besides, hsa-miR-552 and hsa-miR-30a were identified as key miRNAs. the present study provides a series of biomarkers and mechanisms for the diagnosis and therapy of CRC. We also prove that although bioinformatics analysis is a wonderful approach, experiment validation is necessary.
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