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Identification of key pathways and genes in colorectal cancer using bioinformatics analysis

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Abstract

Colorectal cancer (CRC) is the most common malignant tumor of digestive system. The aim of this study was to identify gene signatures during CRC and uncover their potential mechanisms. The gene expression profiles of GSE21815 were downloaded from GEO database. The GSE21815 dataset contained 141 samples, including 132 CRC and 9 normal colon epitheliums. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and protein–protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed by Cytoscape software. In total, 3500 DEGs were identified in CRC, including 1370 up-regulated genes and 2130 down-regulated genes. GO analysis results showed that up-regulated DEGs were significantly enriched in biological processes (BP), including cell cycle, cell division, and cell proliferation; the down-regulated DEGs were significantly enriched in biological processes, including immune response, intracellular signaling cascade and defense response. KEGG pathway analysis showed the up-regulated DEGs were enriched in cell cycle and DNA replication, while the down-regulated DEGs were enriched in drug metabolism, metabolism of xenobiotics by cytochrome P450, and retinol metabolism pathways. The top 10 hub genes, GNG2, AGT, SAA1, ADCY5, LPAR1, NMU, IL8, CXCL12, GNAI1, and CCR2 were identified from the PPI network, and sub-networks revealed these genes were involved in significant pathways, including G protein-coupled receptors signaling pathway, gastrin-CREB signaling pathway via PKC and MAPK, and extracellular matrix organization. In conclusion, the present study indicated that the identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of CRC, and might be used as molecular targets and diagnostic biomarkers for the treatment of CRC.

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Authors and Affiliations

  1. Department of Bioinformatics, Key Laboratory of Cell Biology, Ministry of Public Health and Key Laboratory of Medical Cell Biology, Ministry of Education, College of Basic Medical Science, China Medical University, No. 77, Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning, People’s Republic of China

    Bin Liang & Chunning Li

  2. Department of Clinical Laboratory, No. 202 Hospital of PLA, Shenyang, People’s Republic of China

    Jianying Zhao

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  1. Bin Liang
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  2. Chunning Li
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Correspondence to Bin Liang.

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Liang, B., Li, C. & Zhao, J. Identification of key pathways and genes in colorectal cancer using bioinformatics analysis. Med Oncol 33, 111 (2016). https://doi.org/10.1007/s12032-016-0829-6

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