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Int. J. Mol. Sci. 2017, 18(4), 722; doi:10.3390/ijms18040722

Identification of Key Candidate Genes and Pathways in Colorectal Cancer by Integrated Bioinformatical Analysis

1
Institute of Precision Medicine, Jining Medical University, Jining 272067, China
2
Department of Surgery, Jining Medical University, Jining 272067, China
3
Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA
*
Author to whom correspondence should be addressed.
Received: 21 February 2017 / Revised: 24 March 2017 / Accepted: 24 March 2017 / Published: 28 March 2017
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
View Full-Text   |   Download PDF [3127 KB, uploaded 30 March 2017]   |  

Abstract

Colorectal cancer (CRC) is one of the most common malignant diseases worldwide, but the involved signaling pathways and driven-genes are largely unclear. This study integrated four cohorts profile datasets to elucidate the potential key candidate genes and pathways in CRC. Expression profiles GSE28000, GSE21815, GSE44076 and GSE75970, including 319 CRC and 103 normal mucosa, were integrated and deeply analyzed. Differentially expressed genes (DEGs) were sorted and candidate genes and pathways enrichment were analyzed. DEGs-associated protein–protein interaction network (PPI) was performed. Firstly, 292 shared DEGs (165 up-regulated and 127 down-regulated) were identified from the four GSE datasets. Secondly, the DEGs were clustered based on functions and signaling pathways with significant enrichment analysis. Thirdly, 180 nodes/DEGs were identified from DEGs PPI network complex. Lastly, the most significant 2 modules were filtered from PPI, 31 central node genes were identified and most of the corresponding genes are involved in cell cycle process, chemokines and G protein-coupled receptor signaling pathways. Taken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in CRC, which could improve our understanding of the cause and underlying molecular events, and these candidate genes and pathways could be therapeutic targets for CRC. View Full-Text
Keywords: colorectal cancer; bioinformatical analysis; differentially expressed genes colorectal cancer; bioinformatical analysis; differentially expressed genes
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Guo, Y.; Bao, Y.; Ma, M.; Yang, W. Identification of Key Candidate Genes and Pathways in Colorectal Cancer by Integrated Bioinformatical Analysis. Int. J. Mol. Sci. 2017, 18, 722.

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