Discovery of core genes in colorectal cancer by weighted gene co‑expression network analysis

Liao,Cun; Huang,Xue; Gong,Yizhen; Lin,Qiuning

doi:10.3892/ol.2019.10605

Discovery of core genes in colorectal cancer by weighted gene co‑expression network analysis

Authors:
- Cun Liao
- Xue Huang
- Yizhen Gong
- Qiuning Lin
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Affiliations: Department of Colorectal and Anal Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530000, P.R. China, Department of Gastroenterology, Eighth Affiliated Hospital of Guangxi Medical University, Guigang, Guangxi Zhuang Autonomous Region 537100, P.R. China, Department of Vascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530000, P.R. China
Published online on: July 11, 2019 https://doi.org/10.3892/ol.2019.10605
Pages: 3137-3149
Copyright: © Liao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The aim of the present study was to investigate the interactions among messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs) in colorectal cancer (CRC), in order to examine its underlying mechanisms. The raw gene expression data was downloaded from the Gene Expression Omnibus (GEO) database. An online tool, GEO2R, which is based on the limma package, was used to identify differentially expressed genes. The co‑expression between lncRNAs and mRNAs was identified utilizing the weighted gene co‑expression analysis package of R to construct a coding non‑coding (CNC) network. The function of the genes in the CNC network was determined by performing Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways enrichment analysis. The interactions among miRNAs, mRNAs and lncRNAs were predicted using Lncbase and mirWalk to construct the competing endogenous RNA (ceRNA) network. The expression of the genes involved in the ceRNA network was further validated in The Cancer Genome Atlas dataset. A total of 3,183 dysregulated mRNAs, 78 dysregulated miRNAs and 2,248 dysregulated lncRNAs were screened in two GEO datasets. Combined with the results of the dysregulated genes, 169 genes were selected to construct the CNC network. ‘p53 signaling pathway’ and the ‘cell cycle’ were the most significant enriched pathways in the genes involved in the CNC network. Finally, a validated ceRNA network composed of 2 lncRNAs (MIR22HG and RP11‑61I13.3), 5 miRNAs (hsa‑miR‑765, hsa‑miR‑198, hsa‑miR‑125a‑3p, hsa‑miR‑149‑3p and hsa‑miR‑650) and 5 mRNAs (ANK2, BTK, GBP2, PCSK5 and PDK4) was obtained. In conclusion, MIR22HG may regulate PCSK5, BTK and PDK4, and RP11‑61I13.3 may regulate the ANK2, GBP2, PCSK5 through sponging miRNAs to act on the progression of CRC, and the potential function of these genes have been revealed. However, the diagnostic and prognostic value of these genes requires further validation.

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