Identification of key genes associated with the progression of intrahepatic cholangiocarcinoma using weighted gene co‑expression network analysis

Ye,Zi; Zeng,Zhirui; Wang,Da; Lei,Shan; Shen,Yiyi; Chen,Zubing

doi:10.3892/ol.2020.11600

Identification of key genes associated with the progression of intrahepatic cholangiocarcinoma using weighted gene co‑expression network analysis

Authors:
- Zi Ye
- Zhirui Zeng
- Da Wang
- Shan Lei
- Yiyi Shen
- Zubing Chen
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Affiliations: Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China, Guizhou Provincial Key Laboratory of Pathogenesis and Drug Research on Common Chronic Diseases, Guizhou Medical University, Guiyang, Guizhou 550009, P.R. China, Department of Biliary‑Pancreatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430060, P.R. China, Department of Liver‑Biliary Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou 550009, P.R. China
Published online on: May 13, 2020 https://doi.org/10.3892/ol.2020.11600
Pages: 483-494
Copyright: © Ye et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The present study aimed to identify the key genes that are associated with the progression of intrahepatic cholangiocarcinoma through weighted gene co‑expression network analysis (WGCNA). A total of three gene datasets were downloaded from the Gene Expression Omnibus database, including GSE107943, GSE119336 and GSE26566. Differentially expressed genes (DEGs) between intrahepatic cholangiocarcinoma tissues and adjacent liver tissues were identified using GSE107943, while tissue specific genes between bile duct and liver tissues were identified using GSE26566. Following the removal of tissue‑specific genes, real DEGs were used to construct the WGCNA to investigate the association between gene modules and clinical traits. Following functional analysis, pathway enrichment analysis and the construction of a protein‑protein interaction (PPI) network were performed, hub genes were selected and their diagnostic value was verified in GSE119336 using a receiver operating characteristic curve. Finally, the protein levels of the hub genes were also verified in intrahepatic cholangiocarcinoma tissues. A total of 1,643 real DEGs were identified and used to construct the WGCNA. Additionally, a total of seven co‑expressed gene modules were identified following WGCNA, while genes in brown and yellow modules were identified to be associated with multiple clinical traits (the number of clinical traits >3) and used as key modules. A total of 63 core key module genes were subsequently identified, and it was indicated that these genes were most enriched in the nucleus (Gene Ontology term) and the cell cycle pathway (Kyoto Encyclopedia of Genes and Genomes term). Finally, a total of eight genes, including cyclin B1, cell division cycle 20, cell division cycle associated 8, cyclin dependent kinase 1, centrosomal protein 55, kinesin family member 2C, DNA topoisomerase IIα and TPX2 microtubule nucleation factor, exhibited the highest score in PPI analysis and had a high diagnostic value for intrahepatic cholangiocarcinoma. In addition, the protein levels of these genes were also revealed to be increased in most intrahepatic cholangiocarcinoma tissues. These eight genes may be used as novel biomarkers for the diagnosis of intrahepatic cholangiocarcinoma.

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