Identification of biomarkers of intrahepatic cholangiocarcinoma via integrated analysis of mRNA and miRNA microarray data

Chen,Yaqing; Liu,Dan; Liu,Pengfei; Chen,Yajing; Yu,Huiling; Zhang,Quan

doi:10.3892/mmr.2017.6123

Identification of biomarkers of intrahepatic cholangiocarcinoma via integrated analysis of mRNA and miRNA microarray data

Authors:
- Yaqing Chen
- Dan Liu
- Pengfei Liu
- Yajing Chen
- Huiling Yu
- Quan Zhang
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Affiliations: Department of VIP Ward, Affiliated Hospital of Hebei University, Baoding, Hebei 071000, P.R. China, Department of Ultrasonic Imaging, Zhuhai People's Hospital, Zhuhai, Guangdong 519000, P.R. China, Department of Lymphoma, Sino‑US Center of Lymphoma and Leukemia, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, P.R. China, Department of Internal Medicine, Baoding Xiongxian County Hospital, Baoding, Hebei 071000, P.R. China, Department of Gastroenterology, Affiliated Hospital of Hebei University, Baoding, Hebei 071000, P.R. China, Department of Hepatobiliary Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei 071000, P.R. China
Published online on: January 16, 2017 https://doi.org/10.3892/mmr.2017.6123
Pages: 1051-1056
Copyright: © Chen 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 potential therapeutic targets of intrahepatic cholangiocarcinoma (ICC) via integrated analysis of gene (transcript version) and microRNA (miRNA/miR) expression. The miRNA microarray dataset GSE32957 contained miRNA expression data from 16 ICC, 7 mixed type of combined hepatocellular‑cholangiocarcinoma (CHC), 2 hepatic adenoma, 3 focal nodular hyperplasia (FNH) and 5 healthy liver tissue samples, and 2 cholangiocarcinoma cell lines. In addition, the mRNA microarray dataset GSE32879 contained mRNA expression data from 16 ICC, 7 CHC, 2 hepatic adenoma, 5 FNH and 7 healthy liver tissue samples. The datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and miRNAs (DEMs) in ICC samples compared with healthy liver tissues were identified via the limma package, following data preprocessing. Genes that exhibited alternative splicing (AS) in ICC samples were identified via AltAnalyze software. Functional enrichment analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Analysis. Target genes of DEMs were identified using the TargetScan database. The regulatory association between DEMs and any overlaps among DEGs, alternative splicing genes (ASGs) and target genes of DEMs were retrieved, and a network was visualized using the Cytoscape software. A total of 2,327 DEGs, 70 DEMs and 623 ASGs were obtained. Functional enrichment analysis indicated that DEGs were primarily enriched in biological processes and pathways associated with cell activity or the immune system. A total of 63 overlaps were obtained among DEGs, ASGs and target genes of DEMs, and a regulation network that contained 243 miRNA‑gene regulation pairs was constructed between these overlaps and DEMs. The overlapped genes, including sprouty‑related EVH1 domain containing 1, protein phosphate 1 regulatory subunit 12A, chromosome 20 open reading frame 194, and DEMs, including hsa‑miR‑96, hsa‑miR‑1 and hsa‑miR‑25, may be potential therapeutic targets for the future treatment of ICC.

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