Research Paper Volume 12, Issue 2 pp 1047—1086

CeRNA regulatory network-based analysis to study the roles of noncoding RNAs in the pathogenesis of intrahepatic cholangiocellular carcinoma

Weiyu Xu 1, , Si Yu 2, , Jianping Xiong 3, , Junyu Long 2, , Yongchang Zheng 2, , Xinting Sang 2, ,

  • 1 Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, Xi-Cheng, Beijing 100050, People's Republic of China
  • 2 Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Wangfujing, Beijing 100730, People's Republic of China
  • 3 Department of Interventional Radiology, Beijing Friendship Hospital, Capital Medical University, Xi-Cheng, Beijing 100050, People's Republic of China
* Equal contribution

received: May 11, 2019 ; accepted: December 21, 2019 ; published: January 17, 2020 ;

https://doi.org/10.18632/aging.102634
How to Cite

Copyright © 2020 Xu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

To explore and understand the competitive mechanism of ceRNAs in intrahepatic cholangiocarcinoma (ICC), we used bioinformatics analysis methods to construct an ICC-related ceRNA regulatory network (ceRNET), which contained 340 lncRNA-miRNA-mRNA regulatory relationships based on the RNA expression datasets in the NCBI GEO database. We identified the core regulatory pathway RP11-328K4.1-hsa-miR-27a-3p-PROS1, which is related to ICC, for further validation by molecular biology assays. GO analysis of 44 differentially expressed mRNAs in ceRNET revealed that they were mainly enriched in biological processes including “negative regulation of epithelial cell proliferation” and "positive regulation of activated T lymphocyte proliferation.” KEGG analysis showed that they were mainly enriched in the “complement and coagulation cascade” pathway. The molecular biology assay showed that lncRNA RP11-328K4.1 expression was significantly lower in the cancerous tissues and peripheral plasma of ICC patients than in normal controls (p<0.05). In addition, hsa-miR-27a-3p was found to be significantly upregulated in the cancer tissues and peripheral plasma of ICC patients (p<0.05). Compared to normal controls, the expression of PROS1 mRNA was significantly downregulated in ICC patient cancer tissues (p<0.05) but not in peripheral plasma (p>0.05). Furthermore, ROC analysis revealed that RP11-328K4.1, hsa-miR-27a-3p, and PROS1 had significant diagnostic value in ICC. We concluded that the upregulation of lncRNA RP11-328K4.1, which might act as a miRNA sponge, exerts an antitumor effect in ICC by eliminating the inhibition of PROS1 mRNA expression by oncogenic miRNA hsa-miR-27a.

Abbreviations

ceRNA: competitive endogenous RNA; lncRNA: long noncoding RNA; miRNA: microRNA; ICC: intrahepatic cholangiocarcinoma; ceRNET: ceRNA regulatory network; logFC: log-fold change; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; NCBI: National Center for Biotechnology Information; GEO: Gene Expression Omnibus; CCA: cholangiocarcinoma; pCCA: peri-hilar cholangiocarcinoma; dCCA: distal cholangiocarcinoma; ncRNA: noncoding ribonucleic acids; MRE: miRNA response elements; OS: overall survival; DE: differential expression; T: tumor; C: paracancerous; N: normal; DAVID: Database for Annotation, Visualization and Integrated Discovery; EDTA: ethylene diamine tetraacetic acid; PVDF: Polyvinylidene Difluoride; IHC: immunohistochemistry; BP: biological process; CC: cellular component; MF: molecular function; HCC: hepatocellular carcinoma; ECC: extra-cholangiocarcinoma; ESCC: esophageal squamous cell carcinoma; CRC: colorectal cancer; 3′-UTR: 3′ untranslated region; VE-cadherin: vasculogenic mimicry-associated cadherin; PS: protein S; qRT-PCR: quantitative real time polymerase chain reaction; ROC: receiver operating characteristic; AUC: area under the ROC curve.