Basic Study
Copyright ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Dec 14, 2018; 24(46): 5259-5270
Published online Dec 14, 2018. doi: 10.3748/wjg.v24.i46.5259
Identification and prediction of novel non-coding and coding RNA-associated competing endogenous RNA networks in colorectal cancer
Yu Liang, Cheng Zhang, Ming-Hui Ma, Dong-Qiu Dai
Yu Liang, Cheng Zhang, Ming-Hui Ma, Dong-Qiu Dai, Department of Gastrointestinal Surgery, the Fourth Affiliated Hospital of China Medical University, Shenyang 110032, Liaoning Province, China
Author contributions: Dai DQ conducted the study; Liang Y, Zhang C, and Ma MH applied the experiments on TCGA project; Liang Y wrote the manuscript.
Supported by the National Natural Science Foundation of China, No. 30572162; and Natural Science Foundation of Liaoning Province, No. 201602817.
Conflict-of-interest statement: The authors declare that there is no conflict of interest related to this study.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author to: Dong-Qiu Dai, PhD, Chief Doctor, Professor, Surgical Oncologist, Department of Gastrointestinal Surgery, the Fourth Affiliated Hospital of China Medical University, 4 Chongshan Road, Shenyang 110032, Liaoning Province, China. daidq63@163.com
Telephone: +86-24-62043110 Fax: +86-24-62043110
Received: September 17, 2018
Peer-review started: September 17, 2018
First decision: October 14, 2018
Revised: October 18, 2018
Accepted: November 9, 2018
Article in press: November 9, 2018
Published online: December 14, 2018
Processing time: 88 Days and 0 Hours
ARTICLE HIGHLIGHTS
Research background

With the development of high-throughput technology, dysregulation of non-coding genes has been revealed in colorectal cancer (CRC). Furthermore, accumulating studies have demonstrated that long-noncoding RNAs (lncRNAs) function as competing endogenous RNAs (ceRNAs) to regulate oncogene and tumor suppressor gene expression by sponging microRNAs (miRNAs). In the present research, we constructed and analyzed the ceRNA networks and found the prognosis-related differentially expressed genes (DEGs) by bioinformatics analysis.

Research motivation

CRC is one of the most common malignancies in the world and the prognosis of patients in advanced stage remains poor. Therefore, specific biomarkers and novel therapeutic strategies are urgently required to improve the diagnosis and prognosis for CRC patients.

Research objectives

In our research, we aimed to construct ceRNA networks that include differentially expressed (DE)mRNAs, DElncRNAs, and DEmiRNAs based on co-expression database. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interactions network analysis were performed to confirm the importance of ceRNA networks in the development of CRC. Importantly, our study provides new potential lncRNA/miRNA/mRNA axis for future research and clinical practice.

Research methods

We obtained CRC tissue and normal tissue gene expression profiles from The Cancer Genome Atlas project. DEGs were identified by using the edgeR package in R software. Then, upregulated and downregulated miRNA-centered ceRNA networks were constructed by analyzing the DEGs using multiple bioinformatics approaches. The networks were visualized and mapped using Cytoscape software. DEmRNAs in the ceRNA networks were identified in KEGG pathways using KEGG Orthology Based Annotation System 3.0. Kaplan-Meier survival analysis was conducted for DEGs and real time quantitative polymerase chain reaction (RT-qPCR) was performed to verify the prognosis-associated DElncRNAs in CRC cell lines.

Research results

We constructed CRC ceRNA networks which included 81 DElncRNAs, 20 DEmiRNAs, and 54 DEmRNAs. KEGG pathway analysis indicated that nine pathways were related to cancer and the most significant pathway was “Colorectal cancer”. According to Kaplan-Meier curve analysis, the overall survival was positively associated with five DEGs (IGF2-AS, POU6F2-AS2, hsa-miR-32, hsa-miR-141, and SERPINE1) and it was negatively related to three DEGs (LINC00488, hsa-miR-375, and PHLPP2). The expression of prognosis-related DElncRNAs in CRC cell lines was consistent with the in silico results.

Research conclusions

In the present study, we provide a new pathway to construct ceRNA networks for cancer research and novel insights on non-coding RNAs in CRC. We identified and constructed the ceRNA networks of CRC in large cohorts. Enrichment analysis results verified the critical role of the ceRNA networks in CRC. Besides, multiple prognosis-related DEGs found in this research could be used as potential biomarkers and therapeutic targets.

Research perspectives

Further exploration of ceRNA networks provided a number of potential biomarkers and therapeutic targets for CRC. However, much more work is needed to reveal the function and mechanism of prognosis-related DEGs in the future.