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
Abstract
AIM

To identify and predict the competing endogenous RNA (ceRNA) networks in colorectal cancer (CRC) by bioinformatics analysis.

METHODS

In the present study, we obtained CRC tissue and normal tissue gene expression profiles from The Cancer Genome Atlas project. Differentially expressed (DE) genes (DEGs) were identified. Then, upregulated and downregulated miRNA-centered ceRNA networks were constructed by analyzing the DEGs using multiple bioinformatics approaches. DEmRNAs in the ceRNA networks were identified in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using KEGG Orthology Based Annotation System 3.0. The interactions between proteins were analyzed using the STRING database. Kaplan-Meier survival analysis was conducted for DEGs and real time quantitative polymerase chain reaction (RT-qPCR) was also performed to validate the prognosis-associated lncRNAs in CRC cell lines.

RESULTS

Eighty-one DElncRNAs, 20 DEmiRNAs, and 54 DEmRNAs were identified to construct the ceRNA networks of CRC. The KEGG pathway analysis indicated that nine out of top ten pathways were related with cancer and the most significant pathway was “colorectal cancer”. Kaplan-Meier survival analysis showed that 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). Based on the STRING protein database, it was found that SERPINE1 and PHLPP2 interact with AKT1. Besides, SERPINE1 can interact with VEGFA, VTN, TGFB1, PLAU, PLAUR, PLG, and PLAT. PHLPP2 can interact with AKT2 and AKT3. RT-qPCR revealed that the expression of IGF2-AS, POU6F2-AS2, and LINC00488 in CRC cell lines was consistent with the in silico results.

CONCLUSION

CeRNA networks play an important role in CRC. Multiple DEGs are related with clinical prognosis, suggesting that they may be potential targets in tumor diagnosis and treatment.

Keywords: Colorectal cancer; LncRNA; MicroRNA; Overall survival; Competing endogenous RNA; Bioinformatics analysis

Core tip: We acquired high-throughput data from The Cancer Genome Atlas database and constructed the competing endogenous RNA (ceRNA) networks of colorectal cancer by bioinformatics analysis, which included 81 differentially expressed (DE)lncRNAs, 20 DEmiRNAs, and 54 DEmRNAs. Furthermore, 3 lncRNAs, 3 miRNAs, and 2 mRNAs were found associated with overall survival. Our study revealed that ceRNA networks are important in colorectal cancer and the prognosis-related genes worth exploring further.