Published online Dec 14, 2018. doi: 10.3748/wjg.v24.i46.5259
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
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.
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.
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.
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.
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.
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.
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.