Published online Mar 28, 2020. doi: 10.3748/wjg.v26.i12.1298
Peer-review started: December 1, 2019
First decision: December 23, 2019
Revised: January 8, 2020
Accepted: March 9, 2020
Article in press: March 9, 2020
Published online: March 28, 2020
Processing time: 117 Days and 21.9 Hours
Colorectal cancer (CRC) is one of the most prevalent tumors worldwide. Recently, long noncoding RNAs (lncRNAs) have been shown to influence tumorigenesis and tumor progression by acting as competing endogenous RNAs (ceRNAs). It is difficult to extract prognostic lncRNAs and useful bioinformation from most ceRNA networks constructed previously.
To construct a prognostic related ceRNA regulatory network and lncRNA related signature based on risk score in CRC.
RNA transcriptome profile and clinical information of 506 CRC patients were downloaded from the Cancer Genome Atlas database. R packages and Perl program were used for data processing. Cox regression analysis was used for prognostic model construction. Quantitative real-time polymerase chain reaction was used to detect the expression of lncRNAs.
A prognostic-related ceRNA network was constructed, including 9 lncRNAs, 44 mRNAs, and 30 miRNAs. In addition, a four-lncRNA model was constructed using multivariate Cox regression analysis, which could be an independent prognostic model in CRC. The risk score for each patient was calculated, and the 506 patients were divided into high and low-risk groups (253 for each group) based on the median risk score. The results of the survival analysis showed that patients with a high-risk score had a poor survival rate. Furthermore, the predictive value of the four-lncRNA model was evaluated in GSE38832. Patient survival probabilities could be better predicted when combing the risk score and clinical features. Gene Set Enrichment Analysis results verified that a number of cancer-related signaling pathways were enriched with a high-risk score in CRC. Finally, we validated a novel lncRNA (LINC00488) using quantitative real-time polymerase chain reaction in 22 paired CRC patient tumor tissues compared to adjacent non-tumor tissues.
The four-lncRNA model could give better predictive value for CRC patients. Our understanding of the lncRNA-related ceRNA regulatory mechanism could provide a potential diagnostic indicator for CRC patients.
Core tip: Although there have been improvements in the treatment of colorectal cancer, a number of patients still lost the chance for survival because of a shortage of useful biomarkers. In this study, we systematically analyzed RNA transcriptome profile and constructed a prognostic-related competing endogenous RNA network by a comprehensive analysis, constructed a four-lncRNA model, and evaluated the predictive value of this model in the Gene Expression Omnibus and the Cancer Genome Atlas databases. Our understanding of the long noncoding RNA-related competing endogenous RNA regulatory mechanism could provide a potential diagnostic indicator for colorectal cancer patients.