Home LiteratureArticle Details
PMID: 32095316 Published · epublish English

Genome-wide analysis of lncRNAs, miRNAs, and mRNAs forming a prognostic scoring system in esophageal squamous cell carcinoma.

PeerJ ·Vol. 8 ·2020-00-00

Shi X, Li Y, Sun Y, Zhao X, Sun X, Gong T, Liang Z, Ma Y, Zhang X

Abstract

Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal carcinoma. Protein coding genes and non-coding RNAs can be powerful prognostic factors in multiple cancers, including ESCC. However, there is currently no model that integrates multiple types of RNA expression signatures to predict clinical outcomes. The sequencing data (RNA-sequencing and miRNA-sequencing) and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) database, and Differential gene expression analysis, Cox regression analysis and Spearman correlation analysis were used to construct prognosis-related lncRNA-mRNA co-expression network and scoring system with multiple types of RNA. The potential molecular mechanisms of prognostic mRNAs were explored by functional enrichment analysis. A total of 62 prognostic lncRNAs, eight prognostic miRNAs and 66 prognostic mRNAs were identified in ESCC (P-value < 0.05) and a prognosis-related lncRNA-mRNA co-expression network was created. Five prognosis-related hub RNAs (CDCA2, MTBP, CENPE, PBK, AL033384.1) were identified. Biological process analysis revealed that mRNAs in prognosis-related co-expression RNA network were mainly enriched in cell cycle, mitotic cell cycle and nuclear division. Additionally, we constructed a prognostic scoring system for ESCC using ten signature RNAs (MLIP, TNFSF10, SIK2, LINC01068, LINC00601, TTTY14, AC084262.1, LINC01415, miR-5699-3p, miR-552-5p). Using this system, patients in the low-risk group had better long-term survival than those in the high-risk group (log-rank, P-value < 0.0001). The area under the ROC curve (AUCs) revealed that the accuracy of the prediction model was higher than the accuracy of single type of RNA prediction model. In brief, we constructed a prognostic scoring system based on multiple types of RNA for ESCC that showed high predicting prognosis performance, and deeply understood the regulatory mechanism of prognosis-related lncRNA-mRNA co-expression network.

Keywords
Esophageal squamous cell carcinoma Prognostic scoring system lncRNA mRNA miRNA prognosis-related co-expression network
Article Info
Journal
PeerJ
Abbr.
PeerJ
ISSN
2167-8359
Published
2020-00-00
Language
English
Country/Region
United States
NLM ID
101603425
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: product@genelibs.com