Identification of MSC-AS1, a novel lncRNA for the diagnosis of laryngeal cancer.

PURPOSE

Our study was aimed to identify potential lncRNAs related to laryngeal cancer (LC) and explore their potential regulatory mechanisms.

METHODS

RNA sequencing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to identify differentially expressed genes (DEGs). Receiver operating characteristic (ROC) curve analysis was performed to analyze the sensitivity and specificity of differentially expressed lncRNAs (DElncRNAs) as biomarkers. Weighted gene co-expression network analysis (WGCNA) was applied to identify co-expressed DElncRNAs and differentially expressed mRNAs (DEmRNAs) associated with clinical indicators. We performed functional enrichment analysis on target genes and constructed a lncRNA-miRNA-mRNA ceRNA network. The expression of lncRNA and mRNAs in ceRNA network were validated via RT-qPCR.

RESULTS

By differential expression analyzing TCGA and GEO data, 6 up-regulated DElncRNAs were consistently identified, and their predictive performance were suggested to be considerable via ROC curve. 1998 DEmRNAs and 6 lncRNAs were involved in the construction of WGCNA network, in which the MEblue module was positively correlated with clinical stage. Functional enrichment analysis of this module suggested that the functions of DEmRNAs were closely involved in PI3K/Akt pathway. A ceRNA network composed of MSC-AS1, miR-429, COL4A1 and ITGAV was constructed. It was verified by RT-qPCR that the lncRNA and mRNAs in the ceRNA network were highly expressed in multiple LC tissues.

CONCLUSIONS

This study identified lncRNA MSC-AS1 as a potential biomarker of LC. Besides, we constructed a ceRNA network, which provides a basis for the research of ceRNA in LC.