Identification Invasion-Related Long Non-Coding RNAs in Lung Adenocarcinoma and Analysis of Competitive Endogenous RNA Regulatory Networks.

Abstract

Cell invasion plays a vital role in cancer development and progression. Aberrant expression of long non-coding RNAs (lncRNAs) is also critical in carcinogenesis. However, the prognostic value of invasion-related lncRNAs in lung adenocarcinoma (LUAD) remains unknown. Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and microRNAs (DEmiRNAs) were between LUAD and control samples. Pearson correlation analyses were performed to screen for invasion-related DElncRNAs (DEIRLs). Univariate and multivariate Cox regression algorithms were applied to identify key genes and construct the risk score model, which was evaluated using receiver operating characteristic (ROC) curves. Gene set enrichment analysis (GSEA) was used to explore the underlying pathways of the risk model. Moreover, an invasion-related competitive endogenous RNA (ceRNA) regulatory network was constructed. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to detect the expression of prognostic lncRNAs in the LUAD and control samples. A total of 45 DElncRNAs were identified as DEIRLs. RP3-525N10.2, LINC00857, EP300-AS1, PDZRN3-AS1, and RP5-1102E8.3 were potential prognostic lncRNAs, the expression of which was verified by RT-qPCR in LUAD samples. Both the risk score model and nomogram used the prognostic lncRNAs. ROC curves showed the risk score model had moderate accuracy and the nomogram had high accuracy in predicting patient prognosis. GSEA results indicated that the risk score model was associated with many biological processes and pathways relevant to cell proliferation. A ceRNA regulatory network was constructed in which PDZRN3-miR-96-5p-CPEB1, EP300-AS1-miR-93-5p-CORO2B, and RP3-525N10.2-miR-130a-5p-GHR may be key invasion-related regulatory pathways in LUAD. Our study identified five novel invasion-related prognostic lncRNAs (RP3-525N10.2, LINC00857, EP300-AS1, PDZRN3-AS1, and RP5-1102E8.3) and established an accurate model for predicting the prognosis of patients with LUAD. These findings enrich our understanding of the relationships between cell invasion, lncRNAs, and LUAD and may provide novel treatment directions.