Construction and validation of an angiogenesis-related lncRNA prognostic model in lung adenocarcinoma

Background: There is increasing evidence that long non-coding RNAs (lncRNAs) can be used as potential prognostic factors for cancer. This study aimed to develop a prognostic model for lung adenocarcinoma (LUAD) using angiogenesis-related long non-coding RNAs (lncRNAs) as potential prognostic factors. Methods: Transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify aberrantly expressed angiogenesis-related lncRNAs in LUAD. A prognostic signature was constructed using differential expression analysis, overlap analysis, Pearson correlation analysis, and Cox regression analysis. The model's validity was assessed using K-M and ROC curves, and independent external validation was performed in the GSE30219 dataset. Prognostic lncRNA-microRNA (miRNA)-messenger RNA (mRNA) competing endogenous RNA (ceRNA) networks were identified. Immune cell infiltration and mutational characteristics were also analyzed. The expression of four human angiogenesis-associated lncRNAs was quantified using quantitative real-time PCR (qRT-PCR) gene arrays. Results: A total of 26 aberrantly expressed angiogenesis-related lncRNAs in LUAD were identified, and a Cox risk model based on LINC00857, RBPMS-AS1, SYNPR-AS1, and LINC00460 was constructed, which may be an independent prognostic predictor for LUAD. The low-risk group had a significant better prognosis and was associated with a higher abundance of resting immune cells and a lower expression of immune checkpoint molecules. Moreover, 105 ceRNA mechanisms were predicted based on the four prognostic lncRNAs. qRT-PCR results showed that LINC00857, SYNPR-AS1, and LINC00460 were significantly highly expressed in tumor tissues, while RBPMS-AS1 was highly expressed in paracancerous tissues. Conclusion: The four angiogenesis-related lncRNAs identified in this study could serve as a promising prognostic biomarker for LUAD patients.