Abstract
BACKGROUND: Gastric cancer (GC) is a highly heterogeneous disease, which makes treatment and prognosis prediction difficult. Pyroptosis plays a vital role in the development of GC and influence the prognosis of GC. Long non-coding RNAs (lncRNAs), as regulators of gene expressions, are among putative biomarkers and therapeutic targets. However, the importance of pyroptosis-associated lncRNAs is still unclear in predicting prognosis in gastric cancer. METHODS: In this study, the mRNA expression profiles and clinical data of GC patients were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. A pyroptosis-related lncRNA signature was constructed based on TCGA databases by using the Least Absolute Shrinkage and Selection Operator (LASSO) method Cox regression model. GC patients from the GSE62254 database cohort were used for validation. Univariate and multivariate Cox analyses were used to determine the independent predictors for OS. Gene set enrichment analyses were performed to explore the potential regulatory pathways. The immune cell infiltration level was analyzed via CIBERSORT. RESULTS: A four-pyroptosis-related lncRNA (ACVR2B-AS1, PRSS30P, ATP2B1-AS1, RMRP) signature was constructed using LASSO Cox regression analysis. GC patients were stratified into high- and low-risk groups, and patients in the high-risk group showed significant worse prognosis in TNM stage, gender, and age. The risk score was an independent predictor for OS by multivariate Cox analysis. Functional analysis indicated that the immune cell infiltrate was different between high- and low-risk groups. CONCLUSION: The pyroptosis-related lncRNA prognostic signature can be used for predicting prognosis in GC. Moreover, the novel signature might provide clinical therapeutic intervention for GC patients.