Disulfidptosis-related lncRNA signatures in lung adenocarcinoma: Predicting prognosis and evaluating the tumor immune microenvironment

Abstract

Abstract Background As a novel form of regulated cell death (RCD), disulfidptosis has been reported recently, which brought the significant probability in better understanding for pathogenesis and therapeutic strategies of tumors. Long non-coding RNAs (LncRNAs) regulate the viability of tumor cells by engaging with a range of targets, including DNA, RNA, and proteins. Nonetheless, the understanding about the prognostic value of disulfidptosis-related LncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains incomplete. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRLncRNAs. Methods RNA-seq data and corresponding clinical information were acquired from The Cancer Genome Atlas (TCGA) database, enabling the identification of DRlncRNAs. Subsequently, a prognostic model was formulated for LUAD by utilizing a series of analyses including univariate COX, LASSO, and multivariate COX regression. Patients were then categorized into two groups with distinct level of DRLS score, and subsequently subjected to the consensus clustering analysis for assigning LUAD patients to distinct subtypes by employing the DRlncRNAs. Subsequent studies investigated disparities among groups with distinct risk and molecular subtypes in terms of overall survival (OS), functional enrichment, the tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, in vitro experiments were conducted to validate the LUAD cellular proliferation and migratory behavior upon GSEA knockdown. Results Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Conclusion Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.