Identification of a Novel Disulfideptosis-Related LncRNA Signature and Integrative Analyses in Patients with Gliomas

Abstract Glioma, a prevalent type of brain cancer, is associated with poor prognosis. The purpose of this study was to investigate the correlation between disulfidptosis-related lncRNAs (DRLncs) and survival outcomes of glioma patients. Transcriptome and clinical data for glioma patients were retrieved from The Cancer Genome Atlas (TCGA) database. Ten disulfidptosis-related genes (DRGs) were identified from literature. Co-expression analysis was performed to identify DRLncs associated with glioma. A risk prognostic model for DRLncs was constructed using COX regression analysis and LASSO regression analysis. The model was validated by dividing samples evenly into training and test groups and conducting various analyses including survival analysis, ROC curve analysis, independent prognostic analyses, and PCA. GO and KEGG enrichment analysis was also performed on differentially expressed genes between high-risk and low-risk groups. Variances in the immune microenvironment, immune cells, and immune-related functions were analyzed between high-risk and low-risk groups. Drug sensitivity analysis was conducted to identify potential therapeutic drugs for glioma treatment, and the TIDE database was used to evaluate the potential for immune escape. The expression of DRLncs in glioma was verified through real-time quantitative PCR. Through co-expression analysis, 136 disulfidptosis-related LncRNAs were identified. Univariate Cox analysis revealed that 86 of these LncRNAs significantly correlated with overall survival (OS) in glioma patients. Using the Lasso-Cox method, a model consisting of 7 LncRNAs was constructed and optimized. This model effectively differentiated between individuals at high risk and those at low risk, with good survival prediction ability. GO and KEGG analysis indicated that the differential gene enrichment in the high- and low-risk groups was related to immune-related functions. The study observed divergences in the immune microenvironment, immune cells, and immune-related functions between the high-risk and low-risk groups. Furthermore, immunotherapy response scoring indicated that patients in the low-risk group exhibited better response to immunotherapy. Finally, real-time quantitative PCR results showed that the expression of low-risk LncRNA (ZBTB20-AS4) was low in tumor tissue, while the expression of high-risk LncRNAs (POLR2J4, SUCLG2-AS1, and UBA6-AS1) was high in glioma tumor tissue. Overall, this study established a novel glioma prognosis model that explored disulfidptosis-related lncRNAs to guide glioma prognosis.