# A Novel Signature of Disulfidptosis‐Related lncRNAs Predicts Prognosis in Glioma: Evidence From Bioinformatic Analysis and Experiments

## TL;DR

A new RNA-based model predicts glioma patient survival and suggests personalized treatment strategies based on disulfidptosis-related genes and immune features.

## Contribution

A novel DRL-based prognostic signature for glioma with potential for immune profiling and treatment prediction.

## Key findings

- A seven DRL-based risk model effectively stratifies glioma patients by survival outcomes.
- High-risk patients show distinct immune features and higher predicted drug sensitivity.
- LINC02542 knockdown reduces glioma cell proliferation, migration, and invasion.

## Abstract

Glioma is the most common primary malignant brain tumor, characterized by high mortality and poor prognosis. Disulfidptosis, a recently identified form of regulated cell death, has been implicated in tumor progression; however, its role in glioma remains unclear. In this study, we developed and validated a novel prognostic signature based on disulfidptosis‐related long noncoding RNAs (DRLs) by integrating transcriptomic and clinical data from The Cancer Genome Atlas. Seven DRLs were identified to construct a risk model that effectively stratified patients into high‐ and low‐risk groups with significantly different overall survival outcomes. Functional enrichment and immune‐related analyses revealed that the high‐risk group exhibited distinct immune microenvironment features, including altered immune cell infiltration, immune checkpoint expression, and activity of immune‐related pathways, suggesting a potential link between DRLs and immune modulation. Drug sensitivity analysis identified several chemotherapeutic agents and targeted inhibitors with higher predicted efficacy in the high‐risk group, offering insights into personalized treatment strategies. In vitro experiments further demonstrated that LINC02542 knockdown significantly suppressed glioma cell proliferation, migration, and invasion. Collectively, these findings indicate that the DRL signature functions as an independent prognostic indicator and a potential biomarker for immune landscape profiling and immunotherapy response prediction in glioma. This integrative multiomics approach provides novel perspectives for precision immunotherapy and targeted therapy in glioma.