ArticleCancer cell international2023
Leveraging a disulfidptosis‑related lncRNAs signature for predicting the prognosis and immunotherapy of glioma.
Article in Cancer cell international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Effect of targeted regulation of miR-499a-5p/integrin β1 by circ_001567 on malignant progression of gastric cancer cells.Journal of molecular histology · 2026Article
- Disulfidptosis in tumor progression.Cell death discovery · 2025Review
- A Novel Signature of Disulfidptosis-Related lncRNAs Predicts Prognosis in Glioma: Evidence From Bioinformatic Analysis and Experiments.International journal of genomics · 2025Article
- Macrophage polarization-related gene signature for risk stratification and prognosis of survival in gliomas.Journal of cellular and molecular medicine · 2024Article
- Development and validation of a novel disulfidptosis-related lncRNAs signature in patients with HPV-negative oral squamous cell carcinoma.Scientific reports · 2024Article
- Integrating bioinformatics and experimental validation to unveil disulfidptosis-related lncRNAs as prognostic biomarker and therapeutic target in hepatocellular carcinoma.Cancer cell international · 2024Article
- Disulfidptosis-linked Gene Signatures Constituted of Prognostic Prediction Models in Prostate Cancer.Cancer diagnosis & prognosisArticle
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Authors and funding
10 authors.
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Abstract
backgroundGliomas, a prevalent form of primary brain tumors, are linked with a high mortality rate and unfavorable prognoses. Disulfidptosis, an innovative form of programmed cell death, has received scant attention concerning disulfidptosis-related lncRNAs (DRLs). The objective of this investigation was to ascertain a prognostic signature utilizing DRLs to forecast the prognosis and treatment targets of glioma patients.
methodsRNA-seq data were procured from The Cancer Genome Atlas database. Disulfidptosis-related genes were compiled from prior research. An analysis of multivariate Cox regression and the least absolute selection operator was used to construct a risk model using six DRLs. The risk signature's performance was evaluated via Kaplan-Meier survival curves and receiver operating characteristic curves. Additionally, functional analysis was carried out using GO, KEGG, and single-sample GSEA to investigate the biological functions and immune infiltration. The research also evaluated tumor mutational burden, therapeutic drug sensitivity, and consensus cluster analysis. Reverse transcription quantitative PCR was conducted to validate the expression level of DRLs.
resultsA prognostic signature comprising six DRLs was developed to predict the prognosis of glioma patients. High-risk patients had significantly shorter overall survival than low-risk patients. The robustness of the risk model was validated by receiver operating characteristic curves and subgroup survival analysis. Risk model was used independently as a prognostic indicator for the glioma patients. Notably, the low-risk patients displayed a substantial decrease in the immune checkpoints, the proportion of immune cells, ESTIMATE and immune score. IC50 values from the different risk groups allowed us to discern three drugs for the treatment of glioma patients. Lastly, the potential clinical significance of six DRLs was determined.
conclusionsA novel six DRLs signature was developed to predict prognosis and may provide valuable insights for patients with glioma seeking novel immunotherapy and targeted therapy.
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