KEY TAKEAWAYS
- The study aimed to investigate DRLs in patients with BLCA, build a prognostic model for survival prediction, and identify therapeutic targets.
- Researchers identified 8 DRLs as prognostic and therapeutic targets for bladder carcinoma, with implications for TMB and treatment responsiveness.
Bladder cancer (BLCA) is a prevalent and aggressive cancer associated with high mortality and poor prognosis. Currently, studies on the role of disulfidptosis-related long non-coding RNAs (DRLs) in BLCA are limited.
Xiaoyu Yang and the team aimed to construct a prognostic model based on DRLs to improve the accuracy of survival predictions for patients and identify novel targets for therapeutic intervention in BLCA management.
They performed an inclusive analysis using transcriptomic and clinical datasets from The Cancer Genome Atlas for patients with BLCA. They developed a risk prognostic signature based on DRLs using multivariate Cox regression and least absolute shrinkage and selection operator techniques. Assessment of the model’s accuracy and prognostic relevance included Kaplan-Meier survival plots, receiver operating characteristic curves, concordance index, and principal component analysis.
Functional and pathway enrichment analyses, such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, elucidated underlying biological processes. Immune cell infiltration was quantified using the CIBERSORT algorithm, and differences in immune cell functions between risk groups were evaluated through single-sample Gene Set Enrichment Analysis. Predictions of response to immunotherapy utilized the Tumor Immune Dysfunction and Exclusion predictor and assessed tumor mutational burden (TMB). Drug sensitivity predictions were made using the Genomics of Drug Sensitivity in Cancer database.
They identified a robust 8-DRL risk prognostic model, comprising LINC00513, SMARCA5-AS1, MIR4435-2HG, MIR4713HG, AL122035.1, AL359762.3, AC006160.1, and AL590428.1, as an independent prognostic indicator. This model demonstrated strong predictive power for overall survival in patients with BLCA, revealing significant disparities between high- and low-risk groups regarding tumor microenvironment (TME), immune infiltration, immune functions, TMB, Tumor Immune Dysfunction and Exclusion scores, and drug susceptibility.
The study concluded with the introduction of an innovative prognostic signature comprising 8 DRLs, presenting a valuable prognostic tool and potential therapeutic targets for bladder carcinoma. The findings carry significant implications for TMB, the immune landscape, and patient responsiveness to immunotherapy and targeted treatments.
No funding related information was given.
Source: https://pubmed.ncbi.nlm.nih.gov/38968515/
Yang X, Zhang Y, Liu J, et al. (2024). “Construction and validation of a prognostic model for bladder cancer based on disulfidptosis-related lncRNAs.” Medicine (Baltimore). 2024 Jul 5;103(27):e38750. doi: 10.1097/MD.0000000000038750. PMID: 38968515; PMCID: PMC11224815.