Published in:
Open Access 01-12-2024 | Analysis
Identification of a pyroptosis-immune-related lncRNA signature for prognostic and immune landscape prediction in bladder cancer patients
Published in: Discover Oncology | Issue 1/2024
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Purpose
Individualized medicine has become increasingly important in bladder cancer treatment, whereas useful biomarkers for prognostic prediction are still lacking. The current study, therefore, constructed a novel risk model based on pyroptosis- and immune-related long noncoding RNAs (Pyro-Imm lncRNAs) to evaluate the potential prognosis of bladder cancer.
Methods
Corresponding data of bladder cancer patients were downloaded from the Cancer Genome Atlas (TCGA) database. The univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis were employed to establish a predictive signature, which was evaluated by receiver operator characteristic (ROC) analysis and Kaplan–Meier analysis. Furthermore, the immune infiltration, immune checkpoints, and responses to chemotherapeutic drugs were analyzed with this model.
Results
Three Pyro-Imm lncRNAs (MAFG-DT, AC024060.1, AC116914.2) were finally identified. Patients in the low-risk group demonstrated a significant survival advantage. The area under the ROC curve (AUC) at 1, 3, and 5 years was 0.694, 0.709, and 0.736 respectively in the entire cohort. KEGG and GO analyses showed that the Wnt pathway plays a crucial role in the high-risk group. The risk score was significantly related to the degree of infiltration of different immune cells, the expression of multiple immune checkpoint genes, and the sensitivity of various chemotherapeutic drugs.
Conclusion
This novel signature provides a theoretical basis for cancer immunology and chemotherapy, which might help develop individualized therapy.