Prediction of prognosis and immune response in lung adenocarcinoma by peroxisome related-lncRNA.

Abstract

Background: Lung adenocarcinoma (LUAD) represents the primary tissue subtype of lung cancer, characterized by a significant mortality rate and unfavorable prognosis. Long non-coding RNAs (lncRNAs) serve as critical functional units in the initiation and progression of tumors. Peroxisomes, now recognized as vital organelles in tumor immune metabolism, have garnered considerable attention in recent research. Some LncRNAs regulate peroxisome protein conformation through the mechanism of RNA molecular chaperones to maintain its normal function. This study aims to investigate the role of peroxisome-related lncRNA signatures in predicting clinical outcomes and immunotherapy efficacy, as well as their correlation with drug sensitivity.

Methods: The genomic and clinical information stemmed from the Cancer Genome Atlas (TCGA) database, while the peroxisome-related genes came from relevant studies. We developed prognostic features through co-expression analysis, Cox regression analysis, and LASSO analysis. Then we classified patients into high-risk and low-risk cohorts and performed extensive model validations to assess the prognostic significance of the signature. We used RT-qPCR to detect the expression of six peroxisome-associated lncRNAs in lung adenocarcinoma cells. Following this, we analyzed immune-related functions and tumor mutation burden (TMB). Lastly, we identified potential drugs and evaluated the drug sensitivity for LUAD.

Results: We identified six peroxisome-related lncRNAs that serve as prognostic biomarkers. Our analysis revealed that high-risk patients exhibited decreased survival rates and increased mortality. Independent prognostic evaluations, receiver operating characteristic (ROC) curves, and bar charts demonstrated that these peroxisome-related lncRNAs can effectively predict patient outcomes. RT-qPCR results also indicated that these peroxisomes showed significant differences in mRNA expression in lung normal and lung adenocarcinoma cells. Moreover, in high-risk individuals, we observed reduced immune cell infiltration, inhibited immune functions, and an elevated tumor mutational burden (TMB). Consequently, high-risk patients faced a higher likelihood of immune evasion, resulting in diminished effectiveness of immunotherapy.

Conclusion: In conclusion, the six lncRNAs linked to peroxisomes can reliably forecast the prognosis of LUAD patients and may offer novel perspectives for clinical applications and immunotherapy.