A Risk Score Based on Immune- and Oxidative Stress-Related LncRNAs Predicts Prognosis in Lung Adenocarcinoma: Insights from in vitro Experiments and Large-Scale Transcriptome Analysis

Abstract

Background

Long non-coding RNAs (lncRNAs) were demonstrated to be key to cancer progression and highly associated with the tumor immune microenvironment. Oxidative stress and immune may modulate the biological behaviors of tumors. Therefore, biomarkers that combined oxidative stress, immune, and lncRNA can be a promising candidate bioindicator in clinical therapy of cancers.

Methods

Immune-related genes (IRGs) and oxidative stress-related genes (ORGs) were identified based on a detailed review of published literatures. The transcriptome data and clinical information of lung adenocarcinoma (LUAD) patients were obtained from TCGA database. Lasso and Cox regression analyses were conducted to develop a prognostic model. Additionally, the link between immune checkpoints, immune cells, and the prognostic model was investigated, and predict the sensitivity of immunotherapy.

Results

2498 IRGs and 809 ORGs were extracted from previous studies, and 190 immune- and oxidative stress-related genes (IOGs) were acquired by overlapping the above genes. 658 immune- and oxidative stress-related lncRNAs (IOLs) were screened by Pearson correlation analysis. A total of 25 prognosis-related IOLs were screened by univariate regression analysis. Finally, LASSO Cox regression analysis was adopted for determining a 12-IOLs prognostic risk signature. The signature performance was confirmed in the training cohort and the testing cohort, and cases were classified into low- and high-risk groups by the risk score calculated from the signature. Patients in the high-risk group had poor prognoses and immunosuppression, while the risk score was significantly associated with tumor-infiltrating immune cells, immune checkpoint expression, and immunotherapy responses. In vitro experiments further confirmed the expression of key signature gene.

Conclusion

Our new IOLs-related prognostic signature can be reliable prognostic tools and therapeutic targets for LUAD patients.

Keywords:

• immune
• oxidative stress
• lung adenocarcinoma
• prognostic model

Study Approval

All datasets in the present study were downloaded from public databases. These public databases allowed researchers to download and analyze public datasets for scientific purposes. The current research follows the TCGA data access policies and publication guidelines. Users can download relevant data for free, our study is based on open-source data, there are no ethical issues and other conflicts of interest. Inclusion of the Human cell lines in the study were approved by The Second Hospital of Hebei Medical University review board.

Acknowledgments

We would like to acknowledge reviewers and editors for their helpful comments on this paper.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests in this work.

Additional information

Funding

This study was supported by Hebei Provincial Government sponsored the project of training excellent talents in clinical medicine (No. 303-2022-27-37 to Shujun Li) and Hebei Medical Research Project Plan (No. 20210373 to Xin Liu).