Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes

Abstract

Objectives

The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD).

Materials and Methods

With The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we used Cox regression analysis to construct a prognostic model, and verified independence of riskscore. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves. Immune analysis was performed by using ssGSEA. Additionally, immune checkpoint blockade therapy was assessed by using immunophenoscore, Tumor Immune Dysfunction and Exclusion score. Based on the cMAP database, effective small molecule compounds were predicted.

Results

A prognostic model was established based on 8 MHC-I-related genes, and the predictive capacity of the model was accurate. Immune analysis results revealed that patients classified as high-risk had lower levels of immune cell infiltration and impaired immune function. The low-risk group possessed a better response to immune checkpoint blockade therapy. Theobromine and pravastatin were identified as having great potential in improving the prognosis of LUAD.

Conclusion

Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response.

Keywords:

• Lung adenocarcinoma
• MHC-I-related molecules
• prognostic analysis
• immune therapy response
• drug prediction

Authors’ contributions

Conceptualization: Hangdi Xu. Data curation: Yanjie Hu. Formal analysis: Xiuming Peng, Yanjie Hu. Methodology: Xiuming Peng. Writing—original draft: Hangdi Xu, Yanjie Hu. Writing—review and editing: Xiuming Peng, Enguo Chen.

Disclosure statement

The authors declared no potential conflicts of interest with respect to the research, authorship, or publication of this article.

Data availability statement

The data and materials in the current study are available from the corresponding author on reasonable request.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.