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

The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD). With TCGA-LUAD and GEO datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we identified 8 MHC-I-related genes and established a prognostic model via Cox regression analysis. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves, with outcomes illustrating that the model could accurately forecast the prognosis of LUAD individuals, and high-risk patients exhibiting lower survival rates. Furthermore, Cox regression analysis verified that the riskscore independently predicted the prognosis for LUAD. Immune analysis results revealed that individuals classified as high-risk had lower levels of immune cell infiltration and impaired immune function. Additionally, we found through immunophenoscore, TIDE score, and analysis of an immunotherapy cohort (GSE78220) that the low-risk group possessed a better response to immune checkpoint blockade therapy. Tumor mutation burden and intra-tumor heterogeneity analyses ascertained that the high-risk group exhibited greater malignancy and treatment complexity. Moreover, by employing the cMAP database, we have pinpointed small-molecule medications that possess the ability to enhance the prognosis of LUAD. Among these drugs, theobromine and pravastatin have been identified as having great potential in improving the prognosis of LUAD. Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response.