Identification and Analysis of Amino Acid Metabolism-Related Subtypes in Lung Adenocarcinoma.

Abstract

Background: We aimed to explore the role of Amino acid metabolism (AAM) and identify biomarkers for prognosis management and treatment of lung adenocarcinoma. Methods: Differentially expressed genes (DEGs) associated with AAM in lung adenocarcinoma were selected from public databases. Samples were clustered into varying subtypes using ConsensusClusterPlus based on gene levels. Survival analysis was conducted using a survival package, and immune analysis was performed using ssGSEA and ESTIMATE. Enrichment analysis was performed using GSEA, and a protein-protein interaction network of DEGs between subgroups was established through STRING. Hub genes were screened and verified using survival analysis, and drug sensitivity prediction was performed. Results: 163 DEGs associated with AAM in lung adenocarcinoma were obtained, and two AAM-associated subtypes were identified. Cluster1 showed higher survival rates and immune levels compared with cluster2. The two subtypes were mainly enriched in immune-related signaling pathways such as B cell receptor, Jak-Stat, and natural killer cell-mediated cytotoxicity. Additionally, the mutation landscape between the two groups was significantly different. F2, AHSG, and APOA1 were key hub genes that significantly affected the prognosis differences between the two subtypes. Cluster2 showed higher sensitivity to drugs such as Mithramycin, Depsipeptide, and Actinomycin than cluster1. Conclusion: This study identified two AAM-associated gene subtypes and their biomarkers and predicted the immune status and drug treatment sensitivity of varying subtypes. The results are instructive in the clinical treatment of lung adenocarcinoma.