The immunotherapy of lung adenocarcinoma (LUAD) has received much attention in recent years and metabolic reprogramming is linked to immune infiltration in the tumor microenvironment. Therefore, it is indispensable to dissect the role of immune-related metabolic genes in lung adenocarcinoma.
In this study, we screened immune-related genes by Pearson correlation. The function of these genes was explored by gene ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. The differently expressed immune-related genes were analyzed by Limma. Furthermore, the LUAD patients were clustered based on immune-related genes through consensus clustering. The Unicox was used to identify survival-immune-related metabolic genes. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to optimize the gene sets. A prediction model was constructed and tested. The potential therapeutic target was selected based on two criteria, these immune-related metabolic genes that were highly expressed in tumor tissues and negatively correlated with the survival of patients in LUAD. Quantitative real‐time PCR (qRT‐PCR) was used for
We identified 346 immune-related genes, mainly involved in arachidonic acid metabolism and peroxisome proliferator-activated receptor (PPAR) signaling. Moreover, a total of 141 immune-related genes were dysregulated between tumor and normal tissues. We clustered three subtypes of LUAD based on immune-related metabolic genes and these subtypes exhibited different survival and immune status. We found Ribonucleotide Reductase Regulatory Subunit M2 (
We comprehensively analyzed the immune-related metabolic genes in LUAD.