Background: Immune checkpoint inhibitor (ICI) therapy has shown remarkable clinical benefit in lung adenocarcinoma (LUAD) patients. Genomic mutations may be applicable to predict the response to ICIs. Eph receptor A5 (EPHA5) is frequently mutated in breast cancer, lung cancer and other tumors; however, its association with outcome in patients who receive immunotherapy remains unknown. Methods: Somatic mutation data, gene expression data and clinicopathologic information were curated from patients with LUAD who were treated with ICI therapy (MSKCC ICI-treated cohort) and patients with LUAD who did not receive ICI therapy (TCGA-LUAD cohort). The CIBERSORT and gene set enrichment analysis (GSEA) algorithms were separately used to infer the relative abundance of leukocytes and significantly enriched pathways in the defined subgroups. Tumor mutation burden (TMB), tumor neoantigen load, the fraction of copy number variants (CNVs), the mutation frequency of DNA damage repair (DDR) genes, and the prognosis of patients were compared between the EPHA5-mutated subgroup and the EPHA5 wild-type subgroup. Wholeexome sequencing (WES) data and drug sensitivity data downloaded from the Genomics of Drug Sensitivity in Cancer (GDSC) database were used to evaluate the relationship of the 50% inhibitory concentration (IC50) of multiple drugs and the EPHA5 mutation status in LUAD cells. Results: EPHA5 mutations were associated with increased TMB, neoantigen load, levels of immune-related gene expression signatures, and enhanced tumor-infiltrating lymphocytes (TILs). Patients with EPHA5 mutations in the immunotherapy cohort achieved a longer progression-free survival (PFS) time than patients with wild-type EPHA5. Immune response pathways were among the top enriched pathways in samples with EPHA5 mutations. In addition , patients with EPHA5 mutations tended to be more sensitive to certain targeted molecular inhibitors , including serdemetan, lox2 and PF1-1. Conclusion: Our results suggest that identifying mutations in the EPHA5 gene may provide insight into the genome-wide mutational burden and may serve as a biomarker to predict the immune response of patients with LUAD.