Abstract
Due to biological heterogeneity, lung adenocarcinoma (LUAD) patients with the same stage may exhibit variable responses to immunotherapy and a wide range of outcomes. It is urgent to seek a biomarker that can predict the prognosis and response to immunotherapy in these patients. In this study, we identified two genes (ANLN and ARNTL2) from multiple gene expression data sets, and developed a two-mRNA-based signature that can effectively distinguish high- and low-risk patients and predict patients' response to immunotherapy. Furthermore, taking full advantage of the complementary value of clinical and molecular features, we combined the immune prognostic signature with clinical features to construct and validate a nomogram that can predict the probability of high tumor mutational burden (>10 mutations per megabyte). This may improve the estimation of immunotherapy response in LUAD patients, and provide a new perspective for clinical screening of immunotherapy beneficiaries.