Construction and Validation of an Immune and Tumor Mutation Burden Based Prognostic Model in Lung Adenocarcinoma

Abstract

Background: Lung adenocarcinoma (LUAD), the most common types of cancer, is hard to diagnose and has an unfavorable prognosis. Tumor mutation burden (TMB) is a useful predictor and can also determine the efficacy of immunotherapy in various cancers. The present study focused on unraveling the association between immune infiltration and TMB and developing an immune- and TMB-related prognostic model to predict LUAD patients’ prognosis. Methods: The data of RNA expression and somatic mutation were downloaded by different databases and the immune-related prognostic model (IPM) was constructed according to five immune-related differentially expressed genes (DEGs) between high- and low-TMB groups. Next, an analysis of the IPM on the tumor microenvironment (TME) in LUAD was performed. Findings: The results revealed that the IPM based on TMB was capable of classifying LUAD patients into different risk groups and had a significantly correlation with LUAD patients’ overall survival (OS). And the immune-related model was proved to be an independent predictive biomarker. Furthermore, the five hub genes and the immune-related model were related to different immune infiltrating cells. The IPM was related to immune checkpoint inhibitors (CTLA-4, CD4, CD27, CD276 (B7-H3) and TNFRSF4 (OX40)) expression and was negatively correlated with the immune-related scores. At last, an effective nomogram was established to predict LUAD patients’ prognosis. Interpretation: Our IPM was effective in predicting LUAD patients’ prognosis and provide novel insights into immunotherapy for LUAD. Funding: National Key R&D Program of China (2017YFC1308700), Institutional Fundamental Research Funds (2018PT32033) and ETHICON·Excellent in surgery grant (2018-011-ZZ). Declaration of Interest: None to declare.