Identification of Prognostic DNA Methylation Signatures in Lung Adenocarcinoma

BACKGROUND: Increasing evidence exists of a link between DNA methylation and tumor immunotherapy. However, the impact of DNA methylation on the characteristics of the lung adenocarcinoma microenvironment and its effect on immunotherapy remain unclear. METHOD: This study collected TCGA-LUAD related data sets (LUAD) to explore the characteristics and regulation of 20 DNA methylation-related genes. We further identified two DNA methylation subtypes by analysing the expression profiles of these 20 DNA methylation-related genes. Subsequently, the differences in immune cell infiltration (ICI) and the expression of immune-related signaling factors among different DNA methylation subtypes were explored, and the differentially expressed genes (DEGs) among different LUAD DNA methylation subtypes were identified. Using univariate Cox to screen differentially expressed genes meaningful for survival, a DNA methylation score (DMS) was constructed based on the weight of the first and second dimensions after dimensionality reduction by principal component analysis (PCA). Our study found that DMS can better evaluate the prognosis of lung adenocarcinoma. RESULTS: Based on DMS, LUAD samples were divided into two groups with high and low scores. The differences in clinical characteristics, tumor mutation load, and tumor immune cell infiltration between different DMS groups of LUAD were deeply explored, and the prediction ability of DMS for the benefit of immunotherapy was evaluated. CONCLUSIONS: DMS is a valuable tool for predicting survival, clinicopathological features, and immunotherapeutic efficacy, which may help to promote personalized LUAD immunotherapy in the future.