Immune landscape and a novel immunotherapy-related gene signature associated with clinical outcome in early-stage lung adenocarcinoma.

ABSTRACT: Patients with early-stage lung adenocarcinoma (LUAD) exhibit different overall survival (OS) rates and immunotherapy responses. Understanding the immune landscape facilitates the personalized treatment of LUAD. The immune cell populations in tumour tissues were quantified to depict the immune landscape in early-stage LUAD patients in The Cancer Genome Atlas (TCGA). Early-stage LUAD patients in three immune clusters identified by the immune landscape exhibited different survival potentials. A prognostic immune-related gene signature was built to predict the survival of early-stage LUAD patients. Several machine learning methods (support vector machine, naive Bayes, random forest, and neural network-based deep learning) were applied to train the classifiers to identify the immune clusters in

SUBMITTER: Bao X 

PROVIDER: S-EPMC7297823 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature