Identification of an Immune Gene Expression Signature for Predicting Lung Squamous Cell Carcinoma Prognosis.

ABSTRACT: Growing evidence indicates that immune-related biomarkers play an important role in tumor processes. This study investigates immune-related gene expression and its prognostic value in lung squamous cell carcinoma (LUSC). A cohort of 493 samples of patients with LUSC was collected and analyzed from data generated by the TCGA Research Network and ImmPort database. The R coxph package was employed to mine significant immune-related genes using univariate analysis. Lasso and stepwise regression analyses were used to construct the LUSC prognosis prediction model, and clusterProfiler was used for gene functional annotation and enrichment analysis. The Kaplan-Meier analysis and ROC were used to evaluate the model efficiency in predicting and classifying LUSC case prognoses. We identified 14 immun

SUBMITTER: Yan Y 

PROVIDER: S-EPMC7338973 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature