Integrative bioinformatics approaches to establish potential prognostic immune-related genes signature and drugs in the non-small cell lung cancer microenvironment.

ABSTRACT: Introduction: Research has revealed that the tumor microenvironment (TME) is associated with the progression of malignancy. The combination of meaningful prognostic biomarkers related to the TME is expected to be a reliable direction for improving the diagnosis and treatment of non-small cell lung cancer (NSCLC). Method and Result: Therefore, to better understand the connection between the TME and survival outcomes of NSCLC, we used the "DESeq2" R package to mine the differentially expressed genes (DEGs) of two groups of NSCLC samples according to the optimal cutoff value of the immune score through the ESTIMATE algorithm. A total of 978 up-DEGs and 828 down-DEGs were eventually identified. A fifteen-gene prognostic signature was established via LASSO and Cox regressio

SUBMITTER: Zhou J 

PROVIDER: S-EPMC10106634 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature