Identification of costimulatory molecule signatures for evaluating prognostic risk in non-small cell lung cancer.

ABSTRACT:

Background

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality worldwide. Despite advances in treatment, prognosis remains poor, necessitating the identification of reliable prognostic biomarkers. Costimulatory molecules (CMs) have shown to enhance antitumor immune responses. We aimed to explore their prognostic signals in NSCLC.

Methods

This study is a combination of bioinformatics analysis and laboratory validation. Gene expression profiles from The Cancer Genome Atlas (TCGA), GSE120622, and GSE131907 datasets were collected. NSCLC samples in TCGA were clustered based on CMs using consensus clustering. We used LASSO regression to identify CMs-related signatures and constructed nomogram and risk models. Differences in immune cells and checkpoin

SUBMITTER: Yang Y 

PROVIDER: S-EPMC11403524 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature