Integrated bioinformatics screening and experimental validation: construction of a LUAD prediction model based on Treg-related genes.

ABSTRACT:

Background

The prognosis of lung adenocarcinoma (LUAD) is poor, and clinical treatment mainly comprises a combination of traditional therapy and immunotherapy. However, the role and mechanism of tumor-infiltrating regulatory T cells (Tregs) in immunotherapy remain controversial. Therefore, we aimed to determine the role of Tregs in LUAD and to construct a relevant prognostic model for future clinical treatment.

Methods

A LUAD dataset was downloaded from the Gene Expression Omnibus (GEO) database, screened, integrated, and divided into test and validation datasets. CIBERSORT and weighted correlation network analysis (WGCNA) algorithms were combined to screen for Treg cell-related modules. Minimum absolute contraction and selection operator (LASSO) and univariate and multivari

SUBMITTER: Zhao T 

PROVIDER: S-EPMC12617371 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature