Comprehensive characterization of T cell subtypes in lung adenocarcinoma: Prognostic, predictive, and therapeutic implications.

ABSTRACT:

Background

T cells are crucial for immunosurveillance and tumor eradication, with their dysregulation or absence in the tumor microenvironment linked to immunotherapy resistance. In lung adenocarcinoma (LUAD), this resistance is a significant barrier to effective treatment, highlighting the need for robust biomarkers and therapeutic targets to improve clinical outcomes.

Methods

T cell-related markers were identified through single-cell RNA sequencing analysis. The TCGA dataset was used for consensus clustering to define molecular subtypes associated with distinct survival outcomes and immune profiles. A T cell-related prognostic signature was developed by integrating LUAD datasets from TCGA, GSE31210, GSE50081, and GSE68465 using 10 machine learning algorithms. Further analy

SUBMITTER: Liu S 

PROVIDER: S-EPMC12002896 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature