A Machine Learning-Derived Taurine Metabolism Signature Predicts Prognosis and Immune Landscape in Lung Adenocarcinoma via Integrative Single-Cell Analysis.

ABSTRACT:

Background

Lung adenocarcinoma (LUAD) represents a biologically diverse tumor type, often associated with unfavorable prognosis and unsatisfactory therapeutic outcomes. Over the past few years, increasing attention has been given to metabolic alterations as key contributors to cancer development. Nevertheless, the specific contribution of taurine-related metabolic pathways in LUAD remains unclear. By constructing a model from taurine metabolism-associated genes, we aimed to elucidate its mechanistic basis and evaluate its relevance to clinical outcomes.

Methods

Transcriptomic profiles and clinical annotations from TCGA along with five LUAD datasets from the GEO repository were comprehensively integrated. A risk score indicative of taurine metabolism-associated signature (tau

SUBMITTER: Wang M 

PROVIDER: S-EPMC12672081 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature