A multi-omic machine learning approach deconstructs the role of amino acid metabolism in the immune microenvironment and prognosis of colon adenocarcinoma.

ABSTRACT:

Background

The clinical heterogeneity of colon adenocarcinoma (COAD) complicates patient prognosis and treatment. While metabolic reprogramming is a key driver of tumor progression, the role of histidine metabolism in the COAD immune microenvironment remains unclear.

Methods

Through an integrated analysis of public single-cell and bulk transcriptomic data, we mapped the COAD cellular atlas and assessed histidine metabolism activity. A prognostic Histidine Metabolism-related Model (HRM) was constructed using an ensemble of 101 machine learning algorithms, and its biological underpinnings were explored. The function of the key gene, TRIP6, was validated via in vitro experiments.

Results

Single-cell analysis identified epithelial cells as the hub of histidine meta

SUBMITTER: Zhong H 

PROVIDER: S-EPMC12719496 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature