Machine learning-based comprehensive analysis of m6A RNA methylation regulators in colorectal cancer: implications for prognosis, immune microenvironment, and immunotherapy response.

ABSTRACT: N6-methyladenosine (m6A) RNA methylation regulators have been implicated in colorectal cancer (CRC) progression. However, systematic evaluation using multiple machine learning approaches for prognostic prediction remains limited. This study aimed to develop and validate machine learning models for CRC prognosis based on m6A regulators and assess their potential for immunotherapy response prediction. We analyzed 1,047 CRC patients from TCGA and GEO databases (70% training, 30% validation). Twenty machine learning algorithms were systematically evaluated, with LASSO regression selecting optimal features from 27 m6A regulators. SHAP analysis provided model interpretability. Immune microenvironment characterization and immunotherapy response prediction were performed using established computat

SUBMITTER: Kong F 

PROVIDER: S-EPMC12847061 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature