Integration of 101 machine learning algorithm combinations to unveil m6A/m1A/m5C/m7G-associated prognostic signature in colorectal cancer.

ABSTRACT: Colorectal cancer (CRC) is the most common malignancy in the digestive system, with a lower 5-year overall survival rate. There is increasing evidence showing that RNA modification regulators such as m1A, m5C, m6A, and m7G play crucial roles in tumor progression. However, the prognostic role of integrated m6A/m5C/m1A/m7G methylation modifications in CRC has not been reported and requires further investigation. Five cohorts with 989 samples were first retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Then, Three m6A/m1A/m5C/m7G-associated molecular subtypes were identified in the TCGA cohort via the consensus clustering analysis, and 1710 co-expression module genes associated with subtypes were obtained from weighted gene co-expression network analys

SUBMITTER: Wei H 

PROVIDER: S-EPMC11836460 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature