PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 9, 2026Open Medicine0 citationsOpen Access

Comprehensive analysis of m6A RNA methylation regulators for prognostic risk stratification and immune microenvironment characterization in colorectal cancer

FKFei-Fei KongJFJ FengJLJing-Ya Liu

Key Points

  • This research aims to investigate m6A RNA methylation patterns and their implications for prognosis and immune microenvironment in colorectal cancer.
  • Analyzed 27 m6A regulators in 488 CRC samples and 42 normal controls from TCGA, with validation in 762 additional samples.
  • Implemented consensus clustering to identify distinct m6A modification patterns.
  • Developed a prognostic risk model using multivariate Cox regression based on 268 m6A-associated genes.
  • 24 of 27 m6A regulators showed significant differential expression (p<0.001).
  • Identified ZC3H13, LRPPRC, and IGFBP3 as independent prognostic factors through multivariate analysis.
  • The risk model demonstrated performance across validation cohorts (HR: 8.59–14.27, p<0.0001), especially in early-stage patients.

Abstract

Abstract Objectives Despite mounting evidence of N6-methyladenosine (m6A) dysregulation in colorectal cancer (CRC), comprehensive prognostic association analysis remains limited. We systematically investigated m6A modification patterns and developed a robust risk stratification model. Methods We analyzed 27 m6A regulators in 488 CRC samples and 42 normal controls from TCGA, with external validation in two independent cohorts (n=762). Consensus clustering identified distinct m6A modification patterns. A prognostic risk model incorporating 268 m6A-associated genes was constructed using multivariate Cox regression. Results 24 of 27 m6A regulators exhibited significant differential expression (p<0.001). Multivariate analysis identified ZC3H13, LRPPRC, and IGFBP3 as independent prognostic factors. The risk model showed exceptional performance across all validation cohorts (HR: 8.59–14.27, p<0.0001), maintaining significance in early-stage patients. High-risk patients exhibited significantly elevated PD-L1 expression levels (p=5.7 × 10 −9 to 5 × 10 −7 ) and altered immune cell infiltration patterns. Conclusions Our findings reveal pervasive m6A dysregulation with superior predictive performance compared to conventional approaches. The links between RNA methylation and tumor immunity establish m6A signatures as actionable biomarkers for precision oncology.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Kong et al. (2026) studied this question.

synapsesocial.com/papers/69fecfe9b9154b0b82876f29https://doi.org/10.1515/med-2025-1318
Ask AI
Helpful
Bookmark
Share
View Full Paper