m6A regulator-based methylation modification patterns characterized by distinct tumor microenvironment immune profiles in colon cancer

Recent studies have highlighted the biological significance of RNA N-6-methyladenosine (m(6)A) modification in tumorigenicity and progression. However, it remains unclear whether m(6)A modifications also have potential roles in immune regulation and tumor microenvironment (TME) formation. Methods: In this study, we curated 23 m(6)A regulators and performed consensus molecular subtyping with NMF algorithm to determine m(6)A modification patterns and the m(6)A-related gene signature in colon cancer (CC). The ssGSEA and CIBERSORT algorithms were employed to quantify the relative infiltration levels of various immune cell subsets. An PCA algorithm based m(6)Sig scoring scheme was used to evaluate the m(6)A modification patterns of individual tumors with an immune response. Results: Three distinct m(6)A modification patterns were identified among 1307 CC samples, which were also associated with different clinical outcomes and biological pathways. The TME characterization revealed that the identified m(6)A patterns were highly consistent with three known immune profiles: immune-inflamed, immune-excluded, and immune-desert, respectively. Based on the m(6)Sig score, which was extracted from the m(6)A-related signature genes, CC patients can be divided into high and low score subgroups. Patients with lower m(6)Sig score was characterized by prolonged survival time and enhanced immune infiltration. Further analysis indicated that lower m(6)Sig score also correlated with greater tumor mutation loads, PD-L1 expression, and higher mutation rates in SMGs (e.g., PIK3CA and SMAD4). In addition, patients with lower m(6)Sig scores showed a better immune responses and durable clinical benefits in three independent immunotherapy cohorts. Conclusions: This study highlights that m(6)A modification is significantly associated with TME diversity and complexity. Quantitatively evaluating the m(6)A modification patterns of individual tumors will strengthen our understanding of TME characteristics and promote more effective immunotherapy strategies.