Interpretable deep cross networks unveiled common signatures of dysregulated epitranscriptomes across 12 cancer types.

ABSTRACT: Cancer is a complex and multifaceted group of diseases characterized by uncontrolled cell growth that leads to the formation of malignant tumors. Recent studies suggest that N6-methyladenosine (m6A) RNA methylation plays pivotal roles in cancer pathology by influencing various cellular processes. However, the degree to which these mechanisms are shared across different cancer types remains unclear. In this study, we analyze an expansive array of 167 m6A epitranscriptome profiles covering 12 distinct cancer types and their originating normal tissues. We trained 12 distinct, cancer type-specific interpretable deep cross network models, which successfully distinguish between specific pairs of normal and cancer m6A contexts using integrated information from both the sequences and curated genom

SUBMITTER: Xia R 

PROVIDER: S-EPMC11605186 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature