Subtype-Specific m(6)A circRNA Methylation Patterns Identify Epigenetic Biomarker Candidates of Potential Diagnostic and Prognostic Significance in Breast Cancer

亚型特异性m(6)A环状RNA甲基化模式可识别乳腺癌中具有潜在诊断和预后意义的表观遗传生物标志物候选物

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Abstract

Breast cancer subtypes are known to have important pathobiological and clinical features. For example, triple-negative breast cancer (TNBC) remains one of the most aggressive and treatment-resistant breast cancer subtypes, lacking hormone and HER2 targets. Increasing evidence suggests that circular RNAs (circRNAs) and their N6-methyladenosine (m(6)A) modifications play critical roles in cancer biology through the regulation of gene expression, stability, and signaling networks. This study aimed to identify m(6)A methylation patterns in circRNAs among breast cancer subtypes, explore their potential biological functions, and assess their diagnostic and prognostic relevance compared with luminal breast cancer subtypes. Genome-wide profiling of m(6)A-modified circRNAs was conducted in TNBC and luminal breast tumor samples using methylated RNA immunoprecipitation followed by microarray analysis. Differential methylation and expression analyses were integrated with pathway enrichment, survival correlation, and receiver operating characteristic (ROC) curve assessments to identify subtype-specific and clinically relevant circRNA candidates. Distinct m(6)A circRNA methylation signatures were identified across breast cancer subtypes, with TNBC showing enrichment in pathways related to Wnt/β-catenin, CDC42 GTPase signaling, and cytoskeletal remodeling. Several circRNAs, including those derived from ZBTB16, DOCK1, METTL8, and VAV3, exhibited significant hypermethylation and high diagnostic accuracy (AUC > 0.80). Survival analyses revealed associations between circRNAs from key host genes and overall or relapse-free survival, suggesting prognostic potential. These findings uncover subtype-specific m(6)A circRNA methylation landscapes that may contribute to tumor aggressiveness and heterogeneity. Identified circRNAs represent candidates for investigation as biomarkers for subtype classification and prognosis and may inform future research into epigenetic and post-transcriptional therapeutic targets in breast cancer.

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