A Study on the Diagnostic and Prognostic Value of Extrachromosomal Circular DNA in Breast Cancer

TL;DR

This study explores how extrachromosomal circular DNA (eccDNA) can help diagnose and predict outcomes in breast cancer patients.

Contribution

The study introduces a novel diagnostic and prognostic model based on eccDNA features in breast cancer.

Findings

EccDNA in breast cancer tissues contains more functional elements and repetitive sequences linked to tumor and immune pathways.

The diagnostic model using eccDNA achieved an AUC of 0.83, with repetitive elements and enhancer features being most informative.

The prognostic model reached an AUC of 0.78, showing that repetitive elements are strongly associated with patient outcomes.

Abstract

Objectives: To investigate the clinical diagnostic and prognostic value of extrachromosomal circular DNA (eccDNA) in breast cancer, eccDNA profiles were constructed for 81 breast cancer tumor tissues and 33 adjacent non-tumor tissues. Methods: The distribution characteristics of eccDNA across functional genomic elements and repetitive sequences were systematically analyzed. Furthermore, a diagnostic model for differentiating malignant and normal breast tissues, as well as a prognostic prediction model, was developed using a random forest algorithm. Results: EccDNA in breast cancer tissues harbor a higher proportion of functional elements and repetitive sequences, with their annotated genes significantly enriched in tumor- and immune-related pathways. However, no significant differences in eccDNA features were observed across breast cancer subtypes or pathological stages. In the validation cohort, the eccDNA-based diagnostic model achieved an AUC of 0.83, with repetitive elements and enhancer-associated features contributing the most to diagnostic performance. The prognostic model achieved an AUC of 0.78, with repetitive element annotations also showing strong prognostic relevance. Conclusions: These findings highlight the promising potential of eccDNA in the development of precision diagnostics and prognostic systems for breast cancer.

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