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乳腺癌中染色体外环状DNA的诊断和预后价值研究

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

作者信息

Li Fuyu, Lu Wenxiang, Yao Lingsong, Bai Yunfei

机构信息

State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.

出版信息

Genes (Basel). 2025 Jul 6;16(7):802. doi: 10.3390/genes16070802.

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.

摘要

目的

为研究染色体外环状DNA(eccDNA)在乳腺癌中的临床诊断和预后价值,构建了81例乳腺癌肿瘤组织和33例癌旁非肿瘤组织的eccDNA图谱。

方法

系统分析了eccDNA在功能基因组元件和重复序列中的分布特征。此外,使用随机森林算法建立了区分乳腺恶性组织和正常组织的诊断模型以及预后预测模型。

结果

乳腺癌组织中的eccDNA含有更高比例的功能元件和重复序列,其注释基因在肿瘤和免疫相关途径中显著富集。然而,在不同乳腺癌亚型或病理分期中,未观察到eccDNA特征的显著差异。在验证队列中,基于eccDNA的诊断模型的曲线下面积(AUC)为0.83,其中重复元件和增强子相关特征对诊断性能的贡献最大。预后模型的AUC为0.78,重复元件注释也显示出很强的预后相关性。

结论

这些发现凸显了eccDNA在乳腺癌精准诊断和预后系统开发中的潜在应用前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b508/12295733/0516255dc0fa/genes-16-00802-g001.jpg

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