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全基因组发现循环游离DNA甲基化特征用于三阴性乳腺癌的鉴别诊断

Genome-wide discovery of circulating cell-free DNA methylation signatures for the differential diagnosis of triple-negative breast cancer.

作者信息

Gao Lijing, Li Yanbing, Qu Chao, Dong Yan, Fu Qingzhen, Zhou Haibo, Zhao Ning, Zhang Xianyu, Pang Da, Zhao Yashuang

机构信息

Department of Epidemiology, Harbin Medical University, Harbin, Heilongjiang, China.

Department of Breast Surgery, Harbin Medical University, Harbin, Heilongjiang, China.

出版信息

PeerJ. 2025 Aug 20;13:e19888. doi: 10.7717/peerj.19888. eCollection 2025.

Abstract

BACKGROUND

Preoperative identification of breast cancer (BC) subtypes is essential for optimizing treatment strategies and improving patient outcomes. This study aimed to identify circulating cell-free DNA (cfDNA) methylation signatures to differentiate triple-negative breast cancer (TNBC) from other BC subtypes (non-TNBC).

METHODS

We initially performed a genome-wide analysis to identify differentially methylated CpG sites (DMCs; |Δ| > 0.10 and < 0.05) between five TNBC and nine non-TNBC tissues using the Infinium HumanMethylationEPIC BeadChip. These DMCs were further validated using large-scale data from the Cancer Genome Atlas (TCGA, = 774; |Δ| > 0. 25 and < 0.05), and only CpG sites with average values > 0.90 or < 0.10 in white blood cells (GSE50132, = 233) were retained to minimize potential background methylation interference. Least absolute shrinkage and selection operator (LASSO) regression was applied to select optimal markers. Diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC), and prognostic value was evaluated using Cox regression analysis. A multiplex digital droplet PCR (mddPCR) assay was developed to simultaneously detect cg06268921 and cg23247845 in cfDNA from TNBC ( = 33) and non-TNBC ( = 80) patients.

RESULTS

We identified 113 DMCs, of which eight were selected as optimal markers. They effectively discriminated TNBC from non-TNBC tissues. Then an eight-marker diagnostic panel was developed with an AUC of 0.922 in TCGA and 0.875 in GSE69914. Among them, cg06268921 was significantly associated with overall survival (hazard ratio = 0.249, = 0.044) and disease-free survival (hazard ratio = 0.194, = 0.015) in the TCGA-TNBC cohort. In the cfDNA cohort, cg06268921 significantly differentiated TNBC from non-TNBC ( < 0.001), and the combination of both markers yielded an AUC of 0.728. The findings demonstrated the potential of methylation signatures as non-invasive diagnostic tools for TNBC. Future research with larger cohorts is warranted.

摘要

背景

术前识别乳腺癌(BC)亚型对于优化治疗策略和改善患者预后至关重要。本研究旨在识别循环游离DNA(cfDNA)甲基化特征,以区分三阴性乳腺癌(TNBC)与其他BC亚型(非TNBC)。

方法

我们最初使用Infinium HumanMethylationEPIC BeadChip对5例TNBC组织和9例非TNBC组织进行全基因组分析,以识别差异甲基化的CpG位点(DMCs;|Δ|>0.10且P<0.05)。这些DMCs使用来自癌症基因组图谱(TCGA,n=774;|Δ|>0.25且P<0.05)的大规模数据进一步验证,并且仅保留在白细胞中平均甲基化值>0.90或<0.10的CpG位点(GSE50132,n=233),以尽量减少潜在的背景甲基化干扰。应用最小绝对收缩和选择算子(LASSO)回归来选择最佳标志物。通过受试者操作特征曲线(AUC)下的面积评估诊断性能,并使用Cox回归分析评估预后价值。开发了一种多重数字液滴PCR(mddPCR)检测方法,以同时检测TNBC(n=33)和非TNBC(n=80)患者cfDNA中的cg06268921和cg23247845。

结果

我们识别出113个DMCs,其中8个被选为最佳标志物。它们有效地将TNBC与非TNBC组织区分开来。然后开发了一个八标志物诊断面板,在TCGA中的AUC为0.922,在GSE69914中的AUC为0.875。其中,cg06268921与TCGA-TNBC队列中的总生存期(风险比=0.249,P=0.044)和无病生存期(风险比=0.194,P=0.015)显著相关。在cfDNA队列中,cg06268921显著区分TNBC与非TNBC(P<0.001),两种标志物的组合产生的AUC为0.728。这些发现证明了甲基化特征作为TNBC非侵入性诊断工具的潜力。未来需要更大队列的研究。

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