Cell-free DNA Fragmentomics Assay to Discriminate the Malignancy of Breast Nodules and Evaluate Treatment Response

The fragmentomics-based cell-free DNA (cfDNA) assays have recently illustrated prominent abilities to identify various cancers from non-conditional healthy controls, while their accuracy for identifying early-stage cancers from benign lesions with inconclusive imaging results remains uncertain. Especially for breast cancer, current imaging-based screening methods suffer from high false positive rates for women with breast nodules, leading to unnecessary biopsies, which add to discomfort and healthcare burden. Here, we enrolled 613 female participants in this multi-center study and demonstrated that cfDNA fragmentomics (cfFrag) is a robust non-invasive biomarker for breast cancer using whole-genome sequencing. Among the multimodal cfFrag profiles, the fragment size ratio (FSR), fragment size distribution (FSD), and copy number variation (CNV) show more distinguishing ability than Griffin, motif breakpoint (MBP), and neomer. The cfFrag model using the optimal three fragmentomics features discriminated early-stage breast cancer from benign nodules, even at a low sequencing depth (3×). Notably, it demonstrated a specificity of 94.1% in asymptomatic healthy women at a 90% sensitivity for breast cancer. Moreover, we comprehensively showcased the clinical utility of the cfFrag model in predicting patient responses to neoadjuvant chemotherapy (NAC) and its enhanced performance when combined with multimodal features, including radiological results [area under the curve (AUC) = 0.93-0.94] and cfDNA methylation features (AUC = 0.96).

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Publication Details

Journal
Genomics Proteomics & Bioinformatics
Published
2025-04-01
DOI
https://doi.org/10.1093/gpbjnl/qzaf028
Citations
5
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
4.68

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article

Cell-free DNA Fragmentomics Assay to Discriminate the Malignancy of Breast Nodules and Evaluate Treatment Response

Dongqin Zhu, Yang Shao, Tianyi Qian, Xue Wu et al.
5 citations
Genomics Proteomics & Bioinformatics
Cancer Genomics and Diagnostics
4.68
article

Cell-free DNA Fragmentomics Assay to Discriminate the Malignancy of Breast Nodules and Evaluate Treatment Response

Dongqin Zhu, Yang Shao, Tianyi Qian, Xue Wu, Jianzhong Su, Wanxiangfu Tang, Xuxiaochen Wu, Guangdong Qiao, Dongxu Ma, Hua Bao, Yuchen Liu, Hongyan Chen, Jiaqi Liu, Zhihua Liu, Xiang Wang, Yan Huang, Shanshan Yang, Shuang Chang, Yalun Li, Ziqi Jia, Hengyi Xu, Jiang Wu, Lijun Dai, Chenghao Li, Heng Cao
article en
5 citations

Abstract

The fragmentomics-based cell-free DNA (cfDNA) assays have recently illustrated prominent abilities to identify various cancers from non-conditional healthy controls, while their accuracy for identifying early-stage cancers from benign lesions with inconclusive imaging results remains uncertain. Especially for breast cancer, current imaging-based screening methods suffer from high false positive rates for women with breast nodules, leading to unnecessary biopsies, which add to discomfort and healthcare burden. Here, we enrolled 613 female participants in this multi-center study and demonstrated that cfDNA fragmentomics (cfFrag) is a robust non-invasive biomarker for breast cancer using whole-genome sequencing. Among the multimodal cfFrag profiles, the fragment size ratio (FSR), fragment size distribution (FSD), and copy number variation (CNV) show more distinguishing ability than Griffin, motif breakpoint (MBP), and neomer. The cfFrag model using the optimal three fragmentomics features discriminated early-stage breast cancer from benign nodules, even at a low sequencing depth (3×). Notably, it demonstrated a specificity of 94.1% in asymptomatic healthy women at a 90% sensitivity for breast cancer. Moreover, we comprehensively showcased the clinical utility of the cfFrag model in predicting patient responses to neoadjuvant chemotherapy (NAC) and its enhanced performance when combined with multimodal features, including radiological results [area under the curve (AUC) = 0.93-0.94] and cfDNA methylation features (AUC = 0.96).

Genomics Proteomics & BioinformaticsVol. 23(2)
Qingdao University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Wenzhou Medical University (CN), Peking Union Medical College Hospital (CN), Yuhuangding Hospital (CN), Nanjing University of Science and Technology (CN), Affiliated Eye Hospital of Wenzhou Medical College (CN), Affiliated Hospital of Qingdao University (CN), Zhejiang Lab (CN), National Clinical Research (US), Molecular Oncology (United States) (US), Second Affiliated Hospital of Zhejiang University (CN)
National Natural Science Foundation of China, Beijing Nova Program
Openalex Percentile: Top 5%
Cancer Genomics and Diagnostics
4.68
DOIOpen Access PDFOpenAlex
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