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 (3Ã). 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).
Cell-free DNA Fragmentomics Assay to Discriminate the Malignancy of Breast Nodules and Evaluate Treatment Response.
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作者:Liu ååç¦ Jiaqi, Li æäºä¼¦ Yalun, Tang åçæ¹å¤« Wanxiangfu, Qian é±å¤©ä¸ Tianyi, Dai 代丽å Lijun, Jia è´¾æ¢æ· Ziqi, Cao æ¹æ Heng, Li æææµ© Chenghao, Liu åç ç Yuchen, Huang é»å²©æ¾ Yansong, Wu å´ç Jiang, Ma 马䏿 Dongxu, Qiao ä¹å¹¿ä¸ Guangdong, Bao å å Hua, Chang 常å Shuang, Zhu æ±å¬ç´ Dongqin, Yang æ¨çç Shanshan, Wu å´å¾æè¾° Xuxiaochen, Wu å´éª Xue, Xu å¾ææ¯ Hengyi, Chen éæ´ªå²© Hongyan, Shao éµé³ Yang, Wang çç¿ Xiang, Liu åèå Zhihua, Su èå»ºå¿ Jianzhong
| 期刊: | Genomics Proteomics & Bioinformatics | 影响因子: | 7.900 |
| 时间: | 2025 | 起止号: | 2025 May 30; 23(2):qzaf028 |
| doi: | 10.1093/gpbjnl/qzaf028 | ||
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