Dynamic ctDNA tracking stratifies relapse risk for triple negative breast cancer patients receiving neoadjuvant chemotherapy

Shunying Li, Yudong Li, Wei Wei, Chang Gong, Ting Wang, Guangxin Li, Feng Yao, Jiang-Hua Ou, Yan Xu, Wei Wu, Liang Jin, Nanyan Rao, Yan Nie, Fengyan Yu, Weijuan Jia, Xing-Rui Li, Jun Zhang, Hua-Wei Yang, Yaping Yang, Mengzi Wu, Qin Li, Fang Li, Yuhua Gong, Xin Yi and Qiang Liu ()
Additional contact information
Shunying Li: Sun Yat-sen University
Yudong Li: Sun Yat-sen University
Wei Wei: Peking University Shenzhen Hospital
Chang Gong: Sun Yat-sen University
Ting Wang: The Air Force Medical University
Guangxin Li: Peking University Shenzhen Hospital
Feng Yao: Renmin Hospital of Wuhan University
Jiang-Hua Ou: Xinjiang Medical University
Yan Xu: Army Military Medical University
Wei Wu: Sun Yat-sen University
Liang Jin: Sun Yat-sen University
Nanyan Rao: Sun Yat-sen University
Yan Nie: Sun Yat-sen University
Fengyan Yu: Sun Yat-sen University
Weijuan Jia: Sun Yat-sen University
Xing-Rui Li: Tongji Medical College of Huazhong University of Science and Technology
Jun Zhang: Shenzhen Qianhai Shekou Free Trade Zone Hospital
Hua-Wei Yang: Guangxi Medical University Cancer Hospital
Yaping Yang: Sun Yat-sen University
Mengzi Wu: Sun Yat-sen University
Qin Li: Geneplus-Beijing Institute
Fang Li: Geneplus-Beijing Institute
Yuhua Gong: Geneplus-Beijing Institute
Xin Yi: Geneplus-Beijing Institute
Qiang Liu: Sun Yat-sen University

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract Early Triple negative breast cancer (eTNBC) is the subtype with the worst outcome. Circulating tumor DNA (ctDNA) is shown to predict the prognosis of breast cancer, but its utility in eTNBC remains unclear. 130 stage II-III female eTNBC patients receiving neoadjuvant chemotherapy (NAC) have been enrolled prospectively and subjected to ctDNA analysis. ctDNA at post-NAC (pre-surgery) and post-surgery, but not at baseline, is associated with worse prognosis. A threshold of 1.1% maximum variant allele frequency at baseline stratifies patients with different relapse risk, which is validated internally and externally. A systemic tumor burden model integrating baseline and post-surgery ctDNA is independently prognostic (p = 0.022). Combining systemic tumor burden with pathologic response identifies a highly curable subgroup and a subgroup of high-risk eTNBC patients. ctDNA surveillance during follow-up identifies patients with high relapse risk. In conclusion, systemic ctDNA analysis demonstrates the utility of a systemic tumor burden model of ctDNA in risk stratification of eTNBC patients, which may guide future treatment escalation or de-escalation trials.

Date: 2025
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DOI: 10.1038/s41467-025-57988-z

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