Evidence map›Paper›PMID 40118933›Full record

ArticleNature communications2025

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 and 15 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Shunying Li *Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Yudong Li *Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Wei Wei *Department of Breast and Thyroid Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong Province, China.
Chang Gong *Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0001-5215-7497
Ting Wang *Department of thyroid, breast and vascular surgery, Xijing Hospital, The Air Force Medical University, Xi'an, China.
Guangxin LiDepartment of Breast and Thyroid Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong Province, China.
Feng YaoDepartment of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, China.
Jiang-Hua OuDepartment of Breast Surgery, Xinjiang Cancer Hospital, Xinjiang Medical University, Urumqi, China.
Yan XuDepartment of Breast and Thyroid Surgery, Daping Hospital, Army Military Medical University, Chongqing, China.
Wei WuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Liang JinGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0002-0968-546X
Nanyan RaoGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Yan NieGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0002-8111-6050
Fengyan YuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Weijuan JiaGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Xing-Rui LiDepartment of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Jun ZhangDepartment of Thyroid and Breast Surgery, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, China.
Hua-Wei YangDepartment of Breast Surgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Yaping YangGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Mengzi WuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Qin LiGeneplus-Beijing Institute, Beijing, China.ORCID http://orcid.org/0009-0005-8781-4406
Fang LiGeneplus-Beijing Institute, Beijing, China.
Yuhua GongGeneplus-Beijing Institute, Beijing, China.ORCID http://orcid.org/0000-0001-7893-2084
Xin YiGeneplus-Beijing Institute, Beijing, China.
Qiang LiuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. liuq77@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-5451-4862

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82061148016National Natural Science Foundation of China (National Science Foundation of China) 82102729National Natural Science Foundation of China (National Science Foundation of China) 82203087National Natural Science Foundation of China (National Science Foundation of China) 82230057National Natural Science Foundation of China (National Science Foundation of China) 82272859
6 · The paper itself

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.

Indexed as

Circulating Tumor DNANeoplasm Recurrence, LocalTriple Negative Breast NeoplasmsAdultAgedBiomarkers, TumorFemaleHumansMiddle AgedNeoadjuvant TherapyPrognosisProspective StudiesTumor BurdenBiomarkers, TumorCirculating Tumor DNA

Identifiers

PMID40118933
PMCPMC11928511

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.