Evidence map›Paper›PMID 40539820›Full record

ArticleCancer medicine2025

An Approach for Differential Diagnosis of Breast Tumors by ctDNA Methylation Sequencing.

Xianyu Zhang, Yanling Yin, Zhujia Ye, Xingda Zhang, Wei Wei, Yi Hao, Liuhong Zeng, Ting Yang, Dalin Li, Jun Wang and 17 more

Abstract read
In one paragraph

Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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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

27 authors.

Xianyu ZhangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Yanling YinDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Zhujia YeAnchorDx Medical Co., Ltd., Guangzhou, China.
Xingda ZhangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Wei WeiDepartment of Breast Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Yi HaoDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Liuhong ZengAnchorDx Medical Co., Ltd., Guangzhou, China.
Ting YangAnchorDx Medical Co., Ltd., Guangzhou, China.
Dalin LiDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.ORCID https://orcid.org/0000-0002-6474-5998
Jun WangAnchorDx Medical Co., Ltd., Guangzhou, China.
Dezhi ZhaoAnchorDx Medical Co., Ltd., Guangzhou, China.
Yanbo ChenDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Shan LeiAnchorDx Medical Co., Ltd., Guangzhou, China.
Yongdong JiangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Youxue ZhangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Shouping XuDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.ORCID https://orcid.org/0000-0001-6154-3381
Abiyasi NandingDepartment of Pathology, Harbin Medical University Cancer Hospital, Harbin, China.
Yajie GongDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Siwei LiDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Yuanyuan YuDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.ORCID https://orcid.org/0000-0003-0943-2267
Shilu ZhaoDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Siyu LiuDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Yashuang ZhaoDepartment of Epidemiology, Harbin Medical University, Harbin, China.ORCID https://orcid.org/0000-0002-7425-5773
Zhiwei ChenAnchorDx Medical Co., Ltd., Guangzhou, China.
Shihui YuGuangzhou Kingmed Center for Clinical Laboratory Co., Ltd., Guangzhou, China.
Jian-Bing FanAnchorDx Medical Co., Ltd., Guangzhou, China.
Da PangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.ORCID https://orcid.org/0000-0003-2853-4170

Funding

2020 Guangzhou Development Zone International Science and Technology Cooperation Project 2020GH15China National Science Foundation 82073410China National Science Foundation 82173235China National Science Foundation 82272623Guangzhou Basic and Applied Basic Research Project 202201010943Haiyan Foundation of Harbin Medical University Cancer Hospital JJZD2020-08Heilongjiang Province Applied Technology Research and Development GA20C016Key R&D Plan Projects of Heilongjiang Province, Da Pang JD22C004Key Special Projects of Heilongjiang Province Key Research and Development Program 2023ZX06C10Nn10 Program of Harbin Medical University Cancer Hospital Nn10Scheme of Guangzhou Economic and Technological Development District for Leading Talents in Innovation and Entrepreneurship 2017-L152Scheme of Guangzhou for Leading Talents in Innovation and Entrepreneurship 2016007Scheme of Guangzhou for Leading Team in Innovation 201909010010Science and Technology Program of Guangdong Province 2019B121205010
6 · The paper itself

Abstract

backgroundBreast ultrasonography and mammography remain predominant in breast tumor evaluations, yet they often result in false positives, particularly for tumors classified as BI-RADS 4a or those no more than 10 mm, which are not ideal for core needle biopsy (CNB). Early-stage breast cancer detection via circulating tumor DNA (ctDNA) methylation holds potential to bridge these diagnostic gaps.

methodsWe curated a breast cancer-specific panel by harnessing methylation profiles from in-house and public databases. Leveraging breast tissue-plasma-leukocyte samples, we identified breast cancer-specific markers, culminating in a 103-marker methylation model which underwent rigorous validation in two independent cohorts. To assess its performance, we compared it against the accuracy of ultrasonography, mammography, and CNB.

resultsThe 103-marker model exhibited remarkable proficiency in discerning benign from malignant breast tumors in plasma, with AUCs of 0.838, 0.838 and 0.823 in the validation set and two independent test sets, respectively. In BI-RADS 4a breast cancer, when compared to ultrasonography or mammography, the model augmented breast cancer diagnostic accuracy by 40.58% and 25.49%, separately. Retrospective analyses suggested that our model achieved a sensitivity of 66.67% (4/6) and a specificity of 80.36% (45/56) for surgical patients in the BI-RADS 4a category with tumors ≤ 10 mm, who did not undergo CNB, potentially sparing 45 benign patients from overtreatment. Notably, significant differences emerged in cancer scores between DCIS and invasive ductal carcinoma (p < 0.05). Higher cancer scores correlated with a more unfavorable prognosis (p < 0.05).

conclusionsThe 103-marker methylation model demonstrates impressive performance in distinguishing between malignant and benign tumors, facilitating precise early diagnosis of BC, and holds promise as a prognostic tool.

Indexed as

Biomarkers, TumorBreast NeoplasmsCirculating Tumor DNADNA MethylationAdultAgedDiagnosis, DifferentialFemaleHumansMammographyMiddle AgedBiomarkers, TumorCirculating Tumor DNAbreast cancerbreast ultrasonographycore needle biopsyctDNAmammographymethylation

Identifiers

PMID40539820
PMCPMC12180084

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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.