Evidence map›Paper›PMID 42268298›Full record

ArticleCancer research2026

Circulating Cell-Free DNA Methylation Profiling Enables Detection, Distinction, and Estrogen Receptor Status Classification of Advanced Breast Cancer.

Sasha C Main, Mitchell J Elliott, Althaf Singhawansa, Jinfeng Zou, Yong Zeng, Nicholas Cheng, Celeste Yu, John F Hilton, Philip Awadalla, Housheng H He and 4 more

Abstract read
In one paragraph

Article in Cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Sasha C Main *Princess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0003-2167-8323
Mitchell J Elliott *Princess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0001-6711-7287
Althaf Singhawansa *Princess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0009-0008-2985-4794
Jinfeng ZouPrincess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0002-4309-0961
Yong ZengPrincess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0001-5719-1272
Nicholas ChengOntario Institute for Cancer Research , Toronto, Canada.ORCID 0009-0007-9174-1099
Celeste YuDivision of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada.ORCID 0000-0002-8764-1091
John F HiltonDivision of Medical Oncology, Ottawa Hospital Cancer Centre, Ottawa, Canada.ORCID 0000-0002-6280-8633
Philip AwadallaDepartment of Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-9946-6393
Housheng H HePrincess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0003-2898-3363
Philippe L BedardDivision of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada.ORCID 0000-0002-6771-2999
Mathieu LupienPrincess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0003-0929-9478
Scott V BratmanPrincess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0001-8610-4908
David W CesconDivision of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada.ORCID 0000-0002-1080-0998

Funding

Breast Cancer Research Foundation (BCRF)Canadian Association of Medical Oncologists (CAMO)Canadian Cancer Society (CCS) 708002Canadian Institutes of Health Research (CIHR)Canadian Institutes of Health Research (CIHR) FRN-153234Canadian Institutes of Health Research (CIHR) FRN-158225Canadian Institutes of Health Research (CIHR) FRN-168933Canadian Institutes of Health Research (CIHR) FRN-191847Canadian Institutes of Health Research (CIHR) FRN-198247Conquer Cancer Foundation (CCF)Ontario Institute for Cancer Research (OICR) IA 031Ontario Institute for Cancer Research (OICR) P.AO.075Ontario Institute for Cancer Research (OICR) P.OCT.051Princess Margaret Cancer Foundation (PMCF)Susan G. Komen (SGK)University of Toronto (UofT)
6 · The paper itself

Abstract

The management of metastatic breast cancer (mBC) relies on tissue-based immunohistochemical subtypes. However, biopsies are invasive and may not capture metastatic heterogeneity, and subtypes can change over time under treatment pressure. In this study, we developed cell-free DNA (cfDNA) methylation signatures for minimally invasive breast cancer detection, distinction, and estrogen receptor (ER) status classification. Peripheral blood plasma methylomes were analyzed from 79 patients with mBC spanning ER+/human epidermal growth factor receptor 2 (HER2)- (n = 45), HER2+ (n = 13), and triple-negative breast cancer (n = 21). To derive tissue-informed breast cancer and ER-specific features, public 450K methylation array data (n = 9,730) were leveraged, and features were selected using generalized linear models via elastic net regularization with cross-validation. The tissue-informed features were translated to cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq), and the final signatures were validated across a compendium of cfMeDIP-seq profiles (n = 713) spanning more than 10 cancer types. Across training, validation, and external test cohorts, the signatures demonstrated high accuracy for breast cancer detection versus controls, distinction from multiple other malignancies, and ER status classification. Performance generalized across independent cfMeDIP-seq cohorts and reflected tumor fraction. The sensitivity was reduced in samples with low tumor fractions and bone-only disease while remaining informative for typical tumor fractions observed in the metastatic setting. Promoter-proximal signature regions provided biological insight into tumor phenotypes. This tissue-anchored, platform-translatable framework demonstrates the feasibility of accurate, reproducible cfDNA methylation-based molecular classification in mBC. SIGNIFICANCE: Tissue-anchored cell-free DNA methylation signatures enable minimally invasive detection, cancer-type distinction, and estrogen receptor classification in metastatic breast cancer, offering an interpretable, cross-platform framework to complement tissue biopsies for guiding subtype-directed therapy.

Indexed as

Biomarkers, TumorBreast NeoplasmsCell-Free Nucleic AcidsDNA MethylationReceptors, EstrogenErb-b2 Receptor Tyrosine KinasesFemaleHumansMiddle AgedBiomarkers, TumorCell-Free Nucleic AcidsErb-b2 Receptor Tyrosine KinasesReceptors, Estrogen

Identifiers

PMID42268298
PMCPMC13535318

What OpenQuestion holds

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Registered trials

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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.