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Updated: Jun 11, 2026
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Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
Published on: March 17, 2016
Circulating Cell-Free DNA Methylation Profiling Enables Detection, Distinction, and Estrogen Receptor Status
Sasha C Main1, Mitchell J Elliott2, Althaf Singhawansa3
1University of Toronto Toronto, Ontario Canada.
Cancer Research
|June 10, 2026
Summary
This study introduces cell-free DNA (cfDNA) methylation signatures for non-invasive breast cancer (BC) detection and estrogen receptor (ER) status classification. These minimally invasive biomarkers offer accurate molecular profiling for metastatic breast cancer (mBC) management.
Area of Science:
- Epigenetics and Molecular Oncology
- Liquid Biopsy and Cancer Diagnostics
Background:
- Metastatic breast cancer (mBC) management traditionally relies on invasive tissue biopsies for subtype classification.
- Tissue biopsies have limitations including invasiveness, potential to miss metastatic heterogeneity, and dynamic subtype changes under treatment.
- There is a need for minimally invasive methods to accurately detect and classify breast cancer subtypes.
Purpose of the Study:
- To develop cell-free DNA (cfDNA) methylation signatures for minimally invasive detection and ER status classification of breast cancer (BC).
- To create tissue-informed methylation features translatable to cell-free DNA analysis.
- To validate the accuracy and reproducibility of cfDNA methylation signatures across diverse cohorts and cancer types.
Main Methods:
- Analyzed peripheral blood plasma methylomes from 79 patients with mBC.
- Leveraged public methylation array data (n=9730) to derive tissue-informed BC and ER-specific features using generalized linear models with elastic net regularization (GLMnet).
- Translated tissue-informed features to cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq) and validated signatures across 713 cfMeDIP-seq profiles spanning multiple cancer types.
Main Results:
- Developed cfDNA methylation signatures demonstrating high accuracy for BC detection versus controls and distinction from other malignancies.
- Achieved accurate estrogen receptor (ER) status classification using cfDNA methylation signatures.
- Validated signature performance across independent cfMeDIP-seq cohorts, showing generalization and reflection of tumor fraction, with reduced sensitivity in low tumor fraction and bone-only disease.
Conclusions:
- Tissue-anchored and platform-translatable cfDNA methylation signatures enable accurate and reproducible molecular classification of mBC.
- This minimally invasive approach facilitates BC detection, distinction from other cancers, and ER status classification.
- The developed framework shows significant potential for advancing non-invasive diagnostics and personalized treatment strategies in metastatic breast cancer.
