Abstract PS2-07-05: Methylation-based ctDNA Dynamics as a Biomarker for Treatment Response and Prognosis in Patients on the plasmaMATCH trial

Abstract Background: Early assessment of circulating tumour DNA (ctDNA) dynamic changes on treatment predict response to therapy. Previous studies have tracked mutations in plasma, which requires prior knowledge of the tumour mutations and is also at risk of false results such as tracking mutations arising from clonal haematopoesis. We have developed a robust tumour agnostic ctDNA assay that tracks the level of aberrant breast cancer specific DNA methylation in plasma. We assessed the potential of baseline and early on-treatment changes in breast cancer ctDNA methylation levels, to predict progression-free survival (PFS) and objective response rate (ORR) to therapy. Methods: Patients enrolled on the plasmaMATCH trial with matched cycle 1-day1 (C1D1) and cycle 2-day 1 (C2D1) plasma samples available for analysis were included. PlasmaMATCH was a phase 2 platform trial which assessed the accuracy of ctDNA mutation testing in advanced breast cancer, and the ability of ctDNA testing to select patients for mutation-directed therapy. A capture based enzymatic ctDNA based methylation assay targeting 1297 differentially methylated regions (DMR), as well as specific promoters such as BRCA1, was used to distinguish the presence of breast cancer and the level of ctDNA. Tumour ctDNA levels were inferred by estimating the Methylation Read Percent (MPCT) based on the top 60 DMRs ranked on high entropy or high subtype methylation, with the circulating methylation ratio (CMR) calculated as the ratio of C2D1 MPCT / C1D1 MPCT. Patients with low CMR indicated lower ctDNA levels on treatment. We evaluated the association of baseline MPCT, and median change in CMR, with PFS and ORR. Cohorts A-D were analyzed together (ER-positive breast cancer on targeted therapy), with cohort E analysed separately (TNBC on olaparib PARP and ceralasertib ATR inhibitor combination). Results: We analysed C1D1/C2D1 matched samples from 74 patients for ctDNA methylation (30 from cohorts A-D and 44 from cohort E). All samples were successfully sequenced to a mean CpG coverage of 364x (range 89-975x). Splitting patients by median baseline MPCT was prognostic for PFS for cohort E: mPFS low MPCT 9 months v high 4 months (HR 0.52, 95% CI 0.26-1.02; p = 0.016), and ORR 36% (8/22) v 18% (4/22) (OR 2.56, 95% CI 1.36-4.96, p = 0.006). There was no association in Cohorts A-D: PFS HR 1.27, 95% CI 0.59-2.71, p = 0.463; ORR OR 1, 95% CI 0.49-2, p>0.99. In cohort A-D, splitting patients by median CMR dynamics was predictive of PFS; mPFS low CMR 6 months vs high CMR 2 months (HR 0.43, 95% CI 0.19-0.96; p = 0.008), and ORR 33% (5/15) vs 7% (1/15) (OR 6.54, 95% CI 2.85-16.57, p <0.0001). In cohort E splitting patients by median CMR was also highly predictive of PFS; mPFS low CMR 9 months vs high CMR 3 months (HR 0.47, 95% CI 0.24-0.94, p = 0.01), and ORR 45% (10/22) vs 9% (2/22) (OR 8.27, 95% CI 3.80-18.52, p <0.0001). In cohort E, 36% of patients (16/44) had detectable BRCA1 methylation at C1D1. There was no association between BRCA1 methylation and PFS (HR 0.92, 95% CI 0.47-1.82, p = 0.79), nor ORR (OR 0.86, 95% CI 0.43-1.50, p 0.633). Conclusions: Using a tumour agnostic breast cancer ctDNA methylation assay, we show that on treatment ctDNA methylation dynamics are predictive of response to targeted therapy. There was no association between BRCA1 methylation in ctDNA and outcomes, suggesting the sensitivity to PARP and ATR inhibition combination of cohort E was not mediated by BRCA1 methylation. Subject to further independent validation, ctDNA methylation dynamics may present a simple way to identify early patients who are responding to novel therapy combinations. Citation Format: I. M. Browne, R. J. Cutts, A. Amenssag, I. Garcia-Murillas, C. S. Swift, C. Loader, S. Hrebien, A. Pearson, J. Pascual, A. M. Wardley, M. Esteban-Garcia, L. S. Kilburn, I. R. MacPherson, R. D. Baird, R. Roylance, J. M. Bliss, A. E. Ring, N. C. Turner. Methylation-based ctDNA Dynamics as a Biomarker for Treatment Response and Prognosis in Patients on the plasmaMATCH trial [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-07-05.

Authors

Institutions

Publication Details

Journal
Clinical Cancer Research
Published
2026-02-17
DOI
https://doi.org/10.1158/1557-3265.sabcs25-ps2-07-05
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract PS2-07-05: Methylation-based ctDNA Dynamics as a Biomarker for Treatment Response and Prognosis in Patients on the plasmaMATCH trial

Javier Pascual, Isaac García-Murillas, Sarah Hrebien, R. D. Baird et al.
Clinical Cancer Research
Cancer Genomics and Diagnostics
article

Abstract PS2-07-05: Methylation-based ctDNA Dynamics as a Biomarker for Treatment Response and Prognosis in Patients on the plasmaMATCH trial

Javier Pascual, Isaac García-Murillas, Sarah Hrebien, R. D. Baird, A. M. Wardley, C. S. Swift, L. S. Kilburn, N. C. Turner, R. J. Cutts, C. Loader, I. M. Browne, I. R. MacPherson, M. Esteban-Garcia, R. Roylance, A. Amenssag, A. E. Ring, J. M. Bliss, A. Pearson
article en

Abstract

Abstract Background: Early assessment of circulating tumour DNA (ctDNA) dynamic changes on treatment predict response to therapy. Previous studies have tracked mutations in plasma, which requires prior knowledge of the tumour mutations and is also at risk of false results such as tracking mutations arising from clonal haematopoesis. We have developed a robust tumour agnostic ctDNA assay that tracks the level of aberrant breast cancer specific DNA methylation in plasma. We assessed the potential of baseline and early on-treatment changes in breast cancer ctDNA methylation levels, to predict progression-free survival (PFS) and objective response rate (ORR) to therapy. Methods: Patients enrolled on the plasmaMATCH trial with matched cycle 1-day1 (C1D1) and cycle 2-day 1 (C2D1) plasma samples available for analysis were included. PlasmaMATCH was a phase 2 platform trial which assessed the accuracy of ctDNA mutation testing in advanced breast cancer, and the ability of ctDNA testing to select patients for mutation-directed therapy. A capture based enzymatic ctDNA based methylation assay targeting 1297 differentially methylated regions (DMR), as well as specific promoters such as BRCA1, was used to distinguish the presence of breast cancer and the level of ctDNA. Tumour ctDNA levels were inferred by estimating the Methylation Read Percent (MPCT) based on the top 60 DMRs ranked on high entropy or high subtype methylation, with the circulating methylation ratio (CMR) calculated as the ratio of C2D1 MPCT / C1D1 MPCT. Patients with low CMR indicated lower ctDNA levels on treatment. We evaluated the association of baseline MPCT, and median change in CMR, with PFS and ORR. Cohorts A-D were analyzed together (ER-positive breast cancer on targeted therapy), with cohort E analysed separately (TNBC on olaparib PARP and ceralasertib ATR inhibitor combination). Results: We analysed C1D1/C2D1 matched samples from 74 patients for ctDNA methylation (30 from cohorts A-D and 44 from cohort E). All samples were successfully sequenced to a mean CpG coverage of 364x (range 89-975x). Splitting patients by median baseline MPCT was prognostic for PFS for cohort E: mPFS low MPCT 9 months v high 4 months (HR 0.52, 95% CI 0.26-1.02; p = 0.016), and ORR 36% (8/22) v 18% (4/22) (OR 2.56, 95% CI 1.36-4.96, p = 0.006). There was no association in Cohorts A-D: PFS HR 1.27, 95% CI 0.59-2.71, p = 0.463; ORR OR 1, 95% CI 0.49-2, p>0.99. In cohort A-D, splitting patients by median CMR dynamics was predictive of PFS; mPFS low CMR 6 months vs high CMR 2 months (HR 0.43, 95% CI 0.19-0.96; p = 0.008), and ORR 33% (5/15) vs 7% (1/15) (OR 6.54, 95% CI 2.85-16.57, p <0.0001). In cohort E splitting patients by median CMR was also highly predictive of PFS; mPFS low CMR 9 months vs high CMR 3 months (HR 0.47, 95% CI 0.24-0.94, p = 0.01), and ORR 45% (10/22) vs 9% (2/22) (OR 8.27, 95% CI 3.80-18.52, p <0.0001). In cohort E, 36% of patients (16/44) had detectable BRCA1 methylation at C1D1. There was no association between BRCA1 methylation and PFS (HR 0.92, 95% CI 0.47-1.82, p = 0.79), nor ORR (OR 0.86, 95% CI 0.43-1.50, p 0.633). Conclusions: Using a tumour agnostic breast cancer ctDNA methylation assay, we show that on treatment ctDNA methylation dynamics are predictive of response to targeted therapy. There was no association between BRCA1 methylation in ctDNA and outcomes, suggesting the sensitivity to PARP and ATR inhibition combination of cohort E was not mediated by BRCA1 methylation. Subject to further independent validation, ctDNA methylation dynamics may present a simple way to identify early patients who are responding to novel therapy combinations. Citation Format: I. M. Browne, R. J. Cutts, A. Amenssag, I. Garcia-Murillas, C. S. Swift, C. Loader, S. Hrebien, A. Pearson, J. Pascual, A. M. Wardley, M. Esteban-Garcia, L. S. Kilburn, I. R. MacPherson, R. D. Baird, R. Roylance, J. M. Bliss, A. E. Ring, N. C. Turner. Methylation-based ctDNA Dynamics as a Biomarker for Treatment Response and Prognosis in Patients on the plasmaMATCH trial [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-07-05.

Clinical Cancer ResearchVol. 32(4_Supplement)
University College London Hospitals NHS Foundation Trust (GB), Institute of Cancer Research (GB), Breast Cancer Now (GB), Beatson West of Scotland Cancer Centre (GB), Cambridge University Hospitals NHS Foundation Trust (GB), Royal Marsden Hospital (GB), The Christie NHS Foundation Trust (GB), University College London (GB)
Good health and well-being
Openalex Percentile: Top 55%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.