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A comparative study of four cell-free DNA assays for detecting circulating tumor DNA in early breast cancer

  • Netherlands Cancer Institute
  • Erasmus University Rotterdam

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
38 Downloads (Pure)

Abstract

Early prediction of the response to neoadjuvant chemotherapy (NAC) enables tailoring treatment strategies to the specific needs of individual breast cancer patients. Circulating tumor DNA (ctDNA) has shown to be a prognostic factor for response on NAC during treatment. However, at this point in time mostly tumor-informed ctDNA detection methods are used which are costly, have relatively long turnaround times and are subsequently potentially less feasible for widespread clinical application. In this study, we investigated four tumor-agnostic methods to determine their ability to accurately detect circulating tumor DNA (ctDNA) at baseline. These methods were the Oncomine Breast cell free DNA (cfDNA) NGS panel, the LINE-1 sequencing assay mFAST-SeqS, shallow whole genome sequencing and the genome-wide methylation profiling assay MeD-Seq. In total 40 patients with triple negative or luminal B breast cancer were included and cell free DNA (cfDNA) from plasma before the start of NAC was analyzed with the four assays. We detected ctDNA in 3/24 (12.5%) patients with Oncomine, 5/40 (12.5%) with mFast-SeqS, 3/40 (7.7%) with low pass shallow WGS and 23/40 with MeD-Seq (57.5%). When all methods were combined ctDNA was detected in 65% of patients. In conclusion, we demonstrated that tumor agnostic methods, in particular MeD-Seq, can detect ctDNA in a fraction of the patients with early breast cancer, but further optimization is needed to reach the potential currently demonstrated by tumor-informed methods.

Original languageEnglish
Article number120
Number of pages11
JournalBreast Cancer Research
Volume27
Issue number1
DOIs
Publication statusPublished - 1 Jul 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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