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Comparison of tumor-informed and tumor-naïve sequencing assays for ctDNA detection in breast cancer

  • Angela Santonja
  • , Wendy N. Cooper
  • , Matthew D. Eldridge
  • , Paul A.W. Edwards
  • , James A. Morris
  • , Abigail R. Edwards
  • , Hui Zhao
  • , Katrin Heider
  • , Dominique Laurent Couturier
  • , Aadhitthya Vijayaraghavan
  • , Paulius Mennea
  • , Emma Jane Ditter
  • , Christopher G. Smith
  • , Chris Boursnell
  • , Raquel Manzano García
  • , Oscar M. Rueda
  • , Emma Beddowes
  • , Heather Biggs
  • , Stephen John Sammut
  • , Nitzan Rosenfeld
  • Carlos Caldas, Jean E. Abraham*, Davina Gale*
*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

57 Scopus citations

Abstract

Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21–47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay.

Original languageEnglish
Article numbere16505
JournalEMBO Molecular Medicine
Volume15
Issue number6
DOIs
StatePublished - 7 Jun 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 The Authors. Published under the terms of the CC BY 4.0 license.

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

Keywords

  • circulating tumor DNA
  • hybrid capture
  • liquid biopsy
  • multiplex PCR
  • whole-genome sequencing

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