Evidence map›Paper›PMID 37161793›Full record

ArticleEMBO molecular medicine2023

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 and 13 more

Open access · goldAbstract read
In one paragraph

Article in EMBO molecular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 2 pooled it
13.4field-weighted citation impact, top 1% of its field
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

46 citing papers in PubMed, 2 syntheses or guidelines pooled it, 56 citations in OpenAlex.

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  8. Towards liquid biopsy-based analysis of antitumour immunity.Nature reviews. Clinical oncology · 2026
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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

23 authors at 1 institution in 1 country.

Angela Santonja *Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Wendy N Cooper *Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0003-3416-9982
Matthew D EldridgeCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0002-5799-8911
Paul A W EdwardsCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0002-4789-3374
James A MorrisCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Abigail R EdwardsCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Hui ZhaoCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Katrin HeiderCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0003-4035-1668
Dominique-Laurent CouturierCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Aadhitthya VijayaraghavanCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0002-6095-8961
Paulius MenneaCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Emma-Jane DitterCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0003-0625-7264
Christopher G SmithCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Chris BoursnellCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Raquel Manzano GarcíaCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0002-5124-8992
Oscar M RuedaMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Emma BeddowesCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Heather BiggsDepartment of Oncology, University of Cambridge, Cambridge, UK.
Stephen-John SammutCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0003-4472-904X
Nitzan RosenfeldCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0002-2825-4788
Carlos CaldasCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0003-3547-1489
Jean E AbrahamCancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0003-0688-4807
Davina GaleCancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.ORCID 0000-0002-4521-8199
University of Cambridge · GB

Funding

Cancer Research UK 20240Cancer Research UK 21491Cancer Research UK 25117Cancer Research UK A20240Cancer Research UK A21491Cancer Research UK A28870Cancer Research UK C1287/A26886Cancer Research UK C17918/A28870Cancer Research UK C36857/A27548Cancer Research UK C507/A27657Cancer Research UK C9545/A29580Cancer Research UK C9685/A25177Cancer Research UK EDDCPT\100013Department of Health BRC-1215-20014European Research Council 337905Medical Research Council MC_UU_00002/16Wellcome Trust 106566
6 · The paper itself

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.

Indexed as

Breast NeoplasmsCirculating Tumor DNABiomarkers, TumorFemaleHigh-Throughput Nucleotide SequencingHumansMutationBiomarkers, TumorCirculating Tumor DNAcirculating tumor DNAhybrid captureliquid biopsymultiplex PCRwhole-genome sequencing

Identifiers

PMID37161793
PMCPMC10245040
OpenAlexW4376121423

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.