Evidence map›Paper›PMID 36693953›Full record

ArticleOncogene2023

Comparison of phenomics and cfDNA in a large breast screening population: the Breast Screening and Monitoring Study (BSMS).

Justin Stebbing, Panteleimon G Takis, Caroline J Sands, Lynn Maslen, Matthew R Lewis, Kelly Gleason, Karen Page, David Guttery, Daniel Fernandez-Garcia, Lindsay Primrose and 1 more

Open access · hybridFull text read
In one paragraph

Article in Oncogene, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Using cfDNA and ctDNA as Oncologic Markers: A Path to Clinical Validation.International journal of molecular sciences · 2023
    Review
  7. Article
  8. NMR-based metabolomics: Where are we now and where are we going?Progress in nuclear magnetic resonance spectroscopy
    Review
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

11 authors at 3 institutions in 1 country.

Justin Stebbing *Department of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK.
Panteleimon G Takis *National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK. p.takis@imperial.ac.uk.ORCID 0000-0002-7224-0412
Caroline J SandsNational Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK.
Lynn MaslenNational Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK.ORCID 0000-0002-6657-3296
Matthew R LewisNational Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK.
Kelly GleasonDepartment of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK.
Karen PageLeicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK.
David GutteryLeicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK.ORCID 0000-0003-0418-580X
Daniel Fernandez-GarciaLeicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK.
Lindsay PrimroseLeicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK.
Jacqueline A ShawDepartment of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK.ORCID 0000-0003-4227-503X
Imperial College London · GBUniversity of Leicester · GBUniversity of Cambridge · GB

Funding

Cancer Research UK 23464Medical Research Council MC_PC_12025Medical Research Council MR/R023484/1Medical Research Council MR/T033371/1
6 · The paper itself

Abstract

To assess their roles in breast cancer diagnostics, we aimed to compare plasma cell-free DNA (cfDNA) levels with the circulating metabolome in a large breast screening cohort of women recalled for mammography, including healthy women and women with mammographically detected breast diseases, ductal carcinoma in situ and invasive breast cancer: the Breast Screening and Monitoring Study (BSMS). In 999 women, plasma was analyzed by nuclear magnetic resonance (NMR) and Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) and then processed to isolate and quantify total cfDNA. NMR and UPLC-MS results were compared with data for 186 healthy women derived from the AIRWAVE cohort. Results showed no significant differences between groups for all metabolites, whereas invasive cancers had significantly higher plasma cfDNA levels than all other groups. When stratified the supervised OPLS-DA analysis and total cfDNA concentration showed high discrimination accuracy between invasive cancers and the disease/medication-free subjects. Furthermore, comparison of OPLS-DA data for invasive breast cancers with the AIRWAVE cohort showed similar discrimination between breast cancers and healthy controls. This is the first report of agreement between metabolomics and plasma cfDNA levels for discriminating breast cancer from healthy subjects in a true screening population. It also emphasizes the importance of sample standardization. Follow on studies will involve analysis of candidate features in a larger validation series as well as comparing results with serial plasma samples taken at the next routine screening mammography appointment. The findings here help establish the role of plasma analysis in the diagnosis of breast cancer in a large real-world cohort.

Indexed as

Breast NeoplasmsCell-Free Nucleic AcidsChromatography, LiquidEarly Detection of CancerFemaleHumansMammographyPhenomicsTandem Mass SpectrometryCell-Free Nucleic Acids

Identifiers

PMID36693953
PMCPMC10005936
OpenAlexW4317881705

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read1
measurements read27
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.