Evidence map›Paper›PMID 37500728›Full record

ArticleNature genetics2023

Single-molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer.

Daniel C Bruhm, Dimitrios Mathios, Zachariah H Foda, Akshaya V Annapragada, Jamie E Medina, Vilmos Adleff, Elaine Jiayuee Chiao, Leonardo Ferreira, Stephen Cristiano, James R White and 10 more

Abstract read
In one paragraph

Article in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

41 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Current trends and future directions of artificial intelligence in lung cancer diagnosis.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2026
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  9. Cancer-Like Fragmentomic Characteristics of Somatic Variants in Cell-Free DNA.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  11. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors.

Daniel C BruhmThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Dimitrios MathiosThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Zachariah H FodaThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-3591-8482
Akshaya V AnnapragadaThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-9097-6511
Jamie E MedinaThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Vilmos AdleffThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Elaine Jiayuee ChiaoThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Leonardo FerreiraThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Stephen CristianoThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
James R WhiteThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Sarah A MazzilliDivision of Computational Biomedicine, Department of Medicine, Boston University, Boston, MA, USA.
Ehab BillatosDivision of Computational Biomedicine, Department of Medicine, Boston University, Boston, MA, USA.
Avrum SpiraDivision of Computational Biomedicine, Department of Medicine, Boston University, Boston, MA, USA.
Ali H ZaidiAllegheny Health Network Cancer Institute, Allegheny Health Network, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0002-5463-2252
Jeffrey MuellerAllegheny Health Network Cancer Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Amy K KimThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Valsamo AnagnostouThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0001-9480-3047
Jillian PhallenThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-5492-9013
Robert B ScharpfThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. rscharpf@jhu.edu.ORCID http://orcid.org/0000-0003-4702-2656
Victor E VelculescuThe Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. velculescu@jhmi.edu.ORCID http://orcid.org/0000-0003-1195-438X

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI WILLIAM George NELSON · 1985 to 2026
$208.6M
Tumor Antigens for Individual Signatures and TherapyP50CA062924 · NCI · JOHNS HOPKINS UNIVERSITY · PI JAFFEE, ELIZABETH M. · 1993 to 2022
$54.6M
Medical Scientist Training ProgramT32GM136577 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI ANDREA L COX · 2020 to 2026
$13.4M
ECOG-ACRIN Thoracic Malignancies Integrated Translational Science CenterUG1CA233259 · NCI · EMORY UNIVERSITY · PI CARBONE, DAVID P., LEAL, TICIANA · 2019 to 2025
$5.1M
Large-Scale Genetic Analyses of Human CancerR01CA121113 · NCI · JOHNS HOPKINS UNIVERSITY · PI ANAGNOSTOU, VALSAMO, VELCULESCU, VICTOR E. · 2006 to 2022
$4.3M
NCI NIH HHS P30 CA006973NCI NIH HHS P50 CA062924NCI NIH HHS R01 CA121113NCI NIH HHS UG1 CA233259NIGMS NIH HHS T32 GM136577
6 · The paper itself

Abstract

Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

Indexed as

Cell-Free Nucleic AcidsLung NeoplasmsNeoplasmsHumansMutationMutation RateProspective StudiesCell-Free Nucleic Acids

Identifiers

PMID37500728
PMCPMC10412448

What OpenQuestion holds

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Registered trials

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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.