Evidence map›Paper›PMID 40099973›Full record

ArticleCancer research communications2025

A Blood-Based Assay for Detection of Patients with Advanced Adenomas.

Kamel Lahouel, Christopher Douville, Brenda Diergaarde, Joshua D Cohen, Haley Grant, Albert Kuo, Saad K Ansari, Yuxuan Wang, Anne Marie O'Broin-Lennon, Maria Popoli and 11 more

Abstract read
In one paragraph

Article in Cancer research communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. 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

21 authors.

Kamel Lahouel *Center for Cancer Prevention and Early Detection, City of Hope, Duarte, California.ORCID 0000-0002-4339-5749
Christopher Douville *Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-2510-4151
Brenda Diergaarde *Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.ORCID 0000-0002-3578-6547
Joshua D CohenLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-1158-5668
Haley GrantDepartment of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Maryland.ORCID 0000-0002-8173-5302
Albert KuoDepartment of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Maryland.ORCID 0000-0001-5155-0748
Saad K AnsariDivision of Integrated Cancer Genomics, Translational Genomics Research Institute, Phoenix, Arizona.ORCID 0009-0008-1641-0916
Yuxuan WangLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-2932-6042
Anne Marie O'Broin-LennonLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0001-8957-3945
Maria PopoliLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-2151-7749
Janine PtakLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-1934-8739
Natalie SillimanLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-5198-9037
Lisa DobbynLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-3159-189X
Nadine NehmeLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0009-0001-3868-2305
Jeanne TieDivision of Personalized Oncology, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.ORCID 0000-0001-9244-2057
Peter GibbsDivision of Personalized Oncology, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.ORCID 0000-0003-1423-4484
Nickolas PapadopoulosLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0001-7135-7451
Kenneth W KinzlerLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0001-5591-1176
Bert VogelsteinLudwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-0766-3854
Robert E SchoenDepartment of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.ORCID 0000-0001-7153-2766
Cristian TomasettiCenter for Cancer Prevention and Early Detection, City of Hope, Duarte, California.ORCID 0000-0003-3277-4804

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI Rosalie Wollett · 1985 to 2026
$208.6M
ONCOLOGY: CHEMOTHERAPY, IMMUNOLOGY, BIOLOGYT32CA009071 · NCI · JOHNS HOPKINS UNIVERSITY · PI Mary Y Armanios, Nilofer S. Azad · 1985 to 2026
$12.8M
Refinement and Discovery of Nuclear Matrix Protein Markers for Colorectal CancerU01CA152753 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KINZLER, KENNETH W., SCHOEN, ROBERT E. · 2010 to 2021
$6.8M
Multi-analyte Approach for Earlier Detection of Cancers in Non Plasma BiofluidsU01CA230691 · NCI · JOHNS HOPKINS UNIVERSITY · PI Nishant Agrawal, CHETAN BETTEGOWDA · 2018 to 2026
$6.7M
Blood-Based Testing for Advanced AdenomaU01CA271884 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ROBERT E. SCHOEN, Cristian Tomasetti · 2022 to 2026
$4.6M
NCI NIH HHS P30 CA006973NCI NIH HHS T32 CA009071NCI NIH HHS U01 CA152753NCI NIH HHS U01 CA230691NCI NIH HHS U01 CA271884
6 · The paper itself

Abstract

abstractScreening for colorectal cancer with blood-based testing should detect advanced adenomas (AA), facilitating more effective cancer prevention. We evaluated four different methods to detect AAs in plasma: (i) a machine learning algorithm, Signatures of fragment Length (SignaL), based on cell-free DNA (cfDNA) fragmentation; (ii) a “Protein-17” assay measuring 17 cancer-associated proteins; (iii) a global aneuploidy score (GAS); and (iv) cfDNA mutation analysis querying 15 genes commonly mutated in colorectal cancer. Existing data from study populations with and without cancer were utilized to determine 99.5% specificity thresholds. We studied 40 AA cases and 32 colonoscopy-negative controls. SignaL detected 9/40 AAs [22.5%, 95% confidence interval (CI), 12.3%–37.5%] at 100% specificity (95% CI, 89.3%–100%). Protein-17 detected 5/40 AAs (12.5%, 95% CI, 5.5%–26.1%) including three cases not identified by SignaL, at 100% specificity (95% CI, 89.3%–100%). GAS detected 11/40 AAs (27.5%, 95% CI, 16.1%–42.8%) but resulted in 2/32 positive controls (93.8% specificity, 95% CI, 79.9%–98.3%). Combining SignaL, the Protein-17 assay, and GAS at the 99.5% specificity thresholds resulted in detection of 16/40 AAs (40%, 95% CI, 26.3%–55.4%) at 93.8% specificity (95% CI, 79.9%–98.3%). Of 32/40 evaluable AA plasma samples, only one was cfDNA mutation positive at level of significance of 0.01. A blood-based assay based on the analysis of repeated sequence elements plus proteins seems to be able to detect a considerable fraction of patients with AA at relatively high specificity. Large, prospective studies are required to determine whether this approach can add to the options currently available for screening patients for premalignant lesions of the colon. SIGNIFICANCE: Blood-based screening for colorectal cancer could improve testing uptake and outcomes. We propose novel methods to detect AAs in plasma using cfDNA fragmentation patterns, cancer-associated proteins, and aneuploidy with high specificity. Larger studies are needed to validate clinical utility.

Indexed as

AdenomaBiomarkers, TumorCell-Free Nucleic AcidsColorectal NeoplasmsEarly Detection of CancerAneuploidyHumansSensitivity and SpecificityBiomarkers, TumorCell-Free Nucleic Acids

Identifiers

PMID40099973
PMCPMC12001750

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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.