Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 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.
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
20 authors.
Mohamed A GoudaDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0003-4829-6739
Filip JankuDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-8123-4065
Ying YuanDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0003-3163-480X
Xiaofeng ZhengDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0009-0007-2171-7210
Keyur PatelDepartment of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-5081-2427
Funda Meric-BernstamDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-6816-6072
Funding
NRG Oncology Network Group Operations Center - GY9 BIQSFP Reports/BudgetsU10CA180868 · NCI · NRG ONCOLOGY FOUNDATION, INC. · PI NORMAN WOLMARK · 2014 to 2026
$206.8M
Project-006U10CA180820 · NCI · ECOG-ACRIN MEDICAL RESEARCH FOUNDATION · PI Peter J ODwyer · 2014 to 2026
$167.6M
SWOG Network Group Operations Center of the NCTNU10CA180888 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI PRIMO N. LARA · 2014 to 2026
$152.1M
Statistics CoreU10CA180794 · NCI · DANA-FARBER CANCER INST · PI PAUL J CATALANO, CONSTANTINE A. GATSONIS · 2014 to 2026
$111.2M
Convalescent Plasma to Limit Coronavirus Associated ComplicationsUL1TR003167 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KARP, DANIEL D, MCPHERSON, DAVID D · 2019 to 2023
$45.3M
Kaiser Permanente NCI National Community Oncology Research Program, NCORPUG1CA189821 · NCI · KAISER FOUNDATION RESEARCH INSTITUTE · PI Jennifer Marie Suga · 2014 to 2026
$44.4M
UT MD Anderson Cancer Center Network Lead Academic Participating Site (LAP) UG1UG1CA233329 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KELLY K HUNT, CHELSEA Camille PINNIX · 2019 to 2026
$11.1M
NCTN Lead Academic Participating Site at Dana-Farber/Partners Cancer CareUG1CA233180 · NCI · DANA-FARBER CANCER INST · PI Harold John Burstein · 2019 to 2026
$8.6M
UT Southwestern NCI National Clinical Trials Network (NCTN) LAPS - Supplemental Funds YR4UG1CA233302 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI David Eric Gerber · 2019 to 2026
$6.4M
UM LAPs -UG1 GrantUG1CA233160 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ANNE F SCHOTT · 2019 to 2026
$5.4M
Sidney Kimmel Cancer Center LAPS Institutional CollaborationUG1CA233341 · NCI · THOMAS JEFFERSON UNIVERSITY · PI Steven Cohen, Mitchell Edelson · 2019 to 2026
$3.5M
Center for Clinical and Translational Sciences (CTSA) UL1TR003167National Cancer Institute (NCI) U10CA180794National Cancer Institute (NCI) U10CA180820National Cancer Institute (NCI) U10CA180868National Cancer Institute (NCI) U10CA180888National Cancer Institute (NCI) UG1CA189821National Cancer Institute (NCI) UG1CA233160National Cancer Institute (NCI) UG1CA233180National Cancer Institute (NCI) UG1CA233302National Cancer Institute (NCI) UG1CA233329National Cancer Institute (NCI) UG1CA233341NCATS NIH HHS UL1 TR003167NCI NIH HHS U10 CA180794NCI NIH HHS U10 CA180820NCI NIH HHS U10 CA180868NCI NIH HHS U10 CA180888NCI NIH HHS UG1 CA189821NCI NIH HHS UG1 CA233160NCI NIH HHS UG1 CA233180NCI NIH HHS UG1 CA233302NCI NIH HHS UG1 CA233329NCI NIH HHS UG1 CA233341
6 · The paper itself
Abstract
purposeLiquid biopsies with circulating tumor DNA (ctDNA) analysis are increasingly being utilized as a noninvasive approach to identify actionable genomic alterations in advanced/metastatic cancers. In this study, we report the correlation between ctDNA analysis of plasma samples collected from patients enrolled in the NCI-MATCH trial and tumor tissue-based sequencing. EXPERIMENTAL
designWe analyzed plasma samples collected from patients enrolled on 16 subprotocols of NCI-MATCH who had plasma samples collected within 90 days before starting treatment. Concordance was defined as the detection of the same gene alteration leading to patient enrollment in NCI-MATCH in both tissue and plasma.
resultsWe included 300 patients who were enrolled in NCI-MATCH. Most patients (81%, n = 243) were enrolled based on central tissue testing and had contemporaneous tissue and plasma samples. The tissue alteration of interest was detected in the plasma of 81.1% (n = 197) of patients. Lower rates of detection of the tissue alteration of interest were observed in samples from 57 patients who were enrolled based on outside designated laboratory testing (56.1%, n = 32) and had noncontemporaneous tissue and plasma samples. Variations in concordance rates were observed with different alteration types, by maximum plasma variant allele frequency, and based on tumor biopsy site.
conclusionsThe tumor tissue alteration of interest was detected in the plasma of 81% of patients who were enrolled in the NCI-MATCH trial based on central tissue testing and had contemporaneous tissue and plasma samples. This suggests a potential role for liquid biopsy in patient enrollment in trials evaluating biomarker-driven anticancer therapies. See related commentary by Russo et al., p. 4217.
Indexed as
Biomarkers, TumorCirculating Tumor DNANeoplasmsAdultAgedFemaleGenotypeHumansLiquid BiopsyMaleMiddle AgedBiomarkers, TumorCirculating Tumor DNA
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.
Concordance between Tumor Tissue and Plasma DNA Genotyping in the NCI-MATCH Trial (EAY131). · full record | OpenQuestion