Article in Cancer discovery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
Bernard J PopeMelbourne Bioinformatics, University of Melbourne, Parkville, Australia.ORCID 0000-0002-4840-1095
Amar U KishanJonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, California.ORCID 0000-0002-4836-8483
Alejandro BerlinPrincess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0002-1880-6905
Melvin L K ChuaDepartment of Radiation Oncology, University of Toronto, Toronto, Canada.ORCID 0000-0002-1648-1473
Niall M CorcoranDepartment of Surgery, University of Melbourne, Parkville, Australia.ORCID 0000-0003-4483-6945
Theodorus van der KwastPrincess Margaret Cancer Centre , University Health Network, Toronto, Canada.ORCID 0000-0001-8640-5786
Christopher M HovensDepartment of Surgery, University of Melbourne, Parkville, Australia.ORCID 0000-0002-0610-1289
Robert G BristowDepartment of Medical Biophysics, University of Toronto, Toronto, Canada.ORCID 0000-0002-8553-9544
Paul C BoutrosSanford Burnham Prebys Medical Discovery Institute , La Jolla, California.ORCID 0000-0003-0553-7520
Funding
Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI William E Lowry · 1985 to 2026
$134.5M
UCLA-Caltech Medical Scientist Training ProgramT32GM008042 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DAWSON, DAVID WAYNE · 1985 to 2023
$29.9M
UCLA-Caltech Medical Scientist Training ProgramT32GM152342 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Olujimi A Ajijola, David Wayne Dawson · 2024 to 2026
$5.3M
Virginia-UCLA-Toronto Biomarker Characterization CenterU2CCA271894 · NCI · OLD DOMINION UNIVERSITY · PI Paul Christopher Boutros, OLIVER John SEMMES · 2022 to 2026
$3.2M
Germline Determinants of Prostate Cancer EvolutionR01CA270108 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PAUL T. SPELLMAN · 2023 to 2026
$2.9M
Development of Protein Biomarkers in Post-DRE Urine for use in Liquid Biopsy of Prostate CancerU01CA214194 · NCI · EASTERN VIRGINIA MEDICAL SCHOOL · PI BOUTROS, PAUL CHRISTOPHER, KISLINGER, THOMAS · 2016 to 2021
$2.5M
Canadian Cancer Society (CCS) 705649Canadian Cancer Society (CCS) C5759Canadian Institutes of Health Research (CIHR)DOD Prostate Cancer Research Program (PCRP) W81XWH2210247DOD Prostate Cancer Research Program (PCRP) W81XWH2210751Jonsson Comprehensive Cancer Center, University of California, Los Angeles (JCCC)National Institute of General Medical Sciences (NIGMS) T32GM008042National Institute of General Medical Sciences (NIGMS) T32GM152342National Institutes of Health (NIH) P30CA016042National Institutes of Health (NIH) R01CA270108National Institutes of Health (NIH) U01CA214194National Institutes of Health (NIH) U2CCA271894NCI NIH HHS P30 CA016042NCI NIH HHS R01 CA270108NCI NIH HHS U01 CA214194NCI NIH HHS U2C CA271894NIGMS NIH HHS T32 GM008042NIGMS NIH HHS T32 GM152342Prostate Cancer Canada (PCC) RS2014-01Prostate Cancer Foundation (PCF) 20CHAS01Terry Fox Research Institute (TFRI)
6 · The paper itself
Abstract
Prostate cancer is characterized by profound clinical and molecular heterogeneity. Although its genomic heterogeneity is well characterized, its epigenomic heterogeneity remains less understood. We therefore created a compendium of 3,001 multiancestry prostate methylomes spanning normal tissue through localized disease of all grades to polymetastatic disease. A subset of 884 samples had multiomic DNA and/or RNA characterization. We identify four epigenomic subtypes that risk-stratify patients and reflect distinct evolutionary trajectories. We demonstrate extensive regulatory interplay between DNA copy number and methylation, with transcriptional consequences that vary across genes and disease stages. We define epigenetic dysregulation signatures for 15 important clinicomolecular features, creating predictive models for each. For example, we identify specific epigenetic features that predict patient outcome and are synergistic with clinical prognostic features. These results define a complex interplay between tumor genetics and epigenetics that converges to modify gene expression programs and clinical presentation, in part through modulation of epigenetic aging. SIGNIFICANCE: We define the largest prostate cancer methylome resource to date, revealing four epigenomic subtypes that stratify cancers by their genetics, evolution, and clinical phenotypes. These data demonstrate that genome-epigenome interactions are stage-dependent, positioning DNA methylation as a central, clinically informative driver of prostate cancer heterogeneity.
Indexed as
DNA MethylationProstatic NeoplasmsEpigenesis, GeneticEpigenomeEpigenomicsGene Expression Regulation, NeoplasticHumansMale
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.
The Landscape of Prostate Tumor Methylation. · full record | OpenQuestion