Evidence map›Paper›PMID 31233548›Full record

ArticlePloS one2019

Screening of urine identifies PLA2G16 as a field defect methylation biomarker for prostate cancer detection.

William E Jarrard, Adam Schultz, Tyler Etheridge, Shivashankar Damodaran, Glenn O Allen, David Jarrard, Bing Yang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. The Phospholipase AJournal of lipid and atherosclerosis · 2026
    Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Epigenetic field alterations in non-tumor prostate tissues detect prostate cancer in urine.American journal of clinical and experimental urology · 2021
    Article
  9. Article
  10. Article
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

7 authors at 2 institutions in 1 country.

William E JarrardCarbone Comprehensive Cancer Center, University of Wisconsin, Madison, WI, United States of America.
Adam SchultzCarbone Comprehensive Cancer Center, University of Wisconsin, Madison, WI, United States of America.
Tyler EtheridgeDepartment of Urology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America.
Shivashankar DamodaranDepartment of Urology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America.
Glenn O AllenDepartment of Urology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America.
David JarrardCarbone Comprehensive Cancer Center, University of Wisconsin, Madison, WI, United States of America.
Bing YangDepartment of Urology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America.
University of Wisconsin–Madison · USUniversity of Wisconsin Carbone Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProstate cancer (PC) is a multifocal disease. DNA methylation alterations are not restricted to the immediate peritumor environment, but spatially widespread in the adjacent and distant histologically normal prostate tissues. In the current study, we utilized high-throughput methylation arrays to identify epigenetic changes in the urine from men with and without cancer. DESIGN, SETTING, AND

participantsDNA urine samples were enriched for methylated fragments using MBD methyl-binding antibodies and applied to high density CytoScanHD arrays. Significant loci were validated using quantitative pyrosequencing and binary logistic regression modeling applied to urine sample analyses in a training (n = 83) and validation approach (n = 84). Methylation alterations in prostate tissues using pyrosequencing at the PLA2G16 locus were examined in 38 histologically normal specimens from men with (TA, n = 26) and without (NTA, n = 12) cancer and correlated to gene expression.

resultsMethylation microarrays identified 3,986 loci showing significantly altered methylation in the urine samples from patients with PC compared to those without (TA vs NTA; p<0.01). These loci were then compared against subjects with their prostates removed to exclude non-prostate cell markers yielding 196 significant regions. Multiple CpGs adjacent to PLA2G16 CpG island showed increased methylation in TA compared to NTA (p<0.01) in a large validation study of urine samples. The predictive accuracy of PLA2G16 methylation at CG2 showed the highest predictive value at 0.8 (odds ratio, 1.37; 95% confidence interval, 1.16-1.62; p<0.001). Using a probability cutoff of 0.065, the sensitivity and specificity of the multivariate model was 92% and 35%. When histologically normal prostate tissues/biopsies from patients with PC (TA) were compared to subjects without cancer, significant hypermethylation of PLA2G16 was noted (odds ratio, 1.35; 95% confidence interval, 1.07-1.71; p = 0.01).

conclusionPLA2G16 methylation defines an extensive field defect in histologically normal prostate tissue associated with PC. PLA2G16 methylation in urine and prostate tissues can detect the presence of PC.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorDNA MethylationEarly Detection of CancerEpigenesis, GeneticHumansMaleMass ScreeningMiddle AgedPhospholipases A2, Calcium-IndependentProstateProstatic NeoplasmsSensitivity and SpecificityTumor Suppressor ProteinsBiomarkers, TumorPhospholipases A2, Calcium-IndependentPLAAT3 protein, humanTumor Suppressor Proteins

Identifiers

PMID31233548
PMCPMC6590820
OpenAlexW2955366309

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.