Evidence map›Paper›PMID 37694549›Full record

ArticleCancer medicine2023

Genome-wide methylation profiling of diagnostic tumor specimens identified DNA methylation markers associated with metastasis among men with untreated localized prostate cancer.

Chun R Chao, Jeff Slezak, Kimberly Siegmund, Kimberly Cannavale, Yu-Hsiang Shu, Gary W Chien, Xu-Feng Chen, Feng Shi, Nan Song, Stephen K Van Den Eeden and 1 more

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

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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

11 authors at 4 institutions in 2 countries.

Chun R ChaoDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.ORCID 0000-0002-6072-4954
Jeff SlezakDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.ORCID 0000-0002-6108-9198
Kimberly SiegmundDepartment of Population and Public Health Sciences, USC Keck School of Medicine, University of Southern California, Los Angeles, California, USA.ORCID 0000-0001-7599-9726
Kimberly CannavaleDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.ORCID 0000-0003-3892-9686
Yu-Hsiang ShuDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.ORCID 0009-0007-0114-3950
Gary W ChienDepartment of Urology, Los Angeles Medical Center, Kaiser Permanente Southern California, Los Angeles, California, USA.ORCID 0000-0002-6552-5671
Xu-Feng ChenDepartment of Pathology, School of Medicine, Duke University, Durham, North Carolina, USA.ORCID 0000-0001-9870-4820
Feng ShiDepartment of Pathology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-1850-7796
Nan SongDepartment of Urology Beijing Shijitan Hospital, Capital Medical University, Beijing, China.ORCID 0009-0001-1191-6263
Stephen K Van Den EedenDivision of Research, Kaiser Permanente Northern California, Oakland, California, USA.ORCID 0000-0002-5599-8387
Jiaoti HuangDepartment of Pathology, School of Medicine, Duke University, Durham, North Carolina, USA.ORCID 0000-0003-1195-1998
Kaiser Permanente · USCapital Medical University · CNDuke University · USUniversity of Southern California · US

Funding

Identification of DNA methylation markers for risk of metastasis in localized proR01CA181242 · NCI · KAISER FOUNDATION RESEARCH INSTITUTE · PI CHAO, CHUN R. · 2015 to 2019
$3.0M
NCI NIH HHS R01 CA181242NCI NIH HHS R01CA181242
6 · The paper itself

Abstract

backgroundWe used a genome-wide discovery approach to identify methylation markers associated with metastasis in men with localized prostate cancer (PCa), as better identification of those at high risk of metastasis can inform treatment decision-making.

methodsWe identified men with localized PCa at Kaiser Permanente California (January 1, 1997-December 31, 2006) who did not receive curative treatment and followed them for 10 years to determine metastasis status. Cases were chart review-confirmed metastasis, and controls were matched using density sampling. We extracted DNA from the cancerous areas in the archived diagnostic tissue blocks. We used Illumina's Infinium MethylationEPIC BeadChip for methylation interrogation. We used conditional logistic regression and Bonferroni's correction to identify methylation markers associated with metastasis. In a separate validation cohort (2007), we evaluated the added predictive utility of the methylation score beyond clinical risk score.

resultsAmong 215 cases and 404 controls, 31 CpG sites were significantly associated with metastasis status. Adding the methylation score to the clinical risk score did not meaningfully improve the c-statistic (0.80-0.81) in the validation cohort, though the score itself was statistically significant (p < 0.01). In the validation cohort, both clinical risk score alone and methylation marker score alone are well calibrated for predicted 10-year metastasis risks. Adding the methylation score to the clinical risk score only marginally improved predictive risk calibration.

conclusionOur findings do not support the use of these markers to improve clinical risk prediction. The methylation markers identified may inform novel hypothesis in the roles of these genetic regions in metastasis development.

Indexed as

DNA MethylationProstatic NeoplasmsCpG IslandsHumansMaleRisk Factorsepigeneticsmetastasismethylationprostate cancerrisk model

Identifiers

PMID37694549
PMCPMC10557825
OpenAlexW4386591862

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.