Evidence map›Paper›PMID 27900799›Full record

ArticleThe Prostate2017

Tissue Sources for Accurate Measurement of Germline DNA Genotypes in Prostate Cancer Patients Treated With Radical Prostatectomy.

Nima C Emami, Lancelote Leong, Eunice Wan, Erin L Van Blarigan, Matthew R Cooperberg, Imelda Tenggara, Peter R Carroll, June M Chan, John S Witte, Jeffry P Simko

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Prostate, 2017. 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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

10 authors.

Nima C EmamiProgram in Biological and Medical Informatics, University of California, San Francisco, California.
Lancelote LeongDepartment of Epidemiology and Biostatistics, University of California, San Francisco, California.
Eunice WanInstitute for Human Genetics, University of California, San Francisco, California.
Erin L Van BlariganDepartment of Epidemiology and Biostatistics, University of California, San Francisco, California.
Matthew R CooperbergDepartment of Epidemiology and Biostatistics, University of California, San Francisco, California.
Imelda TenggaraDepartment of Urology, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California.
Peter R CarrollDepartment of Urology, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California.
June M ChanDepartment of Epidemiology and Biostatistics, University of California, San Francisco, California.
John S WitteProgram in Biological and Medical Informatics, University of California, San Francisco, California.
Jeffry P SimkoDepartment of Urology, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California.

Funding

Targeting FOXA1-downstream pathways: a novel therapeutic strategy for castration-resistant prostate cancerP50CA180995 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI CATALONA, WILLIAM J · 2015 to 2025
$19.9M
Clinical and Transtional Science InstituteKL2TR000143 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GRANDIS, JENNIFER RUBIN · 2012 to 2015
$11.9M
BMI Bioinformatics Training GrantsT32GM067547 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HERNANDEZ, RYAN D. · 2003 to 2022
$6.6M
Training in Molecular& Genetic Epidemiology of CancerR25CA112355 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WITTE, JOHN S. · 2005 to 2018
$6.5M
Genetic Epidemiology of Prostate Cancer Risk and ProgressionR01CA088164 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VAN DEN EEDEN, STEPHEN K., WITTE, JOHN S. · 2000 to 2015
$6.1M
Genomewide Association Study of Prostate CancerU01CA127298 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WITTE, JOHN S. · 2008 to 2012
$5.1M
Diet After Colorectal Cancer : Observational Studies to Behavioral InterventionsK07CA197077 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VAN BLARIGAN, ERIN LYNN · 2016 to 2020
$885k
NCATS NIH HHS KL2 TR000143NCI NIH HHS K07 CA197077NCI NIH HHS P50 CA180995NCI NIH HHS R01 CA088164NCI NIH HHS R25 CA112355NCI NIH HHS U01 CA127298NIGMS NIH HHS T32 GM067547
6 · The paper itself

Abstract

backgroundBenign tissue from a tumor-containing organ is commonly the only available source for obtaining a patient's unmutated genome for use in cancer research. While it is critical to identify histologically normal tissue that is independent of the tumor lineage, few additional considerations are applied to the choice of this material for such measurements.

methodsNormal formalin-fixed, paraffin-embedded seminal vesicle, and urethral tissues, in addition to whole blood, were collected from 31 prostate cancer patients having undergone radical prostatectomy. Genotype concordance was evaluated for DNA from each tissue source in relation to whole blood.

resultsOverall, there was a greater genotype call rate for DNA derived from urethral tissue (97.0%) in comparison with patient-matched seminal vesicle tissues (95.9%, P = 0.0015). Furthermore, with reference to patient-matched whole blood, urethral samples exhibited higher genotype concordance (94.1%) than that of seminal vesicle samples (92.5%, P = 0.035).

conclusionsThese findings highlight the heterogeneity between diverse sources of DNA in genotype measurement and motivate the consideration of normal tissue biases in tumor-normal analyses. Prostate 77: 425-434, 2017. © 2016 Wiley Periodicals, Inc.

Indexed as

GenotypeAdult Germline Stem CellsAgedDNAHumansMaleMiddle AgedProstatectomyProstatic NeoplasmsSeminal VesiclesTreatment OutcomeUrethraDNAarchival FFPE tissuegenotype concordanceseminal vesicletumor-normalurethra

Identifiers

PMID27900799
PMCPMC5479703

What OpenQuestion holds

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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.