Evidence map›Paper›PMID 27174589›Full record

ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2016

Analytic validation of a clinical-grade PTEN immunohistochemistry assay in prostate cancer by comparison with PTEN FISH.

Tamara L Lotan, Wei Wei, Olga Ludkovski, Carlos L Morais, Liana B Guedes, Tamara Jamaspishvili, Karen Lopez, Sarah T Hawley, Ziding Feng, Ladan Fazli and 13 more

Open access · bronzeAbstract readComparative StudyMulticenter StudyValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
10.8field-weighted citation impact, top 1% 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

50 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Artificial intelligence in prostate cancer.Chinese medical journal · 2025
    Review
  9. Review
  10. Exploring therapeutic applications ofFrontiers in oncology · 2025
    Review
  11. Article
  12. Review
  13. Predicting Prostate Cancer Molecular Subtype With Deep Learning on Histopathologic Images.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2023
    Article
  14. Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2023
    Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Review
  20. The prognostic significance of p16 expression pattern in diffuse gliomas.Journal of pathology and translational medicine · 2021
    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

23 authors at 12 institutions in 3 countries.

Tamara L LotanPathology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Wei WeiMD Anderson Cancer Center, Houston, TX, USA.
Olga LudkovskiDepartment of Pathology and Molecular Medicine, Queen's University, Kingston, ON, Canada.
Carlos L MoraisPathology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Liana B GuedesPathology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Tamara JamaspishviliDepartment of Pathology and Molecular Medicine, Queen's University, Kingston, ON, Canada.
Karen LopezPathology, UCSF, San Francisco, CA, USA.
Sarah T HawleyCanary Foundation, Palo Alto, CA, USA.
Ziding FengMD Anderson Cancer Center, Houston, TX, USA.
Ladan FazliVancouver Prostate Centre, Vancouver, BC, Canada.
Antonio Hurtado-CollVancouver Prostate Centre, Vancouver, BC, Canada.
Jesse K McKenneyPathology, Cleveland Clinic, Cleveland, OH, USA.
Jeffrey SimkoPathology, UCSF, San Francisco, CA, USA.
Peter R CarrollUrology, UCSF, San Francisco, CA, USA.
Martin GleaveCanary Foundation, Palo Alto, CA, USA.
Daniel W LinUrology, University of Washington, Seattle, WA, USA.
Peter S NelsonUrology, University of Washington, Seattle, WA, USA.
Ian M ThompsonUrology, UTHSCSA, San Antonio, TX, USA.
Lawrence D TruePathology, University of Washington, Seattle, WA, USA.
James D BrooksUrology, Stanford University School of Medicine, Stanford, CA, USA.
Raymond LanceUrology, Eastern Virginia Medical School, Norfolk, VA, USA.
Dean TroyerUrology, Eastern Virginia Medical School, Norfolk, VA, USA.
Jeremy A SquireDepartment of Pathology and Molecular Medicine, Queen's University, Kingston, ON, Canada.
Johns Hopkins University · USCanary Foundation · USEastern Virginia Medical School · USQueen's University · CAThe University of Texas MD Anderson Cancer Center · USUniversity of California, San Francisco · USUniversity of Washington · USCleveland Clinic · USFred Hutch Cancer Center · USStanford University · USUniversidade de São Paulo · BRUrology San Antonio · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI WILLIAM George NELSON · 1985 to 2026
$208.6M
NCI NIH HHS P30 CA006973NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

PTEN loss is a promising prognostic and predictive biomarker in prostate cancer. Because it occurs most commonly via PTEN gene deletion, we developed a clinical-grade, automated, and inexpensive immunohistochemical assay to detect PTEN loss. We studied the sensitivity and specificity of PTEN immunohistochemistry relative to four-color fluorescence in situ hybridization (FISH) for detection of PTEN gene deletion in a multi-institutional cohort of 731 primary prostate tumors. Intact PTEN immunostaining was 91% specific for the absence of PTEN gene deletion (549/602 tumors with two copies of the PTEN gene by FISH showed intact expression of PTEN by immunohistochemistry) and 97% sensitive for the presence of homozygous PTEN gene deletion (absent PTEN protein expression by immunohistochemistry in 65/67 tumors with homozygous deletion). PTEN immunohistochemistry was 65% sensitive for the presence of hemizygous PTEN gene deletion, with protein loss in 40/62 hemizygous tumors. We reviewed the 53 cases where immunohistochemistry showed PTEN protein loss and FISH showed two intact copies of the PTEN gene. On re-review, there was ambiguous immunohistochemistry loss in 6% (3/53) and failure to analyze the same tumor area by both methods in 34% (18/53). Of the remaining discordant cases, 41% (13/32) revealed hemizygous (n=8) or homozygous (n=5) PTEN gene deletion that was focal in most cases (11/13). The remaining 19 cases had two copies of the PTEN gene detected by FISH, representing truly discordant cases. Our automated PTEN immunohistochemistry assay is a sensitive method for detection of homozygous PTEN gene deletions. Immunohistochemistry screening is particularly useful to identify cases with heterogeneous PTEN gene deletion in a subset of tumor glands. Mutations, small insertions, or deletions and/or epigenetic or microRNA-mediated mechanisms may lead to PTEN protein loss in tumors with normal or hemizygous PTEN gene copy number.

Indexed as

ImmunohistochemistryIn Situ Hybridization, FluorescenceBiomarkers, TumorBritish ColumbiaGene DeletionGene DosageGenetic Predisposition to DiseaseHeterozygoteHomozygoteHumansMalePhenotypePredictive Value of TestsProstatic NeoplasmsPTEN PhosphohydrolaseReproducibility of ResultsBiomarkers, TumorPTEN PhosphohydrolasePTEN protein, human

Identifiers

PMID27174589
PMCPMC4967011
OpenAlexW2385742736

What OpenQuestion holds

Textmetadata
LicenceTDM
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.