Prospective-Retrospective Analysis of PTEN Immunohistochemistry Assay for Prediction of Outcomes in Recurrent and Metastatic Prostate Cancer

Abstract

As part of the CDMRP-funded Precision Medicine Biomarker Validating Center, we have developed a robust, highly analytically validated and cost-effective immunohistochemistry (IHC)-based assay to interrogate PTEN loss in prostate cancer. Our PTEN assay is prognostic in multiple cohorts of surgically-treated prostate cancer patients; now, we propose to leverage this body of previous validation studies to test the hypothesis that PTEN loss in primary prostate cancer predicts for a less robust response to hormonal therapies, in the context of two recent, practice-changing Phase III clinical trials for which we have CTEP approval to access specimens. Here, we report on progress to date. We have obtained tissue microarrays containing tissues from 306 patients for RTOG96-01 and immunostained them for PTEN and ERG. In initial analyses, patients with intact PTEN have a 50 percent decrease in cumulative incidence of metastasis with combined radiation therapy and anti-androgen therapy compared to radiation therapy alone, while patients with PTEN loss do not see the benefit of additional anti-androgen therapy.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2020
Accession Number
AD1120882

Entities

People

  • Tamara L Lotan

Organizations

  • Johns Hopkins University

Tags

DTIC Thesaurus Topics

  • Androgens
  • Biological Staining And Labeling
  • Biomedical Research
  • Cancer
  • Data Analysis
  • Demographic Cohorts
  • Department Of Defense
  • Diseases And Disorders
  • Electronic Mail
  • Hazards
  • Immunohistochemistry
  • Immunostaining
  • Internet
  • Maryland
  • Medical Personnel
  • Neoplasms
  • Patent Applications
  • Personalized Medicine
  • Prostate
  • Prostate Cancer
  • Standards
  • Therapy
  • United States
  • Universities

Fields of Study

  • Medicine

Readers

  • Molecular Biology and Genetics
  • Oncology
  • Oncology and Biomarker-Based Cancer Detection.