Biomarker Based Individual Risk Assessment for Prostate Cancer

Abstract

The goal of this work is to develop a biomarker profile for prostate cancer risk, based on cell signaling proteins that serve as high-level biomarkers of cellular subsystems; e.g, tissue transglutaminase (TTGase), gelsolin, beta-catenin, thymosin beta-4, G-actin, E-cadherin, survivin, and purinergic receptor P2X7. TTGase, cadherins, and 6-actin are strong biomarkers of prostate cancer and may be strong biomarkers of field disease and premalignancy. The biomarker profile will identify individuals for prostate cancer prevention and rebiopsy, with high sensitivity and specificity, complementing serum PSA screening that captures 95% of prostate cancer cases with only 20% specificity. Acquisition and fixation of prostate tissues are optimized. Prostate and bladder cell lines are being used for standardization purposes. Optimal labeling conditions including epitope retrieval, incubation periods and indicator systems are tested, analyzed, and compared. Quantitative Fluorescence Imaging Analysis (QFIA) allows precise quantification of high-level biomarkers in prostate tissues and cell lines. The observed down regulation of TTGase and beta-catenin in resected, cancer-bearing prostate glands suggests that high-level biomarkers of cellular subsystems could be effective biomarkers of early prostate cancer and premalignant disease.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2004
Accession Number
ADA430343

Entities

People

  • George P. Hemstreet Iii

Organizations

  • University of Nebraska Medical Center

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Biological Markers
  • Cell Line
  • Cell Physiological Processes
  • Cells
  • Chemistry
  • Diseases And Disorders
  • Fluorescence
  • Glands
  • Medical Personnel
  • Neoplasms
  • Prostate Cancer
  • Prostate Gland
  • Proteins
  • Regulations
  • Risk
  • Risk Analysis

Fields of Study

  • Biology

Readers

  • Oncology (Cancer Research).
  • Oncology and Biomarker-Based Cancer Detection.