Identification and Characterization of Prostate Cancer Associated Protein Biomarkers Using High-Throughput Mass Spectrometry

Abstract

Prostate cancer (PCa) remains to be the most common non-skin cancer in the US. Currently available screening tests for PCa including prostate specific antigen (PSA) test, digital rectal examination (DRE) and prostate biopsy, call for more accurate and non-invasive techniques to detect, diagnose, and stratify the disease based on molecular markers present in the body fluids. Using MALDI-TOF mass spectrometry protein fingerprint profiling, we generated decision tree algorithms to classify cancer from non-cancer. We have also devised strategies to isolate and identify protein biomarkers from the fingerprint profiles of PCa patients in the clinical gray-area where PSA fails to detect cancer. Identification of such cancer biomarkers will assist in development of better non-invasive diagnostic tools for prostate cancer and may also lead to better therapeutic targets.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2007
Accession Number
ADA477537

Entities

People

  • Gunjan Malik

Tags

Communities of Interest

  • Autonomy
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Blood Proteins
  • Body Fluids
  • Chemical Synthesis
  • Chemistry
  • Diseases And Disorders
  • Identification
  • Mass Spectrometry
  • Mass Spectroscopy
  • Neoplasms
  • Prostate Cancer
  • Proteins
  • Proteomics
  • Spectra
  • Spectrometry
  • Spectroscopy
  • Supervised Machine Learning

Fields of Study

  • Biology

Readers

  • Oncology and Biomarker-Based Cancer Detection.
  • Prostate Cancer Biology.