Using molecular markers to predict outcome

J Urol. 2004 Nov;172(5 Pt 2):S18-21; discussion S21-2. doi: 10.1097/01.ju.0000142448.58831.d9.

Abstract

Purpose: Developing molecular tests to predict prostate cancer progression requires first defining meaningful clinical end points and defining strategies to take advantage of emerging technology.

Materials and methods: The select relevant literature was reviewed concerning clinical trials, clinical prostate cancer nomograms, molecular biomarker development and molecular prostate cancer imaging.

Results: There is controversy regarding the use of prostate specific antigen or biochemical failure following prostatectomy or radiation therapy for clinically localized prostate cancer as a marker of progression. As a consequence, advances in prostate cancer biomarker development may require using population based cohorts or cases from clinical trials to identify meaningful associations. Whereas the discovery of novel candidate biomarkers was slow 5 to 10 years ago and often resulted from serendipity, advances in high throughput technologies have led to the identification of a large number of candidate genes. Strategies to identify candidate genes include the use of expression array analysis, single nucleotide polymorphism arrays (single nucleotide polymorphism chips), proteomics and bioinformatics. Monitoring the progression of prostate cancer has been limited to standard approaches such as computerized tomography or magnetic resonance imaging, which in general do not delineate the extent of disease. By carefully selecting novel prostate cancer biomarkers future work should allow in vivo monitoring of prostate cancer. This will represent a revolutionary advance in our ability to monitor prostate cancer progression and ultimately it may be one of the most important applications of cancer biomarkers.

Conclusions: Emerging technology should allow us to analyze clinical prostate cancer trials with sufficient followup to help develop meaningful markers of prostate cancer progression.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Biomarkers, Tumor* / genetics
  • Computational Biology
  • Disease Progression
  • Humans
  • Male
  • Neoplasm Proteins / genetics
  • Oligonucleotide Array Sequence Analysis
  • Polymorphism, Single Nucleotide
  • Predictive Value of Tests
  • Prostatic Neoplasms / diagnosis
  • Prostatic Neoplasms / pathology*
  • Proteomics

Substances

  • Biomarkers, Tumor
  • Neoplasm Proteins
  • TPD52 protein, human