Development and validation of a 32-gene prognostic index for prostate cancer progression

Proc Natl Acad Sci U S A. 2013 Apr 9;110(15):6121-6. doi: 10.1073/pnas.1215870110. Epub 2013 Mar 26.

Abstract

The accurate determination of the risk of cancer recurrence is an important unmet need in the management of prostate cancer. Patients and physicians must weigh the benefits of currently available therapies against the potential morbidity of these treatments. Herein we describe the development of a gene expression-based continuous risk index and a validation of this test in an independent, blinded cohort of post-radical prostatectomy (RP) patients. A gene expression signature, prognostic for prostate-specific antigen (PSA) recurrence, was identified through a bioinformatic analysis of the expression of 1,536 genes in malignant prostate tissue from a training cohort of consecutive patients treated with RP. The assay was transferred to a real-time RT-PCR platform, and a continuous risk index model was constructed based on the expression of 32 genes. This 32-gene risk index model was validated in an independent, blinded cohort of 270 RP patients. In multivariate analyses, the risk index was prognostic for risk of PSA recurrence and had added value over standard prognostic markers such as Gleason score, pathologic tumor stage, surgical margin status, and presurgery PSA (hazard ratio, 4.05; 95% confidence interval, 1.50-10.94; P = 0.0057). Furthermore, RP patients could be stratified based on the risk of PSA recurrence and the development of metastatic disease. The 32-gene signature identified here is a robust prognostic marker for disease recurrence. This assay may aid in postoperative treatment selection and has the potential to impact decision making at the biopsy stage.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Biopsy
  • Cohort Studies
  • Disease Progression
  • Humans
  • Male
  • Middle Aged
  • Neoplasm Recurrence, Local
  • Prognosis
  • Proportional Hazards Models
  • Prostate / metabolism
  • Prostatic Neoplasms / diagnosis*
  • Prostatic Neoplasms / genetics
  • Prostatic Neoplasms / pathology*
  • Real-Time Polymerase Chain Reaction

Associated data

  • GEO/GSE44353