title: A 36-gene signature predicts clinical progression in a subgroup of ERG-positive prostate cancers.
abstract: BACKGROUND
  The molecular basis of the clinical heterogeneity of prostate cancer (PCa) is not well understood.
  
  
  OBJECTIVE
  The purpose of our study was to identify and characterize genes in a clinically relevant gene expression signature in a subgroup of primary PCa positive for transmembrane protease, serine 2 (TMPRSS2)-v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG).
  
  
  METHODS
  We studied gene expression profiles by unsupervised hierarchical clustering in 48 primary PCas from patients with a long clinical follow-up. Results were correlated with clinical outcome and validated in an independent patient cohort. Selected genes from a defined classifier were tested in vitro for biologic properties.
  
  
  METHODS
  Initial treatment of primary tumors was radical prostatectomy.
  
  
  METHODS
  Associations between clinical and histopathologic variables were evaluated by the Pearson χ(2) test, Mann-Whitney U test, or Kruskal-Wallis test, where appropriate. The log-rank test or Breslow method was used for statistical analysis of Kaplan-Meier survival curves.
  
  
  CONCLUSIONS
  Most tumors that overexpressed ERG clustered separately from other primary PCas. No differences in any clinical end points between ERG-positive and ERG-negative cancers were detected. Importantly, within the ERG-positive samples, two subgroups were identified, which differed significantly in prostate-specific antigen recurrence-free survival, and cancer-specific and overall survival. From our findings, we defined a gene expression classifier of 36 genes. In a second, completely independent tumor set, the classifier also distinguished ERG-positive subgroups with different clinical outcome. In both patient cohorts, the classifier was not predictive in ERG-negative tumors. Biologic processes regulated by genes in the classifier included cell adhesion and bone remodeling. Tumor growth factor-β signaling was indicated as the main differing signaling pathway between the two ERG subgroups. In vitro biologic assays of two selected genes from the classifier (inhibin, beta A [INHBA] and cadherin 11, type 2, OB-cadherin (osteoblast) [CDH11]) supported a functional role in PCa progression. Possible multifocality and limited number of PCa samples can be limitations of the study.
  
  
  CONCLUSIONS
  The classifier identified can contribute to prediction of tumor progression in ERG-positive primary prostate tumors and might be instrumental in therapy decisions.
authors.affiliation: Department of Pathology, Josephine Nefkens Institute, Erasmus University Medical Centre, Rotterdam, The Netherlands.
authors.forename: Delila
authors.initials: D
authors.lastname: Gasi Tandefelt
authors.forename: Joost L
authors.initials: JL
authors.lastname: Boormans
authors.forename: Hetty A
authors.initials: HA
authors.lastname: van der Korput
authors.forename: Guido W
authors.initials: GW
authors.lastname: Jenster
authors.forename: Jan
authors.initials: J
authors.lastname: Trapman
mesh_terms: D018450:Disease Progression; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008297:Male; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000737:chemistry / Q000235:genetics*; D015534:Trans-Activators / Q000032:analysis; D000071230:Transcriptional Regulator ERG; D059467:Transcriptome
chemical_list: C072312:ERG protein, human; D015534:Trans-Activators; D000071230:Transcriptional Regulator ERG
keywords: ETS; Expression arrays; Predictor; Prostate cancer; TMPRSS2-ERG