A 36-gene Signature Predicts Clinical Progression in a Subgroup of ERG -positive Prostate Cancers

• Published in: European urology Vol. 64; no. 6; pp. 941 - 950
• Main Authors: Gasi Tandefelt, Delila, Boormans, Joost L, van der Korput, Hetty A, Jenster, Guido W, Trapman, Jan
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 01.12.2013; Elsevier
• Subjects: Biological and medical sciences; Disease Progression; ETS; Expression arrays; Gene Expression Regulation, Neoplastic; Gynecology. Andrology. Obstetrics; Humans; Male; Male genital diseases; Medical sciences; Nephrology. Urinary tract diseases; Predictor; Prognosis; Prostate cancer; Prostatic Neoplasms - chemistry; Prostatic Neoplasms - genetics; TMPRSS2-ERG; Trans-Activators - analysis; Transcriptional Regulator ERG; Transcriptome; Tumors; Tumors of the urinary system; Urinary tract. Prostate gland; Urology; ETS; Predictor; Prostate cancer; TMPRSS2-ERG; Expression arrays; Nephrology; Urinary system disease; Prognosis; Prostate disease; Subgroup; Malignant tumor; Urology; Gene expression profile; C-Onc gene; Evolution; Predictive factor; Male genital diseases; Protooncogene; Cancer
• ISSN: 0302-2838; 1873-7560
• DOI: 10.1016/j.eururo.2013.02.039

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 ). Design, setting, and participants 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. Intervention Initial treatment of primary tumors was radical prostatectomy. Outcome measurements and statistical analysis Associations between clinical and histopathologic variables were evaluated by the Pearson χ2 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. Results and limitations 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.