Prostate cancer genes associated with TMPRSS2–ERG gene fusion and prognostic of biochemical recurrence in multiple cohorts

Abstract

BACKGROUND: Recent studies have indicated that prostate cancer patients with the TMPRSS2 -ERG gene fusion have a higher risk of recurrence. To identify markers associated with TMPRSS2 -ERG fusion and prognostic of biochemical recurrence, we analysed a cohort of 139 men with prostate cancer for 502 molecular markers. METHODS: RNA from radical prostatectomy tumour specimens was analysed using cDNA-mediated, annealing, selection, extension and ligation (DASL) to determine mRNAs associated with TMPRSS2 -ERG T1/E4 fusion and prognostic of biochemical recurrence. Differentially expressed mRNAs in T1/E4-positive tumours were determined using significance analysis of microarrays (false discovery rate (FDR) o5%). Univariate and multivariate Cox regression determined genes, gene signatures and clinical factors prognostic of recurrence (P-value o0.05, log -rank test). Analysis of two prostate microarray studies (GSE1065 and GSE8402) validated the findings. RESULTS: In the 139 patients from this study and from a 455-patient Swedish cohort, 15 genes in common were differentially regulated in T1/E4 fusion-positive tumours (FDR o0.05). The most significant mRNAs in both cohorts coded ERG. Nine genes were found prognostic of recurrence in this study and in a 596-patient Minnesota cohort. A molecular recurrence score was significant in prognosticating recurrence (P-value 0.000167) and remained significant in multivariate analysis of a mixed clinical model considering Gleason score and TMPRSS2 -ERG fusion status. CONCLUSIONS: TMPRSS2 -ERG T1/E4 fusion-positive tumours had differentially regulated mRNAs observed in multiple studies, the most significant one coded for ERG. Several mRNAs were consistently associated with biochemical recurrence and have potential clinical utility but will require further validation for successful translation.

Genomic Predictors of Outcome in Prostate Cancer

“…Barwick and coworkers noted that the expression of several genes was affected by TMPRSS2:ERG fusion status [39]. In fusionpositive cases, upregulated genes were related to mismatch base repair and histone deacetylation, whereas genes involved in insulinlike growth factor (IGF) and Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling were downregulated [39].…”

“…Barwick and coworkers noted that the expression of several genes was affected by TMPRSS2:ERG fusion status [39]. In fusionpositive cases, upregulated genes were related to mismatch base repair and histone deacetylation, whereas genes involved in insulinlike growth factor (IGF) and Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling were downregulated [39]. In addition Brase et al showed the TMPRSS2-ERG gene fusion results in the modulation of certain transcriptional patterns and wellknown PCa biomarkers like CRISP3 and TDRD1 that were found to be associated with the gene fusions [40].…”

Septin roles in tumorigenesis

“…The gene fusion between the transmembrane protease serine 2 (TMPRSS2) and the v-ets erythroblastosis virus E26 oncogene (ERG) is found in a majority of prostate cancers and is associated with a more aggressive clinical phenotype relative to other prostate cancers (Demichelis and Rubin, 2007;Nam et al, 2007;Attard et al, 2008). Multiple studies have revealed that SEPT9 is upregulated in tumors containing this chromosomal fusion (Setlur et al, 2008;Barwick et al, 2010). Of heightened interest was that Setlurs group also indicated that the TMPRSS2-ERG oncogene could be regulated by estrogen receptor (ER) dependent pathways, with ERa agonists stimulating its expression in this distinct class of prostate cancer.…”

Identification of Biomarkers for Prostate Cancer Prognosis Using a Novel Two-Step Cluster Analysis

“…Therefore, genes that do not contribute to accurate classification may not be of clinical use even though they may be biologically related to the disease. One reviewer suggested further Gene Ontology study or Enrichment analysis of the genes that have not been selected in gene identification process owing to the fact that they do not meet the membership criterion in step (2). We agree that such analysis would help gain valuable information conveyed by those "ignored" genes.…”

“…This information would guide treatment choices, avoid inappropriate radical prostatectomy and provide guidance to those who may profit from adjuvant therapy in the post-prostatectomy setting, a period that is seldom utilized as a treatment window. Much effort has been made to identify gene expression changes between aggressive cases and indolent cases [2,3,4]. Standard analytical approaches, such as t-test, significance analysis of microarray (SAM) [5] and linear models for microarray data (LIMMA) [6], have been applied to these studies.…”