Molecular characterisation of ERG, ETV1 and PTEN gene loci identifies patients at low and high risk of death from prostate ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-02

AUTHORS

A H M Reid, G Attard, L Ambroisine, G Fisher, G Kovacs, D Brewer, J Clark, P Flohr, S Edwards, D M Berney, C S Foster, A Fletcher, W L Gerald, H Møller, V E Reuter, P T Scardino, J Cuzick, J S de Bono, C S Cooper

ABSTRACT

BACKGROUND: The discovery of ERG/ETV1 gene rearrangements and PTEN gene loss warrants investigation in a mechanism-based prognostic classification of prostate cancer (PCa). The study objective was to evaluate the potential clinical significance and natural history of different disease categories by combining ERG/ETV1 gene rearrangements and PTEN gene loss status. METHODS: We utilised fluorescence in situ hybridisation (FISH) assays to detect PTEN gene loss and ERG/ETV1 gene rearrangements in 308 conservatively managed PCa patients with survival outcome data. RESULTS: ERG/ETV1 gene rearrangements alone and PTEN gene loss alone both failed to show a link to survival in multivariate analyses. However, there was a strong interaction between ERG/ETV1 gene rearrangements and PTEN gene loss (P<0.001). The largest subgroup of patients (54%), lacking both PTEN gene loss and ERG/ETV1 gene rearrangements comprised a 'good prognosis' population exhibiting favourable cancer-specific survival (85.5% alive at 11 years). The presence of PTEN gene loss in the absence of ERG/ETV1 gene rearrangements identified a patient population (6%) with poorer cancer-specific survival that was highly significant (HR=4.87, P<0.001 in multivariate analysis, 13.7% survival at 11 years) when compared with the 'good prognosis' group. ERG/ETV1 gene rearrangements and PTEN gene loss status should now prospectively be incorporated into a predictive model to establish whether predictive performance is improved. CONCLUSIONS: Our data suggest that FISH studies of PTEN gene loss and ERG/ETV1 gene rearrangements could be pursued for patient stratification, selection and hypothesis-generating subgroup analyses in future PCa clinical trials and potentially in patient management. More... »

PAGES

678

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/sj.bjc.6605554

    DOI

    http://dx.doi.org/10.1038/sj.bjc.6605554

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1048931941

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20104229


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