Display Settings:

Format

Send to:

Choose Destination
    Br J Cancer. 2010 Feb 16;102(4):678-84. Epub 2010 Jan 26.

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

    Source

    The Institute of Cancer Research, Male Urological Cancer Research Centre, Surrey, UK.

    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.

    PMID:
    20104229
    [PubMed - indexed for MEDLINE]
    PMCID:
    PMC2837564
    Free PMC Article

    Images from this publication.See all images (3) Free text

    Figure 2
    Figure 1
    Figure 3

      Supplemental Content

      Icon for Nature Publishing Group Icon for PubMed Central

      Save items

      loading

      Recent activity

      Your browsing activity is empty.

      Activity recording is turned off.

      Turn recording back on

      See more...
      Write to the Help Desk