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ETS-related gene (ERG) expression as a predictor of oncological outcomes in patients with high-grade prostate cancer treated with primary androgen deprivation therapy: A cohort study

BMJ Open, Volume 9, No. 3, Article e025161, Year 2019

Objectives To determine whether ETS-related gene (ERG) expression can be used as a biomarker to predict biochemical recurrence and prostate cancer-specific death in patients with high Gleason grade prostate cancer treated with androgen deprivation therapy (ADT) as monotherapy. Methods A multicentre retrospective cohort study identifying 149 patients treated with primary ADT for metastatic or non-metastatic prostate cancer with Gleason score 8-10 between 1999 and 2006. Patients planned for adjuvant radiotherapy at diagnosis were excluded. Age at diagnosis, ethnicity, prostate-specific antigen and Charlson-comorbidity score were recorded. Prostatic tissue acquired at biopsy or transurethral resection surgery was assessed for immunohistochemical expression of ERG. Failure of ADT defined as prostate specific antigen nadir +2. Vital status and death certification data determined using the UK National Cancer Registry. Primary outcome measures were overall survival (OS) and prostate cancer specific survival (CSS). Secondary outcome was biochemical recurrence-free survival (BRFS). Results The median OS of our cohort was 60.2 months (CI 52.0 to 68.3). ERG expression observed in 51/149 cases (34%). Multivariate Cox proportional hazards analysis showed no significant association between ERG expression and OS (p=0.41), CSS (p=0.92) and BRFS (p=0.31). Cox regression analysis showed Gleason score (p=0.003) and metastatic status (p<1×10 -5) to be the only significant predictors of prostate CSS. Conclusions No significant association was found between ERG status and any of our outcome measures. Despite a limited sample size, our results suggest that ERG does not appear to be a useful biomarker in predicting response to ADT in patients with high risk prostate cancer.
Statistics
Citations: 7
Authors: 7
Affiliations: 6
Identifiers
Research Areas
Cancer
Genetics And Genomics
Health System And Policy
Study Design
Cohort Study
Study Approach
Quantitative