ABSTRACT
PURPOSE: To analyze the expression of hypoxia inducible factor 1 alpha (HIF1A) and its correlation with clinical outcome in men with localized prostate cancer (PC) treated with dose escalation radiotherapy (RT) and androgen deprivation (AD). METHODS: Between 1996 and 2004, 129 PC patients who had diagnostic biopsies pre-treatment and 24-36 months following RT were enrolled in this study. Median follow-up was 129 months. Suitable archival diagnostic tissue was obtained from 86 patients. Correlation analysis was done to assess association between HIF1A expression and clinical outcome. RESULTS: HIF1A expression was observed in 25/86 (29%) of diagnostic biopsies, and in 5/14 (36%) of post-RT biopsies. No significant association was noted between HIF1A expression and clinical and treatment parameters. We also failed to show a significant correlation between HIF1A overexpression and outcome. A borderline significant relationship was observed between expression of HIF1A and overall survival (OS) (HR 0.03, p=0.08). CONCLUSION: To our knowledge this is the first study assessing the pattern of change of HIF1A staining in biopsies of patients prior and following treatment. While we did not find significant variations in the expression of HIF1A following radio-hormone therapy, a high HIF1A expression was unexpectedly associated with a borderline improved OS.
Subject(s)
Hypoxia-Inducible Factor 1, alpha Subunit/biosynthesis , Prostatic Neoplasms/metabolism , Prostatic Neoplasms/radiotherapy , Dose Fractionation, Radiation , Dose-Response Relationship, Radiation , Humans , Male , Prognosis , Prostatic Neoplasms/pathology , Retrospective Studies , Survival Analysis , Treatment OutcomeABSTRACT
Clinical nomograms based on Gleason grade, tumor stage, and serum PSA are still the best predictors of prostate cancer (PC) outcome. The biotechnological advancements achieved in the last decade represent a remarkable source for new prognostic and predictive tissue and serum molecular biomarkers. In this review, we will summarize conventional PC prognostic biomarkers and focus on novel identified biomarkers for PC early diagnosis and progression that might be used in the future. Although they are not ready for widespread, routine use, there are reasons to believe that future models will combine these markers with traditional pretreatment and treatment-related variables and will improve our ability to predict outcome and select the optimal treatment.
