Now showing 1 - 6 of 6
  • Publication
    Uveal Melanoma Cell Line Proliferation Is Inhibited by Ricolinostat, a Histone Deacetylase Inhibitor
    Metastatic uveal melanoma (MUM) is characterized by poor patient survival. Unfortunately, current treatment options demonstrate limited benefits. In this study, we evaluate the efficacy of ACY-1215, a histone deacetylase inhibitor (HDACi), to attenuate growth of primary ocular UM cell lines and, in particular, a liver MUM cell line in vitro and in vivo, and elucidate the underlying molecular mechanisms. A significant (p = 0.0001) dose-dependent reduction in surviving clones of the primary ocular UM cells, Mel270, was observed upon treatment with increasing doses of ACY-1215. Treatment of OMM2.5 MUM cells with ACY-1215 resulted in a significant (p = 0.0001), dose-dependent reduction in cell survival and proliferation in vitro, and in vivo attenuation of primary OMM2.5 xenografts in zebrafish larvae. Furthermore, flow cytometry revealed that ACY-1215 significantly arrested the OMM2.5 cell cycle in S phase (p = 0.0001) following 24 h of treatment, and significant apoptosis was triggered in a time-and dose-dependent manner (p < 0.0001). Additionally, ACY-1215 treatment resulted in a significant reduction in OMM2.5 p-ERK expression levels. Through proteome profiling, the attenuation of the microphthalmia-associated transcription factor (MITF) signaling pathway was linked to the observed anti-cancer effects of ACY-1215. In agreement, pharmacological inhibition of MITF signaling with ML329 significantly reduced OMM2.5 cell survival and viability in vitro (p = 0.0001) and reduced OMM2.5 cells in vivo (p = 0.0006). Our findings provide evidence that ACY-1215 and ML329 are efficacious against growth and survival of OMM2.5 MUM cells.
      116Scopus© Citations 12
  • Publication
    Commercialized biomarkers: new horizons in prostate cancer diagnostics
    Limitations with current clinical tools available for diagnosis and prognosis of prostate cancer (PCa) have resulted in overdiagnosis and costly overtreatment, which is affecting the outcomes and quality of life of men. The biotech industry is investing significant resources into developing more specific biomarkers for PCa detection and patient stratification that would greatly advance the decision-making processes behind PCa management and treatment. In this review, we focus on those biomarkers that have been translated into commercial tests available to clinicians. Since these tests aim to fill specific gaps during the decision-making process of PCa management, we have grouped them based on the clinical question they claim to address, that is, improved PCa screening, false-negative biopsy dilemma, prognostic tests following a positive biopsy and tests predicting relapse/metastases after surgery. We evaluate each test with respect to its development, platform, clinical validation, biomatrix, regulatory approval status and cost.
      1107Scopus© Citations 12
  • Publication
    Relationship between serum response factor and androgen receptor in prostate cancer
    Background: Serum response factor (SRF) is an important transcription factor in castrate-resistant prostate cancer (CRPC). Since CRPC is associated with androgen receptor (AR) hypersensitivity, we investigated the relationship between SRF and AR. Materials and Methods: Transcriptional activity was assessed by luciferase assay. Cell proliferation was measured by MTT and flow cytometry. Protein expression in patients was assessed by immunohistochemistry. Results: To investigate AR involvement in SRF response to androgen, AR expression was down-regulated using siRNA. This resulted in the abrogation of SRF induction post-DHT. Moreover, DHT stimulation failed to induce SRF transcriptional activity in AR-negative PC346 DCC cells, which was only restored following AR over-expression. Next, SRF expression was down-regulated by siRNA, resulting in AR increased transcriptional activity in castrate-resistant LNCaP Abl cells but not in the parental LNCaP. This negative feedback loop in the resistant cells was confirmed by immunohistochemistry which showed a negative correlation between AR and SRF expression in CRPC bone metastases and a positive correlation in androgen-naïve prostatectomies. Cell proliferation was next assessed following SRF inhibition, demonstrating that SRF inhibition is more effective than AR inhibition in castrate-resistant cells. Conclusion: Our data support SRF as a promising therapeutic target in combination with current treatments. Prostate 75:1704–1717, 2015. © 2015 Wiley Periodicals, Inc.
      522Scopus© Citations 6
  • Publication
    Role of serum response factor expression in prostate cancer biochemical recurrence
    Background: Up to a third of prostate cancer patients fail curative treatment strategiessuch as surgery and radiation therapy in the form of biochemical recurrence (BCR) whichcan be predictive of poor outcome. Recent clinical trials have shown that menexperiencing BCR might benefit from earlier intervention post-radical prostatectomy(RP). Therefore, there is an urgent need to identify earlier prognostic biomarkers whichwill guide clinicians in making accurate diagnosis and timely decisions on the nextappropriate treatment. The objective of this study was to evaluate Serum ResponseFactor (SRF) protein expression following RP and to investigate its association with BCR.Materials and Methods: SRF nuclear expression was evaluated by immunohistochemistry(IHC) in TMAs across three international radical prostatectomy cohorts for a totalof 615 patients. Log-rank test and Kaplan-Meier analyses were used for BCRcomparisons. Stepwise backwards elimination proportional hazard regression analysiswas used to explore the significance of SRF in predicting BCR in the context of otherclinical pathological variables. Area under the curve (AUC) values were generated bysimulating repeated random sub-samples.Results: Analysis of the immunohistochemical staining of benign versus cancer coresshowed higher expression of nuclear SRF protein expression in cancer cores comparedwith benign for all the three TMAs analysed (P < 0.001, n = 615). Kaplan-Meier curves ofthe three TMAs combined showed that patients with higher SRF nuclear expression hada shorter time to BCR compared with patients with lower SRF expression (P < 0.001,n = 215). Together with pathological T stage T3, SRF was identified as a predictor of BCRusing stepwise backwards elimination proportional hazard regression analysis(P = 0.0521). Moreover ROC curves and AUC values showed that SRF was betterthan T stage in predicting BCR at year 3 and 5 following radical prostatectomy, thecombination of SRF and T stage had a higher AUC value than the two taken separately.Conclusions: SRF assessment by IHC following RP could be useful in guiding cliniciansto better identify patients for appropriate follow-up and timely treatment.
      448Scopus© Citations 8
  • Publication
    Evaluation of prediction models for the staging of prostate cancer
    Background: There are dilemmas associated with the diagnosis and prognosis of prostate cancer which has lead to over diagnosis and over treatment. Prediction tools have been developed to assist the treatment of the disease. Methods: A retrospective review was performed of the Irish Prostate Cancer Research Consortium database and 603 patients were used in the study. Statistical models based on routinely used clinical variables were built using logistic regression, random forests and k nearest neighbours to predict prostate cancer stage. The predictive ability of the models was examined using discrimination metrics, calibration curves and clinical relevance, explored using decision curve analysis. The N=603 patients were then applied to the 2007 Partin table to compare the predictions from the current gold standard in staging prediction to the models developed in this study. Results: 30% of the study cohort had non organ-confined disease. The model built using logistic regression illustrated the highest discrimination metrics (AUC=0.622, Sens=0.647, Spec=0.601), best calibration and the most clinical relevance based on decision curve analysis. This model also achieved higher discrimination than the 2007 Partin table (ECE AUC=0.572 & 0.509 for T1c and T2a respectively). However, even the best statistical model does not accurately predict prostate cancer stage. Conclusions: This study has illustrated the inability of the current clinical variables and the 2007 Partin table to accurately predict prostate cancer stage. New biomarker features are urgently required to address the problem clinicians face in identifying the most appropriate treatment for their patients. This paper also demonstrated a concise methodological approach to evaluate novel features or prediction models.
      312Scopus© Citations 19
  • Publication
    The analysis of serum response factor expression in bone and soft tissue prostate cancer metastases
    Castration-resistant prostate cancer (CRPC) represents a challenge to treat with no effective treatment options available. We recently identified serum response factor (SRF) as a key transcription factor in an in vitro model of castration resistance where we showed that SRF inhibition resulted in reduced cellular proliferation. We also demonstrated an association between SRF protein expression and CRPC in a cohort of castrate-resistant transurethral resections of the prostate (TURPS). The mechanisms regulating the growth of CRPC bone and visceral metastases have not been explored in depth due to the paucity of patient-related material available for analysis. In this study, we aim to evaluate SRF protein expression in prostate cancer (PCa) metastases, which has not previously been reported.
      574Scopus© Citations 15