Now showing 1 - 3 of 3
  • 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.
      515Scopus© Citations 6
  • Publication
    The Contribution of Morphological Features in the Classification of Prostate Carcinoma in Digital Pathology Images
    In this paper we present work on the development of a system for automated classification of digitized H&E histopathology images of prostate carcinoma (PCa). In our system, images are transformed into a tiled grid from which various texture and morphological features are extracted. We evaluate the contribution of high-level morphological features such as those derived from tissue segmentation algorithms as they relate to the accuracy of our classifier models. We also present work on an algorithm for tissue segmentation in image tiles, and introduce a novel feature vector representation of tissue classes in same. Finally, we present the classification accuracy, sensitivity and specificity results of our system when performing three tasks: distinguishing between cancer and non-cancer tiles, between low and high-grade cancer and between Gleason grades 3, 4 and 5. Our results show that the novel tissue representation outperforms the morphological features derived from tissue segmentation by a significant margin, but that neither feature sets improve on the accuracy gained by features from low-level texture methods.
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  • 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.
      559Scopus© Citations 15