Relapse of prostate cancer after androgen ablation therapy is hormone-refractory, with continued tumor growth being dependent on the androgen receptor (AR). E2F-1, a regulator of cell proliferation and viability, reportedly plays a role in the development of hormone-refractory prostate cancer. Thymoquinone is a component of Nigella sativa, an herb used for thousands of years for culinary and medicinal purposes in Asian and Middle Eastern countries and has been reported to have an antineoplastic effect both in vitro and in vivo. We observed that thymoquinone inhibited DNA synthesis, proliferation, and viability of cancerous (LNCaP, C4-B, DU145, and PC-3) but not noncancerous (BPH-1) prostate epithelial cells by downregulating AR and E2F-1. In LNCaP cells, this was associated with a dramatic increase in p21 Cip1 , p27 Kip1 , and Bax. Thymoquinone blunted progression of synchronized LNCaP cells from G 1 to S phase, with a concomitant decrease in AR and E2F-1 as well as the E2F-1-regulated proteins necessary for cell cycle progression. In a xenograft prostate tumor model, thymoquinone inhibited growth of C4-2B-derived tumors in nude mice. This in vivo suppression of tumor growth, as with C4-2B cell growth in culture, was associated with a dramatic decrease in AR, E2F-1, and cyclin A as determined by Western blot of tissue extracts. Tissue immunohistochemical staining confirmed a marked reduction in E2F-1 and showed induction of apoptosis on terminal deoxyribonucleotidyl transferase-mediated dUTP nick end labeling assay. These findings show that thymoquinone suppresses the expression of AR and E2F-1 necessary for proliferation and viability of androgen-sensitive as well as androgen-independent prostate cancer cells both in vitro and in vivo and, moreover, produced no noticeable side effects in mice. We conclude that thymoquinone, a naturally occurring herbal product, may prove to be effective in treating hormone-sensitive as well as hormone-refractory prostate cancer. Furthermore, because of its selective effect on cancer cells, we believe that thymoquinone can also be used safely to help prevent the development of prostate cancer. [Cancer Res 2007;67(16):7782-8]

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Although inactivation of the androgen receptor (AR) by androgen-ablation or anti-androgen treatment has been frontline therapy for disseminated prostate cancer for over 60 years, it is not curative because castration-resistant prostate cancer cells retain AR activity. Therefore, curative strategy should include targeted elimination of AR protein. Since AR binds to calmodulin (CaM), and since CaM-binding proteins are targets of calpain-mediated proteolysis, we studied the role of CaM and calpain in AR breakdown in prostate cancer cells. Whereas the treatment of prostate cancer cells individually with anti-CaM drug or calcimycin, which increases intracellular Ca ++ and activates calpain, led to minimal AR breakdown, combined treatment led to a precipitous decrease in AR protein levels. This decrease in AR protein occurred without noticeable changes in AR mRNA levels, suggesting an increase in AR protein turnover rather than inhibition of AR mRNA expression. Thus, CaM inactivation seems to sensitize AR to calpain-mediated breakdown in prostate cancer cells. Consistent with this possibility, purified recombinant human AR (rhAR) underwent proteolysis in the presence of purified calpain, and the addition of purified CaM to the incubation blocked rhAR proteolysis. Together, these observations demonstrate that AR is a calpain target and AR-bound CaM plays an important role in protecting AR from calpainmediated breakdown in prostate cancer cells. These observations raise an intriguing possibility that anti-CaM drugs in combination with calpain-activating agents may offer a curative strategy for the treatment of prostate cancer, which relies on AR for growth and survival. KeywordsAndrogen receptor; calmodulin; calpain; hormone-refractory prostate cancer Prostate cancer is the most frequently diagnosed non-skin cancer and second leading cause of cancer deaths in American men (Jemal et al., 2009). Androgen, by activating the androgen receptor (AR), plays a pivotal role in prostate cancer cell proliferation and viability (Magi-Galluzzi et al., 1998). Hence, androgen ablation has been frontline therapy for the treatment of advanced prostate cancer. However, androgen-deprivation therapy (ADT) is only palliative and most patients receiving ADT eventually succumb to castrationresistant prostate cancer (CRPC) that is also resistant to chemotherapy (Feldman and Feldman, 2001). Furthermore, whether normal or mutated, AR continues to play an important role in progression of CRPC (Feldman and Feldman, 2001;van der Kwast et al., 1991) and is required for proliferation and survival of both androgen-sensitive as well as androgen-independent AR-positive prostate cancer cells (Haag et al., 2005;Snoek et Yuan et al., 2006;Zegarra-Moro et al., 2002). Therefore, developing a curative strategy for the treatment of hormone-refractory disease requires identifying effective means to eliminate AR protein in prostate cancer cells .Overexpression of AR is reported to be involved in the progression to CRPC (Chen et al., 2004). Besides AR gen...

OBJECTIVE To assess the magnitude of variability among 11 formulae for human body surface area (BSA) and then among eight for plasma volume (PV), as used to represent physiological indices for body metabolism, drug dosages and body fluid management, and to evaluate the potential cumulative effect of variance inflation with prostate‐specific antigen (PSA) mass as an endpoint. PATIENTS AND METHODS In 3020 men undergoing robotic radical prostatectomy (RRP) at the Vattikuti Urology Institute between 2001 and 2008, the variation in BSA and PV formulae was calculated, as well as PSA mass, using analysis of variance (anova), Bland‐Altman plots, linear regression, and correlation analyses. RESULTS For estimating BSA, anova indicated significant variance among the 11 formulae used (P < 0.001) with a between‐groups variance of 5.45. Bland‐Altman plots reported bias when the Dubois formula was compared to other BSA formulae. Furthermore the anova for PV, with BSA as a predictor, indicated significant variance among the eight formulae used (P < 0.001), with a mean between‐group variance of 444.4 and a mean inflation factor of 81.5. Scatter plots between one PV formula (Boer) and others had a good linear fit. For PSA mass, anova indicated significant variance (P < 0.001) using PV as a predictor, with a mean between‐group variance of 16 799.6 and a mean variance inflation factor of 37.8. CONCLUSIONS There is significant variation in the BSA calculated by commonly used formulae. This variation is carried over and further magnified in the sequential calculation of PV and PSA mass. Hence arbitrary selection of BSA and PV formulae is likely to affect inferences.