Boron uptake in normal melanocytes and melanoma cells and boron biodistribution study in mice bearing B16F10 melanoma for boron neutron capture therapy

Information on B-10 distribution in normal tissues is crucial to any further development of boron neutron capture therapy (BNCT). The goal of this study was to investigate the in vitro and in vivo boron biodistribution in B16F10 murine melanoma and normal tissues as a model for human melanoma treatment by a simple and rapid colorimetric method, which was validated by HR-ICP-MS. The B16F10 melanoma cell line showed higher melanin content than human melanocytes, demonstrating a greater potential for boronophenylalanine uptake. The melanocytes showed a moderate viability decrease in the first few minutes after BNCT application, stabilizing after 75 min, whereas the B16F10 melanoma showed the greatest intracellular boron concentration at 150 min after application, indicating a different boron uptake of melanoma cells compared to normal melanocytes. Moreover, at this time, the increase in boron uptake in melanoma cells was approximately 1.6 times higher than that in normal melanocytes. The B-10 concentration in the blood of mice bearing B16F10 melanoma increased until 90 min after BNCT application and then decreased after 120 min, and remained low until the 240th minute. On the other hand, the B-10 concentration in tumors was increased from 90 min and maximal at 150 min after application, thus confirming the in vitro results. Therefore, the present in vitro and in vivo study of B-10 uptake in normal and tumor cells revealed important data that could enable BNCT to be possibly used as a treatment for melanoma, a chemoresistant cancer associated with high mortality.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.