Application of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model in studying the carcinogenic potential of hexacholorobenzene, PCB 126, and their mixture

Abstract

This dissertation research studied the carcinogenic potential of hexachlorobenzene (HCB), 3,3',4,4',5-pentachlorobiphenyl (PCB 126), and their mixture (HCB+PCB 126) based on the integration of experimental bioassay and physiologically based modeling. It included collecting pharmacokinetic and preneoplastic foci (glutathione S-transferase placental-form, GST-P) data of the individual chemicals and the mixture in the context of an established medium-term liver foci bioassay, and then developing PBPK and clonal growth models based on the data generated. The foci bioassay involved a series of treatments, including a single injection of an initiating agent, a two-thirds partial hepatectomy, and daily oral gavage of a chemical solution in male Fischer 344 rats. The animals were sacrificed at five time points for time-course data. All bioassays were conducted at two doses: HCB 8.55 and 28.5 mg/kg, PCB 126 3.3 and 9.8 μg/kg, and HCB+PCB 126 8.55 mg/kg + 3.3 μg/kg and 28.5 mg/kg + 9.8 μg/kg. HCB was mainly distributed in the fat, followed by the liver and other tissues, in accordance with its lipophilicity. When HCB was co-administrated with PCB 126, its disposition was remarkably affected in two aspects. First, the amount of HCB accumulated in the body was reduced before partial hepatectomy and dramatically increased afterwards. The reason, we believe, is attributed to the alterations in HCB absorption and exsorption processes by PCB 126. Second, the partitioning of HCB into the fat, liver, and muscle was altered by PCB 126, which can be resulted from the severe fat mobilization under the conditions of partial hepatectomy and the treatment of HCB+PCB 126. A PBPK model was developed for HCB. This model included two special features: division of the blood compartment into plasma and erythrocytes due to the binding of HCB to erythrocytes, and the exsorption process (i.e., the plasma-to-gut lumen passive diffusion - a reversal of the absorption process). HCB, PCB 126, and their mixture displayed their carcinogenic potential in the liver foci bioassays by increasing the foci number and/or foci size. The comparisons of the foci data from the three bioassays suggested that there appeared to be a greater-than-additivity interaction at the low doses and a less-than-additivity interaction at the high doses between HCB and PCB 126 in terms of the size and number of foci at the last time point (day 56). A clonal growth model was developed for simulating the foci data from the HCB+PCB 126 bioassay, and then modified to simulate the foci data for the individual chemicals, HCB and PCB 126. The concept of negative selection and two-cell (types A and B; the latter with growth advantage) hypothesis were incorporated in the model. Furthermore, we explored the size-dependent growth kinetics of the initiated cells by grouping the foci into four categories according to their size. Each category was assumed to have distinct growth kinetics. The model was parameterized with the information from the literature as well as from our own study. The simulations were in good agreement with three pieces of data: relative foci volume, foci number/cm3 of liver, and size distribution, which were derived from the bioassays. The interaction between HCB and PCB 126 was also examined by comparing the growth kinetic parameters of type B initiated cells/foci under HCB, PCB 126, and the mixture treatment. At the low doses, a greater-than-additivity interaction occurred in promoting mini- (2-11 cells) and medium-foci (12-399 cells), and at the high doses, a less-than-additivity interaction took place in promoting large-foci (>399 cells). This research improved our understanding in the pharmacokinetics and the pharmacodynamics regarding carcinogenic potential of HCB, PCB 126, and their mixture in the context of a medium-term liver foci bioassay. Continuing on the earlier contribution in PBPK and clonal growth modeling from our laboratory, the present work added the unique perspectives of considering the pharmacokinetics and pharmacodynamics of a chemical mixture, as well as the refinement of clonal growth modeling by categorizing liver GST-P foci into different classes. Once again, we were able to illustrate how the biologically based computational modeling facilitated our study on chemical carcinogenesis.