BACKGROUND: Because of the inefficient vasculature of solid tumors, anticancer drugs must penetrate relatively long distances through the extravascular compartment. The requirement for such diffusion may limit their activity, especially that of hypoxia-targeted drugs. We tested whether a three-dimensional pharmacokinetic/pharmacodynamic (PK/PD) model based on a representative mapped tumor microvascular network could predict the therapeutic activity of anticancer drugs in mouse xenograft tumors. METHODS: Diffusion coefficients of the hypoxia-activated anticancer drug tirapazamine (TPZ) and of 15 TPZ analogs were estimated by measuring their transport through HT29 colon cancer multicellular layers (MCLs). Anoxic cytotoxic potency (by clonogenic assay) and metabolism of the TPZ analogs were measured in HT29 cell suspensions, and their plasma pharmacokinetics was measured in CD-1 nude mice. This information was used to create a spatially resolved PK/PD model for the tumor microvascular network. Model predictions were compared with actual hypoxic cell kill as measured by clonogenic assays on HT29 xenograft tumors 18 hours after treatment with each TPZ analog. RESULTS: Modeling TPZ transport in the tumor microvascular network showed substantial drug depletion in the most hypoxic regions, with predicted maximum cell kill of only 3 logs, compared with more than 10 logs if there were no transport impediment. A large range of tissue diffusion coefficients (0.027 x 10(-6)-1.87 x 10(-6) cm2/s) was observed for the TPZ analogs. There was a strong correlation between model-predicted and measured hypoxic cell kill (R2 = 0.89) but a poor correlation when the model did not include extravascular transport (R2 = 0.32). CONCLUSIONS: Extravascular transport in tumors, and its consequences for tumor cell killing, can be predicted by measuring drug penetration through MCLs in vitro and modeling pharmacokinetics at each position in three-dimensional microvascular networks.
BACKGROUND: Because of the inefficient vasculature of solid tumors, anticancer drugs must penetrate relatively long distances through the extravascular compartment. The requirement for such diffusion may limit their activity, especially that of hypoxia-targeted drugs. We tested whether a three-dimensional pharmacokinetic/pharmacodynamic (PK/PD) model based on a representative mapped tumor microvascular network could predict the therapeutic activity of anticancer drugs in mousexenograft tumors. METHODS: Diffusion coefficients of the hypoxia-activated anticancer drug tirapazamine (TPZ) and of 15 TPZ analogs were estimated by measuring their transport through HT29 colon cancer multicellular layers (MCLs). Anoxic cytotoxic potency (by clonogenic assay) and metabolism of the TPZ analogs were measured in HT29 cell suspensions, and their plasma pharmacokinetics was measured in CD-1 nude mice. This information was used to create a spatially resolved PK/PD model for the tumor microvascular network. Model predictions were compared with actual hypoxic cell kill as measured by clonogenic assays on HT29 xenograft tumors 18 hours after treatment with each TPZ analog. RESULTS: Modeling TPZ transport in the tumor microvascular network showed substantial drug depletion in the most hypoxic regions, with predicted maximum cell kill of only 3 logs, compared with more than 10 logs if there were no transport impediment. A large range of tissue diffusion coefficients (0.027 x 10(-6)-1.87 x 10(-6) cm2/s) was observed for the TPZ analogs. There was a strong correlation between model-predicted and measured hypoxic cell kill (R2 = 0.89) but a poor correlation when the model did not include extravascular transport (R2 = 0.32). CONCLUSIONS: Extravascular transport in tumors, and its consequences for tumor cell killing, can be predicted by measuring drug penetration through MCLs in vitro and modeling pharmacokinetics at each position in three-dimensional microvascular networks.
Authors: Xinjian Mao; Sarah McManaway; Jagdish K Jaiswal; Cho R Hong; William R Wilson; Kevin O Hicks Journal: Cancer Biol Ther Date: 2019-05-26 Impact factor: 4.742
Authors: Michael P Hay; Kevin O Hicks; Karin Pchalek; Ho H Lee; Adrian Blaser; Frederik B Pruijn; Robert F Anderson; Sujata S Shinde; William R Wilson; William A Denny Journal: J Med Chem Date: 2008-10-11 Impact factor: 7.446
Authors: Rafael Duran; Sahar Mirpour; Vasily Pekurovsky; Shanmugasundaram Ganapathy-Kanniappan; Cory F Brayton; Toby C Cornish; Boris Gorodetski; Juvenal Reyes; Julius Chapiro; Rüdiger E Schernthaner; Constantine Frangakis; MingDe Lin; Jessica D Sun; Charles P Hart; Jean-François Geschwind Journal: Clin Cancer Res Date: 2016-07-20 Impact factor: 12.531