Flow cytometry-assisted Monte Carlo simulation predicts clonogenic survival of cell populations with lognormal distributions of radiopharmaceuticals and anticancer drugs

Abstract

Purpose: Although the distribution of therapeutic agents within cell populations may appear uniform at the macroscopic level, the distribution at the multicellular level is nonuniform. As such, the mean agent concentration in tissue may not be a suitable quantity for use in predicting biological effects. Failure in chemotherapy and targeted radionuclide therapy has been attributed, in part, to the ubiquity of lognormal distributions of therapeutic agents. To improve capacity to predict biological response, this work develops approaches that determine the fate of a cell population on a cell-by-cell basis.Methods: Incorporation of the α-particle emitting radiochemical (210Po-citrate) and two anticancer drugs (daunomycin and doxorubicin) by Chinese hamster V79 cells was determined using flow cytometry. Monte Carlo simulation was used to estimate cell survival on the bases of mean and individual cell incorporation of each cytotoxic agent. The interrelationships between the Monte Carlo simulated cell survival and clonogenic cell survival were evaluated.Results: Cell survival obtained by Monte Carlo simulation based on individual cell incorporation was in good agreement with clonogenic cell survival for all agents. However, the agreement was poor when the simulation was carried out using the mean cell incorporation of the agents.Conclusion: These data indicate that, with the aid of flow cytometry, Monte Carlo simulations can be used to predict the toxicity of therapeutic agents in a manner that takes into account the effects of lognormal and other nonuniform distributions of agents within cell populations.