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Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae
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Computational analysis of 5-fluorouracil anti-tumor activity in colon cancer using a mechanistic
Chenhui Ma1, Alex Almasan2,3, Evren Gurkan-Cavusoglu1
1Department of Electrical, Computer and Systems Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America.
Abstract:
5-Fluorouracil (5-FU) is a standard chemotherapeutic agent to treat solid cancers such as breast, colon, head, and neck. Computational modeling plays an essential role in predicting the outcome of chemotherapy and developing optimal dosing strategies. We developed an integrated mechanistic pharmacokinetics/pharmacodynamics (PK/PD) model examining the influence of 5-FU, as an S-phase specific double-strand break (DSB)-inducing agent, on tumor proliferation. The proposed mechanistic PK/PD model simulates the dynamics of critical intermediate components and provides the accurate tumor response prediction. The integrated model is composed of PK, cellular, and tumor growth inhibition (TGI) sub-models, quantitatively capturing the essential drug-related physiological processes. In the cellular model, thymidylate synthase (TS) inhibition, resultant deoxynucleoside triphosphate (dNTP) pool imbalance, and DSB induction are considered, as well as 5-FU incorporation into RNA and DNA. The amount of 5-FU anabolites and DSBs were modeled to drive the kinetics of the pharmacological tumor response. Model parameters were estimated by fitting to literature data. Our simulation results successfully describe the kinetics of the intermediates regulating the 5-FU cytotoxic events and the pattern of tumor suppression. The comprehensive model simulated the tumor volume change under various dose regimens, and its generalizability was attested by comparing it with literature data. The potential causes of the tumor resistance to 5-FU are also investigated through Monte Carlo analysis. The simulation of various dosage regimens helps quantify the relationship between treatment protocols and chemotherapy potency, which will lead to the development of efficacy optimization.
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