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Exploiting the synergy between carboplatin and ABT-737 in the treatment of ovarian carcinomas

Jain, HV; Richardson, A; Meyer-Hermann, M; Byrne, HM

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Authors

HV Jain

M Meyer-Hermann

HM Byrne



Abstract

Platinum drug-resistance in ovarian cancers mediated by anti-apoptotic proteins such as Bcl-xL is a major factor contributing to the chemotherapeutic resistance of recurrent disease. Consequently, concurrent inhibition of Bcl-xL in combination with chemotherapy may improve treatment outcomes for patients. Here, we develop a mathematical model to investigate the potential of combination therapy with ABT-737, a small molecule inhibitor of Bcl-xL, and carboplatin, a platinum-based drug, on a simulated tumor xenograft. The model is calibrated against in vivo experimental data, wherein xenografts established in mice were treated with ABT-737 and/or carboplatin on a fixed periodic schedule. The validated model is used to predict the minimum drug load that will achieve a predetermined level of tumor growth inhibition, thereby maximizing the synergy between the two drugs. Our simulations suggest that the infusion-duration of each carboplatin dose is a critical parameter, with an 8-hour infusion of carboplatin given weekly combined with a daily bolus dose of ABT-737 predicted to minimize residual disease. The potential of combination therapy to prevent or delay the onset of carboplatin-resistance is also investigated. When resistance is acquired as a result of aberrant DNA-damage repair in cells treated with carboplatin, drug delivery schedules that induce tumor remission with even low doses of combination therapy can be identified. Intrinsic resistance due to pre-existing cohorts of resistant cells precludes tumor regression, but dosing strategies that extend disease-free survival periods can still be identified. These results highlight the potential of our model to accelerate the development of novel therapeutics such as BH3 mimetics.

Acceptance Date Oct 23, 2013
Publication Date Jan 6, 2014
Publicly Available Date Mar 29, 2024
Journal PLoS One
Print ISSN 1932-6203
Publisher Public Library of Science
Pages e81582 - ?
DOI https://doi.org/10.1371/journal.pone.0081582
Keywords algorithms, animals, biphenyl compounds, carboplatin, cell line, tumor, computer simulation, disease models, animal, drug resistance, neoplasm, drug synergism, female, humans, mice, models, biological, nitrophenols, ovarian neoplasms, piperazines, sulfona
Publisher URL http://dx.doi.org/10.1371/journal.pone.0081582

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