The margin for optimizing polychemotherapy is wide, but a quantitative comparison of current and new protocols is rare even in preclinical settings. In silico reconstruction of the proliferation process and the main perturbations induced by treatment provides insight into the complexity of drug response and grounds for a more objective rationale to treatment schemes. We analyzed 12 treatment groups in trial on an ovarian cancer xenograft, reproducing current therapeutic options for this cancer including one-, two-, and three-drug schemes of cisplatin (DDP), bevacizumab (BEV), and paclitaxel (PTX) with conventional and two levels ("equi" and "high") of dose-dense schedules. All individual tumor growth curves were decoded via separate measurements of cell death and other antiproliferative effects, gaining fresh insight into the differences between treatment options. Single drug treatments were cytostatic, but only DDP and PTX were also cytotoxic. After treatment, regrowth stabilized with increased propensity to quiescence, particularly with BEV. More cells were killed by PTX dose-dense-equi than with PTX conventional, but with the addition of DDP, cytotoxicity was similar and considerably less than expected from that of individual drugs. In the DDP/PTX dose-dense-high scheme, both cell death and regrowth impairment were intensified enough to achieve complete remission, and addition of BEV increased cell death in all schemes. The results support the option for dose-dense PTX chemotherapy with active single doses, showing the relative additional contribution of BEV, but also indicate negative drug interactions in concomitant DDP/PTX treatments, suggesting that sequential schedules could improve antitumor efficacy. Cancer Res; 77(23); 6759–69. ©2017 AACR.
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Πέμπτη 30 Νοεμβρίου 2017
Modeling Cytostatic and Cytotoxic Responses to New Treatment Regimens for Ovarian Cancer
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Αλέξανδρος Γ. Σφακιανάκης Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,0030693260717...
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heory of COVID-19 pathogenesis Publication date: November 2020Source: Medical Hypotheses, Volume 144Author(s): Yuichiro J. Suzuki ScienceD...
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