Background: We have recently introduced a modification of the seminal Simeoni model for tumor growth, the modification entailing the incorporation of delay differential equations into its formulation. We found that the modification was competitive with the Simeoni construct in modeling mammary tumor growth under cisplatin treatment in an animal model.
Methods: In our original study, we had two cohorts of animals: untreated, and treatment with bolus injection of cisplatin on day 0. We here explore how modifications in the cisplatin dosing scheme affect tumor growth in our model.
Results: We found that modest fractionation dosing schemes have little ultimate impact on tumor growth. In contrast, metronomic dosing schemes seem quite efficacious, and might yield effective control over tumor progression.
Conclusions: With regard to cisplatin as single agent chemotherapy, a minimum level of drug for a prolonged period of time seems more critical than rapid achievement of a very high dose for a shorter time frame for deterring tumor growth or progression. Exploration of tumor dose schedules with mathematical models can provide valuable insights into potentially effective therapeutic regimens.
Background: We have recently published SL-BioDP, a web resource for querying, exploration and visualization of potential synthetic lethal targets and possible synergistic drug combinations for 18 cancer types.
Methods: From our predictive synthetic lethality model used in SL-BioDP, we inferred TP53 mutation lead to potential synergistic drug combination of Bortezomib and Vorinostat. Here we show, how to extrapolate the drug combination results by combining drug screening data from cancer cell lines and showed the potential synergy of the drug targets, proteasome, and histone deacetylase (HDAC) pathways respectively, for patient survival advantage.
Results: We found that TP53 mutation is potentially synthetic lethal with multiple genes from the proteasome and HDAC pathways exclusively in many cancer types. Also, HDAC and proteasomes were found to have potential synthetic lethal relationship. Using drug screening data in cancer cell line, the sensitivity of the HDAC inhibitor drug Vorinostat was found to be increased in TP53 mutated cells where the proteasome pathway was downregulated.
Conclusions: Our in-silico pharmacogenomic study indicates that the potential synergistic drug combination of proteasome and HDAC inhibitors may be considered as potential treatment for TP53-mutant cancers.
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