Use of collateral sensitivity networks to design drug cycling protocols that avoid resistance development.

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Abstract

New drug deployment strategies are imperative to address the problem of drug resistance, which is limiting the management of infectious diseases and cancers. We evolved resistance in Escherichia coli toward 23 drugs used clinically for treating bacterial infections and mapped the resulting collateral sensitivity and resistance profiles, revealing a complex collateral sensitivity network. On the basis of these data, we propose a new treatment framework--collateral sensitivity cycling--in which drugs with compatible collateral sensitivity profiles are used sequentially to treat infection and select against drug resistance development. We identified hundreds of such drug sets and demonstrated that the antibiotics gentamicin and cefuroxime can be deployed cyclically such that the treatment regimen selected against resistance to either drug. We then validated our findings with related bacterial pathogens. These results provide proof of principle for collateral sensitivity cycling as a sustainable treatment paradigm that may be generally applicable to infectious diseases and cancer.

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Sequential application of anticancer drugs enhances cell death by rewiring apoptotic signaling networks.

Michael J. Lee, Albert S. Ye, Alexandra K. Gardino … (2012)

Crosstalk and complexity within signaling pathways and their perturbation by oncogenes limit component-by-component approaches to understanding human disease. Network analysis of how normal and oncogenic signaling can be rewired by drugs may provide opportunities to target tumors with high specificity and efficacy. Using targeted inhibition of oncogenic signaling pathways, combined with DNA-damaging chemotherapy, we report that time-staggered EGFR inhibition, but not simultaneous coadministration, dramatically sensitizes a subset of triple-negative breast cancer cells to genotoxic drugs. Systems-level analysis-using high-density time-dependent measurements of signaling networks, gene expression profiles, and cell phenotypic responses in combination with mathematical modeling-revealed an approach for altering the intrinsic state of the cell through dynamic rewiring of oncogenic signaling pathways. This process converts these cells to a less tumorigenic state that is more susceptible to DNA damage-induced cell death by reactivation of an extrinsic apoptotic pathway whose function is suppressed in the oncogene-addicted state. Copyright © 2012 Elsevier Inc. All rights reserved.

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Mathematical models predict that the future of the multidrug-resistant tuberculosis epidemic will depend on the fitness cost of drug resistance. We show that in laboratory-derived mutants of Mycobacterium tuberculosis, rifampin resistance is universally associated with a competitive fitness cost and that this cost is determined by the specific resistance mutation and strain genetic background. In contrast, we demonstrate that prolonged patient treatment can result in multidrug-resistant strains with no fitness defect and that strains with low- or no-cost resistance mutations are also the most frequent among clinical isolates.