Literature DB >> 24068739

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

Lejla Imamovic1, Morten O A Sommer.   

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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Year:  2013        PMID: 24068739     DOI: 10.1126/scitranslmed.3006609

Source DB:  PubMed          Journal:  Sci Transl Med        ISSN: 1946-6234            Impact factor:   17.956


  155 in total

1.  Prediction of resistance development against drug combinations by collateral responses to component drugs.

Authors:  Christian Munck; Heidi K Gumpert; Annika I Nilsson Wallin; Harris H Wang; Morten O A Sommer
Journal:  Sci Transl Med       Date:  2014-11-12       Impact factor: 17.956

Review 2.  Multidrug evolutionary strategies to reverse antibiotic resistance.

Authors:  Michael Baym; Laura K Stone; Roy Kishony
Journal:  Science       Date:  2016-01-01       Impact factor: 47.728

3.  A Hybrid Drug Limits Resistance by Evading the Action of the Multiple Antibiotic Resistance Pathway.

Authors:  Kathy K Wang; Laura K Stone; Tami D Lieberman; Michal Shavit; Timor Baasov; Roy Kishony
Journal:  Mol Biol Evol       Date:  2015-11-03       Impact factor: 16.240

Review 4.  Evolutionary consequences of drug resistance: shared principles across diverse targets and organisms.

Authors:  Diarmaid Hughes; Dan I Andersson
Journal:  Nat Rev Genet       Date:  2015-07-07       Impact factor: 53.242

5.  Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli.

Authors:  Kyle J Card; Misty D Thomas; Joseph L Graves; Jeffrey E Barrick; Richard E Lenski
Journal:  Proc Natl Acad Sci U S A       Date:  2021-02-02       Impact factor: 11.205

Review 6.  Prediction of antibiotic resistance: time for a new preclinical paradigm?

Authors:  Morten O A Sommer; Christian Munck; Rasmus Vendler Toft-Kehler; Dan I Andersson
Journal:  Nat Rev Microbiol       Date:  2017-07-31       Impact factor: 60.633

7.  Antibiotics: New recipe for targeting resistance.

Authors:  Balázs Papp; Viktória Lázár
Journal:  Nat Chem Biol       Date:  2016-10-18       Impact factor: 15.040

Review 8.  Exploiting Synthetic Lethality and Network Biology to Overcome EGFR Inhibitor Resistance in Lung Cancer.

Authors:  Simon Vyse; Annie Howitt; Paul H Huang
Journal:  J Mol Biol       Date:  2017-05-03       Impact factor: 5.469

9.  Exploiting Temporal Collateral Sensitivity in Tumor Clonal Evolution.

Authors:  Boyang Zhao; Joseph C Sedlak; Raja Srinivas; Pau Creixell; Justin R Pritchard; Bruce Tidor; Douglas A Lauffenburger; Michael T Hemann
Journal:  Cell       Date:  2016-02-25       Impact factor: 41.582

Review 10.  Modeling Tumor Clonal Evolution for Drug Combinations Design.

Authors:  Boyang Zhao; Michael T Hemann; Douglas A Lauffenburger
Journal:  Trends Cancer       Date:  2016-03
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