Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer

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dc.contributor University of Helsinki, Medicum en
dc.contributor University of Helsinki, Institute for Molecular Medicine Finland en
dc.contributor University of Helsinki, Institute for Molecular Medicine Finland en
dc.contributor University of Helsinki, Doctoral Programme in Integrative Life Science en
dc.contributor University of Helsinki, Institute for Molecular Medicine Finland en
dc.contributor University of Helsinki, Computational Systems Medicine en
dc.contributor University of Helsinki, Institute for Molecular Medicine Finland en
dc.contributor University of Helsinki, Institute for Molecular Medicine Finland en
dc.contributor University of Helsinki, Institute for Molecular Medicine Finland en
dc.contributor University of Helsinki, Immunobiology Research Program en
dc.contributor University of Helsinki, HUSLAB en
dc.contributor University of Helsinki, Institute for Molecular Medicine Finland en
dc.contributor University of Helsinki, Krister Wennerberg / Principal Investigator en
dc.contributor University of Helsinki, Tero Aittokallio / Principal Investigator en
dc.contributor.author Tang, Jing
dc.contributor.author Gautam, Prson
dc.contributor.author Gupta, Abhishekh
dc.contributor.author He, Liye
dc.contributor.author Timonen, Sanna
dc.contributor.author Akimov, Yevhen
dc.contributor.author Wang, Wenyu
dc.contributor.author Szwajda, Agnieszka
dc.contributor.author Jaiswal, Alok
dc.contributor.author Turei, Denes
dc.contributor.author Yadav, Bhagwan
dc.contributor.author Kankainen, Matti
dc.contributor.author Saarela, Jani
dc.contributor.author Saez-Rodriguez, Julio
dc.contributor.author Wennerberg, Krister
dc.contributor.author Aittokallio, Tero
dc.date.accessioned 2019-11-21T06:47:01Z
dc.date.available 2019-11-21T06:47:01Z
dc.date.issued 2019-07-08
dc.identifier.citation Tang , J , Gautam , P , Gupta , A , He , L , Timonen , S , Akimov , Y , Wang , W , Szwajda , A , Jaiswal , A , Turei , D , Yadav , B , Kankainen , M , Saarela , J , Saez-Rodriguez , J , Wennerberg , K & Aittokallio , T 2019 , ' Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer ' , npj Systems Biology and Applications , vol. 5 , no. 1 , 20 . https://doi.org/10.1038/s41540-019-0098-z en
dc.identifier.issn 2056-7189
dc.identifier.other PURE: 125596367
dc.identifier.other PURE UUID: 80a383db-5c68-429e-8aa3-04c09fb46e1c
dc.identifier.other RIS: urn:EE44F660543B59AB7A0EE11EFCF75A0D
dc.identifier.other RIS: Tang2019
dc.identifier.other WOS: 000496187100001
dc.identifier.other ORCID: /0000-0001-7306-7175/work/64976232
dc.identifier.other ORCID: /0000-0002-8139-5950/work/64976429
dc.identifier.other ORCID: /0000-0002-0886-9769/work/64976640
dc.identifier.other ORCID: /0000-0001-7480-7710/work/64976714
dc.identifier.uri http://hdl.handle.net/10138/307149
dc.description.abstract Cancer cells with heterogeneous mutation landscapes and extensive functional redundancy easily develop resistance to monotherapies by emerging activation of compensating or bypassing pathways. To achieve more effective and sustained clinical responses, synergistic interactions of multiple druggable targets that inhibit redundant cancer survival pathways are often required. Here, we report a systematic polypharmacology strategy to predict, test, and understand the selective drug combinations for MDA-MB-231 triple-negative breast cancer cells. We started by applying our network pharmacology model to predict synergistic drug combinations. Next, by utilizing kinome-wide drug-target profiles and gene expression data, we pinpointed a synergistic target interaction between Aurora B and ZAK kinase inhibition that led to enhanced growth inhibition and cytotoxicity, as validated by combinatorial siRNA, CRISPR/Cas9, and drug combination experiments. The mechanism of such a context-specific target interaction was elucidated using a dynamic simulation of MDA-MB-231 signaling network, suggesting a cross-talk between p53 and p38 pathways. Our results demonstrate the potential of polypharmacological modeling to systematically interrogate target interactions that may lead to clinically actionable and personalized treatment options. en
dc.format.extent 11
dc.language.iso eng
dc.relation.ispartof npj Systems Biology and Applications
dc.rights en
dc.subject 1182 Biochemistry, cell and molecular biology en
dc.subject 3122 Cancers en
dc.subject 3111 Biomedicine en
dc.title Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer en
dc.type Article
dc.description.version Peer reviewed
dc.identifier.doi https://doi.org/10.1038/s41540-019-0098-z
dc.type.uri info:eu-repo/semantics/other
dc.type.uri info:eu-repo/semantics/publishedVersion
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