Literature DB >> 34403034

Network-Based Systems Analysis Explains Sequence-Dependent Synergism of Bortezomib and Vorinostat in Multiple Myeloma.

Charvi Nanavati1, Donald E Mager2.   

Abstract

Bortezomib and vorinostat exhibit synergistic effects in multiple myeloma (MM) cells when given in sequence, and the purpose of this study was to evaluate the molecular determinants of the interaction using a systems pharmacology approach. A Boolean network model consisting of 79 proteins and 225 connections was developed using literature information characterizing mechanisms of drug action and intracellular signal transduction. Network visualization and structural analysis were conducted, and model simulations were compared with experimental data. Critical biomarkers, such as pNFκB, p53, cellular stress, and p21, were identified using measures of network centrality and model reduction. U266 cells were then exposed to bortezomib (3 nM) and vorinostat (2 μM) as single agents or in simultaneous and sequential (bortezomib for first 24 h, followed by addition of vorinostat for another 24 h) combinations. Temporal changes for nine of the critical proteins in the reduced Boolean model were measured over 48 h, and cellular proliferation was measured over 96 h. A mechanism-based systems model was developed that captured the biological basis of a bortezomib and vorinostat sequence-dependent pharmacodynamic interaction. The model was further extended in vivo by linking in vitro parameter values and dynamics of p21, caspase-3, and pAKT biomarkers to tumor growth in xenograft mice reported in the literature. Network-based methodologies and pharmacodynamic principles were integrated successfully to evaluate bortezomib and vorinostat interactions in a mechanistic and quantitative manner. The model can be potentially applied to evaluate their combination regimens and explore in vivo dosing regimens.
© 2021. American Association of Pharmaceutical Scientists.

Entities:  

Keywords:  Boolean networks; drug-drug interactions; multiple myeloma; pharmacodynamics; systems pharmacology

Mesh:

Substances:

Year:  2021        PMID: 34403034     DOI: 10.1208/s12248-021-00622-9

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


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