title: Identification of myeloproliferative neoplasm drug agents via predictive simulation modeling: assessing responsiveness with micro-environment derived cytokines.
abstract: Previous studies have shown that the bone marrow micro-environment supports the myeloproliferative neoplasms (MPN) phenotype including via the production of cytokines that can induce resistance to frontline MPN therapies. However, the mechanisms by which this occurs are poorly understood. Moreover, the ability to rapidly identify drug agents that can act as adjuvants to existing MPN frontline therapies is virtually non-existent. Here, using a novel predictive simulation approach, we sought to determine the effect of various drug agents on MPN cell lines, both with and without the micro-environment derived inflammatory cytokines. We first created individual simulation models for two representative MPN cell lines; HEL and SET-2, based on their genomic mutation and copy number variation (CNV) data. Running computational simulations on these virtual cell line models, we identified a synergistic effect of two drug agents on cell proliferation and viability; namely, the Jak2 kinase inhibitor, G6, and the Bcl-2 inhibitor, ABT737. IL-6 did not show any impact on the cells due to the predicted lack of IL-6 signaling within these cells. Interestingly, TNFα increased the sensitivity of the single drug agents and their use in combination while IFNγ decreased the sensitivity. In summary, this study predictively identified two drug agents that reduce MPN cell viability via independent mechanisms that was prospectively validated. Moreover, their efficacy is either potentiated or inhibited, by some of the micro-environment derived cytokines. Lastly, this study has validated the use of this simulation based technology to prospectively determine such responses.
authors.affiliation: Department of Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA.
authors.forename: Susumu S
authors.initials: SS
authors.lastname: Kobayashi
authors.affiliation: Cellworks Group, Inc., San Jose, CA, USA.
authors.forename: Shireen
authors.initials: S
authors.lastname: Vali
authors.affiliation: Cellworks Research India Pvt Ltd., Cellworks Group Inc., Bangalore, India.
authors.forename: Ansu
authors.initials: A
authors.lastname: Kumar
authors.affiliation: Cellworks Research India Pvt Ltd., Cellworks Group Inc., Bangalore, India.
authors.forename: Neeraj
authors.initials: N
authors.lastname: Singh
authors.affiliation: Cellworks Group, Inc., San Jose, CA, USA.
authors.forename: Taher
authors.initials: T
authors.lastname: Abbasi
authors.affiliation: Department of Physiology and Functional Genomics, University of Florida College of Medicine, Gainesville, FL, USA.
authors.forename: Peter P
authors.initials: PP
authors.lastname: Sayeski
mesh_terms: D045744:Cell Line, Tumor; D049109:Cell Proliferation / Q000187:drug effects / Q000235:genetics; D002470:Cell Survival / Q000187:drug effects / Q000235:genetics; D003198:Computer Simulation; D004354:Drug Screening Assays, Antitumor / Q000379:methods; D004357:Drug Synergism; D006801:Humans; D015850:Interleukin-6 / Q000494:pharmacology; D053614:Janus Kinase 2 / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D008954:Models, Biological; D009154:Mutation; D009196:Myeloproliferative Disorders / Q000235:genetics / Q000378:metabolism / Q000473:pathology; D047428:Protein Kinase Inhibitors / Q000494:pharmacology*; D019253:Proto-Oncogene Proteins c-bcl-2 / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D059016:Tumor Microenvironment; D014409:Tumor Necrosis Factor-alpha / Q000494:pharmacology
chemical_list: D015850:Interleukin-6; D047428:Protein Kinase Inhibitors; D019253:Proto-Oncogene Proteins c-bcl-2; D014409:Tumor Necrosis Factor-alpha; C507924:JAK2 protein, human; D053614:Janus Kinase 2
keywords: Jak kinase; predictive modeling; signal transduction; simulated signaling