Primary Human Cell Systems Analysis of Drug Mechanisms


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Presentation given at the SBS 15th Annual Conference, Lille, France, 28 April 2009

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  • BioMAP systems are complex primary human cell based disease models that can be used directly for phenotypic screening. The most attractive feature of this platform, however, is it’s ability of the platform to provide target and pathway mechanisms of action. This enables reverse pharmacology of bioactive agents and drugs as well as in depth characterization of leads for identifying on versus off-target biology, which in turn impact safety and also clinical indication selection.
  • Primary Human Cell Systems Analysis of Drug Mechanisms

    1. 1. Primary Human Cell SystemsAnalysis of Drug Mechanisms Ellen L. Berg, PhD BioSeek, Inc. SBS 15th Annual Conference Lille, France 28 April 2009 BioSeek
    2. 2. Presentation Overview • BioMAP Human Cell Systems Platform  Primary human cell-based disease models • Analysis of PPAR agonists  Discriminate clinical-stage compounds • Class and compound-specific activities  Explore alternative clinical indications • Prioritize compounds for indications and/or safety related activities2 BioSeek
    3. 3. Goals for Human Cell Systems Biology Platform • Covers a lot of biology  Targets, pathways, therapeutic areas, diseases • Covers the right biology  Human disease biology • Is quantitative, reproducible, robust, high throughput  Standardized, amenable to database generation • Is useful to broad range of stakeholders  Project leaders, biologists, chemists, preclinical scientists, clinicians • Is predictive  Biomarkers  Clinical indications, efficacy, toxicity BioSeek
    4. 4. BioMAP® Technology Platform Assays Profile Database Informatics LPS BF4T SM3C Human primary cells Biological responses to Specialized informatics tools Disease-like culture drugs and stored in the are used to mine and analyze conditions database biological data Complementary to biochemical target and phenotypic screening Complementary to biochemical target and phenotypic screening BioSeek
    5. 5. BioMAP® Technology Platform Assays • Assay endpoints are cell-based clinical BioMAP Systems include human assays biomarkers and risk complex human engineered to modelfactors (proteins) LPS disease biology  Cytokines, chemokines • Human primary cells receptors  Adhesion and growth BF4T • Co-cultures, multiple (prostaglandins, etc.)  Biological mediators stimulation factors, activated cells SM3C • Quantitative protein readouts plasminogen activators)  Proteases, enzymes (MMPs, - biomarkers • Pharmacologically relevance - validated with known  Others (hemostatic factors, matrix components) Human primary cells Disease-like culture  drugs Clinically relevant conditions >25 BioMAP Systems BioSeek
    6. 6. BioMAP® Technology Platform Assays Profile Database • > 2000 agents • Approved drugs LPS • Clinical stage & BF4T failed drugs • Experimental SM3C compounds Human primary cells Biological responses to drugs • Biologics Disease-like culture and stored in the database conditions • Toxicants BioSeek
    7. 7. Assays are Robust and Highly ReproducibleHigh Correlation of Experimental Replicates Pearson Correlation Coefficient R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R1 1 R2 0.95 1 R3 0.96 0.94 1 R4 0.98 0.98 0.96 1 R5 0.93 0.94 0.91 0.94 1 R6 0.96 0.96 0.93 0.97 0.98 1 R7 0.94 0.91 0.9 0.93 0.89 0.9 1 R8 0.95 0.98 0.94 0.98 0.94 0.98 0.92 1 R9 0.91 0.92 0.88 0.92 0.89 0.91 0.93 0.93 1 R10 0.88 0.9 0.81 0.89 0.93 0.93 0.85 0.91 0.83 1 R11 0.94 0.97 0.9 0.94 0.91 0.93 0.94 0.96 0.91 0.89 1 R12 0.92 0.9 0.84 0.89 0.96 0.96 0.89 0.91 0.87 0.92 0.91 1 5 µM dose Consistent data experiment-to-experiment Consistent data experiment-to-experiment Pearson correlation >0.8 (perfect match = 1) Pearson correlation >0.8 (perfect match = 1) BioSeek
    8. 8. Classification of Drugs By MechanismPairwise Correlation of BioMAP Reveals Functional Similarities Protein Estrogen R synthesis Microtubule PKC Activation Destabilizers Transcription PI-3K JNK NFκB mTOR Hsp90 DNA Calcineurin synthesis Retinoids CDK HMG-CoA reductase Ca++ Mitochondrial Mobilization ET chain p38 MAPK Microtubule Stabilizers MEK BioSeek
    9. 9. BioMAP Systems are Validated Corticosteroids (Prednisolone) Are Active in Inflammation Systems BioMAP SystemsLog expression ratio(Drug/DMSO control) 99% significance envelope Control (no drug) Dose Response Cytotoxicity Readouts Readout Parameters (Biomarkers) Profiles retain shape over multiple concentrations Profiles retain shape over multiple concentrations BioSeek
    10. 10. BioMAP Systems are Validated Activities of Corticosteroids Match Clinical EffectsLog expression ratio SAA(Drug/DMSO control) PAI-1 PAI-1 MMP-1 IL-8 MCP-1 IL-8 PGE2 E-selectin Collagen I & III TNF-α MCP-1, IL-8, E-sel. decrease PGE2 decrease Collagen I, III decrease PAI-1, SAA increase Leukocyte recruitment Skin atrophy CV complications Pain, swelling Sartori et al., 1999 Many, e.g. Jilma et al., 2000 Sebaldt et al., 1990 Autio et al., 1994 Fyfe et al., 1997 Readouts in BioMAP show the same pattern as has been Readouts in BioMAP show the same pattern as has been reported for patients receiving steroid therapy reported for patients receiving steroid therapy BioSeek
    11. 11. Project Goal • Characterize PPAR agonists by BioMAP profiling  Compare and contrast PPARγ agonists (anti-inflammatory activities) Rosiglitazone (Avandia) PPARγ Troglitazone (Resulin) PPARα Fenofibrate (Tricor) Pioglitazone (Actos)  Identify shared and unique pathway effects  Identify potential new indications BioSeek
    12. 12. BioMAP Profile of Rosiglitazone BioMAP SystemsEot3 IP-10 E-sel IP-10 MCP-1 I-TAC MCSF IL-8 I-TAC CD40 TNFα VCAM Macrophage activation Monocyte activation T cell activation • Rosiglitazone has strong anti-inflammatory activities  Inhibition of monocyte and T cell activation (T cell proliferation ) & recruitment  Inhibition of inflammatory chemokines (Eotaxin3, IP-10, ITAC, IL-8)  Consistent with inhibition of NFκB pathway by rosiglitazone • Consistent with efficacy in vivo  Mouse models of colitis (Shah, Y.M., et al., Am. J. Physiol. Gastrointest. Liver Physiol. 2007, 292:G657; Saubermann, L.J., Inflamm. Bowel Dis., 2002, 8:330).  Animal model of exposure-induced asthma (Lee, J. Immunol, 2006 117:5248).  MCP-1 and TNFα are clinical biomarkers BioSeek
    13. 13. BioMAP Profile of Rosiglitazone BioMAP Systems Col IVEot3 MMP9 E-sel IP-10 uPAR Col III MCP-1 PAI-1 MCSF IL-8 I-TAC Col III CD40 TNFα VCAM Macrophage activation Monocyte activation T cell activation • Rosiglitazone has strong effects on tissue remodeling parameters  Inhibition of MMP9, PAI-1, uPAR, Collagen III; upregulation of Collagen IV; Strong inhibition of myofibroblast activation  Consistent with modulation of TGFβ pathway by rosiglitazone • Consistent with results from in vivo studies  Rosigitazone is effective in models of neointimal hyperplasia (MMP9 is a biomarker in vivo)  Rosiglitazone protects in scleroderma model (myofibroblast accumulation and Collagen III) BioSeek
    14. 14. BioMAP Profile of Rosiglitazone BioMAP Systems PGD2 PGE2PGJ2 PGF2a PGJ2 PGD2 PGJ2 PGD2 PGF1a PGF2a PGF2aPGF1a PG1a PGF2a Bronchial epithelial cell-containing systems Leukocyte-containing systems • Rosiglitazone upregulates prostaglandins  In both bronchial epithelial and leukocyte-containing systems  Potent activity BioSeek
    15. 15. Upregulation of Prostaglandins by Rosiglitazone • Are prostaglandin effects PPARγ-dependent?  Not reversed by PPARγ antagonists  Reversed by COX1/2 inhibitors  Non-TZD PPARγ agonists do not upregulate prostaglandins • Consistent with secondary activity / activities  Rosiglitazone has been reported to inhibit 15-hydroxy- prostaglandin dehydrogenase and CYP450 2C8  Q: What about other TZDs, PPAR ligands? BioSeek
    16. 16. Rosiglitazone Upregulation of PGE2 is not a Class EffectSearch of BioMAP Database for Compounds that Increase PGE2 PPARα TXA2 inhibitor Compound Specific Effect PPARγ Retinoids JNK Inhibitor RNA Synthesis Inhibitor AMPK Mechanism activator Class Effect CYP450 Inhibitor Microtubule mTOR Destabilizers Inhibitor BioSeek
    17. 17. BioMAP Profile of Pioglitazone PGD2 PGD2 PGD2 PGD2 IL-8 PGE2 PGF2aPGJ2 PGF2a PGJ2 PGF2a PGJ2 PGF2aPGJ2 MCP-1 CD40 MMP9 VCAM CD38 ITAC PGF1a MCSF PGF1a CD40 Monocyte T cell activation activation • Pioglitazone shows few anti-inflammatory activities  Modest inhibition of VCAM, ITAC  Pioglitazone may be a weaker inhibitor of NFκB than rosiglitazone or have reduced cell uptake • Pioglitazone has modest effects on tissue remodeling parameters  Inhibition of MMP9  Pioglitazone has no effect on myofibroblast activation (in contrast to rosiglitazone) • Pioglitazone has differential effects on prostaglandins  Prostaglandins are inhibited in leukocyte/endothelial cell systems; unaffected in bronchial epithelial cells BioSeek
    18. 18. BioMAP Profile of Troglitazone PGD2 PGD2 PGF2a PGF2a TM Col IVPGF1a PGF1a MMP1 TF MCP-1 MCP-1 Eot3 MMP9 uPAR TNFα IP-10 E-sel I-TAC Col III Macrophage Monocyte T cell activation activation activation • Troglitazone shows modest anti-inflammatory activities  Activities are similar to those of rosiglitazone  Inhibition of inflammatory chemokines (Eotaxin3, IP-10, ITAC, IL-8)  Troglitazone is cytotoxic at higher concentrations • Troglitazone also affects tissue remodeling parameters  Inhibition of MMP9, PAI-1, Collagen III, some inhibition of myofibroblast activation  Upregulation of thrombomodulin in CASM3C system • Troglitazone affects prostaglandin pathways  Upregulation of PGF1a, PGF2a, and PGD2 in bronchial epithelial cells  No effect in leukocyte-containing systems (/LPS and /SAg) BioSeek
    19. 19. BioMAP Profile of Fenofibrate - PPARα TM PGD2 PGD2 MMP1PGJ2 PGF2a PGJ2 IL-8 PGJ2 TM PGF2aEot3 IL-8 MMP9 VCAM PGF1a IL1α MCP-1 ITAC MCSF PGD2 PGD2 uPAR Col III CD69 PGE2 PGF1a PGF2a IL-8 VCAM Mig PGF2a HLA-DR Monocyte T cell activation activation • Fenofibrate shows modest anti-inflammatory activities  Some inhibition of monocyte and T cell activation  Inhibition of inflammatory chemokines (Eot3, IL-8, ITAC) • Modest effects on tissue remodeling parameters  Inhibition of MMP9, Collagen III; upregulation of MMP1 • Differential modulation of prostaglandins QuickTime™ and a decompressor  Inhibition of prostaglandins in leukocyte-containing systems (/LPS and /SAg) are needed to see this picture.  No effect on prostaglandins in epithelial cell-containing systems BioSeek
    20. 20. Summary of PPAR Agonists• BioMAP profiling can discriminate PPAR agonists  Compound-and class-specific effects• PPAR agonists exhibit anti-inflammatory activities consistent with inhibition of NFkappaB pathway  Rosiglitazone, Fenofibrate > Troglitazone > Pioglitazone• Some PPAR agonists inhibit myofibroblast activation (TGFβ signaling)  Rosiglitazone, Troglitazone, but not Pioglitazone• PPAR agonists have diverse effects on prostaglandins  Rosiglitazone upregulates prostaglandins in both leukocyte-containing systems and bronchial epithelial cells  Troglitazone upregulates prostaglandins in bronchial epithelial cells  Pioglitazone and Fenofibrate inhibit prostaglandins in leukocyte-containing systems BioSeek
    21. 21. Summary• Differential activities can suggest prioritization for therapeutic utility  Anti-inflammatory activities ( inhibition of T cell, monocyte activation) • Autoimmune disease, vascular inflammation, atherosclerosis  Inhibition of myofibroblast activation / TGFβ signaling • Fibrotic diseases (IPF, scleroderma)  Upregulation of prostaglandins • Bronchodilation, potential utility in respiratory disease• Differential effects may also be associated with potential for side effects  Differential clinical effects of pioglitazone and rosiglitazone with respect to cardiovascular outcomes (Winkelmeyer, W., 2008, Comparison of cardiovascular outcomes in elderly patients with diabetes who initiated rosiglitazone vs pioglitazone therapy. Arch Intern Med 168:2368) BioSeek
    22. 22. Acknowledgements • BioSeek • Stanford  Eric Kunkel  Eugene Butcher  Jennifer Melrose  Rob Tibshirani  Dat Nguyen  Trevor Hastie  Elen Rosler  Stephanie Tong  Jian Yang  Antal Berenyi  David Patterson  Jonathan Bingham BioSeek
    23. 23. BioSeek