Berg ellen cal epa 29 oct2014
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BioMAP® Systems for Investigative Toxicology & Safety Assessment. Presentation for the California Environmental Protection Agency’s 21st Century Toxicology Seminar Series, October 29, 2014, Sacramento, CA. Ellen Berg
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Berg ellen cal epa 29 oct2014
- 1. BioMAP® Systems for Investigative Toxicology & Safety Assessment Ellen L. Berg, PhD Scientific Director, BioSeek a division of DiscoveRx California EPA Sacramento CA 29 October 2014
- 2. • Part 1: Background on BioSeek Methodology - Challenges in Toxicology and Safety Assessment - The BioMAP® Platform • Part 2: Applications in pesticide prioritization, hazard identification and risk assessments - EPA ToxCastTM Agenda
- 3. • Toxicity mechanisms are diverse - Few toxicity targets have been identified • Animals poor predictors of human toxicity - Species differences Challenges in Safety Assessment
- 4. Feature Mice Man Lifespan 2 Years 70 Years Size 60 g 60 kg Environment Animal facility, cage-mates Outside world, people, animals, etc. Limitations of Animal Models Key differences: DNA repair mechanisms Control of blood flow, hemostasis Immune system status
- 5. • Toxicity mechanisms are diverse - Few toxicity targets have been identified • Animals poor predictors of human toxicity - Species differences • New tools - Opportunity for in vitro testing to transform predictive toxicology and risk assessment Challenges in Safety Assessment
- 6. DATA
- 7. BIG DATA Why now ? • Advances in high throughput technologies • Availability of “omics” data
- 8. BIG DATA What is ? • VOLUME • VELOCITY • VARIETY
- 9. BIG DATA What is ? Large datasets Terabytes+ Integration of diverse data
- 10. Data Driven Research OLD or
- 12. Data Driven Research Issues Many hypotheses are generated Each hypothesis requires validation Validation requires both computational and “domain” expertise
- 13. Data Driven Research Solutions Incorporate “domain” expertise upfront Integrate external data to validate hypotheses
- 14. BioMAP® Technology Platform BioMAP® Assay Systems Reference Profile Database Predictive Informatics Tools > 40 Human Primary Cell Models >1000s of Reference Chemicals, Agents Analysis and Data Mining Tools High-throughput Human Biology 14
- 15. BioMAP® Systems – Key Features 15 Primary human cell types Physiologically relevant “context” Complex activation settings Co-cultures Translational biomarker endpoints
- 16. Closer to the disease process Downstream of multiple pathways and integrate information “Decision-making” Used by clinicians to guide therapy Predictive Benefits of Translational Biomarkers mRNA, epigenome Phospho-sites, intracellular proteins, metabolome Cell surface, secreted molecules 16
- 17. BioMAP® Systems for ToxCast 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT Endothelial Cells Endothelial Cells PBMC + Endothelial Cells PBMC + Endothelial Cells Bronchial epithelial cells Coronary artery SMC Fibroblasts Keratinocytes + Fibroblasts Th1 Th2 TLR4 TCR Th1 Th1 Th1 + GF Th1 + TGF Acute Inflammation E-selectin, IL-8 E-selectin, IL- 1a, IL-8, TNF- a, PGE2 IL-8 IL-1a IL-8, IL-6, SAA IL-8 IL-1α Chronic Inflammation VCAM-1, ICAM- 1, MCP-1, MIG VCAM-1, Eotaxin-3, MCP-1 VCAM-1, MCP-1 MCP-1, E- selectin, MIG IP-10, MIG, HLA-DR MCP-1, VCAM- 1,MIG, HLA- DR VCAM-1, IP-10, MIG MCP-1, ICAM- 1, IP-10 Immune Response HLA-DR CD40, M-CSF CD38, CD40, CD69, T cell Prolif., Cytotox. HLA-DR M-CSF M-CSF Tissue Remodeling uPAR, MMP-1, PAI-1, TGFb1, SRB, tPA, uPA uPAR, Collagen III, EGFR, MMP-1, PAI-1, Fibroblast Prolif., SRB, TIMP-1 MMP-9, SRB, TIMP-2, uPA, TGFβ1 Vascular Biology TM, TF, uPAR, EC Proliferation, SRB, Vis VEGFRII, uPAR, P- selectin, SRB Tissue Factor, SRB SRB TM, TF, LDLR, SMC Proliferation, SRB Vascular Biology, Cardiovascular Disease, Chronic Inflammation Asthma, Allergy, Oncology, Vascular Biology Cardiovascular Disease, Chronic Inflammation, Infectious Disease Autoimmune Disease, Chronic Inflammation, Immune Biology COPD, Respiratory, Epithelial Biology Vascular Biology, Cardiovascular Inflammation, Restenosis Tissue Remodeling, Fibrosis, Wound Healing Skin Biology,Psoriasis, Dermatitis EndpointTypes Disease / Tissue Relevance BioMAP System Primary Human Cell Types Stimuli ! ! ! ! ! Endothelial Cells Bronchial Epithelial Cells Keratinocytes Smooth Muscle Cells Dermal Fibroblasts Peripheral Blood Mononuclear Cells
- 18. BioMAP® Systems for ToxCast 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT Endothelial Cells Endothelial Cells PBMC + Endothelial Cells PBMC + Endothelial Cells Bronchial epithelial cells Coronary artery SMC Fibroblasts Keratinocytes + Fibroblasts Th1 Th2 TLR4 TCR Th1 Th1 Th1 + GF Th1 + TGF Acute Inflammation E-selectin, IL-8 E-selectin, IL- 1a, IL-8, TNF- a, PGE2 IL-8 IL-1a IL-8, IL-6, SAA IL-8 IL-1α Chronic Inflammation VCAM-1, ICAM- 1, MCP-1, MIG VCAM-1, Eotaxin-3, MCP-1 VCAM-1, MCP-1 MCP-1, E- selectin, MIG IP-10, MIG, HLA-DR MCP-1, VCAM- 1,MIG, HLA- DR VCAM-1, IP-10, MIG MCP-1, ICAM- 1, IP-10 Immune Response HLA-DR CD40, M-CSF CD38, CD40, CD69, T cell Prolif., Cytotox. HLA-DR M-CSF M-CSF Tissue Remodeling uPAR, MMP-1, PAI-1, TGFb1, SRB, tPA, uPA uPAR, Collagen III, EGFR, MMP-1, PAI-1, Fibroblast Prolif., SRB, TIMP-1 MMP-9, SRB, TIMP-2, uPA, TGFβ1 Vascular Biology TM, TF, uPAR, EC Proliferation, SRB, Vis VEGFRII, uPAR, P- selectin, SRB Tissue Factor, SRB SRB TM, TF, LDLR, SMC Proliferation, SRB Vascular Biology, Cardiovascular Disease, Chronic Inflammation Asthma, Allergy, Oncology, Vascular Biology Cardiovascular Disease, Chronic Inflammation, Infectious Disease Autoimmune Disease, Chronic Inflammation, Immune Biology COPD, Respiratory, Epithelial Biology Vascular Biology, Cardiovascular Inflammation, Restenosis Tissue Remodeling, Fibrosis, Wound Healing Skin Biology,Psoriasis, Dermatitis EndpointTypes Disease / Tissue Relevance BioMAP System Primary Human Cell Types Stimuli ! ! ! ! !
- 19. • Challenges - Cells and assays are expensive - Primary cells (all cell-based assays!) are variable - Very large number of assay components / choices • Media • Additives • Cell type • Time point • Endpoint Measurements Experimental Design
- 20. • Solutions (compromise) - Automation and standardized methods – microwell plates - Cells from pools of donors, prequalified - Single well per sample - Multiple concentrations per compound (4+) - 6-8 vehicle replicates, two positive controls per plate - Normalize data within plate (Log10 ratio of compound/vehicle) Experimental Design
- 21. Quality Control • Quality Management System in place - Quality Management Plan, external QA manager, controlled documents, equipment and materials tracking, SOPs, audits, training program • Defined assay acceptance criteria - All data provided to EPA has passed these criteria - Vehicle control replicates meet acceptance criteria (95% of plates have CV < 20%) • Ph I data: %CVs ranged from 0.3% to 18.5% (average = 5.3%) - Positive controls (colchicine or no stimulation control) are similar to historical (based on Pearson similarity metric) • Pearson test
- 22. BioMAP Profile of Colchicine • Colchicine is an inhibitor of microtubules - It is active in every system and used as a positive control on every plate • Colchicine profile has a distinctive pattern of activities or “shape” BioMAP Systems Readout Parameters (Biomarkers) Cytotoxicity Readouts Colchicine 1.1 μM Logexpressionratio (Drug/DMSOcontrol) Vehicle Control (no drug) 95% significance envelope
- 23. BioMAP Profile of No Stimulation Control • “No Stimulation” condition also has a specific pattern of activities • Each biomarker readout has a distinctive stim/non-stim ratio Logexpressionratio (Drug/DMSOcontrol) Vehicle Control (no drug) 95% significance envelope BioMAP Systems Readout Parameters (Biomarkers) Cytotoxicity Readouts “No Stimulation”
- 24. Reproducibility of BioMAP Profiles Multiple independent experiments Profile shape and EC50’s remains the same experiment-to-experiment Pearson correlation routinely > 0.8 – 0.9 (perfect match = 1) 12 experiments, each performed at different time, different donors, different lots of the same compound 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
- 25. • Cytotoxicity - Flag compounds (concentrations) that are overtly cytotoxic • Profiles - Profile characteristics - Unsupervised and supervised approaches to compare profiles • Individual activities - Identify statistically significant activities (non-cytotoxic concentrations) • Correlations to external data - MoA hypotheses and support AOPs Analysis Flow for BioMAP Profile Data
- 26. • Cytotoxicity can be a confounding factor - If cells are dead, changes in the levels of biomarker endpoints are non-specific • What can we use to measure cell death? - BioMAP cell systems are highly activated • Metabolic endpoints (e.g. alamar blue, ATP measurements) are not selective for cell death - Total cell protein most closely correlates with cell death: • Sulforhodamine B (SRB, a stain for total protein) • Skehan, P., 1990, J. Natl. Cancer Inst. 82:1107 • How do we define cell death? - SRB Log10 ratio of ≤ -0.3 - This represents a ≥ 50% loss of total protein Overt Cell Cytotoxicity
- 27. Cytotoxicity Depends on Cell Type and Activation State • Cytotoxicity (SRB < -0.3) is indicated by black arrows • Potency of test agent for cytotoxicity differs depending on the system Cytotoxicity (potency) Cell Type Endothelial Cells Epithelial Cells SMC Fibroblasts EC Activation State • Cytotoxicity is dependent on both cell type and activation state
- 28. Types of BioMAP Profiles Inactive Active – Sharp dose-response Active – Dose resistant Active – Selectively
- 29. Rapamycin (mTOR) Genistein (multi-target) Dose Resistance • “Dose resistant” compounds have similar activity profiles over a wide range of concentrations - No sharp activity jumps; Rapamycin > Genistein • Characteristic of approved drugs & target-selective compounds - Rapamycin is highly selective for mTOR - Genistein has multiple targets - The dose resistance index of Rapamycin is > 60,000x 29
- 30. • EC50, Slope, Magnitude of effect • Plateau Dose-resistance • Cytotoxicity Rapamycin Genistein No effect Max Inhibition Increasing Concentration Increasing Concentration Cytotoxicity HLA-DRLevels Plateau EC50 Magnitude Concentration Effects
- 31. • BioSeek definition of key activities (for n=1 screening data): - Log10 ratio values outside historical control 95% significance at more than one concentration tested - Only concentrations that are not overtly cytotoxic (SRB > - 0.3) • Other options - AC50 – 50% activating concentration (EPA) - LEC – lowest effective concentration - Add additional requirement for a 20% effect size - Categorical • BioSeek data has 3 categories (increased, no effect and decreased) Reporting of Activities
- 32. BioMAP Profiling: Example Profile Reference p38 MAPK Inhibitor Logexpressionratio (Drug/DMSOcontrol) Control (no drug) 99% significance envelope BioMAP Systems Readout Parameters (Biomarkers) Dose Response Cytotoxicity Readouts 32 This profile shows dose-resistance – similar over a range of concentrations
- 33. BioMAP Profiling: Example Profile Reference p38 MAPK Inhibitor Logexpressionratio (Drug/DMSOcontrol) 33 Activities relevant to the role of p38 in monocyte / Th1-type inflammation p38 kinase is important for Th1-dependent inflammatory responses Takanami-Ohnishi Y, et al., Essential role of p38 mitogen-activated protein kinase in contact hypersensitivity. J Biol Chem. 2002, 277:37896-903. IL-8 HLA-DR Monocyte activation IL-6IL-1aCD38 HLA-DR TNF-a
- 34. BioMAP Profiling: Example Profile Reference p38 MAPK Inhibitor Logexpressionratio (Drug/DMSOcontrol) 34 Activities relevant to anti-thrombotic effects of p38 inhibitors Tissue factor is the primary cellular initiator of coagulation p38α deficiency impairs thrombus formation Sakurai K, et al. Role of p38 mitogen-activated protein kinase in thrombus formation. J Recept Signal Transduct Res. 2004;24(4):283-96. Tissue Factor
- 35. BioMAP Profiling: Example Profile Reference p38 MAPK Inhibitor Logexpressionratio (Drug/DMSOcontrol) 35 Activities relevant to side effects – clinical finding: skin rash Upregulation of VCAM and ITAC are characteristic of skin hyperreactivity Melikoglu M, et al., Characterization of the divergent wound-healing responses occurring in the pathergy reaction and normal healthy volunteers. J Immunol. 2006, 177:6415-21. ITAC VCAM MMP1 VCAM
- 36. 36 BioMAP® Analyses Predictive Informatics Tools Custom informatics tools are used to predict clinical outcomes Similarity Search Unsupervised analysis Mechanism Classification Supervised analysis Clinical Associations Mechanism of action
- 37. 37 BioMAP® Reference Database BioMAP® Reference Database Biomarker responses to drugs are stored in the database >3000 drugs • More than 3000 agents - Drugs – Clinical stage, approved, and failed - Experimental Chemicals - Research tool compounds, environmental chemicals, nanomaterials - Biologics – Antibodies, cytokines, factors, peptides, soluble receptors • Availability of reference data - Key reference data are published and have been made available (Berg, 2010; Berg, 2013)
- 38. Similarity Analysis of Profiles Highly correlated Similar Pearson’s correlation of r > 0.7 Low correlation Not similar Pearson’s correlation of r < 0.7 38
- 39. Microtubule Stabilizers Mitochondrial ET chain Retinoids Hsp90 CDK NFkB MEK DNA synthesis JNK Protein synthesis Microtubule Destabilizers Estrogen R PI-3K Ca++ Mobilization BioMAP Data Can Cluster Compounds According to Mechanisms of Action mTOR PKC Activation p38 MAPK HMG-CoA reductase Calcineurin Transcription 39 Each circle represents a compound tested at a single dose Lines are drawn between compounds whose profiles are similar (r > 0.7) Figure adopted from Berg, JPTox Meth. 2010
- 40. Microtubule Stabilizers Mitochondrial ET chain Retinoids Hsp90 CDK NFkB MEK DNA synthesis JNK Protein synthesis Microtubule Destabilizers Estrogen R PI-3K Ca++ Mobilization BioMAP Data Can Cluster Compounds According to Mechanisms of Action mTOR PKC Activation p38 MAPK HMG-CoA reductase Calcineurin Transcription p38 MAPK Calcineurin mTOR Mitochondrial ATPase 40 Each circle represents a compound tested at a single dose Lines are drawn between compounds whose profiles are similar (r > 0.7) Figure adopted from Berg, JPTox Meth. 2010
- 41. Microtubule Stabilizers Mitochondrial ET chain Retinoids Hsp90 CDK NFkB MEK DNA synthesis JNK Protein synthesis Microtubule Destabilizers Estrogen R PI-3K Ca++ Mobilization BioMAP Data Can Cluster Compounds According to Mechanisms of Action mTOR PKC Activation p38 MAPK HMG-CoA reductase Calcineurin Transcription Mechanism of Action (On-Target) Pathway Relationships 41
- 42. Consensus Profiles for Mechanism Classes p38 MAPK inhibitor 1 p38 MAPK inhibitor 2 p38 MAPK inhibitor 3 Consensus profile reflects target-specific biology Can define mechanism class 42 1 1 1 1 1 1 1 1 1
- 43. Mechanism Class Consensus Profiles AhR Agonist Calcineurin Inhibitor EGFR Inhibitor EP Agonist ER Agonist GR Agonist (Full) H1 Antagonist HDAC Inhibitor HMG-CoA Reductase Inhibitor Hsp90 Inhibitor IKK2 Inhibitor IL-17A Agonist JAK Inhibitor MEK Inhibitor Microtubule Disruptor Microtubule Stabilizer Mitochondrial Inhibitor mTOR Inhibitor p38 MAPK Inhibitor PDE IV Inhibitor PI3K Inhibitor PKC (c+n) Inhibitor Proteasome Inhibitor RAR/RXR Agonist SR Ca++ ATPase Inhibitor Src Family Inhibitor TNF-alpha Antagonist Vitamin D Receptor Agonist Patterns reflect “mechanism class” or target biology Reproducible patterns permit building of classifiers for automated mechanism assignment MechanismClasses BioMAP Assay / Endpoints CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF K CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF K CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3C CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3C CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 uPA −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 uPA −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 uPA −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 uPA −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 uPA −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD54/ICAM−1 CD62E/E−Selectin CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR Proliferation SRB Visual CCL2/MCP−1 CCL26/Eotaxin−3 CD106/VCAM−1 CD62P/P−selectin CD87/uPAR SRB VEGFR2 CCL2/MCP−1 CD106/VCAM−1 CD142/TissueFactor CD40 CD62E/E−Selectin CXCL8/IL−8 IL−1alpha M−CSF sPGE2 SRB sTNF−alpha CCL2/MCP−1 CD38 CD40 CD62E/E−Selectin CD69 CXCL8/IL−8 CXCL9/MIG PBMCCytotoxicity Proliferation SRB CD87/uPAR CXCL10/IP−10 CXCL9/MIG HLA−DR IL−1alpha MMP−1 PAI−I SRB TGF−betaI tPA uPA CCL2/MCP−1 CD106/VCAM−1 CD141/Thrombomodulin CD142/TissueFactor CD87/uPAR CXCL8/IL−8 CXCL9/MIG HLA−DR IL−6 LDLR M−CSF Proliferation SerumAmyloidA SRB CD106/VCAM−1 CollagenIII CXCL10/IP−10 CXCL8/IL−8 CXCL9/MIG EGFR M−CSF MMP−1 PAI−I Proliferation_72hr SRB TIMP−1 CCL2/MCP−1 CD54/ICAM−1 CXCL10/IP−10 IL−1alpha MMP−9 SRB TGF−betaI TIMP−2 uPA −1.5 −1.4 −1.3 −1.2 −1.1 −1.0 −0.9 −0.8 −0.7 −0.6 −0.5 −0.4 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 LogRatio Profiles Cyclopamine 40 uM Cyclopamine 13.333 u... Cyclopamine 4.444 uM Cyclopamine 1.482 uM 3C 4H LPS SAg BE3C CASM3C HDF3CGF KF3CT 43 TF VCAM
- 44. Building Support Vector Machine Classifiers • 88 Compounds • 28 Target/Pathway mechanisms • 1-8 concentrations • 327 Profiles • 84 endpoints (8 BioMAP Systems) • Support Vector Machine • 2-class models • Mechanism class versus “Null” set • Result = Decision Value (DV) • PPV – positive predictive value (fraction of profiles that are correctly classified) • PPV = TP / (TP + FP)) • Sensitivity (fraction of profiles that are assigned to the class) • Sensitivity = TP / (TP + FN)) Mitochondrial Inhibitor Microtubule Stabilizer Hsp90 Inhibitor Classifier Performance: Examples PDE IV Inhibitor Generate Data Set Build Classifiers Test Performance of Classifiers Berg, Yang & Polokoff, 2013, J. Biomol Screen. 18:1260.
- 45. • AhR agonist (Aryl Hydrocarbon) • Calcineurin • EGFR (Epidermal Growth Factor R) • SERCA (SR Ca++ ATPase) • EP agonist • Estrogen R agonist • Glucocorticoid R agonist • H1R Antagonist (Histamine) • HDAC • HMG-CoA-Reductase • Hsp90 Inhibitor • IKK2 • IL-17 R agonist • JAK Confidential45 List of Classifiers (SVM Mechanism Models) • MEK • Microtubule Disruptor • Microtubule Stabilizer • Mitochondrial Inhibitor • mTOR • p38 MAPK • PDE IV (Phosphodiesterase • PI3K • PKC (c+n) • Proteasome • RAR-RXR agonist • Src family • TNF (Tumor Necrosis Factor) • VDR agonist (Vitamin D R) Berg, Yang & Polokoff, 2013, J. Biomol Screen. 18:1260.
- 46. • Chemical profiling in human cell systems generates activity profiles that can be used to: - Group chemicals into bioactivity classes - Generate MoA hypotheses - Identify activities that may correlate with in vivo outcomes • High throughput in vitro data is most informative when combined with external information - Known targets - In vivo effects Summary
- 47. • Application for predictive toxicology and risk assessment must also include: - Exposure - level and route - Distribution - Metabolism – inactivation or transformation • Test agent issues - Chemical stability and purity - Solubility - Mixtures - Polypharmacy Challenges and Considerations
- 48. BioSeek, A Division of DiscoveRx 310 Utah, Suite 100 South San Francisco, CA 94080 650-416-7600 Ellen L. Berg, PhD eberg@bioseekinc.com www.biomapsystems.com CONTACTS