Enabling Cancer Immunotherapy: From Discovery to Combinations
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Answer four fundamental questions on how to develop the most innovative cancer immunotherapy treatments, starting with screening for lead molecules and ending with evaluation of combination therapies.
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Enabling Cancer Immunotherapy: From Discovery to Combinations
- 1. 1 Enabling Cancer Immunotherapy: From Discovery to Combinations Abhi Saharia, PhD
- 2. 2 The Cancer-Immunity Cycle & Targeted Therapies Multiple potential intervention steps to develop anti-cancer therapies Oncology Meets Immunology: The Cancer-Immunity Cycle. Immunity. 39 (1): 1-10
- 3. 3 Fundamental questions for drug development Screening & Lead Optimization Efficacy & Biomarker Selection Safety & Pre-clinical Studies Clinical Combination Strategies How do I screen for a functionally active lead molecule? How can I determine efficacy in a human tumor microenvironment (TME)? Is my drug active outside the context of the TME? How does my drug act in a combination therapy? Translating Discoveries into Drugs
- 4. 4 Target-based & Phenotypic Assays from DiscoverX Products and services to support drug development 0% KinasesGPCRs Interleukins Pathways Epigenetics Checkpoint 100% Primary Cell Profiling DepthofCoverage 284 410 40 35 34 6
- 5. 5 From drug discovery to clinical combinations Screening & Lead Optimization Efficacy & Biomarker Selection Safety & Pre-clinical Studies Clinical Combination Strategies Enabling Anti-cancer Immunotherapies PathHunter® Checkpoint Assays PathHunter® Bioassays for QC Lot Release Testing BioMAP® Oncology Systems BioMAP Diversity PLUS™ BioMAP® Combo ELECT
- 6. 6 Challenges: Requires specific cell-based assays for each target Requires human cells with complex TCR signaling Donor variability Longer assay times and complicated protocols Screening & Lead Optimization Efficacy & Biomarker Selection Safety & Pre-clinical Studies Clinical Combination Strategies How Do I Screen for Functionally Active Lead Molecules?
- 7. 7 Cancer Cell Immune Cell EFC Technology PD-1 Signaling Assay PathHunter® Checkpoint Assays Ideal for screening and lead optimization
- 8. 8 1 0 -1 0 1 0 -9 1 0 -8 1 0 -7 1 0 -6 1 0 -5 1 0 -4 0 2 0 0 0 0 4 0 0 0 0 6 0 0 0 0 8 0 0 0 0 A n ti-P D -1 D ru g [g /m L ] RLU P e m b ro lizu m ab N iv o lu m ab HillSlope IC50 Pembrolizumab -2.010 6.630e-009 Nivolumab -1.921 9.398e-009 Robust Screening & Lead Optimization Platform 1 0 -1 1 1 0 -1 0 1 0 -9 1 0 -8 1 0 -7 1 0 -6 1 0 -5 1 0 -4 0 1 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 RLU C o m p o u n d [M ] X L -2 8 8 0 D a s a tin ib HillSlope IC50 Dasatinib -1.979 5.762e-009 XL-2880 -1.045 4.740e-007 Screen Biologics in the PathHunter PD-1 Assay Screen Small Molecule Inhibitors in the PathHunter PD-1 Assay PathHunter® assays support both biologics and small molecules
- 9. 9 PD-1 OX40 CD40 HVEM VISTA TIM3 Biologically relevant responses for co-stimulatory & co-inhibitory agents Easy protocol with results in <5hrs Supports development of biologics and small molecules Screen confidently with highly sensitive response Applicable for QC lot release of biologic drug Summary for PathHunter® Checkpoint Assays 1 0 -1 2 1 0 -1 1 1 0 -1 0 1 0 -9 1 0 -8 1 0 -7 1 0 -6 1 0 -5 0 5 0 0 0 0 1 0 0 0 0 0 1 5 0 0 0 0 O X 4 0 S ig n a lin g A s s a y O X 4 0 L [g /m L ] RLU + O X 4 0 n o O X 4 0 Assays currently available Enabling screening & lead optimization for co-stimulatory & co-inhibitory molecules
- 10. 10 Challenges: In vitro assays do not mirror the complexity of TME Animal-xenograft models are not high throughput Lack of appropriate response biomarkers How Can I Determine Efficacy in a Human TME? Screening & Lead Optimization Efficacy & Biomarker Selection Safety & Pre-clinical Studies Clinical Combination Strategies
- 11. 11 Large or Small Molecules and Combinations BioMAP® Models of Human Disease Biology Validated systems that provide predictive results BioMAP Data & Knowledgebase 56+ BioMAP co-culture systems Human Primary Cells
- 12. 12 Development of BioMAP® Human TME Models BioMAP systems mirror intratumoral immune suppression 48h Assay Incubation
- 13. 13 48h Assay Incubation Validation of BioMAP® Human TME Models BioMAP systems mirror intratumoral immune suppression
- 14. 14 48h Assay Incubation Validation of BioMAP® Human TME Models BioMAP systems are robust and reproducible
- 15. 15 CD87/uPAR CEACAM5/CD66e CollagenI CollagenIII Keratin20 P PBMCCytotoxicity sGranzymeB sIFNg SRB sVEGF tPA uPA LogRatio Profiles Trametinib, 1.5 nM Trametinib, 510 p... Trametinib, 170 p... Trametinib, 19 pM StroHT29 sGranB CEA a uPAR CEACAM5 CollagenI CollagenIII Ker P PBMCCytotoxicity sGranzymeB sIFNg SRB sVEGF tPA uPA LogRatio Profiles Trametinib, 1.5 nM Trametinib, 510 pM Trametinib, 170 pM Trametinib, 19 pM StroHT29 sGranB CEACAM5 a 48h Assay Incubation Validation of BioMAP® Human TME Models BioMAP profile shows compound effects on TME biomarkers Protein Biomarker Readouts RelativeExpression(LogRatio) 95% Historical Control Envelope BioMAP profiles reveal translational response biomarkers
- 16. 16 RelativeExpressionLevels |Log10ratio|drug/vehiclecontrol) Pembrolizumab Restores Immune Responses Increased cytokine production with decreased tumor-cell derived sVEGF in human TME Identify response biomarkers CD87/uPAR CEACAM5/CD66e CollagenI CollagenIII Keratin20 P PBMCCytotoxicity sGranzymeB sIFNg SRB sVEGF tPA uPA CD40 CD87/uPAR CEACAM5/CD66e CollagenIV Keratin20 PBMCCytotoxicity sGranzymeB sIFNg SRB Profiles Pembrolizumab, 50000 ng/... Pembrolizumab, 17000 ng/... Pembrolizumab, 1900 ng/ml Pembrolizumab, 620 ng/ml StroHT29 VascHT29 Keratin 20 sGranB sIFNg sVEGF Keratin 20 sGranB sIFNg sTNFa Profiles Pembrolizumab, 50000 ng/ml Pembrolizumab, 17000 ng/ml Pembrolizumab, 1900 ng/ml Pembrolizumab, 620 ng/ml Keratin 20 sGranB sIFNg sVEGF Keratin 20 sGranB sIFNg sTNFa sTNFa VascHT29StroHT29 Protein Biomarker Readouts
- 17. 17 Shared Activities of Pembrolizumab and Nivolumab Both agents similarly increase cytokine production and decrease sVEGF levels Confirm target class signature biomarkers CD87/uPAR CEACAM5/CD66e CollagenI CollagenIII Keratin20 P PBMCCytotoxicity sGranzymeB sIFNg SRB sVEGF tPA uPA CD40 CD87/uPAR CEACAM5/CD66e CollagenIV Keratin20 PBMCCytotoxicity sGranzymeB sIFNg SRB Profiles Pembrolizumab, 17000 ng/... Nivolumab, 10000 ng/ml StroHT29 VascHT29 Keratin 20 sGranB sIFNg sTNFa sVEGF sGranB sIFNg Profiles Pembrolizumab, 17000 ng/ml Nivolumab, 10000 ng/ml Keratin 20 sGranB sIFNg sTNFa sVEGF sTNFa sGranB sIFNg StroHT29 VascHT29 Protein Biomarker Readouts RelativeExpressionLevels |Log10ratio|drug/vehiclecontrol)
- 18. 18 Both Large And Small Molecules Can Be Tested Screen and prioritize drug candidates Anti-CD73 antibodies and Paclitaxel show increased immune cytokine production CD87/uPAR CEACAM5/CD66e CollagenI CollagenIII Keratin20 P PBMCCytotoxicity sGranzymeB sIFNg SRB sVEGF tPA uPA CD40 CD87/uPAR CEACAM5/CD66e CollagenIV Keratin20 PBMCCytotoxicity sGranzymeB sIFNg SRB Profiles Paclitaxel, 14 nM , StroHT29 VascHT29 sIFNg sTNFa sVEGF uP sIFNg Profiles Paclitaxel, 14 nM , sIFNg sTNFa sVEGF uP sTNFa sIFNg StroHT29 VascHT29 Anti-Human CD73 was profiled as part of a collaborative study with MedImmune/AZ Protein Biomarker Readouts RelativeExpressionLevels |Log10ratio|drug/vehiclecontrol)
- 19. 19 Challenges: Current approaches rely on single cell or organ types Bias towards specific targets and target pathways Less complex and often isolated biology Limited testing of broad-scale human biology with drug Is My Drug Active Outside the Context of the TME? Screening & Lead Optimization Efficacy & Biomarker Selection Safety & Pre-clinical Studies Clinical Combination Strategies
- 20. 20 F P f P F f f K P tP P P C K P tP P F P P f C P f P P P LogRatio Profiles Erlotinib, 1.1 uM Erlotinib, 370 nM 3C 4H LPS SAg BT BF4T BE3C CASM3C HDF3CGF KF3CT MyoF lMphg uPAR uPAR P tPA uPA uPAR EGFR F P f P F f f K P tP P P C K P tP P F P P f C P f P P P LogRatio Profiles Erlotinib, 1.1 uM Erlotinib, 370 nM 3C 4H LPS SAg BT BF4T BE3C CASM3C HDF3CGF KF3CT MyoF lMphg uPAR Eot3 uPAR IL1a MMP1 MMP9 P tPA uPA uPAR EGFR IL8 Evaluation of Erlotinib Effects Outside the TME Biomarker activity of EGFR-inhibitors • Inform mechanism of action • Identify biomarkers of efficacy Activities detected at both concentrations are annotated RelativeExpressionLevels |Log10ratio|drug/vehiclecontrol) Monocyte Activation T cell Activation B cell Activation Macrophage Activation Matrix-modulation, fibrosis, tissue remodeling responses Vascular EC Inflammation Epithelial Inflammation and Matrix Remodeling Vascular SM Inflammation
- 21. 21 F P f P F f f K P tP P P C K P tP P F P P f C P f P P P LogRatio Profiles Paclitaxel, 41 nM Paclitaxel, 4.6 nM 3C 4H LPS SAg BT BF4T BE3C CASM3C HDF3CGF KF3CT MyoF lMphg TF uPAR uPAR sIgG F P f P F f f K P tP P P C K P tP P F P P f C P f P P P LogRatio Profiles Paclitaxel, 41 nM Paclitaxel, 4.6 nM 3C 4H LPS SAg BT BF4T BE3C CASM3C HDF3CGF KF3CT MyoF lMphg TF uPAR IL8 uPAR VEGFR2 sIgG CD69 Proliferation Proliferation Proliferation Evaluation of Paclitaxel Outside the TME Biomarkers for cardiovascular AE, anti-angiogenic and anti-metastatic potential • Inform mechanism of action • Identify activities that may highlight potential for adverse events Activities detected at both concentrations are annotated RelativeExpressionLevels |Log10ratio|drug/vehiclecontrol) Monocyte Activation T cell Activation B cell Activation Macrophage Activation Matrix-modulation, fibrosis, tissue remodeling responses Vascular EC Inflammation Epithelial Inflammation and Matrix Remodeling Vascular SM Inflammation
- 22. 22 F P f P F f f K P tP P P C K P tP P F P P f C P f P P P LogRatio Profiles Pembrolizumab, 2000 ng/ml Pembrolizumab, 400 ng/ml 3C 4H LPS SAg BT BF4T BE3C CASM3C HDF3CGF KF3CT MyoF lMphg F P f P F f f K P tP P P C K P tP P F P P f C P f P P P LogRatio Profiles Pembrolizumab, 2000 ng/ml Pembrolizumab, 400 ng/ml 3C 4H LPS SAg BT BF4T BE3C CASM3C HDF3CGF KF3CT MyoF lMphg Evaluation of Pembrolizumab Outside the TME Anti-PD1 antibodies are not inherently inflammatory • Confirm selectivity • Determine on/off target effects and even target related secondary effects • Inform mechanism of action • Nivolumab has an identical profile in this panel Monocyte Activation T cell Activation B cell Activation Macrophage Activation Matrix-modulation, fibrosis, tissue remodeling responses Vascular EC Inflammation Epithelial Inflammation and Matrix Remodeling Vascular SM Inflammation No activities detected RelativeExpressionLevels |Log10ratio|drug/vehiclecontrol)
- 23. 23 Challenges: Pre-clinical testing is technically challenging Current models are poorly predictive & expensive Often directly tested in patients Screening & Lead Optimization Efficacy & Biomarker Selection Safety & Pre-clinical Studies Clinical Combination Strategies How Do My Drugs Act in Combination Therapy?
- 24. 24 Combination Matrix Enhanced Immune Response with Combinations RelativeExpressionLevels |Log10ratio|drug/vehiclecontrol) Protein Biomarker Readouts Pembrolizumab plus Paclitaxel combination enhances cytokine production
- 25. 25 Lead Molecule: PathHunter® assays can help identify and optimize a lead candidate Efficacy: BioMAP® Oncology Systems determine drug efficacy in a human TME model Safety: Diversity PLUS™ evaluates drug activity outside the context of the TME Combinations: Combo ELECT tests the impact of drug interactions in a human TME model Summary Screening & Lead Optimization Efficacy & Biomarker Selection Safety & Pre-clinical Studies Clinical Combination Strategies
- 26. 26 DiscoverX: Enabling Testing to Therapy www.discoverx.com Send your questions to : SupportUS@discoverx.com SupportEurope@discoverx.com