Vice President, Cancer Immunology, Genentech - Ira Mellman, Ph.D. The renaissance of immunotherapy is a revolution for cancer patients
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The renaissance of immunotherapy is a revolution for cancer patients Ira Mellman, Ph.D. Vice President, Cancer Immunology, Genentech 1
This presentation contains certain forward-looking statements. These forward-looking statements may be identified by words such as ‘believes’, ‘expects’, ‘anticipates’, ‘projects’, ‘intends’, ‘should’, ‘seeks’, ‘estimates’, ‘future’ or similar expressions or by discussion of, among other things, strategy, goals, plans or intentions. Various factors may cause actual results to differ materially in the future from those reflected in forward-looking statements contained in this presentation, among others: 1 pricing and product initiatives of competitors; 2 legislative and regulatory developments and economic conditions; 3 delay or inability in obtaining regulatory approvals or bringing products to market; 4 fluctuations in currency exchange rates and general financial market conditions; 5 uncertainties in the discovery, development or marketing of new products or new uses of existing products, including without limitation negative results of clinical trials or research projects, unexpected side-effects of pipeline or marketed products; 6 increased government pricing pressures; 7 interruptions in production; 8 loss of or inability to obtain adequate protection for intellectual property rights; 9 litigation; 10 loss of key executives or other employees; and 11 adverse publicity and news coverage. Any statements regarding earnings per share growth is not a profit forecast and should not be interpreted to mean that Roche’s earnings or earnings per share for this year or any subsequent period will necessarily match or exceed the historical published earnings or earnings per share of Roche. For marketed products discussed in this presentation, please see full prescribing information on our website www.roche.com All mentioned trademarks are legally protected. 2
Early data suggests that anti-PD-L1/PD-1 is active across a wide range of tumor types • Melanoma: FDA approval • NSCLC (squamous): FDA approval, 2nd line • Renal cell carcinoma • Breast cancer (e.g. TNBC) • Metastatic bladder cancer • Head & neck cancer • Hodgkin's lymphoma Response rates are modest, at ~10-30% Broad activity but most patients do not benefit from single agent therapy
Using patient data to understand cancer immunity cycle MPDL3280A Phase 1 Data: Urothelial Bladder Cancer Patients Progressive Disease (PD) Why do many patients not respond? • No pre-existing immunity? Stable disease (SD) What combinations will promote PRs & CRs? • Insufficient T cell immunity? • Multiple negative regulators? Monotherapy durable responses (PR/CR) What are the drivers of single agent response? How can PRs be enhanced to CRs? • Insufficient T cell immunity? • Multiple negative regulators?
The cancer immunity cycle Immunosuppression as the rate limiting step to effective anti-tumor immunity α-CTLA4 (ipilumumab) Immuno- suppression α-PD-L1/PD-1 (multiple) Chen & Mellman (2013) Immunity
Combinations of immunotherapeutics Increasing response rates by keeping cancer immunity cycle turning * = Genentech/Roche programs α-VEGF-A* α-CTLA4* α-OX40* α-CD27* α-CD137 α-GITR vaccines* α-CD40* α-PDL1*/PD1 α-OX40* (Treg) α-LAG-3 α-CTLA4* (Treg) α-TIGIT* α-CSF1R* α-KIR IDO inhibitor* Chen & Mellman (2013) Immunity
IDO (indoleamine di-oxygenase) Another suppressor of effector T cells Adaptive expression of PD-L1 Adaptive expression of IDO IDO IFNγ-‐mediated IFNγ-‐mediated up-‐regulation of up-‐regulation of tumor IDO tumor PD-‐L1 Inhibition of effector T cell function Shp-2 Shp-2 MAPK" MAPK" PI3K PI3K pathways" pathways" Georgia Hatzivassiliou, Yichin Liu
IDO mediates T cell suppression by reducing extracellular tryptophan and increasing kynurenine Tumor cells Dendritic cells Macrophages IDO* IFNg activates Free tryptophan IDO expression Kynurenine high low ñ Uncharged arylhydrocarbon mTOR Tryptophanol-tRNA receptor suppressive GCN2 kinase cytokines FoxP3 Promote translation Stress response Suppress Enhance T effectors T reg *TDO (tryptophan dioxygenase) is a second related target to IDO
Early combination data shows promising efficacy Phase I/II study of INCB024360 plus ipilimumab in melanoma Best percent change in tumor burden in tumor burden Percent change Gibney et al. ASCO 2014
TIGIT Model of TIGIT regulation of T cell responses Tumor cell or DC • Human and murine tumor-infiltrating CD8+ T cells express high levels of TIGIT ITIM • Antibody coblockade of TIGIT and PDL1 1 Competes with CD226 for PVR elicits tumor rejection in preclinical PVR models 100nm 1nm CD226 TIGIT • TIGIT selectively limits the effector function of chronically stimulated ITAM 2 ITIM Disrupts CD226 ac7va7on 3 Directly inhibits T cell in cis CD8+ T cells • TIGIT interacts with CD226 in cis and disrupts CD226 homodimerization T cell
TIGIT TIGIT and PD-L1 combination effective in PD-L1 non-responsive model Median Tumor Volume (mm3) 10000 40 60 + NME1 anti-PD-L1 Tumor cell or DC Control Control Median Tumor Volume (mm3) Anti-PD-L1 anti-PD-L1 NME1 TIGIT anti-PD-L1 Complete Remission (CR) 1000 30 NME1 ITIM Control Day PVR 1 Competes with CD226 for PVR 20 100nm 1nm Anti-PD-L1 anti-PD-L1 100 CD226 TIGIT + TIGIT + NME1 10 ITAM 2 ITIM Disrupts CD226 ac7va7on 3 Directly inhibits T cell in cis Complete Remission (CR) 0 10 10000 1000 100 10 0 10 20 30 40 60 Day T cell
OX40 function and potential in oncology Promote antigen dependent effector T cell activation and T regulatory cell inhibition OX40 engagement on Treg cells Primary Tumor Challenge (EMT6) OX40L Tumor Volume (mm3) Antigen Control Presenting Cell 3000 Anti-mouse OX40 Treg 2000 OX40L OX40L 1000 TCR OX40 0 OX40 IFN-γ 0 10 20 30 40 50 day day Effector T Treatment cell Adapted from Nature Rev Immunol. 4:420 (2004).
Increase in Teff cells by anti-OX40 may create need to combine with anti-PDL1 anti-OX40 OX40L OX40 IFN-γ" T cell IFNγ PD-L1 PD-1 T cell increase CD8 anti-PDL1 receptor HLA PD-L1 Tumor cell Chen & Mellman (2013) Immunity Jul 25;39(1):1-10
Anti-OX40 combined with anti-PDL1 in the MC38 model 2500 anti%PD%L1* Tumor Volume (mm3) 2500 Tumor Volume (mm3) !!!!!!!!!!!!!!!!!!!!!!!anti&OX40! control* 2000 !!!!!!!!!!!!!!!!!control! 2000 1500 1500 1000 1000 500 500 0 0 0 10 20 30 40 50 0 20 40 60 day day 2500 Tumor Volume (mm ) 30000 3 PD-L1 Expression 2000 anti%OX40*+*anti%PD%L1* 20000 1500 1000 10000 500 0 0 0 20 40 60 C T T nu loid C te ye r o 4+ 8+ cy m day D D Tu lo M ra G Jeong Kim et al. AACR 2015
Combination with Avastin Increasing response rates by keeping cancer immunity cycle turning α-VEGF-A Chen & Mellman (2013) Immunity
Increases in CD8+ T cell infiltration and vasculature changes with treatments in RCC Pretreatment Post Avastin Post Avastin + aPD-L1 CD8 (T cells) CD31 (vasculature) Sznol et al. ASCO GU 2015 17
Anti-PDL1 in combination with Avastin Anti-VEGF combination: Combination of anti-PDL1 and Avastin preclinical data (Ph1 data in renal cancer) Cloudman melanoma 2000 a-PD-L1 1500 Control a-VEGF 3 Tumor Volume, mm 1000 a-PD-L1 + a-VEGF 500 0 0 10 20 30 40 50 Day Sznol et al. ASCO GU 2015 18
Combinations with chemotherapy Induced inflammation & antigen release may enhance anti-PDL1 efficacy Chemotherapy Chen & Mellman (2013) Immunity
Inflammation is necessary for response Inflamed Non-inflamed Can responses Can we convert these be improved? to responsive? Tumor phenotype by T cell staining 20-30% patients 70-80% patients • T cells present in tumor • Lack lymphocytic infiltrates • Chemokines present (attract leukocytes) Responsive to single agent Non-responsive to single immunotherapies agent immunotherapies 20
Combinations with chemotherapy extend the benefit of anti-PDL1 Pre-clinical data 3000 oxaliplatin • Platinum chemo increases number of Control α-PDL1 CD8+ cells in animal models 2500 2000 • Compelling chemo+PD-L1 combination efficacy observed in 3 Tumor Volume, mm 1500 phase 1 studies • Broad phase 3 combination program 1000 500 initiated in 1L NSCLC and TNBC combo 0 0 6 12 16 22 29 36 Day Dosing Phase 1 chemo combination data to be presented at ASCO 2015
Not all patients may have pre-existing immunity: monitoring & promoting T cell responses ImmTACs and bispecific antibodies 4 3 5 2 Recognition of cancer 6 cells by T cells (CTLs, cancer cells) ImmTACs Bispecifics 1 7
Recruiting T cells to cancer cells ImmTACs and bispecific antibodies Targeting intracellular tumor markers Targeting extracellular tumor markers Cancer cell Tumor antigen TCR Knob into holes full-length IgG T cell Immune-mobilizing mTCR Against Cancer* T-cell Dependent Bispecific *In colalboaration with Immunocore
Not all patients may have pre-existing immunity: monitoring & promoting T cell responses Vaccines 4 3 5 Cancer antigen presentation 2 (dendritic cells/APCs) 6 Vaccines: • Endogenous • Exogenous 1 7 Chen & Mellman (2013) Immunity
Anti-PDL1 Phase Ia: indication response rates correlate with mutation frequency Schumacher and Schreiber (2015) Science
Structural analysis suggests that only some mutations will be accessible to T cell receptors Immunogenic Non-immunogenic solvent-exposed mutation mutation in MHC groove S E M T S I V Y A G E S W N N M L V PàA RàM DàY REPS1! AQLPNDVVL! Copine-1! SSPDSLHYL! ADPGK! ASMTNRELM! H60! SSVIGVWYL! FLU-NP! ASNENMETM! 26 Yadav et al (2014) Nature
Promise for a PHC vaccine? Immunization with antigenic peptides regresses growth of established MC38 tumors 14-0584: mutated MHCI MC38 peptide vaccine; MC-38 14−0584:mutated 14-0584: mutated MHCI MHCI MC38 MC38 peptide vaccine; peptide MC−38MC-38 vaccine; Raw and LME Fit Tumor Volume Overlay Fits Tumor Volume 700 Raw and LME Fit Tumor Volume 1 0 2 2 4 6 Dose ● Control 01 − untreated control Control Adj ● ● 600 ● Adj02 − d1: anti−CD40 50µg + pIC 100µg, IP injection. d10: anti−CD40 ● 500 ● ● 400 03 Adj+ − d1: anti−CD40 50µg + pIC 100µg + 3Xpeptide mix 100µg, IP Peptides 300 ● ● ● ● ● ● ● ● ● ● ● ● Tumor Volume ( mm3) 200 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 3 700 Adj+peptides 600 500 ● 400 Immunization 300 ● ● 200 ● ● ● ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● 0 0 2 4 6 Day Yadav et al (2014) Nature
Strategic vision: lead by developing best in class combination therapies T cell trafficking Combinations with immunotherapies 4 aCD40 ✔ Priming & activation Vaccines, Oncolytic Viruses ✔✔ anti-CEA-IL2v aCTLA-4 ✔ anti-OX40 anti-CTLA4 3 aOX40 ✔ aCD27 ✔ anti-CD27* aCEA-IL2v ✔ anti cytokine CD38* 5 TaVEGF cell infiltration T Cell Bispecifics ✔ ImmTACs Planned IDOi ✔✔ aCSF1R ✔ aTIGIT Planned Cytokines, anti-cytokines ✔ 2 Immuno- Combinations with other agents suppression 6 aVEGF ✔ Antigen presentation Cancer T cell recognition aCD38 ✔ anti-CD40 anti-HER2-CD3 FGFR1 ✔ IMA942 vaccine* anti-CD20-CD3 EGFRi ✔✔ oncolytic viruses* ImmTAC* ALKi Planned 1 7 BRAFi ✔ Antigen release T cell killing MEKi ✔ EGFRi anti-OX40 BTKi ✔ ALKi anti-CSF-1R aCD20 ✔ BRAFi anti-CEA-IL2v aHER2 ✔ MEKi IDO inhibitor* Chemo ✔ ✔ Chemo TIGIT HDAC ✔ FGFR1* IDO1/TDO inhibitor* A2V ✔ BTKi HDAC Clinical development ✔ Partnered external combo Preclinical development ✔ Internal combo * Partnered projects Chen & Mellman (2013) Immunity
Doing now what patients need next
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