Immunotherapy for Kidney Cancer: Finally Center-Stage? Nizar M. Tannir, MD, FACP Professor and Deputy Chair GU Medical Oncology

Immunotherapy for Kidney Cancer: Finally Center-Stage? Nizar M. Tannir, MD, FACP Professor and Deputy Chair GU Medical Oncology

2013: Breakthrough of the Year December 20, 2013

Why immunotherapy? Immune system can eradicate tumor cells Adaptability Specificity Memory

Rationale for developing immunotherapy as treatment for cancer patients Expression of tumor antigens that can be recognized by T cells Mutations ( drivers and passengers ) that occur during tumor development/progression represent antigens that can be recognized by the immune system Association of tumor infiltrating lymphocytes (TILs) with good prognosis

Somatic Mutations in Different Cancers Lawrence et al, Nature, 2013

Immunotherapy Strategies Cytokines Adoptive cellular immunotherapy Leukapheresis of T cells stimulated in vitro Modified T cells (chimeric antigen receptors [CAR] T cells) Oncolytic viruses Vaccines Immune checkpoint blockade

Cancer Vaccines

Activate the immune system Cancer vaccines Generate specific and targeted immune responses Types: Autologous dendritic cell-based Vector-based Whole-tumor cell

Arcelis Products Induce Patient-specific Memory T cells Arcelis Process Final Product* In Vivo Tumor Cells or Pathogen Monocytes RNA-loaded Dendritic Cell Amplified mrna Synthetic CD40L RNA Proprietary Dendritic Cell IL-12 secretion Naïve CD8 + T cell CD8 + CD28 + Memory T cell * Delivered by intradermal injection

Phase 3 ADAPT Trial Design 450 newly diagnosed, intermediate and poor risk mrcc patients Open label, first-line treatment Similar design as phase 2 combination trial with key enhancements AGS-003 dosing continues through initial progression Intermediate and poor risk patients with 1-4 risk factors (phase 3 patient population is currently ~70% intermediate risk) Primary endpoint ~6 month OS improvement (.708 hazard ratio) Granted SPA by FDA and received Fast Track designation Arm A: AGS-003 + Sunitinib Therapy 1 dose every 3 weeks x 5 Followed by quarterly dosing Diagnosis, Nephrectomy, Screening Randomization (2:1); Leukapheresis (Arm A only) Arm B: Sunitinib.

IMA901 Composition 10 tumor-associated peptides TUMAP ID Name Function / Comments HLA-A*02 TUMAPs ADF-001 Adipose differentiation-related protein Overexpressed in several cancers; established as a ADF-002 marker for clear-cell RCC APO-001 Apolipoprotein L,1 Overexpression in RCC CCN-001 Cyclin D1 Cell cycle regulation; frequently upregulated in many cancer types GUC-001 Guanylate cyclase 1 cgmp synthesis; pro-angiogenic effects in tumors K67-001 Prune homolog 2 MET-001 Met proto-oncogene MUC-001 Mucin 1 RGS-001 Regulator of G-protein signalling 5 HLA-DR TUMAPs MMP-001 Matrix metallopeptidase 7 (matrilysin, uterine) Largely uncharacterized so far; overexpression in RCC Proliferation, motility, adhesion, invasion; various implications in malignant transformation and invasiveness of tumor cells. Well-established TAA in CRC, unmasking of epitope due to altered glycosylation in tumors Regulation of cell signalling; overexpression during revascularization in tumors Tissue remodelling, inhibition of apoptosis Walter, et al. Nature Medicine, 2012

Phase III Trial of IMA901 in mrcc Cyclophosphamide (300 mg/m 2 as single infusion) Sunitinib (1 cycle) R 3:2 IMA901 plus GM-CSF (i.d.) Sunitinib Sunitinib until progression or toxicity Sunitinib Stratification: Vaccination Phase 4 months Risk group (low vs intermediate) 10 IMA901/GM-CSF vaccinations Region (WEE vs. CEE vs. US vs. Asia) Nephrectomy (yes vs. no) Follow-up for PFS Every 12 weeks Max. 19 months Follow-up for OS Every 3 months Up to 8 years N=339 (last patient randomized in Dec 2012) 1st line metastatic and/or locally advanced RCC HLA-A*02-positive Documented tumor lesions Favorable or intermediate risk (Heng et al., 2009) Primary: OS Secondary: OS in biomarker subgroup, PFS safety, immune responses, novel biomarkers.

Immune Checkpoint Blockade Therapy

The Cancer-Immunity Cycle Cancer antigen release Antigen presentation Priming and activation of T cells Trafficking of T cells into tumors Recognition of cancer cells by T cells Killing of cancer cells Chen and Mellman, Immunity, 2013

CTLA-4 Immunologic Checkpoint Michael A. Postow et al. JCO doi:10.1200/jco.2014.59.4358 2015 by American Society of Clinical Oncology

PD-1 Immunologic Checkpoint Michael A. Postow et al. JCO doi:10.1200/jco.2014.59.4358 2015 by American Society of Clinical Oncology

Immune Checkpoint Blockade Therapy Tumor Killing +

Immune Checkpoint Blockade Therapy Tumor Killing

Immune Checkpoint Blockade Therapy Tumor Killing +++

% Survival Standard Survival Curve Control Standard (or Other Therapy) Time

% Survival Improving Survival with Immunotherapy Immunotherapy (e.g. immune checkpoint inhibitor) Control Standard (or Other Therapy) Time

% Survival Improving Survival with Combination Therapy Combination of immune checkpoints Immunotherapy (e.g. immune checkpoint inhibitor) Control Standard (or Other Therapy) Time

Targeted Immunotherapy Agents Gangadhar T et al. Nature Reviews Clinical Oncology, 2014

Phase II Trial of Ipilimumab in mrcc Phase II, open labeled study in patients with mrcc: Group 1: ipi 3mg/kg 1mg/kg x3: PR-1/21 (lasted 18 months) Group 2: ipi 3mg/kg 3mg/kg x3: PR-5/40 (7-21 months) Yang et al. J Immunotherapy, 2007

Single-agent Nivolumab (PD-1 inhibitor) in mrcc Abstract # 5009 MOTZER et al. Abstract # 5012 CHOUEIRI et al. Design Randomized, dose-ranging phase II (N=168) Biomarker-based randomized clinical trial (N=91) (Baseline and on-therapy fresh tumor biopsies) Dose IV Q3W 0.3mg/kg n =60 2 mg/kg n=54 10 mg/kg n=54 0.3mg/kg n =22 2 mg/kg n=22 10 mg/kg n=23 10 mg/kg n=24 (naïve) Prior Tx 70% 2 prior therapies No treatment-naïve pts 74% (1-3) prior therapies 24 (16%) treatment-naïve pts ORR (%) 20% 22% 20% 9% 23% 22% 13% mpfs (m) 1º endpoint 2.7 4.0 4.2 PFS at 24 weeks: 36% mos (m) 18.2 25.5 24.7 Not Reported G3/4 TOX 5% 17% 13% 18% Biomarker None reported Increased T-cell tumor infiltrates after nivolumab Increased serum CXCL9 and CXCL10 post-nivolumab Numerically higher (22% vs. 8%) ORR in PD-L1 (+) pts Perspective Median PFS is not impressive: Axitinib/everolimus: ~5 m (post TKI) mpfs :an appropriate endpoint? Median OS is impressive: AXIS/RECORD-1: ~20/15 m What is the best biomarker for response?

Phase I Nivolumab-based combination studies Arm S Sunitinib 50 mg (4/2) + nivolumab 2mg/kg Q3W (N2) or 5mg/kg Q3W (N5) Abstract # 5010 AMIN et al. (nivo + VEGF TKI) Arm P Pazopanib 800 mg QD + nivolumab 2mg/kg Q3W (N2) (N3+I1) Nivolumab 3mg/kg + ipilimumab 1mg/kg Q3Wx4 Abstract # 4504 HAMMERS et al. (nivo + ipi) (N1+I3) Nivolumab 1mg/kg + ipilimumab 3mg/kg Q3Wx4 Prior therapy 42% 100% 80% Number of patients 33 20 21 23 MSKCC risk Favorable/Intermediate (94%) Favorable/Intermediate (100%) ORR (%) 52% 45% 43% 48% Median DOR range (wks) 54 18.1-80+ 30 12.1-90.1+ 31.1 4.1+ 42.1+ NR 12.1+ 35.1+ Median PFS (wks) ~estimated (mo) 48.9 ~11.4 31.4 ~7.3 36.6 ~8.4 38.3 ~8.9 Gr. 3/4 Toxicity (%) 81.8% 70% 29% (9.5% d/cd) 61% (26% d/cd) ALT elevation 18% Hypertension 18% Hyponatremia 15% 4 DLTs (stopped) (LFTs n=3, 20%) ALT elevation 0% Diarrhea 5% Fatigue 0% ALT elevation 26% Diarrhea 13% Fatigue 8%

PD-L1 (+) tumor by IHC in RCC and outcome Topalian et al.* (NEJM 2012) Cho et al. (ASCO 2013) Choueiri et al. (ASCO 2014) Drug Nivolumab MPDL3280A Nivolumab ORR PD-L1 (+) 36% 20% 22% ORR PD-L1 (-) 0 10% 8% Antibody 5H1 Genentech/Roche Ab 28.8 Cell stained Tumor Immune Cell Tumor Criteria for positivity >5% Any >5% * 5/42 tested tumors were RCC

Results of PD-1 and PD-L1 inhibitors in mrcc and ongoing randomized trials Agent Nivolumab MPDL3280A Avelumab Ph 1 Monotherapy (n=34); RR 29% Monotherapy (n=91); RR 9-23% + Ipilimumab (n=44) RR 43% (N3/11) RR 48% (N1/13) + Sunitinib or pazopanib (n=53) RR 43-48% Monotherapy (n=69) RR 15% + Bevacizumab (n=10) RR 40% + Axitinib Ph II Monotherapy (n=168); RR 20-22% PFS 2.7-25.5 mo OS 18.2-25.2 mo MPDL + Bev vs MPDL vs sunitinib in treatment-naïve (NCT01984242) Ph III Nivolumab vs everolimus with prior VEGFR- TKI treatment (NCT01668784 Nivolumab + Ipilimumab vs Sunitinib in treatment-naïve (NCT02231749)

Randomization Phase III Trial of Nivolumab vs. Everolimus Screening Treatment Follow Up Advanced or metastatic clear cell renal carcinoma progression on or after most recent therapy and within 6 months of study enrollment A B Nivolumab 3 mg/kg IV Q2wks until disease progression* or intolerable toxicity Everolimus 10 mg PO QD until disease progression* or intolerable toxicity Tumor assessments q8 weeks from randomization for 1 year then q12 weeks 2 Follow-up visits: Labs AE Assessments PK Tumor assessments continue for subjects without documented disease progression Survival Follow-up visit: Q 3 months

A Phase 3, Randomized, Open-label Study of Nivolumab plus Ipilimumab vs. Sunitinib in Subjects with Previously Untreated, Advanced or Metastatic Clear-cell RCC

Pre-surgical Combination Trial in mrcc: Nivolumab +/- Bevacizumab or Ipilimumab Arm A: Nivolumab 4 wks A PD CB Off study B Cytoreductive surgery C 4-6 wks Nivolumab 3mg/kg Q2wk Metastatic clear cell RCC Screen for eligibility R Arm B: Nivolumab + Bevacizumab 4 wks PD CB Off study Cytoreductive surgery 4-6 wks Nivolumab 3mg/kg Q2wk Arm C: Nivolumab + Ipilimumab 4 wks PD CB Off study Cytoreductive surgery 4-6 wks Nivolumab 3mg/kg Q2wk PI: Padmanee Sharma, MD, PhD

Immune Related Toxicities Pneumonitis Shortness of breath Enterocolitis Diarrhea, abdominal pain Hepatitis Fatigue, abdominal pain Hypophysitis Headache, vision change, fatigue, low blood pressure Dermatitis Rash Endocrine Adrenal insufficiency, hypothyroidism, diabetes mellitus

Case Study 1: Nivolumab - PP Baseline

Case Study 1: Nivolumab - PP Baseline Continues to respond > 2 years w/o toxicity

Case Study 2: Nivolumab - AA Baseline

Baseline 8 weeks

8 weeks Baseline 21 weeks

Case Study 3: Nivolumab - RD

Baseline

Baseline 16 weeks

2 years Baseline 16 weeks

Immune Checkpoint Blockade: Clinical considerations and ongoing questions Patterns of disease response: irrc Immune related AEs Optimization of dose, schedule, treatment duration Biomarkers associated with disease outcome Optimal combinatorial approaches Rechallenge (Boost)

Conclusions Immunotherapy is witnessing a renaissance The promise of immunotherapy and precision oncology are here Challenges: Biomarkers of response Mechanisms of resistance Overcoming toxicity Ongoing and future trials will address these challenges

Immunotherapy (IMT) Platform James Allison Padmanee Sharma Patrick Hwu Jorge Blando Acknowledgements PATIENTS GU Medical Oncology Eric Jonasch Jianjun Gao Sumit Subudhi Christopher Logothetis Urology Christopher Wood Jose Karam Surena Matin Radiology Chaan Ng Pathology Pheroze Tamboli Priya Rao Kanishka Sircar