A Phase II Study of With or Without Bevacizumab vs in Untreated Metastatic Renal Cell Carcinoma Patients David McDermott, 1 Michael Atkins, 2 Robert Motzer, 3 Brian Rini, 4 Bernard Escudier, 5 Lawrence Fong, 6 Richard W. Joseph, 7 Sumanta Pal, 8 Mario Sznol, 9 John Hainsworth, 10 Walter M. Stadler, 11 Thomas Hutson, 12 Alain Ravaud, 13 Sergio Bracarda, 14 Cristina Suarez, 15 Toni Choueiri, 16 YounJeong Choi, 17 Mahrukh A. Huseni, 17 Gregg D. Fine, 17 Thomas Powles 18 1 Beth Israel Deaconess Medical Center, Boston, MA; 2 Georgetown Lombardi Comprehensive Cancer Center, Washington, DC; 3 Memorial Sloan Kettering Cancer Center, New York, NY; 4 Cleveland Clinic, Cleveland, OH; 5 Gustave Roussy, Villejuif, France; 6 University of California, San Francisco School of Medicine, San Francisco, CA; 7 Mayo Clinic Hospital Florida, Jacksonville, FL; 8 City of Hope Comprehensive Cancer Center, Duarte, CA; 9 Yale School Of Medicine, New Haven, CT; 10 Sarah Cannon Research Institute, Nashville, TN; 11 University of Chicago Medicine, Chicago, IL; 12 Texas Oncology - Baylor Charles A. Sammons Cancer Center, Dallas, TX; 13 CHU Hopitaux de Bordeaux - Hôpital Saint-André, Bordeaux, France; 14 Ospedale San Donato, Arezzo, Italy; 15 Vall d Hebron Institute of Oncology, Vall d Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain; 16 Dana-Farber Cancer Institute, Boston, MA; 17 Genentech, Inc., South San Francisco, CA, USA; 18 Barts Cancer Institute, Queen Mary University of London, London, UK
Shifting the Balance Toward Anti-Cancer Immunity With Combined VEGF/PD-L1 Blockade Anti-Cancer Immunity 2 PD-L1, programmed death-ligand 1; VEGF, vascular endothelial growth factor. Finke, Clin Cancer Res. 2008; McDermott, J Clin Oncol. 2016; Wallin. Nat Commun. 2016. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
Shifting the Balance Toward Anti-Cancer Immunity With Combined VEGF/PD-L1 Blockade Anti-Cancer Immunity 3 Bevacizumab PD-L1, programmed death-ligand 1; VEGF, vascular endothelial growth factor. Finke, Clin Cancer Res. 2008; McDermott, J Clin Oncol. 2016; Wallin. Nat Commun. 2016. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
CD8 IHC + Bevacizumab A Phase Ib study in first-line mrcc showed anti-tumor activity and a tolerable safety profile for atezolizumab + bevacizumab 1,2 Sequential tumor biopsies provided preliminary evidence of enhanced anti-tumor immune responses following treatment with bevacizumab and atezolizumab + bevacizumab 2 Pre-treatment Post bevacizumab Post atezolizumab + bevacizumab 1. Sznol, ASCO GU, 2015. 2. Wallin, Nat Commun, 2016. Figures reprinted from Wallin JJ, et al. Nat Commun. 2016;7:12624. The Authors 2016; licensed under a Creative Commons Attribution 4.0 International License. Presented by: Dr. Thomas Powles
IMmotion150 (Phase II) Trial Design Treatment naive, locally advanced or metastatic RCC N = 305 Stratification: Prior nephrectomy PD-L1 IHC expression ( 5% IC level) MSKCC risk category R 1:1:1 First-line treatment 1200 mg IV + bevacizumab 15 mg/kg q3w 1200 mg IV q3w 50 mg (4 wk on, 2 wk off) PD Crossover treatment permitted a + bevacizumab + bevacizumab The coprimary endpoints are PFS (RECIST v1.1 by IRF) in ITT and PD-L1+ patients IMmotion150 was designed to be hypothesis generating and inform the trial design of the Phase III study IMmotion151 Amendments included: Based on Phase 1a data, the definition of PD-L1 positivity was revised from 5% to 1% of IC expressing PD-L1 1 In addition to ITT patients, PD-L1+ patients were included in the coprimary endpoint of IRF-assessed PFS, after interim analyses IC, tumor-infiltrating immune cells; IRF, independent review facility. 1. McDermott JCO 2016. a Crossover from atezolizumab monotherapy not allowed in Europe. Presented by: Dr. Thomas Powles
Baseline Demographics (ITT) n = 101 + bevacizumab n = 101 n = 103 Age, median (range), y 61 (25-85) 62 (32-88) 61 (27-81) Male, n (%) 79 (78%) 74 (73%) 77 (75%) KPS 80, n (%) 94 (93%) 99 (99%) 101 (99%) Predominant clear cell histology, n (%) 96 (96%) 97 (96%) 95 (92%) Sarcomatoid component, n (%) 14 (14%) 15 (15%) 16 (15%) Prior nephrectomy, n (%) 88 (87%) 88 (87%) 89 (86%) MSKCC risk category, n (%) Favorable (0) 21 (21%) 30 (30%) 26 (25%) Intermediate (1 or 2) 70 (69%) 62 (61%) 69 (67%) Poor ( 3) 10 (10%) 9 (9%) 8 (8%) 1% of IC expressing PD-L1 (PD-L1+), n (%) 60 (59%) 50 (50%) 54 (52%) Clinical cut-off, Oct 17, 2016. Median duration of follow-up, 20.7 mo. Presented by: Dr. Thomas Powles
IRF-Assessed PFS ITT + bevacizumab Atezo + bev vs sunitinib Atezo vs sunitinib Stratified HR (95% CI) 1.00 (0.69, 1.45) 1.19 (0.82, 1.71) P Value a 0.982 0.358 Atezo, atezolizumab; Bev, bevacizumab. a P values are for descriptive purposes only and not adjusted for multiple comparisons. Presented by: Dr. Thomas Powles
IRF-Assessed PFS ITT + bevacizumab Atezo: 6.1 mo (5.4, 13.6) : 8.4 mo (7.0, 14.0) Atezo + bev vs sunitinib Atezo vs sunitinib Stratified HR (95% CI) 1.00 (0.69, 1.45) 1.19 (0.82, 1.71) P Value a 0.982 0.358 Atezo + bev: 11.7 mo (8.4, 17.3) a P values are for descriptive purposes only and not adjusted for multiple comparisons. Presented by: Dr. Thomas Powles
IRF-Assessed PFS 1% of IC Expressing PD-L1 + bevacizumab Atezo + bev vs sunitinib Atezo vs sunitinib Stratified HR (95% CI) 0.64 (0.38, 1.08) 1.03 (0.63, 1.67) P Value a 0.095 0.917 a P values are for descriptive purposes only and not adjusted for multiple comparisons. Presented by: Dr. Thomas Powles
IRF-Assessed PFS 1% of IC Expressing PD-L1 + bevacizumab Atezo: 5.5 mo (3.0, 13.9) : 7.8 mo (3.8, 10.8) Atezo + bev: 14.7 mo (8.2, 25.1) Atezo + bev vs sunitinib Atezo vs sunitinib Stratified HR (95% CI) 0.64 (0.38, 1.08) 1.03 (0.63, 1.67) P Value a 0.095 0.917 a P values are for descriptive purposes only and not adjusted for multiple comparisons. Presented by: Dr. Thomas Powles
IRF-Assessed PFS in Key Subgroups + Bevacizumab vs Sarcomatoid Liver metastasis MSKCC risk IC expressing PD-L1 Baseline Factor Yes No Yes No Favorable Intermediate Poor < 1% 1% and < 5% 5% and < 10% 10% All patients (ITT) n 29 171 48 154 51 132 19 89 76 22 12 202 0.23 0.50 0.63 0.82 0.75 0.98 0.91 0.87 0.92 1.22 1.06 1.47 Clinical cut-off, Oct 17, 2016. Median duration of follow-up, 20.7 mo. In favor of atezo + bev In favor of sunitinib 1 Hazard Ratio Presented by: Dr. Thomas Powles
Confirmed IRF-Assessed ORR ITT 1% of IC expressing PD-L1 46% 29% 32% 25% 27% 28% PR 5% 7% 11% 7% 12% 15% CR 75% of responses are ongoing across treatment arms, and the median DOR is not estimable due to an insufficient number of PFS events in responders Clinical cut-off, Oct 17, 2016. Median duration of follow-up, 20.7 mo. Presented by: Dr. Thomas Powles
All-Cause AEs > 5% difference between arms and at a 20% frequency in either arm Fatigue Diarrhea Nausea Palmar-plantar Mucosal inflammation Dysgeusia Decreased appetite Cough Stomatitis Headache Arthralgia Rash Epistaxis Pyrexia Pruritus Proteinuria 80% + Bevacizumab All-Grade AEs Grade 3-5 AEs Clinical cut-off, Oct 17, 2016. Median duration of follow-up, 20.7 mo. All-Grade AEs Grade 3-5 AEs 60% 40% 20% 0 20% 40% 60% 80% Presented by: Dr. Thomas Powles
All-Cause AEs > 5% difference between arms and at a 20% frequency in either arm Fatigue Diarrhea Nausea Palmar-plantar Hypertension Mucosal inflammation Constipation Dysgeusia Decreased appetite Stomatitis Headache Vomiting Rash Pyrexia 80% All-Grade AEs Grade 3-5 AEs Clinical cut-off, Oct 17, 2016. Median duration of follow-up, 20.7 mo. Presented by: Dr. Thomas Powles All-Grade AEs Grade 3-5 AEs 60% 40% 20% 0 20% 40% 60% 80%
Transcriptome Map of Angiogenesis and Immune-Associated Genes in RCC Tumors PD-L1 IHC 15 Angiogenesis (e.g., CD34, KDR, VEGFA) PD-L1 IHC IC0 IC1 IC2 IC3 Immune, Antigen Presentation Myeloid Inflammation (e.g. CD8A, IFNG, PSMB8) (e.g. IL6, PTGS2, IL8) 3 2 1 0-1 -2-3 Brauer, Clin Cancer Res. 2012; Herbst, Nature 2014; Powles, SITC 2015; Fehrenbacher, Lancet 2016. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
Demonstrated Improved PFS in Angiogenesis High Subset vs Angiogenesis Low Subset 16 Angiogenesis + Bevacizumab High (n = 44) Low (n = 45) High (n = 45) Low (n = 43) High (n = 42) Low (n = 44) Angiogenesis (High vs Low) HR 95% CI 0.31 (0.18, 0.55) + Bevacizumab HR 95% CI Angiogenesis (High vs Low) 0.90 (0.54, 1.51) HR 95% CI Angiogenesis (High vs Low) 0.74 (0.42, 1.28) Angiogenesis gene signature: VEGFA, KDR, ESM1, PECAM1, ANGPTL4, CD34. Angiogenesis High: median expression, Angiogenesis Low: < median expression. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
Demonstrated Improved PFS in Angiogenesis High Subset vs Angiogenesis Low Subset 17 Angiogenesis + Bevacizumab High (n = 44) Low (n = 45) HR (95% CI) 0.31 (0.18, 0.55) High (n = 45) Low (n = 43) High (n = 44) Low (n = 45) High (n = 42) Low (n = 44) Angiogenesis (High vs Low) HR 95% CI 0.32 (0.18-0.55) Atezo + Bev HR 95% CI Angiogenesis (High vs Low) 0.90 (0.53-1.51) HR 95% CI Angiogenesis (High vs Low) 0.74 (0.43, 1.29) Angiogenesis gene signature: VEGFA, KDR, ESM1, PECAM1, ANGPTL4, CD34. Angiogenesis High: median expression, Angiogenesis Low: < median expression. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
+ Bevacizumab Demonstrated Improved PFS vs in the Angiogenesis Low Subset 18 Angiogenesis Angiogenesis Low Atezo + bev (n = 43) Atezo (n = 44) (n = 45) Angiogenesis High Atezo + bev (n = 45) Atezo (n = 42) (n = 44) HR (95% CI) Angiogenesis Low Angiogenesis High Atezo + bev vs sunitinib 0.58 (0.35, 0.98) 1.36 (0.78, 2.36) Atezo vs sunitinib 0.75 (0.45, 1.25) 1.45 (0.81, 2.60) Angiogenesis gene signature: VEGFA, KDR, ESM1, PECAM1, ANGPTL4, CD34. Angiogenesis High: median expression, Angiogenesis Low: < median expression. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
Transcriptome Map of Angiogenesis and Immune-Associated Genes in RCC Tumors PD-L1 IHC 19 Angiogenesis (e.g., CD34, KDR, VEGFA) PD-L1 IHC IC0 IC1 IC2 IC3 Immune, Antigen Presentation Myeloid Inflammation (e.g. CD8A, IFNG, PSMB8) (e.g. IL6, PTGS2, IL8) 3 2 1 0-1 -2-3 Brauer, Clin Cancer Res. 2012; Herbst, Nature 2014; Powles, SITC 2015; Fehrenbacher, Lancet 2016. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
and Bevacizumab Demonstrated Improved PFS in T-Effector High Subset vs T-Effector Low Subset 20 Immune + Bevacizumab High (n = 43) Low (n = 46) High (n = 42) Low (n = 46) High (n = 46) Low (n = 40) T-effector (High vs Low) HR 95% CI 1.31 (0.77, 2.23) + Bevacizumab T-effector (High vs Low) HR 95% CI 0.50 (0.30, 0.86) T-effector (High vs Low) HR 95% CI 0.83 (0.48, 1.45) T-effector gene signature: CD8A, EOMES, PRF1, IFNG, CD274. T-effector High: median expression, T-effector Low: < median expression. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
and Bevacizumab Demonstrated Improved PFS vs in the T-Effector High Subset 21 Immune T-effector Low Atezo + bev (n = 46) Atezo (n = 40) (n = 46) T-effector High Atezo + bev (n = 42) Atezo (n = 46) (n = 43) HR (95% CI) T-effector Low T-effector High Atezo + bev vs sunitinib 1.41 (0.84, 2.36) 0.55 (0.32, 0.95) Atezo vs sunitinib 1.33 (0.76, 2.33) 0.85 (0.50, 1.43) T-effector gene signature: CD8A, EOMES, PRF1, IFNG, CD274. T-effector High: median expression, T-effector Low: < median expression. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
Myeloid Inflammation Immune, Antigen Presentation Angiogenesis Transcriptome Map of Angiogenesis and Immune-Associated Genes in RCC Tumors 22 Myeloid Inflammation PD-L1 IHC T-effector High Subpopulation Tumor cells T-effector cells Myeloid cells Vasculatur e T-effector High Myeloid Inflammation Low T-effector High Myeloid Inflammation High 3 2 1 0-1 -2-3 PD-L1 IHC IC0 IC1 IC2 IC3 Brauer, Clin Cancer Res. 2012; Herbst, Nature 2014; Powles, SITC 2015; Fehrenbacher, Lancet 2016. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
Addition of Bevacizumab to is Associated With Improved Benefit in T-effector High /Myeloid Inflammation High Subgroup Myeloid Inflammation 23 T-effector High Myeloid Low Atezo + bev (n = 23) Atezo (n = 23) (n = 19) T-effector High Myeloid High Atezo + bev (n = 20) Atezo (n = 23) (n = 24) Atezo + bev (n = 20) Atezo (n = 23) (n = 24) T-effector Gene Signature: CD8A, EOMES, PRF1, IFNG, CD274. High: median expression, Low: < median expression. McDermott D, et al. IMmotion150 biomarkers: AACR 2017
Conclusions + bevacizumab resulted in encouraging efficacy vs sunitinib in the PD-L1+ subgroup of first-line mrcc patients The data corroborate the clinical activity of atezolizumab monotherapy in first-line mrcc 1 RNAseq gene expression data shows 3 response signatures of clinical relevance. Its also shows bevacizumab and atezolizumab has significant immune activity even in those with resistance to atezo ( high expression of T effector and myeloid signature). Onong RIII studies in will potentially validate these findings. 1. Herbst Nature 2014. Presented by: Dr. Thomas Powles