Immune Checkpoint Inhibitors: Basics and Results
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1 Immune Checkpoint Inhibitors: Basics and Results Christoph Zielinski Comprehensive Cancer Center Medical University Vienna General Hospital, Vienna, Austria and Central European Cooperative Oncology Group (CECOG,
2 COI Declaration Honoraria: BMS, MSD, AstraZeneca, Novartis, Roche
3 Signalling in T Cell Activation P. Sharma & JP Allison, Science 348: 56, 2015
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5 Immune System Activation and Regulation in the Antitumor Response. Barbara Melosky et al. JCO doi: /jco
6 Immunoediting in Cancer D.P.Carbone, D.R. Gandara, S.J.Antonia, C. Zielinski, L. Paz-Ares: J Thoracic Oncol 10: 974, 2015
7 From: Mechanisms regulating T-cell infiltration and activity in solid tumors Ann Oncol. 2017;28(suppl_12):xii18-xii32. doi: /annonc/mdx238
8 Survival Curves for Tumor Lymphocytic Infiltration for OS and DFS (A,C: Discovery; B,D: Validation Sets) in Resectable NSCLC 2016 by American Society of Clinical Oncology Elisabeth Brambilla et al. JCO 2016;34:
9 Types of Cancers Regarding Immune Function Chen DS & Mellman I: Nature 341: 321, 2017
10 The Cancer-Immunity Cycle J. M. Kim, and D. S. Chen Ann Oncol 2016;27:
11 Enhancement of T Cell Responses by Immune Checkpoint Blockade P. Sharma & JP Allison, Science 348: 56, 2015
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13 T Cells: Regulatory Receptors K.M. Mahoney et al., Nature Rev. Drug Discovery 14: 561, 2015.
14 T-cell Immune Checkpoints as Targets for Immunotherapy There are several T-cell targets for immunotherapy Agonistic antibodies directed towards activating co-stimulatory molecules and blocking antibodies against co-inhibitory molecules may enhance T-cell stimulation to promote tumor destruction Activating receptors Inhibitory receptors CD28 OX40 GITR CD137 CD27 HVEM T cell CTLA-4 PD-1 B7-1 TIM-3 BTLA VISTA LAG-3 Agonistic antibodies T-cell stimulation Blocking antibodies Adapted from Mellman et al. Nature. 2011;480(7378):
15 Mechanisms of Immune Escape in the Tumor Microenvironment. Roman M. Chabanon et al. Clin Cancer Res 2016;22: by American Association for Cancer Research
16 Factors Influencing Tolerance vs. Immunity
17 The Prognostic Role of Immune Cells in Lung Cancer Tumors such as melanoma, renal cell carcinoma and lung malignancies are recognized by and initiate a response from the immune system Presence of certain immune cells are associated with prognosis and outcomes Tumor Adapted from: /03/lungs-graphic.jpg Dendritic Cells Favorable prognosis 1 : OS, diseasespecific survival, DFS CD3 + Cells Favorable prognosis 2-4 : NSCLC survival and lower risk of disease recurrence CD8 + Cells Favorable prognosis 5-8 : OS CD4 + Cells Favorable prognosis 6,9 : OS Macrophages Favorable prognosis 7 : OS NK Cells Favorable prognosis 10 : NSCLCspecific survival NK Cells (Immature / Impaired) Unfavorable prognosis 11 : Disease progression Tregs Unfavorable prognosis 12,13 : OS, relapse- and recurrence-free survival DFS = disease-free survival; NK = natural killer; NSCLC = non-small cell lung cancer; OS = overall survival; Treg = regulatory T cell. 1. Dieu-Nosjean MC, et al. J Clin Oncol. 2008;26: ; 2. Petersen RP, et al. Cancer. 2006;107: ; 3. Al-Shibli K, et al. APMIS. 2010;118: ; 4. Ruffini E, et al. Ann Thorac Surg. 2009;87: ; 5. Zhuang X, et al. Appl Immunohistochem Mol Morphol. 2010;18:24 28; 6. Hiraoka K, et al. Br J Cancer. 2006;94: ; 7. Kawai O, et al. Cancer. 2008;113: ; 8. McCoy MJ, et al. Br J Cancer. 2012;107: ; 9.Wakabayashi O, et al. Cancer Sci. 2003;11: ; 10. Al-Shibli K, et al. Histopathol. 2009;55: ; 11. Jin J, et al. PLoS One. 2013;8:e61024; 12. Tao H, et al. Lung Cancer. 2012;75:95 101; 13. Shimizu K, et al. J Thorac Oncol. 2010;5:
18 The Immune Regulatory Cycle and Possible Interventions Chia et al., Immunity 39: 1-10, 2013
19 Immuno Oncology: Compounds anti-ctla-4: 2010: Ipilimumab in development: Tremelimumab anti-pd-1: 2014: Pembrolizumab 2014: Nivolumab anti-pd-l1, 2017: Atezolizumab Durvalumab Avelumab
20 Anti-PD-1 and PD-L1 Antibodies: Registrations for Firstand Second Line Treatments, Q Metastatic Malignant Melanoma NSCLC, non-squamous, 1st Line Treatment (Pembrolizumab) and 2nd Line Treatment after Platinum-Based Progression NSCLC, squamous, 2nd Line Treatment after Platinum-Based Progression Renal Cell Cancer Bladder Cancer Head and Neck Cancer Gastroesophageal Cancer Merkel Cell Cancer Hodgkin s disaese
21 Use of ICPIs in NSCLC First-Line Treatment: Keynote 024 Keynote 189 in combination with chemotherapy ImPower 150 in combination with chemotherapy Checkmate 227 in combination with chemotherapy Second-Line Treatment Nivolumab, Pembrolizumab, Atezolizumab Early NSCLC (Stage III) Durvalumab
22 ORR in Dependence on PD-L1 Expression in NSCLC E.B. Garon et al., N Engl J Med 2015; Keynote 001 Study
23 Keynote 024: PFS Events, n Median, mo HR (95% CI) P Pembro Chemo ( ) <0.001 PFS, % % 50% 48% 15% No. at risk Time, months Assessed per RECIST v1.1 by blinded, independent central review. Data cut-off: May 9, 2016.
24 Keynote 024: Confirmed ORR ORR, % (95% CI) % Δ17% P = n = 6 n = 63 28% CR PR n = 1 n = 41 TTR, mo median (range) DOR, mo median (range) Pembro Responders n = ( ) NR (1.9+ to 14.5+) Chemo Responders n = ( ) 6.3 (2.1+ to 12.6+) 0 Pembrolizumab Chemotherapy Assessed per RECIST v1.1 by blinded, independent central review. Data cut-off: May 9, 2016.
25 Biological Differences of NSCLC Reflected by Checkpoint Inhibitor Treatment Outcomes: Non-Squamous vs. Squamous Cell Cancer The Checkmate 057 and Checkmate 017 Trials
26 CheckMate 057: Study Design L. Paz-Ares et al., ASCO 2015 Stage IIIB/IV non-sq NSCLC Pre-treatment (archival or recent) tumor samples required for PD-L1 ECOG PS 0 1 Failed 1 prior platinum doublet Prior maintenance therapy allowed a Prior TKI therapy allowed for known ALK translocation or EGFR mutation N = 582 Randomize 1:1 Nivolumab 3 mg/kg IV Q2W until PD or unacceptable toxicity n = 292 Docetaxel 75 mg/m 2 IV Q3W until PD or unacceptable toxicity n = 290 Primary Endpoint OS Additional Endpoints ORR b PFS b Safety Efficacy by tumor PD-L1 expression Quality of life (LCSS) Patients stratified by prior maintenance therapy and line of therapy (second- vs third-line) PD-L1 expression measured using the Dako/BMS automated IHC assay 14,15 Fully validated with analytical performance having met all pre-determined acceptance criteria for sensitivity, specificity, precision, and robustness a Maintenance therapy included pemetrexed, bevacizumab, or erlotinib (not considered a separate line of therapy); b Per RECIST v1.1 criteria as determined by the investigator.
27 CheckMate 017: Study Design Stage IIIb/IV SQ NSCLC 1 prior platinum doubletbased chemotherapy ECOG PS 0 1 Pre-treatment (archival or fresh) tumor samples required for PD-L1 analysis N = 272 Randomize 1:1 Nivolumab 3 mg/kg IV Q2W until PD or unacceptable toxicity n = 135 Docetaxel 75 mg/m 2 IV Q3W until PD or unacceptable toxicity n = 137 Primary Endpoint: OS Additional Endpoints: Investigator-assessed ORR Investigator-assessed PFS Correlation between PD-L1 expression and efficacy Safety Quality of life (LCSS) Patients stratified by region and prior paclitaxel use One pre-planned interim analysis for OS At time of DBL (December 15, 2014), 199 deaths were reported (86% of deaths required for final analysis) The boundary for declaring superiority for OS at the pre-planned interim analysis was P <0.03 LCSS = Lung cancer symptom scale D.R. Spigel et al., ASCO 2015
28 Checkmate 017 and 057: OS and PFS at 2 Years Published in: Leora Horn; David R. Spigel; Everett E. Vokes; Esther Holgado; Neal Ready; Martin Steins; Elena Poddubskaya; Hossein Borghaei; Enriqueta Felip; Luis Paz-Ares; Adam Pluzanski; Karen L. Reckamp; Marco A. Burgio; Martin Kohlhäeufl; David Waterhouse; Fabrice Barlesi; Scott Antonia; Oscar Arrieta; Jérôme Fayette; Lucio Crinò; Naiyer Rizvi; Martin Reck; Matthew D. Hellmann; William J. Geese; Ang Li; Anne Blackwood-Chirchir; Diane Healey; Julie Brahmer; Wilfried E.E. Eberhardt; JCO 2017, 35, DOI: /JCO Copyright 2017 American Society of Clinical Oncology
29 Checkmate 017 and 057: Time to Response, Analysis at 2 Years Published in: Leora Horn; David R. Spigel; Everett E. Vokes; Esther Holgado; Neal Ready; Martin Steins; Elena Poddubskaya; Hossein Borghaei; Enriqueta Felip; Luis Paz-Ares; Adam Pluzanski; Karen L. Reckamp; Marco A. Burgio; Martin Kohlhäeufl; David Waterhouse; Fabrice Barlesi; Scott Antonia; Oscar Arrieta; Jérôme Fayette; Lucio Crinò; Naiyer Rizvi; Martin Reck; Matthew D. Hellmann; William J. Geese; Ang Li; Anne Blackwood-Chirchir; Diane Healey; Julie Brahmer; Wilfried E.E. Eberhardt; JCO 2017, 35, DOI: /JCO Copyright 2017 American Society of Clinical Oncology
30 Checkmate 017 and 057: Treatment-Related Adverse Events Published in: Leora Horn; David R. Spigel; Everett E. Vokes; Esther Holgado; Neal Ready; Martin Steins; Elena Poddubskaya; Hossein Borghaei; Enriqueta Felip; Luis Paz-Ares; Adam Pluzanski; Karen L. Reckamp; Marco A. Burgio; Martin Kohlhäeufl; David Waterhouse; Fabrice Barlesi; Scott Antonia; Oscar Arrieta; Jérôme Fayette; Lucio Crinò; Naiyer Rizvi; Martin Reck; Matthew D. Hellmann; William J. Geese; Ang Li; Anne Blackwood-Chirchir; Diane Healey; Julie Brahmer; Wilfried E.E. Eberhardt; JCO 2017, 35, DOI: /JCO Copyright 2017 American Society of Clinical Oncology
31 PD-L1 Immune Checkpoint Inhibitor Treatment in Previously Treated NSCLC (POPLAR): A Phase II Randomised Trial of Atezolizumab vs. Docetaxel L. Fehrenbacher et al., Lancet 387: 1837, 2016
32 CheckMate 153: Continuous vs 1-Year Nivolumab PFS From Randomization Median, months (95% CI) PFS rate, % 6- month 1-year Continuous tx NR (NR) year tx b 10.3 (6.4, 15.2) HR: 0.42 (95% CI: 0.25, 0.71) PFS (%) No. at risk Continuous tx 1-year tx Time post-randomization 2 5(months) a Patients who did not have PD at randomization; minimum/median follow-up time post-randomization, 10.0/14.9 months b With optional retreatment allowed at PD NR = not reached; tx = treatment D.R. Spige
33 CheckMate 153: Continuous vs 1-Year Nivolumab PFS From Randomization by Response Status 100 CR/PR Continuous tx 1-year tx b,c Median, months (95% CI) NR (NR) 10.6 (4.8, NA) 100 SD Continuous tx Median, months (95% CI) NR (5.6, NA) 1-year tx b 9.6 (4.5, 12.6) 80 HR: 0.45 (95% CI: 0.24, 0.85) 80 HR: 0.44 (95% CI: 0.17, 1.09) PFS (%) PFS (%) Time post-randomization (months) No. at risk Continuous tx year tx Time post-randomization (months) a Best overall response prior to randomization; minimum/median follow-up time post-randomization, 10.0/14.9 months; b With optional retreatment allowed at PD; c Two patients who stopped treatment had CR prior to randomization; both patients lost CR (6 and 13 months after stopping treatment) with progression due to new lesions; NA = not available D.R. Spigel et al. ESMO 2017
34 The Issue of PD-L1 Targeting: Is this an Appropriate Biomarker? induced by IFN-gamma, IL-4 MAPK PI3K-AKT HIF-1alpha STAT3 J. Chen et al. Ann Oncol 2016;27:
35 CA : OS at 5 Years of all Treated Patients : (A) overall, (B) by tumor histology, (C) by dose, (D) by PD-L1 expression level. Scott Gettinger et al.; JCO Ahead of Print, DOI: /JCO
36 Induction of PD-L1 by IFNγ. Masaki Mandai et al. Clin Cancer Res 2016;22: by American Association for Cancer Research
37 PD-L1 Immune Checkpoint Inhibitor Treatment in Previously Treated NSCLC (POPLAR): A Phase II Randomised Trial of Atezolizumab vs. Docetaxel 287 patients stratified by PD-L1 Status, histology and previous lines of therapy with OS as primary endpoint. OS: 12.6 mos. (Atezolizumab, n=144) vs. 9.7 mos. (Docetaxel, n=143), HR=0.73 (p=0.04) and associated with increasing PD-L1 expression up to a HR of 0.49 (p=0.068) L. Fehrenbacher et al., Lancet 387: 1837, 2016
38 IFNγ-signature for Atezolizumab in NSCLC (POPLAR Trial) 100 T eff /IFN-γ gene signature subgroups OS (%) T eff /IFN-γ high HR 0.43 (95% CI ) T eff /IFN-γ low HR 1.10 (95% CI ) Follow-up (months) Fehrenbacher L et al. Lancet. 2016;387(10030):
39 Prevalence of Somatic Mutations across Cancer Types Alexandrov et al., Nature 2013; 500: 415
40 Correlation between Tumor Mutational Burden and Objective Response Rate with Anti PD-1 or Anti PD-L1 Therapy in 27 Tumor Types. Yarchoan M et al. N Engl J Med 2017;377:
41 Preliminary Analyses of TMB in Lung Cancers Treated With Nivolumab + Ipilimumab 100 NSCLC (CheckMate 012; n = 75) 100 SCLC (CheckMate 032; n = 78) PFS (%) TMB > median TMB median PFS (%) Low TMB tertile High TMB tertile Medium TMB tertile Months Months Whole exome sequencing in tumor tissue samples from patients with NSCLC and SCLC treated with nivolumab + ipilimumab demonstrates the potential of TMB as an independent biomarker of efficacy, distinct from PD-L1 1, Hellmann MD, et al. Cancer Cell doi: Epub; 2. Hellmann MD, et al. Cancer Cell (in press) 2018.
42 Pathological Assessment of Response to Neoadjuvant Blockade of Programmed Death 1 (PD-1). PM Forde et al. N Engl J Med DOI: /NEJMoa
43 Patterns of Radiologic and Pathological Response to Neoadjuvant Therapy with Nivolumab. PM Forde et al. N Engl J Med DOI: /NEJMoa
44 Association between Mutational Burden and Pathological Response to PD-1 Blockade. PM Forde et al. N Engl J Med DOI: /NEJMoa
45 MD Hellmann et al. N Engl J Med DOI: /NEJMoa Trial Design: Checkmate 227
46 TMB and Tumor PD-L1 Expression Identify Distinct and Independent Populations of NSCLC a Symbols (dots) in the scatterplot may represent multiple data points, especially for patients with <1% tumor PD-L1 expression. The black line shows the relationship between TMB and PD-L1 expression as described by a linear regression model; b Among patients in the nivolumab +ipilimumab and chemotherapy arms; TMB 10 mut/mb, n = 299; TMB <10 mut/mb, n = TMB and tumor PD-L1 expression a Tumor PD-L1 expression TMB (number of mutations/mb) TMB 10 mut/mb b TMB <10 mut/mb b 1% 71% 1% 1% 71% 71% <1% 29% <1% 29% <1% <1% 29% 29% PD-L1 expression (%) MD Hellmann et al. N Engl J Med DOI: /NEJMoa
47 PFS in All Randomized vs TMB-Evaluable Patients MD Hellmann et al. N Engl J Med DOI: /NEJMoa All randomized patients a Patients with evaluable TMB a PFS (%) Nivo + ipi (n = 583) Chemo (n = 583) HR (95% CI) 0.83 (0.72, 0.96) 1-y PFS = 31% Nivolumab + ipilimumab Nivo + ipi (n = 330) Chemo (n = 349) HR (95% CI) 0.82 (0.68, 0.99) 1-y PFS = 32% Nivolumab + ipilimumab No. at risk 1-y PFS = 17% Months Chemotherapy Nivo + ipi Chemo y PFS = 15% Months Chemotherapy a Patients who did not progress or die were censored on the date of their last evaluable tumor assessment; those who did not have any study tumor assessments and did not die were censored on their date of randomization
48 Efficacy of Nivolumab plus Ipilimumab versus Chemotherapy in Patients with a High Tumor Mutational Burden (>10mut/Mb) MD Hellmann et al. N Engl J Med DOI: /NEJMoa
49 ORR and DOR in Patients With High TMB ( 10 mut/mb) MD Hellmann et al. N Engl J Med DOI: /NEJMoa ORR (%) ORR (TMB 10 mut/mb) b CR PR Patients in response (%) DOR (TMB 10 mut/mb) Median DOR, mo (95% CI) Nivo + ipi (n = 63) NR (12.2, NR) 1-y DOR = 68% 1-y DOR = 25% Chemo (n = 43) 5.4 (4.2, 6.9) Nivolumab + ipilimumab Chemotherapy 10 n/n: 0 Nivo + ipi Nivo + Ipi 63/139 Chemo Chemo 43/160 No. at risk Months Nivo + ipi Chemo Median time to response was 2.7 months with nivolumab + ipilimumab and 1.5 months with chemotherapy 49
50 Preliminary Overall Survival With Nivolumab + Ipilimumab vs Chemotherapy in Patients With High TMB ( 10 mut/mb) 100 MD Hellmann et al. N Engl J Med DOI: /NEJMoa Nivo + ipi (n = 139) Chemo (n = 160) Median OS, b mo OS (%) a y OS = 58% 1-y OS = 67% HR 95% CI Nivolumab + ipilimumab Chemotherapy , No. at risk Months Nivo + ipi Chemo a In the first 1.5 months, 8 deaths occurred in the nivo + ipi arm (4 due to disease progression; 1 patient never treated [respiratory sepsis]; 2 due to AEs unrelated to study drug per investigator [thromboembolism, septic shock]; 1 due to myocarditis related to study drug), and 2 deaths occurred in the chemo arm (1 due to disease progression; 1 due to multiple brain infarctions related to carboplatin); b 95% CI: nivo + ipi (16.5 mo, NR), chemo (12.6 mo, NR); c Per investigator
51 Progression-free Survival among Patients with a High Tumor Mutational Burden According to Tumor PD-L1 Expression and Histologic Type. MD Hellmann et al. N Engl J Med DOI: /NEJMoa
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53 New Approaches to Build on Active Immunotherapies to Maximize Clinical Benefit Plus chemotherapy Plus radiotherapy Active immunotherapy Plus other immunotherapy Plus targeted therapy Immuno-Oncology research and development will continue to inform future strategies, including new targets and rationale drug combinations and sequencing Drake CG. Ann Oncol. 2012;23(suppl 8):viii41 viii46; Hannani D, et al. Cancer J. 2011;17: ; Ménard C, et al. Cancer Immunol Immunother. 2008;57: ; Ribas A, et al. Curr Opin Immunol. 2013:25:
54 Survival Outcomes in Patients with Advanced NSCLC Treated with Nivolumab plus Platinum-Based Doublet Chemotherapy. Naiyer A. Rizvi et al. JCO 2016;34: by American Society of Clinical Oncology
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63 New Approaches to Build on Active Immunotherapies to Maximize Clinical Benefit Plus chemotherapy Do not forget Angiogenesis! Plus radiotherapy Active immunotherapy Plus other immunotherapy Plus targeted therapy Immuno-Oncology research and development will continue to inform future strategies, including new targets and rationale drug combinations and sequencing Drake CG. Ann Oncol. 2012;23(suppl 8):viii41 viii46; Hannani D, et al. Cancer J. 2011;17: ; Ménard C, et al. Cancer Immunol Immunother. 2008;57: ; Ribas A, et al. Curr Opin Immunol. 2013:25:
64 Mechanisms of Resistance Towards I-0 Treatment T.N. Gide et al., Clin. Cancer Res. Nov 10, 2017, DOI: / CCR
65 Mechanisms of Resistance Towards I-0 Treatment and Therapeutic Consequences T.N. Gide et al., Clin. Cancer Res. Nov 10, 2017, DOI: / CCR
66 Conclusions Immune Oncology is currently rewriting the textbooks for treatment of malignancies Currently, anti-pd-1 antibodies constitute the backbone of treatment, but many other compounds are on the way A personalized signature might be involved in the efficacy of immune mediated treatment options.
Conversations in Oncology. November Kerry Hotel Pudong, Shanghai China
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