1. Cezary Szczylik Klinika Onkologii Wojskowy Instytut Medyczny. Warszawa

2. 1857 1893 1957 1991 1995 1998 2010 2011 immunologic infiltrations described by Virchow Burnets hypothesis of immune surveillance in cancer 1 Tumor specific antigens (Rosenberg i Boon) 1 IFNα in melanoma High dose IL-2 registered in metastatic melanoma 2 FDA sipuleucel registered in prostate cancer 1 Ipilimumab registartion in metastaic melanoma 4 Coley toxin – American Journal of Medical Sciences 5 Immunotherapy history in oncolgy 1.Lesterhuis WJ i wsp. Nat Rev Drug Discov. 2011;10:591-600 2.http://www.cancer.gov/cancertopics/pdq/treatment/melanoma/HealthProfessional/Page9#Section_457;http://www.cancer.gov/cancertopics/pdq/treatment/melanoma/HealthProfessional/Page9#Section_457 3. http://www.cancer.gov/cancertopics/pdq/treatment/melanoma/HealthProfessional/page1/AllPages#Section_363. 4. US Food and Drug Administration. http://www.fda.gov/newsevents/newsroom/pressannouncements/ucm1193237.htm. 5.Coley W. American Journal of Medical Sciences.1893; 105(5): 487-510.

3. What is a role of immmunotherapy? What do we expext from todays therapeutic abilities?

4. I-O is an emerging therapeutic modality I-O treatments are different from other treatment modalities Rather than directly targeting the tumour itself, I-O agents use the natural capability of the patient’s own immune system to fight cancer Surgery Radiation Cytotoxic & targeted therapies I-O DeVita VT, Rosenberg SA. N Eng J Med 2012;366:2207 – 2214 Borghaei H, et al. Eur J Pharmacol 2009;625:41 – 54

5. The Role of the Immune System in Cancer and the Process of Immunoediting The three E’s of cancer immunoediting describe the immune system’s roles in protecting against tumor development and promoting tumor growth [1]The three E’s of cancer immunoediting describe the immune system’s roles in protecting against tumor development and promoting tumor growth [1] *Various mechanisms for immune “escape” exist (See Section IV. Mechanisms of Immune Escape in NSCLC). NK, natural killer; Treg, regulatory T cell. EquilibriumEscape*Elimination  Effective antigen processing/presentation  Effective activation and function of effector cells ‒ T cell activation without co-inhibitory signals Tumors may avoid elimination by the immune system through outgrowth tumor cells that can suppress, disrupt, or “escape” the immune system  Genetic instability  Tumor heterogeneity  Immune selection Cancer immunosurveillanceCancer dormancyCancer progression 1. Vesely MD et al. Annu Rev Immunol. 2011;29:235-271. Adapted from Vesely et al 2011. [1] Tumor cells Normal cells Treg CD8 + T cell CD4 + T cell NK cell

6. Tumours use various mechanisms to escape the immune system Immune escape mechanisms are complex and frequently overlapping Tumour cells CD8 + T cell A. Ineffective presentation of tumour antigens to the immune system Treg MDSC Vesely MD, et al. Ann Rev Immunol 2011;29:235–271 B. Recruitment of immunosuppressive cells (Tregs, MDSCs, others) CD8 + T cell CD4 + T cell  TGF-β  IL-10  TGF-β  ARG1  iNOS C. Release of immunosuppressive factors  VEGF APC  TGF-β  IDO  IL-10 D. T cell checkpoint dysregulation PD-1 P-DL1 PD-1 PD-L1 CTLA-4 TCR MHC

7. Immune system checkpoints  Immune responces, whether against tumor cells, infected cells, or as a result of autoimmunity, can damage healthy tissue if - left unchecked.  To protect against this, the immune system has multiple mechsanisms to downregulate immune rsponses – collectively known as immune checkpoint pathways  Davies M. Case Managment and Res.2014.6, 63-75

8. Numerous immune checkpoints control normal immune response  Various ligand-receptor interactions occur between T cells and APCs  PD-1 and CTLA-4 are examples of inhibitory checkpoint receptors 1 Pardoll DM. Nat Rev Cancer 2012;12(4):252–264

9. 1. Mellman I et al. Nature. 2011;480(7378):480-489. T-Cell Immune Checkpoints as Targets for Immunotherapy There are several T-cell targets for immunotherapy [1]There are several T-cell targets for immunotherapy [1] Agonistic antibodies directed towards activating co-stimulatory molecules and blocking antibodies against co-inhibitory molecules may enhance T-cell stimulation to promote tumor destruction [1]Agonistic antibodies directed towards activating co-stimulatory molecules and blocking antibodies against co-inhibitory molecules may enhance T-cell stimulation to promote tumor destruction [1] CTLA-4 PD-1 TIM-3 BTLA VISTA LAG-3 HVEM CD27 CD137 GITR OX40 CD28 T cell stimulation Blocking antibodies Agonistic antibodies Inhibitory receptors Activating receptors T cell B7-1 T cell Adapted from Mellman et al 2011. [1]

10. Role of PD-1/PD-L1 and PD-L2 in cancer PD-1 expression is upregulated in activated T cells PD-1 engages two known ligands: PD-L1 and PD-L2 Associated with decreased cytokine production and effector function PD-L1 (B7-H1):  Expressed on a wide variety of solid tumours  Expression upregulated by cytokines  Expressed in approximately 40% of metastatic melanoma and 50% of NSCLC tissue samples by IHC  Can also suppress immunity by binding to B7.1 (CD80) PD-L2 (B7-DC):  Expression in melanoma not well characterised but shown to be present on several solid tumours as a negative prognostic indicator Korman AJ, et al. Adv Immunol 2006;90:297–339 Butte MJ, et al. Immunity 2007;27:111–122 Zou W, et al. Nat Rev Immunol 2008;8:467–477

11. MHC PD-L1 PD-1 Nivolumab is a PD-1 receptor blocking antibody Recognition of tumour by T cell through MHC/antigen interaction mediates IFN  release and PD-L1/2 upregulation on tumour Priming and activation of T cells through MHC/antigen and CD28/B7 interactions with antigen- presenting cells T cell receptor PD-L1 PD-L2 MHC CD28B7 T cell NF  Other PI3K IFN  IFNγR Shp-2 Role of PD-1 pathway in suppressing antitumour immunity Ribas A. N Engl J Med 2012;366(26):2517–2519

12. Ipilimumab, a CTLA-4 blocking human monoclonal antibody, augments T-cell activation T cell TCR CTLA-4 APC MHC B7 T-cell inhibition T cell TCR CTLA-4 APC MHC B7 T-cell activation T cell TCR CTLA-4 APC MHC B7 T-cell potentiation Ipilimumab blocks CTLA-4 CD28 Adapted from Weber J. Cancer Immunol Immunother 2009;58:823

13. PD-L1 expression and evidence of poor prognosis 1. Thompson RH, et al. Proc Natl Acad Sci 2004;101:17174–17179 2. Konishi J, et al. Clin Cancer Res 2004;10:5094–5100 3. Hino R, et al. Cancer 2010;116:1757–1766

14. Pooled Analysis of Long-term Survival Data From Phase II and Phase III Trials of Ipilimumab in Metastatic or Locally Advanced, Unresectable Melanoma Schadendorf D, 1 Hodi FS, 2 Robert C, 3 Weber JS, 4 Margolin K, 5 Hamid O, 6 Chen TT, 7 Berman DM, 8 Wolchok JD 9 1 University Hospital Essen, Essen, Germany; 2 Dana-Farber Cancer Institute, Boston, MA, USA; 3 Institute Gustave Roussy, Villejuif, France; 4 Moffitt Cancer Center, Tampa, FL, USA; 5 University of Washington, Seattle, WA, USA; 6 The Angeles Clinic and Research Institute, Los Angeles, CA, USA; 7 Bristol-Myers Squibb, Wallingford, CT, USA; 8 Bristol- Myers Squibb, Lawrenceville, NJ, USA; 9 Memorial Sloan-Kettering Cancer Center, New York, NY, USA. Abstract Number 24LBA 14 ESMO 2013

15.  Historical controls  Phase II: 1278 patients in 42 cooperative group trials from 1975 to 2005  Phase III: 3739 patients in 10 trials from 1999 to 2011 OS Relative to Historical Data 15 Schadendorf et al., ESMO 2013, abs 24LBA

16. Ipilimumab atypical responce kinetics Ocena przesiewowa Tydzień 12 Wstępny wzrost łącznej objętości nowotworu (mWHO PD) Tydzień 16 Odpowiedź Tydzień 96 Trwała i utrzymująca się odpowiedź bez oznak IRAE Dzięki uprzejmości K. Harmankaya, Wiedeń Harmankaya i wsp. Praca przedstawiona podczas EADO 2009, Wiedeń

17. Advancements in understanding the biology of NSCLC have elucidated disease characteristics (eg, histology, molecular pathology) that must be considered for targeted therapeutic approaches [1]Advancements in understanding the biology of NSCLC have elucidated disease characteristics (eg, histology, molecular pathology) that must be considered for targeted therapeutic approaches [1] –Over the past several years, immunotherapies have emerged as a new therapeutic approach in NSCLC [6] Although there have been advances in NSCLC and SCLC management, the prognosis for patients with advanced NSCLC remains poor [1]Although there have been advances in NSCLC and SCLC management, the prognosis for patients with advanced NSCLC remains poor [1] –75% of patients diagnosed with NSCLC have advanced/metastatic disease with a 1-year survival rate <16% [2,3] Treatment options for patients whose tumors have failed to respond to two or more conventional chemotherapy regimens are limited [4,5]Treatment options for patients whose tumors have failed to respond to two or more conventional chemotherapy regimens are limited [4,5] Unmet Needs in NSCLC and SCLC Current therapies Histology Molecular status Unmet needs Patients failing conventional chemotherapies Squamous Patients failing targeted therapies 4.NCCN Guidelines ®. NSCLC. V3.2014. 5.Peters S et al. Ann Oncol. 2012;23(suppl 7):vii56-vii64. 6.Brahmer JR. J Clin Oncol. 2013;31(8):1021-1028. NSCLC, non-small cell lung cancer. 1.Bonomi PD. Cancer. 2010;116:1155-1164. 2.SEER Stat Fact Sheets: Lung and Bronchus. Available at: http://seer.cancer.gov/statfacts/html/lungb.html. Accessed April 4, 2013. 3.Cetin K et al. Clin Epidemiol. 2011;3:139-148.

18. Summary of the Prognostic Roles of Immune Cells in NSCLC and SCLC Dendritic Cells Favorable prognosis [1] : Overall survival, disease-specific survival, and disease-free survival CD3+ Cells Favorable prognosis [2,3] : Disease-specific survival and lower risk of disease recurrence CD8+ Cells Favorable prognosis [4-8] : Overall survival CD4+ Cells Favorable prognosis [4,6,9] : Overall survival Macrophages Favorable prognosis [7] : Overall survival Tregs Unfavorable prognosis [12,13] : Overall survival, relapse- and recurrence-free survival NK Cells Favorable prognosis [10] : Disease-specific survival NK Cells (Immature / Impaired) Unfavorable prognosis [11] : Disease progression Similar to other tumor types (eg, melanoma and renal cell carcinoma), data show that lung tumors are recognized by, and initiate a response from, the immune systemSimilar to other tumor types (eg, melanoma and renal cell carcinoma), data show that lung tumors are recognized by, and initiate a response from, the immune system Certain immune cells are associated with a better prognosis/improved outcome, while others suggest an unfavorable prognosis and disease outcomeCertain immune cells are associated with a better prognosis/improved outcome, while others suggest an unfavorable prognosis and disease outcome NK, natural killer; NSCLC, non-small cell lung cancer; Treg, regulatory T cell. 1.Dieu-Nosjean MC et al. J Clin Oncol. 2008;26(27):4410-4117. 2.Petersen RP et al. Cancer. 2006;107(12):2866-2872. 3.Al-Shibli K et al. APMIS. 2010;118(5):371-382. 4.Ruffini E et al. Ann Thorac Surg. 2009;87(2):356-372. 5.Zhuang X et al. Appl Immunohistochem Mol Morphol. 2010;18(1):24-28. 6.Hiraoka K et al. Br J Cancer. 2006;94(2):275-280. Tumor 7.Kawai O et al. Cancer. 2008;113(6):1387-1395. 8.McCoy MJ et al. Br J Cancer. 2012;107(7):1107-1115. 9.Wakabayashi O et al. Cancer Sci. 2003;94(11):1003-1009. 10.Al-Shibli K et al. Histopathol. 2009;55(3):301-312. 11.Jin J et al. PLoS One. 2013;8(4):e61024. 12.Tao H et al. Lung Cancer. 2012;75(1):95-101. 13.Shimizu K et al. J Thorac Oncol. 2010;5(5):585-590.

19. Immune Escape in NSCLC/SCLC A. Ineffective presentation of tumor antigens to the immune system [2] Tumor cell Downregulation of MHC expression Many tumors, including NSCLC, escape the immune response by creating an immunosuppressive microenvironment that prevents an effective antitumor response [1,2] Many tumors, including NSCLC, escape the immune response by creating an immunosuppressive microenvironment that prevents an effective antitumor response [1,2] C. Release of immunosuppressive factors [2] Factors/enzymes directly or indirectly suppress immune response The mechanisms tumors use to escape the immune system provide a range of potential therapeutic targets for NSCLC [2]The mechanisms tumors use to escape the immune system provide a range of potential therapeutic targets for NSCLC [2] Suppression of APC APC D. T cell checkpoint dysregulation [2] CTLA-4 PD-1 TIM-3 BTLA VISTA LAG-3 B7-1 HVEM CD27 CD137 GITR OX40 CD28 Co-inhibitory receptors Co-stimulatory receptors T cell B. Recruitment of immunosuppressive cells [1,2] MDSCs Tregs Tumor cells Tumor microenvironment Adapted from Mellman et al 2011. [3] APC, antigen-presenting cell; BTLA, B and T lymphocyte attenuator; CTLA-4, cytotoxic T-lymphocyte antigen-4; HVEM, herpesvirus entry mediator; LAG-3, lymphocyte activation gene-3; MDSC, myeloid-derived suppressor cell; MHC, major histocompatibility complex; NSCLC, non-small cell lung cancer; PD-1, programmed death-1; Treg, regulatory T cell; TIM-3, T cell immunoglobulin and mucin protein 3; VISTA, V-domain immunoglobulin suppressor of T cell activation. 1.Bremnes RM et al. J Thorac Oncol. 2011;6(4):824-833. 2.Jadus MR et al. Clin Dev Immunol. 2012;2012:160724. 3.Mellman I et al. Nature. 2011;480(7378):480-489.

20. Immunotherapies in NSCLC Targeting T-cell checkpoint dysregulation Nivolumab [3,4] (anti-PD-1) Ipilimumab [3,4] (anti-CTLA-4) Other mAbs [3,8] Anti-PD-1 Anti-PD-L1 Anti-PD-L2 Enhancing antigen recognition/presentation APC Stimuvax ®[3,4] (MUC-1) TG4010 [3,4] (MUC-1) Racotumomab [5] (anti-idiotype vaccine) T cells APC, antigen-presenting cell; CTLA-4, cytotoxic T-lymphocyte antigen-4; EGF, epidermal growth factor; EGFR, epidermal growth factor receptor; MUC-1, mucin-1; NSCLC, non-small cell lung cancer; PD-1, programmed death-1; PD-L1, programmed death ligand-1; PS, phosphatidylserine. 1.Bavituximab Oncology. First-in-Class PS-Targeting Monoclonal Antibody. Available at: http://www.peregrineinc.com/pipeline/ bavituximab- oncology.html. Accessed April 10, 2014. 2.Oncolytics. Reolysin. Available at: http://www. oncolyticsbiotech.com/reolysin. Accessed May 17, 2013. 3. Brahmer JR. J Clin Oncol. 2013;31(8):1021-1028. 4.Dasanu CA et al. Expert Opin Biol Ther. 2012;12(7):923-937. 5.Segatori VI et al. Front Oncol. 2012;2(160):1-7. 6. NewLink Genetics [press release]. Available at: http://investors.linkp.com/releasedetail.cfm?ReleaseID=768475. Accessed March 28, 2014. 7.Rodriguez PC et al. MEDICC Rev. 2010;12(1):17-23. 8.Ceeraz S et al. Trends Immunol. 2013;34(11):556-565. Tumor microenvironment Tumor cells  Current immunotherapies target NSCLC through a variety of approaches: Targeting the tumor Tumor cells Novel vaccine approaches Belagenpumatucel-L and Tergenpumatucel-L [3,4,6] (Live engineered tumor cell vaccines) CimaVax-EGF [3,4,7] (EGF–EGFR vaccine) Bavituximab [1] (anti-PS) Reolysin ®[2] (oncolytic virus)

21. OS of patients treated with nivolumab monotherapy by dose GroupDied/TreatedMedian OS (95% CI) 1-year 2-year 1 mg/kg26/339.2 (5.3, 11.1) 32 (16, 49) [8] 12 (3, 27) [2] 3 mg/kg20/3714.9 (7.3, —) 56 (38, 71) [17] 45 (27, 61) [9] 10 mg/kg48/599.2 (5.2, 12.4) 40 (27, 52) [23] 19 (10, 31) [9] OS rate % (95% CI) [patients at risk] Censored 061218243027211593333642485439455157 2-year OS Rate 45% (9 patients at risk) 1-year OS Rate 56% (17 patients at risk) 0.0 0.2 0.4 0.6 0.8 1.0 Overall Survival Months Since Treatment Initiation Brahmer JR, et al. Poster presented at ASCO 2014 (Abstract 8112) CA209-003

22. Response of Squamous NSCLC to BMS-936558 58-year-old former smoker with squamous NSCLC 4 prior treatments for stage IV disease Left flank pain (adrenal lesion) resolved within 2 months of starting BMS- 936558 Response ongoing after completing 2 years of BMS-936558 treatment in June of 2012

23. Summary of survival outcomes in patients treated with 1st-line nivolumab monotherapy CA209-012 Gettinger SN, et al. Poster presented at ASCO 2014 (Abstract 8024) Squamous (n=9) Nonsquamous (n=11) Total (N=20) PFS PFS rate at 24 weeks, % (95% CI) 44 (14, 72)73 (37, 90)60 (36, 78) Median PFS, weeks (range) 15.1 (5.9, 63.3+)47.3 (9.6, 80.7+)36.1 (5.9, 80.7+) OS 1-year OS rate, % (95% CI) 67 (28, 88)82 (45, 95)75 (50, 89) Median OS, weeks (range) 68.0 (13.3, 73.1)NR (16.6, 89.1+)NR (13.3, 89.1+)

24. Phase II Study of Ipilimumab and Paclitaxel/Carboplatin: OS in the Squamous NSCLC Subset Proportion Alive Regimen [1] Events/Patients Median (mo) HR (95% CI) Control Concurrent Phased * 14/15 17/21 13/21 7.9 6.2 10.9 – 1.02 (0.50–2.08) 0.48 (0.22–1.03) Months Patients at risk: Concurrent2113116433200 Phased * 21191512998530 Control1511107411100 1.0 0.8 0.6 0.4 0.2 0 0369121518212427 Data from trial CA184-041. 1. Reck M et al. Ann Oncol. 2012;23(suppl 8):viii28-viii34. *Phased regimen: 2 doses of paclitaxel (175 mg/m 2 )/carboplatin (AUC=6) prior to start of ipilimumab. AUC, area under the curve; CI, confidence interval; HR, hazard ratio; NSCLC, non-small cell lung cancer; OS, overall survival.

25. RCC renal cell carcinoma molecular pathology  RCC it is a heterogenous group of tumors  Most of them has clear cell morphology Collecting duct Clear cell Papillary type I,II +II II) Chromopho b Oncocytic VHL c-METBHD Histologic subtype (%) Genetic mutation FH 75–85 12–142–44–6 1 BHD Non clear cell BHD = Birt–Hogg–Dubé; FH = fumarate hydratase; VHL = von Hippel–Lindau

26. Molecular pathology of renal cell carcinoma

27. HIF-1β RCC Tumour cell Endothelial cell Bone marrow derived cells Stromal cells cytosol Pericyte NOSAktPI3KSrcFAK P38 MAPK Smad 2/3 Erk 1/2 TIE2 FGFR VEGFR PDGFR PDGF PDGF PDGF VEGF VEGFR PDGFR VEGFR Proliferation Migration Vascular permeability Survival Increased pericyte expression and coverage Recruitment of proangiogenic BMDCs Immuno- modulatory effect PDGF PDGF VEGF FGF IL-8 Ang-2 PlG F Mutated KIT PDGF PDGFR Sunitinib sorafenib TGFRβ2 Cell survival SDF-1 PDGF PDGF PDGF VEGF Alternalive signalling in condition of RCC resistance to TKIs VEGFR Acquisition of secondary KIT mutation PLC-γ TKI-MEDIATED BLOCKAGE OF VEGF- AND PDGF- MEDIATED ANGIOGENESIS PATHWAY AXIS Alternalive signalling in condition of RCC resistance to TKIs nucleus TCEB2 TCEB1 Cul2 Rbx1 VHL HIF-1 α Ub E3 Ligase Complex degradation Ang-2 PlG F FGF IL-8 VEGF SDF-1 PDGF downregulation ESM1 HOXA9 PECAM Increased migration and invasiveness/ EMT S6K eIF-4E1 mTOR CXCR4 EGFR Mek 1/2 PI3K Akt Erk 1/2 Ras VEGFR SHC GRB2 SOS PDGFR HIF-1α PRKX TTBK2 RSK JAK/STAT MITF Β-catenin TYRO3 Ras MAPK FGF SHC GRB2 SOS FGFR EGFR TARGET GENES HIF-1 α HIF-1β CPB/p300 HRE upregulation Gene expression switch downregulation sunitinib EGF SDF-1 CXCR2 TGF- β CXCR4 Lysosomal sequestration Alk1 VEGF PDGF PDGF Ang-2 IL-8 FGF FF PlG F SDF-1 TGF- β MET HGF T cell B cell T cell B cell T cell ? Ang-2 Fig. by M. Buczek et al.

31. DF. McDermott, CG. Drake, M. Sznol, TK. Choueiri, J. Powderly, DC. Smith, J. Wigginton, D. McDonald, G. Kollia, A K.Gupta, MB. Atkins Abstract 4505

32. R. Motzer, B. Rini, D. McDermott, B. Redman, T. Kuzel, M. Harrison, U. Vaishampayan, H. Drabkin, S. George, T. Logan, K. Margolin, E. R. Plimack, I. Waxman, A. Lambert, H. Hammers Abstract 5009

33. Progression-free survival in Phase II trial Number of patients at risk 0.3 mg/kg602417131211300 2 mg/kg542715976100 10 mg/kg5430181087310 0 20 30 40 50 60 70 80 90 100 3691215182124 Time (months) 0 Progression-free survival (%) Median PFS, months (80% CI) Stratified trend test P value 0.3 mg/kg2.7 (1.9, 3.0) 0.9 2 mg/kg4.0 (2.8, 4.2) 10 mg/kg4.2 (2.8, 5.5) 0.3 mg/kg (events: 48/60) 2 mg/kg (events: 43/54) 10 mg/kg (events: 45/54) Symbols represent censored observations. 33 R. Motzer at all. J Clin Oncol 32:5s, 2014 (suppl; abstr 5009)

34. Overall survival in Phase II trial Based on data cutoff of March 5, 2014; Symbols represent censored observations. 34 Number of patients at risk 0.3 mg/kg 60 56 50 41 37 35 31 27 24 13 0 0 2 mg/kg 54 52 45 42 38 35 32 28 26 12 0 0 10 mg/kg 54 50 47 45 38 32 29 26 8 1 0 Median OS, months (80% CI) 0.3 mg/kg18.2 (16.2, 24.0) 2 mg/kg25.5 (19.8, 28.8) 10 mg/kg24.7 (15.3, 26.0) R. Motzer at all. J Clin Oncol 32:5s, 2014 (suppl; abstr 5009)

35. Progression-free survival Symbols represent censored observation. Number of patients at risk listed is number at risk before entering the time period. Tx, treatment Number of patients at risk S + N33272321164110 P + N20139752221 S + N (n=33) 57.6% Tx-naïve P + N (n=20) 0% Tx-naïve 0.8 1.0 0.6 0.4 0.2 0.0 Proportion of PFS Time since first dose (weeks) 24BL48729684603612 Median PFS, weeks (95% CI) S + N (n=33)48.9 (41.6-66.0) P + N (n=20)31.4 (12.1-48.1) A. Amin, ASCO 2014

36. Overall survival by MSKCC risk group and number of prior treatments 33 Median OS, months (95% CI) FavorableNR (24.9, NR) Intermediate20.3 (13.4, NR) Poor12.5 (8.1, 18.6) 0 10 20 30 40 50 60 70 80 90 100 3691215182133 Time (months) 0 Overall survival (%) 242730 1 Prior treatment (events: 22/46) ≥2 Prior treatments (events: 75/122) Median OS, months (95% CI) 1NR (19.8, NR) ≥218.7 (13.4, 26.0) Risk groupNumber of prior treatments NR, not reached; Symbols represent censored observations. R. Motzer, ASCO 2014

37. Immuno-checkpoints targeting (CTLA-4, PD- 1) – hopes & threats  Hopes  Durable responses (long-term survival)  Off-treatment efficacy  Potential cure  Threats  Delayed response to treatment  No validated predictors  Autoimmune AEs Eggermont A. et al., E J Cancer, 2013; Blank Ch. Curr Opin Oncol, 2014; Finn O, N Engl J Med, 2008

38. Finally –immunotherapy is back