IMMUNONKOLOGIA – SZANSE I ZAGROŻENIA W LECZENIU CZERNIAKA, RAKA NERKI I PŁUC

Cezary SzczylikKlinika OnkologiiWojskowy Instytut Medyczny. Warszawa

1857 1893 1957 1991 1995 1998 2010 2011

immunologic infiltrations

described by Virchow

Burnets hypothesis of immune surveillance in cancer1

Tumor specific antigens (Rosenberg i Boon)1

IFNα in melanoma

High dose IL-2 registered in metastatic melanoma2

FDA sipuleucel registered in prostate cancer 1

Ipilimumab registartion in metastaic melanoma4

Coley toxin – American Journal of Medical Sciences5

Immunotherapy history in oncolgy

1.Lesterhuis WJ i wsp. Nat Rev Drug Discov. 2011;10:591-6002.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.

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

Long term survival

Median OS

PFS

Responce rates

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

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]

* Various mechanisms for immune “escape” exist(See Section IV. Mechanisms of Immune Escape in NSCLC).NK, natural killer; Treg, regulatory T cell.

Equilibrium Escape*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 immunosurveillance

Cancer dormancy Cancer 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

Tumours use various mechanisms to escape the immune systemImmune escape mechanisms are complex and frequently overlapping

Tumour cells

CD8+ T cell

A. Ineffective presentation of tumour antigens to the immune system

TregMDSC

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

VEGFAPC

TGF-β IDO IL-10

D. T cell checkpoint dysregulation

PD-1

P-DL1PD-1

PD-L1

CTLA-4TCR

MHC

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

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

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]

• 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-3HVEM

CD27

CD137

GITR

OX40

CD28

T cellstimulation

Blockingantibodies

Agonisticantibodies

Inhibitoryreceptors

Activatingreceptors

T cell

B7-1

T cell

Adapted from Mellman et al 2011.[1]

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 and50% 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;27:111–122Zou W, et al. Nat Rev Immunol 2008;8:467–477

MHC

PD-L1

PD-1 PD-1

PD-1 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 cellreceptor

T cellreceptor

PD-L1PD-L2

PD-L2

MHC

CD28 B7

T cell

NFOther

PI3KDendritic

cellTumour cell

IFN

IFNγR

Shp-2

Shp-2

Role of PD-1 pathway in suppressingantitumour immunity

Ribas A. N Engl J Med 2012;366(26):2517–2519

Ipilimumab, a CTLA-4 blocking human monoclonal antibody, augments T-cell activation

T cell

TCRCTLA-4

APC

MHCB7

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

IpilimumabblocksCTLA-4

CD28CD28

Adapted from Weber J. Cancer Immunol Immunother 2009;58:823

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

• Patients with ↑PD-L1 on tumours and TILs had 4.5x higher risk of death (P<0.001)

RCC1

• ↑PD-L1 on tumour cells correlated with ↓TILs in same region

NSCLC2

• Patients with ↑PD-L1 on TIL had 2x higher risk of death (P=0.01)• Patients with stage IV disease had ↑PD1 expression on peripheral

CD8+/CD4+ T cells• ↑PD1 expression on CD8+ TILs with disease progression

Melanoma3

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 JD9

1University Hospital Essen, Essen, Germany; 2Dana-Farber Cancer Institute, Boston, MA, USA; 3Institute Gustave Roussy, Villejuif, France; 4Moffitt Cancer Center, Tampa, FL, USA; 5University of Washington, Seattle, WA, USA; 6The Angeles Clinic and Research Institute, Los Angeles, CA, USA; 7Bristol-Myers Squibb, Wallingford, CT, USA; 8Bristol-Myers Squibb, Lawrenceville, NJ, USA; 9Memorial Sloan-Kettering Cancer Center, New York, NY, USA.

Abstract Number 24LBA

14

ESMO 2013

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

15Schadendorf et al., ESMO 2013, abs 24LBA

Ipilimumab atypical responce kinetics

Ocena przesiewowa

Tydzień 12Wstępny wzrost łącznej objętości

nowotworu (mWHO PD)

Tydzień 16Odpowiedź

Tydzień 96Trwała i utrzymująca się odpowiedź

bez oznak IRAE

Dzięki uprzejmości K. Harmankaya, Wiedeń

Harmankaya i wsp. Praca przedstawiona podczas EADO 2009, Wiedeń

• 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]

– 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]

Unmet Needs in NSCLC and SCLC

Current therapie

s

HistologyMolecular

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.

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+ CellsFavorable prognosis[2,3]: Disease-specific survival and lower risk of disease recurrence

CD8+ CellsFavorable prognosis[4-8]: Overall survivalCD4+ CellsFavorable prognosis[4,6,9]: Overall survivalMacrophagesFavorable prognosis[7]: Overall survival

TregsUnfavorable prognosis[12,13]: Overall survival, relapse- and recurrence-free survival

NK CellsFavorable prognosis[10]: Disease-specific survivalNK 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 system

• Certain 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.

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]

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]

Suppression of APC

APCD. T cell checkpoint

dysregulation[2]

CTLA-4PD-1

TIM-3

BTLA

VISTALAG-3

B7-1

HVEM

CD27

CD137

GITR

OX40

CD28

Co-inhibitory receptors

Co-stimulatory

receptors

T cell

B. Recruitment of immunosuppressive cells[1,2]

MDSCsTregs

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.

Immunotherapies in NSCLC

Targeting T-cell checkpoint

dysregulationNivolumab[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 cellsTumor cells

Current immunotherapies target NSCLC through a variety of approaches:

Targeting the tumor

Tumor cells

Novel vaccine approachesBelagenpumatucel-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)

OS of patients treated with nivolumab monotherapy by dose

Group Died/Treated Median OS (95% CI) 1-year 2-year1 mg/kg 26/33 9.2 (5.3, 11.1) 32 (16, 49) [8] 12 (3, 27) [2]3 mg/kg 20/37 14.9 (7.3, —) 56 (38, 71) [17] 45 (27, 61) [9]10 mg/kg 48/59 9.2 (5.2, 12.4) 40 (27, 52) [23] 19 (10, 31) [9]

OS rate % (95% CI) [patients at risk]

Censored

0 6 12 18 24 3027211593 33 36 42 48 5439 45 51 57

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

Ove

rall

Su

rviv

al

Months Since Treatment Initiation

Brahmer JR, et al. Poster presented at ASCO 2014 (Abstract 8112)

CA209-003

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

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+)

Phase II Study of Ipilimumab and Paclitaxel/Carboplatin: OS in the Squamous NSCLC Subset

Pro

po

rtio

n A

live

Regimen[1]

Events/Patients

Median (mo) HR (95% CI)

ControlConcurrentPhased*

14/1517/2113/21

7.9 6.2

10.9

–1.02 (0.50–2.08)0.48 (0.22–1.03)

MonthsPatients at risk:Concurrent 21 13 11 6 4 3 3 2 0 0Phased* 21 19 15 12 9 9 8 5 3 0Control 15 11 10 7 4 1 1 1 0 0

1.0

0.8

0.6

0.4

0.2

00 3 6 9 12 15 18 21 24 27

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/m2)/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.

RCC renal cell carcinoma molecular pathology

RCC it is a heterogenous group of tumors Most of them has clear cell morphology

Collecting duct

Clear cellPapillary type I,II

+II II)Chromopho

bOncocytic

VHL c-MET BHD

Histologic subtype

(%)

Genetic mutation

FH

75–85 12–14 2–44–6 1

BHD

Non clear cell

BHD = Birt–Hogg–Dubé; FH = fumarate hydratase; VHL = von Hippel–Lindau

Molecular pathology of renal cell carcinoma

HIF-1β

R C C Tu m o u r

c e l l

Endothelial cell

B o n e m a r r o w d e r i v e d c e l l s

S t r o m a l c e l l s

c y t o s o l

P e r i c y t e

NOS

Akt PI3K

Src

FAK

P38 MAPK

Smad 2/3

Erk 1/2

TIE2

FGFR

VEGFR

PDGFR

PD

GF

Erk 1/2

PDGFPDGF

VEGF

VEGF

VEGF

VEG

F

VEGFR

PDGFR

VEGFR

Proliferation

Migration

Vascular permeabilit

y

Survival

Increased pericyte

expression and

coverage

Recruitment of

proangiogenic BMDCs

Immuno-modulatory

effect

PDGF

PDGF

VEGF

VEGF

FGF

FGF

IL-8

IL-8

Ang-2

Ang-2

PlGF

PlGF

Mutated KIT

PD

GF

PDGFR

Sunitinib sorafenib

TGFRβ2

Cell survival

SDF-

1

SDF-1

SDF-1

PDGF

PDGF

PDGF

VEGF

VEGF

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

n u c l e u s

TCEB2

TCEB1

Cul2

Rbx1

VHL

HIF-1α

HIF-1α

UbUb

UbUb

E3 Ligase Complex

degradation

Ang-2

PlGF

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

SH

C

GR

B2 SO

S

PDGFR HIF-1α

PRKX TTBK2

RSK

JAK/STAT

MITF

Β-catenin

TYRO3

Ras

MAPK

FGF

SH

C

GR

B2 SO

S

FGFR

EGFR

TARGET GENES

HIF-1α

HIF-1β

CPB/p300

HRE

upregulation Gene

expression switch

downregulation

sunitinib

EG

F

SDF-1

CXCR2

TGF-β

CXCR4

Lysosomal sequestration

Alk1

VEGF

VEGF

PDGF

PDGF

Ang-2 Ang-

2Ang-

2IL-8IL-8IL-8

FGFFGF

FGF FGFFF

PlGF

SDF-1

TGF-β TGF-

β

TGF-β TGF-

β

TGF-β

TGF-β MET

HG

F

T cell

T cell

B cell

B cell

B cell

B cellT cell

T cell B

cellT cell

?

Ang-2

Fig. by M. Buczek et al.

CLINICAL ACTIVITY AND SAFETY OF ANTI-PD-1 (BMS-936558, MDX-1106) IN PATIENTS WITH PREVIOUSLY TREATED METASTATIC RENAL CELL CARCINOMA (MRCC)

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

ASCO 2012

NIVOLUMAB FOR METASTATIC RENAL CELL CARCINOMA (MRCC): RESULTS OF A RANDOMIZED, DOSE-RANGING PHASE II TRIALR. 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

ASCO 2014

Progression-free survival in Phase II trial

Number of patients at risk

0.3 mg/kg 60 24 17 13 12 11 3 0 0

2 mg/kg 54 27 15 9 7 6 1 0 0

10 mg/kg 54 30 18 10 8 7 3 1 0

0

10

20

30

40

50

60

70

80

90

100

3 6 9 12 15 18 21 24Time (months)

0

Pro

gres

sion

-fre

e su

rviv

al (

%)

Median PFS, months (80% CI)

Stratified trend test P value

0.3 mg/kg 2.7 (1.9, 3.0)0.92 mg/kg 4.0 (2.8, 4.2)

10 mg/kg 4.2 (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. 33R. Motzer at all. J Clin Oncol 32:5s, 2014 (suppl; abstr 5009)

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 29 26 8 1 0

0

10

20

30

40

50

60

70

80

90

100

3 6 9 12 15 18 21 33Time (months)

0

Ove

rall

surv

ival

(%

)

0.3 mg/kg (events: 36/60)2 mg/kg (events: 29/54)10 mg/kg (events: 32/54)

24 27 30

Median OS, months (80% CI)

0.3 mg/kg 18.2 (16.2, 24.0)

2 mg/kg 25.5 (19.8, 28.8)

10 mg/kg 24.7 (15.3, 26.0)

R. Motzer at all. J Clin Oncol 32:5s, 2014 (suppl; abstr 5009)

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 + N 33 27 23 21 16 4 1 1 0

P + N 20 13 9 7 5 2 2 2 1

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

Pro

port

ion of

PFS

Time since first dose (weeks)

24BL 48 72 9684603612

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

Overall survival by MSKCC risk group and number of prior

treatments

33

0

10

20

30

40

50

60

70

80

90

100

3 6 9 12 15 18 21Time (months)

0

Ove

rall

surv

ival

(%

)

24 27 30

Favorable (events: 25/56)Intermediate (events: 40/70)Poor (events: 32/42)

Median OS, months (95% CI)

Favorable NR (24.9, NR)Intermediate 20.3 (13.4, NR)Poor 12.5 (8.1, 18.6)

0

10

20

30

40

50

60

70

80

90

100

3 6 9 12 15 18 21 33Time (months)

0O

vera

ll su

rviv

al (

%)

24 27 30

1 Prior treatment (events: 22/46)≥2 Prior treatments (events: 75/122)

Median OS, months (95% CI)

1 NR (19.8, NR)

≥2 18.7 (13.4, 26.0)

Risk group Number of prior treatments

NR, not reached; Symbols represent censored observations.

R. Motzer, ASCO 2014

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

Finally –immunotherapy is back