Download T cell

Cezary Szczylik
Klinika Onkologii
Wojskowy Instytut Medyczny. Warszawa
IMMUNONKOLOGIA – SZANSE I
ZAGROŻENIA W LECZENIU
CZERNIAKA, RAKA NERKI I PŁUC
Immunotherapy history in oncolgy
Ipilimumab registartion in
metastaic melanoma4
Burnets hypothesis of
immune surveillance in
cancer1
immunologic infiltrations
described by Virchow
1857
1893
Coley toxin –
American Journal of
Medical Sciences5
1957
High dose
IL-2 registered in
metastatic melanoma2
1991 1995 1998
2010 2011
FDA sipuleucel
registered in prostate
cancer 1
Tumor specific antigens (Rosenberg
i Boon)1
IFNα in melanoma
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;
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
I-O
Radiation
Cytotoxic
& targeted
therapies
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]


Elimination
Equilibrium
Escape*
Cancer immunosurveillance
Cancer dormancy
Cancer progression
Genetic
instability
Tumor
heterogeneity
Immune
selection
Tumors may avoid
elimination by the immune
system through outgrowth
tumor cells that can
suppress, disrupt, or
“escape” the immune system
Effective antigen
processing/presentation
Effective activation and
function of effector cells
‒
CD8+
T cell
T cell activation without
co-inhibitory signals
CD4+
T cell



NK cell
Treg
Tumor cells
Normal cells
Adapted from Vesely et al 2011.[1]
* Various mechanisms for immune “escape” exist
(See Section IV. Mechanisms of Immune Escape in NSCLC).
NK, natural killer; Treg, regulatory T cell.
1. Vesely MD et al. Annu Rev Immunol. 2011;29:235-271.
Tumours use various mechanisms to
escape the immune system
Immune escape mechanisms are complex and frequently overlapping
A. Ineffective presentation of
tumour antigens to the
immune system
CD8+
T cell
TCR
 VEGF
APC
B. Recruitment of
immunosuppressive cells
(Tregs, MDSCs, others)
MHC
CTLA-4
MDSC
Treg
PD-L1
Tumour cells
PD-1
P-DL1
PD-1
D. T cell checkpoint
dysregulation
 TGF-β
 IDO
 IL-10
 TGF-β
 IL-10
CD4+
T cell
 TGF-β
 ARG1
 iNOS
CD8+
T cell
C. Release of immunosuppressive
factors
Vesely MD, et al. Ann Rev Immunol 2011;29:235–271
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
1
examples of inhibitory
checkpoint receptors
Pardoll DM. Nat Rev Cancer 2012;12(4):252–264
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]
Activating
receptors
Inhibitory
receptors
CTLA-4
CD28
PD-1
OX40
B7-1
GITR
cell
TTcell
TIM-3
CD137
BTLA
CD27
VISTA
HVEM
Agonistic
antibodies
LAG-3
Blocking
antibodies
T cell
stimulation
Adapted from Mellman et al 2011.[1]
1. Mellman I et al. Nature. 2011;480(7378):480-489.
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
Role of PD-1 pathway in suppressing
antitumour immunity
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 antigenpresenting cells
IFN
IFNγR
MHC
T cell
receptor
T cell
receptor
MHC
PI3K
NF
Other
Tumour cell
PD-L1
Shp-2
PD-L2
PD-1
PD-1
CD28
B7
Dendritic
cell
T cell
PD-1
PD-L1
Shp-2
PD-1
PD-L2
Nivolumab is a PD-1 receptor blocking antibody
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
activation
T-cell
inhibition
T-cell
potentiation
CTLA-4
T cell
CD28
TCR
MHC
APC
T cell
T cell
CD28
TCR
B7
MHC
APC
CTLA-4
CTLA-4
B7
TCR
Ipilimumab
MHC
B7
blocks
CTLA-4
APC
Adapted from Weber J. Cancer Immunol Immunother 2009;58:823
PD-L1 expression and evidence of
poor prognosis
RCC1
• Patients with ↑PD-L1 on tumours and TILs had 4.5x higher risk of
death (P<0.001)
NSCLC2
• ↑PD-L1 on tumour cells correlated with ↓TILs in same region
Melanoma3
• 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
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
ESMO 2013
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; 8BristolMyers Squibb, Lawrenceville, NJ, USA; 9Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
Abstract Number 24LBA
14
OS Relative to Historical Data
 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
Schadendorf et al., ESMO 2013,15
abs 24LBA
Ipilimumab atypical responce kinetics
Tydzień 96
Trwała i utrzymująca się odpowiedź
bez oznak IRAE
Ocena przesiewowa
Tydzień 12
Wstępny wzrost
łącznej objętości
nowotworu
(mWHO PD)
Tydzień 16
Odpowiedź
Dzięki uprzejmości K. Harmankaya, Wiedeń
Harmankaya i wsp. Praca przedstawiona podczas EADO 2009, Wiedeń
•
Unmet Needs in NSCLC and
SCLC
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]
Advancements in understanding the biology
of NSCLC have elucidated disease
characteristics (eg, histology, molecular
Squamous
Current
pathology) that must be considered for
Patients failing
[1]
therapies
targeted therapeutic approaches
targeted therapies
–
Patients failing
conventional
chemotherapies
Over the past several years,
immunotherapies have emerged as a
new therapeutic approach in NSCLC[6]
Unmet needs
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.
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.
Summary of the Prognostic Roles of
Immune Cells in NSCLC and SCLC
•
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
Dendritic Cells
Favorable prognosis[1]: Overall survival,
disease-specific survival, and disease-free
survival
•
Certain immune cells are associated with a better
prognosis/improved outcome, while others suggest
an unfavorable prognosis and disease outcome
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
NK Cells
Favorable prognosis[10]: Disease-specific
survival
NK Cells (Immature / Impaired)
Unfavorable prognosis[11]: Disease progression
Tumor
Tregs
Unfavorable prognosis[12,13]: Overall survival,
relapse- and recurrence-free survival
NK, natural killer; NSCLC, non-small cell lung cancer; Treg, regulatory T cell.
1.
2.
3.
4.
5.
6.
Dieu-Nosjean MC et al. J Clin Oncol. 2008;26(27):4410-4117.
Petersen RP et al. Cancer. 2006;107(12):2866-2872.
Al-Shibli K et al. APMIS. 2010;118(5):371-382.
Ruffini E et al. Ann Thorac Surg. 2009;87(2):356-372.
Zhuang X et al. Appl Immunohistochem Mol Morphol. 2010;18(1):24-28.
Hiraoka K et al. Br J Cancer. 2006;94(2):275-280.
7.
8.
9.
10.
11.
12.
13.
Kawai O et al. Cancer. 2008;113(6):1387-1395.
McCoy MJ et al. Br J Cancer. 2012;107(7):1107-1115.
Wakabayashi O et al. Cancer Sci. 2003;94(11):1003-1009.
Al-Shibli K et al. Histopathol. 2009;55(3):301-312.
Jin J et al. PLoS One. 2013;8(4):e61024.
Tao H et al. Lung Cancer. 2012;75(1):95-101.
Shimizu K et al. J Thorac Oncol. 2010;5(5):585-590.
Immune Escape in NSCLC/SCLC
•
Many tumors, including NSCLC, escape the immune response by creating an immunosuppressive
microenvironment that prevents an effective antitumor response[1,2]
A. Ineffective presentation of tumor
antigens to the immune
C. Release of
system[2]
Downregulation of
MHC expression
Suppression of APC
Tumor cell
APC
immunosuppressive factors[2]
Factors/enzymes directly or indirectly
suppress immune response
Tumor cells
D. T cell checkpoint
dysregulation[2]
CTLA-4
PD-1
B7-1
CD28
B. Recruitment of immunosuppressive
OX40
cells[1,2]
GITR
T cell
TIM-3
CD137
CD27
HVEM
Tregs
MDSCs
Tumor
microenvironment
Co-stimulatory
receptors
BTLA
VISTA
LAG-3
Co-inhibitory
receptors
Adapted from Mellman et al 2011.[3]
•
The mechanisms tumors use to escape the immune system provide a range of potential
therapeutic targets for NSCLC[2]
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

Current immunotherapies target NSCLC through a variety of approaches:
Novel vaccine approaches
Targeting the tumor
Belagenpumatucel-L and
Tergenpumatucel-L[3,4,6]
(Live engineered tumor cell
vaccines)
Bavituximab[1]
(anti-PS)
Reolysin®[2]
(oncolytic virus)
CimaVax-EGF[3,4,7]
(EGF–EGFR vaccine)
Tumor cells
Enhancing antigen
recognition/presentation
Tumor cells
Tumor cells
Targeting T-cell checkpoint
dysregulation
Stimuvax®[3,4] (MUC-1)
Nivolumab[3,4] (anti-PD-1)
TG4010[3,4] (MUC-1)
Ipilimumab[3,4] (anti-CTLA-4)
Racotumomab[5]
(anti-idiotype vaccine)
Other mAbs[3,8]
APC
Tumor
microenvironment
• Anti-PD-1
• Anti-PD-L1
• Anti-PD-L2
APC, antigen-presenting cell; CTLA-4, cytotoxic T-lymphocyte antigen-4; EGF,
3. Brahmer JR. J Clin Oncol. 2013;31(8):1021-1028.
epidermal growth factor; EGFR, epidermal growth factor receptor; MUC-1, mucin-1; 4. Dasanu CA et al. Expert Opin Biol Ther. 2012;12(7):923-937.
NSCLC, non-small cell lung cancer; PD-1, programmed death-1;
5. Segatori VI et al. Front Oncol. 2012;2(160):1-7.
PD-L1, programmed death ligand-1; PS, phosphatidylserine.
1. Bavituximab Oncology. First-in-Class PS-Targeting Monoclonal Antibody. 6.
Available at: http://www.peregrineinc.com/pipeline/ bavituximaboncology.html. Accessed April 10, 2014.
7.
2. Oncolytics. Reolysin. Available at: http://www.
oncolyticsbiotech.com/reolysin. Accessed May 17, 2013.
8.
T cells
NewLink Genetics [press release]. Available at:
http://investors.linkp.com/releasedetail.cfm?ReleaseID=768475. Accessed
March 28, 2014.
Rodriguez PC et al. MEDICC Rev. 2010;12(1):17-23.
Ceeraz S et al. Trends Immunol. 2013;34(11):556-565.
CA209-003
OS of patients treated with nivolumab
monotherapy by dose
OS rate % (95% CI) [patients at risk]
Group Died/Treated Median OS (95% CI)
1-year
2-year
1 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]
Censored
1.0
Overall Survival
0.8
1-year OS Rate 56% (17 patients at risk)
0.6
2-year OS Rate 45% (9 patients at risk)
0.4
0.2
0.0
0
3
6
9
12
15
18
21
24
27
30
33
36
39
42
45
48
51
54
57
Months Since Treatment Initiation
Brahmer JR, et al. Poster presented at ASCO 2014 (Abstract 8112)
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 BMS936558
 Response ongoing after
completing 2 years of
BMS-936558 treatment in
June of 2012
CA209-012
Summary of survival outcomes in patients
treated with 1st-line nivolumab
monotherapy
Squamous
(n=9)
Nonsquamous
(n=11)
Total
(N=20)
44 (14, 72)
73 (37, 90)
60 (36, 78)
15.1 (5.9, 63.3+)
47.3 (9.6, 80.7+)
36.1 (5.9, 80.7+)
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+)
PFS
PFS rate at 24 weeks, %
(95% CI)
Median PFS, weeks
(range)
OS
Gettinger SN, et al. Poster presented at ASCO 2014 (Abstract 8024)
Phase II Study of Ipilimumab and
Paclitaxel/Carboplatin: OS in the Squamous NSCLC
Subset
Data from trial CA184-041.
1.0
Proportion Alive
0.8
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)
0.6
0.4
0.2
0
Patients at risk:
Concurrent
Phased*
Control
0
3
6
9
12
15
Months
18
21
24
27
21
21
15
13
19
11
11
15
10
6
12
7
4
9
4
3
8
1
2
5
1
0
3
0
0
0
0
* 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.
1.
3
9
1
Reck M et al. Ann Oncol. 2012;23(suppl 8):viii28-viii34.
RCC renal cell carcinoma molecular
pathology

RCC it is a heterogenous group of tumors
 Most of them has clear cell morphology
Clear cell
Histologic
subtype
(%)
Non clear cell
Papillary type I,II
+II II)
75–85
Genetic mutation VHL
12–14
c-MET
FH
Chromopho Oncocytic Collecting
b
duct
4–6
2–4
BHD
BHD
BHD = Birt–Hogg–Dubé; FH = fumarate hydratase; VHL = von Hippel–Lindau
1
Molecular pathology of renal cell
carcinoma
Acquisition of secondary KIT mutation
Proliferation
Erk 1/2
PLC-γ
Survival
Akt
PI3K
Mutated
KIT
Recruitment of
proangiogenic
BMDCs
Bone marrow
derived cells
PDGFR
CXCR4
Vascular
permeability
VEGFR
NOS
Migration
Src
Sunitinib
sorafenib
PlG
F
TKI-MEDIATED
BLOCKAGE OF
VEGF- AND PDGFMEDIATED
ANGIOGENESIS
PATHWAY AXIS
PDGFR
FAK
P38
MAPK
VEGFR
PDGF
Immunomodulatory
effect
VEGF
SDF-1
Stromal cells
PDGF
Alternalive
signalling in
condition of RCC
resistance to TKIs
TIE2
TGFβ
VEGF
Cell survival
CXCR2
FGFR
PDGF
SDF-1
PlG
F
PlG
F
VEGF
VEGFR
PDGF
VEGF
Alternalive
signalling in
condition of RCC
resistance to TKIs
Ang-2
Ang-2
IL-8
sunitinib
FGF
IL-8
FGF
FGF
IL-8
FGF
Lysosomal
sequestration
VEGF
VEGF
PDGFR
Β-catenin
VEGF
TYRO3
MITF
PlG
F
PDGF
Ras
VEGF
MAPK
Ang-2
Ang-2
IL-8
IL-8
FGF
HIF-1β
FF
FGF
upregulation
PRKX TTBK2
RSK
Gene
CPB/p300
expression
HIF-1β HIF-1α
switch
HRE TARGET GENES
HIF-1α
MET
Erk 1/2
Pericyte
Ras
Alk1
JAK/STAT
downregulation
E3 Ligase Complex
Rbx1 TCEB2
TGFRβ2
CXCR4
eIF-4E1
Mek 1/2
ESM1downregulation
HOXA9 PECAM
FGFR
mTOR
EGFR
PI3K
Erk 1/2
PDGFR
S6K
Akt
EGFR
Increased
pericyte
expression
and
coverage
Ang-2
SDF-1
SDF-1
PDGF
PDGF
VEGF
VEGF
?
VEGFR
Smad 2/3
Endothelial
cell
T cell
B cell
B cell
T cell
T cell
B cellT cell
B cell
T cellB cell
VEGFR
PDGF PDGF
RCC cytosol
Tumour cell
Increased
migration and
invasiveness/ EMT
nucleus
Cul2
HIF-1α
TCEB1
VHL
Ub
Ub
Ub
Ub
HIF-1α
degradation
Fig. by M. Buczek et al.
Abstract 4505
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 5009
NIVOLUMAB FOR METASTATIC RENAL CELL
CARCINOMA (MRCC): RESULTS OF A
RANDOMIZED, DOSE-RANGING PHASE II TRIAL
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
Progression-free survival in
Phase II trial
100
Median PFS,
months (80% CI)
Progression-free survival (%)
90
80
0.3 mg/kg
2.7 (1.9, 3.0)
70
2 mg/kg
4.0 (2.8, 4.2)
60
10 mg/kg
4.2 (2.8, 5.5)
50
Stratified trend
test P value
0.9
0.3 mg/kg (events: 48/60)
2 mg/kg (events: 43/54)
10 mg/kg (events: 45/54)
40
30
20
10
0
0
3
6
9
Number of patients at risk
12
15
18
Time (months)
21
24
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
Symbols represent censored observations.
33 2014 (suppl; abstr 5009)
R. Motzer at all. J Clin Oncol 32:5s,
Overall survival in Phase II
trial
Based on data cutoff of March 5, 2014; Symbols represent censored observations.
100
Overall survival (%)
90
0.3 mg/kg (events: 36/60)
2 mg/kg (events: 29/54)
10 mg/kg (events: 32/54)
80
70
60
50
Median OS,
months (80% CI)
40
30
0.3 mg/kg
18.2 (16.2, 24.0)
20
2 mg/kg
25.5 (19.8, 28.8)
10
10 mg/kg
24.7 (15.3, 26.0)
0
0
3
6
9
12
15
18
21
24
27
30
33
Time (months)
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
34 2014 (suppl; abstr 5009)
R. Motzer at all. J Clin Oncol 32:5s,
Progression-free survival
1.0
S + N (n=33) 57.6% Tx-naïve
P + N (n=20) 0% Tx-naïve
0.8
Proportion of PFS
Median PFS, weeks
(95% CI)
0.6
S + N (n=33)
48.9 (41.6-66.0)
P + N (n=20)
31.4 (12.1-48.1)
0.4
0.2
0.0
BL
12
24
S+N
33
27
23
21
16
4
P+N
20
13
9
7
5
2
Number of
patients at risk
36
48
60
72
Time since first dose (weeks)
84
96
1
1
0
2
2
1
Symbols represent censored observation. Number of patients at risk listed is number at risk before entering the time period.
Tx, treatment
A. Amin, ASCO 2014
Overall survival by MSKCC risk group
and number of prior treatments
Risk group
100
90
90
Overall survival (%)
Overall survival (%)
Number of prior treatments
100
80
70
60
50
40
30
Favorable (events: 25/56)
Intermediate (events: 40/70)
Poor (events: 32/42)
20
10
0
0
3
6
9
12 15 18 21 24
Time (months)
Favorable
Intermediate
Poor
70
60
50
40
30
20
1 Prior treatment (events: 22/46)
≥2 Prior treatments (events: 75/122)
10
0
27
30 33
Median OS, months
(95% CI)
NR (24.9, NR)
20.3 (13.4, NR)
12.5 (8.1, 18.6)
NR, not reached; Symbols represent censored observations.
R. Motzer, ASCO 2014
80
0
3
6
9
12 15 18 21
Time (months)
24
Median OS,
months (95% CI)
1
NR (19.8, NR)
≥2
18.7 (13.4, 26.0)
27
30
33
Immuno-checkpoints targeting (CTLA-4, PD1) – 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