Inmuterapia & Cáncer de Pulmón - Abordaje … · Cáncer de pulmón no microcítico: la...
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Cáncer de pulmón no microcítico: la oportunidad del sistema inmune E. Holgado Martín MD. PhD. Inmuno-Oncología Sº Oncología Médica Hospital Ramón y Cajal Madrid, 7 Abril 2016
Transcript of Inmuterapia & Cáncer de Pulmón - Abordaje … · Cáncer de pulmón no microcítico: la...
Cáncer de pulmón no microcítico: la
oportunidad del sistema inmune
E. Holgado Martín MD. PhD.
Inmuno-Oncología
Sº Oncología Médica
Hospital Ramón y Cajal
Madrid, 7 Abril 2016
Lung cancer: most common malignancy and leading cause of cancer-related mortality
• 1. Ferlay J, et al. GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11[Internet]. Lyon, France: International Agency for Research on Cancer; 2013. Available from: http://globocan.iarc.fr. Accessed September 2014;
2. Ferlay J, et al. Eur J Cancer. 2013;49:1374–1403.
0
500
1000
1500
2000
LungCancer
BreastCancer
ColorectalCancer
ProstateCancer
Incidence
Mortality
GLOBOCAN 2012 (worldwide, both sexes)1
1.59 million1
(1 in 5) estimated deaths worldwide
1.82 million1
estimated new cases worldwide
More people die from lung cancer than breast, colorectal and prostate cancers
combined1
Within Europe, ~1,000 people die from lung cancer every day1,2
Li T, et al. J Clin Oncol. 2013;31:1039-1049.
Evolution of NSCLC Subtyping to a Multitude of Molecular-Defined Subsets
NSCLC
as one
disease
Histology-Based Subtyping
Squamous
34%
Other
11%
Adenoca
55%
Adenocarcinoma
Squamous Cell Cancer
ALK
HER2
BRAF
PIK3CA
AKT1
MAP2K1
NRAS
ROS1
RET
EGFR
KRAS
Unknown
EGFRvIII
PI3KCA
EGFR
DDR2
FGFR1 Amp
Unknown
First-targeted tx
ALK
EGFR
History of therapy in advanced NSCLC : FDA Approval Dates
First line
Second line
Third line
Maintenance
Not approved
1970 1980 1990 2000
Median
OS (mos)
12+
~ 6 ~ 2-4
BSC Single-agent platinum Doublets
Bevacizumab + PC
Carboplatin 1989
Erlotinib Pemetrexed 2004
Docetaxel 1999
Paclitaxel Gemcitabine 1998
Vinorelbine 1994
Docetaxel 2002
Bevacizumab 2006
Gefitinib 2003
Standard therapies
Pemetrexed 2008/2009
Histology-directed therapy
~ 8-10
Cisplatin* 1978
1. FDA Web site. 2. NCCN. Clinical practice guidelines in oncology. v.3.2011. 3. Schrump, et al. Non-small cell lung cancer.
In: Cancer: Principles and Practice of Oncology. 7th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2005.
Johnson B, et al. ASCO 2013. Abstract 8019.
Lung Cancer Mutation Consortium: OS by Mutation and Treatment
Driver mutation + targeted therapy (n = 313; median OS: 3.5 yrs)
Driver mutation + no targeted therapy (n = 265; median OS: 2.4 yrs)
No driver mutation (n = 361; median OS: 2.1 yrs)
100
80
60
40
20
0
OS
(%
)
0 1 2 3 4 5
Yrs
Targeted therapy vs no targeted
therapy; P < .0001
Targeted Therapy Focuses on Driver Gene Alterations: “Oncogenic Addiction”
Gefitinib[1,2] Erlotinib[3,4] Afatinib[5,6] Crizotinib[7-9]
Activity EGFR EGFR EGFR
(ErbB family) ALK, ROS1, MET
Target EGFR EGFR EGFR ALK
RR, % 60-80 50-80 ~ 60 ~ 60
PFS, mos 10-11 10-14 ~ 11 ~ 10
TRD, % 1~2 1~2 1.7 < 1
EGFR mutants ALK ROS/RET
1. Maemondo M, et al. N Engl J Med. 2010;362:2380-2388. 2. Mitsudomi T, et al. Lancet Oncol. 2010;11:121-128. 3. Rosell R, et al. Lancet Oncol. 2012;13:239-246. 4. Zhou C, et al. Lancet Oncol. 2011;12:735-742. 5. Sequist LV, et al. J Clin Oncol. 2013;31:3327-3334. 6.
Wu YL, et al. Lancel Oncol. 2014;15:213-222. 7. Camidge DR, et al. Lancet Oncol 2012;10:1011-1019. 8. Kim DW, et al. ASCO 2012. Abstract 7533. 9. Shaw AT, et al. N Engl J Med 2013;368:2385-2394.
Rationale for immune-based anti-tumor therapies
Bases del Sistema Inmune
Barreras
Respuesta Innata
R.Adaptativa
APC Macrófago Eosinófilo Neutrófilo Basófilo Complemento Mastocito
Inmunoglobulinas Linfocito T CD8 Linfocito T CD4
NK
Linfocito B
React. Fase aguda
IL1 IL1 IL12
IFNϒ
IL6 TNF
IL8 TNF IL2
IL4 IL13
IL5
IFNϒ
Activación
Diferenciación
Activación
Activación
Macrófago Eosinófilo
Linf B
NK
Monocito Neutrófilo
Linf T
Neoantígenos-Immunogenicidad Elementos de la respuesta inmune anti-tumoral
Anticuerpos -> Baja eficacia
Linfocitos T citotóxicos
Células NK - ADCC.
Citocinas Antineoplásicas (??)
Janeway - Immunobiology
Neoantigens-Immunogenicity Respuesta Inmune Antitumoral = Reconocimiento de Antígeno + Acción antitumoral
• Más allá de la Respuesta Innata (las NKs por si solas pueden ser antitumorales), el reconocimiento de antígeno por los receptores antigénicos (BcR y TcR) es fundamental.
• 2 elementos del reconocimiento antitumoral:
Antígeno Tumoral <-> TcR
Bases del Sistema Inmune
•Inmunovigilancia y tolerancia
Golgi
R.endopl
Proteosoma
Ag endógeno
MHCI
Célula
MHCII
APC
Ag. exógeno
R.endopl
Lisis
T CD4 Help T CD8 NK
T CD4 Foxp3,Reg
B
TH1 TH2 TH17
nat-Treg: 5-10% de Cd4+ in-Treg •TH3 •Tr1 •Foxp3 in-Tregs
Citotoxicidad
Inmunotolerancia
Pardoll, D. M. NatRevCancer 2012
Bases del Sistema Inmune
•Immune checkpoints
CD80(B7-1),86(B7-2)/CTLA4(CD152)
PD-L1(B7-H1,CD274 ),-L2(B7-DC,CD273)/PD1(CD279)
Programmed cell death-1 pathway
Cytotoxic T-lymphocyte-associated protein 4
Neoantígenos-Inmunogenicidad Modelo progresión tumoral
Inflamación, atrofia y proliferación
Carcinógenos y mutaciones específicas
Catástrofe gen/epi
Displasia
Carcinoma pulmón invasivo
Selección clonal , ventaja
proliferativa/supervivencia
Metastasis #2
Metastasis #1
Metastasis #3
Variabilidad en la transmisión de
alteraciones gen/epi
Antigenicidad R. Inmune
?
Inmunogenicidad tumoral Neoantígenos
Alexandrov L,B. Nature 2013
•Neoantígenos
Ocasional Regular Frecuente
Prevalencia de mutaciones somáticas
Mutaciones por megabase 0.01 0.1 1.0 10 100 1,000 0.001
Melanoma
Escamoso pulmón
Adenocarcinoma pulmón
Vejiga
Microcítico
Esófago
Colorrectal
Cérvix
Cabeza y cuello
Estómago
Útero Hígado
Renal c. claras
Renal papilar
Ovario
Próstata
Mieloma
Linfoma B
Glioma bajo grado Mama
Páncreas
Glioblastoma
Neuroblastoma
LLC
Tiroides
Renal cromófobo
LMA
Meduloblastoma
LLA
Astrocitoma pilocítico
Alteraciones en la maquinaria de
replicación y reparación del DNA.
Exposición a mutágenos endo/exógenos.
Modificaciones enzimáticas del DNA.
Análisis secuencias de exones de 7.042 tumores
primarios de 30 diferentes tipos comparadas con
DNA no tumoral del mismo individuo.
Se identifican 21 perfiles mutacionales
específicos:
o Edad.
o Linaje celular.
o Oncogenes.
o Exposición al tabaco & UV.
Gubin, M.M. J. Clin. Invest. 2015
Antígenos tumorales
TSAs: tumor specific antigens: neoantigen. TAAs: tumor associated antigens: Her2/neu. TRA or CTAs: tissue restricted antigens or cancer testis antigens.
TSA TAA TRA
Immunogenicity +++ + ++
Tolerance - ++ +
Coulie et al. Nature Reviews Cancer 2014
Inmunogenicidad tumoral Predicción matemática
•Neoantígenos (melanoma)
De cuantos neoantigenos estamos hablando?
Snyder A. N Engl J Med. 2014
Existe correlación entre carga antigénica, antigenicidad y
respuesta?
Comunes a los tumores?
64 pts melanoma CTLA-4 inh
25 CTLA4inh 39 CTLA4inh
10
15
DNA exon genome seq
Long term response No benefit
17
22
Bioinformatic analysis of mutation burden and predicted MHCI restricted neoantigens
Murino Humano
Meth A CMS5 Prost Meln
Transcriptoma 75% 54%
SNV en exones 1,528 208
Mut. no sinónimas 77.10% 78.50%
Alta afinidad MHCI 823 112 14 >100
Antigenicidad BALBc 11 7
CD44 citometría 6/18
In vivo
IFN ELISA 10/18
In vitro
Inmunogenicidad tumoral Presentación MCH I
Duan F. J. Exp.Medicine 2014
•Neoantígenos (sarcoma)
Las mutaciones somáticas no sinónimas (neoantígenos)
observadas pueden inducir una respuesta inmune?
o Mediada por MHCI?
Genoma viral Vacuna
Respuesta CD8+ Presentación
15%
50% 2.5%
Secuenciación de exones (RNA-seq) Predicción de mutaciones no sinónimas
Linf. T CD8+ CD4-/-
Inoculación Sc
Activación de CD8 por expresión de CD44 e IFNϒ
in vitro e in vivo
Inmunogenicidad tumoral Presentación MHC II
Linnemann C. Nat Medicine 2015
Schumacher T, N. Science 2015
•Neoantígenos (melanoma)
Las mutaciones somáticas no sinónimas
(neoantígenos) observadas pueden inducir una
respuesta inmune?
o mediada por MHCII?:
Secuenciación de exones (RNA-seq) Predicción de mutaciones no sinónimas
Linf. BBCL-6 BCL-XL +/+
Linf. T CD4+ (TIL) Autólogos
Carga de antígenos (8)
Expresión en sobrenadante de co-cultivos de citoquinas de TH1, Th2 y TH17, IFNϒ, TNFα,
Il2,4,6,10 y 17a
+ en 4/5 melanoma pts
Inmunogenicidad tumoral Neoantígenos
• El sistema inmune responde contra el tumor al reconocer el antígeno
• ¿De cuántos neoantígenos estamos hablando? 150 en 10mut/Mb.
• Existen TAA y TSA. Los TSA son los que permiten una respuesta inmune más dirigida (menos efectos “fuera de la diana” el tumor)
• NO todas las mutaciones somáticas no sinónimas (neoantígenos) observadas inducen una respuesta inmune
• El HLA del individuo es determinante
• Existe correlación entre carga antigénica, antigenicidad y respuesta
• Los neoantígenos NO son comunes a los tumores
Inmunogenicidad tumoral Immuno-editing
Eliminación Equilibrio Escape
CTL
NK
CTL
T reg
T cyto
NKT
T reg
T reg
CTL
NK T reg
CTL
•Immuno-editing/Immune-selection
Tumor
Antigenicidad
Inmunocompetencia ?
Inmunogenicidad tumoral
•Neoantígenos
Presión inmune sobre el tumor:
o elimina las células portadoras de mayor antigenicidad, bien
por número o calidad de antígenos.
o disminuye la expresión de antígenos con mayor afinidad por
MHC1.
La claves son la antigenicidad y la duración de la expresión del péptido
?
Inmunocompetencia Mecanismos de escape
MHC
CD80
MHC
CD80
TCR
CD28
APC madura
Ag
APC activada
T T activado
Expansión clonal
Presentación intacta?
o NO existencia de PAMP y
DAMP
Asumida la antigenicidad del tumor
o Immuno-editing
o Represión MHCI
Mecanismos de escape tumoral de la
presión del sistema inmune:
IL10, TGFB
PDL1
MHCI Epítopos
FasL
Tumor
RCAS1 CD99
ICAM-1
Previene identificación por T CD4/8
Induce T reg
Inhibe activación Th
Inhibe NK Inhibe Fas+ T
Inhibe RCAS1R+ NK & T
Previene conjugación con T
Mecanismos de escape Inmuno-checkpoints
Rationale for immune-based anti-tumor therapies in NSCLC
¿De qué datos disponemos para
contemplar el uso del tratamiento
inmunomodulador en carcinoma de
pulmón?
Homeostasis inmune pulmonar
• Puerta de entrada de alergenos y gérmenes ajenos al individuo.
• Elementos linfoides.
• Presencia de IgAs, y elementos de la respuesta inmune innata frente a patógenos diarios.
• Expresión de MHCII clave en la identificación y presentación de antígenos.
Kreisel D, J. Immunol 2010
Kambayashi T. NatRevImmunol 2014
Presentadoras/MHCII+ Efectoras Respuesta
APC Macrófago
Profesionales/mieloide
T CD4+ hel/reg
T CD8+
Antígeno
No profesionales
Epitelio pulmonar
Endotelio vascular
B6 B6 MHCII--
Treg TCD8+
50% de las MHCII+ pulmonares
Linf. B
Inmunogenicidad del Ca.Pulmón
Ocasional Regular Frecuente
Prevalencia de mutaciones somáticas
Mutaciones por megabase 0.01 0.1 1.0 10 100 1,000 0.001
Melanoma
Escamoso pulmón
Adenocarcinoma pulmón
Vejiga
Microcítico
Esófago
Colorrectal
Cérvix
Cabeza y cuello
Estómago
Útero Hígado
Renal c. claras
Renal papilar
Ovario
Próstata
Mieloma
Linfoma B
Glioma bajo grado Mama
Páncreas
Glioblastoma
Neuroblastoma
LLC
Tiroides
Renal cromófobo
LMA
Meduloblastoma
LLA
Astrocitoma pilocítico Brown S, D. Geno,me Res 2014
Alexandrov L,B. Nature 2013
Rooney M, S. Cell 2015
Número de mutaciones por paciente
Células del sistema inmune impactan en el pronóstico del CNMP
• 1. Dieu-Nosjean M, et al. J Clin Oncol. 2008;26:4410‒4117; 2. Petersen R, et al. Cancer. 2006;107:2866‒2872; 3. Al-Shibli K, et al. APMIS. 2010;118:371‒382; 4. Ruffini E, et al. Ann Thorac Surg. 2009;87:365‒372; 5. Zhuang X, et al. Appl Immunohistochem Mol Morphol. 2010;18:24‒28; 6. Hiraoka K, et al. Br J Cancer. 2006;94:275‒280; 7. Kawai O, et al. Cancer. 2008;113:1387‒1395; 8. McCoy M, et al. Br J Cancer. 2012;107:1107‒1115; 9. Wakabayashi O, et al. Cancer Sci. 2003;11:1003‒1009; 10. Al-Shibli K, et al. Histopathol. 2009;55:301‒312; 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;5:585‒590.
Dendritic cells OS, disease-specific survival, disease-free survival1
CD3+ cells NSCLC survival and lower risk of disease recurrence2–4
CD8+ cells OS5–8
CD4+ cells OS6,9
Macrophages OS7
Tregs OS, relapse- and recurrence-free survival12,13
NK cells (immature/impaired) Disease progression11
NK cells NSCLC-specific survival10
Favourable prognosis1
Unfavourable prognosis1
Inmunogenicidad del Ca.Pulmón
Expresión PD-L1
Target PD-L1 Is Broadly Expressed in Human
Cancer
31
Positive PD-L1 staining in lung cancer (NSCLC)
(proprietary Genentech/Roche PD-L1 IHC)
High sensitivity and specificity in FFPE samples
* Surgical tumor specimens (internal Genentech data). NSCLC samples include collaboration with Ignacio Wistuba (MD Anderson)
and David Shames (Genentech).
Tumor TypeEstimated PD-L1
Prevalence, ≈ %*
NSCLC (SCC) 50%
NSCLC (adeno) 45%
Colon 45%
Melanoma 40%
Renal 20%
Nearly all human cancer types can
express PD-L1
Target PD-L1 Is Broadly Expressed in Human
Cancer
31
Positive PD-L1 staining in lung cancer (NSCLC)
(proprietary Genentech/Roche PD-L1 IHC)
High sensitivity and specificity in FFPE samples
* Surgical tumor specimens (internal Genentech data). NSCLC samples include collaboration with Ignacio Wistuba (MD Anderson)
and David Shames (Genentech).
Tumor TypeEstimated PD-L1
Prevalence, ≈ %*
NSCLC (SCC) 50%
NSCLC (adeno) 45%
Colon 45%
Melanoma 40%
Renal 20%
Nearly all human cancer types can
express PD-L1
PD-L1 se expresa en la mayoría de tumores
PD-L1 + CNMP (IHQ) Casi la totalidad de los tumores expresan PD-L1
Inmunocompetencia en Ca.Pulmón
•Valor pronóstico de la expresión de PD-L1 en NSCLC,
metaanálisis 2015.
•Estudios que no incluyen los datos de estudios anti-
PD1/CTLA4.
ES (95%)
Heterogeneity among the studies (I2 = 0%, p= 0.634)
Wang A. Eur J Sur Oncol 2015
Inmunocompetencia en Ca.Pulmón
Azuma k. Eur J SAnn Oncol 2014
Chen N. J. Thorac Oncol 2015
•EGFR regula la expresi´n de PD-L1, n=166 pts.
En líneas celulares de NSCLC con mutación de
EGFR la de-fosforilación del receptor se
acompaña de un descenso en los niveles de
expresión de PDL1. MHC-TCR
PDL1-PD1
erk akt
PD-L1
EGFRmt
TCD4 Tumor
Antigenicidad/Inmunocompetencia en Ca.Pulmón
Respuesta clínica
Inmunoterapia PD-1/PD-L1
Inmunoterapia en Ca.Pulmón
Rizvi N, A. Science 2015
34 pts NSCLC PD1inh
Pembrolizumab
16 PD1inh 18 PD14inh
7
9
DNA exon genome seq 94.5% target sequence
Long term response No benefit
7
11
Bioinformatic analysis of mutation burden and predicted MHCI restricted neoantigens
Discovery cohort
DCB NCB p val
Pts 7 9
m#mut 209
m#mut 302 148 0.02
Validation cohort
DCB NCB p val
Pts 7 11
m#mut 200
m#mut 244 125 0.04
DCB ORR p val PFS p val
>209mut 73% 63% 0.03
14.5m 0.01
HR:0.19
(0.05-0.7) <209mut 13% 0% 3.7m
DCB ORR p val PFS p val
>200mut 83% NA NR 0.006
HR0.15
(0.04-
0.59) <200mut 22% NA 3.4m
Discovery cohort Validation cohort
DCB: durable clinical benefit, NCB: no clinical benefit, m#mut: median number of mutations, ORR: objective response rate, PFS: progression free survival
NDB (Mann-Whitney P = 0.01 for both) (fig. S5).
A previously validated binary classifier to identi-
fy the molecular signature of smoking (17) was
applied to differentiate transversion-high (TH,
smoking signature) from transversion-low (TL,
never-smoking signature) tumors. Efficacy was
greatest in patients with tumors harboring the
smoking signature. The ORR in TH tumors was
56% versus 17% in TL tumors (Fisher ’s exact P =
0.03); the rateof DCB was77%versus22%(Fisher’s
exact P = 0.004); the PFS was also significantly
longer in TH tumors (median not reached versus
3.5 months, log-rank P = 0.0001) (Fig. 2A). Self-
reported smoking history did not significantly
discriminate those most likely to benefit from
pembrolizumab. The rates of neither DCB nor
PFS were significantly different in ever-smokers
versus never-smokers (Fisher’s exact P = 0.66 and
log-rank P = 0.29, respectively) or heavy smokers
(median pack-years>25) versus light/never smokers
(pack-years≤25) (Fisher’s exact P = 0.08 and log-
rank P= 0.15, respectively). Themolecular smoking
signature correlated more significantly with non-
synonymous mutation burden than smoking his-
tory (fig. S6, A and B).
Although carcinogens in tobacco smoke are
largely responsible for the mutagenesis in lung
cancers (19), the wide range of mutation burden
within both smokers and never-smokers impli-
cates additional pathways contributing to the
accumulation of somatic mutations. We found
deleterious mutations in a number of genes that
are important in DNA repair and replication. For
example, in three responders with the highest
mutation burden, we identified deleterious mu-
tations in POLD1, POLE, and MSH2 (Fig. 3). Of
particular interest, a POLD1E374K mutation was
identified in a never-smoker with DCB whose tu-
mor harbored the greatest nonsynonymous muta-
tion burden (n = 507) of all never-smokers in our
series. POLD1Glu374 lies in the exonuclease proof-
reading domain of Pol d (20), and mutation of
this residue may contribute to low-fidelity repli-
cation of the lagging DNA strand. Consistent with
this hypothesis, this tumor exome had a relatively
low proportion of C-to-A transversions (20%) and
predominance of C-to-T transitions (51%), similar
to other POLD1 mutant, hypermutated tumors
(21) and distinct from smoking-related lung can-
cers. Another responder, with the greatest muta-
tion burden in our series, had a C284Y mutation
in POLD1, which is also located in the exonu-
clease proofreading domain. We observed non-
sense mutations in PRKDC, the catalytic subunit
of DNA-dependent protein kinase (DNA-PK),
and RAD17. Both genes are required for proper
DNA repair and maintenance of genomic integ-
rity (22, 23).
Genes harboring deleterious mutations com-
mon to four or moreDCB patientsand not present
in NDB patients included POLR2A, KEAP1, PAPPA2,
PXDNL, RYR1, SCN8A, and SLIT3. Mutations in
KRAS were found in 7of 14 tumors from patients
with DCB compared to 1of 17 in the NDB group,
a finding that may be explained by the asso-
ciation between smoking and the presence of
KRAS mutations in NSCLC (24). There were no
mutations or copy-number alterations in antigen-
presentation pathway–associated genes or CD274
SCI EN CE sciencemag.org 3 APRI L 2015 • VOL 348 I SSUE 6230 125
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Discovery Cohort Validation Cohort
Months
All Tumors
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Fig. 1. Nonsynonymous mutat ion burden associated with clinical bene-
f it of ant i–PD-1 therapy. (A) Nonsynonymous mutation burden in tumors
from patients with DCB (n = 7) or with NDB (n = 9) (median 302 versus
148, Mann-Whitney P = 0.02). (B) PFS in tumors with higher nonsynony-
mous mutation burden (n = 8) compared to tumors with lower nonsynony-
mous mutation burden (n = 8) in patients in the discovery cohort (HR 0.19,
95% CI 0.05 to 0.70, log-rank P = 0.01). (C) Nonsynonymous mutation
burden in tumors with DCB (n = 7) compared to those with NDB (n = 8) in
pat ients in the validat ion cohort (median 244 versus 125, Mann-Whitney
P = 0.04). (D) PFS in tumors with higher nonsynonymous mutation burden
(n = 9) compared to those with lower nonsynonymous mutat ion burden
(n = 9) in pat ients in the validat ion cohort (HR 0.15, 95% CI 0.04 to 0.59,
log-rank P = 0.006). (E) ROC curve for the correlat ion of nonsynonymous
mutat ion burden with DCB in discovery cohort. AUC is 0.86 (95% CI 0.66
to 1.05, null hypothesis test P = 0.02). Cut-off of ≥178 nonsynonymous mu-
tations is designated by triangle. (F) Nonsynonymous mutation burden in
patients with DCB (n = 14) compared to those with NDB (n = 17) for the
ent ire set of sequenced tumors (median 299 versus 127, Mann-Whitney P =
0.0008). (G) PFS in those with higher nonsynonymous mutation burden
(n = 17) compared to those with lower nonsynonymous mutat ion burden
(n = 17) in the entire set of sequenced tumors (HR 0.19, 95% CI 0.08-0.47,
log-rank P = 0.0004). In (A), (C), and (F), median and interquartile ranges of
total nonsynonymous mutations are shown, with individual values for each
tumor shown with dots.
RESEARCH | REPORTS
Inmunoterapia en Ca.Pulmón
Carga de mutaciones no sinónimas se asocia a el beneficio del tratamiento con
inh. PD1
Rizvi N, A. Science 2015
Rizvi N, A. Science 2015
•Firma molecular de hábito tabáquico se
asocia de forma significativa con PFS en
NSCLC.
•Carga de mutaciones, respuesta clínica y factores que contribuyen a la carga mutacional.
HR 0.15, 95% 0.06-0.39, p=0.0001
Inmunoterapia en Ca.Pulmón
Rizvi N, A. Science 2015
•Neoantígenos candidatos, respuesta T-específica y respuesta a pembrolizumab.
Inmunoterapia en Ca.Pulmón
Latest advances with immune-based anti-tumor therapies in NSCLC
Management of Cancer in the Post Anti–PD-1/PD-L1 Era
Anti–PD-1/anti–PD-L1
Generate T cells:
+ Anti–CTLA-4
+ Immune-activating antibodies
or cytokines
+ TLR agonists or oncolytic
viruses
+ IDO or macrophage inhibitors
+ Targeted therapies
Bring T cells
into tumors:
Vaccines
TCR-engineered ACT
CAR-engineered ACT
Adapted From CCO Oncology
Desarrollo clínico de anti-PD-1 en tumores sólidos
Agente Molécula Desarrollo clínico
Nivolumab IgG4 human
Aprobado en melanoma y Sq-NSCLC avanzado en progresion a primera linea
Fase III en múltiples tumores(NSCLC, Melanoma, Renal, CyC, GBM, Gástrico)
Pembrolizumab IgG4
humanized
Aprobado en melanoma y NSCLC PD-L1+ Fases III múltiples tumores (SCyC, NSCLC, Melanoma,
Vejiga, Gástrico)
Pidilizumab IgG1
humanized Fase II múltiples tumores (pancreas, CRC, Renal, Próstata,
Gliomas)
AMP-224 Fc & PD-L2
fusion Fase I
Agente Molécula Desarrollo clínico
MEDI4736 (durvalumab)
Engineered human IgG1 Fase III múltiples tumores (NSCLC, CyC)
MPDL3280A (atezolizumab)
Engineered human IgG1 Fase III múltiples tumores (NSCLC, Vejiga,
Renal, TNBC)
MSB0010718C (avelumab)
Fully human IgG1 Fase III (NSCLC)
Desarrollo clínico de anti-PD-L1 en tumores sólidos
Diana Agente Molécula Desarrollo clínico
CTLA-4
Ipilimumab Humanized IgG1 Aprobado en melanoma avanzado.
Fase III múltiples tumores (Melanoma, NSCLC, SCLC, Próstata, GBM, Renal)
Tremelimumab Fully human IgG2 Fase III múltiples tumores (SCyC, NSCLC)
IDO
INCB024360 Small-molecule
inhibitor Fase II múltiples tumores (Ovario,
Melanoma)
NLG919 Small-molecule
inhibitor Fase I
B7-H3 MGA271 Humanized IgG1kappa Fase I
LAG-3 BMS-986016 --- Fase I
Desarrollo clínico de otros inhibidores de inmuno-checkpoints en tumores sólidos
Nivolumab
A Phase III Study (CheckMate 017) of Nivolumab (Anti-Programmed Death-1)
vs Docetaxel in Previously Treated Advanced or Metastatic Squamous (SQ) cell Non-small Cell Lung Cancer (NSCLC)
David R. Spigel,1 Karen Reckamp,2 Naiyer Rizvi,3 Elena Poddubskaya,4 Howard West,5 Wilfried Ernst Erich Eberhardt,6 Paul Baas,7 Scott J. Antonia,8 Adam Pluzanski,9 Everett E.
Vokes,10 Esther Holgado,11 David Waterhouse,12 Neal Ready,13 Justin Gainor,14 Osvaldo Arén Frontera,15 Leora Horn,16 Luis Paz-Ares,17 Christine Baudelet,18 Brian Lestini,18 Julie
Brahmer19
Stage IIIb/IV SQ NSCLC
1 prior PT-DC, ECOG PS 0–1, pre-treatment (archival or fresh) tumor samples required for PD-L1 analysis
N = 272
Nivolumab 3 mg/kg IV Q2W
n = 135 Until PD or unacceptable
toxicity
Docetaxel 75 mg/m2 IV Q3W
n = 137 Until PD or
unacceptable toxicity
Primary endpoint: OSa
Additional endpoints: ORR (investigator-assessed), PFSa (investigator-assessed), correlation between PD-L1 expression and efficacy, safetyb, quality of life (LCSS)
Randomized 1: 1
• DMC recommended early termination of study based on pre-specified interim analysis showing superior OS of nivolumab over docetaxel.
• Updated safety and longer term survival (18 month) are reported here.
Stratification factors: region,
prior paclitaxel use
Time (months)
Nivolumab n = 135
Docetaxel n = 137
mOS mo,
(95% CI)
9.2 (7.3, 13.3)
6.0 (5.1, 7.3)
# events 86 113
HR = 0.59 (95% CI: 0.44, 0.79), p= 0.00025
Nivolumab
Docetaxel
1-yr OS rate = 42%
1-yr OS rate = 24%
OS
(%)
24
21
18
15
12
9 6 3 0
100
90
80
70
60
50
40
30
10
0
20
CheckMate 017
OS 90 80 70 60 50 40 30
10 0
20
Nivolumab
Docetaxel
Time (months)
1-yr PFS rate = 21%
1-yr PFS rate = 6.4%
PFS
(%
)
24
21
18
15
12
9 6 3 0
100
Nivolumab n = 135
Docetaxel n = 137
mPFS, mo (95% CI)
3.5 (2.1, 4.9)
2.8 (2.1, 3.5)
HR = 0.62 (95% CI: 0.47, 0.81); p = 0.0004
SLP
Aprobación de Nivolumab por la FDA y EMA en CNMP escamoso
metastásico tras progresión a QT basada en platino, basándose
en los datos del CheckMate-063 y -017
Phase 3, Randomized Trial (CheckMate 057) of Nivolumab vs Docetaxel in Advanced Non-Squamous (Non-SQ) Non-Small Cell Lung Cancer (NSCLC): Subgroup Analyses and
Patient-Reported Outcomes (PROs)
Leora Horn,1 Julie Brahmer,2 Martin Reck,3 Hossein Borghaei,4 David R. Spigel,5 Martin Steins,6 Neal E. Ready,7 Laura Q. Chow,8 Everett E. Vokes,9 Enriqueta
Felip,10 Esther Holgado11, Fabrice Barlesi,12 Martin Kohlhäufl,13 Marco Angelo Burgio,14 Jerome Fayette,15 Scott N. Gettinger,16 Christopher T. Harbison,17 Ang
Li,17 Friedrich Graf Finckenstein,17 Luis Paz-Ares18
CheckMate 057
• Pretreatment (archival or recent) tumor samples required for measurement of PD-L1 expression
• Fully validated with analytical performance having met all pre-determined acceptance criteria for sensitivity, specificity, precision, and robustness
46
Ran
do
miz
e 1
:1
• Stage IIIB/IV non-SQ NSCLC
• ECOG PS 0–1
• Failed one prior platinum- based chemotherapy
• Prior maintenance therapy alloweda
• Prior TKI therapy allowed for known ALK translocation or EGFR mutation
(N = 582)
Nivolumab 3 mg/kg IV Q2W
until PD or unacceptable toxicity
(n = 292)
Docetaxel 75 mg/m2 IV Q3W
until PD or unacceptable toxicity
(n = 290)
• Primary end pointb
– OS • Additional end pointsc
– ORR – PFS
– Safety – Efficacy by tumor PD-L1
expression – PROs (LCSS)
Patients stratified by prior maintenance therapy and line of therapy (second-line vs third-line)
aMaintenance therapy included pemetrexed, bevacizumab, or erlotinib (not considered a separate line of therapy). bUpdated based on a July 2, 2015, DBL. cBased on a March 18, 2015, DBL, with OS by PD-L1 expression updated as of July 2, 2015.
LCSS = Lung cancer symptom scale.
Nivo (n = 292) Doc (n =
290)
mOS, mos 12.2 9.4
1-yr OS rate, % 51 39
HR (96% CI) = 0.73 (0.59, 0.89) p = 0.0015
100
90
80
70
60
50
40
30
10
0
20
27 18 15 9 6 21 12 3 0 24 30
Nivolumab
Docetaxel
18-mo OS rate = 23%
18-mo OS rate = 39%
1-yr OS rate = 39%
1-yr OS rate = 51%
Time (mos)
OS
(%
)
Nivolumab
Docetaxel
No. of patients at risk (18-mo OS)b 292 233 195 171 148 128 107 55 4 27
290 244 194 150 111 89 61 23 4
0
0 6
Nivolumab
Docetaxel
292 232 194 169 146 123 62 32 0 9
290 244 194 150 111 88 34 10 0 5
0
0
• Minimum follow-up for 12-mo OS rate, 13.2 mos; for 18-mo OS rate, 17.1 mos
47
CheckMate 057 Overall Survival
PD-L1 Expression Level Median OS
Nivolumab, mos
Median OS
Docetaxel, mos
Unstratified HR
(95% CI)
Interaction
P Value
≥ 1%
< 1%
17.2
10.4
9.0
10.1
0.59 (0.43-0.82)
0.90 (0.66-1.24) .0646
≥ 5%
< 5%
18.2
9.7
8.1
10.1
0.43 (0.30-0.63)
1.01 (0.77-1.34) .0004
≥ 10%
< 10%
19.4
9.9
8.0
10.3
0.40 (0.26-0.59)
1.00 (0.76-1.31) .0002
Aprobación por la FDA de Nivolumab para CNMP no escamoso
tras progresión a QT basada en platino, con los datos del
CheckMate-057
Pembrolizumab
KEYNOTE-001: Subanalysis of Phase I Pembrolizumab Trial in NSCLC
• Administered tumor assessment: imaging every 9 wks
• Primary: RECIST v.1.1 (independent central review)
• Secondary: immune-related response criteria (irRC; investigator assessed)
• Tumor biopsy
• Tumor biopsy within 60 days prior to first dose of pembrolizumab required
• Tumor PD-L1 expression determined by prototype assay to inform enrollment; Samples were independently reanalyzed using clinical trial IHC assay
Garon EB, et al. N Engl J Med. 2015 Apr 19. [Epub ahead of print]
Treatment-naive or
previously treated
advanced NSCLC
(N = 495)
Pembrolizumab IV
2 mg/kg q3w (n = 6)
Mandatory tumor biopsy
Pembrolizumab IV 10 mg/kg q3w (n = 287)
Pembrolizumab IV
10 mg/kg q2w (n = 202)
CR, PR, SD
PD, unacceptable
AE, or investigator
decision
Continue dosing
and assessments
every 9 wks
Off study
100
80
60
40
20
0
Keynote-001: Pembrolizumab Efficacy in Overall Population
PFS OS 100
80
60
40
20
0
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Mos
PF
S, %
OS
, %
0 4 8 12 16 20 24
Mos
28
ORR by RECIST, % (95% CI) N All Cohorts
Total 495 19.4 (16.0-23.2)
Treatment naive 101 24.8 (16.7-34.4)
Previously treated 394 18.0 (14.4-22.2)
Nonsquamous 401 18.7 (15.0-22.9)
Squamous 85 23.5 (15.0-34.0)
All patients
Previously treated
Treatment-naïve
All patients
Previously treated
Treatment-naïve
Garon EB, et al. N Engl J Med. 2015;372:2018-2028.
Keynote-001: Pembrolizumab Efficacy by PD-L1 Expression
PFS OS
Proportion score for 356 pts in training, validation groups with slides sectioned ≤ 6 months of staining
100
80
60
40
20
0
PF
S, %
100
80
60
40
20
0
OS
, %
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Months
0 4 8 12 16 20 24
Months
28
PS ≥ 50% (n = 119)
PS < 1% (n = 76)
PS 1 - 49% (n = 161)
PS ≥ 50% (n = 119)
PS < 1% (n = 76)
PS 1 - 49% (n = 161)
ORR by RECIST, % (95% CI) N All Cohorts
Percent PD-L1 staining
≥ 50% 73 45.2 (33.5-57.3)
1% - 49% 103 16.5 (9.9-25.1)
< 1% 28 10.7 (2.3-28.2)
Garon EB, et al. N Engl J Med. 2015;372:2018-2028.
Aprobación de Pembrolizumab por la FDA en CNMP metastásico
con expresión de PD-L1 tras progresión a QT basada en platino
bsándose en los datos del KEYNOTE-001
Atezolizumab
Spira A, et al ASCO 2015
Efficacy, safety and predictive biomarker from a randomized phase II study comparing atezolizumab (MPL3280A) vs. docetaxel in 2L/3L NSCLC (POPLAR)
Spira A, et al ASCO 2015
(MPL3280A) vs. docetaxel in 2L/3L NSCLC (POPLAR)
Toxicidad IT
Toxicidad
Melero I et al. Clin Cancer Res 2013.
Cinética
Weber JS et al. J Clin Oncol 2012.
Treatment-related AEs > 10% pts
057
Nivolumab (n = 287)
Docetaxel (n = 268)
Any grade
Grade 3–4a
Any grade
Grade 3–4a
Percentage (%) of patients with an event
Any event 69 10 88 54
Fatigue 16 1 29 5
Nausea 12 1 26 1
Decreased appetite
10 0 16 1
Asthenia 10 <1 18 2
Diarrhea 8 1 23 1
Peripheral edema
3 0 10 <1
Myalgia 2 <1 11 0
Anemia 2 <1 20 3
Alopecia <1 0 25 0
Neutropenia <1 0 31 27
Febrile neutropenia
0 0 10 10
Leukopenia 0 0 10 8
Treatment related AEs…
Leading to discontinuation %
5 4 15 7
Death % 0 <1
017
Nivolumab (n = 131)
Docetaxel (n = 129)
Any grade
Grade 3–4
Any grade
Grade 3–4
Percentage (%) of patients with an event
Any event 59 8 87 56
Fatigue 16 1 33 8
Nausea 9 0 23 2
Decreased appetite
11 1 19 1
Asthenia 12 0 14 4
Diarrhea 8 1 20 2
Peripheral neuropathy
1 0 12 2
Myalgia 2 0 10 0
Anemia 2 0 22 3
Alopecia 0 0 22 1
Neutropenia 1 0 33 30
Febrile neutropenia
0 0 11 10
Treatment related AEs…
Leading to discontinuation %
5 3 10 7
Death % 0 2
Garon EB. New Engl J Med 2015
Pembrolizumab NSCLC Safety Profile
Differential diagnosis
- Infectious diseases Pneumocystis jirovecii, Clostridium difficile, salmonella, viral hepatitis… - Tumor progression Linfangitis, liver metastases… - Other drugs - Others Crohn’s disease, radiation pneumonitis…
General principles
Robert C. ESMO Meeting 2014.
Special situations
- Colitis: Infliximab (anti-TNF-α) 5mg/kg iv (maximum 2-3 doses) Octeotride 100-200µg tds if high volume liquid diarrhea Colectomy
- Hepatitis: Mycophenolate mofetil 1g BD po
- Endocrine: Propranolol, levothyroxine, steroids as replacement therapy, insuline…
- Uveitis: 1% Prednisolone acetate (1 drop/1-2h)
- Neurologic: IVIg 0.4g/kg x 5 days (Guillain-Barré syndrome)
- Cytokine release syndrome: Tocilizumab 4-8mg/kg iv
Toxicity
Endocrinologist
Endocrinologist
Gastroenterologist
Neurologist
Ophtalmologist
Hepatologist
Pneumologist
Dermatologist
Infectologist
ONCOLOGIST
Adapted from Melero I et al. Clin Cancer Res 2013.
Intensive care
Futuro
Nat Rev Clin Oncol. 2015 Nov 24.
Nat Rev Cancer. 2015 Aug;15(8):457-72
Nat Rev Cancer. 2015 Aug;15(8):457-72
α-OX40
Radiotherapy
Chemotherapy
Vaccination
T-reg depletion/
inactivation
Adoptive T-cell
immunotherapy
–Clinical Standard
–Clinical Trials
–Preclinical Studies
Antiangiogenic
therapy
α-TIM-3
α-LAG3
α-CTLA-4
α-CD137
α-PD1
α-PD-L1
α-CD40
Virotherapy
Conclusiones
CONCLUSIONES
• A pesar del optimismo lógico del empleo de la inmunoterapia en cáncer, nos ha costado 50 años desarrollar una estrategia terapéutica realmente eficaz y segura.
• Varios fármacos similares compitiendo en el mismo área terapéutica
• Las terapias inmunes actuales, muy a nuestro pesar, no son aplicables a todos los pacientes: RR en torno al 20%
• En 2ª línea aumenta la SG, menor toxicidad en comparación con Docetaxel (brazo control)
• Mayores tasas de respuesta en pacientes PD-L1 + (excepto en Chackemate 017)
• Necesidad de biomarcadores para seleccionar y optimizar los recursos.
• A pesar del perfil de toxicidad favorable es “vital” identificar y tratar los efectos secundarios de forma precoz
