Post on 19-Jan-2021
IMUNOTERAPIA NO CÂNCER DE PULMÃO: PRINCÍPIOS
Dr. Gilberto de Castro Junior Professor Colaborador Livre-Docente – Faculdade de Medicina da USP. Serviço de Oncologia Clínica - Instituto do Câncer do Estado de São Paulo Centro de Oncologia - Hospital Sírio Libanês Grupo Brasileiro de Oncologia Torácica – GBOT/LACOG São Paulo - BRASIL
Potenciais conflitos de interesses
Apoio em participação de eventos de cunho científico Roche, AstraZeneca, MSD, BMS, Boehringer-Ingelheim,
Novartis, Bayer, Eurofarma
Dr. Gilberto de Castro Junior CRM:84448
Investigador de ensaios clínicos patrocinados Investigador de ensaios clínicos patrocinados
Aulas e apresentações Roche, AstraZeneca, BMS, MSD, Merck Serono,
Eurofarma, Pfizer
Consultorias científicas Roche, AstraZeneca, MSD, Merck Serono, Eurofarma,
Boehringer-Ingelheim, Pfizer
Kandoth et al. Nature 2013
Mutational landscape across 12 major cancer types
Pardoll. Nat Rev Cancer 2012
T cell activation in lymph node
Ribas. NEJM 2015
T cell activation in tumor milieu
Ribas. NEJM 2015
A Via do PD-L1 inibindo a Resposta Imune
MHC
PD-L1
PD-1 PD-1
PD-1 PD-1
Nivolumab PD-1 Receptor Blocking Ab
Recognition of tumor by T cell through MHC/antigen interaction mediates IFNγ release
and PD-L1/2 up-regulation on tumor
Priming and activation of T cells through MHC/antigen & CD28/B7 interactions with
antigen-presenting cells
T-cell receptor
T-cell receptor
PD-L1 PD-L2
PD-L2
MHC
CD28 B7
T cell
NFκB Other
PI3K Dendritic
cell Tumor cell
IFNγ
IFNγR
Shp-2
Shp-2
http://www.ackc.org/nivolumab-mechanism-cartoon/
PD-L1 Expression Associated with Favorable Outcome With Pembrolizumab
1. Garon EB et al. N Engl J Med 2015;372:2018-28.
• TPS ≥50% cutpoint rigorously determined using independent training and validation sets derived from KEYNOTE-0011
• PD-L1 IHC 22C3 pharmDx (Dako) approved in the US as a companion diagnostic for pembrolizumab
Negative TPS 1%–49% TPS ≥50%
20x
40x
Keynote 010: PD-L1 Expression Correlates with improved OS in Advanced NSCLC
Imagens de IHC images de três amostras diagnósticas anti-PDL-1
Marianne J. Ratcliffe et al. Clin Cancer Res 2017;23:3585-3591
PD-L1 expression on tumor cells
Journal of Thoracic Oncology Vol. 12 No. 2: 208-222
Each dot represents the mean score of 3 pathologists
0
10
20
30
40
50
60
70
80
90
100
% T
um
or
Sta
inin
g
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39
Cases
SP263SP14228-822C3
Conclusion 1: 3 assays showed similar staining
characteristics for PD-L1 staining on tumor cells, but
SP142 comparatively showed less tumor cells stained
David P Carbone et al. N Engl J Med 2017; 376:2415-2426
Phase 3 CheckMate 026 Study Design: Nivolumab vs Chemotherapy in First-line NSCLC
Primary endpoint: PFS per BIRC (≥5% PD-L1+)
Secondary endpoints:
•PFS per BIRC (≥1% PD-L1+)
•OS
•ORR
Exploratory objective: Predictive biomarkers for outcomes with nivolumab
Nivolumab 3 mg/kg IV Q2W
n = 271
Randomize 1:1
Key eligibility criteria:
• Stage IV or recurrent NSCLC
• No prior systemic therapy for advanced disease
• No EGFR/ALK mutations sensitive to available targeted inhibitor therapy
• ≥1% PD-L1 expression Chemotherapy
(histology dependent) Maximum of 6 cycles
n = 270
Disease progression or unacceptable toxicity
Disease progression
Crossover nivolumab (optional)
Tumor scans Q6W until week 48 then Q12W
Stratification factors at randomization:
• PD-L1 expression (<5% vs ≥5%)
• Histology (squamous vs non-squamous)
An exploratory analysis was conducted in CheckMate 026 to test the hypothesis that patients with high TMB may derive enhanced benefit from nivolumab
Exploratory TMB Methods CheckMate 026 TMB Analysis: Nivolumab in First-line NSCLC
N3
Whole exome sequencinga
Tumor DNA
Germline DNA (blood)
Somatic missense mutations
Tumor exome data
Germline exome data
TMB
Sample size throughout TMB determination
Patients, n (%) Tumor DNA Germline
DNA
Randomized 541 (100) 541 (100)
Samples available for DNA extractiona 485 (90) 452 (84)
DNA available for sequencing 408 (75) 452 (84)
Successful preparation of next-generation sequencing library
402 (74) 452 (84)
Passed internal quality controlb
320 (59) 432 (80)
Matched tumor-germline exome sequences for TMB analysisc
312 (58)
aSamples were not available for various reasons, including but not limited to lack of patient pharmacogenetic consent, samples exhausted for PD-L1 testing, or poor tissue sampling bInternal quality control failure included factors such as discordance between tumor and germline DNA, too few sequence reads, and low or uneven target region coverage c8 patients with available tumor DNA sequences did not have matched germline DNA sequences
aDNA was sequenced on the Illumina HiSeq 2500 using 2 × 100-bp paired-end reads; an average of 84 and 89 million reads were sequenced per tumor and germline sample, respectively (average 84.6 × and 93 × the mean target coverage, respectively)
David P Carbone et al. N Engl J Med 2017; 376:2415-2426
PFS by Tumor Mutation Burden Tertile CheckMate 026 TMB Analysis: Nivolumab in First-line NSCLC
100
90
80
70
60
50
40
30
20
10
0
0 3 6 9 12
Months
15 18 21 24
PF
S (
%)
High
Low
Medium
Medium n = 49 n = 47
3.6
(2.7, 6.9)
Low n = 62
4.2
(1.5, 5.6)
9.7
(5.1, NR)
Median PFS, months
(95% CI)
High
Nivolumab Arm Chemotherapy Arm
Medium n = 53 n = 60
6.5
(4.3, 8.6)
Low n = 41
6.9
(5.4, NR)
5.8
(4.2, 8.5)
Median PFS, months
(95% CI)
High 100
90
80
70
60
50
40
30
20
10
0
0 3 6 9 12
Months
15 18
High
Low
Medium
21
Data for patients with low and medium TMB were pooled in subsequent analyses
David P Carbone et al. N Engl J Med 2017; 376:2415-2426
Characteristic
High TMB (n = 107)
Low/medium TMB (n = 205)
Median age, years (range) 65 (40, 87) 65 (32, 89)
Female, % 36.4 42.0
ECOG PS, % 0 1/2
31.8
67.3/0.9
32.2
66.3/1.0
Smoking status, % Current smoker Former smoker Never smoker
22.4 73.8 2.8
15.6 70.2 12.7
Disease stage, % Stage IV Recurrent
91.6 7.5
94.1 5.9
Tumor histology, % Squamous Non-squamous
29.0 71.0
19.5 80.5
PD-L1 expression level, % ≥5% ≥25% ≥50%
77 60 45
83 59 40
Baseline Characteristics According to TMB Subgroup- CheckMate 026 TMB Analysis:
Nivolumab in First-line NSCLC
N3
500
300
1000
10
50
100
200
Current Former
Smoking Status
Never Unknown
No
. o
f M
iss
en
se
Mu
tati
on
s 400
David P Carbone et al. N Engl J Med 2017; 376:2415-2426
Anti-PDL1 + anti-CTLA4
Anti-PDL1 + anti-CTLA4
N3
• CTLA-4 inhibition may also induce compensatory signals, including PD-L1 upregulation, that in turn dampen the immune response
• PD-L1 expression reduces T-cell activation by binding to two important regulatory receptors:
- Binding to PD-1 delivers an inhibitory signal that reduces cytokine production and T-cell proliferation
- Binding to CD80, further reduces CD28 co-stimulation of T cells
• PD-L1 blockade may overcome this immune checkpoint, resulting in prolonged T-cell activation
Combinação anti-CTLA4 & anti-PD1
Tumour cell
T cell
PD-L1
TCR
MHC
PD-1 PD-L1 PD-1
CD80
CD80
Inhibition
CD80
Inhibition
Inhibition
Inhibition
Activation
TCR MHC
PD-L1
CD80
CD86
CTLA-4
CD28
Inhibition
Activation
Tumour antigen
Immune
cell
Combinação anti-CTLA4 & anti-PD1
Tumour cell
T cell
PD-L1
PD-1 PD-L1 PD-1
Activation
CD80 CD80
CD80
CD86 CTLA-4
CD28 Activation
Anti-CTLA4
Anti-CTLA4 blocks CTLA-4 binding to CD80 and CD86
–
TCR MHC
Anti-PD(L)1
–
Anti-PD(L)1
Blocking PDL1-PD1 & PDL1-CD80 interaction
PD-L1
CD80
TCR MHC
Tumour antigen
Immune cell
Inhibition
–
–
Combinação anti-CTLA4 & anti-PD1
N3
Das et al. J Immunol 2015
Munn, Mellor. J Clin Invest 2007
Indoleamina 2,3-dioxigenase
• Epacadostat is an oral inhibitor of IDO1
• Phase 1/2 study
- Safety and efficacy of oral epacadostat plus IV nivolumab in pts with advanced tumors
• No DLT was observed in P1 (36 pts)
• Most common TRAEs (≥15%) in pts treated with E 100 mg (n = 70) and E 300 mg (n = 135) were rash (33% and 22%), fatigue (26% and 31%), and nausea (24% and 19%).
• For the 23 SCCHN pts treated with E 300 mg, preliminary DCR was 70% (n = 16).
• Of 30 MEL pts, 8 were treated with E 100 mg and 22 with E 300 mg. ORR 75% (n = 6; all PR) and and DCR 100% (n = 8; 2 SD) (E 100 mg).
Perez et al. ASCO 2017
ECHO-204 trial
• Como identificar os pacientes candidatos?
- Biomarcadores preditivos
• Emergência da resistência ao tratamento
- Diagnóstico e tratamento
• Identificação e tratamento de toxicidades
- Educação da equipe e do paciente
• Custo da medicação e acesso
- Farmacoeconomia: custo-efetividade local
Desafios