Checkpoint inhibition e tumori - Romano Danesi Farmacologia Università di Pisa - Milano 5.7.2018
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Checkpoint inhibition e tumori
Romano Danesi
Farmacologia
Università di Pisa
Progetto Formativo SIE 2018 - 2019
LE NUOVE IMMUNOTERAPIE IN EMATOLOGIA
Hilton Milan Hotel, Milano, 5 luglio 2018
DICHIARAZIONE
Relatore: Romano Danesi
Come da nuova regolamentazione della Commissione Nazionale per la Formazione Continua del Ministero della Salute, è richiesta la trasparenza
delle fonti di finanziamento e dei rapporti con soggetti portatori di interessi commerciali in campo sanitario.
• Posizione di dipendente in aziende con interessi commerciali in campo sanitario (NIENTE DA DICHIARARE)
• Consulenza ad aziende con interessi commerciali in campo sanitario (NIENTE DA DICHIARARE)
• Fondi per la ricerca da aziende con interessi commerciali in campo sanitario (Pfizer, Novartis, AstraZeneca, Sanofi)
• Partecipazione ad Advisory Board (Pfizer, Novartis, AstraZeneca, Sanofi)
• Titolarietà di brevetti in compartecipazione ad aziende con interessi commerciali in campo sanitario (NIENTE DA DICHIARARE)
• Partecipazioni azionarie in aziende con interessi commerciali in campo sanitario (NIENTE DA DICHIARARE)
2
A diagram depicting the tumor microenvironment TL Whiteside. Oncogene (2008) 27, 5904–5912 3
Expression and function of NOS isoforms Bogdan C. Nat Immunol 2001;2(10):907-16 4
Overview of immune-system NO function Bogdan C. Nat Immunol 2001;2(10):907-16 5
Tumors recruit MSC from the bone marrow TL Whiteside. Oncogene (2008) 27, 5904–5912 6
Accumulation and expansion of Treg in the tumor
microenvironment
7
TL Whiteside. Oncogene (2008) 27, 5904–5912
Mechanisms for ‘immunoediting’ of tumor cells
in the microenvironment
8
TL Whiteside. Oncogene (2008) 27, 5904–5912Mechanisms orchestrated by the tumor that contribute to its
escape from the host immune system
• Interference with the induction of anti-tumor
immune responses
– Decreased expression of costimulatory molecules on the
tumor or APC
– Alterations in TCR signaling in TIL
– Death receptor/ligand signaling and ‘tumor counterattack’
– Dysfunction of DC and inadequate cross-presentation of
tumor-associated antigens to T cells
– DC apoptosis in the tumor microenvironment
TL Whiteside. Oncogene (2008) 27, 5904–5912
9Mechanisms orchestrated by the tumor that contribute to its
escape from the host immune system
• Inadequate effector cell function in the tumor
microenvironment
– Suppression of T-cell responses by Treg
– Suppression of immune cells by myeloid suppressor cells
(MSC)
– Apoptosis of effector T cells in the tumor and in the
periphery
– Microvesicles (MV, exosomes) secreted by human tumors
and inducing apoptosis of CD8+ effector T cells
TL Whiteside. Oncogene (2008) 27, 5904–5912
10Mechanisms orchestrated by the tumor that contribute to its
escape from the host immune system
• Insufficient recognition signals
– Downregulation of surface expression of HLA
molecules on tumor cells
– Downregulation of surface TAA displayed by tumor
cells: antigen loss variants
– Alterations in APM component expression in tumor
cells or APC
– Suppression of NK activity in the tumor
microenvironment
TL Whiteside. Oncogene (2008) 27, 5904–5912
11Mechanisms orchestrated by the tumor that contribute to its
escape from the host immune system
• Development of immunoresistance by the
tumor
– Lack of susceptibility to immune effector cells
– Immunoselection of resistant variants
– Tumor stem cells
TL Whiteside. Oncogene (2008) 27, 5904–5912
12What is Tumor Mutational Burden (TMB)?
Tumor mutational burden
(TMB) is the total number of
mutations per coding area of
a tumor genome.
Rizvi et al. Mutational landscape determines
sensitivity to PD-1 blockade in non-small cell
lung cancer. Science. 2015;348(6230):124-128
13The landscape of tumor mutation burden
14
Chalmers ZR et al. Genome Medicine (2017) 9:34moAbs targeting PD-1 or PD-L1
(B7-DC-Fc fusion protein)
(durvalumab)
(atezolizumab)
(avelumab)
Kim C. Ohaegbulam et al. Trends Mol Med 2015, Vol. 21, No. 1
15Interactions between PD-1 and anti-PD-1
moAbs
PD-1/PD-L1 PD-1/Pembrolizumab PD-1/Nivolumab
PD-1
PD-L1
binding site Pembro Nivo
binding sites binding sites
Ju Yeon Lee et al. Nature Communica;ons Oct 2016 DOI: 10.1038/ncomms13354
16Interactions between PD-L1 and anti-PD-L1
moAbs
Shuguang Tan et al., Protein Cell DOI 10.1007/s13238-017-0412-8
17Binding kinetics of anti-PD-L1 moAbs
Shuguang Tan et al., Protein Cell DOI 10.1007/s13238-017-0412-8
18Binding affinity (Kd, nM) of PD-1/PD-L1 to their
ligands and blocking antibodies
Kd, nM
PD-1:PD-L1 270-526
PD-1:PD-L2 590
PD-1:nivolumab 2.6
PD-1:pembrolizumab 0.028
PD-L1:atezolizumab 1.75
PD-L1:durvalumab 0.67
PD-L1:avelumab 0.046
PD-L1:BMS-936559 0.83
Kathleen M. Mahoney et al. Clinical Therapeutics, DOI 10.1016/j.clinthera.2015.02.018 ; Shuguang Tan et al. Protein Cell DOI 10.1007/
19
s13238-017-0412-8Comparison table of moAbs anti-PD-1
Nivoluma Pembrolizumab Pidilizumab AMP-224
b
Humanized -- ✓ ✓ --
Fully human ✓ -- -- --
Ig subclass IgG4 IgG4 IgG1 Fusion
protein
ADCC/CDC -- -- ✓ ✓
KD +/++ ++ + ?
20Comparison table of moAbs anti-PD-L1
Atezolizumab Durvaluma Avelumab BMS-93655
b 9
Humanized ✓ -- -- --
Fully human -- ✓ ✓ ✓
Ig subclass IgG1 IgG1 IgG1 IgG4
modified modified
ADCC/CDC -- -- ✓ --
KD +/++ ++ +++ ++
21Schematic representation of target-mediated
drug disposition (TMDD)
Rong Deng et al. Expert Opin. Drug Metab. Toxicol. (2012) 8(2):141-160 22Effect of the antibody affinity (Ka) on total and
free mAb concentration 48 hr after bolus
injection
Kenji Fujimori et al. J NucIMed1990:31:1191-1198 23Determination of representative body weight
for flat-dose calculation
X. Zhao et al. Annals of Oncology 28: 2002–2008, 2017 24Simulated nivolumab Cavg1 across body
weight in patients across tumor types
X. Zhao et al. Annals of Oncology 28: 2002–2008, 2017 25Comparison of summary of exposures in
patients across tumor types
X. Zhao et al. Annals of Oncology 28: 2002–2008, 2017 26Comparison of summary of exposures in
patients across tumor types
X. Zhao et al. Annals of Oncology 28: 2002–2008, 2017 27Conclusions
• Monoclonal antibodies have complex pharmacokinetic and
pharmacodynamic characteristics that are dependent on several
factors.
• Therefore, it is important to improve our understanding of the
pharmacokinetics and pharmacodynamics of monoclonal
antibodies from a basic research standpoint.
• It is also equally important to apply mechanistic
pharmacokinetic/pharmacodynamic models to interpret the
experimental results and facilitate efforts to predict the safety
and efficacy of monoclonal antibodies.
28You can also read
