PD-L1 and Immunotherapy of GI cancers: What do you need to know
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1 None.
2 PD-L1 and Immunotherapy of GI cancers: What do you need to know Rondell P. Graham September 3, MFMER slide-2
3 Disclosure No conflicts of interest to disclose 2017 MFMER slide-3
4 Objectives Define immunotherapy Describe the biology underlying the PD-1/ PD-L1 axis Discuss the available biomarkers for prediction of response to PD-1 axis inhibition Outline the challenges with PD-L1 immunohistochemistry Summarize the role of the diagnostic pathologist in patient selection for immunotherapy 2017 MFMER slide-4
5 Immunotherapy Immunotherapy is a treatment that uses parts of the host immune system to attack a disease 2017 MFMER slide-5
6 Advances in the understanding of immunology Cellular constituents of the immune system How they functioned T-cells TCR and CD28 CTLA MFMER slide-7
7 1. T-cell regulation is complex 2. T-cell regulation is dynamic 2017 MFMER slide-9
8 PD-L1 (programmed cell death ligand-1) Recognized as a T-cell inhibitory protein Binds to PD-1 Promotes effector T-cell exhaustion Promotes persistence of immunosuppressive T-reg Downregulates active tumor immunity in vivo Dong et al, MFMER slide-10
9 1. T-cell regulation is complex 2. T-cell regulation is dynamic 3. PD-1/PD-L1 provides a mechanism of immune evasion 2017 MFMER slide-11
10 Under physiologic conditions The immune system detects foreign antigen Cytotoxic T-cells are generated and traffic to the site Cytotoxic T-cells attack the foreign cells and kill them PD-1/PD-L1 provide brakes to ensure appropriate intensity and scope to cytotoxic activity 2017 MFMER slide-12
11 PD-1 T-cell APC TCR MHC-1 PD-L1 Cancer 2017 MFMER slide-13
12 Targeting the PD-1/PD-L1 axis Requires activated T-cells in the tumor microenvironment A prerequisite for activated T-cells is an immunogenic tumor A tumor with neo-antigens A tumor with a permissive genetic and epigenetic makeup 2017 MFMER slide-14
13 This disrupted the existing order of anti-cancer therapy PD-1/PD-L1 axis therapies do not target the tumor cells Do not focus activation on a particular target on the tumor cells Anti PD-1/PD-L1 therapy is somewhat tumor-type agnostic 2017 MFMER slide-15
14 Biomarkers to predict efficacy of PD-1/PD-L1 blockade PD-L1 expression by immunohistochemistry Mutation associated neoantigens Others 2017 MFMER slide-16
15 Does PD-L1 expression predict clinical response PD-L1 expressed by colorectal, gastric, esophageal, hepatobiliary and pancreatic carcinomas 2017 MFMER slide-17
16 Gastric Pancreatic 2017 MFMER slide-18
17 Does PD-L1 expression predict clinical response Reasonable from the foregoing to believe that PD-L1 expressing tumors should respond to PD-1 axis inhibition Study ORR in PD-L1 positive (%) ORR in PD-L1 negative (%) Topalian et al (2012) 36 0 Grosso et al (2013) Powles et al (2014) Herbst et al (2014) MFMER slide-19
18 Does PD-L1 expression predict clinical response PD-L1 expression correlates with response but does not predict response And there are other issues 2017 MFMER slide-20
19 Issues with PD-L1 expression Antibody variability Observer variability Threshold variability Tumor heterogeneity Differences across tumor types 2017 MFMER slide-21
20 PD-L1 antibody variability Therapy Therapy target Antibody clone Antibody vendor Atezolizumab PD-L1 SP142 Ventana Nivolumab PD Dako/Agilent Pembrolizumab PD-1 22c3 Dako/Agilent Durvalumab PD-L1 SP263 Ventana 2017 MFMER slide-22
21 PD-L1 antibody variability 22C3, 28-8, SP263 closely aligned in tumor cells stained SP142 stained fewer tumor cells Immune staining showed greater variability Hirsch et al, MFMER slide-23
22 PD-L1 antibody variability SP142 labels fewer tumor and inflammatory cells Rimm et al, MFMER slide-24
23 Observer variability Pathologists concordant in assessment of tumor cells Not concordant in assessment of immune cells 2017 MFMER slide-25
24 PD-L1 and Tumor Heterogeneity Rehman et al, Mod Pathol MFMER slide-27
25 PD-L1 and Differences across Tumor types PD-L1 expression varies across tumor types May not predict degree of response May not predict survival Kluger et al, MFMER slide-28
26 PD-L1 IHC is limited as a predictive biomarker 2017 MFMER slide-29
27 Neoantigens Mutation associated neoantigens Mutations alter the coding sequence In the appropriate context this leads to an immunogenic tumor 2017 MFMER slide-30
28 Neoantigens Mutation associated neoantigens Microsatellite instability leads to the development of neoantigens Tumor Normal Stable Tumor Unstable Normal 2017 MFMER slide-31
29 2017 MFMER slide-32
30 2017 MFMER slide-33
31 2017 MFMER slide-34
32 2017 MFMER slide-35
33 Microsatellite instability is a good predictive marker of response to PD-1/PD-L1 axis inhibition 2017 MFMER slide-36
34 Histology teaches us that there must be other mechanisms of immunogenic tumors Gastric carcinoma with lymphoid stroma Lymphocyte rich HCC 2017 MFMER slide-37
35 Role of Diagnostic Pathologist Accurate diagnosis Identify adequate and appropriate specimens for microsatellite instability and other ancillary testing Ensure efficient use of tissue samples 2017 MFMER slide-38
36 PD-L1 and Immunotherapy in GI malignancy An important subset of malignancies have an immunogenic environment Inhibition of the PD-1/PD-L1 axis is a disruptive new modality in GI cancer therapy In GI malignancies, MSI-H is an excellent predictor of response to PD-1 inhibition Other predictive biomarkers are under study Pathologists will be key participants in the new wave of immuno-oncology 2017 MFMER slide-39
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