Immunogenomics of Colorectal Cancer Response to Checkpoint Blockade: Analysis of the KEYNOTE 177 Trial and Validation Cohorts.
Antibodies, Monoclonal, Humanized
/ adverse effects
Biomarkers, Tumor
/ genetics
CD8-Positive T-Lymphocytes
/ drug effects
Clinical Trials as Topic
Colorectal Neoplasms
/ drug therapy
Cytotoxicity, Immunologic
/ drug effects
Gene Expression Profiling
Humans
Immune Checkpoint Inhibitors
/ adverse effects
Immunogenetic Phenomena
Immunogenetics
Lymphocytes, Tumor-Infiltrating
/ drug effects
Mutation
Nivolumab
/ adverse effects
Predictive Value of Tests
Programmed Cell Death 1 Receptor
/ antagonists & inhibitors
RNA-Seq
Reproducibility of Results
Time Factors
Transcriptome
Treatment Outcome
Tumor Microenvironment
Tumor-Associated Macrophages
/ drug effects
Exome Sequencing
Anti-PD1 Immunotherapy
CD8 T cells
Interferon Gamma
Tumor Mutational Burden
Wnt Signaling
Journal
Gastroenterology
ISSN: 1528-0012
Titre abrégé: Gastroenterology
Pays: United States
ID NLM: 0374630
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
received:
05
02
2021
revised:
18
05
2021
accepted:
22
06
2021
pubmed:
2
7
2021
medline:
18
1
2022
entrez:
1
7
2021
Statut:
ppublish
Résumé
Colorectal cancer (CRC) shows variable response to immune checkpoint blockade, which can only partially be explained by high tumor mutational burden (TMB). We conducted an integrated study of the cancer tissue and associated tumor microenvironment (TME) from patients treated with pembrolizumab (KEYNOTE 177 clinical trial) or nivolumab to dissect the cellular and molecular determinants of response to anti- programmed cell death 1 (PD1) immunotherapy. We selected multiple regions per tumor showing variable T-cell infiltration for a total of 738 regions from 29 patients, divided into discovery and validation cohorts. We performed multiregional whole-exome and RNA sequencing of the tumor cells and integrated these with T-cell receptor sequencing, high-dimensional imaging mass cytometry, detection of programmed death-ligand 1 (PDL1) interaction in situ, multiplexed immunofluorescence, and computational spatial analysis of the TME. In hypermutated CRCs, response to anti-PD1 immunotherapy was not associated with TMB but with high clonality of immunogenic mutations, clonally expanded T cells, low activation of Wnt signaling, deregulation of the interferon gamma pathway, and active immune escape mechanisms. Responsive hypermutated CRCs were also rich in cytotoxic and proliferating PD1 Our study clarified the limits of TMB as a predictor of response of CRC to anti-PD1 immunotherapy. It identified a population of antigen-presenting macrophages interacting with CD8 T cells that consistently segregate with response. We therefore concluded that anti-PD1 agents release the PD1-PDL1 interaction between CD8 T cells and macrophages to promote cytotoxic antitumor activity.
Sections du résumé
BACKGROUND & AIMS
Colorectal cancer (CRC) shows variable response to immune checkpoint blockade, which can only partially be explained by high tumor mutational burden (TMB). We conducted an integrated study of the cancer tissue and associated tumor microenvironment (TME) from patients treated with pembrolizumab (KEYNOTE 177 clinical trial) or nivolumab to dissect the cellular and molecular determinants of response to anti- programmed cell death 1 (PD1) immunotherapy.
METHODS
We selected multiple regions per tumor showing variable T-cell infiltration for a total of 738 regions from 29 patients, divided into discovery and validation cohorts. We performed multiregional whole-exome and RNA sequencing of the tumor cells and integrated these with T-cell receptor sequencing, high-dimensional imaging mass cytometry, detection of programmed death-ligand 1 (PDL1) interaction in situ, multiplexed immunofluorescence, and computational spatial analysis of the TME.
RESULTS
In hypermutated CRCs, response to anti-PD1 immunotherapy was not associated with TMB but with high clonality of immunogenic mutations, clonally expanded T cells, low activation of Wnt signaling, deregulation of the interferon gamma pathway, and active immune escape mechanisms. Responsive hypermutated CRCs were also rich in cytotoxic and proliferating PD1
CONCLUSIONS
Our study clarified the limits of TMB as a predictor of response of CRC to anti-PD1 immunotherapy. It identified a population of antigen-presenting macrophages interacting with CD8 T cells that consistently segregate with response. We therefore concluded that anti-PD1 agents release the PD1-PDL1 interaction between CD8 T cells and macrophages to promote cytotoxic antitumor activity.
Identifiants
pubmed: 34197832
pii: S0016-5085(21)03178-4
doi: 10.1053/j.gastro.2021.06.064
pmc: PMC8527923
pii:
doi:
Substances chimiques
Antibodies, Monoclonal, Humanized
0
Biomarkers, Tumor
0
Immune Checkpoint Inhibitors
0
PDCD1 protein, human
0
Programmed Cell Death 1 Receptor
0
Nivolumab
31YO63LBSN
pembrolizumab
DPT0O3T46P
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
1179-1193Subventions
Organisme : Arthritis Research UK
ID : FC001745
Pays : United Kingdom
Organisme : Arthritis Research UK
ID : FC001169
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Arthritis Research UK
ID : FC001130
Pays : United Kingdom
Organisme : Arthritis Research UK
ID : FC001002
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C7893/A26233
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C604/A25135
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C43634/A25487
Pays : United Kingdom
Informations de copyright
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.
Références
N Engl J Med. 2015 Jun 25;372(26):2509-20
pubmed: 26028255
Nat Commun. 2013;4:2680
pubmed: 24157944
BMC Genomics. 2014 Jan 28;15:74
pubmed: 24467841
Science. 2018 Mar 23;359(6382):1350-1355
pubmed: 29567705
Gut. 2020 Apr;69(4):691-703
pubmed: 31270164
J Natl Cancer Inst. 2010 Sep 22;102(18):1388-97
pubmed: 20826737
Nat Biotechnol. 2013 Nov;31(11):1023-31
pubmed: 24142049
Cell. 2017 Nov 30;171(6):1259-1271.e11
pubmed: 29107330
Cancer Cell. 2018 Dec 10;34(6):1012-1026.e3
pubmed: 30537506
Ann Oncol. 2019 Jul 1;30(7):1096-1103
pubmed: 31038663
Nat Commun. 2017 Oct 26;8(1):1136
pubmed: 29070816
Cancer Discov. 2021 Jul;11(7):1844-1859
pubmed: 33653693
Proc Natl Acad Sci U S A. 2010 Sep 28;107(39):16910-5
pubmed: 20837533
Cancer Res. 2020 Oct 1;80(19):4244-4257
pubmed: 32855204
N Engl J Med. 2020 Dec 3;383(23):2207-2218
pubmed: 33264544
Genome Med. 2020 Mar 30;12(1):33
pubmed: 32228719
Genome Biol. 2014;15(12):550
pubmed: 25516281
JCO Precis Oncol. 2019;3:
pubmed: 31008436
Cancer Discov. 2018 Jun;8(6):730-749
pubmed: 29510987
Immunity. 2019 Jan 15;50(1):195-211.e10
pubmed: 30635237
Nat Biotechnol. 2015 Nov;33(11):1152-8
pubmed: 26372948
Nat Methods. 2014 Apr;11(4):396-8
pubmed: 24633410
Nucleic Acids Res. 2010 Sep;38(16):e164
pubmed: 20601685
Sci Rep. 2017 Dec 4;7(1):16878
pubmed: 29203879
Nat Biotechnol. 2018 Jun;36(5):411-420
pubmed: 29608179
Nat Commun. 2019 Jul 15;10(1):3101
pubmed: 31308377
Nat Rev Gastroenterol Hepatol. 2019 Jun;16(6):361-375
pubmed: 30886395
Nature. 2009 Nov 5;462(7269):108-12
pubmed: 19847166
Nat Methods. 2021 Feb;18(2):144-155
pubmed: 33398189
Nature. 2019 Dec;576(7787):465-470
pubmed: 31827286
Nat Genet. 2021 Jan;53(1):11-15
pubmed: 33398197
Nature. 2012 Jul 18;487(7407):330-7
pubmed: 22810696
BMC Bioinformatics. 2019 May 22;20(1):264
pubmed: 31117948
Nat Methods. 2018 Aug;15(8):591-594
pubmed: 30013048
Mol Cancer Ther. 2017 Nov;16(11):2598-2608
pubmed: 28835386
Nature. 2015 Jul 9;523(7559):231-5
pubmed: 25970248
Science. 2017 Jul 28;357(6349):409-413
pubmed: 28596308
Nat Genet. 2019 Feb;51(2):202-206
pubmed: 30643254