Immune checkpoints are predominantly co-expressed by clonally expanded CD4
Cancer
Flow cytometry
Immune checkpoints
Immunology
Immunotherapy
Single-cell RNA-Seq
T-cells
TCR repertoire
Journal
Journal of experimental & clinical cancer research : CR
ISSN: 1756-9966
Titre abrégé: J Exp Clin Cancer Res
Pays: England
ID NLM: 8308647
Informations de publication
Date de publication:
06 Dec 2023
06 Dec 2023
Historique:
received:
14
07
2023
accepted:
11
11
2023
medline:
11
12
2023
pubmed:
7
12
2023
entrez:
7
12
2023
Statut:
epublish
Résumé
In addition to anti-PD(L)1, anti-CTLA-4 and anti-LAG-3, novel immune checkpoint proteins (ICP)-targeted antibodies have recently failed to demonstrate significant efficacy in clinical trials. In these trials, patients were enrolled without screening for drug target expression. Although these novel ICP-targeted antibodies were expected to stimulate anti-tumor CD8 + T-cells, the rationale for their target expression in human tumors relied on pre-clinical IHC stainings and transcriptomic data, which are poorly sensitive and specific techniques for assessing membrane protein expression on immune cell subsets. Our aim was to describe ICP expression on intratumoral T-cells from primary solid tumors to better design upcoming neoadjuvant cancer immunotherapy trials. We prospectively performed multiparameter flow cytometry and single-cell RNA sequencing (scRNA-Seq) paired with TCR sequencing on freshly resected human primary tumors of various histological types to precisely determine ICP expression levels within T-cell subsets. Within a given tumor type, we found high inter-individual variability for tumor infiltrating CD45 + cells and for T-cells subsets. The proportions of CD8 Tumor histology alone does not reveal the complete picture of the tumor immune contexture. In clinical trials, assumptions regarding target expression should rely on more sensitive and specific techniques than conventional IHC or transcriptomics. Flow cytometry and scRNAseq accurately characterize ICP expression within immune cell subsets. Much like in hematology, flow cytometry can better describe the immune contexture of solid tumors, offering the opportunity to guide patient treatment according to drug target expression rather than tumor histological type.
Sections du résumé
BACKGROUND
BACKGROUND
In addition to anti-PD(L)1, anti-CTLA-4 and anti-LAG-3, novel immune checkpoint proteins (ICP)-targeted antibodies have recently failed to demonstrate significant efficacy in clinical trials. In these trials, patients were enrolled without screening for drug target expression. Although these novel ICP-targeted antibodies were expected to stimulate anti-tumor CD8 + T-cells, the rationale for their target expression in human tumors relied on pre-clinical IHC stainings and transcriptomic data, which are poorly sensitive and specific techniques for assessing membrane protein expression on immune cell subsets. Our aim was to describe ICP expression on intratumoral T-cells from primary solid tumors to better design upcoming neoadjuvant cancer immunotherapy trials.
METHODS
METHODS
We prospectively performed multiparameter flow cytometry and single-cell RNA sequencing (scRNA-Seq) paired with TCR sequencing on freshly resected human primary tumors of various histological types to precisely determine ICP expression levels within T-cell subsets.
RESULTS
RESULTS
Within a given tumor type, we found high inter-individual variability for tumor infiltrating CD45 + cells and for T-cells subsets. The proportions of CD8
CONCLUSIONS
CONCLUSIONS
Tumor histology alone does not reveal the complete picture of the tumor immune contexture. In clinical trials, assumptions regarding target expression should rely on more sensitive and specific techniques than conventional IHC or transcriptomics. Flow cytometry and scRNAseq accurately characterize ICP expression within immune cell subsets. Much like in hematology, flow cytometry can better describe the immune contexture of solid tumors, offering the opportunity to guide patient treatment according to drug target expression rather than tumor histological type.
Identifiants
pubmed: 38057799
doi: 10.1186/s13046-023-02897-6
pii: 10.1186/s13046-023-02897-6
pmc: PMC10699039
doi:
Substances chimiques
Receptors, Antigen, T-Cell
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
333Informations de copyright
© 2023. The Author(s).
Références
J Immunother Cancer. 2022 Oct;10(10):
pubmed: 36316061
Bioinformatics. 2020 Apr 1;36(7):2311-2313
pubmed: 31764967
Nat Immunol. 2020 Nov;21(11):1346-1358
pubmed: 32868929
Nat Commun. 2018 Jul 13;9(1):2724
pubmed: 30006565
J Exp Clin Cancer Res. 2021 May 18;40(1):172
pubmed: 34006331
Cancer Res. 2013 Dec 15;73(24):7189-7198
pubmed: 24177180
J Immunother Cancer. 2019 Oct 18;7(1):265
pubmed: 31627744
Proc Natl Acad Sci U S A. 2019 May 14;116(20):9999-10008
pubmed: 31028147
Oncotarget. 2018 Dec 11;9(97):36993-37007
pubmed: 30651930
Oncoimmunology. 2022 Jan 2;11(1):2012961
pubmed: 36524209
Nature. 2018 May;557(7706):575-579
pubmed: 29769722
Front Med (Lausanne). 2019 Mar 13;6:27
pubmed: 30931305
Bioinformatics. 2019 Nov 1;35(21):4472-4473
pubmed: 31073610
Ann Oncol. 2022 Feb;33(2):169-180
pubmed: 34800678
J Exp Clin Cancer Res. 2021 Oct 1;40(1):311
pubmed: 34598713
Clin Cancer Res. 2021 Jan 15;27(2):460-472
pubmed: 33148673
Front Immunol. 2020 Oct 21;11:568931
pubmed: 33193345
J Immunother Cancer. 2023 Mar;11(3):
pubmed: 36927527
Clin Cancer Res. 2022 Sep 1;28(17):3695-3708
pubmed: 35511938
Clin Cancer Res. 2022 Aug 15;28(16):3452-3463
pubmed: 35699599
Gigascience. 2018 Jul 1;7(7):
pubmed: 30010766
J Exp Clin Cancer Res. 2019 Apr 15;38(1):162
pubmed: 30987642
Nat Biotechnol. 2016 May;34(5):525-7
pubmed: 27043002
Cell Discov. 2022 Mar 28;8(1):29
pubmed: 35351857
J Natl Cancer Inst. 2021 Jan 4;113(1):7-8
pubmed: 32516413
Nat Rev Clin Oncol. 2019 Mar;16(3):151-167
pubmed: 30523282
Genome Biol. 2019 Mar 22;20(1):63
pubmed: 30902100
J Clin Invest. 2013 Jun;123(6):2447-63
pubmed: 23728179
Bioinformatics. 2020 Feb 15;36(4):1150-1158
pubmed: 31501871
EMBO Mol Med. 2021 Jan 11;13(1):e12850
pubmed: 33372722
Clin Cancer Res. 2020 Oct 15;26(20):5358-5367
pubmed: 32816951
Nat Commun. 2020 Apr 14;11(1):1801
pubmed: 32286271
Cell Biosci. 2018 May 2;8:34
pubmed: 29744030
Clin Cancer Res. 2022 Jan 1;28(1):71-83
pubmed: 34615725
Nat Biotechnol. 2018 Jun;36(5):411-420
pubmed: 29608179
Cancer Immunol Res. 2020 Oct;8(10):1311-1321
pubmed: 32759363
Cell. 2015 Jul 2;162(1):184-97
pubmed: 26095251
Am J Hematol. 2020 May;95(5):510-520
pubmed: 32052473
F1000Res. 2016 Aug 31;5:2122
pubmed: 27909575
Clin Cancer Res. 2017 Apr 15;23(8):1920-1928
pubmed: 27827313
Clin Cancer Res. 2018 Apr 15;24(8):1816-1823
pubmed: 29549159
Nat Commun. 2021 May 20;12(1):2965
pubmed: 34017005
F1000Res. 2018 Aug 24;7:1338
pubmed: 30254741
Nat Rev Cancer. 2012 Mar 22;12(4):252-64
pubmed: 22437870
Nat Biotechnol. 2021 Jul;39(7):813-818
pubmed: 33795888
BMC Immunol. 2021 Aug 19;22(1):58
pubmed: 34407765
Ann Transl Med. 2023 Mar 15;11(5):227
pubmed: 37007583
AAPS J. 2021 Mar 7;23(2):39
pubmed: 33677681
Transl Oncol. 2020 Jan;13(1):17-24
pubmed: 31733591
Mol Cancer. 2022 Jan 21;21(1):28
pubmed: 35062949