An ex vivo tumor fragment platform to dissect response to PD-1 blockade in cancer.
Antineoplastic Agents, Immunological
/ pharmacology
B7-H1 Antigen
/ antagonists & inhibitors
CD8-Positive T-Lymphocytes
/ cytology
Cell Differentiation
/ immunology
Cell Line, Tumor
Cytokines
/ analysis
Humans
Immune Checkpoint Inhibitors
/ pharmacology
Lymphocyte Activation
/ drug effects
Lymphocytes, Tumor-Infiltrating
/ cytology
Neoplasms
/ drug therapy
Programmed Cell Death 1 Receptor
/ antagonists & inhibitors
Tumor Microenvironment
/ immunology
Journal
Nature medicine
ISSN: 1546-170X
Titre abrégé: Nat Med
Pays: United States
ID NLM: 9502015
Informations de publication
Date de publication:
07 2021
07 2021
Historique:
received:
28
04
2020
accepted:
17
05
2021
pubmed:
10
7
2021
medline:
24
9
2021
entrez:
9
7
2021
Statut:
ppublish
Résumé
Inhibitors of the PD-1-PD-L1 axis have been approved as therapy for many human cancers. In spite of the evidence for their widespread clinical activity, little is known about the immunological alterations that occur in human cancer tissue after PD-1 blockade. We developed and employed a patient-derived tumor fragment platform to dissect the early immunological response of human tumor tissue to ex vivo PD-1 blockade. We observed that the capacity of immune cells to be reactivated ex vivo was predictive of clinical response, and perturbation analyses identified tumor-resident T cells as a key component of this immunological response. In addition, through combined analysis of baseline properties and immune response capacity, we identified a new subgroup of infiltrated tumors that lacks the capacity to respond to PD-1 blockade. Finally, the baseline presence of tertiary lymphoid structures and their components correlated with the capacity of cancers to undergo intratumoral immune cell reactivation.
Identifiants
pubmed: 34239134
doi: 10.1038/s41591-021-01398-3
pii: 10.1038/s41591-021-01398-3
doi:
Substances chimiques
Antineoplastic Agents, Immunological
0
B7-H1 Antigen
0
CD274 protein, human
0
Cytokines
0
Immune Checkpoint Inhibitors
0
PDCD1 protein, human
0
Programmed Cell Death 1 Receptor
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1250-1261Commentaires et corrections
Type : CommentIn
Type : CommentIn
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.
Références
Xin Yu, J. et al. Trends in clinical development for PD-1/PD-L1 inhibitors. Nat. Rev. Drug Discov. 19, 163–164 (2020).
pubmed: 32127660
doi: 10.1038/d41573-019-00182-w
Yost, K. E. et al. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nat. Med. 25, 1251–1259 (2019).
pubmed: 31359002
pmcid: 6689255
doi: 10.1038/s41591-019-0522-3
Wu, T. D. et al. Peripheral T cell expansion predicts tumour infiltration and clinical response. Nature 579, 274–278 (2020).
doi: 10.1038/s41586-020-2056-8
pubmed: 32103181
Zhang, J. et al. Compartmental analysis of T-cell clonal dynamics as a function of pathologic response to neoadjuvant PD-1 blockade in resectable non-small cell lung cancer. Clin. Cancer Res. 26, 1327–1337 (2020).
pubmed: 31754049
doi: 10.1158/1078-0432.CCR-19-2931
Strauss, L. et al. Targeted deletion of PD-1 in myeloid cells induces antitumor immunity. Sci. Immunol. 5, eaay1863 (2020).
pubmed: 31901074
pmcid: 7183328
doi: 10.1126/sciimmunol.aay1863
Mayoux, M. et al. Dendritic cells dictate responses to PD-L1 blockade cancer immunotherapy. Sci. Transl. Med. 12, eaav7431 (2020).
pubmed: 32161104
doi: 10.1126/scitranslmed.aav7431
Tumeh, P. C. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014).
pubmed: 25428505
pmcid: 4246418
doi: 10.1038/nature13954
Amaria, R. N. et al. Neoadjuvant immune checkpoint blockade in high-risk resectable melanoma. Nat. Med. 24, 1649–1654 (2018).
pubmed: 30297909
pmcid: 6481682
doi: 10.1038/s41591-018-0197-1
Huang, A. C. et al. A single dose of neoadjuvant PD-1 blockade predicts clinical outcomes in resectable melanoma. Nat. Med. 25, 454–461 (2019).
pubmed: 30804515
pmcid: 6699626
doi: 10.1038/s41591-019-0357-y
Neal, J. T. et al. Organoid modeling of the tumor immune microenvironment. Cell 175, 1972–1988.e16 (2018).
pubmed: 30550791
pmcid: 6656687
doi: 10.1016/j.cell.2018.11.021
Jenkins, R. W. et al. Ex vivo profiling of PD-1 blockade using organotypic tumor spheroids. Cancer Discov. 8, 196–215 (2018).
pubmed: 29101162
doi: 10.1158/2159-8290.CD-17-0833
Blank, C. et al. PD-L1/B7H-1 inhibits the effector phase of tumor rejection by T cell receptor (TCR) transgenic CD8
pubmed: 14871849
doi: 10.1158/0008-5472.CAN-03-3259
Gros, A. et al. PD-1 identifies the patient-specific CD8
pubmed: 24667641
pmcid: 4001555
doi: 10.1172/JCI73639
Gros, A. et al. Prospective identification of neoantigen-specific lymphocytes in the peripheral blood of melanoma patients. Nat. Med. 22, 433–438 (2016).
pubmed: 26901407
pmcid: 7446107
doi: 10.1038/nm.4051
Thommen, D. S. et al. A transcriptionally and functionally distinct PD-1
pubmed: 29892065
pmcid: 6110381
doi: 10.1038/s41591-018-0057-z
Herbst, R. S. et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515, 563–567 (2014).
pubmed: 25428504
pmcid: 4836193
doi: 10.1038/nature14011
Sharma, P. & Allison, J. P. The future of immune checkpoint therapy. Science 348, 56–61 (2015).
pubmed: 25838373
doi: 10.1126/science.aaa8172
Hegde, P. S., Karanikas, V. & Evers, S. The where, the when, and the how of immune monitoring for cancer immunotherapies in the era of checkpoint inhibition. Clin. Cancer Res. 22, 1865–1874 (2016).
pubmed: 27084740
doi: 10.1158/1078-0432.CCR-15-1507
Galon, J. & Bruni, D. Approaches to treat immune hot, altered and cold tumours with combination immunotherapies. Nat. Rev. Drug Discov. 18, 197–218 (2019).
pubmed: 30610226
doi: 10.1038/s41573-018-0007-y
Sanmamed, M. F. et al. Changes in serum interleukin-8 (IL-8) levels reflect and predict response to anti-PD-1 treatment in melanoma and non-small-cell lung cancer patients. Ann. Oncol. 28, 1988–1995 (2017).
pubmed: 28595336
pmcid: 5834104
doi: 10.1093/annonc/mdx190
Schalper, K. A. et al. Elevated serum interleukin-8 is associated with enhanced intratumor neutrophils and reduced clinical benefit of immune-checkpoint inhibitors. Nat. Med. 26, 688–692 (2020).
pubmed: 32405062
pmcid: 8127102
doi: 10.1038/s41591-020-0856-x
Yuen, K. C. et al. High systemic and tumor-associated IL-8 correlates with reduced clinical benefit of PD-L1 blockade. Nat. Med. 26, 693–698 (2020).
pubmed: 32405063
doi: 10.1038/s41591-020-0860-1
pmcid: 8286544
Wherry, E. J. et al. Molecular signature of CD8
doi: 10.1016/j.immuni.2007.09.006
pubmed: 17950003
Baitsch, L. et al. Extended co-expression of inhibitory receptors by human CD8 T-cells depending on differentiation, antigen-specificity and anatomical localization. PLoS ONE 7, e30852 (2012).
pubmed: 22347406
pmcid: 3275569
doi: 10.1371/journal.pone.0030852
Thommen, D. S. et al. Progression of lung cancer is associated with increased dysfunction of T cells defined by coexpression of multiple inhibitory receptors. Cancer Immunol. Res. 3, 1344–1355 (2015).
pubmed: 26253731
doi: 10.1158/2326-6066.CIR-15-0097
Kurtulus, S. et al. Checkpoint blockade immunotherapy induces dynamic changes in PD-1
pubmed: 30635236
pmcid: 6336113
doi: 10.1016/j.immuni.2018.11.014
Siddiqui, I. et al. Intratumoral Tcf1
doi: 10.1016/j.immuni.2018.12.021
pubmed: 30635237
Miller, B. C. et al. Subsets of exhausted CD8
pubmed: 30778252
pmcid: 6673650
doi: 10.1038/s41590-019-0312-6
Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013.e20 (2018).
pubmed: 30388456
pmcid: 6641984
doi: 10.1016/j.cell.2018.10.038
Krishna, S. et al. Stem-like CD8 T cells mediate response of adoptive cell immunotherapy against human cancer. Science 370, 1328–1334 (2020).
pubmed: 33303615
doi: 10.1126/science.abb9847
pmcid: 8883579
Duhen, T. et al. Co-expression of CD39 and CD103 identifies tumor-reactive CD8 T cells in human solid tumors. Nat. Commun. 9, 2724 (2018).
pubmed: 30006565
pmcid: 6045647
doi: 10.1038/s41467-018-05072-0
Byrne, A. et al. Tissue-resident memory T cells in breast cancer control and immunotherapy responses. Nat. Rev. Clin. Oncol. 17, 341–348 (2020).
pubmed: 32112054
doi: 10.1038/s41571-020-0333-y
Edwards, J. et al. CD103
pubmed: 29599411
doi: 10.1158/1078-0432.CCR-17-2257
Menares, E. et al. Tissue-resident memory CD8
pubmed: 31562311
pmcid: 6765014
doi: 10.1038/s41467-019-12319-x
Ansel, K. M. et al. A chemokine-driven positive feedback loop organizes lymphoid follicles. Nature 406, 309–314 (2000).
pubmed: 10917533
doi: 10.1038/35018581
Gettinger, S. N. et al. A dormant TIL phenotype defines non-small cell lung carcinomas sensitive to immune checkpoint blockers. Nat. Commun. 9, 3196 (2018).
pubmed: 30097571
pmcid: 6086912
doi: 10.1038/s41467-018-05032-8
Schietinger, A. et al. Tumor-specific T cell dysfunction is a dynamic antigen-driven differentiation program initiated early during tumorigenesis. Immunity 45, 389–401 (2016).
pubmed: 27521269
pmcid: 5119632
doi: 10.1016/j.immuni.2016.07.011
Philip, M. et al. Chromatin states define tumour-specific T cell dysfunction and reprogramming. Nature 545, 452–456 (2017).
pubmed: 28514453
pmcid: 5693219
doi: 10.1038/nature22367
Scheper, W. et al. Low and variable tumor reactivity of the intratumoral TCR repertoire in human cancers. Nat. Med. 25, 89–94 (2019).
pubmed: 30510250
doi: 10.1038/s41591-018-0266-5
Rizvi, N. A. et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 348, 124–128 (2015).
pubmed: 25765070
pmcid: 4993154
doi: 10.1126/science.aaa1348
Helmink, B. A. et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature 577, 549–555 (2020).
pubmed: 31942075
doi: 10.1038/s41586-019-1922-8
pmcid: 8762581
Petitprez, F. et al. B cells are associated with survival and immunotherapy response in sarcoma. Nature 577, 556–560 (2020).
pubmed: 31942077
doi: 10.1038/s41586-019-1906-8
Cabrita, R. et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature 577, 561–565 (2020).
pubmed: 31942071
doi: 10.1038/s41586-019-1914-8
Decalf, J., Albert, M. L. & Ziai, J. New tools for pathology: a user’s review of a highly multiplexed method for in situ analysis of protein and RNA expression in tissue. J. Pathol. 247, 650–661 (2019).
pubmed: 30570141
doi: 10.1002/path.5223
Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019).
pubmed: 30923225
pmcid: 6927209
doi: 10.1126/science.aaw1219
Vickovic, S. et al. High-definition spatial transcriptomics for in situ tissue profiling. Nat. Methods 16, 987–990 (2019).
pubmed: 31501547
pmcid: 6765407
doi: 10.1038/s41592-019-0548-y
Roederer, M., Nozzi, J. L. & Nason, M. C. SPICE: exploration and analysis of post-cytometric complex multivariate datasets. Cytometry A 79, 167–174 (2011).
pubmed: 21265010
pmcid: 3072288
doi: 10.1002/cyto.a.21015
McInnes, L., Healy, J. & Melville, J. UMAP: uniform manifold approximation and projection for dimension reduction. Preprint at arXiv https://arxiv.org/abs/1802.03426v3 (2020).
Samusik, N., Good, Z., Spitzer, M. H., Davis, K. L. & Nolan, G. P. Automated mapping of phenotype space with single-cell data. Nat. Methods 13, 493–496 (2016).
pubmed: 27183440
pmcid: 4896314
doi: 10.1038/nmeth.3863
Dijkgraaf, F. E. et al. Tissue patrol by resident memory CD8
pubmed: 31110315
doi: 10.1038/s41590-019-0404-3