Extricating human tumour immune alterations from tissue inflammation.
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
05 2022
05 2022
Historique:
received:
23
03
2021
accepted:
01
04
2022
pubmed:
12
5
2022
medline:
28
5
2022
entrez:
11
5
2022
Statut:
ppublish
Résumé
Immunotherapies have achieved remarkable successes in the treatment of cancer, but major challenges remain
Identifiants
pubmed: 35545675
doi: 10.1038/s41586-022-04718-w
pii: 10.1038/s41586-022-04718-w
pmc: PMC9132772
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
728-735Subventions
Organisme : NCI NIH HHS
ID : F99 CA245735
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI123323
Pays : United States
Organisme : NIDCR NIH HHS
ID : R21 DE026565
Pays : United States
Organisme : NIH HHS
ID : S10 OD028685
Pays : United States
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2022. The Author(s).
Références
Chen, D. S. & Mellman, I. Oncology meets immunology: the cancer-immunity cycle. Immunity 39, 1–10(2013).
pubmed: 23890059
doi: 10.1016/j.immuni.2013.07.012
Martins, F. et al. Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance. Nat. Rev. Clin. Oncol. 16, 563–580 (2019).
pubmed: 31092901
doi: 10.1038/s41571-019-0218-0
Greten, F. R. & Grivennikov, S. I. Inflammation and cancer: triggers, mechanisms, and consequences. Immunity 51, 27–41 (2019).
pubmed: 31315034
pmcid: 6831096
doi: 10.1016/j.immuni.2019.06.025
Mujal, A. M. & Krummel, M. F. Immunity as a continuum of archetypes. Science 364, 28–29 (2019).
pubmed: 30948539
doi: 10.1126/science.aau8694
Fan, X. & Rudensky, A. Y. Hallmarks of tissue-resident lymphocytes. Cell 164, 1198–1211 (2016).
pubmed: 26967286
pmcid: 4973889
doi: 10.1016/j.cell.2016.02.048
Kumar, B. V. et al. Human tissue-resident memory T cells are defined by core transcriptional and functional signatures in lymphoid and mucosal sites. Cell Rep. 20, 2921–2934 (2017).
pubmed: 28930685
pmcid: 5646692
doi: 10.1016/j.celrep.2017.08.078
Szabo, P. A. et al. Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and disease. Nat. Commun. 10, 4706–4716 (2019).
pubmed: 31624246
pmcid: 6797728
doi: 10.1038/s41467-019-12464-3
Amsen, D., van Gisbergen, K. P. J. M., Hombrink, P. & van Lier, R. A. W. Tissue-resident memory T cells at the center of immunity to solid tumors. Nat. Immunol. 19, 538–546 (2018).
pubmed: 29777219
doi: 10.1038/s41590-018-0114-2
Ji, A. L. et al. Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma. Cell 182, 497–514.e422 (2020).
pubmed: 32579974
pmcid: 7391009
doi: 10.1016/j.cell.2020.05.039
Scott, A. C. et al. TOX is a critical regulator of tumour-specific T cell differentiation. Nature 571, 270–274 (2019).
pubmed: 31207604
pmcid: 7698992
doi: 10.1038/s41586-019-1324-y
Chao, J. L. & Savage, P. A. Unlocking the complexities of tumor-associated regulatory T cells. J. Immunol. 200, 415–421 (2018).
pubmed: 29311383
doi: 10.4049/jimmunol.1701188
Sharma, P. & Allison, J. P. Dissecting the mechanisms of immune checkpoint therapy. Nat. Rev. Immunol. 20, 75–76 (2020).
pubmed: 31925406
doi: 10.1038/s41577-020-0275-8
Woodward Davis, A. S. et al. The human tissue-resident CCR5
pubmed: 31801887
doi: 10.1126/scitranslmed.aaw8718
Guilliams, M. et al. Dendritic cells, monocytes and macrophages: a unified nomenclature based on ontogeny. Nat. Rev. Immunol. 14, 571–578 (2014).
pubmed: 25033907
pmcid: 4638219
doi: 10.1038/nri3712
Cabeza-Cabrerizo, M., Cardoso, A., Minutti, C. M., Pereira da Costa, M. & Reis, E. S. C. dendritic cells revisited. Annu. Rev. Immunol. 39, 131–166 (2021).
pubmed: 33481643
doi: 10.1146/annurev-immunol-061020-053707
Binnewies, M. et al. Unleashing type-2 dendritic cells to drive protective antitumor CD4
pubmed: 30955881
pmcid: 6954108
doi: 10.1016/j.cell.2019.02.005
Wculek, S. K. et al. Dendritic cells in cancer immunology and immunotherapy. Nat. Rev. Immunol. 144, 646–618 (2019).
Chow, L. Q. M. Head and neck cancer. New Engl. J. Med. 382, 60–72 (2020).
pubmed: 31893516
doi: 10.1056/NEJMra1715715
Mair, F. & Prlic, M. OMIP-044: 28-color immunophenotyping of the human dendritic cell compartment. Cytometry A 106, 255 (2018).
Suzuki, S. et al. Immune-checkpoint molecules on regulatory T-cells as a potential therapeutic target in head and neck squamous cell cancers. Cancer Sci. 111, 1943–1957 (2020).
pubmed: 32304268
pmcid: 7293074
doi: 10.1111/cas.14422
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
Savas, P. et al. Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis. Nat. Med. 24, 986–993 (2018).
pubmed: 29942092
doi: 10.1038/s41591-018-0078-7
Blank, C. U. et al. Defining ‘T cell exhaustion’. Nat. Rev. Immunol. 19, 665–674 (2019).
pubmed: 31570879
pmcid: 7286441
doi: 10.1038/s41577-019-0221-9
Bourdely, P. et al. Transcriptional and functional analysis of CD1c
pubmed: 32610077
pmcid: 7445430
doi: 10.1016/j.immuni.2020.06.002
Segura, E. & Amigorena, S. Inflammatory dendritic cells in mice and humans. Trends Immunol. 34, 440–445 (2013).
pubmed: 23831267
doi: 10.1016/j.it.2013.06.001
Dutertre, C.-A. et al. Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells. Immunity 51, 573–589.e578 (2019).
pubmed: 31474513
doi: 10.1016/j.immuni.2019.08.008
Salmon, H. et al. Expansion and activation of CD103
pubmed: 27096321
pmcid: 4980762
doi: 10.1016/j.immuni.2016.03.012
Lavin, Y. et al. Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. Cell 169, 750–765.e717 (2017).
pubmed: 28475900
pmcid: 5737939
doi: 10.1016/j.cell.2017.04.014
Greene, E. et al. New interpretable machine-learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy. Patterns 2, 100372 (2021).
pubmed: 34950900
pmcid: 8672150
doi: 10.1016/j.patter.2021.100372
Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).
pubmed: 31740819
pmcid: 6884693
doi: 10.1038/s41592-019-0619-0
McInnes, L., Healy, J. & Melville, J. UMAP: uniform manifold approximation and projection for dimension reduction. Preprint at arXiv https://doi.org/10.48550/arXiv.1802.03426 (2018).
doi: 10.48550/arXiv.1802.03426
Aran, D. et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat. Immunol. 20, 163–172 (2019).
pubmed: 30643263
pmcid: 6340744
doi: 10.1038/s41590-018-0276-y
Maier, B. et al. A conserved dendritic-cell regulatory program limits antitumour immunity. Nature 580, 257–262 (2020).
pubmed: 32269339
pmcid: 7787191
doi: 10.1038/s41586-020-2134-y
Finak, G. et al. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biol. 16, 278 (2015).
pubmed: 26653891
pmcid: 4676162
doi: 10.1186/s13059-015-0844-5
Browaeys, R., Saelens, W. & Saeys, Y. NicheNet: modeling intercellular communication by linking ligands to target genes. Nat. Methods 17, 159–162 (2020).
pubmed: 31819264
doi: 10.1038/s41592-019-0667-5
Mair, F. et al. A targeted multi-omic analysis approach measures protein expression and low-abundance transcripts on the single-cell level. Cell Rep. 31, 107499 (2020).
pubmed: 32268080
pmcid: 7224638
doi: 10.1016/j.celrep.2020.03.063
Freeman, Z. T. et al. A conserved intratumoral regulatory T cell signature identifies 4-1BB as a pan-cancer target. J. Clin. Invest. 130, 1405–1416 (2020).
pubmed: 32015231
pmcid: 7269585
doi: 10.1172/JCI128672
Cillo, A. R. et al. Immune landscape of viral- and carcinogen-driven head and neck cancer. Immunity 52, 183–199.e189 (2020).
pubmed: 31924475
pmcid: 7201194
doi: 10.1016/j.immuni.2019.11.014
Zheng, L. et al. Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science 374, abe6474 (2021).
pubmed: 34914499
doi: 10.1126/science.abe6474
Luoma, A. M. et al. Molecular pathways of colon inflammation induced by cancer immunotherapy. Cell 182, 655–671.e622 (2020).
pubmed: 32603654
pmcid: 7415717
doi: 10.1016/j.cell.2020.06.001
Kinter, A. L. et al. The common γ-chain cytokines IL-2, IL-7, IL-15, and IL-21 induce the expression of programmed death-1 and its ligands. J. Immunol. 181, 6738–6746 (2008).
pubmed: 18981091
doi: 10.4049/jimmunol.181.10.6738
Maurice, N. J., Berner, J., Taber, A. K., Zehn, D. & Prlic, M. Inflammatory signals are sufficient to elicit TOX expression in mouse and human CD8
pmcid: 8410038
doi: 10.1172/jci.insight.150744
Arpaia, N. et al. A distinct function of regulatory T cells in tissue protection. Cell 162, 1078–1089 (2015).
pubmed: 26317471
pmcid: 4603556
doi: 10.1016/j.cell.2015.08.021
Alvarez, F. et al. The alarmins IL-1 and IL-33 differentially regulate the functional specialisation of Foxp3
pubmed: 30872761
doi: 10.1038/s41385-019-0153-5
Mercer, F., Kozhaya, L. & Unutmaz, D. Expression and function of TNF and IL-1 receptors on human regulatory T cells. PLoS ONE 5, e8639 (2010).
pubmed: 20066156
pmcid: 2799662
doi: 10.1371/journal.pone.0008639
Nikolouli, E. et al. Recirculating IL-1R2
Tran, D. Q. et al. Selective expression of latency-associated peptide (LAP) and IL-1 receptor type I/II (CD121a/CD121b) on activated human FOXP3
pubmed: 19299332
pmcid: 2686183
doi: 10.1182/blood-2009-01-199950
De Martin, A. et al. Distinct microbial communities colonize tonsillar squamous cell carcinoma. Oncoimmunology 10, 1945202 (2021).
pubmed: 34367729
pmcid: 8312615
doi: 10.1080/2162402X.2021.1945202
Di Pilato, M. et al. CXCR6 positions cytotoxic T cells to receive critical survival signals in the tumor microenvironment. Cell 184, 4512–4530.e4522 (2021).
pubmed: 34343496
doi: 10.1016/j.cell.2021.07.015
Togashi, Y., Shitara, K. & Nishikawa, H. Regulatory T cells in cancer immunosuppression—implications for anticancer therapy. Nat. Rev. Clin. Oncol. 16, 356–371 (2019).
pubmed: 30705439
doi: 10.1038/s41571-019-0175-7
Plitas, G. & Rudensky, A. Regulatory T cells in cancer. Annu. Rev. Cancer Biol. 4, 459–477 (2020).
doi: 10.1146/annurev-cancerbio-030419-033428
Simpson, T. R. et al. Fc-dependent depletion of tumor-infiltrating regulatory T cells co-defines the efficacy of anti–CTLA-4 therapy against melanoma. J. Exp. Med. 210, 1695–1710 (2013).
pubmed: 23897981
pmcid: 3754863
doi: 10.1084/jem.20130579
Leelatian, N. et al. Single cell analysis of human tissues and solid tumors with mass cytometry. Cytometry B 92, 68–78 (2017).
doi: 10.1002/cyto.b.21481
Cossarizza, A. et al. Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition). Eur. J. Immunol. 51, 2708–3145 (2021).
pubmed: 34910301
doi: 10.1002/eji.202170126
Liechti, T. et al. An updated guide for the perplexed: cytometry in the high-dimensional era. Nat. Immunol. 22, 1190–1197 (2021).
pubmed: 34489590
doi: 10.1038/s41590-021-01006-z
Mair, F. & Tyznik, A. J. High-dimensional immunophenotyping with fluorescence-based cytometry: a practical guidebook. Methods Mol. Biol. 2032, 1–29 (2019).
pubmed: 31522410
doi: 10.1007/978-1-4939-9650-6_1
Perfetto, S. P., Ambrozak, D., Nguyen, R., Chattopadhyay, P. K. & Roederer, M. Quality assurance for polychromatic flow cytometry using a suite of calibration beads. Nat. Protoc. 7, 2067–2079 (2012).
pubmed: 23138348
doi: 10.1038/nprot.2012.126
Erickson, J. R. et al. AbSeq protocol using the nano-well cartridge-based rhapsody platform to generate protein and transcript expression data on the single-cell level. STAR Protoc. 1, 100092 (2020).
pubmed: 33000001
pmcid: 7523635
doi: 10.1016/j.xpro.2020.100092
Rongvaux, A. et al. Development and function of human innate immune cells in a humanized mouse model. Nat. Biotechnol. 32, 364–372 (2014).
pubmed: 24633240
pmcid: 4017589
doi: 10.1038/nbt.2858
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902.e1821 (2019).
pubmed: 31178118
pmcid: 6687398
doi: 10.1016/j.cell.2019.05.031
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).
pubmed: 29608179
pmcid: 6700744
doi: 10.1038/nbt.4096
Amezquita, R. A. et al. Orchestrating single-cell analysis with Bioconductor. Nat. Methods 17, 137–145 (2020).
pubmed: 31792435
doi: 10.1038/s41592-019-0654-x