Spatial dynamics of CD39


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
19 Oct 2024
Historique:
received: 13 12 2023
accepted: 07 10 2024
medline: 20 10 2024
pubmed: 20 10 2024
entrez: 19 10 2024
Statut: epublish

Résumé

Despite the success of immune checkpoint blockade (ICB) therapy for esophageal squamous cell cancer, the key immune cell populations that affect ICB efficacy remain unclear. Here, imaging mass cytometry of tumor tissues from ICB-treated patients identifies a distinct cell population of CD39

Identifiants

pubmed: 39426955
doi: 10.1038/s41467-024-53262-w
pii: 10.1038/s41467-024-53262-w
doi:

Substances chimiques

Apyrase EC 3.6.1.5
Programmed Cell Death 1 Receptor 0
Immune Checkpoint Inhibitors 0
ENTPD1 protein, human EC 3.6.1.5
PDCD1 protein, human 0
Antigens, CD 0
CD39 antigen EC 3.6.1.5

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

9033

Subventions

Organisme : MEXT | Japan Society for the Promotion of Science (JSPS)
ID : JP20K08311
Organisme : MEXT | Japan Society for the Promotion of Science (JSPS)
ID : JPK07376

Informations de copyright

© 2024. The Author(s).

Références

Doki, Y. et al. Nivolumab combination therapy in advanced esophageal squamous-cell carcinoma. N. Engl. J. Med. 386, 449–462 (2022).
pubmed: 35108470 doi: 10.1056/NEJMoa2111380
Sun, Jong-Mu et al. Pembrolizumab plus chemotherapy versus chemotherapy alone for first-line treatment of advanced oesophageal cancer (KEYNOTE-590): a randomised, placebo-controlled, phase 3 study. Lancet 398, 759–771 (2021).
pubmed: 34454674 doi: 10.1016/S0140-6736(21)01234-4
Kelly, R. J. et al. Adjuvant nivolumab in resected esophageal or gastroesophageal junction cancer. N. Engl. J. Med. 384, 1191–1203 (2021).
pubmed: 33789008 doi: 10.1056/NEJMoa2032125
Kato, Ken et al. Nivolumab versus chemotherapy in patients with advanced oesophageal squamous cell carcinoma refractory or intolerant to previous chemotherapy (ATTRACTION-3): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 20, 1506–1517 (2019).
pubmed: 31582355 doi: 10.1016/S1470-2045(19)30626-6
Ikeda, G., Miyakoshi, J., Yamamoto, S. & Kato, K. Nivolumab in unresectable advanced, recurrent or metastatic esophageal squamous cell carcinoma. Future Oncol. 20, 665–677 (2024).
pubmed: 38126175 doi: 10.2217/fon-2022-1092
Simoni, Y. et al. Bystander CD8(+) T cells are abundant and phenotypically distinct in human tumour infiltrates. Nature 557, 575–579 (2018).
pubmed: 29769722 doi: 10.1038/s41586-018-0130-2
Chow, Andrew et al. The ectonucleotidase CD39 identifies tumor-reactive CD8+ T cells predictive of immune checkpoint blockade efficacy in human lung cancer. Immunity 56, 1–14 (2023).
doi: 10.1016/j.immuni.2022.12.001
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
Caushi, J. X. et al. Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers. Nature 596, 126–132 (2021).
pubmed: 34290408 pmcid: 8338555 doi: 10.1038/s41586-021-03752-4
Lowery, F. J. et al. Molecular signatures of antitumor neoantigen-reactive T cells from metastatic human cancers. Science 375, 877–884 (2022).
pubmed: 35113651 pmcid: 8996692 doi: 10.1126/science.abl5447
Lee, Y. J. et al. CD39+ tissue-resident memory CD8+ T cells with a clonal overlap across compartments mediate antitumor immunity in breast cancer. Sci. Immunol. 7, eabn8390 (2022).
pubmed: 36026440 doi: 10.1126/sciimmunol.abn8390
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
Li, H. et al. Dysfunctional CD8 T cells form a proliferative, dynamically regulated compartment within human melanoma. Cell 176, 775–789.e18 (2019).
pubmed: 30595452 doi: 10.1016/j.cell.2018.11.043
Abdel-Hakeem, M. S. et al. Epigenetic scarring of exhausted T cells hinders memory differentiation upon eliminating chronic antigenic stimulation. Nat. Immunol. 22, 1008–1019 (2021).
pubmed: 34312545 pmcid: 8323971 doi: 10.1038/s41590-021-00975-5
Philip, M. & Schietinger, A. CD8+ T cell differentiation and dysfunction in cancer. Nat. Rev. Immunol. 22, 209–223 (2022).
pubmed: 34253904 doi: 10.1038/s41577-021-00574-3
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
van der Leun, A. M., Thommen, D. S. & Schumacher, T. N. CD8+ T cell states in human cancer: insights from single-cell analysis. Nat. Rev. Cancer 20, 218–232 (2020).
pubmed: 32024970 pmcid: 7115982 doi: 10.1038/s41568-019-0235-4
Canale, F. P. et al. CD39 expression defines cell exhaustion in tumor-infiltrating CD8+ T cells. Cancer Res 78, 115–128 (2018).
pubmed: 29066514 doi: 10.1158/0008-5472.CAN-16-2684
McLane, L. M., Abdel-Hakeem, M. S. & Wherry, E. J. CD8 T cell exhaustion during chronic viral infection and cancer. Annu. Rev. Immunol. 37, 457–495 (2019).
pubmed: 30676822 doi: 10.1146/annurev-immunol-041015-055318
Huang, A. C. et al. T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature 545, 60–65 (2017).
pubmed: 28397821 pmcid: 5554367 doi: 10.1038/nature22079
Miller, B. C. et al. Subsets of exhausted CD8+ T cells differentially mediate tumor control and respond to checkpoint blockade. Nat. Immunol. 20, 326–336 (2019).
pubmed: 30778252 pmcid: 6673650 doi: 10.1038/s41590-019-0312-6
Im, S. J. et al. Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy. Nature 537, 417–421 (2016).
pubmed: 27501248 pmcid: 5297183 doi: 10.1038/nature19330
Hudson, W. H. et al. Proliferating transitory T cells with an effector-like transcriptional signature emerge from PD-1(+) stem-like CD8(+) T cells during chronic infection. Immunity 51, 1043–1058.e4 (2019).
pubmed: 31810882 pmcid: 6920571 doi: 10.1016/j.immuni.2019.11.002
Siddiqui, I. et al. Intratumoral Tcf1+PD-1+CD8+ T cells with stem-like properties promote tumor control in response to vaccination and checkpoint blockade immunotherapy. Immunity 50, 195–211.e10 (2019).
pubmed: 30635237 doi: 10.1016/j.immuni.2018.12.021
Liu, B. et al. Temporal single-cell tracing reveals clonal revival and expansion of precursor exhausted T cells during anti-PD-1 therapy in lung cancer. Nat. Cancer 3, 108–121 (2022).
pubmed: 35121991 doi: 10.1038/s43018-021-00292-8
Beltra, J. C. et al. Developmental relationships of four exhausted CD8+ T cell subsets reveals underlying transcriptional and epigenetic landscape control mechanisms. Immunity 52, 825–841.e8 (2020).
pubmed: 32396847 pmcid: 8360766 doi: 10.1016/j.immuni.2020.04.014
Moldoveanu, D. et al. Spatially mapping the immune landscape of melanoma using imaging mass cytometry. Sci. Immunol. 7, eabi5072 (2022).
pubmed: 35363543 doi: 10.1126/sciimmunol.abi5072
Antoniotti, C. et al. GONO foundation investigators. upfront FOLFOXIRI plus bevacizumab with or without atezolizumab in the treatment of patients with metastatic colorectal cancer (AtezoTRIBE): a multicentre, open-label, randomised, controlled, phase 2 trial. Lancet Oncol. 23, 876–887 (2022).
pubmed: 35636444 doi: 10.1016/S1470-2045(22)00274-1
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
Hoch T. et al. Multiplexed imaging mass cytometry of the chemokine milieus in melanoma characterizes features of the response to immunotherapy. Sci. Immunol. 7, eabk1692 (2022).
Thommen, D. S. et al. A transcriptionally and functionally distinct PD-1+ CD8+ T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade. Nat. Med. 24, 994–1004 (2018).
pubmed: 29892065 pmcid: 6110381 doi: 10.1038/s41591-018-0057-z
Kumagai, S. et al. The PD-1 expression balance between effector and regulatory T cells predicts the clinical efficacy of PD-1 blockade therapies. Nat. Immunol. 21, 1346–1358 (2020).
pubmed: 32868929 doi: 10.1038/s41590-020-0769-3
Rahim, M. K. et al. Dynamic CD8+ T cell responses to cancer immunotherapy in human regional lymph nodes are disrupted in metastatic lymph nodes. Cell 186, 1127–1143.e18 (2023).
pubmed: 36931243 pmcid: 10348701 doi: 10.1016/j.cell.2023.02.021
Huang, Q. et al. The primordial differentiation of tumor-specific memory CD8+ T cells as bona fide responders to PD-1/PD-L1 blockade in draining lymph nodes. Cell 185, 4049–4066.e25 (2022).
pubmed: 36208623 doi: 10.1016/j.cell.2022.09.020
Galletti, G. et al. Two subsets of stem-like CD8+ memory T cell progenitors with distinct fate commitments in humans. Nat. Immunol. 21, 1552–1562 (2020).
pubmed: 33046887 pmcid: 7610790 doi: 10.1038/s41590-020-0791-5
Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013 (2018).
pubmed: 30388456 pmcid: 6641984 doi: 10.1016/j.cell.2018.10.038
Wang, X. Q. et al. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature 621, 868–876 (2023).
pubmed: 37674077 pmcid: 10533410 doi: 10.1038/s41586-023-06498-3
Eberhardt, C. S. et al. Functional HPV-specific PD-1+ stem-like CD8 T cells in head and neck cancer. Nature 597, 279–284 (2021).
pubmed: 34471285 pmcid: 10201342 doi: 10.1038/s41586-021-03862-z
Vanhersecke, L. et al. Mature tertiary lymphoid structures predict immune checkpoint inhibitor efficacy in solid tumors independently of PD-L1 expression. Nat. Cancer 2, 794–802 (2021).
pubmed: 35118423 pmcid: 8809887 doi: 10.1038/s43018-021-00232-6
Helmink, B. A. et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature 577, 549–555 (2020).
pubmed: 31942075 pmcid: 8762581 doi: 10.1038/s41586-019-1922-8
Ng, K. W. et al. Antibodies against endogenous retroviruses promote lung cancer immunotherapy. Nature 616, 563–573 (2023).
pubmed: 37046094 pmcid: 10115647 doi: 10.1038/s41586-023-05771-9
Holm, J. S. et al. Neoantigen-specific CD8 T cell responses in the peripheral blood following PD-L1 blockade might predict therapy outcome in metastatic urothelial carcinoma. Nat. Commun. 13, 1935 (2022).
pubmed: 35410325 pmcid: 9001725 doi: 10.1038/s41467-022-29342-0
Dammeijer, F. et al. The PD-1/PD-L1-checkpoint restrains T cell immunity in tumor-draining lymph nodes. Cancer Cell 38, 685–700 (2020).
pubmed: 33007259 doi: 10.1016/j.ccell.2020.09.001
Dähling, S. et al. Type 1 conventional dendritic cells maintain and guide the differentiation of precursors of exhausted T cells in distinct cellular niches. Immunity 55, 656–670 (2022).
pubmed: 35366396 doi: 10.1016/j.immuni.2022.03.006
Cercek, A. et al. PD-1 blockade in mismatch repair-deficient, locally advanced rectal cancer. N. Engl. J. Med. 386, 2363–2376 (2022).
pubmed: 35660797 pmcid: 9492301 doi: 10.1056/NEJMoa2201445
Chow, A., Perica, K., Klebanoff, C. A. & Wolchok, J. D. Clinical implications of T cell exhaustion for cancer immunotherapy. Nat. Rev. Clin. Oncol. 19, 775–790 (2022).
pubmed: 36216928 pmcid: 10984554 doi: 10.1038/s41571-022-00689-z
Ryu, H. et al. Merkel cell polyomavirus-specific and CD39+CLA+ CD8 T cells as blood-based predictive biomarkers for PD-1 blockade in Merkel cell carcinoma. Cell Rep. Med 5, 101390 (2024).
pubmed: 38340724 pmcid: 10897544 doi: 10.1016/j.xcrm.2023.101390
Schumacher, T. N. & Thommen, D. S. Tertiary lymphoid structures in cancer. Science 375, eabf9419 (2022).
pubmed: 34990248 doi: 10.1126/science.abf9419
Luo, J. et al. Deciphering radiological stable disease to immune checkpoint inhibitors. Ann. Oncol. 33, 824–835 (2022).
pubmed: 35533926 doi: 10.1016/j.annonc.2022.04.450
Zanotelli, V. & Bodenmiller, B. IMC segmentation pipeline: a pixelclassification based multiplexed image segmentation pipeline. Zenodo https://doi.org/10.5281/zenodo.3841960 (2017).
Lu, P. et al. IMC-Denoise: a content aware denoising pipeline to enhance Imaging Mass Cytometry. Nat. Commun. 14, 1601 (2023).
pubmed: 36959190 pmcid: 10036333 doi: 10.1038/s41467-023-37123-6
Berg, S. et al. ilastik: interactive machine learning for (bio)image analysis. Nat. Methods 16, 1226–1232 (2019).
pubmed: 31570887 doi: 10.1038/s41592-019-0582-9
Lamprecht, M. R., Sabatini, D. M. & Carpenter, A. E. CellProfiler: free, versatile software for automated biological image analysis. Biotechniques 42, 71–75 (2007).
pubmed: 17269487 doi: 10.2144/000112257
Schapiro, D. et al. histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. Nat. Methods 14, 873–876 (2017).
pubmed: 28783155 pmcid: 5617107 doi: 10.1038/nmeth.4391
Chevrier, S. et al. Compensation of signal spillover in suspension and imaging mass cytometry. Cell Syst. 6, 612–620.e5 (2018).
pubmed: 29605184 pmcid: 5981006 doi: 10.1016/j.cels.2018.02.010
Hunter, B. et al. OPTIMAL: An OPTimized imaging mass cytometry AnaLysis framework for benchmarking segmentation and data exploration. Cytom. A 105, 36–53 (2024).
doi: 10.1002/cyto.a.24803
Stoltzfus, C. R. et al. CytoMAP: a spatial analysis toolbox reveals features of myeloid cell organization in lymphoid tissues. Cell Rep. 31, 107523 (2020).
pubmed: 32320656 pmcid: 7233132 doi: 10.1016/j.celrep.2020.107523
Mathew, D. et al. UPenn COVID processing unit; Betts MR, Meyer NJ, Wherry EJ. deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications. Science 369, eabc8511 (2020).
pubmed: 32669297 pmcid: 7402624 doi: 10.1126/science.abc8511
Tanoue, K., & Baba, E. Spatial dynamics of CD39

Auteurs

Kenro Tanoue (K)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Hirofumi Ohmura (H)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Department of Oncology and Social Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Koki Uehara (K)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Mamoru Ito (M)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Kyoko Yamaguchi (K)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Kenji Tsuchihashi (K)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Yudai Shinohara (Y)

Department of Hematology/Oncology, Japan Community Healthcare Organization Kyushu Hospital, Fukuoka, Japan.

Peng Lu (P)

Department of Imaging Science Program, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, USA.

Shingo Tamura (S)

Department of Medical Oncology, NHO National Hospital Organization Kyushu Medical Center, Fukuoka, Japan.

Hozumi Shimokawa (H)

Department of Medical Oncology, Hamanomachi Hospital, Fukuoka, Japan.

Taichi Isobe (T)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Department of Oncology and Social Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Hiroshi Ariyama (H)

Department of Medical Oncology, Kitakyushu Municipal Medical Center, Fukuoka, Japan.

Yoshihiro Shibata (Y)

Department of Medical Oncology, Fukuoka Wajiro Hospital, Fukuoka, Japan.

Risa Tanaka (R)

Department of Medical Oncology, St Mary's Hospital, Kurume, Japan.

Hitoshi Kusaba (H)

Department of Medical Oncology, Hamanomachi Hospital, Fukuoka, Japan.

Taito Esaki (T)

Department of Gastrointestinal and Medical Oncology, National Kyushu Cancer Center, Fukuoka, Japan.

Kenji Mitsugi (K)

Department of Medical Oncology, Sasebo Kyosai Hospital, Nagasaki, Japan.

Daisuke Kiyozawa (D)

Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Takeshi Iwasaki (T)

Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Hidetaka Yamamoto (H)

Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Department of Pathology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.

Yoshinao Oda (Y)

Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Koichi Akashi (K)

Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Eishi Baba (E)

Department of Oncology and Social Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan. baba.eishi.889@m.kyushu-u.ac.jp.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH