Immunophenotypic correlates of sustained MRD negativity in patients with multiple myeloma.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
02 09 2023
02 09 2023
Historique:
received:
28
02
2022
accepted:
18
08
2023
medline:
4
9
2023
pubmed:
3
9
2023
entrez:
2
9
2023
Statut:
epublish
Résumé
The role of the immune microenvironment in maintaining disease remission in patients with multiple myeloma (MM) is not well understood. In this study, we comprehensively profile the immune system in patients with newly diagnosed MM receiving continuous lenalidomide maintenance therapy with the aim of discovering correlates of long-term treatment response. Leveraging single-cell RNA sequencing and T cell receptor β sequencing of the peripheral blood and CyTOF mass cytometry of the bone marrow, we longitudinally characterize the immune landscape in 23 patients before and one year after lenalidomide exposure. We compare patients achieving sustained minimal residual disease (MRD) negativity to patients who never achieved or were unable to maintain MRD negativity. We observe that the composition of the immune microenvironment in both the blood and the marrow varied substantially according to both MRD negative status and history of autologous stem cell transplant, supporting the hypothesis that the immune microenvironment influences the depth and duration of treatment response.
Identifiants
pubmed: 37660077
doi: 10.1038/s41467-023-40966-8
pii: 10.1038/s41467-023-40966-8
pmc: PMC10475030
doi:
Substances chimiques
Lenalidomide
F0P408N6V4
Receptors, Antigen, T-Cell, alpha-beta
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
5335Subventions
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Informations de copyright
© 2023. Springer Nature Limited.
Références
Fonseca, R. et al. Trends in overall survival and costs of multiple myeloma, 2000–2014. Leukemia 31, 1915–1921 (2017).
pubmed: 28008176
pmcid: 5596206
Ludwig, H. et al. IMWG consensus on maintenance therapy in multiple myeloma. Blood 119, 3003–3015 (2012).
pubmed: 22271445
pmcid: 3321864
McCarthy, P. L. et al. Lenalidomide maintenance after autologous stem-cell transplantation in newly diagnosed multiple myeloma: a meta-analysis. J. Clin. Oncol. 35, 3279–3289 (2017).
pubmed: 28742454
pmcid: 5652871
Ludwig, H. & Zojer, N. Fixed duration vs continuous therapy in multiple myeloma. Hematol. Am. Soc. Hematol. Educ. Program 2017, 212–222 (2017).
Diamond, B. et al. Dynamics of minimal residual disease in patients with multiple myeloma on continuous lenalidomide maintenance: a single-arm, single-centre, phase 2 trial. Lancet Haematol. 8, e422–e432 (2021).
pubmed: 34048681
Landgren, O., Lu, S. X. & Hultcrantz, M. MRD testing in multiple myeloma: the main future driver for modern tailored treatment. Semin Hematol. 55, 44–50 (2018).
pubmed: 29759154
Rustad, E. H. et al. Revealing the impact of structural variants in multiple myeloma. Blood Cancer Discov. 1, 258–273 (2020).
pubmed: 33392515
pmcid: 7774871
Rustad, E. H. et al. Timing the initiation of multiple myeloma. Nat. Commun. 11, 1917 (2020).
pubmed: 32317634
pmcid: 7174344
Maura, F. et al. Genomic landscape and chronological reconstruction of driver events in multiple myeloma. Nat. Commun. 10, 3835 (2019).
pubmed: 31444325
pmcid: 6707220
Jones, J. R. et al. Clonal evolution in myeloma: the impact of maintenance lenalidomide and depth of response on the genetics and sub-clonal structure of relapsed disease in uniformly treated newly diagnosed patients. Haematologica 104, 1440–1450 (2019).
pubmed: 30733268
pmcid: 6601103
D’Agostino, M. et al. Early relapse risk in patients with newly diagnosed multiple myeloma characterized by next-generation sequencing. Clin. Cancer Res. 26, 4832–4841 (2020).
pubmed: 32616499
Tirier, S. M. et al. Subclone-specific microenvironmental impact and drug response in refractory multiple myeloma revealed by single‐cell transcriptomics. Nat. Commun. 12, 6960 (2021).
pubmed: 34845188
pmcid: 8630108
Zhu, Y. X., Kortuem, K. M. & Stewart, A. K. Molecular mechanism of action of immune-modulatory drugs thalidomide, lenalidomide and pomalidomide in multiple myeloma. Leuk. Lymphoma 54, 683–687 (2012).
pubmed: 22966948
pmcid: 3931443
Zavidij, O. et al. Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma. Nat. Cancer 1, 493–506 https://doi.org/10.1038/s43018-020-0053-3 (2020).
Glanville, J. et al. Identifying specificity groups in the T cell receptor repertoire. Nature 547, 94–98 (2017).
pubmed: 28636589
pmcid: 5794212
Mueller, S. N., Gebhardt, T., Carbone, F. R. & Heath, W. R. Memory T cell subsets, migration patterns, and tissue residence. Annu. Rev. Immunol. 31, 137–161 (2013).
pubmed: 23215646
Shugay, M. et al. VDJdb: a curated database of T-cell receptor sequences with known antigen specificity. Nucleic Acids Res. 46, D419–D427 (2017).
pmcid: 5753233
Tickotsky, N., Sagiv, T., Prilusky, J., Shifrut, E. & Friedman, N. McPAS-TCR: a manually curated catalogue of pathology-associated T cell receptor sequences. Bioinformatics 33, 2924–2929 (2017).
pubmed: 28481982
Zhang, W. et al. PIRD: pan immune repertoire database. Bioinformatics 36, 897–903 (2019).
Kanakry, C. G. et al. Origin and evolution of the T cell repertoire after posttransplantation cyclophosphamide. JCI Insight 1, e86252 (2016).
pubmed: 27213183
pmcid: 4874509
Sethna, Z., Elhanati, Y., Callan, C. G., Walczak, A. M. & Mora, T. OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs. Bioinformatics 35, 2974–2981 (2019).
pubmed: 30657870
pmcid: 6735909
Attal, M. et al. Lenalidomide, bortezomib, and dexamethasone with transplantation for myeloma. N. Engl. J. Med. 376, 1311–1320 (2017).
pubmed: 28379796
pmcid: 6201242
Richardson, P. G. et al. Triplet therapy, transplantation, and maintenance until progression in myeloma. N. Engl. J. Med. 387, 132–147 (2022).
pubmed: 35660812
pmcid: 10040899
Gay, F. et al. Carfilzomib with cyclophosphamide and dexamethasone or lenalidomide and dexamethasone plus autologous transplantation or carfilzomib plus lenalidomide and dexamethasone, followed by maintenance with carfilzomib plus lenalidomide or lenalidomide alone for patients with newly diagnosed multiple myeloma (FORTE): a randomised, open-label, phase 2 trial. Lancet Oncol. 22, 1705–1720 (2021).
pubmed: 34774221
Parmar, H., Gertz, M., Anderson, E. I., Kumar, S. & Kourelis, T. V. Microenvironment immune reconstitution patterns correlate with outcomes after autologous transplant in multiple myeloma. Blood Adv. 5, 1797–1804 (2021).
pubmed: 33787859
pmcid: 8045512
Redoglia, V. et al. Multiple myeloma: altered CD4/CD8 ratio in bone marrow. Haematologica 75, 129–131 (1990).
pubmed: 2113506
Oka, S. & Nohgawa, M. Impact of the CD4:CD8 ratio in bone marrow on stem cell mobilization and engraftment in autologous stem cell transplant patients. J. Clin. Apher. 35, 479–482 (2020).
pubmed: 32722890
Zhao, Y. et al. Increased TOX expression associates with exhausted T cells in patients with multiple myeloma. Exp. Hematol. Oncol. 11, 12 (2022).
pubmed: 35246241
pmcid: 8895562
Prabhala, R. H. et al. Dysfunctional T regulatory cells in multiple myeloma. Blood 107, 301–304 (2006).
pubmed: 16150935
pmcid: 1895365
Beyer, M. et al. In vivo peripheral expansion of naive CD4+CD25highFoxP3+ regulatory T cells in patients with multiple myeloma. Blood 107, 3940–3949 (2006).
pubmed: 16410445
Hadjiaggelidou, C. et al. Evaluation of regulatory T cells (Tregs) alterations in patients with multiple myeloma treated with bortezomib or lenalidomide plus dexamethasone: correlations with treatment outcome. Ann. Hematol. 98, 1457–1466 (2019).
pubmed: 30895351
Zahran, A. M. et al. Higher proportion of non-classical and intermediate monocytes in newly diagnosed multiple myeloma patients in Egypt: a possible prognostic marker. Afr. J. Lab. Med. 10, 129 (2021).
pubmed: 34522628
pmcid: 8424713
Zahran, A. M. et al. Corrigendum: Higher proportion of non-classical and intermediate monocytes in newly diagnosed multiple myeloma patients in Egypt: a possible prognostic marker. Afr. J. Lab. Med. 10, 129 (2021).
Petitprez, V. et al. CD14+ CD16+ monocytes rather than CD14+ CD51/61+ monocytes are a potential cytological marker of circulating osteoclast precursors in multiple myeloma. A preliminary study. Int. J. Lab. Hematol. 37, 29–35 (2015).
pubmed: 24661393
Zheng, Y. et al. Macrophages are an abundant component of myeloma microenvironment and protect myeloma cells from chemotherapy drug-induced apoptosis. Blood 114, 3625–3628 (2009).
pubmed: 19710503
pmcid: 2766678
Landau, H. J. et al. Accelerated single cell seeding in relapsed multiple myeloma. Nat. Commun. 11, 3617 (2020).
pubmed: 32680998
pmcid: 7368016
Flores-Montero, J. et al. Next generation flow for highly sensitive and standardized detection of minimal residual disease in multiple myeloma. Leukemia 31, 2094–2103 (2017).
pubmed: 28104919
pmcid: 5629369
Kumar, S. et al. International Myeloma Working Group consensus criteria for response and minimal residual disease assessment in multiple myeloma. Lancet Oncol. 17, e328–e346 (2016).
pubmed: 27511158
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).
pubmed: 34062119
pmcid: 8238499
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
pubmed: 30787437
pmcid: 6434952
Squair, J. W. et al. Confronting false discoveries in single-cell differential expression. Nat. Commun. 12, 5692 (2021).
pubmed: 34584091
pmcid: 8479118
Gastwirth, J. L. The estimation of the Lorenz curve and Gini index. Rev. Econ. Stat. 54, 306 (1972).
Gassen, S. V. et al. FlowSOM: using self-organizing maps for visualization and interpretation of cytometry data: FlowSOM. Cytom. Part A 87, 636–645 (2015).
Amir, E. D. et al. Development of a comprehensive antibody staining database using a standardized analytics pipeline. Front. Immunol. 10, 1315 (2019).
pubmed: 31244854
pmcid: 6579881
Maecker, H. T., McCoy, J. P. & Nussenblatt, R. Standardizing immunophenotyping for the Human Immunology Project. Nat. Rev. Immunol. 12, 191–200 (2012).
pubmed: 22343568
pmcid: 3409649
Finak, G. et al. Standardizing flow cytometry immunophenotyping analysis from the Human ImmunoPhenotyping Consortium. Sci. Rep. 6, 20686 (2016).
pubmed: 26861911
pmcid: 4748244
McCarthy, D. J., Chen, Y. & Smyth, G. K. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 40, 4288–4297 (2012).
pubmed: 22287627
pmcid: 3378882
Mohanraj, S. et al. CReSCENT: cancer single cell expression toolkit. Nucleic Acids Res. 48, W372–W379 (2020).
pubmed: 32479601
pmcid: 7319570
Coffey, D. G. Immunophenotypic correlates of sustained MRD negativity in patients with multiple myeloma. UM-Myeloma-Genomics/Immunophenotypic-correlates-of-sustained-MRD-negativity https://doi.org/10.5281/zenodo.8101986 (2023).
Coffey, D. G. Immunophenotypic correlates of sustained MRD negativity in patients with multiple myeloma. davidcoffey/TCellPack https://doi.org/10.5281/zenodo.8102052 (2023).