[en] Investigation of the cellular and molecular mechanisms of disease progression from precursor plasma cell disorders to active disease increases our understanding of multiple myeloma (MM) pathogenesis and supports the development of novel therapeutic strategies. In this analysis, single-cell RNA sequencing, surface protein profiling, and B lymphocyte antigen receptor profiling of unsorted, whole bone marrow (BM) mononuclear cell samples was used to study molecular changes in tumor cells and the tumor microenvironment (TME). A cell atlas of the BM microenvironment was generated from 123 subjects including healthy volunteers and patients with monoclonal gammopathy of unknown significance (MGUS), smoldering MM (SMM), and MM. These analyses revealed commonalities in molecular pathways, including MYC signaling, E2F targets and interferon alpha response, that were altered during disease progression. Evidence of early dysregulation of the immune system in MGUS and SMM, which increases and impacts many cell types as the disease progresses, was found. In parallel with disease progression, population shifts in CD8 + T cells, macrophages, and classical dendritic cells were observed, and the resulting differences in CD8 + T cells and macrophages were associated with poor overall survival outcomes. Potential ligand-receptor interactions that may play a role during the transition from precursor stages to MM were identified, along with potential biomarkers of disease progression, some of which may represent novel therapeutic targets. MIF, IL15, CD320, HGF and FAM3C were detected as potential regulators of the TME by plasma cells, while SERPINA1 and BAFF (TNFSF13B) were found to have the highest potential to contribute to the downstream changes observed between precursor stage and MM cells. These findings demonstrate that myeloma tumorigenesis is associated with dysregulation of molecular pathways driven by gradually occurring immunophenotypic changes in the tumor and TME. Trial registration: This project has been registered at EudraCT (European Union Drug Regulating Authorities Clinical Trials Database) with protocol number NOPRODMMY0001 and EudraCT Number 2018-004443-23 on 12 December 2018.
Disciplines :
Hematology
Author, co-author :
Bergiers, Isabelle ; Johnson & Johnson, Beerse, Belgium
Köse, Murat Cem ; Department of Hematology, CHU of Liège, Liège, Belgium
Skerget, Sheri; Johnson & Johnson, Spring House, Spring House, Pennsylvania, United States of America
Malfait, Milan ; Department of Applied Mathematics, Computer Science and Statistics, University of Ghent, Ghent, Belgium
Fourneau, Nele ; Johnson & Johnson, Beerse, Belgium
Ellis, Jenna-Claire ; Johnson & Johnson, Beerse, Belgium
Vanhoof, Greet; Johnson & Johnson, Beerse, Belgium
Smets, Tina; Johnson & Johnson, Beerse, Belgium
Verbist, Bie; Johnson & Johnson, Beerse, Belgium
De Maeyer, Dries ; Johnson & Johnson, Beerse, Belgium
Van Houdt, Jeroen; Johnson & Johnson, Beerse, Belgium
Van der Borght, Koen; Johnson & Johnson, Beerse, Belgium
Verona, Raluca; Johnson & Johnson, Spring House, Spring House, Pennsylvania, United States of America
Heidrich, Bradley; Johnson & Johnson, Spring House, Spring House, Pennsylvania, United States of America
Kurth, William ; Université de Liège - ULiège > Département des sciences cliniques
Delforge, Michel; University Hospital Leuven, Leuven, Belgium
Meuleman, Nathalie; Department of Hematology, Institut Jules Bordet, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
Van Droogenbroeck, Jan; Department of Haematology, AZ Sint-Jan Brugge-Oostende AV, Brugge, Belgium
Vlummens, Philip; Department of Clinical Hematology, Ghent University Hospital, Ghent, Belgium
Heuck, Christoph J; Johnson & Johnson, Spring House, Spring House, Pennsylvania, United States of America
Beguin, Yves ; Université de Liège - ULiège > Département des sciences cliniques
Bahlis, Nizar ; Department of Hematology and Oncology, University of Calgary, Calgary, Alberta, Canada
Casneuf, Tineke; Johnson & Johnson, Beerse, Belgium
Caers, Jo ; Université de Liège - ULiège > Département des sciences cliniques > Hématologie
1. Bianchi G, Anderson KC. Understanding biology to tackle the disease: multiple myeloma from bench to bedside, and back. CA Cancer J Clin. 2014;64(6): 422–44. https://doi.org/10.3322/caac.21252 PMID: 25266555
2. National Cancer Institute (NCI). Surveillance, Epidemiology, and End Results (SEER) Program. Available from: https://seer.cancer.gov/
3. Braunlin M, Belani R, Buchanan J, Wheeling T, Kim C. Trends in the multiple myeloma treatment landscape and survival: a U.S. analysis using 2011–2019 oncology clinic electronic health record data. Leuk Lymphoma. 2021;62(2): 377–86. https://doi.org/10.1080/10428194.2020.1827253 PMID: 33026271
4. Neumeister P, Schulz E, Pansy K, Szmyra M, Deutsch AJ. Targeting the microenvironment for treating multiple myeloma. Int J Mol Sci. 2022;23(14):7627. https://doi.org/10.3390/ijms23147627 PMID: 35886976
5. Rajkumar SV. Multiple myeloma: 2022 update on diagnosis, risk stratification, and management. Am J Hematol. 2022;97(8): 1086–107. https://doi.org/10.1002/ajh.26590 PMID: 35560063
6. van de Donk NWCJ, Pawlyn C, Yong KL. Multiple myeloma. Lancet. 2021;397(10272): 410–27. https://doi.org/10.1016/S0140-6736(21)00135-5 PMID: 33516340
7. Ho M, Patel A, Goh CY, Moscvin M, Zhang L, Bianchi G. Changing paradigms in diagnosis and treatment of monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). Leukemia. 2020;34(12): 3111–25. https://doi.org/10.1038/s41375-020-01051-x PMID: 33046818
8. Zhan F, Huang Y, Colla S, Stewart JP, Hanamura I, Gupta S, et al. The molecular classification of multiple myeloma. Blood. 2006;108(6): 2020–8. https://doi.org/10.1182/blood-2005-11-013458 PMID: 16728703
9. Skerget S, Penaherrera D, Chari A, Jagannath S, Siegel DS, Vij R, et al. Comprehensive molecular profiling of multiple myeloma identifies refined copy number and expression subtypes. Nat Genet. 2024;56(9): 1878–89. https://doi.org/10.1038/s41588-024-01853-0 PMID: 39160255
10. Bustoros M, Anand S, Sklavenitis-Pistofidis R, Redd R, Boyle EM, Zhitomirsky B, et al. Genetic subtypes of smoldering multiple myeloma are associated with distinct pathogenic phenotypes and clinical outcomes. Nat Commun. 2022;13(1):3449. https://doi.org/10.1038/s41467-022-30694-w PMID: 35705541
11. Bustoros M, Sklavenitis-Pistofidis R, Park J, Redd R, Zhitomirsky B, Dunford AJ, et al. Genomic profiling of smoldering multiple myeloma identifies patients at a high risk of disease progression. J Clin Oncol. 2020;38(21): 2380–9. https://doi.org/10.1200/JCO.20.00437 PMID: 32442065
12. Oben B, Froyen G, Maclachlan KH, Leongamornlert D, Abascal F, Zheng-Lin B, et al. Whole-genome sequencing reveals progressive versus stable myeloma precursor conditions as two distinct entities. Nat Commun. 2021;12(1):1861. https://doi.org/10.1038/s41467-021-22140-0 PMID: 33767199
13. Alberge J-B, Dutta AK, Poletti A, Coorens THH, Lightbody ED, Toenges R, et al. Genomic landscape of multiple myeloma and its precursor conditions. Nat Genet. 2025;57(6): 1493–503. https://doi.org/10.1038/s41588-025-02196-0 PMID: 40399554
14. Ledergor G, Weiner A, Zada M, Wang S-Y, Cohen YC, Gatt ME, et al. Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma. Nat Med. 2018;24(12): 1867–76. https://doi.org/10.1038/s41591-018-0269-2 PMID: 30523328
15. Zavidij O, Haradhvala NJ, Mouhieddine TH, Sklavenitis-Pistofidis R, Cai S, Reidy M, et al. Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma. Nat Cancer. 2020;1(5): 493–506. https://doi.org/10.1038/s43018-020-0053-3 PMID: 33409501
16. Schinke C, Poos AM, Bauer M, John L, Johnson S, Deshpande S, et al. Characterizing the role of the immune microenvironment in multiple myeloma progression at a single-cell level. Blood Adv. 2022;6(22): 5873–83. https://doi.org/10.1182/bloodadvances.2022007217 PMID: 35977111
17. de Jong MME, Kellermayer Z, Papazian N, Tahri S, Hofste Op Bruinink D, Hoogenboezem R, et al. The multiple myeloma microenvironment is defined by an inflammatory stromal cell landscape. Nat Immunol. 2021;22(6): 769–80. https://doi.org/10.1038/s41590-021-00931-3 PMID: 34017122
18. Boiarsky R, Haradhvala NJ, Alberge J-B, Sklavenitis-Pistofidis R, Mouhieddine TH, Zavidij O, et al. Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis. Nat Commun. 2022;13(1):7040. https://doi.org/10.1038/s41467-022-33944-z PMID: 36396631
19. Liu R, Gao Q, Foltz SM, Fowles JS, Yao L, Wang JT, et al. Co-evolution of tumor and immune cells during progression of multiple myeloma. Nat Commun. 2021;12(1):2559. https://doi.org/10.1038/s41467-021-22804-x PMID: 33963182
21. Rizzieri D, Paul B, Kang Y. Metabolic alterations and the potential for targeting metabolic pathways in the treatment of multiple myeloma. J Cancer Metastasis Treat. 2019;5:26. https://doi.org/10.20517/2394-4722.2019.05 PMID: 31020046
22. Derksen PWB, Tjin E, Meijer HP, Klok MD, MacGillavry HD, van Oers MHJ, et al. Illegitimate WNT signaling promotes proliferation of multiple myeloma cells. Proc Natl Acad SciUSA. 2004;101(16): 6122–7. https://doi.org/10.1073/pnas.0305855101 PMID: 15067127
23. Colombo M, Galletti S, Garavelli S, Platonova N, Paoli A, Basile A, et al. Notch signaling deregulation in multiple myeloma: a rational molecular target. Oncotarget. 2015;6(29): 26826–40. https://doi.org/10.18632/oncotarget.5025 PMID: 26308486
24. van Andel H, Kocemba KA, Spaargaren M, Pals ST. Aberrant Wnt signaling in multiple myeloma: molecular mechanisms and targeting options. Leukemia. 2019;33(5): 1063–75. https://doi.org/10.1038/s41375-019-0404-1 PMID: 30770859
25. Ashman LK, Griffith R. Therapeutic targeting of c-KIT in cancer. Expert Opin Investig Drugs. 2013;22(1): 103–15. https://doi.org/10.1517/13543784.2013.740010 PMID: 23127174
26. Tohami T, Drucker L, Shapiro H, Radnay J, Lishner M. Overexpression of tetraspanins affects multiple myeloma cell survival and invasive potential. FASEB J. 2007;21(3): 691–9. https://doi.org/10.1096/fj.06-6610com PMID: 17210782
27. Gao Q, Yellapantula V, Fenelus M, Pichardo J, Wang L, Landgren O, et al. Tumor suppressor CD99 is downregulated in plasma cell neoplasms lacking CCND1 translocation and distinguishes neoplastic from normal plasma cells and B-cell lymphomas with plasmacytic differentiation from primary plasma cell neoplasms. Mod Pathol. 2018;31(6): 881–9. https://doi.org/10.1038/s41379-018-0011-0 PMID: 29403080
29. Mikulasova A, Smetana J, Wayhelova M, Janyskova H, Sandecka V, Kufova Z, et al. Genomewide profiling of copy-number alteration in monoclonal gammopathy of undetermined significance. Eur J Haematol. 2016;97(6): 568–75. https://doi.org/10.1111/ejh.12774 PMID: 27157252
30. Blank CU, Haining WN, Held W, Hogan PG, Kallies A, Lugli E, et al. Defining “T cell exhaustion”. Nat Rev Immunol. 2019;19(11): 665–74. https://doi.org/10.1038/s41577-019-0221-9 PMID: 31570879
31. Zhao Y, Liao P, Huang S, Deng T, Tan J, Huang Y, et al. Increased TOX expression associates with exhausted T cells in patients with multiple myeloma. Exp Hematol Oncol. 2022;11(1):12. https://doi.org/10.1186/s40164-022-00267-0 PMID: 35246241
32. Wherry EJ, Ha S-J, Kaech SM, Haining WN, Sarkar S, Kalia V, et al. Molecular signature of CD8+ T cell exhaustion during chronic viral infection. Immunity. 2007;27(4): 670–84. https://doi.org/10.1016/j.immuni.2007.09.006 PMID: 17950003
33. Yan M, Hu J, Yuan H, Xu L, Liao G, Jiang Z, et al. Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition. Mol Ther Nucleic Acids. 2021;26: 1115–29. https://doi.org/10.1016/j.omtn.2021.10.011 PMID: 34786214
34. Benson MJ, Dillon SR, Castigli E, Geha RS, Xu S, Lam K-P, et al. Cutting edge: the dependence of plasma cells and independence of memory B cells on BAFF and APRIL. J Immunol. 2008;180(6): 3655–9. https://doi.org/10.4049/jimmunol.180.6.3655 PMID: 18322170
35. Novak AJ, Darce JR, Arendt BK, Harder B, Henderson K, Kindsvogel W, et al. Expression of BCMA, TACI, and BAFF-R in multiple myeloma: a mechanism for growth and survival. Blood. 2004;103(2): 689–94. https://doi.org/10.1182/blood-2003-06-2043 PMID: 14512299
36. Rébé C, Ghiringhelli F. Interleukin-1β and cancer. Cancers (Basel). 2020;12(7):1791. https://doi.org/10.3390/cancers12071791 PMID: 32635472
37. Deng L, Chen N, Li Y, Zheng H, Lei Q. CXCR6/CXCL16 functions as a regulator in metastasis and progression of cancer. Biochim Biophys Acta. 2010;1806(1): 42–9. https://doi.org/10.1016/j.bbcan.2010.01.004 PMID: 20122997
38. Korbecki J, Bajdak-Rusinek K, Kupnicka P, Kapczuk P, Simińska D, Chlubek D, et al. The role of CXCL16 in the pathogenesis of cancer and other diseases. Int J Mol Sci. 2021;22(7):3490. https://doi.org/10.3390/ijms22073490 PMID: 33800554
39. Delli Carpini J, Karam AK, Montgomery L. Vascular endothelial growth factor and its relationship to the prognosis and treatment of breast, ovarian, and cervical cancer. Angiogenesis. 2010;13(1): 43–58. https://doi.org/10.1007/s10456-010-9163-3 PMID: 20229258
40. Rao L, Giannico D, Leone P, Solimando AG, Maiorano E, Caporusso C, et al. HB-EGF-EGFR signaling in bone marrow endothelial cells mediates angiogenesis associated with multiple myeloma. Cancers (Basel). 2020;12(1):173. https://doi.org/10.3390/cancers12010173 PMID: 31936715
41. Zhang L, Tai Y-T, Ho MZG, Qiu L, Anderson KC. Interferon-alpha-based immunotherapies in the treatment of B cell-derived hematologic neoplasms in today’s treat-to-target era. Exp Hematol Oncol. 2017;6:20. https://doi.org/10.1186/s40164-017-0081-6 PMID: 28725493
42. Jego G, Palucka AK, Blanck J-P, Chalouni C, Pascual V, Banchereau J. Plasmacytoid dendritic cells induce plasma cell differentiation through type I interferon and interleukin 6. Immunity. 2003;19(2): 225–34. https://doi.org/10.1016/s1074-7613(03)00208-5 PMID: 12932356
43. Knight A, Rihova L, Kralova R, Penka M, Adam Z, Pour L, et al. Plasmacytoid dendritic cells in patients with MGUS and multiple myeloma. J Clin Med. 2021;10(16):3717. https://doi.org/10.3390/jcm10163717 PMID: 34442012
44. van der Leun AM, Thommen DS, Schumacher TN. CD8+ T cell states in human cancer: insights from single-cell analysis. Nat Rev Cancer. 2020;20(4): 218–32. https://doi.org/10.1038/s41568-019-0235-4 PMID: 32024970
45. Guillerey C, Harjunpää H, Carrié N, Kassem S, Teo T, Miles K, et al. TIGIT immune checkpoint blockade restores CD8+ T-cell immunity against multiple myeloma. Blood. 2018;132(16): 1689–94. https://doi.org/10.1182/blood-2018-01-825265 PMID: 29986909
46. Hallett WHD, Jing W, Drobyski WR, Johnson BD. Immunosuppressive effects of multiple myeloma are overcome by PD-L1 blockade. Biol Blood Marrow Transplant. 2011;17(8): 1133–45. https://doi.org/10.1016/j.bbmt.2011.03.011 PMID: 21536144
47. Tan J, Chen S, Huang J, Chen Y, Yang L, Wang C, et al. Increased exhausted CD8+ T cells with programmed death-1, T-cell immunoglobulin and mucin-domain-containing-3 phenotype in patients with multiple myeloma. Asia Pac J Clin Oncol. 2018;14(5):e266–74. https://doi.org/10.1111/ajco.13033 PMID: 29943497
48. Zelle-Rieser C, Thangavadivel S, Biedermann R, Brunner A, Stoitzner P, Willenbacher E, et al. T cells in multiple myeloma display features of exhaustion and senescence at the tumor site. J Hematol Oncol. 2016;9(1):116. https://doi.org/10.1186/s13045-016-0345-3 PMID: 27809856
49. Pilcher W, Thomas BE, Bhasin SS, Jayasinghe RG, Yao L, Gonzalez-Kozlova E, et al. Cross center single-cell RNA sequencing study of the immune microenvironment in rapid progressing multiple myeloma. NPJ Genom Med. 2023;8(1):3. https://doi.org/10.1038/s41525-022-00340-x PMID: 36702834
50. Vishwamitra D, Skerget S, Cortes D, et al. Mechanisms of resistance and relapse with talquetamab in patients with relapsed/refractory multiple myeloma from the phase 1/2 MonumenTAL-1 study. Presented at ASH 2023; 2023 Dec 10–13; San Diego, CA. Poster #1933.
51. Vishwamitra D SS, Cortes D, et al. Longitudinal correlative profiles of responders, nonresponders, and those with relapse on treatment with teclistamab in the phase 1/2 MajesTEC-1 study of patients with relapsed/refractory multiple myeloma. Presented at ASH 2022; 2022 Dec 10; San Diego, CA. Presentation #455. 2022.
52. Berardi S, Ria R, Reale A, De Luisi A, Catacchio I, Moschetta M, et al. Multiple myeloma macrophages: pivotal players in the tumor microenvironment. J Oncol. 2013;2013:183602. https://doi.org/10.1155/2013/183602 PMID: 23431298
53. Sun J, Park C, Guenthner N, Gurley S, Zhang L, Lubben B, et al. Tumor-associated macrophages in multiple myeloma: advances in biology and therapy. J Immunother Cancer. 2022;10(4):e003975. https://doi.org/10.1136/jitc-2021-003975 PMID: 35428704
54. Hengeveld PJ, Kersten MJ. B-cell activating factor in the pathophysiology of multiple myeloma: a target for therapy? Blood Cancer J. 2015;5(2):e282. https://doi.org/10.1038/bcj.2015.3 PMID: 25723853
55. Li W, Li J, Su C, Zou WY, Luo S. New targets of PS-341: BAFF and APRIL. Med Oncol. 2010;27(2): 439–45. https://doi.org/10.1007/s12032-009-9230-z PMID: 19452288
56. Moreaux J, Legouffe E, Jourdan E, Quittet P, Rème T, Lugagne C, et al. BAFF and APRIL protect myeloma cells from apoptosis induced by interleukin 6 deprivation and dexamethasone. Blood. 2004;103(8): 3148–57. https://doi.org/10.1182/blood-2003-06-1984 PMID: 15070697
57. Mantovani A, Allavena P, Marchesi F, Garlanda C. Macrophages as tools and targets in cancer therapy. Nat Rev Drug Discov. 2022;21(11): 799–820. https://doi.org/10.1038/s41573-022-00520-5 PMID: 35974096
58. Beyar-Katz O, Magidey K, Reiner-Benaim A, Barak N, Avivi I, Cohen Y, et al. Proinflammatory macrophages promote multiple myeloma resistance to bortezomib therapy. Mol Cancer Res. 2019;17(11): 2331–40. https://doi.org/10.1158/1541-7786.MCR-19-0487 PMID: 31409628
59. Chen J, He D, Chen Q, Guo X, Yang L, Lin X, et al. BAFF is involved in macrophage-induced bortezomib resistance in myeloma. Cell Death Dis. 2017;8(11):e3161. https://doi.org/10.1038/cddis.2017.533 PMID: 29095438
60. Abdelmagid SM, Barbe MF, Safadi FF. Role of inflammation in the aging bones. Life Sci. 2015;123: 25–34. https://doi.org/10.1016/j.lfs.2014.11.011 PMID: 25510309
61. Schlundt C, Fischer H, Bucher CH, Rendenbach C, Duda GN, Schmidt-Bleek K. The multifaceted roles of macrophages in bone regeneration: a story of polarization, activation and time. Acta Biomater. 2021;133: 46–57. https://doi.org/10.1016/j.actbio.2021.04.052 PMID: 33974949
62. Brimnes MK, Svane IM, Johnsen HE. Impaired functionality and phenotypic profile of dendritic cells from patients with multiple myeloma. Clin Exp Immunol. 2006;144(1): 76–84. https://doi.org/10.1111/j.1365-2249.2006.03037.x PMID: 16542368
63. Ratta M, Fagnoni F, Curti A, Vescovini R, Sansoni P, Oliviero B, et al. Dendritic cells are functionally defective in multiple myeloma: the role of interleukin-6. Blood. 2002;100(1): 230–7. https://doi.org/10.1182/blood.v100.1.230 PMID: 12070032
64. Hoang M-D, Jung S-H, Lee H-J, Lee Y-K, Nguyen-Pham T-N, Choi N-R, et al. Dendritic cell-based cancer immunotherapy against multiple myeloma: from bench to clinic. Chonnam Med J. 2015;51(1): 1–7. https://doi.org/10.4068/cmj.2015.51.1.1 PMID: 25914874
65. Nguyen-Pham T-N, Lee Y-K, Kim H-J, Lee J-J. Immunotherapy using dendritic cells against multiple myeloma: how to improve? Clin Dev Immunol. 2012;2012:397648. https://doi.org/10.1155/2012/397648 PMID: 22481968
66. Verheye E, Bravo Melgar J, Deschoemaeker S, Raes G, Maes A, De Bruyne E, et al. Dendritic cell-based immunotherapy in multiple myeloma: challenges, opportunities, and future directions. Int J Mol Sci. 2022;23(2):904. https://doi.org/10.3390/ijms23020904 PMID: 35055096
67. Dhodapkar MV, Krasovsky J, Olson K. T cells from the tumor microenvironment of patients with progressive myeloma can generate strong, tumor-specific cytolytic responses to autologous, tumor-loaded dendritic cells. Proc Natl Acad SciUSA. 2002;99(20): 13009–13. https://doi.org/10.1073/pnas.202491499 PMID: 12235374
68. Leone P, Berardi S, Frassanito MA, Ria R, De Re V, Cicco S, et al. Dendritic cells accumulate in the bone marrow of myeloma patients where they protect tumor plasma cells from CD8+ T-cell killing. Blood. 2015;126(12): 1443–51. https://doi.org/10.1182/blood-2015-01-623975 PMID: 26185130
69. Vasir B, Borges V, Wu Z, Grosman D, Rosenblatt J, Irie M, et al. Fusion of dendritic cells with multiple myeloma cells results in maturation and enhanced antigen presentation. Br J Haematol. 2005;129(5): 687–700. https://doi.org/10.1111/j.1365-2141.2005.05507.x PMID: 15916692
71. Soumoy L, Kindt N, Ghanem G, Saussez S, Journe F. Role of macrophage Migration Inhibitory Factor (MIF) in melanoma. Cancers (Basel). 2019;11(4):529. https://doi.org/10.3390/cancers11040529 PMID: 31013837
72. Xu J, Yu N, Zhao P, Wang F, Huang J, Cui Y, et al. Intratumor heterogeneity of MIF expression correlates with extramedullary involvement of multiple myeloma. Front Oncol. 2021;11:694331. https://doi.org/10.3389/fonc.2021.694331 PMID: 34268123
73. Gutiérrez-González A, Martínez-Moreno M, Samaniego R, Arellano-Sánchez N, Salinas-Muñoz L, Relloso M, et al. Evaluation of the potential therapeutic benefits of macrophage reprogramming in multiple myeloma. Blood. 2016;128(18): 2241–52. https://doi.org/10.1182/blood-2016-01-695395 PMID: 27625360
74. Wang Q, Zhao D, Xian M, Wang Z, Bi E, Su P, et al. MIF as a biomarker and therapeutic target for overcoming resistance to proteasome inhibitors in human myeloma. Blood. 2020;136(22): 2557–73. https://doi.org/10.1182/blood.2020005795 PMID: 32582913
75. Zheng Y, Wang Q, Li T, Qian J, Lu Y, Li Y, et al. Role of myeloma-derived MIF in myeloma cell adhesion to bone marrow and chemotherapy response. J Natl Cancer Inst. 2016;108(11):djw131. https://doi.org/10.1093/jnci/djw131 PMID: 27381622
76. Doedens AL, Rubinstein MP, Gross ET, Best JA, Craig DH, Baker MK, et al. Molecular programming of tumor-infiltrating CD8+ T cells and IL15 resistance. Cancer Immunol Res. 2016;4(9): 799–811. https://doi.org/10.1158/2326-6066.CIR-15-0178 PMID: 27485135
77. Knudson KM, Hicks KC, Alter S, Schlom J, Gameiro SR. Mechanisms involved in IL-15 superagonist enhancement of anti-PD-L1 therapy. J Immunother Cancer. 2019;7(1):82. https://doi.org/10.1186/s40425-019-0551-y PMID: 30898149
78. Zhang S, Zhao J, Bai X, Handley M, Shan F. Biological effects of IL-15 on immune cells and its potential for the treatment of cancer. Int Immunopharmacol. 2021;91:107318. https://doi.org/10.1016/j.intimp.2020.107318 PMID: 33383444
79. Mahtouk K, Tjin EPM, Spaargaren M, Pals ST. The HGF/MET pathway as target for the treatment of multiple myeloma and B-cell lymphomas. Biochim Biophys Acta. 2010;1806(2): 208–19. https://doi.org/10.1016/j.bbcan.2010.07.006 PMID: 20655987
80. Owusu BY, Galemmo R, Janetka J, Klampfer L. Hepatocyte growth factor, a key tumor-promoting factor in the tumor microenvironment. Cancers (Basel). 2017;9(4):35. https://doi.org/10.3390/cancers9040035 PMID: 28420162
81. Spina A, De Pasquale V, Cerulo G, Cocchiaro P, Della Morte R, Avallone L, et al. HGF/c-MET axis in tumor microenvironment and metastasis formation. Biomedicines. 2015;3(1): 71–88. https://doi.org/10.3390/biomedicines3010071 PMID: 28536400
82. Li L, Zhang X, Kovacic S, Long AJ, Bourque K, Wood CR, et al. Identification of a human follicular dendritic cell molecule that stimulates germinal center B cell growth. J Exp Med. 2000;191(6): 1077–84. https://doi.org/10.1084/jem.191.6.1077 PMID: 10727470
83. Zhang X, Li L, Jung J, Xiang S, Hollmann C, Choi YS. The distinct roles of T cell-derived cytokines and a novel follicular dendritic cell-signaling molecule 8D6 in germinal center-B cell differentiation. J Immunol. 2001;167(1): 49–56. https://doi.org/10.4049/jimmunol.167.1.49 PMID: 11418631
84. Bendre A, Büki KG, Määttä JA. Fam3c modulates osteogenic differentiation by down-regulating Runx2. Differentiation. 2017;93: 50–7. https://doi.org/10.1016/j.diff.2016.11.005 PMID: 27914282
85. Määttä JA, Bendre A, Laanti M, Büki KG, Rantakari P, Tervola P, et al. Fam3c modulates osteogenic cell differentiation and affects bone volume and cortical bone mineral density. Bonekey Rep. 2016;5:787. https://doi.org/10.1038/bonekey.2016.14 PMID: 27087939
86. Du J-S, Yen C-H, Hsu C-M, Hsiao H-H. Management of myeloma bone lesions. Int J Mol Sci. 2021;22(7):3389. https://doi.org/10.3390/ijms22073389 PMID: 33806209
87. Terpos E, Christoulas D, Gavriatopoulou M, Dimopoulos MA. Mechanisms of bone destruction in multiple myeloma. Eur J Cancer Care (Engl). 2017;26(6):10.1111/ecc.12761. https://doi.org/10.1111/ecc.12761 PMID: 28940410
88. Janiszewska M, Primi MC, Izard T. Cell adhesion in cancer: Beyond the migration of single cells. J Biol Chem. 2020;295(8): 2495–505. https://doi.org/10.1074/jbc.REV119.007759 PMID: 31937589
89. Rajkumar SV, Dimopoulos MA, Palumbo A, Blade J, Merlini G, Mateos M-V, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538-48. https://doi.org/10.1016/S1470-2045(14)70442-5 PMID: 25439696
90. Wolf FA, Angerer P, Theis FJ. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 2018;19(1):15. https://doi.org/10.1186/s13059-017-1382-0 PMID: 29409532
91. Wolock SL, Lopez R, Klein AM. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Cell Syst. 2019;8(4): 281–291.e9. https://doi.org/10.1016/j.cels.2018.11.005 PMID: 30954476
92. Satija R, Farrell JA, Gennert D, Schier AF, Regev A. Spatial reconstruction of single-cell gene expression data. Nat Biotechnol. 2015;33(5): 495–502. https://doi.org/10.1038/nbt.3192 PMID: 25867923
93. Kowalczyk MS, Tirosh I, Heckl D, Rao TN, Dixit A, Haas BJ, et al. Single-cell RNA-seq reveals changes in cell cycle and differentiation programs upon aging of hematopoietic stem cells. Genome Res. 2015;25(12): 1860–72. https://doi.org/10.1101/gr.192237.115 PMID: 26430063
94. Stoeckius M, Hafemeister C, Stephenson W, Houck-Loomis B, Chattopadhyay PK, Swerdlow H, et al. Simultaneous epitope and transcriptome measurement in single cells. Nat Methods. 2017;14(9): 865–8. https://doi.org/10.1038/nmeth.4380 PMID: 28759029
95. Korsunsky I, Millard N, Fan J, Slowikowski K, Zhang F, Wei K, et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods. 2019;16(12): 1289–96. https://doi.org/10.1038/s41592-019-0619-0 PMID: 31740819
96. McInnes L, Healy J, Melville J. UMAP: uniform manifold approximation and projection for dimension reduction Arxiv. Cornell University; 2018. Available from: https://arxiv.org/abs/1802.03426
97. Traag VA, Waltman L, van Eck NJ. From Louvain to Leiden: guaranteeing well-connected communities. Sci Rep. 2019;9(1):5233. https://doi.org/10.1038/s41598-019-41695-z PMID: 30914743
98. Crowell HL, Soneson C, Germain P-L, Calini D, Collin L, Raposo C, et al. muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data. Nat Commun. 2020;11(1):6077. https://doi.org/10.1038/s41467-020-19894-4 PMID: 33257685
100. Sergushichev AA. An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation. bioRxiv. 2016:060012.
101. Browaeys RGJ, Sang-Aram C, et al. MultiNicheNet: a flexible framework for differential cell-cell communication analysis from multi-sample multi-condition single-cell transcriptomics data. 2023.
102. Pilcher WC, Yao L, Gonzalez-Kozlova E, Pita-Juarez Y, Karagkouni D, Acharya CR. A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma. bioRxiv. 2024.