Characterizing the role of the immune microenvironment in multiple myeloma progression at a single-cell level
Early alterations within the bone marrow microenvironment that contribute to the progression of multiple myeloma (MM) from its precursor stages could be the key to identifying novel therapeutic approaches. However, the intrinsic variability in cellular populations between patients and the difference...
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| Hauptverfasser: | , , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
22 November 2022
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| In: |
Blood advances
Year: 2022, Jahrgang: 6, Heft: 22, Pages: 5873-5883 |
| ISSN: | 2473-9537 |
| DOI: | 10.1182/bloodadvances.2022007217 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1182/bloodadvances.2022007217
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| Verfasserangaben: | Carolina Schinke, Alexandra M. Poos, Michael Bauer, Lukas John, Sarah Johnson, Shayu Deshpande, Luis Carrillo, Daisy Alapat, Leo Rasche, Sharmilan Thanendrarajan, Maurizio Zangari, Samer Al Hadidi, Frits van Rhee, Faith Davies, Marc S. Raab, Gareth Morgan and Niels Weinhold |
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| 520 | |a Early alterations within the bone marrow microenvironment that contribute to the progression of multiple myeloma (MM) from its precursor stages could be the key to identifying novel therapeutic approaches. However, the intrinsic variability in cellular populations between patients and the differences in sample processing and analysis methods have made it difficult to identify consistent changes between data sets. Here, we used single-cell RNA sequencing of bone marrow cells from precursor stages, monoclonal gammopathy of unknown significance, smoldering MM, and newly diagnosed MM and analyzed our data in combination with a previously published data set that used a similar patient population and sample processing. Despite the vast interpatient heterogeneity, some alterations were consistently observed in both data sets. We identified changes in immune cell populations as the disease progressed, which were characterized by a substantial decrease in memory and naïve CD4 T cells, and an increase in CD8+ effector T cells and T-regulatory cells. These alterations were further accompanied by an enrichment of nonclonal memory B cells and an increase in CD14 and CD16 monocytes in MM compared with its precursor stages. These results provide crucial information on the immune changes associated with the progression to clinical MM and can help to develop immune-based strategies for patient stratification and early therapeutic intervention. | ||
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