ArticleBlood2025
Profiling the spatial architecture of multiple myeloma in human bone marrow trephine biopsy specimens with spatial transcriptomics.
Article in Blood, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Spatial transcriptomics identifies a suppressive, T-cell-excluded tumor microenvironment in extramedullary myeloma.Blood advances · 2026Article
- Ex vivo bone marrow subniches influence the fate of human antibody-secreting cells.Science advances · 2026Article
- Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.Nature communications · 2026Article
- Binary-SPA: a reference-free method for cell annotation in high-resolution spatial transcriptomics.Nucleic acids research · 2026Article
- Multiscale analysis and functional validation of the cellular and genetic determinants of skeletal disease.Nature genetics · 2026Article
- Review
- Stromal and endothelial transcriptional changes during progression from MGUS to myeloma and after treatment response.Nature communications · 2026Article
- Multiscale analysis and functional validation of the cellular and genetic determinants of skeletal disease.bioRxiv : the preprint server for biology · 2026Article
- Engineering bone marrow in a dish-a bloody business: preclinical opportunities, translational use cases, and a call for consensus.Journal of thrombosis and haemostasis : JTH · 2026Review
- Targeting the immunological synapse in multiple myeloma.Discover oncology · 2026Review
- Microenvironmentally derived fatty acid-binding proteins 4 and 5 are novel therapeutic vulnerabilities in multiple myeloma.Blood neoplasia · 2026Article
- Spatial multi-omics of multiple myeloma uncovers niche-dependent pro-myeloma and immunosuppressive signaling in the bone marrow and extramedullary lesions.bioRxiv : the preprint server for biology · 2026Article
- Binary-SPA: A Reference-Free Method for Cell Annotation in High-Resolution Spatial Transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Integrated RNA-seq and RT-qPCR Workflow Identifies Non-IGH Fusion Transcripts as Individualized Molecular Markers for Monitoring Multiple Myeloma.Biomedicines · 2026Article
- Nanomedicine-Empowered CAR-T Therapy for Multiple Myeloma: Toward Programmable, Durable, and Precision Immunotherapy.International journal of nanomedicine · 2026Review
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18 authors.
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No grant is acknowledged in the PubMed record.
Abstract
abstractThe bone marrow microenvironment is intimately linked to the biology that underpins the development and progression of multiple myeloma. However, the complex cellular and molecular features that form bone marrow niches are poorly defined. Here, we used subcellular spatial transcriptomics to profile the expression of 5001 genes in human bone marrow in the context of multiple myeloma. Using this approach, we explored the plasma cell and stroma ecosystem in bone marrow trephine biopsy specimens (herein referred to as trephines) from 21 individuals, including 7 with premalignant disease and 10 with newly diagnosed multiple myeloma. Using spatial transcriptomics in conjunction with an optimized trephine biobanking methodology, we could resolve major components of the human bone marrow microenvironment and reliably characterize distinct plasma cell populations in samples from healthy, premalignant disease and active myeloma. When plasma cells were visualized in the context of location, we detected spatially restricted subpopulations of plasma cells in 5 of 10 newly diagnosed myeloma trephines. Surprisingly, the composition of hematopoietic and stromal microenvironments varied significantly between newly diagnosed myeloma trephines. Furthermore, these differences in microenvironments were also observed within trephines that had spatially restricted plasma cell subpopulations. Thus, these data are not consistent with the hypothesis that a universal bone marrow microenvironment supports the expansion of malignant plasma cells in myeloma. Instead, we propose that myeloma subpopulations form distinct microenvironments and can vary both between patients and spatial locations.
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