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Sozanska, A.

Publications and source records attributed to Sozanska, A..

2 recordsLinked to original sources

A platform for deep topographic multiomic mapping of the bone marrow environment in multiple myeloma

Multiple myeloma is a genetically complex plasma cell malignancy in which profound intratumoral heterogeneity shapes disease progression and therapeutic resistance. Genomic subclones dynamically emerge and evolve under treatment pressure, yet their spatial organization within intact bone marrow remains poorly defined. We hypothesized that genetically distinct myeloma subclones occupy spatially discrete ecological niches associated with unique molecular and microenvironmental states. To test this, we here demonstrate a proof-of-concept spatial tri-omics workflow combining laser capture microdissection-based genomics and deep LC-MS/MS proteomics with single-cell spatial transcriptomics, integrated by digital co-registration of adjacent tissue sections. Applied to a myeloma bone marrow trephine, this approach enabled coordinated profiling of matched anatomical regions demonstrating that genomic, transcriptomic and proteomic profiles converged to define clone-specific microenvironmental programmes. We show that genetically distinct myeloma subclones occupy mutually exclusive regions of the same bone marrow biopsy. Remarkably, an aggressive del(17p) clone and a gain(12q) clone occupied defined anatomical territories within the same trephine-biopsied section, each clone exhibiting distinct genomic, transcriptomic, proteomic and cellular ecosystems. The del(17p) clone localized to a fibrotic, osteolytic and angiogenic niche enriched for activated stromal cells, osteoblasts, osteoclasts and immunoregulatory myeloid populations, whereas the gain(12q) clone occupied a comparatively quiescent marrow niche with limited stromal remodelling. Together, these findings demonstrate that genetically distinct myeloma subclones establish spatially and biologically discrete ecological niches through coordinated remodelling of stromal, immune and bone compartments, providing a framework for understanding clonal evolution within the bone marrow microenvironment.

cancer biology↗

Redefining the topology of the human bone marrow using augmented spatial transcriptomic analysis

The bone marrow (BM) is the main site of haematopoiesis in adult life. Our understanding of the pathogenesis of BM-derived blood cancers is limited by lack of spatial contextualisation. While emerging spatial transcriptomic (ST) platforms offer unprecedented opportunities for spatially-resolved cellular phenotyping, we recognise and incorporate the power of AI-based tissue feature detection to enhance ST workflows. We perform ST analysis to define the topology of the normal bone marrow (BM) and BM in myeloproliferative neoplasms (MPNs), profiling 5,104,452 cells across 30 human BM samples. Following rigorous histology-based QC, we identify spatially-restricted trajectories of haematopoiesis and extend our understanding of the haematopoietic stem cell (HSC) niche. We find that BM fibrosis in MPN is associated with expansion of distinct immune and stromal co-enriched cell neighbourhoods. We then present a machine learning (ML)-based model trained on ST data that quantifies BM microenvironmental deviation, identifying heretofore unrecognised inter- and intra-individual sample heterogeneity in MPN. Our study demonstrates the potential for AI-based augmented ST analysis, and redefines our understanding of human BM topology.

cancer biology↗