(PA-212) Spatial Transcriptomics in Extramedullary Multiple Myeloma Reveals an M2 Macrophage Prominent TME

Extramedullary disease (EMD) in multiple myeloma (MM) is associated with poor prognosis due to aggressive disease kinetics and therapy resistance. Bone marrow (BM) restricted MM is highly dependent on the BM microenvironment for survival, putatively contributing to drug-resistance. In EMD, the biology and particularly the role of the tumour microenvironment (TME) is unknown.


Methods:

Eight biopsies from 8 patients with haematogenous EMD were analysed using 10x Xenium In Situ Prime 5K. Subsequent analysis utilised the recently described high resolution ProSeg cell segmentation algorithm (Jones D et al, Nat Methods 2025).


Results:

A total of 499,726 cells from 8 samples were included. Plasma cells (PC) in EMD maintain a PC transcriptome with expression of transcription factors XBP1, IRF4 and PRDM1 without significant expression of PAX5, FOXP1. After dimensionality reduction, like BM-restricted MM, PC clustering was driven primarily by inter-patient variability. The TME was assessed. The most numerous immune cells were macrophages, specifically those with an immune-suppressive M2 phenotype, demonstrated by expression of markers such as CD163 and MRC1. Myeloma infiltration by T-cells was associated with proximity to M1 macrophages. Infiltrating CD8+ T-cells co-expressed cytotoxicity and exhaustion genes. Cancer associated fibroblasts were the most common non-immune cell in the TME.

Spatial analysis was performed with recurrent microenvironments identified. Perivascular niches, characterised by fibroblasts and endothelial cells, were enriched for immune cells and more proliferative PC subsets. The bulk of tumours were characterized by immune-excluded regions with a high proportion of PC ( >80%). Rarer areas with increased T-cells, presumed immune-permissive regions, were also present. Predicted cell-cell interactions identified a complex, bidirectional network. PC interactions with the TME via signals including prostaglandin E2 and VEGFB were evident, predicted to drive M2 macrophage differentiation. Conversely, macrophages in the TME expressing APRIL and BAFF are predicted to promote PC survival via canonical ligands including BCMA, CXCR4 and CD38. This bidirectional signalling between suppressive myeloid cells in the TME and PC thus putatively promote myeloma growth directly whilst concurrently constraining anti-myeloma immunity.

Across all samples, subsets of PC showed upregulation of cell cycle genes, consistent with proliferative transcriptional programs. There was also an enrichment of SOST, SNHG15 and LENG8, genes implicated in bone formation and oncogenesis. While described in BM-restricted MM, the presence of these clusters in all samples suggests an important role in EMD biology.


Conclusions:

Our findings provide new insights into the spatial organisation of MM EMD and identify prominent M2 macrophage rich niches in the context of T cell exclusion within the TME, together with proliferative signalling networks in PC, that represent new clinically tractable targets.