Sex-specific plasma-immune architectural differences in bone marrow predicts overall survival in multiple myeloma

Background: Multiple myeloma (MM) disproportionately affects men (57% vs. 43% women), yet the biological basis for these sex differences remains unexplored. The bone-marrow immune microenvironment, particularly plasma-immune spatial organisation, plays a critical role in disease progression and therapeutic response. Emerging evidence suggests that sex-specific immunologic differences contribute to disparities in cancer biology and outcomes, yet these patterns remain poorly characterised in MM. Understanding whether plasma-immune architectural features differ by sex and whether they carry prognostic value may inform more personalised risk stratification in MM. Methods: We identified 104 MM whole-slide bone-marrow biopsies from the Cancer Moonshot Biobank. Using pre-trained deep learning models, immune cells were segmented, followed by plasma cell detection. Morphological (density and spatial) patterns of plasma cells and other immune cells were quantified in peri-tumoral and non-tumoral compartments, and FDR-corrected Welch's t-tests were performed to compare gender specific differences. Prognostic associations of these features were assessed using univariate Cox proportional hazard models. Results: On comparing the immune cell phenotypes, males exhibited higher plasma density relative to tumor density (0.158 vs female 0.105, FDR p=0.029). Spatial analysis showed that males also had higher plasma-lymphocyte cluster overlap in the peri-tumoral stroma (0.418 vs female 0.238, FDR p= 0.036). In survival analysis, overlap of plasma-lymphocyte cluster was prognostic of overall survival: HR = 1.730 (95% CI: 1.074-2.787), p= 0.018, c-index = 0.552. In contrast, there were no significant differences in density or spatial features of lymphocytes across the genders. Conclusions: Plasma cell shows gender specific differences in density and spatial arrangement, despite no significant differences in lymphocyte morphology. These sex-specific patterns appear to predict survival, supporting the need for sex-stratified risk assessment and personalised prognostication strategies in MM.