Oral Presentation ANZBMS-MEPSA-ANZORS 2022

Spatially resolving the bone marrow microenvironment in MGUS and multiple myeloma   (#68)

Melissa D Cantley 1 2 , Laura Trainor 1 2 , Nicholas West 3 , Duncan Hewett 1 2 , Andrew C.W Zannettino 1 2 4 , Kate Vandyke 1 2
  1. Myeloma Research Laboratory, School of Biomedicine, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
  2. Precision Cancer Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
  3. Central Facility for Genomics, Griffith University, Gold Coast, Queensland, Australia
  4. Central Adelaide Local Health Network (CALHN), Adelaide, South Australia, Australia

Multiple myeloma (MM) is a haematological malignancy characterised by proliferation of clonal plasma cells (PCs) in the bone marrow (BM) and is proceeded by an asymptomatic stage known as monoclonal gammopathy of undetermined significance (MGUS). BM microenvironment cells support proliferation and survival of MMPCs and may play a role in MGUS-to-MM progression. Here, we aimed to characterise BM microenvironment changes with MGUS-to-MM progression in trephine biopsies.

Nanostring GeoMx Digital Spatial Protein profiling was performed on paraffin embedded decalcified BM trephine biopsies from 3 patients with matched samples at MGUS and subsequent MM diagnosis. Tissues were stained with immunofluorescent CD138 and CD45 antibodies, Syto13 nuclear stain and 68 barcoded antibodies (Nanostring immune-oncology panel). Regions of interest (ROI) (4/tissue section) were selected representing low (0-40%) to high (70%-100%) CD138+ PC% (Figure 1A-C) and barcoded antibodies were quantitated using the nCounter system. Affymetrix microarray gene expression analysis was conducted on sorted PCs (CD138+CD38+CD45lowCD19-) from BM aspirates (n=5 matched MGUS/MM diagnosis) to identify PC expression of markers included in the spatial analysis.  

Results demonstrated significant positive correlations (Pearson) between tumour cell infiltration (PC%) as assessed by CD138 immunostaining and expression of CD56, BAD, BCL2, and BCL-XL, reflective of expression of these markers by myeloma PCs, as shown by microarray analysis. Interestingly, microenvironment cell markers CD127 and SMA, which are not expressed by MM PCs, significantly positively correlated with PC% whilst ARG1 expression was inversely correlated with PC% (Figure 1D). SMA expression was significantly increased in myeloma samples compared to MGUS in 2/3 patients (p<0.05; 2way ANOVA).

This study optimised Digital Spatial Protein Profiling of trephine biopsies revealing correlations of PC% with tumour markers and with microenvironment markers. Future studies will utilise this method on additional matched MGUS and MM samples, to increase our understanding of how the BM microenvironment changes with MGUS-to-MM progression. 

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