Single-cell Transcriptional Analysis of the Bone Marrow Microenvironment in Multiple Myeloma
Danielle Croucher1, Zhihua Li2, Laura Richards1, Neil Winegarden2, Suzanne Trudel1,2, Trevor Pugh1,2
1Department of Medical Biophysics, University of Toronto, ON, Canada;
2Princess Margaret Cancer Centre, University Health Network, ON, Canada
Similar to other cancers, Multiple Myeloma (MM) tumour cells do not exist in isolation, but are rather dynamically interacting with components of their microenvironment in the bone marrow (BMME), holistically contributing to oncologic processes. While studies that focus on characterizing the MM BMME are intrinsically biased by pre-selecting cell populations of interest, single-cell RNA sequencing (scRNA-seq) now permits analysis of heterogeneous cell populations without a priori knowledge/selection of cell types.
We therefore performed an unbiased scRNA-seq screen to simultaneously characterize tumour cells and BMME cells from MM patients. Using a droplet-based scRNA-seq platform (Chromium, 10x Genomics), we transcriptionally profiled BM mononuclear cells (BMMCs) from MM patients and compared the resulting cell populations to two healthy BMMC datasets (10x Genomics). We observed several distinct cell clusters that were enriched for cell type-specific markers, enabling the discrimination of non-malignant cell types including normal plasma cells (PCs). These cell types were consistent with expected BMMCs subtypes and clustered independently of donor. In contrast, MM cells did not overlap with the normal PC cluster, and formed patient-specific cluster, supporting intertumoural heterogeneity. Differentially expressed genes in the MM tumour cell clusters were associated with a PC phenotype, and correlated with patient-specific cytogenetic/immunophenotyping clinical data.
Collectively, this data supports the feasibility of using scRNA-seq to profile heterogenous cell populations. Future work will focus on validating the observed cell types and characterizing differential gene expression in MM-derived BMME cells in the context of predicting disease characteristics and response to therapy.
Credits: None available.
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