Single cell multiomic analysis and immune cell type profiling of multiple myeloma with t(4;14).

Abstract

e20013 Background: Multiple Myeloma (MM) is an incurable plasma cell (PC) malignancy and high risk (HR) MM remains an unmet clinical need. Translocation 4;14 occurs in 15% of MM and is associated with an adverse prognosis. A deeper understanding of the biology and immune micro-environment of t(4;14) MM is necessary for the development of effective targeted therapies. Single Cell multi-omics provides a new tool for phenotypic characterization of MM. Here we used Proteona’s ESCAPE™ single cell multi-omics platform to study a cohort of patients with t(4;14) MM. Methods: Diagnostic bone marrow (BM) samples from 14 patients with t(4;14) MM were analysed using the ESCAPE platform from Proteona which simultaneously measures gene and cell surface protein expression in single cells. Cryopreserved BM samples were stained with 65 DNA barcoded antibodies and subsequently sorted on CD138 expression. The CD138 positive and negative fractions were recombined at a known ratio for analysis using the 10x Genomics 3’ RNAseq kit. Resulting data were analyzed with Seurat and MapCell. Results: The patients had a median age of 63 years. All received novel agent based induction. Median progression free and overall survival (PFS and OS) were 22 and 34 months respectively. MMSET was overexpressed in all PCs while FGFR3 expression could be categorized into zero cells expressing FGFR3, low expression (< 10% of cells expressing FGFR3) or high expression (> 80% of cells expressing FGFR3). We also found heterogeneity in the expression of cancer testis antigens (CTA) such as FA133A and CTAG2 between PC clusters across samples. Variation in the immune microenvironment of the BM was seen across all patient samples with no correlation between cell types and PFS or OS. However, an analysis of BM samples at diagnosis and relapse in one patient showed a shift in the ratio of T cells to CD14 monocytes with a ratio of 5.7 at diagnosis compared to 0.6 at relapse. Further analysis of PCs in this patient found 8 PC populations, each containing variable numbers of cells from both the diagnostic and relapse samples. This suggests that all populations present at relapse were also present at diagnosis, although at variable proportions. Increased expression of RCAN3 (associated with cereblon depletion) was detected at relapse. Conclusions: We present the first application of single cell multi-omics immune profiling in high risk MM. The heterogeneity in expression of CTA has implications for the application of immunotherapies, while the upregulation of RCAN3 may explain failure of immunomodulatory therapy. Our small sample size may explain the lack of correlation between gene or protein expression with clinical outcomes. We propose that t(4;14) MM is a genomically and immunologically heterogeneous disease. Single cell analysis of larger cohorts is required to build on our findings.