Identifying the Cells of Origin and Risk-Stratification Strategy By Single-Cell Sequencing in Multiple Myeloma

Background: With the advent of novel agents, poor prognosis remains an unsolved problem for some patients. Identifying patients with super-high-risk and offering novel therapeutic strategy is essential. The aim of our study is to infer the identity of cells of origin in MM and dig out the novel strategy for risk sub-stratification and treatment.

Method: We applied single cell RNA sequencing to fresh bone marrow mononuclear cell samples from 7 healthy donors and 12 newly diagnosed MM patients utilizing 10x Chromium platform.

Results: Firstly, we separated plasma cells (PCs) in silico and identified 10 cellular subpopulations in total. Via the CNV score and pseudotime trajectory analysis, we distinguished normal PCs and observed the differentiation trajectory from normal PCs to malignant PCs. We identified cluster 4 as the starting point of malignant transition and possessed plasmablast-like gene signature, which displayed high expression of B-cell gene signatures and specifically high level of CD24. Additionally, cluster 4 was featured by high expression of high-risk genes and drug-resistance genes. Gene enrichment analysis implicated that Wnt, Notch, stem cell differentiation and Hedgehog pathway were enriched in cluster4. Notably, we identified the top upregulated differentially expressed genes in cluster 4 including LILRB4, CRIP1, etc. We next explored their biological function in MM cell lines. We found that both LILRB4 and CRIP1 could promote the proliferation of MM cells, indicating their potential novel therapeutic target in MM. Finally, we constructed a 7-Star stratification model, which was validated to better facilitate discrimination of super-high-risk MM patients when combined with International Staging System (ISS).

Conclusion: Our study inferred the cells of origin in MM at single cell resolution. We suggested targeting marker genes of cells of origin as potential novel therapeutic strategy, and our 7-Star stratification model as a powerful tool for discrimination of super-high-risk MM patients when combined with ISS stage.

No relevant conflicts of interest to declare.