Single‐cell RNA‐seq reveals clonal diversity and prognostic genes of relapsed multiple myeloma

Abstract

Background Multiple myeloma (MM) is a clinically and biologically heterogeneous plasma‐cell malignancy. Despite extensive research, disease heterogeneity and relapse remain a big challenge in MM therapeutics. We tried to dissect this disease and identify novel biomarkers for patient stratification and treatment outcome prediction by applying single‐cell technology. Methods We performed single‐cell RNA sequencing (scRNA‐seq) and variable‐diversity‐joining regions‐targeted sequencing (scVDJ‐seq) concurrently on bone marrow samples from a cohort of 18 patients with newly diagnosed MM (NDMM; n = 12) or refractory/relapsed MM (RRMM; n = 6). We analysed the malignant clonotypes using scVDJ‐seq data and conducted data integration and cell‐type annotation through the CCA algorithm based on gene expression profiling. Furthermore, we identified disease status‐specific genes and modules by comparison of NDMM and RRMM datasets and explored the findings in a larger MM cohort from the MMRF CoMMpass study. Results We found that all the myeloma cells in either diagnosed or relapsed samples were dominated by a major clone, with a few subclones in several samples (n = 5). Next, we investigated the universal transcriptional features of myeloma cells and identified eight meta‐programs correlated with this disease, especially meta‐programs 1 and 8 (M1 and M8), which were the most significant and related to cell cycle and stress response, respectively. Furthermore, we classified the malignant plasma cells into eight clusters and found that the cell numbers in clusters 2/6/7 were exclusively higher in relapsed samples. Besides, we identified several attractive candidates for biomarkers (e.g. SMAD1 and STMN1) associated with disease progression and relapse in our dataset and related to overall survival in the CoMMpass dataset. Conclusions Our data provide insights into the heterogeneity of MM as well as highlight the relevance of intra‐tumour heterogeneity and discover novel biomarkers that might be a potent therapy.

Single‐cell transcriptome profiling reveals the key role of ZNF683 in natural killer cell exhaustion in multiple myeloma

“…In recent years, single‐cell RNA sequencing has become a powerful tool in uncovering intratumor heterogeneity and immune landscape of MM. 25 , 26 , 27 This high‐throughput technology potentially paves way for exploring molecular mechanisms of NK cell dysfunction in MM. In the current study, we performed single‐cell transcriptome analysis of NK cells from MM patients and healthy volunteers to dissect mechanisms for NK cell dysfunction in MM.…”

“…In recent years, single‐cell RNA sequencing has become a powerful tool in uncovering intratumor heterogeneity and immune landscape of MM 25–27 . This high‐throughput technology potentially paves way for exploring molecular mechanisms of NK cell dysfunction in MM.…”

Current perspectives on interethnic variability in multiple myeloma: Single cell technology, population pharmacogenetics and molecular signal transduction

“…Recently, He et al. [23] used single-cell RNA sequencing (scRNA-seq) on bone marrow samples obtained from 18 MM patients and demonstrated the heterogeneity of MM as well as intra-tumor heterogeneity with myeloma cells being dominated by a major clone. Interestingly, a functional assay has been developed to investigate the ex vivo sensitivity of single MM cells to various standard-of-care drugs based on measurement of the mass accumulation rate of the cells, thus, serving as a predictor of drug response in MM [24] .…”

Dynamic single-cell RNA-seq analysis reveals distinct tumor program associated with microenvironmental remodeling and drug sensitivity in multiple myeloma

“…A unique feature of this malignancy is the clonal heterogeneity including both primary and secondary cytogenetic abnormalities as well as specific molecular alterations, which have been demonstrated to influence therapeutic outcomes [ 4 – 7 ]. Previous attempts to unravel the tumor complexity at single-cell resolution have revealed significant inter-patient heterogeneity across disease spectrum from precursor asymptomatic disease stages to active MM [ 8 ] and even the relapsed/refractory multiple myeloma (RRMM) stage [ 9 , 10 ]. In addition to these inter-tumor heterogeneities, MM also displays enormous intra-tumor heterogeneity (ITH) comprised of a mixture of clones [ 4 , 11 , 12 ] and diverse transcriptional programs [ 10 , 13 ], which pose both challenges and opportunities for myeloma therapy.…”