Molecular signatures of multiple myeloma progression through single cell RNA-Seq

Blood Cancer J. 2019 Jan 3;9(1):2. doi: 10.1038/s41408-018-0160-x.


We used single cell RNA-Seq to examine molecular heterogeneity in multiple myeloma (MM) in 597 CD138 positive cells from bone marrow aspirates of 15 patients at different stages of disease progression. 790 genes were selected by coefficient of variation (CV) method and organized cells into four groups (L1-L4) using unsupervised clustering. Plasma cells from each patient clustered into at least two groups based on gene expression signature. The L1 group contained cells from all MGUS patients having the lowest expression of genes involved in the oxidative phosphorylation, Myc targets, and mTORC1 signaling pathways (p < 1.2 × 10-14). In contrast, the expression level of these pathway genes increased progressively and were the highest in L4 group containing only cells from MM patients with t(4;14) translocations. A 44 genes signature of consistently overexpressed genes among the four groups was associated with poorer overall survival in MM patients (APEX trial, p < 0.0001; HR, 1.83; 95% CI, 1.33-2.52), particularly those treated with bortezomib (p < 0.0001; HR, 2.00; 95% CI, 1.39-2.89). Our study, using single cell RNA-Seq, identified the most significantly affected molecular pathways during MM progression and provided a novel signature predictive of patient prognosis and treatment stratification.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biopsy
  • Bone Marrow / pathology
  • Computational Biology / methods
  • Disease Progression
  • Gene Expression Profiling / methods
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Kaplan-Meier Estimate
  • Multiple Myeloma / genetics*
  • Multiple Myeloma / mortality
  • Multiple Myeloma / pathology*
  • Prognosis
  • Sequence Analysis, RNA
  • Single-Cell Analysis / methods
  • Transcriptome*
  • Workflow