Single cell RNA-seq data and bulk gene profiles reveal a novel signature of disease progression in multiple myeloma

Apeng Yang,Kejie Zhang,Xizhe Guo,Zhiyong Zeng,Junfang Lin,Xiaoqiang Zheng,Junmin Chen

doi:10.1186/s12935-021-02190-6

Abstract

BackgroundThe development of multiple myeloma (MM) is considered to involve a multistep transformation process, but the role of cytogenetic abnormalities and molecular alterations in determining the cell fate of multiple myeloma (MM) remains unclear. Here, we have analyzed single cell RNA-seq data and bulk gene profiles to reveal a novel signature associated with MM development.MethodsThe scRNA-seq data from GSE118900 was used to profile the transcriptomes of cells from MM patients at different stages. Pseudotemporal ordering of the single cells was performed using Monocle package to feature distinct transcriptomic states of the developing MM cells. The bulk microarray profiles from GSE24080 and GSE9782 were applied to identify a signature associated with MM development.ResultsThe 597 cells were divided into 7 clusters according to different risk levels. They were initiated mainly from monoclonal gammopathy of undetermined significance (MGUS), newly diagnosed MM (NDMM), or relapsed and/or refractory myeloma (RRMM) with cytogenetically favorable t(11;14), moved towards the cells from smoldering MM (SMM) or NDMM without t(11;14) or t(4;14), and then finally to cells from SMM or RRMM with t(4;14). Based on the markers identified in the late stage, the bulk data was used to develop a 20-gene signature stratifying patients into high and low-risk groups (GSE24080: HR = 3.759, 95% CI 2.746–5.145; GSE9782: HR = 2.612, 95% CI 1.894–3.603), which was better than the previously published gene signatures (EMC92, UAMS70, and UAMS17) and International Staging System. This signature also succeeded in predicting the clinical outcome of patients treated with bortezomib (HR = 2.884, 95% CI 1.994–4.172, P = 1.89e−8). The 20 genes were further verified by quantitative real-time polymerase chain reaction using samples obtained from the patients with MM.ConclusionOur comprehensive analyses offered new insights in MM development, and established a 20-gene signature as an independent biomarker for MM.

Highlights

Multiple myeloma (MM) is a plasma cell malignancy characterized by a spectrum of monoclonal gammopathy of undetermined significance (MGUS), smoldering
ScRNA‐seq profiling demonstrated gene expression patterns during disease development of MM From dataset GSE118900, a total of 23,398 transcripts in 597 individual cells isolated from 15 MM patients at different stages were downloaded and pre-processed for scRNA-sequencing analysis
The 16 statistically significant principal components in the principal component analysis (PCA) were reduced to two dimensions using t-distributed stochastic neighbor embedding (t-SNE) (Fig. 1d)

Summary

Introduction

Multiple myeloma (MM) is a plasma cell malignancy characterized by a spectrum of monoclonal gammopathy of undetermined significance (MGUS), smolderingMM (SMM), and newly diagnosed MM (NDMM), and progresses to a relapsed or refractory multiple myeloma (RRMM) [1,2,3]. Many studies have reported the influence of the presence of cytogenetic abnormalities and molecular alterations in disease progression, response to therapy, and prognosis during the occurrence and development of MM [5, 6]. Their role in determining the fate of MM cells still remains unclear. The development of multiple myeloma (MM) is considered to involve a multistep transformation process, but the role of cytogenetic abnormalities and molecular alterations in determining the cell fate of multiple myeloma (MM) remains unclear. We have analyzed single cell RNA-seq data and bulk gene profiles to reveal a novel signature associated with MM development

Methods

Results

Conclusion