文章：

多发性骨髓瘤进展的分子特征：基于单细胞RNA测序的研究

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

原文发布日期：2019-01-03

DOI: 10.1038/s41408-018-0160-x

类型: Article

开放获取: 是

英文摘要：

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.

摘要翻译： 

我们采用单细胞RNA测序技术，对15名不同疾病进展阶段患者的骨髓穿刺样本中597个CD138阳性细胞进行了多发性骨髓瘤分子异质性研究。通过变异系数法筛选出790个基因，并采用无监督聚类将细胞分为四组（L1-L4）。基于基因表达特征，每位患者的浆细胞均聚类为至少两个组别。L1组包含所有意义未明的单克隆丙种球蛋白病患者的细胞，其氧化磷酸化、Myc靶点和mTORC1信号通路相关基因表达水平最低（p < 1.2 × 10−14）。与之相反，这些通路基因的表达水平在L4组中呈现渐进式上升并达到最高值，该组仅包含携带t(4;14)易位的多发性骨髓瘤患者细胞。四组中持续过表达的44个基因特征与多发性骨髓瘤患者较差的总生存期显著相关（APEX试验：p < 0.0001；风险比1.83；95%置信区间1.33-2.52），特别是在接受硼替佐米治疗的患者群体中更为显著（p < 0.0001；风险比2.00；95%置信区间1.39-2.89）。本研究通过单细胞RNA测序技术，揭示了多发性骨髓瘤进展过程中影响最显著的分子通路，并提供了可预测患者预后和治疗分层的新型基因特征。

原文链接：

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