Tao Yi, Jin Shi-Wei, Wang Zhe, Pan Mengmeng, Ouyang Wanyan, Xu Jie, Liu Yuanfang, Wang Yan, Zhang Weiping, Li Jian, Mi Jian-Qing
State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Department of Hematology, Shanghai Institute of Hematology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Department of Physiology, College of Basic Medical Sciences, Naval Medical University, Shanghai, China.
BMC Med. 2025 May 2;23(1):257. doi: 10.1186/s12916-025-04086-y.
Extramedullary myeloma disease (EMD) can present at disease relapse (secondary EMD, sEMD) and confers an aggressive clinical course. Identifying predictive markers for sEMD is crucial for clinical management.
Our study, spanning February 2013 to October 2022, identified sEMD in 77 (12.5%) of 618 newly diagnosed multiple myeloma patients. We categorized sEMD patients into bone-related extramedullary (EM-B) and extraosseous extramedullary (EM-E) relapse groups, as well as into early and late relapse groups based on the median interval from initial MM diagnosis, and assessed their overall survival (OS). We investigated independent predictors for the development of sEMD and focused on double-hit (DH) myeloma, one of the predictors of sEMD. Through the analysis of single-cell RNA from DH myeloma samples, we explored the potential mechanisms by which it may contribute to sEMD.
Median OS post-sEMD diagnosis was 11 months, with no significant OS difference between EM-B and EM-E relapse groups. A median interval of 22 months from initial MM diagnosis to sEMD relapse divided the 77 sEMD patients into early and late relapse groups, with early sEMD associated with significantly inferior OS post-sEMD (5.0 vs 27.0 months, p = 0.028). Driven by the prognostic difference of early vs late sEMD relapse, we used a time-to-event model and identified five independent predictors: double-hit (DH) cytogenetics, ≥ 3 osteolytic lesions, IgD subtype, and non-autologous stem-cell transplantation (ASCT) status, each scoring one point, alongside EM-E scoring two points. These predictors informed an additive score, stratifying patients into low (0-2 points) and high (3-5 points) risk categories for sEMD, showing a significant difference in 3-year sEMD rates (6.6% vs 52.8%, p < 0.001). Moreover, the single-cell RNA sequencing of newly diagnosed DH myeloma samples uncovered significant mitogen-activated protein kinase (MAPK) activation in DH cells and exhaustion in CD8 + memory and NK effector cells. Potential therapeutic targets such as EZH2 have emerged from this analysis.
Our study introduces a five-predictor scoring system informed by the potential mechanisms underlying sEMD progression in DH myeloma, with the goal of delaying or possibly preventing sEMD.
髓外骨髓瘤疾病（EMD）可在疾病复发时出现（继发性EMD，sEMD），并具有侵袭性临床病程。识别sEMD的预测标志物对临床管理至关重要。
我们的研究涵盖2013年2月至2022年10月，在618例新诊断的多发性骨髓瘤患者中，有77例（12.5%）被诊断为sEMD。我们将sEMD患者分为骨相关髓外（EM-B）和骨外髓外（EM-E）复发组，并根据从初始MM诊断开始的中位间隔时间分为早期和晚期复发组，评估其总生存期（OS）。我们研究了sEMD发生的独立预测因素，并重点关注双打击（DH）骨髓瘤，它是sEMD的预测因素之一。通过对DH骨髓瘤样本的单细胞RNA分析，我们探索了其可能导致sEMD的潜在机制。
sEMD诊断后的中位OS为11个月，EM-B和EM-E复发组之间的OS无显著差异。从初始MM诊断到sEMD复发的中位间隔时间为22个月，将77例sEMD患者分为早期和晚期复发组，早期sEMD患者sEMD后的OS显著较差（5.0个月对27.0个月，p = 0.028）。受早期与晚期sEMD复发预后差异的驱动，我们使用事件时间模型并确定了五个独立预测因素：双打击（DH）细胞遗传学、≥3个溶骨性病变、IgD亚型、非自体干细胞移植（ASCT）状态，每个因素得1分，EM-E得2分。这些预测因素构成一个累加评分，将患者分为sEMD低风险（0 - 2分）和高风险（3 - 5分）类别，显示3年sEMD发生率有显著差异（6.6%对52.8%，p < 0.001）。此外，新诊断的DH骨髓瘤样本的单细胞RNA测序发现DH细胞中有显著的丝裂原活化蛋白激酶（MAPK）激活，以及CD8 + 记忆细胞和NK效应细胞耗竭。此分析还发现了潜在的治疗靶点，如EZH2。
我们的研究引入了一个基于DH骨髓瘤中sEMD进展潜在机制的五预测因素评分系统，目的是延迟或可能预防sEMD。
