Lightbody Elizabeth D, Sklavenitis-Pistofidis Romanos, Wu Ting, Tsuji Junko, Firer Danielle T, Agius Michael P, Dutta Ankit K, Barr Hadley, Kim Sungjae, Alberge Jean-Baptiste, Nersesian Sarah, Coorens Tim, Haradhvala Nicholas J, Su Nang Kham, Boehner Cody J, Aranha Michelle P, Rahmat Mahshid, Konishi Yoshinobu, Hevenor Laura, Towle Katherine, Horowitz Erica, Perry Jacqueline, Davis Maya, Walsh Kelly A, Cea-Curry Christian J, Fleming Grace, Vinyard Michael E, Heilpern-Mallory Daniel, El-Khoury Habib, Cowan Annie, Ready John E, Marinac Catherine R, Getz Gad, Ghobrial Irene M
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Harvard Medical School, Boston, MA, USA.
Nat Cancer. 2025 Aug 8. doi: 10.1038/s43018-025-01006-0.
Multiple myeloma is a bone marrow (BM) plasma cell malignancy preceded by precursor conditions. BM biopsies are conducted infrequently and can yield inconclusive results due to technical limitations. Profiling circulating tumor cells (CTCs) may enable noninvasive routine clinical assessments but remains challenging. Here, to address this, we describe a single-cell sequencing workflow to interrogate few tumor cells (SWIFT-seq), and employ single-cell RNA sequencing and B cell receptor sequencing on paired BM and CTCs from 101 patients and healthy donors. We establish a sequencing-based CTC enumeration strategy and develop a CTC classifier to infer cytogenetic abnormalities. Additionally, we leverage expression profiling to measure tumor proliferative index in CTCs, and demonstrate that clonal dynamics can be captured in CTCs. Last, we propose a circulatory dynamics model whereby tumor burden, proliferation, cytogenetics and a circulatory capacity signature influence CTC burden. Overall, SWIFT-seq may advance blood-based myeloma diagnostics, surveillance and prognostication, and reveal biological mechanisms of tumor dissemination.
多发性骨髓瘤是一种骨髓浆细胞恶性肿瘤，之前存在前驱病症。骨髓活检不常进行，且由于技术限制可能产生不确定的结果。分析循环肿瘤细胞（CTC）或许能够实现非侵入性的常规临床评估，但仍然具有挑战性。在此，为解决这一问题，我们描述了一种用于检测少量肿瘤细胞的单细胞测序工作流程（SWIFT-seq），并对101例患者和健康供体的配对骨髓和循环肿瘤细胞进行单细胞RNA测序和B细胞受体测序。我们建立了一种基于测序的循环肿瘤细胞计数策略，并开发了一种循环肿瘤细胞分类器以推断细胞遗传学异常。此外，我们利用表达谱来测量循环肿瘤细胞中的肿瘤增殖指数，并证明克隆动态可以在循环肿瘤细胞中被捕获。最后，我们提出了一种循环动力学模型，据此肿瘤负荷、增殖、细胞遗传学和循环能力特征会影响循环肿瘤细胞负荷。总体而言，SWIFT-seq可能会推动基于血液的骨髓瘤诊断、监测和预后评估，并揭示肿瘤播散的生物学机制。
