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Updated: Jan 17, 2026

Interphase Fluorescence in situ Hybridization of Bone Marrow Smears of Multiple Myeloma
Published on: April 15, 2022
Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma
Juan-Jose Garces1, Benjamin Diamond2, Tereza Sevcikova3,4,5
1Myeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
None:
Circulating tumor cells (CTCs) have emerged as a key prognostic factor in newly diagnosed multiple myeloma (NDMM). However, it remains unclear if high CTC counts represent a mere surrogate of tumor burden or might reflect a distinct genomic or transcriptomic entity. In this study, we characterized the genomic and transcriptomic features associated with CTC burden and assessed their combined prognostic value in NDMM patients. We analyzed 540 NDMM patients from the CoMMpass dataset with available baseline CTC information and matched bone marrow transcriptomic (n = 374) and genomic (n = 460) sequencing data. We then validated the results on an external cohort of 135 NDMM patients with CTCs enumerated by next-generation flow cytometry. Higher CTC levels were significantly associated with high-risk clinical features (e.g., ISS or IMS/IMWG 2024). Furthermore, genomic analyses revealed that high CTC counts were associated with complex genomic features such as chromothripsis, APOBEC mutagenesis, and loss of key tumor suppressors, typically linked to high-risk disease. Transcriptomic analyses revealed that elevated CTCs were enriched in cell cycle and proliferation (PR) genes while presenting a reduced association with immune response. Importantly, CTCs also emerged as a surrogate for PR transcriptomic signatures and demonstrated prognostic superiority, potentially simplifying application in the clinical setting. Elevated CTC levels reflect aggressive biological features of multiple myeloma and outperform prognostic markers such as PR signatures. Integrating CTC data into genomic and transcriptomic classifiers could enhance risk stratification and provide a streamlined and powerful tool for clinical decision-making in NDMM.
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