Multiple myeloma gammopathies

Flow cytometry for fast screening and automated risk assessment in systemic light-chain amyloidosis


Early diagnosis and risk stratification are key to improve outcomes in light-chain (AL) amyloidosis. Here we used multidimensional-flow-cytometry (MFC) to characterize bone marrow (BM) plasma cells (PCs) from a series of 166 patients including newly-diagnosed AL amyloidosis (N = 94), MGUS (N = 20) and multiple myeloma (MM, N = 52) vs. healthy adults (N = 30). MFC detected clonality in virtually all AL amyloidosis (99%) patients. Furthermore, we developed an automated risk-stratification system based on BMPCs features, with independent prognostic impact on progression-free and overall survival of AL amyloidosis patients (hazard ratio: ≥ 2.9;P ≤ .03). Simultaneous assessment of the clonal PCs immunophenotypic protein expression profile and the BM cellular composition, mapped AL amyloidosis in the crossroad between MGUS and MM; however, lack of homogenously-positive CD56 expression, reduction of B-cell precursors and a predominantly-clonal PC compartment in the absence of an MM-like tumor PC expansion, emerged as hallmarks of AL amyloidosis (ROC-AUC = 0.74;P < .001), and might potentially be used as biomarkers for the identification of MGUS and MM patients, who are candidates for monitoring pre-symptomatic organ damage related to AL amyloidosis. Altogether, this study addressed the need for consensus on how to use flow cytometry in AL amyloidosis, and proposes a standardized MFC-based automated risk classification ready for implementation in clinical practice.

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This study was supported by the Centro de Investigación Biomédica en Red – Área de Oncología—del Instituto de Salud Carlos III (CIBERONC; CB16/12/00369, CB16/12/00400 and CB16/12/00489), Instituto de Salud Carlos III/Subdirección General de Investigación Sanitaria (FIS No. PI13/02196), Asociación Española Contra el Cáncer (GCB120981SAN and Accelerator Award), the Black Swan Research Initiative of the International Myeloma Foundation, and the European Research Council (ERC) 2015 Starting Grant (MYELOMANEXT). We thank all the investigators that included patients in this study: Abelardo Barez, Albert Oriol, Albert Perez, Alfonso Garcia De Coca, Amaia Balerdi, Angel Ramirez, Cristina Martinez, Daniel Borrego, Elena Cabezudo, Elham Askari, Enrique Ocio, Esther Gonzalez, Felipe Arriba, Felipe Prosper, Gonzalo Caballero, Isabel Krsnik, Javier de la Rubia, Javier Marco, Jesus San Miguel, Joaquin Martinez-Lopez, Jorge Labrador, Jose Enrique De La Puerta, Jose Julio Hernandez, Jose Luis Sastre, Jose Maria Alonso, Juan Jose Bargay, Juan Jose Gavira, Juan Jose Lahuerta,Luis Palomera, Maria Casanova, Maria Dolores Garcia-Malo, Maria Jesus Blanchard, Maria Jose Cejalvo, Maria Lourdes Elicegui, Maria Sarasa, Maria Victoria Mateos, Martin Mascaro, Martin Nuñez, Mercedes Berenguer, Mercedes Gironella, Noemi Puig, Norma Gutiérrez, Perla Salama Bendayan, Rafael Del Orbe,Rafael Ríos, Ramon Garcia-Sanz,Ramon Lecumberri, Rebeca Cuello, Roberto Hernandez, Rosa Lopez, Valentin Cabañas, Vicente Carrasco, and Tomas Gonzalez.

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Correspondence to Bruno Paiva.

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Puig, N., Paiva, B., Lasa, M. et al. Flow cytometry for fast screening and automated risk assessment in systemic light-chain amyloidosis. Leukemia 33, 1256–1267 (2019).

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