Format

Send to

Choose Destination
Leukemia. 2019 May;33(5):1256-1267. doi: 10.1038/s41375-018-0308-5. Epub 2018 Dec 12.

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

Author information

1
Hospital Universitario de Salamanca, Instituto de Investigacion Biomedica de Salamanca (IBSAL), Centro de Investigación del Cancer (IBMCC-USAL, CSIC), Salamanca, Spain.
2
Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), IDISNA, CIBERONC Pamplona, Pamplona, Spain. bpaiva@unav.es.
3
Clinica Universidad de Navarra, Centro de Investigacion Medica Aplicada (CIMA), IDISNA, CIBERONC Pamplona, Pamplona, Spain.
4
Hospital 12 de Octubre, Madrid, CNIO, Universidad Complutese CIBERONC, Madrid, Spain.
5
Hospital Clínico Universitario de Valladolid, Valladolid, Spain.
6
Hospital Universitario de Burgos, Burgos, Spain.
7
Hospital de Cabueñes, Gijon, Spain.
8
Hospital Clinico Universitario Lozano Blesa, Zaragoza, Spain.
9
Hospital Universitari Vall d'Hebron, Barcelona, Spain.
10
Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain.
11
Hospital Costa del Sol, Marbella, Spain.
12
Institut Català d'Oncologia i Institut Josep Carreras, Hospital Germans Trias i Pujol, Badalona, Spain.
13
Hospital Puerta de Hierro, Madrid, Spain.
14
Hospital Son Espases, Palma, Spain.
15
Hospital Doctor Peset, Valencia, Spain.
16
Hospital de Galdakao, Vizcaya, Spain.
17
Hospital Universitario Morales Meseguer. IMIB-Arrixaca, Murcia, Spain.
18
Servicio General de Citometría, Universidad de Salamanca, IBSAL, and IBMCC CSIC-USAL, CIBERONC, Salamanca, Spain.
19
Cytognos SL, Salamanca, Spain.

Abstract

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.

PMID:
30542145
DOI:
10.1038/s41375-018-0308-5
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Nature Publishing Group
Loading ...
Support Center