Infinicyt v2

Bone marrow samples were routinely examined by eight-color labelling method. During the examined period, the combination of antibodies was slightly changed in accordance with the new guideline (Supplementary Figure S1) [29 (link)]. Conventional FC analysis was performed by FACS Diva software v 8.0.3 (Becton Dickinson, San Jose, CA, USA). The raw data from the bi-dimensional FC examination was reanalyzed with novel protocols based on multidimensional dot-plots of Kaluza v 2.1 (Beckman Coulter, Brea, CA, USA) and Infinicyt v 2.0 (Cytognos, Salamanca, Spain) software.

Data were analyzed using FlowCT, a semi-automated workflow developed for deconvolution of immunophenotypic data and objective reporting on large datasets [33 ]. Briefly, FlowCT starts by creating a matrix with expression data generating a SingleCellExperiment object and correcting possible discrepancies in markers’ nomenclature. Subsequently, it performs internal data quality control and normalization, and automated clustering followed by dimensionality reduction to visualize clusters’ identity before manual annotation. This step is completed using the Infinicyt software (Infinicyt v2.0; Cytognos SL, Salamanca, Spain). Afterwards, sub-clustering of APC, T, and B cells was performed. Comma-separated value files with population abundances were finally exported to evaluate statistical correlations and differences across groups.

All samples were stained using the first three tubes of the EF AML/MDS antibody panel (7 (link)). Sample preparation and acquisition were performed according to the EF standard operating procedure and using the recommended EF instrument settings (8 (link)).
Appropriate instrument performance was confirmed by performing FranceFlow and EuroFlow quality assessments (9 (link), 10 (link)).
At least 100,000 BM cells/tube were acquired using a three-laser, eight-color BD FACSCanto-II™ flow cytometer (BD Bioscience, San José, CA, USA) at each study site. Acquired cells were then analyzed using Infinicyt V2.0 (Cytognos, Salamanca, Spain).

Subsequently, we applied FlowCT [21 (link)], an R-based package, to identify possible differences in the immune microenvironment among multiple myeloma patients with low or high ferritin levels. FlowSOM and Seurat clustering approaches were used for automated clustering. The median expression of each marker on multi-uniform manifold approximation and projection (UMAP) and the Infinicyt software (Infinicyt v2.0; Cytognos SL, Salamanca, Spain) were used to characterize each cluster.