Immune Profiling of Multiple Myeloma

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.

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Plano F., Gigliotta E., Corsale A.M., Azgomi M.S., Santonocito C., Ingrascì M., Di Carlo L., Augello A.E., Speciale M., Vullo C., Rotolo C., Camarda G.M., Caccamo N., Meraviglia S., Dieli F., Siragusa S, & Botta C. (2023). Ferritin Metabolism Reflects Multiple Myeloma Microenvironment and Predicts Patient Outcome. International Journal of Molecular Sciences, 24(10), 8852.

Publication 2023

Infinicyt Infinicyt v2.0

Ferritin Multiple myeloma Patients

Corresponding Organization : University of Palermo

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Variable analysis

independent variables

Ferritin levels in multiple myeloma patients

dependent variables

Immune microenvironment characteristics

control variables

No specific control variables mentioned

controls

No positive or negative controls mentioned

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