Evaluation of the role of different cell populations in mycosis fungoides microenvironment as a tool for biomarker identification for disease progression and individualized therapy

Introduction and objectives: Tumor microenvironment constitutes a promising area for the investigation of mechanisms involved in the development, progression, and drug responses in MF-CTCL. Mass cytometry (CyTOF) analysis gives a holistic view of different cell populations on skin tumor microenvironment by simultaneous identification and enumeration of over 37 immune cell subsets providing more information from other already established techniques. This study is focused on the evaluation of MF-CTCL patients’ immune profile, in different types of skin lesions or sequential analysis of patients’ skin lesions. Materials and methods: 14 MF-CTCL patients enrolled in this study. 4 patients with IA stage, 5 patients with IB stage, 5 patients IIB stage. Single cells were isolated from skin biopsies as follows: 2 samples from patch, 18 samples from plaques, and 7 samples from tumors. Sequential pre-, during and post-treatment biopsies were obtained from 3 patients, whereas biopsies before and after treatment were obtained from 2 patients. Finally, paired samples (plaque and tumors) were obtained from 5 patients. Five skin biopsies deriving from patients with non-malignant skin lesions were used as control. Single cells from 6mm punch biopsies were processed for CyTOF analysis using the Maxmar Direct Immune Profiling Assay for identification and enumeration of CD4+ and CD8+ (naive, central memory, effector memory, and terminal effector), CD4+ regulatory T cells, CD4–mucosal-associated invariant T cells (MAIT)/natural killer T (NKT) cells, B cell subsets (naive and memory, plasmablasts), natural killer (early and late) cells, T helper (Th) cell phenotypic subsets (Th1-like, Th2-like, and Th17-like), gamma delta (γδ) T cells, monocytes (classical, transitional, and nonclassical), dendritic cell subsets (plasmacytoid and myeloid), granulocytes, basophils, eosinophils, and neutrophils. We also determined the expression of 6 additional markers (PD-1, PD-L1, OX40, CD7, CD26, CD206). Results: We identified different cell subpopulations, either of malignant clones or immune cells of the microenvironment, providing evidence for the single-cell heterogeneity factors that are responsible for the heterogeneity in patients with MF at different disease stages. Conclusions: The heterogeneity that characterizes different stages of MF, the intra-individual and inter-individual differences, necessitates the application of this new “state of the art” technology (CyTOF) to provide holistic consideration of malignancy in correlation with the microenvironment, and it can be considered as a tool for precision and personalized therapeutic approach.