Methodology of high-dimensional flow cytometry in monitoring immune microenvironment of pituitary neuroendocrine tumors

Abstract

Characterization of the tumor immune microenvironment (TIME) of pituitary neuroendocrine tumors (PitNETs) is crucial for understanding the behavior of different types of PitNETs and identification of possible causes of their aggressiveness, rapid growth, and resistance to therapy. High-dimensional flow cytometry (FC) is a promising technology for studying TIME but poses unique technical challenges, especially when applied to solid tissues and PitNETs, in particular. This paper evaluates the potential of FC for analyzing TIME in PitNETs by addressing methodological difficulties across all stages of the workflow and proposing solutions. We developed a protocol for preparing single-cell suspensions from PitNET tissues for FC. This involved optimization of enzymatic digestion and comparison of it with mechanical tissue dissociation assessing cell yield, viability, and target antigen expression. We designed four multicolor FC panels to analyze major lymphocyte and myeloid cell subsets including determination of subpopulations of T, B, NK cells and their activation and cytotoxic potential, neutrophils, monocytes, CD68 + CD64 + CD11b^low macrophages of M2 and M1 subtypes, and two types of myeloid suppressor cells - PMN-MDSC and M-MDSC. Principles of multicolor panel design, spreading error, and importance of voltage balance for proper flow cytometer setting are discussed. The panels were validated and demonstrated the feasibility of their simultaneous use on pituitary tumor surgical tissue for comprehensive TIME characterization. We compared lymphocyte frequencies in blood, PitNETs, and three sequential PitNET eluates to find out the contamination level of PitNET samples with blood leukocytes. To address technical challenges, we propose a strategy of logical data gating that removes spurious signals from aggregates, dead cells, and subcellular debris that can interfere with analysis. Our results indicate that despite all technical difficulties, multiparametric FC can effectively characterize different types of PitNETs. This enhanced understanding of the immune infiltrate provides valuable insights into PitNET biology and advances clinical diagnostics.