Mass Cytometry Datasets Research Articles

Single Cell Mass Cytometry for Phenotypic Analysis of Diffuse Large B-Cell Lymphoma

Diffuse Large B-cell Lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin Lymphoma (NHL). Despite its improved outcome with R-CHOP chemotherapy, 40% of patients still suffer with relapsed or refractory disease. Further investigation is needed to understand the complexity of DLBCL. Time-of-flight mass cytometry (CyTOF) is a recently developed technology that combines traditional flow cytometry with mass spectrometry and supports analysis of up to 30-40 parameters simultaneously at the single cell level with minimal spectral overlap (Bendall et al, Science 2011). In this study, we sought to develop a CyTOF method for phenotypic analysis of DLBCL to obtain high resolution profiles of the malignant clone(s) represented in individual tumor samples and resolve any underlying population substructure that might be informative in understanding the clinical and biologic heterogeneity of this disease.We designed a two-tube assay for this study. Tube #1 contained 35 cell surface markers including CD45, CD19, CD20, CD22, CD79B, IgM, IgD, Ig Kappa, Ig Lambda, CD5, CD10, CD23, CD43, CD38, CD138, CD44, CD21, CD24, CD40, CD72, CD80, CD45RA, CD49D, CD49F, CD62L, CD25, CD27, CD30, CD127, CD184, CD194, CD200, CD34, HLA-DR, and CD3. Tube #2 contained 37 markers in total including 17 cell surface markers overlapping with Tube #1 plus an additional 20 intracellular markers (BCL2, BCL6, IRF4/MUM1, LMO2, MYC, MCL1, MEF2B, KAT3B/P300, CBP, FOXP1, RUNX1, Ikaros, EZH2, BMI1, NOTCH1, CARD11, IkBa, phospho-Rb, Ki67, and CyclinD2). Metal-conjugated antibodies were purchased from DVS Sciences or unconjugated antibodies labeled in-house using DVS MaxPar metal labeling kits. Data were acquired using a DVS CyTOF2 instrument. We examined both fresh and viably frozen single cell suspensions from diagnostic lymph node biopsy samples received for flow cytometric analysis at the BC Cancer Agency. We used SPADE (spanning-tree progression analysis of density-normalized events) for initial data analysis.We first performed preliminary validation studies including cross-comparison of mass cytometry (CyTOF2) vs. flow cytometry (BD Canto2) datasets and fresh vs. previously frozen cell suspension material. Although individual marker intensities using matched antibody clones were in general lower by CyTOF, eight-parameter surface staining results were qualitatively comparable between the two platforms. Also there were essentially no differences observed in CyTOF staining profiles between fresh and previously frozen samples. Preliminary clustering analysis of cell populations using SPADE revealed clear separation between normal and malignant B cell populations as well as apparent substructure to the malignant population in a subset of DLBCL samples. These findings suggest intratumoral heterogeneity can be resolved by high dimensional CyTOF analysis. Ongoing efforts will focus on determining if phenotypically defined subsets show enrichment for subclonal mutations. DisclosuresNo relevant conflicts of interest to declare.

RchyOptimyx: cellular hierarchy optimization for flow cytometry.

Analysis of high-dimensional flow cytometry datasets can reveal novel cell populations with poorly understood biology. Following discovery, characterization of these populations in terms of the critical markers involved is an important step, as this can help to both better understand the biology of these populations and aid in designing simpler marker panels to identify them on simpler instruments and with fewer reagents (i.e., in resource poor or highly regulated clinical settings). However, current tools to design panels based on the biological characteristics of the target cell populations work exclusively based on technical parameters (e.g., instrument configurations, spectral overlap, and reagent availability). To address this shortcoming, we developed RchyOptimyx (cellular hieraRCHY OPTIMization), a computational tool that constructs cellular hierarchies by combining automated gating with dynamic programming and graph theory to provide the best gating strategies to identify a target population to a desired level of purity or correlation with a clinical outcome, using the simplest possible marker panels. RchyOptimyx can assess and graphically present the trade-offs between marker choice and population specificity in high-dimensional flow or mass cytometry datasets. We present three proof-of-concept use cases for RchyOptimyx that involve 1) designing a panel of surface markers for identification of rare populations that are primarily characterized using their intracellular signature; 2) simplifying the gating strategy for identification of a target cell population; 3) identification of a non-redundant marker set to identify a target cell population.

Abstract SY22-01: Multiscale perspective of combination therapy for human cancer

Abstract SY22-01: Multiscale perspective of combination therapy for human cancer