A central goal of our research at Vanderbilt is to understand how changes at the single cell level alter signaling in healthy cells and lead to therapy resistant populations in human diseases.
In the Irish Lab, we use new tools and computational approaches to do basic and translational research in human cancer and immunology.
In addition to making discoveries at the frontier of cell biology, we aspire to use knowledge of cell signaling to create therapeutic technologies and to guide clinical decisions. In the long term, great potential exists to detect disease earlier and to tailor a patient's therapy to the biological alterations detected in the cells of their disease. By better understanding the cellular systems (cytomes) which control development through cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or specifically target and kill malignant cancer cells.
Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data
Kirsten E. Diggins, P. Brent Ferrell, & Jonathan M. Irish
Characterizing Phenotypes and Signaling Networks of Single Human Cells by Mass Cytometry
Nalin Leelatian , Kirsten E. Diggins , & Jonathan M. Irish
Single cell mass cytometry allows for quantitative measurement of 25-35 features per cells. Here, we present two detailed protocol for mass cytometry analysis. The first protocol detailed a phenotype analysis of single human peripheral blood mononuclear cells (PBMCs). The second protocol, for characterizing 25 signaling node states in a human acute myeloid leukemia cell line. Additionally, manual analysis is compared to unsupervised techniques, which includes bivariate analysis, heatmaps, histogram overlays, SPADE, and viSNE.