It is increasingly recognized that in order to gain
further insights into human disorders and develop new therapeutic strategies
and diagnostic tools, it is critical to have a comprehensive overview of
immune cell subsets resident in tissues under physiological and pathological
conditions. Flow cytometry has been the golden standard for analyzing immune
cell subsets, and with a typical experiment, dozens of immune subsets can be
discriminated. Due to the lack of spectrally-resolvable fluorochromes, mass
cytometry utilizing metal-conjugated antibodies has shown to be a powerful
tool for dissecting the immune landscape even further.
Inflammatory intestinal diseases can only be understood by studying
specialized cell types within the tissue niche itself. In this thesis, we
applied mass cytometry and data-driven, automated analysis approaches to
investigate the complex compositions of heterogeneous cell subsets, such as
those encountered in intestinal biopsies. These types of data have the
potential to greatly improve our understanding of human disease. In concert
with clinical data, mass cytometry could enable a finer classification of
patients and might aid in the development of improved diagnostics,
prognostics and personalized therapeutic regimens.