Applying bioinformatics in dendritic cell-mediated immune cell activation research: automated analysis of high-dimensional flow cytometry datasets.

Can the bioinformatics R package FlowSOM – for high-dimensional single-cell flow cytometry datasets – assist research on dendritic cell-mediated immune cell activation?The primary objective of this Small Project is to evaluate the R package FlowSOM for the analysis of high-dimensional flow cytometry data and to explore its use in the preclinical and clinical evaluation of immunogenicity of next-generation anticancer dendritic cell vaccine candidates that are currently under investigation at the Laboratory of Experimental Hematology (UAntwerp) and the Center for Cell Therapy and Regenerative Medicine (Antwerp University Hospital). With increasing dimensionality of biological data and technical advances, manual flow cytometry data analysis will become inadequate. Applying bioinformatics, automated and unbiased comparisons between in vitro/ex vivo-stimulated immune effector cells with novel dendritic cell vaccine candidates will assist further development of potent dendritic cell preparations with the most superior immune-stimulating capacities and will be essential in unraveling therapy responsive immune profiles in longitudinal studies. FlowSOM is a powerful algorithm that builds self-organizing maps (SOMs) to provide an overview of marker expression on all cells and reveal cell subsets that could be overlooked with manual gating. Ultimately, our aim is to develop an advanced immune profiling platform for evaluation of preclinical and clinical dendritic cell-mediated immune responses.

Keywords:CANCER IMMUNOTHERAPY, BIOINFORMATICS, IMMUNE RESPONSE, DENDRITIC CELLS

Disciplines:Bio-informatics, Single-cell data analysis, Vaccinology, Vaccines, Cancer therapy