Introduction:

Identification and isolation of specific human immune cell populations with technologies that are minimally disruptive to the native biological states are critical requirements in modern cellular immunotherapy approaches. Such technologies can enable the improvement of product quality as well as clinical efficacy of cell therapy drug products, including both autologous and allogeneic cellular therapeutics. Here we used VisionSort, powered by Ghost Cytometry (GC) technology, to enable high resoloution morphological analysis and sorting of cells without the use of molecular labels (i.e., antibodies). We demonstrate the application of VisionSort to characterize human pan T-cells, where the platform was able to identify cells by complex morphotypes such as (i) early apoptosis, (ii) glycolysis level, (iii) exhaustion state, and (iv) activation state with high accuracy. These results described here highlight a new promising approach for isolation of functionally distinct cells, untouched by external labels, for investigators and drug developers in immunology and immunotherapy research and development.

Summary:

1. High resolution single cell morphological profiling with VisionSort was used for label-free analysis of human T-cells across a variety of complex phenotypes 
2. VisionSort enables researchers access to phenotypically defined and truly untouched T-cells, avoiding unwanted stimulation or activation by antibody-based labels
3. VisionSort can be used to support the development of better cell-based therapies

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