Introduction:

Chimeric antigen receptor T-cells (CAR-T) have emerged as promising new approach for the treatment of cancer, with over 500 CAR-T worldwide clinical trials underway in 2021. Conventional thinking was that all CAR-T cells have similar therapeutic potential, however new research has found that not all CAR-T cells are created equal. A recent study showed that CAR-T cells with lower levels of glycolysis led to better clinical responses in leukemia patients. Here we use VisionSort to identify metabolically distinct CAR-T cell subsets without the use of molecular labels or tags as an approach to identify cells with the potential for higher therapeutic efficacy. 

Summary:

1. VisionSort can identify and classify metabolically distinct subsets of CAR-T cells without external markers or tags
2. A label-free approach can significantly contribute to identifying and isolating higher quality CAR-T therapy products
3. This could potentially improve CAR-T cell therapy efficacy and clinical outcomes.

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