Identification of broadly tumour-reactive γδ TCRs from multiple myeloma
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TL;DR - Nature reports PreGame, a machine-learning algorithm that identifies broadly tumour-reactive γδ T cells in multiple myeloma from single-cell CITE-seq data. Expansion of this T-cell population may provide a biomarker of therapeutic response.
- PreGame analyzes combined single-cell transcriptomic and surface-protein measurements.
- The method focuses on γδ T-cell receptors with broad tumour reactivity.
- Changes in the identified cell population could help monitor treatment response in multiple myeloma.
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Identification of broadly tumour-reactive γδ TCRs from multiple myeloma
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TL;DR - Nature reports PreGame, a machine-learning algorithm that identifies broadly tumour-reactive γδ T cells in multiple myeloma from single-cell CITE-seq data. Expansion of this T-cell population may provide a biomarker of therapeutic response.
- PreGame analyzes combined single-cell transcriptomic and surface-protein measurements.
- The method focuses on γδ T-cell receptors with broad tumour reactivity.
- Changes in the identified cell population could help monitor treatment response in multiple myeloma.