Deciphering T Cell Immunometabolism with Activity-Based Protein Profiling
- Curr Top Microbiol Immunol. 2019;420:175-210. doi: 10.1007/82_2018_124.
- 1. Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA, 22908, USA.
- 2. Department of Chemistry, University of Virginia, McCormick Road, P.O. Box 400319, Charlottesville, VA, 22904, USA.
- 3. Department of Pathology, University of Virginia School of Medicine, Charlottesville, VA, 22908, USA.
- 4. Department of Chemistry, University of Virginia, McCormick Road, P.O. Box 400319, Charlottesville, VA, 22904, USA. [email protected].
- 5. Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA, 22908, USA. [email protected].
As a major sentinel of adaptive immunity, T cells seek and destroy diseased cells using antigen recognition to achieve molecular specificity. Strategies to block checkpoint inhibition of T cell activity and thus reawaken the patient's antitumor immune responses are rapidly becoming standard of care for treatment of diverse cancers. Adoptive transfer of patient T cells genetically engineered with tumor-targeting capabilities is redefining the field of personalized medicines. The diverse opportunities for exploiting T Cell Biology in the clinic have prompted new efforts to expand the scope of targets amenable to immuno-oncology. Given the complex spatiotemporal regulation of T cell function and fate, new technologies capable of global molecular profiling in vivo are needed to guide selection of appropriate T cell targets and subsets. In this chapter, we describe the use of activity-based protein profiling (ABPP) to illuminate different aspects of T cell metabolism and signaling as fertile starting points for investigation. We highlight the merits of ABPP methods to enable target, inhibitor, and biochemical pathway discovery of T cells in the burgeoning field of immuno-oncology.
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Cat. No.Product NameDescriptionTargetResearch Area
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target: PhospholipaseResearch Areas: Metabolic Disease