Dr. E. John Wherry is currently the Chair, Department of Systems Pharmacology and Translational Therapeutics, Richard and Barbara Schiffrin President’s Distinguished Professor and Director, Institute for Immunology at the Perelman School of Medicine at the University of Pennsylvania. Dr. Wherry’s expertise focuses on T cell exhaustion in chronic infections and cancer and on the mechanisms by which immunoregulatory “checkpoint” pathways such as PD-1 control T cell exhaustion. Dr. Wherry’s work has defined the molecular mechanisms of T cell exhaustion, including defining the role of inhibitory receptor biology, transcriptional control and regulation of T cell differentiation. This work has helped define key principles about inhibitory receptor blockade and co-blockade to reverse T cell exhaustion (e.g. coblockade of PD-1 and LAG3, etc). Work on combination treatment to reverse exhaustion is now being extended to include other complementary approaches such as radiation and other “orthogonal” treatments. Moreover, Dr. Wherry’s work has defined central transcriptional pathways including those controlled by Blimp-1, T-bet and Eomes in the biology of exhausted T cells. Major efforts continue in transcriptional profiling, genomics and computational biology and multiparameter flow cytometry to understand the nature and reversibility of T cell exhaustion in preclinical and clinical settings.

A major goal of the research the Wherry laboratory is to understand the fundamental biology of T cell exhaustion during chronic infections and cancer. Our work has defined the nature of T cell exhaustion including altered function, limited responses to antigen restimulation, high co-expression of inhibitory receptors such as PD-1, and a characteristically distinct transcriptional program. We have defined the importance of limited protective capacity of these cells during infection and cancer and have also uncovered the pathways involved in re-invigorating these cells by checkpoint blockade. We have identified subsets of exhausted T cells with different functions and reinvigoration potential and delineated the developmental relationships between these subsets. We have also found a major mechanism limiting responses of exhausted T cells. By profiling the open chromatin landscape of exhausted CD8 T cells we found that these cells were completely distinct from effector and memory CD8 T cells. Moreover, this epigenetic landscape did not change upon checkpoint blockade resulting in a reversion to exhaustion after transient benefit. These data identified exhausted T cells as a distinct immune lineage separate from effector and memory CD8 T cells. Our work has also now discovered the lineage programmer of exhausted CD8 T cells call Tox, an HMG transcription factor that induces the epigenetic changes associated with CD8 T cell exhaustion. Ongoing work continues to interrogate the mechanisms of Tox and other regulators of exhausted T cell formation, regulation and reversibility.
A second major focus in the lab is to use knowledge of fundamental immune biology, including of exhausted T cells, but also follicular helper T cells and B cells, to perform high dimensional immune profiling in human disease. We have applied these approaches to immune oncology where we first identified exhausted T cells as the major responding cell type in human cancer patients receiving PD-1 blockade treatment. We have also applied these approaches to understanding the combination of checkpoint blockade and radiation in cancer, HIV infection, human influenza virus vaccination, human immune cell migration, and pediatric respiratory infections. Our goal is to use such approaches to define the baseline, and disease associated, features of overall Immune Health and use this information to interrogate individual responses to therapeutic interventions.
Overall, our laboratory uses many high dimensional immune profiling approaches, genomics including RNA-seq, scRNA-seq, ATA-seq, scATAC-seq, other epigenetic profiling approaches, high dimensional imaging (CODEX) and rests on a strong foundation of computational biology and informatics.

https://en.wikipedia.org/wiki/Edward_...

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