Transcriptional and epigenetic regulators of human CD8+ T cell function identified through orthogonal CRISPR screens
Clinical response to adoptive T cell therapies is associated with the transcriptional and epigenetic state of the cell product. Thus, discovery of regulators of T cell gene networks and their corresponding phenotypes has potential to improve T cell therapies. Here we developed pooled, epigenetic CRI...
Gespeichert in:
Veröffentlicht in: | Nature genetics 2023-12, Vol.55 (12), p.2211-2223 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Clinical response to adoptive T cell therapies is associated with the transcriptional and epigenetic state of the cell product. Thus, discovery of regulators of T cell gene networks and their corresponding phenotypes has potential to improve T cell therapies. Here we developed pooled, epigenetic CRISPR screening approaches to systematically profile the effects of activating or repressing 120 transcriptional and epigenetic regulators on human CD8
+
T cell state. We found that BATF3 overexpression promoted specific features of memory T cells and attenuated gene programs associated with cytotoxicity, regulatory T cell function, and exhaustion. Upon chronic antigen stimulation, BATF3 overexpression countered phenotypic and epigenetic signatures of T cell exhaustion. Moreover, BATF3 enhanced the potency of CAR T cells in both in vitro and in vivo tumor models and programmed a transcriptional profile that correlates with positive clinical response to adoptive T cell therapy. Finally, we performed CRISPR knockout screens that defined cofactors and downstream mediators of the BATF3 gene network.
CRISPR activation/interference screens identify transcriptional regulators of human CD8
+
T cells, including BATF3. BATF3 overexpression counteracts T cell exhaustion and enhances cancer immunotherapy in in vivo models. |
---|---|
ISSN: | 1061-4036 1546-1718 1546-1718 |
DOI: | 10.1038/s41588-023-01554-0 |