bioRxivGenomicsPreprint
Degradation of IKAROS prevents epigenetic progression of T cell exhaustion in a novel antigen-specific assay
Tristan TayiD, Gayathri BommakantiiD, Elizabeth S. JaenschiD, Aparna GorthiiD, Iswarya Karapa Reddy, Yan HuiD, Ruochi ZhangiD, Aatman S. DoshiiD, Sin Lih TaniD, Verena Brucklacher-WaldertiD, Laura B. PrickettiD, James H. KurasawaiD, Michael Glen OverstreetiD, Steven W. CriscioneiD, Jason Daniel BuenrostroiD, Deanna A. MeleiD
Abstract
In cancer, chronic antigen stimulation drives effector T cells to exhaustion, limiting the efficacy of T cell therapies. Recent studies have demonstrated that epigenetic rewiring governs the transition of T cells from effector to exhausted states and makes a subset of exhausted T cells non-responsive to PD1 checkpoint blockade. Here, we describe an antigen-specific assay for T cell exhaustion that generates T cells that are phenotypically and transcriptionally similar to those found in human tumors. We performed a screen of human epigenetic regulators, identifying and validating IKAROS as a driver of T cell exhaustion. We found that the IKAROS degrader iberdomide prevents exhaustion by blocking chromatin remodeling at T cell effector enhancers and preserving binding of AP-1, NF-{kappa}B, and NFAT. Thus, our study uncovered a role for IKAROS as a driver of T cell exhaustion through epigenetic modulation, providing a rationale for the potential use of iberdomide in solid tumors to prevent T cell exhaustion. HighlightsO_LINovel in vitro assay generates antigen-specific exhausted T cells from human T cells C_LIO_LIIKAROS (IKZF1) is a key driver of T cell exhaustion C_LIO_LIIberdomide (IKZF1/3 degrader) prevents the progression of exhaustion C_LIO_LITF footprinting reveals IKAROS silences effector genes by inhibiting AP-1, NF-{kappa}B and NFAT binding C_LI
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: drug response / drug discovery
- approach: statistical model
- approach: experimental assay
- Citations
- 3
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