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[Preprint]. 2023 Dec 14:2023.12.13.571465. [Version 1] doi: 10.1101/2023.12.13.571465

Massively parallel base editing screens to map variant effects on anti-tumor hallmarks of primary human T cells

Zachary H Walsh, Parin Shah, Neeharika Kothapalli, Gergo Nikolenyi, Shivem B Shah, Giuseppe Leuzzi, Michael Mu, Patricia Ho, Sinan Abuzaid, Zack D Brodtman, Neil Vasan, Mohammed AlQuraishi, Joshua D Milner, Alberto Ciccia, Johannes C Melms, Benjamin Izar
PMCID: PMC10760091  PMID: 38168306

ABSTRACT

Base editing enables generation of single nucleotide variants, but large-scale screening in primary human T cells is limited due to low editing efficiency, among other challenges 1 . Here, we developed a high-throughput approach for high-efficiency and massively parallel adenine and cytosine base-editor screening in primary human T cells. We performed multiple large-scale screens editing 102 genes with central functions in T cells and full-length tiling mutagenesis of selected genes, and read out variant effects on hallmarks of T cell anti-tumor immunity, including activation, proliferation, and cytokine production. We discovered a broad landscape of gain- and loss-of-function mutations, including in PIK3CD and its regulatory subunit encoded by PIK3R1, LCK , AKT1, CTLA-4 and JAK1 . We identified variants that affected several (e.g., PIK3CD C416R) or only selected (e.g. LCK Y505C) hallmarks of T cell activity, and functionally validated several hits by probing downstream signaling nodes and testing their impact on T cell polyfunctionality and proliferation. Using primary human T cells in which we engineered a T cell receptor (TCR) specific to a commonly presented tumor testis antigen as a model for cellular immunotherapy, we demonstrate that base edits identified in our screens can tune specific or broad T cell functions and ultimately improve tumor elimination while exerting minimal off-target activity. In summary, we present the first large-scale base editing screen in primary human T cells and provide a framework for scalable and targeted base editing at high efficiency. Coupled with multi-modal phenotypic mapping, we accurately nominate variants that produce a desirable T cell state and leverage these synthetic proteins to improve models of cellular cancer immunotherapies.

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