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1.
Nature ; 603(7902): 728-735, 2022 03.
Artículo en Inglés | MEDLINE | ID: mdl-35296855

RESUMEN

The engineering of autologous patient T cells for adoptive cell therapies has revolutionized the treatment of several types of cancer1. However, further improvements are needed to increase response and cure rates. CRISPR-based loss-of-function screens have been limited to negative regulators of T cell functions2-4 and raise safety concerns owing to the permanent modification of the genome. Here we identify positive regulators of T cell functions through overexpression of around 12,000 barcoded human open reading frames (ORFs). The top-ranked genes increased the proliferation and activation of primary human CD4+ and CD8+ T cells and their secretion of key cytokines such as interleukin-2 and interferon-γ. In addition, we developed the single-cell genomics method OverCITE-seq for high-throughput quantification of the transcriptome and surface antigens in ORF-engineered T cells. The top-ranked ORF-lymphotoxin-ß receptor (LTBR)-is typically expressed in myeloid cells but absent in lymphocytes. When overexpressed in T cells, LTBR induced profound transcriptional and epigenomic remodelling, leading to increased T cell effector functions and resistance to exhaustion in chronic stimulation settings through constitutive activation of the canonical NF-κB pathway. LTBR and other highly ranked genes improved the antigen-specific responses of chimeric antigen receptor T cells and γδ T cells, highlighting their potential for future cancer-agnostic therapies5. Our results provide several strategies for improving next-generation T cell therapies by the induction of synthetic cell programmes.


Asunto(s)
Linfocitos T CD8-positivos , Neoplasias , Linfocitos T CD4-Positivos , Proliferación Celular , Humanos , Inmunoterapia Adoptiva , Activación de Linfocitos/genética
2.
iScience ; 24(11): 103380, 2021 Nov 19.
Artículo en Inglés | MEDLINE | ID: mdl-35814872

RESUMEN

Prime editors (PEs) are clustered regularly interspaced short palindromic repeats (CRISPR)-based genome engineering tools that can introduce precise base-pair edits. We developed an automated pipeline to correct (therapeutic editing) or introduce (disease modeling) human pathogenic variants from ClinVar that optimizes the design of several RNA constructs required for prime editing and avoids predicted off-targets in the human genome. However, using optimal PE design criteria, we find that only a small fraction of these pathogenic variants can be targeted. Through the use of alternative Cas9 enzymes and extended templates, we increase the number of targetable pathogenic variants from 32,000 to 56,000 variants and make these pre-designed PE constructs accessible through a web-based portal (http://primeedit.nygenome.org). Given the tremendous potential for therapeutic gene editing, we also assessed the possibility of developing universal PE constructs, finding that common genetic variants impact only a small minority of designed PEs.

3.
Cell Genom ; 1(1)2021 Oct 13.
Artículo en Inglés | MEDLINE | ID: mdl-35664829

RESUMEN

The recent characterization of RNA-targeting CRISPR nucleases has enabled diverse transcriptome engineering and screening applications that depend crucially on prediction and selection of optimized CRISPR guide RNAs (gRNAs). Previously, we developed a computational model to predict RfxCas13d gRNA activity for all human protein-coding genes. Here, we extend this framework to six model organisms (human, mouse, zebrafish, fly, nematode, and flowering plants) for protein-coding genes and noncoding RNAs (ncRNAs) and also to four RNA virus families (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2], HIV-1, H1N1 influenza, and Middle East respiratory syndrome [MERS]). We include experimental validation of predictions by testing knockdown of multiple ncRNAs (MALAT1, HOTAIRM1, Gas5, and Pvt1) in human and mouse cells. We developed a freely available web-based platform (cas13design) with pre-scored gRNAs for transcriptome-wide targeting in several organisms and an interactive design tool to predict optimal gRNAs for custom RNA targets entered by the user. This resource will facilitate CRISPR-Cas13 RNA targeting in model organisms, emerging viral threats to human health.

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