Sign in

Abstract

CRISPR/Cas9 gene editing technology is a promising tool for correcting pathogenic variants for autologous cell therapies for Inborn Errors of Immunity (IEI). The present IEI correction strategies mainly focus on the knock-in of therapeutic cDNAs, or knockout of the disease-causing gene when feasible. These strategies address many single-gene defects but may disrupt gene expression and require significant optimization for each newly discovered IEI-causing gene, highlighting the need for complementary platforms that can precisely correct diverse pathogenic variants. Here, we present a safe and efficient T cell single nucleotide variant (SNV) correction pipeline based on homology-directed repair (HDR), suitable for diverse monogenic mutations. By using founder mutations of Deficiency of ADA2 (DADA2), Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) and Cartilage Hair Hypoplasia (CHH) as IEI models, we show that our pipeline can achieve up to 80% bi-allelic editing, with resultant functional correction of the disease phenotype in patient T cells. We do not find detectable pre-malignant off-target effects or karyotypic, transcriptomic or proteomic aberrations upon profiling patient T cells with GUIDE-seq, single cell RNA sequencing, PacBio based long-read whole genome sequencing, and high-throughput proteomics. This study demonstrates that HDR-based SNV editing is a safe and effective option for IEI T cell correction and that it could be developed to an autologous T cell therapy, as the presented protocol is scalable for a GMP-compatible workflow. This study is a step towards the development of gene correction platform that targets a broad number of monogenic mutations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/610811v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1f1eb47org.highwire.dtl.DTLVardef@18dbcc2org.highwire.dtl.DTLVardef@63862dorg.highwire.dtl.DTLVardef@1fe1561_HPS_FORMAT_FIGEXP M_FIG GRAPHICAL ABSTRACT C_FIG

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.