Translation of NK Cell CAR Therapy to the Clinic: Critical Role of Performance & Clinical-scalability

The prognosis for adult B-cell malignancies, such as acute lymphoblastic leukemia (ALL),1,2 non-Hodgkin lymphoma (NHL)3 and chronic lymphocytic leukemia (CLL),4 is poor, particularly for patients with refractory or relapsing disease. Recently, two breakthrough anti-CD19 CAR-T cell therapies were approved by the FDA for use in adults with specific relapsed or refractory B-cell malignancies.

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Guide Profiler™: A Genetic Variant-Aware Computational Tool for Improved Guide RNA Selection for CRISPR-Based Therapeutic Applications

A table for guides that then lists off-target score (by MIT and CFD), Activity (CRISPRater), number of loci (L. Distance, and Risk Profiler number.

Guide Profiler evaluates off-target risk during the guide RNA (gRNA) selection process. Using in silico off-target enumeration and computational methods, the tool rapidly screens large numbers of gRNA sequences and makes an informed list of viable candidates. Guide Profiler will allow therapy makers to take into account ancestry of target donor and intent-to-treat populations, as well as to assess preparedness for diverse populations in clinical trial design.

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SAFER Detection™ for Efficient Interrogation of DNA Rearrangements in Gene-Edited Human Cells

Breakpoint site alignment. The reference CCR5 target site is shown at the top. Mismatched nucleotides and indels are highlighted. The alignment score is listed on the right. Diamonds indicate off-target sites detected at validated inter-chromosomal translocation breakpoints.

In this study, we introduce SAFER Detection (Selective Amplification for Efficient Rearrangement Detection), a tagmentation and next-generation sequencing method designed to enable quantitative detection of chromosomal rearrangement breakpoints with single base resolution. The method is capable of classifying rearrangements resulting from on-target and off-target editing by programmable nucleases.

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ONE-seq™ for Variant-Aware Therapeutic Guide Selection

A map of the world with different colored dots representing the varying number of samples across different geographic regions.

ONE-seq leverages computational tools and biochemical assays to nominate candidate off-target sites across thousands of genomes with high sensitivity. Here, we present an application of ONE-seq to identify guides with the lowest potential off-target editing risk.

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