Development of Genome-Wide Off-target Detection Methods
- Importance of the Research Topic
The irreversible nature of off-target effects from CRISPR-based human therapeutics sets them apart from traditional drugs based on chemicals and biologics. As a result, the USFDA’s guidance on ‘Human Gene Therapy Products Incorporating Human Genome Editing’ mandates rigorous safety testing for off-target prediction and detection. This was a pivotal issue during the BLA (Biological License Agreement) meeting for Casgevy, the first approved CRISPR-based drug. There is a strong market demand for the development of optimized off-target prediction methods, a challenge actively pursued by a consortium of major pharmaceutical companies, biotech firms, hospitals, universities, and regulatory authorities.
- Our Research
At GRIT-Lab, our focus is on testing, optimizing, and developing next-generation methods for detecting off-target effects. In 2023, Dr. Lee’s Toolgen team introduced Extru-seq, a disruptive technology that physically ‘disrupts’ the cell membrane of live cells. Extru-seq combines the advantages of both cell-based and in-vitro methods, exhibiting a high validation rate, a low miss rate, and the highest area under the ROC (Receiver operating characteristic) curve among tested methods. This technique can also be applied to primary cells.
Furthermore, Dr. Lee’s Toolgen team has made significant strides with TAPE-seq, the inaugural off-target prediction method utilizing Prime-editor technology. TAPE-seq demonstrated superior performance with high validation rates, low miss rates, and the highest area under the ROC curve, outperforming other methods. The team’s research indicates that this enhanced predictive capability stems from the use of Prime-editor rather than Cas9 or nickase.
We are committed to advancing our ‘Re-InnovaTion’ process in genome-wide off-target detection methods to further refine and enhance the safety and efficacy of genome editing technologies
From left; Dr. Eugenio Marco Rubio (Editas), Prof. Luca Pinello (Harvard University), Dr. Jungjoon Lee (Toolgen), and Prof. Ross Wilson (UC Berkeley)