MIT refines prime editing to reduce gene therapy errors
Researchers at MIT have improved prime editing, a gene-editing technique, to make it 60 times more accurate by minimizing unintended DNA mutations. This advancement could enhance the safety of treatments for genetic diseases. The study, led by Vikash Chauhan, was published in Nature.
Prime editing, introduced in 2019 by scientists at the Broad Institute of MIT and Harvard, offers a precise alternative to earlier gene-editing methods like CRISPR-Cas9. Unlike CRISPR, which cuts both DNA strands, prime editing makes a single-strand cut using a modified Cas9 enzyme, reducing risks to the genome. However, it still carries error rates, sometimes as high as one in seven edits, potentially leading to harmful mutations.
To address this, the MIT team, including senior authors Phillip Sharp and Robert Langer, engineered mutations in the Cas9 protein. These changes destabilize the original DNA strand, allowing the corrected sequence to integrate more reliably. By combining mutations and incorporating an RNA-binding protein for better template stability, they created a system called vPE. This reduced errors to one in 101 for standard edits and one in 543 for precise modes, tested in mouse and human cells.
"This paper outlines a new approach to doing gene editing that doesn't complicate the delivery system and doesn't add additional steps, but results in a much more precise edit with fewer unwanted mutations," says Phillip Sharp, an MIT Institute Professor Emeritus.
The improvement builds on a 2023 study observing Cas9's cutting variability. Prime editing has already shown promise, such as in treating chronic granulomatous disease in a patient. "In principle, this technology could eventually be used to address many hundreds of genetic diseases by correcting small mutations directly in cells and tissues," says Chauhan.
The team aims to boost efficiency and delivery to specific tissues. They also encourage its use in research on tissue development, cancer evolution, and drug responses. The work was funded by the Life Sciences Research Foundation, National Institute of Biomedical Imaging and Bioengineering, National Cancer Institute, and Koch Institute grants.