Gene of the Month – June: ATM
The researchers systematically assessed all 27,513 possible single nucleotide variants (SNVs) in ATM. For genome editing, they used prime editing, a tool which allows to precisely and specifically rewrite single base pairs in the genome while avoiding DNA double strand breaks. Additionally, they developed a highly accurate deep learning model (DeepATM) for predicting functional impacts of ATM variants. Integration of their data with the UK Biobank cohort identified 382 high-risk SNVs linked to cancer.
Lee KS, Min JG, Cheong Y, … Kim HH. Functional assessment of all ATM SNVs using prime editing and deep learning. Cell. 2025 Jun 25:S0092-8674(25)00634-8. doi: 10.1016/j.cell.2025.05.046. Epub ahead of print.