Beyond the Edit: Predicting and Preventing Network Mismatch After Gene Repair

Create a pipeline that combines precise repair (via HDR or prime editing) with perturb-seq, phosphoproteomics, and dynamic pathway modeling to identify why phenotype fails to recover after correcting a driver mutation. Use the model to nominate minimal co-edits (e.g., regulatory elements or pathway modulators) that restore function, and validate in organoids or disease-relevant cells. This approach leverages precise editors with advanced delivery methods and integrates computational modeling from synthetic biology to design co-edit strategies. It aims to address secondary dependencies and epigenetic scars causing network rewiring, turning partial rescues into true functional restorations, particularly relevant in cancer and chronic disease, thus increasing the success rate of CRISPR-based disease correction and informing combination editing strategies.

References:

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