This technology is a method for high-throughput modeling of endogenous kinase inhibition to predict breast cancer treatment response.
Breast cancer treatment responses to PI3K/AKT inhibitors are variable due to patient genetic heterogeneity for mutations like those in PIK3R1. Current methods to study treatment response depend on gene knockout or overexpression systems that do not accurately mimic enzyme inhibition from small molecule drugs.
This technology is a high-throughput method for modeling endogenous enzyme inhibition that enables rapid functional assessments of PI3K/AKT inhibitors to predict patient treatment response. This approach uses adenine base editing to create endogenous cellular models that replicate kinase inhibition, allowing for high-throughput screening of mutation effects on drug sensitivity. Pooled screening provides an internal control to study enzyme inhibition and effects on cell growth and other phenotypes. As such, this technology has the potential to screen for effective inhibitors for breast cancer treatment and provide fast genetic screens to model the effects of kinase inhibitor drugs.
This technology has been validated using patient-derived genomic data and in in vitro and in vivo functional models.
IR CU26021, CU22283
Licensing Contact: Jerry Kokoshka
