Predicting breast cancer treatment response through PIK3R1 mutation profiling

This technology is a method for high-throughput modeling of endogenous kinase inhibition to predict breast cancer treatment response.

Unmet Need: Simple method to predict 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.

The Technology: High-throughput modeling of endogenous enzyme inhibition

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.

Applications:

• Precision oncology screening
• Research model for examining kinase inhibition and enzyme function
• High-throughput genetic screening platform for drug discovery
• Preclinical testing of kinase inhibitor therapies
• Personalized medicine applications for breast cancer treatment

Advantages:

• Accurately mimics enzyme inhibition
• Fast genetic screens
• Does not remove entire gene

Lead Inventor:

Neil Vasan, M.D., Ph.D.

Related Publications:

• Chaki M, Benrashid M, Puri S, Sivakumar S, Sokol ES, Briceno JM, Neil Vasan. Retrospective comparison between breast cancer tissue- and blood-based next-generation sequencing results in detection of PIK3CA, AKT1, and PTEN alterations. Breast Cancer Res. 2025 Jul 1; 27(1): 122.

• Tao JJ, Sisoudiya SD, Tukachinsky H, Schrock A, Sivakumar S, Sokol ES, Vasan N. “Clinicogenomic landscape and function of PIK3CA, AKT1, and PTEN mutations in breast cancer.” medRxiv [Preprint]. 2025 Jun 18: 2025.06.18.25329632.

• Sivakumar S, Jin DX, Rathod R, Ross J, Cantley LC, Scaltriti M, Chen JW, Hutchinson KE, Wilson TR, Sokol ES, Vasan N. “Genetic Heterogeneity and Tissue-specific Patterns of Tumors with Multiple PIK3CA Mutations.” Clin Cancer Res. 2023 Mar 14; 29(6): 1125-1136.

• Vasan N, Razavi P, Johnson JL, Shao H, Shah H, Antoine A, Ladewig E, Gorelick A, Lin TY, Toska E, Xu G, Kazmi A, Chang MT, Taylor BS, Dickler MN, Jhaveri K, Chandarlapaty S, Rabadan R, Reznik E, Smith ML, Sebra R, Schimmoller F, Wilson TR, Friedman LS, Cantley LC, Scaltriti M, Baselga J. “Double PIK3CA mutations in cis increase oncogenicity and sensitivity to PI3Kα inhibitors.” Science. 2019 Nov 8; 366(6466): 714-723.

Tech Ventures Reference:

• IR CU26021, CU22283

• Licensing Contact: Jerry Kokoshka