Research & Projects
Overview
Motivated by both kinase VUSs observed in Apsel Winger’s clinical practice and the remarkable responses of molecularly targeted kinase inhibitors in patients with vascular anomalies and cancer, the lab’s long-term goal is to expand targeted therapy options for patients with kinase mutations. Our lab uses molecular and chemical biology techniques to understand the mechanism by which uncharacterized mutations in kinases impact function.
Characterizing the mechanism of mutant kinases in vascular anomalies
Our research seeks to understand the mechanisms by which mutant kinases drive the development of vascular anomalies with the goal of advancing kinase-directed therapy for these conditions.
Characterizing kinase VUSs
An important focus of our lab is to develop and implement a rigorous, quantitative computational method to identify activating, drug-sensitive mutations in kinases in collaboration with our computational biology colleagues in the Jacobson Laband the Mobley Lab. This method will be based on molecular dynamics (MD), a computational method that simulates the movement of atoms and molecules based on Newton’s laws of motion. Accomplishing this goal will create a new computational pipeline for predicting if kinase VUSs are activating and sensitive to kinase inhibitors. We are grateful to our funders in the Bachrach Family Foundation and TeamConnor Childhood Cancer Foundation for supporting this work.
We hypothesize that kinase-activating mutations can be identified based on free energy changes in MD simulations between wildtype and mutant kinases. Decades of research in statistical mechanics and computational biophysics has demonstrated that MD-based calculations can predict kinase activity, however this has never been applied to clinical mutations with the goal of improving patient care.
We have demonstrated the feasibility of applying this method to patient-derived mutations. One of our teenage patients with refractory acute lymphoblastic leukemia had a VUS in the oncogenic kinase PDGFRA, PDGFRA D842N. We used MD-based free energy calculations to predict PDGFRA D842N was activating, guiding the decision to treat with a PDGFR inhibitor in combination with chemotherapy, which put this patient into remission (Paolino et al, 2023). We are expanding this type of work to characterize additional mutations in PDGFRA as well as mutations in other medically relevant kinases, such as FLT3, KIT, RET, and others (Sandoval-Perez et al, 2022).
Our two-fold research goal is:
- To develop an MD-based workflow to predict if kinase VUSs are activating and sensitive to available kinase inhibitors, and
- To biochemically annotate kinase VUSs and determine their drug sensitivity, which, in addition to its utility in guiding treatment, will aid in validation of the MD workflow.
Once we establish the workflow from VUS detection to prediction of effect, this method will be applied to other kinases and integrated into molecular tumor board and clinical care. This work will expand our mechanistic understanding of which mutations can lead to kinase activation and drug sensitivity which will ultimately expand targeted therapy options for pediatric cancer patients with genetic testing of their tumors.
Understanding the mechanism of gatekeeper mutations
There are many mechanisms by which gatekeeper mutations in kinases have been shown to impact kinase function and drug sensitivity. Based on our previous work in cancer research (see ATP-Competitive Inhibitors Midostaurin and Avapritinib Have Distinct Resistance Profiles in Exon 17–Mutant KIT), we hypothesize that gatekeeper mutations in the kinase KIT impact drug sensitivity through unique mechanisms involving conformational changes in portions of the kinase not previously described as being impacted by gatekeeper mutations, such as the P-loop. Using Ba/F3 cells we are interrogating how the chemistry of the residue at the gatekeeper position impacts kinase function. Based on these studies, we hope to learn about the mechanism by which gatekeeper mutations in KIT cause drug resistance to help inform future generations of KIT inhibitors.