A new approach to understand kinase pathway wiring, rewiring, and drug resistance in cancer and other diseases

Phosphorylation is a vital cellular regulatory mechanism. Alterations in phosphorylation are major contributors to disease, and numerous clinically-important drugs target kinases to treat cancer and other disorders. Acquired resistance to these therapies can arise by rewiring of kinase pathways. Characterising signalling networks is therefore crucial to delineate changes in disease, to improve predictions of drug efficacy and patient response to targeted therapies, to understand resistance, and to identify biomarkers and diagnostics. To this end, Kinomica offers mass-spectrometry-based and computational services that interrogate thousands of phosphorylation sites and elucidate large phosphoproteomic networks.
Although thousands of phosphorylation sites are known, identifying the kinases for particular phosphorylation events is a major roadblock. This hinders understanding of signalling changes in disease and, for Kinomica, means that the depth of their phosphoproteomic datasets cannot be fully exploited. To address these problems, we recently developed a generally-applicable method ("KiPIK") to identify kinases for specific phosphorylation sites that uses libraries of kinase inhibitors that have been profiled on near-kinome-wide panels of protein kinases. The inhibition profile for each kinase provides a 'fingerprint' that allows unknown kinases acting on target phosphosites in cell extracts to be identified. The method has clear advantages over in silico and genetic screening, and we have validated it on diverse kinase-phosphosite pairs. It has potential to help reveal kinase pathway rewiring in disease, particularly cancer, and perhaps to reveal therapeutic targets in individual patients. However, a remaining question is whether KiPIK can unambiguously identify kinases for phosphorylation sites of kinases with related consensus motifs.
In this project, the student will identify suitable known phosphorylation sites (eg target motifs of basophilic kinases; R/K-x-x-x-x-S/T, R/K-x-x-S/T and R/K-x-R/K-x-x-S/T) and test whether KiPIK can distinguish kinases for related consensus sites, beginning with targets of the basophilic kinase Akt1. They will use KiPIK to identify candidate kinases for phosphorylation sites commonly present in Kinomica's datasets for which the corresponding kinase(s) are unknown, and validate them using cell biological approaches such as RNA interference, CRISPR, inhibition studies, and in vitro kinase assays. The student will visit Kinomica within year 1 to familiarise themselves with their technology and identify additional targets for study, and then later for an extended period to integrate knowledge from the CASE project. Success would validate KiPIK as a platform for fundamental and disease-based research, allowing the elucidation kinase signalling and pathway rewiring in disease, and would increase the information provided by Kinomica's technologies.