Data-Independent Acquisition Mass Spectrometry (DIA-MS) enables deep, reproducible, and quantitative proteome coverage across large sample cohorts. We apply DIA-MS workflows to characterize how post-translational modifications (PTMs) — particularly phosphorylation — change across disease states, treatment conditions, and aging.
Our proteomics work has two primary aims. First, we use DIA-MS to validate and extend findings from our peptide biosensor assays, providing unbiased, system-wide confirmation of kinase pathway changes. Second, we pursue biomarker discovery by comparing PTM profiles across clinical samples to identify candidate signatures with diagnostic or prognostic value.
We combine phosphoproteomics with total proteome measurements (multi-omics) to separate changes in protein abundance from changes in modification stoichiometry. This integrated view enables a more complete understanding of how signaling networks are rewired in cancer and other diseases, and how those changes can be exploited therapeutically.