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Mcilwain, S. J.

Publications and source records attributed to Mcilwain, S. J..

2 recordsLinked to original sources

Proteoform-Resolved Phosphorylation Dynamics in Kinase Complexes by Hybrid Precision Mass Spectrometry

Protein kinases integrate cellular signals through complex phosphorylation cascades, yet resolving how chemical perturbations trigger and modulate these cascades in therapeutic targets remains a major challenge. Here, we dissect AMP-activated protein kinase (AMPK) proteoforms during activation through controlled biochemical reactions with a hybrid mass spectrometry (MS) approach integrating bottom-up MS for site-specific kinetics with top-down proteoform characterization. We reveal that AMPK phosphorylation proceeds through hierarchical cascades rather than binary switching, with dual entry points: canonical CaMKK2-mediated phosphorylation or allosteric activator PF-739 both triggering extensive autophosphorylation with 1-S496 showing highest kinetic priority. Proteoform-resolved analysis uncovers channeled {beta}1-S24/25+S108 co-phosphorylation linking subcellular localization with allosteric responsiveness. Site-directed mutagenesis demonstrates CaMKK2 targets only 1-T183, with all other modifications arising through autophosphorylation. Phosphatase competition reveals asymmetric control where PP1A selectively removes activation-loop phosphorylation while autophosphorylation sites remain protected, establishing persistent regulatory states. Resolving AMPKs temporal kinetics and proteoform architecture during activation enables a proteoform-centric understanding on kinase regulation.

biochemistry↗

Integrating Subclonal Response Heterogeneity to Define Cancer Organoid Therapeutic Sensitivity

Tumor heterogeneity is predicted to confer inferior clinical outcomes, however modeling heterogeneity in a manner that still represents the tumor of origin remains a formidable challenge. Sequencing technologies are limited in their ability to identify rare subclonal populations and predict response to the multitude of available treatments for patients. Patient-derived organotypic cultures have significantly improved the modeling of cancer biology by faithfully representing the molecular features of primary malignant tissues. Patient-derived cancer organoid (PCO) cultures contain numerous individual organoids with the potential to recapitulate heterogeneity, though PCOs are most commonly studied in bulk ignoring any diversity in the molecular profile or treatment response. Here we demonstrate the advantage of evaluating individual PCOs in conjunction with cellular level optical metabolic imaging to characterize the largely ignored heterogeneity within these cultures to predict clinical therapeutic response, identify subclonal populations, and determine patient specific mechanisms of resistance.

cancer biology↗