Mass Spectrometry-Based Phosphoproteomics: From Method Development to Application

Phosphorylation is one of the most prevalent and dynamic post-translational modifications, functioning as a molecular switch that regulates protein activity, localization, interactions, and stability across nearly all cellular pathways. By reversibly adding phosphate groups, cells rapidly adjust signaling networks in response to environmental and intracellular cues. Because dysregulated phosphorylation is central to diseases such as cancer and infection, systematic characterization of phosphorylation events is essential for understanding cellular regulation and improving therapeutic strategies. Mass spectrometry (MS) has become the leading platform for phosphoproteomics due to its sensitivity, specificity, and scalability. It enables precise localization of phosphorylation sites, discrimination of phospho-isomers, and multiplexed quantification across thousands of proteins in a single experiment. These capabilities make MS indispensable for mapping signaling networks, identifying novel phosphosites, and investigating disease-associated signaling alterations. This thesis focused on developing and applying advanced MS-based phosphoproteomic approaches to investigate phosphorylation-driven signaling in cancer, secretion biology, and infection. The work centers on three pillars: optimization of sample preparation, development of innovative MS acquisition strategies, and integration of phosphoproteomics with biological assays to interpret phenotypic changes and improve therapeutic outcomes. Chapter 1 provides a comprehensive overview of MS-based phosphoproteomics. It outlines the biological roles of kinases and phosphatases, describes LC-MS workflows, ionization techniques, ion mobility separation, fragmentation methods, and high-resolution mass analyzers, and details essential steps in sample preparation, phosphopeptide enrichment, and data acquisition. Chapter 2 addresses limitations in phosphoproteome sample preparation using suspension trapping (S-Trap). Although widely adopted for its robustness, standard protocols incorporating phosphoric acid were found to impair phosphopeptide enrichment and substantially reduce phosphosite identifications. By replacing phosphoric acid with trifluoroacetic acid, the optimized workflow restored phosphoproteomic performance without compromising global proteome analysis. Application to extracellular vesicles demonstrated improved sensitivity for low-abundance, membrane-rich samples. Chapter 3 introduces Targeted Signal Amplification of Phosphopeptides (TSAP), designed to overcome trade-offs between global discovery and targeted quantification in limited samples. Combining tandem mass tag (TMT) labeling with real-time MS3 acquisition, TSAP enhances detection sensitivity and quantification accuracy of low-abundance phosphopeptides while preserving discovery capacity. Chapter 4 investigates differential signaling landscapes in PIK3CA H1047R and E545K mutants under PI3K inhibition and insulin stimulation. Deep proteomic and phosphoproteomic profiling of MCF10A models revealed mutation-specific responses. Insulin rescued alpelisib-treated mutant cells by reactivating PI3K signaling and promoting adaptive reprogramming, including p90RSK activation within the MAPK pathway. These findings provide mechanistic insight into reduced inhibitor efficacy in PIK3CA-mutant breast cancer. Chapter 5 synthesizes methodological principles and highlights emerging opportunities in phosphoproteomics. As technologies mature, integrative phosphoproteomic profiling will increasingly inform precision medicine by linking signaling dynamics to therapeutic response.