Extracellular vesicles (EVs) are increasingly being recognized as important vehicles for intercellular communication and as promising sources for biomarker discovery. Because the state of protein post-translational modifications (PTMs) such as phosphorylation and glycosylation can be a key determinant of cellular physiology, comprehensive characterization of protein PTMs in EVs can be particularly valuable for early-stage diagnostics and monitoring of disease status. However, the analysis of PTMs in EVs has been complicated by limited amounts of purified EVs, low-abundance PTM proteins, and interference from proteins and metabolites in biofluids. Recently, we developed an approach to isolate phosphoproteins and glycoproteins in EVs from small volumes of human plasma that enabled us to identify nearly 10,000 unique phosphopeptides and 1,500 unique N-glycopeptides. The approach demonstrated the feasibility of using these data to identify potential markers to differentiate disease from healthy states. Here we present an updated workflow to sequentially isolate phosphopeptides and N-glycopeptides, enabling multiple PTM analyses of the same clinical samples. In this updated workflow, we have improved the reproducibility and efficiency of EV isolation, protein extraction, and phosphopeptide/Nglycopeptide enrichment to achieve sensitive analyses of low-abundance PTMs in EVs isolated from 1 mL of plasma. The modularity of the workflow also allows for the characterization of phospho-or glycopeptides only and enables additional analysis of total proteomes and other PTMs of interest. After blood collection, the protocol takes 2 d, including EV isolation, PTM/peptide enrichment, mass spectrometry analysis, and data quantification. Reprints and permissions information is available at www.nature.com/reprints.

Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.

Glycoproteins have vast structural diversity which plays an important role in many biological processes and have great potential as disease biomarkers. Here we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase GlycoProtein Array (polyGPA), to specifically capture and profile glycoproteomes, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture pre-oxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous alpha-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

Extracellular vesicles (EVs) have emerged as important carriers for intercellular communication and biological sources for diagnosis and therapeutics. Low efficiency in EV isolation from biofluids, however, severely restricts their downstream characterization and analysis. Here, we introduced a novel strategy for EV isolation from urine for prostate cancer diagnosis using bifunctionalized magnetic beads through high affinity Ti­(IV) ions and the insertion of a phospholipid derivative, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine, into the EV membrane synergistically. We demonstrated its efficient isolation of EVs from urine samples with low contamination, high recovery (>80%), and short separation time (within 1 h), resulting in the identification of 36,262 unique EV peptides corresponding to 3302 unique proteins and 3233 unique phosphopeptides representing 1098 unique phosphoproteins using only 100 μL and 5 mL urine samples, respectively. Coupled with trapped ion mobility spectrometry and parallel accumulation–serial fragmentation for phosphosite-specific resolution, quantitative phosphoproteomics of urine samples from prostate cancer patients and healthy individuals revealed 121 upregulated phosphoproteins in cancer patients in contrast to the healthy group. These particular advantages indicate that the novel bifunctional material enables sensitive EV phosphoproteomic analysis for noninvasive biomarker screening and early cancer diagnosis.