There is a real need for biomarkers that can indicate glioma disease burden and inform clinical management, particularly in the recurrent glioblastoma (GBM; grade IV glioma) setting where treatment-associated brain changes can confound current and expensive tumour surveillance methods. In this regard, extracellular vesicles (EVs; 30-1000 nm membranous particles) hold major promise as robust tumour biomarkers. GBM-EVs encapsulate molecules that reflect the identity and molecular state of their cell-of-origin and cross the blood-brain-barrier into the periphery where they are readily accessible. Despite the suitability of circulating-EVs for GBM biomarker discovery, sample complexity has hindered comprehensive quantitative proteomic studies. Here, sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used in conjunction with a targeted data extraction strategy to comprehensively profile circulating-EVs isolated from plasma. Plasma-EVs sourced from pre-operative glioma II-IV patients (n=41) and controls (n=11) were sequenced by SWATH-MS, and the identities and absolute quantities of the proteins were extracted by aligning the SWATH-MS data against a custom glioma spectral library comprised of 8662 high confidence protein species. Overall, 4054 plasma-EV proteins were quantified across the cohorts, and putative circulating-EV biomarker proteins identified (adjusted p-value<0.05) included previously reported GBM-EV proteins identified in vitro and in neurosurgical aspirates. Principle component analyses showed that plasma-EV protein profiles clustered according to glioma subtype and WHO-grade, and plasma-EV proteins reflected the extent of glioma aggression. Using SWATH-MS, we describe the most comprehensive proteomic plasma-EV profiles for glioma and highlight the promise of this approach as an accurate and sensitive tumour monitoring method. Objective blood-based measurements of glioma tumour activity will support the implementation of next-generation, patient-centred therapies and are ideal surrogate endpoints for recurrent progression that would allow clinical trial protocols to be more dynamic and adapt to the individual patient and their cancer.
