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Extracellular vesicles (EVs) are mediators of intercellular communication and a promising class of biomarkers. Surface proteins of EVs play decisive roles in establishing a connection with recipient cells, and they are putative targets for diagnostic assays. Analysis of the surface proteins can thus both illuminate the biological functions of EVs and help identify potential biomarkers. We developed a strategy combining high-resolution mass spectrometry (HRMS) and  proximity ligation assays (PLA) to first identify and then validate surface proteins discovered on EVs. We applied our workflow to investigate surface proteins of small EVs found in seminal fluid (SF-sEV). We identified 1,014 surface proteins and verified the presence of a subset of these on the surface of SF-sEVs. Our work demonstrates a general strategy for deep analysis of EVs' surface proteins across patients and pathological conditions, proceeding from unbiased screening by HRMS to ultra-sensitive targeted analyses via PLA.

Gastric cancer (GC) is the third leading cause of cancer death. Early detection and efficient monitoring of tumor dynamics are prerequisites for reducing disease burden and mortality. Blood-based biomarker assays for the detection of early-stage GC could be of great relevance for population-wide or risk-group-based screening programs. Extracellular vesicles (EVs) are nano-sized membrane-enclosed particles released from all cells, which play an essential role as mediators of intercellular communication and are a promising class of biomarkers. We aimed to determine the putative panel of protein targets by collecting EVs from GC cell lines for future diagnostic assays. We measured levels of over 430 proteins using highly sensitive and high-throughput proximity extension assays (PEA). The protein network and function of each protein were analyzed. In conclusion, despite a similarity between GC EVs and EVs from the prostate as a control, we identified a set of 39 proteins in GC EVs that are involved in different cellular pathways and are not expressed or have low expression in exosomes from the prostate.

Extracellular vesicles (EVs), whose main subtypes are exosomes, microparticles, and apoptotic bodies, are secreted by all cells and harbor biomolecules such as DNA, RNA, and proteins. They function as intercellular messengers and, depending on their cargo, may have multiple roles in cancer development. Thymidine kinase 1 (TK1) is a cell cycle-dependent enzyme used as a biomarker for cell proliferation. TK1 is usually elevated in cancer patients' serum, making the enzyme a valuable tumor proliferation biomarker that strongly correlates with cancer stage and metastatic capabilities. Here, we investigated the presence of TK1 in EVs derived from three prostate cancer cell lines with various p53 mutation statuses (LNCaP, PC3, and DU145), EVs from the normal prostate epithelial cell line RWPE-1 and EVs isolated from human seminal fluid (prostasomes). We measured the TK1 activity by a real-time assay for these EVs. We demonstrated that the TK1 enzyme activity is higher in EVs derived from the malignant cell lines, with the highest activity from cells deriving from the most aggressive cancer, compared to the prostasomes and RWPE-1 EVs. The measurement of TK1 activity in EVs may be essential in future prostate cancer studies.

To improve our ability to monitor cellular responses to e.g. cytokines or drugs, Lonn et al have developed a semi-automated system for large-scale in situ proximity ligation assays (isPLA) in HaCAT keratinocyte cells. Their approach expands the scope for image-based single cell analyses by combining observations of protein interactions and modifications with morphological details of individual cells at high throughput. Protein interactions and posttranslational modifications orchestrate cellular responses to e.g. cytokines and drugs, but it has been difficult to monitor these dynamic events in high-throughput. Here, we describe a semi-automated system for large-scale in situ proximity ligation assays (isPLA), combining isPLA in microtiter wells with automated microscopy and computer-based image analysis. Phosphorylations and interactions are digitally recorded along with subcellular morphological features. We investigated TGF-beta-responsive Smad2 linker phosphorylations and complex formations over time and across millions of individual cells, and we relate these events to cell cycle progression and local cell crowding via measurements of DNA content and nuclear size of individual cells, and of their relative positions. We illustrate the suitability of this protocol to screen for drug effects using phosphatase inhibitors. Our approach expands the scope for image-based single cell analyses by combining observations of protein interactions and modifications with morphological details of individual cells at high throughput.