The technical difficulty of separating extracellular vesicles (EVs) from plasma proteins in human blood presents a significant hurdle in EV research, particularly during nano ultra-high-performance liquid chromatography–tandem mass spectrometric (UHPLC-MS/MS) analysis, where detecting “vesicular” proteins among abundant plasma proteins is challenging. Standardisation is a pressing issue in EV research, prompting collaborative global efforts to address it. While the MISEV guidelines offer valuable recommendations, unanswered questions remain, particularly regarding sample storage. We compared size exclusion chromatography (SEC) columns with pore sizes of 35 nm and 70 nm to identify fractions with minimal contaminating proteins and the highest concentration of small EVs (sEVs). Following column selection, we explored potential differences in the quality and quantity of sEVs isolated from platelet-free plasma (PFP) after long-term storage at −80 °C (>2.5 years) compared to freshly drawn blood. Our methodologically rigorous study indicates that prolonged storage, under correct storage and processing conditions, does not compromise sEV quality. Both columns effectively isolated vesicles, with the 70 nm column exhibiting a higher abundance of “vesicular” proteins. We propose a relatively rapid and moderately efficient protocol for obtaining a comparatively pure sEV fraction from plasma, facilitating sEV processing in clinical trials.

Lung cancer is a severe disease for which better diagnostic and therapeutic approaches are urgently needed. Increasing evidence implies that aberrant protein glycosylation plays a crucial role in the pathogenesis and progression of lung cancer. Differences in glycosylation patterns have been previously observed between healthy and cancerous samples as well as between different lung cancer subtypes, which suggests untapped diagnostic potential. In addition, understanding the changes mediated by glycosylation may shed light on possible novel therapeutic targets and personalized treatment strategies for lung cancer patients. Mass spectrometry based glycomics and glycoproteomics have emerged as powerful tools for in‐depth characterization of changes in protein glycosylation, providing valuable insights into the molecular basis of lung cancer. This paper reviews the literature on the analysis of protein glycosylation in lung cancer using mass spectrometry, which is dominated by manuscripts published over the past 5 years. Studies analyzing N ‐glycosylation, O ‐glycosylation, and glycosaminoglycan patterns in tissue, serum, plasma, and rare biological samples of lung cancer patients are highlighted. The current knowledge on the potential utility of glycan and glycoprotein biomarkers is also discussed.

Extracellular vesicles (EVs) are implicated in inter-organ communication, which becomes particularly relevant during aging and exercise. DNA methylation-based aging clocks reflect lifestyle and environmental factors, while regular exercise is known to induce adaptive responses, including epigenetic adaptations. Twenty individuals with High-fitness (aged 57.7 ± 9.8 years) and twenty Medium–Low-fitness (aged 57.5 ± 9.7 years) subjects provided blood samples. EVs were isolated from the samples using a size exclusion chromatography (SEC)-based method, and their protein content was analyzed by mass spectrometry (MS). Acceleration of the biological age estimator DNAmFitAge (AgeAccelFit) was associated with the protein cargo of EVs, whereas PhenoAge and GrimAge acceleration did not show a significant relationship. This finding suggests that the epigenetic aging-modulating role of exercise may involve inter-organ communication via EVs. Set Enrichment Analysis was performed to identify enriched Gene Ontology (GO) terms for sets of proteins that were either correlated with AgeAccelFit or detected exclusively in individuals with high levels of aerobic fitness. The protein cargo of EVs further suggests that inter-organ communication influences inflammation, the immune system, cellular repair, adhesion, metabolism and coagulation. Our findings help to understand the preventive role of exercise, which could be mediated in part by EVs.

Pulmonary adenocarcinomas (pADCs) with an ALK rearrangement are a rare cancer subtype, necessitating comprehensive molecular investigations to unravel their heterogeneity and improve therapeutic strategies. In this pilot study, we employed spatial transcriptomic (NanoString GeoMx) and proteomic profiling to investigate seven treatment-naïve pADCs with an ALK rearrangement. On each FFPE tumor slide, 12 smaller and 2–6 larger histopathologically annotated regions were selected for transcriptomic and proteomic analysis, respectively. The correlation between proteomics and transcriptomics was modest (average Pearson’s r = 0.43 at the gene level). Intertumoral heterogeneity was more pronounced than intratumoral heterogeneity, and normal adjacent tissue exhibited distinct molecular characteristics. We identified potential markers and dysregulated pathways associated with tumors, with a varying extent of immune infiltration, as well as with mucin and stroma content. Notably, some markers appeared to be specific to the ALK-driven subset of pADCs. Our data showed that within tumors, elements of the extracellular matrix, including FN1, exhibited substantial variability. Additionally, we mapped the co-localization patterns of tumor microenvironment elements. This study represents the first spatially resolved profiling of ALK-driven pADCs at both the gene and protein expression levels. Our findings may contribute to a better understanding of this cancer type prior to treatment with ALK inhibitors.

Extracellular vesicles (EVs) are central to intercellular communication and have gained attention as rich sources of molecular information in cancer research, but their molecular composition remains incompletely characterized. Protein glycosylation is a frequent post-translational modification; however, most EV studies focus on proteomics, while mapping glycosylation changes of proteins are still underrepresented. To address this gap, we analyzed the proteomic, N-glycoproteomic, and chondroitin/dermatan sulfate (CS/DS) glycosaminoglycan (GAG) profiles of small EVs (sEVs) derived from A549 lung adenocarcinoma and BEAS-2B non-tumorigenic epithelial cells. Principal component analysis and hierarchical clustering revealed that all three profiles strongly reflect sEV origin. Comparative proteomic analysis showed enrichment of proteins associated with cell cycle regulation, deoxyribonucleic acid repair, metabolism, and protein synthesis in A549 sEVs, while immune-related processes were enriched in BEAS-2B sEVs. Five differentially expressed CS proteoglycans were identified, highlighting the value of complementary GAG-level analysis. N-glycoproteomics revealed a shift from oligomannose to complex N-glycans in A549 sEVs. Prominent glycoproteins with multiple glycosylation sites included versican, galectin-3-binding protein and laminins. CS/DS content increased 3.4-fold in A549 sEVs, while the ratio of the two monosulfated disaccharides changed 2-fold. These findings demonstrate the utility of N-glycoproteomics and GAG profiling for sensitively characterizing molecular differences between sEVs derived from different cell culture models, thereby providing a foundation for future EV biomarker studies.

The optimization of solid-phase extraction (SPE) purification and chromatographic separation is usually neglected during proteomics studies. However, the effects on detection performance are not negligible, especially when working with highly glycosylated samples. We performed a comparative study of different SPE setups, including an in-house optimized method and reversed-phase chromatographic gradients for the analysis of highly glycosylated plasma fractions as a model sample for glycopeptide analysis. The in-house-developed SPE method outperformed the graphite-based and hydrophilic interaction liquid chromatography (HILIC) purification methods in detection performance, recovery, and repeatability. During optimization of the chromatography, peak distribution was maximized to increase the peptide detection rate. As a result, we present sample purification and chromatographic separation methods optimized for the analysis of hydrophilic samples, the most important of which is heavily N-glycosylated protein mixtures.