Journal of extracellular biology最新文献

Cellular elements that infiltrate and surround tumours and pre-metastatic tissues have a prominent role in tumour invasion and growth. The extracellular vesicles specifically entrapped and stored within the extracellular matrix (ECM-EVs) may reflect the different populations of the tumour microenvironment and their change during tumour progression. However, their profile is at present unknown. To elucidate this aspect, we isolated and characterized EVs from decellularized surgical specimens of colorectal cancer and adjacent colon mucosa and analyzed their surface marker profile. ECM-EVs in tumours and surrounding mucosa mainly expressed markers of lymphocytes, natural killer cells, antigen-presenting cells, and platelets, as well as epithelial cells, representing a multicellular microenvironment. No difference in surface marker expression was observed between tumour and mucosa ECM-EVs in stage II-III tumours. At variance, in the colon mucosa adjacent to stage IV carcinomas, ECM-EV profile showed a significantly increased level of immune, epithelial and platelet markers in comparison to the matrix of the corresponding tumour. The increase of EVs from immune cells and platelets was not observed in the mucosa adjacent to low-stage tumours. In addition, CD25, a T-lymphocyte marker, resulted specifically overexpressed by ECM-EVs from stage IV carcinomas, possibly correlated with the pro-tolerogenic environment found in the corresponding tumour tissue. These results outline the tissue microenvironmental profile of EVs in colorectal carcinoma-derived ECM and unveil a profound change in the healthy mucosa adjacent to high-stage tumours.

Epithelial-mesenchymal transition (EMT) is associated with tumorigenesis and drug resistance. The Rab superfamily of small G-proteins plays a role in regulating cell cytoskeleton and vesicle transport. However, it is not yet clear how the Rab family contributes to cancer progression by participating in EMT. By analysing various in silico datasets, we identified a statistically significant increase in RAB31 expression in the oxaliplatin-resistant group compared to that in the parental or other chemotherapy drug groups. Our findings highlight RAB31's powerful effect on colorectal cancer cell lines when compared with other family members. In a study that analysed multiple online meta-databases, RAB31 RNA levels were continually detected in colorectal tissue arrays. Additionally, RAB31 protein levels were correlated with various clinical parameters in clinical databases and were associated with negative prognoses for patients. RAB31 expression levels in all three probes were calculated using a computer algorithm and were found to be positively correlated with EMT scores. The expression of the epithelial-type marker CDH1 was suppressed in RAB31 overexpression models, whereas the expression of the mesenchymal-type markers SNAI1 and SNAI2 increased. Notably, RAB31-induced EMT and drug resistance are dependent on extracellular vesicle (EV) secretion. Interactome analysis confirmed that RAB31/AGR2 axis-mediated exocytosis was responsible for maintaining colorectal cell resistance to oxaliplatin. Our study concluded that RAB31 alters the sensitivity of oxaliplatin, a supplementary chemotherapy approach, and is an independent prognostic factor that can be used in the treatment of colorectal cancer.

Extracellular vesicles (EVs) have been involved in metabolic syndrome, although their specific role in the development of the pathology is still unknown. To further study the role of EVs, we have analysed by Raman tweezers microspectroscopy and mass spectrometry-based lipidomics the small EVs population secreted by fatty (ZF) and lean (ZL) hepatocytes obtained from Zucker rats. We have also explored in vivo and ex vivo biodistribution of these EVs through fluorine-18-radiolabelling using a positron emission tomography imaging. Based on the proportion of proteins to lipids and the types of lipids, our results indicate that within the range of small EVs, primary hepatocytes secrete different subpopulations of particles. These differences were observed in the enrichment of triglyceride species in EVs secreted by ZF hepatocytes. Biodistribution experiments showed accumulation in the brain, heart, lungs, kidney and specially in bladder after intravenous administration. In summary, we show that EVs released by a fatty hepatocytes carry a different lipid signature compared to their lean counterpart. Biodistribution experiment has shown no difference in the distribution of EVs secreted by ZF and ZL hepatocytes but has given us a first view of possible target organs for these particles. Our results might open a door to both pathology studies and therapeutic interventions.

Extracellular vesicles (EVs) in biofluids are highly heterogeneous entities in terms of their origins and physicochemical properties. Considering the application of EVs in diagnostic and therapeutic fields, it is of extreme importance to establish differentiating methods by which focused EV subclasses are operationally defined. Several differentiation protocols have been proposed; however, they have mainly focused on smaller types of EVs, and the heterogeneous nature of large EVs has not yet been fully explored. In this report, to classify large EVs into subgroups based on their physicochemical properties, we have developed a protocol, named EV differentiation by sedimentation patterns (ESP), in which entities in the crude large EV fraction are first moved through a density gradient of iodixanol with small centrifugation forces, and then the migration patterns of molecules through the gradients are analysed using a non-hierarchical data clustering algorithm. Based on this method, proteins in the large EV fractions of oral fluids clustered into three groups: proteins shared with small EV cargos and enriched in immuno-related proteins (Group 1), proteins involved in energy metabolism and protein synthesis (Group 2), and proteins required for vesicle trafficking (Group 3). These observations indicate that the physiochemical properties of EVs, which are defined through low-speed gradient centrifugation, are well associated with their functions within cells. This protocol enables the detailed subclassification of EV populations that are difficult to differentiate using conventional separation methods.

Colon cancer is one of the most commonly occurring tumours among both women and men, and over the past decades the incidence has been on the rise. As such, the need for biomarker identification as well as an understanding of the underlying disease mechanism has never been greater. Extracellular vesicles are integral mediators of cell-to-cell communication and offer a unique opportunity to study the machinery that drives disease progression, and they also function as vectors for potential biomarkers. Tumour tissue and healthy mucosal tissue from the colons of ten patients were used to isolate tissue-resident EVs that were subsequently subjected to global quantitative proteomic analysis through LC-MS/MS. In total, more than 2000 proteins were identified, with most of the common EV markers being among them. Bioinformatics revealed a clear underrepresentation of proteins involved in energy production and cellular adhesion in tumour EVs, while proteins involved in protein biosynthesis were overrepresented. Additionally, 53 membrane proteins were found to be significantly upregulated in tumour EVs. Among them were several proteins with enzymatic functions that degrade the extracellular matrix, and three of these, Fibroblast activating factor (FAP), Cell surface hyaluronidase (CEMIP2), as well as Ephrin receptor B3 (EPHB3), were validated and found to be consistent with the global quantitative results. These stark differences in the proteomes between healthy and cancerous tissue emphasise the importance of the interstitial vesicle secretome as a major player of disease development.

Most living organisms secrete tiny lipid bilayer particles encapsulating various biomolecular entities, including nucleic acids and proteins. These secreted extracellular vesicles (EVs) are shown to aid in communication between cells and their environment. EVs are mainly involved in the signalling and manipulation of physiological processes. Plant EVs display similar functional activity as seen in mammalian EVs. Medicinal plants have many bioactive constituents with potential applications in cancer treatment. Particularly, Basil (Ocimum basilicum), has wide therapeutic properties including anti-inflammatory, anti-cancer, and anti-infection, among others. In this study, we focused on using EVs purified from Apoplast Washing Fluid (AWF) of Basil plant leaves as a biological therapeutic agent against cancer. Characterization of Basil EVs revealed a size range of 100–250 nm, which were later assessed for their cell uptake and apoptosis inducing abilities in pancreatic cancer cells. Basil plant EVs (BasEVs) showed a significant cytotoxic effect on pancreatic cancer cell line MIA PaCa-2 at a concentration of 80 and 160 μg/mL in cell viability, as well as clonogenic assays. Similarly, RT-PCR and western blot analysis has shown up regulation in apoptotic gene and protein expression of Bax, respectively, in BasEV treatment groups compared to untreated controls of MIA PaCa-2. Overall, our results suggest that EVs from basil plants have potent anti-cancer effects in pancreatic cancer cells and can serve as a drug delivery system, demanding an investigation into the therapeutic potential of other medicinal plant EVs.

The interferon stimulated gene 15 (ISG15), a ubiquitin like protein and its conjugates have been implicated in various human malignancies. However, its role in ovarian cancer progression and metastasis is largely unknown. In high grade serous ovarian cancer (HGSOC), ascites is the major contributor to peritoneal metastasis. In this study, we identified significantly elevated ISG15 protein expression in HGSOC patient ascites, ascites derived primary ovarian cancer cells (POCCs), POCC small extracellular vesicles (sEVs) as well as metastatic tissue. Our results demonstrates that ISG15 increases exocytosis in ascites-derived POCCs by decreasing the endosome-lysosomal fusion, indicating a key role in sEV secretion. Further, knockdown (KD) of ISG15 resulted in a significant decrease in vesicles secretion from HGSOC cells and in vivo mouse models, leading to reduced HGSOC cell migration and invasion. Furthermore, our pre-clinical mouse model studies revealed the influence of vesicular ISG15 on disease progression and metastasis. In addition, knockdown of ISG15 or using the ISG15 inhibitor, DAP5, in combination therapy with carboplatin showed to improve the platinum sensitivity in-vitro and reduce tumour burden in-vivo. We also found that ISG15 expression within sEV represents a promising prognostic marker for HGSOC patients. Our findings suggest that ISG15 is a potential therapeutic target for inhibiting progression and metastasis in HGSOC and that vesicular ISG15 expression could be a promising biomarker in the clinical management of ovarian cancer.

Significance: High-grade serous ovarian cancer (HGSOC) has high morbidity and mortality rates, but its progression and metastasis are still poorly understood, and there is an urgent need for early detection and targeted therapies. Our study presents novel findings that implicate ISG15-mediated vesicular proteins in the advancement and spread of HGSOC. These results offer pre-clinical evidence of potential new molecular targets, prognostic markers and therapeutic strategies for HGSOC that could ultimately enhance patient survival.

Extracellular vesicles (EVs) are cell derived membranous nanoparticles. EVs are important mediators of cell–cell communication via the transfer of bioactive content and as such they are being investigated for disease diagnostics as biomarkers and for potential therapeutic cargo delivery to recipient cells. However, existing methods for isolating EVs from biological samples suffer from challenges related to co-isolation of unwanted materials such as proteins, nucleic acids, and lipoproteins. In the pursuit of improved EV isolation techniques, we introduce multimodal flowthrough chromatography (MFC) as a scalable alternative to size exclusion chromatography (SEC). The use of MFC offers significant advantages for purifying EVs, resulting in enhanced yields and increased purity with respect to protein and nucleic acid co-isolates from conditioned 3D cell culture media. Compared to SEC, significantly higher EV yields with similar purity and preserved functionality were also obtained with MFC in 2D cell cultures. Additionally, MFC yielded EVs from serum with comparable purity to SEC and similar apolipoprotein B content. Overall, MFC presents an advancement in EV purification yielding EVs with high recovery, purity, and functionality, and offers an accessible improvement to researchers currently employing SEC.

The “QuantitatEVs: multiscale analyses, from bulk to single vesicle” workshop aimed to discuss quantitative strategies and harmonized wet and computational approaches toward the comprehensive analysis of extracellular vesicles (EVs) from bulk to single vesicle analyses with a special focus on emerging technologies. The workshop covered the key issues in the quantitative analysis of different EV-associated molecular components and EV biophysical features, which are considered the core of EV-associated biomarker discovery and validation for their clinical translation. The in-person-only workshop was held in Trento, Italy, from January 31^st to February 2^nd, 2023, and continued in Milan on February 3^rd with “Next Generation EVs,” a satellite event dedicated to early career researchers (ECR). This report summarizes the main topics and outcomes of the workshop.

Extracellular vesicles (EVs) are membranous structures released by cells into the extracellular space and are thought to be involved in cell-to-cell communication. While EVs and their cargo are promising biomarker candidates, sorting mechanisms of proteins to EVs remain unclear. In this study, we ask if it is possible to determine EV association based on the protein sequence. Additionally, we ask what the most important determinants are for EV association. We answer these questions with explainable AI models, using human proteome data from EV databases to train and validate the model. It is essential to correct the datasets for contaminants introduced by coarse EV isolation workflows and for experimental bias caused by mass spectrometry. In this study, we show that it is indeed possible to predict EV association from the protein sequence: a simple sequence-based model for predicting EV proteins achieved an area under the curve of 0.77 ± 0.01, which increased further to 0.84 ± 0.00 when incorporating curated post-translational modification (PTM) annotations. Feature analysis shows that EV-associated proteins are stable, polar, and structured with low isoelectric point compared to non-EV proteins. PTM annotations emerged as the most important features for correct classification; specifically, palmitoylation is one of the most prevalent EV sorting mechanisms for unique proteins. Palmitoylation and nitrosylation sites are especially prevalent in EV proteins that are determined by very strict isolation protocols, indicating they could potentially serve as quality control criteria for future studies. This computational study offers an effective sequence-based predictor of EV associated proteins with extensive characterisation of the human EV proteome that can explain for individual proteins which factors contribute to their EV association.