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Oviductal extracellular vesicles (oEVs) are emerging as key players in the gamete/embryo-oviduct interactions that contribute to successful pregnancy. Various positive effects of oEVs on gametes and early embryos have been found in vitro. To determine whether these effects are associated with changes of embryonic gene expression, the transcriptomes of embryos supplemented with bovine fresh (FeEVs) or frozen (FoEVs) oEVs during in vitro culture compared to controls without oEVs were analyzed by low-input RNA sequencing. Analysis of RNA-seq data revealed 221 differentially expressed genes (DEGs) between FoEV treatment and control, 67 DEGs for FeEV and FoEV treatments, and minor differences between FeEV treatment and control (28 DEGs). An integrative analysis of mRNAs and miRNAs contained in oEVs obtained in a previous study with embryonic mRNA alterations pointed to direct effects of oEV cargo on embryos (1) by increasing the concentration of delivered transcripts; (2) by translating delivered mRNAs to proteins that regulate embryonic gene expression; and (3) by oEV-derived miRNAs which downregulate embryonic mRNAs or modify gene expression in other ways. Our study provided the first high-throughput analysis of the embryonic transcriptome regulated by oEVs, increasing our knowledge on the impact of oEVs on the embryo and revealing the oEV RNA components that potentially regulate embryonic development.

Multi‐analyte liquid biopsies represent an emerging opportunity for non‐invasive cancer assessment. We developed ONCE (One Aliquot for Circulating Elements), an approach for the isolation of extracellular vesicles (EV) and cell‐free DNA (cfDNA) from a single aliquot of blood. We assessed ONCE performance to classify HER2‐positive early‐stage breast cancer (BrCa) patients by combining EV‐associated RNA (EV‐RNA) and cfDNA signals on n = 64 healthy donors (HD) and non–metastatic BrCa patients. Specifically, we isolated EV‐enriched samples by a charge‐based (CB) method and investigated EV‐RNA and cfDNA by next‐generation sequencing (NGS) and by digital droplet PCR (ddPCR). Sequencing of cfDNA and EV‐RNA from HER2‐ and HER2+ patients demonstrated concordance with in situ molecular analyses of matched tissues. Combined analysis of the two circulating analytes by ddPCR showed increased sensitivity in ERBB2/HER2 detection compared to single nucleic acid components. Multi‐analyte liquid biopsy prediction performance was comparable to tissue‐based sequencing results from TCGA. Also, imaging flow cytometry analysis revealed HER2 protein on the surface of EV isolated from the HER2+ BrCa plasma, thus corroborating the potential relevance of studying EV as companion analyte to cfDNA. This data confirms the relevance of combining cfDNA and EV‐RNA for HER2 cancer assessment and supports ONCE as a valuable tool for multi‐analytes liquid biopsies’ clinical implementation.

Extracellular vesicles (EVs), including exosomes, have significant potential for diagnostic and therapeutic applications. The lack of standardized methods for efficient and high-throughput isolation and analysis of EVs, however, has limited their widespread use in clinical practice. Surface epitope immunoaffinity (SEI) isolation utilizes affinity ligands, including antibodies, aptamers, or lectins, that target specific surface proteins present on EVs. Paramagnetic bead-SEI isolation represents a fit-for-purpose solution for the reproducible, high-throughput isolation of EVs from biofluids and downstream analysis of RNA, protein, and lipid biomarkers that is compatible with clinical laboratory workflows. This study evaluates a new SEI isolation method for enriching subpopulations of EVs. EVs were isolated from human plasma using a bead-based SEI method designed for on-bead and downstream analysis of EV-associated RNA and protein biomarkers. Western blot analysis confirmed the presence of EV markers in the captured nanoparticles. Mass spectrometry analysis of the SEI lysate identified over 1500 proteins, with the top 100 including known EV-associated proteins. microRNA (miRNA) sequencing followed by RT-qPCR analysis identified EV-associated miRNA transcripts. Using SEI, EVs were isolated using automated high-throughput particle moving instruments, demonstrating equal or higher protein and miRNA yield and recovery compared to manual processing. SEI is a rapid, efficient, and high-throughput method for isolating enriched populations of EVs; effectively reducing contamination and enabling the isolation of a specific subpopulation of EVs. In this study, high-throughput EV isolation and RNA extraction have been successfully implemented. This technology holds great promise for advancing the field of EV research and facilitating their application for biomarker discovery and clinical research.

Extracellular vesicles (EVs) are membrane-surrounded vesicles that carry heterogeneous cellular components, including proteins, nucleic acids, lipids, and metabolites. EVs’ intravesicular and surface contents possess many biomarkers of physiological and pathological importance. Because of the heterogeneous cargo, EVs can mediate local and distal cell–cell communication. However, the way in which the genome signature regulates EV cargo has not been well studied. This study aimed to understand how genetics impact EV cargo loading. EVs were isolated from vector copy number cells with a fluorescent reporter (GFP) with varying inserted transgene copies and from NIST SRM 2373 cells (MDA-MB-231, MDA-MB-453, SK-BR-3, and BT-474), which contain varying copies of the HER2 gene. Spectradyne nCS1 was utilized to count EVs and measure size distribution. Imaging Flow Cytometry was used to analyze the surface protein content of single EVs and for total EV counts. The RNA content of the EVs was measured using ddPCR. Our results from stable reporter cell lines and breast cancer cell lines suggest that the gene copy number dictates the protein cargo of the EVs but not the RNA content. Increasing copies of a reporter gene (GFP) or a naturally occurring gene (HER2) from breast cancer cells correlated with increasing EV counts positive for the protein cargo compared to total EV counts until a copy threshold was reached. This study has broad implications for understanding EV biology in the context of cancer biology, diagnostics, EV biology/manufacturing, and therapeutic delivery.

Background Extracellular vesicles (EVs) are actively secreted by cells into body fluids and contain nucleic acids of the cells they originate from. The goal of this study was to detect circulating tumor-derived EVs (ctEVs) by mutant mRNA transcripts (EV-RNA) in plasma of patients with solid cancers and compare the occurrence of ctEVs with circulating tumor DNA (ctDNA) in cell-free DNA (cfDNA). Methods For this purpose, blood from 20 patients and 15 healthy blood donors (HBDs) was collected in different preservation tubes (EDTA, BCT, CellSave) and processed into plasma within 24 h from venipuncture. EVs were isolated with the ExoEasy protocol from this plasma and from conditioned medium of 6 cancer cell lines and characterized according to MISEV2018-guidelines. RNA from EVs was isolated with the ExoRNeasy protocol and evaluated for transcript expression levels of 96 genes by RT-qPCR and genotyped by digital PCR. Results Our workflow applied on cell lines revealed a high concordance between cellular mRNA and EV-RNA in expression levels as well as variant allele frequencies for PIK3CA , KRAS and BRAF . Plasma CD9-positive EV and GAPDH EV-RNA levels were significantly different between the preservation tubes. The workflow detected only ctEVs with mutant transcripts in plasma of patients with high amounts (> 20%) of circulating tumor DNA (ctDNA). Expression profiling showed that the EVs from patients resemble healthy donors more than tumor cell lines supporting that most EVs are derived from healthy tissue. Conclusions We provide a workflow for ctEV detection by spin column-based generic isolation of EVs and PCR-based measurement of gene expression and mutant transcripts in EV-RNA derived from cancer patients’ blood plasma. This workflow, however, detected tumor-specific mutations in blood less often in EV-RNA than in cfDNA.

Extracellular vesicles (EVs) are lipid bilayer nanoparticles released from all known cells and are involved in cell-to-cell communication via their molecular content. EVs have been found in all tissues and body fluids, carrying a variety of biomolecules, including DNA, RNA, proteins, metabolites, and lipids, offering insights into cellular and pathophysiological conditions. Despite the emergence of EVs and their molecular contents as important biological indicators, it remains difficult to explore EV-mediated biological processes due to their small size and heterogeneity and the technical challenges in characterizing their molecular content. EV-associated small RNAs, especially microRNAs, have been extensively studied. However, other less characterized RNAs, including protein-coding mRNAs, long noncoding RNAs, circular RNAs, and tRNAs, have also been found in EVs. Furthermore, the EV-associated proteins can be used to distinguish different types of EVs. The spectrum of EV-associated RNAs, as well as proteins, may be associated with different pathophysiological conditions. Therefore, the ability to comprehensively characterize EVs’ molecular content is critical for understanding their biological function and potential applications in disease diagnosis. Here, we set out to provide an overview of EV-associated RNAs and proteins as well as approaches currently being used to characterize them.

The benefits of regular physical exercise on cancer prevention, as well as reducing fatigue, treatment side effects and recurrence, and improving quality of life and overall survival of cancer patients, are increasingly recognised. Initial studies showed that the concentration of extracellular vesicles (EVs) increases during physical activity and that EVs carry biologically active cargo. These EVs are released by blood cells, skeletal muscle and other organs involved in exercise, thus suggesting that EVs may mediate tissue crosstalk during exercise. This possibility triggered a great interest in the study of the roles of EVs in systemic adaptation to exercise and in their potential applications in the prevention and treatment of various diseases, including cancer. This review presents studies exploring the concentration and molecular cargo of EVs released during exercise. Furthermore, we discuss putative stimuli that may trigger EV release from various cell types, the biological functions and the impact of exercise‐induced EVs on cancer development and progression. Understanding the interplay between exercise, EVs, and cancer biology may offer insights into novel therapeutic strategies and preventive measures for cancer.

EVs are isolated from plasma collected from NSCLC patients harboring known EGFR mutations using ultracentrifugation. RNA and protein are extracted from the EV samples and tested for EGFR mutations using ddPCR and western blot, respectively. In non-small cell lung cancer (NSCLC), identifying the presence of sensitizing and resistance epidermal growth factor receptor (EGFR) mutations dictates treatment plans. Extracellular vesicles (EVs) are emerging as abundant, stable potential liquid biopsy targets that offer the potential to quantify EGFR mutations in NSCLC patients at the RNA and protein level at multiple points through treatment. In this study, we present a systematic approach for serial mutation profiling of 34 EV samples from 10 metastatic NSCLC patients with known EGFR mutations through treatment. Using western blot and droplet digital PCR (ddPCR), sensitizing (exon 19 deletion, L858R) mutations were detected in EV-Protein, and both sensitizing and resistance (T790M) mutations were quantified in EV-RNA. EGFR mutations were detected in EV-Protein from four patients at multiple time points through treatment. Using EV-RNA, tumor biopsy matched sensitizing mutations were detected in 90% of patients and resistance mutations in 100% of patients. Finally, mutation burden in EV-RNA at each time point was compared to disease status, described as either stable or progressing. For 6/7 patients who were longitudinally monitored through treatment, EV mutation burden mirrored clinical trajectory. When comparing mutation detection between EV-RNA and ctDNA using ddPCR, EVs had a better detection rate for exon 19 deletions and the L858R point mutation. In conclusion, this study demonstrates that integrating EV analysis into liquid biopsy mutation screening has the potential to advance beyond the current standard of care “rule in” test. The multi-analyte testing allows future integration of EGFR mutation monitoring with additional EV-markers for a comprehensive patient monitoring biomarker.