The study of extracellular vesicles (EVs), especially in the liquid biopsy field, has rapidly evolved in recent years. However, most EV studies have focused on RNA or protein content and DNA in EVs (EV-DNA) has largely been unnoticed. In this review, we compile current evidence regarding EV-DNA and provide an extensive discussion on EV-DNA biology. We look into EV-DNA biogenesis and mechanisms of DNA loading into EVs, as well as describe the particularly significant function of DNA-carrying EVs in the maintenance of cellular homeostasis, intracellular communication, and immune response modulation. We also examine the current role of EV-DNA in the clinical setting, specifically in cancer, infections, pregnancy, and prenatal diagnosis.
Extracellular Vesicles (EVs), membrane vesicles released by all cells, are emerging mediators of cell-cell communication. By carrying biomolecules from tissues to biofluids, EVs have attracted attention as non-invasive sources of clinical biomarkers in liquid biopsies. EVs-based liquid biopsies usually require EVs isolation before content analysis, which frequently increases sample volume requirements. We here present a Flow Cytometry (FC) strategy that does not require isolation or concentration of EVs prior to staining. By doing so, it enables population analysis of EVs in samples characterized by challenging small volumes, while reducing overall sample processing time. To illustrate its application, we performed longitudinal non-lethal population analysis of EVs in mouse plasma and in single-animal collections of murine vitreous humor. By quantifying the proportion of vesicular particles in purified and non-purified biological samples, this method also serves as a precious tool to quality control isolates of EVs purified by different protocols. Our FC strategy has an unexplored clinical potential to analyze EVs in biofluids with intrinsically limited volumes and to multiply the number of different analytes in EVs that can be studied from a single collection of biofluid.
The amplification of estrogen receptor alpha (ERα) encoded by the ESR1 gene has been described as having a prognostic role in breast cancer patients. However, increased dosage of the ESR1 gene (tested by real-time PCR) is also observed in ER-negative breast cancers, which might suggest the expression of alternative isoforms of ERα (other than classical ERα of 66 kDa). In the current work, we have investigated the ESR1 gene dosage in 402 primary breast cancer patients as well as the expression of ERα isoforms—ERα66 and ERα36—on mRNA and protein levels. The obtained results were correlated with clinicopathological data of the patients. Results showed that increased ESR1 gene dosage is not related to ESR1 gene amplification measured by fluorescent in situ hybridization (FISH), but it correlates with the decreased expression of ERα66 isoform (p = 0.01). Interestingly, the short ER isoform ERα36 was expressed in samples with increased ESR1 gene dosage, suggesting that genomic aberration might influence the expression of that particular isoform. Similarly to ESR1 increased gene dosage, high ERα36 expression was linked with the decreased disease-free survival of the patients (p = 0.05), which was independent of the status of the classical ERα66 level in breast tumors.
(1) Background: Extracellular vesicles (EVs) have emerged as crucial players in the communication between cells in both physiological and pathological scenarios. The functions of EVs are strongly determined by their molecular content, which includes all bioactive molecules, such as proteins, lipids, RNA, and, as more recently described, double-stranded DNA. It has been shown that in oncological settings DNA associated with EVs (EV-DNA) is representative of the genome of parental cells and that it reflects the mutational status of the tumor, gaining much attention as a promising source of biomarker mutant DNA. However, one of the challenges in studies of EV-DNA is the lack of standardization of protocols for the DNA extraction from EVs, as well as ways to assess quality control, which hinders its future implementation in clinics. (2) Methods: We performed a comprehensive comparison of commonly used approaches for EV-DNA extraction by assessing DNA quantity, quality, and suitability for downstream analyses. (3) Results: We here established strategic points to consider for EV-DNA preparation for mutational analyses, including qPCR and NGS. (4) Conclusions: We put in place a workflow that can be applied for the detection of clinically relevant mutations in the EV-DNA of cancer patients.
Extracellular Vesicles (EVs), membrane vesicles released by all cells, are emerging mediators of cell-cell communication. By carrying biomolecules from tissues to biofluids, EVs have attracted attention as non-invasive sources of clinical biomarkers in liquid biopsies. Although frequently employed for content characterization of EVs, the study of bulk preparations lacks information on sub-populations and the intrinsic heterogeneity of vesicles. Importantly, these strategies also difficult the characterization of EVs from small quantities of samples. We here present a Flow Cytometry strategy that enables detailed population analysis of EVs, at the same time decreasing sample volume requirements and accelerating the overall processing time. We show its unique application for quality control of isolates of EVs by comparing the proportion of vesicular and non-vesicular particles in samples prepared by different protocols. In addition, we demonstrate its suitability for the study of populations of EVs from samples characterized by challenging small volumes. To illustrate that, we perform longitudinal non-lethal analysis of EVs in mouse plasma and in single-animal collections of murine vitreous humor. By allowing for the analysis of EVs from minimal amounts of sample, our Flow Cytometry strategy has an unexplored potential in the study of EVs in clinical samples with intrinsically limited volumes. When compared to conventional methods, it also multiplies by several times the number of different analytes that can be studied from a single collection of biofluid.
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