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Extracellular vesicles (EVs) have been proposed to play dual roles in cellular homeostasis, functioning both to remove unwanted intracellular molecules, and to enable communication between cells as a means of modulating cellular responses in different physiological and pathological scenarios. EVs contain a broad range of cargoes, including multiple biotypes of RNA, which can vary depending on the cell status, and may function as signalling molecules. In this study, we carried out comparative transcriptomic analysis of Drosophila EVs and cells, demonstrating that the RNAprofile of EVs is distinct from cells and shows dose-dependent changes in response to oxidative stress. We identified a high abundance of snoRNAs in EVs, alongside an enrichment of intronic and untranslated regions (UTRs) of mRNAs under stress. We also observed an increase in the relative abundance of either aberrant or modified mRNAs under stress. These findings suggest that EVsmay function both for the elimination of specific cellular RNAs, and for the incorporation of RNAs that may hold signalling potential. [ABSTRACT FROM AUTHOR]

Abstract Extracellular vesicles (EVs) have been proposed to play dual roles in cellular homeostasis, functioning both to remove unwanted intracellular molecules, and to enable communication between cells as a means of modulating cellular responses in different physiological and pathological scenarios. EVs contain a broad range of cargoes, including multiple biotypes of RNA, which can vary depending on the cell status, and may function as signalling molecules. In this study, we carried out comparative transcriptomic analysis of Drosophila EVs and cells, demonstrating that the RNA profile of EVs is distinct from cells and shows dose‐dependent changes in response to oxidative stress. We identified a high abundance of snoRNAs in EVs, alongside an enrichment of intronic and untranslated regions (UTRs) of mRNAs under stress. We also observed an increase in the relative abundance of either aberrant or modified mRNAs under stress. These findings suggest that EVs may function both for the elimination of specific cellular RNAs, and for the incorporation of RNAs that may hold signalling potential.

Gastric cancer (GC) has the fifth highest incidence among cancers and is the fourth leading cause of cancer-related death GC has predominantly a higher number of cases in certain ethnic groups such as the Korean population. GC found at an early stage is more treatable and has a higher survival rate as compared with GC found at a late stage. However, a diagnosis of GC is often delayed due to the lack of early symptoms and available screening programs in United States. Extracellular RNA (exRNA) is an emerging paradigm; exRNAs have the potential to serve as biomarkers in panels aimed at early detection of cancer. We previously reported the successful use of a panel of salivary exRNA for detecting GC in a high-prevalence Korean cohort, and that genetic changes reflected cancer-associated salivary exRNA changes. The current study is a case-control study of salivary exRNA biomarkers for detecting GC in an ethnically distinct U.S. cohort. A model constructed for the U.S. cohort combined demographic characteristics and salivary miRNA and mRNA biomarkers for GC and yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.78. However, the constituents of this model differed from that constructed for the Korean cohort, thus, emphasizing the importance of population-specific biomarker development and validation.

The RNA contained in exosomes plays a crucial role in information transfer between cells in various life activities. The accurate detection of low-abundance exosome RNA (exRNA) is of great significance for cell function studies and the early diagnosis of diseases. However, their intrinsic properties, such as their short length and high sequence homology, represent great challenges for exRNA detection. In this paper, we developed a dual-signal isothermal amplification method based on rolling circle amplification (RCA) coupled with DNAzyme (RCA–DNAzyme). The sensitive detection of low-abundance exRNA, the specific recognition of their targets and the amplification of the detection signal were studied and explored. By designing padlock probes to specifically bind to the target exRNA, while relying on the ligation reaction to enhance recognition, the precise targeting of exosome RNA was realized. The combination of RCA and DNAzyme could achieve a twice-as-large isothermal amplification of the signal compared to RCA alone. This RCA–DNAzyme assay could sensitively detect a target exRNA at a concentration as low as 527 fM and could effectively distinguish the target from other miRNA sequences. In addition, this technology was successfully proven to be effective for the quantitative detection of miR-21 by spike recovery, providing a new research approach for the accurate detection of low-abundance exRNA and the exploration of unknown exRNA functions. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is characterized by aberrant vascularization and a complex tumor microenvironment. The failure of anti-angiogenic therapies suggests pathways of GBM neovascularization, possibly attributable to glioblastoma stem cells (GSCs) and their interplay with the tumor microenvironment. It has been established that GSC-derived extracellular vesicles (GSC-EVs) and their cargoes are proangiogenic in vitro. To further elucidate EV-mediated mechanisms of neovascularization in vitro, we perform RNA-seq and DNA methylation profiling of human brain endothelial cells exposed to GSC-EVs. To correlate these results to tumors in vivo, we perform histoepigenetic analysis of GBM molecular profiles in the TCGA collection. Remarkably, GSC-EVs and normal vascular growth factors stimulate highly distinct gene regulatory responses that converge on angiogenesis. The response to GSC-EVs shows a footprint of post-transcriptional gene silencing by EV-derived miRNAs. Our results provide insights into targetable angiogenesis pathways in GBM and miRNA candidates for liquid biopsy biomarkers.

Data from omics studies have been used for prediction and classification of various diseases in biomedical and bioinformatics research. In recent years, Machine Learning (ML) algorithms have been used in many different fields related to healthcare systems, especially for disease prediction and classification tasks. Integration of molecular omics data with ML algorithms has offered a great opportunity to evaluate clinical data. RNA sequence (RNA-seq) analysis has been emerged as the gold standard for transcriptomics analysis. Currently, it is being used widely in clinical research. In our present work, RNA-seq data of extracellular vesicles (EV) from healthy and colon cancer patients are analyzed. Our aim is to develop models for prediction and classification of colon cancer stages. Five different canonical ML and Deep Learning (DL) classifiers are used to predict colon cancer of an individual with processed RNA-seq data. The classes of data are formed on the basis of both colon cancer stages and cancer presence (healthy or cancer). The canonical ML classifiers, which are k-Nearest Neighbor (kNN), Logistic Model Tree (LMT), Random Tree (RT), Random Committee (RC), and Random Forest (RF), are tested with both forms of the data. In addition, to compare the performance with canonical ML models, One-Dimensional Convolutional Neural Network (1-D CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM) DL models are utilized. Hyper-parameter optimizations of DL models are constructed by using genetic meta-heuristic optimization algorithm (GA). The best accuracy in cancer prediction is obtained with RC, LMT, and RF canonical ML algorithms as 97.33%. However, RT and kNN show 95.33% performance. The best accuracy in cancer stage classification is achieved with RF as 97.33%. This result is followed by LMT, RC, kNN, and RT with 96.33%, 96%, 94.66%, and 94%, respectively. According to the results of the experiments with DL algorithms, the best accuracy in cancer prediction is obtained with 1-D CNN as 97.67%. BiLSTM and LSTM show 94.33% and 93.67% performance, respectively. In classification of the cancer stages, the best accuracy is achieved with BiLSTM as 98%. 1-D CNN and LSTM show 97% and 94.33% performance, respectively. The results reveal that both canonical ML and DL models may outperform each other for different numbers of features. [ABSTRACT FROM AUTHOR]

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Extracellular RNA (exRNA) is a special form of RNA in the body. RNA carries information about genes and metabolic regulation in the body, which can reflect the real-time status of cells. This characteristic renders it a biomarker for disease diagnosis, treatment, and prognosis. ExRNA is transported through extracellular vesicles as a signal medium to mediate communication between cells. Tumor cells can release more vesicles than normal cells, thereby promoting tumor development. Depending on its easy detection, the advantages of non-invasive molecular diagnostic technology can be realized. In this systematic review, we present the types, vectors, and biological value of exRNA. We briefly describe new methods of tumor diagnosis and treatment, as well as the difficulties faced in the progress of such research. This review highlights the groundbreaking potential of exRNA as a clinical biomarker. [ABSTRACT FROM AUTHOR]

The RNA contained in exosomes plays a crucial role in information transfer between cells in various life activities. The accurate detection of low-abundance exosome RNA (exRNA) is of great significance for cell function studies and the early diagnosis of diseases. However, their intrinsic properties, such as their short length and high sequence homology, represent great challenges for exRNA detection. In this paper, we developed a dual-signal isothermal amplification method based on rolling circle amplification (RCA) coupled with DNAzyme (RCA–DNAzyme). The sensitive detection of low-abundance exRNA, the specific recognition of their targets and the amplification of the detection signal were studied and explored. By designing padlock probes to specifically bind to the target exRNA, while relying on the ligation reaction to enhance recognition, the precise targeting of exosome RNA was realized. The combination of RCA and DNAzyme could achieve a twice-as-large isothermal amplification of the signal compared to RCA alone. This RCA–DNAzyme assay could sensitively detect a target exRNA at a concentration as low as 527 fM and could effectively distinguish the target from other miRNA sequences. In addition, this technology was successfully proven to be effective for the quantitative detection of miR-21 by spike recovery, providing a new research approach for the accurate detection of low-abundance exRNA and the exploration of unknown exRNA functions.

AimThis study tests the hypothesis that salivary extracellular RNA (exRNA) biomarkers can be developed for gingivitis detection and monitoring disease regression.Materials and methodsSalivary exRNA biomarker candidates were developed from a total of 100 gingivitis and non-gingivitis individuals using Affymetrix's expression microarrays. The top 10 differentially expressed exRNAs were tested in a clinical cohort to determine whether the discovered salivary exRNA markers for gingivitis were associated with clinical gingivitis and disease regression. For this purpose, unstimulated saliva was collected from 30 randomly selected gingivitis subjects, the gingival and plaque indexes scores were taken at baseline, 3 and 6 weeks and salivary exRNAs were assayed by means of reverse transcription quantitative polymerase chain reaction.ResultsEight salivary exRNA biomarkers developed for gingivitis were statistically significantly changed over time, consistent with disease regression. A panel of four salivary exRNAs [SPRR1A, lnc-TET3-2:1, FAM25A, CRCT1] can detect gingivitis with a clinical performance of 0.91 area under the curve, with 71% sensitivity and 100% specificity.ConclusionsThe clinical values of the developed salivary exRNA biomarkers are associated with gingivitis regression. They offer strong potential to be advanced for definitive validation and clinical laboratory development test.

Extracellular vesicles (EVs) are lipid bilayer-enclosed structures that represent newly discovered means for cell-to-cell communication as well as promising disease biomarkers and therapeutic tools. Apart from proteins, lipids, and metabolites, EVs can deliver genetic information such as mRNA, eliciting a response in the recipient cells. In the present study, we have analyzed the mRNA content of brain-derived EVs (BDEVs) isolated 72 h after experimental stroke in mice and compared them to controls (shams) using nCounter® Nanostring panels, with or without prior RNA isolation. We found that both panels show similar results when comparing upregulated mRNAs in stroke. Notably, the highest upregulated mRNAs were related to processes of stress and immune system responses, but also to anatomical structure development, cell differentiation, and extracellular matrix organization, thus indicating that regenerative mechanisms already take place at this time-point. The five top overrepresented mRNAs in stroke mice were confirmed by RT-qPCR and, interestingly, found to be full-length. We could reveal that the majority of the mRNA cargo in BDEVs was of microglial origin and predominantly present in small BDEVs (≤ 200 nm in diameter). However, the EV population with the highest increase in the total BDEVs pool at 72 h after stroke was of oligodendrocytic origin. Our study shows that nCounter® panels are a good tool to study mRNA content in tissue-derived EVs as they can be carried out even without previous mRNA isolation, and that the mRNA cargo of BDEVs indicates a possible participation in inflammatory but also recovery processes after stroke. [ABSTRACT FROM AUTHOR]

The aim of this systemic review was to collate and analyze existing data from published literature sources to identify the current understanding of the role of epigenetic and biological biomarkers in periodontal disease and diagnostics. A comprehensive searching strategy was undertaken in Embase, Medline, The Dentistry and Oral Sciences and CINAHL databases. Grey literature searching strategies were also employed. Articles published in the English language between 2017–2020 were included. A total of 1014 studies were returned of which 15 studies were included. All included articles were cross-sectional, case–control studies. Relevant data were extracted according to various demographic and methodological factors including cohort size, oral biofluid sampled, number of examiners, smoking status and reported outcomes. A measure of the biomarker levels and corresponding significance were documented where possible. This review identified that exRNA has the greatest diagnostic potential, with four biomarkers (SPRR1A, lnc-TET3-2:1, FAM25A, CRCT1) displaying sensitivity of >71% and specificity of 100% in the assessed samples (p < 0.001) for gingivitis. This work also identifies the need for a unified approach to future research to draw meaningful comparison. Further investigations are warranted to definitively validate exRNA data and for the development of an exRNA-specific point-of-care diagnostic test. [ABSTRACT FROM AUTHOR]

Growing bodies of evidence have demonstrated that the identification of prostate cancer (PCa) biomarkers in the patients' blood and urine may remarkably improve PCa diagnosis and progression monitoring. Among diverse cancer-derived circulating materials, extracellular RNA molecules (exRNAs) represent a compelling component to investigate cancer-related alterations. Once outside the intracellular environment, exRNAs circulate in biofluids either in association with protein complexes or encapsulated inside extracellular vesicles (EVs). Notably, EV-associated RNAs (EV-RNAs) were used for the development of several assays (such as the FDA-approved Progensa Prostate Cancer Antigen 3 (PCA3 test) aiming at improving early PCa detection. EV-RNAs encompass a mixture of species, including small non-coding RNAs (e.g. miRNA and circRNA), lncRNAs and mRNAs. Several methods have been proposed to isolate EVs and relevant RNAs, and to perform RNA-Seq studies to identify potential cancer biomarkers. However, EVs in the circulation of a cancer patient include a multitude of diverse populations that are released by both cancer and normal cells from different tissues, thereby leading to a heterogeneous EV-RNA-associated transcriptional signal. Decrypting the complexity of such a composite signal is nowadays the major challenge faced in the identification of specific tumor-associated RNAs. Multiple deconvolution algorithms have been proposed so far to infer the enrichment of cancer-specific signals from gene expression data. However, novel strategies for EVs sorting and sequencing of RNA associated to single EVs populations will remarkably facilitate the identification of cancer-related molecules. Altogether, the studies summarized here demonstrate the high potential of using EV-RNA biomarkers in PCa and highlight the urgent need of improving technologies and computational approaches to characterize specific EVs populations and their relevant RNA cargo. [ABSTRACT FROM AUTHOR]

One of the hallmarks of the immune system is a dynamic landscape of cellular communication through the secretion of soluble factors, production of cell‐bound ligands, and expression of surface receptors. This communication affects all aspects of immune cell behavior, integrates the responses of immune cells in tissues, and is fundamental to orchestrating effective immunity. Recent pioneering work has shown that the transfer of ribonucleic acids (RNAs) constitutes a novel mode of cellular communication. This communication involves diverse RNA species, with short noncoding RNAs especially enriched in the extracellular space. These RNAs are highly stable and selectively packaged for secretion. Transferred RNAs have functions in target cells that both mirror their cell‐intrinsic roles and adopt novel mechanisms of action. These extracellular RNAs both impact the behavior of individual immune cells and participate in local and systemic immune responses. The impacts of RNA communication on immune cells and disease states have important implications for the development of novel clinical biomarkers and innovative therapeutic designs in immune‐related disease. In this review, we will discuss the foundation of knowledge that is establishing RNA communication as an active and functional process in the immune system. [ABSTRACT FROM AUTHOR]

Ten ongoing studies designed to test the possibility that extracellular RNAs may serve as biomarkers in human disease are described. These studies, funded by the NIH Common Fund Extracellular RNA Communication Program, examine diverse extracellular body fluids, including plasma, serum, urine and cerebrospinal fluid. The disorders studied include hepatic and gastric cancer, cardiovascular disease, chronic kidney disease, neurodegenerative disease, brain tumours, intracranial haemorrhage, multiple sclerosis and placental disorders. Progress to date and the plans for future studies are outlined.

The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

Gastric cancer (GC) has the fifth highest incidence among cancers and is the fourth leading cause of cancer-related death GC has predominantly a higher number of cases in certain ethnic groups such as the Korean population. GC found at an early stage is more treatable and has a higher survival rate as compared with GC found at a late stage. However, a diagnosis of GC is often delayed due to the lack of early symptoms and available screening programs in United States. Extracellular RNA (exRNA) is an emerging paradigm; exRNAs have the potential to serve as biomarkers in panels aimed at early detection of cancer. We previously reported the successful use of a panel of salivary exRNA for detecting GC in a high-prevalence Korean cohort, and that genetic changes reflected cancer-associated salivary exRNA changes. The current study is a case-control study of salivary exRNA biomarkers for detecting GC in an ethnically distinct U.S. cohort. A model constructed for the U.S. cohort combined demographic characteristics and salivary miRNA and mRNA biomarkers for GC and yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.78. However, the constituents of this model differed from that constructed for the Korean cohort, thus, emphasizing the importance of population-specific biomarker development and validation.

Circulating extracellular RNAs (exRNAs) have great potential to serve as biomarkers for a wide range of diagnostic, therapeutic, and prognostic applications. So far, knowledge of the difference among different sources of exRNAs is limited. To address this issue, we performed a sequential physical and biochemical precipitation to collect four fractions (platelets and cell debris, the thrombin-induced precipitates, extracellular vesicles, and supernatant) from each of 10 plasma samples. From total RNAs of the 40 fractions, we prepared ligation-free libraries to profile full spectrum of all RNA species, without size selection and rRNA reduction. Due to complicated RNA composition in these libraries, we utilized a successive stepwise alignment strategy to map the RNA sequences to different RNA categories, including miRNAs, piwi-interacting RNAs, tRNAs, rRNAs, lincRNAs, snoRNAs, snRNAs, other ncRNAs, protein coding RNAs, and circRNAs. Our data showed that each plasma fraction had its own unique distribution of RNA species. Hierarchical cluster analyses using transcript abundance demonstrated similarities in the same plasma fraction and significant differences between different fractions. In addition, we observed various unique transcripts, and novel predicted miRNAs among these plasma fractions. These results demonstrate that the distribution of RNA species and functional RNA transcripts is plasma fraction-dependent. Appropriate plasma preparation and thorough inspection of different plasma fractions are necessary for an exRNA-based biomarker study.

Circulating extracellular RNAs (exRNAs) have great potential to serve as biomarkers for a wide range of diagnostic, therapeutic, and prognostic applications. So far, knowledge of the difference among different sources of exRNAs is limited. To address this issue, we performed a sequential physical and biochemical precipitation to collect four fractions (platelets and cell debris, the thrombin-induced precipitates, extracellular vesicles, and supernatant) from each of 10 plasma samples. From total RNAs of the 40 fractions, we prepared ligation-free libraries to profile full spectrum of all RNA species, without size selection and rRNA reduction. Due to complicated RNA composition in these libraries, we utilized a successive stepwise alignment strategy to map the RNA sequences to different RNA categories, including miRNAs, piwi-interacting RNAs, tRNAs, rRNAs, lincRNAs, snoRNAs, snRNAs, other ncRNAs, protein coding RNAs, and circRNAs. Our data showed that each plasma fraction had its own unique distribution of RNA species. Hierarchical cluster analyses using transcript abundance demonstrated similarities in the same plasma fraction and significant differences between different fractions. In addition, we observed various unique transcripts, and novel predicted miRNAs among these plasma fractions. These results demonstrate that the distribution of RNA species and functional RNA transcripts is plasma fraction-dependent. Appropriate plasma preparation and thorough inspection of different plasma fractions are necessary for an exRNA-based biomarker study. [ABSTRACT FROM AUTHOR]

Circulating factors are well known to influence aging and age-related disease. As part of the Aging Science Talks: Science for the Community series, data was presented on two types of circulating functional biomarkers: extracellular RNA (exRNA) and extracellular vesicles (EVs). EVs in the context of type 2 diabetes mellitus was also discussed, as this is an area of interest due to the growing global epidemic of this age-related disease.

The aim of this systemic review was to collate and analyze existing data from published literature sources to identify the current understanding of the role of epigenetic and biological biomarkers in periodontal disease and diagnostics. A comprehensive searching strategy was undertaken in Embase, Medline, The Dentistry and Oral Sciences and CINAHL databases. Grey literature searching strategies were also employed. Articles published in the English language between 2017–2020 were included. A total of 1014 studies were returned of which 15 studies were included. All included articles were cross-sectional, case–control studies. Relevant data were extracted according to various demographic and methodological factors including cohort size, oral biofluid sampled, number of examiners, smoking status and reported outcomes. A measure of the biomarker levels and corresponding significance were documented where possible. This review identified that exRNA has the greatest diagnostic potential, with four biomarkers (SPRR1A, lnc-TET3-2:1, FAM25A, CRCT1) displaying sensitivity of >71% and specificity of 100% in the assessed samples (p < 0.001) for gingivitis. This work also identifies the need for a unified approach to future research to draw meaningful comparison. Further investigations are warranted to definitively validate exRNA data and for the development of an exRNA-specific point-of-care diagnostic test.

Extracellular vesicles (EVs) are important for intercellular communication and act as vehicles for biological material, such as various classes of coding and non-coding RNAs, a few of which were shown to selectively target into vesicles. However, protein factors, mechanisms, and sequence elements contributing to this specificity remain largely elusive. Here, we use a reporter system that results in different types of modified transcripts to decipher the specificity determinants of RNAs released into EVs. First, we found that small RNAs are more efficiently packaged into EVs than large ones, and second, we determined absolute quantities for several endogenous RNA transcripts in EVs (U6 snRNA, U1 snRNA, Y1 RNA, and GAPDH mRNA). We show that RNA polymerase III (pol III) transcripts are more efficiently secreted into EVs compared to pol II-derived transcripts. Surprisingly, our quantitative analysis revealed no RNA accumulation in the vesicles relative to the total cellular levels, based on both overexpressed reporter transcripts and endogenous RNAs. RNA appears to be EV-associated only at low copy numbers, ranging between 0.02 and 1 molecule per EV. This RNA association may reflect internal EV encapsulation or a less tightly bound state at the vesicle surface.

Cancer stem cells (CSCs) are considered as responsible for initiation, maintenance and recurrence of solid tumors, thus representing the key for tumor eradication. The antitumor activity of extracellular vesicles (EVs) derived from different stem cell sources has been investigated with conflicting results. In our study, we evaluated, both in vitro and in vivo, the effect of EVs derived from human bone marrow mesenchymal stromal cells (MSCs) and from a population of human liver stem cells (HLSCs) of mesenchymal origin on renal CSCs. In vitro, both EV sources displayed pro‐apoptotic, anti‐proliferative and anti‐invasive effects on renal CSCs, but not on differentiated tumor cells. Pre‐treatment of renal CSCs with EVs, before subcutaneous injection in SCID mice, delayed tumor onset. We subsequently investigated the in vivo effect of MSC‐ and HLSC‐EVs systemic administration on progression of CSC‐generated renal tumors. Tumor bio‐distribution analysis identified intravenous treatment as best route of administration. HLSC‐EVs, but not MSC‐EVs, significantly impaired subcutaneous tumor growth by reducing tumor vascularization and inducing tumor cell apoptosis. Moreover, intravenous treatment with HLSC‐EVs improved metastasis‐free survival. In EV treated tumor explants, we observed both the transfer and the induction of miR‐145 and of miR‐200 family members. In transfected CSCs, the same miRNAs affected cell growth, invasion and survival. In conclusion, our results showed a specific antitumor effect of HLSC‐EVs on CSC‐derived renal tumors in vivo, possibly ascribed to the transfer and induction of specific antitumor miRNAs. Our study provides further evidence for a possible clinical application of stem cell‐EVs in tumor treatment. What's new? Stem cell‐derived extracellular vesicles (EVs) can reprogram target cells and promote tissue repair by transferring their cargo. However, the anti‐tumor activity of EVs derived from different stem cell sources has been investigated with conflicting results. Here, the authors demonstrate for the first time the anti‐tumor effect of EVs from human liver stem cells (HLSC‐EVs) in a systemic intravenous administration model. HLSC‐EVs had a selective effect on cancer stem cells that could be ascribed to the transfer and induction of anti‐tumor miRNAs. This study highlights the potential clinical use of stem cell‐derived EVs, alone or in combination with other cancer therapies. [ABSTRACT FROM AUTHOR]

Ten ongoing studies designed to test the possibility that extracellular RNAs may serve as biomarkers in human disease are described. These studies, funded by the NIH Common Fund Extracellular RNA Communication Program, examine diverse extracellular body fluids, including plasma, serum, urine and cerebrospinal fluid. The disorders studied include hepatic and gastric cancer, cardiovascular disease, chronic kidney disease, neurodegenerative disease, brain tumours, intracranial haemorrhage, multiple sclerosis and placental disorders. Progress to date and the plans for future studies are outlined.

The Extracellular RNA (exRNA) Communication Consortium was launched by the National Institutes of Health to focus on the extent to which RNA might function in a non-cell-autonomous manner. With the availability of increasingly sensitive tools, small amounts of RNA can be detected in serum, plasma, and other bodily fluids. The exact mechanism(s) by which RNA can be secreted from cells and the mechanisms for the delivery and uptake by recipient cells remain to be determined. This review will summarize current knowledge about the biogenesis and delivery of exRNA and outline projects seeking to understand the functional impact of exRNA.

The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

The Extracellular RNA (exRNA) Communication Consortium, funded as an initiative of the NIH Common Fund, represents a consortium of investigators assembled to address the critical issues in the exRNA research arena. The overarching goal is to generate a multi-component community resource for sharing fundamental scientific discoveries, protocols, and innovative tools and technologies. The key initiatives include (a) generating a reference catalogue of exRNAs present in body fluids of normal healthy individuals that would facilitate disease diagnosis and therapies, (b) defining the fundamental principles of exRNA biogenesis, distribution, uptake, and function, as well as development of molecular tools, technologies, and imaging modalities to enable these studies, (c) identifying exRNA biomarkers of disease, (d) demonstrating clinical utility of exRNAs as therapeutic agents and developing scalable technologies required for these studies, and (e) developing a community resource, the exRNA Atlas, to provide the scientific community access to exRNA data, standardized exRNA protocols, and other useful tools and technologies generated by funded investigators.

In the central nervous system (CNS), the crosstalk between neural cells is mediated by extracellular mechanisms, including brain-derived extracellular vesicles (bdEVs). To study endogenous communication across the brain and periphery, we explored Cre-mediated DNA recombination to permanently record the functional uptake of bdEVs cargo over time. To elucidate functional cargo transfer within the brain at physiological levels, we promoted the continuous secretion of physiological levels of neural bdEVs containing Cre mRNA from a localized region in the brain by in situ lentiviral transduction of the striatum of Flox-tdTomato Ai9 mice reporter of Cre activity. Our approach efficiently detected in vivo transfer of functional events mediated by physiological levels of endogenous bdEVs throughout the brain. Remarkably, a spatial gradient of persistent tdTomato expression was observed along the whole brain, exhibiting an increment of more than 10-fold over 4 months. Moreover, bdEVs containing Cre mRNA were detected in the bloodstream and extracted from brain tissue to further confirm their functional delivery of Cre mRNA in a novel and highly sensitive Nanoluc reporter system. Overall, we report a sensitive method to track bdEV transfer at physiological levels, which will shed light on the role of bdEVs in neural communication within the brain and beyond., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

Summary: Circulating extracellular RNAs (exRNAs) are potential biomarkers of disease. We thus hypothesized that age‐related changes in exRNAs can identify age‐related processes. We profiled both large and small RNAs in human serum to investigate changes associated with normal aging. exRNA was sequenced in 13 young (30–32 years) and 10 old (80–85 years) African American women to identify all RNA transcripts present in serum. We identified age‐related differences in several RNA biotypes, including mitochondrial transfer RNAs, mitochondrial ribosomal RNA, and unprocessed pseudogenes. Age‐related differences in unique RNA transcripts were further validated in an expanded cohort. Pathway analysis revealed that EIF2 signaling, oxidative phosphorylation, and mitochondrial dysfunction were among the top pathways shared between young and old. Protein interaction networks revealed distinct clusters of functionally‐related protein‐coding genes in both age groups. These data provide timely and relevant insight into the exRNA repertoire in serum and its change with aging. [ABSTRACT FROM AUTHOR]

Background Cell-free DNA (cfDNA) and extracellular RNA (exRNA) are both suspected to activate coagulation cascades in sepsis. Therefore, our study investigated the influence of plasmatic nucleic acids on coagulation in septic patients in comparison to patients after major abdominal surgery. Materials and methods A total of 15 patients with sepsis, 10 postoperative patients, and 10 healthy volunteers were included in this longitudinal study. Blood was collected at sepsis onset and after surgery respectively, as well as after 24, 72 and 168 h. Levels of cfDNA and exRNA were measured by quantitative probe-based polymerase chain reaction. In addition, thromboelastography for coagulation as well as thromboaggregometry for platelet function was conducted. Results Both cfDNA and exRNA were elevated in patients with sepsis compared with postoperative patients and healthy volunteers. While higher exRNA levels correlated with a faster clotting time and more stable clots, cfDNA correlated with a shorter clotting time but also less fibrinolysis. In addition, higher cfDNA seems to be associated with kidney dysfunction as well as with general markers of cell damage (lactate dehydrogenase and lactate). Conclusions Both nucleic acid species might be associated with different effects on coagulation during sepsis, with an overall procoagulatory influence. For this reason, individualized therapeutic approaches in patients suffering from coagulation-associated organ dysfunction might be feasible. [ABSTRACT FROM AUTHOR]

Treatment with ribonuclease (RNase) reportedly protects the heart after myocardial ischemia–reperfusion (I/R), but its potential effect on lung I/R injury (LIRI) is unknown. Thus, we aim to explore whether RNase treatment would relieve LIRI. Thirty-six C57BL/6J adult male wild-type mice were evenly divided into I/R + RNase (I/R + R) group, I/R group, and sham group. Lung I/R was induced by left pulmonary hilum occlusion for 1 h and reperfusion for 2 h. All mice were treated with RNase or same dosage of normal saline in advance. After I/R, blood and lung tissues were collected for analysis. The results showed that lung injury scores, wet/dry ratio, expressions of inflammatory cytokines, pulmonary apoptosis, and levels of serum extracellular RNA (exRNA), including microRNAs, were markedly elevated after I/R. However, RNase treatment significantly attenuated cytokine production in both lung tissue and serum and also suppressed pulmonary apoptosis as reflected by TUNEL staining and activated caspase-3. In addition, total serum exRNA levels in the I/R + R group had a downward trend versus the I/R group. In conclusion, the increase of circulating exRNA levels contributed to LIRI in adult mice, which could be relieved by injection of RNase during perioperative window. The potential mechanism is the decrease of serum exRNA level and the suppression of pulmonary inflammation and apoptosis. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) are nanosized vesicles secreted from virtually all cell types and are thought to transport proteins, lipids and nucleic acids including non-coding RNAs (ncRNAs) between cells. Since, ncRNAs are central to transcriptional regulation during developmental processes; eukaryotes might have evolved novel means of post-transcriptional regulation by trans-locating ncRNAs between cells. EV-mediated transportation of regulatory elements provides a novel source of trans-regulation between cells. In the last decade, studies were mainly focused on microRNAs; however, functions of long ncRNA (lncRNA) have been much less studied. Here, we review the regulatory roles of EV-linked ncRNAs, placing a particular focus on lncRNAs, how they can foster dictated patterns of trans-regulation in recipient cells. This refers to envisaging novel mechanisms of epigenetic regulation, cellular reprogramming and genomic instability elicited in recipient cells, ultimately permitting the generation of cancer initiating cell phenotypes, senescence and resistance to chemotherapies. Conversely, such trans-regulation may introduce RNA interference in recipient cancer cells causing the suppression of oncogenes and anti-apoptotic proteins; thus favoring tumor inhibition. Collectively, understanding these mechanisms could be of great value to EV-based RNA therapeutics achieved through gene manipulation within cancer cells, whereas the ncRNA content of EVs from cancer patients could serve as non-invasive source of diagnostic biomarkers and prognostic indicators in response to therapies.

As an essential part of central dogma, RNA delivers genetic and regulatory information and reflects cellular states. Based on high‐throughput sequencing technologies, cumulating data show that various RNA molecules are able to serve as biomarkers for the diagnosis and prognosis of various diseases, for instance, cancer. In particular, detectable in various bio‐fluids, such as serum, saliva and urine, extracellular RNAs (exRNAs) are emerging as non‐invasive biomarkers for earlier cancer diagnosis, tumor progression monitor, and prediction of therapy response. In this review, we summarize the latest studies on various types of RNA biomarkers, especially extracellular RNAs, in cancer diagnosis and prognosis, and illustrate several well‐known RNA biomarkers of clinical utility. In addition, we describe and discuss general procedures and issues in investigating exRNA biomarkers, and perspectives on utility of exRNAs in precision medicine.

The Extracellular RNA (exRNA) Communication Consortium was launched by the National Institutes of Health to focus on the extent to which RNA might function in a non-cell-autonomous manner. With the availability of increasingly sensitive tools, small amounts of RNA can be detected in serum, plasma, and other bodily fluids. The exact mechanism(s) by which RNA can be secreted from cells and the mechanisms for the delivery and uptake by recipient cells remain to be determined. This review will summarize current knowledge about the biogenesis and delivery of exRNA and outline projects seeking to understand the functional impact of exRNA. [ABSTRACT FROM AUTHOR]

The Extracellular RNA (exRNA) Communication Consortium, funded as an initiative of the NIH Common Fund, represents a consortium of investigators assembled to address the critical issues in the exRNA research arena. The overarching goal is to generate a multi-component community resource for sharing fundamental scientific discoveries, protocols, and innovative tools and technologies. The key initiatives include (a) generating a reference catalogue of exRNAs present in body fluids of normal healthy individuals that would facilitate disease diagnosis and therapies, (b) defining the fundamental principles of exRNA biogenesis, distribution, uptake, and function, as well as development of molecular tools, technologies, and imaging modalities to enable these studies, (c) identifying exRNA biomarkers of disease, (d) demonstrating clinical utility of exRNAs as therapeutic agents and developing scalable technologies required for these studies, and (e) developing a community resource, the exRNA Atlas, to provide the scientific community access to exRNA data, standardized exRNA protocols, and other useful tools and technologies generated by funded investigators. [ABSTRACT FROM AUTHOR]

Extracellular RNA (exRNA) is a special form of RNA in the body. RNA carries information about genes and metabolic regulation in the body, which can reflect the real-time status of cells. This characteristic renders it a biomarker for disease diagnosis, treatment, and prognosis. ExRNA is transported through extracellular vesicles as a signal medium to mediate communication between cells. Tumor cells can release more vesicles than normal cells, thereby promoting tumor development. Depending on its easy detection, the advantages of non-invasive molecular diagnostic technology can be realized. In this systematic review, we present the types, vectors, and biological value of exRNA. We briefly describe new methods of tumor diagnosis and treatment, as well as the difficulties faced in the progress of such research. This review highlights the groundbreaking potential of exRNA as a clinical biomarker., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wu, Tao, Eshraghian, Lin, Li and Zhu.)

Extracellular vesicles (EVs) are important for intercellular communication and act as vehicles for biological material, such as various classes of coding and non-coding RNAs, a few of which were shown to selectively target into vesicles. However, protein factors, mechanisms, and sequence elements contributing to this specificity remain largely elusive. Here, we use a reporter system that results in different types of modified transcripts to decipher the specificity determinants of RNAs released into EVs. First, we found that small RNAs are more efficiently packaged into EVs than large ones, and second, we determined absolute quantities for several endogenous RNA transcripts in EVs (U6 snRNA, U1 snRNA, Y1 RNA, and GAPDH mRNA). We show that RNA polymerase III (pol III) transcripts are more efficiently secreted into EVs compared to pol II-derived transcripts. Surprisingly, our quantitative analysis revealed no RNA accumulation in the vesicles relative to the total cellular levels, based on both overexpressed reporter transcripts and endogenous RNAs. RNA appears to be EV-associated only at low copy numbers, ranging between 0.02 and 1 molecule per EV. This RNA association may reflect internal EV encapsulation or a less tightly bound state at the vesicle surface. [ABSTRACT FROM AUTHOR]