Extracellular RNA Communication Consortium Research Articles

The EV antibody database: An interactive database of curated antibodies for extracellular vesicle and nanoparticle research

Antibodies are critical tools for research into extracellular vesicles (EVs) and other extracellular nanoparticles (ENPs), where they can be used for their identification, characterization, and isolation. However, the lack of a centralized antibody platform where researchers can share validation results thus minimizing wasted personnel time and reagents, has been a significant obstacle. Moreover, because the performance of antibodies varies among assay types and conditions, detailed information on assay variables and protocols is also of value. To facilitate sharing of results on antibodies that are relevant to EV/ENP research, the EV Antibody Database has been developed by the investigators of the Extracellular RNA Communication Consortium (ERCC). Hosted by the ExRNA Portal (https://exrna.org/resources/evabdb/), this interactive database aggregates and shares results from antibodies that have been tested by research groups in the EV/ENP field. Currently, the EV Antibody Database includes modules for antibodies tested for western Blot, EV Flow Cytometry, and EV Sandwich Assays, and holds 110 records contributed by 6 laboratories from the ERCC. Detailed information on antibody sources, assay conditions, and results is provided, including negative results. We encourage ongoing expert input and community feedback to enhance the database's utility, making it a valuable resource for comprehensive validation data on antibodies and protocols in EV biology.

Open Problems in Extracellular RNA Data Analysis: Insights From an ERCC Online Workshop.

We now know RNA can survive the harsh environment of biofluids when encapsulated in vesicles or by associating with lipoproteins or RNA binding proteins. These extracellular RNA (exRNA) play a role in intercellular signaling, serve as biomarkers of disease, and form the basis of new strategies for disease treatment. The Extracellular RNA Communication Consortium (ERCC) hosted a two-day online workshop (April 19–20, 2021) on the unique challenges of exRNA data analysis. The goal was to foster an open dialog about best practices and discuss open problems in the field, focusing initially on small exRNA sequencing data. Video recordings of workshop presentations and discussions are available (https://exRNA.org/exRNAdata2021-videos/). There were three target audiences: experimentalists who generate exRNA sequencing data, computational and data scientists who work with those groups to analyze their data, and experimental and data scientists new to the field. Here we summarize issues explored during the workshop, including progress on an effort to develop an exRNA data analysis challenge to engage the community in solving some of these open problems.

Profiling Extracellular Long RNA Transcriptome in Human Plasma and Extracellular Vesicles for Biomarker Discovery.

SummaryThe recent discovery of extracellular RNAs in blood, including RNAs in extracellular vesicles (EVs), combined with low-input RNA-sequencing advances have enabled scientists to investigate their role in human disease. To date, most studies have been focusing on small RNAs, and methodologies to optimize long RNAs measurement are lacking. We used plasma RNA to assess the performance of six long RNA sequencing methods, at two different sites, and we report their differences in reads (%) mapped to the genome/transcriptome, number of genes detected, long RNA transcript diversity, and reproducibility. Using the best performing method, we further compare the profile of long RNAs in the EV- and no-EV-enriched RNA plasma compartments. These results provide insights on the performance and reproducibility of commercially available kits in assessing the landscape of long RNAs in human plasma and different extracellular RNA carriers that may be exploited for biomarker discovery.

ExceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling.

Small RNA sequencing has been widely adopted to study the diversity of extracellular RNAs (exRNAs) in biofluids; however, the analysis of exRNA samples can be challenging: they are vulnerable to contamination and artifacts from different isolation techniques, present in lower concentrations than cellular RNA, and occasionally of exogenous origin. To address these challenges, we present exceRpt, the exRNA-processing toolkit of the NIH Extracellular RNA Communication Consortium (ERCC). exceRpt is structured as a cascade of filters and quantifications prioritized based on one's confidence in a given set of annotated RNAs. It generates quality control reports and abundance estimates for RNA biotypes. It is also capable of characterizing mappings to exogenous genomes, which, in turn, can be used to generate phylogenetic trees. exceRpt has been used to uniformly process all ∼3,500 exRNA-seq datasets in the public exRNA Atlas and is available from genboree.org and github.gersteinlab.org/exceRpt.

ExRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids

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 bydeconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of theexRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Towards mechanisms and standardization in extracellular vesicle and extracellular RNA studies: results of a worldwide survey

ABSTRACTThe discovery that extracellular vesicles (EVs) can transfer functional extracellular RNAs (exRNAs) between cells opened new avenues into the study of EVs in health and disease. Growing interest in EV RNAs and other forms of exRNA has given rise to research programmes including but not limited to the Extracellular RNA Communication Consortium (ERCC) of the US National Institutes of Health. In 2017, the International Society for Extracellular Vesicles (ISEV) administered a survey focusing on EVs and exRNA to canvass-related views and perceived needs of the EV research community. Here, we report the results of this survey. Overall, respondents emphasized opportunities for technical developments, unraveling of molecular mechanisms and standardization of methodologies to increase understanding of the important roles of exRNAs in the broader context of EV science. In conclusion, although exRNA biology is a relatively recent emphasis in the EV field, it has driven considerable interest and resource commitment. The ISEV community looks forward to continuing developments in the science of exRNA and EVs, but without excluding other important molecular constituents of EVs.

Extracellular Vesicle Based Therapeutic Targeting of Beta-Catenin to Modulate Anti-Cancer Immune Responses in Hepatocellular Cancer

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer related death worldwide. Although HCC can respond to immune checkpoint inhibitors such as monoclonal antibodies against PD-1, many patients fail to respond or develop secondary resistance. Activation of Wnt/β-catenin signaling can contribute to immune evasion. Mutations in β-catenin are amongst the most frequent mutations associated with HCC. Thus, our aim was to directly target β-catenin to enhance the therapeutic response to immune checkpoint inhibition. Methods: A synthetic transgenic mouse of experimental HCC induced by MET/ β-catenin expression, and extracellular vesicles as a therapeutic delivery agent were used to evaluate the efficacy of directly targeting β-catenin on response to anti-PD-1. Findings: These studies show that (1) oncogenic β-catenin could be therapeutically targeted using a biological nanoparticle based delivery approach, (2) targeting β-catenin using siRNA delivered within extracellular vesicles can reduce tumor growth, and (3) the therapeutic response to anti-PD-1 can be enhanced by concomitantly targeting β-catenin using therapeutic extracellular vesicles. These preclinical studies establish the efficacy of use of biological nanoparticles as an endogenous delivery vehicle for therapeutic RNA delivery and support the use of therapeutic strategies targeting tumor-intrinsic β-catenin as an adjunct to anti-PD-1 based therapy. Interpretation: Combination therapy with anti PD-1 and β-catenin siRNA delivered using biological nanoparticles provide an effective strategy for the treatment of HCC. This strategy could be further exploited into targeted approaches for immune potentiation by countering oncogenemediated resistance to immunotherapies. Funding Statement: Supported in part by the National Institutes of Health.TP is funded by NIH (UH3-TR000884). This publication is part of the NIH Extracellular RNA Communication Consortium paper package and was supported by the NIH Common Fund's exRNA Communication Program Declaration of Interests: There are no conflicts for any of the authors related to design, execution or analysis of the experiments presented in this manuscript. Ethics Approval Statement: All studies involving animals were performed in accordance with protocols approved by the Mayo Clinic Institutional Animal Care and Use committee.

Overview of Protocols for Studying Extracellular RNA and Extracellular Vesicles.

Understanding the role of extracellular RNA (exRNA) has emerged as an exciting avenue for biomarker, therapeutic, as well as basic cell-cell communication applications and discoveries. Multiple protocols, kits, and procedures have been developed in the last decade to allow fractionation as well as isolation of subpopulations of macromolecules of interest found in biofluids. Here, we introduce the protocols decision tree developed by the Extracellular RNA Communication Consortium and available on their website (exRNA portal), and compare all methods currently available to the exRNA field and report pros and cons for each platform.

Meeting report: discussions and preliminary findings on extracellular RNA measurement methods from laboratories in the NIH Extracellular RNA Communication Consortium

Extracellular RNAs (exRNAs) have been identified in all tested biofluids and have been associated with a variety of extracellular vesicles, ribonucleoprotein complexes and lipoprotein complexes. Much of the interest in exRNAs lies in the fact that they may serve as signalling molecules between cells, their potential to serve as biomarkers for prediction and diagnosis of disease and the possibility that exRNAs or the extracellular particles that carry them might be used for therapeutic purposes. Among the most significant bottlenecks to progress in this field is the lack of robust and standardized methods for collection and processing of biofluids, separation of different types of exRNA-containing particles and isolation and analysis of exRNAs. The Sample and Assay Standards Working Group of the Extracellular RNA Communication Consortium is a group of laboratories funded by the U.S. National Institutes of Health to develop such methods. In our first joint endeavour, we held a series of conference calls and in-person meetings to survey the methods used among our members, placed them in the context of the current literature and used our findings to identify areas in which the identification of robust methodologies would promote rapid advancements in the exRNA field.

Potential functional applications of extracellular vesicles: a report by the NIH Common Fund Extracellular RNA Communication Consortium

The NIH Extracellular RNA Communication Program's initiative on clinical utility of extracellular RNAs and therapeutic agents and developing scalable technologies is reviewed here. Background information and details of the projects are presented. The work has focused on modulation of target cell fate by extracellular vesicles (EVs) and RNA. Work on plant-derived vesicles is of intense interest, and non-mammalian sources of vesicles may represent a very promising source for different therapeutic approaches. Retro-viral-like particles are intriguing. Clearly, EVs share pathways with the assembly machinery of several other viruses, including human endogenous retrovirals (HERVs), and this convergence may explain the observation of viral-like particles containing viral proteins and nucleic acid in EVs. Dramatic effect on regeneration of damaged bone marrow, renal, pulmonary and cardiovascular tissue is demonstrated and discussed. These studies show restoration of injured cell function and the importance of heterogeneity of different vesicle populations. The potential for neural regeneration is explored, and the capacity to promote and reverse neoplasia by EV exposure is described. The tremendous clinical potential of EVs underlies many of these projects, and the importance of regulatory issues and the necessity of general manufacturing production (GMP) studies for eventual clinical trials are emphasized. Clinical trials are already being pursued and should expand dramatically in the near future.

Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies

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.