Unlocking the
Mysteries of
Extracellular RNA
Communication

Once thought to exist only inside cells, RNA is
known to travel outside of cells and play a role in newly
discovered mechanisms of cell-to-cell communication.

Quantitative measurements of the number, size, and cargo of extracellular vesicles (EVs) are essential to both basic research on how EVs are produced and function, and to application of this knowledge to the development of EV-based biomarkers and therapeutics. Flow cytometry is a popular method for analyzing EVs, but their small size and dim signals have made this a challenge using the conventional flow cytometry approaches developed for analysis of cells (1). Moreover, established flow cytometry calibrators, standards, and experimental design considerations for cell studies are not regularly used in EV studies. As a result, there is significant variation in instrument set up, sample preparation, and data reporting for flow cytometric measurements of EVs. These issues are increasingly appreciated (1-5), but much needs to be done to develop consensus on best practices. To address these issues, members of the International Society for Extracellular Vesicles (ISEV), the International Society for Advancement of Cytometry (ISAC), and the International Society on Thrombosis and Hemostasis (ISTH) are participating in a tri-Society Working Group, which includes several ERCC members, to improve the reporting of methods and results for FC-based EV measurements.

Reporting of EV Measurement Methods

A flow cytometer is an instrument, not a method. An EV analysis method that uses a flow cytometer involves many instrument setup, sample preparation, and data analysis decisions, including: 1) what signal to use for EV detection (light scatter or fluorescence); 2) how to resolve single EVs from the simultaneous occurrence of many EVs in the laser at the same time (aka coincidence or “swarm”); 3) how to gate the data to focus on EVs versus background events (without introducing artifacts or mis-representing the data); 4) how to estimate the size of the particles detected; 5) how to estimate the brightness of the particles detected; 6) how to verify that the particles detected are EVs and not other particles present in the sample, to name just some of the many decisions involved.

Several years ago, ISAC developed and introduced the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) (6), a set of guidelines to promote the sharing, reproducibility, and proper interpretation of flow cytometry data. These guidelines were developed with cell analysis, and particularly high parameter immunophenotyping, in mind, but they also apply to multiparameter EV analysis. However, there are several additional details about an EV measurement that are essential to include. The ISEV-ISAC-ISTH EV FC Working Group has been conducting a series of standardization studies to develop a consensus on the essential elements of an FC-based EV measurement that should be reported. These studies will be reported, along with the consensus reporting guidelines, in a paper planned for the coming year.

Standards and Calibrators for EV Analysis

Standards and calibration are essential components of any analytical method. These standards, and their use, are well established for flow cytometry and include 1) counting beads that can be used to calibrate sample flow rates for reporting of absolute particle concentrations, 2) fluorescence intensity standards that enable particle brightness to be expressed in NIST-traceable absolute units of mean equivalent soluble fluorochromes (MESF) (7) or equivalent reference fluorochromes (ERF) (8); 3) antibody-capture standards that can be used to estimate antibody binding in immunofluorescence measurements; and 4) NIST-traceable particle size standards.

Most of these standards and calibrators, and their methods of use, can be applied to EV measurements, with some caveats and cautions. Particle size standards, in particular, are often mis-used in FC-based EV measurements due to a lack of understanding of the effect on light scatter of refractive index (RI), which is different for polystyrene, silica, and lipids. With care, however, these differences can be used in conjunction with Mie scattering theory to enable estimates of EV size based on FC light scatter measurements. Commercially available fluorescence intensity and antibody-capture standards are generally designed for cell measurements, and tend to be brighter than EVs, but still have value for facilitating comparison of measurements between labs or instruments. EV-scaled intensity and antibody-binding standards will be a useful addition to the EV analysis toolbox, and are in development by several groups and companies.

A major unmet need is for EV standards, which will have use not only in FC-based EV measurements, but across the EV field. This is a challenging prospect, as an ideal EV standard will reflect not only the size and number of EVs, but also cargo, including surface molecules (for immunophenotyping) and intra-vesicular cargo, including nucleic acids, soluble proteins, and small molecules. Moreover, EVs are themselves quite diverse, raising the question of what type of EV, if any, might represent a universal standard. EV preparations for various cultured cell lines are commercially available from a number of sources but, in general, these have not been subjected to rigorous, independent characterization of these essential features or their uniformity, stability, or reproducibility. Such characterization is essential for validation of any putative standard and may be the subject of future activities by the ISEV-ISAC-ISTH EV FC Working Group.

Conclusions and Prospects

As EV research expands to impact every area of biology, issues with rigor and reproducibility are front and center. Translating observations made in the basic research lab into mechanistic understanding of EV actions and clinically actionable knowledge requires robust and validated analytical methods. Careful attention to the description of methods, standardization and calibration of analytical instrument and methods, and reporting of results are essential. Community efforts by the ERCC and relevant international societies will be key to helping researchers maximize the value of their work to the broader community.

In future blog posts we will discuss the controversial issue of whether to use light scatter or fluorescence to detect EVs, as well as new EV detection methods we’ve developed using fluorogenic membrane probes.

References

1. Nolan JP. Flow cytometry of extracellular vesicles: potential, pitfalls, and prospects. Curr. Protoc. Cytom. (2015) 73:13.14.1-13.14.16. PMID: 26132176. doi: 10.1002/0471142956.cy1314s73.
2. Chandler WL. Measurement of microvesicle levels in human blood using flow cytometry. Cytometry B Clin. Cytom. (2016) 90:326-336. PMID: 26606416. doi: 10.1002/cyto.b.21343.
3. Coumans FA, et al. Methodological guidelines to study extracellular vesicles. Circ. Res. (2017) 120:1632-1648. PMID: 28495994. doi: 10.1161/CIRCRESAHA.117.309417.
4. Nolan JP, Duggan E. Analysis of individual extracellular vesicles by flow cytometry. Methods Mol. Biol. (2018) 1678:79-92. PMID: 29071676. doi: 10.1007/978-1-4939-7346-0_5.
5. Nolan JP, Jones JC. Detection of platelet vesicles by flow cytometry. Platelets (2017) 28:256-262. PMID: 28277059. doi: 10.1080/09537104.2017.1280602.
6. Lee JA, et al. MIFlowCyt: the minimum information about a flow cytometry experiment. Cytometry A. (2008) 73:926-930. PMID: 18752282 doi: 10.1002/cyto.a.20623.
7. Wang L, Gaigalas AK, Abbasi F, Marti GE, Vogt RF, Schwartz A. Quantitating fluorescence intensity from fluorophores: practical use of MESF values. J. Res. Natl. Inst. Stand. Technol. (2002) 107:339-354. PMID: 27446735. doi: 10.6028/jres.107.027.
8. Wang L, Gaigalas AK. Development of multicolor flow cytometry calibration standards: Assignment of equivalent reference fluorophores (ERF) unit. J. Res. Natl. Inst. Stand. Technol. (2011) 116:671-83. PMID: 26989591. doi: 10.6028/jres.116.012.


Scientists from the ERCC have joined forces to create a CSF Consortium to pool resources and establish standard practices in the study of cerebrospinal fluid (CSF).

One of the goals of the ERCC is not only to understand the fundamental biology of extracellular RNA (exRNA), but to develop exRNA-based biomarkers of disease. When such biomarkers have been found, studied, and cleared for clinical use, liquid biopsy of blood and other biofluids can enable earlier disease detection and less invasive tracking of disease progression. For neurological disorders, drawing CSF from the spinal cord has clear benefits over a more invasive brain biopsy. Progress in our technical understanding of how to accurately assess biomarkers in CSF will increase our basic understanding and promote clinical advancements in the diagnosis and treatment of neurological disease. Unfortunately, there are many inconsistencies between the processing of CSF in current studies. Data replication is often difficult, in large part due to variability across laboratories and institutions in protocols for sample isolation, purification, and analysis. Thus, the CSF Consortium, spearheaded by Dr. Fred Hochberg (https://fredhhochbergmd.com), was designed to be a resource for researchers to help minimize these discrepancies.

The CSF consortium plan calls for CSF researchers and clinicians to work together to improve standard practices. A major focus is transparency through open sharing of their work. Researchers are encouraged to establish collaborations, share in-depth details of experimental designs and reagents (including batch/lot numbers), and release any details of in-house protocol modifications. Working with the same biosamples shared through the Virtual Biorepository (VBR) enables multiple labs to compare and synchronize their protocols with one source of variability removed. The expectation is that sharing of detailed information will enable future researchers to avoid common pitfalls and plan their own experiments appropriately. Ultimately, the goal is to have open-access information available from each stage of every project: from biofluid, RNA, and extracellular vesicle (EV) collection, isolation, and storage to downstream analyses such as RT-qPCR and RNA sequencing.

If you are a CSF researcher, please contact us so that we can work with you as well!

Highlights of recent CSF Consortium efforts
Saugstad et al. (2017) recently demonstrated the strength of the CSF consortium. In a collaboration between three institutions (UC San Diego, Oregon Health & Science University, and the Translational Genomics Research Institute), researchers worked together to characterize the EV and RNA composition of identical pools of CSF at each institute from patients with five different neurological disorders. This work in parallel allowed the groups to identify potential sources of variability in protocols including sample preparation, RNA isolation, and quantification of RNA via RNA sequencing and RT-qPCR. The study identified changes in EVs and RNA in the disease CSF samples and detected an enrichment of microRNAs and mRNAs related to disease in both EV and total RNA. The paper highlights the importance of stringent standard operating procedures, including the use of common standard sample collection and data analysis protocols across institutions.

In other work, Figueroa et al., 2017 performed a multi-institutional study of RNA extracted from CSF-derived EVs of patients with glioblastoma (GBM), a very aggressive form of brain cancer. (See this related blog on glioblastoma.) A key diagnostic biomarker in classical GBM is the functional status of the Epidermal Growth Factor Receptor (EGFR). This cell-surface receptor is the starting point of a series of signaling pathways related to cell growth. When its expression surges or it folds incorrectly, the result is cells with hyper-active signaling that never stop growing. This study involved the development of a liquid biopsy that scans RNA extracted from CSF EVs for tumor-associated amplifications and mutations in EGFR. The test has very high specificity and fair sensitivity: it almost never incorrectly flags a healthy patient as having GBM and correctly identifies almost two thirds of GBM sufferers. The clinical standard for diagnosis of GBM is magnetic resonance imaging (MRI), which correctly classifies most brain tumors, but in too many cases incorrectly suggests that healthy brain tissue might be cancerous. The complementarity of highly sensitive MRI and highly specific RNA liquid biopsy argues that updating the standard of care to include collection of CSF and brain images at the same time would better separate healthy from diseased brain tissue.

The CSF Consortium is casting its nets wider in its fight against glioblastoma, looking at molecules beyond EGFR in the attempt to develop an RNA-based diagnosis tool for GBM. Akers et al., 2017 developed a diagnostic panel of 9 miRNA biomarkers by analyzing the EV RNA from 135 CSF samples in 3 cohorts, followed by validation of the miRNA panel in 60 CSF samples from 2 cohorts. The researchers found that even with that fairly large sample size, the miRNA profiles in lumbar and cisternal CSF — fluid collected from the spine or the base of the neck, respectively — are significantly different, which is problematic, since cisternal CSF is much more difficult to collect. On the other hand, they also found that RNAs extracted from raw CSF had a similar profile and diagnostic power as RNAs extracted from vesicles after an initial EV purification step, which might simplify the translation of this biomarker research into the clinic.

References
Akers, J.C. et al. A cerebrospinal fluid microRNA signature as biomarker for glioblastoma. Oncotarget (2017) 8: 68769-68779.
Figueroa, J.M et al. Detection of wtEGFR amplification and EGFRvIII mutation in CSF-derived extracellular vesicles of glioblastoma patients. Neuro. Oncol. (2017) Advance online publication. doi: 10.1093/neuonc/nox085
Saugstad, J.A. et al. Analysis of extracellular RNA in cerebrospinal fluid. J. Extracellular Vesicles (2017) 6: 1317577.

We are pleased to announce the publication of miRandola 2017 in Nucleic Acids Research, Database issue 2018!
Citation:
miRandola 2017: a curated knowledge base of non-invasive biomarkers.
Francesco Russo*, Sebastiano Di Bella, Federica Vannini, Gabriele Berti, Flavia Scoyni, Helen V. Cook, Alberto Santos, Giovanni Nigita, Vincenzo Bonnici, Alessandro Laganà, Filippo Geraci, Alfredo Pulvirenti, Rosalba Giugno, Federico De Masi, Kirstine Belling, Lars J. Jensen, Søren Brunak, Marco Pellegrini, Alfredo Ferro.

*Correspondence to francesco.russo@cpr.ku.dk
URL: Nucleic Acids Research
Website: http://mirandola.iit.cnr.it/