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Liquid biopsy-derived extracellular vesicles (EVs) are an auspicious source for transcriptomic biomarker studies. Here, we review the potential of EV microRNAs (miRNAs) biomarkers, exemplary outline commonly used methods to elucidate new biomarker signatures, and pivotally discuss their applicability at present. Keywords: extracellular vesicles, liquid biopsies, transcriptomic biomarkers, microRNAs

Extracellular vesicles (EVs) play central physiological and pathophysiological roles in intercellular communication. Biomarker studies addressing disorders such as cardiovascular diseases often focus on circulating microRNAs (miRNAs) and may, depending on the type of disease and clinic routine, utilise patient specimens sampled from arterial or venous blood vessels. Thus, it is essential to test whether circulating miRNA profiles depend on the respective sampling site. We assessed potential differences in arterial and venous cell-free miRNA profiles in a cohort of 20 patients scheduled for cardiac surgery. Prior to surgery, blood was simultaneously sampled from the radial artery and the internal jugular vein. After precipitating crude EVs, we performed small RNA Sequencing, which failed to detect significantly regulated miRNAs using stringent filtering criteria for differential expression analysis. Filtering with less strict criteria, we detected four miRNAs slightly upregulated in arterial samples, one of which could be validated by reverse transcription real-time PCR. The applicability of these findings to purified arterial and venous EVs was subsequently tested in a subset of the initial study population. While an additional clean-up step using size-exclusion chromatography seemed to reduce overall miRNA yield compared to crude EV samples, no miRNAs with differential arteriovenous expression were detected. Unsupervised clustering approaches were unable to correctly classify samples drawn from arteries or veins based on miRNAs in either crude or purified preparations. Particle characterisation of crude preparations as well as characterisation of EV markers in purified EVs resulted in highly similar characteristics for arterial and venous samples. With the exception of specific pathologies (e.g. severe pulmonary disorders), arterial versus venous blood sampling should therefore not represent a likely confounder when studying differentially expressed circulating miRNAs. The use of either arterial or venous serum EV samples should result in highly similar data on miRNA expression profiles for the majority of biomarker studies. Abbreviations ACE inhibitors: Angiotensin-converting-enzyme inhibitors; ApoA1: Apolipoprotein A1; CNX: Calnexin; Cv: Coefficient of variation; cDNA: Complementary DNA; CABG: Coronary artery bypass graft; DGE: Differential gene expression; DPBS: Dulbecco’s Phosphate Buffered Saline; EVs: Extracellular vesicles; log2FC: Log2 fold change; baseMean: Mean miRNA expression; miRNA: MicroRNA; NTA: Nanoparticle Tracking Analysis; NGS: Next-Generation Sequencing; RT-qPCR: Reverse transcription quantitative real-time PCR; rRNA: Ribosomal RNA; RT: Room temperature; SEC: Size-exclusion chromatography; snoRNA: Small nucleolar RNA; snRNA: Small nuclear RNA; small RNA-Seq: Small RNA Sequencing; SD: Standard deviation; tRNA: Transfer RNA; TEM: Transmission electron microscopy; UA: Uranyl acetate.

MicroRNAs (miRNAs), a class of small non-coding RNAs that modulate gene expression at the post-transcriptional level, are attractive targets in many academic and diagnostic applications. Among them, assessing miRNA biomarkers in minimally invasive liquid biopsies was shown to be a promising tool for managing diseases, particularly cancer. The initial screening of disease-relevant transcripts is often performed by high-throughput next-generation sequencing (NGS), in here RNA sequencing (RNA-Seq). After complex processing of small RNA-Seq data, differential gene expression analysis is performed to evaluate miRNA biomarker signatures. To ensure experimental validity, biomarker candidates are commonly validated by an orthogonal technology such as reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR). This chapter outlines in detail the material and methods one can apply to reproducibly identify miRNA biomarker signatures from blood total RNA. After screening miRNA profiles by small RNA-Seq, resulting data is validated in compliance with the "Minimum Information for Publication of Quantitative Real-Time PCR Experiments" (MIQE) guidelines.

Extracellular vesicles (EVs) are intercellular communicators with key functions in physiological and pathological processes and have recently garnered interest because of their diagnostic and therapeutic potential. The past decade has brought about the development and commercialization of a wide array of methods to isolate EVs from serum. Which subpopulations of EVs are captured strongly depends on the isolation method, which in turn determines how suitable resulting samples are for various downstream applications. To help clinicians and scientists choose the most appropriate approach for their experiments, isolation methods need to be comparatively characterized. Few attempts have been made to comprehensively analyse vesicular microRNAs (miRNAs) in patient biofluids for biomarker studies. To address this discrepancy, we set out to benchmark the performance of several isolation principles for serum EVs in healthy individuals and critically ill patients. Here, we compared five different methods of EV isolation in combination with two RNA extraction methods regarding their suitability for biomarker discovery-focused miRNA sequencing as well as biological characteristics of captured vesicles. Our findings reveal striking method-specific differences in both the properties of isolated vesicles and the ability of associated miRNAs to serve in biomarker research. While isolation by precipitation and membrane affinity was highly suitable for miRNA-based biomarker discovery, methods based on size-exclusion chromatography failed to separate patients from healthy volunteers. Isolated vesicles differed in size, quantity, purity and composition, indicating that each method captured distinctive populations of EVs as well as additional contaminants. Even though the focus of this work was on transcriptomic profiling of EV-miRNAs, our insights also apply to additional areas of research. We provide guidance for navigating the multitude of EV isolation methods available today and help researchers and clinicians make an informed choice about which strategy to use for experiments involving critically ill patients.