Exploration of Extracellular Vesicle miRNAs, Targeted mRNAs and Pathways in Prostate Cancer: Relation to Disease Status and Progression.

BACKGROUND: Prostate cancer (PCa) lacks non-invasive specific biomarkers for aggressive disease. We studied the potential of urinary extracellular vesicles (uEV) as a liquid PCa biopsy by focusing on the micro RNA (miRNA) cargo, target messenger RNA (mRNA) and pathway analysis. METHODS: We subjected uEV samples from 31 PCa patients (pre-prostatectomy) to miRNA sequencing and matched uEV and plasma EV (pEV) from three PCa patients to mRNA sequencing. EV quality control was performed by electron microscopy, Western blotting and particle and RNA analysis. We compared miRNA expression based on PCa status (Gleason Score) and progression (post-prostatectomy follow-up) and confirmed selected miRNAs by quantitative PCR. Expression of target mRNAs was mapped in matched EV. RESULTS: Quality control showed typical small uEV, pEV, RNA and EV-protein marker enriched samples. Comparisons between PCa groups revealed mostly unique differentially expressed miRNAs. However, they targeted comprehensive and largely overlapping sets of cancer and progression-associated signalling, resistance, hormonal and immune pathways. Quantitative PCR confirmed changes in miR-892a (Gleason Score 7 vs. ≥8), miR-223-3p (progression vs. no progression) and miR-146a-5p (both comparisons). Their target mRNAs were expressed widely in PCa EV. CONCLUSIONS: PCa status and progression-linked RNAs in uEV are worth exploration in large personalized medicine trials.

Urinary extracellular vesicles: Assessment of pre-analytical variables and development of a quality control with focus on transcriptomic biomarker research.

Urinary extracellular vesicles (uEV) are a topical source of non-invasive biomarkers for health and diseases of the urogenital system. However, several challenges have become evident in the standardization of uEV pipelines from collection of urine to biomarker analysis. Here, we studied the effect of pre-analytical variables and developed means of quality control for uEV isolates to be used in transcriptomic biomarker research. We included urine samples from healthy controls and individuals with type 1 or type 2 diabetes and normo-, micro- or macroalbuminuria and isolated uEV by ultracentrifugation. We studied the effect of storage temperature (-20°C vs. -80°C), time (up to 4 years) and storage format (urine or isolated uEV) on quality of uEV by nanoparticle tracking analysis, electron microscopy, Western blotting and qPCR. Urinary EV RNA was compared in terms of quantity, quality, and by mRNA or miRNA sequencing. To study the stability of miRNA levels in samples isolated by different methods, we created and tested a list of miRNAs commonly enriched in uEV isolates. uEV and their transcriptome were preserved in urine or as isolated uEV even after long-term storage at -80°C. However, storage at -20°C degraded particularly the GC-rich part of the transcriptome and EV protein markers. Transcriptome was preserved in RNA samples extracted with and without DNAse, but read distributions still showed some differences in e.g. intergenic and intronic reads. MiRNAs commonly enriched in uEV isolates were stable and concordant between different EV isolation methods. Analysis of never frozen uEV helped to identify surface characteristics of particles by EM. In addition to uEV, qPCR assays demonstrated that uEV isolates commonly contained polyoma viruses. Based on our results, we present recommendations how to store and handle uEV isolates for transcriptomics studies that may help to expedite standardization of the EV biomarker field.

Pre-analytical factors affecting the establishment of a single tube assay for multiparameter liquid biopsy detection in melanoma patients.

The combination of liquid biomarkers from a single blood tube can provide more comprehensive information on tumor development and progression in cancer patients compared to single analysis. Here, we evaluated whether a combined analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and circulating cell-free microRNA (miRNA) in total plasma and extracellular vesicles (EV) from the same blood sample is feasible and how the results are influenced by the choice of different blood tubes. Peripheral blood from 20 stage IV melanoma patients and five healthy donors (HD) was collected in EDTA, Streck, and Transfix tubes. Peripheral blood mononuclear cell fraction was used for CTC analysis, whereas plasma and EV fractions were used for ctDNA mutation and miRNA analysis. Mutations in cell-free circulating DNA were detected in 67% of patients, with no significant difference between the tubes. CTC was detected in only EDTA blood and only in 15% of patients. miRNA NGS (next-generation sequencing) results were highly influenced by the collection tubes and could only be performed from EDTA and Streck tubes due to hemolysis in Transfix tubes. No overlap of significantly differentially expressed miRNA (patients versus HD) could be found between the tubes in total plasma, whereas eight miRNA were commonly differentially regulated in the EV fraction. In summary, high-quality CTCs, ctDNA, and miRNA data from a single blood tube can be obtained. However, the choice of blood collection tubes is a critical pre-analytical variable.

Multicenter Evaluation of Circulating Plasma MicroRNA Extraction Technologies for the Development of Clinically Feasible Reverse Transcription Quantitative PCR and Next-Generation Sequencing Analytical Work Flows.

BACKGROUND: In human body fluids, microRNA (miRNA) can be found as circulating cell-free miRNA (cfmiRNA), as well as secreted into extracellular vesicles (EVmiRNA). miRNAs are being intensively evaluated as minimally invasive liquid biopsy biomarkers in patients with cancer. The growing interest in developing clinical assays for circulating miRNA necessitates careful consideration of confounding effects of preanalytical and analytical parameters. METHODS: By using reverse transcription quantitative real-time PCR and next-generation sequencing (NGS), we compared extraction efficiencies of 5 different protocols for cfmiRNA and 2 protocols for EVmiRNA isolation in a multicentric manner. The efficiency of the different extraction methods was evaluated by measuring exogenously spiked cel-miR-39 and 6 targeted miRNAs in plasma from 20 healthy individuals. RESULTS: There were significant differences between the tested methods. Although column-based extraction methods were highly effective for the isolation of endogenous miRNA, phenol extraction combined with column-based miRNA purification and ultracentrifugation resulted in lower quality and quantity of isolated miRNA. Among all extraction methods, the ubiquitously expressed miR-16 was represented with high abundance when compared with other targeted miRNAs. In addition, the use of miR-16 as an endogenous control for normalization of quantification cycle values resulted in a decreased variability of column-based cfmiRNA extraction methods. Cluster analysis of normalized NGS counts clearly indicated a method-dependent bias. CONCLUSIONS: The choice of plasma miRNA extraction methods affects the selection of potential miRNA marker candidates and mechanistic interpretation of results, which should be done with caution, particularly across studies using different protocols.

TRAC in high-content gene expression analysis: applications in microbial population studies, process biotechnology and biomedical research.

More than a decade of intensive use of microarray technology has flooded the scientific community with genome-wide expression data of diverse biological states. As a result, connection of the expression signatures of a relatively small number of genes related to, for example, disease states, patient responses or toxicological responses has become possible. Development of tools that enable cost- and time-efficient analysis of such signatures from large sample numbers is currently of major interest for research, drug screening and diagnostic purposes. A method named transcript analysis with aid of affinity capture (TRAC) is a novel solution hybridization and bead-based assay enabling multiplex mRNA target detection simultaneously from large sample numbers. Functionality of TRAC has been shown in a number of applications, including microbial quantification, gene expression-based monitoring of biotechnical processes, cell-based cancer marker gene screening and siRNA validation, which are reviewed here.