Assessing the complementary information from an increased number of biologically relevant features in liquid biopsy-derived RNA-Seq data.

Liquid biopsy-derived RNA sequencing (lbRNA-seq) exhibits significant promise for clinic-oriented cancer diagnostics due to its non-invasiveness and ease of repeatability. Despite substantial advancements, obstacles like technical artefacts and process standardisation impede seamless clinical integration. Alongside addressing technical aspects such as normalising fluctuating low-input material and establishing a standardised clinical workflow, the lack of result validation using independent datasets remains a critical factor contributing to the often low reproducibility of liquid biopsy-detected biomarkers. Considering the outlined drawbacks, our objective was to establish a workflow/methodology characterised by: 1. Harness the rich diversity of biological features accessible through lbRNA-seq data, encompassing a holistic range of molecular and functional attributes. These components are seamlessly integrated via a Machine Learning-based Ensemble Classification framework, enabling a unified and comprehensive analysis of the intricate information encoded within the data. 2. Implementing and rigorously benchmarking intra-sample normalisation methods to heighten their relevance within clinical settings. 3. Thoroughly assessing its efficacy across independent test sets to ascertain its robustness and potential utility. Using ten datasets from several studies comprising three different sources of biological material, we first show that while the best-performing normalisation methods depend strongly on the dataset and coupled Machine Learning method, the rather simple Counts Per Million method is generally very robust, showing comparable performance to cross-sample methods. Subsequently, we demonstrate that the innovative biofeature types introduced in this study, such as the Fraction of Canonical Transcript, harbour complementary information. Consequently, their inclusion consistently enhances prediction power compared to models relying solely on gene expression-based biofeatures. Finally, we demonstrate that the workflow is robust on completely independent datasets, generally from different labs and/or different protocols. Taken together, the workflow presented here outperforms generally employed methods in prediction accuracy and may hold potential for clinical diagnostics application due to its specific design.

In vitro cross-talk between metastasis-competent circulating tumor cells and platelets in colon cancer: a malicious association during the harsh journey in the blood.

Background: Platelets are active players in hemostasis, coagulation and also tumorigenesis. The cross-talk between platelets and circulating tumor cells (CTCs) may have various pro-cancer effects, including promoting tumor growth, epithelial-mesenchymal transition (EMT), metastatic cell survival, adhesion, arrest and also pre-metastatic niche and metastasis formation. Interaction with CTCs might alter the platelet transcriptome. However, as CTCs are rare events, the cross-talk between CTCs and platelets is poorly understood. Here, we used our established colon CTC lines to investigate the colon CTC-platelet cross-talk in vitro and its impact on the behavior/phenotype of both cell types. Methods: We exposed platelets isolated from healthy donors to thrombin (positive control) or to conditioned medium from three CTC lines from one patient with colon cancer and then we monitored the morphological and protein expression changes by microscopy and flow cytometry. We then analyzed the transcriptome by RNA-sequencing of platelets indirectly (presence of a Transwell insert) co-cultured with the three CTC lines. We also quantified by reverse transcription-quantitative PCR the expression of genes related to EMT and cancer development in CTCs after direct co-culture (no Transwell insert) with platelets. Results: We observed morphological and transcriptomic changes in platelets upon exposure to CTC conditioned medium and indirect co-culture (secretome). Moreover, the expression levels of genes involved in EMT (p < 0.05) were decreased in CTCs co-cultured with platelets, but not of genes encoding mesenchymal markers (FN1 and SNAI2). The expression levels of genes involved in cancer invasiveness (MYC, VEGFB, IL33, PTGS2, and PTGER2) were increased. Conclusion: For the first time, we studied the CTC-platelet cross-talk using our unique colon CTC lines. Incubation with CTC conditioned medium led to platelet aggregation and activation, supporting the hypothesis that their interaction may contribute to preserve CTC integrity during their journey in the bloodstream. Moreover, co-culture with platelets influenced the expression of several genes involved in invasiveness and EMT maintenance in CTCs.

Tumor-educated platelet blood tests for Non-Small Cell Lung Cancer detection and management.

Liquid biopsy approaches offer a promising technology for early and minimally invasive cancer detection. Tumor-educated platelets (TEPs) have emerged as a promising liquid biopsy biosource for the detection of various cancer types. In this study, we processed and analyzed the TEPs collected from 466 Non-small Cell Lung Carcinoma (NSCLC) patients and 410 asymptomatic individuals (controls) using the previously established thromboSeq protocol. We developed a novel particle-swarm optimization machine learning algorithm which enabled the selection of an 881 RNA biomarker panel (AUC 0.88). Herein we propose and validate in an independent cohort of samples (n = 558) two approaches for blood samples testing: one with high sensitivity (95% NSCLC detected) and another with high specificity (94% controls detected). Our data explain how TEP-derived spliced RNAs may serve as a biomarker for minimally-invasive clinical blood tests, complement existing imaging tests, and assist the detection and management of lung cancer patients.

Liquid Biopsy: Current Status and Future Perspectives.

Since the discovery of the Bence Jones protein in the middle to late 1800s and the subsequent identification of the carcinoembryonic antigen and alpha-fetoprotein in the 1970s, it has been demonstrated that the analysis of biofluids is essential to the diagnostic and follow-up processes of cancer [...].

Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection.

Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.

ALL-tRNAseq enables robust tRNA profiling in tissue samples.

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.

miRGalaxy: Galaxy-Based Framework for Interactive Analysis of microRNA and isomiR Sequencing Data.

Tools for microRNA (miR) sequencing data analyses are broadly used in biomedical research. However, the complexity of computational approaches still remains a challenge for biologists with scarce experience in data analytics and bioinformatics. Here, we present miRGalaxy, a Galaxy-based framework for comprehensive analysis of miRs and their sequence variants-miR isoforms (isomiRs). Though isomiRs are commonly reported in deep-sequencing experiments, their detailed structure complexity and specific differential expression (DE) remain not fully examined by the majority of the available analysis tools. miRGalaxy encompasses biologist-user-friendly tools and workflows dedicated to the analysis of the isomiR-ome and its complex behavior in various biological samples. miRGalaxy is developed as a modular, accessible, redistributable, shareable, and user-friendly framework for scientists working with small RNA (sRNA)-seq data. Due to its modular workflow, advanced users can customize the steps and tools for their needs. In addition, the framework provides an analysis report where the significant output results are summarized in charts and visualizations. miRGalaxy can be accessed via preconfigured Docker image flavor and a Toolshed installation if the user already has a running Galaxy instance. Over the last decade, studies on the expression of miRs and isomiRs in normal and deregulated tissues have led to the discovery of their potential as diagnostic biomarkers. The detection of miRs in biofluids further expanded the exploration of the miR repertoire as a source of liquid biopsy biomarkers. Here we show the miRGalaxy framework application for in-depth analysis of the sRNA-seq data from two different biofluids, milk and plasma, to identify, annotate, and discover specific differentially expressed miRs and isomiRs.

The Analysis of Platelet-Derived circRNA Repertoire as Potential Diagnostic Biomarker for Non-Small Cell Lung Cancer.

Tumor-educated Platelets (TEPs) have emerged as rich biosources of cancer-related RNA profiles in liquid biopsies applicable for cancer detection. Although human blood platelets have been found to be enriched in circular RNA (circRNA), no studies have investigated the potential of circRNA as platelet-derived biomarkers for cancer. In this proof-of-concept study, we examine whether the circRNA signature of blood platelets can be used as a liquid biopsy biomarker for the detection of non-small cell lung cancer (NSCLC). We analyzed the total RNA, extracted from the platelet samples collected from NSCLC patients and asymptomatic individuals, using RNA sequencing (RNA-Seq). Identification and quantification of known and novel circRNAs were performed using the accurate CircRNA finder suite (ACFS), followed by the differential transcript expression analysis using a modified version of our thromboSeq software. Out of 4732 detected circRNAs, we identified 411 circRNAs that are significantly (p-value < 0.05) differentially expressed between asymptomatic individuals and NSCLC patients. Using the false discovery rate (FDR) of 0.05 as cutoff, we selected the nuclear receptor-interacting protein 1 (NRIP1) circRNA (circNRIP1) as a potential biomarker candidate for further validation by reverse transcription-quantitative PCR (RT-qPCR). This analysis was performed on an independent cohort of platelet samples. The RT-qPCR results confirmed the RNA-Seq data analysis, with significant downregulation of circNRIP1 in platelets derived from NSCLC patients. Our findings suggest that circRNAs found in blood platelets may hold diagnostic biomarkers potential for the detection of NSCLC using liquid biopsies.

Circulating platelets as liquid biopsy sources for cancer detection.

Nucleic acids and proteins are shed into the bloodstream by tumor cells and can be exploited as biomarkers for the detection of cancer. In addition, cancer detection biomarkers can also be nontumor-derived, having their origin in other organs and cell types. Hence, liquid biopsies provide a source of direct tumor cell-derived biomolecules and indirect nontumor-derived surrogate markers that circulate in body fluids or are taken up by circulating peripheral blood cells. The capacity of platelets to take up proteins and nucleic acids and alter their megakaryocyte-derived transcripts and proteins in response to external signals makes them one of the richest liquid biopsy biosources. Platelets are the second most abundant cell type in peripheral blood and are routinely isolated through well-established and fast methods in clinical diagnostics but their value as a source of cancer biomarkers is relatively recent. Platelets do not have a nucleus but have a functional spliceosome and protein translation machinery, to process RNA transcripts. Platelets emerge as important repositories of potential cancer biomarkers, including several types of RNAs (mRNA, miRNA, circRNA, lncRNA, and mitochondrial RNA) and proteins, and several preclinical studies have highlighted their potential as a liquid biopsy source for detecting various types and stages of cancer. Here, we address the usability of platelets as a liquid biopsy for the detection of cancer. We describe several studies that support the use of platelet biomarkers in cancer diagnostics and discuss what is still lacking for their implementation into the clinic.

Expression of Oncolytic Adenovirus-Encoded RNAi Molecules Is Most Effective in a pri-miRNA Precursor Format.

Oncolytic adenoviruses are being developed as new anti-cancer agents. Their efficacy can be improved by incorporating RNA interference (RNAi) molecules. RNAi molecules can be expressed in various precursor formats. The aim of this study was to determine the most effective format. To this end, we constructed three Δ24-type oncolytic adenoviruses, with human microRNA-1 (miR-1) expression cassettes in short hairpin RNA (shRNA), precursor microRNA (pre-miRNA), and primary miRNA (pri-miRNA) format, respectively. The viruses were compared for virus replication, mature miR-1 expression, and target gene silencing in cancer cells. Incorporation of the cassettes had only minor effects on virus replication. Mature miR-1 expression from the pri-miRNA format reached on average 100-fold higher levels than from the other two formats. This expression remained stable upon long-term virus propagation. Infection with the pri-miR-1-expressing virus silenced the validated miR-1 targets FOXP1 and MET. Drosha knockout almost completely abrogated mature miR-1 expression, confirming that processing of adenovirus-encoded pri-miR-1 was dependent on the host cell miRNA machinery. Using simple in vitro recombination cloning, a similar virus expressing miR-26b was made and shown to silence the validated miR-26b target PTGS2. We thus provide a platform for construction of oncolytic adenoviruses with high expression of RNAi molecules of choice.

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

isomiRs-Hidden Soldiers in the miRNA Regulatory Army, and How to Find Them?

Numerous studies on microRNAs (miRNA) in cancer and other diseases have been accompanied by diverse computational approaches and experimental methods to predict and validate miRNA biological and clinical significance as easily accessible disease biomarkers. In recent years, the application of the next-generation deep sequencing for the analysis and discovery of novel RNA biomarkers has clearly shown an expanding repertoire of diverse sequence variants of mature miRNAs, or isomiRs, resulting from alternative post-transcriptional processing events, and affected by (patho)physiological changes, population origin, individual's gender, and age. Here, we provide an in-depth overview of currently available bioinformatics approaches for the detection and visualization of both mature miRNA and cognate isomiR sequences. An attempt has been made to present in a systematic way the advantages and downsides of in silico approaches in terms of their sensitivity and accuracy performance, as well as used methods, workflows, and processing steps, and end output dataset overlapping issues. The focus is given to the challenges and pitfalls of isomiR expression analysis. Specifically, we address the availability of tools enabling research without extensive bioinformatics background to explore this fascinating corner of the small RNAome universe that may facilitate the discovery of new and more reliable disease biomarkers.

Omics Analysis of Educated Platelets in Cancer and Benign Disease of the Pancreas.

Pancreatic ductal adenocarcinoma (PDAC) is traditionally associated with thrombocytosis/hypercoagulation and novel insights on platelet-PDAC "dangerous liaisons" are warranted. Here we performed an integrative omics study investigating the biological processes of mRNAs and expressed miRNAs, as well as proteins in PDAC blood platelets, using benign disease as a reference for inflammatory noise. Gene ontology mining revealed enrichment of RNA splicing, mRNA processing and translation initiation in miRNAs and proteins but depletion in RNA transcripts. Remarkably, correlation analyses revealed a negative regulation on SPARC transcription by isomiRs involved in cancer signaling, suggesting a specific "education" in PDAC platelets. Platelets of benign patients were enriched for non-templated additions of G nucleotides (#ntaG) miRNAs, while PDAC presented length variation on 3' (lv3p) as the most frequent modification on miRNAs. Additionally, we provided an actionable repertoire of PDAC and benign platelet-ome to be exploited for future studies. In conclusion, our data show that platelets change their biological repertoire in patients with PDAC, through dysregulation of miRNAs and splicing factors, supporting the presence of de novo protein machinery that can "educate" the platelet. These novel findings could be further exploited for innovative liquid biopsies platforms as well as possible therapeutic targets.

Altered microRNA processing proteins in HPV-induced cancers.

High-risk human papilloma virus (hrHPV) infections are associated with the development of anogenital cancers, in particular cervical cancer, and a subset of head and neck cancers. Previous studies have shown that microRNAs (miRNAs) contribute to the development and progression of HPV-induced malignancies. miRNAs are small non-coding RNAs that exist as multiple length and sequence variants, termed isomiRs. Efficient processing of miRNAs and generation of isomiRs is accomplished by several processing proteins. Deregulation of Drosha, AGO2, and TENT2, among others, has been observed in HPV-induced cancers and was even found at the precancerous stage. This suggests that miRNA processing proteins may be involved during early cancer development and that the generated isomiRs could provide promising biomarkers for early cancer diagnosis.

Vesicle-bound EBV-BART13-3p miRNA in circulation distinguishes nasopharyngeal from other head and neck cancer and asymptomatic EBV-infections.

Cell-free microRNA (miRNA) in biofluids released by tumors in either protein or vesicle-bound form, represent promising minimally-invasive cancer biomarkers. However, a highly abundant non-tumor background in human plasma and serum complicates the discovery and detection of tumor-selective circulating miRNAs. We performed small RNA sequencing on serum and plasma RNA from Nasopharyngeal Carcinoma (NPC) patients. Collectively, Epstein Barr virus-encoded miRNAs, more so than endogenous miRNAs, signify presence of NPC. However, RNAseq-based EBV miRNA profiles differ between NPC patients, suggesting inter-tumor heterogeneity or divergent secretory characteristics. We determined with sensitive qRT-PCR assays that EBV miRNAs BART7-3p, BART9-3p and BART13-3p are actively secreted by C666.1 NPC cells bound to extracellular vesicles (EVs) and soluble ribonucleoprotein complexes. Importantly, these miRNAs are expressed in all primary NPC tumor biopsies and readily detected in nasopharyngeal brushings from both early and late-stage NPC patients. Increased levels of BART7-3p, BART9-3p and particularly BART13-3p, distinguish NPC patient sera from healthy controls. Receiver operating characteristic curve analysis using sera from endemic NPC patients, other head and neck cancers and individuals with asymptomatic EBV-infections reveals a superior diagnostic performance of EBV miRNAs over anti-EBNA1 IgA serology and EBV-DNA load (AUC 0.87-0.96 vs 0.86 and 0.66 respectively). The high specificity of circulating EBV-BART13-3p (97%) for NPC detection is in agreement with active secretion from NPC tumor cells. We conclude EV-bound BART13-3p in circulation is a promising, NPC-selective, biomarker that should be considered as part of a screening strategy to identify NPC in endemic regions.

liqDB: a small-RNAseq knowledge discovery database for liquid biopsy studies.

MiRNAs are important regulators of gene expression and are frequently deregulated under pathologic conditions. They are highly stable in bodily fluids which makes them feasible candidates to become minimally invasive biomarkers. In fact, several studies already proposed circulating miRNA-based biomarkers for different types of neoplastic, cardiovascular and degenerative diseases. However, many of these studies rely on small RNA sequencing experiments that are based on different RNA extraction and processing protocols, rendering results incomparable. We generated liqDB, a database for liquid biopsy small RNA sequencing profiles that provides users with meaningful information to guide their small RNA liquid biopsy research and to overcome technical and conceptual problems. By means of a user-friendly web interface, miRNA expression profiles from 1607 manually annotated samples can be queried and explored at different levels. Result pages include downloadable expression matrices, differential expression analysis, most stably expressed miRNAs, cluster analysis and relevant visualizations by means of boxplots and heatmaps. We anticipate that liqDB will be a useful tool in liquid biopsy research as it provides a consistently annotated large compilation of experiments together with tools for reproducible analysis, comparison and hypothesis generation. LiqDB is available at http://bioinfo5.ugr.es/liqdb.

Glycosylated extracellular vesicles released by glioblastoma cells are decorated by CCL18 allowing for cellular uptake via chemokine receptor CCR8.

Cancer cells release extracellular vesicles (EVs) that contain functional biomolecules such as RNA and proteins. EVs are transferred to recipient cancer cells and can promote tumour progression and therapy resistance. Through RNAi screening, we identified a novel EV uptake mechanism involving a triple interaction between the chemokine receptor CCR8 on the cells, glycans exposed on EVs and the soluble ligand CCL18. This ligand acts as bridging molecule, connecting EVs to cancer cells. We show that glioblastoma EVs promote cell proliferation and resistance to the alkylating agent temozolomide (TMZ). Using in vitro and in vivo stem-like glioblastoma models, we demonstrate that EV-induced phenotypes are neutralised by a small molecule CCR8 inhibitor, R243. Interference with chemokine receptors may offer therapeutic opportunities against EV-mediated cross-talk in glioblastoma.

Plasma vesicle miRNAs for therapy response monitoring in Hodgkin lymphoma patients.

BACKGROUND. Cell-free circulating nucleic acids, including 22-nt microRNAs (miRNAs), represent noninvasive biomarkers for treatment response monitoring of cancer patients. While the majority of plasma miRNA is bound to proteins, a smaller, less well-characterized pool is associated with extracellular vesicles (EVs). Here, we addressed whether EV-associated miRNAs reflect metabolic disease in classical Hodgkin lymphoma (cHL) patients. METHODS. With standardized size-exclusion chromatography (SEC), we isolated EV-associated extracellular RNA (exRNA) fractions and protein-bound miRNA from plasma of cHL patients and healthy subjects. We performed a comprehensive small RNA sequencing analysis and validation by TaqMan qRT-PCR for candidate discovery. Fluorodeoxyglucose-PET (FDG-PET) status before treatment, directly after treatment, and during long-term follow-up was compared directly with EV miRNA levels. RESULTS. The plasma EV miRNA repertoire was more extensive compared with protein-bound miRNA that was heavily dominated by a few abundant miRNA species and was less informative of disease status. Purified EV fractions of untreated cHL patients and tumor EVs had enriched levels of miR24-3p, miR127-3p, miR21-5p, miR155-5p, and let7a-5p compared with EV fractions from healthy subjects and disease controls. Serial monitoring of EV miRNA levels in patients before treatment, directly after treatment, and during long-term follow-up revealed robust, stable decreases in miRNA levels matching a complete metabolic response, as observed with FDG-PET. Importantly, EV miRNA levels rose again in relapse patients. CONCLUSION. We conclude that cHL-related miRNA levels in circulating EVs reflect the presence of vital tumor tissue and are suitable for therapy response and relapse monitoring in individual cHL patients. FUNDING. Cancer Center Amsterdam Foundation (CCA-2013), Dutch Cancer Society (KWF-5510), Technology Foundation STW (STW Perspectief CANCER-ID).

Non­invasive prostate cancer detection by measuring miRNA variants (isomiRs) in urine extracellular vesicles.

In many cancer types, the expression and function of ~22 nucleotide-long microRNAs (miRNA) is deregulated. Mature miRNAs can be stably detected in extracellular vesicles (EVs) in biofluids, therefore they are considered to have great potential as biomarkers. In the present study, we investigated whether miRNAs have a distinct expression pattern in urine-EVs of prostate cancer (PCa) patients compared to control males. By next generation sequencing, we determined the miRNA expression in a discovery cohort of 4 control men and 9 PCa patients. miRNAs were validated by using a stemloop RT-PCR in an independent cohort of 74 patients (26 control and 48 PCa-patients). Whereas standard mapping protocols identified > 10 PCa associated miRNAs in urinary EVs, miR-21, miR-375 and miR-204 failed to robustly discriminate for disease in a validation study with RT-PCR-detection of mature miRNA sequences. In contrast, we observed that miRNA isoforms (isomiRs) with 3' end modifications were highly discriminatory between samples from control men and PCa patients. Highly differentially expressed isomiRs of miR-21, miR-204 and miR-375 were subsequently validated in an independent group of 74 patients. Receiver-operating characteristic analysis was performed to evaluate the diagnostic performance of three isomiRs, resulting in a 72.9% sensitivity with a high (88%) specificity and an area under the curve (AUC) of 0.866. In comparison, prostate specific antigen had an AUC of 0.707 and measuring the mature form of these miRNAs yielded a lower 70.8% sensitivity and 72% specificity (AUC 0.766). We propose that isomiRs may carry discriminatory information which is useful to generate stronger biomarkers.

Sensing of latent EBV infection through exosomal transfer of 5'pppRNA.

Complex interactions between DNA herpesviruses and host factors determine the establishment of a life-long asymptomatic latent infection. The lymphotropic Epstein-Barr virus (EBV) seems to avoid recognition by innate sensors despite massive transcription of immunostimulatory small RNAs (EBV-EBERs). Here we demonstrate that in latently infected B cells, EBER1 transcripts interact with the lupus antigen (La) ribonucleoprotein, avoiding cytoplasmic RNA sensors. However, in coculture experiments we observed that latent-infected cells trigger antiviral immunity in dendritic cells (DCs) through selective release and transfer of RNA via exosomes. In ex vivo tonsillar cultures, we observed that EBER1-loaded exosomes are preferentially captured and internalized by human plasmacytoid DCs (pDCs) that express the TIM1 phosphatidylserine receptor, a known viral- and exosomal target. Using an EBER-deficient EBV strain, enzymatic removal of 5'ppp, in vitro transcripts, and coculture experiments, we established that 5'pppEBER1 transfer via exosomes drives antiviral immunity in nonpermissive DCs. Lupus erythematosus patients suffer from elevated EBV load and activated antiviral immunity, in particular in skin lesions that are infiltrated with pDCs. We detected high levels of EBER1 RNA in such skin lesions, as well as EBV-microRNAs, but no intact EBV-DNA, linking non-cell-autonomous EBER1 presence with skin inflammation in predisposed individuals. Collectively, our studies indicate that virus-modified exosomes have a physiological role in the host-pathogen stand-off and may promote inflammatory disease.