Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision.

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.

mTOR Inhibition Enhances Delivery and Activity of Antisense Oligonucleotides in Uveal Melanoma Cells.

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Owing to a lack of effective treatments, patients with metastatic disease have a median survival time of 6-12 months. We recently demonstrated that the Survival Associated Mitochondrial Melanoma Specific Oncogenic Non-coding RNA (SAMMSON) is essential for UM cell survival and that antisense oligonucleotide (ASO)-mediated silencing of SAMMSON impaired cell viability and tumor growth in vitro and in vivo. By screening a library of 2911 clinical stage compounds, we identified the mammalian target of rapamycin (mTOR) inhibitor GDC-0349 to synergize with SAMMSON inhibition in UM. Mechanistic studies revealed that mTOR inhibition enhanced uptake and reduced lysosomal accumulation of lipid complexed SAMMSON ASOs, improving SAMMSON knockdown and further decreasing UM cell viability. We found mTOR inhibition to also enhance target knockdown in other cancer cell lines as well as normal cells when combined with lipid nanoparticle complexed or encapsulated ASOs or small interfering RNAs (siRNAs). Our results are relevant to nucleic acid treatment in general and highlight the potential of mTOR inhibition to enhance ASO and siRNA-mediated target knockdown.

Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models enables specific monitoring of tumour-derived extracellular RNA.

While cell-free DNA (cfDNA) is widely being investigated, free circulating RNA (extracellular RNA, exRNA) has the potential to improve cancer therapy response monitoring and detection due to its dynamic nature. However, it remains unclear in which blood subcompartment tumour-derived exRNAs primarily reside. We developed a host-xenograft deconvolution framework, exRNAxeno, with mapping strategies to either a combined human-mouse reference genome or both species genomes in parallel, applicable to exRNA sequencing data from liquid biopsies of human xenograft mouse models. The tool enables to distinguish (human) tumoural RNA from (murine) host RNA, to specifically analyse tumour-derived exRNA. We applied the combined pipeline to total exRNA sequencing data from 95 blood-derived liquid biopsy samples from 30 mice, xenografted with 11 different tumours. Tumoural exRNA concentrations are not determined by plasma platelet levels, while host exRNA concentrations increase with platelet content. Furthermore, a large variability in exRNA abundance and transcript content across individual mice is observed. The tumoural gene detectability in plasma is largely correlated with the RNA expression levels in the tumour tissue or cell line. These findings unravel new aspects of tumour-derived exRNA biology in xenograft models and open new avenues to further investigate the role of exRNA in cancer.

The long non-coding RNA SAMMSON is essential for uveal melanoma cell survival.

Long non-coding RNAs (lncRNAs) can exhibit cell-type and cancer-type specific expression profiles, making them highly attractive as therapeutic targets. Pan-cancer RNA sequencing data revealed broad expression of the SAMMSON lncRNA in uveal melanoma (UM), the most common primary intraocular malignancy in adults. Currently, there are no effective treatments for UM patients with metastatic disease, resulting in a median survival time of 6-12 months. We aimed to investigate the therapeutic potential of SAMMSON inhibition in UM. Antisense oligonucleotide (ASO)-mediated SAMMSON inhibition impaired the growth and viability of a genetically diverse panel of uveal melanoma cell lines. These effects were accompanied by an induction of apoptosis and were recapitulated in two uveal melanoma patient derived xenograft (PDX) models through subcutaneous ASO delivery. SAMMSON pulldown revealed several candidate interaction partners, including various proteins involved in mitochondrial translation. Consequently, inhibition of SAMMSON impaired global, mitochondrial and cytosolic protein translation levels and mitochondrial function in uveal melanoma cells. The present study demonstrates that SAMMSON expression is essential for uveal melanoma cell survival. ASO-mediated silencing of SAMMSON may provide an effective treatment strategy to treat primary and metastatic uveal melanoma patients.

Custom long non-coding RNA capture enhances detection sensitivity in different human sample types.

Long non-coding RNAs (lncRNAs) are a heterogeneous group of transcripts that lack protein coding potential and display regulatory functions in various cellular processes. As a result of their cell- and cancer-specific expression patterns, lncRNAs have emerged as potential diagnostic and therapeutic targets. The accurate characterization of lncRNAs in bulk transcriptome data remains challenging due to their low abundance compared to protein coding genes. To tackle this issue, we describe a unique short-read custom lncRNA capture sequencing approach that relies on a comprehensive set of 565,878 capture probes for 49,372 human lncRNA genes. This custom lncRNA capture approach was evaluated on various sample types ranging from artificial high-quality RNA mixtures to more challenging formalin-fixed paraffin-embedded tissue and biofluid material. The custom enrichment approach allows the detection of a more diverse repertoire of lncRNAs, with better reproducibility and higher coverage compared to classic total RNA-sequencing.

The RNA Atlas expands the catalog of human non-coding RNAs.

Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.

Messenger RNA capture sequencing of extracellular RNA from human biofluids using a comprehensive set of spike-in controls.

Comprehensive transcriptome analysis of extracellular RNA (exRNA) purified from human biofluids is challenging because of the low RNA concentration and compromised RNA integrity. Here, we describe an optimized workflow to (1) isolate exRNA from different types of biofluids and (2) to prepare messenger RNA (mRNA)-enriched sequencing libraries using complementary hybridization probes. Importantly, the workflow includes 2 sets of synthetic spike-in RNA molecules as processing controls for RNA purification and sequencing library preparation and as an alternative data normalization strategy. For complete details on the use and execution of this protocol, please refer to Hulstaert et al. (2020).

Charting Extracellular Transcriptomes in The Human Biofluid RNA Atlas.

Extracellular RNAs present in biofluids have emerged as potential biomarkers for disease. Where most studies focus on blood-derived fluids, other biofluids may be more informative. We present an atlas of messenger, circular, and small RNA transcriptomes of a comprehensive collection of 20 human biofluids. By means of synthetic spike-in controls, we compare RNA content across biofluids, revealing a 10,000-fold difference in concentration. The circular RNA fraction is increased in most biofluids compared to tissues. Each biofluid transcriptome is enriched for RNA molecules derived from specific tissues and cell types. Our atlas enables an informed selection of the most relevant biofluid to monitor particular diseases. To verify the biomarker potential in these biofluids, four validation cohorts representing a broad spectrum of diseases were profiled, revealing numerous differential RNAs between case and control subjects. Spike-normalized data are publicly available in the R2 web portal for further exploration.

Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles.

RNA profiling has emerged as a powerful tool to investigate the biomarker potential of human biofluids. However, despite enormous interest in extracellular nucleic acids, RNA sequencing methods to quantify the total RNA content outside cells are rare. Here, we evaluate the performance of the SMARTer Stranded Total RNA-Seq method in human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. We found the method to be accurate, precise, compatible with low-input volumes and able to quantify a few thousand genes. We picked up distinct classes of RNA molecules, including mRNA, lncRNA, circRNA, miscRNA and pseudogenes. Notably, the read distribution and gene content drastically differ among biofluids. In conclusion, we are the first to show that the SMARTer method can be used for unbiased unraveling of the complete transcriptome of a wide range of biofluids and their extracellular vesicles.

LNCipedia 5: towards a reference set of human long non-coding RNAs.

While long non-coding RNA (lncRNA) research in the past has primarily focused on the discovery of novel genes, today it has shifted towards functional annotation of this large class of genes. With thousands of lncRNA studies published every year, the current challenge lies in keeping track of which lncRNAs are functionally described. This is further complicated by the fact that lncRNA nomenclature is not straightforward and lncRNA annotation is scattered across different resources with their own quality metrics and definition of a lncRNA. To overcome this issue, large scale curation and annotation is needed. Here, we present the fifth release of the human lncRNA database LNCipedia (https://lncipedia.org). The most notable improvements include manual literature curation of 2482 lncRNA articles and the use of official gene symbols when available. In addition, an improved filtering pipeline results in a higher quality reference lncRNA gene set.

Targeted Genomic Screen Reveals Focal Long Non-Coding RNA Copy Number Alterations in Cancer Cell Lines.

The landscape of somatic copy-number alterations (SCNAs) affecting long non-coding RNAs (lncRNAs) in human cancers remains largely unexplored. While the majority of lncRNAs remain to be functionally characterized, several have been implicated in cancer development and metastasis. Considering the plethora of lncRNAs genes that have been currently reported, it is conceivable that many more lncRNAs might function as oncogenes or tumor suppressor genes. We devised a strategy to detect focal lncRNA SCNAs using a custom DNA microarray platform probing 10,519 lncRNA genes. By screening a panel of 80 cancer cell lines, we detected numerous focal aberrations targeting one or multiple lncRNAs without affecting neighboring protein-coding genes. These focal aberrations are highly suggestive for a tumor suppressive or oncogenic role of the targeted lncRNA gene. Although functional validation remains an essential step in the further characterization of the involved candidate cancer lncRNAs, our results provide a direct way of prioritizing candidate lncRNAs that are involved in cancer pathogenesis.

Measurable impact of RNA quality on gene expression results from quantitative PCR.

Compromised RNA quality is suggested to lead to unreliable results in gene expression studies. Therefore, assessment of RNA integrity and purity is deemed essential prior to including samples in the analytical pipeline. This may be of particular importance when diagnostic, prognostic or therapeutic conclusions depend on such analyses. In this study, the comparative value of six RNA quality parameters was determined using a large panel of 740 primary tumour samples for which real-time quantitative PCR gene expression results were available. The tested parameters comprise of microfluidic capillary electrophoresis based 18S/28S rRNA ratio and RNA Quality Index value, HPRT1 5'-3' difference in quantification cycle (Cq) and HPRT1 3' Cq value based on a 5'/3' ratio mRNA integrity assay, the Cq value of expressed Alu repeat sequences and a normalization factor based on the mean expression level of four reference genes. Upon establishment of an innovative analytical framework to assess impact of RNA quality, we observed a measurable impact of RNA quality on the variation of the reference genes, on the significance of differential expression of prognostic marker genes between two cancer patient risk groups, and on risk classification performance using a multigene signature. This study forms the basis for further rational assessment of reverse transcription quantitative PCR based results in relation to RNA quality.