Circular RNAs (circRNAs) represent a class of widespread and diverse endogenous RNAs that may regulate gene expression in eukaryotes. However, the regulation and function of human circRNAs remain largely unknown. Here we generate ribosomal-depleted RNA sequencing data from six normal tissues and seven cancers, and detect at least 27,000 circRNA candidates. Many of these circRNAs are differently expressed between the normal and cancerous tissues. We further characterize one abundant circRNA derived from Exon2 of the HIPK3 gene, termed circHIPK3. The silencing of circHIPK3 but not HIPK3 mRNA significantly inhibits human cell growth. Via a luciferase screening assay, circHIPK3 is observed to sponge to 9 miRNAs with 18 potential binding sites. Specifically, we show that circHIPK3 directly binds to miR-124 and inhibits miR-124 activity. Our results provide evidence that circular RNA produced from precursor mRNA may have a regulatory role in human cells.

Exosomes, which are nanosized endocytic vesicles that are secreted by most cells, contain an abundant cargo of different RNA species that can modulate the behavior of recipient cells and may be used as circulating biomarkers for diseases. Here, we develop a web-accessible database (http://www.exoRBase.org), exoRBase, which is a repository of circular RNA (circRNA), long non-coding RNA (lncRNA) and messenger RNA (mRNA) derived from RNA-seq data analyses of human blood exosomes. Experimental validations from the published literature are also included. exoRBase features the integration and visualization of RNA expression profiles based on normalized RNA-seq data spanning both normal individuals and patients with different diseases. exoRBase aims to collect and characterize all long RNA species in human blood exosomes. The first release of exoRBase contains 58 330 circRNAs, 15 501 lncRNAs and 18 333 mRNAs. The annotation, expression level and possible original tissues are provided. exoRBase will aid researchers in identifying molecular signatures in blood exosomes and will trigger new exosomal biomarker discovery and functional implication for human diseases.

BACKGROUND: Extracellular vesicles (EVs) contain a rich cargo of different RNA species with specialized functions and clinical applications. However, the landscape and characteristics of extracellular vesicle long RNA (exLR) in human blood remain largely unknown. METHODS: We presented an optimized strategy for exLR sequencing (exLR-seq) of human plasma. The sample cohort included 159 healthy individuals, 150 patients with cancer (5 cancer types), and 43 patients with other diseases. Bioinformatics approaches were used to analyze the distribution and features of exLRs. Support vector machine algorithm was performed to construct the diagnosis classifier, and diagnostic efficiency was evaluated by ROC analysis. RESULTS: More than 10000 exLRs, including mRNA, circRNA, and lncRNA, were reliably detected in each exLR-seq sample from 1–2 mL of plasma. We observed that blood EVs contain a substantial fraction of intact mRNAs and a large number of assembling spliced junctions; circRNA was also enriched in blood EVs. Interestingly, blood exLRs reflected their tissue origins and the relative fractions of different immune cell types. Additionally, the exLR profile could distinguish patients with cancer from healthy individuals. We further showed that 8 exLRs can serve as biomarkers for hepatocellular carcinoma (HCC) diagnosis with high diagnostic efficiency in training [area under the curve (AUC) = 0.9527; 95% CI, 0.9170–0.9883], validation cohort (AUC = 0.9825; 95% CI, 0.9606–1), and testing cohort (AUC = 0.9627; 95% CI, 0.9263–0.9991). CONCLUSIONS: In summary, this study revealed abundant exLRs in human plasma and identified diverse specific markers potentially useful for cancer diagnosis.