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.
Recurrent chromosomal aberrations have led to the discovery of oncogenes or tumour suppressors involved in carcinogenesis. Here we characterized an oncogenic long intergenic non-coding RNA in the frequent DNA-gain regions in hepatocellular carcinoma (HCC), LINC01138 (long intergenic non-coding RNA located on 1q21.2). The LINC01138 locus is frequently amplified in HCC; the LINC01138 transcript is stabilized by insulin like growth factor-2 mRNA-binding proteins 1/3 (IGF2BP1/IGF2BP3) and is associated with the malignant features and poor outcomes of HCC patients. LINC01138 acts as an oncogenic driver that promotes cell proliferation, tumorigenicity, tumour invasion and metastasis by physically interacting with arginine methyltransferase 5 (PRMT5) and enhancing its protein stability by blocking ubiquitin/proteasome-dependent degradation in HCC. The discovery of LINC01138, a promising prognostic indicator, provides insight into the molecular pathogenesis of HCC, and the LINC01138/PRMT5 axis is an ideal therapeutic target for HCC treatment.
Human cancer cell lines are fundamental models for cancer research and therapeutic strategy development. However, there is no characterization of circular RNAs (circRNAs) in a large number of cancer cell lines. Here, we apply four circRNA identification algorithms to heuristically characterize the expression landscape of circRNAs across ~ 1000 human cancer cell lines from CCLE polyA-enriched RNA-seq data. By using integrative analysis and experimental approaches, we explore the expression landscape, biogenesis, functional consequences, and drug response of circRNAs across different cancer lineages. We revealed highly lineage-specific expression patterns of circRNAs, suggesting that circRNAs may be powerful diagnostic and/or prognostic markers in cancer treatment. We also identified key genes involved in circRNA biogenesis and confirmed that TGF-β signaling may promote biogenesis of circRNAs. Strikingly, we showed that clinically actionable genes are more likely to generate circRNAs, potentially due to the enrichment of RNA-binding protein (RBP) binding sites. Among these, circMYC can promote cell proliferation. We observed strong association between the expression of circRNAs and the response to drugs, especially those targeting chromatin histone acetylation. Finally, we developed a user-friendly data portal, CircRNAs in cancer cell lines (CircRiC, https://hanlab.uth.edu/cRic ), to benefit the biomedical research community. Our study provides the characterization of circRNAs in cancer cell lines and explored the potential mechanism of circRNA biogenesis as well as its therapeutic implications. We also provide a data portal to facilitate the related biomedical researches.
Cervical cancer (CC) is the fourth leading cause of deaths in gynecological malignancies. Although the etiology of CC has been extensively investigated, the exact pathogenesis of CC remains incomplete. Recently, single-cell technologies demonstrated advantages in exploring intra-tumoral diversification among various tumor cells. However, single-cell transcriptome analysis (single-cell RNA sequencing [scRNA-seq]) of CC cells and microenvironment has not been conducted. In this study, a total of 20,938 cells from CC and adjacent normal tissues were examined by scRNA-seq. We identified four tumor cell subpopulations in tumor cells, which had specific signature genes with different biological functions and presented different prognoses. Among them, we identified a subset of cancer stem cells (CSCs) that was related to the developmental hierarchy of tumor progression. Then, we compared the expressive differences between tumor-derived endothelial cells (TECs) and normal ECs (NECs) and revealed higher expression of several metabolism-related genes in TECs. Then, we explored the potential biological function of ECs in vascularization and found several marker genes, which played a prior role in connections between cancer cells and ECs. Our findings provide valuable resources for deciphering the intra-tumoral heterogeneity of CC and uncover the developmental procedure of ECs, which paves the way for CC therapy.