OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs

Wang, Dongfang; Gu, Jin; Wang, Ting; Ding, Zijian

doi:10.1093/bioinformatics/btu155

Cited by 139 publications

(77 citation statements)

References 18 publications

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“…The raccoon miRNAs from the tumor tissue samples were mapped to the mouse mature miRNA sequences build on miRBase (40-44), without allowing for any mismatches. To annotate each raccoon miRNA as an oncogene or a tumor suppressor, each miRNA was referenced to two independent databases, the OncomiRDB (45) and miRCancer (46). …”

Section: Methodsmentioning

confidence: 99%

Identification of a polyomavirus microRNA highly expressed in tumors

et al. 2015

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Polyomaviruses (PyVs) are associated with tumors including Merkel cell carcinoma (MCC). Several PyVs encode microRNAs (miRNAs) but to date no abundant PyV miRNAs have been reported in tumors. To better understand the function of the Merkel cell PyV (MCPyV) miRNA, we examined phylogenetically-related viruses for miRNA expression. We show that two primate PyVs and the more distantly-related raccoon PyV (RacPyV) encode miRNAs that share genomic position and partial sequence identity with MCPyV miRNAs. Unlike MCPyV miRNA in MCC, RacPyV miRNA is highly abundant in raccoon tumors. RacPyV miRNA negatively regulates reporters of early viral (T antigen) transcripts, yet robust viral miRNA expression is tolerated in tumors. We also identify raccoon miRNAs expressed in RacPyV-associated neuroglial brain tumors, including several likely oncogenic miRNAs (oncomiRs). This work describes the first PyV miRNA abundantly expressed in tumors and is consistent with a possible role for both host and viral miRNAs in RacPyV-associated tumors.

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Section: Methodsmentioning

confidence: 99%

Identification of a polyomavirus microRNA highly expressed in tumors

et al. 2015

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“…(1) SE loss in over 2 cancer types, (2) SE gain in over 2 cancer types, (3) complex pattern: gain or loss in multiple cancer types, (4) relatively specific loss, and (5) specific gain of SE around miRNA genes (Figure 7A). By analyzing a database for the experimentally verified oncogenic and tumor-suppressive miRNAs (Wang et al, 2014a), miRNAs with SE gain in cancer cells were biased toward miRNAs with oncogenic roles, and SE loss correlated with tumor-suppressive miRNAs (Figure 7B). These changes included SE loss for miR-9 in glioblastoma cells, which is brain-specific and decreases during glioblastoma progression (Kim et al, 2011) (Figure S7A), and SE loss for miR-15a/16-1, a tumor suppressive miRNAs, observed in multiple cancer cells with hematopoietic malignancies (Figure S7B).…”

Section: Resultsmentioning

confidence: 99%

Super-Enhancer-Mediated RNA Processing Revealed by Integrative MicroRNA Network Analysis

Suzuki

Young

Sharp

2017

Cell

238

264

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Summary Super-enhancers are an emerging sub-class of regulatory regions controlling cell identity and disease genes. However, their biological function and impact on miRNA networks are unclear. Here we report that super-enhancers drive the biogenesis of master miRNAs crucial for cell identity by enhancing both transcription and Drosha/DGCR8-mediated primary miRNA (pri-miRNA) processing. Super-enhancers, together with broad H3K4me3 domains, shape a tissue-specific and evolutionarily conserved atlas of miRNA expression and function. CRISPR/Cas9 genomics revealed that super-enhancer constituents act cooperatively and facilitate Drosha/DGCR8 recruitment and pri-miRNA processing to boost cell-specific miRNA production. The BET-bromodomain inhibitor JQ1 preferentially inhibits super-enhancer-directed cotranscriptional pri-miRNA processing. Furthermore, super-enhancers are characterized by pervasive interaction with DGCR8/Drosha and DGCR8/Drosha-regulated mRNA stability control, suggesting unique RNA regulation at super-enhancers. Finally, super-enhancers mark multiple miRNAs associated with cancer hallmarks. This study presents principles underlying miRNA biology in health and disease and a unrecognized higher-order property of super-enhancers in RNA processing beyond transcription.

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“…On the other side, unbalanced expression of miRNAs triggering compensatory β-cell mass expansion may also be inappropriate. In fact, many of these miRNAs are oncomiRs and are deregulated in several forms of cancers [59]. Thus, in the absence of a counteracting effect, these miRNAs can potentially trigger uncontrolled proliferation of insulin-secreting cells and favor the development of insulinomas.…”

Section: Discussionmentioning

confidence: 99%

MicroRNAs and the functional β cell mass: For better or worse

Guay

Regazzi

2015

Diabetes & Metabolism

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Insulin secretion from pancreatic β-cells plays a central role in the control of blood glucose levels. The amount of insulin released by β-cells is precisely adjusted to match the organism requirements. A number of conditions occurring during life, including pregnancy and obesity, can result in a decrease in the sensitivity of insulin target tissues and in the consequent rise in the insulin needs. To preserve glucose homeostasis, the augmented insulin demand requires a compensatory expansion of the mass of pancreatic β-cells and an increase in their secretory activity. This compensatory process is known to be accompanied by modifications in β-cell gene expression but the molecular mechanisms underlying this phenomenon are still poorly understood. Emerging evidence indicate that at least part of these compensatory events may be orchestrated by changes in the level of a novel class of gene regulators, the microRNAs.Indeed, several of these small non-coding RNAs have either positive or negative impacts on β-cell proliferation and survival. The studies reviewed in this paper suggest that the balance between the actions of these two groups of microRNAs with opposing functional effects determines whether β-cells expand sufficiently to maintain blood glucose levels in the normal range or fail to meet the insulin demand with a consequent progression toward diabetes manifestation. A better understanding of the mechanisms governing the changes in the microRNA profile will open the way for the development of new strategies to prevent and/or treat type 2 and gestational diabetes.

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OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 139 publications

References 18 publications

Identification of a polyomavirus microRNA highly expressed in tumors

Identification of a polyomavirus microRNA highly expressed in tumors

Super-Enhancer-Mediated RNA Processing Revealed by Integrative MicroRNA Network Analysis

MicroRNAs and the functional β cell mass: For better or worse

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