The database of experimentally supported targets: a functional update of TarBase

MicroRNAs (miRNAs) are a class of small RNAs that play a critical role in the coordination of fundamental cellular processes. Recent studies suggest that miRNAs participate in the cellular stress response (CSR), but their specific involvement remains unclear. In this study, we identify a group of thermally regulated miRNAs (TRMs) that are associated with the CSR. Using miRNA microarrays, we show that dermal fibroblasts differentially express 123 miRNAs when exposed to hyperthermia. Interestingly, only 27 of these miRNAs are annotated in the current Sanger registry. We validated the expression of the annotated miRNAs using qPCR techniques, and we found that the qPCR and microarray data was in well agreement. Computational target-prediction studies revealed that putative targets for the TRMs are heat shock proteins and Argonaute-2-the core functional unit of RNA silencing. These results indicate that cells express a specific group of miRNAs when exposed to hyperthermia, and these miRNAs may function in the regulation of the CSR. Future studies will be conducted to determine if other cells lines differentially express these miRNAs when exposed to hyperthermia.

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“…The last tool we used was the Tarbase database. This database is a collection of empirically validated targets (Papadopoulos et al 2009).…”

Section: Resultsmentioning

confidence: 99%

Identification of microRNAs associated with hyperthermia-induced cellular stress response

Wilmink

Roth

Ibey

et al. 2010

Cell Stress and Chaperones

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“…Prior to the present study, the data regarding adenocarcinoma was scattered across various databases, including TransmiR (13), computational predicted methods (42), experimentally validated databases (15,16), miRBase (17), the KEGG pathway database (18), the miR2Disease database (19), the GeneCards database (20) and numerous relevant studies (13,(17)(18)(19)(20). The analysis and use of this data is challenging.…”

Section: Discussionmentioning

confidence: 99%

“…It has also been demonstrated that TFs and miRNA may regulate genes (8) and miRNA may regulate target genes (10). In addition, the data of numerous studies have been combined to form various databases, including TransmiR (13), computational predicted methods (14), experimentally validated databases (15,16), miRBase (17), the KEGG pathway database (18), the miR2Disease database (19) and the GeneCards database (20). In these databases, a large amount of data may be found, which was the basis for the present study.…”

Section: Introductionmentioning

confidence: 99%

Construction and analysis of three networks of genes and microRNAs in adenocarcinoma

et al. 2015

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Abstract. Adenocarcinoma is one of the most serious diseases that threaten human health. Numerous studies have investigated adenocarcinoma and have obtained a considerable amount of data regarding genes and microRNA (miRNA) in adenocarcinoma. However, studies have only focused on one or a small number of genes and miRNAs, and the data is stored in a scattered form, making it challenging to summarize and assess the associations between the genes and miRNAs. In the present study, three networks of genes and miRNAs in adenocarcinoma were focused on. This enabled the construction of networks of elements involved in adenocarcinoma and the analysis of these networks, rather than only discussing one gene. Transcription factors (TFs), miRNAs, and target and host genes of miRNAs in adenocarcinoma, and the regulatory associations between these elements were identified in the present study. These elements and associations were then used to construct three networks, which consisted of the differentially-expressed, associated and global networks. The similarities and differences between the three networks were compared and analyzed. In total, 3 notable TFs, consisting of TP53, phosphatase and tensin homolog and SMAD4, were identified in adenocarcinoma. These TFs were able to regulate the differentially-expressed genes and the majority of the differentially-expressed miRNAs. Certain important regulatory associations were also found in adenocarcinoma, in addition to self-regulating associations between TFs and miRNAs. The upstream and downstream elements of the differentially-expressed genes and miRNAs were recorded, which revealed the regulatory associations between genes and miRNAs. The present study clearly revealed components of the pathogenesis of adenocarcinoma and the regulatory associations between the elements in adenocarcinoma. The present study may aid the investigation of gene therapy in adenocarcinoma and provides a theoretical basis for studies of gene therapy methods as a treatment for adenocarcinoma.

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“…These target genes (targets) are important to uncover the biological role of miRNAs. Numerous databases, including computational method (Betel et al, 2008) and experimentally validated databases (Papadopoulos et al, 2009), supply enough resource to study relations between miRNAs and their targets. MiRNAs locate inside of many genes that are named their host genes.…”

Section: Introductionmentioning

confidence: 99%

Complex Regulatory Network of MicroRNAs, Transcription Factors, Gene Alterations in Adrenocortical Cancer

Zhang

Xu²,

Wang³

et al. 2013

Asian Pacific Journal of Cancer Prevention

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Several lines of evidence indicate that cancer is a multistep process. To survey the mechanisms involving gene alteration and miRNAs in adrenocortical cancer, we focused on transcriptional factors as a point of penetration to build a regulatory network. We derived three level networks: differentially expressed; related; and global. A topology network ws then set up for development of adrenocortical cancer. In this network, we found that some pathways with differentially expressed elements (genetic and miRNA) showed some self-adaption relations, such as EGFR. The differentially expressed elements partially uncovered mechanistic changes for adrenocortical cancer which should guide medical researchers to further achieve pertinent research.

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The database of experimentally supported targets: a functional update of TarBase

Cited by 374 publications

References 19 publications

Identification of microRNAs associated with hyperthermia-induced cellular stress response

Identification of microRNAs associated with hyperthermia-induced cellular stress response

Construction and analysis of three networks of genes and microRNAs in adenocarcinoma

Complex Regulatory Network of MicroRNAs, Transcription Factors, Gene Alterations in Adrenocortical Cancer

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