Accurate microRNA target prediction correlates with protein repression levels

Maragkakis, Manolis; Alexiou, Panagiotis; Papadopoulos, Giorgio L.; Reczko, Martin; Dalamagas, Theodore; Giannopoulos, Giorgos; Goumas, George I.; Koukis, E.; Kourtis, Kornilios; Simossis, Victor A.; Sethupathy, Praveen; Vergoulis, Thanasis; Koziris, Nectarios; Sellis, Timos; Tsanakas, Panayiotis; Hatzigeorgiou, Artemis G.

doi:10.1186/1471-2105-10-295

Cited by 316 publications

(254 citation statements)

References 26 publications

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“…Moreover, multiple small RNA sequences are often missed due to technical difficulties of the sequencing methodology such as library construction. Experimental verification for all tools, in accordance to previous data, 10 however it should be noted that these statistics are irrespective of the use of conservation as a filtering criterion, which is frequently utilized to boost performance of target prediction classifiers (see below).…”

Section: Resultsmentioning

confidence: 58%

“…[7][8][9] In order to provide an estimation of a false positive rate, false or mock miRNAs are often generated by randomly shuffling the nucleotide sequence of experimentally supported miRNAs. 10 Performing target prediction with these mock miRNAs can provide an estimation of the overall false positive rate of a miRNA target prediction tool. of miRNA targets can be achieved via the use of luciferase assays whereby the miRNA is expressed in vitro while simultaneously expressing and monitoring the target mRNA linked to a luciferase reporter gene.…”

Section: Introductionmentioning

confidence: 99%

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A new microRNA target prediction tool identifies a novel interaction of a putative miRNA with CCND2

et al. 2012

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Section: Resultsmentioning

confidence: 58%

Section: Introductionmentioning

confidence: 99%

A new microRNA target prediction tool identifies a novel interaction of a putative miRNA with CCND2

et al. 2012

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“…DIANA-MicroT yields a final score named miTG via integrating data on conserved and non-conserved 3'UTR of the target gene (16). The highest miTG was derived for miR-330-3p (6.4), followed by miR-142-5p (3.1).…”

Section: Analysis Of Data According To Diana-microtmentioning

confidence: 99%

BMI1 as a Potential Target of miR-330-3p in Colorectal Cancer

Soheilifar

Moshtaghian

Amini

et al. 2018

Middle East J Rehabil Health Stud

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Background: Colorectal cancer (CRC) is one of the most common cancers worldwide. CRC therapy is still a serious problem because of the presence of cancer stem cells (CSCs) within the tumor. BMI1 (B lymphoma Mo-MLV insertion region 1 homolog) is one of the important molecules for self-renewal of the CSCs and a component of poly comb repressive complex 1 that plays an important role in stimulating the progression of the cell cycle through epigenetic inhibition of tumor suppressors. BMI1 is a marker of colon stem cells that its expression increases in colorectal CSCs. The inhibition of BMI1 expression by miRNA could be one of the promising treatment options in CRC. Furthermore, investigating the regulation of BMI1 expression by miRNAs during tumorigenesis could be valuable in the identification of molecular mechanisms involved in CRC. Our aim was to conduct a bioinformatics analysis of known tumor suppressor miRNAs in CRC that have a potential to inhibit BMI1 expression. Methods:The presence of BMI-1, as a potential target of the selected miRNAs, was explored in various databases of miRNA target prediction including TargetScan, DIANA-microT, PicTar, miRanada, miRtar, mirMAP, and miRDB. These databases are based on algorithms such as miRNA-target interactions and thermodynamic stability (∆G). miRNA with the highest score was selected according to the prediction score. Results: According to bioinformatics analysis, the highest score was derived for miR-330-3p. As a new miRNA to suppress BMI-1, miR-330-3p can be used in applied studies. Conclusions: Compared to other tumor suppressor miRNAs in CRC, miR-330-3p has the greatest probability to inhibit BMI1. Therefore, the experimental validation of miR-330-3p/BMI1 axis would be useful in identifying novel therapeutics and biomarkers in CRC.

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“…The most Nowadays, multiple miR target prediction algorithms are developed based on different criteria such as target conservation, seed-target complementarity, seed pairing stability, free energy of duplex, etc. [99][100][101][102][103][104][105][106] . We decided to use the ComiRNet database of predicted miR regulatory network 107) to search for the potential targets of our miRs in the CXCL16 3´ UTR sequence.…”

Section: -2 Cxcl16 and Micrornamentioning

confidence: 99%

CXCL16 in Vascular Pathology Research: from Macro Effects to microRNAs

Jovanović

Živković

Djurić

et al. 2015

J Atheroscler Thromb

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Chemokines and their receptors have become significant factors in atherosclerosis research. CXCL16 is a multifunctional agent located on a separate locus to all other known chemokines and binds only to its "unique" receptor named CXCR6. As a scavenger receptor, adhesion molecule, and chemokine, it quickly became an interesting target in atherosclerosis research as all its functions have a role in vascular pathology. The investigation of the role of CXCL16 in atherosclerosis, although shown in in vitro studies, animal knockout models, and CXCL16 gene polymorphisms, haplotypes, and circulating levels, still shows puzzling results. Genetic and epigenetic studies have just scratched the surface of research necessary for a better assessment of the significance and perspective of this marker in plaque development and progression. In this review, we will summarize current knowledge about CXCL16 in atherosclerosis. Additionally, we will point out the importance of bioinformatics tools for the detection of potentially new CXCL16 regulatory networks through microRNA activity. This review aims to provide a better understanding of the underlying mechanisms, define more specific biomarkers, and discover new therapeutic targets.

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Accurate microRNA target prediction correlates with protein repression levels

Cited by 316 publications

References 26 publications

A new microRNA target prediction tool identifies a novel interaction of a putative miRNA with CCND2

A new microRNA target prediction tool identifies a novel interaction of a putative miRNA with CCND2

BMI1 as a Potential Target of miR-330-3p in Colorectal Cancer

CXCL16 in Vascular Pathology Research: from Macro Effects to microRNAs

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