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      Integrated analysis of colorectal cancer microRNA datasets: identification of microRNAs associated with tumor development

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          Abstract

          Colorectal cancer (CRC) is one of the leading cause of cancer death worldwide. Currently, no effective early diagnostic biomarkers are available for colorectal carcinoma. Therefore, there is a need to discover new molecules able to identify pre-cancerous lesions. Recently, microRNAs (miRNAs) have been associated with the onset of specific pathologies, thus the identification of miRNAs associated to colorectal cancer may be used to detect this pathology at early stages. On these bases, the expression levels of miRNAs were analyzed to compare the miRNAs expression levels of colorectal cancer samples and normal tissues in several miRNA datasets. This analysis revealed a group of 19 differentially expressed miRNAs. To establish the interaction between miRNAs and the most altered genes in CRC, the mirDIP gene target analysis was performed in such group of 19 differentially expressed miRNAs. To recognize miRNAs able to activate or inhibit genes and pathways involved in colorectal cancer development DIANA-mirPath prediction analysis was applied. Overall, these analyses showed that the up-regulated hsa-miR-183-5p and hsa-miR-21-5p, and the down-regulated hsa-miR-195-5p and hsa-miR-497-5p were directly related to colorectal cancer through the interaction with the Mismatch Repair pathway and Wnt, RAS, MAPK, PI3K, TGF-β and p53 signaling pathways involved in cancer development.

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          Most cited references45

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          DIANA-TarBase v7.0: indexing more than half a million experimentally supported miRNA:mRNA interactions

          microRNAs (miRNAs) are short non-coding RNA species, which act as potent gene expression regulators. Accurate identification of miRNA targets is crucial to understanding their function. Currently, hundreds of thousands of miRNA:gene interactions have been experimentally identified. However, this wealth of information is fragmented and hidden in thousands of manuscripts and raw next-generation sequencing data sets. DIANA-TarBase was initially released in 2006 and it was the first database aiming to catalog published experimentally validated miRNA:gene interactions. DIANA-TarBase v7.0 (http://www.microrna.gr/tarbase) aims to provide for the first time hundreds of thousands of high-quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. DIANA-TarBase v7.0 enables users to easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments. More than half a million miRNA:gene interactions have been curated from published experiments on 356 different cell types from 24 species, corresponding to 9- to 250-fold more entries than any other relevant database. DIANA-TarBase v7.0 is freely available.
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            mirDIP 4.1—integrative database of human microRNA target predictions

            Abstract MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA–target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA–target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA–target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.
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              Human colon cancer profiles show differential microRNA expression depending on mismatch repair status and are characteristic of undifferentiated proliferative states

              Background Colon cancer arises from the accumulation of multiple genetic and epigenetic alterations to normal colonic tissue. microRNAs (miRNAs) are small, non-coding regulatory RNAs that post-transcriptionally regulate gene expression. Differential miRNA expression in cancer versus normal tissue is a common event and may be pivotal for tumor onset and progression. Methods To identify miRNAs that are differentially expressed in tumors and tumor subtypes, we carried out highly sensitive expression profiling of 735 miRNAs on samples obtained from a statistically powerful set of tumors (n = 80) and normal colon tissue (n = 28) and validated a subset of this data by qRT-PCR. Results Tumor specimens showed highly significant and large fold change differential expression of the levels of 39 miRNAs including miR-135b, miR-96, miR-182, miR-183, miR-1, and miR-133a, relative to normal colon tissue. Significant differences were also seen in 6 miRNAs including miR-31 and miR-592, in the direct comparison of tumors that were deficient or proficient for mismatch repair. Examination of the genomic regions containing differentially expressed miRNAs revealed that they were also differentially methylated in colon cancer at a far greater rate than would be expected by chance. A network of interactions between these miRNAs and genes associated with colon cancer provided evidence for the role of these miRNAs as oncogenes by attenuation of tumor suppressor genes. Conclusion Colon tumors show differential expression of miRNAs depending on mismatch repair status. miRNA expression in colon tumors has an epigenetic component and altered expression that may reflect a reversion to regulatory programs characteristic of undifferentiated proliferative developmental states.
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                Author and article information

                Journal
                Aging (Albany NY)
                Aging (Albany NY)
                Aging
                Aging (Albany NY)
                Impact Journals
                1945-4589
                May 2018
                18 May 2018
                : 10
                : 5
                : 1000-1014
                Affiliations
                [1 ]Department of Biomedical and Biotechnological Sciences, University of Catania , Catania, 95123, Italy
                [2 ]Department of Pathobiology and Medical Biotechnologies, University of Palermo , Palermo, 90127, Italy
                [3 ]Department of Medical and Surgical Sciences and Advanced Technology "G.F. Ingrassia", University of Catania , Catania, 95125, Italy
                [4 ]Department of General Surgery, Vittorio Emanuele Hospital, University of Catania , Catania, 95124, Italy
                [5 ]Research Center for Prevention, Diagnosis and Treatment of Cancer (PreDiCT), University of Catania , Catania, 95123, Italy
                [* ]Equal contribution
                Author notes
                Correspondence to: Massimo Libra; email: mlibra@ 123456unict.it
                Article
                101444
                10.18632/aging.101444
                5990389
                29779016
                9493766b-2c92-4a1e-840c-9a708340eb41
                Copyright © 2018 Falzone et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 04 April 2018
                : 07 May 2018
                Categories
                Research Paper

                Cell biology
                colorectal cancer,microrna,bioinformatics,dataset,biomarker
                Cell biology
                colorectal cancer, microrna, bioinformatics, dataset, biomarker

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