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Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes

The development of breast cancer (BC) subtypes is controlled by distinct sets of candidate genes, and the expression of these genes is regulated by the binding of their mRNAs with miRNAs. Predicting miRNA associations and target genes is thus essential when studying breast cancer. The MirTarget prog...

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Autores principales: Aisina, Dana, Niyazova, Raigul, Atambayeva, Shara, Ivashchenko, Anatoliy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858813/
https://www.ncbi.nlm.nih.gov/pubmed/31741798
http://dx.doi.org/10.7717/peerj.8049
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author Aisina, Dana
Niyazova, Raigul
Atambayeva, Shara
Ivashchenko, Anatoliy
author_facet Aisina, Dana
Niyazova, Raigul
Atambayeva, Shara
Ivashchenko, Anatoliy
author_sort Aisina, Dana
collection PubMed
description The development of breast cancer (BC) subtypes is controlled by distinct sets of candidate genes, and the expression of these genes is regulated by the binding of their mRNAs with miRNAs. Predicting miRNA associations and target genes is thus essential when studying breast cancer. The MirTarget program identifies the initiation of miRNA binding to mRNA, the localization of miRNA binding sites in mRNA regions, and the free energy from the binding of all miRNA nucleotides with mRNA. Candidate gene mRNAs have clusters (miRNA binding sites with overlapping nucleotide sequences). mRNAs of EPOR, MAZ and NISCH candidate genes of the HER2 subtype have clusters, and there are four clusters in mRNAs of MAZ, BRCA2 and CDK6 genes. Candidate genes of the triple-negative subtype are targets for multiple miRNAs. There are 11 sites in CBL mRNA, five sites in MMP2 mRNA, and RAB5A mRNA contains two clusters in each of the three sites. In SFN mRNA, there are two clusters in three sites, and one cluster in 21 sites. Candidate genes of luminal A and B subtypes are targets for miRNAs: there are 21 sites in FOXA1 mRNA and 15 sites in HMGA2 mRNA. There are clusters of five sites in mRNAs of ITGB1 and SOX4 genes. Clusters of eight sites and 10 sites are identified in mRNAs of SMAD3 and TGFB1 genes, respectively. Organizing miRNA binding sites into clusters reduces the proportion of nucleotide binding sites in mRNAs. This overlapping of miRNA binding sites creates a competition among miRNAs for a binding site. From 6,272 miRNAs studied, only 29 miRNAs from miRBase and 88 novel miRNAs had binding sites in clusters of target gene mRNA in breast cancer. We propose using associations of miRNAs and their target genes as markers in breast cancer subtype diagnosis.
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spelling pubmed-68588132019-11-18 Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes Aisina, Dana Niyazova, Raigul Atambayeva, Shara Ivashchenko, Anatoliy PeerJ Bioinformatics The development of breast cancer (BC) subtypes is controlled by distinct sets of candidate genes, and the expression of these genes is regulated by the binding of their mRNAs with miRNAs. Predicting miRNA associations and target genes is thus essential when studying breast cancer. The MirTarget program identifies the initiation of miRNA binding to mRNA, the localization of miRNA binding sites in mRNA regions, and the free energy from the binding of all miRNA nucleotides with mRNA. Candidate gene mRNAs have clusters (miRNA binding sites with overlapping nucleotide sequences). mRNAs of EPOR, MAZ and NISCH candidate genes of the HER2 subtype have clusters, and there are four clusters in mRNAs of MAZ, BRCA2 and CDK6 genes. Candidate genes of the triple-negative subtype are targets for multiple miRNAs. There are 11 sites in CBL mRNA, five sites in MMP2 mRNA, and RAB5A mRNA contains two clusters in each of the three sites. In SFN mRNA, there are two clusters in three sites, and one cluster in 21 sites. Candidate genes of luminal A and B subtypes are targets for miRNAs: there are 21 sites in FOXA1 mRNA and 15 sites in HMGA2 mRNA. There are clusters of five sites in mRNAs of ITGB1 and SOX4 genes. Clusters of eight sites and 10 sites are identified in mRNAs of SMAD3 and TGFB1 genes, respectively. Organizing miRNA binding sites into clusters reduces the proportion of nucleotide binding sites in mRNAs. This overlapping of miRNA binding sites creates a competition among miRNAs for a binding site. From 6,272 miRNAs studied, only 29 miRNAs from miRBase and 88 novel miRNAs had binding sites in clusters of target gene mRNA in breast cancer. We propose using associations of miRNAs and their target genes as markers in breast cancer subtype diagnosis. PeerJ Inc. 2019-11-13 /pmc/articles/PMC6858813/ /pubmed/31741798 http://dx.doi.org/10.7717/peerj.8049 Text en ©2019 Aisina et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Aisina, Dana
Niyazova, Raigul
Atambayeva, Shara
Ivashchenko, Anatoliy
Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes
title Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes
title_full Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes
title_fullStr Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes
title_full_unstemmed Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes
title_short Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes
title_sort prediction of clusters of mirna binding sites in mrna candidate genes of breast cancer subtypes
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858813/
https://www.ncbi.nlm.nih.gov/pubmed/31741798
http://dx.doi.org/10.7717/peerj.8049
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