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Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors

BACKGROUND: The understanding of the molecular biology of pediatric neuronal and mixed neuronal-glial brain tumors is still insufficient due to low frequency and heterogeneity of those lesions which comprise several subtypes presenting neuronal and/or neuronal-glial differentiation. Important is tha...

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Autores principales: Zakrzewska, Magdalena, Gruszka, Renata, Stawiski, Konrad, Fendler, Wojciech, Kordacka, Joanna, Grajkowska, Wiesława, Daszkiewicz, Paweł, Liberski, Paweł P., Zakrzewski, Krzysztof
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555720/
https://www.ncbi.nlm.nih.gov/pubmed/31170943
http://dx.doi.org/10.1186/s12885-019-5739-5
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author Zakrzewska, Magdalena
Gruszka, Renata
Stawiski, Konrad
Fendler, Wojciech
Kordacka, Joanna
Grajkowska, Wiesława
Daszkiewicz, Paweł
Liberski, Paweł P.
Zakrzewski, Krzysztof
author_facet Zakrzewska, Magdalena
Gruszka, Renata
Stawiski, Konrad
Fendler, Wojciech
Kordacka, Joanna
Grajkowska, Wiesława
Daszkiewicz, Paweł
Liberski, Paweł P.
Zakrzewski, Krzysztof
author_sort Zakrzewska, Magdalena
collection PubMed
description BACKGROUND: The understanding of the molecular biology of pediatric neuronal and mixed neuronal-glial brain tumors is still insufficient due to low frequency and heterogeneity of those lesions which comprise several subtypes presenting neuronal and/or neuronal-glial differentiation. Important is that the most frequent ganglioglioma (GG) and dysembryoplastic neuroepithelial tumor (DNET) showed limited number of detectable molecular alterations. In such cases analyses of additional genomic mechanisms seem to be the most promising. The aim of the study was to evaluate microRNA (miRNA) profiles in GGs, DNETs and pilocytic asytrocytomas (PA) and test the hypothesis of plausible miRNA connection with histopathological subtypes of particular pediatric glial and mixed glioneronal tumors. METHODS: The study was designed as the two-stage analysis. Microarray testing was performed with the use of the miRCURY LNA microRNA Array technology in 51 cases. Validation set comprised 107 samples used during confirmation of the profiling results by qPCR bioinformatic analysis. RESULTS: Microarray data was compared between the groups using an analysis of variance with the Benjamini-Hochberg procedure used to estimate false discovery rates. After filtration 782 miRNAs were eligible for further analysis. Based on the results of 10 × 10-fold cross-validation J48 algorithm was identified as the most resilient to overfitting. Pairwise comparison showed the DNETs to be the most divergent with the largest number of miRNAs differing from either of the two comparative groups. Validation of array analysis was performed for miRNAs used in the classification model: miR-155-5p, miR-4754, miR-4530, miR-628-3p, let-7b-3p, miR-4758-3p, miRPlus-A1086 and miR-891a-5p. Model developed on their expression measured by qPCR showed weighted AUC of 0.97 (95% CI for all classes ranging from 0.91 to 1.00). A computational analysis was used to identify mRNA targets for final set of selected miRNAs using miRWalk database. Among genomic targets of selected molecules ZBTB20, LCOR, PFKFB2, SYNJ2BP and TPD52 genes were noted. CONCLUSIONS: Our data showed the existence of miRNAs which expression is specific for different histological types of tumors. miRNA expression analysis may be useful in in-depth molecular diagnostic process of the tumors and could elucidate their origins and molecular background. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-019-5739-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-65557202019-06-10 Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors Zakrzewska, Magdalena Gruszka, Renata Stawiski, Konrad Fendler, Wojciech Kordacka, Joanna Grajkowska, Wiesława Daszkiewicz, Paweł Liberski, Paweł P. Zakrzewski, Krzysztof BMC Cancer Research Article BACKGROUND: The understanding of the molecular biology of pediatric neuronal and mixed neuronal-glial brain tumors is still insufficient due to low frequency and heterogeneity of those lesions which comprise several subtypes presenting neuronal and/or neuronal-glial differentiation. Important is that the most frequent ganglioglioma (GG) and dysembryoplastic neuroepithelial tumor (DNET) showed limited number of detectable molecular alterations. In such cases analyses of additional genomic mechanisms seem to be the most promising. The aim of the study was to evaluate microRNA (miRNA) profiles in GGs, DNETs and pilocytic asytrocytomas (PA) and test the hypothesis of plausible miRNA connection with histopathological subtypes of particular pediatric glial and mixed glioneronal tumors. METHODS: The study was designed as the two-stage analysis. Microarray testing was performed with the use of the miRCURY LNA microRNA Array technology in 51 cases. Validation set comprised 107 samples used during confirmation of the profiling results by qPCR bioinformatic analysis. RESULTS: Microarray data was compared between the groups using an analysis of variance with the Benjamini-Hochberg procedure used to estimate false discovery rates. After filtration 782 miRNAs were eligible for further analysis. Based on the results of 10 × 10-fold cross-validation J48 algorithm was identified as the most resilient to overfitting. Pairwise comparison showed the DNETs to be the most divergent with the largest number of miRNAs differing from either of the two comparative groups. Validation of array analysis was performed for miRNAs used in the classification model: miR-155-5p, miR-4754, miR-4530, miR-628-3p, let-7b-3p, miR-4758-3p, miRPlus-A1086 and miR-891a-5p. Model developed on their expression measured by qPCR showed weighted AUC of 0.97 (95% CI for all classes ranging from 0.91 to 1.00). A computational analysis was used to identify mRNA targets for final set of selected miRNAs using miRWalk database. Among genomic targets of selected molecules ZBTB20, LCOR, PFKFB2, SYNJ2BP and TPD52 genes were noted. CONCLUSIONS: Our data showed the existence of miRNAs which expression is specific for different histological types of tumors. miRNA expression analysis may be useful in in-depth molecular diagnostic process of the tumors and could elucidate their origins and molecular background. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-019-5739-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-06 /pmc/articles/PMC6555720/ /pubmed/31170943 http://dx.doi.org/10.1186/s12885-019-5739-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zakrzewska, Magdalena
Gruszka, Renata
Stawiski, Konrad
Fendler, Wojciech
Kordacka, Joanna
Grajkowska, Wiesława
Daszkiewicz, Paweł
Liberski, Paweł P.
Zakrzewski, Krzysztof
Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors
title Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors
title_full Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors
title_fullStr Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors
title_full_unstemmed Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors
title_short Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors
title_sort expression-based decision tree model reveals distinct microrna expression pattern in pediatric neuronal and mixed neuronal-glial tumors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555720/
https://www.ncbi.nlm.nih.gov/pubmed/31170943
http://dx.doi.org/10.1186/s12885-019-5739-5
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