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MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model
Acute myeloid leukemia (AML) in children is a complex and heterogeneous disease. The identification of reliable and stable molecular biomarkers for diagnosis, especially early diagnosis, remains a significant therapeutic challenge. Aberrant microRNA expression could be used for cancer diagnosis and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4694912/ https://www.ncbi.nlm.nih.gov/pubmed/26317787 |
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author | Yan, Wenying Xu, Lihua Sun, Zhandong Lin, Yuxin Zhang, Wenyu Chen, Jiajia Hu, Shaoyan Shen, Bairong |
author_facet | Yan, Wenying Xu, Lihua Sun, Zhandong Lin, Yuxin Zhang, Wenyu Chen, Jiajia Hu, Shaoyan Shen, Bairong |
author_sort | Yan, Wenying |
collection | PubMed |
description | Acute myeloid leukemia (AML) in children is a complex and heterogeneous disease. The identification of reliable and stable molecular biomarkers for diagnosis, especially early diagnosis, remains a significant therapeutic challenge. Aberrant microRNA expression could be used for cancer diagnosis and treatment selection. Here, we describe a novel bioinformatics model for the prediction of microRNA biomarkers for the diagnosis of paediatric AML based on computational functional analysis of the microRNA regulatory network substructure. microRNA-196b, microRNA-155 and microRNA-25 were identified as putative diagnostic biomarkers for pediatric AML. Further systematic analysis confirmed the association of the predicted microRNAs with the leukemogenesis of AML. In vitro q-PCR experiments showed that microRNA-155 is significantly overexpressed in children with AML and microRNA-196b is significantly overexpressed in subgroups M4–M5 of the French-American-British classification system. These results suggest that microRNA-155 is a potential diagnostic biomarker for all subgroups of paediatric AML, whereas microRNA-196b is specific for subgroups M4–M5. |
format | Online Article Text |
id | pubmed-4694912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-46949122016-01-20 MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model Yan, Wenying Xu, Lihua Sun, Zhandong Lin, Yuxin Zhang, Wenyu Chen, Jiajia Hu, Shaoyan Shen, Bairong Oncotarget Research Paper Acute myeloid leukemia (AML) in children is a complex and heterogeneous disease. The identification of reliable and stable molecular biomarkers for diagnosis, especially early diagnosis, remains a significant therapeutic challenge. Aberrant microRNA expression could be used for cancer diagnosis and treatment selection. Here, we describe a novel bioinformatics model for the prediction of microRNA biomarkers for the diagnosis of paediatric AML based on computational functional analysis of the microRNA regulatory network substructure. microRNA-196b, microRNA-155 and microRNA-25 were identified as putative diagnostic biomarkers for pediatric AML. Further systematic analysis confirmed the association of the predicted microRNAs with the leukemogenesis of AML. In vitro q-PCR experiments showed that microRNA-155 is significantly overexpressed in children with AML and microRNA-196b is significantly overexpressed in subgroups M4–M5 of the French-American-British classification system. These results suggest that microRNA-155 is a potential diagnostic biomarker for all subgroups of paediatric AML, whereas microRNA-196b is specific for subgroups M4–M5. Impact Journals LLC 2015-07-01 /pmc/articles/PMC4694912/ /pubmed/26317787 Text en Copyright: © 2015 Yan et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Yan, Wenying Xu, Lihua Sun, Zhandong Lin, Yuxin Zhang, Wenyu Chen, Jiajia Hu, Shaoyan Shen, Bairong MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model |
title | MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model |
title_full | MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model |
title_fullStr | MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model |
title_full_unstemmed | MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model |
title_short | MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model |
title_sort | microrna biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4694912/ https://www.ncbi.nlm.nih.gov/pubmed/26317787 |
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