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In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma
PURPOSE: Osteosarcoma is the most common bone tumor in children, adolescents, and young adults. In contrast to other childhood malignancies, no biomarkers have been consistently identified as predictors of outcome. This study was conducted to assess the microRNAs(miRs) expression signatures in pre-t...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4278335/ https://www.ncbi.nlm.nih.gov/pubmed/25594070 |
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author | Sanchez-Diaz, Patricia C. Hsiao, Tzu-Hung Zou, Yi Sugalski, Aaron J. Heim-Hall, Josefine Chen, Yidong Langevin, Anne-Marie Hung, Jaclyn Y. |
author_facet | Sanchez-Diaz, Patricia C. Hsiao, Tzu-Hung Zou, Yi Sugalski, Aaron J. Heim-Hall, Josefine Chen, Yidong Langevin, Anne-Marie Hung, Jaclyn Y. |
author_sort | Sanchez-Diaz, Patricia C. |
collection | PubMed |
description | PURPOSE: Osteosarcoma is the most common bone tumor in children, adolescents, and young adults. In contrast to other childhood malignancies, no biomarkers have been consistently identified as predictors of outcome. This study was conducted to assess the microRNAs(miRs) expression signatures in pre-treatment osteosarcoma specimens and correlate with outcome to identify biomarkers for disease relapse. RESULTS: A 42-miRs signature whose expression levels were associated with overall and relapse-free survival waas identified. There were 8 common miRs between the two sets of survival-associated miRs. Bioinformatic analyses of these survival-associated miRs suggested that they might regulate genes involved in ubiquitin proteasome system, TGFb, IGF, PTEN/AKT/mTOR, MAPK, PDGFR/RAF/MEK/ERK, and ErbB/HER pathways. METHODS: The cohort consisted of 27 patients of 70% Mexican-American ethnicity. High-throughput RT-qPCR approach was used to generate quantitative expression of 754 miRs in the human genome. We examined tumor recurrence status, survival time and their association with miR expression levels by Cox proportional hazard regression analysis. TargetScan was used to predict miR/genes interactions, and functional analyses using KEGG, BioCarta, Gene Ontology were applied to these potential targets to predict deregulated pathways. CONCLUSIONS: Our findings suggested that these miRs might be potentially useful as prognostic biomarkers and therapeutic targets in pediatric osteosarcoma. |
format | Online Article Text |
id | pubmed-4278335 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-42783352015-01-15 In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma Sanchez-Diaz, Patricia C. Hsiao, Tzu-Hung Zou, Yi Sugalski, Aaron J. Heim-Hall, Josefine Chen, Yidong Langevin, Anne-Marie Hung, Jaclyn Y. Oncoscience Research Paper PURPOSE: Osteosarcoma is the most common bone tumor in children, adolescents, and young adults. In contrast to other childhood malignancies, no biomarkers have been consistently identified as predictors of outcome. This study was conducted to assess the microRNAs(miRs) expression signatures in pre-treatment osteosarcoma specimens and correlate with outcome to identify biomarkers for disease relapse. RESULTS: A 42-miRs signature whose expression levels were associated with overall and relapse-free survival waas identified. There were 8 common miRs between the two sets of survival-associated miRs. Bioinformatic analyses of these survival-associated miRs suggested that they might regulate genes involved in ubiquitin proteasome system, TGFb, IGF, PTEN/AKT/mTOR, MAPK, PDGFR/RAF/MEK/ERK, and ErbB/HER pathways. METHODS: The cohort consisted of 27 patients of 70% Mexican-American ethnicity. High-throughput RT-qPCR approach was used to generate quantitative expression of 754 miRs in the human genome. We examined tumor recurrence status, survival time and their association with miR expression levels by Cox proportional hazard regression analysis. TargetScan was used to predict miR/genes interactions, and functional analyses using KEGG, BioCarta, Gene Ontology were applied to these potential targets to predict deregulated pathways. CONCLUSIONS: Our findings suggested that these miRs might be potentially useful as prognostic biomarkers and therapeutic targets in pediatric osteosarcoma. Impact Journals LLC 2014-09-23 /pmc/articles/PMC4278335/ /pubmed/25594070 Text en © 2014 Sanchez-Diaz 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 Sanchez-Diaz, Patricia C. Hsiao, Tzu-Hung Zou, Yi Sugalski, Aaron J. Heim-Hall, Josefine Chen, Yidong Langevin, Anne-Marie Hung, Jaclyn Y. In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma |
title | In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma |
title_full | In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma |
title_fullStr | In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma |
title_full_unstemmed | In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma |
title_short | In silico functional analyses and discovery of survival-associated microRNA signatures in pediatric osteosarcoma |
title_sort | in silico functional analyses and discovery of survival-associated microrna signatures in pediatric osteosarcoma |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4278335/ https://www.ncbi.nlm.nih.gov/pubmed/25594070 |
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