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Meta-mining of copy number profiles of high-risk neuroblastoma tumors

Neuroblastoma, a pediatric tumor of the sympathetic nervous system, is predominantly driven by copy number aberrations, which predict survival outcome in global neuroblastoma cohorts and in low-risk cases. For high-risk patients there is still a need for better prognostic biomarkers. Via an internat...

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Autores principales: Depuydt, Pauline, Koster, Jan, Boeva, Valentina, Hocking, Toby D., Speleman, Frank, Schleiermacher, Gudrun, De Preter, Katleen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207068/
https://www.ncbi.nlm.nih.gov/pubmed/30375995
http://dx.doi.org/10.1038/sdata.2018.240
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author Depuydt, Pauline
Koster, Jan
Boeva, Valentina
Hocking, Toby D.
Speleman, Frank
Schleiermacher, Gudrun
De Preter, Katleen
author_facet Depuydt, Pauline
Koster, Jan
Boeva, Valentina
Hocking, Toby D.
Speleman, Frank
Schleiermacher, Gudrun
De Preter, Katleen
author_sort Depuydt, Pauline
collection PubMed
description Neuroblastoma, a pediatric tumor of the sympathetic nervous system, is predominantly driven by copy number aberrations, which predict survival outcome in global neuroblastoma cohorts and in low-risk cases. For high-risk patients there is still a need for better prognostic biomarkers. Via an international collaboration, we collected copy number profiles of 556 high-risk neuroblastomas generated on different array platforms. This manuscript describes the composition of the dataset, the methods used to process the data, including segmentation and aberration calling, and data validation. t-SNE analysis shows that samples cluster according to MYCN status, and shows a difference between array platforms. 97.3% of samples are characterized by the presence of segmental aberrations, in regions frequently affected in neuroblastoma. Focal aberrations affect genes known to be involved in neuroblastoma, such as ALK and LIN28B. To conclude, we compiled a unique large copy number dataset of high-risk neuroblastoma tumors, available via R2 and a Shiny web application. The availability of patient survival data allows to further investigate the prognostic value of copy number aberrations.
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spelling pubmed-62070682018-11-06 Meta-mining of copy number profiles of high-risk neuroblastoma tumors Depuydt, Pauline Koster, Jan Boeva, Valentina Hocking, Toby D. Speleman, Frank Schleiermacher, Gudrun De Preter, Katleen Sci Data Data Descriptor Neuroblastoma, a pediatric tumor of the sympathetic nervous system, is predominantly driven by copy number aberrations, which predict survival outcome in global neuroblastoma cohorts and in low-risk cases. For high-risk patients there is still a need for better prognostic biomarkers. Via an international collaboration, we collected copy number profiles of 556 high-risk neuroblastomas generated on different array platforms. This manuscript describes the composition of the dataset, the methods used to process the data, including segmentation and aberration calling, and data validation. t-SNE analysis shows that samples cluster according to MYCN status, and shows a difference between array platforms. 97.3% of samples are characterized by the presence of segmental aberrations, in regions frequently affected in neuroblastoma. Focal aberrations affect genes known to be involved in neuroblastoma, such as ALK and LIN28B. To conclude, we compiled a unique large copy number dataset of high-risk neuroblastoma tumors, available via R2 and a Shiny web application. The availability of patient survival data allows to further investigate the prognostic value of copy number aberrations. Nature Publishing Group 2018-10-30 /pmc/articles/PMC6207068/ /pubmed/30375995 http://dx.doi.org/10.1038/sdata.2018.240 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Depuydt, Pauline
Koster, Jan
Boeva, Valentina
Hocking, Toby D.
Speleman, Frank
Schleiermacher, Gudrun
De Preter, Katleen
Meta-mining of copy number profiles of high-risk neuroblastoma tumors
title Meta-mining of copy number profiles of high-risk neuroblastoma tumors
title_full Meta-mining of copy number profiles of high-risk neuroblastoma tumors
title_fullStr Meta-mining of copy number profiles of high-risk neuroblastoma tumors
title_full_unstemmed Meta-mining of copy number profiles of high-risk neuroblastoma tumors
title_short Meta-mining of copy number profiles of high-risk neuroblastoma tumors
title_sort meta-mining of copy number profiles of high-risk neuroblastoma tumors
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207068/
https://www.ncbi.nlm.nih.gov/pubmed/30375995
http://dx.doi.org/10.1038/sdata.2018.240
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