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Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages

BACKGROUND: Cancer immunotherapy has recently entered a remarkable renaissance phase with the approval of several agents for treatment. Cancer treatment platforms have demonstrated profound tumor regressions including complete cure in patients with metastatic cancer. Moreover, technological advances...

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Autores principales: Dander, Andreas, Baldauf, Matthias, Sperk, Michael, Pabinger, Stephan, Hiltpolt, Benjamin, Trajanoski, Zlatko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4261581/
https://www.ncbi.nlm.nih.gov/pubmed/25230706
http://dx.doi.org/10.1186/1471-2105-15-306
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author Dander, Andreas
Baldauf, Matthias
Sperk, Michael
Pabinger, Stephan
Hiltpolt, Benjamin
Trajanoski, Zlatko
author_facet Dander, Andreas
Baldauf, Matthias
Sperk, Michael
Pabinger, Stephan
Hiltpolt, Benjamin
Trajanoski, Zlatko
author_sort Dander, Andreas
collection PubMed
description BACKGROUND: Cancer immunotherapy has recently entered a remarkable renaissance phase with the approval of several agents for treatment. Cancer treatment platforms have demonstrated profound tumor regressions including complete cure in patients with metastatic cancer. Moreover, technological advances in next-generation sequencing (NGS) as well as the development of devices for scanning whole-slide bioimages from tissue sections and image analysis software for quantitation of tumor-infiltrating lymphocytes (TILs) allow, for the first time, the development of personalized cancer immunotherapies that target patient specific mutations. However, there is currently no bioinformatics solution that supports the integration of these heterogeneous datasets. RESULTS: We have developed a bioinformatics platform – Personalized Oncology Suite (POS) – that integrates clinical data, NGS data and whole-slide bioimages from tissue sections. POS is a web-based platform that is scalable, flexible and expandable. The underlying database is based on a data warehouse schema, which is used to integrate information from different sources. POS stores clinical data, genomic data (SNPs and INDELs identified from NGS analysis), and scanned whole-slide images. It features a genome browser as well as access to several instances of the bioimage management application Bisque. POS provides different visualization techniques and offers sophisticated upload and download possibilities. The modular architecture of POS allows the community to easily modify and extend the application. CONCLUSIONS: The web-based integration of clinical, NGS, and imaging data represents a valuable resource for clinical researchers and future application in medical oncology. POS can be used not only in the context of cancer immunology but also in other studies in which NGS data and images of tissue sections are generated. The application is open-source and can be downloaded at http://www.icbi.at/POS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-306) contains supplementary material, which is available to authorized users.
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spelling pubmed-42615812014-12-10 Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages Dander, Andreas Baldauf, Matthias Sperk, Michael Pabinger, Stephan Hiltpolt, Benjamin Trajanoski, Zlatko BMC Bioinformatics Software BACKGROUND: Cancer immunotherapy has recently entered a remarkable renaissance phase with the approval of several agents for treatment. Cancer treatment platforms have demonstrated profound tumor regressions including complete cure in patients with metastatic cancer. Moreover, technological advances in next-generation sequencing (NGS) as well as the development of devices for scanning whole-slide bioimages from tissue sections and image analysis software for quantitation of tumor-infiltrating lymphocytes (TILs) allow, for the first time, the development of personalized cancer immunotherapies that target patient specific mutations. However, there is currently no bioinformatics solution that supports the integration of these heterogeneous datasets. RESULTS: We have developed a bioinformatics platform – Personalized Oncology Suite (POS) – that integrates clinical data, NGS data and whole-slide bioimages from tissue sections. POS is a web-based platform that is scalable, flexible and expandable. The underlying database is based on a data warehouse schema, which is used to integrate information from different sources. POS stores clinical data, genomic data (SNPs and INDELs identified from NGS analysis), and scanned whole-slide images. It features a genome browser as well as access to several instances of the bioimage management application Bisque. POS provides different visualization techniques and offers sophisticated upload and download possibilities. The modular architecture of POS allows the community to easily modify and extend the application. CONCLUSIONS: The web-based integration of clinical, NGS, and imaging data represents a valuable resource for clinical researchers and future application in medical oncology. POS can be used not only in the context of cancer immunology but also in other studies in which NGS data and images of tissue sections are generated. The application is open-source and can be downloaded at http://www.icbi.at/POS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-306) contains supplementary material, which is available to authorized users. BioMed Central 2014-09-18 /pmc/articles/PMC4261581/ /pubmed/25230706 http://dx.doi.org/10.1186/1471-2105-15-306 Text en © Dander et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Software
Dander, Andreas
Baldauf, Matthias
Sperk, Michael
Pabinger, Stephan
Hiltpolt, Benjamin
Trajanoski, Zlatko
Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
title Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
title_full Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
title_fullStr Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
title_full_unstemmed Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
title_short Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
title_sort personalized oncology suite: integrating next-generation sequencing data and whole-slide bioimages
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4261581/
https://www.ncbi.nlm.nih.gov/pubmed/25230706
http://dx.doi.org/10.1186/1471-2105-15-306
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