Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
| Autor: | Stephan Pabinger, Zlatko Trajanoski, Matthias Baldauf, Benjamin Hiltpolt, Michael Sperk, Andreas Dander |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Open-source
Databases Factual Application medicine.medical_treatment Genomics Computational biology Whole-slide bioimaging Biology Bioinformatics Biochemistry Polymorphism Single Nucleotide DNA sequencing Cancer immunotherapy INDEL Mutation Structural Biology Neoplasms medicine Humans In patient Precision Medicine Molecular Biology Internet business.industry Applied Mathematics Suite Cancer High-Throughput Nucleotide Sequencing medicine.disease Personalized oncology Computer Science Applications Molecular Imaging Next-generation sequencing Data integration Personalized medicine business Software |
| Zdroj: | BMC Bioinformatics |
| ISSN: | 1471-2105 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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