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

BackgroundCancer 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.ResultsWe 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.ConclusionsThe 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.

[1]  B Schütze [Use of medical treatment data outside of the patient supply: best way pseudonymisation]. , 2012, Deutsche medizinische Wochenschrift.

[2]  Nasir M. Rajpoot,et al.  BioIMAX: A Web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data , 2011, BMC Bioinformatics.

[3]  Mahadev Satyanarayanan,et al.  OpenSlide: A vendor-neutral software foundation for digital pathology , 2013, Journal of pathology informatics.

[4]  Ambuj K. Singh,et al.  Bisque: a platform for bioimage analysis and management , 2009, Bioinform..

[5]  Pornpimol Charoentong,et al.  Information technology solutions for integration of biomolecular and clinical data in the identification of new cancer biomarkers and targets for therapy. , 2010, Pharmacology & therapeutics.

[6]  Hagen Blankenburg,et al.  Integrating biological data – the Distributed Annotation System , 2008, BMC Bioinformatics.

[7]  Jennifer Couzin-Frankel,et al.  Breakthrough of the year 2013. Cancer immunotherapy. , 2013, Science.

[8]  Mingming Jia,et al.  COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer , 2010, Nucleic Acids Res..

[9]  Hubert Hackl,et al.  MARS: Microarray analysis, retrieval, and storage system , 2005, BMC Bioinformatics.

[10]  Ugur Sahin,et al.  Galaxy LIMS for next-generation sequencing , 2013, Bioinform..

[11]  Bernd Rinn,et al.  openBIS: a flexible framework for managing and analyzing complex data in biology research , 2011, BMC Bioinformatics.

[12]  Shuigeng Zhou,et al.  A comparison study on feature selection of DNA structural properties for promoter prediction , 2012, BMC Bioinformatics.

[13]  Carole A. Goble,et al.  The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud , 2013, Nucleic Acids Res..

[14]  C. Rueden,et al.  Metadata matters: access to image data in the real world , 2010, The Journal of cell biology.

[15]  Michael R. Speicher,et al.  A survey of tools for variant analysis of next-generation genome sequencing data , 2013, Briefings Bioinform..

[16]  Gérald Salin,et al.  NG6: Integrated next generation sequencing storage and processing environment , 2012, BMC Genomics.

[17]  Arek Kasprzyk,et al.  BioMart: driving a paradigm change in biological data management , 2011, Database J. Biol. Databases Curation.

[18]  Riccardo Bellazzi,et al.  An ICT infrastructure to integrate clinical and molecular data in oncology research , 2012, BMC Bioinformatics.

[19]  David A. Nix,et al.  Next generation tools for genomic data generation, distribution, and visualization , 2010, BMC Bioinformatics.