BMC Bioinformatics · 2014 · 11 citations · 17 references
MedicineBioinformaticsOncologyCancer ImmunologyMolecular OncologyPrecision OncologyCancer GenomicsCancer ImmunotherapyGenomic Data IntegrationNext-generation Sequencing In OncologyPersonalized Cancer TherapyPersonalized ImmunotherapyCancer BioinformaticsCancer Data IntegrationCancer Genomics DatabasesCd8+ Tumor-infiltrating LymphocytesGenome Browser InfrastructureNext-generation Sequencing Data AnalysisPersonalized Cancer MedicinePersonalized Cancer Treatment
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.
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