A semantic interoperability approach to support integration of gene expression and clinical data in breast cancer. (1st August 2017) - Alonso-Calvo, Raul; Paraiso-Medina, Sergio; Perez-Rey, David; Alonso-Oset, Enrique; van Stiphout, Ruud; Yu, Sheng; Taylor, Marian; Buffa, Francesca; Fernandez-Lozano, Carlos; Pazos, Alejandro; Maojo, Victor
Abstract: Introduction: The introduction of omics data and advances in technologies involved in clinical treatment has led to a broad range of approaches to represent clinical information. Within this context, patient stratification across health institutions due to omic profiling presents a complex scenario to carry out multi-center clinical trials. Methods: This paper presents a standards-based approach to ensure semantic integration required to facilitate the analysis of clinico-genomic clinical trials. To ensure interoperability across different institutions, we have developed a Semantic Interoperability Layer (SIL) to facilitate homogeneous access to clinical and genetic information, based on different well-established biomedical standards and following International Health (IHE) recommendations. Results: The SIL has shown suitability for integrating biomedical knowledge and technologies to match the latest clinical advances in healthcare and the use of genomic information. This genomic data integration in the SIL has been tested with a diagnostic classifier tool that takes advantage of harmonized multi-center clinico-genomic data for training statistical predictive models. Conclusions: The SIL has been adopted in national and international research initiatives, such as the EURECA-EU research project and the CIMED collaborative Spanish project, where the proposed solution has been applied and evaluated by clinical experts focused on clinico-genomic studies. Highlights: Standard-based semantic interoperability solution integrating clinical and genomic data. Use of biomedical standards (HL7, SNOMED, HGNC) and IHE recommendations. It has been used for testing in diagnostic classifier tool. Clinical variables and gene expression data are retrieved through SPARQL for feeding biomedical tools.