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Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes. We acknowledge the support of the developers of PhenoTips, which was used in the past by RD-Connect and NeurOmics as the primary tool to collate phenotypic data. We would also like to thank the leaders and members of the Instituto Nacional de Bioinformática (INB) and ELIXIR for their support and collaboration throughout the years. RD-Connect (RD-Connect, an integrated platform connecting registries, biobanks, and clinical bioinformatics) received funding from the Seventh Framework (FP7) Programme of the European Union under grant agreement No 305444. Data were analyzed using the RD-Connect GPAP, which received funding from EU projects Solve-RD, EJP-RD (grant numbers H2020 779257, H2020 825575), Instituto de Salud Carlos III (Grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática, INB), ELIXIR-EXCELERATE (Grant number EU H2020 #676559) and ELIXIR Implementation Studies (Remote real-time visualization of human rare disease genomics data (RD-Connect) stored at the EGA ELIXIR. 2017-2018; ELIXIR IT-2017-INTEGRATION, Rare Disease Infrastructure ELIXIR, 2019-2020 and the Beacon ELIXIR, 2019-2021). The RD-Connect GPAP has leveraged developments funded through project VEIS (001-P-001647 co-financed by the European Regional Development Fund of the European Union in the framework of the Operational Program FEDER of Catalonia 2014-2020 with the support of the Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement de la Generalitat de Catalunya) and URD-Cat (PERIS SLT002/16/00174, Departament de Salut, Generalitat de Catalunya). The research leading to these results has received funding from Consequitur (Newton Fund UK/Turkey, MR/N027302/1), BBMRI-LPC (EU FP7 #313010), NeurOmics (EU FP7 #305121), the Economic Development Department of the Navarra Government (Grant number 001114112017), the European Reference Network for Rare Neurological Diseases (Project ID number 739510) and NIH, National Institute of Child Health and Human Development (1R01HD103805-01). We acknowledge the support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Program/Generalitat de Catalunya. We also acknowledge the support of the Generalitat de Catalunya through Departament de Salut and Departament d'Empresa i Coneixement and Co-financing by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) with funds from the European Regional Development Fund (ERDF) corresponding to the 2014-2020 Smart Growth Operating Program. HL receives support from the Canadian Institutes of Health Research (Foundation Grant FDN-167281), the Canadian Institutes of Health Research and Muscular Dystrophy Canada (Network Catalyst Grant for NMD4C), the Canada Foundation for Innovation (CFI-JELF 38412), and the Canada Research Chairs program (Canada Research Chair in Neuromuscular Genomics and Health, 950-232279).

Background: Aneuploidy, centrosome abnormalities and gene amplification are hallmarks of chromosome instability (CIN) in cancer. Yet there are no studies of the in vivo behavior of these phenomena within the same bladder tumor. Methods: Twenty-one paraffin-embedded bladder tumors were analyzed by conventional comparative genome hybridization and fluorescence in situ hybridization (FISH) with a cyclin D1 gene (CCND1)/centromere 11 dual-color probe. Immunofluorescent staining of α, β and γ tubulin was also performed. Results: Based on the CIN index, defined as the percentage of cells not displaying the modal number for chromosome 11, tumors were classified as CIN-negative and CIN-positive. Fourteen out of 21 tumors were considered CIN-positive. All T1G3 tumors were included in the CIN-positive group whereas the majority of Ta samples were classified as CIN-negative tumors. Centrosome clustering was observed in six out of 12 CIN-positive tumors analyzed. CCND1 amplification in homogeneously staining regions was present in six out of 14 CIN-positive tumors; three of them also showed amplification of this gene in double minutes. Conclusions: Complex in vivo behavior of CCND1 amplicon in bladder tumor cells has been demonstrated by accurate FISH analysis on paraffin-embedded tumors. Positive correlation between high heterogeneity, centrosome abnormalities and CCND1 amplification was found in T1G3 bladder carcinomas. This is the first study to provide insights into the coexistence of CCND1 amplification in homogeneously staining regions and double minutes in primary bladder tumors. It is noteworthy that those patients whose tumors showed double minutes had a significantly shorter overall survival rate (p < 0.001). The work has been supported by ISCIII: EPICUR-Red (FIS G03/174), SAF2007-64167 and RD06/0020/1020. Javier del Rey was a fellow of Generalitat de Catalunya and is supported by RD06/0020/1020