Approximately 10% of cancers can be attributed to genetic variants present in all patient’s cells since birth. These variants predispose the patient to suffer tumors at younger ages than the rest of the population. The early identification of these variants makes it possible to advise them based on a personalized calculation of their risk, adapt their follow-up, offer them some targeted therapies, and offer predictive studies to their relatives.<\/p>\n
Bioinformaticians from the Bellvitge Biomedical Research Institute (IDIBELL) and geneticists from the Molecular Diagnostic Laboratory of the Catalan Institute of Oncology (ICO) joined forces to develop a program called vaRHC, which facilitates genetic variants classification since it collects and combines the available information to offer a first classification of the variants.<\/p>\n
The results have been published in the journal Bioinformatics<\/em> and are available to the entire scientific community for genetic variants classification, especially in genes responsible for hereditary cancer.<\/p>\n \u00a0<\/strong><\/p>\n <\/p>\n Today, genetic diagnosis is performed by analyzing gene panels with massive sequencing techniques. This makes it possible to study more genes and detect more pathogenic variants than before but also to detect more variants of unknown significance. The correct clinical interpretation of genetic variants is a great challenge, also leading to the greatest workload in genetic diagnostic laboratories. This is so because it is necessary to know the gene, the structure, and the function, and to combine biological, clinical, experimental, and computational information. In addition, scientific advances constantly provide new data that make it necessary to reclassify the variants to maintain an accurate classification.<\/p>\n The geneticists of the Institut Catal\u00e0 Oncologia already use it to collect the available data and to have a first classification of the variant. They then review the data and complete the classification with data from the literature (specifically functional and clinical studies) that need expert interpretation. The vaRHC program avoids manual errors in data acquisition and reduces the time needed to classify each variant, allowing genetic studies to be carried out in less time than usual. For the predoctoral researcher of the IDIBELL and ICO hereditary cancer group and first author of the study, Elisabet Munt\u00e9<\/strong>, “this program demonstrates how technology can streamline the work of scientists, allowing them to dedicate themselves to tasks that require their knowledge and experience<\/em>\u201d.<\/p>\n The study has had the support of various research projects of the Carlos III Health Institute, and some of the participating researchers are members of CIBERONC, as well as a research group accredited by AGAUR (SGR). In addition, the first study author, Elisabet Munt\u00e9, has a competitive PERIS contract.<\/p>\n <\/p>\n <\/p>\n The Bellvitge Biomedical Research Institute (IDIBELL) is a biomedical research center created in 2004. It is participated by the Bellvitge University Hospital and the Viladecans Hospital of the Catalan Institute of Health, the Catalan Institute of Oncology, the University of Barcelona and the City Council of L’Hospitalet de Llobregat.<\/p>\n IDIBELL is a member of the Campus of International Excellence of the University of Barcelona HUBc and is part of the CERCA institution of the Generalitat de Catalunya. In 2009 it became one of the first five Spanish research centers accredited as a health research institute by the Carlos III Health Institute. In addition, it is part of the “HR Excellence in Research” program of the European Union and is a member of EATRIS and REGIC. Since 2018, IDIBELL has been an Accredited Center of the AECC Scientific Foundation (FCAECC).<\/p>\n","protected":false},"excerpt":{"rendered":" Bioinformaticians from the Bellvitge Biomedical Research Institute (IDIBELL) and geneticists from the Molecular Diagnostic Laboratory of the Catalan Institute of Oncology (ICO) joined forces to develop a program that facilitates genetic variants classification, as it collects and combines the available information to offer a first classification of the variants.<\/p>\n","protected":false},"author":8,"featured_media":22378,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"default","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"default","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center 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program that avoids manual errors and reduces the wait for results<\/h3>\n