Fco. Xavier De la Cruz Montserrat Our main research aims at understanding the molecular basis of hereditary disease, integrating two complementary aspects: the molecular impact of causative variants and how genetic background regulates the propagation of this impact. At a technical level, to reach our objective, we integrate the results of the most advanced genomic experiments (single-cell, Hi-C, etc.) using state-of-the-art machine learning tools. To enhance the biomedical reach of our research, we work in collaboration with clinical groups from different hospitals. As a result of these efforts, we have recently made significant advances in understanding the functional effect of BRCA1/2 protein variants underlying hereditary breast and ovarian cancers. Finally, mention that we are also devoting an important part of our efforts to the fundamental study of epigenetic processes, to reach a full picture of which phenomena contribute to the generation of phenotype and, more precisely, of clinical phenotype. Instituciones de las que forman parte Jefe de grupo Bioinformática Clínica y Translacional Vall Hebron Institut de Recerca Fco. Xavier De la Cruz Montserrat Instituciones de las que forman parte Jefe de grupo Bioinformática Clínica y Translacional Vall Hebron Institut de Recerca Our main research aims at understanding the molecular basis of hereditary disease, integrating two complementary aspects: the molecular impact of causative variants and how genetic background regulates the propagation of this impact. At a technical level, to reach our objective, we integrate the results of the most advanced genomic experiments (single-cell, Hi-C, etc.) using state-of-the-art machine learning tools. To enhance the biomedical reach of our research, we work in collaboration with clinical groups from different hospitals. As a result of these efforts, we have recently made significant advances in understanding the functional effect of BRCA1/2 protein variants underlying hereditary breast and ovarian cancers. Finally, mention that we are also devoting an important part of our efforts to the fundamental study of epigenetic processes, to reach a full picture of which phenomena contribute to the generation of phenotype and, more precisely, of clinical phenotype.
INTERESTS My interests are devoted to studying the impact of pathogenic mutations and transform the results into clinically useful Artificial Intelligence (AI) models. HIGHLIGHTS We ranked second in the groups' classification at the international challenge for in silico methods, CAGI 5 (inherited breast/ovarian cancers section). We won the Best Poster Prize of the Editor of 'Science' in HGM 2018 (Japan). In 2015, we participated in the identification of the glioblastoma signature in cerebro-spinal fluid (De Mattos-Arruda et al., Nature Communications, 6:8839), a project that won the Prize "La Vanguardia de la Ciencia". EARLY CAREER .- Ph.D. Thesis Thesis (1990-1993, UPC, Barcelona). I worked in a relationship between atomic areas and free energies (de la Cruz et al., J.Mol.Graphics, 10:96, 1992). During a stay in the lab of van Gunsteren (ETH-Z, Zürich), I shifted toward the study of the structure/function relationship (de la Cruz et al., J. Mol. Biol., 236:1186, 1994). Fellowships: FPI Generalitat (1990-93, UPC); EMBO Short Term (1992, ETH-Z). .- Post-doctoral stays (1993-2000) Two post-doctoral stays: NIH, USA (4 years) and UCL-EBI, UK (3 years). In these stays, I increased my background on structure/function relationship (analog structure comparisons: de la Cruz & Lee, Protein Sci., 5:857, 1996; beta-turn prediction: de la Cruz et al., PNAS, 99:11157, 2002). Fellowships: Fogarty Fellowship (1993-97, USA); MEC fellowship for doctors (1997); Human Frontier Science Program (HFSP) (1997-99, UK). PRESENT (2000-**) ICREA Research Professor Our research aims at understanding/predicting the impact of pathogenic of variants using AI. Our initial approach (Ferrer-Costa et al., J. Mol. Biol. 2002; Proteins, 2004; Bioinformatics, 2005) has been broadly followed (>920 citations). After joining VHIR (2012) we have designed a novel approach to pathogenicity prediction (Riera et al., Hum. Mut., 2016). This crystallized in the model for BRCA1/2 variants (Padilla et al., Hum. Mut., 2019) that we presented at the international CAGI contest (see above). We have further tested this result to extend it to the clinical genome (Özkan et al., IJMS, 2020). Our expertise is reflected in our collaborations (see below for our collaboration with E. Bhoj at the Children’s Hospital of Philadelphia). We have worked also in the epigenetic regulation of gene expression, where I would like to single out two of our publications (co-corresponding author in both), one in PNAS (Pappa et al., 2019) about DNA damage prevention and the second in Development (Estarás et al., 2012) on the regulation of neural development by JMJD3. Contracts: Reincorporación MEC (2000-2001), ICREA Research Professor (2001-nowadays). -Skills. We have a deep understanding of the molecular basis of hereditary diseases. Technically, we are proficient in the development of AI tools for pathogenicity prediction. We are also proficient in the structural/functional characterization of protein mutations using computational/bioinformatics approaches. -International collaborations. We have an ongoing collaboration with E. Bhoj (Children’s Hospital of Philadelphia) for the clinical characterization of histone H3.3 variants. This work has lead to a high-impact publication (Bryant et al., Science Advances, 2020) in which we leadered the in silico analyses of the whole consortium (137 authors) in a study resulting in the discovery of a new neurodegenerative disorder. -Training researchers. I have supervised 11 Ph.D. theses. The majority of the students work in bioinformatics/computation.
Líneas de investigación Predicción de mutaciones patológicas En los últimos años hemos dedicado parte de nuestra investigación al desarrollo de herramientas bioinformáticas aplicadas a la predicción de mutaciones patológicas en proteínas (PMID: 11812146, 15390262, 15879453, 16208716, 17059831). Para ello hemos seguido un protocolo de dos pasos. En primer lugar, hemos caracterizado las mutaciones patológicas en términos de propiedades de secuencia, de estructura y evolutivas. En segundo lugar, hemos utilizado los resultados de este trabajo descriptivo para identificar aquellos parámetros con un mayor poder predictivo. Posteriormente, con estos parámetros hemos "entrenado" una red neuronal que nos ha proporcionado un modelo empírico que permite la identificación de mutaciones patológicas, con una tasa de acierto moderadamente elevada (cerca del 70%; PMID: 15390262, 15879453, 16208716). En estos momentos, estamos aplicando esta aproximación al caso de patologías específicas. Creemos que este es un paso natural hacia el desarrollo de una medicina personalizada. Dentro de este contexto, estamos caracterizando el impacto de las mutaciones causantes de la enfermedad de Fabry sobre la estructura y función de la alfa-galactosidasa. Seguimos en este caso la aproximación antes descrita, aunque aquí nos beneficiamos de la colaboración estrecha con el grupo del Dr. Joan Montaner. IP: Fco. Xavier De la Cruz Montserrat Proyectos Hacia una mejor aplicabilidad de la Inteligencia Artificial en Medicina Genómica: Integrando capacidad predictiva e interpretabilidad en una nueva generación de herramientas para la anotación de variantes de proteínas IP: Fco. Xavier De la Cruz Montserrat Colaboradores: Natalia Padilla Sirera, Selen Ozkan Entidad financiadora: Ministerio de Ciencia e Innovación-MICINN Financiación: 219650 Referencia: TED2021-130342B-I00 Duración: 01/12/2022 - 30/11/2024 Therapeutical approaches against chemoresistant cancers IP: Matilde Lleonart Pajarin Colaboradores: Yoelsis Garcia Mayea, Fco. Xavier De la Cruz Montserrat, Juan Lorente Guerrero, Cristina Mir Perez, Natalia Padilla Sirera, Marina Bataller Fernández, Almudena Sanchez Garcia, Selen Ozkan Entidad financiadora: AGAUR no fer servir-correcte 4301-37 Financiación: 0.01 Referencia: 2021 SGR 01205 Duración: 01/01/2022 - 31/12/2024 Una aproximación traslacional a la interpretación de variantes de secuencia en proteínas: integrando impacto molecular, regulación por el entorno genético y coste clínico IP: Fco. Xavier De la Cruz Montserrat Colaboradores: Natalia Padilla Sirera, Selen Ozkan Entidad financiadora: Ministerio de Ciencia e Innovación-MICINN Financiación: 133100 Referencia: PID2019-111217RB-I00 Duración: 01/06/2020 - 31/05/2023 Nuevas aproximaciones para identificar variantes patogénicas en experimentos de secuenciación masiva basadas en la integración de impacto molecular e información biomédica IP: Fco. Xavier De la Cruz Montserrat Colaboradores: - Entidad financiadora: Ministerio Economía, Industria y Competitividad Financiación: 96800 Referencia: SAF2016-80255-R Duración: 30/12/2016 - 29/12/2019 Paginación Página actual 1 Página 2 Siguiente página › Última página »
