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. Institutions of which they are part Head of group Clinical and Translational Bioinformatics Vall Hebron Institut de Recerca Email Fco. Xavier De la Cruz Montserrat Email Institutions of which they are part Head of group Clinical and Translational Bioinformatics 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.
Research lines Prediction of pathological mutations Since a few years ago, we have been working in the development of computational tools for the prediction of pathological mutations in proteins (PMID: 11812146, 15390262, 15879453, 16208716, 17059831). In this work we have followed a two-step approach. First, we have characterized pathological mutations in terms of sequence, structure and evolutionary properties (PMID: 11812146). Second, we have used the results of this descriptive work to identify those parameters with the best predictive power. Also we have used these results to train a neural network and obtain an empirical model that allows the identification of disease-causing mutations with moderately high accuracies (around 70%; PMID: 15390262, 15879453, 16208716). At present, we are applying this approach to the case of specific diseases. We believe that this is a natural step towards the advancement of personalized medicine. Within this context, we are characterizing the impact on the structure and function of alpha-galactosidase of Fabry disease-causing mutations. Again our approach is the same as in the general case, but here we are benefitting from the close collaboration with the group of Dr. Joan Montaner. IP: Fco. Xavier De la Cruz Montserrat Projects Avanzando hacia el diagnóstico de precisión a través de la comprensión mecanística de las patologias: de la interpretación de variantes a la identificación del perfil celular. IP: Fco. Xavier De la Cruz Montserrat Collaborators: Miriam Izquierdo Sans, Javier Guerrero Flores Funding agency: Ministerio de Ciencia e Innovación-MICINN Funding: 111758 Reference: PREP2022-000566 Duration: 01/02/2024 - 31/01/2028 Advancing towards precision diagnostics using a mechanistic understanding of disease processes: from variant interpretation to single-cell profiling IP: Fco. Xavier De la Cruz Montserrat Collaborators: Natalia Padilla Sirera, Selen Ozkan Funding agency: Ministerio de Ciencia e Innovación-MICINN Funding: 262500 Reference: PID2022-142753OB-I00 Duration: 01/09/2023 - 31/08/2026 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 Collaborators: Natalia Padilla Sirera, Selen Ozkan Funding agency: Ministerio de Ciencia e Innovación-MICINN Funding: 219650 Reference: TED2021-130342B-I00 Duration: 01/12/2022 - 30/09/2025 Therapeutical approaches against chemoresistant cancers IP: Matilde Lleonart Pajarin Collaborators: Yoelsis Garcia Mayea, Fco. Xavier De la Cruz Montserrat, Juan Lorente Guerrero, Natalia Padilla Sirera, Marina Bataller Fernández, Almudena Sanchez Garcia, Selen Ozkan Funding agency: Agència Gestió Ajuts Universitaris i de Recerca Funding: 0.01 Reference: 2021 SGR 01205 Duration: 01/01/2022 - 30/06/2025 Pagination Current page 1 Page 2 Page 3 Next page › Last page »
