Combatting Disorders of Adaptive Immunity with Systems Medicine
Consortium description
COSMIC brings together 10 beneficiaries from 9 different European countries with industrial and academic backgrounds:
- Academic Medical Center, AMC, NL-Coordinator
- Bioinformatics Laboratory, Prof. dr. A.H.C. van Kampen
- Rheumatology and clinical immunology, Dr. N. de Vries
- Dept. of Pathology, Dr. J.E.J. Guikema
- Research Centre Inria, INRIA, FR, DRACULA team Dr. O. Gandrillon Dr. F. Crauste
- Karolinska institute, KI, SE, Dept. of Medical Biochemistry and Biophysics Prof. dr. R. Holmdahl
- Babraham Institute, BI, UK, Lymphocyte signalling and development Dr. M. Turner
- FIRC Institute of Molecular Oncology, IFOM, IT, Genetics of B cells and lymphomas Dr. S. Casola
- Anaxomics Biotech S.L, ANX, ES Expertise: systems biology, Dr. J. Farres
- Redoxis AB, RDX, SE, Expertise: pre-clinical models of autoimmune disease, Dr. M. Hultqvist Hopkins
- Helmholtz Centre for Infection Research, HZI, DE, Systems Immunology Prof. dr. M. Meyer- Hermann
- IBM, IBM, CH, Expertise: systems biology Dr. María Rodríguez Martínez
- Centre for Research and Technology Hellas, CERTH, EL Institute of Applied Biosciences, Dr. K. Stamatopoulos
Project Description
COSMIC establishes state-of-the art experimental and computational approaches to elucidate the cellular and molecular mechanisms that control the normal germinal centre reaction and its role in B-cell lymphoma (BCL; WP3) and rheumatoid arthritis (RA; WP4). Computational disease models (WP5) will be developed to complement and guide the experimental work. Through the combination of these approaches we also aim at the identification of putative diagnostic markers and/or drug targets for BCL and RA. COSMIC established a unique cross-fertilization between the oncology and auto-immunity research fields
Publications
Junet, V., Matos-Filipe, P., García-Illarramendi, J.M., Ramírez, E., Oliva, B., Farrés, J., Daura, X., Mas, J.M., Morales, R., 2023. A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status. CPT: Pharmacometrics & Systems Pharmacology 00, 1–13.
Junet Valentin, 2021. Machine Learning techniques in bioinformatics: From data integration to the development of application-oriented tools. Doctoral dissertation. Universitat Autònoma de Barcelona, Barcelona.
Junet, V., Daura, X., 2021. CNN-PepPred: An open-source tool to create convolutional NN models for the discovery of patterns in peptide sets. Application to peptide-MHC class II binding prediction. Bioinformatics Volume 37, Issue 23, 1 December 2021, Pages 4567–4568.
Junet, V., Farrés, J., Mas, J.M., Daura, X., 2021. CuBlock: a cross-platform normalization method for gene-expression microarrays. Bioinformatics 37, 2365-2373.
Agathangelidis, A., Galigalidou, C., Iatrou, A., Zaragoza-Infante, L., Scarfò, L., Maniou, M.C., Ranghetti, P., Pechlivanis, N., Junet, V., Skaftason, A., Tsagiopoulou, M., Psomopoulos, F., Rosenquist, R., Ghia, P., Chatzidimitriou, A., Stamatopoulos, K., 2022. P593: multidimensional analysis of the b cell receptor offers insight into the ontogenetic relationship of monoclonal b-cell lymphocytosis with chronic lymphocytic leukemia. HemaSphere 6, 492–493.
Zaragoza-Infante, L., Agathangelidis, A., Junet, V., Pechlivanis, N., Koletsa, T., Bruscaggin, A., Davis, Z., Markantonatou, S., Spina, V., Verney, A., Iatrou, A., Psomopoulos, F., Oscier, D., Traverse-Glehen, A., Papaioannou, M., Rossi, D., Chatzidimitriou, A., Stamatopoulos, K., 2021. Distinct Modes of Ongoing Antigen Interactions Shape Intraclonal Dynamics in Splenic Marginal Zone Lymphoma. Blood 138, 1330.
Zaragoza-Infante, L., Junet, V., Pechlivanis, N., Fragkouli, S.-C., Amprachamian, S., Koletsa, T., Chatzidimitriou, A., Papaioannou, M., Stamatopoulos, K., Agathangelidis, A., Psomopoulos, F. 2022. IgIDivA: immunoglobulin intraclonal diversification analysis. Briefings in Bioinformatics 23, bbac349.
Gutiérrez-Casares, J.R., Quintero, J., Jorba, G., Junet, V., Martínez, V., Pozo-Rubio, T., Oliva, B., Daura, X., Mas, J.M., Montoto, C., 2021. Methods to Develop an in silico Clinical Trial: Computational Head-to-Head Comparison of Lisdexamfetamine and Methylphenidate. Frontiers in Psychiatry 12, 1902.
Jorba, G., Aguirre-Plans, J., Junet, V., Segú-Vergés, C., Ruiz, J.L., Pujol, A., Fernández-Fuentes, N., Mas, J.M., Oliva, B., 2020. In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan. PLOS ONE 15, e0228926.
Financing: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765158.