Patient-specific B-cell lymphoma modeling identifies cooperating genetic alterations and the critical influence of patient context

Patient-specific B-cell lymphoma modeling identifies cooperating genetic alterations and the critical influence of patient context | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Patient-specific B-cell lymphoma modeling identifies cooperating genetic alterations and the critical influence of patient context Fabian Konrath, Sophy Denker, Clemens Schmitt, Björn Chapuy, Jana Wolf This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9022766/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Diffuse large B-cell lymphoma (DLBCL) is a molecularly heterogeneous disease with high genetic complexity and interpatient variability. Sequencing studies of representative patient cohorts have identified a comprehensive set of genetic driver alterations, enabling patient stratification for personalized treatment strategies. To date, it remains insufficiently understood how these ncogenic driver alterations operate in concert and shape malignant cell states. Here, we use a computational approach that embeds patient data and experimentally characterized molecular perturbations in mechanism-based mathematical modeling to study the effect of genetic alterations in a network context. Based on a detailed pathway model capturing key cellular processes, including apoptosis, cell division, and B-cell differentiation, we created personalized models for a cohort of 284 patients, of which 90.5% reflect an aberrant cell state. Systematic assessment of the functional effects of individual and combinatorial alterations within these models identified previously not appreciated cooperating alterations that operate in synergy, such as mutated NFKBIE and BCL6 structural variant. Notably, we identify a strong context dependency of functional effects, as identical alterations exert varying effects in different patient models. Incorporation of the network context is therefore essential for understanding DLBCL heterogeneity and selecting therapeutic targets for personalized and more efficient treatment strategies. Biological sciences/Computational biology and bioinformatics/Computational models Health sciences/Oncology/Cancer/Tumour heterogeneity Biological sciences/Computational biology and bioinformatics/Computational models Health sciences/Oncology/Cancer/Tumour heterogeneity Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9022766","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":601232070,"identity":"df7e7f7a-dbaa-4c50-b74a-25b21b8110cf","order_by":0,"name":"Fabian Konrath","email":"","orcid":"https://orcid.org/0000-0002-6843-6252","institution":"Mathematical Modelling of Cellular Processes, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany","correspondingAuthor":false,"prefix":"","firstName":"Fabian","middleName":"","lastName":"Konrath","suffix":""},{"id":601232071,"identity":"1a8e1dcd-c63e-4252-8473-c1c76733ef61","order_by":1,"name":"Sophy Denker","email":"","orcid":"","institution":"Charité - Universitätsmedizin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Department of Hematology, Oncology and Tumor Immunology, and Molekulares Krebsforschungszentrum – MKFZ, Campus Virchow Klinikum, Berlin, Germany Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany","correspondingAuthor":false,"prefix":"","firstName":"Sophy","middleName":"","lastName":"Denker","suffix":""},{"id":601232072,"identity":"fa88585d-500c-465c-9986-a3443a33e6cd","order_by":2,"name":"Clemens Schmitt","email":"","orcid":"https://orcid.org/0000-0002-4731-2226","institution":"Charité - Universitätsmedizin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Department of Hematology, Oncology and Tumor Immunology, and Molekulares Krebsforschungszentrum – MKFZ, Campus Virchow Klinikum, Berlin, Germany Cancer Genetics and Cellular Stress Responses, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany Kepler University Hospital, Department of Hematology and Oncology, Medical Faculty, Johannes Kepler University, Linz, Austria","correspondingAuthor":false,"prefix":"","firstName":"Clemens","middleName":"","lastName":"Schmitt","suffix":""},{"id":601232073,"identity":"2b9e69b8-f397-4f5f-b1f5-2934a6675e1b","order_by":3,"name":"Björn Chapuy","email":"","orcid":"https://orcid.org/0000-0002-6485-8773","institution":"Charité - 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Sequencing studies of representative patient cohorts have identified a comprehensive set of genetic driver alterations, enabling patient stratification for personalized treatment strategies. To date, it remains insufficiently understood how these ncogenic driver alterations operate in concert and shape malignant cell states. Here, we use a computational approach that embeds patient data and experimentally characterized molecular perturbations in mechanism-based mathematical modeling to study the effect of genetic alterations in a network context. Based on a detailed pathway model capturing key cellular processes, including apoptosis, cell division, and B-cell differentiation, we created personalized models for a cohort of 284 patients, of which 90.5% reflect an aberrant cell state. Systematic assessment of the functional effects of individual and combinatorial alterations within these models identified previously not appreciated cooperating alterations that operate in synergy, such as mutated NFKBIE and BCL6 structural variant. Notably, we identify a strong context dependency of functional effects, as identical alterations exert varying effects in different patient models. 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