{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T16:55:02Z","timestamp":1785776102372,"version":"3.56.0"},"reference-count":46,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"vor","delay-in-days":33,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon Europe","award":["101072891"],"award-info":[{"award-number":["101072891"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,7,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Agent-based models (ABMs) offer a powerful framework for representing emergent immune dynamics, yet their integration with single-cell datasets and therapeutics simulation remains limited. Here, we presented an integrative, single-cell informed systems immunology modeling framework built on universal immune system simulator (UISS) to mechanistically represent autoimmune skin inflammation specifically systemic and cutaneous lupus erythematosus. The framework incorporates (i) data-driven initialization from lesion single-cell RNA sequence cell fractions, (ii) modular immune processes coupling type I interferon signaling, ultraviolet induced keratinocyte injury, and (iii) a digital patient generation pipeline that captures inter-individual variability through stochastic parameter perturbation and quality-controlled cohort assembly. Using this platform, we constructed a cohort of 50 digital patients initially and implemented modular therapy components for B-cell Activating Factor (BAFF) neutralization (belimumab) and anti-CD20 B-cell depletion (rituximab) . In silico, pre\u2013post treatment experiments revealed heterogeneous serologic responses, modest median reductions in immunoglobulin G antibodies that target the Ro\/SSA protein (Ro-reactive IgG), and strong correlations between plasmablast dynamics and circulation autoantibodies, highlighting the mechanistic constraints on B-cell targeted therapies. Overall, our results demonstrated how single-cell benchmarking, rule-based immune modeling, and digital patient ensembles can be integrated into a generalizable computational workflow for studying autoimmune pathophysiology and simulating therapeutic mechanisms to explore mechanistic determinants of disease progression and therapeutic response.<\/jats:p>","DOI":"10.1093\/bib\/bbag416","type":"journal-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T11:36:55Z","timestamp":1784029015000},"source":"Crossref","is-referenced-by-count":0,"title":["Integrative agent-based modeling of cutaneous lupus: single-cell benchmarking and\n                    <i>in silico<\/i>\n                    evaluation of B-cell therapies"],"prefix":"10.1093","volume":"27","author":[{"given":"Abdul","family":"Wahab","sequence":"first","affiliation":[{"name":"Department of Mathematics and Computer Science, University of Catania , V.le A. Doria, 6, 95125 Catania ,","place":["Italy"]},{"name":"Department of Drug and Health Sciences, University of Catania , Via Valdisavoia, 5, 95123 Catania ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulia","family":"Russo","sequence":"additional","affiliation":[{"name":"Department of Drug and Health Sciences, University of Catania , Via Valdisavoia, 5, 95123 Catania ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Pappalardo","sequence":"additional","affiliation":[{"name":"Department of Drug and Health Sciences, University of Catania , Via Valdisavoia, 5, 95123 Catania ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"2026080312294432100_ref1","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1038\/s41584-019-0272-0","article-title":"Cutaneous lupus erythematosus: new insights into pathogenesis and therapeutic strategies","volume":"15","author":"Wenzel","year":"2019","journal-title":"Nat Rev Rheumatol"},{"key":"2026080312294432100_ref2","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/s11926-020-00946-z","article-title":"An update on the pathogenesis of cutaneous lupus erythematosus and its role in clinical practice","volume":"22","author":"Patel","year":"2020","journal-title":"Curr Rheumatol Rep"},{"key":"2026080312294432100_ref3","doi-asserted-by":"crossref","first-page":"915828","DOI":"10.3389\/fmed.2022.915828","article-title":"Current concepts on pathogenic mechanisms and histopathology in cutaneous lupus erythematosus","volume":"9","author":"Fetter","year":"2022","journal-title":"Front Med"},{"key":"2026080312294432100_ref4","doi-asserted-by":"crossref","first-page":"i37","DOI":"10.1136\/ard.2010.138057","article-title":"The genetics of systemic lupus erythematosus and implications for targeted therapy","volume":"70","author":"Sestak","year":"2011","journal-title":"Ann Rheum Dis"},{"key":"2026080312294432100_ref5","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1111\/exd.14146","article-title":"Cutaneous lupus erythematosus: the impact of self-amplifying innate and adaptive immune responses and future prospects of targeted therapies","volume":"29","author":"Fetter","year":"2020","journal-title":"Exp Dermatol"},{"key":"2026080312294432100_ref6","doi-asserted-by":"crossref","first-page":"e1010168","DOI":"10.1371\/journal.pcbi.1010168","article-title":"From affinity selection to kinetic selection in germinal Centre modelling","volume":"18","author":"Lashgari","year":"2022","journal-title":"PLoS Comput Biol"},{"key":"2026080312294432100_ref7","doi-asserted-by":"crossref","first-page":"620716","DOI":"10.3389\/fimmu.2020.620716","article-title":"Multiscale modeling of germinal center recapitulates the temporal transition from memory B cells to plasma cells differentiation as regulated by antigen affinity-based Tfh cell help","volume":"11","author":"Merino Tejero","year":"2021","journal-title":"Front Immunol"},{"key":"2026080312294432100_ref8","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s12064-023-00390-4","article-title":"A biological and a mathematical model of SLE treated by mesenchymal stem cells covering all the stages of the disease","volume":"142","author":"Yazdani","year":"2023","journal-title":"Theory Biosci"},{"key":"2026080312294432100_ref9","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1016\/j.jtbi.2010.03.027","article-title":"Model of colonic inflammation: immune modulatory mechanisms in inflammatory bowel disease","volume":"264","author":"Wendelsdorf","year":"2010","journal-title":"J Theor Biol"},{"key":"2026080312294432100_ref10","first-page":"281","article-title":"Model-based meta-analysis using latent variable modeling to set benchmarks for new treatments of systemic lupus erythematosus. 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