{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T04:07:25Z","timestamp":1774498045064,"version":"3.50.1"},"reference-count":61,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T00:00:00Z","timestamp":1755129600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Sepsis is characterized by life-threatening organ dysfunction caused by dysregulated host response to infection. A key contributor is the disruption of neutrophil-endothelial interactions. Despite extensive research, there are no FDA-approved therapies that directly target altered neutrophil function in sepsis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We previously identified three functionally distinct neutrophil phenotypes in sepsis patients: Hyperimmune, Hypoimmune, and Hybrid, using clinical profiling, organ-on-chip models, and proteomics. In this study, we applied bioinformatics tools to elucidate the molecular pathways and druggable targets associated with each phenotype. Differentially expressed proteins were identified using ExpressAnalyst, while pathway enrichment and modeling were performed via Metascape and KEGG-based analyses. DrugBank and the Broad Institute Drug Repurposing Hub were queried to identify FDA-approved therapeutics. STRING and Cytoscape were used to build protein\u2013protein interaction networks and prioritize hub targets.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In our study, the Hyperimmune and Hybrid neutrophil phenotypes had similar numbers of upregulated proteins, while the Hypoimmune and Hybrid neutrophil phenotypes had approximately the same numbers of downregulated proteins. Functional enrichment analysis highlighted several biological processes and pathways that impacted adhesion\/migration patterns, such as calcium transport and neutrophil degranulation. Neutrophil pathway analysis highlighted nine differentially expressed proteins that were directly implicated in known neutrophil processes related to sepsis, such as leukocyte transendothelial migration. These findings were leveraged to identify FDA-approved therapeutics that could be repurposed to target proteins within each phenotype highlighting the impact in normalizing altered neutrophil-related responses such as adhesion, migration and pro-inflammatory mediator release. Finally, a protein-protein interaction network was employed to prioritize these target proteins within each phenotype using network analysis and identified three distinct drug targets across phenotypes that could modulate the neutrophil response in sepsis: VTN in the Hybrid phenotype, TRPV2 in the Hypoimmune phenotype and H2AC21 in the Hyperimmune phenotype.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>Our integrative approach highlights phenotype-specific drug targets and FDA-approved candidates to modulate dysfunctional neutrophil responses in sepsis. This strategy supports a precision medicine framework for repurposing existing drugs based on neutrophil functional phenotyping.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2025.1646141","type":"journal-article","created":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T10:43:04Z","timestamp":1755168184000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Prioritizing FDA approved therapeutics for treating sepsis phenotypes: A network modeling approach based on neutrophil proteomics"],"prefix":"10.3389","volume":"16","author":[{"given":"Jordan C.","family":"Langston","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingliang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Salim","family":"Merali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carmen","family":"Merali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Narender","family":"Singh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer L.","family":"Fisher","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Balabhaskar","family":"Prabhakarpandian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laurie E.","family":"Kilpatrick","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad F.","family":"Kiani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,8,14]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0287","article-title":"The third international consensus definitions for sepsis and septic shock (sepsis-3)","volume":"315","author":"Singer","year":"2016","journal-title":"JAMA"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201504-0781OC","article-title":"Assessment of global incidence and mortality of hospital-treated sepsis","volume":"193","author":"Fleischmann","year":"2016","journal-title":"Am J Respir Crit Care Med"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000000026","article-title":"Two decades of mortality trends among patients with severe sepsis: A comparative meta-analysis","volume":"42","author":"Stevenson","year":"2014","journal-title":"Crit Care Med"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(19)32989-7","article-title":"Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study","volume":"395","author":"Rudd","year":"2020","journal-title":"Lancet"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1097\/SHK.0000000000002047","article-title":"Leukocyte phenotyping in sepsis using omics, functional analysis and in silico modeling","volume":"59","author":"Langston","year":"2022","journal-title":"Shock"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201910-1911TR","article-title":"Endothelial responses in sepsis","volume":"202","author":"Joffre","year":"2020","journal-title":"Am J Respir Crit Care Med"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1038\/cmi.2013.21","article-title":"Of mice and men: what rodent models don\u2019t tell us","volume":"10","author":"Drake","year":"2013","journal-title":"Cell Mol Immunol"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1222878110","article-title":"Genomic responses in mouse models poorly mimic human inflammatory diseases","volume":"110","author":"Seok","year":"2013","journal-title":"PNAS"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1097\/SHK.0000000000000153","article-title":"Abandon the mouse research ship? 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