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Prioritizing FDA approved therapeutics for treating sepsis phenotypes: A network modeling approach based on neutrophil proteomics.

作者信息

Langston Jordan C, Liu Dan, Yang Qingliang, Merali Salim, Merali Carmen, Singh Narender, Fisher Jennifer L, Prabhakarpandian Balabhaskar, Kilpatrick Laurie E, Kiani Mohammad F

机构信息

Department of Bioengineering, Temple University, Philadelphia, PA, United States.

Department of Mechanical Engineering, Temple University, Philadelphia, PA, United States.

出版信息

Front Immunol. 2025 Aug 14;16:1646141. doi: 10.3389/fimmu.2025.1646141. eCollection 2025.


DOI:10.3389/fimmu.2025.1646141
PMID:40895536
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12391923/
Abstract

INTRODUCTION: 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. METHODS: 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-protein interaction networks and prioritize hub targets. RESULTS: 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. DISCUSSION: 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.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/5fbb1e61fe99/fimmu-16-1646141-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/ce20d0134925/fimmu-16-1646141-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/84c82b23a3e8/fimmu-16-1646141-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/b4658560be98/fimmu-16-1646141-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/b40f23c643e3/fimmu-16-1646141-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/25b53d485e51/fimmu-16-1646141-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/b844ab6f8a8a/fimmu-16-1646141-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/5fbb1e61fe99/fimmu-16-1646141-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/ce20d0134925/fimmu-16-1646141-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/84c82b23a3e8/fimmu-16-1646141-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/b4658560be98/fimmu-16-1646141-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/b40f23c643e3/fimmu-16-1646141-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/25b53d485e51/fimmu-16-1646141-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/b844ab6f8a8a/fimmu-16-1646141-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/12391923/5fbb1e61fe99/fimmu-16-1646141-g007.jpg

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本文引用的文献

[1]
A transcriptome-based risk model in sepsis enables prognostic prediction and drug repositioning.

iScience. 2024-10-28

[2]
Alpha-1 antitrypsin targeted neutrophil elastase protects against sepsis-induced inflammation and coagulation in mice via inhibiting neutrophil extracellular trap formation.

Life Sci. 2024-9-15

[3]
Distinct functional neutrophil phenotypes in sepsis patients correlate with disease severity.

Front Immunol. 2024

[4]
The Proteomic Analysis of Cancer-Related Alterations in the Human Unfoldome.

Int J Mol Sci. 2024-1-26

[5]
The critical role of neutrophil-endothelial cell interactions in sepsis: new synergistic approaches employing organ-on-chip, omics, immune cell phenotyping and modeling to identify new therapeutics.

Front Cell Infect Microbiol. 2023

[6]
DrugBank 6.0: the DrugBank Knowledgebase for 2024.

Nucleic Acids Res. 2024-1-5

[7]
Highly Selective MIF Ketonase Inhibitor KRP-6 Diminishes M1 Macrophage Polarization and Metabolic Reprogramming.

Antioxidants (Basel). 2023-9-22

[8]
ExpressAnalyst: A unified platform for RNA-sequencing analysis in non-model species.

Nat Commun. 2023-5-24

[9]
Drug Repurposing Using Gene Co-Expression and Module Preservation Analysis in Acute Respiratory Distress Syndrome (ARDS), Systemic Inflammatory Response Syndrome (SIRS), Sepsis, and COVID-19.

Biology (Basel). 2022-12-15

[10]
LEUKOCYTE PHENOTYPING IN SEPSIS USING OMICS, FUNCTIONAL ANALYSIS, AND IN SILICO MODELING.

Shock. 2023-2-1

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