Evidence map›Paper›PMID 40895536›Full record

ArticleFrontiers in immunology2025

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

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

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jordan C LangstonDepartment of Bioengineering, Temple University, Philadelphia, PA, United States.
Dan LiuDepartment of Bioengineering, Temple University, Philadelphia, PA, United States.
Qingliang YangDepartment of Mechanical Engineering, Temple University, Philadelphia, PA, United States.
Salim MeraliSchool of Pharmacy, Temple University, Philadelphia, PA, United States.
Carmen MeraliSchool of Pharmacy, Temple University, Philadelphia, PA, United States.
Narender SinghBiotechnology, Energy, and Materials Division, CFD Research Corporation, Huntsville, AL, United States.
Jennifer L FisherBiotechnology, Energy, and Materials Division, CFD Research Corporation, Huntsville, AL, United States.
Balabhaskar PrabhakarpandianBiotechnology, Energy, and Materials Division, CFD Research Corporation, Huntsville, AL, United States.
Laurie E KilpatrickCenter for Inflammation and Lung Research, Department of Microbiology, Immunology and Inflammation, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States.
Mohammad F KianiDepartment of Bioengineering, Temple University, Philadelphia, PA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

NeutrophilsProteomicsSepsisComputational BiologyHumansPhenotypeProtein Interaction MapsUnited StatesUnited States Food and Drug Administrationbioinformaticsdrug repurposingneutrophilsorgan on chipproteomicssepsis

Identifiers

PMID40895536
PMCPMC12391923

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.