Evidence map›Paper›PMID 41111514›Full record

ArticleFrontiers in pharmacology2025

Decoding monocyte heterogeneity in sepsis: a single-cell apoptotic signature for immune stratification and guiding precision therapy.

Wenjuan Duan, Qi Chen, Wei Li, Haiying Zhou, Xiaorong Deng, Yan Zhang

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Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Wenjuan Duan *Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China.
Qi Chen *School of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.
Wei Li *School of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.
Haiying ZhouSchool of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.
Xiaorong DengSchool of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.
Yan ZhangSchool of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The effectiveness of immunomodulatory therapies in sepsis is often hampered by profound and patient-specific immune heterogeneity. Classical monocytes play a central role in the progression toward sepsis-induced immunoparalysis, with their apoptotic rate serving as a sensitive marker of immune dysfunction. Traditional bulk transcriptomic approaches fail to resolve this complexity. Here, we harness single-cell RNA sequencing to delineate the apoptotic landscape of classical monocytes and identify robust molecular biomarkers for immunological stratification and targeted intervention. Methods: We integrated single-cell and bulk transcriptomic data from four independent cohorts. A machine learning pipeline incorporating SVM, RF, XGB, and GLM algorithms was used to identify hub genes associated with monocyte apoptosis. A diagnostic nomogram was constructed based on the selected gene signature and validated across external datasets. Clinical relevance was confirmed through Western blot analysis of purified monocytes from sepsis patients and healthy controls. Results: A four-gene signature (G0S2, GZMA, ITM2A, PAG1) emerged as a specific apoptotic fingerprint of classical monocytes. The diagnostic model based on these signature genes demonstrated excellent discriminatory performance, effectively stratifying patients into high-risk and low-risk groups (AUC >0.8 across multiple validation cohorts), with each risk group exhibiting distinctly different immune states. High-risk patients exhibited a pro-inflammatory transcriptomic profile with elevated apoptotic pathway activity (e.g., neutrophil degranulation), whereas the low-risk group showed enrichment in adaptive immunity and T cell receptor signaling. Protein-level validation in clinical samples corroborated the transcriptomic findings. Conclusion: This study elucidates a critical facet of immune heterogeneity in sepsis through the identification of a validated, four-gene apoptotic signature in classical monocytes. Beyond its diagnostic utility, this signature serves as a molecular indicator of immune state, enabling refined patient stratification. These findings lay the groundwork for precision immunopharmacology, where apoptosis-targeted or anti-inflammatory therapies can be tailored to individual immune profiles.

Indexed as

apoptoticbulk RNA-seqclassical monocytesmonocyteScRNA-seqsepsis

Identifiers

PMID41111514
PMCPMC12531134

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