Role of immune cell subsets in liver fibrosis through single-cell RNA sequencing and array

BackgroundImmune-inflammatory responses and dysregulation play a key role in liver fibrosis (LF) and cirrhosis progression, but the phenotypic and functional dynamics of immune cell populations remain poorly characterized.MethodsLF-related data from the GEO database were analyzed using ssGSEA to quantify immune cell infiltration and Kaplan-Meier analysis to assess the prognostic value of specific immune cell populations. Single-cell RNA sequencing data were used to establish an immune cell atlas, identify cell types linked to poor prognosis, and validate characteristic genes. Additionally, the functional distinctions and cell-cell interactions were further investigated.ResultsLF patients showed increased infiltration of monocytes, T cells, and NK cells, associated with poor outcomes. Genes linked to poor prognosis were markedly expressed in mononuclear phagocytes, T cells, and innate lymphoid cells (ILCs), which were further classified into 24 distinct subpopulations. Pro-fibrotic scar-associated macrophages and pro-inflammatory ILCs increased, while anti-inflammatory Kupffer cells and protective ILCs decreased. CCR7-expressing T cells and depletion-related genes were elevated in peripheral blood mononuclear cells, with ILCs showing increased expression of S1PR4 and S1PR5. Furthermore, macrophages expressing CD9 and IGFBP7 were identified.ConclusionThis study highlights immune heterogeneity in LF, identifying key cell populations linked to disease progression, offering potential immunotherapy targets.

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Publication Details

Journal
Cancer Biomarkers
Published
2025-09-01
DOI
https://doi.org/10.1177/18758592251374861
Citations
2
Primary Topic
Liver Diseases and Immunity
Type
article
Field-Weighted Citation Impact
2.64
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article

Role of immune cell subsets in liver fibrosis through single-cell RNA sequencing and array

Jingwen Zhao, Xin Chen, Bo Yang, Junjie Yuan
2 citations
Cancer Biomarkers
Liver Diseases and Immunity
2.64
article

Role of immune cell subsets in liver fibrosis through single-cell RNA sequencing and array

Jingwen Zhao, Xin Chen, Bo Yang, Junjie Yuan
article en
2 citations

Abstract

BackgroundImmune-inflammatory responses and dysregulation play a key role in liver fibrosis (LF) and cirrhosis progression, but the phenotypic and functional dynamics of immune cell populations remain poorly characterized.MethodsLF-related data from the GEO database were analyzed using ssGSEA to quantify immune cell infiltration and Kaplan-Meier analysis to assess the prognostic value of specific immune cell populations. Single-cell RNA sequencing data were used to establish an immune cell atlas, identify cell types linked to poor prognosis, and validate characteristic genes. Additionally, the functional distinctions and cell-cell interactions were further investigated.ResultsLF patients showed increased infiltration of monocytes, T cells, and NK cells, associated with poor outcomes. Genes linked to poor prognosis were markedly expressed in mononuclear phagocytes, T cells, and innate lymphoid cells (ILCs), which were further classified into 24 distinct subpopulations. Pro-fibrotic scar-associated macrophages and pro-inflammatory ILCs increased, while anti-inflammatory Kupffer cells and protective ILCs decreased. CCR7-expressing T cells and depletion-related genes were elevated in peripheral blood mononuclear cells, with ILCs showing increased expression of S1PR4 and S1PR5. Furthermore, macrophages expressing CD9 and IGFBP7 were identified.ConclusionThis study highlights immune heterogeneity in LF, identifying key cell populations linked to disease progression, offering potential immunotherapy targets.

Cancer BiomarkersVol. 42(9)
Tianjin Medical University General Hospital (CN), Guizhou Aerospace Power Science & Tech (China) (CN)
Openalex Percentile: Top 9%
Liver Diseases and Immunity
2.64
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Role of immune cell subsets in liver fibrosis through single-cell RNA sequencing and array — Jingwen Zhao, Xin Chen, et al. · Cancer Biomarkers (2025) | TGRS Research Map | TGRS