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Peer-reviewedCC BY 4.0Frontiers in Immunology

Mechanistic insights and translational perspectives on liver fibrosis through single-cell transcriptomics

  • Weiwei Lu1,2
  • Jun Xu3
  • Kexin Wang1,2
  • Yumu Chen1,2
  • Alessandro Cherubini4
  • Luca Valenti4,5
  • Shusen Zheng1,2,3,6,7
  • Zhengtao Liu1,2,6,7
7 affiliations
  1. 1Key Laboratory of Artificial Organs and Computational Medicine in Zhejiang Province, Shulan International Medical College, Zhejiang Shuren University
  2. 2Shulan (Hangzhou) Hospital, Shulan International Medical College, Zhejiang Shuren University
  3. 3Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University
  4. 4Precision Medicine Lab, Biological Resource Center and Transfusion Medicine, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Ca’ Granda Ospedale Maggiore Policlinico
  5. 5Department of Pathophysiology and Transplantation, Università degli Studi di Milano
  6. 6National Health Commission of the People's Republic of China Key Laboratory of Combined Multi-Organ Transplantation, Key Laboratory of the Diagnosis and Treatment of Organ Transplantation, First Affiliated Hospital, School of Medicine, Zhejiang University
  7. 7Key Laboratory of Organ Transplantation, Zhejiang Province, First Affiliated Hospital, School of Medicine, Zhejiang University
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Abstract

Liver fibrosis is a defining feature of chronic liver diseases and can progress to cirrhosis and liver failure. Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity and multicellular interactions during fibrogenesis. In this narrative review, we analyzed published single-cell transcriptomic studies from experimental models and human cohorts, focusing on cell-type–specific programs, cell-state trajectories inferred by Monocle, and intercellular communication networks predicted using CellChat and CellPhoneDB. Hepatic stellate cells (HSCs) consistently emerged as the primary extracellular matrix–producing cells, with conserved activation signatures involving collagen synthesis, Phosphatidylinositol 3-kinase–Protein kinase B (PI3K–AKT) signaling, and matrix organization. Macrophage analyses identified fibrosis-associated subsets, including CD9 ⁺ and TREM2 ⁺ scar-associated macrophages (SAMs), which regulate inflammation, angiogenesis, and stromal remodeling. Liver sinusoidal endothelial cells undergo capillarization and transcriptional reprogramming linked to WNT signaling and antigen presentation. B cells exhibit activation signatures related to B-cell receptor signaling. Trajectory analyses infer potential cell-state transitions based on transcriptional similarity from quiescent to pathogenic states, including stepwise HSC activation and monocyte-to-macrophage differentiation. Cell–cell communication analysis highlights HSC–macrophage interactions, with key axes such as predicted Chemokine ligand 2–chemokine receptor 2 (CCL2–CCR2) and transforming growth factor-β–transforming growth factor-β receptor (TGFβ–TGFβR) signaling interactions that may contribute to fibrogenic communication networks. These findings define conserved multicellular programs and support integrated multi-omics approaches for biomarker discovery and therapy.

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Cite

BibTeXRIS
BibTeX
@article{lu2026mechanistic,
  title = {{Mechanistic insights and translational perspectives on liver fibrosis through single-cell transcriptomics}},
  author = {Weiwei Lu and Jun Xu and Kexin Wang and Yumu Chen and Alessandro Cherubini and Luca Valenti and Shusen Zheng and Zhengtao Liu},
  journal = {Frontiers in Immunology},
  year = {2026},
  month = oct,
  doi = {10.3389/fimmu.2026.1954491},
  url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1954491/full},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Mechanistic insights and translational perspectives on liver fibrosis through single-cell transcriptomics
AU  - Weiwei Lu
AU  - Jun Xu
AU  - Kexin Wang
AU  - Yumu Chen
AU  - Alessandro Cherubini
AU  - Luca Valenti
AU  - Shusen Zheng
AU  - Zhengtao Liu
PY  - 2026
DA  - 2026/10/27
JO  - Frontiers in Immunology
DO  - 10.3389/fimmu.2026.1954491
UR  - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1954491/full
AB  - Liver fibrosis is a defining feature of chronic liver diseases and can progress to cirrhosis and liver failure. Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity and multicellular interactions during fibrogenesis. In this narrative review, we analyzed published single-cell transcriptomic studies from experimental models and human cohorts, focusing on cell-type–specific programs, cell-state trajectories inferred by Monocle, and intercellular communication networks predicted using CellChat and CellPhoneDB. Hepatic stellate cells (HSCs) consistently emerged as the primary extracellular matrix–producing cells, with conserved activation signatures involving collagen synthesis, Phosphatidylinositol 3-kinase–Protein kinase B (PI3K–AKT) signaling, and matrix organization. Macrophage analyses identified fibrosis-associated subsets, including CD9 ⁺ and TREM2 ⁺ scar-associated macrophages (SAMs), which regulate inflammation, angiogenesis, and stromal remodeling. Liver sinusoidal endothelial cells undergo capillarization and transcriptional reprogramming linked to WNT signaling and antigen presentation. B cells exhibit activation signatures related to B-cell receptor signaling. Trajectory analyses infer potential cell-state transitions based on transcriptional similarity from quiescent to pathogenic states, including stepwise HSC activation and monocyte-to-macrophage differentiation. Cell–cell communication analysis highlights HSC–macrophage interactions, with key axes such as predicted Chemokine ligand 2–chemokine receptor 2 (CCL2–CCR2) and transforming growth factor-β–transforming growth factor-β receptor (TGFβ–TGFβR) signaling interactions that may contribute to fibrogenic communication networks. These findings define conserved multicellular programs and support integrated multi-omics approaches for biomarker discovery and therapy.
SN  - 1664-3224
ER  -