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Cellular Senescence and Immune Dysregulation in Acute-on-Chronic Liver Failure: A Case Report Integrating Single-Cell and Spatial Transcriptomic Profiling

IJMRB | Published: September 6, 2026 | Vol. 5 Issue 5 | ISSN: 3108-1428
Hao Sun1✉,
Gaoyang Guo2,
Liangyu Li2,
Jinze Yu3,
Wei Wang4,
Bing Liu5,
Yuquan Li6,
Keyang Xu7
1 College of Animal Sciences, (ZJU-Xinchang Joint Innovation Centre (TianMu Laboratory)),Zhejiang University,China;Wolfson Institute for Biomedical Research, Division of Medicine,University College London,London, United Kingdom.
2 Faculty of Information Science and Technology (FTSM), University Kebangsaan Malaysia (UKM).
3 Computer Science and Communication Engineering, Global Center for Science and Engineering, Faculty of Science, Waseda University, Tokyo, Japan.
4 Center for Precision Health, School of Medical and Health Science, Edith Cowan University
5 College of Animal Sciences, Zhejiang University, Hangzhou, China.
6 College of Computer Science and Technology, Guizhou University, Guizhou, China.
7 Faculty of Chinese Medicine, State Key Laboratory of Mechanism and Quality of Chinese Medicine, Macau University of Science and Technology, Macau, China.
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Abstract

Background: Acute-on-chronic liver failure (ACLF) is a clinical syndrome characterized by acute decompensation of cirrhosis, systemic inflammation, and high short-term mortality (1). The underlying mechanisms involve a complex interplay between cellular senescence, immune dysregulation, and multi-organ failure, yet the spatiotemporal dynamics within the liver tissue remain poorly understood (2). Case presentation: We report a 58-year-old male with chronic hepatitis B-related cirrhosis who presented with acute jaundice, ascites, hepatic encephalopathy, and coagulopathy. He met the CLIF-C criteria for ACLF grade 2 (13). Liver biopsy and peripheral blood samples were obtained within 48 hours of admission. We performed single-cell RNA sequencing (scRNA-seq) on 87,046 intrahepatic cells, spatial transcriptomics (10x Visium) on liver tissue sections, and integrated these with clinical and laboratory parameters. Methods and Results: scRNA-seq identified 17 distinct cell clusters, including a prominent population of senescent hepatocytes (p16⁺, p21⁺, γH2AX⁺) localized to fibrotic septa (14, 15). Spatial transcriptomics revealed a sharp senescence score gradient from fibrotic niches (score >0.8) to normal zones (score <0.2) (9, 10). The immune landscape was dominated by CXCR2⁺ neutrophils, CD163⁺ monocytes, and exhausted CD8⁺ T cells (PD-1⁺TIM-3⁺LAG3⁺, 65.3% of total CD8⁺) (17, 41). NicheNet and CellChat analyses identified CCL2-CCR2 and CXCL8-CXCR1/2 as the strongest communication axes between senescent hepatocytes and myeloid cells (3, 11). TREM2⁺ Kupffer cells emerged as a novel maladaptive population restricted to fibrotic areas (47). Trajectory analysis showed a directional progression from normal hepatocytes through an intermediate state to fully senescent cells, with concomitant upregulation of SASP factors (IL-6, IL-1β, TNF-α, TGF-β1) (4,5). Correlation matrix demonstrated strong positive correlations between senescence markers and MELD score (r=0.88, p<0.001) and INR (r=0.85, p<0.001) (36). Discussion: This integrative case reveals that fibrotic niches act as pathological hotspots where senescent hepatocytes orchestrate intrahepatic inflammation via SASP-mediated recruitment of dysfunctional myeloid cells, while adaptive immunity succumbs to exhaustion (6, 7). The identification of TREM2⁺ macrophages and the dominant chemokine axes provides novel mechanistic insights and therapeutic targets, including senolytics, CXCR2 antagonists, and checkpoint modulators (48, 49, 50). Conclusion: Spatially organized senescence–immune crosstalk drives ACLF pathogenesis. Multi-omics profiling of individual cases can uncover disease mechanisms and guide precision medicine approaches (55).
Keywords: Acute-on-chronic liver failure, cellular senescence, single-cell RNA sequencing, spatial transcriptomics, immune exhaustion, senescent-associated secretory phenotype.

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🔓 Open Access | Published by IR Publishing Group. This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

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