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Updated: May 25, 2025

Isolation and Enrichment of Liver Progenitor Subsets Identified by a Novel Surface Marker Combination
Published on: February 18, 2017
Integrative single-cell and spatial transcriptome analysis reveals heterogeneity of human liver progenitor cells
Chuanjun Liu1,2, Kai Wang3, Junpu Mei4
1College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.
Background:
Liver progenitor cells (LPCs) with bipotential differentiation capacities are essential for restoring liver homeostasis and hepatocyte population after damage. However, the low proportion and shared markers with epithelial cells make studying LPC heterogeneity difficult, especially in humans. To address this gap, we explored over 259,400 human liver single cells across 4 conditions (fetal, healthy, cirrhotic, and HCC-affected livers).
Methods:
Human liver tissue samples were analyzed using spatial transcriptomics sequencing technologies to describe the heterogeneity of LPCs. Liver tissue was characterized by LPC heterogeneity at single-cell resolution by employing cellular modules, differentiation trajectories, and gene co-expression patterns.
Results:
We annotated and identified 1 LPC cluster, 3 LPC subpopulations, and 4 distinct cellular modules, indicating the heterogeneity within LPC and the diversity between LPCs and epithelial cells. LPCs showed spatial colocalization with cholangiocytes and comprised a small proportion (2.95±1.91%) within the merged epithelial cells and LPC populations, exhibiting marked differences in marker expression patterns compared to those in mice. LPCs exhibited distinct cellular states in functional restoration, activation, proliferation, and cell transition. Additionally, the gene co-expression network of LPCs exhibited 3 unique modules, reflecting the distinct connectivity of genes encoding apolipoproteins and heat shock proteins in the gene co-expression network modules.
Conclusions:
Our study provides valuable insights into the multifaceted heterogeneity of human LPCs. Future studies focusing on spatial gene expression dynamics will contribute to our understanding of the spatial arrangement of liver regeneration.
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