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March 27, 2026Frontiers in Immunology2 citationsOpen Access

Investigating the role of the TGF-β–SLC20A1 axis in the spatial heterogeneity of hepatocellular carcinoma through single-cell and spatial transcriptomics

JLJ P LiJAJingqi AnYJYong Bae Ji

Key Points

  • The aim is to explore the role of the TGF-β–SLC20A1 axis in the spatial heterogeneity of hepatocellular carcinoma.
  • Integrated spatial transcriptomics, single-cell RNA sequencing, and bulk RNA sequencing data.
  • Used non-negative matrix factorization for data analysis.
  • Conducted cell–cell communication analysis using CellChat.
  • Applied machine learning to identify key driver genes related to TGF-β activity.
  • Performed various functional assays (CCK-8, colony formation, wound-healing, Western blot) in HCC cell lines.
  • TGF-β signaling showed highest activity at the tumor–stroma interface.
  • Identified significant enrichment of cancer-associated fibroblasts and immunosuppressive cells in this region.
  • TGF-β interactions between tumor cells, CAFs, and immune cells were markedly enhanced.
  • SLC20A1 emerged as a critical regulator of proliferation, migration, and EMT in HCC cells.
  • Knockout of SLC20A1 suppressed malignant behaviors in HCC cell lines.

Abstract

Background Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy characterized by marked cellular and spatial diversity within the tumor microenvironment (TME). The transforming growth factor-β (TGF-β) signaling pathway plays a dual role in the initiation and progression of HCC. However, the spatial distribution characteristics and key regulatory mechanisms of TGF-β signaling within HCC tissues remain inadequately elucidated. Methods This study integrated spatial transcriptomics (ST), single-cell RNA sequencing (scRNA-seq), and bulk RNA-seq data to systematically characterize the spatial heterogeneity of the TGF-β signaling pathway in HCC. By combining non-negative matrix factorization (NMF), CellChat-based cell–cell communication analysis, and multi-algorithm machine learning approaches, we identified key driver genes closely associated with TGF-β activity. Subsequently, CCK-8 assays, colony formation, wound-healing, and Western blot experiments were performed in HCC cell lines to validate the biological functions of the identified gene. Results The results revealed that the TGF-β signaling pathway exhibited the highest activity at the tumor–stroma interface, which was enriched with cancer-associated fibroblasts (CAFs), immunosuppressive cells, and genes related to extracellular matrix (ECM) remodeling. CellChat analysis showed that TGF-β–TGFBR ligand–receptor interactions between tumor cells, CAFs, and immune cells were markedly enhanced, contributing to the formation of a localized immunosuppressive microenvironment. Machine learning analysis identified SLC20A1 as a key regulatory factor. Functional assays demonstrated that SLC20A1 enhances the proliferation, migration, and epithelial–mesenchymal transition (EMT) of HCC cells, whereas its knockout significantly suppresses these malignant phenotypes. Conclusion This study represents the first comprehensive integration of spatial and single-cell transcriptomics to uncover the spatial organization of TGF-β signaling in HCC and to identify the TGF-β–SLC20A1 axis as a critical driver of tumor invasion at the tumor–stroma interface. Our findings provide new mechanistic insights into tumor–stroma interactions and suggest a potential therapeutic target for precision treatment of HCC.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69c61f2515a0a509bde17b95https://doi.org/10.3389/fimmu.2026.1723334
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