Decoding the Mechanisms of Hepatocellular Carcinoma Cancer Stem Cells and Identifying Potential Therapeutic Strategies Based on Single-cell Omics.
[BACKGROUND/AIM] Cancer stem cells (CSCs) play key roles in hepatocellular carcinoma (HCC) initiation, progression, therapeutic resistance, and recurrence, yet their cellular and spatial heterogeneity
APA
Tan X, Luo Q, et al. (2026). Decoding the Mechanisms of Hepatocellular Carcinoma Cancer Stem Cells and Identifying Potential Therapeutic Strategies Based on Single-cell Omics.. Cancer genomics & proteomics, 23(2), 281-299. https://doi.org/10.21873/cgp.20577
MLA
Tan X, et al.. "Decoding the Mechanisms of Hepatocellular Carcinoma Cancer Stem Cells and Identifying Potential Therapeutic Strategies Based on Single-cell Omics.." Cancer genomics & proteomics, vol. 23, no. 2, 2026, pp. 281-299.
PMID
41771574
Abstract
[BACKGROUND/AIM] Cancer stem cells (CSCs) play key roles in hepatocellular carcinoma (HCC) initiation, progression, therapeutic resistance, and recurrence, yet their cellular and spatial heterogeneity remains poorly understood. This study aimed to systematically characterize HCC-associated CSCs and identify prognostic biomarkers and potential therapeutic strategies using single-cell omics.
[MATERIALS AND METHODS] Single-cell RNA sequencing and spatial transcriptomics data were obtained from HCCDB v2.0. Malignant cells were re-clustered using Harmony-based batch correction, followed by uniform manifold approximation and projection (UMAP) and Louvain clustering. Copy number variation analysis validated malignant identities. CSC-associated molecular features were characterized using differential expression, gene regulatory network analysis (SCENIC), pathway enrichment (GSVA), pseudotime trajectory inference (Monocle, CytoTRACE2), and cell-cell communication analysis (CellChat). CSC-specific genes were integrated with GEO survival datasets (GSE76427, GSE14520) to construct a prognostic model, and potential CSC-targeting compounds were predicted using Connectivity Map.
[RESULTS] Six malignant subpopulations were identified, including a progenitor-like CSC subset expressing EPCAM, SOX9, and SOX4. Spatial transcriptomics revealed CSC enrichment at the tumor-stroma interface. CSCs exhibited strong stemness, metabolic plasticity, and invasive potential, with activation of WNT/β-catenin, TGF-β, Notch, EMT, MYC, and mTORC1 pathways. Key transcription factors (TEAD2, SOX4, HNF1B, KLF7) were identified. A 12-gene CSC-derived signature stratified patients into distinct risk groups with significantly different overall survival. Several candidate compounds, including fluspirilene, genistein, and daunorubicin, showed potential CSC-suppressive activity.
[CONCLUSION] This study provides a comprehensive single-cell-based atlas of CSCs in HCC, highlighting their spatial niches, regulatory programs, and clinical relevance. The identified prognostic signature and candidate drugs offer promising avenues for CSC-targeted therapies.
[MATERIALS AND METHODS] Single-cell RNA sequencing and spatial transcriptomics data were obtained from HCCDB v2.0. Malignant cells were re-clustered using Harmony-based batch correction, followed by uniform manifold approximation and projection (UMAP) and Louvain clustering. Copy number variation analysis validated malignant identities. CSC-associated molecular features were characterized using differential expression, gene regulatory network analysis (SCENIC), pathway enrichment (GSVA), pseudotime trajectory inference (Monocle, CytoTRACE2), and cell-cell communication analysis (CellChat). CSC-specific genes were integrated with GEO survival datasets (GSE76427, GSE14520) to construct a prognostic model, and potential CSC-targeting compounds were predicted using Connectivity Map.
[RESULTS] Six malignant subpopulations were identified, including a progenitor-like CSC subset expressing EPCAM, SOX9, and SOX4. Spatial transcriptomics revealed CSC enrichment at the tumor-stroma interface. CSCs exhibited strong stemness, metabolic plasticity, and invasive potential, with activation of WNT/β-catenin, TGF-β, Notch, EMT, MYC, and mTORC1 pathways. Key transcription factors (TEAD2, SOX4, HNF1B, KLF7) were identified. A 12-gene CSC-derived signature stratified patients into distinct risk groups with significantly different overall survival. Several candidate compounds, including fluspirilene, genistein, and daunorubicin, showed potential CSC-suppressive activity.
[CONCLUSION] This study provides a comprehensive single-cell-based atlas of CSCs in HCC, highlighting their spatial niches, regulatory programs, and clinical relevance. The identified prognostic signature and candidate drugs offer promising avenues for CSC-targeted therapies.
MeSH Terms
Humans; Carcinoma, Hepatocellular; Liver Neoplasms; Neoplastic Stem Cells; Single-Cell Analysis; Biomarkers, Tumor; Prognosis; Transcriptome; Gene Expression Regulation, Neoplastic; Gene Regulatory Networks; Gene Expression Profiling
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