Single-cell transcriptomics identifies an

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer with complex tumor-immune interactions. This heterogeneity, particularly in tumor and immune cells, complicates treatment and prognostic evaluation. Although recent studies have revealed distinct tumor cell states and immune dysfunction in HCC, the molecular basis underlying tumor aggressiveness remains poorly understood. A deeper understanding of the molecular and functional diversity of both tumor and immune cell populations, especially the identification of stem-like tumor subpopulations and immunosuppressive mechanisms, along with the development of robust prognostic biomarkers, is essential for advancing precision oncology and improving clinical outcomes. Methods: We integrated three publicly available single-cell RNA sequencing (scRNA-seq) datasets from GEO to delineate the cellular architecture of the HCC tumor microenvironment. Unsupervised clustering and dimensionality reduction were employed to identify major cell types and tumor subpopulations. Functional annotation was performed using canonical markers, Monocle, CytoTRACE, and AUCell scoring. Results: Six major cell types were identified in HCC TME. Tumor cells were subdivided into three distinct clusters: Tumor_C0, Tumor_C1 and Tumor_C2. Tumor_C2 showed the highest stemness, pro-metastatic activity and immunogenic cell death signatures. Conclusion: We identified a proliferative, stem-like tumor cell subpopulation (Tumor_C2) in HCC characterized by high