Multimodal Single-Cell Network Analysis Identifies Basigin/Cluster of Differentiation 147 as a Tumor-Associated Signaling Hub in Hepatocellular Carcinoma.

Background and Aims: Hepatocellular carcinoma (HCC) ranks among the leading causes of cancer mortality globally, driven by late diagnosis and inadequate sensitivity of biomarkers like α-fetoprotein for early or indeterminate lesions. Single-cell RNA sequencing (scRNA-seq) enables precise mapping of tumor heterogeneity and early malignant transitions. This study aims to apply scRNA-seq analysis to detect clinically important molecular patterns that define the early stages of malignant transformation in HCC and facilitate the diagnosis of small or ambiguous lesions. Methods: Here, we integrated 2 independent scRNA-seq datasets (GSE149614 and GSE189903) from non-tumor and HCC tissues. Following batch correction, hepatocyte subpopulations were delineated via clustering, differential expression, pseudotime, and Cellular Trajectory Reconstruction Analysis using gene Counts and Expression analyses to reconstruct normal-to-malignant trajectories. High-dimensional weighted gene coexpression network analysis identified stage-correlated modules, while CellChat and protein-protein interaction networks revealed intercellular signaling. Candidate expression was validated in paired human liver specimens via quantitative immunofluorescence. Results: We uncovered a hepatocyte continuum with escalating stemness and oncogenic activation (MYC, E2F, G2M pathways). The Hep-M20 module, most strongly stage-associated, pinpointed Basigin (BSG)/cluster of differentiation 147 (CD147) as a hub gene with monotonic pseudotime upregulation and stemness correlation (ρ = 0.48, Conclusion: This multimodal analysis identifies BSG/CD147 as a tumor-associated signaling hub linked to hepatocyte state transitions and microenvironmental remodeling with potential utility for enhancing detection of small lesions in targeted imaging contexts.