Integrative single-cell transcriptomic and multi-dimensional bioinformatic analysis reveals proliferation-associated gene expression signatures and cellular heterogeneity in hepatocellular carcinoma.

backgroundHepatocellular carcinoma (HCC) remains one of the most lethal malignancies worldwide, characterized by substantial molecular heterogeneity and limited therapeutic options. Understanding the complex gene expression landscapes and cellular composition within the tumor microenvironment is critical for identifying novel biomarkers and therapeutic targets.

methodsWe performed comprehensive single-cell RNA sequencing (scRNA-seq, GSE149614) to characterize cellular heterogeneity and identify distinct cell populations. Multi-dimensional bioinformatic analyses were employed to compare proliferation-related gene expression patterns between highly invasive MHCC97H and less aggressive HepG2 cell lines, focusing on five key genes: AURKA, FANCD2, HELLS, RRM2, and STMN1. Advanced visualization techniques, including UMAP projections, correlation matrices, hierarchical clustering, and density plots, were utilized to map transcriptomic relationships and identify molecular subtypes. Quantitative real-time PCR validation was performed across normal hepatic (LO2) and three HCC cell lines (Huh7, HepG2, MHCC97H) to experimentally confirm transcriptomic findings.

resultsSingle-cell analysis revealed dynamic shifts in cellular composition across samples, with two major cell populations (W1 and W2) showing distinct temporal patterns. MBOAT2-expressing cells exhibited substantial heterogeneity, segregating into five to six functionally distinct subtypes with varying transcriptional signatures. Comparative analysis demonstrated that MHCC97H cells consistently exhibited elevated expression of all five proliferation-related genes compared to HepG2 cells, with STMN1 showing the most pronounced differential expression (approximately 100 vs. 40 units). Correlation analysis revealed moderate positive correlations among proliferation markers (r = 0.14-0.47), suggesting coordinated but not strictly coupled regulation. Three-dimensional expression space analysis identified discrete cellular clusters with distinct transcriptional programs. Hierarchical clustering of approximately 30 samples revealed at least three major molecular subtypes with varying expression signatures. qPCR validation confirmed progressive upregulation of all five genes from normal hepatocytes through increasingly malignant HCC cell lines, with STMN1 and RRM2 demonstrating the most dramatic elevation in highly invasive MHCC97H cells.

conclusionsThis integrative multi-scale analysis reveals complex proliferation-associated gene expression patterns and substantial cellular heterogeneity within hepatocellular carcinoma. STMN1 and RRM2 emerge as dominant markers of proliferative reprogramming and promising candidate therapeutic targets warranting further functional investigation in HCC progression.