Cancer Cell Int. 2026 May 14. doi: 10.1186/s12935-026-04330-2. Online ahead of print.

ABSTRACT

BACKGROUND: Liver hepatocellular carcinoma (LIHC) is a common malignancy, yet the core genes driving its progression and potential therapeutic targets remain insufficiently explored. Ribosome biogenesis (RB) is a critical biological process linked to various cancers; however, its systematic role in LIHC remains unclear.

METHODS: This study integrated LIHC single-cell RNA-Seq, bulk RNA-Seq, and spatial transcriptomic data with ribosome biogenesis-related gene sets to construct a single-cell atlas of LIHC. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to characterize myeloid cell subsets. Furthermore, an LIHC prognostic risk model based on RB-related genes was developed using 117 machine-learning algorithm combinations. Key findings were subsequently corroborated through experimental validation and clinical sample analysis.

RESULTS: We identified a distinct macrophage subpopulation with high ribosome biogenesis activity, termed ribosome biogenesis-active macrophages (RAMs). These cells exhibited strong communication with inflammatory macrophages, potentially mediated by MIF-related receptor-ligand interactions. We further constructed an 8-gene prognostic model (PA2G4, GNL2, PWP1, DDX49, NOC4L, GDI2, CST7, and RCL1), which showed good predictive performance. Drug sensitivity analysis suggested that the high-risk group may be more responsive to several agents, including docetaxel. Among these genes, GNL2 was selected for further investigation. Elevated GNL2 expression was associated with increased stemness features in myeloid cells. Molecular docking analysis identified several candidate compounds with potential binding affinity to GNL2. Functionally, GNL2 knockdown in macrophages reduced TGF-β and TNF-α expression and was associated with decreased proliferation, migration, and invasion of LIHC cells.

CONCLUSION: We identified a highly active ribosome biogenesis-macrophage subpopulation (RAM), and constructed a robust risk model to aid in the diagnosis, prognosis, and treatment of LIHC. GNL2 is associated with increased expression of TGF-β and TNF-α and may contribute to LIHC progression.

PMID:42135716 | DOI:10.1186/s12935-026-04330-2

Neoplasia. 2026 May;75:101298. doi: 10.1016/j.neo.2026.101298. Epub 2026 Mar 20.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits high recurrence rates and limited therapeutic options. Endothelial cell-specific molecule 1 (ESM1) and angiopoietin-like 4 (ANGPTL4) are implicated in tumor progression, yet their synergistic role in HCC lipid metabolism and angiogenesis remains unexplored.

METHODS: We integrated multi-omics approaches, including RNA sequencing, metabolomics, and immunoprecipitation-mass spectrometry, in HCC cell lines and patient-derived xenograft models. Key experiments involved Co-IP, Western blotting, tube formation assays, and clinical tissue microarray analysis to validate the ESM1-ANGPTL4-FASN-trioleate axis.

RESULTS: ESM1 and ANGPTL4 formed a positive feedback loop, stabilizing fatty acid synthase (FASN) to promote trioleate synthesis. Trioleate activated the NF-κB/IL-17 pathway in HCC cells and upregulated CD99 in endothelial cells, driving angiogenesis. In vivo, ESM1/ANGPTL4 knockdown suppressed tumor growth, which was rescued by trioleate supplementation. Clinical data revealed elevated ESM1/ANGPTL4 expression in bevacizumab-resistant HCC, correlating with poor prognosis.

CONCLUSIONS: The ESM1-ANGPTL4-FASN-trioleate axis orchestrates metabolic reprogramming and endothelial activation, representing a promising therapeutic target. Future studies should explore combination therapies targeting this axis and overcoming bevacizumab resistance in HCC.

PMID:41864037 | PMC:PMC13019581 | DOI:10.1016/j.neo.2026.101298