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

Gut. 2026 Feb 9;75(3):576-587. doi: 10.1136/gutjnl-2025-337506.

ABSTRACT

BACKGROUND: Current guidelines recommend a two-step approach for risk stratification of metabolic dysfunction-associated steatotic liver disease (MASLD), starting with Fibrosis-4 index (FIB-4) followed by liver stiffness measurement (LSM) using vibration-controlled transient elastography (VCTE).

OBJECTIVE: To evaluate this approach for predicting advanced fibrosis and liver-related events (LREs) in patients with type 2 diabetes (T2D).

DESIGN: A prospective liver biopsy cohort of T2D patients with histologically confirmed MASLD from seven centres in China was used to assess diagnostic performance for advanced fibrosis. The international VCTE-Prognosis cohort, including T2D patients with MASLD who underwent VCTE at 16 centres in the USA, Europe and Asia, with longitudinal follow-up, was used to assess LREs, defined as hepatic decompensation or hepatocellular carcinoma.

RESULTS: 4781 participants were included. In the liver biopsy cohort (n=352; 22.2% with advanced fibrosis), applying LSM thresholds of <8 kPa and >12 kPa after FIB-4 classified patients into 63.4% low-risk, 9.4% intermediate-risk and 27.3% high-risk, with a correct classification rate of 71%. In the VCTE-Prognosis cohort (n=4429; median follow-up 51.3 (IQR 27.4-70.7) months), 140 (3.2%) patients developed LREs (110 (2.5%) with hepatic decompensation and 59 (1.3%) with hepatocellular carcinoma). The two-step approach classified 72.6%, 6.8% and 20.6% of patients into low-risk, intermediate-risk and high-risk groups, with corresponding 5-year cumulative LRE incidences of 0.7%, 0.9% and 11.8%. Refining classification of intermediate FIB-4 patients using LSM <10 kPa (low-risk) and >15 kPa (high-risk) reduced the intermediate-risk group to 5.6% while preserving predictive accuracy.

CONCLUSION: The non-invasive two-step approach of FIB-4 followed by LSM effectively stratifies MASLD-related advanced fibrosis and LREs risk in T2D. Applying LSM cut-offs of 10 and 15 kPa further optimises risk stratification for future LREs.

PMID:41911049 | DOI:10.1136/gutjnl-2025-337506

J Proteome Res. 2026 Apr 3;25(4):2014-2023. doi: 10.1021/acs.jproteome.5c00983. Epub 2026 Mar 17.

ABSTRACT

OBJECTIVE: 19-Hydroxybufalin (19-H) is a natural bioactive compound with anticancer potential, but its molecular target and mechanism of action remain unclear. This study aimed to systematically evaluate its antigastric cancer activity and identify potential molecular targets.

METHODS: The antitumor effect of 19-H was evaluated in both in vitro and in vivo models. Multiomics analysis, thermal proteome profiling, molecular docking, and molecular dynamics simulations were employed to elucidate the mechanism of action. Functional assays were further conducted to validate the key target.

RESULTS: 19-H exhibited nanomolar-level inhibitory activity against various gastric cancer cell lines, significantly suppressing tumor growth in subcutaneous xenograft and patient-derived xenograft models. Multiomics analysis revealed that 19-H reshaped metabolic pathways in gastric cancer. TPP screening identified PLPP2 as a potential target with significantly increased thermal stability upon 19-H treatment. Molecular simulations further revealed that 19-H binds stably to the α-helical region of PLPP2.

CONCLUSIONS: 19-H exerts its antigastric cancer effect by targeting PLPP2 and remodeling the metabolic network. PLPP2 may represent a novel therapeutic target for gastric cancer.

PMID:41842934 | DOI:10.1021/acs.jproteome.5c00983