J Hepatocell Carcinoma. 2026 Aug 26;13:615781. doi: 10.2147/JHC.S615781. eCollection 2026.

ABSTRACT

OBJECTIVE: Hepatocellular carcinoma (HCC) has poor prognosis and variable immunotherapy response. Resveratrol exhibits anti-HCC activity, but its direct targets and association with immunotherapy response are unclear. This study identifies core resveratrol targets in HCC and evaluates their prognostic and predictive value.

METHODS: Resveratrol targets were intersected with TCGA-LIHC differentially expressed genes. A prognostic risk model was built using LASSO-Cox regression. Drug-target binding was assessed by molecular dynamics simulations and qRT-PCR. Single-cell and spatial transcriptomics, cell-cell communication, and a pan-immunotherapy cohort were used to investigate KIF11. An HCC mouse model validated immunomodulatory effects via flow cytometry.

RESULTS: Thirty-four resveratrol-associated targets were identified, enriched in metabolism pathways. A nine-gene risk model showed robust prognostic performance. Resveratrol stably binds to KIF11's ATP-binding pocket. KIF11 is overexpressed in malignant hepatocytes and proliferating T cells; KIF11⁺ cells orchestrate VEGF-mediated microenvironment remodeling. High KIF11 expression correlated with poor prognosis but predicted superior survival in the immunotherapy cohort, a phenomenon attributed to the observation that KIF11-high tumors exhibit both enhanced immunogenicity and active immunosuppression. In vivo, resveratrol enhanced CD8⁺ T cell infiltration, proliferation, effector function, and central memory T cells, while reducing Tregs.

CONCLUSION: KIF11 drives HCC progression and predicts immunotherapy response. It is a candidate direct resveratrol target and a potential biomarker for patient stratification in immune checkpoint therapy, although further experimental validation is warranted.

PMID:42670538 | PMC:PMC13526380 | DOI:10.2147/JHC.S615781

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

World J Oncol. 2026 Mar 5;17(2):247-255. doi: 10.14740/wjon2689. eCollection 2026 Apr.

ABSTRACT

BACKGROUND: We aimed to evaluate the potential association between genetically predicted vanin-2 (VNN2) expression and lung adenocarcinoma (LUAD) risk, and to explore the immune cell subtype that may underlie this relationship.

METHODS: We integrated whole-blood expression quantitative trait loci (eQTL) data from eQTLGen, plasma protein quantitative trait loci (pQTL) data from deCODE, and LUAD genome-wide association study (GWAS) data from European-ancestry cohorts, together with differential expression analysis using GEPIA2, to identify candidate genes for subsequent single-cell eQTL (sc-eQTL) Mendelian randomization (MR) analysis. For the sc-eQTL analysis, VNN2-associated eQTLs from 14 immune cell types profiled in the OneK1K single-cell eQTL resource were tested for associations with LUAD risk.

RESULTS: Bulk-level MR analysis showed that genetically predicted increases in VNN2 expression and protein levels were significantly associated with a reduced risk of LUAD (eQTL-MR: odds ratio (OR) = 0.964, 95% confidence interval (95% CI), 0.934-0.995; P = 0.024; pQTL-MR: OR = 0.946, 95% CI, 0.921-0.970; P = 2.87 × 10^-5). Transcriptomic analyses confirmed significant downregulation of VNN2 in LUAD tumors compared with normal lung tissues. sc-eQTL MR identified the strongest association in resting natural killer (rNK) cells (OR = 0.896, 95% CI, 0.829-0.967; P = 0.005).

CONCLUSIONS: Multi-omics and sc-eQTL MR analyses indicated that genetically predicted increases in VNN2 expression were associated with a reduced risk of LUAD, with the most pronounced effect observed in rNK cells. These findings suggest a potential cell type-specific role of VNN2 in LUAD susceptibility and warrant further studies to validate its biological relevance and clinical implications.

PMID:41822323 | PMC:PMC12978397 | DOI:10.14740/wjon2689