Ecotoxicol Environ Saf. 2026 Apr 1;314:120063. doi: 10.1016/j.ecoenv.2026.120063. Epub 2026 Mar 23.

NO ABSTRACT

PMID:41875554 | DOI:10.1016/j.ecoenv.2026.120063

Technol Cancer Res Treat. 2026 Jan-Dec;25:15330338261435022. doi: 10.1177/15330338261435022. Epub 2026 Mar 23.

ABSTRACT

IntroductionHepatocellular carcinoma (HCC) screening in patients with hepatic cirrhosis (HC) relies on ultrasound and alpha-fetoprotein (US + AFP), which has limitations in sensitivity, particularly for early-stage HCC detection. This study aims to evaluate the performance of a novel multi-omics blood test, HCCscreen, with its individual components (methylation, AFP, Des-γ-Carboxy Prothrombin (DCP), mutations) and the standard US + AFP for HCC screening in a hepatic cirrhotic population.MethodsA total of 5078 patients with known high-risk for HCC were recruited. A prospective screening study was conducted on 650 patients with hepatic cirrhosis identified by ultrasound. Blood samples were collected from all patients before the confirmation of diagnosis by imaging and/or pathological examinations. The performance of HCCscreen, individual markers and US + AFP were calculated and compared. Statistics was performed with Graphpad Prism 5.0.ResultsHCCscreen exhibited a sensitivity of 86.3% at a specificity of 81.3%, with a positive predictive value (PPV) of 28.2% and a negative predictive value (NPV) of 98.6%. The positive likelihood ratio (LR+) was 4.61 and the negative LR (LR-) was 0.17. The positive detection rate (PDR) for all markers increased with more advanced HCC stages, whether Barcelona Clinic Liver Cancer (BCLC) or clinical staging. Among the single-omics, methylation showed the highest PDR, followed by AFP, DCP and mutations. HCCscreen demonstrated superior overall performance with an AUC of 0.87, outperforming individual markers like methylation (AUC = 0.76), AFP (AUC = 0.83), and DCP (AUC = 0.77). Crucially, HCCscreen's PDR was significantly higher than US + AFP in early-stage HCC (BCLC-0 and clinical stage I). Furthermore, while AFP's PDR varied significantly by sex, HCCscreen's performance remained consistent across all demographics. Correlation analysis revealed a significant association only between the HCCscreen score and the methylation score.ConclusionsThe multi-omics approach of HCCscreen significantly enhances early HCC detection in patients with hepatic cirrhosis compared to both its individual components and the current standard of US + AFP. Its robust and consistent performance across patient demographics underscores its potential as a superior tool for population-wide early HCC screening.

PMID:41869803 | PMC:PMC13009828 | DOI:10.1177/15330338261435022

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

Front Oncol. 2026 Mar 4;16:1771313. doi: 10.3389/fonc.2026.1771313. eCollection 2026.

ABSTRACT

N⁶-methyladenosine (m⁶A), as the most abundant RNA epitranscriptional modification in eukaryotes, its key component of the methyltransferase complex, METTL14, not only cooperates in catalyzing m⁶A deposition but also has functions independent of methyltransferase activity. This article systematically reviews the dual regulatory role of METTL14 in tumors and its molecular mechanisms, mainly organizing the relevant research in a logical sequence of "tumor suppressive effect - tumor promoting effect - controversial or context-dependent". Studies have shown that METTL14 often plays a tumor suppressive role in tumors such as hepatocellular carcinoma and colorectal cancer, while in pancreatic cancer and nasopharyngeal carcinoma, it mostly promotes malignant progression, showing a high degree of context dependence. This article focuses on two key mechanisms: on the one hand, METTL14 precisely regulates the processing, stability, and function of non-coding RNAs (including miRNAs, lncRNAs, and circRNAs) through m⁶A modification, reshaping the competitive endogenous RNA (ceRNA) network; on the other hand, it shapes an immunosuppressive tumor microenvironment by directly upregulating immune checkpoints such as PD-L1, mediating metabolism-immune interactions, and regulating the function of immune cells. Its functional duality also stems from the selective regulation of key pathways such as PI3K/AKT, as well as the differential interpretation by different m⁶A readers (such as YTHDF2 and IGF2BPs). Given the close association of these mechanisms with clinical prognosis, the expression level of METTL14 shows significant potential as a prognostic marker and therapeutic target; in the future, it is necessary to combine single-cell multi-omics and other technologies to analyze its dynamic regulatory network in specific tumor contexts and explore precise treatment strategies based on synthetic lethality or targeting downstream effector molecules.

PMID:41858346 | PMC:PMC12995618 | DOI:10.3389/fonc.2026.1771313

Gut. 2026 Mar 30:gutjnl-2025-337938. doi: 10.1136/gutjnl-2025-337938. Online ahead of print.

ABSTRACT

BACKGROUND: Survival outcomes after transarterial chemoembolisation (TACE) vary in hepatocellular carcinoma (HCC) patients, and existing prognostic scores and imaging models often lack generalisability and biological interpretability.

OBJECTIVE: To develop and validate a multimodal prognostication model for HCC that allows for a precise assessment of survival outcomes of HCC patients receiving TACE therapy.

DESIGN: This study enrolled 1448 HCC patients, including a TACE cohort (n=1349), a biomarker subset from a randomised trial (n=41), a single-cell RNA sequencing cohort and The Cancer Genome Atlas (TCGA) HCC cohort (n=50). Pre-treatment contrast-enhanced CT images were used to construct deep learning and conventional radiomic models. The early-fusion and late-fusion models (LFMs) were compared, and a clinical-radiologic model (CRM) was formed by integrating the better-performing LFM with clinical variables. Using TCGA data and single-cell transcriptomic profiles, the differences between high-score and low-score groups in tumour immune microenvironment, cellular functional states and key signalling pathways were investigated.

RESULTS: The CRM effectively stratified patients' survival across multiple independent cohorts and achieved more granular risk stratification than the existing clinical models. Multi-omic analyses revealed that in the LFM high-score group, myelocytomatosis oncogene was activated, epithelial-mesenchymal transition enhanced, glycolysis upregulated and hypoxia pathway activated. Single-cell transcriptomic data confirmed that virtually all cell types in high-risk patients scored high in hypoxia, and cytotoxic T cells had a reduced cytotoxic activity.

CONCLUSION: The CRM model can non-invasively predict the prognosis of HCC patients treated by TACE therapy.

PMID:41856522 | DOI:10.1136/gutjnl-2025-337938

Cell Mol Life Sci. 2026 Mar 19. doi: 10.1007/s00018-026-06167-4. Online ahead of print.

NO ABSTRACT

PMID:41854876 | DOI:10.1007/s00018-026-06167-4

BMC Gastroenterol. 2026 Mar 19. doi: 10.1186/s12876-026-04756-y. Online ahead of print.

NO ABSTRACT

PMID:41851828 | DOI:10.1186/s12876-026-04756-y

J Hepatocell Carcinoma. 2026 Mar 11;13:574690. doi: 10.2147/JHC.S574690. eCollection 2026.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits significant molecular heterogeneity and complex immune microenvironment, which to some extent limits the accuracy of prognosis assessment and the formulation of individualized treatment strategies. This study aims to identify immune-derived molecular signatures based on multi-omics data and machine learning methods for the prognosis prediction and risk stratification of HCC.

METHODS: Based on weighted gene co-expression network analysis(WGCNA) and differential gene analysis,immune-derived molecular signature (IDMS) were screened in both single-cell and bulk transcriptomes. Prognostic model was constructed by multi-machine learning approachs. Subsequently, we investigated the differences in mutations, biological functions, and immune cell infiltration within the tumor microenvironment between the high- and low-risk groups.In addition, we comprehensively analyzed the drug sensitivity of IDMS and predicted potential drugs.

RESULTS: We identified seven hub genes at the single-cell and bulk transcriptome levels. Based on multiple machine learning, we constructed a prognostic model that demonstrated excellent performance in predicting overall survival for patients with HCC. IDMS -integrated normograms provide a promising and quantitative tool for clinical risk management.Notably, a significant difference in microsatellite instability (MSI) was observed between the high- and low-risk groups. This indicates that patients in the high-risk group might have a better response to immunotherapy. Additionally, we predicted potential drugs targeting to these risk subgroups.

CONCLUSION: Our research developed an IDMS that could serve as an effective tool for patient stratification management and prognosis prediction. This signature could provide a reference for immunotherapy for patients with HCC and improve their prognosis.

PMID:41847219 | PMC:PMC12991065 | DOI:10.2147/JHC.S574690

Cell Death Differ. 2026 Mar 16. doi: 10.1038/s41418-026-01713-w. Online ahead of print.

ABSTRACT

Hepatitis B virus (HBV) infection remains a leading etiological driver of hepatocellular carcinoma (HCC). Cuproptosis is a recently defined copper-dependent form of regulated cell death that selectively eliminates mitochondria-dependent cells; whether HBV rewires this vulnerability remains unknown. Here we unveil a novel HBV X protein (HBx)-driven mechanism of cuproptosis evasion. Integrative analysis of clinical specimens, HBx-transgenic (HBx-Tg) mice, and multi-omics datasets revealed marked downregulation of STEAP4 (six-transmembrane epithelial antigen of prostate 4), a metalloreductase essential for cuproptosis sensitivity, in HBV-positive HCC. Mechanistically, HBx attenuates sirtuin 3 (SIRT3), impairing deacetylation of STEAP4 at lysine 404 and abolishing its mitochondrial targeting. Consequently, cells switch from the tricarboxylic acid (TCA) cycle respiration to glycolysis, reducing sensitivity to the copper ionophore elesclomol (ES). Restoring STEAP4 expression or pharmacological activation of SIRT3 with honokiol (HKL) re-instated mitochondrial STEAP4 localization and re-sensitized HBV-related HCC cells to cuproptosis; combination with ES produced synergistic tumor suppression in vitro and in orthotopic models. Collectively, our findings establish the SIRT3-STEAP4 axis as a novel regulator of cuproptosis resistance in HBV-related HCC. HBx-mediated repression of SIRT3 disrupts STEAP4 deacetylation and mitochondrial targeting, fostering metabolic reprogramming and evasion of copper-induced cell death. The results provide a pre-clinical rationale for copper-directed combination strategies in HBV-associated HCC.

PMID:41840161 | DOI:10.1038/s41418-026-01713-w

Clin Chim Acta. 2026 Mar 12;587:120973. doi: 10.1016/j.cca.2026.120973. Online ahead of print.

ABSTRACT

Hepatic fibrosis is a dynamic and progressive condition that can lead to cirrhosis and hepatocellular carcinoma (HCC) if left untreated. Appropriate assessment of the disease progression of fibrosis is critical for early intervention and individualized treatment regimens. Traditional biopsy techniques are invasive and prone to sampling errors, highlighting the need for less invasive predictive techniques. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long ncRNAs (lncRNAs), and circular RNAs (circRNAs), have emerged as key regulators of hepatic fibrogenesis and as a possible biomarker for disease staging and prognosis. The emergence of artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has revolutionized the comprehensive large-scale analysis of transcriptomic data, enhancing the identification of ncRNA biomarkers and predictive modeling. The AI-based algorithms have been found to be more precise in anticipating fibrosis progression by means of integrating multi-omics data, ncRNA interaction networks, and by improving non-invasive diagnostic tools. This review involves the analysis of AI and ncRNA research in hepatic fibrosis, highlighting recent discoveries, possible challenges, and future opportunities. We address the necessity of standardization of data and clinical validation, as well as discuss the role of AI in identifying biomarkers of ncRNA, predicting the stage of fibrosis and risk stratification. ncRNA analysis with AI has a tremendous potential of transforming the diagnostics and prognostics of hepatic fibrosis, enabling precision hepatology.

PMID:41831666 | DOI:10.1016/j.cca.2026.120973

Transl Cancer Res. 2026 Feb 28;15(2):77. doi: 10.21037/tcr-2025-aw-2179. Epub 2026 Feb 11.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits notable characteristics, encompassing frequent recurrence, weak immunotherapeutic outcomes and unfavorable prognosis. BTF3L4 has been identified as a critical factor in the progression of various malignancies. However, its specific role in HCC remains to be elucidated. This investigation sought to examine BTF3L4 levels in HCC and BTF3L4's connection with clinical prognosis and immune infiltration.

METHODS: We performed an extensive multi-omics evaluation in the course of our research. Bioinformatics tools were utilized to assess BTF3L4 messenger RNA (mRNA) expression in HCC. Multiplex immunohistochemistry (mIHC) was utilized to examine BTF3L4 protein expression and to explore its correlation with tumor-infiltrating immune cells (TIICs). Cox regression analysis and Kaplan-Meier survival curves were applied to determine BTF3L4's impact on patient outcomes.

RESULTS: Our analysis revealed markedly elevated levels of both BTF3L4 mRNA and protein in HCC tissues. BTF3L4 protein abundance emerged as an independent predictor of reduced survival in patients with HCC. Furthermore, elevated BTF3L4 protein expression was positively associated with cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression and markedly negatively correlated with CD4⁺ T cells and CD66b⁺ neutrophils in HCC tissues.

CONCLUSIONS: This evidence indicates that BTF3L4 functions as a predictive indicator and is a potential candidate for HCC immunotherapy.

PMID:41815168 | PMC:PMC12971597 | DOI:10.21037/tcr-2025-aw-2179

NPJ Precis Oncol. 2026 Mar 11. doi: 10.1038/s41698-026-01372-7. Online ahead of print.

ABSTRACT

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide, and its progression is closely linked to the establishment of an immunosuppressive tumor microenvironment. Myristoylated alanine-rich C kinase substrate (MARCKS) has been implicated in tumor biology; however, its role in regulating immune interactions in HCC remains poorly defined. Here, we performed an integrated multi-omics analysis combining bulk transcriptomics, single-cell RNA sequencing, and spatial transcriptomics to systematically investigate the expression pattern and functional relevance of MARCKS in HCC. We found that MARCKS was significantly upregulated in HCC tissues and that high MARCKS expression was associated with aggressive clinicopathological features and unfavorable prognosis. Single-cell and spatial analyses revealed that MARCKS expression was enriched in myeloid cell populations within the tumor microenvironment. Functional annotation and mIF(Multiple immunofluorescence) validation demonstrated that MARCKS expression was associated with enhanced JAK/STAT3 signaling and M2-like macrophage polarization. Consistently, MARCKS silencing in HCC cell lines reduced STAT3 phosphorylation, suppressed malignant phenotypes in vitro, inhibited tumor growth in vivo, and diminished the capacity of tumor-derived conditioned media to promote macrophage M2 polarization. Together, these findings identify MARCKS as a key regulator of the immunosuppressive tumor microenvironment in HCC and highlight its potential as a therapeutic target for overcoming immune evasion.

PMID:41813922 | DOI:10.1038/s41698-026-01372-7

Clin Mol Hepatol. 2026 Mar 11. doi: 10.3350/cmh.2025.1269. Online ahead of print.

ABSTRACT

BACKGROUND/AIMS: Lenvatinib resistance and immune exclusion limit outcomes in HCC. We hypothesized that metabolic rewiring orchestrates resistance to lenvatinib and PD-1 blockade.

METHODS: We established LS/LR HCC models and employed multi-omics (proteomics/RNA-seq), ChIP, luciferase, and RIP assays to map HKDC1 regulation. Tumor immunity was profiled by scRNA-seq, mIHC, and flow cytometry. SPD + lenvatinib efficacy was tested in cell lines, patient-derived organoids/xenografts. Tested therapy effect in an immunocompetent hydrodynamic HCC model with hepatocyte-specific Hkdc1 deletion; and analyzed a postoperative cohort (n = 40) treated with lenvatinib + PD-1.

RESULTS: HKDC1, upregulated in LR HCC, was transcriptionally activated by USF1 and promoted SMS-mediated polyamine rewiring. This impaired CD8⁺ T-cell metabolism, reversible by HKDC1 knockdown or spermidine (SPD). SPD synergized with lenvatinib, triggering autophagy and suppressing tumor growth in vitro and in vivo. High HKDC1 predicted poor response and survival in patients receiving lenvatinib + aPD-1.

CONCLUSIONS: A USF1/HKDC1/SMS axis couples polyamine metabolism to immune dysfunction and lenvatinib resistance. HKDC1 is a predictive biomarker and therapeutic node and support polyamine-axis modulation to sensitize HCC to lenvatinib plus PD-1 therapy.

PMID:41812646 | DOI:10.3350/cmh.2025.1269

World J Hepatol. 2026 Feb 27;18(2):116475. doi: 10.4254/wjh.v18.i2.116475.

ABSTRACT

In this editorial, we comment on the article by Wang et al, which investigates molecular and immune biomarkers predictive of response to sintilimab plus lenvatinib in hepatitis B virus-associated hepatocellular carcinoma (HCC). Yet, despite remarkable progress with immune-checkpoint and anti-angiogenic combinations, the biological heterogeneity of HCC continues to limit durable responses and individualized care. By integrating high-resolution transcriptomic, exomic, and immune-cell-profiling data, Wang et al identified a coherent triad - elevated LINC01554 expression, enrichment of CD4+ central-memory T cells, and solitary-tumour morphology - that independently predicted prolonged progression-free survival. This constellation links tumour-intrinsic transcriptional restraint, adaptive immune competence, and anatomical containment, illustrating how multi-omic profiling can clarify determinants of therapeutic benefit. These insights signify a shift from empiricism to biologically guided therapy, providing a scaffold for biologic stratification, longitudinal response monitoring, and rational sequencing of immunotherapeutic and anti-angiogenic agents. Collectively, they redefine HCC as a dynamic biological ecosystem rather than a uniform malignancy and highlight the imperative to embed multi-omic biomarker platforms within future clinical-trial design - marking a decisive step toward precision hepatology in inflammation-driven cancers.

PMID:41809466 | PMC:PMC12968698 | DOI:10.4254/wjh.v18.i2.116475

Genes Immun. 2026 Mar 10. doi: 10.1038/s41435-026-00382-6. Online ahead of print.

ABSTRACT

The prognosis for hepatocellular carcinoma remains grim. Combining radiotherapy with immune checkpoint blockade (ICB) has shown potential to enhance therapeutic outcomes, yet there is a pressing need for further advancements. Our previous research demonstrated that this combined approach suppresses ALKBH5 gene expression and increases m6A modification levels in hepatocellular carcinoma tissues. High-throughput sequencing and detailed molecular analysis revealed that inhibiting ALKBH5 amplifies CIITA m6A modifications post-therapy. This modulation triggers MHC II molecule expression in tumors, facilitating the presentation of tumor-associated antigens to CD4 + T lymphocytes and the recruitment of CD8 + T cells for an anti-tumor immune response. Building on these findings, we engineered a CIITA vector with a specific site mutation to confirm that the regulation of CIITA by the combined radiotherapy and immunotherapy is mediated through m6A methylation. Consequently, we established a comprehensive network involving ALKBH5, CIITA, MHC II, and CD4+ and CD8 + T cells. To elucidate the role and underlying molecular mechanisms of this combined therapy in reshaping the tumor immune microenvironment for hepatocellular carcinoma, we employed multi-omics approaches across in vitro, animal model, and clinical multi-dimensional studies, offering novel insights for enhancing treatment efficacy.

PMID:41807814 | DOI:10.1038/s41435-026-00382-6