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