J Transl Med. 2026 May 25. doi: 10.1186/s12967-026-08301-z. Online ahead of print.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden and a leading cause of cancer-related mortality. Advanced disease is characterized by a profoundly immunosuppressive tumor microenvironment (TME) and limited durable responses to therapy. However, the upstream genetic determinants that drive tumor-associated macrophage (TAM) dysfunction in HCC remain poorly defined. Using an integrative genetic and multi-omics framework, we investigated complement receptor 1 (CR1) as a candidate regulator of this immunosuppressive niche.

METHODS: We combined Mendelian randomization (MR) and metabolite mediation analyses with bulk, single-cell, and spatial transcriptomics to define the role of CR1 in HCC. Public datasets included the TCGA-HCC cohort, a single-cell RNA-sequencing dataset comprising 53,474 high-quality cells from 21 samples, and two spatially profiled HCC sections. Clinical validation was performed in 30 paired HCC and adjacent liver tissues. Functional assays were conducted in THP-1-derived macrophages using CR1 gain- and loss-of-function approaches, phagocytosis assays, and macrophage-CD8⁺ T-cell co-culture experiments.

RESULTS: MR analyses implicated CR1 in HCC susceptibility at both the protein and transcript levels. pQTL analysis linked genetically predicted circulating CR1 levels to HCC risk (IVW OR = 1.403, p = 0.017), and mediation analysis identified specific metabolites as candidate intermediates. Integrative multi-omics analyses showed that CR1 was preferentially enriched in TAMs, spatially co-localized with the M2 marker CD206, and associated with reduced CD8⁺ T-cell infiltration, enhanced T-cell exhaustion signatures, advanced clinicopathological features, and poorer survival. In 30 paired clinical samples, CR1-high tumors exhibited increased M2-like macrophage accumulation and reduced CD8⁺ T-cell infiltration. Functionally, CR1 overexpression drove macrophages toward an M2-like phenotype, enhanced phagocytic activity, increased PD-L1 expression, and suppressed CD8⁺ T-cell proliferation as well as IFN-gamma and granzyme B production, whereas CR1 knockdown produced the opposite phenotype.

CONCLUSIONS: Our study provides the first integrated genetic, spatial, and functional evidence that CR1⁺ TAMs constitute a clinically relevant immunoregulatory axis in HCC. These findings extend current understanding of complement-associated immunosuppression beyond canonical complement cascade activity and support CR1 as a candidate biomarker and therapeutic target for macrophage reprogramming, with potential translational relevance for combination strategies involving immune checkpoint blockade.

PMID:42185899 | DOI:10.1186/s12967-026-08301-z

Front Immunol. 2026 May 8;17:1762222. doi: 10.3389/fimmu.2026.1762222. eCollection 2026.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits profound molecular heterogeneity and aberrant cellular senescence. This study systematically dissects the senescence-associated molecular landscape to identify key regulators driving HCC progression and immune evasion.

METHODS: Integrating multi-cohort transcriptomic datasets, we developed a robust prognostic signature using 101 machine-learning models, identifying prognostic signature. We employed preliminary proteomic, exploratory metabolomic, and single-cell RNA sequencing (scRNA-seq) analyses to explore multi-omics alterations. The functional senescence status and MCM7 were validated in a clinical HCC cohort by RT-qPCR, Western blotting, immunohistochemistry, and multiplex immunofluorescence (mIF). Causality was established using in vitro functional assays in HepG2 cells.

RESULTS: A 12-gene random survival forest (RSF) signature accurately predicted patient survival across independent cohorts. MCM7 emerged as a central senescence-associated driver. ScRNA-seq and mIF confirmed MCM7 characterizes a highly proliferative, clonally expanding subset of CD8⁺ T cells within the tumor microenvironment. In vitro, MCM7 knockdown significantly inhibited HepG2 cell proliferation and upregulated senescence enforcers p16 and p21, whereas overexpression facilitated evasion. Additionally, TIDE analysis revealed that high-risk patients exhibited elevated immune evasion potential, predicting poor immunotherapy response.

CONCLUSION: This integrative multi-omics framework uncovers an MCM7 MCM7-driven senescence-associated axis promising HCC progression and immune dysfunction, offering a robust tool for prognostic stratification and novel therapeutic insights.

PMID:42183188 | PMC:PMC13195000 | DOI:10.3389/fimmu.2026.1762222

J Clin Transl Hepatol. 2026 Apr 28;14(4):462-477. doi: 10.14218/JCTH.2025.00589. Epub 2026 Apr 8.

ABSTRACT

Hepatocellular carcinoma (HCC) is one of the most prevalent and aggressive malignant tumors globally, with a notably low five-year survival rate. Its high mortality is largely attributed to challenges in early detection. Extracellular vesicles (EVs) are naturally occurring nanoparticles secreted by nearly all cell types and carry a diverse array of bioactive molecules, including proteins, nucleic acids (particularly non-coding RNAs), and lipids. EVs play pivotal roles in remodeling the tumor microenvironment and driving cancer progression through intercellular communication. Accumulating evidence has established that EVs are critically involved in the pathogenesis of HCC and are emerging as promising biomarkers for its early detection. With advances in EV isolation technologies, these vesicles have garnered considerable attention in the field of liquid biopsy for HCC. This review provides a comprehensive overview of the diagnostic potential of EV-derived biomarkers in HCC, including DNA, RNA, proteins, and lipids. Additionally, it discusses the advantages of integrating multi-omics approaches for HCC diagnosis. Furthermore, the review highlights the technical challenges in EV isolation and characterization, as well as the crucial role of reference genes in the standardization of EV data. These insights underscore the potential of EVs as novel, minimally invasive liquid biopsy biomarkers for the early diagnosis of HCC.

PMID:42181837 | PMC:PMC13195390 | DOI:10.14218/JCTH.2025.00589

Prog Mol Biol Transl Sci. 2026;222:241-259. doi: 10.1016/bs.pmbts.2026.02.004. Epub 2026 Apr 6.

ABSTRACT

Liver diseases, including hepatocellular carcinoma (HCC), Cholangiocarcinoma (CCA), non-alcoholic fatty liver disease (NAFLD), and cirrhosis, account for over 2 million deaths each year worldwide. Due to their intricate etiology, which encompasses genetic, epigenetic, environmental, and metabolic factors cause late diagnosis. Advances in multi-omics techniques generate huge and complex data including genomics, epigenomics, transcriptomics, proteomics, and metabolomics which revolutionize the understanding of biological systems at different layers of complexity. Furthermore, advances in integrating multi-omics data using artificial intelligence(AI) helping in identifying common factors dysregulated at different layers in biological systems to identify the disease etiology, diseases subtyping, diagnosis and prognosis modeling. This chapter discusses the common omics data and application of AI in the integration of multi-omics data for deep investigation of liver diseases to enhance the understanding of disease mechanisms, identify biomarkers, and discover therapeutic targets for the progression of precision medicine. Furthermore, we discuss about persistent challenges in integrating heterogeneous omics datasets including variations in data format, scale, and AI model interpretability. The incorporation of AI-driven multi-omics approach in clinical hepatology will support more accurate and early diagnosis, disease subtyping, and better treatment planning for precision medicine.

PMID:42173632 | DOI:10.1016/bs.pmbts.2026.02.004

J Gastrointest Oncol. 2026 Apr 30;17(2):96. doi: 10.21037/jgo-2025-aw-848. Epub 2026 Mar 27.

ABSTRACT

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) is characterized by high postoperative recurrence rates and poor long-term survival despite advances in surgical and systemic therapies. Accurate prediction of postoperative recurrence and survival risk is critical for individualized surveillance, adjuvant treatment selection, and precision management. With the rapid development of artificial intelligence (AI) and medical informatics, multimodal data-driven models integrating clinical, imaging, pathological, and omics information have emerged as a promising paradigm. This narrative review aims to systematically summarize recent advances in multimodal prediction models for postoperative recurrence and survival in HCC, compare modeling strategies and fusion approaches, and discuss current challenges and future directions for clinical translation.

METHODS: A narrative literature review was conducted by searching PubMed, Web of Science, and Google Scholar for studies published between 2020 and 2025. Articles focusing on postoperative recurrence or survival prediction in HCC using single-modal or multimodal data were included. Relevant studies were identified using keywords related to HCC, multimodal data, AI, machine learning, deep learning, recurrence, and prognosis.

KEY CONTENT AND FINDINGS: This review summarizes commonly used data modalities, including clinical variables, medical imaging, pathological features, and multi-omics data, and outlines their respective strengths and limitations. Conventional statistical models and AI-based approaches, including non-deep learning and deep learning algorithms, are compared. Particular emphasis is placed on multimodal fusion strategies at the feature level and decision level, with discussion of their methodological characteristics and suitable clinical scenarios. Overall, multimodal models consistently demonstrate superior predictive performance compared with single-modality approaches. However, key challenges remain, including data heterogeneity, limited interpretability of complex models, insufficient external validation, and the predominance of static baseline modeling.

CONCLUSIONS: Multimodal data-driven prediction models represent a promising strategy for improving postoperative risk stratification and personalized management in HCC. While current evidence highlights their potential advantages over traditional prognostic tools, broader clinical adoption is hindered by methodological limitations and a lack of standardized frameworks. Future research should focus on longitudinal multimodal modeling, multi-center prospective validation, and enhanced model interpretability to facilitate integration into clinical workflows and inform precision oncology-oriented decision-making.

PMID:42169935 | PMC:PMC13187996 | DOI:10.21037/jgo-2025-aw-848

J Hepatocell Carcinoma. 2026 May 15;13:608436. doi: 10.2147/JHC.S608436. eCollection 2026.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits substantial biological and metabolic heterogeneity, contributing to variable therapeutic responses in unresectable disease. Although immune checkpoint inhibitors combined with anti-angiogenic agents have improved outcomes, treatment selection remains largely empirical because validated predictive biomarkers are lacking. Recent multi-omics studies have identified fatty acid degradation (FAD)-related transcriptional signatures that classify HCC into distinct metabolic subtypes with different immune microenvironment characteristics and therapeutic vulnerabilities. Retrospective analyses suggest that F1/F2 subtypes may derive greater benefit from immune checkpoint inhibitor-based systemic therapy, whereas F3 tumours may be more responsive to transarterial chemoembolisation (TACE). However, whether FAD-based metabolic stratification can prospectively inform treatment allocation remains unknown.

METHODS: FAD-HCC-01 is a prospective, multicentre, open-label proof-of-concept Phase II study designed to evaluate the feasibility and preliminary clinical activity of FAD-informed treatment allocation in patients with unresectable HCC. Eligible patients with Barcelona Clinic Liver Cancer stage B or C disease and no prior systemic therapy will undergo baseline tumour transcriptomic profiling to determine FAD subtype. Patients with F1/F2 tumours will receive camrelizumab plus rivoceranib, whereas patients with F3 tumours will receive TACE combined with camrelizumab and rivoceranib. Eighty-six patients will be enrolled, with 43 in each biomarker-defined cohort. The primary endpoint is objective response rate according to RECIST version 1.1. Secondary endpoints include objective response rate by mRECIST, disease control rate, progression-free survival, overall survival, duration of response, conversion to curative treatment, and safety. Exploratory analyses will assess concordance between MRI-derived proton density fat fraction and transcriptomic FAD classification.

CONCLUSION: This proof-of-concept study will prospectively assess whether FAD-based metabolic subtyping can inform treatment allocation in unresectable HCC. The results may provide early evidence supporting metabolism-informed precision therapy and the design of future biomarker-guided clinical trials.

PMID:42164571 | PMC:PMC13186218 | DOI:10.2147/JHC.S608436

J Transl Med. 2026 May 20. doi: 10.1186/s12967-026-08278-9. Online ahead of print.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) is characterized by a highly immunosuppressive and heterogeneous tumor microenvironment that limits the effectiveness of current immunotherapies. Conventional two-dimensional cultures and animal models fail to fully capture patient-specific tumor-immune interactions, creating an urgent need for more physiologically relevant platforms.

MAIN BODY: This review summarizes recent advances in co-culture systems integrating patient-derived HCC organoids with defined immune cell populations to reconstruct essential features of the tumor microenvironment. We describe strategies for organoid establishment and validation, outline immune cell integration approaches, and compare static three-dimensional cultures, microfluidic organ-on-chip systems, and bioengineered multicellular platforms. We further highlight key tumor-immune interaction mechanisms that have been functionally interrogated in these systems, including immune checkpoint-mediated T-cell dysfunction, adenosine-driven metabolic suppression, and chemokine-regulated immune recruitment. Importantly, we critically evaluate current limitations, including immune cell exhaustion artifacts, lack of stromal and vascular complexity, and variability across protocols, which may affect the reproducibility and translational interpretation of these models. While emerging studies suggest potential for predicting immunotherapy responses, robust clinical validation in HCC remains limited.

CONCLUSIONS: Organoid-immune co-culture platforms represent an emerging translational framework that bridges mechanistic tumor immunology with functional precision oncology. With improved standardization and integration of multicellular bioengineering and multi-omics technologies, these systems have strong potential to guide personalized immunotherapy strategies, although further clinical validation is required.

PMID:42163357 | DOI:10.1186/s12967-026-08278-9

Biosci Trends. 2026 May 21. doi: 10.5582/bst.2026.01000. Online ahead of print.

ABSTRACT

Oncolytic adenovirus H101 has shown antitumor activity in hepatocellular carcinoma (HCC), but the molecular determinants of treatment response remain unclear. In this study, a Hepa1-6 subcutaneous tumor model was established in C57BL/6 mice and treated with intratumoral H101, followed by integrated transcriptomic and proteomic analyses to identify candidate genes associated with H101 response. PRXL2B was selected for further investigation using public multi-omics datasets, tissue microarray-based immunohistochemistry, in vitro functional assays, mechanistic analyses, and in vivo validation experiments. Integrated multi-omics analyses identified PRXL2B as a candidate gene downregulated after H101 treatment. Public datasets and tissue-based validation further showed that PRXL2B was upregulated in HCC tissues. In MHCC97H and HCCLM3 cells, PRXL2B knockdown inhibited proliferation, migration, and invasion, promoted apoptosis and cell-cycle arrest, and enhanced the antitumor effect of H101. Mechanistically, PRXL2B silencing reduced AKT phosphorylation and PD-L1 expression. In vivo, PRXL2B knockdown suppressed tumor growth, and the combination of PRXL2B knockdown and H101 produced the strongest antitumor effect. These findings indicate that PRXL2B promotes malignant phenotypes in HCC and may modulate H101 efficacy through the PI3K/AKT/PD-L1 axis. Targeting PRXL2B may therefore represent a potential strategy to enhance the therapeutic efficacy of oncolytic virus therapy in HCC.

PMID:42161529 | DOI:10.5582/bst.2026.01000

Int Immunopharmacol. 2026 May 19;183:116866. doi: 10.1016/j.intimp.2026.116866. Online ahead of print.

ABSTRACT

Hepatocellular carcinoma (HCC) is a lethal malignancy with a high recurrence rate and limited treatment options. Ubiquitin-conjugating enzyme E2 C (UBE2C) is implicated in various cancers, yet its impact on the HCC immune landscape remains incompletely understood. Herein, hub genes in HCC were identified, by integrating co-expression networks and protein-protein interaction analyses, from the TCGA, GEO, and CPTAC databases. Their expression was analysed using a single-cell transcriptomic database and verified in HCC tissues and cell lines via quantitative reverse transcription-PCR and immunoblotting. Functional roles of UBE2C were assessed using in vitro knockdown experiments and an in vivo subcutaneous tumour model. The tumour immune microenvironment was profiled using spatial transcriptomics, RNA-seq data, and ssGSEA. A prognostic nomogram was constructed based on multivariate Cox regression. UBE2C was identified as a significantly upregulated hub gene in HCC. Single-cell RNA-seq revealed predominant expression of UBE2C in hepatocytes, with dynamic upregulation along differentiation trajectories. UBE2C knockdown suppressed proliferation, induced apoptosis, and inhibited tumour growth. Spatial transcriptomics highlighted UBE2C-high regions within proliferative niches exhibiting immunosuppressive traits-including TGFB1 enrichment, impaired CXCL9-CXCR3 signalling, and exclusion of cytotoxic T cells-which were reduced in immunotherapy responders. UBE2C expression correlated with immune checkpoint genes and specific immune cell subsets. A UBE2C-based nomogram integrating T stage and tumour stage robustly predicted patient survival, and miR-300 and miR-381-3p were identified as potential upstream regulators. These findings establish UBE2C as a key driver of HCC progression and a biomarker for prognosis and immunotherapy stratification.

PMID:42155390 | DOI:10.1016/j.intimp.2026.116866

Curr Mol Med. 2026 May 11. doi: 10.2174/0115665240438824260113042223. Online ahead of print.

ABSTRACT

BACKGROUND: 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/ IMP cyclohydrolase(ATIC) is a 64-kDa bifunctional enzyme, 5-aminoimidazole- 4-carboxamide ribonucleotide formyltransferase (AICART) and IMP cyclohydrolase, respectively. catalyzes the last two steps of the purine ab initio biosynthetic pathway. ATIC has been implicated in cancer progression, but its pan-cancer profile and specific prognostic utility in liver hepatocellular carcinoma (LIHC) remain incompletely defined.

METHODS: We analyzed TCGA RNA-seq data across 33 tumor types to assess ATIC expression, diagnostic performance (ROC/AUC), and prognostic associations (OS, DSS, PFI). We correlated ATIC expression with immune infiltration, TMB, MSI, and predicted neoantigen load, and constructed a LIHC-specific prognostic nomogram integrating ATIC and clinicopathologic features. Enrichment analyses (STRING, GO/KEGG, GSEA) and pharmacogenomic correlations (GDSC, CTRP) were performed to explore mechanisms and drug sensitivities.

RESULTS: ATIC was significantly upregulated in 16 tumor types, including LIHC (p<0.001). Pan-cancer ROC analyses showed high diagnostic accuracy in several cancers (examples: CHOL AUC=1.000, LIHC AUC=0.936, LUAD AUC=0.947). High ATIC expression associated with poorer OS in ACC, HNSC, LIHC, and PAAD (eg, LIHC: HR=1.39(1.04-1.85), p=0.028). In LIHC, ATIC correlated with advanced T stage, higher grade, elevated AFP, and shorter OS. Multivariable Cox regression identified ATIC expression and pathological T stage as independent predictors; time-dependent ROC for the LIHC nomogram showed AUCs of 0.711, 0.649, and 0.653 at 1, 3, and 5 years, respectively. GSEA indicated enrichment of PI3K-AKT-mTOR, MYC targets, and cell-cycle pathways in ATIC-high LIHC. High ATIC expression correlated with predicted increased sensitivity to sorafenib, doxorubicin, cisplatin, epothilone, and mitomycin in the TCGA-LIHC cohort.

DISCUSSION: ATIC upregulation across cancers links to tumor progression, immune modulation, and prognosis (LIHC), suggesting oncogenic roles in pan-cancer contexts. TCGA multi-omics show ATIC associates with immune/molecular subtypes, MSI/TMB/neoantigens, and predicts drug sensitivity, indicating diagnostic/prognostic potential.

CONCLUSION: ATIC is broadly upregulated across cancers and functions as an independent prognostic biomarker in LIHC. The ATIC-integrated nomogram shows modest predictive accuracy for LIHC survival. Our results implicate ATIC in oncogenic signaling (PI3K-AKT-mTOR, MYC, and cell-cycle) and suggest ATIC as a candidate biomarker to guide targeted and chemotherapeutic strategies in LIHC. Further in vitro and in vivo validation is warranted.

PMID:42152649 | DOI:10.2174/0115665240438824260113042223

J Hepatocell Carcinoma. 2026 May 10;13:586916. doi: 10.2147/JHC.S586916. eCollection 2026.

ABSTRACT

PURPOSE: 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a persistent environmental pollutant that promotes hepatocellular carcinoma (HCC) through non-genotoxic mechanisms. However, stromal regulatory factors that counteract its tumor-promoting effects remain poorly defined. This study aimed to elucidate the role of actin alpha-2 (ACTA2) in TCDD-associated hepatocarcinogenesis.

METHODS: An integrative strategy combining network toxicology, Mendelian randomization, multi-omics and single-cell analyses, molecular docking and molecular dynamics simulations, along with in vitro experiments, was employed to investigate the functional role of ACTA2.

RESULTS: ACTA2 was identified as a stromal-associated factor linked to reduced HCC risk and improved patient survival. Single-cell and multi-omics analyses revealed that ACTA2 is predominantly expressed in hepatic stellate cells and fibroblast-like populations, reflecting tumor microenvironment composition rather than tumor cell-intrinsic expression. Functional enrichment analyses indicated that ACTA2 is associated with extracellular matrix remodeling and PI3K-AKT signaling. Molecular simulations demonstrated stable binding of TCDD to ACTA2 (ΔG_bind ≈ -7.05 kcal/mol), suggesting potential structural perturbation. In vitro experiments showed that TCDD downregulated ACTA2 expression, promoted proliferation of LX-2 and cancer-associated fibroblasts (CAFs), and activated PI3K-AKT-mTOR signaling, whereas ACTA2 overexpression attenuated these effects.

CONCLUSION: ACTA2 acts as a context-dependent stromal regulator that modulates PI3K-AKT-mTOR signaling in TCDD-induced hepatocarcinogenesis. These findings highlight the importance of stromal remodeling in environmental carcinogenesis and suggest ACTA2 as a potential biomarker and therapeutic target in dioxin-associated HCC.

PMID:42148320 | PMC:PMC13175077 | DOI:10.2147/JHC.S586916

Front Nutr. 2026 Apr 30;13:1818086. doi: 10.3389/fnut.2026.1818086. eCollection 2026.

ABSTRACT

INTRODUCTION: Metabolism-associated fatty liver disease (MAFLD) has emerged as a severe worldwide public health burden with insufficient available clinical therapeutic strategies, which underscores the urgent demand for safe, natural dietary interventions. Raspberry (Rubus idaeus L.), a typical food-medicine homologous fruit abundant in diverse bioactive components including anthocyanins, flavonoids and polysaccharides, possesses prominent nutritional and medicinal potential.

METHODS: In this study, raspberry aqueous extract (RE) was prepared to comprehensively investigate its ameliorative effects and underlying molecular mechanisms against MAFLD. MAFLD animal model was established in C57BL/6 mice via 12-week high-fat diet (HFD) feeding. From the 9th week, model mice were intragastrically administered with RE at doses of 1 g/kg/d and 2 g/kg/d for continuous intervention. Integrated multi-omics analyses including 16S rRNA microbial sequencing, serum/hepatic biochemical detection, histopathological examination, in vivo microbial colonization assay, and in vitro cellular and metabolomic experiments were performed to systematically clarify the regulatory mechanism.

RESULTS: RE treatment markedly improved the core pathological phenotypes of MAFLD mice, and significantly mitigated hepatic steatosis and hepatocellular injury. 16S rRNA sequencing demonstrated that RE remodeled the gut microbial dysbiosis, specifically elevating the abundance of beneficial genus Ileibacterium and suppressing pathogenic microbial taxa. Meanwhile, RE strengthened intestinal mucosal barrier integrity by upregulating tight junction protein expression, and activated hepatic purine metabolic reprogramming to boost the levels of critical metabolites including inosine and ADP. Spearman correlation analysis verified the significantly positive correlation between Ileibacterium abundance and hepatic inosine content, and both factors were closely correlated with the remission of MAFLD pathological indicators. In vivo colonization experiments further validated that Ileibacterium intervention alone remarkably alleviated hepatic lipid deposition and liver damage in MAFLD mice. In vitro strain metabolomics confirmed that Ileibacterium could directly biosynthesize and secrete inosine extracellularly. Furthermore, in vitro AML12 hepatocyte experiments revealed that 100 μM inosine remarkably relieved palmitic acid-induced lipotoxicity via reducing intracellular lipid overload, reactive oxygen species (ROS) accumulation and mitochondrial dysfunction, alongside modulating the expression of lipid metabolism, inflammatory and autophagy-related genes.

DISCUSSION: Collectively, our results elucidate that raspberry aqueous extract alleviates experimental MAFLD through the gut microbiota-purine metabolism-inosine regulatory axis, in which Ileibacterium and inosine act as the core synergistic mediators. This study provides solid preclinical experimental evidence for the development and application of raspberry as a promising functional food for the prevention and nutritional intervention of MAFLD.

PMID:42146077 | PMC:PMC13171365 | DOI:10.3389/fnut.2026.1818086

Cytotechnology. 2026 Jun;78(3):119. doi: 10.1007/s10616-026-00993-x. Epub 2026 May 14.

ABSTRACT

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer worldwide, with increasing incidence and mortality rates. Although several targeted therapies are currently available, the therapeutic outcomes remain unsatisfactory due to the high heterogeneity and drug resistance of HCC. Therefore, novel molecular mechanisms and therapeutic strategies urgently need to be explored. In this study, we obtained the GSE39791 dataset from the GEO database and identified 1,186 differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was conducted to obtain 776 key module genes, which were intersected with 11,671 HCC-related genes from the GeneCards database, resulting in 226 candidate genes. A protein-protein interaction (PPI) network was constructed using the STRING database, and the top 20 hub genes were identified using the MNC algorithm in Cytoscape. Among these, the five most significant hub genes-RFC4, TOP2A, AURKA, HSP90AA1, and MCM4-were selected for further analysis. KEGG enrichment analysis was performed to explore their functional pathways. Potential therapeutic agents were predicted using the CMap database, and molecular docking was conducted via AutoDock Vina. To validate the computational predictions, a quercetin intervention model was established. The optimal dose was determined through CCK-8 assays in HepG2 cells, and the expression of the five hub genes was examined in normal liver cells (LO2), HepG2 cells, and HepG2 cells treated with quercetin using RT-qPCR. The five hub genes-RFC4, TOP2A, AURKA, HSP90AA1, and MCM4-were significantly overexpressed in both HCC tissues and cell lines. Enrichment analysis revealed that these genes were mainly involved in cancer-related pathways, including the cell cycle, p53 signaling pathway, and FoxO signaling pathway. Drug prediction analysis showed that quercetin exhibited a negative regulatory pattern with respect to HCC and displayed binding energies below - 5 kcal/mol with all five hub proteins. CCK-8 assays confirmed the dose-dependent inhibitory effect of quercetin on HepG2 cell viability. RT-qPCR results demonstrated that quercetin significantly downregulated the expression of the five hub genes, consistent with the bioinformatics predictions. This study integrated multi-omics analysis and experimental validation to identify five core genes closely associated with HCC and suggested that quercetin may exert anti-HCC effects partly associated with the regulation of these genes. Our findings offer new insights into the molecular mechanisms of HCC and provide a promising strategy for the development of targeted therapeutics.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10616-026-00993-x.

PMID:42145839 | PMC:PMC13176377 | DOI:10.1007/s10616-026-00993-x

PLoS Med. 2026 May 15;23(5):e1004703. doi: 10.1371/journal.pmed.1004703. eCollection 2026 May.

ABSTRACT

BACKGROUND: Microvascular invasion (MVI) is closely related to the recurrence and metastasis of hepatocellular carcinoma (HCC), but the underlying cellular mechanism remains largely elusive. This study aims to elucidate the regional cellular discrepancy between MVI-positive (MVI+) and MVI-negative (MVI-) HCC by integrating Spatial transcriptomics (ST) and spatial metabolomics (SM).

METHODS AND FINDINGS: ST and SM were performed on six tissue samples from four patients (including 2 MVI+, 2 MVI-, and 2 paratumor tissues), with the integration of 79 public single-cell RNA sequencing datasets of HCC. Patient identity was used as a covariate in the linear equation for regional differentially expressed gene analysis with the ST data. Clinical validation was conducted through multiplex immunofluorescence staining in 79 patients, together with external validation in the cancer genome atlas (TCGA)-liver hepatocellular carcinoma (LIHC) cohort (n = 299) and an independent microarray dataset (n = 62). For cell-type-specific metabolic profiling, spatial transcriptomic-metabolic registration was performed. The functional roles of key metabolites were further validated in vitro using inflammatory cancer-associated fibroblasts (iCAFs) derived from hepatic stellate cells (HSCs) and primary CAFs through co-culture models and various functional assays assessing cell proliferation, migration, and invasion. In the tumor lesion, a malignant STMN1+HMGN2+GPC3+ cell subtype enriched in MVI+ HCC was identified, which exhibited enhanced proliferative activity and was associated with poor prognosis. This finding was further confirmed in a local cohort of 79 patients, where multiplex immunofluorescence staining for the three genes (STMN1, HMGN2, and GPC3) showed significantly higher expression in the MVI+ group than in the MVI- group (p = 0.046). Integrated SM analysis further revealed that this cell population underwent metabolic reprogramming characterized by suppressed glycerolipid metabolism. In the tumor capsule, iCAFs-related genes were downregulated in MVI+ cases, and iCAFs were located distally from the tumor boundary. Spatial metabolite mapping showed a strong correlation between taurine and iCAFs, and functional assays demonstrated that taurine promotes HCC proliferation and migration by suppressing iCAF activity. One limitation of this study is the small sample size of spatial omics data, which hinders a more complete molecular functional analysis of the STMN1+HMGN2+GPC3+ cell subtype and iCAFs in MVI+ HCC. Larger-scale ST cohorts are required to further validate and expand the findings of this study.

CONCLUSIONS: This integrative spatial atlas proposes a hypothesis that there exists a highly proliferative and metabolically reprogrammed malignant cell subtype in the tumor lesion of MVI+ HCC, and that taurine in the tumor capsule modulates iCAF activity to influence tumor progression. The exploratory results provide mechanistic insights into MVI-related HCC progression and offer potential avenues for targeted therapeutic intervention of MVI+ HCC.

PMID:42139279 | PMC:PMC13178920 | DOI:10.1371/journal.pmed.1004703

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

Environ Int. 2026 Apr 8;210:110249. doi: 10.1016/j.envint.2026.110249. Online ahead of print.

ABSTRACT

BACKGROUND: Deoxynivalenol (DON), a prevalent food-borne mycotoxin, increasingly recognized as a potent driver in the progression of chronic liver disease to cirrhosis and hepatocellular carcinoma (HCC); however, its systematic role is unclear. This study aims to decode the pathogenic networks of DON through an integrated multi-omics and toxicological framework.

METHODS: We integrated transcriptomic datasets from public repositories (GSE139602 and GSE25097) and single-cell RNA-seq data (GSE136103 and GSE149614) with toxicogenomics data. Analytical approaches included differential expression analysis, protein-protein interaction networks, profiling, single-cell trajectory analysis, trend testing, and machine learning modeling, and molecular docking. Key findings were validated through in vitro assays in human hepatocytes (THLE-2), as well as in vivo mouse models.

RESULTS: Five core hub genes (FAT1, CCND1, FOS, GADD45G, and PHLDA1) were identified as consistent drivers of DON-induced liver injury progression. Longitudinal analysis revealed that FAT1 and CCND1 underwent progressive upregulation, while GADD45G, and PHLDA1 were significantly suppressed across disease stages. Molecular docking and Cellular Thermal Shift Assays (CETSA) provided physical evidence of direct binding between DON and these hub proteins. Furthermore, prolonged DON exposure induced significant G2/M phase arrest in hepatocytes, consistent with the sustained dysregulation of the GADD45G/CCND1 axis. In vivo results corroborated that DON triggers noticeable hepatic structural damage and inflammatory infiltration, synchronized with hub protein dysregulation.

CONCLUSION: Chronic DON exposure drives liver disease progression by dysregulating core molecular networks and direct interaction with key hub proteins. Our integrated approach provides novel mechanistic insights and highlights potential biomarkers for DON-induced hepatotoxicity.

PMID:41967175 | DOI:10.1016/j.envint.2026.110249

Discov Oncol. 2026 Apr 11. doi: 10.1007/s12672-026-04951-z. Online ahead of print.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality. Chromosome 8 open reading frame 33 (C8orf33) has been noted as a potential oncogenic factor in several cancers, but its biological roles and regulatory mechanism in HCC microenvironment remain unknown.

METHODS: We integrated bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics (ST) to characterize the expression landscape of C8orf33. We then performed C8orf33 loss-of-function studies in HCC cell lines, including in vitro phenotypic assays and subcutaneous xenografts.

RESULTS: C8orf33 was broadly overexpressed and associated with unfavorable prognosis across multiple Cancers. In HCC, higher C8orf33 aligned with advanced stage and shorter overall survival. C8orf33 knockdown reduced proliferation and migration, impaired tumorigenic capacity, and increased apoptosis. ScRNA-seq analyses identified a malignant population of Epi3 with high C8orf33 expression. Cell-cell communication analysis suggested that C8orf33-high Epi3 state was associated with an enriched MIF-CD74/CXCR4/CD44 signaling program toward macrophage populations with M2-like features. ST analyses further confirmed the colocalization of C8orf33 with malignant features in tumor cores. In Huh7 cells, C8orf33 knockdown was accompanied by reduced mRNA and protein levels of MIF and its receptor components. Consistently, xenografts derived from C8orf33-silenced cells showed lower expression of these MIF-axis components and reduced infiltration of CD163 and CD206-positive macrophages.

CONCLUSION: These results support a tumor-promoting association of C8orf33 in HCC and suggest a potential link to macrophage-associated immunomodulatory features, nominating C8orf33 as a candidate biomarker and therapeutic target.

PMID:41965457 | DOI:10.1007/s12672-026-04951-z

Phytomedicine. 2026 Mar 30;155:158128. doi: 10.1016/j.phymed.2026.158128. Online ahead of print.

ABSTRACT

BACKGROUND: The global prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) continues to rise, and its pathogenesis is complex, creating an urgent need to discover novel and effective therapeutic strategies. The Zuogui Jiangtang Qinggan formula (ZGJTQGF), an approved in-hospital preparation, has demonstrated significant clinical efficacy in treating diabetes over several decades. However, the mechanisms underlying its potential therapeutic effects on MASLD remain unclear PURPOSE: This study systematically investigates the therapeutic effects and molecular mechanisms of ZGJTQGF on MASLD through the integration of network pharmacology and multi-omics strategies.

METHODS: The model of MASLD was successfully induced in db/db mice by a high-fat diet (HFD), which displayed characteristic dyslipidaemia. Serum biomarkers, histology, and hepatic multi-omics analyses were employed to assess metabolic status, steatosis, targets, and pathways. Ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), molecular docking analysis and in vitro verification were applied to explore the active ingredients of ZGJTQGF.

RESULTS: ZGJTQGF significantly reduced dyslipidemia in HFD-fed mice, inhibited pro-inflammatory cytokines, and restored glucose metabolic balance by lowering levels of glucose, insulin, OGTT, and HOMA-IR. Histopathology showed reduced lipid deposition and hepatocyte damage. Comprehensive multi-omics analysis suggested that regulating the AMPK/PGC-1α/PPARα and FXR-BSEP signaling pathways could be potential targets for ZGJTQGF in reprogramming glucose and lipid metabolism in MASLD treatment. Blood component analysis identified 52 ZGJTQGF-derived compounds. In molecular docking experiments, Wogonin, Naringenin, Quercetin, Tanshinone IIA and Berberine showed high-affinity binding to core targets in AMPK, PPARα, PGC-1α, FXR and FAS. Mechanistically, ZGJTQGF activated AMPK/PPARα /PGC-1α and FXR-BSEP signaling pathway, promotes fatty acid β oxidation and enhances energy consumption in AML-2 and 3T3-L1 cells, downregulates SREBP-1-dependent adipogenesis (reduces ACC1 and FAS expression), alleviates MASLD driven reprogramming of glucose and lipid metabolism, and regulates lipid metabolism and fatty acid synthesis.

CONCLUSIONS: ZGJTQGF activates the AMPK/PPARα /PGC-1α pathway and inhibits abnormal lipid accumulation in diabetic fatty liver by promoting fatty acid β-oxidation, energy consumption, and bile acid metabolism. These findings provide new insights into the mechanism of ZGJTQGF in the treatment of diabetic fatty liver disease.

PMID:41962267 | DOI:10.1016/j.phymed.2026.158128

JHEP Rep. 2026 Feb 18;8(5):101790. doi: 10.1016/j.jhepr.2026.101790. Online ahead of print.

ABSTRACT

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) exhibits diverse aetiologies and molecular heterogeneity, with a median 5-year overall survival of <70% due to high recurrence rates following curative-intent surgery. This study investigated the complex tumour microenvironment (TME) in HCC and explored interactions between various cell types and their roles in disease recurrence.

METHODS: Using a multi-omics approach on multi-region samples of surgically resected HCC from the PLANet 1.0 cohort (NCT03267641), we performed spatial transcriptomics on 17 tissue samples from four patients and bulk RNA sequencing on 329 sectors from 90 patients. Findings were validated using immunofluorescence and multiplex immunohistochemistry.

RESULTS: Our analysis revealed extensive intra- and intertumour gene expression heterogeneity and identified a specific subset of endothelial cells (ECs), INTS6⁺ ECs, enriched and spatially colocalised with tumour cells in primary tumours from patients with recurrence (p = 0.021, n = 49). A significant ANGPTL4-SDC1 ligand-receptor interaction was identified between INTS6⁺ ECs and tumour cells. Notably, INTS6⁺ ECs were enriched in microvascular invasion regions and spatially colocalised with tumour cells in patients with recurrence (p = 0.036, n = 53). These findings highlight endothelial-tumour cell interactions within the TME as potential therapeutic targets.

CONCLUSIONS: INTS6⁺ ECs are enriched in microvascular invasion regions and spatially colocalised with tumour cells in recurrent HCC, suggesting a potential role in disease recurrence and representing a promising therapeutic target within the TME.

IMPACT AND IMPLICATIONS: The spatial co-localisation of cell types plays a significant role in the recurrence of hepatocellular carcinoma. In this study, we have pinpointed a particular group of endothelial cells, known as INTS6+ endothelial cells, which are spatially colocalised with tumour cells and enriched in microvascular invasion regions in patients experiencing recurrence. These discoveries highlight novel therapeutic targets that focus on endothelial cell interactions within the tumour microenvironment to prevent recurrence and enhance overall patient survival.

PMID:41950768 | DOI:10.1016/j.jhepr.2026.101790

J Adv Res. 2026 Apr 5:S2090-1232(26)00280-8. doi: 10.1016/j.jare.2026.04.002. Online ahead of print.

ABSTRACT

INTRODUCTION: The clinical benefit of combining lenvatinib with PD-1 blockade in HCC is frequently constrained by adaptive resistance and the development of an immune-cold tumor microenvironment.

OBJECTIVES: This study aimed to elucidate the molecular mechanisms underlying adaptive resistance and immune exclusion during lenvatinib-PD-1 therapy in HCC, with a particular focus on a UBTF/HSP90A/MIF regulatory circuit. We examined whether genetic or pharmacologic targeting of macrophage migration inhibitory factor (MIF) could restore lenvatinib sensitivity, remodel the tumor immune microenvironment, and serve as a predictive biomarker in clinical cohorts.

METHODS: Paired lenvatinib-sensitive and -resistant HCC models were interrogated using integrated multi-omic and functional approaches, including RNA sequencing, promoter pull-down assays, ChIP, luciferase reporter assays, PLA, and flow cytometry. Key findings were validated in patient-derived organoids and xenografts, as well as in an immunocompetent hydrodynamic HCC mouse model. Clinical relevance was evaluated in independent cohorts treated with lenvatinib plus anti-PD-1 therapy.

RESULTS: UBTF directly bound to and transcriptionally activated the HSP90A promoter, resulting in increased HSP90A expression and stabilization of MIF. MIF signaling through CD74 co-activated the PI3K-AKT and MAPK pathways, sustaining tumor cell proliferation under lenvatinib pressure. Single-cell RNA sequencing and multiplex immunohistochemistry revealed macrophage enrichment and CD8⁺ T-cell exclusion in resistant tumors. Genetic ablation of Mif (Alb-Cre; Mif^flox/flox) or pharmacologic inhibition with 4-IPP (4-Iodo-6-phenylpyrimidine) restored lenvatinib sensitivity, reprogrammed the tumor immune microenvironment, and, when combined with PD-1 blockade, achieved superior tumor control and prolonged survival. In clinical datasets, low pretreatment MIF expression was associated with improved responses to lenvatinib plus PD-1 therapy.

CONCLUSIONS: These findings define a UBTF/HSP90A/MIF axis linking proteostasis and cytokine signaling to immune-metabolic dysfunction and lenvatinib resistance in HCC. MIF emerges as both a mechanistic driver and a predictive biomarker, supporting prospective evaluation of therapeutic strategies combining lenvatinib-PD-1 with MIF- or HSP90A-targeted interventions to personalize TKI-ICI therapy.

PMID:41946392 | DOI:10.1016/j.jare.2026.04.002