Transl Oncol. 2026 Sep 9;73:103020. doi: 10.1016/j.tranon.2026.103020. Online ahead of print.

ABSTRACT

BACKGROUND: The prognostic relevance of inflammatory bowel disease (IBD)-colorectal cancer (CRC) shared host-microbe signatures in non-intestinal epithelial malignancies remains unclear. This study aimed to evaluate the prognostic and biological significance of an IBD-CRC shared host-microbe interactome signature in bladder urothelial carcinoma (BLCA).

METHODS: Gene set variation analysis (GSVA) was used to assess the activity of the IBD-CRC shared signature across The Cancer Genome Atlas (TCGA) pan-cancer solid tumor cohorts, including lung, liver, colorectal, and urinary system tumors. In BLCA, weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO)-Cox regression were applied to construct a prognostic risk model, which was validated in independent transcriptomic cohorts. An attention-based multiple instance learning (MIL) model was developed to predict the LASSO-derived high- or low-risk group from H&E whole-slide images (WSIs), using TCGA cases for training and internal validation and an independent institutional cohort of 39 BLCA patients for external validation. Molecular subtype, immune infiltration, immunohistochemistry (IHC), machine learning, single nucleotide variation/copy number variation (SNV/CNV), single-cell/spatial transcriptomics, and WSI-based deep learning analyses were integrated to characterize the biological relevance of the signature.

RESULTS: High GSVA scores were significantly associated with poor prognosis in BLCA. The LASSO-derived high-risk group was enriched in basal/squamous molecular features and exhibited an immune-infiltrated but immunosuppressive tumor microenvironment, characterized by increased immunosuppressive cell infiltration and elevated immune checkpoint expression. Conventional IHC markers supported distinct subtype-related protein phenotypes between risk groups. Single-cell and spatial transcriptomic analyses revealed that malignant cells with high signature activity were enriched in Wnt, Hippo, and cell adhesion pathways. The WSI-based MIL model achieved an area under the curve (AUC) of 0.852 in the internal validation cohort. Machine learning and SNV/CNV analyses further characterized key molecular features associated with the LASSO risk score, including AKR1B1, LY6E, MEST, and others. Pan-cancer characterization of AKR1B1 across multiple malignancies, including lung adenocarcinoma (LUAD), liver hepatocellular carcinoma (LIHC), and kidney renal clear cell carcinoma (KIRC), revealed cancer-type-specific associations with immunosuppressive microenvironmental features and tumor stemness.

CONCLUSION: The IBD-CRC shared host-microbe signature has significant prognostic value in BLCA and is associated with basal/squamous differentiation, immunosuppressive microenvironmental features, genomic alteration patterns, and malignant cell functional heterogeneity. The integrated multi-omics framework and externally validated pathology AI model provide potential tools for BLCA risk stratification and biological interpretation.

PMID:42715652 | DOI:10.1016/j.tranon.2026.103020

Gut. 2026 Sep 7:gutjnl-2025-337414. doi: 10.1136/gutjnl-2025-337414. Online ahead of print.

ABSTRACT

BACKGROUND: Neutrophils are increasingly recognised as immunosuppressive drivers of hepatocellular carcinoma (HCC), yet their persistence in the oxidative, lipid-rich tumour microenvironment remains poorly understood.

OBJECTIVE: To elucidate the metabolic and molecular programmes that enable tumour-associated neutrophils (TANs) to resist ferroptosis and sustain immunosuppression in HCC.

DESIGN: We employed human HCC samples, multiple murine HCC models, transcriptomic and lipidomic profiling, genetic loss-of-function systems and therapeutic interventions. Ferroptosis sensitivity, lipid metabolic rewiring and immunological consequences of TANs were systematically evaluated across models and validated in patient datasets and biospecimens.

RESULTS: TANs in human HCC and mouse models exhibit pronounced lipid accumulation and oxidative stress compared with peripheral neutrophils. Multi-omic profiling revealed that TANs are enriched for lipid-binding gene programmes and undergo rewiring towards sphingolipid and unsaturated fatty acid metabolism. We identified triggering receptor expressed on myeloid cells 2 (TREM2) as a key lipid-sensing receptor selectively expressed in TANs. Functional deletion of TREM2 reprogrammed the tumour immune microenvironment, restoring CD8⁺ T cell activity and suppressing HCC progression. Mechanistically, tumour-derived sphingosine-1-phosphate (S1P) activates TREM2, triggering nuclear factor erythroid 2-related factor 2 (NRF2)-mediated transcription of glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11), thereby promoting ferroptosis resistance. TREM2 expression is transcriptionally induced by granulocyte-macrophage colony-stimulating factor-signal transducer and activator of transcription 3 (GM-CSF-STAT3) signalling. Genetic deletion of TREM2, clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated knockout of sphingosine kinase 1/2 (SPHK1/2) in tumour cells, or pharmacological inhibition of S1P synthesis disrupts this protective lipid-immune circuit, sensitises TANs to ferroptosis and restricts tumour growth. Therapeutically, a peptide-based TREM2 inhibitor reprogrammes TANs, restores CD8⁺ T cell function and enhances anti-programmed cell death protein 1 (PD-1) immunotherapy efficacy. Clinically, TREM2⁺ polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) are enriched in HCC tumours, correlate with SPHK1/2 expression and T cell dysfunction and associate with poor patient prognosis.

CONCLUSION: Our study uncovers the S1P-TREM2-NRF2 axis as a critical metabolic-immune circuit that preserves neutrophil survival and immunosuppressive function in HCC. Targeting this lipid-dependent ferroptosis resistance pathway offers a promising therapeutic strategy to overcome immunotherapy resistance in liver cancer.

PMID:42705697 | DOI:10.1136/gutjnl-2025-337414

Front Pharmacol. 2026 Aug 21;17:1911035. doi: 10.3389/fphar.2026.1911035. eCollection 2026.

ABSTRACT

Ribophorin I (RPN1), a core component of the oligosaccharyltransferase complex, is traditionally known for its role in endoplasmic reticulum-associated N-glycosylation. Recent studies have identified RPN1 as an emerging regulator of tumor progression and immunity. Aberrant RPN1 overexpression has been reported in multiple malignancies, including glioma, hepatocellular carcinoma, sarcoma, and triple-negative breast cancer, where it is frequently associated with aggressive clinicopathological features and poor prognosis. RPN1 promotes tumor immune evasion by promoting N-glycosylation and stabilization of programmed death-ligand 1 (PD-L1), thereby enhancing immune checkpoint signaling and directly inhibiting anti-tumor T-cell responses. Consequently, elevated RPN1 expression is consistently associated with an immunosuppressive tumor microenvironment rich in M2 macrophages and poor in CD8⁺ T cells. More importantly, multiple omics signature analyses indicate RPN1 is integrated into several disulfidptosis-related risk models; however, direct experimental evidence confirming the causal linkage between RPN1 and disulfidptosis remains limited. Correlative database data also show potential associations between RPN1 upregulation and genomic instability and treatment resistance. Based on tiered classification of existing evidence (biochemical functional validation vs. multi-omics correlation), this review systematically summarizes the biological roles of RPN1 in cancer, its functions in tumor immunity and disulfidptosis-associated pathways and finally evaluates its potential as a therapeutic target in precision oncology.

PMID:42698633 | PMC:PMC13542368 | DOI:10.3389/fphar.2026.1911035

Biofactors. 2026 Sep-Oct;52(5):e70136. doi: 10.1002/biof.70136.

ABSTRACT

Primary liver cancer (PLC) is a biologically heterogeneous group of malignancies dominated by hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and a smaller subset of combined hepatocellular-cholangiocarcinoma (cHCC-CCA), and its clinical burden remains high because current diagnostic and prognostic tools do not adequately capture molecular diversity. Conventional imaging, serum markers, and histopathological assessment remain insufficient for precise early diagnosis, subtype-resolved classification, and outcome stratification, while tissue and liquid biopsy approaches have expanded the range of analytes available for clinical assessment. Recent studies have identified candidate biomarker signatures across genomic, epigenomic, transcriptomic, proteomic, metabolomic, and circulating layers, suggesting that integrated multi-omics profiling may better represent tumor lineage, clonal evolution, immune context, and therapeutic vulnerability than isolated molecular readouts. However, these layers are not equally mature for clinical use: genomic testing is closest to routine therapeutic application in iCCA, plasma methylation assays are advancing for HCC surveillance augmentation, and many proteomic or metabolomic panels remain validation-stage tools. Their clinical value remains constrained by sampling bias, biospecimen-dependent signal loss, assay standardization, cost, and the need for prospective validation across clinically diverse populations. This narrative review critically synthesizes current evidence on multi-omics biomarker signatures for precision diagnosis and prognosis in primary liver cancer and argues that clinically useful signatures should be question-specific, stage-aware, and specimen-aware rather than universal multi-analyte panels.

PMID:42697859 | PMC:PMC13545153 | DOI:10.1002/biof.70136

Zhongguo Zhong Yao Za Zhi. 2026 Aug;51(15):4401-4409. doi: 10.19540/j.cnki.cjcmm.20260421.801.

ABSTRACT

Based on the gut-liver axis, this study integrated multi-omics and network pharmacology strategies to explore the mechanism of Biejia-Ruangan Compound Tablets(BRC), a preferred Chinese patent medicine for anti-hepatic fibrosis, in alleviating alcoholic liver disease(ALD). The Lieber-DeCarli ethanol liquid diet was used to establish the ALD model, and the pharmacodynamic effects of BRC were evaluated. Non-targeted metabolomics and network pharmacology were employed to screen key metabolites and pathways, while multiple technical methods such as immunohistochemistry were used to verify key molecules in the gut-liver axis. The results showed that BRC significantly improved liver morphology and pathological damage in mice, reduced organ indices, and decreased serum levels of aspartate aminotransferase(AST) and alanine aminotransferase(ALT). BRC also alleviated hepatocellular steatosis, inflammatory infiltration, and fibrosis, and reduced the levels of reactive oxygen species(ROS) and partially restored superoxide dismutase(SOD) activity. Metabolomic analysis indicated that BRC could significantly reverse the disordered metabolic profiles of the intestine and liver, and increase the level of the differential metabolite prostaglandin E_2(PGE_2), which may be closely related to the adenosine 5'-monophosphate(AMP)-activated protein kinase(AMPK) signaling pathway. Compared with the model group, BRC effectively upregulated the expression of prostaglandin G/H synthase-2(COX-2) in the small intestine, inhibited the levels of inflammatory factors such as lipopolysaccharide(LPS), tumor necrosis factor-α(TNF-α), and interleukin-1β(IL-1β) in the liver, and promoted the expression of phosphorylated AMP-activated protein kinase catalytic subunit α2(p-AMPKα2), forkhead box protein O1(FOXO1), and peroxisome proliferator-activated receptor gamma coactivator-1α(PGC-1α) in the liver, as well as the activity of cytoplasmic phosphoenolpyruvate carboxykinase 1(PCK1). In conclusion, BRC may alleviate ALD by alleviating hepatic inflammation, oxidative stress, and metabolic disorders through the gut-liver axis via the COX-2/AMPK/FOXO1/PGC-1α/PCK1 signaling pathway. This study provides a scientific basis and new insights for the clinical application of BRC and the prevention and treatment of ALD with TCM.

PMID:42693054 | DOI:10.19540/j.cnki.cjcmm.20260421.801

Int J Immunopathol Pharmacol. 2026 Jan-Dec;40:3946320261486727. doi: 10.1177/03946320261486727. Epub 2026 Sep 3.

ABSTRACT

BackgroundWD Repeat Domain 76 (WDR76) plays a potential role in cellular regulation; however, its comprehensive landscape across human malignancies and its specific biological function in hepatocellular carcinoma (HCC) remain largely unexplored.MethodsWe conducted a systematic pan-cancer analysis utilizing multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) atabases to evaluate WDR76 expression, subcellular localization, and its correlation with clinicopathologic features, genomic instability, and immune infiltration. Diagnostic and prognostic values were assessed via Receiver operating characteristic (ROC) and Kaplan-Meier analyses. Furthermore, the functional role of WDR76 in HCC was validated in vitro using Hep-3B and Huh7 cell lines through siRNA-mediated knockdown, followed by CCK-8, wound-healing, and transwell assays.ResultsWDR76 was significantly upregulated in the majority of tumor types, including LIHC, LUAD, and COAD, while exhibiting nuclear localization. Elevated WDR76 expression correlated with advanced tumor staging, metastasis, and poor clinical outcomes across multiple cohorts, particularly in ACC, KIRP, and LIHC. ROC analysis highlighted its exceptional diagnostic precision in cancers such as GBM and LIHC. Immunologically, WDR76 expression was intricately linked to immune cell infiltration, immune checkpoint markers, and genomic instability parameters, suggesting a role in shaping the tumor microenvironment. Drug sensitivity profiling revealed that high WDR76 levels correlate with resistance to specific chemotherapeutic agents. Experimentally, silencing WDR76 in HCC cells significantly suppressed cell proliferation, migration, and invasion capabilities.ConclusionOur study establishes WDR76 as a robust pan-cancer prognostic biomarker and a potential immunotherapeutic target. Specifically, we provide experimental evidence that WDR76 functions as an oncogenic driver in liver cancer, promoting malignant phenotypes and offering a novel avenue for targeted therapeutic intervention.

PMID:42690047 | PMC:PMC13542525 | DOI:10.1177/03946320261486727

Front Immunol. 2026 Aug 19;17:1856643. doi: 10.3389/fimmu.2026.1856643. eCollection 2026.

ABSTRACT

BACKGROUND: Metastasis is the primary cause of treatment failure and adverse prognosis in hepatocellular carcinoma (HCC), and the molecular basis of HCC metastasis remains poorly defined. This work investigated the potential mechanisms underlying HCC metastasis through integrated multi-omics analysis of metabolomics and proteomics.

METHOD: This retrospective study included 105 individuals with HCC, with comparative analysis between metastatic and non-metastatic cases. We further evaluated the effects of metastasis on serum metabolomics and proteomics in HCC patients.

RESULT: Widespread disturbances in amino acid metabolism were identified via untargeted metabolomics in HCC patients with metastasis, closely governing inflammation-related metabolic remodeling and oxidative stress responses. Specifically, we identified 91 and 59 distinct differential metabolites capable of indicating HCC metastasis, with the screening criteria set as log₂ fold change > 1.5, adjusted P value < 0.05, and VIP > 1.5 in positive and negative modes, respectively. The alanine, aspartate and glutamate metabolism pathway correlated with HCC-associated lung metastasis, while the gluconeogenesis pathway was linked to HCC-associated bone metastasis. Compared with HCC (non-metastatic hepatocellular carcinoma), the key molecular alterations in the multi-omics network of HCC_M (HCC with metastasis) are implicated in inflammatory metabolic reprogramming, oxidative stress response, gluconeogenesis, glycolysis, and the tricarboxylic acid (TCA) cycle. Twenty-five proteins, including PKM2, PERCK, ALDH2, CPS1, GLS1, GLUD1, GOT1, and SLC38A2, were identified as potential biomarkers for HCC metastasis.

CONCLUSION: By integrating untargeted metabolomic and proteomic profiling, we identified distinct metabolic and proteomic changes linked to HCC metastasis. This work also characterized the pathological characteristics and core pathways underlying HCC metastasis, while identifying potential therapeutic candidates.

PMID:42688489 | PMC:PMC13534100 | DOI:10.3389/fimmu.2026.1856643

Front Med (Lausanne). 2026 Aug 18;13:1899423. doi: 10.3389/fmed.2026.1899423. eCollection 2026.

ABSTRACT

The liver serves the triple functions of metabolism, detoxification, and immune surveillance. Its unique immune microenvironment is shaped by continuous exposure to gut-derived antigens, pathogen-associated molecular patterns (PAMPs), and metabolites arriving via the portal vein, necessitating a delicate equilibrium between immune tolerance and effector activation. This equilibrium relies on the coordinated activities of diverse liver-resident immune cell populations-including Kupffer cells (KCs), liver sinusoidal endothelial cells (LSECs), hepatic stellate cells (HSCs), dendritic cells (DCs), tissue-resident memory T cells (TRM), innate-like T cells, including mucosal-associated invariant T (MAIT) cells, natural killer T (NKT) cells, and γδ T cells, innate lymphoid cells (ILCs, encompassing conventional NK cells and helper ILC subsets), and neutrophils. With advancing age and chronic injury, these resident immune cell populations undergo profound senescence-associated phenotypic reprogramming that is spatially organized along the portal-to-central axis of the hepatic lobule. Key mechanisms include: telomere dysfunction and DNA damage accumulation driving persistent activation of p53/p21 and p16/Rb pathways; mitochondrial dysfunction with mitochondrial DNA (mtDNA) leakage fueling the senescence-associated secretory phenotype (SASP) via the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway; epigenetic age acceleration, including genome-wide H3K27me3 heterochromatinization; and metabolic reprogramming toward glycolysis and lipid accumulation. This review proposes a "spatial niche remodeling" framework to integrate these cell-intrinsic senescence programs with their lobular context, intercellular communication network rewiring, and pathogenic roles across the spectrum of chronic liver disease-from steatosis through steatohepatitis, fibrosis, cirrhosis, to hepatocellular carcinoma. We critically evaluate emerging senotherapeutic strategies targeting specific liver-resident immune cell subsets, discuss the barriers to clinical translation, and identify priority areas for future investigation, including the application of spatial multi-omics, humanized models, and epigenetic clock-guided clinical trials.

PMID:42683053 | PMC:PMC13530898 | DOI:10.3389/fmed.2026.1899423

Ther Adv Med Oncol. 2026 Aug 31;18:17588359261481797. doi: 10.1177/17588359261481797. eCollection 2026.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) is driven by extensive metabolic reprogramming, vascular remodeling, and immune microenvironmental dysfunction. Although numerous stratification signatures have been proposed, few are grounded in clinically derived serum multi-omics and biologically linked to endothelial remodeling, endothelial regulation, and immune exclusion.

OBJECTIVES: This study aimed to identify a serum-derived lipid-endothelial program associated with immune exclusion and clinical stratification in HCC.

DESIGN: A translational multi-omics study integrating clinically collected serum samples, public transcriptomic cohorts, single-cell RNA sequencing, and experimental validation.

METHODS: Proteomic and metabolomic sequencing was performed on serum samples from patients with HCC and normal controls. Dysregulated pathways were integrated with transcriptomic data from TCGA-LIHC and ICGC-LIRI-JP cohorts to identify genes jointly associated with lipid metabolism and leukocyte transendothelial migration. A risk score was calculated using the expression of PON1, TXNRD1, CLDN4, CLDN6, CYP2C9, and CTSA. Higher expression of TXNRD1, CLDN4, CLDN6, and CTSA contributed to a higher risk score, whereas PON1 and CYP2C9 contributed protective coefficients. Immune contexture, tumor mutation burden, and exploratory therapeutic sensitivity patterns were further evaluated using transcriptome-based drug sensitivity prediction, followed by single-cell RNA sequencing and experimental expression validation.

RESULTS: Serum multi-omics analysis revealed prominent dysregulation of lipid metabolic pathways and leukocyte transendothelial migration-related processes in HCC. Integrative analysis identified a six-gene lipid-endothelial signature (PON1, TXNRD1, CLDN4, CLDN6, CYP2C9, and CTSA) that stratified patients into high- and low-risk groups. In the TCGA-LIHC cohort, high-risk patients had significantly poorer overall survival than low-risk patients (log-rank P < 0.0001), and this survival-stratifying association was externally supported in the ICGC-LIRI-JP cohort (log-rank P = 0.016). The high-risk phenotype was associated with immune-excluded features, distinct somatic mutation patterns, and altered predicted sensitivity to several selected anticancer agents. Single-cell analysis and experimental assays further supported the association between the six-gene program, malignant epithelial states, endothelial-related remodeling, and immune microenvironmental heterogeneity.

CONCLUSION: This study defines a clinically derived lipid-endothelial program associated with immune exclusion, adverse prognosis, and potential differences in therapeutic vulnerability in HCC. The proposed signature provides a biologically informed framework for prognostic assessment and may support future evaluation of targeted interventions in HCC.

PMID:42682961 | PMC:PMC13530516 | DOI:10.1177/17588359261481797

J Gene Med. 2026 Sep;28(9):e70111. doi: 10.1002/jgm.70111.

ABSTRACT

BACKGROUND: Metabolic pathways are crucial in hepatocellular carcinoma (HCC) pathogenesis, but causal metabolic genes remain unclear. This study used Summary data-based Mendelian Randomization (SMR) and colocalization to identify metabolism-related genetic loci influencing HCC risk.

METHODS: Differentially expressed genes in hepatic malignancy phenotype versus normal tissues from TCGA and GTEx were analyzed. Metabolism-related candidates were examined via SMR and colocalization using multi-omics data: methylation (mQTL), expression (eQTL), and protein (pQTL) quantitative trait loci.

RESULTS: Multi-omics integration identified NIT2 as a key metabolic regulator for HCC. The cg13016775 locus of NIT2 was associated with elevated HCC risk at gene (OR = 1.618, 95% CI: 1.199-2.182) and protein (OR = 4.432, 95% CI: 1.783-11.018) levels. Colocalization supported a shared causal variant (PPH4 > 0.6), linking NIT2 to hepatocarcinogenesis via metabolic regulation.

CONCLUSIONS: This study provides multi-omics evidence for NIT2 as a potential causal gene in HCC, enhancing understanding of metabolic contributions to HCC pathogenesis and highlighting integrative genomics for uncovering causal relationships.

PMID:42681890 | PMC:PMC13534973 | DOI:10.1002/jgm.70111

Nat Commun. 2026 Jul 31;17(1):9381. doi: 10.1038/s41467-026-75949-y.

ABSTRACT

Hepatocellular carcinoma (HCC) is a cancer with high incidence and mortality rate. Although immune checkpoint inhibitors (ICIs) improved survival outcomes for HCC patients, limited objective response rate highlights the urgency of investigating determinants of immunotherapy. Here, we explore HCC resistance mechanisms following neoadjuvant αPD-1 immunotherapy by constructing a comprehensive multi-modal single-cell transcriptomic atlas consisting of 14 HCC patients treated with αPD-1 from our cohort (ClinicalTrials.gov ID: NCT06571396) and 60 external HCC cases with heterogeneous treatment backgrounds. Supervised by clinical outcomes of our cohort, we identify positive and negative regulators of immunotherapy within the tumor immune microenvironment (TIME), especially lipid-associated macrophages (LAM) with increased lipid metabolic state in non-responders and characterized by C1QA, FABP1, and APOA1 expression. We further show the presence, exogenous inducements and immunosuppressive functions of LAM, along with regulation strategies of its lipid-associated condition, including lycopene and chiglitazar. Furthermore, we construct interaction networks of immune regulators across responders and non-responders, showing distinct ligand-receptor landscapes with intervention targets. We reveal the TIME components including immunosuppressive LAMs that influence immunotherapy outcomes, thus providing evidence and insights for exploring immune landscape and therapeutic strategies for HCC immunotherapy. ClinicalTrials.gov ID: NCT06571396.

PMID:42680737 | PMC:PMC13534469 | DOI:10.1038/s41467-026-75949-y

Anal Cell Pathol (Amst). 2026;2026(1):e1554526. doi: 10.1155/ancp/1554526.

ABSTRACT

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of tumor initiation and progression through transcriptional and posttranscriptional mechanisms. UPK1A antisense RNA 1 (UPK1A-AS1), a cancer-associated lncRNA, has been reported to participate in oncogenic processes; however, its overall landscape across human malignancies and its biological role in therapy resistance remain poorly understood. Given the increasing importance of identifying functional lncRNAs with prognostic and therapeutic potential, this study presents a comprehensive multiomics characterization of UPK1A-AS1 and its experimental validation in hepatocellular carcinoma (HCC). We integrated datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression Project (GTEx), the cancer immunology data engine (CIDE), and the cBioPortal for cancer genomics (cBioPortal) to systematically assess its expression pattern, genomic alterations, clinical significance, and immunological associations. Our analyses revealed that UPK1A-AS1 is significantly upregulated in multiple tumor types, with copy-number amplification as the predominant genomic alteration driving its overexpression. Elevated UPK1A-AS1 expression was correlated with advanced disease stage, poor differentiation, immune exclusion, and unfavorable prognosis, supporting its potential as a cancer type-dependent biomarker. In parallel, functional studies demonstrated that hypoxia transcriptionally induces UPK1A-AS1 in HCC, where it promotes sorafenib resistance by suppressing apoptosis. Silencing UPK1A-AS1 restored apoptotic and enhanced sorafenib efficacy both in vitro and in vivo. Collectively, our findings suggest that UPK1A-AS1 is a hypoxia-inducible oncogenic lncRNA that plays dual roles in cancer, with cancer type-dependent associations with progression and immune modulation across malignancies and mechanistically mediating hypoxia-associated drug resistance in HCC.

PMID:42678131 | PMC:PMC13532061 | DOI:10.1155/ancp/1554526

Cell Cycle. 2026 Dec;25(1):1-29. doi: 10.1080/15384101.2026.2725418. Epub 2026 Sep 1.

ABSTRACT

Gastrointestinal (GI) cancers, including colorectal, gastric, pancreatic, hepatocellular, and esophageal malignancies, remain a leading cause of cancer-related mortality worldwide. Emerging evidence identifies the gut microbiome as a critical regulator of GI carcinogenesis, influencing tumor initiation, immune evasion, therapeutic response, and clinical outcomes through inflammation, genotoxicity, metabolic reprogramming, and epithelial barrier disruption. Importantly, biological rationale, clinical evidence, and translational opportunities differ across GI tumor types. Specific taxa, including Fusobacterium nucleatum, enterotoxigenic Bacteroides fragilis, pks⁺ Escherichia coli, and Helicobacter pylori, exhibit tumor-specific oncogenic roles with causal evidence ranging from associative to guideline-validated. Microbiome-based biomarkers, including composite multi-taxon models and signatures predictive of immune checkpoint inhibitor response, are evaluated using a four-tier framework (preclinical, associative, near-clinical, and validated). Microbiome-targeted therapies, including probiotics, fecal microbiota transplantation, dietary modulation, and engineered microbial therapeutics, are critically appraised according to clinical evidence and translational readiness. Advances in spatial microbiomics, single-cell analysis, multi-omics, and artificial intelligence may further accelerate microbiome-based precision oncology. This review provides a translationally stratified synthesis of microbiome-GI cancer interactions and their implications for precision oncology.

PMID:42677508 | PMC:PMC13540093 | DOI:10.1080/15384101.2026.2725418

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

Front Oncol. 2026 Aug 14;16:1918635. doi: 10.3389/fonc.2026.1918635. eCollection 2026.

ABSTRACT

OBJECTIVE: Hepatocellular carcinoma (HCC) is characterized by frequent recurrence, therapeutic resistance, and marked metabolic adaptability. Disulfidptosis is a recently described form of regulated cell death associated with glucose deprivation and disulfide stress. This study aimed to identify disulfidptosis-related genes associated with HCC progression and to investigate the potential biological role of SLC5A6.

METHODS: Single-cell RNA sequencing and TCGA-LIHC transcriptomic data were integrated. A literature-derived, non-directional disulfidptosis-related gene-set enrichment score was calculated using ssGSEA, and copy-number alterations were inferred using inferCNV. WGCNA, differential expression analysis, and the SLC-family gene list were integrated to identify candidate genes. Bayesian deconvolution, ESTIMATE, TIDE, and GSVA were used to evaluate tumor-microenvironment-related features and pathway signatures. The biological effects of SLC5A6 silencing were assessed using proliferation, migration, invasion, apoptosis, and xenograft assays. Glucose-deprivation-induced disulfide stress was further evaluated by measuring protein disulfide content, the NADP+/NADPH ratio, and FLNA and FLNB band patterns under non-reducing conditions.

RESULTS: Single-cell analysis showed that malignant hepatocytes with higher inferCNV-derived CNV scores exhibited greater enrichment of the disulfidptosis-related gene signature. Integration of glucose-deprivation-associated DEGs, WGCNA modules, and SLC-family genes identified SLC5A6 as a candidate disulfidptosis-related gene that was upregulated in HCC and associated with poor prognosis. Bayesian deconvolution, ESTIMATE, TIDE, and GSVA analyses linked elevated SLC5A6 expression to advanced disease, stromal and immunosuppressive cell enrichment, higher T-cell exclusion scores, and activation of Wnt/mTOR-related signaling signatures. In SLC7A11-high HCC cells, glucose deprivation increased protein disulfide content and the NADP+/NADPH ratio and altered non-reducing FLNA and FLNB band patterns, whereas these changes were partially attenuated by SLC5A6 silencing. Under conventional culture conditions, SLC5A6 silencing inhibited proliferation, migration, invasion, and xenograft growth and increased apoptosis.

CONCLUSION: SLC5A6 is a candidate disulfidptosis-related gene and prognostic biomarker associated with malignant progression in HCC. The findings suggest that SLC5A6 may participate in glucose-deprivation-induced disulfide stress, while its direct role in regulating disulfidptotic cell death remains to be established. Its associations with immune-exclusion-related features also require further functional validation.

PMID:42666251 | PMC:PMC13521847 | DOI:10.3389/fonc.2026.1918635

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