J Liq Biopsy. 2026 Sep 19;14:100496. doi: 10.1016/j.jlb.2026.100496. eCollection 2026 Dec.

ABSTRACT

BACKGROUND: Circulating tumor DNA (ctDNA) analysis has revolutionized minimal residual disease (MRD) monitoring, but conventional tumor-informed amplicon-based sequencing (AMP) is limited by the narrow variant capacity and diversity. Hybrid capture-based sequencing (HYB) is more versatile and enables both tumor-informed and tumor-naïve liquid biopsy profiling.

METHODS: We analytically validated the performance of our novel HYB workflow and VarSURE variant calling pipeline, using reference standards (n = 6), plasma samples of cancer patients (n = 75) and healthy donors (n = 90). Genome-wide (GW) non-mutation features including copy number alterations, fragmentomics, and end-motif signatures were also evaluated to enhance ctDNA-MRD detection. Clinical performance was directly compared against our legacy AMP method (K-TRACK, Gene Solutions), using pre-treatment blood samples across multiple cancers (n = 290) and longitudinal cohorts of colorectal cancer (CRC, n = 64), and hepatocellular carcinoma (HCC, n = 47).

RESULTS: Optimal parameters to maximize assay performance included single-stranded DNA ligation technology, cfDNA input ≥ 15 ng, post-UMI sequencing depth ≥ 2500X, and high number of tracked mutations. In the tumor-informed setting, the HYB workflow was modestly better than the AMP method in detection of pre-treatment ctDNA; addition of GW features was marginally beneficial except in lung cancer. Surveillance ctDNA determined by the HYB workflow had superior sensitivity to predict recurrence in both CRC (AMP: 90.0%, HYB: 100%) and HCC (AMP: 80.0%, HYB: 96.0%). In the tumor-naïve setting, the performance gap widened significantly, and the combined HYB and GW workflow showed the highest performance in baseline ctDNA detection across all cancers, and achieved sensitivity of 90.0% and 92.0% to detect recurrence in CRC and HCC respectively.

CONCLUSIONS: The new methodology offers a streamlined and scalable solution for both comprehensive liquid biopsy profiling and longitudinal MRD tracking in routine clinical practice.

PMID:42830887 | PMC:PMC13634064 | DOI:10.1016/j.jlb.2026.100496

Biochem Biophys Res Commun. 2026 Sep 30;838:154646. doi: 10.1016/j.bbrc.2026.154646. Online ahead of print.

ABSTRACT

Mitophagy, a selective form of autophagy, has been implicated in tumor progression and therapeutic resistance; however, its prognostic significance in hepatocellular carcinoma (HCC) remains unclear. In this study, we comprehensively evaluated the role of mitophagy-related genes in HCC using multi-omics data. Gene expression profiles were obtained from the TCGA-LIHC and GSE14520 cohorts, and mitophagy-related genes were retrieved from the GeneCards database. Twenty differentially expressed mitophagy-related genes with prognostic value (pDEMGs) were identified, and consensus clustering stratified HCC patients into two clusters with significantly different survival outcomes (P = 0.001). A mitophagy enrichment score (MIES) was then calculated using single-sample gene set enrichment analysis (ssGSEA). Elevated MIES was associated with poorer overall survival (HR = 2.17, P = 0.005), metabolic activation, immune suppression, and differential drug sensitivity. Single-cell analysis of the GSE140228 dataset revealed heterogeneous MIES activity across cell populations, with relatively higher enrichment observed in proliferating T cells and dendritic cells. A six-gene prognostic signature (ACTR6, GAPDH, ATIC, ANP32E, CCT6A, and BSG) was developed using LASSO-Cox regression, which effectively stratified patients into high- and low-risk groups with distinct overall survival outcomes (1-, 3-, and 5-year AUCs: 0.780, 0.682, and 0.690, respectively). The risk score was correlated with immune infiltration patterns, mutational landscape, and chemotherapy response. qPCR validation further confirmed the upregulation of ACTR6, CCT6A, ATIC, and BSG in HCC cells. Collectively, these findings establish a mitophagy-related scoring system that reflects immune and genomic characteristics, as well as a six-gene signature with independent prognostic value, highlighting the potential clinical relevance of mitophagy in HCC.

PMID:42828884 | DOI:10.1016/j.bbrc.2026.154646

Cell Rep Med. 2026 Oct 2:103085. doi: 10.1016/j.xcrm.2026.103085. Online ahead of print.

ABSTRACT

Hepatocellular carcinoma (HCC) management is challenging due to its complex tumor microenvironment and poor treatment responses. Here, using tumor specimens from a prospective clinical trial of combined transarterial chemoembolization (TACE) with immune checkpoint blockade (ICB), we perform exhaustive multi-omics analysis including spatial proteomics and transcriptomics, single-cell RNA sequencing, and bulk transcriptomics. These analyses reveal that treatment response is associated with enrichment of anti-tumor T cell regions that are regulated by cGAS-STING activation within immune-suppressive epithelial cells. Conversely, fibrotic processes impede these pro-response processes. Based on these insights, we test triple combination therapy consisting of cGAS activation, immune checkpoint blockade, and anti-fibrosis strategies, which shows improved efficacy over dual therapy. To identify patients who would benefit, we construct a predictive model using a group sparse learning algorithm. Our findings provide a blueprint for crafting personalized HCC therapies using next-generation biomarkers.

PMID:42826719 | DOI:10.1016/j.xcrm.2026.103085

Clin Gastroenterol Hepatol. 2026 Oct 1:S1542-3565(26)00737-8. doi: 10.1016/j.cgh.2026.09.034. Online ahead of print.

ABSTRACT

Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly prevalent worldwide, yet most affected individuals remain undiagnosed, and pathways for non-invasive risk stratification and linkage to specialty care remain inconsistently implemented. With the emergence of pharmacologic therapies for metabolic dysfunction-associated steatohepatitis (MASH), accurate patient identification, disease staging, treatment selection, and longitudinal monitoring have become increasingly consequential. In this narrative review, we examine the evolving role of artificial intelligence (AI) across three levels of MASLD care, defined by where an AI output informs a decision and who acts on it: the individual patient, the health system, and health policy. At the patient level, machine-learning and deep-learning approaches have demonstrated potential applications in fibrosis assessment, histopathologic and imaging interpretation, multi-omics integration, treatment-response prediction, and hepatocellular carcinoma risk stratification. Across selected datasets, several models have performed comparably to or better than conventional non-invasive tests and expert interpretation, although no validated tool currently predicts treatment response before therapy. At the health-system level, AI may support population-level case finding, extraction of clinically relevant information from unstructured health records, prognostic assessment, and more efficient allocation of confirmatory testing and specialty care. At the policy level, AI-informed disease-burden modeling and risk stratification may help guide decisions regarding workforce capacity, resource allocation, reimbursement, and treatment coverage. However, most available studies are retrospective, frequently originate from single centers, and have limited external validation. No randomized trial has yet demonstrated that AI-guided management improves clinical outcomes in MASLD, while governance, transparency, and equity frameworks remain underdeveloped. Realizing the clinical value of AI will require prospective multicenter studies embedded within clearly defined MASLD care decisions, validation across genetically and socioeconomically diverse populations and health-system settings, standardized reporting and risk-of-bias assessment, and sustained attention to implementation, governance, and equity.

PMID:42822578 | DOI:10.1016/j.cgh.2026.09.034

Chem Biodivers. 2026 Oct;23(10):e71778. doi: 10.1002/cbdv.71778.

ABSTRACT

Pancreatic cancer has a dismal prognosis and limited therapeutic options, highlighting an urgent need for effective treatments. Sophoricoside (SOP), a natural isoflavone glycoside, has exhibited anticancer activities in multiple malignancies, including lung cancer, glioblastoma, and hepatocellular carcinoma. We combined cellular assays, network pharmacology, machine learning, and multi-omics to investigate SOP's effects. SOP-inhibited proliferation of MIA PaCa-2, SW1990, and PANC-1 cells dose-dependently. Network pharmacology revealed 85 overlapping targets enriched in MAPK, apoptosis, and PD-L1/PD-1 pathways. Machine learning and differential expression identified PTPN1 as the core target. PTPN1 was markedly upregulated in pancreatic adenocarcinoma, and its high expression correlated with poor survival and immune infiltration. Functional enrichment linked PTPN1 to TGF-β, VEGF, and metabolic reprogramming. Molecular docking suggested a possible binding mode between SOP and PTPN1, involving four predicted hydrogen bonds. SOP reduced PTPN1 mRNA, and PTPN1 knockdown phenocopied SOP's antiproliferative effect with no additivity upon combination. Collectively, this first report demonstrates that SOP restrains pancreatic cancer cell proliferation, with PTPN1 identified as a key functionally required downstream mediator based on integrative computational and functional evidence. This work offers an integrated strategy for mechanistic exploration and highlights PTPN1 as a promising therapeutic biomarker and target for pancreatic cancer.

PMID:42814531 | PMC:PMC13626263 | DOI:10.1002/cbdv.71778

J Hepatocell Carcinoma. 2026 Sep 24;13:637010. doi: 10.2147/JHC.S637010. eCollection 2026.

ABSTRACT

BACKGROUND: Hypoxia is a key driver of tumor progression across cancers, yet oxygen-sensing mechanisms beyond HIFs remain underexplored. 2-Aminoethanethiol dioxygenase (ADO) has recently been identified as an oxygen sensor, but its role in malignancy is poorly defined. We conducted a pan-cancer analysis of ADO with a special focus on hepatocellular carcinoma (HCC), to assess its oncogenic significance and clinical potential.

METHODS: A multi-omics pan-cancer analysis of ADO expression and survival was performed using TCGA and GTEx, with validation in HCC across ICGC, GEO, and CNHPP proteomic cohorts. Correlations with genetic, epigenetic, immune, and pathways were evaluated. Drug sensitivity was predicted. Functional validation was conducted in HCC cells through proliferation, colony formation, Western blotting, and xenograft assays.

RESULTS: ADO was aberrantly expressed across cancers and showed cancer type-specific survival associations. Integrative analyses revealed links with tumor mutation burden, microsatellite instability, chromatin regulator methylation, RNA modification, proliferative signaling (G2M checkpoint, MYC, TGF-β), an immunosuppressive microenvironment, and negative correlations with ROS-responsive genes. In HCC, ADO was consistently overexpressed, associated with advanced stage, poor differentiation, residual disease, and unfavorable survival across independent cohorts. ADO-high HCC showed reduced predicted responsiveness to checkpoint blockade but increased sensitivity to sorafenib and fluorouracil. Experimentally, ADO overexpression activated ERK signaling, upregulated CD276 and HMGB1, and promoted HCC cell proliferation, while ADO depletion suppressed tumor growth in vitro and in vivo, reversible upon re-expression.

CONCLUSION: ADO plays oncogenic and immunomodulatory roles in HCC, and may serve as a potential prognostic biomarker and therapeutic target in liver cancer.

PMID:42812529 | PMC:PMC13620309 | DOI:10.2147/JHC.S637010

Adv Sci (Weinh). 2026 Sep 29:e78039. doi: 10.1002/advs.78039. Online ahead of print.

ABSTRACT

Durable responses to current therapies remain limited in hepatocellular carcinoma (HCC), highlighting the need to identify regulators of malignant progression. By integrating multi-omics analyses, spatial transcriptomics, clinical specimens, and multiple models, we identified chromatin assembly factor 1B (CHAF1B) as a functional regulator of HCC phenotypes. Gain- and loss-of-function of CHAF1B altered proliferative, migratory, clonogenic, and tumorigenic phenotypes. LC-MS/MS, DIA proteomics, and cell-based assays revealed CHAF1B-associated lipogenic remodeling characterized by SREBP1C nuclear localization, lipogenic gene/protein induction, and lipid-droplet accumulation. Mechanistically, the WD40 repeat-containing region of CHAF1B contributed to its association with UHRF1 and SETDB1, supporting UHRF1-associated K63-linked ubiquitination and CRM1/exportin-1-dependent cytoplasmic redistribution of SETDB1. Conversely, CHAF1B depletion enhanced SETDB1 association with VHL and favored a predominantly K11-associated degradative ubiquitin state linked to proteasomal SETDB1 loss. SETDB1 redistribution and catalytic activity were associated with AKT T308-linked signaling. A focused CRISPR-based screen of deubiquitinases identified USP4 as an upstream regulator of CHAF1B protein homeostasis. USP4 depletion or Akebia saponin D (ASD) increased K48-linked ubiquitination of CHAF1B, reduced CHAF1B protein abundance, attenuated AKT T308-linked signaling, and suppressed malignant and lipogenic phenotypes. These findings reveal distinct ubiquitin-dependent states governing SETDB1 stability and identify USP4-dependent CHAF1B stabilization as an upstream regulatory node in HCC.

PMID:42811544 | PMC:PMC13624420 | DOI:10.1002/advs.78039

Int J Biol Sci. 2026 Sep 10;22(14):8090-8118. doi: 10.7150/ijbs.137262. eCollection 2026.

ABSTRACT

The tumor leading edge (TLE) is a critical region where tumor cells interact with the microenvironment to drive invasion and metastasis; however, its cellular architecture in early hepatocellular carcinoma (HCC) remains poorly understood. Here, we integrated single-nucleus RNA-seq (snRNA-seq), spatial transcriptomics, and computational pathology to investigate TLE in early HCC. We annotated 35 cell subpopulations and identified STMN1-high tumor cells as a key malignant subset enriched at the invasive front, interacting with Treg, plasma B, LAMP3⁺ dendritic cells and SPP1⁺ macrophages. Spatial analysis revealed three co-localized cell pairs-(SPP1⁺ macrophages co-localized with Tip-like and inflammatory endothelial cells), (LAMP3⁺ DCs co-localized with naive T cells), and (plasma B cells co-localized with cancer-associated fibroblasts)-forming a leading-edge tumor microenvironment (L-TME) niche associated with early relapse. We developed an L-TME-related machine-learning benchmark framework incorporating 71 imaging features (65 deep-learning + 6 pathological) based on the snRNA-seq, spatial transcriptomics and pathomics. The pathology model achieved robust performance (mean C-index=0.77) and successfully predicted the recurrence of early HCC (log-rank p < 0.05) in TCGA (n=147) and an independent in-house cohort (n=123). This study delineates the TLE cellular ecosystem of early HCC, defines a spatially coordinated immunosuppressive L-TME niche, and provides a clinically applicable predictive tool for postoperative recurrence. Integrating multi-omics with computational pathology deepens our understanding of early HCC metastasis and offers insights into improved prognostication and therapeutic strategies.

PMID:42807944 | PMC:PMC13618224 | DOI:10.7150/ijbs.137262

Signal Transduct Target Ther. 2026 Sep 28;11(1):418. doi: 10.1038/s41392-026-02875-2.

ABSTRACT

Hepatocellular carcinoma (HCC) exhibits a suboptimal response to immune checkpoint blockade (ICB) therapy; to overcome this resistance, we aimed to delineate key immune resistance factors via multi-omics analysis, develop strategies to block their immunosuppressive axes, and engineer a targeted nanosystem to enhance immunotherapy efficacy against PD-1 resistance in HCC. Using transcriptomic and proteomic data from anti-PD-1-treated HCC patients, along with functional validation in murine models and mechanistic molecular and cell biology studies, we identified transketolase-like 1 (TKTL1) as a dual-nature biomarker where overexpression predicted poor baseline prognosis yet enhanced response to ICB. Mechanistically, TKTL1 diverts glucose flux into glycolysis rather than pentose phosphate pathway (PPP), recruiting USP9X to deubiquitinate and stabilize HIF-1α, which upregulates HK2 to amplify glycolytic output and lactate accumulation. This metabolic rewiring orchestrates dual immunosuppressive circuits through HIF-1α-driven CCL4 secretion recruiting PD-L1^high dendritic cells (DCs), coupled with lactate-induced TRIM28^K408 lactylation that stabilizes PD-L1 by blocking ubiquitin-mediated degradation. We engineered a hepatoma-membrane-coated MnO₂ nanosystem (CQLH) co-delivering a TKTL1 inhibitor and lactate oxidase, which disrupted the TKTL1-HIF-1α-HK2 axis, depleted lactate, and reprogrammed the tumor microenvironment, thereby enhanced anti-PD-1 therapy to suppress tumor growth, especially in TKTL1^high tumors. These findings define a critical "TKTL1-glycolysis-lactate-DC" axis driving anti-PD-1 sensitivity in HCC, position TKTL1 as both a potential biomarker for ICB response and a tractable therapeutic target, and demonstrate that the targeted CQLH nanosystem overcomes resistance and enhances anti-PD-1 efficacy, offering a precision immunotherapeutic strategy for TKTL1^high HCC.

PMID:42802226 | PMC:PMC13616917 | DOI:10.1038/s41392-026-02875-2

Biomedicines. 2026 Aug 27;14(9):1919. doi: 10.3390/biomedicines14091919.

ABSTRACT

Immune checkpoint blockade has changed the management of several digestive system cancers, but its impact is highly context dependent. This review evaluates evidence for esophageal, gastric and gastroesophageal junction, colorectal, hepatocellular, biliary tract and gallbladder, and pancreatic cancers. Randomized phase III trials have established chemoimmunotherapy or dual-checkpoint strategies in advanced esophageal cancer, biomarker- and regimen-dependent first-line therapy in gastric cancer, PD-1-based therapy for MSI-H/dMMR colorectal cancer, atezolizumab-bevacizumab and STRIDE for unresectable hepatocellular carcinoma, and chemoimmunotherapy for advanced biliary tract cancer. Recent results also expand perioperative treatment: neoadjuvant checkpoint blockade produces high pathological response rates in dMMR colon cancer, adjuvant atezolizumab plus mFOLFOX6 improves disease-free survival in stage III dMMR colon cancer, and perioperative serplulimab improves event-free survival in PD-L1-positive resectable gastric cancer. These advances coexist with important negative findings. Pembrolizumab-containing therapy did not meet superiority end points in KEYNOTE-062, the initial adjuvant signal in IMbrave050 was not sustained, and unselected pancreatic ductal adenocarcinoma remains largely resistant to checkpoint blockade. Early vaccine, cellular, TIGIT, radiomics, spatial, and multi-omics studies remain hypothesis-generating and require external or randomized validation. Clinical interpretation should integrate evidence maturity, biomarker validity, immune-related toxicity, patient-reported outcomes, cost, access, and manufacturing demands rather than response rate alone.

PMID:42792661 | PMC:PMC13604390 | DOI:10.3390/biomedicines14091919

Biomedicines. 2026 Aug 25;14(9):1898. doi: 10.3390/biomedicines14091898.

ABSTRACT

Background/Objectives: Hepatocellular carcinoma (HCC) is the most prevalent primary liver tumor and is often diagnosed at advanced stages with very poor therapeutic response, leading to high mortality. Thus, new therapeutic strategies and biomarkers are urgently needed. We previously showed that the combination of loratadine, raloxifene, and sorafenib exerts synergistic cytotoxicity on HCC cells. Here, we explored potential molecular mechanisms underlying the anticancer effects of this combination using multiomics analyses. Methods: We performed proteomic analyses based on mass spectrometry, transcriptomic analyses using the Clariom D Plus human microarray (Affymetrix), and metabolomic analyses based on nuclear magnetic resonance to investigate the profile changes induced by the drug combination in HuH7 cells. Bioinformatic analyses were applied to associate the omics changes with biological functions, molecular interactions, and clinical relevance in terms of patient survival. Results: We identified several molecules whose expression changed in response to treatment across the three omics profiles analyzed. Some of them were found to be involved in hallmarks of cancer, including sustained proliferation, evasion of growth suppressors, and resistance to cell death. Integrated multi-omics analyses revealed that the drug combination suppresses critical oncogenic drivers (C7orf50, NUP188, and HS2ST1) and that the mitotic cell cycle process, DNA synthesis and cholesterol biosynthesis are the primary pathways affected. Protein-protein interaction analysis revealed five key hubs (KIF2C, PCNA, TRIP13, NDC80, and RPA3), whose expression in HCC is associated with poor clinical prognosis. Conclusions: The combined treatment rewired molecular networks involved in HCC progression. These findings identify clinically relevant molecular targets associated with poor prognosis and provide mechanistic insights into the synergistic anticancer activity of this drug combination.

PMID:42792641 | PMC:PMC13604568 | DOI:10.3390/biomedicines14091898

Biology (Basel). 2026 Sep 17;15(18):1646. doi: 10.3390/biology15181646.

ABSTRACT

Salinity, temperature and body weight dominate seawater acclimation in rainbow trout (Oncorhynchus mykiss), yet few studies simultaneously explore their main effects and potential correlative interactive patterns in hepatic responses. A 60-day L₉ (3³) orthogonal trial was performed on triploid rainbow trout with three gradients of body weight, temperature and salinity. Hepatic transcriptomics revealed that salinity drove global transcriptional remodeling and high salinity induced far fewer DEGs than medium salinity. WGCNA screened a salinity-positive blue module (r = 0.408, p = 0.0346), while alternative splicing confirmed extensive salinity-dependent post-transcriptional regulation. Semi-quantitative histology showed that 20 °C was associated with more pronounced salinity-caused hepatocellular vacuolation and karyopyknosis in the orthogonal test. Survival statistics indicated that salinity was the only factor with significant main effects (p < 0.05), and the 500 g-10 °C-10 ppt group obtained the highest survival. This multi-omics and histological dataset reveals a suggestive regulatory hierarchy-like pattern: salinity acts as the primary driver, temperature serves as a synergistic amplifier, and body weight plays a minor modulatory role. These findings provide a theoretical basis for developing size-specific salinity acclimation protocols in commercial triploid rainbow trout farming.

PMID:42792591 | PMC:PMC13604319 | DOI:10.3390/biology15181646

Anticancer Agents Med Chem. 2026 Sep 23. doi: 10.2174/0118715206470187260914042941. Online ahead of print.

ABSTRACT

INTRODUCTION: Hepatocellular carcinoma (HCC) is one of the largest health burdens in the world because of high mortality rates, low early diagnostic sensitivity, and poor response to conventional treatment. The existing diagnostic and treatment methods tend to be non-specific and linked with systemic toxicity and late cancer detection, which provokes the necessity of more accurate, precision-driven methods.

METHODS: This review analyzes recent developments in HCC diagnosis and treatment, including new biomarkers, liquid biopsy, and nanotechnology-based therapeutic systems. We critically analysed relevant studies on molecular biomarkers, tumour microenvironment targets, and various nanocarrier platforms.

RESULTS: Newer biomarkers such as Glypican-3, Exosomal microRNAs, circulating tumour DNA methylation panels, AFP-L3, IFI44L, miR-375, miR-203, and CD19 on tumour-associated macrophages showed better diagnostic sensitivity and specificity. Nanotherapeutics approaches that use lipid-based nanoparticles, polymeric systems, inorganic nanoparticles, metal-based nanoparticles, and carbon-based nanocarriers displayed enhanced therapy delivery, targeting, and therapeutic effects. Liposomes, dendrimers, polymeric nanoparticles, and mesoporous silica nanoparticles had especially promising outcomes.

DISCUSSION: A combination of biomarker-based diagnostics and nanotechnology-based diagnostic delivery systems will enable earlier detection, treatment, and delivery of therapeutic agents, reducing systemic toxicity. The liquid biopsy, multi-omics profiling, and AI-assisted imaging developments further improve the accuracy of diagnosis and personalised treatment.

CONCLUSION: Biomarker-based diagnostics and nanocarrier-based therapeutics are potential solutions to enhance HCC management by improving early diagnosis, treatment outcomes, and prognosis.

PMID:42786871 | DOI:10.2174/0118715206470187260914042941

Biochim Biophys Acta Mol Basis Dis. 2027 Jan;1873(1):168471. doi: 10.1016/j.bbadis.2026.168471. Epub 2026 Sep 24.

ABSTRACT

BACKGROUND: The global burden of metabolic-associated hepatocellular carcinoma (HCC) is increasing, with obesity emerging as a key causal factor. However, the molecular mechanisms linking lipid metabolic dysregulation to HCC progression and therapeutic vulnerability remain unclear.

METHODS: We analyzed Global Burden of Disease 2021 data to assess liver cancer burden attributable to metabolic risks from 1990 to 2021. Mendelian randomization was used to evaluate causal associations between metabolic traits and liver cancer risk. TCGA, GTEx, and GEO datasets were integrated to identify lipid stress-responsive regulators. Clinical relevance was assessed using public datasets and tissue microarray immunohistochemistry. Functional validation was performed in HCC cells and a high-fat diet-fed syngeneic mouse tumor model.

RESULTS: Liver cancer deaths and DALYs attributable to metabolic risks increased markedly from 1990 to 2021. Mendelian randomization showed that obesity-related traits, including BMI, waist circumference, and body fat percentage, were causally associated with liver cancer risk, whereas glycemic traits were not. Bioinformatics screening identified GPAT3 as a lipid metabolism regulator upregulated in HCC, induced by palmitic acid, associated with poor prognosis, and enriched in patients with higher BMI. Tissue microarray analysis confirmed increased GPAT3 protein expression in HCC and its association with higher BMI and GPX4 expression. GPAT3 depletion sensitized HCC cells to palmitic acid-induced ferroptosis, whereas Fer-1 rescue and GPAT3 overexpression supported its protective role. In vivo, FSG67 enhanced sorafenib-associated antitumor effects and increased tumor lipid peroxidation.

CONCLUSIONS: GPAT3 protects HCC cells from lipid stress-induced ferroptosis and represents a potential metabolic vulnerability in obesity-associated HCC.

PMID:42785105 | DOI:10.1016/j.bbadis.2026.168471

Metabolites. 2026 Aug 25;16(9):608. doi: 10.3390/metabo16090608.

ABSTRACT

With the advent of the new definition, fatty liver disorders have been reframed into metabolic dysfunction-associated steatotic liver disease (MASLD), alcohol-related liver disease (ALD), and the mixed phenotype referred to as MetALD (MASLD and increased alcohol intake). This change reflects the real-world clinical practice, where metabolic dysfunction and alcohol frequently coexist and synergize to increase risks of steatohepatitis, fibrosis, and hepatocellular carcinoma (HCC). While conventional non-invasive tests (NITs) remain the backbone of risk stratification, lipidomics and metabolomics can capture biological information on disease mechanisms and may improve early detection and prognosis. Here, we summarize the current evidence on circulating and tissue lipidomic and metabolomic signatures across MASLD, ALD and MetALD, discuss how the new definitions affect clinical risk assessment, and highlight recent studies which partially distinguish molecular fingerprints for mixed etiology disease.

PMID:42783733 | PMC:PMC13609168 | DOI:10.3390/metabo16090608

Cancer Rep (Hoboken). 2026 Sep;9(9):e70685. doi: 10.1002/cnr2.70685.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and remains a major cause of cancer-related mortality worldwide. Its poor clinical outcomes are largely attributed to late-stage diagnosis and the limited accuracy of currently available diagnostic and prognostic biomarkers. Therefore, identifying novel molecular markers with improved sensitivity, specificity, and therapeutic relevance is essential for enhancing early detection and guiding personalized treatment strategies.

AIMS: To identify and prioritize novel candidate HCC biomarkers with diagnostic and prognostic value and potential therapeutic vulnerability using integrated multi-omics, survival, functional dependency, and tumor microenvironment analyses.

METHODS AND RESULTS: We examined the mRNA and protein expression levels of 8 DEGs in HCC tissues in the TCGA and CPTAC datasets using UALCAN, which showed that MSTO1 and LIG1 were overexpressed consistently in HCC relative to normal liver tissues. Moreover, elevated expression levels of these genes were significantly associated with higher tumor grade and advanced stage. Kaplan-Meier plotter survival data confirmed that increased expression of MSTO1 and LIG1 was associated with poorer overall survival. The DepMap CRISPR knockout data confirmed a functional dependency of both genes in HCC cell lines. CBioPortal analyses provided characterization of genomic alterations and enabled enrichment analysis of co-expressed genes, and the TCGA-UALCAN pan-cancer analyses supported the assessment of tissue specificity across tumor types. TIMER3 analyses linked candidate gene expression with immune cell infiltration patterns. Diagnostic performance by ROC analysis showed excellent discrimination for MSTO1 (AUC = 0.987) and good discrimination for LIG1 (AUC = 0.897). Multivariate Cox regression with Benjamini-Hochberg FDR correction across the eight genes supported MSTO1 as a candidate independent prognostic factor after adjustment for tumor stage, grade, etiology, age, and sex (HR = 1.29, p = 0.035), whilst LIG1 showed no independent prognostic value. Promoter methylation of MSTO1 and ADH4, assessed via UALCAN, showed that both genes were significantly differentially methylated in the promoter region of primary HCC tissues compared with normal liver tissues. Our study also confirmed the biological and clinical relevance of established HCC biomarkers: TERT, IRAK1, and ADH4.

CONCLUSION: MSTO1 and LIG1 emerged as candidate diagnostic biomarkers in HCC. Additionally, MSTO1 showed a candidate prognostic association with overall survival that remained significant after adjusting for tumor stage, grade, and etiology, as well as patients' age, but not after further adjustment for AFP status. Functional data also highlighted MSTO1 as a candidate therapeutic dependency. On the other hand, LIG1 showed no independent prognostic association in either multivariate model. Their differential expression and functional essentiality in HCC cell lines highlighted their value for further experimental and independent-cohort validation before potential integration into biomarker development pipelines aimed at improving early detection and targeted therapy in HCC.

PMID:42732946 | DOI:10.1002/cnr2.70685

Int Immunopharmacol. 2026 Sep 13;189:117355. doi: 10.1016/j.intimp.2026.117355. Online ahead of print.

ABSTRACT

Immune evasion in hepatocellular carcinoma (HCC) represents a major biological barrier limiting the efficacy of immunotherapy, yet its molecular basis remains incompletely understood. Increasing evidence indicates that tumor metabolic reprogramming and ferroptosis-related signaling play critical roles in shaping an immunosuppressive tumor microenvironment (TME); however, the specific regulatory factors involved remain unclear. This study aims to systematically elucidate the functional role of S100 calcium-binding protein A10 (S100A10) in immune evasion in HCC, with a particular focus on the molecular mechanisms by which S100A10 regulates CD8⁺ T-cell exhaustion through arachidonic acid (AA) metabolism and ferroptosis, as well as its potential therapeutic implications. To this end, data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort are integrated to analyze the expression patterns of S100A10, its prognostic value, and its association with the immune microenvironment. S100A10 overexpression and knockout models are established in HCCLM3 and MHCC97L cell lines, and S100A10-mediated metabolic pathway reprogramming is characterized using transcriptomic profiling, untargeted metabolomics, and ferroptosis-related functional assays. In parallel, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics are employed to delineate the cell-type specificity and spatial distribution of S100A10. Furthermore, human CD8⁺ T-cell co-culture systems and orthotopic mouse HCC models are used to evaluate the impact of S100A10 on immune function and responsiveness to anti-programmed cell death protein 1 (anti-PD-1) therapy. The results demonstrate that S100A10 is significantly upregulated in HCC and is closely associated with poor prognosis and an immunosuppressive state. Mechanistically, S100A10 activates cytosolic phospholipase A₂-arachidonate 5-lipoxygenase (cPLA₂-5-LOX)-mediated AA oxidative metabolism, leading to the accumulation of lipid peroxidation products and ferroptosis-associated signals, thereby driving CD8⁺ T-cell exhaustion and promoting immune evasion. Significantly, inhibition of S100A10 reshapes the tumor immune microenvironment (TIME) and enhances the therapeutic efficacy of anti-PD-1 treatment. Collectively, these findings identify S100A10 as a critical regulator of metabolic-immune coupling in HCC and provide a theoretical basis for combinatorial strategies targeting metabolism and immunotherapy.

PMID:42732672 | DOI:10.1016/j.intimp.2026.117355

Front Oncol. 2026 Aug 28;16:1907210. doi: 10.3389/fonc.2026.1907210. eCollection 2026.

ABSTRACT

Clonal evolution in hepatocellular carcinoma (HCC), esophageal squamous cell carcinoma (ESCC), and gastric cancer (GC) reflects the interaction of genetic diversification, cell-state plasticity, and tissue-specific selection. Multi-region and single-cell DNA sequencing resolve truncal and subclonal lineages, whereas single-cell and spatial transcriptomics, proteomics, and serial liquid biopsy characterize cellular states, ecological niches, and temporal dynamics. The three cancers differ in dissemination timing, dominant selective pressures, and biomarker maturity: early seeding is best supported in selected HCC cohorts, ESCC is strongly influenced by field cancerization and epithelial-stromal crosstalk, and GC follows subtype- and ecotype-dependent trajectories. We discuss the assumptions and sampling biases that constrain phylogenetic inference, the causal limits of cross-sectional tumor atlases, clonal hematopoiesis, and the incremental value of broad multi-omics over focused assays. Liquid-biopsy detection of minimal residual disease is prognostic, but treatment benefit from marker-guided intervention remains context dependent. Near-term translation requires standardized, decision-linked assays; adaptive therapy and evolutionary steering remain investigational.

PMID:42729528 | PMC:PMC13563159 | DOI:10.3389/fonc.2026.1907210

Cell Commun Signal. 2026 Sep 11;24(1):488. doi: 10.1186/s12964-026-03206-2.

ABSTRACT

BACKGROUND: While over 170 RNA modifications have been identified and implicated in various cancers, their role in hepatocellular carcinoma (HCC) progression is increasingly recognized. Despite this established relevance in tumor biology, the landscape of RNA modifications in the peripheral blood of HCC patients-and their potential diagnostic utility-remains largely unexplored.

METHODS: Peripheral blood samples from patients with HCC, liver cirrhosis (LC), and normal healthy (NH) controls were collected. The abundances of 55 RNA modifications were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to assess their diagnostic potential for HCC, particularly at early stages. Correlations among these modifications and their associations with clinical parameters were analyzed. Simultaneously, differentially expressed genes, including those encoding RNA-modifying enzymes, were screened in peripheral blood. The biological relevance of the identified signatures was subsequently validated using in vitro co-culture and in vivo syngeneic HCC mouse models.

RESULTS: Compared to the combined non-HCC group (NH and LC), the abundances of 11 RNA modifications were significantly altered in both overall and stage I HCC groups, with N²,N²-dimethylguanosine (m^2,2G) emerging as a key component exhibiting the most pronounced dysregulation. A diagnostic model centered on an m^2,2G-based modification panel achieved area under the curves (AUCs) of 0.901 and 0.891 for detecting HCC and stage I HCC, respectively, demonstrating promising diagnostic potential. Notably, the incorporation of two upregulated genes in peripheral blood-IFI27 and CCR2-significantly enhanced the model's performance, yielding improved AUCs of 0.972 and 0.968, respectively. Further analysis revealed distinct correlation patterns among RNA modifications, as well as between RNA modifications and clinical laboratory parameters, exhibiting both shared and HCC-specific features that suggest systemic reprogramming of RNA modification network in HCC. This biological relevance was confirmed by elevated m^2,2G abundances in human lymphocytes co-cultured with HCC cells and blood from a syngeneic HCC mouse model.

CONCLUSIONS: This study systematically profiled peripheral blood RNA modifications and provided preliminary evidence supporting their potential as diagnostic biomarkers for HCC. By integrating key modifications (m^2,2G, m^2,2,7G, m^6,6A) with two mRNA markers (IFI27 and CCR2), we developed a multi-omics signature that demonstrated promising diagnostic performance, particularly for early-stage HCC.

PMID:42732057 | PMC:PMC13570552 | DOI:10.1186/s12964-026-03206-2

Clin Exp Med. 2026 Jul 26;26(1):329. doi: 10.1007/s10238-026-02264-7.

ABSTRACT

KANSL2, a core component of the NSL histone acetyltransferase complex, has been implicated in tumorigenesis. However, its pan-cancer relevance and functional role in liver hepatocellular carcinoma (LIHC) remain unclear. Multi-omics data from TCGA, GEO, and HPA were integrated to systematically evaluate KANSL2 expression, clinical significance, genomic alterations, and immune associations across cancers. Functional enrichment, immune infiltration analyses, and single-cell transcriptomics were performed. In vitro assays were conducted to validate the biological effects of KANSL2 in LIHC cells. KANSL2 is broadly upregulated across cancers and exhibits strong diagnostic performance. Elevated KANSL2 expression correlates with unfavorable prognosis, particularly in LIHC. Mechanistically, KANSL2 and its co-expressed genes are enriched in cell-cycle progression. KANSL2 expression is also closely associated with immune infiltration and immunoregulatory signaling within the tumor microenvironment, with single-cell data indicating preferential expression in proliferative T-cell subsets. Functional experiments demonstrate that KANSL2 silencing suppresses proliferation, migration, and invasion, and induces G2/M phase arrest in LIHC cells. Notably, its effects on apoptosis are limited, suggesting that KANSL2 primarily drives tumor progression through cell-cycle-dependent mechanisms. This study identifies KANSL2 as a key regulator of tumor progression and immune remodeling in LIHC. By promoting malignancy predominantly via cell-cycle control, KANSL2 represents a promising biomarker for diagnosis and prognosis, and a potential therapeutic target.

PMID:42726304 | PMC:PMC13569553 | DOI:10.1007/s10238-026-02264-7