Background/Objectives: Immune evasion remains a critical barrier to effective hepatocellular carcinoma (HCC) therapy. Lactate dehydrogenase A (LDHA) drives lactate accumulation and histone lysine lactylation (Kla), reshaping the immunosuppressive microenvironment, while bromodomain-containing protein 4 (BRD4) sustains B7-H3 transcription via super-enhancer occupancy. Despite their synergistic roles in the lactate-Kla-B7-H3 immunosuppressive axis, no dual-target inhibitor simultaneously engaging both proteins has been reported. This study aimed to discover dual LDHA/BRD4 inhibitors from natural product libraries using an integrated AI-driven computational pipeline. Methods: We established a multi-tier virtual screening cascade comprising Lipinski/QED drug-likeness filtration, DiffDock-based AI docking, QuickVina binding energy validation, PLIP interaction profiling, 200 ns all-atom molecular dynamics simulations, MM-GBSA binding free energy calculations, and density functional theory analysis. Natural product libraries from COCONUT and CMNPD databases (84,730 compounds post-filtration) were screened against both targets. Results: High-throughput DiffDock screening identified 11 dual-target hits, from which CNP0038114.1 and CMNPD16582 emerged as prioritized lead candidates. All four protein-ligand complexes maintained structural stability throughout MD simulations, with MM-GBSA binding free energies ranging from -27.24 to -32.45 kcal/mol, predominantly driven by van der Waals interactions. DFT calculations revealed distinct electronic profiles: CNP0038114.1 exhibited a narrow HOMO-LUMO gap (2.718 eV) favoring charge-transfer reactivity, whereas CMNPD16582 displayed a larger gap (4.822 eV), suggesting superior chemical stability. Conclusions: This computational study furnishes two novel natural product leads for targeting the lactate-Kla-B7-H3 immunosuppressive axis in HCC, establishing a generalizable AI-driven workflow for dual-target inhibitor discovery.

The immunosuppressive tumor microenvironment contributes to the poor prognosis of hepatocellular carcinoma (HCC). The transcriptional profiles of senescence-associated genes (SAGs) in peripheral blood mononuclear cells (PBMCs) are enriched with pathways linked to immune dysfunction and may serve as noninvasive proxies of systemic immune status. This study aimed to identify and validate a PBMC-derived transcriptional signature enriched with SAGs as a noninvasive prognostic tool for HCC. We performed RNA sequencing on PBMCs from an orthotopic HCC mouse model treated with Qizhu anti-cancer prescription (QZACP). Senescence-associated differentially expressed genes (SAG-DEGs) were identified. Core candidates were screened by intersecting QZACP-modulated SAG-DEGs with predicted targets of blood-absorbed components through network pharmacology. The expression, prognostic value, and immune correlations of the core genes were validated using human HCC cohorts and public databases. We identified 587 SAG-DEGs enriched for immune pathways (e.g., interleukin-17 and tumor necrosis factor). Integration of transcriptomic and network pharmacology data identified five core genes. HSPA1A and ENPP2 were consistently upregulated in PBMCs and HCC tumor tissues. High ENPP2 expression was significantly associated with shorter overall survival, immunosuppressive tumor microenvironment features, and remained an independent prognostic factor in multivariate analysis. HSPA1A was consistently upregulated and correlated with immunosuppressive features. This study identified a PBMC-derived senescence-associated transcriptional signature associated with immunosuppression and poor HCC outcomes. ENPP2 emerged as a noninvasive independent prognostic biomarker, whereas HSPA1A was identified as a candidate biomarker associated with immunosuppression.

The co-occurrence of liver cirrhosis (LC) and heart failure (HF) poses considerable clinical challenges, yet the cellular and molecular determinants of this comorbidity remain poorly characterized. To address this, we developed an integrative multi-omics pipeline encompassing GWAS meta-analysis, gsMap-based spatial transcriptomic projection, GeneEnrich functional annotation, single-cell atlas construction, seismicGWAS and ECLIPSER cell-type scoring, eCAVIAR and fastenloc colocalization, hdWGCNA network inference, scTenifoldKnk in silico gene perturbation, and GCTA-COJO fine-mapping. Quality-controlled meta-analysis yielded 12,347,758 and 9,256,862 variant-level associations for LC and HF, respectively. Spatial projection confirmed preferential enrichment of disease signals within embryonic hepatic and cardiac compartments. Pathway analyses disclosed that LC-linked loci were concentrated in lipid metabolic programs, whereas HF-linked loci implicated mitochondrial bioenergetics and lysosomal degradation. At the cellular level, endothelial cells emerged as the dominant HF-associated population. Convergent evidence from five orthogonal algorithms pinpointed CRIM1 as the sole robustly supported shared gene, selectively enriched in HF endothelial cells; virtual perturbation further identified LCP1 and PTPRC as downstream regulatory nodes. Fine-mapping of the chromosome 2 locus harboring rs12476437 revealed multiple statistically independent signals in the vicinity of CRIM1. Collectively, these findings computationally prioritize the endothelial–CRIM1 axis as a previously unappreciated candidate mechanistic bridge between LC and HF requiring experimental validation.

Hepatocellular carcinoma (HCC) progression is shaped by crosstalk between the tumor immune microenvironment (TME) and metabolic reprogramming. This study aims to characterize a macrophage-lactylation molecular axis in HCC and to develop a quantitative prognostic stratification model. Using the TCGA-LIHC cohort, differentially expressed genes were intersected with Paeoniflorin (PF)-related targets, HCC disease targets, and macrophage-/lactylation-related genes to identify candidate genes. Prognostic genes were selected through Cox and LASSO-Cox analyses to construct a risk score model, followed by survival analysis and ROC curve evaluation. Immune infiltration was assessed using ESTIMATE and ssGSEA algorithms, and PF-protein binding interactions were explored via molecular docking and molecular dynamics simulations. Intersection analysis identified eight key genes, and prognostic model genes (HNRNPU, LDHA, and NPM1) were used to construct the prognostic model. High-risk patients exhibited significantly poorer overall survival (p < 0.001), with 1- and 3-year AUC values ranging from 0.70 to 0.90. HNRNPU was positively correlated with activated CD4 T cells (r = 0.385) and negatively correlated with eosinophils (r = -0.498). Molecular docking indicated favorable binding of PF to the model proteins, with the highest predicted affinity observed for LDHA (Vina score = -8.9 kcal/mol), and molecular dynamics simulations suggested the formation of a stable LDHA-PF complex during the later stage of the simulation. We propose a prognostic risk model for HCC constructed using three prognostic model genes and provide computational evidence linking PF to key molecular nodes such as LDHA. External cohort validation and experimental studies are warranted.

BackgroundMetabolic Dysfunction-associated Steatotic Liver Disease (MASLD) frequently coexists with Type 2 Diabetes Mellitus (T2DM) and Primary Hypothyroidism (PH); nevertheless, the relationship between thyroid hormone sensitivity and FIB-4-defined fibrosis risk across these metabolic diseases is yet unknown.MethodsIn 102 patients with MASLD, MASLD+T2DM, and MASLD+T2DM+treated PH (34 per group), this exploratory cross-sectional study examined the association between the Thyroid Feedback Quantile Index (TFQI) and the Fibrosis-4 Index (FIB-4). The cumulative distribution functions of TSH and FT4 were used to calculate TFQI. A surrogate indicator of the risk of fibrosis was FIB-4. G*Power 3.1.9.7 was used for post-hoc power analysis after multivariable regression and correlation analyses were completed.ResultsIn the MASLD-alone group, TFQI and FIB-4 had a significant inverse correlation in unadjusted analysis (r = −0.384, P = 0.025). Nevertheless, after controlling for age, sex, and BMI, this link was diminished and no longer significant (β = −0.195, P = 0.073). The most powerful independent predictor of FIB-4 was age (β = 0.704, P < 0.001). Age significantly confounded the association, according to sensitivity analyses such as age-adjusted partial correlation, FIB-4 component analysis, and FIB-4 category analysis. In the other two groups, no noteworthy correlations were found.ConclusionsAge played a major role in explaining the inverse correlation between TFQI and FIB-4 in patients with MASLD alone in this exploratory study. These results should be considered hypothesis-generating and should be validated in bigger prospective trials with direct measurements of fibrosis. Future research may benefit from the heterogeneous associations across metabolic backgrounds.

Primary sclerosing cholangitis (PSC) and ulcerative colitis (UC) exhibit a striking clinical comorbidity, with 60-80% of PSC patients concurrently harboring UC, yet the shared immunogenetic mechanisms remain poorly understood. Here, we constructed a multi-omics integrative framework to systematically dissect the cellular and molecular basis of this comorbidity. GWAS meta-analyses were performed for each disease, followed by tissue-level enrichment assessment using QTLEnrich, MAGMA, and gsMap spatial mapping. Single-cell transcriptomic atlases were constructed, and cell-type prioritization was conducted using four complementary methods. Core genes were identified through cross-validation of five algorithms, with subsequent genomic fine-mapping via FUMA and GCTA-COJO. Tissue-level analyses consistently identified the intestine and immune-related tissues as commonly affected. Multi-dimensional evidence integration prioritized natural killer (NK) cells as the core effector cell type for both diseases, supported principally by CELLECT (Cell-type Expression-specific Integration for Complex Traits) heritability enrichment and single-cell differential analysis. Convergence of five gene-level algorithms pinpointed STAT3 as the sole high-confidence comorbidity gene, broadly expressed across immune cell populations and exhibiting tissue-differential alternative splicing. Colocalization identified a high-risk variant (rs3736161) within the STAT3 locus, with conditional analysis revealing 35 additional independent signals. These findings identify the NK cell-STAT3 axis as a central immunogenetic hub connecting PSC and UC, offering potential therapeutic targets for comorbidity management.

Drug resistance in hepatocellular carcinoma (HCC) presents a substantial therapeutic challenge. Ferroptosis has emerged as a promising therapeutic strategy, yet the mechanisms underlying resistance are not fully elucidated. Here, we highlight the tumor suppressor FAT4 as a crucial regulator of ferroptosis sensitivity in HCC. We examined the role of FAT4 in ferroptosis in HCC using a combination of bioinformatics analysis, experiments on tissue samples from patients with HCC, and a subcutaneous xenograft tumor model in nude mice. FAT4 expression was significantly downregulated in HCC tissues, and this downregulation correlated with poor patient survival. Functionally, FAT4 loss promoted tumor growth and resistance to ferroptosis inducers (RSL3 and sorafenib), evidenced by reduced lipid peroxidation and increased levels of GPX4 and SLC7A11. Mechanistically, FAT4 deficiency was associated with activation of the PI3K/AKT signaling pathway. Notably, pharmacological inhibition of PI3K/AKT restored ferroptosis sensitivity and resensitized FAT4-deficient HCC cells to sorafenib. FAT4 may enhance ferroptosis sensitivity in HCC by suppressing GPX4 and SLC7A11 expression, potentially by inhibiting PI3K/AKT signaling. Thus, this study presents FAT4 as a biomarker associated with tumor progression and a potential determinant for overcoming ferroptosis resistance in HCC.

Background: Hepatocellular carcinoma (HCC) remains a leading cause of cancer mortality. The c-Met and VEGFR2 pathways synergistically drive HCC progression. Marine natural products offer chemically diverse drug reservoirs; however, conventional activity-guided isolation faces labor intensity, low throughput, and frequent compound rediscovery, limiting marine drug development. Objective: To pioneer an artificial intelligence-driven marine drug discovery workflow integrating deep learning virtual screening for identifying dual c-Met/VEGFR2 promising in silico candidate from marine natural product repositories. Methods: UniSite predicted binding pockets in c-Met (PDB: 4R1V) and VEGFR2 (PDB: 2XIR). Drug-likeness filtering of 695,000 compounds from COCONUT and CMNPD databases yielded 84,730 candidates. DiffDock-based screening identified dual-target binders, validated through 200 ns molecular dynamics simulations, MM-GBSA calculations, and DFT analyses. Results: The marine phthalide CMNPD30506 [(S)-3-ethyl-5,6-dihydroxyphthalide] emerged as the lead candidate, engaging VEGFR2 via four hydrophobic contacts and one π-cation interaction with LYS868, while binding c-Met through four hydrophobic interactions, two hydrogen bonds, and π-π stacking. Molecular dynamics demonstrated stable RMSD profiles and dynamic hydrogen bond enrichment. MM-GBSA revealed binding free energies of −14.79 and −13.28 kcal/mol for VEGFR2 and c-Met, respectively, driven by van der Waals forces. DFT calculations indicated a HOMO-LUMO gap of 2.410 eV. Conclusions: This AI-augmented workflow successfully identified CMNPD30506 as a promising dual c-Met/VEGFR2 HCC therapeutic from marine libraries, overcoming traditional discovery bottlenecks through integrated deep learning and physics-based simulations, exemplifying AI’s potential in marine pharmacological research.

Apoptosis signal-regulating kinase 1 (ASK1) represents a critical therapeutic target for metabolic dysfunction-associated steatohepatitis (MASH). Natural products, owing to their unique chemical diversity, constitute a rich reservoir for discovering novel ASK1 inhibitors. The emergence of artificial intelligence-assisted drug discovery (AIDD) has opened new avenues for exploring small-molecule inhibitors. Through virtual screening, molecular docking, interaction profiling, molecular dynamics simulations, and MM-GBSA binding free energy calculations, we systematically evaluated the binding mode, stability, and key residue contributions of the CMNPD10921-ASK1 complex. CMNPD10921 stably occupied the ASK1 active pocket, forming hydrophobic interactions and hydrogen bonds with multiple key amino acid residues. MM-GBSA analysis yielded a total computed binding free energy of -31.15 kcal/mol, suggesting a computationally favorable interaction, with van der Waals forces serving as the dominant energetic driver of complex stabilization. Residue energy decomposition further identified ILE324, THR288, and THR639 as major contributors to ligand binding. Integrating deep learning, molecular simulation, and quantum chemical calculations, this study successfully identified CMNPD10921 from a vast natural product library as a putative lead compound candidate targeting the ASK1 central regulatory region, offering a novel candidate molecule for anti-MASH drug development.

BACKGROUND AND AIMS:Metabolic dysfunction-associated steatotic liver disease (MASLD) is a progressive liver disease that ranges from simple steatosis to inflammation, fibrosis and cirrhosis. To address the unmet need for new MASLD biomarkers, we aimed to identify candidate biomarkers using publicly available RNA sequencing (RNA-seq) and proteomics data. METHODS:An approach involving unsupervised gene clustering was performed using homogeneously processed and integrated RNA-seq data of 625 liver specimens to screen for MASLD biomarkers, in combination with public proteomics data from healthy controls and MASLD patients. Additionally, we validated the results in the MASLD and healthy cohorts using enzyme-linked immunosorbent assay (ELISA) of plasma and immunohistochemical staining (IHC) of liver samples. RESULTS:We generated a database (https://dreamapp.biomed.au.dk/NAFLD/) for exploring gene expression changes along MASLD progression to facilitate the identification of genes and pathways involved in the disease's progression. Through cross-analysis of the gene and protein clusters, we identified 38 genes as potential biomarkers for MASLD severity. Up-regulation of Quiescin sulfhydryl oxidase 1 (QSOX1) and down-regulation of Interleukin-1 receptor accessory protein (IL1RAP) were associated with increasing MASLD severity in RNA-seq and proteomics data. Particularly, the QSOX1/IL1RAP ratio in plasma demonstrated effectiveness in diagnosing MASLD, with an area under the receiver operating characteristic (AUROC) of up to 0.95 as quantified by proteomics profiling and an AUROC of 0.82 with ELISA. CONCLUSIONS:We discovered a significant association between the levels of QSOX1 and IL1RAP and MASLD severity. Furthermore, the QSOX1/IL1RAP ratio shows promise as a non-invasive biomarker for diagnosing MASLD and assessing its severity.

Background/Objective: Histone deacetylase inhibitors (HDACi) represent a novel class of antineoplastic agents, yet their comprehensive safety profile warrants further investigation. This study aimed to examine the safety of HDACi using the FDA Adverse Event Reporting System (FAERS) and to explore causal relationships through Mendelian randomization (MR) analysis of drug targets. Methods: Adverse drug event (ADE) reports for Vorinostat, Romidepsin, Belinostat, and Panobinostat submitted to the FAERS from their respective market entry dates through 31 December 2023, were analyzed using disproportionality analyses with four algorithms, supplemented by time-to-onset analysis, logistic regression, and MR analysis. Results: A total of 1360, 1065, 225, and 1234 ADE reports were documented for Vorinostat, Romidepsin, Belinostat, and Panobinostat, respectively. Eight preferred terms, including decreased white blood cell, platelet, and neutrophil counts, hypophosphatemia, hypocalcemia, QT prolongation, increased aspartate aminotransferase, and anemia, exhibited positive signals across all four HDACi. A temporal decline in the risk of most HDACi-related ADEs was observed, and age, gender, and weight were identified as potential confounding factors for important medical events. Notably, MR analysis revealed a positive correlation between HDAC5 expression and serum phosphate levels. Conclusions: This pharmacovigilance study provides hypothesis-generating evidence that hypophosphatemia may represent a potential class effect of HDACi.

Thyroid hormones profoundly modulate hepatic fatty acid and cholesterol synthesis and turnover. Although nonalcoholic fatty liver disease (NAFLD) shows epidemiological links to hypothyroidism, the genetic substrates of this relationship remain unresolved. Integrating large-scale genome-wide association studies with single-cell transcriptomics, spatial transcriptomics, and single-cell chromatin accessibility via state-of-the-art computational approaches, we interrogated the association between NAFLD and hypothyroidism across organ systems, cellular expression landscapes, and molecular-genetic strata. We uncovered pronounced spatial specificity in genetic risk within the liver, prioritized hepatocytes as the principal shared cell type affected, and, leveraging spatial transcriptomics, advanced a dynamic spatiotemporal two-hit model. We further nominated MAGI3, RRNAD1, and PRCC as high-confidence candidate genes and pinpointed a key risk locus, rs926103. These findings deliver a dynamic, testable framework for the full pathophysiological continuum linking NAFLD and hypothyroidism and yield new targets and leads for precision intervention.

Acute liver injury (ALI) is defined as rapidly progressing hepatic dysfunction or hepatocellular necrosis caused by drugs or chemicals, viral infection, or autoimmune diseases, among which drug-induced liver injury (DILI) is the major etiology. Numerous monomeric compounds have shown hepatoprotective effects in animal models; however, their therapeutic specificity is limited, and their clinical applicability remains restricted. This study moved beyond the single-compound paradigm and systematically identified key candidate hubs of ALI by integrating the shared efficacy and mechanisms of hepatoprotective monomers. Monomeric compounds with preclinically confirmed hepatoprotective effects were obtained from PubMed. Network pharmacology was used to identify overlapping targets between monomers and ALI. Transcriptomic datasets were analyzed to explore the differential expression of candidate targets. In vivo validation was conducted in C57BL/6 mice using APAP- and LPS/D-GalN-induced ALI models. Molecular docking and molecular dynamics (MD) simulations were conducted to predict compound-target interactions. A total of 186 active monomers and four hub genes (JUN, STAT3, ESR1, and CTNNB1) were identified. Across multiple GEO datasets, JUN was the only consistently upregulated gene. In vivo models confirmed robust activation of phosphorylated c-Jun. Docking and MD analysis indicated stable binding of Schisandrol A, Withaferin A, and Schizandrin to JUN. This integrated strategy revealed JUN as a key candidate molecular hub in ALI. This study not only provides new ideas for exploring the common mechanism of ALI but also offers clues for the development of JUN-targeted hepatoprotective agents.

Neutrophils are an important component of the tumor microenvironment, with the majority of previous research concentrating on their anti-tumor role. Recent research indicates that elevated neutrophil-lymphocyte ratios are indicative of worse cancer prognoses. In addition, it revealed the functional transition of neutrophils are related with metabolic regulation within the tumor microenvironment.The metabolic-immune axis has emerged as a master regulator of tumor progression, yet the role of neutrophil-centric crosstalk in this paradigm remains enigmatic. Therefore, this study highlights the innovative role of neutrophils in tumorigenesis, particularly the regulatory effect on tumor niche transformation after glucose metabolism reprogramming. Simultaneously, we discussed how the tumor microenvironment alters the glucose metabolism of neutrophils, influences their life cycle, and modifies their localization and activity inside the tumor niche. In addition, targeted neutrophils, including new therapies in clinical trials, offer new possibilities for cancer treatment. This work establishes neutrophil glycolysis as a linchpin of the metabolic-immune ecosystem and provides a combinatorial therapeutic blueprint to dismantle pro-tumorigenic niches.

BackgroundIn recent years, the incidence of alcoholic liver disease (ALD) has rapidly increased worldwide, becoming a significant health issue. Silibinin capsules have shown potential in treating ALD, but clinical evidence is still insufficient. This meta-analysis aimed to evaluate the efficacy and safety of Silibinin capsules in the treatment of ALD.MethodsThe study was registered with PROSPERO (CRD42024509676). Randomized controlled trials (RCTs) were included from six databases, covering the period from database inception to 30 December 2023. Primary outcomes included liver function indicators such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), total bilirubin (TBIL), lipid indicators including triglycerides (TG) and total cholesterol (TC), coagulation indicators including prothrombin time (PT), liver fibrosis indicator (PC-III), and Effective Rate. Analysis was performed using Review Manager 5.4.1 and STATA 14.0.ResultsIn 15 RCTs involving 1,221 patients, compared to the non-Silibinin group, Silibinin capsules showed significant efficacy in terms of liver function, lipid levels, and effective rate in patients with ALD. Detailed parameters were as follows: ALT [SMD = −1.16, 95% CI (−1.84, −0.47)], AST [SMD = −1.56, 95% CI (−2.18, −0.95)], GGT [SMD = −1.48, 95% CI (−2.09, −0.87)], TBIL [SMD = −1.14, 95% CI (−2.16, −0.13)], TG [SMD = −1.29, 95% CI (−1.93, −0.66)], TC [SMD = −1.11, 95% CI (−1.61, −0.61)], PT [SMD = −0.01, 95% CI (−0.29, 0.26)], PC-III [SMD = −1.94, 95% CI (−3.04, −0.84)], and Effective Rate [OR = 3.60, 95% CI (2.28, 5.70)]. Importantly, Silibinin capsules exhibited a favorable safety profile, with only mild gastrointestinal reactions and reports of insomnia as adverse events.ConclusionThis review reveals the clinical efficacy and safety of Silibinin capsules in the treatment of ALD, and confirms that the drug is an effective adjuvant therapy to alleviate ALD. At present, the mechanism of action of this drug for ALD is still unclear, and we expect more experimental studies to prove the clinical value of Silibinin capsules.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=509676.

ETHNOPHARMACOLOGICAL RELEVANCE:Mitophagy regulates cellular homeostasis and liver inflammation; however, it is inhibited in acute-on-chronic liver failure (ACLF), which drives disease progression. The JianPi LiShi YangGan formula (YGF) has the potential to improve inflammatory responses and reduce mortality in patients with ACLF. However, the precise mechanisms underlying these effects remain unknown. AIM OF THE STUDY:We investigated the role of S100A9/RAGE signaling in mitophagy and the protective effects of traditional Chinese medicinal compounds on ACLF. MATERIALS AND METHODS:An ACLF mouse model was established using carbon tetrachloride, lipopolysaccharide, and d-galactose. Hematoxylin and eosin staining and enzyme-linked immunosorbent assay were employed to evaluate the hepatoprotective effect of YGF in ACLF mice. Mitochondrial damage was assessed using transmission electron microscopy. Protein levels of mitophagy-related indicators were assessed through immunohistochemistry and western blotting, and immunofluorescence staining was performed to observe Lamp2 and COX-IV co-localization. RESULTS:The hepatocytes of ACLF mice contained damaged mitochondria, decreased mitophagy-related protein (Pink1, Parkin, and LC3B) expression and activated S100A9/RAGE signaling. Inhibiting S100A9 or RAGE improved liver injury in ACLF mice and enhanced Lamp2-COX-IV co-localization. In alpha mouse liver 12 (AML12) cells overexpressing RAGE, recombinant S100A9 protein inhibited mitophagy induced by 3-chlorocarbonyl benzoyl chloride. YGF reduced mitochondrial damage, increased Pink1, Parkin, and LC3B levels, and enhanced mitophagy while inhibiting S100A9/RAGE activation in the hepatocytes of ACLF mice. CONCLUSIONS:This study found that S100A9/RAGE pathway activation impairs mitophagy, and YGF alleviates liver injury by downregulating S100A9 and RAGE signaling, which may be a novel therapeutic strategy for ACLF.

Early detection of hepatocellular carcinoma (HCC) can greatly improve the survival rate of patients. Plasma cfDNA methylation has been shown to have the potential to be a non-invasive method for diagnosing HCC. However, the identified HCC plasma cfDNA methylation sites were less sensitive to early HCC diagnosis. Therefore, we aimed to develop a highly sensitive marker panel based on cell-free DNA (cfDNA) methylation for the detection of HCC. The study included 374 participants, including 102 healthy individuals, 51 HBV patients, 50 cirrhosis patients, and 171 HCC patients (56 at stage 0 or A according to BCLC staging). Two cfDNA methylation sequencing assays (whole genome bisulfite sequencing (WGBS) and targeted bisulfite sequencing (TBS)) were used along with machine learning modeling to detect HBV-related HCC based on differentially methylated regions (DMR) among the four participant groups. TBS analysis achieved an overall sensitivity of 96.67

Ethnopharmacological relevance: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide, largely due to the limitations of available therapeutic strategies. The traditional Chinese medicine Qizhu Anticancer Prescription (QZACP) can improve the quality of life and prolong the survival time of patients with HCC. However, the precise mechanisms underlying the anti-cancer properties of QZACP remain unclear. Purpose: This study examined the anti-hepatocarcinogenic properties of QZACP, with a specific focus on its influence on the p21-activated secretory phenotype (PASP)-mediated immune surveillance, to elucidate the underlying molecular pathways involved in HCC. Materials and methods: Cell proliferation was measured using the Cell Counting Kit -8, 5-ethynyl-2 ' -deoxyuridine, and clonogenic assays. The cell cycle was evaluated using flow cytometry, and senescence was identified by staining with senescence-associated beta-galactosidase (SA- beta-gal). A primary liver cancer model produced by diethylnitrosamine was established in C57 BL/6 mice to assess the tumor-inhibitory effect of QZACP. The liver 's pathological characteristics were examined using hematoxylin and eosin staining. PASP screening was performed using GeneCards, DisGeNet, Online Mendelian Inheritance in Man, and The Cancer Genome Atlas databases. Western blot analysis, enzyme-linked immunosorbent assay (ELISA), immunofluorescence staining, and Transwell migration assays were performed. Results: Serum containing QZACP enhanced p21 expression, triggered cell cycle arrest, accelerated cell senescence, and suppressed cell proliferation in Huh7 and MHCC-97H liver cancer cells. QZACP reduced the quantity and dimensions of liver tumor nodules and enhanced p21 protein expression, SA- beta-Gal staining in tumor lesions, and cytotoxic CD8 + T cell infiltration. Bioinformatic analyses indicated that PASP factors, including hepatocyte growth factor, decorin (DCN), dermatopontin, C -X -C motif chemokine ligand 14 (CXCL14), and Wnt family member 2 (WNT2), play an important role in the development of HCC. In addition, these factors are associated with the presence of natural killer cells and CD8 + T cells within tumors. Western blotting and ELISA confirmed that QZACP increased DCN, CXCL14, and WNT2 levels in tumor tissues and peripheral blood. Conclusions: QZACP 's suppression of HCC progression may involve cell senescence mediated via p21 upregulation, DCN, CXCL14, and WNT2 secretion, and reversal of the immunosuppressive microenvironment. This study provides insights that can be used in the development of new treatment strategies for HCC.