Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths globally, and with current treatments proving less effective, there is an urgent need for specific biomarkers and therapeutic targets. Lipid metabolism reprogramming is a crucial cancer hallmark, yet comprehensive studies on lipid metabolic fluxes remain limited. In this study, combined with non-targeted lipidomics, a comprehensive workflow for stable isotope tracing lipidomics was established to analyze changes in lipid levels of HepG2 cells and LO2 cells from both static and dynamic perspectives. Through the screening of differential metabolites and the enrichment analysis of lipid metabolic pathways, the most significant differential metabolic pathways were found. Finally, the TCGA and CPTAC databases were utilized to analyze the gene expression levels and protein expression levels of pivotal enzymes in the differential metabolic pathways, and these findings were verified by Western Blotting experiments. The results demonstrated that the lipid metabolism of HCC was disordered, and the metabolic pathways that caused lipid changes in HCC were mainly glycerophospholipid metabolism and sphingolipid signaling pathway. LPCAT1 and SMPD1 played a crucial role in the reprogramming of lipid metabolism in HCC. The established "static-dynamic" lipidomics workflow improves the coverage and accuracy of dynamic lipid monitoring, elucidating the roles of lipids in physiological and pathological processes, providing tools for studying lipid function, and offering new perspectives on the pathogenesis of HCC as well as the identification of drug targets.

Hepatocellular carcinoma (HCC) is a highly aggressive malignancy with limited treatment options in advanced stages. While c-Met is a promising therapeutic target in HCC, identifying patients who will benefit from c-Met inhibitors remains a significant challenge. This study aimed to investigate the role of HHLA2, a B7 family member, in HCC and its potential as a liquid biopsy marker for c-Met inhibitor therapy.

HHLA2 expression was analyzed in clinical HCC samples and public databases. In vitro studies using HCC cell lines assessed HHLA2's impact on proliferation, migration, invasion, and angiogenesis. In vivo studies using mouse models (orthotopic xenografts and hydrodynamic tail vein injection) evaluated HHLA2's role in tumor growth and metastasis. Mass spectrometry, co-immunoprecipitation, split-luciferase, and ELISA assays were used to investigate HHLA2-c-Met interactions. Patient-derived organoids (PDOs) were used to assess drug response. Statistical analyses included Student's t-tests, ANOVA, and Cox regression.

HHLA2 was found to be upregulated in HCC and associated with advanced disease, aggressive clinicopathological features, and poor prognosis. HHLA2 interacted with and constitutively activated c-Met, leading to increased expression of MMP9 and VEGFA, enhancing HCC cell proliferation, invasion, and angiogenesis. HHLA2 also suppressed hepatic natural killer cell infiltration in vivo. Inhibition of c-Met with PHA665752 effectively reversed HHLA2-mediated tumor-promoting effects in vitro and in vivo. HHLA2 expression in HCC tissues correlated with c-Met phosphorylation, and HHLA2 could be detected in the serum of patients with high tumor HHLA2 levels. PDOs with high HHLA2 expression exhibited increased sensitivity to c-Met inhibition.

HHLA2 acts as an oncogene in HCC by activating c-Met, promoting tumor progression and metastasis. HHLA2 expression correlates with c-Met activation and predicts poor prognosis in HCC patients. Importantly, HHLA2 can serve as a stratification marker for c-Met inhibitor therapy, potentially enabling a personalized approach to improve therapeutic outcomes in this challenging disease.

Hepatocellular carcinoma (HCC) is a common malignancy associated with high morbidity and mortality rates worldwide. To improve the prognosis of HCC, early diagnosis is crucial. However, to date, little is known about the role of natural killer cell-related genes (NKCRGs) in predicting the prognosis of hepatocellular carcinoma patients. In this study, we identified 24 differentially expressed NKCRGs in HCC specimens from the TCGA dataset, including 22 upregulated genes and 2 downregulated genes. Functional enrichment analysis revealed that these genes were mainly involved in immune response pathways and various cancer-related pathways. Univariate analysis identified 21 prognostic NKCRGs, with eight genes (PAK1, MAP2K2, MAPK3, PLCG1, SHC1, HRAS, NRAS, and MICB) confirmed to be involved in HCC prognosis through Venn diagram analysis. A prognostic model was developed using LASSO-Cox regression, incorporating four genes (MAP2K2, SHC1, HRAS, and NRAS). The model's risk score was significantly associated with overall survival (OS) in both the TCGA and ICGC cohorts. Patients with high-risk scores had poorer OS, as demonstrated by Kaplan-Meier curves and ROC analyses. The risk score was not significantly correlated with gender or age but was higher in patients with advanced tumor grades and stages. Immune status analysis using ssGSEA showed higher enrichment scores for various immune cells and pathways in the high-risk group. Additionally, the risk score was positively correlated with the immune score, indicating its potential role in tumor microenvironment modulation. Expression analysis revealed that HRAS, SHC1, MAP2K2, and NRAS were upregulated in HCC tissues, with higher expressions of HRAS, MAP2K2, and NRAS associated with shorter OS. Knockdown experiments confirmed that silencing NRAS suppressed the proliferation of HCC cells, highlighting its potential as a therapeutic target. Overall, our findings suggest that the identified NKCRGs, particularly NRAS, play crucial roles in HCC progression and could serve as valuable prognostic markers and therapeutic targets.

Phosphoglycerate mutase 2 (PGAM2) is a crucial glycolytic enzyme. Recently, we have found that both the protein and acetylation levels of PGAM2 are down-regulated in hepatocellular carcinoma (HCC) tissues. However, the functional significance of PGAM2 in HCC progression remains poorly characterized. In this study, we demonstrated that PGAM2 functioned as a tumor suppressor in HCC progression, and knockdown of PGAM2 promoted proliferation of HCC cells and tumor growth both in vitro and in vivo. Moreover, we identified lysine 100 (K100) in PGAM2 as the predominant deacetylation site of sirtuin-2 (SIRT2), and that deacetylation of K100 destabilized PGAM2 by promoting its ubiquitination and degradation. Importantly, we discovered that PGAM2 suppressed aerobic glycolysis through an enzymatic activity-independent mechanism in HCC cells. Mechanistic investigations revealed that PGAM2 knockdown upregulated lactate dehydrogenase A (LDHA) expression via activation of the signal transducer and activator of transcription 3 (STAT3). Furthermore, we found that knockdown of PGAM2 sensitized HCC cells to sorafenib treatment. In conclusion, these findings elucidate the tumor-suppressive role of PGAM2 in HCC progression and its post-translational regulation through SIRT2-mediated deacetylation, which provide novel biomarkers and therapeutic targets for HCC treatment.

Although numerous molecular classifications are available to predict the prognosis of patients with hepatocellular carcinoma (HCC), they are still unsatisfactory. Forkhead box O3 (FOXO3) has been widely reported as a transcription factor involved in human cancers, but its role in HCC remains controversial. The present study aimed to explore the role of FOXO3 in HCC, as well as to identify biomarkers and construct prognostic models based on FOXO3. FOXO3 was highly expressed in HCC and was closely associated with poor prognosis in The Cancer Genome Atlas (the training set) and International Cancer Genome Consortium (the validation set). Subsequently, a co-expression network indicated that the red modules were closely related to FOXO3. Five key FOXO3-related genes [DEAD-box helicase 55 (DDX55), RAB10, member RAS oncogene family (RAB10), RAB7A, TATA-box binding protein associated factor, RNA polymerase I subunit B (TAF1B) and TAF3] were obtained using Cox-least absolute shrinkage and selection operator analyses. The 5-gene signature successfully predicted the prognosis of patients with HCC in both the training and validation sets. Enrichment analysis suggested marked differences in AKT and cell cycle-related (E2F targets and G2/M checkpoints) pathways between HCC subgroups. Furthermore, the tumor microenvironment analysis suggested that the difference in the distribution of M2 macrophages among various subgroups may contribute to the poor prognosis using the CIBERSORTx framework. Furthermore, the mRNA and protein expressions of DDX55, RAB10, RAB7A, TAF1B and TAF3 were found to be higher in HCC tissues compared with paracancerous tissues using RT-qPCR and western blotting. Additionally, knockdown of RAB10, RAB7A and TAF3 inhibited proliferation of Huh7 cells, assessed by a Cell Counting Kit-8 assay. In conclusion, a novel FOXO3-related model was constructed and revealed that RAB10, RAB7A and TAF3 may be potential molecular targets or biomarkers for HCC.

Bortezomib, as a proteasome inhibitor, is used in clinical trials related to solid cancers. However, its use is not always associated with a good response to treatment. Taking into account the above, we decided to analyze the effect of the time-dependency (24 vs. 48 h) and the dose-dependency of bortezomib (2, 4, 8 and 16 nM) on apoptosis and activities of antioxidant enzymes such as catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR), glutathione peroxidase (GPx) and glutathione transferase (GST), as well as concentrations of reduced glutathione (GSH) and malondialdehyde (MDA) in hepatoblastoma cell line (HepG2) cells. We have shown that increasing concentrations of bortezomib caused (I) a gradual decrease in the levels of GSH; (II) changes in MDA concentrations and antioxidant enzymes activities; (III) increase in apoptosis levels in HepG2 cells. We did not find significant association between antioxidant parameters and number of apoptotic cells. Our study showed that the analyzed parameters (such as: CAT, SOD, GR, GPx, GST, GSH, MDA) changed after bortezomib treatment. It is important to search for new anti-cancer therapies based on next-generation proteasome inhibitors. It is possible that the use of proteins associated with oxidative stress will help enhance the action of these inhibitors and will provide a better treatment effect.

Accurate and early detection of hepatocellular carcinoma (HCC) is critical for improving patient outcomes. Current biomarkers like AFP have limited sensitivity, necessitating novel diagnostic markers. A novel semi-nested RT-PCR assay was developed to quantify circulating Ceruloplasmin (CP) mRNA in peripheral blood. This method co-amplifies CP mRNA and an internal control (IC) gene, followed by DNA melting analysis to distinguish and quantify CP mRNA. CP mRNA levels were significantly higher in the HCC group (median: 3.37) compared to both the CLD group (0.24, p = 0.0066) and the HD group (0.17, p < 0.0001). Further analysis using ROC curves highlighted the diagnostic performance of the assay. For differentiating HCC from CLD, the area under the ROC curve (AUC) was 0.704, with 50.98% sensitivity and 95.24% specificity. In comparison to HD, the AUC was 0.812, with 74.51% sensitivity and 80.65% specificity. Against the combined control group (CLD and HD), the AUC was 0.768, with 50.98% sensitivity and 96.15% specificity. Additionally, in 59.1% of HCC cases with AFP levels below 20 ng/mL, CP mRNA levels were elevated, indicating that CP mRNA could help detect a substantial proportion of AFP-negative HCC cases. This study, the first comprehensive clinical investigation of cell-free CP mRNA for HCC diagnosis, demonstrates its potential as a sensitive and specific non-invasive biomarker. Further validation in larger cohorts is needed to confirm its clinical utility.

Cynaropicrin, a sesquiterpene lactone, has diverse pharmacological activities. However, its anticancer activity against hepatocellular carcinoma (HCC) has not been fully elucidated. Here, we investigated the cytotoxic effects of cynaropicrin and examined its mechanism of action in human HCC cells. The results demonstrated that cynaropicrin significantly induced cytotoxicity and autophagy in HCC cells, but not in immortalized non-cancerous hepatocytes, which was related to the generation of mitochondrial reactive oxygen species (mtROS) and induction of mitochondrial membrane potential loss. Under cynaropicrin treatment, the expression of microtubule-associated protein light chain 3, which is involved in the elongation of the phagophore membrane, was upregulated, whereas the expression of Beclin-1 and p62, which are essential for the formation of autophagosomes, was downregulated. In addition, the expression of mitophagy regulators PTEN-induced kinase 1 (PINK1) and Parkin in the mitochondria increased, suggesting the induction of autophagic flux in the mitochondria. However, N-acetyl-l-cysteine, a ROS scavenger, counteracted cynaropicrin-induced effects. Moreover, cynaropicrin increased the phosphorylation of p38 mitogen-activated protein kinase (MAPK), and the p38 MAPK inhibitor, SB203580, specifically attenuated cynaropicrin-induced cytotoxicity and mtROS production. Importantly, SB203580 reversed cynaropicrin-induced expression of PINK1 and Parkin in the mitochondria. Collectively, our findings demonstrate that cynaropicrin exerts cytotoxic effects against HCC cells by inducing mitochondrial autophagy through the activation of the p38 MAPK-ROS pathway, indicating that cynaropicrin could be a potential therapeutic agent for liver cancer treatment.

Accumulating evidence indicates that elevated polyamine levels are closely linked to tumor initiation and progression. However, the precise role of polyamine metabolism in hepatocellular carcinoma (HCC) remains poorly understood.

We conducted differential expression analysis on bulk RNA sequencing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to identify 65 polyamine metabolism-related genes. By employing unsupervised consensus clustering, AddModuleScore, single-sample gene set enrichment analysis (ssGSEA), and weighted gene co-expression network analysis (WGCNA), we identified polyamine metabolism-related genes at both the bulk RNA-seq and single-cell RNA-seq (scRNA-seq) levels. Utilizing 101 machine learning algorithms, we constructed a polyamine metabolism-related signature (PMRS) and validated its predictive power across training, testing, and external validation cohorts. Additionally, we developed a prognostic nomogram model by integrating PMRS with clinical variables. To explore immune treatment sensitivity, we assessed tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) score, mutation frequency, and immune checkpoint genes expression. Immune cell infiltration was analyzed using the CIBERSORT algorithm. Finally, RT-qPCR experiments were conducted to validate the expression of key genes.

Using 101 machine learning algorithms, we established a polyamine metabolism-related signature comprising 9 genes, which exhibited strong prognostic value for HCC patients. Further analysis revealed significant differences in clinical features, biological functions, mutation profiles, and immune cell infiltration between high-risk and low-risk groups. Notably, TIDE analysis and immune phenotype scoring (IPS) demonstrated distinct immune treatment sensitivities between the two risk groups. RT-qPCR validation confirmed that these 9 genes were highly expressed in normal cells but significantly downregulated in tumor cells.

Our study developed a polyamine metabolism-based prognostic risk signature for HCC, which may provide valuable insights for personalized treatment strategies in HCC patients.

Cyclin-dependent kinase 1 (CDK1) has emerged as a critical regulator of cell cycle progression, yet its role in liver fibrosis-associated hepatocellular carcinoma (LF-HCC) remains underexplored. This study aimed to systematically evaluate CDK1's prognostic significance, immune regulatory functions, and therapeutic potential in LF-HCC pathogenesis. Integrated bioinformatics approaches were applied to multi-omics datasets from GEO, TCGA, and TIMER databases. Differentially expressed genes were identified through enrichment analysis and protein-protein interaction networks. Survival outcomes were assessed via Kaplan-Meier analysis, while immune cell infiltration patterns were quantified using CIBERSORT. Molecular docking simulations evaluated CDK1's binding affinity with pharmacologically active compounds (alvocidib, seliciclib, alsterpaullone) using AutoDock Vina. CDK1 demonstrated significant overexpression in LF-HCC tissues compared to normal controls (p < 0.001). Elevated CDK1 expression correlated with reduced overall survival (HR = 2.41, 95% CI:1.78-3.26, p = 0.003) and advanced tumor staging (p = 0.007). Immune profiling revealed strong associations between CDK1 levels and immunosuppressive cell infiltration, particularly regulatory T cells (r = 0.63, p = 0.001) and myeloid-derived suppressor cells (r = 0.58, p = 0.004). Molecular docking confirmed high-affinity binding of CDK1 to kinase inhibitors through conserved hydrogen-bond interactions (binding energy ≤ -8.5 kcal/mol), with alvocidib showing optimal binding stability. This multimodal analysis establishes CDK1 as both a prognostic biomarker and immunomodulatory regulator in LF-HCC pathogenesis. The enzyme's dual role in driving tumor progression and reshaping the immune microenvironment positions it as a promising therapeutic target. Computational validation of CDK1 inhibitors provides a rational basis for developing precision therapies against LF-HCC, bridging translational gaps between biomarker discovery and clinical application.

Despite nearly 250 million people worldwide estimated to have chronic HBV infection, health-related quality of life (HRQOL) in HBV-related disease has not been well characterised. Here, we summarise existing data on HBV-related HRQOL and quantify summary utility values by stage of disease.

Embase, Global Health, PubMed, and Web of Science were searched for articles investigating HBV HRQOL. Meta-analyses for utility scores were pooled by stage of disease and utility instrument; meta-regression was further adjusted for the effect of current health expenditure as a percentage of gross domestic product (CHE/GDP), as a proxy of the importance of healthcare perceived by different countries.

Twenty-two articles from 19 studies, comprising 10,311 patients, were included. Of these studies, 74% were performed in the Western Pacific Region, and 47% used the EuroQoL-5D-3L instrument. HRQOL was found to decrease with advancing stages of HBV-related disease. Meta-regression showed the following predicted mean utility scores for the different stages of chronic HBV infection: non-cirrhotic, 0.842; compensated cirrhosis, 0.820 (p = 0.474 compared with non-cirrhotic); decompensated cirrhosis, 0.722 (p = 0.001); and hepatocellular carcinoma, 0.749 (p = 0.008). The type of tool affected HRQOL and populations with a higher CHE/GDP were associated with higher predicted utility values.

Chronic HBV infection impairs the HRQOL of patients, even when there is no evidence of cirrhosis. HRQOL is particularly impaired in the advanced stages of decompensated cirrhosis and hepatocellular carcinoma. These results have important implications for global hepatitis elimination efforts and are useful for economic analyses. However, further research is needed, particularly in high-burden, low-income settings where data are lacking.

This study, based on 22 articles and 10,311 patients, provides a comprehensive synthesis of data on the impact of chronic hepatitis B virus (HBV) infection on patients' health-related quality of life (HRQOL) worldwide. These findings, of how HRQOL is affected in people living with HBV, highlight the importance of patient-centred care and holistic approaches to management, even at the early stages of disease. These results are useful for cost-effectiveness analyses and may help inform decision-making in improving public health policy towards the elimination of viral hepatitis. The study also underscores the need for further data from low-to middle-income settings, and on the effects of treatment on HRQOL.

Primary liver cancer (PLC), also known as hepatocellular carcinoma (HCC), is a common type of malignant tumor of the digestive system. Its pathological form has a significant negative impact on the patients' quality of life and ability to work, as well as a significant financial burden on society. Current researches had identified chronic hepatitis B virus infection, aflatoxin B1 exposure, and metabolic dysfunction-associated steatotic liver disease (MASLD) as the main causative factors of HCC. Numerous variables, including inflammatory ones, oxidative stress, apoptosis, autophagy, and others, have been linked to the pathophysiology of HCC. On the other hand, autoimmune regulation, inflammatory response, senescence of the hepatocytes, and mitochondrial dysfunction are all closely related to the pathogenesis of HCC. In fact, a growing number of studies have suggested that mitochondrial dysfunction in hepatocytes may be a key factor in the pathogenesis of HCC. In disorders linked to cancer, mitochondrial dysfunction has gained attention in recent 10 years. As the primary producer of adenosine triphosphate (ATP) in liver cells, mitochondria are essential for preserving cell viability and physiological processes. By influencing multiple pathological processes, including mitochondrial fission/fusion, mitophagy, cellular senescence, and cell death, mitochondrial dysfunction contributes to the development of HCC. We review the molecular mechanisms of HCC-associated mitochondrial dysfunction and discuss new directions for quality control of mitochondrial disorders as a treatment for HCC.

Hepatocellular carcinoma (HCC) remains one of the most prevalent malignant tumors, exhibiting a high morbidity and mortality rate. The mechanism of its occurrence and development requires further study. The objective of this study was to investigate the role of SERPINA12 in the diagnosis, prognosis prediction and biological function within HCC.

The Cancer Genome Atlas (TCGA) data were employed to analyze the relationship between clinical features and SERPINA12 expression in HCC. Kaplan-Meier curves were utilized to analyze the correlation between SERPINA12 expression and prognosis in HCC. The function of SERPINA12 was determined by enrichment analysis, and the relationship between SERPINA12 expression and immune cell infiltration was investigated. The expression of SERPINA12 was examined in 75 patients with HCC using RT-qPCR and immunohistochemistry, and survival analysis was performed.

The expression of SERPINA12 from TCGA database was found to be significantly higher in HCC tissues than in normal tissues and carried a poor prognosis. ROC curve demonstrated the diagnostic potential of SERPINA12 for HCC. The multivariate Cox regression analysis showed that pathologic T stage, tumor status, and SERPINA12 expression were independently associated with patient survival. The SERPINA12 expression was found to correlate with immune cell infiltration. Our RT-qPCR and immunohistochemical analysis revealed high expression of SERPINA12 in tumor tissues. Survival analysis indicated its association with poor prognosis.

SERPINA12 is a promising biomarker for diagnosis and prognosis, and it is associated with immune cell infiltration.

Hepatocellular carcinoma (HCC) is a lethal tumor. Predicting the prognosis of HCC remains challenging. Cellular senescence, which is one of the hallmarks of cancer, and its related prognostic-gene signature can provide critical information for clinical decision making. Our objective was to investigate the role of cellular senescence in HCC.

The RNA sequencing data and clinical information of HCC patients from The Cancer Genome Atlas (TCGA) database were obtained. The HCC subtypes and a senescence score model were established to predict the prognosis of HCC.

In this study, patients from TCGA-HCC dataset were stratified into low- and high-risk groups based on cellular senescence-related genes. The analysis of the various subtypes revealed that the distribution of Cluster 1 (C1) was significantly correlated with numerous factors, including age, sex, pathological T stage, tumor node metastasis (TNM) classification, and grade staging. Further, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that the upregulated genes in the high-risk C1 group were primarily engaged in pathways related to the cell cycle, DNA replication, cellular senescence, extracellular matrix (ECM)-receptor interactions, and the mechanisms of mismatch repair. Conversely, the 90 downregulated genes were mainly associated with metabolic pathways, chemical carcinogenesis involving DNA adducts, complement and coagulation cascades, and the peroxisome proliferator-activated receptor (PPAR) signaling pathway. The resultant boxplots revealed significant differences in the populations of immune cells, such as B cells, endothelial cells, natural killer (NK) cells, macrophages, cluster of differentiation (CD)4+ T cells, and CD8+ T cells, in the C1 HCC samples compared to the C2 HCC samples. Additionally, the prognostic outcomes of the HCC patients were predicted using a cellular senescence-related gene model that included VDAC2, CXCL8, MYBL2, RAD9A, LIN52, RHEB, GADD45G, E2F5, MAP2K2, CDC25A, PPP1CB, and HRAS.

This study established a prognostic model of HCC based on cellular senescence-related gene expression. Our findings may provide insights that can be used to develop novel potential targeted therapies.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, characterized by a high rate of postoperative recurrence and poor long-term survival outcomes. Structural maintenance of chromosome 4 (SMC4) is frequently overexpressed in various types of cancer and plays a pivotal role in tumor cell growth, migration, and invasion. Bioinformatics analysis has revealed a significant correlation between the tumor-node metastasis (TNM) stage (P < 0.01) and SMC4 expression (P < 0.05), and SMC4 was associated with poor prognosis in HCC. Furthermore, SMC4 was identified as an independent prognostic factor for HCC. Ubiquitin-specific peptidase 39 (USP39) was found whether the regulation was observed to affect protein synthesis or stability through bioinformatics analysis and immunoprecipitation. The expression levels and cellular localization of SMC4 and USP39 in hepatoma cells were evaluated using quantitative real-time PCR (qPCR), western blotting, and immunohistochemistry (IHC), all of which indicated significantly elevated expression of USP39 and SMC4 in HCC. The roles of the SMC4/USP39 were further investigated through several assays, including the 3-(4,5-Dimethylthiazol-2-yl) -2,5- diphenyltetrazolium bromide (MTT) assay, 5-ethynyl-2'-deoxyuridine (EdU) incorporation assay, and wound healing assay. The results demonstrated that USP39/SMC4 plays a crucial role in enhancing the viability and proliferation of HepG2 cells. Additionally, bioinformatics analysis identified ZNF207 and TIAL1 as potential target proteins of SMC4. Drug-resistant hepatoma cell lines were established, and both MTT and EdU assays were performed to assess cell viability and proliferation. The results demonstrated that HepG2/5-FU cells regained their sensitivity to 5-FU following the knockdown of SMC4. Additionally, the knockdown of either TIAL1 or ZNF207 also restored 5-FU sensitivity in HepG2/5-FU cells, effectively inhibiting cell viability and proliferation. Our study underscores the significant role of the USP39/SMC4 in HCC development and suggests that SMC4 may contribute to the regulation of drug resistance in hepatoma cell lines, potentially through interactions with TIAL1 and ZNF207.

Prostate-specific membrane antigen (PSMA) is overexpressed in prostate hypercellularity, making it an effective target for molecular imaging and therapy of prostate cancer. PSMA is expressed in the neovasculature of hepatic malignancies and regulates tumor cell invasion and angiogenesis. The diagnosis and treatment of hepatic malignancies remain challenging. Thus, radiopharmaceuticals targeting PSMA are gaining prominence in the treatment of hepatic malignancies. Therefore, this review aims to discuss the applications of PSMA-targeting radiopharmaceuticals in hepatic malignant tumors, focusing on hepatocellular carcinoma (HCC), to assess their value as a diagnostic and therapeutic agent for hepatic malignancies.

The potentials of PSMA-targeting radiopharmaceuticals for diagnostic and therapeutic use in hepatic malignancies were investigated. Moreover, their characteristics, diagnostic and therapeutic efficacies, and potential synergies when used in conjunction with other therapeutic modalities were elucidated.

Computed tomography (CT) and magnetic resonance imaging (MRI) are the most common imaging modalities in clinical practice; however, their sensitivity is not optimal. PSMA positron emission tomography/CT can be used as a complementary modality to conventional imaging for characterizing lesions, staging and/or re-staging HCC, and assessing treatment response when conventional imaging results are unclear. Moreover, most patients with HCC are diagnosed at an advanced stage in which treatment options are limited. Hence, PSMA-based radioligand therapy serves as a promising alternative treatment when multiple treatments fail.

Further research and clinical transformation are required to effectively diagnose and treat HCC via PSMA targeting. This will have significant clinical application prospects in primary and secondary hepatic malignancies.

Liver diseases represent a worldwide health problem accountable for two million deaths per year. Oxidative stress is critical for the development of these diseases. N-acetyl cysteine (NAC) is effective in preventing liver damage, both in experimental and clinical studies, and evidence has shown that the pharmacodynamic mechanisms of NAC are related to its antioxidant nature and ability to modulate key signaling pathways. Here, we provide a comprehensive description of the beneficial effects of NAC in the treatment of liver diseases, addressing the first evidence of its role as a scavenger and precursor of reduced glutathione, along with studies showing its immunomodulatory action, as well as the ability of NAC to modulate epigenetic hallmarks. We searched the PubMed database using the following keywords: oxidative stress, liver disease, epigenetics, antioxidants, NAC, and antioxidant therapies. There was no time limit to gather all available information on the subject. NAC has shown efficacy in treating liver damage, exerting mechanisms of action different from those of free radical scavengers. Like different antioxidant therapies, its effectiveness and safety are related to the administered dose; therefore, designing new pharmacological formulations for this drug is imperative to achieve an adequate response. Finally, there is still much to explore regarding its effect on epigenetic marker characteristics of liver damage, turning it into a drug with broad therapeutic potential. According to the literature reviewed, NAC could be an appropriate option in clinical studies related to hepatic injury and, in the future, a repurposing alternative for treating liver diseases.

Treating unresectable hepatocellular carcinoma (uHCC) is challenging. Clinical trials have shown that Single Tremelimumab Regular Interval Durvalumab (STRIDE) offers clinical benefits as a first-line treatment for uHCC, but its cost effectiveness remains unknown in the USA.

We aimed to assess the cost effectiveness of STRIDE (tremelimumab plus durvalumab) versus sorafenib and durvalumab monotherapy as the first-line treatment for uHCC in the USA.

A partitioned survival model was constructed to assess the cost effectiveness of STRIDE compared to sorafenib and durvalumab monotherapy as the first-line treatment for uHCC from the US societal perspective. The time horizon was 48 months with 1-month cycles. Seven parametric survival functions replicated survival curves from clinical trials, with the best-fitting model used to calculate survival probabilities. Costs, health utilities, and adverse events were included, with quality-adjusted life-years (QALYs) as the primary effectiveness measure. Both costs and effectiveness were discounted at 3%. In the base-case analysis, the incremental cost-effectiveness ratio was compared to a willingness-to-pay threshold of $150,000 per QALY gained. Deterministic and probabilistic sensitivity analyses were conducted to examine the uncertainty of the model.

In the base-case analysis, STRIDE was cost effective compared to sorafenib, with an incremental cost-effectiveness ratio of $97,995.51 per QALY gained, based on a willingness-to-pay threshold of $150,000 per QALY gained. However, STRIDE was not cost effective compared to durvalumab monotherapy at the same threshold, with an incremental cost-effectiveness ratio of $754,408.92 per QALY gained. Deterministic sensitivity analyses were consistent with the base-case analysis. A probabilistic sensitivity analysis indicated that STRIDE was more likely to be cost effective than sorafenib and durvalumab monotherapy when the willingness-to-pay exceeded $101,000 and $713,000, respectively.

The STRIDE regimen appears to be cost effective compared to sorafenib but not compared to durvalumab for first-line uHCC treatment in the USA. However, durvalumab has not yet been approved for uHCC in the USA. Future research should focus on long-term data and economic evaluations of other recommended biologics.

The therapeutic diagnosis of liver diseases has garnered significant interest within the medical community. In recent years, mesoporous silica nanoparticles (MSNs) have emerged as crucial nanocarriers for the treatment of liver ailments. Their remarkable diagnostic capabilities enable them to be used in techniques such as high-throughput mass spectrometry (MS), magnetic resonance imaging (MRI), near-infrared (NIR) fluorescence imaging, photoacoustic imaging (PAI), and ultrasonography (US), attracting considerable attention. Furthermore, the introduction of amino and carboxyl group modifications in MSNs has facilitated their use as drug delivery carriers for treating liver diseases, including hepatocellular carcinoma. This paper reviews the preparation methods, in vitro diagnostic capabilities, and in vivo therapeutic delivery systems of MSNs for liver disease treatment. It also summarizes relevant toxicity studies, aiming to provide a comprehensive overview of the diagnostic and therapeutic applications of MSNs in the treatment of liver diseases, particularly hepatocellular carcinoma. Through this review, we seek to offer theoretical insights into the potential of MSNs for diagnostic and therapeutic applications in liver disease treatment.

Within the tumor microenvironment, survival pressures are prevalent with potent drivers of tumor progression, angiogenesis, and therapeutic resistance. N6-methyladenosine (m6A) methylation has been recognized as a critical post-transcriptional mechanism regulating various aspects of mRNA metabolism. Understanding the intricate interplay between survival pressures and m6A modification provides new insights into the molecular mechanisms underlying hepatocellular carcinoma (HCC) progression and highlights the potential for targeting the survival pressures-m6A axis in HCC diagnosis and treatment.

A literature search was conducted in PubMed, MEDLINE, and Web of Science for relevant articles published up to April 2024. The keywords used for the search included hepatocellular carcinoma, cellular survival, survival pressure, N6-methyladenosine, tumor microenvironment, stress response, and hypoxia.

This review delves into the multifaceted roles of survival pressures and m6A RNA methylation in HCC, highlighting how survival pressures modulate the m6A landscape, the impact of m6A modification on survival pressure-responsive gene expression, and the consequent effects on HCC cell survival, proliferation, metastasis, and resistance to treatment. Furthermore, we explored the therapeutic potential of targeting this crosstalk, proposing strategies that leverage the understanding of survival pressures and m6A RNA methylation mechanisms to develop novel, and more effective treatments for HCC.

The interplay between survival pressures and m6A RNA methylation emerges as a complex regulatory network that influences HCC pathogenesis and progression.

Hepatocellular carcinoma is one of the deadliest and fastest-growing cancers. Among HCC etiologies, metabolic dysfunction-associated fatty liver disease (MAFLD) has served as a major HCC driver due to its great potential for increasing cirrhosis. The obesogenic environment fosters a positive energy balance and results in a continuous rise of obesity and metabolic syndrome. However, it is difficult to understand how metabolic complications lead to the poor prognosis of liver diseases and which molecular mechanisms are underpinning MAFLD-driven HCC development. Thus, suitable preclinical models that recapitulate human etiologies are essentially required. Numerous preclinical models have been created but not many mimicked anthropometric measures and the course of disease progression shown in the patients. Here we review the literature on adipose tissues, liver-related HCC etiologies and recently discovered genetic mutation signatures found in MAFLD-driven HCC patients. We also critically review current rodent models suggested for MAFLD-driven HCC study.

Liver fibrosis is a critical liver disease that can progress to more severe manifestations, such as cirrhosis, yet no effective targeted therapies are available. Here, we identify that ATF4, a master transcription factor in ER stress response, promotes liver fibrosis by facilitating a stress response-independent epigenetic program in hepatic stellate cells (HSCs). Unlike its canonical role in regulating UPR genes during ER stress, ATF4 activates epithelial-mesenchymal transition (EMT) gene transcription under fibrogenic conditions. HSC-specific depletion of ATF4 suppresses liver fibrosis in vivo. Mechanistically, TGFβ resets ATF4 to orchestrate a unique enhancer program for the transcriptional activation of pro-fibrotic EMT genes. Analysis of human data confirms a strong correlation between HSC ATF4 expression and liver fibrosis progression. Importantly, a small molecule inhibitor targeting ATF4 translation effectively mitigates liver fibrosis. Together, our findings identify a mechanism promoting liver fibrosis and reveal new opportunities for treating this otherwise non-targetable disease.

BackgroundHepatocellular carcinoma (LIHC), a prevalent liver cancer with a grim prognosis due to high recurrence rates, is under scrutiny for its association with zinc finger proteins (ZNFs) in tumorigenesis. This study aims to create a prognostic model for LIHC incorporating ZNF-related genes.MethodsBy analyzing TCGA data, we identified differentially expressed genes (DEGs) between normal and LIHC samples, focusing on ZNF-related genes through univariate Cox and LASSO Cox regression. A multivariate Cox regression model was built, categorizing LIHC patients into high- and low-ZNFRS groups based on ZNF-related risk scores. Model performance was evaluated using ROC curves, with a nomogram integrating clinical data and ZNFRS. Immune microenvironment, enrichment analysis, mutations, and drug responses in LIHC were also explored.ResultsA prognostic model utilizing 10 ZNF-related genes accurately predicted LIHC survival. The low-risk group exhibited enhanced immune cell infiltration, contrasting with cell cycle and DNA replication enrichment in the high-risk group, which also displayed increased mutation rates. Promising drug candidates like SNS-314 and Decitabine warrant further investigation in LIHC treatment.ConclusionThis study introduces impactful prognostic markers for LIHC management, emphasizing the significance of ZNFs in predicting patient outcomes and guiding treatment strategies.

This study aims to develop a prognostic model for HCC based on TME-related factors.

Hepatocellular carcinoma (HCC) is characterized by a poor prognosis, largely due to the complex and heterogeneous interactions between stromal and immune cells within the tumor microenvironment (TME).

Genome and transcriptome data, as well as clinical information of HCC patients, were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The TME score was evaluated using the "ESTIMATE" R package. Differentially expressed genes (DEGs) associated with TME phenotype were analyzed using the LIMMA R-package. Survival outcomes were compared using Kaplan-Meier curves with log-rank test and Cox proportional hazards model. Protein-Protein Interaction (PPI) networks integrated with multivariate survival and LASSO analyses were utilized to identify TME-related hub genes for a risk score model. A nomogram predicting prognosis of HCC patients was developed through four independent cohorts.

The TME scores showed a negative correlation with tumor progression and survival in HCC patients. We identified 50 core genes with high connectivity in the PPI network, as along with 33 key DEGs associated with survival in HCC. Intersection analysis revealed six hub genes -CXCL8, CXCL1, CCR7, IL7R, MMP9, and CD69. The risk score based on these six TME-related hub genes was significantly associated with overall survival and clinicopathological characteristics of HCC patients. Furthermore, the nomogram demonstrated its ability to discriminate HCC patients from healthy individuals using peripheral blood mononuclear cells.

We have developed a TME-related risk scoring model for HCC patients and identified six hub gene panel that serve as a potential biomarker for personalized prognosis of immunotherapy and non-invasive diagnostics of HCC.

To evaluate the efficacy of re-resection in recurrent hepatocellular carcinoma (rHCC), identify prognostic factors, and provide clinical guidance.

A retrospective analysis was conducted on 130 rHCC patients undergoing re-resection and 60 primary HCC patients undergoing initial hepatectomy at Peking University People's Hospital (2014-2022). Disease-free survival (DFS) and overall survival (OS) were compared. Prognostic factors were identified using univariate and multivariate COX regression analyses.

Baseline characteristics were comparable between groups (P > 0.05). DFS was similar between groups (30.8 vs. 32.2 months, P = 0.612). The 1-year, 2-year, and 3-year DFS rates for the re-resection group were 88.5 %, 64.9 %, and 56.7 %, respectively, versus 88.3 %, 65.0 %, and 53.3 % for the primary resection group. OS was lower in the re-resection group (36.1 vs. 47.2 months, P = 0.041) with 1-year, 2-year, and 3-year OS rates of 90.8 %, 73.1 %, and 60.0 %, compared to 95.0 %, 80.0 %, and 68.3 % for the primary resection group. Significant factors affecting DFS were Child-Pugh classification (P = 0.044), time to recurrence (P = 0.002), tumor differentiation (P = 0.044), and satellite nodules (P = 0.019). Factors influencing OS included Child-Pugh classification (P = 0.040), time to recurrence (P = 0.002), and tumor differentiation (P = 0.032).

Re-resection is an effective treatment option for rHCC, with favorable outcomes as measured by DFS and OS, though OS is lower compared to initial hepatectomy. Key prognostic factors include Child-Pugh classification, time to recurrence, tumor differentiation, and satellite nodules.

Hepatocellular Carcinoma (HCC) is the most common form of primary liver cancer, with cirrhosis being its strongest risk factor. Interestingly, an increasing number of HCC cases is also observed without cirrhosis. We developed an HCC model via intrasplenic injection of highly tumorigenic HCC cells, which, due to cellular tropism, invade the liver and allow for a controllable disease progression. Specifically, C57BL/6JRj mice were intrasplenically inoculated with Dt81Hepa1-6 HCC cells, with a subgroup pre-treated with CCl4 to induce cirrhosis (C-HCC). At four weeks post-inoculation, mice were sacrificed, and diseased livers were analyzed via histology, flow cytometry, and RT-qPCR to profile the extracellular matrix (ECM), angiogenesis, and immune cells. In addition, tumor-bearing mice were treated with the first-line therapy, AtezoBev, to assess therapeutic responsiveness of the model. Dt81Hepa1-6 cells displayed similar gene expression as human HCC. After intrasplenic injection, all mice developed multifocal disease. C-HCC mice had a significantly higher tumor load than non-cirrhotic HCC mice. Both HCC and C-HCC models displayed extensive ECM formation, increased levels of vascularization, and immune cell infiltration compared to healthy and non-cancerous cirrhotic livers. AtezoBev treatment produced robust antitumor efficacy, validating the model's suitability for therapy testing. In conclusion, we established a rapidly developing and high-yield HCC model through a simple intrasplenic injection, with or without cirrhotic damage. The model overexpressed key human HCC genes and showed high responsiveness to first-line treatment. Our model uniquely combines all the above-mentioned features, promoting its use towards HCC therapy testing.

Alpha fetoprotein (AFP) is a glycoprotein of foetal origin belonging to the albumin protein family. Serum AFP is a long-conceived early-diagnostic biomarker for HCC with its elevated expression in different liver pathologies ranging from hepatitis viral infections to fibrosis, cirrhosis, and HCC. Beyond their utility as biomarkers, in support of its contribution to these clinical outcomes, the function of AFP as an immune suppressor and inducer of malignant transformation in HCC patients is well reported. Multiple reports show that AFP is secreted by hepatocytes, binds to its cognate receptor, AFP-receptor (AFPR), and exerts its actions. However, there is only limited information available in this context. There is an urgent need to gather more insight into the AFP signalling pathway and consider it a classical intracellular signalling pathway, among others. AFP is a highly potent intracellular molecule that has the potential to bind to many interactors like PTEN, Caspase, RAR, and so on. It has been shown that cellular AFP and secreted AFP have different roles in HCC pathophysiology, and a comprehensive map of the AFP signalling pathway is warranted for further theranostic applications.

Due to current challenges in the early detection, less than 40% of individuals diagnosed with hepatocellular carcinoma (HCC) are viable candidates for surgical intervention. Therefore, validating and launching of a novel precise diagnostic approach is essential for early diagnosis. Based on developing evidence using circulating tumor cells and their derivatives, circulating miRNAs, and extracellular vesicles (EVs), liquid biopsy may offer a reliable platform for the HCC's early diagnosis. Each liquid biopsy analyte may provide significant areas for diagnosis, prognostic assessment, and treatment monitoring of HCC patients depending on its kind, sensitivity, and specificity. The current review addresses potential clinical applications, current research, and future developments for liquid biopsy in HCC management.

Although the combination of atezolizumab and bevacizumab (A+B) shows promise for advanced hepatocellular carcinoma (HCC), its response rate is still inadequate. Previous studies indicate that the integration of FOLFOX-based hepatic arterial infusion chemotherapy (HAIC) with transarterial chemoembolization (TACE) is advantageous for the management of HCC. This meta-analysis aims to assess the safety and efficacy of the A+B+TACE or HAIC therapy protocol in patients with advanced HCC.

We collected pertinent studies from databases such as PubMed, Cochrane Library, Web of Science, and Embase, all published prior to August 1, 2024. We used Stata MP 14.0 software for data analysis, incorporating data extraction and quality assessment procedures.

Data synthesis employed a fixed-effects model in certain contexts and a random-effects model where significant variability was present. A total of 405 patients were involved over ten trials. The overall objective response rate (ORR) was 57.2% (95% CI, 46.9-67.6%), and the disease control rate (DCR) was 85.9% (95% CI, 82.0-89.7%), as determined by the modified response assessment criteria in solid tumors (mRECIST). The rates for complete response (CR) and partial response (PR) were 10.8% (95% CI, 5.0-16.6%) and 45.5% (95% CI, 38.0-53.0%), respectively. The median progression-free survival (mPFS) was 10.9 months, with a 95% confidence interval (CI) of 8.0 to 13.8. 91.0% (95% CI: 84.9-97.1%) of patients experienced adverse events (AEs) of any severity during therapy, with 24.8% (95% CI: 8.8-40.9%) reporting AEs of grade 3 or higher.

The A+B+TACE-HAIC therapy demonstrates promising efficacy and tolerance for the management of advanced HCC.

Background: Hepatocellular carcinoma (HCC) is a prevalent liver cancer with poor prognosis, often linked to hepatitis B (HBV) and C (HCV) infections. This meta-analysis evaluates the efficacy of immunotherapy in HCC, particularly in cases arising from viral hepatitis. Methods: In adherence to PRISMA Statement 2020 guidelines, the immunotherapeutic outcomes comprised objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Data were analyzed from randomized controlled trials up to April 2024 using the fixed-effects models in R (V.4.3.3.) and RevMan (Cochrane). Results: This study included 9 trials with 5316 patients. The ORR was slightly higher in the viral group at 27.93% compared to 24.07% in the non-viral group, though this difference was not significant (p = 0.15). Viral HCC patients exhibited a median PFS of 7.3 months (IQR: 6.2-8.4) compared to 5.8 months (IQR: 5.48-6.13) in non-viral patients, a significant improvement (p = 0.005). Similarly, median OS was longer in the viral group at 16.8 months (IQR: 12.99-20.61) versus 15.2 months (IQR: 13.25-17.15) for non-viral HCC, which was also significant (p < 0.0001). The median OS for viral HCC was 16.8 months (IQR: 14.11-19.49 months), with HBV patients experiencing slightly higher survival at 17.15 months (IQR: 14.3-20 months) compared to 16.8 months (IQR: 12.99-20.61 months) for HCV patients; this difference was not statistically significant (p = 0.89). Conclusions: Immunotherapy shows potential in treating HCC, with significantly better outcomes in viral HCC, particularly HBV-associated cases. The heterogeneity highlights the need for personalized treatment approaches based on the viral background of HCC patients. Further research should aim to optimize these therapies to improve survival rates.

This study aimed to explore novel targets for hepatocellular carcinoma (HCC) treatment by investigating the role of fatty acid metabolism.

RNA-seq and clinical data of HCC were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatic analyses were employed to identify differentially expressed genes (DEGs) related to prognosis. A signature was then constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression to classify HCC patients from the TCGA database into low-risk and high-risk groups. The predictive performance of the signature was evaluated through principal components analysis (PCA), Kaplan Meier (KM) survival analysis, receiver operating characteristics (ROC) curves, nomogram, genetic mutations, drug sensitivity analysis, immunological correlation analysis, and enrichment analysis. Single-cell maps were constructed to illustrate the distribution of core genes. Immunohistochemistry (IHC), quantitative real-time PCR (qRT-PCR), and western blot were employed to verify the expression of core genes. The function of one core gene was validated through a series of in vitro assays, including cell viability, colony formation, wound healing, trans-well migration, and invasion assays. The results were analyzed in the context of relevant signaling pathways.

Bioinformatic analyses identified 15 FAMGs that were related to prognosis. A 4-gene signature was constructed, and patients were divided into high- and low-risk groups according to the signature. The high-risk group exhibited a poorer prognosis compared to the low-risk group in both the training (P < 0.001) and validation (P = 0.020) sets. Furthermore, the risk score was identified as an independent predictor of OS (P < 0.001, HR = 8.005). The incorporation of the risk score and clinicopathologic features into a nomogram enabled the effective prediction of patient prognosis. The model was able to effectively predict the immune microenvironment, drug sensitivity to chemotherapy, and gene mutation for each group. Single-cell maps demonstrated that FAMGs in the model were distributed in tumor cells. Enrichment analyses revealed that the cell cycle, fatty acid β oxidation and PPAR signaling pathways were the most significant pathways. Among the four key prognostically related FAMGs, Spermine Synthase (SMS) was selected and validated as a potential oncogene affecting cell cycle, PPAR-γ signaling pathway and fatty acid β oxidation in HCC.

The risk characteristics based on FAMGs could serve as independent prognostic indicators for predicting HCC prognosis and could also serve as evaluation criteria for gene mutations, immunity, and chemotherapy drug therapy in HCC patients. Meanwhile, targeted fatty acid metabolism could be used to treat HCC through related signaling pathways.

Hepatocellular carcinoma remains a health challenge for humanity. Therefore, there is an urgent need to develop novel biomarkers with high efficiency yet fast ability to meet the requirements of hepatocellular carcinoma treatment.

A total of 229 patients with HBV-associated hepatocellular carcinoma (HCC), 298 patients with chronic hepatitis B (CHB), and 96 healthy controls were retrospectively analyzed. Methylation levels of the Mex3a promoter in peripheral blood mononuclear cells (PBMCs) were measured using MethyLight to obtain clinical and laboratory parameters.

The Mex3a promoter methylation level in HCC patients (median: 0.289% and interquartile range: 0.126%-0.590%) was significantly lower than that in CHB patients (median: 0.999%, interquartile range: 0.417%-1.268%, and p < 0.001) and healthy people (median: 2.172%, interquartile range: 1.225%-3.098%, and p < 0.001). The Mex3a mRNA levels in HCC patients (median: 12.198 and interquartile range: 3.112-18.996) were significantly higher than those in CHB patients (median: 1.623 and interquartile range: 0.066-6.000, and p < 0.001) and healthy controls (median: 0.329, interquartile range: 0.031-1.547, and p < 0.001). MethyLight data were expressed as a percentage of the methylated reference (PMR) value. The Mex3a PMR value was negatively correlated with the mRNA expression level (Spearman's R = -0.829 and p < 0.001). The Mex3a PMR value of HCC patients was significantly correlated with age (Spearman's R = 0.113 and p = 0.044), and the mRNA level was significantly correlated with ALT (Spearman's R = 0.132 and p = 0.046). The Mex3a promoter methylation levels and mRNA levels were also independent factors in the development of liver cancer. The Mex3a promoter methylation and mRNA levels were better at distinguishing HCC from CHB than AFP [area under the receiver operating characteristic curve (AUC) for predicting HCC vs. CHB: 0.915 vs. 0.715: p < 0.001]. The combined use of AFP and Mex3a methylation levels and mRNA levels further improved the area under the receiver operating characteristic curve.

The presence of Mex3a promoter hypomethylation in hepatocellular carcinoma can be used as a non-invasive biomarker for the early detection of liver cancer.

This review aims to synthesize the old issues and current understandings of the etiology of liver cancer, focusing on the diverse causative factors influenced by geographical, socioeconomic, and lifestyle variations across different regions.

We highlight significant geographic disparities in liver cancer risk factors. While hepatitis B and C viruses, aflatoxin exposure, and alcohol consumption remain globally established contributors; metabolic dysfunction-associated steatotic liver disease and metabolic syndromes are increasingly prominent in the West. Chronic HBV and aflatoxin continue to dominate as risk factors in Asia and Africa. Dietary factors, metabolic diseases like diabetes and obesity, genetic predispositions, environmental risk factors and lifestyle choices such as smoking and alcohol use play substantial roles in specific populations. Protective factors like coffee and tea consumption, along with aspirin use, vegetables and fruits have shown potential in reducing HCC risk, although findings vary by population and dietary habits. Liver cancer etiology is influenced by various factors that differ by region. Established risk factors include hepatitis B and C, aflatoxin, and alcohol. Emerging risks, such as metabolic dysfunction-associated steatotic liver disease, are more prevalent in Western countries, while aflatoxin and HBV remains significant in Asia and Africa. Diet, metabolic conditions like diabetes and obesity, genetic predispositions, and lifestyle choices also play crucial roles. Coffee, tea, aspirin, vegetables, and fruits may reduce HCC risk, but effectiveness varies. Future research should integrate epidemiology, genetics, and nutrition, with global cooperation and data sharing essential for effective cancer control strategies.

In advanced hepatocellular carcinoma (HCC) tissues, M2-like tumor-associated macrophages (TAMs) are in the majority and promotes HCC progression. Contrary to the pro-tumor effect of M2-like TAMs, M1-like TAMs account for a small proportion and have anti-tumor effects. Since TAMs can switch from one type to another, reprogramming TAMs may be an important treatment for HCC therapy. However, the mechanisms of phenotypic switch and reprogramming TAMs are still obscure. In this study, we analyzed differential genes in normal macrophages and TAMs, and found that loss of MANF in TAMs accompanied by high levels of downstream genes negatively regulated by MANF. MANF reprogrammed TAMs into M1 phenotype. Meanwhile, loss of MANF promoted HCC progression in HCC patients and mice HCC model, especially tumor neovascularization. Additionally, macrophages with MANF supplement suppressed HCC progression in mice, suggesting MANF supplement in macrophage was an effective treatment for HCC. Mechanistically, MANF enhanced the HSF1-HSP70-1 interaction, restricted HSF1 in the cytoplasm of macrophages, and decreased both mRNA and protein levels of HSP70-1, which in turn led to reprogramming TAMs, and suppressing neovascularization of HCC. Our study contributes to the exploration the mechanism of TAMs reprogramming, which may provide insights for future therapeutic exploitation of HCC neovascularization.

5-methylcytosine/N6-methyladenosine/N7-methylguanosine (m5C/m6A/m7G)-related genes play a critical role in tumor occurrence and progression, and non-apoptotic regulatory cell death (NARCD) is closely linked to tumor development and immunity. However, the role of m5C/m6A/m7G-related NARCD genes in hepatocellular carcinoma (HCC) remains unclear. We used m5C/m6A/m7G-related NARCD genes to construct a prognostic model of HCC for prognostic prediction and clinical treatment of patients.

We obtained transcriptome data for HCC from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Using the least absolute shrinkage and selection operator (LASSO) regression, we identified m5C/m6A/m7G-related NARCD genes and constructed a prognostic model through multivariate Cox regression. Model performance was assessed using Kaplan-Meier and receiver operating characteristic (ROC) curves, with external validation using the ICGC. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were used to study differentially expressed genes between high- and low-risk groups. We also examined immune cell infiltration, drug response, and cell communication between tumor cells and immune cells in high-risk groups.

We identified 140 m5C/m6A/m7G-related NARCD genes, using five of them to build the prognostic model. Functional enrichment analysis revealed enrichment in tumor and immune-related pathways for risk genes. The high-risk group displayed increased immune cell infiltration and better responses to immune checkpoint inhibitors (ICIs). High-risk patients were more responsive to cisplatin, doxorubicin, and mitomycin C, while low-risk patients were more sensitive to erlotinib. Cell communication analysis indicated that high-risk tumor cells used insulin-like growth factor (IGF) and macrophage migration inhibitory factor (MIF) signaling pathways to send signals to immune cells and received signals through the bone morphogenetic protein (BMP) and lymphotoxin-related inducible ligand (LIGHT) pathways.

We have developed a prognostic model with m5C/m6A/m7G-related NARCD genes to predict the prognosis of HCC patients. This model can offer insights into the effectiveness of immunotherapy and chemotherapy for HCC patients.

To targeted overcome the multidrug resistance (MDR) and metastasis of liver tumors, we proposed to develop a palladium (Pd) agent based on a specific residue of human serum albumin (HSA) for multiacting on tumor cell and other components in the tumor microenvironment. To this end, a series of Pd(II) 2-acetylpyridine thiosemicarbazone compounds were optimized to obtain a Pd(II) compound (5b) with significant cytotoxicity against HepG2/ADM cells. Subsequently, we constructed a HSA-5b complex delivery system and revealed the structural mechanism of HSA delivering 5b. Importantly, 5b/HSA-5b effectively inhibited the growth and metastasis of multidrug resistant liver tumors, and HSA enhanced the targeting ability of 5b and reduced its side effects in vivo. Furthermore, we confirmed the mechanisms of 5b/HSA-5b integrating to overcome MDR and metastasis of liver tumors: multiacting on cancer cell, activating immune response, and inactivating cancer-associated fibroblasts.

Recent development in immunotherapy for cancer treatment has substantiated to be more effective than most of the other treatments. Immunity is the first line of defence of the body; nevertheless, cancerous cells can manipulate immunity compartments to play several roles in tumour progression. Tumour-associated macrophages (TAMs), one of the most dominant components in the tumour microenvironment, are recognized as anti-tumour suppressors. Unfortunately, the complete behaviour of TAMs is still unclear and understudied. TAM density is directly correlated with the progression and poor prognosis of hepatocellular carcinoma (HCC), therefore studying TAMs from different points of view passing by all the factors that may affect its existence, polarization, functions and repolarization are of great importance. Different epigenetic regulations were reported to have a direct relation with both HCC and TAMs. Here, this review discusses different epigenetic regulations that can affect TAMs in HCC whether positively or negatively.

Hepatocellular carcinoma (HCC) is highly aggressive, with delayed diagnosis, poor prognosis, and a lack of comprehensive and accurate prognostic models to assist clinicians. This study aimed to construct an HCC prognosis-related gene signature (HPRGS) and explore its clinical application value.

TCGA-LIHC cohort was used for training, and the LIRI-JP cohort and HCC cDNA microarray were used for validation. Machine learning algorithms constructed a prognostic gene label for HCC. Kaplan-Meier (K-M), ROC curve, multiple analyses, algorithms, and online databases were used to analyze differences between high- and low-risk populations. A nomogram was constructed to facilitate clinical application.

We identified 119 differential genes based on transcriptome sequencing data from five independent HCC cohorts, and 53 of these genes were associated with overall survival (OS). Using 101 machine learning algorithms, the 10 most prognostic genes were selected. We constructed an HCC HPRGS with four genes (SOCS2, LCAT, ECT2, and TMEM106C). Good predictive performance of the HPRGS was confirmed by ROC, C-index, and K-M curves. Mutation analysis showed significant differences between the low- and high-risk patients. The low-risk group had a higher response to transcatheter arterial chemoembolization (TACE) and immunotherapy. Treatment response of high- and low-risk groups to small-molecule drugs was predicted. Linifanib was a potential drug for high-risk populations. Multivariate analysis confirmed that HPRGS were independent prognostic factors in TCGA-LIHC. A nomogram provided a clinical practice reference.

We constructed an HPRGS for HCC, which can accurately predict OS and guide the treatment decisions for patients with HCC.