DNA methylation-based prognosis and epidrivers in hepatocellular carcinoma

Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer and a leading cause of cancer-related deaths globally. The tumour microenvironment (TME) influences treatment response and prognosis, yet its heterogeneity remains unclear.

METHODS

The unsupervised machine learning methods- agglomerative hierarchical clustering, Multi-Omics Factor Analysis with K-means++, and an autoencoder with K-means++ - stratified patients using microarray data from HCC samples. Immune deconvolution algorithms estimated the proportions of infiltrating immune cells across identified clusters.

RESULTS

Thirteen genes were found to influence HCC subtyping in both primary and validation datasets, with three genes-TOP2A, DCN, and MT1E-showing significant associations with survival and recurrence. DCN, a known tumour suppressor, was significant across datasets and associated with improved survival, potentially by modulating the TME and promoting an anti-tumour immune response.

CONCLUSIONS

The discovery of the 13 conserved genes is an important step toward understanding HCC heterogeneity and the TME, potentially leading to the identification of more reliable biomarkers and therapeutic targets. We have stratified and validated the liver cancer populations. The findings suggest further research is needed to explore additional factors influencing the TME beyond gene expression, such as tumour microbiome and stromal cell interactions.

Molecular Testing and Targeted Therapies in Hepatobiliary Cancers: A Review

Importance

Hepatobiliary cancers are heterogeneous and molecularly complex. Recent advances in next-generation sequencing (NGS) have enhanced the understanding of their molecular landscape and enabled deployment of biomarker-based gene- and immune-targeted therapies. This review examines the role of molecular testing and targeted therapies in these malignant neoplasms.

Observations

Patients with hepatobiliary cancers have poor outcomes. Precision oncology studies have shown that while many common molecular alterations are not currently targetable in hepatocellular carcinoma (HCC), a large number of actionable alterations characterize biliary tract cancers (BTCs), with several therapies now approved by the US Food and Drug Administration. Immunotherapy is increasingly adopted in clinical practice, either as monotherapy or combined with cytotoxic chemotherapy, for both HCC and BTCs. Moreover, multiple solid cancer tumor-agnostic therapies are approved (larotrectinib, entrectinib, and repotrectinib for NTRK fusions; selpercatinib for RET fusions; dabrafenib and trametinib combination for BRAF V600E mutations; dostarlimab or pembrolizumab for tumors with high microsatellite instability and pembrolizumab for tumor mutation burden ≥10 mutations/megabase), highlighting the need for NGS as well as ERBB2 (formerly HER2) immunohistochemistry (IHC) (with the recent approval of solid tissue-agnostic deruxtecan trastuzumab for ERBB2-positive [IHC 3+] cancer) across cancers. N-of-1 clinical trials using customized drug combinations matched to the tumor's molecular profile have yielded encouraging results and provide a promising framework for future clinical trial design.

Conclusions and Relevance

Molecular testing and gene- and immune-targeted therapies are transforming hepatobiliary cancer treatment. Tumor-agnostic and N-of-1 clinical trials have challenged traditional clinical trial paradigms and provide the foundation for truly personalized oncology for patients with these aggressive cancers. Further work is needed to determine how to leverage these novel approaches into the management of operable disease.

Predictive factors and prognostic models for Hepatic arterial infusion chemotherapy in Hepatocellular carcinoma: a comprehensive review

Hepatocellular carcinoma (HCC) is a prevalent and lethal cancer, often diagnosed at advanced stages where traditional treatments such as surgical resection, liver transplantation, and locoregional therapies provide limited benefits. Hepatic arterial infusion chemotherapy (HAIC) has emerged as a promising treatment modality for advanced HCC, enhancing anti-tumor efficacy through targeted drug delivery while minimizing systemic side effects. However, the heterogeneous nature of HCC leads to variable responses to HAIC, highlighting the necessity for reliable predictive indicators to tailor personalized treatment strategies. This review explores the factors influencing HAIC success, including patient demographics, tumor characteristics, biomarkers, genomic profiles, and advanced imaging techniques such as radiomics and deep learning models. Additionally, the synergistic potential of HAIC combined with immunotherapy and molecular targeted therapies is examined, demonstrating improved survival outcomes. Prognostic scoring systems and nomograms that integrate clinical, molecular, and imaging data are discussed as superior tools for individualized prognostication compared to traditional staging systems. Understanding these predictors is essential for optimizing HAIC efficacy and enhancing survival and quality of life for patients with advanced HCC. Future research directions include large-scale prospective studies, integration of multi-omics data, and advancements in artificial intelligence to refine predictive models and further personalize treatment approaches.

Noninvasive prognostication of hepatocellular carcinoma based on cell-free DNA methylation

BACKGROUND

The current noninvasive prognostic evaluation methods for hepatocellular carcinoma (HCC), which are largely reliant on radiographic imaging features and serum biomarkers such as alpha-fetoprotein (AFP), have limited effectiveness in discriminating patient outcomes. Identification of new prognostic biomarkers is a critical unmet need to improve treatment decision-making. Epigenetic changes in cell-free DNA (cfDNA) have shown promise in early cancer diagnosis and prognosis. Thus, we aim to evaluate the potential of cfDNA methylation as a noninvasive predictor for prognostication in patients with active, radiographically viable HCC.

METHODS

Using Illumina HumanMethylation450 array data of 377 HCC tumors and 50 adjacent normal tissues obtained from The Cancer Genome Atlas (TCGA), we identified 158 HCC-related DNA methylation markers associated with overall survival (OS). This signature was further validated in 29 HCC tumor tissue samples. Subsequently, we applied the signature to an independent cohort of 52 patients with plasma cfDNA samples by calculating the cfDNA methylation-based risk score (methRisk) via random survival forest models with 10-fold cross-validation for the prognostication of OS.

RESULTS

The cfDNA-based methRisk showed strong discriminatory power when evaluated as a single predictor for OS (3-year AUC = 0.81, 95% CI: 0.68-0.94). Integrating the methRisk with existing risk indices like Barcelona clinic liver cancer (BCLC) staging significantly improved the noninvasive prognostic assessments for OS (3-year AUC = 0.91, 95% CI: 0.80-1), and methRisk remained an independent predictor of survival in the multivariate Cox model (P = 0.007).

CONCLUSIONS

Our study serves as a pilot study demonstrating that cfDNA methylation biomarkers assessed from a peripheral blood draw can stratify HCC patients into clinically meaningful risk groups. These findings indicate that cfDNA methylation is a promising noninvasive prognostic biomarker for HCC, providing a proof-of-concept for its potential clinical utility and laying the groundwork for broader applications.

Methylation Risk Score Modelling in Endometriosis: Evidence for Non-Genetic DNA Methylation Effects in a Case-Control Study

Endometriosis is a chronic gynaecological disease characterised by endometrial-like tissue found external to the uterus. While several studies have reported strong evidence of a genetic contribution to the disease, studies on the environmental impact on endometriosis are limited. DNA methylation (DNAm) can be influenced by genetic and environmental factors and serves as a useful biological marker of the effects of genetic and environmental exposures on complex diseases. This study aims to develop a methylation risk score (MRS) for endometriosis to increase the power to detect DNAm signals associated with the disease and enhance our understanding of the pathogenesis of the disease. Endometrial methylation and genotype data from 318 controls and 590 cases were analysed. MRSs were developed using several different models. MRS performances were evaluated by splitting samples into training and test sets based on independent cohort institutions, and the area under the receiver-operator curve (AUC) was calculated. The maximum AUC obtained from the best-performing MRS is 0.6748, derived from 746 DNAm sites. The classification performance of MRS and polygenic risk score (PRS) combined was consistently higher than PRS alone. This study demonstrates that there are DNAm signals independent of common genetic variants associated with endometriosis.

Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma

BACKGROUND/AIMS

Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery.

METHODS

In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63).

RESULTS

The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69-0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14-0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy.

CONCLUSION

Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

Sensitive detection of circulating methylated SEPT9 in hepatocellular carcinoma patients using a novel quantitative PCR assay

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Early detection is crucial, yet reliable biomarkers are limited. Methylated SEPT9 (mSEPT9) has emerged as a promising biomarker for HCC. Building upon previous ExBP technology, we enhanced the semi-nested realtime PCR assay by integrating TaqMan probes, enabling quantitative detection of mSEPT9 in plasma samples of HCC patients. The assay was validated using synthetic DNA standards and plasma samples from 49 HCC patients, 20 chronic liver disease (CLD) patients, and 32 healthy donors (HDs). Our assay demonstrated sensitivity in detecting methylation ratios as low as 1 : 100 000. The assay showed a strong linear correlation between Ct values and methylation levels over four orders of magnitude (R2 = 0.96178), indicating robust quantification. Clinically, the assay revealed significant differences in ΔCt values between HCC patients (median ΔCt = 19.55) and controls (CLD: 29.32 and HDs: 26.19, p < 0.005). ROC analysis for HCC vs. controls yielded an AUC of 0.729, with 77.55% sensitivity and 59.62% specificity at the optimal cutoff (≤25.98). Notably, the assay identified 72.73% of HCC cases with AFP levels below 20 ng mL-1, underscoring its potential in detecting AFP-negative cases. These findings suggest that the novel mSEPT9 assay is a sensitive and specific tool for early HCC detection, offering prognostic value for clinical monitoring.

Hepatocellular carcinoma: signaling pathways and therapeutic advances

Liver cancer represents a major global health concern, with projections indicating that the number of new cases could surpass 1 million annually by 2025. Hepatocellular carcinoma (HCC) constitutes around 90% of liver cancer cases and is primarily linked to factors incluidng aflatoxin, hepatitis B (HBV) and C (HCV), and metabolic disorders. There are no obvious symptoms in the early stage of HCC, which often leads to delays in diagnosis. Therefore, HCC patients usually present with tumors in advanced and incurable stages. Several signaling pathways are dis-regulated in HCC and cause uncontrolled cell propagation, metastasis, and recurrence of HCC. Beyond the frequently altered and therapeutically targeted receptor tyrosine kinase (RTK) pathways in HCC, pathways involved in cell differentiation, telomere regulation, epigenetic modification and stress response also provide therapeutic potential. Investigating the key signaling pathways and their inhibitors is pivotal for achieving therapeutic advancements in the management of HCC. At present, the primary therapeutic approaches for advanced HCC are tyrosine kinase inhibitors (TKI), immune checkpoint inhibitors (ICI), and combination regimens. New trials are investigating combination therapies involving ICIs and TKIs or anti-VEGF (endothelial growth factor) therapies, as well as combinations of two immunotherapy regimens. The outcomes of these trials are expected to revolutionize HCC management across all stages. Here, we provide here a comprehensive review of cellular signaling pathways, their therapeutic potential, evidence derived from late-stage clinical trials in HCC and discuss the concepts underlying earlier clinical trials, biomarker identification, and the development of more effective therapeutics for HCC.

Selective inhibition of TGF-β-induced epithelial-mesenchymal transition overcomes chemotherapy resistance in high-risk lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) represents a major subtype of lung cancer, and it demonstrates limited treatment options and worse survival. Identifications of a prognostic model and chemoresistance mechanism can be helpful for improving stratification and guiding therapy decisions. The integrative development of machine learning-based models reveals a random survival forest (RSF) prognostic model for LUSC. The 12-gene RSF model exhibits high prognostic power in more than 1,000 LUSC patients. High-risk LUSC patients are associated with worse survival and the activation of the epithelial-mesenchymal transition pathway. Additionally, high-risk LUSC patients are resistant to docetaxel or vinorelbine treatment. In vitro and in vivo drug sensitivity experiments indicates that high-risk HCC15/H226 tumour cells and cell line-derived xenograft models are more resistant to vinorelbine treatment. Furthermore, the combination of chemotherapy with transforming growth factor-β inhibition augments antitumour responses in LUSC tumours. Our study provides valuable insights into prognosis stratification and the development of therapeutic strategies for LUSC.

Liquid biopsy in hepatocellular carcinoma: Challenges, advances, and clinical implications

Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional's skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

The Cell Polarity Protein MPP5/PALS1 Controls the Subcellular Localization of the Oncogenes YAP and TAZ in Liver Cancer

The oncogenes yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are potent liver oncogenes. Because gene mutations cannot fully explain their nuclear enrichment, we aim to understand which mechanisms cause YAP/TAZ activation in liver cancer cells. The combination of proteomics and functional screening identified numerous apical cell polarity complex proteins interacting with YAP and TAZ. Co-immunoprecipitation (Co-IP) experiments confirmed that membrane protein palmitoylated 5 (MPP5; synonym: PALS1) physically interacts with YAP and TAZ. After removing different MPP5 protein domains, Co-IP analyses revealed that the PDZ domain plays a crucial role in YAP binding. The interaction between YAP and MPP5 in the cytoplasm of cancer cells was demonstrated by proximity ligation assays (PLAs). In human hepatocellular carcinoma (HCC) tissues, a reduction in apical MPP5 expression was observed, correlating with the nuclear accumulation of YAP and TAZ. Expression data analysis illustrated that MPP5 is inversely associated with YAP/TAZ target gene signatures in human HCCs. Low MPP5 levels define an HCC patient group with a poor clinical outcome. In summary, MPP5 facilitates the nuclear exclusion of YAP and TAZ in liver cancer. This qualifies MPP5 as a potential tumor-suppressor gene and explains how changes in cell polarity can foster tumorigenesis.

Tumor-associated neutrophils attenuate the immunosensitivity of hepatocellular carcinoma

Tumor-associated neutrophils (TANs) are heterogeneous; thus, their roles in tumor development could vary depending on the cancer type. Here, we showed that TANs affect metabolic dysfunction-associated steatohepatitis hepatocellular carcinoma (MASH-related HCC) more than viral-associated HCC. We attributed this difference to the predominance of SiglecFhi TANs in MASH-related HCC tumors. Linoleic acid and GM-CSF, which are commonly elevated in the MASH-related HCC microenvironment, fostered the development of this c-Myc-driven TAN subset. Through TGFβ secretion, SiglecFhi TANs promoted HCC stemness, proliferation, and migration. Importantly, SiglecFhi TANs supported immune evasion by directly suppressing the antigen presentation machinery of tumor cells. SiglecFhi TAN removal increased the immunogenicity of a MASH-related HCC model and sensitized it to immunotherapy. Likewise, a high SiglecFhi TAN signature was associated with poor prognosis and immunotherapy resistance in HCC patients. Overall, our study highlights the importance of understanding TAN heterogeneity in cancer to improve therapeutic development.

Alcohol-associated liver cancer

Heavy alcohol intake induces a wide spectrum of liver diseases ranging from steatosis, steatohepatitis, cirrhosis, and HCC. Although alcohol consumption is a well-known risk factor for the development, morbidity, and mortality of HCC globally, alcohol-associated hepatocellular carcinoma (A-HCC) is poorly characterized compared to viral hepatitis-associated HCC. Most A-HCCs develop after alcohol-associated cirrhosis (AC), but the direct carcinogenesis from ethanol and its metabolites to A-HCC remains obscure. The differences between A-HCC and HCCs caused by other etiologies have not been well investigated in terms of clinical prognosis, genetic or epigenetic landscape, molecular mechanisms, and heterogeneity. Moreover, there is a huge gap between basic research and clinical practice due to the lack of preclinical models of A-HCC. In the current review, we discuss the pathogenesis, heterogeneity, preclinical approaches, epigenetic, and genetic profiles of A-HCC, and discuss the current insights into and the prospects for future research on A-HCC. The potential effect of alcohol on cholangiocarcinoma and liver metastasis is also discussed.

GD-Net: An Integrated Multimodal Information Model Based on Deep Learning for Cancer Outcome Prediction and Informative Feature Selection

Multimodal information provides valuable resources for cancer prognosis and survival prediction. However, the computational integration of this heterogeneous data information poses significant challenges due to the complex interactions between molecules from different biological modalities and the limited sample size. Here, we introduce GD-Net, a Graph Deep learning algorithm to enhance the accuracy of survival prediction with an average accuracy of 72% by early fusing of multimodal information, which includes an interpretable and lightweight XGBoost module to efficiently extract informative features. First, we applied GD-Net to eight cancer datasets and achieved superior performance compared to benchmarking methods, with an average 7.9% higher C-index value. The ablation experiments strongly supported that multi-modal integration could significantly improve accuracy over the single-modality model. In the deep case study of liver cancer, 319 differential genes, 15 differential miRNAs and 155 methylated differential genes based on the predicted risk subgroups are identified as the informative features, and then we have statistically and biologically validated the efficacy of these key molecules in internal and external test datasets. The comprehensive independent validations demonstrated that GD-Net is accurate and competitive in predicting different cancer outcomes in real-time, and it is an effective tool for identifying new multimodal prognosis biomarkers.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Network pharmacology and bioinformatic integrative analysis reveals candidate gene targets and potential therapeutic of East Kalimantan propolis against hepatocellular carcinoma

Introduction

Hepatocellular Carcinoma (HCC) is commonly treated with surgery, liver transplantation, and chemotherapy, but recurrence and metastasis remain challenges. Natural complementary therapies like propolis, known for its hepatoprotective properties, are gaining interest due to limited efficacy and toxicity of conventional chemotherapy. This study aims to identify core targets for HCC, assess the therapeutic potential of East Kalimantan propolis (EKP) from stingless bees, and analyze the molecular interactions.

Methods

EKP compounds were analyzed using target prediction tools related to HCC, alongside clinical data from the Gene Expression Omnibus (GEO) database, to identify overlapping genes with clinical relevance. The selected genes were then subjected to protein-protein interaction (PPI), GO and KEGG enrichment, immunohistochemical comparison and survival analysis to identify potential core targets and related pathways for HCC therapy. Furthermore, molecular docking and dynamics were conducted to verify the molecular interactions and stability of EKP compounds with targets.

Results

108 genes have been selected as HCC potential targets, which mostly associated with MicroRNAs in cancer, chemical carcinogenesis, and viral carcinogenesis pathways. These targets were obtained by overlapping genes from GEO clinical databases and target predictors. PPI network analysis revealed 4 main targets of propolis in HCC. Furthermore, differential expression genes, survival analysis, and Immunohistochemical analysis from databases suggested that AKR1C3 and MAPK1 promote HCC progression and shorten survival rate of HCC patients. Molecular docking and dynamic studies confirmed strong binding affinity and stability of Baicalein, Chrysin, Quercetin, and Myricetin with receptor targets within simulation time.

Conclusions

This study provides insight into the mechanism of action of EKP on HCC and identifies AKR1C3 and MAPK1 as candidate target treatments for future drug development.

Integration of epigenomic and transcriptomic profiling uncovers EZH2 target genes linked to cysteine metabolism in hepatocellular carcinoma

Enhancer of zeste homolog 2 (EZH2), a key protein implicated in various cancers including hepatocellular carcinoma (HCC), is recognized for its association with epigenetic dysregulation and pathogenesis. Despite clinical explorations into EZH2-targeting therapies, the mechanisms underlying its role in gene suppression in HCC have remained largely unexplored. Here, we integrate epigenomic and transcriptomic analyses to uncover the transcriptional landscape modulated by selective EZH2 inhibition in HCC. By reanalyzing transcriptomic data of HCC patients, we demonstrate that EZH2 overexpression correlates with poor patient survival. Treatment with the EZH2 inhibitor tazemetostat restored expression of genes involved in cysteine-methionine metabolism and lipid homeostasis, while suppressing angiogenesis and oxidative stress-related genes. Mechanistically, we demonstrate EZH2-mediated H3K27me3 enrichment at cis-regulatory elements of transsulfuration pathway genes, which is reversed upon inhibition, leading to increased chromatin accessibility. Among 16 EZH2-targeted candidate genes, BHMT and CDO1 were notably correlated with poor HCC prognosis. Tazemetostat treatment of HCC cells increased BHMT and CDO1 expression while reducing levels of ferroptosis markers FSP1, NFS1, and SLC7A11. Functionally, EZH2 inhibition dose-dependently reduced cell viability and increased lipid peroxidation in HCC cells. Our findings reveal a novel epigenetic mechanism controlling lipid peroxidation and ferroptosis susceptibility in HCC, providing a rationale for exploring EZH2-targeted therapies in this malignancy.

DNA methylation biomarker panels for differentiating various liver adenocarcinomas, including hepatocellular carcinoma, cholangiocarcinoma, colorectal liver metastases and pancreatic adenocarcinoma liver metastases

BACKGROUND

DNA methylation biomarkers are one of the most promising tools for the diagnosis and differentiation of adenocarcinomas of the liver, which are among the most common malignancies worldwide. Their differentiation is important because of the different prognoses and treatment options. This study aimed to validate previously identified DNA methylation biomarkers that successfully differentiate between liver adenocarcinomas, including the two most common primary liver cancers, hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), as well as two common metastatic liver cancers, colorectal liver metastases (CRLM) and pancreatic ductal adenocarcinoma liver metastases (PCLM), and translate them to the methylation-sensitive high-resolution melting (MS-HRM) and digital PCR (dPCR) platforms.

METHODS

Our study included a cohort of 149 formalin-fixed, paraffin-embedded tissue samples, including 19 CRLMs, 10 PCLMs, 15 HCCs, 15 CCAs, 15 colorectal adenocarcinomas (CRCs), 15 pancreatic ductal adenocarcinomas (PDACs) and their paired normal tissue samples. The methylation status of the samples was experimentally determined by MS-HRM and methylation-specific dPCR. Previously determined methylation threshold were adjusted according to dPCR data and applied to the same DNA methylation array datasets (provided by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)) used to originally identify the biomarkers for the included cancer types and additional CRLM projects. The sensitivities, specificities and diagnostic accuracies of the panels for individual cancer types were calculated.

RESULTS

In the dPCR experiment, the DNA methylation panels identified HCC, CCA, CRC, PDAC, CRLM and PCLM with sensitivities of 100%, 66.7%, 100%, 86.7%, 94.7% and 80%, respectively. The panels differentiate between HCC, CCA, CRLM, PCLM and healthy liver tissue with specificities of 100%, 100%, 97.1% and 94.9% and with diagnostic accuracies of 100%, 94%, 97% and 93%, respectively. Reevaluation of the same bioinformatic data with new additional CRLM projects demonstrated that the lower dPCR methylation threshold still effectively differentiates between the included cancer types. The bioinformatic data achieved sensitivities for HCC, CCA, CRC, PDAC, CRLM and PCLM of 88%, 64%, 97.4%, 75.5%, 80% and 84.6%, respectively. Specificities between HCC, CCA, CRLM, PCLM and healthy liver tissue were 98%, 93%, 86.6% and 98.2% and the diagnostic accuracies were 94%, 91%, 86% and 98%, respectively. Moreover, we confirmed that the methylation of the investigated promoters is preserved from primary CRC and PDAC to their liver metastases.

CONCLUSIONS

The cancer-specific methylation biomarker panels exhibit high sensitivities, specificities and diagnostic accuracies and enable differentiation between primary and metastatic adenocarcinomas of the liver using methylation-specific dPCR. High concordance was achieved between MS-HRM, dPCR and bioinformatic data, demonstrating the successful translation of bioinformatically identified methylation biomarkers from the Illumina Infinium HumanMethylation450 BeadChip (HM450) and lllumina MethylationEPIC BeadChip (EPIC) platforms to the simpler MS-HRM and dPCR platforms.

Comprehensive review and updated analysis of DNA methylation in hepatocellular carcinoma: From basic research to clinical application

Hepatocellular carcinoma (HCC) is a primary malignant tumour, ranking second in global mortality rates and posing significant health threats. Epigenetic alterations, particularly DNA methylation, have emerged as pivotal factors associated with HCC diagnosis, therapy, prognosis and malignant progression. However, a comprehensive analysis of the DNA methylation mechanism driving HCC progression and its potential as a therapeutic biomarker remains lacking. This review attempts to comprehensively summarise various aspects of DNA methylation, such as its mechanism, detection methods and biomarkers aiding in HCC diagnosis, treatment and prognostic assessment of HCC. It also explores the role of DNA methylation in regulating HCC's malignant progression and sorafenib resistance, alongside elaborating the therapeutic effects of DNA methyltransferase inhibitors on HCC. A detailed examination of these aspects underscores the significant research on DNA methylation in tumour cells to elucidate malignant progression mechanisms, identify diagnostic markers and develop new tumour-specific inhibitors for HCC. KEY POINTS: A comprehensive summary of various aspects of DNA methylation, such as its mechanism, detection methods and biomarkers aiding in diagnosis and treatment. The role of DNA methylation in regulating hepatocellular carcinoma's (HCC) malignant progression and sorafenib resistance, alongside elaborating therapeutic effects of DNA methyltransferase inhibitors. Deep research on DNA methylation is critical for discovering novel tumour-specific inhibitors for HCC.

Comprehensive in silico CpG methylation analysis in hepatocellular carcinoma identifies tissue- and tumor-type specific marks disconnected from gene expression

DNA methylation is crucial for chromatin structure, transcription regulation and genome stability, defining cellular identity. Aberrant hypermethylation of CpG-rich regions is common in cancer, influencing gene expression. However, the specific contributions of individual epigenetic modifications to tumorigenesis remain under investigation. In hepatocellular carcinoma (HCC), DNA methylation alterations are documented as in other tumor types. We aimed to identify hypermethylated CpGs in HCC, assess their specificity across other tumor types, and investigate their impact on gene expression. To this end, public methylomes from HCC, other liver diseases, and 27 tumor types as well as expression data from TCGA-LIHC and GTEx were analyzed. This study identified 39 CpG sites that were hypermethylated in HCC compared to control liver tissue, and were located within promoter, gene bodies, and intergenic CpG islands. Notably, these CpGs were predominantly unmethylated in healthy liver tissue and other normal tissues. Comparative analysis with 27 other tumors revealed both common and HCC-specific hypermethylated CpGs. Interestingly, the HCC-hypermethylated genes showed minimal expression in the different healthy tissues, with marginal changes in the level of expression in the corresponding tumors. These findings confirm previous evidence on the limited influence of DNA hypermethylation on gene expression regulation in cancer. It also highlights the existence of mechanisms that allow the selection of tissue-specific methylation marks in normally unexpressed genes during carcinogenesis. Overall, our study contributes to demonstrate the complexity of cancer epigenetics, emphasizing the need of better understanding the interplay between DNA methylation, gene expression dynamics, and tumorigenesis.

Oncogenic role of PMEPA1 and its association with immune exhaustion and TGF-β activation in HCC

Background & Aims

Transforming growth factor β (TGF-β) plays an oncogenic role in advanced cancer by promoting cell proliferation, metastasis and immunosuppression. PMEPA1 (prostate transmembrane protein androgen induced 1) has been shown to promote TGF-β oncogenic effects in other tumour types. Thus, we aimed to explore the role of PMEPA1 in hepatocellular carcinoma (HCC).

Methods

We analysed 1,097 tumours from patients with HCC, including discovery (n = 228) and validation (n = 361) cohorts with genomic and clinicopathological data. PMEPA1 levels were assessed by qPCR (n = 228), gene expression data (n = 869) and at the single-cell level (n = 54). Genetically engineered mouse models overexpressing MYC+PMEPA1 compared to MYC were generated and molecular analyses were performed on the HCCs obtained.

Results

PMEPA1 was overexpressed in 18% of HCC samples (fold-change >2; n = 201/1,097), a feature associated with TGF-β signalling activation (p <0.05) and absence of gene body hypomethylation (p <0.01). HCCs showing both TGF-β signalling and high PMEPA1 levels (12% of cases) were linked to immune exhaustion, late TGF-β activation, aggressiveness and higher recurrence rates after resection, in contrast to HCCs with only TGF-β signalling (8%) or PMEPA1 overexpression (9%). Single-cell RNA sequencing analysis identified PMEPA1 expression in HCC and stromal cells. PMEPA1-expressing tumoural cells were predicted to interact with CD4+ regulatory T cells and CD4+ CXCL13+ and CD8+ exhausted T cells. In vivo, overexpression of MYC+PMEPA1 led to HCC development in ∼60% of mice and a decreased survival compared to mice overexpressing MYC alone (p = 0.014). MYC+PMEPA1 tumours were enriched in TGF-β signalling, paralleling our human data.

Conclusions

In human HCC, PMEPA1 upregulation is linked to TGF-β activation, immune exhaustion, and an aggressive phenotype. Overexpression of PMEPA1+MYC led to tumoural development in vivo, demonstrating the oncogenic role of PMEPA1 in HCC for the first time.

Impact and implications

PMEPA1 can enhance the tumour-promoting effects of TGF-β in cancer. In this study, we demonstrate that PMEPA1 is highly expressed in ∼18% of patients with hepatocellular carcinoma (HCC), a feature associated with poor prognosis, TGF-β activation and exhaustion of immune cells. Similarly, in mouse models, PMEPA1 overexpression promotes HCC development, which demonstrates its oncogenic role. The identification of PMEPA1 as oncogenic driver in HCC and its role in immune exhaustion and poor clinical outcomes enhances our understanding of HCC pathogenesis and opens new avenues for targeted therapeutic interventions.

Deciphering the multifaceted role of microRNAs in hepatocellular carcinoma: Integrating literature review and bioinformatics analysis for therapeutic insights

Hepatocellular carcinoma (HCC) poses a significant global health challenge, necessitating innovative therapeutic strategies. MicroRNAs (miRNAs) have emerged as pivotal regulators of HCC pathogenesis, influencing key processes such as self-renewal, angiogenesis, glycolysis, autophagy, and metastasis. This article integrates findings from a comprehensive literature review and bioinformatics analysis to elucidate the role of miRNAs in HCC. We discuss how dysregulation of miRNAs can drive HCC initiation, progression, and metastasis by modulating various signaling pathways and target genes. Moreover, leveraging high-throughput technology and bioinformatics tools, we identify key miRNAs involved in multiple cancer hallmarks, offering insights into potential combinatorial therapeutic strategies. Through our analysis considering p-values and signaling pathways associated with key features, we unveil miRNAs with simultaneous roles across critical cancer characteristics, providing a basis for the development of high-performance biomarkers. The microRNAs, miR-34a-5p, miR-373-3p, miR-21-5p, miR-214-5p, miR-195-5p, miR-139-5p were identified to be shared microRNAs in stemness, angiogenesis, glycolysis, autophagy, EMT, and metastasis of HCC. However, challenges such as miRNA stability and delivery hinder the translation of miRNA-based therapeutics into clinical practice. This review underscores the importance of further research to overcome existing barriers and realize the full potential of miRNA-based interventions for HCC management.

ACSL6-activated IL-18R1-NF-κB promotes IL-18-mediated tumor immune evasion and tumor progression

Aberrant activation of IL-18 signaling regulates tumor immune evasion and progression. However, the underlying mechanism remains unclear. Here, we report that long-chain acyl-CoA synthase 6 (ACSL6) is highly expressed in liver cancer and correlated with poor prognosis. ACSL6 promotes tumor growth, metastasis, and immune evasion mediated by IL-18, independent of its metabolic enzyme activity. Mechanistically, upon IL-18 stimulation, ACSL6 is phosphorylated by ERK2 at S674 and recruits IL-18RAP to interact with IL-18R1, thereby reinforcing the IL-18R1-IL-18RAP heterodimer and triggering NF-κB-dependent gene expression to facilitate tumor development. Furthermore, the up-regulation of CXCL1 and CXCL5 by ACSL6 promotes tumor-associated neutrophil and tumor-associated macrophage recruitment, thereby inhibiting cytotoxic CD8+ T cell infiltration. Ablation or S674A mutation of ACSL6 potentiated anti-PD-1 therapeutic efficacy by increasing the effector activity of intertumoral CD8+ T cells. We revealed that ACSL6 is a potential adaptor that activates IL-18-NF-κB axis-mediated tumor immune evasion and provides valuable insights for developing effective immunotherapy strategies for cancer.

Biomarkers for diagnosis and therapeutic options in hepatocellular carcinoma

Liver cancer is a global health challenge, causing a significant social-economic burden. Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer, which is highly heterogeneous in terms of molecular and cellular signatures. Early-stage or small tumors are typically treated with surgery or ablation. Currently, chemotherapies and immunotherapies are the best treatments for unresectable tumors or advanced HCC. However, drug response and acquired resistance are not predictable with the existing systematic guidelines regarding mutation patterns and molecular biomarkers, resulting in sub-optimal treatment outcomes for many patients with atypical molecular profiles. With advanced technological platforms, valuable information such as tumor genetic alterations, epigenetic data, and tumor microenvironments can be obtained from liquid biopsy. The inter- and intra-tumoral heterogeneity of HCC are illustrated, and these collective data provide solid evidence in the decision-making process of treatment regimens. This article reviews the current understanding of HCC detection methods and aims to update the development of HCC surveillance using liquid biopsy. Recent critical findings on the molecular basis, epigenetic profiles, circulating tumor cells, circulating DNAs, and omics studies are elaborated for HCC diagnosis. Besides, biomarkers related to the choice of therapeutic options are discussed. Some notable recent clinical trials working on targeted therapies are also highlighted. Insights are provided to translate the knowledge into potential biomarkers for detection and diagnosis, prognosis, treatment response, and drug resistance indicators in clinical practice.

Role of Epigenetic Factors in Determining the Biological Behavior and Prognosis of Hepatocellular Carcinoma

BACKGROUND

The current study's objective is to evaluate the molecular genetic mechanisms influencing the biological behavior of hepatocellular carcinoma (HCC) by analyzing the transcriptomic and epigenetic signatures of the tumors.

METHODS

Transcriptomic data were downloaded from the NCBI GEO database. We investigated the expression differences between the GSE46444 (48 cirrhotic tissues versus 88 HCC tissues) and GSE63898 (168 cirrhotic tissues versus 228 HCC tissues) data sets using GEO2R. Differentially expressed genes were evaluated using GO and KEGG metabolic pathway analysis websites. Whole genome bisulfite sequencing (WGBS) and Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq) data sets (26 HCC tissues versus 26 adjacent non-tumoral tissues) were also downloaded from the NCBI SRA database. These data sets were analyzed using Bismark and QSEA, respectively. The methylation differences between the groups were assessed using functional enrichment analysis.

RESULTS

In the GSE46444 data set, 80 genes were upregulated, and 315 genes were downregulated in the tumor tissue (HCC tissue) compared to the non-tumor cirrhotic tissue. In the GSE63898 data set, 1261 genes were upregulated, and 458 genes were downregulated in the cirrhotic tissue compared to the tumor tissues. WGBS revealed that 20 protein-coding loci were hypermethylated. while the hypomethylated regions were non-protein-coding. The methylated residues of the tumor tissue, non-tumorous cirrhotic tissue, and healthy tissue were comparable. MeDIP-Seq, conducted on tumoral and non-tumoral tissues, identified hypermethylated or hypomethylated areas as protein-coding regions. The functional enrichment analysis indicated that these genes were related to pathways including peroxisome, focal adhesion, mTOR, RAP1, Phospholipase D, Ras, and PI3K/AKT signal transduction.

CONCLUSIONS

The investigation of transcriptomic and epigenetic mechanisms identified several genes significant in the biological behavior of HCC. These genes present potential targets for the development of targeted therapy.

AGXT2 Suppresses the Proliferation and Dissemination of Hepatocellular Carcinoma Cells by Modulating Intracellular Lipid Metabolism

Purpose

Alanine glyoxylate aminotransferase (AGXT) family members are crucial in cancer processes, but their role in hepatocellular carcinoma (HCC) metabolism is unclear. This study investigates AGXT2's function in HCC.

Patients and Methods

AGTX2 expression was studied using bioinformatics, real-time reverse transcriptase-polymerase chain reaction (RT-qPCR), Western blot, and Enzyme-linked immunosorbent assay (ELISA). A lentivirus-induced AGTX2 overexpression cell model was analyzed with RNA sequencing (RNA-seq) and liquid chromatography-mass spectrometry (LC-MS). Cholesterol levels were confirmed by Oil Red O staining. AGTX2 effects were evaluated through cell cycle analysis, wound healing, and transwell migration assays.Tumorigenic effects were observed in NOD-SCID IL2Rγnull (NTG) mice in subcutaneous experiments. Protein interaction was examined through co-immunoprecipitation methods.

Results

We observed a significant reduction in AGXT2 mRNA and protein levels in both HCC tumor tissues and serum samples from patients with liver cancer, which was associated with a worse prognosis. The activation of AGXT2 has been shown to effectively decrease cholesterol levels in liver cancer cells, serving as an antagonist in the cholesterol metabolism pathway. An increase in low density lipoprotein receptor (LDLR) mRNA was noted in cells overexpressing AGXT2, accompanied by a decrease in LDLR protein and an elevation in proprotein convertase subtilisin/kexin type 9 (PCSK9) mRNA and protein levels. Molecular docking and co-immunoprecipitation experiments further elucidated the interaction between AGXT2 and LDLR proteins. AGXT2 was observed to suppress the migratory and invasive capabilities of HCC cells, inducing cell cycle arrest in the G2/M phase. AGXT2 activation inhibited subcutaneous liver cancer tumor growth in NTG mice.

Conclusion

AGXT2 was found to lower cholesterol levels in liver cancer cells, possibly through interactions with the LDLR protein and modulation of PCSK9-mediated LDLR degradation. This mechanism may impede cholesterol transport to liver cancer cells, thereby suppressing their growth and metastasis.

A male mouse model for metabolic dysfunction-associated steatotic liver disease and hepatocellular carcinoma

The lack of an appropriate preclinical model of metabolic dysfunction-associated steatotic liver disease (MASLD) that recapitulates the whole disease spectrum impedes exploration of disease pathophysiology and the development of effective treatment strategies. Here, we develop a mouse model (Streptozotocin with high-fat diet, STZ + HFD) that gradually develops fatty liver, metabolic dysfunction-associated steatohepatitis (MASH), hepatic fibrosis, and hepatocellular carcinoma (HCC) in the context of metabolic dysfunction. The hepatic transcriptomic features of STZ + HFD mice closely reflect those of patients with obesity accompanying type 2 diabetes mellitus, MASH, and MASLD-related HCC. Dietary changes and tirzepatide administration alleviate MASH, hepatic fibrosis, and hepatic tumorigenesis in STZ + HFD mice. In conclusion, a murine model recapitulating the main histopathologic, transcriptomic, and metabolic alterations observed in MASLD patients is successfully established.

Establishment of diagnostic model and identification of diagnostic markers between liver cancer and cirrhosis based on multi-chip and machine learning

OBJECTIVE

Most cases of hepatocellular carcinoma (HCC) arise as a consequence of cirrhosis. In this study, our objective is to construct a comprehensive diagnostic model that investigates the diagnostic markers distinguishing between cirrhosis and HCC.

METHODS

Based on multiple GEO datasets containing cirrhosis and HCC samples, we used lasso regression, random forest (RF)-recursive feature elimination (RFE) and receiver operator characteristic analysis to screen for characteristic genes. Subsequently, we integrated these genes into a multivariable logistic regression model and validated the linear prediction scores in both training and validation cohorts. The ssGSEA algorithm was used to estimate the fraction of infiltrating immune cells in the samples. Finally, molecular typing for patients with cirrhosis was performed using the CCP algorithm.

RESULTS

The study identified 137 differentially expressed genes (DEGs) and selected five significant genes (CXCL14, CAP2, FCN2, CCBE1 and UBE2C) to construct a diagnostic model. In both the training and validation cohorts, the model exhibited an area under the curve (AUC) greater than 0.9 and a kappa value of approximately 0.9. Additionally, the calibration curve demonstrated excellent concordance between observed and predicted incidence rates. Comparatively, HCC displayed overall downregulation of infiltrating immune cells compared to cirrhosis. Notably, CCBE1 showed strong correlations with the tumour immune microenvironment as well as genes associated with cell death and cellular ageing processes. Furthermore, cirrhosis subtypes with high linear predictive scores were enriched in multiple cancer-related pathways.

CONCLUSION

In conclusion, we successfully identified diagnostic markers distinguishing between cirrhosis and hepatocellular carcinoma and developed a novel diagnostic model for discriminating the two conditions. CCBE1 might exert a pivotal role in regulating the tumour microenvironment, cell death and senescence.

Indolent cancer and pattern of progression: Two missing parameters in trial design for hepatology

The indolent and aggressive behaviors of HCC might have a role in clinical trial (CT) results; however, the indolent HCC is less analyzed compared to others cancer. Indolent profile could be characterized as follows: (1) patients with low risk of progression itself due to the HCC molecular profile and/or due to the interaction between cancer cell their microenvironment; (2) patients who achieve objective response or present spontaneous regression; and (3) patients who develop radiological progression with no consequence on either the liver function or general status, and without trigger a change in the tumor stage. Patients with "indolent HCC" generally never develop cancer-related symptoms neither die for HCC-related causes. Thus, we hypothesize that the imbalance in the proportion of "indolent" versus "aggressive HCC" between arms or the underestimation/overestimation of HCC behavior at baseline in single-arm CT could be associated with CT failure or under-overestimation of trial results. The "indolent progression" may also explain the discrepancy between radiological progression-based end points and survival. Moreover, we discuss the related causes that explain the indolent profile of HCC and propose (1) refining the progression-related end point by the pattern of progression to minimize the limitations of the current end points; (2) considering alternative statistical tools for survival analysis such as milestone survival, or restricted mean survival time to capture the value of indolent HCC. According to these considerations, we propose incorporating novel end points into the single arm of phase I/II CT as exploratory analysis or as a secondary end point in phase III CT.

Hepatitis Delta Virus and Hepatocellular Carcinoma

The hepatitis D virus (HDV) is a compact, enveloped, circular RNA virus that relies on hepatitis B virus (HBV) envelope proteins to initiate a primary infection in hepatocytes, assemble, and secrete new virions. Globally, HDV infection affects an estimated 12 million to 72 million people, carrying a significantly elevated risk of developing cirrhosis, liver failure, and hepatocellular carcinoma (HCC) compared to an HBV mono-infection. Furthermore, HDV-associated HCC often manifests at a younger age and exhibits more aggressive characteristics. The intricate mechanisms driving the synergistic carcinogenicity of the HDV and HBV are not fully elucidated but are believed to involve chronic inflammation, immune dysregulation, and the direct oncogenic effects of the HDV. Indeed, recent data highlight that the molecular profile of HCC associated with HDV is unique and distinct from that of HBV-induced HCC. However, the question of whether the HDV is an oncogenic virus remains unanswered. In this review, we comprehensively examined several crucial aspects of the HDV, encompassing its epidemiology, molecular biology, immunology, and the associated risks of liver disease progression and HCC development.

Prognostic effect of DNA methylation of BTG2 gene in Chinese hepatocellular carcinoma

Background

This study aims to develop a prognostic model for overall survival based on potential methylation sites within B-cell translocation gene 2 (BTG2) in Chinese patients with hepatocellular carcinoma (HCC).

Methods

This is a retrospective study. The beta values of nine CpG sites and RSEM normalized count values of BTG2 gene were extracted from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (TCGA-LIHC) dataset, with the beta value representing the methylation level by indicating the ratio of the intensity of the methylated bead type to the combined locus intensity. Pyrosequencing was performed to determine the range of methylation values surrounding cg01798157 site in BTG2 gene. A weighted linear model was developed to predict the overall survival (OS).

Results

The beta value of cg01798157 was significantly negatively associated with the mRNA expression of BTG2 in the TCGA-LIHC dataset (Spearman's rho = -0.5306, P = 2.27 × 10-27). The methylation level of cg01798157 was significantly associated with OS in the cohort of 51 Chinese HCC patients (Hazard ratio = 0.597, 95% CI: 0.434-0.820, P = 0.001). Multivariate Cox regression analysis identified methylation level of cg01798157, cirrhosis, and microvascular invasion as independent prognostic factors. The prognostic efficiency of death risk score was superior to that of cirrhosis or microvascular invasion alone.

Conclusions

The methylation level of cg01798157 in BTG2 may be an epigenetic biomarker in Chinese patients with resectable HCC.

Hepatocellular carcinoma in Peru: A molecular description of an unconventional clinical presentation

INTRODUCTION AND AIM

Hepatocellular carcinoma (HCC) is the third most frequent cancer of digestive tract tumors in Peru, with a high mortality rate of 17.7 per 100,000 inhabitants. A significant number of HCC cases in Peru do not follow the classic clinical epidemiology of the disease described in other parts of the world. Those patients present with a distinct transcriptome profile and a singular tumor process, suggesting a particular type of hepatocarcinogenesis in a portion of the Peruvian population. Our aim was to understand the clinical and biologic involvement of the epigenetic profile (methylation) and gene expression (transcriptome) of HCC in Peruvian patients.

METHODS

HCC and liver transcriptome and DNA methylation profiles were evaluated in 74 Peruvian patients.

RESULTS

When grouped by age, there was greater DNA methylation in younger patients with HCC but no differences with respect to the transcriptomic profile. A high prevalence of the hepatitis B virus (HBV) (>90%) was also observed in the younger patients with HCC. Enrichment analyses in both molecular profiles pinpointed PRC2 as an important molecular effector of that liver tumor process in Peruvian patients.

CONCLUSION

HCC in Peruvian patients has a unique molecular profile, associated with the presence of HBV, as well as overall DNA hypermethylation related to undifferentiated liver cells or cellular reprogramming.

Detection of hepatocellular carcinoma methylation markers in salivary DNA

BACKGROUND

Alterations to DNA methylation have been identified in both hepatocellular carcinoma (HCC) tumor and circulating DNA from affected individuals. These markers have potential utility in HCC screening. Adherence to HCC screening is poor and acceptable HCC screening tests are needed.

METHODS

A feasibility study was performed on a subset of case patients and control subjects from a prior study of risk factors for HCC. Case patients (n=12) included adults aged 47-85 years with a first diagnosis of HCC between 2011 and 2016 and without viral hepatitis. Control subjects (n=12) were matched on age, sex, and state of residence. Participants provided saliva samples for DNA genotyping. Log fold change in salivary DNA methylation at 1359 CpG sites representing 25 candidate genes previously associated with HCC was compared across case patients and control subjects.

RESULTS

The quantity of DNA ranged from 9.65 to 257.79 μg. The purity of DNA isolates was good, with mean OD260/280 ratio of 1.78 (SD: 0.14). Of 25 candidate genes, 16 had at ≥1 CpG site with detectable differences in methylation across HCC case patients and control subjects. Sites differentially methylated in HCC case patients included genes encoding tumor suppressors (PRDM2, RUNX3, p15/16, and RASSF1/5), regulators of cell cycle progression (DAPK1 and TP73), and DNA repair (MGMT and GSTP1). No associations met the significance threshold 3.7 × 10-5 required for multiple comparisons.

CONCLUSIONS

Salivary DNA may be a feasible alternative to blood samples in the era of novel DNA-based screening tests for HCC. The ease of saliva-based testing supports further investigation of its potential.

Study protocol: Identifying transcriptional regulatory alterations of chronic effects of blast and disturbed sleep in United States Veterans

Injury related to blast exposure dramatically rose during post-911 era military conflicts in Iraq and Afghanistan. Mild traumatic brain injury (mTBI) is among the most common injuries following blast, an exposure that may not result in a definitive physiologic marker (e.g., loss of consciousness). Recent research suggests that exposure to low level blasts and, more specifically repetitive blast exposure (RBE), which may be subconcussive in nature, may also impact long term physiologic and psychological outcomes, though findings have been mixed. For military personnel, blast-related injuries often occur in chaotic settings (e.g., combat), which create challenges in the immediate assessment of related-injuries, as well as acute and post-acute sequelae. As such, alternate means of identifying blast-related injuries are needed. Results from previous work suggest that epigenetic markers, such as DNA methylation, may provide a potential stable biomarker of cumulative blast exposure that can persist over time. However, more research regarding blast exposure and associations with short- and long-term sequelae is needed. Here we present the protocol for an observational study that will be completed in two phases: Phase 1 will address blast exposure among Active Duty Personnel and Phase 2 will focus on long term sequelae and biological signatures among Veterans who served in the recent conflicts and were exposed to repeated blast events as part of their military occupation. Phase 2 will be the focus of this paper. We hypothesize that Veterans will exhibit similar differentially methylated regions (DMRs) associated with changes in sleep and other psychological and physical metrics, as observed with Active Duty Personnel. Additional analyses will be conducted to compare DMRs between Phase 1 and 2 cohorts, as well as self-reported psychological and physical symptoms. This comparison between Service Members and Veterans will allow for exploration regarding the natural history of blast exposure in a quasi-longitudinal manner. Findings from this study are expected to provide additional evidence for repetitive blast-related physiologic changes associated with long-term neurobehavioral symptoms. It is expected that findings will provide foundational data for the development of effective interventions following RBE that could lead to improved long-term physical and psychological health.

Association of methylation risk score with incident type 2 diabetes mellitus: A nested case-control study

AIMS

To investigate the association of methylation risk score (MRS) and its interactions with environmental factors with type 2 diabetes mellitus (T2DM) risk.

METHODS

We conducted a nested case-control study with 241 onset cases and 241 matched controls. Conditional logistic regression models were employed to identify risk CpG sites. Simple and weighted MRSs were constructed based on the methylation levels of ATP-binding cassette G1 gene, fat mass and obesity associated gene, potassium voltage-gated channel member 1 gene, and thioredoxin-interacting protein gene previously associated with T2DM to estimate the association of MRS with T2DM risk. Stratified analyses were used to investigate interactions between MRS and environmental factors.

RESULTS

A total of 10 CpG loci were identified from the aforementioned genes to calculate MRS. After controlling for potential confounding factors, taking tertile 1 as reference, the odds ratios (ORs) and 95% confidence intervals (CIs) for T2DM of tertile 3 was 2.39 (1.36-4.20) for simple MRS and 2.59 (1.45-4.63) for weighted MRS. With per SD score increment in MRS, the OR (95% CI) was 1.66 (1.29-2.14) and 1.60 (1.24-2.08) for simple and weighted MRSs, respectively. J-curved associations were observed between both simple and weighted MRSs and T2DM risks. Additionally, multiplication interactions for smoking and hypertension with simple MRS on the risk of T2DM were found, similarly for smoking and obesity with weighted MRS on the risk of T2DM (all Pinteraction  < .05).

CONCLUSION

Elevated simple and weighted MRSs were associated with increased risk of T2DM. Environmental risk factors may influence the association between MRS and T2DM.

Acetyl-CoA synthetase 2 contributes to a better prognosis for liver cancer by switching acetate-glucose metabolism

Acetyl-CoA synthetase 2 (ACSS2)-dependent acetate usage has generally been associated with tumorigenesis and increased malignancy in cancers under nutrient-depleted conditions. However, the nutrient usage and metabolic characteristics of the liver differ from those of other organs; therefore, the mechanism of ACSS2-mediated acetate metabolism may also differ in liver cancer. To elucidate the underlying mechanisms of ACSS2 in liver cancer and acetate metabolism, the relationships between patient acetate uptake and metabolic characteristics and between ACSS2 and tumor malignancies were comprehensively studied in vitro, in vivo and in humans. Clinically, we initially found that ACSS2 expression was decreased in liver cancer patients. Moreover, PET-CT imaging confirmed that lower-grade cancer cells take up more 11C-acetate but less 18F-fluorodeoxyglucose (18F-FDG); however, this trend was reversed in higher-grade cancer. Among liver cancer cells, those with high ACSS2 expression avidly absorbed acetate even in a glucose-sufficient environment, whereas those with low ACSS2 expression did not, thereby showing correlations with their respective ACSS2 expression. Metabolomic isotope tracing in vitro and in vivo revealed greater acetate incorporation, greater lipid anabolic metabolism, and less malignancy in high-ACSS2 tumors. Notably, ACSS2 downregulation in liver cancer cells was associated with increased tumor occurrence in vivo. In human patient cohorts, patients in the low-ACSS2 subgroup exhibited reduced anabolism, increased glycolysis/hypoxia, and poorer prognosis. We demonstrated that acetate uptake by ACSS2 in liver cancer is independent of glucose depletion and contributes to lipid anabolic metabolism and reduced malignancy, thereby leading to a better prognosis for liver cancer patients.

THBS1+ myeloid cells expand in SLD hepatocellular carcinoma and contribute to immunosuppression and unfavorable prognosis through TREM1

Hepatocellular carcinoma (HCC) is an inflammation-associated cancer arising from viral or non-viral etiologies including steatotic liver diseases (SLDs). Expansion of immunosuppressive myeloid cells is a hallmark of inflammation and cancer, but their heterogeneity in HCC is not fully resolved and might underlie immunotherapy resistance. Here, we present a high-resolution atlas of innate immune cells from patients with HCC that unravels an SLD-associated contexture characterized by influx of inflammatory and immunosuppressive myeloid cells, including a discrete population of THBS1+ regulatory myeloid (Mreg) cells expressing monocyte- and neutrophil-affiliated genes. THBS1+ Mreg cells expand in SLD-associated HCC, populate fibrotic lesions, and are associated with poor prognosis. THBS1+ Mreg cells are CD163+ but distinguished from macrophages by high expression of triggering receptor expressed on myeloid cells 1 (TREM1), which contributes to their immunosuppressive activity and promotes HCC tumor growth in vivo. Our data support myeloid subset-targeted immunotherapies to treat HCC.

Tissue of origin prediction for cancer of unknown primary using a targeted methylation sequencing panel

RATIONALE

Cancer of unknown primary (CUP) is a group of rare malignancies with poor prognosis and unidentifiable tissue-of-origin. Distinct DNA methylation patterns in different tissues and cancer types enable the identification of the tissue of origin in CUP patients, which could help risk assessment and guide site-directed therapy.

METHODS

Using genome-wide DNA methylation profile datasets from The Cancer Genome Atlas (TCGA) and machine learning methods, we developed a 200-CpG methylation feature classifier for CUP tissue of origin prediction (MFCUP). MFCUP was further validated with public-available methylation array data of 2977 specimens and targeted methylation sequencing of 78 Formalin-fixed paraffin-embedded (FFPE) samples from a single center.

RESULTS

MFCUP achieved an accuracy of 97.2% in a validation cohort (n = 5923) representing 25 cancer types. When applied to an Infinium 450 K array dataset (n = 1052) and an Infinium EPIC (850 K) array dataset (n = 1925), MFCUP achieved an overall accuracy of 93.4% and 84.8%, respectively. Based on MFCUP, we established a targeted bisulfite sequencing panel and validated it with FFPE sections from 78 patients of 20 cancer types. This methylation sequencing panel correctly identified tissue of origin in 88.5% (69/78) of samples. We also found that the methylation levels of specific CpGs can distinguish one cancer type from others, indicating their potential as biomarkers for cancer diagnosis and screening.

CONCLUSION

Our methylation-based cancer classifier and targeted methylation sequencing panel can predict tissue of origin in diverse cancer types with high accuracy.

Identification of differentially methylated regions associated with both liver fibrosis and hepatocellular carcinoma

BACKGROUND

Liver fibrosis is a major risk factor for hepatocellular carcinoma (HCC). We have previously reported that differentially methylated regions (DMRs) are correlated with the fibrosis stages of metabolic dysfunction-associated steatotic liver disease (MASLD). In this study, the methylation levels of those DMRs in liver fibrosis and subsequent HCC were examined.

METHODS

The methylation levels of DMRs were investigated using alcoholic cirrhosis and HCC (GSE60753). The data of hepatitis C virus-infected cirrhosis and HCC (GSE60753), and two datasets (GSE56588 and GSE89852) were used for replication analyses. The transcriptional analyses were performed using GSE114564, GSE94660, and GSE142530.

RESULTS

Hypomethylated DMR and increased transcriptional level of zinc finger and BTB domain containing 38 (ZBTB38) were observed in HCC. Hypermethylated DMRs, and increased transcriptional levels of forkhead box K1 (FOXK1) and zinc finger CCCH-type containing 3 (ZC3H3) were observed in HCC. The methylation levels of DMR of kazrin, periplakin interacting protein (KAZN) and its expression levels were gradually decreased as cirrhosis progressed to HCC.

CONCLUSIONS

Changes in the methylation and transcriptional levels of ZBTB38, ZC3H3, FOXK1, and KAZN are important for the development of fibrosis and HCC; and are therefore potential therapeutic targets and diagnostic tools for cirrhosis and HCC.

Circulating Tumor DNA Clinical Applications in Hepatocellular Carcinoma: Current Trends and Future Perspectives

BACKGROUND

Globally, liver cancers are the second most lethal malignancy after lung cancer (0.83 million deaths in 2020). Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer and is typically associated with liver fibrosis or cirrhosis. HCC diagnosis relies on histologic examination of surgical specimens or conventional tissue biopsy material. However, standard tissue biopsies are invasive and often do not accurately reflect the tumor heterogeneity. On the other hand, the use of liquid biopsies, represented mainly by circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs), has greatly increased in the past 2 decades. Indeed, liquid biopsies are a noninvasive, repeatable, and sensitive approach to studying tumor biology.

CONTENT

This review describes current clinical applications of ctDNA analysis in the management of patients with chronic liver disease, cirrhosis, and HCC. There is a substantial clinical potential of ctDNA, but interventional studies are still lacking for the moment.

SUMMARY

Detection of ctDNA in both asymptomatic individuals and high-risk patients (with chronic liver disease or cirrhosis) contributes to the early diagnosis of HCC. ctDNA analysis also offer tremendous information on the tumor burden and on the risk of early recurrence. The implementation of ctDNA analysis, in association with classical tumor markers (e.g., alpha-fetoprotein), may improve (a) HCC screening in high-risk patients, (b) stratification of the recurrence risk after surgery, and (c) prognosis evaluation of patients with HCC.

HCC-Related lncRNAs: Roles and Mechanisms

Hepatocellular carcinoma (HCC) presents a significant global health threat, particularly in regions endemic to hepatitis B and C viruses, and because of the ongoing pandemic of obesity causing metabolic-dysfunction-related fatty liver disease (MAFLD), a precursor to HCC. The molecular intricacies of HCC, genetic and epigenetic alterations, and dysregulated signaling pathways facilitate personalized treatment strategies based on molecular profiling. Epigenetic regulation, encompassing DNA methyltion, histone modifications, and noncoding RNAs, functions as a critical layer influencing HCC development. Long noncoding RNAs (lncRNAs) are spotlighted for their diverse roles in gene regulation and their potential as diagnostic and therapeutic tools in cancer. In this review, we explore the pivotal role of lncRNAs in HCC, including MAFLD and viral hepatitis, the most prevalent risk factors for hepatocarcinogenesis. The dysregulation of lncRNAs is implicated in HCC progression by modulating chromatin regulation and transcription, sponging miRNAs, and influencing structural functions. The ongoing studies on lncRNAs contribute to a deeper comprehension of HCC pathogenesis and offer promising routes for precision medicine, highlighting the utility of lncRNAs as early biomarkers, prognostic indicators, and therapeutic targets.

Phytochemicals as Potential Lead Molecules against Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, accounting for 85-90% of liver cancer cases and is a leading cause of cancer-related mortality worldwide. The major risk factors for HCC include hepatitis C and B viral infections, along with chronic liver diseases, such as cirrhosis, fibrosis, and non-alcoholic steatohepatitis associated with metabolic syndrome. Despite the advancements in modern medicine, there is a continuous rise in the annual global incidence rate of HCC, and it is estimated to reach >1 million cases by 2025. Emerging research in phytomedicine and chemotherapy has established the anti-cancer potential of phytochemicals, owing to their diverse biological activities. In this review, we report the major phytochemicals that have been explored in combating hepatocellular carcinoma and possess great potential to be used as an alternative or in conjunction with the existing HCC treatment modalities. An overview of the pre-clinical observations, mechanism of action and molecular targets of some of these phytochemicals is also incorporated.

DNA methylation-activated full-length EMX1 facilitates metastasis through EMX1-EGFR-ERK axis in hepatocellular carcinoma

Altered DNA methylation is a crucial epigenetic event in hepatocellular carcinoma (HCC) development and progression. Through methylation-transcriptomic analysis, we identified a set of sixty potential DNA methylation-based epidriver genes. In this set of genes, we focused on the hypermethylation of EMX1, which is frequently observed in hepatobiliary tumors. Despite of its frequent occurrence, the function of EMX1 remains largely unknown. By utilizing bisulfite-next-generation sequencing, we have detected EMX1 DNA hypermethylation on the gene body, which is positively correlated with EMX1 mRNA expression. Further analysis revealed that EMX1 mRNA terminal exon splicing in HCC generated two protein isoforms: EMX1 full length (EMX1-FL) and alternative terminal exon splicing isoform (EMX1-X1). Cellular functional assays demonstrated that gain-of-function EMX1-FL, but not EMX1-X1, induced HCC cells migration and invasion while silencing EMX1-FL inhibited HCC cells motility. This result was further validated by in vivo tumor metastasis models. Mechanistically, EMX1-FL bound to EGFR promoter, promoting EGFR transcription and activating EGFR-ERK signaling to trigger tumor metastasis. Therefore, EGFR may be a potential therapeutic target for EMX1-high expression HCC. Our work illuminated the crucial role of gene body hypermethylation-activated EMX1-FL in promoting tumorigenesis and metastasis in HCC. These findings pave the way for targeting the EMX1-EGFR axis in HCC tumorigenicity and metastasis.

Benefit and harm of waiting time in liver transplantation for HCC

Liver transplantation is the most successful treatment for limited-stage HCC. The waiting time for liver transplantation (LT) can be a critical factor affecting the oncological prognosis and outcome of patients with HCC. Efficient strategies to optimize waiting time are essential to maximize the benefits of LT and to reduce the harm of delay in transplantation. The ever-increasing demand for donor livers emphasizes the need to improve the organization of the waiting list for transplantation and to optimize organ availability for patients with and without HCC. Current progress in innovations to expand the donor pool includes the implementation of living donor LT and the use of grafts from extended donors. By expanding selection criteria, an increased number of patients are eligible for transplantation, which necessitates criteria to prevent futile transplantations. Thus, the selection criteria for LT have evolved to include not only tumor characteristics but biomarkers as well. Enhancing our understanding of HCC tumor biology through the analysis of subtypes and molecular genetics holds significant promise in advancing the personalized approach for patients. In this review, the effect of waiting time duration on outcome in patients with HCC enlisted for LT is discussed.

Methylomics and cancer: the current state of methylation profiling and marker development for clinical care

Epigenetic modifications have long been recognized as an essential level in transcriptional regulation linking behavior and environmental conditions or stimuli with biological processes and disease development. Among them, methylation is the most abundant of these reversible epigenetic marks, predominantly occurring on DNA, RNA, and histones. Methylation modification is intimately involved in regulating gene transcription and cell differentiation, while aberrant methylation status has been linked with cancer development in several malignancies. Early detection and precise restoration of dysregulated methylation form the basis for several epigenetics-based therapeutic strategies. In this review, we summarize the current basic understanding of the regulation and mechanisms responsible for methylation modification and cover several cutting-edge research techniques for detecting methylation across the genome and transcriptome. We then explore recent advances in clinical diagnostic applications of methylation markers of various cancers and address the current state and future prospects of methylation modifications in therapies for different diseases, especially comparing pharmacological methylase/demethylase inhibitors with the CRISPRoff/on methylation editing systems. This review thus provides a resource for understanding the emerging role of epigenetic methylation in cancer, the use of methylation-based biomarkers in cancer detection, and novel methylation-targeted drugs.

Is Cell-Free DNA Testing in Hepatocellular Carcinoma Ready for Prime Time?

Revamping the current biomarker landscape of hepatocellular carcinoma (HCC) with cell-free DNA (cfDNA) could improve overall outcomes. The use of commercially available cfDNA testing (also known as liquid biopsy) is limited by the low prevalence of targetable mutations and does not have any prognostic or predictive value. Thus, current cfDNA testing cannot be relied upon for perioperative risk stratification (POR), including early detection of recurrence, long-term surveillance, predicting outcomes, and treatment response. Prior evidence on cfDNA mutation profiling (non-specific detection or gene panel testing) suggests that it can be a reliable tool for POR and prognostication, but it still requires significant improvements. cfDNA methylation changes or epigenetic markers have not been explored extensively, but early studies have shown potential for it to be a prognostic biomarker tool. The predictive value of cfDNA (mutations and EM) to assist treatment selection (systemic therapy, immune-checkpoint inhibitor vs. tyrosine kinase inhibitor) and to monitor response to systemic and locoregional therapies should be a future area of focus. We highlighted the unmet needs in the HCC management and the current role of cfDNA testing in HCC in addressing them.

The Current Status of the Liver Liquid Biopsy in MASH Related HCC: Overview and Future Directions

Metabolic dysfunction-associated steatohepatitis (MASH) is one of the major risk factors for chronic liver disease and hepatocellular carcinoma (HCC). The incidence of MASH in Western countries continues to rise, driving HCC as the third cause of cancer-related death worldwide. HCC has become a major global health challenge, partly from the obesity epidemic promoting metabolic cellular disturbances but also from the paucity of biomarkers for its early detection. Over 50% of HCC cases are clinically present at a late stage, where curative measures are no longer beneficial. Currently, there is a paucity of both specific and sensitive biological markers for the early-stage detection of HCC. The search for biological markers in the diagnosis of early HCC in high-risk populations is intense. We described the potential role of surrogates for a liver biopsy in the screening and monitoring of patients at risk for nesting HCC.