Genetic Landscape and Biomarkers of Hepatocellular Carcinoma

Genes of DLK1-DIO3 Locus and miR-379/656 Cluster is a Potential Diagnostic and Prognostic Marker in Patients With Hepatocellular Carcinoma: A Systems Biology Study

Background

Hepatocellular carcinoma is the sixth most common malignancy reported globally. This highlights the need for reliable biomarkers that can be employed for diagnostic and prognostic applications. The present study aimed to classify and characterize the clinical potential of delta like non-canonical Notch ligand 1-type III iodothyronine deiodinase (DLK1-DIO3) and miR-379/656 cluster genes in hepatocellular carcinoma.

Methods

We extensively studied the clinical potential of DLK1-DIO3 genes through a comprehensive systems biology approach and assessed the diagnostic and prognostic potential of the genes associated with the region. Additionally, we have predicted the gene targets of the miR-379/656 cluster associated with the locus and have identified the gene ontology, pathway, and disease associations.

Results

We report this region as a potential biomarker for hepatocellular carcinoma. About thirty clustered miRNAs, a long-non-coding RNA, and two coding genes of the region were underexpressed in tumors. The receiver operating characteristic analysis identified 11 clustered miRNAs with diagnostic potential. Survival analyses identified maternally expressed gene 3 and the miR-379/656 cluster as prognostically significant. Further, the random forest model predicted that the miRNA cluster classifies patients according to Tumor, Node, Metastasis (TNM) staging. Furthermore, overrepresentation analysis identified several key pathways, molecular functions, and biological processes associated with the cluster gene targets.

Conclusion

Our study suggests that DLK1-DIO3 genes, miR-379/656 cluster, and its target gene network might be potential diagnostic and prognostic markers for hepatocellular carcinoma management and therapy.

Unveiling the link between chronic inflammation and cancer

The highly nuanced transition from an inflammatory process to tumorigenesis is of great scientific interest. While it is well known that environmental stimuli can cause inflammation, less is known about the oncogenic modifications that chronic inflammation in the tissue microenvironment can bring about, as well as how these modifications can set off pro-tumorigenic processes. It is clear that no matter where the environmental factors come from, maintaining an inflammatory microenvironment encourages carcinogenesis. In addition to encouraging angiogenesis and metastatic processes, sustaining the survival and proliferation of malignant transformed cells, and possibly altering the efficacy of therapeutic agents, inflammation can negatively regulate the antitumoral adaptive and innate immune responses. Because chronic inflammation has multiple pathways involved in tumorigenesis and metastasis, it has gained recognition as a marker of cancer and a desirable target for cancer therapy. Recent advances in our knowledge of the molecular mechanisms that drive cancer's progression demonstrate that inflammation promotes tumorigenesis and metastasis while suppressing anti-tumor immunity. In many solid tumor types, including breast, lung, and liver cancer, inflammation stimulates the activation of oncogenes and impairs the body's defenses against the tumor. Additionally, it alters the microenvironment of the tumor. As a tactical approach to cancer treatment, these findings have underscored the importance of targeting inflammatory pathways. This review highlights the role of inflammation in cancer development and metastasis, focusing on its impact on tumor progression, immune suppression, and therapy resistance. It examines current anti-inflammatory strategies, including NSAIDs, cytokine modulators, and STAT3 inhibitors, while addressing their potential and limitations. The review emphasizes the need for further research to unravel the complex mechanisms linking inflammation to cancer progression and identify molecular targets for specific cancer subtypes.

Correlation between CTNNB1 mutation status and tumour phenotype in hepatitis B virus-related hepatocellular carcinoma

AIMS

The frequency of CTNNB1 mutation, one of the most frequent genetic events in hepatocellular carcinoma (HCC), is lower in Asian countries and in hepatitis B virus (HBV)-related HCCs. In this study, we evaluated the prevalence and types of CTNNB1-mutation in HBV-related HCC and correlated the molecular status with the histomorphological and immunohistochemical features.

METHODS AND RESULTS

A total of 108 consecutive cases of treatment-naïve, surgically resected HBV-related HCCs were selected. Targeted sequencing for CTNNB1 exons 3, 7 and 8 was performed, and the results were correlated with the expression pattern of glutamine synthetase (GS), nuclear β-catenin expression status and the histomorphological characteristics of the tumour. CTNNB1 mutations were identified in 13% of HBV-related HCCs; of these cases, mutations were found in D32-S37 (7%), T41 (4%) and S45 (2%) of exon 3. None of the HCCs demonstrated alterations in exons 7 and 8. CTNNB1 mutation was strongly associated with diffuse strong GS expression (P < 0.001), nuclear β-catenin expression (P < 0.001) and the classic CTNNB1 morphology (P = 0.038). Diffuse strong GS expression was observed in 78.6% of the CTNNB1-mutated HCCs, and nuclear β-catenin expression was identified in 64.3% of these cases. The classic CTNNB1 morphology was observed in 57% of all CTNNB1-mutated HCCs. Furthermore, programmed death-ligand 1 (PD-L1) was less frequently expressed in HCCs with classic CTNNB1 morphology.

CONCLUSIONS

CTNNB1 mutation was observed in 13% of HBV-related HCCs in this Korean cohort, and was associated with diffuse strong GS expression, nuclear β-catenin expression and classic CTNNB1 morphology.

MASH as an emerging cause of hepatocellular carcinoma: current knowledge and future perspectives

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.

Advances and challenges in molecular understanding, early detection, and targeted treatment of liver cancer

In this review, we explore the application of next-generation sequencing in liver cancer research, highlighting its potential in modern oncology. Liver cancer, particularly hepatocellular carcinoma, is driven by a complex interplay of genetic, epigenetic, and environmental factors. Key genetic alterations, such as mutations in TERT, TP53, and CTNNB1, alongside epigenetic modifications such as DNA methylation and histone remodeling, disrupt regulatory pathways and promote tumorigenesis. Environmental factors, including viral infections, alcohol consumption, and metabolic disorders such as nonalcoholic fatty liver disease, enhance hepatocarcinogenesis. The tumor microenvironment plays a pivotal role in liver cancer progression and therapy resistance, with immune cell infiltration, fibrosis, and angiogenesis supporting cancer cell survival. Advances in immune checkpoint inhibitors and chimeric antigen receptor T-cell therapies have shown potential, but the unique immunosuppressive milieu in liver cancer presents challenges. Dysregulation in pathways such as Wnt/β-catenin underscores the need for targeted therapeutic strategies. Next-generation sequencing is accelerating the identification of genetic and epigenetic alterations, enabling more precise diagnosis and personalized treatment plans. A deeper understanding of these molecular mechanisms is essential for advancing early detection and developing effective therapies against liver cancer.

Adjuvant transarterial chemoembolization in resected macrotrabecular-massive hepatocellular carcinoma (ATAC-MACRO): a multicenter real-world retrospective study

RATIONALE AND OBJECTIVES

The purpose of this study was to demonstrate the impact of postoperative adjuvant transarterial chemoembolization (TACE) on the prognosis of patients with macrotrabecular-massive hepatocellular carcinoma (MTM-HCC).

MATERIALS AND METHODS

This retrospective study used the clinical records of patients with resected MTM-HCC with/without adjuvant TACE at three centers between January 2015 and December 2022. The primary end point was recurrence free survival (RFS). The secondary end points were overall survival (OS) and safety.

RESULTS

A total of 559 eligible patients were classified into the adjuvant TACE group and the observation group. After propensity score matching analysis, both RFS (HR 0.62 [95% CI, 0.48 to 0.80]; P < 0.001) and OS (HR 0.59 [95% CI, 0.42 to 0.84]; P = 0.013) in the adjuvant TACE group were significantly better than the observation group. By Cox regression models, mALBI grade, types of hepatectomy, number, satellite lesion, without adjuvant TACE were identified as independent risk factors for RFS, and mALBI grade, number, maximum tumor size, satellite lesion, microvascular invasion, high AFP level, without adjuvant TACE were identified as independent risk factors for OS. The incidence of surgery-related adverse events (AEs) had no significant difference between the two groups (P = 0.609). The majority of AEs associated with adjuvant TACE were grade I (84.4%), and no treatment-related deaths occurred in either group.

CONCLUSIONS

Adjuvant TACE significantly improved the RFS and OS of patients with resected MTM-HCC with acceptable toxicity.

LCAT deficiency promotes hepatocellular carcinoma progression and lenvatinib resistance by promoting triglyceride catabolism and fatty acid oxidation

Lecithin cholesterol acyltransferase (LCAT), a crucial enzyme in lipid metabolism, plays important yet poorly understood roles in tumours, especially in hepatocellular carcinoma (HCC). In this study, our investigation revealed that LCAT is a key downregulated metabolic gene and an independent risk factor for poor prognosis in patients with HCC. Functional experiments showed that LCAT inhibited HCC cell proliferation, migration and invasion. Mechanistically, LCAT interacts with caveolin-1 (CAV1) to promote the binding of CAV1 to PRKACA and inhibit its phosphorylation, thereby inhibiting triglyceride (TAG) catabolism. On the other hand, LCAT inhibits fatty acid oxidation (FAO) by interacting with CPT1A to promote its ubiquitination and degradation. These events result in an inadequate supply of raw materials and energy and inhibit the malignant behaviours of HCC cells. In addition, LCAT is a reliable predictive biomarker for the efficacy of lenvatinib treatment in HCC patients, and the inhibition of FAO can increase lenvatinib sensitivity in patients with LCATlow HCC. This study revealed that LCAT plays a critical role in the regulation of lipid metabolic reprogramming and is a reliable predictive biomarker for the efficacy of lenvatinib treatment in HCC patients.

Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and distinguishing its subtypes holds significant value for diagnosis, treatment, and the prognosis. Methods: Unsupervised clustering analysis was conducted to classify HCC subtypes. Subtype signature genes were identified using LASSO, SVM, and logistic regression. Survival-related genes were identified using Cox regression, and their expression and function were validated via qPCR and gene interference. GO, KEGG, GSVA, and GSEA were used to determine enriched signaling pathways. ESTIMATE and CIBERSORT were used to calculate the stromal score, tumor purity, and immune cell infiltration. TIDE was employed to predict the patient response to immunotherapy. Finally, drug sensitivity was analyzed using the oncoPredict algorithm. Results: Two HCC subtypes with different gene expression profiles were identified, where subtype S1 exhibited a significantly shorter survival time. A subtype scoring formula and a nomogram were constructed, both of which showed an excellent predictive performance. COL11A1 and ACTL8 were identified as survival-related genes among the signature genes, and the downregulation of COL11A1 could suppress the invasion and migration of HepG2 cells. Subtype S1 was characterized by the upregulation of pathways related to collagen and the extracellular matrix, as well as downregulation associated with the xenobiotic metabolic process and fatty acid degradation. Subtype S1 showed higher stromal scores, immune scores, and ESTIMATE scores and infiltration of macrophages M0 and plasma cells, as well as lower tumor purity and infiltration of NK cells (resting/activated) and resting mast cells. Subtype S2 was more likely to benefit from immunotherapy. Subtype S1 appeared to be more sensitive to BMS-754807, JQ1, and Axitinib, while subtype S2 was more sensitive to SB505124, Pevonedistat, and Tamoxifen. Conclusions: HCC patients can be classified into two subtypes based on their gene expression profiles, which exhibit distinctions in terms of signaling pathways, the immune microenvironment, and drug sensitivity.

Role of immune cell homeostasis in research and treatment response in hepatocellular carcinoma

Introduction Recently, immune cells within the tumor microenvironment (TME) have become crucial in regulating cancer progression and treatment responses. The dynamic interactions between tumors and immune cells are emerging as a promising strategy to activate the host's immune system against various cancers. The development and progression of hepatocellular carcinoma (HCC) involve complex biological processes, with the role of the TME and tumor phenotypes still not fully understood. Therefore, it is essential to investigate the importance of immune cell homeostasis in HCC. Additionally, understanding the molecular mechanisms and biological functions underlying tumor-immune cell interactions is increasingly recognized as vital for improving therapeutic outcomes in clinical settings. Methods A total of 790 HCC samples were selected from public databases and real-world independent clinical cohorts. Machine learning methods, focusing on immune-related indicators, were applied to these samples. The Boruta algorithm was employed to develop an ICI score, which was used to assess patient prognosis and predict responses to immunotherapy. Additionally, a new immune subtype analysis of HCC was performed. Cellular-level experiments confirmed the interaction between TME-related factors and the tumor microenvironment in HCC. To further validate the predictive power of the ICI score, a clinical cohort study was conducted at an independent clinical center. Results By evaluating immune gene expression levels, immune cell abundance, Immunescore, and Stromalscore, we initially identified three distinct immune subtypes of HCC, each showing significant differences in survival rates and heterogeneity. Subsequently, DEGs from 1022 immune subtypes were used to classify HCC samples into three immune genotypes, each characterized by distinct prognosis and tumor immune microenvironment (TIME) profiles. Furthermore, we developed the ICI score, a novel immunophenotyping method for HCC, which revealed significant variations based on gender, stage, progression, and DNA mutation profiles (p < 0.05). The ICI score also effectively predicted responses to immunotherapies, particularly through the chemokine signaling, focal adhesion, and JAK/STAT signaling pathways. Conclusion This research demonstrated that TME and immunophenotyping clusters can enhance prognostic accuracy for HCC patients. The independent prognostic indicators identified underscore the connection between tumor phenotype and the immune environment in HCC.

N6-methyladenosine-modification of USP15 regulates chemotherapy resistance by inhibiting LGALS3 ubiquitin-mediated degradation via AKT/mTOR signaling activation pathway in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is among the most malignant tumors and seriously threatens human health worldwide, and its incidence rate is increasing annually. USP15 is a member of the ubiquitination-specific protease (USP) family, which can regulate protein ubiquitination, thereby affecting their stability, and is dysregulated in many cancers, but its expression and regulatory mechanism in HCC are unclear. The aims of this study were to explore the role and mechanism of USP15 in regulating HCC cell stemness, proliferation, and lenvatinib resistance. Immunohistochemistry and high-throughput sequencing analyses of tumor and adjacent normal tissue samples from 52 patients with HCC were conducted. Functional analyses of immortalized human liver and HCC cell lines were conducted, including quantitative real-time PCR; western blot; plasmid, lentivirus, and siRNA transfection; co-immunoprecipitation; mass spectrometry; MeRIP-qPCR; and ubiquitination, cell growth, colony formation, and spheroid formation assays. HCC tumor growth was also assessed using cell transplantation in nude mice. We found that USP15 is upregulated in HCC and affects patient prognosis. Our results demonstrated that USP15 can increase LGALS3 stability in HCC through deubiquitination modification, and affect the stemness, proliferation, and lenvatinib resistance of HCC cells by activating the AKT/mTOR pathway. USP15 expression levels were positively correlated with HCC cell stemness, proliferation, and lenvatinib resistance. In addition, methyltransferase-like protein 3 (Mettl3) N6-methyladenosine (m6A) modified USP15 to upregulate its levels by increasing its mRNA stability. These findings provide a theoretical basis for the potential discovery of new HCC oncogenes, as well as the identification of effective targets and development of novel anti-HCC drugs and clinical applications.

In Vivo CRISPR Activation Screening Reveals Chromosome 1q Genes VPS72, GBA1, and MRPL9 Drive Hepatocellular Carcinoma

BACKGROUND & AIMS

Hepatocellular carcinoma (HCC) frequently undergoes regional chromosomal amplification, resulting in elevated gene expression levels. We aimed to elucidate the role of these poorly understood genetic changes by using CRISPR activation (CRISPRa) screening in mouse livers to identify which genes within these amplified loci are cancer driver genes.

METHODS

We used data from The Cancer Genome Atlas to identify that frequently copy number-amplified and up-regulated genes all reside on human chromosomes 1q and 8q. We generated CRISPRa screening transposons that contain oncogenic Myc to drive tumor formation. We conducted CRISPRa screens in vivo in the liver to identify tumor driver genes. We extensively validated the findings in separate mice and performed RNA sequencing analysis to explore mechanisms driving tumorigenesis.

RESULTS

We targeted genes that frequently undergo amplification in human HCC using an in vivo CRISPRa screening system in mice, which induced extensive liver tumorigenesis. Human chromosome 1q genes Zbtb7b, Vps72, Gba1, and Mrpl9 emerged as drivers of liver tumorigenesis. In human HCC there is a trend in correlation between levels of MRPL9, VPS72, or GBA1 and poor survival. In validation assays, activation of Vps72, Gba1, or Mrpl9 resulted in extensive liver tumorigenesis and decreased survival in mice. RNA sequencing revealed different mechanisms driving HCC, with Mrpl9 activation altering genes functionally related to mitochondrial function, Vps72 levels altering phospholipid metabolism, and Gba1 activation enhancing endosomal-lysosomal activity, all leading to promotion of cellular proliferation. Analysis of human tumor tissues with high levels of MRPL9, VPS72, or GBA1 revealed congruent results, indicating conserved mechanisms driving HCC.

CONCLUSIONS

This study reveals chromosome 1q genes Vps72, Gba1, and Mrpl9 as drivers of HCC. Future efforts to prevent or treat HCC can focus on these new driver genes.

Miniaturization and characterization of patient derived hepatocellular carcinoma tumor organoid cultures for cancer drug discovery applications

Patient derived tumor organoid (PDTO) models retain the structural, morphological, genetic, and clonal heterogeneity of the original tumors. The ability to efficiently generate, expand, and biobank PDTOs has the potential to make the clinical diversity of cancer accessible for personalized medicine assay guided therapeutic drug selection and drug discovery. We describe the miniaturization and growth in 96- and 384-well formats of a single non-tumor liver and two Hepatocellular carcinoma (HCC) organoids derived from cryopreserved PDTO cells and the application of high content imaging (HCI) to characterize the models and enhance drug sensitivity testing. Non-invasive sequentially acquired transmitted light images showed that seeding cryopreserved cells from non-tumoral and HCC PDTOs into 96- or 384-well plates in reduced growth factor Matrigel (rgf-MG) that were fed with growth medium every 3 days supported organoid growth up to 15 days. The number and sizes of organoids increased with longer times in culture. HCC PDTO's had more heterogeneous morphologies than non-tumor organoids with respect to size, shape, and optical density. Organoids cultured in rgf-MG could be stained in situ with HCI reagents without mechanical, chemical or enzymatic disruption of the hydrogel matrices and quantitative data extracted by image analysis. Hoechst and live/dead reagents provided organoid numbers and viability comparisons. HCC PDTO's stained with phalloidin or immuno-stained with α-tubulin antibodies revealed F-actin and microtubule cytoskeleton organization. HCC PDTO's stained with antibodies to signaling pathway proteins and their phosphorylation status allowed comparisons of relative expression levels and inference of pathway activation. Images of HCC PDTO's exposed to ellipticine showed that drugs penetrate Matrigel hydrogels and accumulate in organoid cells. 9-day 384-well HCC organoid cultures exhibited robust and reproducible growth signals suitable for cancer drug testing. Complimenting cell viability readouts with multiple HCI parameters including morphological features and dead cell staining improved the analysis of drug impact and enhanced the value that could be extracted from these more physiologically relevant three-dimensional HCC organoid cultures.

Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells

Hepatocellular carcinoma (HCC) circulating tumor cells (CTCs) exhibit significant phenotypic heterogeneity and diverse gene expression profiles due to epithelial-mesenchymal transition (EMT). However, current detection methods lack the capacity for simultaneous quantification of multidimensional biomarkers, impeding a comprehensive understanding of tumor biology and dynamic changes. Here, the CTC Digital Simultaneous Cross-dimensional Output and Unified Tracking (d-SCOUT) technology is introduced, which enables simultaneous quantification and detailed interpretation of HCC transcriptional and phenotypic biomarkers. Based on self-developed multi-real-time digital PCR (MRT-dPCR) and algorithms, d-SCOUT allows for the unified quantification of Asialoglycoprotein Receptor (ASGPR), Glypican-3 (GPC-3), and Epithelial Cell Adhesion Molecule (EpCAM) proteins, as well as Programmed Death Ligand 1 (PD-L1), GPC-3, and EpCAM mRNA in HCC CTCs, with good sensitivity (LOD of 3.2 CTCs per mL of blood) and reproducibility (mean %CV = 1.80-6.05%). In a study of 99 clinical samples, molecular signatures derived from HCC CTCs demonstrated strong diagnostic potential (AUC = 0.950, sensitivity = 90.6%, specificity = 87.5%). Importantly, by integrating machine learning, d-SCOUT allows clustering of CTC characteristics at the mRNA and protein levels, mapping normalized heterogeneous 2D molecular profiles to assess HCC metastatic risk. Dynamic digital tracking of eight HCC patients undergoing different treatments visually illustrated the therapeutic effects, validating this technology's capability to quantify the treatment efficacy. CTC d-SCOUT enhances understanding of tumor biology and HCC management.

Current advances in nanoparticle-based approaches for the hepatocellular carcinoma treatment

Hepatocellular carcinoma (HCC) is the most common form of liver (LC) with a high mortality rate, driven by risk factors including viral hepatitis, alcoholic liver disease, and nonalcoholic steatohepatitis. The incident of HCC increases 2-4% of the worldwide population each year which would most certainly exceed one million per year by 2025. Despite advances in our knowledge, 25% of HCC tumors have actionable mutations which demands for innovative treatments strategies. In this perspective, we are providing a comprehensive summary of nanoparticles (NPs) based therapeutic approaches for HCC. We begin with an overview of HCC, concentrating on its pathogenesis, current conventional therapies, and their limitations. Then we delve into the therapeutic application of various nanoparticles (NPs) platforms for HCC, including polymeric micelles, dendrimers, liposomes, solid-lipid nanoparticles, nanostructured lipid carriers, exosomes, niosomes, mesoporous silica nanoparticles, carbon nanotubes. Special attention is given to the application of NPs in photothermal and photodynamic treatment was also investigated, with a focus on their effectiveness in targeted cancer ablation. Additionally, the review discusses recent patents and clinical studies that demonstrate the promise of NPs-based therapies in improving HCC treatment outcomes. This article underscores the potential of NPs based technologies to address the challenges faced by traditional therapies and offers insights into future directions for HCC management.

"Update on pediatric primary liver tumors"

Liver masses are common in children, however primary malignant neoplasms are rare, representing only 1% of all pediatric cancers. Hepatocellular neoplasms are the most common primary liver malignancies and hepatoblastoma (HB) is the most frequently diagnosed. The incidence of HB, which is increasing, is approximately of 2 cases per million in the United States, followed by hepatocellular carcinoma (HCC). Pediatric primary liver tumors of mesenchymal origin are less common, except for benign vascular tumors (hemangiomas). Malignant mesenchymal neoplasms represent approximately 10-15% of all, the most common being embryonal sarcoma and malignant rhabdoid tumor. Malignant vascular tumors are rare, but epithelioid hemangioendothelioma (EHE) and angiosarcoma can be seen in children. The development and adoption of consensus diagnostic, therapeutic and risk-stratifying approaches for pediatric patients with malignant liver tumors has been historically challenged by their rarity and by their diverse clinical and histological appearance. On-going collaborative efforts of international consortia including the Children's Oncology Group (COG) in North America, the German Society of Paediatric Oncology and Haematology (GPOH), the Societe Internationale d' Oncologie Pediatrique Liver Tumor Study Group (SIOPEL) in Europe and the Japanese Liver Tumor group (JPLT), have made significant contributions to understanding the clinical and histopathological features, as well as the underlying biology of pediatric liver tumors, in particular HB. A new classification of pediatric liver tumors drafted at the international consensus meeting held in Los Angeles, has been incorporated in the recent WHO classification and is currently used by the PHITT (Paediatric Hepatic Malignancy International Tumour Trial) and other therapeutic protocols. This manuscript provides an overview of salient diagnostic features and updates in classification and molecular characterization for the most common pediatric primary liver neoplasms. It also includes a brief overview of other less common but relevant tumors, which should be considered in the differential diagnosis.

Lipid Nanovesicle Platforms for Hepatocellular Carcinoma Precision Medicine Therapeutics: Progress and Perspectives

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality globally. HCC is highly heterogenous with diverse etiologies leading to different driver mutations potentiating unique tumor immune microenvironments. Current therapeutic options, including immune checkpoint inhibitors and combinations, have achieved limited objective response rates for the majority of patients. Thus, a precision medicine approach is needed to tailor specific treatment options for molecular subsets of HCC patients. Lipid nanovesicle platforms, either liposome- (synthetic) or extracellular vesicle (natural)-derived present are improved drug delivery vehicles which may be modified to contain specific cargos for targeting specific tumor sites, with a natural affinity for liver with limited toxicity. This mini-review provides updates on the applications of novel lipid nanovesicle-based therapeutics for HCC precision medicine and the challenges associated with translating this therapeutic subclass from preclinical models to the clinic.

Differences between hepatocellular carcinoma caused by alcohol and other aetiologies

Alcohol-related liver disease is the third cause of hepatocellular carcinoma worldwide and the leading cause in Europe. Additionally, the recent definition of Metabolic dysfunction-Associated Steatotic Liver Disease with increased alcoholic intake will enrich this population with a more nuanced phenotype, reflecting recent epidemiological trends. In these patients, hepatocellular carcinoma diagnosis is often delayed and less frequently detected through screening programs. Moreover, at the time of diagnosis, patients with alcohol-related hepatocellular carcinoma tend to have a poorer general condition, more severely impaired liver function, and a higher prevalence of comorbidities, leading to increased competitive mortality. However, when hepatocellular carcinoma is diagnosed during surveillance programs in patients with alcohol-related liver disease or metabolic dysfunction-Associated steatotic liver disease with increased alcoholic intake, the rate of allocation to first-line curative treatments is high (56%) and comparable to that of patients with virus-related hepatocellular carcinoma. As a consequence, the etiology of the underlying cirrhosis cannot be considered an independent prognostic factor in patients with hepatocellular carcinoma. Instead, prognosis is driven by liver function, general condition, and tumor burden. This underscores the crucial role of early diagnosis through periodic surveillance in patients with Alcohol-related liver disease or Metabolic dysfunction-Associated Steatotic Liver Disease with increased alcoholic intake -related cirrhosis.

Noninvasive identification of proliferative hepatocellular carcinoma on multiphase dynamic CT: quantitative and LI-RADS lexicon-based evaluation

OBJECTIVE

To identify proliferative hepatocellular carcinoma (HCC) preoperatively using quantitative measurements combined with the updated standard 2021 LI-RADS universal lexicon-based qualitative features on multiphase dynamic CT (MDCT).

METHODS

We retrospectively analyzed 273 patients (102 proliferative HCCs) who underwent preoperative MDCT with surgically confirmed HCC in two medical centers. Imaging features were evaluated according to the updated 2021 LI-RADS universal lexicon, and quantitative measurements were analyzed. All MDCT findings and clinical factors were compared. Four predictive models (clinical, CT quantitative-clinical, CT qualitative-clinical, and combinational models) were developed and validated in an external cohort for identifying proliferative HCC. ROC analysis was used to assess model performances. All models were tested in a subgroup of patients with a single lesion ≤ 5 cm (n = 124).

RESULTS

Both the CT quantitative-clinical and CT qualitative-clinical models effectively identified proliferative HCC in the training and external validation cohorts (all AUCs > 0.79). The combinational model, integrating one clinical (AFP ≥ 200 ng/mL), three qualitative (rim arterial phase hyperenhancement (APHE), non-smooth tumor margin, and incomplete or absent capsule), and one quantitative feature (standardized tumor-to-aorta density ratio in portal venous phase ≤ (- 0.13), showed significant improvement in the training cohort (AUC 0.871) and comparable performance in the validation cohort (AUC 0.870). Additionally, AFP ≥ 200 ng/mL and Rim APHE were significantly associated with HCC recurrence (p < 0.05).

CONCLUSIONS

The combinational model, integrating clinical, CT quantitative, and qualitative features, shows potential for the noninvasively preoperative prediction of proliferative HCC. Further validation is needed to establish its broader clinical utility.

KEY POINTS

Question Preoperative identification of proliferative HCC could influence patient treatment and prognosis, yet there is no CT-based universally applicable model to identify this subtype. Findings The updated standard 2021 LI-RADS universal lexicon-based features, in combination with quantitative MDCT measurements, could aid in the noninvasive detection of proliferative HCC. Clinical relevance The updated standard 2021 LI-RADS universal lexicon-based CT qualitative features and quantitative measurements may aid in identifying proliferative HCC and tumor recurrence, offering potential guidance for personalized treatment. Further studies are required to assess their generalizability to different clinical scenarios.

Efficacy and safety of lenvatinib plus gefitinib in lenvatinib-resistant hepatocellular carcinomas: a prospective, single-arm exploratory trial

Lenvatinib, a multi-kinase inhibitor, has been approved as first-line treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is limited. We have shown previously that lenvatinib and epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) combination therapy overcomes lenvatinib resistance in HCC with high level of EGFR expression (EGFRhigh). We present here the results of a single-arm, open-label, exploratory study of lenvatinib plus the EGFR-TKI gefitinib for patients with HCC resistance to lenvatinib (NCT04642547; n = 30). Only patients with EGFRhigh HCC and progressive disease after lenvatinib treatment were recruited in the study. The most frequent adverse events of all grades were fatigue (27 patients; 90%), followed by rash (25 patients; 83.3%), diarrhea (24 patients; 80%), and anorexia (12 patients; 40%). Among 30 patients, 9 (30%) achieved a confirmed partial response and 14 (46.7%) had stable disease according to mRECIST criteria. Based on RECIST1.1, 5 (16.7%) achieved a confirmed partial response and 18 (60%) had stable disease. The estimated median progression free survival (PFS) and overall survival (OS) time were 4.4 months (95% CI: 2.5 to 5.9) and13.7 months (95% CI: 9.0 to NA), respectively. The objective response rate (ORR) of the patients in the present study compares very favorable to that seen for the two approved second line treatments for HCC (cabozantinib ORR of 4%; regorafenib ORR of 11%). Given that this combination was well-tolerated, a further clinical study of this combination is warranted.

Integrative multi-omics analysis reveals a novel subtype of hepatocellular carcinoma with biological and clinical relevance

Background

Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and the development of accurate predictive models for prognosis and drug sensitivity remains challenging.

Methods

We integrated laboratory data and public cohorts to conduct a multi-omics analysis of HCC, which included bulk RNA sequencing, proteomic analysis, single-cell RNA sequencing (scRNA-seq), spatial transcriptomics sequencing (ST-seq), and genome sequencing. We constructed a tumor purity (TP) and tumor microenvironment (TME) prognostic risk model. Proteomic analysis validated the TP-TME-related signatures. Joint analysis of scRNA-seq and ST-seq revealed characteristic clusters associated with TP high-risk subtypes, and immunohistochemistry confirmed the expression of key genes. We conducted functional enrichment analysis, transcription factor activity inference, cell-cell interaction, drug efficacy analysis, and mutation information analysis to identify a novel subtype of HCC.

Results

Our analyses constructed a robust HCC prognostic risk prediction model. The patients with TP-TME high-risk subtypes predominantly exhibit hypoxia and activation of the Wnt/beta-catenin, Notch, and TGF-beta signaling pathways. Furthermore, we identified a novel subtype, XPO1+Epithelial. This subtype expresses signatures of the TP risk subtype and aligns with the biological behavior of high-risk patients. Additional analyses revealed that XPO1+Epithelial is influenced primarily by fibroblasts via ligand-receptor interactions, such as FN1-(ITGAV+ITGB1), and constitute a significant component of the TP-TME subtype. Moreover, XPO1+Epithelial interact with monocytes/macrophages, T/NK cells, and endothelial cells through ligand-receptor pairs, including MIF-(CD74+CXCR4), MIF-(CD74+CD44), and VEGFA-VEGFR1R2, respectively, thereby promoting the recruitment of immune-suppressive cells and angiogenesis. The ST-seq cohort treated with Tyrosine Kinase Inhibitors (TKIs) and Programmed Cell Death Protein 1 (PD-1) presented elevated levels of TP and TME risk subtype signature genes, as well as XPO1+Epithelial, T-cell, and endothelial cell infiltration in the treatment response group. Drug sensitivity analyses indicated that TP-TME high-risk subtypes, including sorafenib and pembrolizumab, were associated with sensitivity to multiple drugs. Further exploratory analyses revealed that CTLA4, PDCD1, and the cancer antigens MSLN, MUC1, EPCAM, and PROM1 presented significantly increase expression levels in the high-risk subtype group.

Conclusions

This study constructed a robust prognostic model for HCC and identified novel subgroups at the single-cell level, potentially assisting in the assessment of prognostic risk for HCC patients and facilitating personalized drug therapy.

Deciphering the Prognostic and Therapeutic Value of a Gene Model Associated with Two Aggressive Hepatocellular Carcinoma Phenotypes Using Machine Learning

Background

Macrotrabecular-massive (MTM) and vessels encapsulating tumor clusters (VETC)-hepatocellular carcinoma (HCC) are aggressive histopathological phenotypes with significant prognostic implications. However, the molecular markers associated with MTM-HCC and VETC-HCC and their implications for clinical outcomes and therapeutic strategies remain unclear.

Methods

Utilizing the TCGA-LIHC cohort, we employed machine learning techniques to develop a prognostic risk score based on MTM and VETC-related genes. The performance of the risk score was assessed by investigating various aspects including clinical outcomes, biological pathways, treatment responses, drug sensitivities, tumor microenvironment, and molecular subclasses. To validate the risk score, additional data from the ICGC-JP, GSE14520, GSE104580, GSE109211, and an in-house cohort were collected and analyzed.

Results

The machine learning algorithm established a 4-gene-based risk score. High-risk patients had significantly worse prognosis compared to low-risk patients, with the risk score being associated with malignant progression of HCC. Functionally, the high-risk group exhibited enrichment in tumor proliferation pathways. Additionally, patients in the low-risk group exhibited improved response to TACE and sorafenib treatments compared to the high-risk group. In contrast, the high-risk group exhibited reduced sensitivity to immunotherapy and increased sensitivity to paclitaxel. In the in-house cohort, high-risk patients displayed higher rates of early recurrence, along with an increased frequency of elevated alpha-fetoprotein, microvascular invasion, and aggressive MRI features associated with HCC.

Conclusion

This study has successfully developed a risk score based on MTM and VETC-related genes, providing a promising tool for prognosis prediction and personalized treatment strategies in HCC patients.

Spatially Resolved in vivo CRISPR Screen Sequencing via Perturb-DBiT

Perturb-seq enabled the profiling of transcriptional effects of genetic perturbations in single cells but lacks the ability to examine the impact on tissue environments. We present Perturb-DBiT for simultaneous co-sequencing of spatial transcriptome and guide RNAs (gRNAs) on the same tissue section for in vivo CRISPR screen with genome-scale gRNA libraries, offering a comprehensive understanding of how genetic modifications affect cellular behavior and tissue architecture. This platform supports a variety of delivery vectors, gRNA library sizes, and tissue preparations, along with two distinct gRNA capture methods, making it adaptable to a wide range of experimental setups. In applying Perturb-DBiT, we conducted un-biased knockouts of tens of genes or at genome-wide scale across three cancer models. We mapped all gRNAs in individual colonies and corresponding transcriptomes in a human cancer metastatic colonization model, revealing clonal dynamics and cooperation. We also examined the effect of genetic perturbation on the tumor immune microenvironment in an immune-competent syngeneic model, uncovering differential and synergistic perturbations in promoting immune infiltration or suppression in tumors. Perturb-DBiT allows for simultaneously evaluating the impact of each knockout on tumor initiation, development, metastasis, histopathology, and immune landscape. Ultimately, it not only broadens the scope of genetic inquiry, but also lays the groundwork for developing targeted therapeutic strategies.

Metabolic dysfunction-associated steatotic liver disease: a key factor in hepatocellular carcinoma therapy response

The conceptual evolution of non-alcoholic fatty liver disease (NAFLD) to what, since 2023, is called metabolic dysfunction-associated steatotic liver disease (MASLD) not only represents a change in the classification and definition of the disease but also reflects a broader understanding of this heterogeneous condition, which still with many aspects to refine. Although the definition of NAFLD can be interchanged to a high percentage with the new MASLD concept in different aspects, MASLD has been proposed as a relevant factor that influences the response to new immunotherapeutic treatments in the management of MASLD-related hepatocellular carcinoma (HCC), compared to HCC of other etiologies. This indicates that the etiology of HCC plays a relevant role in the prognosis, highlighting the urgency of evaluating treatment regimens for this subgroup of patients in upcoming clinical trials. A better understanding of the pathophysiology of MASLD generates strategies that not only aid in its management but also provide strategies to directly intervene in the carcinogenesis of HCC.

Compound 4a induces paraptosis in liver cancer through endoplasmic reticulum stress mediated by the calreticulin protein

BACKGROUND AND PURPOSE

Emerging evidence has highlighted that paraptosis may be an effective strategy for treating liver cancer. In our previous studies, Compound 4a induced paraptosis in cancer cells. Here, the characteristics of Compound 4a-induced paraptosis were further revealed and, for the first time, the target and related molecular mechanisms of Compound 4a-induced paraptosis in liver cancer were defined.

EXPERIMENTAL APPROACH

The effects and mechanism of Compound 4a in liver cancer cells were studied in in vitro and in vivo (BALB/c-nude xenograft model) experiments, and the targets of Compound 4a that trigger paraptosis were identified and confirmed via mass spectrometry-based drug affinity responsive target stability (DARTS) analyses, siRNA experiments and a cellular thermal shift assay (CETSA). The function and distribution of calreticulin (CRT) protein were detected via Cal-520 AM and immunofluorescence staining, respectively.

KEY RESULTS

Compound 4a effectively induced paraptosis-like cell death in liver cancer, both in vitro and in vivo, and its effect was comparable with the first-line anti-liver cancer drug oxaliplatin but with a higher safety profile. We identified the CRT protein as a target of Compound 4a, which caused cellular endoplasmic reticulum stress (ERS) and calcium overload. CRT knockdown weakened the anti-liver cancer activity of Compound 4a, which may be related to the inhibition of paraptosis.

CONCLUSION

Compound 4a represents a potentially safe and effective agent for the treatment of liver cancer. The characteristics of Compound 4a-triggered paraptosis was clarified and a unique function of CRT in paraptosis was revealed.

The combined signatures of programmed cell death and immune landscape provide a prognostic and therapeutic biomarker in the hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks as the fourth most common cause of mortality globally among all cancer types. Programmed cell death (PCD) is a crucial biological mechanism governing cancer progression, tumor expansion, and metastatic dissemination. Furthermore, the tumor microenvironment (TME) is critical in influencing overall survival (OS) and immune responses to immunotherapeutic interventions. From a multi-omics perspective, the combination of PCD and TME could help to predict the survival of HCC patient survival and immunotherapy response. Our study analyzed variations in the PCD- and TME-classifier used in the classification of HCC patients into two subgroups: PCD high-TME low and PCD low-TME high. In the following step, we compared the tumor somatic mutation (TMB), immunotherapy response, and functional annotation of both groups of patients. Lastly, Western Blot (WB) were conducted. The immunohistochemistry (IHC) was performed on the Human Protein Atlas (HPA). In the PCD-TME classifier, 23 PCD-related genes and three immune cell types were identified. Patients' prognoses and responses to therapy could be accurately predicted using this model. The findings of this study provide a new instrument for the clinical management of HCC patients, and they contribute to the development of accurate treatment strategies for these patients.

Estimating the Number of Polygenic Diseases Among Six Mutually Exclusive Entities of Non-Tumors and Cancer

In the era of precision medicine with increasing amounts of sequenced cancer and non-cancer genomes of different ancestries, we here enumerate the resulting polygenic disease entities. Based on the cell number status, we first identified six fundamental types of polygenic illnesses, five of which are non-cancerous. Like complex, non-tumor disorders, neoplasms normally carry alterations in multiple genes, including in 'Drivers' and 'Passengers'. However, tumors also lack certain genetic alterations/epigenetic changes, recently named 'Goners', which are toxic for the neoplasm and potentially constitute therapeutic targets. Drivers are considered essential for malignant transformation, whereas environmental influences vary considerably among both types of polygenic diseases. For each form, hyper-rare disorders, defined as affecting <1/108 individuals, likely represent the largest number of disease entities. Loss of redundant tumor-suppressor genes exemplifies such a profoundly rare mutational event. For non-tumor, polygenic diseases, pathway-centered taxonomies seem preferable. This classification is not readily feasible in cancer, but the inclusion of Drivers and possibly also of epigenetic changes to the existing nomenclature might serve as initial steps in this direction. Based on the detailed genetic alterations, the number of polygenic diseases is essentially countless, but different forms of nosologies may be used to restrict the number.

Positivity of high-sensitivity HBsAg test, not previous HBV infection, indicates poor prognosis in patients with non-HBV-related HCC

BACKGROUND AND AIMS

The prognostic impact of previous-HBV-infection (pHBV) in non-HBV-related hepatocellular carcinoma (non-HBV-related-HCC) and the prevalence, characteristics and significance of recently developed high-sensitivity HBs antigen positivity (hHBsAg+) in these patients remain unclear. We aimed to close these gaps.

METHODS

We retrospectively screened patients with newly diagnosed non-HBV-related-HCC (standard HBsAg-test negative) at Hokkaido University. Patients with complete clinical information and preserved serum for hHBsAg+ were included. We evaluated the prevalence, characteristics and prognostic impact of pHBV and hHBsAg+ in non-HBV-related-HCC.

RESULTS

A total of 401 non-HBV-related-HCC patients were included (288 with pHBV/113 without pHBV). In non-HBV-related-HCC, pHBV did not affect overall survival (OS). Among non-HBV-related-HCC patients with pHBV, 11.8% (34/288) were hHBsAg+ and had more advanced stages of HCC, higher AFP levels, higher vascular invasion rates, and significantly shorter OS than others (OS: 19.3 vs. 61.4 months, p = 0.012). Comparison of OS among non-HBV-related-HCC patients without pHBV (group 1), those with pHBV and without hHBsAg+ (group 2), and those with pHBV and hHBsAg+ (group 3) revealed significantly shorter OS in group 3 (19.3, 56.6 and 66.4 months in groups 1, 2 and 3, respectively; p = 0.036). Multivariate Cox regression indicated that compared with group 1, only group 3 was significantly and independently associated with shorter OS (HR: 2.044, p = 0.011). Subgroup analysis revealed that this association was particularly evident in non-HBV-related-HCC patients with non-B-non-C aetiology and advanced HCC.

CONCLUSIONS

In non-HBV-related-HCC patients, hHBsAg+, not pHBV, is significantly and independently associated with poor prognosis.

The utility of next-generation sequencing in challenging liver FNA biopsies

BACKGROUND

Fine-needle aspiration (FNA) biopsy is increasingly used for the diagnosis of hepatocellular masses. Because distinguishing well differentiated hepatocellular carcinoma (HCC) from other well differentiated hepatocellular lesions (e.g., large regenerative nodules or focal nodular hyperplasia) requires an assessment of architectural features, this may be challenging on FNA when intact tissue fragments are not sampled. Poorly differentiated HCC and intrahepatic cholangiocarcinoma (ICC) may exhibit overlapping pathologic features. Molecular testing can be helpful, because mutations in TERT promoter and CTNNB1 (β-catenin) are characteristic of HCC, whereas mutations in BAP1, IDH1/IDH2, and PBRM1 may favor ICC. The goal of this study was to assess the role of next-generation sequencing (NGS) in further subclassifying indeterminate liver lesions sampled by FNA.

METHODS

A retrospective review of liver cytology cases with NGS on cell block material was performed. Age, radiologic features, background hepatic disease and treatment, outcome, and NGS data were obtained from the electronic medical record.

RESULTS

Twelve FNA biopsies that had cell blocks from clinically suspected primary hepatic masses were identified. The presence of a TERT promoter mutation supported a diagnosis of HCC for one well differentiated neoplasm. For three patients, the presence of mutations, such as IDH1, CDKN2A/CDKN2B, and BRAF, supported a diagnosis of ICC. Of the eight poorly differentiated carcinomas, NGS helped refine the diagnosis in six of eight cases, with one HCC, three ICCs, and two that had combined HCC-ICC, with two cases remaining unclassified.

CONCLUSIONS

Molecular diagnostics can be helpful to distinguish HCC and ICC on FNA specimens, although a subset of primary hepatic tumors may remain unclassifiable.

TERT upregulation promotes cell proliferation via degradation of p21 and increases carcinogenic potential

Telomerase reverse transcriptase (TERT) gene aberration is detectable in >80% of cases with hepatocellular carcinoma (HCC). TERT reactivation is essential for cellular immortalization because it stabilizes telomere length, although the role of TERT in hepatocarcinogenesis remains unelucidated. To elucidate the significance of aberrant TERT expression in hepatocytes in inflammation-associated hepatocarcinogenesis, we generated Alb-Cre;TertTg mice, which overexpress TERT in the liver and examined their phenotype during chronic inflammation. Based on transcriptome data from the liver tissue of Alb-Cre;TertTg mice, we examined the role of TERT in hepatocarcinogenesis in vitro. We also evaluated the relationship between TERT and cell-cycle-related molecules, including p21, in HCC samples. The liver tumor development rate was increased by TERT overexpression during chronic inflammation, especially in the absence of p53 function. Gene set enrichment analysis of liver tissues revealed that gene sets related to TNF-NFκB signaling, cell cycle, and apoptosis were upregulated in Alb-Cre;TertTg liver. A luciferase reporter assay and immunoprecipitation revealed that TERT interacted with NFκB p65 and enhanced NFκB promoter activity. On the other hand, TERT formed protein complexes with p21, cyclin A2, and cyclin E and promoted ubiquitin-mediated degradation of p21, specifically in the G1 phase. In the clinical HCC samples, TERT was highly expressed but p21 was conversely downregulated, and TERT expression was associated with the upregulation of molecules related to the cell cycle. Taken together, the aberrant upregulation of TERT increased NFκB promoter activity and promoted cell cycle progression via p21 ubiquitination, leading to hepatocarcinogenesis. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Deep Learning Model for Predicting Proliferative Hepatocellular Carcinoma Using Dynamic Contrast-Enhanced MRI: Implications for Early Recurrence Prediction Following Radical Resection

RATIONALE AND OBJECTIVES

The proliferative nature of hepatocellular carcinoma (HCC) is closely related to early recurrence following radical resection. This study develops and validates a deep learning (DL) prediction model to distinguish between proliferative and non-proliferative HCCs using dynamic contrast-enhanced MRI (DCE-MRI), aiming to refine preoperative assessments and optimize treatment strategies by assessing early recurrence risk.

MATERIALS AND METHODS

In this retrospective study, 355 HCC patients from two Chinese medical centers (April 2018-February 2023) who underwent radical resection were included. Patient data were collected from medical records, imaging databases, and pathology reports. The cohort was divided into a training set (n = 251), an internal test set (n = 62), and external test sets (n = 42). A DL model was developed using DCE-MRI images of primary tumors. Clinical and radiological models were generated from their respective features, and fusion strategies were employed for combined model development. The discriminative abilities of the clinical, radiological, DL, and combined models were extensively analyzed. The performances of these models were evaluated against pathological diagnoses, with independent and fusion DL-based models validated for clinical utility in predicting early recurrence.

RESULTS

The DL model, using DCE-MRI, outperformed clinical and radiological feature-based models in predicting proliferative HCC. The area under the curve (AUC) for the DL model was 0.98, 0.89, and 0.83 in the training, internal validation, and external validation sets, respectively. The AUCs for the combined DL and clinical feature models were 0.99, 0.86, and 0.83 in these sets, while the AUCs for the combined DL, clinical, and radiological model were 0.99, 0.87, and 0.8, respectively. Among models predicting early recurrence, the DL plus clinical features model showed superior performance.

CONCLUSION

The DL-based DCE-MRI model demonstrated robust performance in predicting proliferative HCC and stratifying patient risk for early postoperative recurrence. As a non-invasive tool, it shows promise in enhancing decision-making for individualized HCC management strategies.

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.

Single-cell and bulk transcriptomic datasets enable the development of prognostic models based on dynamic changes in the tumor immune microenvironment in patients with hepatocellular carcinoma and portal vein tumor thrombus

Background

Hepatocellular carcinoma (HCC) patients exhibiting portal vein tumor thrombosis (PVTT) face a high risk of rapid malignant progression and poor outcomes, with this issue being compounded by a lack of effective treatment options. The integration of bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) datasets focused on samples from HCC patients with PVTT has the potential to yield unprecedented insight into the dynamic changes in the tumor microenvironment (TME) and associated immunological characteristics in these patients, providing an invaluable tool for the reliable prediction of disease progression and treatment responses.

Methods

scRNA-seq data from both primary tumor (PT) and PVTT cells were downloaded from the Gene Expression Omnibus (GEO) database, while the International Cancer Genome Consortium (ICGC) and Cancer Genome Atlas (TCGA) databases were used to access bulk RNA-seq datasets. scRNA-seq, clustering, GSVA enrichment, mutational profiling, and predictive immunotherapeutic treatment analyses were conducted using these data with the goal of systematically assessing the heterogeneity of PT and PVTT cells and establishing a model capable of predicting immunotherapeutic and prognostic outcomes in patients with HCC.

Results

These analyses revealed that PVTT cells exhibited patterns of tumor proliferation, stromal activation, and low levels of immune cell infiltration, presenting with immune desert and immune rejection-like phenotypes. PT cells, in contrast, were found to exhibit a pattern of immunoinflammatory activity. Core PVTT-associated genes were clustered into three patterns consistent with the tumor immune rejection and immune desert phenotypes. An established clustering model was capable of predicting tumor inflammatory stage, subtype, TME stromal activity, and patient outcomes. PVTT signature genes were further used to establish a risk model, with the risk scores derived from this model providing a tool to evaluate patient clinicopathological features including clinical stage, tumor differentiation, histological subtype, microsatellite instability status, and tumor mutational burden. These risk scores were also able to serve as an independent predictor of patient survival outcomes, responses to adjuvant chemotherapy, and responses to immunotherapy. In vitro experiments were used to partially validate the biological prediction results.

Conclusion

These results offer new insight into the biological and immunological landscape of PVTT in HCC patients, By utilizing individual patient risk scores, providing an opportunity to guide more effective immunotherapeutic interventional efforts.

The Prognostic Significance of CTSV Expression in Patients with Hepatocellular Carcinoma

Purpose

Cathepsin V (CTSV) is a cysteine protease peptidase, which is typically upregulated in cancer and is associated with various oncogenic processes, such as angiogenesis, proliferation, apoptosis, and invasion. The study explored the role of CTSV in hepatocellular carcinoma (HCC) and its potential as a potential biomarker.

Patients and Methods

This study collected tumor and peritumoral archived specimens from 180 HCC patients who underwent surgical resection at Zhongshan Hospital, Fudan University (Shanghai, China) between 2009 and 2010. We extracted data from the TCGA and GEO databases and conducted differential expression analysis, univariate Cox regression, and Kaplan-Meier analysis. Ultimately, we determined that CTSV may emerge as a potential biomarker. Then, immunohistochemical staining for CTSV was performed on tumors and adjacent tissues of HCC patients, and a Cox proportional hazards model was constructed to evaluate the prognostic significance of CTSV expression levels. Applied functional enrichment analysis to reveal the underlying molecular mechanisms. Utilized ssGSEA enrichment analysis and TIMER2.0 algorithm to explore the correlation between CTSV expression and immune cells in HCC. In vitro and in vivo experiments were conducted using human liver cancer cell lines to further validate the clinical application value of CTSV.

Results

In this study, we observed that CTSV expression was notably elevated in HCC (P < 0.001), and identified a significant association between elevated CTSV expression and reduced overall survival rates in patients. In vitro and in vivo experiments indicated that CTSV knockdown could significantly inhibit the proliferation, migration, and invasion of liver cancer cells, and it was found that the combination of CTSV knockdown with PD-1 inhibitors might enhance the therapeutic effect of PD-1 inhibitors in HCC.

Conclusion

CTSV serves as a standalone negative prognostic indicator and possesses clinical significance in HCC.

Hypoxia-induced DTL promotes the proliferation, metastasis, and sorafenib resistance of hepatocellular carcinoma through ubiquitin-mediated degradation of SLTM and subsequent Notch pathway activation

Denticleless E3 ubiquitin protein ligase homolog (DTL), the substrate receptor of the CRL4A complex, plays a central role in genome stability. Even though the oncogenic function of DTL has been investigated in several cancers, its specific role in hepatocellular carcinoma (HCC) still needs further elucidation. Data from a clinical cohort (n = 209), RNA-sequencing, and public database (TCGA and GEO) were analyzed, indicating that DTL is closely related to patient prognosis and could serve as a promising prognostic indicator in HCC. Functionally, DTL promoted the proliferation, metastasis, and sorafenib resistance of HCC in vitro. In the orthotopic tumor transplantation and tail vein injection model, DTL promoted the growth and metastasis of HCC in vivo. Mechanically, we revealed for the first time that DTL was transcriptionally activated by hypoxia-inducible factor 1α (HIF-1α) under hypoxia and functioned as a downstream effector molecule of HIF-1α. DTL promotes the ubiquitination of SAFB-like transcription modulator (SLTM) and subsequently relieves the transcriptional repression of Notch1. These results suggested that DTL may be a potential biomarker and therapeutic target for HCC.

Tumor-Targeted CO Nanodelivery System Design and Therapy for Hepatocellular Carcinoma

In recent years, carbon monoxide (CO) has garnered increased attention as a novel green therapy for hepatocellular carcinoma (HCC) treatment. However, the CO donor is still limited in clinical application due to its lack of targeted ability and unstable release rate. Here, self-assembled amphiphilic nanomicelles glucose-polyethylene glycol (PEG)-lipoic acid (LA)-Fe2(CO)6 (Glu-Fe2(CO)6) are first designed as a CO donor and synthesized via a chemical method, combining glucose with Fe2(CO)6 through PEG-LA. Some advantages of this tumor-targeted Glu-Fe2(CO)6 delivery system include (I) good water-solubility, (II) the glutathione responsive CO slow release, (III) the active tumor-targeted ability of glucose as targeted ligands, and (IV) outstanding efficacy of antitumor and safety of CO therapy of HCC both in vitro and in vivo. These findings suggest that Glu-Fe2(CO)6 nanomicelles hold promise for enhancing antitumor therapeutic capabilities, presenting a novel tumor-targeted delivery strategy in gas therapy for HCC treatment.

A Gluconeogenesis-Related Genes Model for Predicting Prognosis, Tumor Microenvironment Infiltration, and Drug Sensitivity in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a prevalent malignancy within the digestive system, known for its poor prognosis. Gluconeogenesis, a critical metabolic pathway, is responsible for the synthesis of glucose in the normal liver. This study aimed to examine the role of gluconeogenesis-related genes (GRGs) in HCC and evaluate their impact on the tumor microenvironment infiltration and drug sensitivity in HCC.

Methods

We retrieved gene expression and clinical pathological data of HCC from The Cancer Genome Atlas (TCGA) database. This dataset was utilized to develop a prognosis model. The data from The International Cancer Genome Consortium (ICGC) served as an independent validation cohort. A least absolute shrinkage and selection operator (LASSO) regression analysis was applied to a curated panel of GRGs to construct and validate the predictive model. Furthermore, unsupervised consensus clustering, based on the expression levels of GRGs, categorized HCC patients into distinct subgroups.

Results

A four-gene prognostic model, referred to as GRGs, has been successfully developed with high accuracy and stability for the prediction of HCC patient prognosis. This model enables the stratification of patients into high or low risk groups based on individual risk scores, revealing significant differences in immune infiltration patterns and anti-tumor drug responses. Unsupervised consensus clustering analysis delineated four distinct subgroups of patients, each characterized by a unique prognosis and tumor immune microenvironment (TIME).

Conclusion

This study is the first to develop a prognostic model incorporating 4-GRGs that effectively predicts the prognosis, tumor microenvironment infiltration, and drug sensitivity in HCC patients. The model based on 4 GRGs may contribute to predict the prognosis, immunotherapy and chemotherapy response of HCC patients.

Oncogenic plasmid DNA and liver injury agent dictates liver cancer development in a mouse model

Primary liver cancer is an increasing problem worldwide and is associated with significant mortality. A popular method of modeling liver cancer in mice is plasmid hydrodynamic tail vein injection (HTVI). However, plasmid-HTVI models rarely recapitulate the chronic liver injury which precedes the development of most human liver cancer. We sought to investigate how liver injury using thioacetamide contributes to the pathogenesis and progression of liver cancer in two oncogenic plasmid-HTVI-induced mouse liver cancer models. Fourteen-week-old male mice received double-oncogene plasmid-HTVI (SB/AKT/c-Met and SB/AKT/NRas) and then twice-weekly intraperitoneal injections of thioacetamide for 6 weeks. Liver tissue was examined for histopathological changes, including fibrosis and steatosis. Further characterization of fibrosis and inflammation was performed with immunostaining and real-time quantitative PCR. RNA sequencing with pathway analysis was used to explore novel pathways altered in the cancer models. Hepatocellular and cholangiocellular tumors were observed in mice injected with double-oncogene plasmid-HTVI models (SB/AKT/c-Met and SB/AKT/NRas). Thioacetamide induced mild fibrosis and increased alpha smooth muscle actin-expressing cells. However, the combination of plasmids and thioacetamide did not significantly increase tumor size, but increased multiplicity of small neoplastic lesions. Cancer and/or liver injury up-regulated profibrotic and proinflammatory genes while metabolic pathway genes were mostly down-regulated. We conclude that the liver injury microenvironment can interact with liver cancer and alter its presentation. However, the effects on cancer development vary depending on the genetic drivers with differing active oncogenic pathways. Therefore, the choice of plasmid-HTVI model and injury agent may influence the extent to which injury promotes liver cancer development.

The contribution of genetics and epigenetics to MAFLD susceptibility

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most common liver disease worldwide. The risk of developing MAFLD varies among individuals, due to a combination of environmental inherited and acquired genetic factors. Genome-wide association and next-generation sequencing studies are leading to the discovery of the common and rare genetic determinants of MAFLD. Thanks to the great advances in genomic technologies and bioinformatics analysis, genetic and epigenetic factors involved in the disease can be used to develop genetic risk scores specific for liver-related complications, which can improve risk stratification. Genetic and epigenetic factors lead to the identification of specific sub-phenotypes of MAFLD, and predict the individual response to a pharmacological therapy. Moreover, the variant transcripts and protein themselves represent new therapeutic targets. This review will discuss the current status of research into genetic as well as epigenetic modifiers of MAFLD development and progression.

Impact of anesthesia-related genes on prognosis and tumor microenvironment in hepatocellular carcinoma: A comprehensive analysis

Hepatocellular carcinoma (HCC), renowned for its bleak prognosis and high recurrence rates, necessitates innovative strategies for prognosis assessment and therapeutic intervention. In this pursuit, we systematically investigated the influence of anesthesia-related genes (ANARGs) on HCC outcomes. Leveraging data from The Cancer Genome Atlas (TCGA), our study scrutinized RNA sequencing data and clinical profiles from 374 HCC patients alongside 50 non-tumor liver samples to unravel ANARG expression patterns and their clinical relevance. Employing consensus clustering, we segregated HCC samples into two distinct subtypes based on ANARG profiles, unveiling significant survival disparities between them. Further differential expression analysis pinpointed pivotal genes and pathways distinguishing these subtypes, notably implicating lipid metabolism and the MTOR signaling pathway in HCC pathogenesis. A prognostic model, comprising five key ANARGs (DAGLA, CYP26B, HAVCR, G6PD and AKR1B), exhibited robust predictive capability for patient outcomes, validated across independent patient cohorts. Furthermore, immune infiltration analysis uncovered a nuanced interplay between ANARG expression and the tumor immune microenvironment, spotlighting variations in immune cell infiltration and function across the identified HCC subtypes. This comprehensive analysis underscores not only the prognostic significance of ANARGs in HCC but also their potential to modulate the tumor microenvironment, providing novel insights for tailoring anesthetic management and therapeutic strategies in HCC care. Our findings advocate for a more integrative approach to HCC management, amalgamating molecular profiling with traditional clinical parameters to refine patient stratification and personalize treatment strategies.

Morphomolecular Pathology and Genomic Insights into the Cells of Origin of Cholangiocarcinoma and Combined Hepatocellular-Cholangiocarcinoma

Cholangiocarcinomas are a highly heterogeneous group of malignancies that, despite recent progress in the understanding of their molecular pathogenesis and clinical management, continue to pose a major challenge to public health. The traditional view posits that cholangiocarcinomas derive from the neoplastic transformation of cholangiocytes lining the biliary tree. However, increasing genetic and experimental evidence has recently pointed to a more complex, and nuanced, scenario for the potential cell of origin of cholangiocarcinomas. Hepatocytes as well as hepatic stem/progenitor cells are being considered as additional potential sources, depending on microenvironmental contexts, including liver injury. The hypothesis of potentially diverse cells of origin for cholangiocarcinoma, albeit controversial, is certainly not surprising given the plasticity of the cells populating the liver as well as the existence of liver cancer subtypes with mixed histologic and molecular features. This review carefully examines the current pathologic, genomic, and experimental evidence supporting the existence of multiple cells of origin of liver and biliary tract cancers, with particular focus on cholangiocarcinoma and combined hepatocellular-cholangiocarcinoma.

Identification of two heterogeneous subtypes of hepatocellular carcinoma with distinct pathway activities and clinical outcomes based on gene set variation analysis

Background

High heterogeneity is an essential feature of malignant tumors. This study aims to reveal the drivers of hepatocellular carcinoma heterogeneity for prognostic stratification and to guide individualized treatment.

Methods

Omics data and clinical data for two HCC cohorts were derived from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Atlas (ICGC), respectively. CNV data and methylation data were downloaded from the GSCA database. GSVA was used to estimate the transcriptional activity of KEGG pathways, and consensus clustering was used to categorize the HCC samples. The pRRophetic package was used to predict the sensitivity of samples to anticancer drugs. TIMER, MCPcounter, quanTIseq, and TIDE algorithms were used to assess the components of TME. LASSO and COX analyses were used to establish a prognostic gene signature. The biological role played by genes in HCC cells was confirmed by in vitro experiments.

Results

We classified HCC tissues into two categories based on the activity of prognostic pathways. Among them, the transcriptional profile of cluster A HCC is similar to that of normal tissue, dominated by cancer-suppressive metabolic pathways, and has a better prognosis. In contrast, cluster B HCC is dominated by high proliferative activity and has significant genetic heterogeneity. Meanwhile, cluster B HCC is often poorly differentiated, has a high rate of serum AFP positivity, is prone to microvascular invasion, and has shorter overall survival. In addition, we found that mutations, copy number variations, and aberrant methylation were also crucial drivers of the differences in heterogeneity between the two HCC subtypes. Meanwhile, the TME of the two HCC subtypes is also significantly different, which offers the possibility of precision immunotherapy for HCC patients. Finally, based on the prognostic value of molecular subtypes, we developed a gene signature that could accurately predict patients' OS. The riskscore quantified by the signature could evaluate the heterogeneity of HCC and guide clinical treatment. Finally, we confirmed through in vitro experiments that RFPL4B could promote the progression of Huh7 cells.

Conclusion

The molecular subtypes we identified effectively exposed the heterogeneity of HCC, which is important for discovering new effective therapeutic targets.

Comprehensive molecular classification predicted microenvironment profiles and therapy response for HCC

BACKGROUND AND AIMS

Tumor microenvironment (TME) heterogeneity leads to a discrepancy in survival prognosis and clinical treatment response for patients with HCC. The clinical applications of documented molecular subtypes are constrained by several issues.

APPROACH AND RESULTS

We integrated 3 single-cell data sets to describe the TME landscape and identified 6 prognosis-related cell subclusters. Unsupervised clustering of subcluster-specific markers was performed to generate transcriptomic subtypes. The predictive value of these molecular subtypes for prognosis and treatment response was explored in multiple external HCC cohorts and the Xiangya HCC cohort. TME features were estimated using single-cell immune repertoire sequencing, mass cytometry, and multiplex immunofluorescence. The prognosis-related score was constructed based on a machine-learning algorithm. Comprehensive single-cell analysis described TME heterogeneity in HCC. The 5 transcriptomic subtypes possessed different clinical prognoses, stemness characteristics, immune landscapes, and therapeutic responses. Class 1 exhibited an inflamed phenotype with better clinical outcomes, while classes 2 and 4 were characterized by a lack of T-cell infiltration. Classes 5 and 3 indicated an inhibitory tumor immune microenvironment. Analysis of multiple therapeutic cohorts suggested that classes 5 and 3 were sensitive to immune checkpoint blockade and targeted therapy, whereas classes 1 and 2 were more responsive to transcatheter arterial chemoembolization treatment. Class 4 displayed resistance to all conventional HCC therapies. Four potential therapeutic agents and 4 targets were further identified for high prognosis-related score patients with HCC.

CONCLUSIONS

Our study generated a clinically valid molecular classification to guide precision medicine in patients with HCC.

Unveiling EFNB2 as a Key Player in Sorafenib Resistance: Insights from Bioinformatics Analysis and Functional Validation in Hepatocellular Carcinoma

Sorafenib resistance has become a big hurdle for treating advanced HCC; thus, identifying novel targets to overcome sorafenib resistance is of great importance. Thanks to the massive progress in the sequencing and data analysis, high-throughput screening of novel targets in HCC development has been extensively used in recent years. In present study, we harnessed the public dataset and aimed to identify novel targets related to sorafenib resistance in HCC via bioinformatics analysis and in vitro validation. This study examined three GEO datasets (GSE140202, GSE143233, GSE182593) and identified 20 common DEGs. Functional enrichment analysis suggested these DEGs might play a role in regulating drug resistance pathways. PPI network analysis pinpointed 14 hub genes, with EFNB2 showing high connectivity to other genes. Subsequent in vitro experiments demonstrated that EFNB2 was up-regulated in sorafenib-resistant HCC cells. EFNB2 suppression sensitized HepG2 and Huh7 sorafenib-resistant cells. Furthermore, EFNB2 knockdown increased caspase-3/-7 activities and hindered EMT in sorafenib-resistant HCC cells. Conversely, EFNB2 overexpression promoted sorafenib resistance, decreased caspase-3/-7 activity, and enhanced EMT in HCC cells. Overall, this study identified 14 promising genes potentially linked to sorafenib resistance in HCC, with EFNB2 emerging as a potential contributor to this resistance mechanism.

Multifaceted role of FAM210B in hepatocellular carcinoma: Implications for tumour progression, microenvironment modulation and therapeutic selection

Hepatocellular carcinoma (HCC) is a common and lethal liver cancer characterized by complex aetiology and limited treatment options. FAM210B, implicated in various cancers, is noteworthy for its potential role in the progression and treatment response of HCC. Yet, its expression patterns, functional impacts and correlations with patient outcomes and resistance to therapy are not well understood. We employed a comprehensive methodology to explore the role of FAM210B in HCC, analysing its expression across cancers, subcellular localization and impacts on cell proliferation, invasion, migration, biological enrichment and the immune microenvironment. Additionally, we investigated its expression in single cells, drug sensitivity and relationships with genomic instability, immunotherapy efficacy and key immune checkpoints. While FAM210B expression varied across cancers, there was no notable difference between HCC and normal tissues. Elevated levels of FAM210B were associated with improved survival outcomes. Subcellular analysis located FAM210B in the plasma membrane and cytosol. FAM210B was generally downregulated in HCC, and its suppression significantly enhanced cell proliferation, invasion and migration. Biological enrichment analysis linked FAM210B to metabolic and immune response pathways. Moreover, its expression modified the immune microenvironment of HCC, affecting drug responsiveness and immunotherapy outcomes. High expression levels of FAM202B correlated with increased resistance to sunitinib and enhanced responsiveness to immunotherapy, as evidenced by associations with tumour mutation burden, PDCD1, CTLA4 and TIDE scores. FAM210B exerts a complex influence on HCC, affecting tumour cell behaviour, metabolic pathways, the immune microenvironment and responses to therapy.

Apigenin inhibits tumor angiogenesis by hindering microvesicle biogenesis via ARHGEF1

Extracellular vesicles are essential for intercellular communication and are involved in tumor progression. Inhibiting the direct release of extracellular vesicles seems to be an effective strategy in inhibiting tumor progression, but lacks of investigation. Here, we report a natural flavonoid compound, apigenin, could significantly inhibit the growth of hepatocellular carcinoma by preventing microvesicle secretion. Mechanistically, apigenin primarily targets the guanine nucleotide exchange factor ARHGEF1, inhibiting the activity of small G protein Cdc42, which is essential in regulating the release of microvesicles from tumor cells. In turn, this inhibits tumor angiogenesis related to VEGF90K transported on microvesicles, ultimately impeding tumor progression. Collectively, these findings highlight the therapeutic potential of apigenin and shed light on its anticancer mechanisms through inhibiting microvesicle biogenesis, providing a solid foundation for the refinement and practical application of apigenin.

Cannabidiol reverts the malignant phenotype of hepatocellular carcinoma cells via the GPR55/TP53/MAPK axis

Cannabidiol (CBD) has antioxidant and anti-inflammatory activities. However, the anti-tumor effect of CBD on hepatocellular carcinoma (HCC) remains unclear. Here, we investigated whether CBD displays anti-tumorigenic effects in HCC cells and whether it could reduce tumorigenesis and metastases in vivo. First, this study treated HCC cells with different concentrations of CBD, followed by analyzing the changes in the proliferative, apoptotic, migratory and invasive abilities. The effects of CBD on the growth and metastasis of HCC cells in vivo were verified by tumorigenesis and metastasis assays. Subsequently, the target genes of CBD were predicted through the SwissTarget website and the genes differentially expressed in cells after CBD treatment were analyzed by microarray for intersection. The enrichment of the pathways after CBD treatment was analyzed by KEGG enrichment analysis, followed by western blot validation. Finally, rescue assays were used to validate the functions of genes as well as pathways in the growth and metastasis of HCC cells. A significant weakening of the ability of HCC cells to grow and metastasize in vitro and in vivo was observed upon CBD treatment. Mechanistically, CBD reduced GRP55 expression in HCC cells, along with increased TP53 expression and blocked MAPK signaling activation. In CBD-treated cells, the anti-tumor of HCC cells was restored after overexpression of GRP55 or deletion of TP53. CBD inhibits the MAPK signaling activation and increases the TP53 expression by downregulating GRP55 in HCC cells, thereby suppressing the growth and metastasis of HCC cells.

Developing targeted therapeutics for hepatocellular carcinoma: a critical assessment of promising phase II agents

INTRODUCTION

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the first for primary liver tumors. In recent years greater therapeutic advancement was represented by employment of tyrosine kinase inhibitors (TKIs) either in monotherapy or in combination with immune checkpoint inhibitors (ICIs).

AREAS COVERED

Major attention was given to target therapies in the last couple of years, especially in those currently under phase II trials. Priority was given either to combinations of novel ICI and TKIs or those targeting alternative mutations of major carcinogenic pathways.

EXPERT OPINION

As TKIs are playing a more crucial role in HCC therapeutic strategies, it is fundamental to further expand molecular testing and monitoring of acquired resistances. Despite the recent advancement in both laboratory and clinical studies, further research is necessary to face the discrepancy in clinical practice.

Deciphering KDM8 dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning

Aim: This study investigates the altered expression and CpG methylation patterns of histone demethylase KDM8 in hepatocellular carcinoma (HCC), aiming to uncover insights and promising diagnostics biomarkers.Materials & methods: Leveraging TCGA-LIHC multi-omics data, we employed R/Bioconductor libraries and Cytoscape to analyze and construct a gene correlation network, and LASSO regression to develop an HCC-predictive model.Results: In HCC, KDM8 downregulation is correlated with CpGs hypermethylation. Differential gene correlation analysis unveiled a liver carcinoma-associated network marked by increased cell division and compromised liver-specific functions. The LASSO regression identified a highly accurate HCC prediction signature, prominently featuring CpG methylation at cg02871891.Conclusion: Our study uncovers CpG hypermethylation at cg02871891, possibly influencing KDM8 downregulation in HCC, suggesting these as promising biomarkers and targets.

Changes in Mutations of Cell-Free DNA and Liver Tumor Tissue in Patients with Advanced Hepatocellular Carcinoma before and after Introduction of Lenvatinib

INTRODUCTION

Cell-free DNA (cfDNA) is expected to contribute to the decision for treatment and prediction of effects with minimally invasion. We investigated the correlation between gene mutations before and after lenvatinib (LEN) treatment and its effectiveness, in order to find advanced hepatocellular carcinoma (HCC) patients who would benefit greatly from the therapy.

METHODS

We analyzed cfDNA before and 6-8 weeks after the start of treatment in 20 advanced HCC patients who started LEN. A next-generation sequencer was used for CTNNB1 and TP53. Concerning TERT promoter, -124C>T and -146C>T mutations are researched using digital PCR. In addition, we examined liver tumor biopsy tissues by the same method. Computerized tomography evaluation was performed at 6-8 weeks and 3-4 months to assess the efficacy.

RESULTS

Frequencies of TERT promoter, CTNNB1, and TP53 mutations in pretreatment cfDNA were 45%, 65%, and 65%, but 53%, 41%, and 47% in HCC tissues, respectively. There were no clear correlations between these gene mutations and the disease-suppressing effect or progression-free survival. Overall, there were many cases showing a decrease in mutations after LEN treatment. Integrating the reduction of CTNNB1 and TP53 genetic mutations increased the potential for disease suppression.

CONCLUSION

This study suggests that analysis of cfDNA in advanced HCC patients may be useful for identifying LEN responders and determining therapeutic efficacy. Furthermore, it has potential for selecting responders for other molecular-targeted drugs.