Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma

State-of-the-Art Liver Cancer Organoids: Modeling Cancer Stem Cell Heterogeneity for Personalized Treatment

Liver cancer poses a global health challenge with limited therapeutic options. Notably, the limited success of current therapies in patients with primary liver cancers (PLCs) may be attributed to the high heterogeneity of both hepatocellular carcinoma (HCCs) and intrahepatic cholangiocarcinoma (iCCAs). This heterogeneity evolves over time as tumor-initiating stem cells, or cancer stem cells (CSCs), undergo (epi)genetic alterations or encounter microenvironmental changes within the tumor microenvironment. These modifications enable CSCs to exhibit plasticity, differentiating into various resistant tumor cell types. Addressing this challenge requires urgent efforts to develop personalized treatments guided by biomarkers, with a specific focus on targeting CSCs. The lack of effective precision treatments for PLCs is partly due to the scarcity of ex vivo preclinical models that accurately capture the complexity of CSC-related tumors and can predict therapeutic responses. Fortunately, recent advancements in the establishment of patient-derived liver cancer cell lines and organoids have opened new avenues for precision medicine research. Notably, patient-derived organoid (PDO) cultures have demonstrated self-assembly and self-renewal capabilities, retaining essential characteristics of their respective in vivo tissues, including both inter- and intratumoral heterogeneities. The emergence of PDOs derived from PLCs serves as patient avatars, enabling preclinical investigations for patient stratification, screening of anticancer drugs, efficacy testing, and thereby advancing the field of precision medicine. This review offers a comprehensive summary of the advancements in constructing PLC-derived PDO models. Emphasis is placed on the role of CSCs, which not only contribute significantly to the establishment of PDO cultures but also faithfully capture tumor heterogeneity and the ensuing development of therapy resistance. The exploration of PDOs' benefits in personalized medicine research is undertaken, including a discussion of their limitations, particularly in terms of culture conditions, reproducibility, and scalability.

Comprehensive analysis of protein post-translational modifications reveals PTPN2-STAT1-AOX axis-mediated tumor progression in hepatocellular carcinomas

Hepatocellular carcinoma (HCC) is a common malignant tumor. Although the proteomics of HCC is well studied, the landscape of post-translational modifications (PTMs) in HCC is poorly understood. The PTMs themselves and their crosstalk might be deeply involved in HCC development and progression. Herein, we investigated nine types of PTMs in paired tumor and normal tissues from nine patients with HCC using the label-free quantitative liquid chromatography with tandem mass spectrometry (LC-MS)-based technique. We identified >60,000 modified sites, and found that phosphorylation and ubiquitination were two most frequently changed PTMs between tumor and normal tissues. Crosstalk between malonylation-ubiquitination, phosphorylation-ubiquitination, and succinylation-propionylation were most significant among all PTMs. Further analysis revealed that Thr-160 of CDK2 regulated EZH2 via H3K27me3, and proposed a PTPN2-STAT1-AOX1 axis for HCC development through driver PTM exploration. In conclusion, our study provides a database of multiple PTMs in HCC, which might help to understand the biology of HCC and reveal novel targets for drug development.

Integrated Analysis of Proteome and Transcriptome Profiling Reveals Pan-Cancer-Associated Pathways and Molecular Biomarkers

Understanding dysregulated genes and pathways in cancer is critical for precision oncology. Integrating mass spectrometry-based proteomic data with transcriptomic data presents unique opportunities for systematic analyses of dysregulated genes and pathways in pan-cancer. Here, we compiled a comprehensive set of datasets, encompassing proteomic data from 2404 samples and transcriptomic data from 7752 samples across 13 cancer types. Comparisons between normal or adjacent normal tissues and tumor tissues identified several dysregulated pathways including mRNA splicing, interferon pathway, fatty acid metabolism, and complement coagulation cascade in pan-cancer. Additionally, pan-cancer upregulated and downregulated genes (PCUGs and PCDGs) were also identified. Notably, RRM2 and ADH1B, two genes which belong to PCUGs and PCDGs, respectively, were identified as robust pan-cancer diagnostic biomarkers. TNM stage-based comparisons revealed dysregulated genes and biological pathways involved in cancer progression, among which the dysregulation of complement coagulation cascade and epithelial-mesenchymal transition are frequent in multiple types of cancers. A group of pan-cancer continuously upregulated and downregulated proteins in different tumor stages (PCCUPs and PCCDPs) were identified. We further constructed prognostic risk stratification models for corresponding cancer types based on dysregulated genes, which effectively predict the prognosis for patients with these cancers. Drug prediction based on PCUGs and PCDGs as well as PCCUPs and PCCDPs revealed that small molecule inhibitors targeting CDK, HDAC, MEK, JAK, PI3K, and others might be effective treatments for pan-cancer, thereby supporting drug repurposing. We also developed web tools for cancer diagnosis, pathologic stage assessment, and risk evaluation. Overall, this study highlights the power of combining proteomic and transcriptomic data to identify valuable diagnostic and prognostic markers as well as drug targets and treatments for cancer.

Combining Radioembolization and Immune Checkpoint Inhibitors for the Treatment of Hepatocellular Carcinoma: The Quest for Synergy

Hepatocellular carcinoma is a leading and increasing contributor to cancer-related death worldwide. Recent advancements in both liver-directed therapies in the form of yttrium-90 (90Y) radioembolization (RE) and systemic therapy in the form of immune checkpoint inhibitors (ICI) have expanded treatment options for patients with an otherwise poor prognosis. Despite these gains, ICIs and 90Y-RE each have key limitations with low objective response rates and persistent hazard of out-of-field recurrence, respectively, and overall survival remains low. However, each therapy's strength may mitigate the other's weakness, making them potentially ideal partners for combination treatment strategies. This review discusses the scientific and clinical rationale for combining 90Y-RE with ICIs, highlights early clinical trial data on its safety and effectiveness, and proposes key issues to be addressed in this emerging field. With optimal strategies, combination therapies can potentially result in increasing likelihood of durable and curative outcomes in later stage patients.

Molecular and immune landscape of hepatocellular carcinoma for therapeutic development

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with an estimated 750,000 deaths in 2022. Recent emergence of molecular targeted agents and immune checkpoint inhibitors and their combination therapies have been transforming HCC care, but their prognostic impact in advanced-stage disease remains unsatisfactory. In addition, their application to early-stage disease is still an unmet need. Omics profiling studies have elucidated recurrent and heterogeneously present molecular aberrations involved in pro-cancer tumor (immune) microenvironment that may guide therapeutic strategies. Recurrent aberrations such somatic mutations in TERT promoter and TP53 have been regarded undruggable, but recent studies have suggested that these may serve as new classes of therapeutic targets. HCC markers such as alpha-fetoprotein, glypican-3, and epithelial cell adhesion molecule have also been explored as therapeutic targets. These molecular features may be utilized as biomarkers to guide the application of new approaches as companion biomarkers to maximize therapeutic benefits in patients who are likely to benefit from the therapies, while minimizing unnecessary harm in patients who will not respond. The explosive number of new agents in the pipelines have posed challenges in their clinical testing. Novel clinical trial designs guided by predictive biomarkers have been proposed to enable their efficient and cost-effective evaluation. These new developments collectively facilitate clinical translation of personalized molecular-targeted therapies in HCC and substantially improve prognosis of HCC patients.

Genetic, Epigenetic, and Microenvironmental Drivers of Cholangiocarcinoma

Cholangiocarcinoma (CCA) is an aggressive and heterogeneous malignancy of the biliary tree that carries a poor prognosis. Multiple features at the genetic, epigenetic, and microenvironmental levels have been identified to better characterize CCA carcinogenesis. Genetic alterations, such as mutations in IDH1/2, BAP1, ARID1A, and FGFR2, play significant roles in CCA pathogenesis, with variations across different subtypes, races/ethnicities, and causes. Epigenetic dysregulation, characterized by DNA methylation and histone modifications, further contributes to the complexity of CCA, influencing gene expression and tumor behavior. Furthermore, CCA cells exchange autocrine and paracrine signals with other cancer cells and the infiltrating cell types that populate the microenvironment, including cancer-associated fibroblasts and tumor-associated macrophages, further contributing to an immunosuppressive niche that supports tumorigenesis. This review explores the multifaceted genetic, epigenetic, and microenvironmental drivers of CCA. Understanding these diverse mechanisms is essential for characterizing the complex pathways of CCA carcinogenesis and developing targeted therapies to improve patient outcomes.

Molecular and immune landscape of hepatocellular carcinoma to guide therapeutic decision-making

Liver cancer, primarily HCC, exhibits highly heterogeneous histological and molecular aberrations across tumors and within individual tumor nodules. Such intertumor and intratumor heterogeneities may lead to diversity in the natural history of disease progression and various clinical disparities across the patients. Recently developed multimodality, single-cell, and spatial omics profiling technologies have enabled interrogation of the intertumor/intratumor heterogeneity in the cancer cells and the tumor immune microenvironment. These features may influence the natural history and efficacy of emerging therapies targeting novel molecular and immune pathways, some of which had been deemed undruggable. Thus, comprehensive characterization of the heterogeneities at various levels may facilitate the discovery of biomarkers that enable personalized and rational treatment decisions, and optimize treatment efficacy while minimizing the risk of adverse effects. Such companion biomarkers will also refine HCC treatment algorithms across disease stages for cost-effective patient management by optimizing the allocation of limited medical resources. Despite this promise, the complexity of the intertumor/intratumor heterogeneity and ever-expanding inventory of therapeutic agents and regimens have made clinical evaluation and translation of biomarkers increasingly challenging. To address this issue, novel clinical trial designs have been proposed and incorporated into recent studies. In this review, we discuss the latest findings in the molecular and immune landscape of HCC for their potential and utility as biomarkers, the framework of evaluation and clinical application of predictive/prognostic biomarkers, and ongoing biomarker-guided therapeutic clinical trials. These new developments may revolutionize patient care and substantially impact the still dismal HCC mortality.

A mutational signature and ARID1A mutation associated with outcome in hepatocellular carcinoma

OBJECTIVE

The prognosis of hepatocellular carcinoma (HCC) is poor and there is no stable and reliable molecular biomarker for evaluation. This study attempted to find reliable prognostic markers from tumor mutational profiles.

METHODS

A total of 362 HCC samples with whole-exome sequencing were collected as discovery datasets, and 200 samples with targeted sequencing were used for validation of the relevant results. All HCC samples were obtained from previously published studies. Bayesian non-negative matrix factorization was used to extract mutational signatures, and multivariate Cox regression models were utilized to identify the prognostic role of mutational factors. Gene set enrichment analysis was employed to discover potential signaling pathways associated with specific mutational groups.

RESULTS

In the HCC discovery dataset, a total of four mutational signatures (i.e., signatures 4, 6, 16, and 22) were extracted, of which signature 16 characterized by T>C mutations was observed to be associated with favorable HCC prognosis, and this correlation was also found in the validation dataset. Further analysis showed that patients with ARID1A mutations exhibited inferior survival outcomes in both discovery and validation datasets. Mechanistic exploration revealed that the presence of signature 16 was associated with better immune infiltration and tumor immunogenicity, while patients with ARID1A mutations were away from these favorable immunological features.

CONCLUSION

By integrating somatic mutation data and clinical information of HCC, this study identified that signature 16 and ARID1A mutations were associated with better and worse outcomes respectively, providing a basis for prognosis prediction and clinical treatment strategies of HCC.

Human-correlated genetic models identify precision therapy for liver cancer

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, is a leading cause of cancer-related mortality worldwide1,2. HCC occurs typically from a background of chronic liver disease, caused by a spectrum of predisposing conditions. Tumour development is driven by the expansion of clones that accumulate progressive driver mutations3, with hepatocytes the most likely cell of origin2. However, the landscape of driver mutations in HCC is broadly independent of the underlying aetiologies4. Despite an increasing range of systemic treatment options for advanced HCC, outcomes remain heterogeneous and typically poor. Emerging data suggest that drug efficacies depend on disease aetiology and genetic alterations5,6. Exploring subtypes in preclinical models with human relevance will therefore be essential to advance precision medicine in HCC7. Here we generated a suite of genetically driven immunocompetent in vivo and matched in vitro HCC models. Our models represent multiple features of human HCC, including clonal origin, histopathological appearance and metastasis. We integrated transcriptomic data from the mouse models with human HCC data and identified four common human-mouse subtype clusters. The subtype clusters had distinct transcriptomic characteristics that aligned with the human histopathology. In a proof-of-principle analysis, we verified response to standard-of-care treatment and used a linked in vitro-in vivo pipeline to identify a promising therapeutic candidate, cladribine, that has not previously been linked to HCC treatment. Cladribine acts in a highly effective subtype-specific manner in combination with standard-of-care therapy.

Precision models in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents a global health challenge, and ranks among one of the most prevalent and deadliest cancers worldwide. Therapeutic advances have expanded the treatment armamentarium for patients with advanced HCC, but obstacles remain. Precision oncology, which aims to match specific therapies to patients who have tumours with particular features, holds great promise. However, its implementation has been hindered by the existence of numerous 'HCC influencers' that contribute to the high inter-patient heterogeneity. HCC influencers include tumour-related characteristics, such as genetic alterations, immune infiltration, stromal composition and aetiology, and patient-specific factors, such as sex, age, germline variants and the microbiome. This Review delves into the intricate world of HCC, describing the most innovative model systems that can be harnessed to identify precision and/or personalized therapies. We provide examples of how different models have been used to nominate candidate biomarkers, their limitations and strategies to optimize such models. We also highlight the importance of reproducing distinct HCC influencers in a flexible and modular way, with the aim of dissecting their relative contribution to therapy response. Next-generation HCC models will pave the way for faster discovery of precision therapies for patients with advanced HCC.

Strategies for discovering novel hepatocellular carcinoma biomarkers

Liver cancer, particularly hepatocellular carcinoma (HCC), remains a significant global health challenge due to its high mortality rate and late-stage diagnosis. The discovery of reliable biomarkers is crucial for improving early detection and patient outcomes. This review provides a comprehensive overview of current and emerging biomarkers for HCC, including alpha-fetoprotein, des-gamma-carboxy prothrombin, glypican-3, Golgi protein 73, osteopontin, and microRNAs. Despite advancements, the diagnostic limitations of existing biomarkers underscore the urgent need for novel markers that can detect HCC in its early stages. The review emphasizes the importance of integrating multi-omics approaches, combining genomics, proteomics, and metabolomics, to develop more robust biomarker panels. Such integrative methods have the potential to capture the complex molecular landscape of HCC, offering insights into disease mechanisms and identifying targets for personalized therapies. The significance of large-scale validation studies, collaboration between research institutions and clinical settings, and consideration of regulatory pathways for clinical implementation is also discussed. In conclusion, while substantial progress has been made in biomarker discovery, continued research and innovation are essential to address the remaining challenges. The successful translation of these discoveries into clinical practice will require rigorous validation, standardization of protocols, and cross-disciplinary collaboration. By advancing the development and application of novel biomarkers, we can improve the early detection and management of HCC, ultimately enhancing patient survival and quality of life.

Coilin Affects the Prognosis of Hepatocellular Carcinoma Through Cell Cycle and Apoptosis

Purpose

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality with a challenging prognosis. HCC lacks effective prognostic biomarkers. We investigated the diagnostic and prognostic value of COIL expression in HCC.

Patients and Methods

This study evaluated the expression and prognostic significance of COIL using data from the TCGA and local hospital samples, with 374 and 118 liver cancer patients in the TCGA database and local hospital, respectively. The techniques include bioinformatics analysis, qRT-PCR, immunohistochemistry (IHC), and in vitro cell experiments, which encompass CCK-8 assays, wound healing assays, and Transwell invasion assays. The relationship between COIL expression and clinical outcomes was assessed, and COIL's biological function in HCC was investigated through cellular assays.

Results

Analysis of cell lines and HCC tissue samples revealed that COIL mRNA or protein expression levels were significantly higher in HCC cell lines/tissues compared to normal liver cells/tissues. Univariate and multivariate analyses indicated that COIL is an independent prognostic factor for overall survival (OS) in HCC. Additionally, 14% of HCC patients had alterations in the COIL gene, and patients with COIL gene alterations had significantly lower OS (p<0.001) and disease-free survival (DFS) (p<0.001) compared to those without gene alterations. Knockdown of COIL expression inhibited the proliferation, migration, and invasion of Hep3B, HepG2, and Huh7. Compared to the control group, COIL knockdown cells showed a marked reduction in CDC25C and CCNB1 protein levels, suggesting that COIL knockdown leads to G2/M phase cell cycle arrest. After COIL knockdown, caspase-3 and BCL-2 protein levels were downregulated, while cleaved caspase and BAX protein levels were upregulated, indicating that COIL knockdown promotes apoptosis in liver cancer cells.

Conclusion

COIL is an independent predictor of prognosis. COIL's association with poor OS and its role in enhancing cancer cell proliferation and invasion highlight its potential as a therapeutic target.

HBV Remodels PP2A Complexes to Rewire Kinase Signaling in Hepatocellular Carcinoma

Hepatitis B virus (HBV) infections promote liver cancer initiation by inducing inflammation and cellular stress. Despite a primarily indirect effect on oncogenesis, HBV is associated with a recurrent genomic phenotype in hepatocellular carcinoma (HCC), suggesting that it impacts the biology of established HCC. Characterization of the interaction of HBV with host proteins and the mechanistic contributions of HBV to HCC initiation and maintenance could provide insights into HCC biology and uncover therapeutic vulnerabilities. In this study, we used affinity purification mass spectrometry to comprehensively map a network of 145 physical interactions between HBV and human proteins in HCC. A subset of the host factors targeted by HBV proteins were preferentially mutated in non-HBV-associated HCC, suggesting that their interaction with HBV influences HCC biology. HBV interacted with proteins involved in mRNA splicing, mitogenic signaling, and DNA repair, with the latter set interacting with the HBV oncoprotein X (HBx). HBx remodeled the PP2A phosphatase complex by excluding striatin regulatory subunits from the PP2A holoenzyme, and the HBx effects on PP2A caused Hippo kinase activation. In parallel, HBx activated mTOR complex 2, which can prevent YAP degradation. mTOR complex 2-mediated upregulation of YAP was observed in human HCC specimens and mouse HCC models and could be targeted with mTOR kinase inhibitors. Thus, HBV interaction with host proteins rewires HCC signaling rather than directly activating mitogenic pathways, providing an alternative paradigm for the cellular effects of a tumor-promoting virus. Significance: Integrative proteomic and genomic analysis of HBV/host interactions illuminated modifiers of hepatocellular carcinoma behavior and key signaling mechanisms in advanced disease, which suggested that HBV may have therapeutically actionable effects.

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.

DNAJB1-PRKACA Fusion Drives Fibrolamellar Liver Cancer through Impaired SIK Signaling and CRTC2/p300-Mediated Transcriptional Reprogramming

SIGNIFICANCE

This work combines functional studies in model systems and examination of human tumor specimens to define a central oncogenic pathway driven by DNAJB1-PRKACA fusions in FLC. DNAJB1-PRKACA-mediated inactivation of the SIK stimulates CRTC2-p300-mediated transcription to drive tumor growth. The findings illuminate pathogenic mechanisms and inform therapeutic development.

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.

Pediatric Hepatocellular Carcinoma: A Review of Predisposing Conditions, Molecular Mechanisms, and Clinical Considerations

Pediatric hepatocellular carcinoma (HCC) is a rare malignant liver tumor affecting children and adolescents and occurring either sporadically or in the context of underlying liver disease. In this review, we detail the epidemiology of pediatric HCC with a focus on predisposing factors including hepatic or systemic disease, genetic disorders, and familial cancer syndromes. We summarize existing research on the pathophysiology of pediatric HCC, including molecular mechanisms of oncogenesis, highlighting unique disease features differentiating pediatric HCC from adult HCC. We then survey the landscape of therapeutic options for pediatric HCC, including novel therapeutics. Lastly, we discuss the pathologic spectrum upon which pediatric HCC is postulated to exist, ranging from hepatoblastoma to HCC and including the hybrid entity hepatocellular neoplasm not otherwise specifed (HCN-NOS). In summary, we highlight the key clinical and molecular features of pediatric HCC that may inform future research and novel approaches to the clinical care of these patients.

Characteristics and clinical significance of immune cells in omental milky spots of patients with gastric cancer

The omentum is a common site of peritoneal metastasis in various cancers, including gastric cancer. It contains immune cell aggregates known as milky spots, which provide a microenvironment for peritoneal immunity by regulating innate and adaptive immune responses. In this study, we investigated gene expression profiles in cells from omental milky spots of patients with gastric cancer (n = 37) by RNA sequencing analysis and classified the patients into four groups (G1-4). Notably, significant differences were observed between the groups in terms of macroscopic type, lymphatic invasion, venous invasion, and pathological stage (pStage). G3, which was enriched in genes related to acquired immunity, showed earlier tumor stages (macroscopic type 0, Ly0, V0, and pStage I) and a better prognosis. In contrast, G4 showed enrichment of genes related to neutrophils and innate immunity; G1 and G2 showed no enrichment of innate or adaptive immune-related genes, suggesting an immune desert microenvironment. Cytometric analysis revealed significantly more T and B cells and fewer neutrophils in G3. Accordingly, the immune microenvironment in omental milky spots may vary depending on the stage of gastric cancer progression. When univariate Cox proportional hazards regression models were used to search for prognostically relevant genes specific to G3, 23 potential prognostic genes were identified as common genes associated with relapse-free survival and overall survival. In addition, the multivariate Cox proportional hazards model using these prognostic genes and clinicopathological information showed that combining the B cell marker CD19 and Ly had a high predictive accuracy for prognosis. Based on this study's results, it is possible that tumor progression, such as lymphatic and/or venous infiltration of tumor cells, may affect the immune cell composition and proportions in omental milky spots of patients with gastric cancer and analysis of gene expression in omental milky spots may help to predict gastric cancer prognosis.

Radiomics-based biomarker for PD-1 status and prognosis analysis in patients with HCC

Purpose

To investigate the impact of preoperative contrast-enhanced CT-based radiomics model on PD-1 prediction in hepatocellular carcinoma (HCC) patients.

Methods

The study included 105 HCC patients (training cohort: 72; validation cohort: 33) who underwent preoperative contrast-enhanced CT and received systemic sorafenib treatment after surgery. Radiomics score was built for each patient and was integrated with independent clinic radiologic predictors into the radiomics model using multivariable logistic regression analysis.

Results

Seventeen radiomics features were finally selected to construct the radiomics score. In multivariate analysis, serum creatine and peritumoral enhancement were significant independent factors for PD-1 prediction. The radiomics model integrated radiomics signature with serum creatine and peritumoral enhancement showed good discriminative performance (AUC of 0.897 and 0.794 in the training and validation cohort). Overall survival (OS) was significantly different between the radiomics-predicted PD-1-positive and PD-1-negative groups (OS: 29.66 months, CI:16.03-44.40 vs. 31.04 months, CI: 17.10-44.07, P<0.001). Radiomics-predicted PD-1 was an independent predictor of OS of patients treated with sorafenib after surgery. (Hazard ratio [HR]: 1.61 [1.23-2.1], P<0.001).

Conclusion

The proposed model based on radiomic signature helps to evaluate PD-1 status of HCC patients and may be used for evaluating patients most likely to benefit from sorafenib as a potentially combination therapy regimen with immune checkpoint therapies.

Exploring the efficacy of fluorouracil and platinum based chemotherapy in advanced hepatocellular carcinoma to bridge the treatment gap in resource limited settings

Advanced hepatocellular carcinoma (HCC) poses treatment challenges, especially where access to multi-kinase inhibitors and ICIs is limited by high costs and lack of insurance. This study evaluates the effectiveness of 5-fluorouracil (5-FU) plus platinum-based chemotherapy as an alternative systemic treatment for advanced HCC. A retrospective analysis of advanced HCC patients treated with 5-FU plus platinum-based chemotherapy was conducted. The Kaplan-Meier method determined median progression-free survival (PFS) and overall survival (OS). From April 2009 to October 2023, 48 patients with advanced HCC were included in the study. Nearly all patients (97.9%) had extrahepatic metastasis and stable liver function, with three-quarters previously treated with sorafenib. At a median follow-up of 7.8 months, the median PFS was 4.2 months (95% CI, 1.3-7.1), and the median OS was 8.2 months (95% CI, 2.5-13.9). A high pretreatment neutrophil-to-lymphocyte ratio (≥ 3.0) adversely affected both PFS (HR = 1.79; 95% CI, 0.99-3.25; p = 0.034) and OS (HR = 2.02; 95% CI, 1.10-3.69; p = 0.011). Hematologic toxicities related to the treatment were substantial, with 62.5% of patients experiencing grade 3 or 4 events, primarily neutropenia, which affected 60.4% of them. Our findings suggest that 5-FU combined with platinum-based chemotherapy is a viable, cost-effective alternative for advanced HCC treatment in resource-limited settings, particularly compared to ICIs and multi-kinase inhibitors, with significant implications for developing countries.

Personalized Immunity: Neoantigen-Based Vaccines Revolutionizing Hepatocellular Carcinoma Treatment

Hepatocellular carcinoma (HCC), the most prevalent form of primary liver cancer, presents significant therapeutic challenges due to its molecular complexity, late-stage diagnosis, and inherent resistance to conventional treatments. The intermediate to low mutational burden in HCC and its ability to evade the immune system through multiple mechanisms complicate the development of effective therapies. Recent advancements in immunotherapy, particularly neoantigen-based vaccines, offer a promising, personalized approach to HCC treatment. Neoantigens are tumor-specific peptides derived from somatic mutations in tumor cells. Unlike normal cellular antigens, neoantigens are foreign to the immune system, making them highly specific targets for immunotherapy. Neoantigens arise from genetic alterations such as point mutations, insertions, deletions, and gene fusions, which are expressed as neoepitopes that are not present in healthy tissues, thus evading the immune tolerance mechanisms that typically protect normal cells. Preclinical and early-phase clinical studies of neoantigen-based vaccines have shown promising results, demonstrating the ability of these vaccines to elicit robust T cell responses against HCC. The aim of the current review is to provide an in-depth exploration of the therapeutic potential of neoantigen-based vaccines in HCC, focusing on neoantigen identification, vaccine platforms, and their integration with immune checkpoint inhibitors to enhance immunogenicity. It also evaluates preclinical and clinical data on efficacy and safety while addressing challenges in clinical translation. By taking advantage of the unique antigenic profile of each patient's tumor, neoantigen-based vaccines represent a promising approach in the treatment of HCC, offering the potential for improved patient outcomes, long-term remission, and a shift towards personalized, precision medicine in liver cancer therapy.

TP53 Mutation Predicts Worse Survival and Earlier Local Progression in Patients with Hepatocellular Carcinoma Treated with Transarterial Embolization

The aim of this study was to evaluate associations between TP53 status and outcomes after transarterial embolization (TAE) for the treatment of patients with hepatocellular carcinoma (HCC). This single-institution study included patients from 1/2014 to 6/2022 who underwent TAE of HCC and genomic analysis of tumoral tissue. The primary outcome was overall survival (OS) with relation to TP53 status, and the secondary outcome was the time to progression. Survival analysis was performed using the Kaplan-Meier method. The time to progression with death or the last patient contact without progression as competing risks were used to obtain a cumulative incidence function, and the association with TP53 status was evaluated using the Gray test. In total, 75 patients (63 men) with a median age of 70.0 (IQR 62.0-76.3) years were included. Of these, 26/75 (34.7%) patients had TP53-mutant HCC. Patients with TP53-mutant HCC had a significantly worse median OS of 15.2 (95% CI, 9.5-29.3) months, versus 31.2 (95% CI, 21.2-52.4) months as the median OS (p = 0.023) for TP53 wild-type HCC. Competing risk analysis showed a shorter time to local hepatic progression (at the site of the previously treated tumor) after TAE in patients with TP53-mutant HCC. The cumulative incidences of local progression at 6 and 12 months for TP53-mutant HCC were 65.4% and 84.6%, versus 40.8% and 55.1% for TP53 wild-type HCC (p = 0.0072). A TP53 mutation may predict a worse overall survival and a shorter time to local progression in HCC patients treated with TAE.

Quantitative proteomic analysis unveils a critical role of VARS1 in hepatocellular carcinoma aggressiveness through the modulation of MAGI1 expression

BACKGROUND

Hepatocellular carcinoma (HCC) genetic/transcriptomic signatures have been widely described. However, its proteomic characterization is incomplete. We performed non-targeted quantitative proteomics of HCC samples and explored its clinical, functional, and molecular consequences.

METHODS

Non-targeted quantitative proteomics were performed on cytosolic and nuclear fractions of liver samples [HCC vs. non-tumour adjacent tissue (NTAT), n = 42 patients]. Changes were confirmed in 7 in silico HCC cohorts. Functional and molecular implications were evaluated on HCC-derived cell lines after silencing/overexpressing VARS1 and/or MAGI1. VARS1-overexpressing Hep3B cells were used for in vivo studies [Extreme Limiting Dilution Assay (ELDA) and orthotopic tumour formation]. Quantitative proteomics were performed on VARS1-overexpressing HCC cell lines.

RESULTS

Quantitative proteomics revealed the dysregulation of the cytosolic and nuclear proteomes in HCC, and defined two proteomic HCC subgroups, the most aggressive associated to the dysregulation of the aminoacyl-tRNA synthetases (ARSs). ARSs dysregulation was corroborated in in silico HCC cohorts and associated to poor prognosis. Patients with ARSs upregulation had genomic/transcriptomic characteristics of the proliferative HCC. Valine tRNA-aminoacyl synthetase (VARS1) was the ARSs most consistently overexpressed and associated to aggressiveness. VARS1 modulation (silencing/overexpression) altered tumour establishment-associated parameters in vitro and/or in vivo. Quantitative proteomics on cells overexpressing VARS1 and rescue experiments identified the downregulation of MAGI1, a tumour suppressor in HCC, as a mediator of VARS1 function.

CONCLUSIONS

Quantitative proteomics defines two prognosis-related proteomic HCC subgroups. ARSs machinery is dysregulated in the aggressive subgroup, bearing potential as prognostic biomarkers. VARS1 promotes aggressiveness through the modulation of MAGI1, representing a novel targetable vulnerability in HCC.

The Pentose Phosphate Pathway: From Mechanisms to Implications for Gastrointestinal Cancers

The pentose phosphate pathway (PPP), traditionally recognized for its role in generating nicotinamide adenine dinucleotide phosphate (NADPH) and ribose-5-phosphate (R5P), has emerged as a critical metabolic hub with involvements in various gastrointestinal (GI) cancers. The PPP plays crucial roles in the initiation, development, and tumor microenvironment (TME) of GI cancers by modulating redox homeostasis and providing precursors for nucleotide biosynthesis. Targeting PPP enzymes and their regulatory axis has been a potential strategy in anti-GI cancer therapies. In this review, we summarize the regulatory mechanisms of PPP enzymes, elucidate the relationships between the PPP and TME's elements, and discuss the therapeutic potential of targeting the PPP in GI cancers.

Bile acid synthesis impedes tumor-specific T cell responses during liver cancer

The metabolic landscape of cancer greatly influences antitumor immunity, yet it remains unclear how organ-specific metabolites in the tumor microenvironment influence immunosurveillance. We found that accumulation of primary conjugated and secondary bile acids (BAs) are metabolic features of human hepatocellular carcinoma and experimental liver cancer models. Inhibiting conjugated BA synthesis in hepatocytes through deletion of the BA-conjugating enzyme bile acid-CoA:amino acid N-acyltransferase (BAAT) enhanced tumor-specific T cell responses, reduced tumor growth, and sensitized tumors to anti-programmed cell death protein 1 (anti-PD-1) immunotherapy. Furthermore, different BAs regulated CD8+ T cells differently; primary BAs induced oxidative stress, whereas the secondary BA lithocholic acid inhibited T cell function through endoplasmic reticulum stress, which was countered by ursodeoxycholic acid. We demonstrate that modifying BA synthesis or dietary intake of ursodeoxycholic acid could improve tumor immunotherapy in liver cancer model systems.

MicroRNA-3145 as a potential therapeutic target for hepatitis B virus: inhibition of viral replication via downregulation of HBS and HBX

Current treatments for hepatitis B virus (HBV), such as interferons and nucleic acid analogs, have limitations due to side effects like depression and the development of drug-resistant mutants, highlighting the need for new therapeutic approaches. In this study, we identified microRNA-3145 (miR-3145) as a host-derived miRNA with antiviral activity that is upregulated in primary hepatocytes during HBV infection. The expression of its precursor, pri-miR-3145, increased in response to the the virus infection, and miR-3145 downregulated the hepatitis B virus S (HBS) antigen and hepatitis B virus X (HBX), thereby inhibiting viral replication. The binding site for miR-3145 was located in the HBV polymerase (pol) region, as experimentally confirmed. Moreover, overexpression of HBS and HBX induced pri-miR-3145 expression through endoplasmic reticulum stress. The expression of pri-miR-3145 showed a strong correlation with the Nance-Horan syndrome-like 1 (NHSL1) gene, as it is encoded within an intron of NHSL1, and higher NHSL1 expression in hepatocellular carcinoma patients with HBV infection was associated with better prognosis. These findings suggest that miR-3145-3p, along with small molecules targeting its binding sites, holds promise as a potential therapeutic candidate for HBV treatment.

Tumor cell-based liquid biopsy using high-throughput microfluidic enrichment of entire leukapheresis product

Circulating Tumor Cells (CTCs) in blood encompass DNA, RNA, and protein biomarkers, but clinical utility is limited by their rarity. To enable tumor epitope-agnostic interrogation of large blood volumes, we developed a high-throughput microfluidic device, depleting hematopoietic cells through high-flow channels and force-amplifying magnetic lenses. Here, we apply this technology to analyze patient-derived leukapheresis products, interrogating a mean blood volume of 5.83 liters from seven patients with metastatic cancer. High CTC yields (mean 10,057 CTCs per patient; range 100 to 58,125) reveal considerable intra-patient heterogeneity. CTC size varies within patients, with 67% overlapping in diameter with WBCs. Paired single-cell DNA and RNA sequencing identifies subclonal patterns of aneuploidy and distinct signaling pathways within CTCs. In prostate cancers, a subpopulation of small aneuploid cells lacking epithelial markers is enriched for neuroendocrine signatures. Pooling of CNV-confirmed CTCs enables whole exome sequencing with high mutant allele fractions. High-throughput CTC enrichment thus enables cell-based liquid biopsy for comprehensive monitoring of cancer.

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients

With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high-throughput technologies with imaging phenotypes. However, with advancements in medical imaging, high-throughput omics technologies, and artificial intelligence, both the concept and application of radiogenomics have significantly broadened. In this review, the history of radiogenomics is enumerated, related omics technologies, the five basic workflows and their applications across tumors, the role of AI in radiogenomics, the opportunities and challenges from tumor heterogeneity, and the applications of radiogenomics in tumor immune microenvironment. The application of radiogenomics in positron emission tomography and the role of radiogenomics in multi-omics studies is also discussed. Finally, the challenges faced by clinical transformation, along with future trends in this field is discussed.

Establishment and Validation of the Novel Necroptosis-related Genes for Predicting Stemness and Immunity of Hepatocellular Carcinoma via Machine-learning Algorithm

BACKGROUND

Necroptosis, a recently identified mechanism of programmed cell death, exerts significant influence on various aspects of cancer biology, including tumor cell proliferation, stemness, metastasis, and immunosuppression. However, the role of necroptosis-related genes (NRGs) in Hepatocellular Carcinoma (HCC) remains elusive.

METHODS

In this study, we assessed the mutation signature, copy number variation, and expression of 37 NRGs in HCC using the TCGA-LIHC dataset. We further validated our results using the ICGC-LIRI-JP dataset. To construct our prognostic model, we utilized the least absolute shrinkage and selection operator (LASSO), and evaluated the predictive efficacy of the NRGs-score using various machine learning algorithms, including K-M curves, time-ROC curves, univariate and multivariate Cox regression, and nomogram. In addition, we analyzed immune infiltration using the CIBERSOFT and ssGSEA algorithms, calculated the stemness index through the one-class logistic regression (OCLR) algorithm, and performed anti-cancer stem cells (CSCs) drug sensitivity analysis using oncoPredict. Finally, we validated the expression of the prognostic NRGs through qPCR both in vitro and in vivo.

RESULTS

About 18 out of 37 NRGs were found to be differentially expressed in HCC and correlated with clinical outcomes. To construct a prognostic model, six signature genes (ALDH2, EZH2, PGAM5, PLK1, SQSTM1, and TARDBP) were selected using LASSO analysis. These genes were then employed to categorize HCC patients into two subgroups based on NRGs-score (low vs. high). A high NRGs score was associated with a worse prognosis. Furthermore, univariate and multivariate Cox regression analyses were performed to confirm the NRGs-score as an independent risk factor. These analyses revealed strong associations between NRGs-score and critical factors, such as AFP, disease stage, and tumor grade in the HCC cohort. NRGs-score effectively predicted the 1-, 3-, and 5-year survival of HCC patients. Immune infiltration analysis further revealed that the expression of immune checkpoint molecules was significantly enhanced in the high NRGs-score group. Stemness analysis in the HCC cohort showed that NRGs-score was positively correlated with mRNA stemness index, and patients with high NRGs-score were sensitive to CSCs inhibitors. The findings from the external validation cohort provided confirmation that the NRGs-score presented a trait with universal applicability in accurately predicting the survival of HCC. Additionally, the six prognostic genes were consistently differentially expressed in both the HCC cell line and the mouse HCC model.

CONCLUSION

Our study demonstrated the pivotal role of NRGs in promoting stemness and immune suppression in HCC and established a robust model which could successfully predict HCC prognosis.

Development of a genetically tailored implantation hepatocellular carcinoma model in Oncopigs by somatic cell CRISPR editing

Hepatocellular carcinoma (HCC) is an aggressive disease with poor prognosis, necessitating preclinical models for evaluating novel therapies. Large-animal models are particularly valuable for assessing locoregional therapies, which are widely employed across HCC stages. This study aimed to develop a large-animal HCC model with tailored tumor mutations. The Oncopig, a genetically engineered pig with inducible TP53R167H and KRASG12D, was used in the study. Hepatocytes were isolated from Oncopigs and exposed to Cre recombinase in vitro to create HCC cells, and additional mutations were introduced by CRISPR/Cas9 knockout of PTEN and CDKN2A. These edits increased Oncopig HCC cell proliferation and migration. Autologous HCC cells with these CRISPR edits were implanted into Oncopigs using two approaches: ultrasound-guided percutaneous liver injections, which resulted in the development of localized intrahepatic masses, and portal vein injections, which led to multifocal tumors that regressed over time. Tumors developed by both approaches harbored PTEN and CDKN2A knockout mutations. This study demonstrates the feasibility of developing genetically tailored HCC tumors in Oncopigs using somatic cell CRISPR editing and autologous implantation, providing a valuable large-animal model for in vivo therapeutic assessment.

MAD2L1 supports MYC-driven liver carcinogenesis in mice and predicts poor prognosis in human hepatocarcinoma

Mitotic arrest-deficient 2 like 1 (MAD2L1) is a component of the mitotic spindle assembly checkpoint implicated in cancer cell proliferation and tumorigenesis. The functional role of MAD2L1 in hepatocellular carcinoma (HCC) has not been adequately investigated, especially in vivo. In the current manuscript, we sought to address the function of MAD2L1 in hepatocarcinogenesis. We found that MAD2L1 expression is upregulated in human HCCs, where its expression is associated with higher aggressive tumor grade, elevated proliferative activity, and poor prognosis. In human HCC cell lines, MAD2L1 knockdown led to decreased cell growth. Moreover, RNA-seq results demonstrated that MAD2L1 silencing induces the expression of genes associated with cell cycle, DNA replication, and various cancer-related pathways, supporting the critical role of MAD2L1 during HCC growth and differentiation. In a c-MYC-induced mouse HCC model, we revealed an increased expression of Mad2l1. Furthermore, Mad2l1 CRIPSR-mediated silencing prevented c-MYC-driven mouse liver development. Altogether, our study suggests that MAD2L1 plays a crucial role in hepatocarcinogenesis, and that its suppression could be a promising therapeutic strategy for treating human HCC. MAD2L1 plays a critical role in liver cancer development, silencing MAD2L1 reduced cell growth in vitro and inhibited c-MYC-driven liver cancer development in vivo. MAD2L1 suppression might be a promising therapeutic approach for treating human liver cancer.

Elucidation of Factors Affecting the Age-Dependent Cancer Occurrence Rates

Cancer occurrence rates exhibit diverse age-related patterns, and understanding them may shed new and important light on the drivers of cancer evolution. This study systematically analyzes the age-dependent occurrence rates of 23 carcinoma types, focusing on their age-dependent distribution patterns, the determinants of peak occurrence ages, and the significant difference between the two genders. According to the SEER reports, these cancer types have two types of age-dependent occurrence rate (ADOR) distributions, with most having a unimodal distribution and a few having a bimodal distribution. Our modeling analyses have revealed that (1) the first type can be naturally and simply explained using two age-dependent parameters: the total number of stem cell divisions in an organ from birth to the current age and the availability levels of bloodborne growth factors specifically needed by the cancer (sub)type, and (2) for the second type, the first peak is due to viral infection, while the second peak can be explained as in (1) for each cancer type. Further analyses indicate that (i) the iron level in an organ makes the difference between the male and female cancer occurrence rates, and (ii) the levels of sex hormones are the key determinants in the onset age of multiple cancer types. This analysis deepens our understanding of the dynamics of cancer evolution shared by diverse cancer types and provides new insights that are useful for cancer prevention and therapeutic strategies, thereby addressing critical gaps in the current paradigm of oncological research.

Liver cancer multiomics reveals diverse protein kinase A disruptions convergently produce fibrolamellar hepatocellular carcinoma

Fibrolamellar Hepatocellular Carcinoma (FLC) is a rare liver cancer characterized by a fusion oncokinase of the genes DNAJB1 and PRKACA, the catalytic subunit of protein kinase A (PKA). A few FLC-like tumors have been reported showing other alterations involving PKA. To better understand FLC pathogenesis and the relationships among FLC, FLC-like, and other liver tumors, we performed a massive multi-omics analysis. RNA-seq data of 1412 liver tumors from FLC, hepatocellular carcinoma, hepatoblastoma and intrahepatic cholangiocarcinoma are analyzed, obtaining transcriptomic signatures unrestricted by experimental processing methods. These signatures reveal which dysregulations are unique to specific tumors and which are common to all liver cancers. Moreover, the transcriptomic FLC signature identifies a unifying phenotype for all FLC tumors regardless of how PKA was activated. We study this signature at multi-omics and single-cell levels in the first spatial transcriptomic characterization of FLC, identifying the contribution of tumor, normal, stromal, and infiltrating immune cells. Additionally, we study FLC metastases, finding small differences from the primary tumors.

Asynchronous Transitions from Hepatoblastoma to Carcinoma in High-Risk Pediatric Tumors

Most malignant hepatocellular tumors in children are classified as either hepatoblastoma (HB) or hepatocellular carcinoma (HCC), but some tumors demonstrate features of both HB and HCC1-3. These tumors have been recognized under a provisional diagnostic category by the World Health Organization and are distinguished from HB and HCC by a combination of histological, immunohistochemical, and molecular features4-6. Their outcomes and cellular composition remain an open question7-9. The heterogeneous histological and molecular profiles of hepatoblastomas with carcinoma features (HBCs)4 may result from cells with combined HB and HCC characteristics (HBC cells) or from mixtures of cells displaying either HB or HCC signatures. We used multiomics profiling to show that HBCs are mixtures of HB, HBC, and HCC cell types. HBC cells are more chemoresistant than HB cells, and their chemoresistance-a driver of poor outcomes10-12-is determined by their cell types, genetic alterations, and embryonic differentiation stages. We showed that the prognosis of HBCs is significantly worse than that of HBs. We also showed that HBC cells are derived from HB cells at early hepatoblast differentiation stages, that aberrant activation of WNT-signaling initiates HBC transformation, and that WNT inhibition promotes differentiation and increases sensitivity to chemotherapy. Furthermore, our analysis revealed that each HBC is the product of multiple HB-to-HBC and HBC-to-HCC transitions. Thus, multiomics profiling of HBCs provided key insights into their biology and resolved major questions regarding the etiology of these childhood liver tumors.

Artificial intelligence model predicts M2 macrophage levels and HCC prognosis with only globally labeled pathological images

Background and aims

The levels of M2 macrophages are significantly associated with the prognosis of hepatocellular carcinoma (HCC), however, current detection methods in clinical settings remain challenging. Our study aims to develop a weakly supervised artificial intelligence model using globally labeled histological images, to predict M2 macrophage levels and forecast the prognosis of HCC patients by integrating clinical features.

Methods

CIBERSORTx was used to calculate M2 macrophage abundance. We developed a slide-level, weakly-supervised clustering method for Whole Slide Images (WSIs) by integrating Masked Autoencoders (MAE) with ResNet-32t to predict M2 macrophage abundance.

Results

We developed an MAE-ResNet model to predict M2 macrophage levels using WSIs. In the testing dataset, the area under the curve (AUC) (95% CI) was 0.73 (0.59-0.87). We constructed a Cox regression model showing that the predicted probabilities of M2 macrophage abundance were negatively associated with the prognosis of HCC (HR=1.89, p=0.031). Furthermore, we incorporated clinical data, screened variables using Lasso regression, and built the comprehensive prediction model that better predicted prognosis. (HR=2.359, p=0.001).

Conclusion

Our models effectively predicted M2 macrophage levels and HCC prognosis. The findings suggest that our models offer a novel method for determining biomarker levels and forecasting prognosis, eliminating additional clinical tests, thereby delivering substantial clinical benefits.

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.

Integrative analysis of multi-omics data identified PLG as key gene related to Anoikis resistance and immune phenotypes in hepatocellular carcinoma

PURPOSE

The extracellular matrix (ECM) plays a pivotal role in the initiation and progression of hepatocellular carcinoma (HCC) by facilitating the proliferation of HCC cells and enabling resistance to Anoikis. ECM also provide structural support that aids in the invasion of HCC cells, thereby influencing the tumor microenvironment. Due to genetic variations and molecular heterogeneity, significant challenges exist in the treatment of HCC, particularly with immunotherapy, which frequently leads to immune tolerance and suboptimal immune responses. Therefore, there is an urgent need for a multi-omics-based classification system for HCC that clarifies the molecular mechanisms underlying the establishment of immune phenotypes and Anoikis resistance in HCC cells. In this study, we employed advanced clustering algorithms to analyze and integrate multi-omics data from HCC patients, with the objective of identifying key genes that possess prognostic potential associated with the Anoikis resistance phenotype. This methodology resulted in the development of a consensus machine learning-driven signature (CMLS), which demonstrates robust predictive capabilities by examining variations in epigenetics, transcription, and immune metabolism, as well as their effects on the core differential gene, plasminogen (PLG).

RESULTS

The integrated multi-omics approach has identified PLG as a critical node within the gene regulatory network associated with Anoikis resistance and immunometabolic phenotypes. As an independent risk factor for poor prognosis in patients with HCC, PLG facilitates Anoikis resistance and enhances the migration of HCC cells. This study provides novel insights into the molecular subtypes of HCC through the application of robust clustering algorithms based on multi-omics data. The constructed CMLS serves as a valuable tool for early prognostic prediction and for screening potential drug candidates that may enhance the efficacy of immunotherapy, thereby establishing a foundation for personalized treatment strategies in HCC.

CONCLUSIONS

Our data underscore the pivotal role of PLG in the development of Anoikis resistance and the immunometabolic phenotype in HCC cells. Furthermore, we present compelling experimental evidence that PLG functions as a significant tumor promoter, suggesting its potential as a target for the formulation of tailored therapeutic strategies for HCC.

The three YTHDF paralogs and VIRMA are strong cross-histotype tumor driver candidates among m6A core genes

N6-Methyladenosine (m6A) is the most abundant internal modification in mRNAs. Despite accumulating evidence for the profound impact of m6A on cancer biology, there are conflicting reports that alterations in genes encoding the m6A machinery proteins can either promote or suppress cancer, even in the same tumor type. Using data from The Cancer Genome Atlas, we performed a pan-cancer investigation of 15 m6A core factors in nearly 10000 samples from 31 tumor types to reveal underlying cross-tumor patterns. Altered expression, largely driven by copy number variations at the chromosome arm level, results in the most common mode of dysregulation of these factors. YTHDF1, YTHDF2, YTHDF3 and VIRMA are the most frequently altered factors and the only ones to be uniquely altered when tumors are grouped according to the expression pattern of the m6A factors. These genes are also the only ones with coherent, pan-cancer predictive power for progression-free survival. On the contrary, METTL3, the most intensively studied m6A factor as a cancer target, shows much lower levels of alteration and no predictive power for patient survival. Therefore, we propose the non-enzymatic YTHDF and VIRMA genes as preferred subjects to dissect the role of m6A in cancer and as priority cancer targets.

Specific features of ß-catenin-mutated hepatocellular carcinomas

CTNNB1, encoding the ß-catenin protein, is a key oncogene contributing to liver carcinogenesis. Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer in adult, representing the third leading cause of cancer-related death. Aberrant activation of the Wnt/ß-catenin pathway, mainly due to mutations of the CTNNB1 gene, is observed in a significant subset of HCC. In this review, we first resume the major recent advances in HCC classification with a focus on CTNNB1-mutated HCC subclass. We present the regulatory mechanisms involved in β-catenin stabilisation, transcriptional activity and binding to partner proteins. We then describe specific phenotypic characteristics of CTNNB1-mutated HCC thanks to their unique gene expression patterns. CTNNB1-mutated HCC constitute a full-fledged subclass of HCC with distinct pathological features such as well-differentiated cells with low proliferation rate, association to cholestasis, metabolic alterations, immune exclusion and invasion. Finally, we discuss therapeutic approaches to target ß-catenin-mutated liver tumours and innovative perspectives for future drug developments.

Lower Serum Albumin Level: A Prospective Risk Predictor of Hepatocellular Carcinoma in Patients With Chronic Hepatitis B Virus Infection

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours in China, at high annual incidence and mortality. Chronic hepatitis B virus infection (CHB) is considered as a leading cause to bring about HCC in China. Serum albumin (ALB) level has been adopted to verify its risk with HCC development as a combination variable with other factors. However, the predictive value of a single ALB level on HBV-related HCC risk remained unclear. The aim of this study was to evaluate the prediction ability of serum ALB concentration on the risk of HBV-related HCC development. A prospectively enrolled clinical cohort compromising 2932 cases of CHB patients with at least 1-year exclusion window was selected to explore the predictive role of serum ALB level on incident HCC risk. Baseline clinical data including host characters and laboratory test were collected at the initial period of hospitalisation. The hazard ratio of ALB level associated with HCC development was assessed by Cox proportional hazards regression model using univariate and multivariate analyses. We evaluated the discrimination accuracy of ALB level in predicting HCC development by receiver operating characteristic (ROC) curves. Dose-dependent and time-dependent effects of ALB level on HCC risk prediction were demonstrated, respectively, using a restricted cubic spline and a Fine and Grey competing risk model. Referred to patients with higher ALB level, those with lower ALB level exhibited significantly increased risk of HCC development after adjustment for host variables (dichotomised analyses: hazard ratio = 3.12, 95% confidence interval 1.63-5.97, p = 8.23 × 10-4, plog-rank = 5.97 × 10-4; tertile analyses: hazard ratio = 2.07, 95% confidence interval 1.63-2.64, p = 3.77 × 10-9, plog-rank < 2.00 × 10-16; quartile analyses: hazard ratio = 2.10, 95% confidence interval 1.56-2.84, p = 9.87 × 10-7, plog-rank < 2.00 × 10-16). There was a statistically increasing trend on HCC risk which was found following by the decrease of ALB level (ptrend < 0.0001). Similar findings were present by the Kaplan-Meier analysis, cumulative incidences of HCC development were significantly higher in patients with lower ALB levels, with the p value obtained from log-rank test were all < 0.0001. The result of dose-dependent effect showed hazard ratio (HR) value of HCC risk was gradually decreasing as the increasing of ALB level, with non-linear correlation being statistically significant (Wald χ2 = 20.59, p = 0.000). HR value in lower ALB level remained persistently prominent by fluctuating around 2.73 in the whole follow-up time by adjusting for host variables. Sub-cohort analysis by ROC revealed that the discrimination ability of the ALB model was performed better than Child-Pugh (C-P) model in both cohort of patients with 1-year (area under curve [AUC] 0.762 vs. 0.720) and 2-year exclusion window (AUC 0.768 vs. 0.728). The AUC added by ALB level was demonstrated significantly from host model to full model. Lower ALB level was significantly associated with an increased risk of HBV-related HCC and could provide extra useful clinical utility to other host features, which might be a promising non-invasive indicator for surveillance on HCC development.

AAV-mediated combination gene therapy of inducible Caspase 9 and miR-199a-5p is therapeutic in hepatocellular carcinoma

Advanced-stage hepatocellular carcinoma (HCC) remains an untreatable disease with an overall survival of less than one year. One of the critical molecular mediators contributing to increased resistance to therapy and relapse, is increased hypoxia-inducible factor 1α (HIF-1α) levels, leading to metastasis of tumor cells. Several microRNAs are known to be dysregulated and impact HIF-1α expression in HCC. An in silico analysis demonstrated that hsa-miR-199a-5p is downregulated at various stages of HCC and is known to repress HIF-1α expression. Based on this analysis, we developed a combinatorial suicide gene therapy by employing hepatotropic Adeno-associated virus-based vectors encoding an inducible caspase 9 (iCasp9) and miR-199a. The overexpression of miR-199a-5p alone significantly decreased ( ~ 2-fold vs. Mock treated cells, p < 0.05) HIF-1α mRNA levels, with a concomitant increase in cancer cell cytotoxicity in Huh7 cells in vitro and in xenograft models in vivo. To further enhance the efficacy of gene therapy, we evaluated the synergistic therapeutic effect of AAV8-miR-199a and AAV6-iCasp9 in a xenograft model of HCC. Our data revealed that mice receiving combination suicide gene therapy exhibited reduced expression of HIF-1α ( ~ 4-fold vs. Mock, p < 0.001), with a significant reduction in tumor growth when compared to mock-treated animals. These findings underscore the therapeutic potential of downregulating HIF-1α during suicide gene therapy for HCC.

Current status and new directions for hepatocellular carcinoma diagnosis

Liver cancer ranks as the sixth most common cancer globally, with hepatocellular carcinoma (HCC) accounting for approximately 75%-85% of cases. Most patients present with moderately advanced disease, while those with advanced HCC face limited and ineffective treatment options. Despite diagnostic efforts, no ideal tumor marker exists to date, highlighting the urgent clinical need for improved early detection of HCC. A key research objective is the development of assays that target specific pathways involved in HCC progression. This review explores the pathological origin and development of HCC, providing insights into the mechanistic rationale, clinical statistics, and the advantages and limitations of commonly used diagnostic tumor markers. Additionally, it discusses the potential of emerging biomarkers for early diagnosis and offers a brief overview of relevant assay methodologies. This review aims to summarize existing markers and investigate new ones, providing a basis for subsequent research.

Chinese expert consensus on the clinical application of molecular diagnostics in hepatobiliary cancers (2024 edition)

Hepatocellular carcinoma (HCC) and biliary tract cancer (BTC) are significant health challenges in China because of their high prevalence and mortality rates. Advances in molecular diagnostics have opened new avenues for personalized treatment strategies. This consensus provides a comprehensive update on the clinical applications of molecular diagnostics in HCC and BTC and addresses the urgent need for personalized treatment strategies tailored to the Chinese population, emphasizing the importance of molecular markers in guiding targeted therapies and immunotherapies. By employing the Delphi method and the Grading of Recommendations Assessment, Development, and Evaluation system, the expert panel formulated evidence-based recommendations for the use of molecular diagnostics in the clinical management of HCC and BTC. Key molecular markers, such as isocitrate dehydrogenase (IDH) 1 and 2, fibroblast growth factor receptor 2 (FGFR2), BRAF V600E, human epidermal growth factor receptor 2 (HER2), rearranged during transfection (RET), and neurotrophic tyrosine receptor kinase (NTRK), are highlighted for their roles in optimizing treatment regimens. The consensus also explores the significance of emerging biomarkers, such as tumor mutation burden and microsatellite instability, in predicting responses to immune checkpoint inhibitors. The recommendations aim to enhance precision medicine approaches, improve patient outcomes, and foster the integration of molecular diagnostics into routine clinical practice.

Proteo-genomic characterization of cirrhosis-associated liver cancers reveals potential subtypes and therapeutic targets

BACKGROUND

This study aimed to identify potential subtypes of hepatocellular carcinoma (HCC) associated with cirrhosis and to investigate key markers using bioinformatic analysis of gene expression datasets-0.

METHODS

Three data sets (GSE17548, GSE56140, and GSE87630) were extracted from the Gene Expression Omnibus (GEO) database and normalized using the Limma package in R. Principal component analysis (PCA) and cluster analysis was performed to examine data distribution and identify subtypes. Differential gene expression analysis was performed using the Limma software package. Protein-protein interaction analysis and functional annotation were performed using the STRING database and Cytoscape software. Important signaling pathways and processes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis.

RESULTS

The analysis revealed different subtypes of HCC associated with cirrhosis and identified several key genes, including CCNB2, MCM4, and CDC20, with strong binding power and prognostic value. Functional annotation indicated involvement in cell cycle regulation and metabolic pathways. ROC analysis showed high sensitivity and specificity of these genes in predicting HCC prognosis.

CONCLUSION

These results suggest that CCNB2, MCM4, and CDC20 may serve as potential biomarkers for predicting HCC prognosis in patients with cirrhosis and provide insights into the molecular mechanisms of HCC progression.

Integrative multi-omics characterization of hepatocellular carcinoma in Hispanic patients

BACKGROUND

The incidence and mortality rates of hepatocellular carcinoma among Hispanic individuals in the United States are much higher than in non-Hispanic White people. We conducted multi-omics analyses to elucidate molecular alterations in hepatocellular carcinoma among Hispanic patients.

METHODS

Paired tumor and adjacent nontumor samples were collected from 31 Hispanic hepatocellular carcinomas in South Texas for genomic, transcriptomic, proteomic, and metabolomic profiling. Serum lipids were profiled in 40 Hispanic and non-Hispanic patients with or without clinically diagnosed hepatocellular carcinoma.

RESULTS

Exome sequencing revealed high mutation frequencies of AXIN2 and CTNNB1 in South Texas Hispanic hepatocellular carcinoma patients, suggesting a predominant activation of the Wnt/β-catenin pathway. TERT promoter mutations were also statistically significantly more frequent in the Hispanic cohort (Fisher exact test, P < .05). Cell cycles and liver function were positively and negatively enriched, respectively, with gene set enrichment analysis. Gene sets representing specific liver metabolic pathways were associated with dysregulation of corresponding metabolites. Negative enrichment of liver adipogenesis and lipid metabolism corroborated with a significant reduction in most lipids in serum samples of hepatocellular carcinoma patients (paired t test, P < .0001). Two hepatocellular carcinoma subtypes from our Hispanic cohort were identified and validated with the Cancer Genome Atlas liver cancer cohort. Patients with better overall survival showed higher activity of immune and angiogenesis signatures and lower activity of liver function-related gene signatures. They also had higher levels of immune checkpoint and immune exhaustion markers.

CONCLUSIONS

Our study revealed specific molecular features of Hispanic hepatocellular carcinoma and potential biomarkers for therapeutic management. It provides a unique resource for studying Hispanic hepatocellular carcinoma.

Proceedings of the 5th Meeting of Translational Hepatology, organized by the Spanish Association for the Study of the Liver (AEEH)

This is the summary report of the 5th Translational Hepatology Meeting, endorsed by the Spanish Association for the Study of the Liver (AEEH) and held in Seville, Spain, in October 2023. The meeting aimed to provide an update on the latest advances in the field of basic and translational hepatology, covering different molecular, cellular, and pathophysiological aspects of the most relevant clinical challenges in liver pathologies. This includes the identification of novel biomarkers and diagnostic tools, the understanding of the relevance of immune response and inflammation in liver diseases, the characterization of current medical approaches to reverse liver diseases, the incorporation of novel molecular insights through omics techniques, or the characterization of the impact of toxic and metabolic insults, as well as other organ crosstalk, in liver pathophysiology.

The evolutionary history of metastatic pancreatic neuroendocrine tumours reveals a therapy driven route to high-grade transformation

Tumour evolution with acquisition of more aggressive disease characteristics is a hallmark of disseminated cancer. Metastatic pancreatic neuroendocrine tumours (PanNETs) in particular may progress from a low/intermediate to a high-grade disease. The aim of this work was to understand the molecular mechanisms underlying metastatic progression as well as PanNET transformation from a low/intermediate to a high-grade disease. We performed multi-omics analysis (genome/exome sequencing, total RNA-sequencing and methylation array) of 32 longitudinal samples from six patients with metastatic low/intermediate grade PanNET. The clonal composition of tumour lesions and underlying phylogeny of each patient were determined with bioinformatics analyses. Findings were validated in post-alkylating chemotherapy samples from 24 patients with PanNET using targeted next generation sequencing. We validate the current PanNET evolutionary model with MEN1 inactivation that occurs very early in tumourigenesis. This was followed by pronounced genetic diversity on both spatial and temporal levels, with parallel and convergent tumour evolution involving the ATRX/DAXX and mechanistic target of the rapamycin (mTOR) pathways. Following alkylating chemotherapy treatment, some PanNETs developed mismatch repair deficiency and acquired a hypermutational phenotype. This was validated among 16 patients with PanNET who had high-grade progression after alkylating chemotherapy, of whom eight had a tumour mutational burden >50 (50%). In comparison, among the eight patients who did not show high-grade progression, 0 had a tumour mutational burden >50 (0%; odds ratio 'infinite', 95% confidence interval 1.8 to 'infinite', p = 0.02). Our findings contribute to broaden the understanding of metastatic/high-grade PanNETs and suggests that therapy driven disease evolution is an important hallmark of this disease. © 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. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Loss of Carbamoyl Phosphate Synthetase 1 Potentiates Hepatocellular Carcinoma Metastasis by Reducing Aspartate Level

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Numerous studies have shown that metabolic reprogramming is crucial for the development of HCC. Carbamoyl phosphate synthase 1 (CPS1), a rate-limiting enzyme in urea cycle, is an abundant protein in normal hepatocytes, however, lacking systemic research in HCC. It is found that CPS1 is low-expressed in HCC tissues and circulating tumor cells, negatively correlated with HCC stage and prognosis. Further study reveals that CPS1 is a double-edged sword. On the one hand, it inhibits the activity of phosphatidylcholine-specific phospholipase C to block the biosynthesis of diacylglycerol (DAG), leading to the downregulation of the DAG/protein kinase C pathway to inhibit invasion and metastasis of cancer cells. On the other hand, CPS1 promotes cell proliferation by increasing intracellular S-adenosylmethionin to enhance the m6A modification of solute carrier family 1 member 3 mRNA, a key transporter for aspartate intake. Finally, CPS1 overexpressing adeno-associated virus can dampen HCC progression. Collectively, this results uncovered that CPS1 is a switch between HCC proliferation and metastasis by increasing intracellular aspartate level.

Genetic alterations are related to clinicopathological features and risk of recurrence/metastasis of hepatocellular carcinoma

Lack of efficient biomarkers and clinical translation of molecular typing impedes the implementation of targeted therapy for hepatocellular carcinoma (HCC). High-throughput sequencing techniques represented by next-generation sequencing (NGS) are tools for detecting targetable genes. The objective of this study is to explore the genetic alterations associated with clinicopathological features and the risk of recurrence/metastasis in HCC. NGS analysis was conducted on formalin-fixed paraffin-embedded tissues from 164 resected liver samples obtained from Chinese patients. Morphologic subtypes were reviewed based on hematoxylin-eosin and immunohistochemistry staining, Correlation to the acquired molecular features were analyzed with clinicopathological information. We also retrieved follow-up information of the 123 transplanted cases from 2017 to 2019 to screen recurrence/metastasis-associated factors by univariate analysis. Generally, the most frequently mutated genes include TP53 and CTNNB1 which showed a trend of mutually exclusive mutation. Copy-number variant with the highest frequency was detected in TAF1 and CCND1 in 11q13.3 loci. Correlation analysis showed that various genetic alterations were associated with morphologic subtypes and other pathologic features. While gene signatures of proliferation/nonproliferation class were correlated with differentiation, satellite foci and other invasive morphological features. Macrotrabecular-massive subtype, TSC2 (tuberous sclerosis complex 2) mutation, Ki-67 expression, and other six factors were found to be associated with recurrence/metastasis after liver transplantation. Genetic alterations detected by NGS show correlation with not only pathological and clinical features, but also with recurrence/metastasis after liver transplantation. Further gene-level molecular typing will be practical for targeted therapy and individual recurrence risk assessment in HCC patients.

c-Jun and Fra-2 pair up to Myc-anistically drive HCC

Hepatocellular carcinoma (HCC), a leading cause of cancer-related death with limited therapies, is a complex disease developing in a background of Hepatitis Virus infection or systemic conditions, such as the metabolic syndrome. Investigating HCC pathogenesis in model organisms is therefore crucial for developing novel diagnostic and therapeutic tools. Genetically engineered mouse models (GEMMs) have been instrumental in recapitulating the local and systemic features of HCC. Early studies using GEMMs and patient material implicated members of the dimeric Activator Protein-1 (AP-1) transcription factor family, such as c-Jun and c-Fos, in HCC formation. In a recent report, we described how switchable, hepatocyte-restricted expression of a single-chain c-Jun~Fra-2 protein, functionally mimicking the c-Jun/Fra-2 AP-1 dimer, results in spontaneous and largely reversible liver tumors in GEMMs. Dysregulated cell cycle, inflammation, and dyslipidemia are observed at early stages and tumors display molecular HCC signatures. We demonstrate that increased c-Myc expression is an essential molecular determinant of tumor formation that can be therapeutically targeted using the BET inhibitor JQ1. Here, we discuss these findings with additional results illustrating how AP-1 GEMMs can foster preclinical research on liver diseases with novel perspectives offered by the constantly increasing wealth of HCC-related datasets.