Chimeric antigen receptor-natural killer (CAR-NK) therapy represents an emerging new direction in fighting against cancer. In recent years, it has attracted significant attention, largely due to its notable safety advantages over CAR-T cell therapy and its potential for reduced side effects. In this article, we will review the recent preclinical advances and translational challenges in CAR-NK therapy for the treatment of hepatocellular carcinoma (HCC). Several preclinical studies have successfully demonstrated that targeting HCC-associated tumor antigens such as glypican-3 and cluster of differentiation 147 (CD147) could exert a strong anti-tumor efficacy. However, only a few studies have entered the clinical stage, with none having progressed to late-phase trials. The clinical translation of CAR-NK in HCC is mainly hindered by significant challenges, including the immunosuppressive tumor microenvironment, inefficient tumor trafficking, tumor heterogeneity, and poor persistence of infused cells. To overcome these barriers, researchers have been exploring different innovative strategies such as disrupting the transforming growth factor-β signaling, engineering homing chemokine receptors, developing multi-specific CARs, and enhancing persistence with cytokine support (e.g., interleukin-15). Further ongoing research is important to optimize the CAR constructs and identify effective combination approaches to enhance the overall treatment efficacy.
Aim: To identify factors influencing liver-controlled attenuation parameter (CAP, dB/m) and establish its optimal diagnostic thresholds for hepatic steatosis grading in metabolic dysfunction-associated steatotic liver disease (MASLD).
Methods: A total of 758 prospectively enrolled MASLD patients at Zhongshan Hospital, Shanghai, China (September 2022-June 2023) were randomized into a training cohort (n = 619) and a validation cohort (n = 139), stratified by body mass index (BMI: normal-weight < 25 kg/m2; overweight ≥ 25 kg/m2). Demographics, laboratory parameters, CAP, and magnetic resonance imaging (MRI) proton density fat fraction (PDFF) were recorded. Using MRI-derived PDFF (MRI-PDFF) as the reference, receiver operating characteristic (ROC) analysis was performed to establish CAP thresholds for steatosis grades.
Results: In the training cohort, multivariate analysis showed that CAP was correlated with uric acid, glucose, and high-density lipoprotein (HDL) in normal-weight patients, and with alanine aminotransferase (ALT), total cholesterol (TC), and BMI in overweight patients. Overall cohort CAP thresholds were: S1, 283.5 dB/m [area under the curve (AUC) = 0.880]; S2, 311.5 dB/m (AUC = 0.712); S3, 328.5 dB/m (AUC = 0.799). Normal-weight thresholds: S1, 259.5 dB/m (AUC = 0.922); S2-3, 323.5 dB/m (AUC = 0.779). Overweight thresholds: S1, 304.0 dB/m (AUC = 0.829); S2, 311.5 dB/m (AUC = 0.677); S3, 328.5 dB/m (AUC = 0.767). Validation confirmed robust diagnostic performance.
Conclusion: CAP correlates significantly with metabolic factors (glucose, HDL) and shows a trend toward association with uric acid (P = 0.073) in normal-weight MASLD patients, and with liver markers/metabolic factors (BMI, ALT, TC) in overweight patients. CAP demonstrates good diagnostic accuracy for grading the severity of hepatic steatosis in MASLD, particularly for mild to moderate steatosis.
Highlights
1. Study of 758 MASLD patients stratified by BMI to identify factors influencing CAP and its diagnostic value for hepatic steatosis, using MRI-derived PDFF as reference.
2. CAP correlates with glucose, HDL, and uric acid in normal-weight patients, and with ALT, total cholesterol (TC), and BMI in overweight patients.
3. BMI-specific CAP thresholds were established, with the highest diagnostic performance in normal-weight individuals (AUC = 0.922 for S1).
4. Validation confirmed robust diagnostic accuracy (Youden index 0.81-0.83), supporting CAP as a practical non-invasive tool for grading mild-to-moderate steatosis.
The liver is the most common metastatic site of gastric cancer, and liver metastasis is one of the leading causes of death in patients with gastric cancer, characterized by a complex and unique tumor microenvironment (TME). The molecular classification and pathological characteristics of gastric cancer provide a basis for its research and treatment. The dynamic remodeling mechanisms of the TME involve multiple aspects, including stromal cell reprogramming, immune microenvironment characteristics, and regulation of the extracellular matrix and mechanical forces. The clinical challenges of gastric cancer liver metastasis (GC-LM) are severe, and effective intervention strategies need to be proposed, including overcoming physical barriers, precision therapies targeting the microenvironment, and biomarker development. In the future, integrating multi-omics and spatial dynamic analyses and establishing a molecular pathology-clinical translation feedback loop will be essential directions and challenges in this field. This review summarizes the research progress on the TME of GC-LM from clinical molecular pathology to precision medicine, aiming to provide a theoretical basis and new insights for the precision therapy of GC-LM.
The therapeutic landscape of hepatocellular carcinoma (HCC) is undergoing a substantial transformation driven by advances in systemic therapies and locoregional treatments. High response rates observed with immune checkpoint inhibitors and combination regimens have opened the door to conversion therapy. Initially unresectable or non-curable patients can achieve a tumour downsizing to access potentially curative options such as surgery, ablation, or transplantation. This evolving strategy is framed within the concept of the converse therapeutic hierarchy, which promotes a dynamic, response-guided approach. In this model, every treatment is no longer a terminal option but a potential gateway to curative interventions. This review explores the clinical rationale and current evidence supporting conversion therapy in HCC, detailing systemic regimens, transarterial and percutaneous treatments, and their integration into multimodal strategies. Emphasis is placed on response-guided treatment reassessment, perioperative immunotherapy, and the potential of tailored sequencing to redefine clinical practice in HCC. Barriers such as biological heterogeneity, the lack of predictive biomarkers, and organisational gaps in multidisciplinary coordination remain significant. At the same time, improvements in systemic efficacy, advances in locoregional techniques, and new evidence from real-world data point toward a future in which therapeutic intent is no longer fixed but can evolve according to patient response. Conversion therapy, once aspirational, is becoming a realistic and strategic objective in modern HCC care.
Metabolic reprogramming is a fundamental mechanism through which tumor cells reshape their energy metabolism to sustain rapid proliferation. It facilitates malignant growth by reprogramming key pathways, including glycolysis and amino acid metabolism. The tumor microenvironment (TME) is composed of tumor cells, stromal cells, and immune cells. The characteristics of hypoxia, acidity, and nutrient deficiency are mainly driven by the metabolic products and cytokines secreted by tumor cells. This metabolic pressure not only inhibits the functions of immune cells, but also further enhances immune evasion through nutrient competition. Targeting metabolic reprogramming can reverse immunosuppression within the TME and enhance the response to immunotherapy. This article systematically reviews the regulatory mechanisms of metabolic reprogramming in hepatocellular carcinoma and its impact on the TME, while also exploring therapeutic strategies based on metabolic interventions.
Hepatocellular carcinoma (HCC) remains a significant global health issue, linked to chronic liver diseases such as viral hepatitis, cirrhosis, and metabolic dysfunction-related steatohepatitis. Early, accurate diagnosis is vital for treatment, but many cases are diagnosed at advanced stage. Contrast-enhanced ultrasound (CEUS) is a valuable, radiation-free tool for real-time liver lesion assessment with high accuracy. This review examines the growing role of ultrasound and CEUS in diagnosing, monitoring, and post-treatment care of HCC. CEUS has sensitivity and specificity similar to computed tomography and magnetic resonance imaging, especially for nodules ≥ 1 cm, and helps clarify uncertain Liver Imaging Reporting and Data System findings. Dynamic CEUS improves diagnosis by allowing microvascular perfusion measurement. Artificial intelligence (AI) and machine learning integration promises automated lesion classification and better consistency. CEUS is especially useful in outpatient and resource-limited settings, enabling quick decision-making and reducing delays. Meta-analyses and studies support CEUS for initial detection and post-treatment follow-up. As advanced ultrasound becomes more accessible, CEUS can be more widely used in hepatology. Future steps include standard protocols, clinician training, and AI integration. Overall, CEUS complements other imaging methods and aids precision medicine in liver cancer management.
Hepatocellular carcinoma remains a leading cause of cancer-related mortality worldwide. Despite advances in surgical and systemic therapies, recurrence rates remain high, and translational models for therapeutic testing are limited. This review explores the evolving role of ex vivo liver perfusion (EVLP) as a translational platform in hepatoma research, highlighting its applications in tumour modelling, therapeutic testing, and biomarker discovery. A narrative synthesis of recent literature was performed, focusing on EVLP modalities such as normothermic machine perfusion, hypothermic oxygenated perfusion, split-liver perfusion, and segmental perfusion of resected tumour-bearing tissue. EVLP preserves hepatic architecture and metabolic function, enabling real-time study of tumour microenvironments, pharmacological responses, and recurrence mechanisms. Segmental perfusion provides an ethically viable translational model. Overall, EVLP represents a transformative tool in hepatobiliary oncology, bridging the gap between in vitro models and clinical practice, enhancing mechanistic understanding, and accelerating therapeutic innovation.
Aim: Aberrant metabolism represents a hallmark feature of malignancies, which is crucial for facilitating adenosine triphosphate (ATP) production and biosynthesis of macromolecules that sustain cell proliferation, differentiation, and survival. In the context of tumorigenesis, fatty acids (FAs) have garnered substantial attention due to their dual role as secondary messengers and energy substrates. Notably, the pivotal role of FA metabolism in hepatocellular carcinoma (HCC) progression has been extensively explored. Therefore, this study aims to investigate the contributions of FA metabolism in the immunotherapy of HCC, which remain undefined.
Methods: We analyzed messenger RNA expression and genetic alterations of regulators of FA metabolism from public HCC datasets. Based on their FA metabolism profiles, patients were classified into two distinct molecular subtypes: cluster A and cluster B. Using subtype-derived differentially expressed genes, we established an unsupervised FA_score algorithm. Immune infiltration analysis and prognostic screening of 2,484 immune genes were integrated to develop a risk model, ultimately classifying patients into four integrated subtypes: mixed index (MI)-1 to MI-4.
Result: Cluster B exhibited significantly worse overall survival than cluster A. Higher FA_score correlated with shorter survival and increased infiltration of immunosuppressive cells. The MI-2 subgroup showed abundant CD4+ T cells, myeloid-derived suppressor cells, and regulatory T cells, indicating strong immunosuppression and poor prognosis, suggesting limited benefit from immunotherapy.
Conclusion: We developed a novel classification system integrating FA metabolism and immune features. The MI-2 subtype is characterized by immunosuppression and poor outcomes, highlighting the clinical relevance of FA metabolic patterns in shaping the immune microenvironment and guiding personalized treatment in HCC.
Liver cancer, particularly hepatocellular carcinoma (HCC), poses a severe global public health threat owing to its high incidence, frequent late-stage diagnosis, and poor 5-year survival rate. Conventional approaches to liver cancer diagnosis and treatment are limited by their reliance on subjective physician experience, uniform and undifferentiated treatment strategies, and imprecise prognostic assessment. This review synthesizes studies published between 2019 and 2025 on the application of multi-modal data in liver cancer care, including computed tomography (CT), magnetic resonance imaging (MRI), pathology, and multi-omics data. We explore the utility of single-modal data analysis including the role of CT or MRI in enhancing diagnostic accuracy and the application of pathological data. Subsequently, the review focuses on multi-modal data fusion strategies, including feature-level, decision-level, and modal-level fusion, which collectively support precision diagnosis, personalized treatment recommendation, and accurate prognosis prediction in clinical practice. Additionally, it addresses critical challenges such as data heterogeneity and low physician acceptance of integrated data-driven tools, while outlining future directions including the development of standardized multi-modal data ecosystems. This review highlights multi-modal data as a core driver of precision liver cancer care, with the objective of accelerating its translation into routine clinical practice.
Aim: Microvascular invasion (MVI) and recurrence significantly impact hepatocellular carcinoma (HCC) prognosis. This study aims to develop a multi-task deep learning (DL) model using contrast-enhanced computed tomography (CT) to predict preoperative MVI, recurrence-free survival (RFS), and overall survival (OS).
Methods: Preoperative CT scans from 308 patients across five institutions were collected for training and internal validation. A multi-task 3D neural network was trained using a novel augmentation strategy. An independent external cohort (n = 80) from Institution VI was used to rigorously assess generalizability. Model performance was assessed using the concordance index (C-index) for RFS/OS and the F1-score for MVI.
Results: In the training cohort (n = 192), the model achieved an MVI F1 score of 0.739, and C-indices of 0.965 (OS) and 0.869 (RFS). In the internal validation cohort (n = 116), the corresponding values were 0.716, 0.831, and 0.741, respectively. Notably, in the independent external cohort, the model maintained robust performance, with an OS C-index of 0.767, RFS C-index of 0.733, and MVI F1 score of 0.708. Class activation maps confirmed that the model focused on clinically relevant liver regions.
Conclusion: Our interpretable multi-task DL model demonstrates robust predictive capabilities for RFS, OS, and MVI in HCC patients across multiple centers, offering a non-invasive tool to enhance clinical decision-making.
Kupffer cells, the resident liver macrophages, are characterized by self-renewal capacity and extensive plasticity. Kupffer cells are involved in the regulation of several liver functions such as the maintenance of liver tolerance against antigens arriving at the liver through the portal vein, the autophagy and apoptosis of hepatocytes and other liver sinusoidal cells.and various metabolic functions such as iron homeostasis and lipid metabolism. In acute liver injury, Kupffer cells are involved in both liver damage and resolution. During chronic liver injury, resident and bone marrow-derived macrophages drive either the progression or resolution of fibrosis and cirrhosis. Inevitably, they are implicated in the initiation, progression or defense against hepatocellular carcinoma (HCC) as members of the tumor microenvironment together with bone marrow-derived macrophages. The present review describes the heterogeneity of Kupffer cells and liver-infiltrating macrophages, their functions and their participation in liver cancer with particular emphasis on factors modulating their pro-tumoral and anti-tumoral differentiation. The review is further focused on their involvement in HCC as they participate in the population of tumor-associated macrophages. Finally, the potential use of Kupffer cells and macrophages for the treatment of HCC, including the potentiation of immune checkpoint inhibitors, is presented.
The Multiparametric Therapeutic Hierarchy (MTH) has been proposed as an evolution of the Barcelona Clinic Liver Cancer (BCLC) algorithm to better reflect the complexity of real-world hepatocellular carcinoma (HCC) management. While the BCLC often assumes idealised conditions, the MTH explicitly incorporates “treatment unfeasibility” as a variable in clinical decision-making, a concept this review seeks to examine and refine. We propose that unfeasibility should not be limited to absolute contraindications but should be understood as a multidimensional construct comprising four interacting dimensions: (1) Technical Feasibility; (2) Resources; (3) Equity; and (4) Values and Acceptability. This concept of unfeasibility adapts the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence-to-Decision (EtD) framework, originally designed for population-level guideline development, to individual-level clinical reasoning. At the point of care, the five EtD domains (Feasibility, Resources, Acceptability, Equity, and Values and Preferences) converge into a unified assessment of treatment feasibility for the specific patient. A precise mapping between our four dimensions and the original GRADE domains is provided. This approach is complementary to, rather than a departure from, GRADE methodology and is particularly relevant in settings characterised by low or very low certainty of evidence. Our analysis reveals a recurring inverse relationship between therapeutic efficacy and feasibility: the most effective treatments, such as liver transplantation, are often constrained by technical, resource-related, and systemic barriers. This tension results in widespread undertreatment across the HCC population. By defining unfeasibility as a key element of expert reasoning, this framework aims to enhance transparency in how multidisciplinary tumour boards weigh multiple considerations when making individualised treatment decisions under uncertainty, without prescribing decision rules or treatment recommendations.
FOLFOX (oxaliplatin, leucovorin, 5-fluorouracil)-based hepatic arterial infusion chemotherapy (FOLFOX-HAIC) has emerged as a promising locoregional strategy in the multimodal management of hepatocellular carcinoma (HCC), particularly for patients with intermediate or advanced-stage disease. This narrative review summarizes recent clinical evidence on the application of FOLFOX-HAIC across the therapeutic continuum: in conversion, neoadjuvant, and adjuvant settings. We conducted an analysis based on a search of PubMed, Embase, China National Knowledge Infrastructure (CNKI) and conference abstracts, which incorporated phase II/III trials, retrospective cohort studies, multicenter real-world studies, and meta-analyses. Evidence indicates that FOLFOX-HAIC, especially when combined with targeted therapy and immunotherapy, yields superior objective response rates and higher rates of conversion to curative resection compared to conventional transarterial chemoembolization (TACE). Furthermore, as postoperative adjuvant therapy, it significantly reduces recurrence risk and prolongs survival in high-risk patients, such as those with microvascular invasion. In the neoadjuvant setting, these combinations can induce profound pathological responses, potentially improving outcomes for resectable patients at high risk of recurrence. Consequently, FOLFOX-HAIC represents an evolving cornerstone of HCC therapy. However, current evidence is largely derived from retrospective and small prospective studies, underscoring the urgent need for large-scale phase III randomized controlled trials to standardize regimens, optimize patient selection, and confirm long-term survival benefits.
Aim: Oxaliplatin (OXA), a cornerstone chemotherapeutic agent for malignant tumors, can induce hepatic steatosis, inflammation, and fibrosis, meeting the criteria for drug-induced fatty liver disease (DIFLD). However, OXA-induced DIFLD lacks a clear definition and effective interventions. Therefore, our study aimed to verify the OXA-DIFLD link and explore cordycepin’s protective role in DIFLD.
Methods: (1) A retrospective analysis was conducted to compare the degrees of hepatic inflammation, fibrosis, and steatosis among 161 patients with colorectal cancer liver metastasis in the OXA chemotherapy (OCG) and non-chemotherapy (NCG) groups; (2) Fifteen mice were randomly allocated into Control, OXA, and OCordy (OXA + cordycepin) groups. The OXA and OCordy groups received OXA (8 mg/kg, 3 days) injections to induce acute DIFLD; the OCordy group additionally received oral cordycepin (100 mg/kg, 6 days). Liver injury across the three groups was assessed via hepatic pathology, serum biochemical indicators, and oxidative stress markers; (3) Untargeted metabolomics and Data-Independent Acquisition (DIA) proteomics were conducted across the three groups to clarify OXA-induced liver injury mechanisms and pinpoint targets for cordycepin intervention.
Results: (1) Clinical investigations demonstrated markedly elevated hepatic inflammation, fibrosis, and steatosis in the OCG group compared with the NCG group; (2) Animal experiments showed that OXA induced hepatic dysfunction, lipid accumulation, and oxidative stress, which were mitigated by cordycepin; (3) Multi-omics analyses revealed that OXA disrupted lipid metabolism and oxidative stress pathways, whereas cordycepin restored homeostasis by modulating arginine biosynthesis and bile secretion and suppressing α-ketoglutarate levels.
Conclusion: This study characterized OXA-induced DIFLD and validated cordycepin’s protective effects via the α-ketoglutarate-arginine/bile acid axis, offering a foundation for treating OXA-induced liver injury.
Hepatocellular carcinoma (HCC) is a malignant tumor with extremely high global morbidity and mortality. Its initiation and progression are tightly associated with the complex tumor microenvironment (TME), which drives immune escape and treatment resistance in liver cancer. In recent years, epigenetic regulation, particularly histone modification mediated by cellular metabolism, has emerged as a critical advance in deciphering tumor malignant behavior and its interaction with the microenvironment. Histone lactylation, a newly identified post-translational modification directly mediated by lactate, offers a novel perspective for understanding how abnormal tumor metabolism (especially the Warburg effect) shapes the immune microenvironment via epigenetic reprogramming. This review elaborates on the role of histone lactylation in HCC progression, focusing on its mechanisms in regulating oncogenic signaling pathways, metabolic reprogramming and reshaping the HCC TME, thereby serving as a core node in metabolic-epigenetic-immune crosstalk. In addition, we summarize the intervention strategies and drug development targeting this modification, and discuss future directions, aiming to provide a basis for the development of novel HCC therapeutic strategies based on metabolic-epigenetic regulation.