Journal of Hepatocellular Carcinoma最新文献

Purpose: The anti-tumor effects of Dendrobium officinale, as a medicinal and dietary Chinese medicine, have long been documented. However, the mechanism of action for its therapeutic effect has not been fully elucidated.

Methods: The chemical constituents of Dendrobium officinale were screened using PubMed, CNKI, and Wanfang databases. Swiss Target Prediction was used to predict ingredient targets, while liver cancer targets were obtained from multiple databases. Venny 2.1.0 software identified intersection genes between the drug and disease, and a Protein-Protein Interaction (PPI) network was constructed. The DAVID database was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Following this, the compound molecules were docked onto the core targets, and a visual analysis was conducted. The network pharmacology results were experimentally validated through in vitro studies with HepG2 cells.

Results: The study identified 17 core components and 374 ingredient targets, with 1,249 disease targets collected from databases, yielding 50 overlapping targets. GO analysis revealed 284 Biological Process (BP) terms, 38 Cellular Component (CC) terms, and 75 Molecular Function (MF) terms. KEGG enrichment highlighted key pathways, including Pathways in cancer, PI3K-AKT signaling, Prostate cancer, and Proteoglycans in cancer. Molecular docking showed strong activity of Butin, Skimmin, and N-p-Coumaroyltyramine with core targets AKT1, EGFR, and CCND1. In vitro experiments demonstrated that Dendrobium officinale aqueous extracts significantly inhibited HepG2 cell proliferation. Western blotting analysis further revealed that the extracts downregulated the expression levels of p-PI3K, PI3K, AKT1, EGFR, and CCND1 proteins.

Conclusion: The key active components of Dendrobium officinale in treating liver cancer include butin, skimmin, and N-p-coumaroyltyramine, etc. The specific mechanism of action may be related to the modulation of targets such as p-PI3K/PI3K, AKT1, EGFR, and CCND1, and signaling pathways such as PI3K-Akt.

Purpose: To develop machine learning radiomics models for preoperative risk stratification of multifocal hepatocellular carcinoma (MHCC) beyond Milan criteria.

Methods: Patients with pathologically proven MHCC beyond Milan criteria between January 2015 and January 2019 were retrospectively included. Radiomic features were extracted from tumor, peritumor, and tumor-peritumor regions using multiparametric MRI (mpMRI). An unsupervised spectral clustering algorithm was used to identify radiomics-based patient subtypes. Radiomics risk scores (RRS) for overall survival (OS) and recurrence-free survival (RFS) were generated using supervised extreme gradient boosting (XGBoost)-LASSO Cox proportional hazard regression analysis. The Concordance index (C-Index) was used to evaluate the model performance in the training and validation sets.

Results: A total of 156 patients were divided into training (n = 78) and validation (n = 78) groups. Two distinct unsupervised subtypes were identified using spectral clustering, and subtype B was associated with worse OS and poor RFS. Incorporating radiomics predictors into the conventional preoperative clinical-radiological features improved the OS prediction performance (training set: from 0.616 to 0.712; validation set: from 0.522 to 0.710), and RFS prediction (training set: from 0.653 to 0.735; validation set: from 0.574 to 0.698). The combined models showed good predictive performance for 5-year OS (AUC, 0.77) and RFS (AUC, 0.81) in the training set and for 5-year OS (AUC, 0.75) and RFS (AUC, 0.76) in the validation set.

Conclusion: Two preoperative models combining mpMRI-based clinico-radiological and radiomics predictors effectively predicted outcomes for patients with MHCC beyond the Milan criteria.

Background: Transarterial chemoembolization (TACE) remains a cornerstone for unresectable hepatocellular carcinoma (uHCC) but is limited by tumor progression. Combining TACE with systemic therapies may enhance efficacy. Notably, sintilimab combined with bevacizumab biosimilar has shown synergistic effects in tumor control and has been incorporated into the first-line treatment regimen in China. This study evaluates the therapeutic efficacy and safety of TACE combined with sintilimab and bevacizumab biosimilar in patients with uHCC.

Methods: This retrospective cohort study analyzed 76 uHCC patients who received TACE plus sintilimab-bevacizumab biosimilar at the First Affiliated Hospital of Guilin Medical University between September 2020 and March 2024, with follow-up continuing until March 31, 2025. The primary outcomes, overall survival (OS) and progression-free survival (PFS), were evaluated through Kaplan-Meier survival analysis. Independent risk factors for OS and PFS were evaluated using both univariate and multivariate analyses. Secondary outcomes comprised objective response rate (ORR), disease control rate (DCR), and treatment-related adverse events (tr-AEs).

Results: The study cohort comprised 76 patients meeting predefined eligibility criteria, achieving median OS of 23.2 months and median PFS of 14.5 months. Tumor response was assessed per mRECIST criteria, demonstrating an ORR of 59.2% and DCR of 81.6%. Multivariable analysis confirmed the modified albumin-bilirubin (mALBI) grade 3, alpha-fetoprotein (AFP) level, and macrovascular invasion as independent risk factors for OS and PFS (all P<0.05). All tr-AEs were manageable, with no fatal events reported.

Conclusion: TACE combined with sintilimab and bevacizumab biosimilar demonstrated favorable efficacy and manageable safety in patients with uHCC.

Background: Conversion therapies after immune checkpoint inhibitors (ICIs) plus tyrosine-kinase inhibitors (TKIs) provide curative surgery chance and prolong survival for unresectable hepatocellular carcinoma (uHCC). However, only some patients have the opportunity to receive conversion therapies. To this end, we aimed to develop and validate a machine-learning model to identify patients who may have the chance to undergo conversion therapy.

Methods: This retrospective cohort study included 443 patients with uHCC who received ICIs and TKIs from four centers. Variables were analyzed using univariate and multivariate logistic regression to identify independent indicators of conversion therapy. The Gradient Boosting Machine (GBM) algorithm was used to develop and validate model, and the Shapley additive explanation algorithm was used to mechanically explain the prediction of the model.

Results: Overall, 84 (19%) patients underwent conversion therapy, and their prognosis were significantly longer than those did not (P < 0.05). CA125 level, pre-TKI therapy, pre-antiviral therapy, lymph node metastasis status, and number of intrahepatic lesions were identified as indicators of conversion therapy. The GBM-based combined model outperformed the BCLC classification (P < 0.05), yielding an AUC of 0.76 and 0.74 in the training and external validation cohorts, respectively. Survival analyses indicated that patients who underwent surgery as conversion therapy had a better prognosis than those who underwent ablation therapy (P < 0.05).

Conclusion: The GBM-based combined model could identify patients who may benefit from conversion therapy for uHCC treated with ICIs and TKIs. Surgical resection as curative conversion therapy may provide better survival benefits than ablation therapy.

Background: Unresectable hepatocellular carcinoma (uHCC) remains a major clinical challenge with limited effective therapeutic options. Triple therapy combining interventional treatments, donafenib, and anti-PD-1 monoclonal antibodies has shown promise in recent studies, but real-world data remain limited.

Objective: To evaluate the real-world efficacy and safety of triple therapy with interventional treatment, donafenib, and anti-PD-1 monoclonal antibodies in patients with uHCC.

Methods: This retrospective study included 89 patients with uHCC who received donafenib, anti-PD-1 monoclonal antibodies (tislelizumab or sintilimab), and interventional therapies (TACE and/or HAIC) between March 2022 and December 2023. Outcomes included objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and safety. Efficacy was assessed using modified RECIST (mRECIST) criteria; prognostic factors were analyzed using Cox regression models.

Results: Among 89 patients, the ORR was 75.3% and the disease control rate was 100%. The median PFS was 18.5 months (95% CI: 15.0-NA); median OS was not reached after a median follow-up of 13.7 months. PFS rates at 6, 12, and 18 months were 87.6%, 72.4%, and 52.7%, and OS rates were 93.3%, 81.6%, and 72.4%, respectively. Conversion surgery was achieved in 15.7% of patients. Subgroup analysis indicated that ECOG PS 1, extrahepatic metastases, and high baseline AFP were associated with worse survival outcomes, while interventional modality did not significantly affect prognosis. Multivariate analysis confirmed ECOG PS 1 and extrahepatic metastases as independent predictors of shorter PFS, and ECOG PS 1 and elevated AFP as independent predictors of worse OS. Grade ≥3 treatment-related adverse events occurred in 30.3% of patients; no treatment-related deaths were reported.

Conclusion: The combination of interventional therapies, donafenib, and anti-PD-1 monoclonal antibodies demonstrated promising efficacy and manageable safety in uHCC, warranting further validation in prospective trials.

Background: The tumor immune microenvironment (TME) plays a key role in the development of hepatocellular carcinoma (HCC). As the important components of TME, interleukin-2 (IL-2) mediates immune responses by specifically binding to the interleukin-2 receptor (IL-2R). This study aimed to explore the role of IL-2R in HCC development and provided possible clinical implications in HCC prognosis and treatment.

Methods: The IL-2R genetic data were acquired from publicly available TCGA and CCLE databases. Data processing and analysis, including construction of the prognostic model and evaluation of immune status in HCC, were performed on Xiantao platform by using statistical methods including the Wilcoxon test, Cox regression analysis, correlation analysis. GEPIA2 was used to explore the relationship between IL-2R genes expression and clinical stages, while genetic variations in IL-2R subunits in HCC were determined using cBioPortal. The IL-2Rα co-expression gene analysis was conducted on the LinkedOmics database. Enzyme-linked immunosorbent assay (ELISA), colorimetric method, and flow cytometric method were used to analyze peripheral blood samples from patients with HCC.

Results: A prognostic risk model was established by incorporating IL-2Rα, IL-2Rβ, and IL-2Rγ expression. The infiltration levels of B cell memory, T cell regulatory cells (Tregs), and immune checkpoints (PDCD1, CTLA4, CD274 and TIGIT) were significantly elevated in high-risk group of the risk model. Additionally, sIL-2Rα levels were positively correlated with tumor-specific growth factor (TSGF) and Tregs in the peripheral blood of HCC patients.

Conclusion: The prognostic risk model based on IL-2R subunits may play a role in the regulation of immune function within the HCC tumor microenvironment. Besides, IL-2Rα may act as a more important role in HCC development among the three IL-2R subunits. Further research will be needed to verify these initial findings. Overall, these results may provide important insights in clinical prognosis and therapeutic strategies for HCC.

Background: Hepatocellular carcinoma (HCC) is a prevalent lethal cancer that remains challenging to treat. Therefore, investigation of novel targets and therapeutic strategies is essential. The role of ZBED4 in cancer remains unclear.

Methods: Data were sourced from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), and Genomics of Drug Sensitivity in Cancer (GDSC) databases. Various web platforms and R software, have been utilized. Multiplex immunofluorescence was performed on a human HCC tissue microarray.

Results: High ZBED4 expression correlates with poor prognosis and immune cell infiltration in multiple cancers. ZBED4 is potentially involved in the regulation of the tumor environment by T cells, with a focus on CD8⁺ T cells. In HCC, tissues with elevated ZBED4 expression exhibit a higher prevalence of Tregs and neutrophils, whereas those with reduced ZBED4 expression show an increased abundance of CD8⁺ T cells, activated CD4⁺ T cells, gamma/delta T cells, and activated natural killer (NK) cells. Elevated ZBED4 expression in HCC patients is associated with a reduced response to immune checkpoint blockade but an improved response to chemotherapy and most targeted therapies. A multi-gene prognostic signature has been developed and confirmed across various HCC cohorts. Multiplex immunofluorescence study demonstrated that ZBED4 was linked to poor prognosis and negatively correlated with CD8⁺ T cell infiltration.

Conclusion: Our research elucidates the role of ZBED4, its strong link to immune infiltration, and its potential as a prognostic and therapeutic biomarker for HCC.

Purpose: To establish a patient charter that articulates the principles of quality care for individuals living with hepatocellular carcinoma (HCC), aiming to improve patient outcomes and survival rates globally.

Methods: A multidisciplinary group comprising healthcare professionals, patient advocacy representatives, and policymakers convened to identify the critical areas of unmet need in HCC care. The group shared patient experiences, barriers, and insights - particularly with input from Patient Advocacy Groups (PAGs) - to better understand the challenges faced by patients. They reviewed existing literature, current care practices, and patient experiences to formulate a patient charter that outlines the principles of quality care for HCC.

Results: The patient charter identifies the seven principles of quality care that people with HCC or at risk of developing HCC should expect to receive in order to benefit from improved outcomes and increased survival. These principles address the need for policy prioritization, early diagnosis, multidisciplinary care, personalized treatment, shared decision-making, stigma-free access to services and increased research funding.

Conclusion: The patient charter serves as a call to action for stakeholders to unite in enhancing the care and treatment of HCC, with the ultimate goal of improving health outcomes for patients.

Introduction: Large language models (LLMs) are increasingly used in healthcare, yet their reliability in specialized clinical fields remains uncertain. Liver cancer, as a complex and high-burden disease, poses unique challenges for AI-based tools. This study aimed to evaluate the comprehensibility and clinical applicability of five mainstream LLMs in addressing liver cancer-related clinical questions.

Methods: We developed 90 standardized questions covering multiple aspects of liver cancer management. Five LLMs-GPT-4, Gemini, Copilot, Kimi, and Ernie Bot-were evaluated in a blinded fashion by three independent hepatobiliary experts. Responses were scored using predefined criteria for comprehensibility and clinical applicability. Overall group comparisons were conducted using the Fisher-Freeman-Halton test (for categorical data) and the Kruskal-Wallis test (for ordinal scores), followed by Dunn's post-hoc test or Fisher's exact test with Bonferroni correction. Inter-rater reliability was assessed using Fleiss' kappa.

Results: Kimi and GPT-4 achieved the highest proportions of fully applicable responses (68% and 62%, respectively), while Ernie Bot and Copilot showed the lowest. Comprehensibility was generally high, with Kimi and Ernie Bot scoring over 98%. However, none of the LLMs consistently provided guideline-concordant answers to all questions. Performance on professional-level questions was significantly lower than on common-sense ones, highlighting deficiencies in complex clinical reasoning.

Conclusion: LLMs demonstrate varied performance in liver cancer-related queries. While GPT-4 and Kimi show promise in clinical applicability, limitations in accuracy and consistency-particularly for complex medical decisions-underscore the need for domain-specific optimization before clinical integration.

Trial registration: Not applicable.

Objective: This retrospective study was conducted to evaluate the effectiveness and safety of a new combination therapy of the multi-level comprehensive collateral artery embolism (CAE) sequential hepatic arterial infusion chemotherapy (HAIC), tyrosine kinase inhibitors (TKI) and immune checkpoint inhibitors (ICI) for unresectable huge hepatocellular carcinoma (>10cm) patients.

Methods: A propensity score-matching (PSM) cohort study was conducted. The initial tumor response, treatment-related adverse events, and survival outcomes were compared. The Forestplot package was used to visualize and interpret forest plots of overall survival subgroup analyses. Univariate and multivariate analyses were conducted to explore the risk factors of overall survival.

Results: Thirty-one pairs of patients were evaluated after PSM. There were statistically significant differences in the initial tumor response and objective response rate (ORR) between the two groups (74.2% vs 48.4%, P=0.037). Compared with the "HAIC" group, the incidence of abdominal pain was higher in the "CAE+HAIC" group (71.0% vs 41.9%, P=0.021). The OS and progression-free survival (PFS) of the "CAE+HAIC" group were longer than those of the "HAIC" group (OS: HR=0.439, 95% CI: 0.199-0.970, P=0.042; PFS: HR=0.475; 95% CI: 0.252-0.895; P=0.021). The CAE (HR=0.403, 95% CI: 0.213-0.762; P=0.005), prealbumin levels <170 mg/L (HR=2.195, 95% CI: 1.226-3.929; P=0.008), and lactic dehydrogenase levels >245 U/L (HR=2.136, 95% CI: 1.215-3.757; P=0.008) were independent risk factors of OS.

Conclusions: The multi-level comprehensive CAE sequential HAIC, combined with TKI and ICI, can improve tumor response and prolong survival time in unresectable huge HCC patients while remaining safe and tolerable.