Journal of Hepatocellular Carcinoma最新文献

Background: Transarterial chemoembolization (TACE) is widely used for unresectable hepatocellular carcinoma (HCC) and as adjuvant therapy to prevent postoperative recurrence. However, accurate prognostic models for HCC patients undergoing TACE remain underutilized clinically.

Methods: This retrospective study included 265 HCC patients who underwent TACE, randomly assigned to training and validation sets (6:4 ratio). Recurrence-related risk factors were identified using Cox regression and further screened by Least Absolute Shrinkage and Selection Operator (LASSO) regression. A prognostic nomogram was constructed, with decision curve analysis (DCA) assessing its clinical utility.

Results: Univariate Cox regression identified sex, vascular invasion, ascites, modified albumin-bilirubin grade (mALBI), China Liver Cancer (CNLC) staging, white blood cell count, neutrophils, fibrinogen (Fib), and neutrophil-to-lymphocyte ratio as significant risk factors (all HR > 1, P < 0.05). Albumin (ALB), prognostic nutritional index, and alkaline phosphatase-to-albumin ratio (AAPR) were protective factors (all HR < 1, P < 0.05). Multivariate analysis identified elevated Fib and higher CNLC stage as independent predictors (all P < 0.05). LASSO extracted vascular invasion, neutrophils, ALB, activated partial thromboplastin time, Fib, and AAPR as prognostic variables. Areas under the ROC curve at 6 months, 1 year, and 2 years were 0.717, 0.794, and 0.884, respectively. DCA demonstrated greater net clinical benefit than Barcelona Clinic Liver Cancer and CNLC staging systems. Risk stratification by nomogram tertiles showed significantly earlier recurrence in high-risk patients (all P < 0.05).

Conclusion: This TACE-based prognostic nomogram integrating clinical and laboratory parameters accurately predicts postoperative recurrence and enables individualized risk stratification, assisting clinicians in tailoring interventions and delivering personalized therapy.

Purpose: Targeted therapy for hepatocellular carcinoma (HCC) is limited by drug resistance and other constraints, leaving treatments sub-optimal and making identification of new target genes urgent. Nuclear pore protein 205 (NUP205) is highly expressed in HCC and associated with poor prognosis but mechanisms of action remain unclear. The current study investigated functions of NUP205 in HCC.

Methods: Bioinformatics analyses of NUP205 expression in HCC samples from The Cancer Genome Atlas, Gene Expression Omnibus and Kaplan-Meier databases were conducted. Proliferation and apoptosis were measured in HCC LM3 and SK-Hep1 cells with NUP205 knockdown and overexpression and growth of HCC xenografts in a nude mouse model. The stability of Yes-associated protein (YAP1) mRNA and protein in cells with NUP205 knockdown and overexpression was assessed.

Results: NUP205 was overexpressed in HCC tissues and expression correlated with pathological grade and prognosis. NUP205 knockdown in vitro inhibited cell proliferation 2-3-fold, induced apoptosis 4-5-fold and suppressed in vivo tumor growth by 40%. Opposing effects were found for NUP205 overexpression. NUP205 acted via the ubiquitin-proteasome pathway to stabilize YAP1 protein.

Conclusion: NUP205 stabilizes YAP1 and may be considered to act as an HCC oncogene. The NUP205-YAP1 axis may be a therapeutic target.

Immune checkpoint inhibitors have significantly transformed the treatment of advanced solid tumors, revolutionizing the therapeutic landscape. However, drug resistance is a key clinical obstacle to the application of immune checkpoint inhibitors in patients. We describe a patient who developed pulmonary metastases from hepatocellular carcinoma 5 years after hepatectomy. After continuous targeted therapy and immunotherapy, the lesion still progressed slowly, but after ablation of one lesion, the other lesions were significantly reduced when immunotherapy was used again. This case might provide insight into to the current low response rate to immunotherapy, providing a new direction for further exploration.

Purpose: Transcatheter arterial chemoembolization (TACE) resistance compromises prognosis in unresectable hepatocellular carcinoma (HCC). This study aimed to develop an interpretable prediction model using machine learning (ML) and Shapley Additive Explanations (SHAP) for preoperative assessment of TACE resistance.

Patients and methods: A single-center retrospective analysis included 562 HCC patients who received ≥3 TACE sessions (2013-2024). Multi-modal features (blood routine, coagulation, biochemistry, imaging) were integrated. Seven ML models (LR, RF, DT, XGBoost, LightGBM, SVM, ANN) were constructed. Feature selection used univariate Logistic regression and Lasso regression. Model performance was evaluated via AUC, F1 score, and accuracy; SHAP analyzed feature importance.

Results: Data were split into training (n=394, 70%) and validation (n=168, 30%) sets. Seven core predictors (NLR, tumor capsule integrity, AFP, etc.) were identified. XGBoost outperformed other models, with AUCs of 0.942 (95% CI: 0.919-0.966) and 0.898 (95% CI: 0.853-0.944) in training and validation sets, respectively, and an F1 score of 0.741. SHAP revealed NLR (mean Shapley value=0.13) and tumor capsule absence (0.08) as the strongest predictors.

Conclusion: This interpretable ML model efficiently predicts TACE resistance using multi-modal data, with AUC>0.8. It offers a preoperative tool to identify high-risk patients, optimize treatment strategies, and holds significant clinical translational value.

Purpose: This study aimed to investigate the clinical significance of MAP4 in hepatocellular carcinoma (HCC), particularly its association with metastasis-related early recurrence after curative hepatic resection.

Patients and methods: We enrolled 172 patients with hepatitis B virus-associated HCC (HBV-HCC) who underwent curative resection in our cohort. After excluding potential confounders such as vascular invasion and portal vein thrombosis, 101 patients were selected for MAP4 gene expression analysis by qRT-PCR. Kaplan-Meier and Cox regression analyses were conducted to evaluate its association with early recurrence and prognostic factors. Our findings were further validated in an independent cohort.

Results: MAP4 expression was upregulated in HCC cell lines and tumor tissues, compared to their corresponding non-tumorous controls. The clinical analysis showed that high MAP4 overexpression in liver tumor tissues was positively correlated with early (p = 0.042) rather than late recurrence (p = 0.221) in our cohort. Moreover, it was linked to shorter recurrence-free survival (p = 0.023) and reduced overall survival (p = 0.015). The expression level of serum alpha-fetoprotein (p = 0.001), tumor size (p = 0.012), tumor number (p = 0.018), satellite tumor (p = 0.001), and MAP4 expression (p = 0.042) were correlated with HCC early recurrence by univariate analysis. Consistent clinical findings were observed in the validation cohort.

Conclusion: This study demonstrated that MAP4 overexpression in liver tumor tissue was positively correlated with early recurrence in HBV-HCC patients following curative hepatic resection, providing insights into its clinical significance and potential involvement in underlying molecular mechanisms, particularly in metastasis-related early recurrence.

Background: Hepatocellular carcinoma (HCC) exhibits significant molecular heterogeneity and complex immune microenvironment, which to some extent limits the accuracy of prognosis assessment and the formulation of individualized treatment strategies. This study aims to identify immune-derived molecular signatures based on multi-omics data and machine learning methods for the prognosis prediction and risk stratification of HCC.

Methods: Based on weighted gene co-expression network analysis(WGCNA) and differential gene analysis,immune-derived molecular signature (IDMS) were screened in both single-cell and bulk transcriptomes. Prognostic model was constructed by multi-machine learning approachs. Subsequently, we investigated the differences in mutations, biological functions, and immune cell infiltration within the tumor microenvironment between the high- and low-risk groups.In addition, we comprehensively analyzed the drug sensitivity of IDMS and predicted potential drugs.

Results: We identified seven hub genes at the single-cell and bulk transcriptome levels. Based on multiple machine learning, we constructed a prognostic model that demonstrated excellent performance in predicting overall survival for patients with HCC. IDMS -integrated normograms provide a promising and quantitative tool for clinical risk management.Notably, a significant difference in microsatellite instability (MSI) was observed between the high- and low-risk groups. This indicates that patients in the high-risk group might have a better response to immunotherapy. Additionally, we predicted potential drugs targeting to these risk subgroups.

Conclusion: Our research developed an IDMS that could serve as an effective tool for patient stratification management and prognosis prediction. This signature could provide a reference for immunotherapy for patients with HCC and improve their prognosis.

Background: Hepatocytes demonstrate significant heterogeneity between normal liver tissue and hepatocellular carcinoma (HCC), with malignant hepatocytes playing a crucial role in remodeling the tumor microenvironment through specific ligand-receptor interactions. However, the mechanisms by which hepatocytes drive HCC progression at the single-cell level remain poorly understood.

Methods: We analyzed single-cell RNA sequencing datasets (GSE174748 and GSE166635) from the GEO database using CellChat to decode intercellular communication networks, which specifically revealed enhanced EPHA signaling in HCC hepatocytes and identified EFNA1-EPHA1 as the most prominent ligand-receptor pair. This key finding was validated through immunofluorescence analysis in both clinical HCC tissues and HepG2/LO2 cell lines, and its clinical relevance was assessed using the TCGA-LIHC dataset via UALCAN.

Results: Single-cell analysis revealed that HCC hepatocytes act as both senders and receivers of pro-tumorigenic signals, with upregulated expression of malignancy-related genes (AFP, ACSL4, and SERPINA1). CellChat inference demonstrated significantly strengthened outgoing interaction signals from hepatocytes in the HCC microenvironment. The EFNA1-EPHA1 axis was identified as a key mediator of hepatocyte-microenvironment crosstalk, showing marked activation in HCC tissues and high co-expression in HepG2 cells. TCGA analysis confirmed EFNA1 upregulation in HCC, correlating with advanced clinical stage, higher tumor grade, and metastatic events.

Conclusion: Our study provides single-cell resolution evidence that malignant hepatocytes promote HCC progression through autocrine and paracrine signaling via the EFNA1-EPHA1 axis, reshaping the tumor microenvironment. These findings delineate a key autocrine-paracrine mechanism in HCC progression and nominate the EFNA1-EPHA1 axis as a promising candidate for therapeutic development.

Curative surgical treatment of hepatocellular carcinoma (HCC) is limited to liver transplantation (LT) and liver resection (LR), but many patients are ineligible due to insufficient future liver remnant (FLR). Liver venous deprivation (LVD) induces more rapid hypertrophy than portal vein embolization (PVE) but may trigger the hepatic arterial buffer response (HABR), leading to increased arterial inflow and potentially stimulating tumor growth, especially for HCC. We report a 75-year-old male with HCC and advanced fibrosis, in whom extended LVD was followed 3 days later by balloon-occluded transarterial chemoembolization (B-TACE) to coincide with HABR, providing more selective tumor control, higher intratumoral drug concentration, and low risk of non-target embolization compared to standard TACE, which is desirable in the field of deprived livers. Within three weeks, FLR increased from 33% to 51% with degree of hypertrophy (DH) 15.8%, kinetic growth rate (KGR) 5.3%/week and relative growth rate (RGR) 47,6% accompanied by near-complete tumor response, enabling curative hepatectomy. Despite postoperative complications, R0 resection was achieved. This case illustrates the technical feasibility of sequential LVD followed by B-TACE in this specific order, suggesting that such an approach may help reduce the hepatic arterial buffer response within the tumor, support rapid hypertrophy, and facilitate resectability in carefully selected patients, including elderly individuals with comorbidities. To the best of our knowledge, and based on a comprehensive literature search, this is the first reported case of LVD-B-TACE.

Liver cancer is ranked as the sixth most prevalent and the third deadliest cancer worldwide. Macrophages play a crucial role in cancer resistance mechanisms, and the regulation of their polarization state can alter their anti-tumor activity. Additionally, alterations in liver cancer pathways can shift the polarization of macrophages. Inflammatory agents and medications have the potential to alter macrophage polarization, favoring M1 differentiation and enhancing their anti-tumor activity. This review explores metabolic alterations in liver cancer, macrophage polarization processes, and their interconnections in hepatic oncogenesis. It further elaborates on the prospects and challenges of investigating targeted macrophage metabolism for liver cancer treatment. Modulating macrophage metabolic pathways represents a promising therapeutic approach for hepatic carcinoma.

Objective: To evaluate the benefit of nomogram-based model for predicting response and survival in patients with early recurrent hepatocellular carcinoma after hepatic resection by CK19 positive expression treated with transarterial chemoembolization (TACE).

Materials and methods: We retrospectively analyzed 82 patients with early recurrent HCC expressing CK19 positivity after hepatectomy who underwent TACE between January 2014 and December 2023. OS and PFS were compared using the Kaplan-Meier method and Log rank test. Based on the COX regression results, independent predictors were identified from them. These factors were used to construct a nomogram model. The discriminatory, predictive efficacy of this model was assessed using receiver operating characteristic curves (ROC), calibration curves, and internal validation.

Results: CK19 expression grade and distant metastasis were independent prognostic risk factors, and the number of TACE sessions and whether it was combined with systemic therapy were prognostic protective factors, and survival after resection was strongly correlated with the CK19 grade. Compared with TACE alone, TACE combined with targeted and immunotherapy provided more survival benefit for patients with CK19-positive postoperative recurrence. The nomogram model has promising predictive efficacy.

Conclusion: We constructed a validated tool for the prognosis of patients with postoperative recurrence of hepatocellular carcinoma, which helps to identify the risk level of hepatocellular carcinoma recurrence and optimize the treatment as early as possible in the clinic, and brings survival benefit to patients.