European and Swiss guidelines recommend hepatocellular carcinoma surveillance of high-risk patients every 6 months using ultrasound (US), with/without α-fetoprotein (AFP). Other surveillance strategies are available, but evidence of their comparative cost-effectiveness is lacking. This study evaluated the cost-effectiveness of current hepatocellular carcinoma surveillance strategies in Switzerland, including the novel GAAD (gender [biological sex], age, α-fetoprotein, protein induced by vitamin K absence or antagonist-II [PIVKA-II]) serum-based algorithm in high-risk patients. A micro-simulated Markov model estimated the cost-effectiveness of hepatocellular carcinoma surveillance strategies (no surveillance, US, US+AFP, GAAD) performed at 6-monthly intervals in a simulated cohort of 100,000 patients with compensated liver cirrhosis over a lifetime horizon. Performance parameters were sourced from published meta-analyses and multicentre study data. Epidemiological parameters were estimated based on literature identified during a previous systematic literature review. Similarly, utility parameters were sourced from published literature. Costs were sourced from TARMED, the Analysis List, the Swiss Federal Statistical Office, publicly available data and published literature. Primary outcomes were life years lived, quality-adjusted life years, and costs per patient and per cohort. The cost-effectiveness of each strategy was analysed through incremental cost-effectiveness ratios at a cost-effectiveness threshold of Swiss Franc (CHF) 100,000/quality-adjusted life year. Overall, the total costs and quality-adjusted life years per patient, respectively, were CHF 43,493.61 and 5.893 for no surveillance; CHF 48,702.79 and 6.018 for US; CHF 49,980.60 and 6.042 for US+AFP; and CHF 49,983.10 and 6.048 for GAAD. Compared with US+AFP and US alone, GAAD was cost-effective, with higher quality-adjusted life years and the highest rate of early-stage hepatocellular carcinoma detection (56%). Compared with no surveillance, incremental cost-effectiveness ratios for US, US+AFP and GAAD were considered to be cost-effective, ranging from CHF 41,509.01 to CHF 43,321.81. The current model indicates that hepatocellular carcinoma surveillance with any of these strategies was cost-effective in Switzerland. GAAD was nearly cost-neutral versus US+AFP, although these findings were dependent on the performance of GAAD and operator-dependent US combined with AFP. Compared with US alone, GAAD was the most cost-effective strategy. Further investigations are required to confirm these findings and to optimise hepatocellular carcinoma surveillance.
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, particularly among patients with chronic hepatitis C virus (HCV) infection. The limited sensitivity of current diagnostic tools, including imaging and serum alpha-fetoprotein (AFP), underscores the need for novel biomarkers to enable early detection. This study aimed to assess the diagnostic value of circulating miRNA-106 b.5p and to develop an integrated predictive model combining this marker with routine biochemical parameters for early HCC detection in HCV-infected patients. A total of 42 HCC patients, 83 liver cirrhosis (LC) patients, and 20 healthy controls were enrolled. Serum miRNA-106 b.5p levels were quantified using qRT-PCR, and biochemical markers, including AFP, albumin, platelets, ALT, and bilirubin, were measured. Receiver operating characteristic (ROC) and multivariate discriminant analyses were performed to evaluate diagnostic performance and to construct a combined predictive score. Serum miRNA-106 b.5p expression was significantly higher in HCC patients compared with LC patients and controls (p < 0.001), showing a progressive increase along the disease spectrum. ROC analysis revealed miRNA-106 b.5p (AUC = 0.679) outperformed AFP (AUC = 0.731) in discriminating HCC from cirrhosis. The newly developed miRNA-106 b.5p HCC score, integrating miRNA-106 b.5p, AFP, albumin, platelet count, total bilirubin, and ALT, achieved 94% sensitivity and 91% specificity (AUC = 0.744) at a cut-off value of 0.42. The model demonstrated superior performance in detecting early-stage and low-grade tumors compared with AFP alone. Integration of miRNA-106 b.5p with routine biochemical markers markedly enhances non-invasive diagnosis of HCV-related HCC. The proposed miRNA-106 b.5p HCC score represents a cost-effective, accurate, and clinically applicable tool for early tumor detection and improved management of high-risk patients.
To develop and validate a machine learning-guided system (MLGS) for stratifying prognostic risk of unresectable hepatocellular carcinoma (uHCC) based on clinical data before and after intra-arterial therapy (IAT). Between April 2008 and June 2022, a total of 5646 eligible patients with uHCC who underwent initial IAT were consecutively identified in 15 hospitals. The 5 year mortality was used as primary predictive outcome. Thirty-five sets of clinical data, including 29 preoperative and 6 postoperative data, were input successively into five supervised ML models. The performance of the ML models was compared using the area under the receiver operating characteristic (AUC) curve with the DeLong test. Kaplan-Meier analysis was used to revealed overall survival (OS) risk stratification of the MLGS. These patients were divided into training datasets (TD, n=3387), internal testing datasets (ITD, n=1130), and external test datasets (ETD, n=1129), respectively.The CatBoost model yield the best discrimination using preoperative data in the ML models using 23 variables, the AUC of CatBoost model were 0.777-0.735 in three datasets. Meanwhile, the XGBoost model yield the best discrimination using postoperative 20 variables and the AUC of XGBoost model were 0.904-0.861 in three datasets, which outperform significantly the performance of the CatBoost model (DeLong test, P < 0.001). The MLGS based on the XGBoost model provide significantly different OS between three risk stratification in three datasets (all, P < 0.001). The MLGS may guide radiologists in developing strategies of IAT for uHCC. Prospective studies are needed to evaluate its clinical utility.
Melanoma-associated antigen D4 (MAGED4) belongs to the melanoma-associated antigen family and is upregulated in various cancer types. However, the functional role and molecular mechanisms of MAGED4 in hepatocellular carcinoma (HCC) remain largely unknown. In this study, we observed that MAGED4 expression levels were significantly higher in HCC tissues than in non-cancerous tissues and elevated expression was associated with poor patient outcomes. Functional assays demonstrated that MAGED4 promoted proliferation and migration of HCC. We found that MAGED4 can activate the Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway. Mass spectrometry and co-immunoprecipitation assays revealed an interaction between MAGED4 and tripartite motif-containing 21 (TRIM21). Confocal microscopy experiments confirmed the colocalization of MAGED4 with TRIM21. Mechanistically, MAGED4 can regulate the stability of TRIM21 by preventing its ubiquitination and degradation. Furthermore, MAGED4 contributes to the downregulation of suppressor of cytokine signaling 3 (SOCS3) via TRIM21, and this effect can be partially reversed by si-TRIM21 in MAGED4-overexpressing cells. These findings indicate that MAGED4 promotes HCC progression through the activation of the JAK2/STAT3 pathway by stabilizing TRIM21, suggesting that targeting MAGED4 may provide new insights into HCC treatment strategies.
Hepatocellular carcinoma (HCC) is a prevalent and lethal form of liver cancer that necessitates the exploration of innovative strategies due to the limitations of current therapies, including high recurrence rates and drug resistance. Lenvatinib-resistant Huh7-LR and PLC/PRF/5-LR cell lines were established. RNA sequence analysis was performed to identify differentially expressed genes associated with lenvatinib resistance in HCC tissues. A prognostic model was constructed using Cox regression analysis incorporating eight prognosis-related genes. A nomogram was developed by combining clinical factors and risk scores. Functional validation of the key gene, CPB2, was performed to explore its role in HCC progression and lenvatinib resistance. Lenvatinib-resistant Huh7-LR and PLC/PRF/5-LR cell lines exhibited significant resistance indices of 4.59 and 4.37, respectively. RNA sequence analysis revealed 82 genes associated with lenvatinib resistance that were differentially expressed in HCC tissues. The prognostic model stratified patients into high-risk and low-risk groups with significantly distinct overall survival outcomes (p = 3.057e-05). The nomogram demonstrated high concordance in predicting survival probabilities (AUC = 0.78). CPB2 has emerged as a core gene linked to lenvatinib resistance; low expression of CPB2 in HCC tissues is associated with poor prognosis and promotes HCC progression and lenvatinib resistance via inhibition of the MAPK signaling pathway. These findings underscore the importance of understanding lenvatinib resistance mechanisms, providing a foundation for future therapeutic strategies targeting CPB2, and advancing personalized treatment approaches for HCC.
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. Ubiquitin-specific proteases (USPs) modulate tumor progression by regulating substrate protein stability. However, the mechanisms of most DUBs in HCC remain poorly understood. This study aimed to investigate the role of USP9X in promoting HCC cell proliferation, survival, migration, and invasion. Transcriptomic and clinical data of LIHC patients were obtained from TCGA to assess USP9X expression, prognosis, and pathway enrichment. USP9X expression in HCC and adjacent tissues was examined by immunohistochemistry and Western blotting. Functional assays (CCK-8, colony formation, wound-healing, Transwell) were performed following USP9X knockdown or overexpression in Lm3 and Huh7 cells. The USP9X-HSP90AA1 interaction was evaluated by Co-IP and mass spectrometry, and deubiquitination assays elucidated the mechanism. In vitro and in vivo experiments determined the effects of USP9X-HSP90AA1 signaling on HCC growth and metastasis. Bioinformatic analyses revealed that USP9X expression was significantly elevated in LIHC tissues and correlated with poor prognosis. Immunohistochemistry and Western blotting confirmed higher USP9X protein levels in tumor tissues. Knockdown of USP9X inhibited proliferation and migration of Lm3 and Huh7 cells, whereas USP9X overexpression enhanced these phenotypes. Co-IP demonstrated a direct interaction between USP9X and HSP90AA1, and deubiquitination assays showed that USP9X decreased HSP90AA1 ubiquitination and increased its stability. Both in vitro and in vivo data indicated that USP9X promotes HCC progression through stabilization of HSP90AA1. USP9X is a tumor-promoting factor that accelerates HCC progression by stabilizing HSP90AA1, highlighting USP9X as a potential therapeutic target for HCC.
Hepatocellular carcinoma (HCC) exhibits substantial biological and metabolic heterogeneity, contributing to variable therapeutic responses in unresectable disease. Although immune checkpoint inhibitors combined with anti-angiogenic agents have improved outcomes, treatment selection remains largely empirical because validated predictive biomarkers are lacking. Recent multi-omics studies have identified fatty acid degradation (FAD)-related transcriptional signatures that classify HCC into distinct metabolic subtypes with different immune microenvironment characteristics and therapeutic vulnerabilities. Retrospective analyses suggest that F1/F2 subtypes may derive greater benefit from immune checkpoint inhibitor-based systemic therapy, whereas F3 tumours may be more responsive to transarterial chemoembolisation (TACE). However, whether FAD-based metabolic stratification can prospectively inform treatment allocation remains unknown. FAD-HCC-01 is a prospective, multicentre, open-label proof-of-concept Phase II study designed to evaluate the feasibility and preliminary clinical activity of FAD-informed treatment allocation in patients with unresectable HCC. Eligible patients with Barcelona Clinic Liver Cancer stage B or C disease and no prior systemic therapy will undergo baseline tumour transcriptomic profiling to determine FAD subtype. Patients with F1/F2 tumours will receive camrelizumab plus rivoceranib, whereas patients with F3 tumours will receive TACE combined with camrelizumab and rivoceranib. Eighty-six patients will be enrolled, with 43 in each biomarker-defined cohort. The primary endpoint is objective response rate according to RECIST version 1.1. Secondary endpoints include objective response rate by mRECIST, disease control rate, progression-free survival, overall survival, duration of response, conversion to curative treatment, and safety. Exploratory analyses will assess concordance between MRI-derived proton density fat fraction and transcriptomic FAD classification. This proof-of-concept study will prospectively assess whether FAD-based metabolic subtyping can inform treatment allocation in unresectable HCC. The results may provide early evidence supporting metabolism-informed precision therapy and the design of future biomarker-guided clinical trials.
Hepatocellular carcinoma (HCC) predominantly arises against a background of chronic liver disease and cirrhosis, with its development typically following the three-step pattern of "hepatitis-cirrhosis-liver cancer." Hepatocellular carcinoma precursor lesions represent a critical stage in this process and constitute a vital window for early diagnosis and targeted intervention. This review aims to systematically summarize the pathological basis, malignant potential, diagnostic approaches, risk stratification strategies, and precision intervention perspectives of HCC precursor lesions. Specifically, we review the pathological characteristics and malignant potential of HCC precursor lesions such as hepatocellular large/small cell transformation, dysplastic foci (DF), low/high-grade dysplastic nodules (LGDN/HGDN), and β-catenin-activated hepatocellular adenoma. We further summarize the application value and limitations of ultrasound/contrast-enhanced ultrasound (US), computed tomography (CT), and Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) in screening and differential diagnosis. In addition, we discuss the progress in serum markers such as AFP, AFP-L3, DCP, and GP73, as well as liquid biopsy markers including CTC, ctDNA methylation, cfRNA, and tumor metabolites. We also outline the application of multivariable risk models like age-Male-ALBI-Platelet (aMAP), Gender-Age-AFP-L3-AFP-DCP (GALAD), and THRI in risk stratification and dynamic monitoring of high-risk populations. Finally, we review current treatment and follow-up strategies for HCC precursor lesions and explore the potential of radiomics, artificial intelligence, and multi-omics integration to improve risk assessment and diagnostic support, while also discussing their current limitations and the gap between research findings and routine clinical implementation. Overall, HCC precursor lesions represent an important target for early surveillance and precise intervention, and the integrated application of pathology, imaging, biomarkers, risk models, and emerging technologies may improve early identification, individualized management, and future translational research in HCC.
Transarterial chemoembolization, TACE continues to be the primary treatment option for patients diagnosed with intermediate-stage (BCLC B) hepatocellular carcinoma, HCC. However, emerging real-world evidence suggests that it may also be applicable for selected early-stage patients (BCLC A) who are not candidates for surgical resection or thermal ablation. This study aimed to evaluate the long-term outcomes of TACE within a large single-centre cohort. This retrospective observational cohort study included patients with HCC treated with TACE at Ente Ospedaliero Cantonale, EOC in Ticino, Switzerland between 2013 and 2023. The study was conducted and reported in accordance with the STROBE guidelines. Overall survival, OS and progression-free survival, PFS were estimated using Kaplan-Meier analysis and compared across Barcelona Clinic Liver Cancer, BCLC stages. A total of 195 patients were included, with a median follow-up of 56 months. Most patients were classified as BCLC stage A (55.4%) or B (43.6%). Median OS for the entire cohort was 56 months. PFS was significantly longer in stage A compared with stage B patients (15 vs 9 months, p=0.003). Early modification of treatment within one month was associated with inferior outcomes, whereas patients who subsequently underwent curative-intent therapies achieved markedly prolonged survival. In this retrospective study, TACE demonstrated sustained tumour control and prolonged survival, exceeding the survival durations reported in previous studies (20-42 months), particularly among early-stage HCC patients who were initially deemed unsuitable for resection or ablation. These findings emphasise the value of centralisation, multidisciplinary evaluation, tailored therapeutic approaches, and systematic periodic reassessment to optimise patient outcomes. Hepatocellular carcinoma, HCC is the most common type of primary liver cancer. Many patients are not eligible for surgery, transplantation, or heat-based tumour ablation. In such situations, transarterial chemoembolization, TACE is frequently used. TACE delivers chemotherapy directly into the liver arteries supplying the tumour and blocks these blood vessels to reduce tumour blood flow. In this retrospective study, we evaluated real-world outcomes of TACE in a Swiss referral centre over a 10-year period (2013–2023). We analysed medical records of 195 patients with HCC treated with TACE and followed them for a median of 56 months. Most patients had early-stage (BCLC A) or intermediate-stage (BCLC B) disease. Median overall survival for the entire cohort was 56 months. Cancer control lasted longer in early-stage disease: median progression-free survival was 15 months in BCLC A compared with 9 months in BCLC B. Patients requiring an early change of treatment within the first month after TACE tended to have worse outcomes. Importantly, patients who later received more effective treatments, including curative-intent options such as transplantation, surgery, or ablation, achieved very long survival. These findings suggest that TACE can provide durable tumour control and long-term survival, especially in carefully selected early-stage patients, and highlight the value of multidisciplinary care and regular reassessment over time.
Steatotic liver disease (SLD) has emerged as an important risk factor for hepatocellular carcinoma (HCC), often in the absence of cirrhosis. We aimed to develop explainable machine learning (ML) models to predict HCC risk in individuals with SLD using routinely collected screening data. Using the Korean National Health Insurance Service database, we included adults aged 20-79 years who underwent national health screening in 2017. SLD was defined as a fatty liver index (FLI) ≥ 60. Multiple ML algorithms, including deep learning models, were trained using a 7:3 train-test split with repeated non-replacement undersampling at a 1:3 case-to-control ratio to address extreme class imbalance. Among 1,241,560 adults with SLD, 2,152 (0.17%) developed HCC during a 6-year follow-up period. In the internal validation cohort, the final weighted multi-head attention deep neural network ensemble achieved an area under the receiver operating characteristic curve of 0.923, with a sensitivity of 71.36% and specificity of 93.65%. SHapley Additive exPlanations consistently identified age, sex, triglycerides, total cholesterol, aminotransferases, gamma-glutamyl transferase (GGT), Charlson Comorbidity Index, and FLI as key contributors to HCC risk. In multivariable Cox models, older age, male sex, elevated GGT, higher aspartate aminotransferase and FLI, and greater comorbidity burden were positively associated with HCC risk, whereas higher triglyceride and total cholesterol levels were inversely associated. Model-based risk stratification identified four groups with distinct HCC-free survival curves; the extremely high-risk group had an approximately 74.9-fold higher hazard of HCC than the low-risk group (95% CI, 55.3-101.5). Overall, this explainable ML model based on routine health screening variables enables robust HCC risk stratification and may help inform future targeted surveillance strategies in SLD populations after external validation.
Hepatocellular carcinoma (HCC) immunotherapy is significantly constrained by a low objective response rate (~30%) and the lack of universally applicable predictive biomarkers. Radiomics, a non-invasive technique that extracts high-throughput hidden features from medical images, offers innovative solutions for patient selection, treatment response assessment, and prognosis prediction. This review systematically summarizes the application scenarios, feature extraction, and model construction of multimodal imaging data in HCC immunotherapy. It highlights advances in radiomics for predicting treatment response and evaluating the tumor immune microenvironment (TIME) and underlying molecular signatures. It also analyzes key challenges, including limited sample sizes and poor model generalization, and outlines future directions such as multicenter standardized studies and multi-omics integration. The goal is to inform the clinical translation of radiomics for precision management of HCC immunotherapy.
To identify radiomics subtypes that reflect tumor heterogeneity in bifocal hepatocellular carcinoma (bHCC) using an unsupervised machine learning approach. Additionally, to develop a preoperative model and a postoperative fusion model aimed at predicting recurrence-free survival (RFS) and overall survival (OS) in bHCC patients following hepatectomy. This retrospective study included 182 bHCC patients (91 in the training set, 91 in the test set). To capture the overall tumor characteristics, radiomics features were extracted from both lesions across six MR sequences and integrated using a two-lesion fusion approach to represent each patient as a single analytical entity. The similarity network fusion approach was utilized to construct a patient similarity matrix based on multi-sequence radiomic features, aiming to identify distinct subgroups that capture patterns of tumor imaging heterogeneity through spectral clustering. Multivariable Cox regression analysis was conducted to develop prognostic models for RFS and OS. The preoperative radiomics image heterogeneity (RIH) model and postoperative model including pathological features were built to predict prognosis of bHCC patients after hepatectomy. Unsupervised clustering analysis based on multi-parametric radiomics revealed two subtypes correlated with distinct clinical outcomes, where high-radiomics image heterogeneity (high-RIH) was associated with poorer RFS (Log-rank p = 0.0059) and OS (Log-rank p = 0.0343). The independent predictors of shorter RFS included RIH cluster (HR, 1.782; 95% CI, 1.189-2.670), pathological satellite nodule (HR, 1.946; 95% CI, 1.094-3.460), MVI (HR, 1.714; 95% CI, 1.231-2.386). The independent predictors of shorter OS included RIH cluster (HR, 2.008; 95% CI, 1.119-3.605), radiological satellite nodule (HR, 1.982; 95% CI, 1.008-3.901), MVI (HR, 4.350; 95% CI, 2.358-8.028). This study identified two different radiomics subtypes in bHCC which could reveal the heterogeneity of bHCC and predict clinical outcomes in post-hepatectomy bHCC patients.
Hepatocellular carcinoma (HCC) is associated with high recurrence rates despite curative-intent liver resection. This necessitates improved prognostic tools and novel therapeutic strategies, including immune checkpoint inhibitors (ICIs). Circulating stem cells (CSCs) have emerged as potential prognostic biomarkers. To assess the prognostic relevance of CSCs expressing programmed death-ligand 1 (PD-L1+CSCs) in relation to recurrence-free survival (RFS) and overall survival (OS) in patients undergoing surgery for HCC. PD-L1+CSCs (CD45-/CD146+/ASGPR+/CD90+/PD-L1+) were analyzed in 27 HCC patients before surgery, immediately after surgery, and at 6 and 12 months after surgery using fluorescence-activated cell sorting and immunofluorescence microscopy. Tumor recurrence was monitored biannually through alpha-fetoprotein (AFP) measurements and imaging (CT/MRI). Control groups included patients with benign liver disease, non-HCC malignancies, and healthy donors. Before surgery, 29.7% (8/27) of HCC patients had detectable PD-L1+CSCs. Postoperatively, their frequency initially declined to 22.3%, followed by a significant rise to 85% at six months and 88% at twelve months (both p < 0.01). Increasing postoperative PD-L1+CSC levels were associated with tumor recurrence (51.8%). The presence of preoperative PD-L1+CSCs correlated with reduced OS (p = 0.05) and shorter RFS (p = 0.07). PD-L1+CSCs are associated with poor oncological outcomes and represent promising prognostic and therapeutic targets in HCC.
To evaluate the efficacy and safety of a quadruple regimen of transarterial chemoembolization (TACE)-hepatic arterial infusion chemotherapy (HAIC) plus molecular targeted therapy (MTT) and immune checkpoint inhibitors (ICIs) for unresectable hepatocellular carcinoma (uHCC). 274 uHCC patients were divided into two groups based on two treatment methods:TACE-HAIC combined with MTT and ICIs (THTI) and TACE combined with MTT and ICIs (TTI). The primary endpoints were progression-free survival (PFS) and overall survival (OS). The secondary endpoints included the objective response rate (ORR), disease control rate (DCR), and treatment-related adverse events (TRAEs). After Propensity score matching (PSM), the THTI group significantly prolonged median PFS (14.0 vs 10.6 months, P< 0.001) and median OS (30.8 vs 24.8 months, P = 0.001) compared with the TTI group. Compared with the TTI group, the THTI group demonstrated significantly superior ORR (64.5% vs 44.9%, P=0.004) and DCR (94.4% vs 84.1%, P=0.015). In addition, responses to THTI (THTI-R) had superior median PFS (17.1 vs 13.8 months, P = 0.007) and median OS (38.1 vs 27.5 months, P = 0.002) versus responses to TTI (TTI-R). All adverse events were manageable in two groups. For patients with uHCC, the THTI quadruple therapy demonstrated a superior clinical benefit over current TTI triple therapy, including significant prolongation of both PFS and OS, as well as improvements in ORR and DCR, with a manageable safety profile.
After ablation for hepatocellular carcinoma (HCC), tumors may persist as residual lesions after incomplete ablation or remain untreated in patients undergoing palliative ablation for multifocal disease. The post-ablation growth kinetics of these two lesion types have not been systematically compared. This study aimed to compare the post-ablation growth kinetics of residual and synchronous untreated HCC lesions after microwave ablation (MWA) and to identify factors associated with rapid progression. In this retrospective cohort study from September 2013 to December 2021, patients who underwent MWA and had residual lesions or synchronous untreated lesions were included. Tumor volume doubling time (TVDT) was calculated from serial MRI. Paired comparisons were used to assess changes in growth kinetics before and after ablation when longitudinal measurements were available, and a multivariable mixed-effects model was used to identify predictors of rapid growth (TVDT ≤ 3 months). A total of 103 patients were included: 30 with residual lesions (30 lesions) and 73 with synchronous untreated lesions (82 lesions). Among lesions with serial imaging, synchronous untreated lesions showed a shorter TVDT after ablation than before ablation (median ΔTVDT: -3.51 months; P = 0.030), while residual lesions showed no significant change (median ΔTVDT: +0.91 months; P = 0.734). Post-ablation TVDTs did not differ significantly between the two groups (2.75 vs. 3.78 months; P = 0.997). Poor tumor differentiation (odds ratio [OR] = 10.79, 95% CI 2.07-56.33; P = 0.005) and maximum ablation lesion diameter > 3 cm (OR = 4.01, 95% CI 1.21-13.24; P = 0.023) were independently associated with rapid growth. An interaction with neutrophil-to-lymphocyte ratio was observed in exploratory subgroup analysis. Synchronous untreated HCC lesions appeared to show faster growth during the post-ablation period, whereas residual lesions showed no consistent change in growth kinetics. These findings may support closer post-ablation surveillance and individualized management.
Although resection surgery is a curative treatment for hepatocellular carcinoma (HCC), high HCC recurrence leads to poor patient survival. Chronic hepatitis B virus (HBV) infection is an important risk factor for HCC. Deletion mutation in HBV pre-S2 gene results in expression of pre-S2 mutant oncoprotein and represents an independent prognostic biomarker for HCC recurrence. MicroRNAs (miRNAs) are small non-coding RNAs that play key roles in HBV-related HCC. This study aimed to identify the miRNAs whose expression levels in tumor tissues were correlated with pre-S2 gene deletion mutation and post-resection HCC recurrence and investigate their potential in combination with pre-S2 gene deletion mutation to predict HCC recurrence in a retrospective cohort of patients. The results showed that the expression level of miR-369-3p was decreased in tumor tissues of patients with pre-S2 gene deletion mutation or HCC recurrence. miR-369-3p was identified as a prognostic biomarker for HCC recurrence. Patients with pre-S2 gene deletion mutation combined with a low level of miR-369-3p had a higher risk of HCC recurrence than patients with either one or none of these two biomarkers. The combination of pre-S2 gene deletion mutation and miR-369-3p expression level showed a greater prognostic potential for HCC recurrence than either biomarker alone. Collectively, miR-369-3p held exploratory promise in serving as a combination biomarker with pre-S2 gene deletion mutation to provide a better potential in predicting HBV-related HCC recurrence after curative surgical resection. This study provided preliminary evidence indicating a negative association between HBV pre-S2 gene deletion mutation and miR-369-3p expression level in tumor tissues of HCC patients and demonstrating a superior prognostic potential of combining these two biomarkers for post-resection HCC recurrence.
The HAUS family proteins (HAUS1-HAUS8) are essential for mitotic spindle microtubule nucleation. Although HAUS dysregulation has been linked to tumor progression, whether these oncogenic functions are conserved or tissue-specific remains unclear. Therefore, a pan-cancer analysis is needed to identify universal HAUS drivers and context-dependent members for precision oncology. We systematically evaluated the expression and prognostic significance of all eight HAUS genes across 33 cancer types using TCGA data. Focusing on liver hepatocellular carcinoma (LIHC), we identified molecular subtypes based on HAUS co-expression patterns and characterized their associations with clinicopathological features, the tumor microenvironment (TME), immune checkpoint expression, and therapeutic response. A HAUS-related prognostic signature was developed using LASSO and Cox regression analyses and validated in independent ICGC cohorts. Regulatory relationships among HAUS members and key signature genes were experimentally validated using immunohistochemistry and Western blotting. Most HAUS members were overexpressed across multiple cancers and correlated with poor clinical outcomes. In LIHC, two HAUS-based subtypes differed significantly in survival, clinicopathological profiles, immune features, mutational burden, stemness indices, and predicted therapeutic response. A prognostic signature comprising DTYMK and SPP1 effectively stratified LIHC patients into distinct risk groups, with the high-risk group showing significantly worse survival. A nomogram integrating the HAUS-related risk score with clinicopathological variables demonstrated strong predictive performance. Recombinant osteopontin induced HAUS1 and DTYMK expression in LIHC cell lines, supporting a functional SPP1-HAUS1/DTYMK axis. This study establishes the broad oncogenic relevance of HAUS genes across cancers and demonstrates that a HAUS-based signature enables prognostic stratification in LIHC.
Hepatocellular carcinoma (HCC) is the leading cause of cancer-related mortality in Egypt. The model for end-stage liver disease (MELD) score is the standard for prioritizing liver transplantation (LT) candidates but often underestimates hepatic biosynthetic failure in patients with compensated cirrhosis. This study evaluated the utility of an integrated "MELD-ALBI" classification to refine risk stratification in patients undergoing living donor liver transplantation (LDLT). This retrospective study included 76 adult patients with HCC who underwent LDLT between 2010 and 2021. Patients with early postoperative mortality (<1 month) were excluded. An integrated model was developed stratifying patients into three classes: Class 1 (low risk): ALBI grade 1, or ALBI grade 2 with MELD <12; Class 2 (intermediate risk): ALBI grade 2 with MELD ≥ 12; and Class 3 (high risk): ALBI grade 3. The integrated model achieved a numerically higher diagnostic performance for predicting 1-year mortality (AUC=0.625) compared to MELD (AUC=0.611) or ALBI (AUC=0.593). Kaplan-Meier analysis showed significantly superior survival for Class 1 compared to Class 2 (P=0.029). In univariate Cox regression, Class 2 was associated with a threefold increase in mortality risk compared to Class 1 (HR 3.22, 95% CI 1.05-9.90, P=0.041), whereas survival outcomes for Class 2 and Class 3 were statistically comparable (P=0.27). In multivariate analysis adjusted for age, Class 2 maintained a high hazard ratio (HR 2.59), though statistical significance was attenuated (P=0.101). The integrated MELD-ALBI classification identifies a "hidden high-risk" subgroup (Class 2) underserved by standard allocation. We propose assigning exception "Z-points" to these patients to align their priority with biological urgency. This framework offers a potential model for refining allocation.
To investigate whether adding stereotactic body radiotherapy (SBRT) to lenvatinib improves outcomes for patients with unresectable hepatocellular carcinoma (uHCC) and portal vein tumor thrombosis (PVTT). This retrospective cohort study enrolled 133 cases of uHCC with PVTT treated with either lenvatinib plus SBRT (n = 65) or lenvatinib alone (n = 68) between 2021 and 2023. To minimize baseline imbalances, 1:1 propensity score matching (PSM, caliper width, 0.02) was performed. The primary endpoints were overall survival (OS) and progression-free survival (PFS). Across the full study population, patients receiving lenvatinib in combination with SBRT experienced significantly longer median OS relative to those who received lenvatinib alone (24.7 vs 16.4 months; HR=0.521, 95% CI: 0.338-0.802, p = 0.003). A similar advantage was observed for PFS (13.0 vs 8.6 months; HR=0.494, 95% CI: 0.335-0.728, p < 0.0001). These findings remained consistent after PSM, with hazard ratios of 0.589 for OS and 0.540 for PFS. The objective response rate was also substantially higher in the combination arm than in the monotherapy arm (55.4% vs 30.9%, p = 0.004). Subgroup analyses revealed that the survival advantage was confined to patients with Cheng's type I-II PVTT, whereas no significant benefit was observed in those with type III-IV disease. Furthermore, salvage hepatectomy was an independent protective factor for survival in 33 cases (24.8%), with a significantly higher conversion rate in the combined treatment group (30.8%). Both treatment groups had comparable and manageable safety profiles. Lenvatinib in combination with SBRT confers meaningful advantages in both survival and tumor response over lenvatinib monotherapy in individuals with uHCC and PVTT, particularly among those with Cheng's type I-II involvement. Moreover, this multimodal approach appears to be an effective strategy for achieving tumor downstaging and enabling subsequent salvage hepatectomy.
Ki-67 is a well-established biomarker for tumor aggressiveness and poor prognosis in hepatocellular carcinoma (HCC). A reliable non-invasive method for preoperative Ki-67 assessment is clinically needed for risk stratification and individualized treatment. This study aimed to develop and validate a prediction model integrating triphasic contrast-enhanced CT radiomics with clinical features for preoperative Ki-67 expression status in HCC. This retrospective dual-center study enrolled 200 patients with 213 pathologically confirmed HCC lesions, Ki-67 expression was dichotomized as high (Ki-67 >20%) and low (≤20%) based on established clinical criteria. Radiomic features were extracted from arterial, portal venous, and delayed phases. After rigorous feature selection, logistic regression was used to construct single-phase models, a multi-phase radiomics fusion model, a clinical model, and a combined clinical-radiomics fusion model. Performance was assessed by area under the curve, net reclassification index, integrated discrimination improvement, and decision curve analysis. The combined fusion model showed robust discrimination, with AUCs of 0.866 and 0.824 in the training and internal test sets, respectively. In independent external validation (n=64), it achieved an AUC of 0.829 (95% CI: 0.709-0.948), significantly outperforming the arterial phase model (AUC=0.713, P=0.031) and the radiomics-only fusion model (AUC=0.722, P=0.031). NRI and IDI confirmed significant incremental value (NRI=0.374, P=0.005; IDI=0.191, P<0.001), and DCA demonstrated superior clinical net benefit. The fusion model integrating multi-phase CECT radiomic features with clinical indicators provides an effective, non-invasive tool for preoperative prediction of Ki-67 expression in HCC. It may facilitate risk stratification and inform individualized treatment planning in clinical practice. : A reliable non-invasive method for preoperative Ki-67 assessment in HCC is needed for risk stratification and personalized treatment. : A model combining triphasic CT radiomics and clinical features effectively predicted Ki-67 expression, showing robust performance (AUC=0.829) in external validation. : This CT-based model provides an accessible, non-invasive tool to preoperatively assess tumor proliferation, potentially aiding individualized treatment planning and improving prognosis in HCC patients.