OBJECTIVE: To compare therapeutic outcomes of predicted proliferative and nonproliferative hepatocellular carcinoma (HCC) after microwave ablation (MWA) using a previously developed imaging-based predictive model, the SMARS score.
METHODS: This multicenter retrospective study included consecutive 635 patients with unresectable HCC who underwent MWA between August 2013 and September 2020. Patients were stratified into predicted proliferative and nonproliferative phenotypes according to the SMARS score. Overall survival (OS) and recurrence-free survival (RFS) were compared between the predicted proliferative and nonproliferative HCCs before and after propensity score matching (PSM). OS and RFS were also compared between the two groups in subgroups of tumor size smaller than 30 mm and tumor size 30-50 mm.
RESULTS: The SMARS score classified 127 and 508 patients into predicted proliferative and nonproliferative HCCs, respectively. The predicted proliferative HCCs exhibited worse RFS but equivalent OS when compared with nonproliferative HCCs before (p < 0.001 for RFS; p = 0.166 for OS) and after (p < 0.001 for RFS; p = 0.456 for OS) matching. Regarding subgroups of tumor size smaller than 30 mm (p = 0.098) and tumor size 30-50 mm (p = 0.680), the OSs were similar between the two groups. However, predicted proliferative HCCs had worse RFS compared to nonproliferative HCCs in the subgroup of tumor size 30-50 mm (p < 0.001), while the RFS did not differ in the subgroup of tumor size smaller than 30 mm (p = 0.141).
CONCLUSIONS: Predicted proliferative HCCs have worse RFS than nonproliferative ones after MWA, especially in tumor size larger than 30 mm. However, the phenotype of the tumor may not affect the OS.
UNASSIGNED: Before performing microwave ablation for hepatocellular carcinoma, the tumor phenotype should be considered because it may affect the therapeutic outcome.
CONCLUSIONS: Proliferative hepatocellular carcinoma (HCC) may be identified using the SMARS score, an imaging-based predictive model. SMARS predicted proliferative HCCs have worse recurrence-free and equivalent overall survival compared to nonproliferative HCC after microwave ablation. Tumor phenotype should be considered before performing microwave ablation.

Enhanced liver fibrosis (ELF) score is a noninvasive assessment for liver fibrosis. We aimed to evaluate the performance of changes in ELF score 3 years apart in combination with liver stiffness measurement (LSM)-hepatocellular carcinoma (HCC) score to predict HCC in chronic hepatitis B (CHB) patients. This is a prospective cohort study. Patients who underwent transient elastography (TE) examinations and at intermediate or high risk of HCC defined by LSM-HCC score were invited to repeat the examination about 3 years later. Their serum samples at these two time points were retrieved to assess the ELF score changes. The primary endpoint was HCC. There were 445 CHB patients (males: 73.9%; mean age: 51.6 ± 10.3 years) who received two TE examinations and ELF scores. Among them, 252 (56.6%) and 193 (43.4%) patients were at intermediate and high HCC risk at first assessment defined by LSM-HCC score, respectively. Kaplan-Meier analysis showed that the changes in ELF score could stratify the HCC risk in both intermediate- and high-risk patients defined by LSM-HCC score (p < 0.001 for intermediate-risk group; p = 0.011 for high-risk group). Patients remained having mild or moderate fibrosis at both assessments had the lowest risk of HCC (4.0%), followed by patients with fibrosis regressed (11.3%; p = 0.014) during a mean follow-up of 163 months. Patients remained having or progressed to severe fibrosis were at highest risk of HCC (>20%). Consistent findings were demonstrated in patients at both intermediate and high risk of HCC defined by LSM-HCC score. Dynamic changes in ELF score provided additional value to LSM-HCC score for stratifying HCC risk in CHB patients.

UNASSIGNED: This study aims to investigate the potential functions of miR-19a-3p in HCC.
UNASSIGNED: We collected serum samples to analyze miR-19a-3p expression. We utilized CCK8 and Transwell assays to access miR-19a-3p\'s influence on HCC cells malignancy. We used dual-luciferase reporter and western blotting to validate the impact of p53/miR-19 on miR-19/SOX4.
UNASSIGNED: The results demonstrated that miR-19a-3p was highly expressed in pre-operative serum samples and HCC cells, which can promote cell proliferation, migration and invasion in HCC under in vitro conditions. Additionally, there was a p53 binding site on the upstream of miR-19a-3p, which was inhibited by p53. SOX4 was the direct gene targeted by miR-19a-3p. The imbalance of p53-miR-19-SOX4 loop was one reason for the progress of HCC.
UNASSIGNED: Our findings validate the mechanisms of miR-19a-3p and highlight its potential as a therapeutic target in HCC.

The aim of this systematic review and meta-analysis is to evaluate the performance of classification metrics of machine learning-driven radiomics in diagnosing hepatocellular carcinoma (HCC). Following the PRISMA guidelines, a comprehensive search was conducted across three major scientific databases-PubMed, ScienceDirect, and Scopus-from 2018 to 2022. The search yielded a total of 436 articles pertinent to the application of machine learning and deep learning for HCC prediction. These studies collectively reflect the burgeoning interest and rapid advancements in employing artificial intelligence (AI)-driven radiomics for enhanced HCC diagnostic capabilities. After the screening process, 34 of these articles were chosen for the study. The area under curve (AUC), accuracy, specificity, and sensitivity of the proposed and basic models were assessed in each of the studies. Jamovi (version 1.1.9.0) was utilised to carry out a meta-analysis of 12 cohort studies to evaluate the classification accuracy rate. The risk of bias was estimated, and Logistic Regression was found to be the most suitable classifier for binary problems, with least absolute shrinkage and selection operator (LASSO) as the feature selector. The pooled proportion for HCC prediction classification was high for all performance metrics, with an AUC value of 0.86 (95 % CI: 0.83-0.88), accuracy of 0.83 (95 % CI: 0.78-0.88), sensitivity of 0.80 (95 % CI: 0.75-0.84) and specificity of 0.84 (95 % CI: 0.80-0.88). The performance of feature selectors, classifiers, and input features in detecting HCC and related factors was evaluated and it was observed that radiomics features extracted from medical images were adequate for AI to accurately distinguish the condition. HCC based radiomics has favourable predictive performance especially with addition of clinical features that may serve as tool that support clinical decision-making.

Hepatocellular carcinoma (HCC) is a typical highly heterogeneous solid tumor with high morbidity and mortality worldwide, especially in China; however, the immune microenvironment of HCC has not been clarified so far. Here, we employed single-cell RNA sequencing (scRNA-seq) on diethylnitrosamine (DEN)-induced mouse HCC model to dissect the immune cell dynamics during tumorigenesis. Our findings reveal distinct immune profiles in both precancerous and cancerous lesions, indicating early tumor-associated immunological alterations. Notably, specific T and B cell subpopulations are preferentially enriched in the HCC tumor microenvironment (TME). Furthermore, we identified a subpopulation of naïve B cells with high CD83 expression, correlating with improved prognosis in human HCC. These signature genes were validated in The Cancer Genome Atlas HCC RNA-seq dataset. Moreover, cell interaction analysis revealed that subpopulations of B cells in both mouse and human samples are activated and may potentially contribute to oncogenic processes. In summary, our study provides insights into the dynamic immune microenvironment and cellular networks in HCC pathogenesis, with a specific emphasis on naïve B cells. These findings emphasize the significance of targeting TME in HCC patients to prevent HCC pathological progression, which may give a new perspective on the therapeutics for HCC.

Hepatocellular carcinoma (HCC) is a lethal form of liver cancer, and the tumor microenvironment, particularly cancer-associated fibroblasts (CAFs), plays a critical role in its progression. This study aimed to elucidate the mechanism by which CAF-derived exosomes regulate the development of HCC. The study employed quantitative real-time polymerase chain reaction for mRNA expression analysis and western blot analysis for protein expression detection. Chromatin immunoprecipitation assay and dual-luciferase reporter assay were performed to investigate the relationship between zinc finger protein 250 (ZNF250) and programmed cell death 1 ligand 1 (PD-L1). Transmission electron microscopy and western blot analysis were used to characterize the isolated exosomes. The transferability of CAF-derived exosomes and normal fibroblasts (NFs)-derived exosomes into HCC cells was analyzed using a green fluorescent labeling dye PKH67. Cell proliferation was assessed via a 5-Ethynyl-2\'-deoxyuridine assay, while Transwell assays were conducted to evaluate cell migration and invasion. Flow cytometry was performed to measure cell apoptosis, while enzyme-linked immunosorbent assays were used to assess the levels of tumor necrosis factor-α and perforin. Finally, a xenograft mouse model was constructed to examine the effects of exosomes derived from ZNF250-deficient CAFs on the tumor properties of HCC cells. The study revealed increased expression of ZNF250 in HCC tissues and cells, with ZNF250 transcriptionally activating PD-L1 in HCC cells. ZNF250 expression was associated with HbsAg, clinical stage and tumor size of HCC patients. CAF-derived exosomal ZNF250 can regulate PD-L1 expression in HCC cells. Furthermore, exosomes derived from ZNF250-deficient CAFs inhibited the proliferation, migration, invasion, and immune escape of HCC cells by downregulating PD-L1 expression. Moreover, CAF-derived exosomal ZNF250 promoted tumor formation in vivo. These findings provide insights into the role of CAF-derived exosomes in the suppression of HCC development, highlighting the significance of ZNF250 and PD-L1 regulation in tumor progression.

BACKGROUND: Transcatheter arterial chemoembolization (TACE) combined with targeted therapy and immunotherapy can significantly improve the prognosis of patients with hepatocellular carcinoma (HCC). T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) is a novel immunosuppressive molecule. This study aimed to analyze the clinical correlation between TIGIT expression on T cells and patients with HCC.
METHODS: Clinical data from 140 patients with HCC were retrospectively collected, and TIGIT expression on T cells was examined in each patient. Patients were subsequently divided into high- and low-expression groups, and their prognosis was analyzed.
RESULTS: Patients with a high TIGIT expression on their T cells at baseline had a larger tumor volume, later staging, higher proportion of regulatory T cells, higher blood concentrations of interleukin (IL)-6 and IL-10, and lower interferon-γ concentrations. Following TACE, CD155 concentration decreased; however, TACE did not affect TIGIT expression on T cells. Additionally, among patients receiving TACE combined with apatinib and camrelizumab treatment, patients with a high TIGIT expression on T cells had significantly shorter progression-free survival (PFS) and overall survival times than those of patients in the low-expression group. Patients receiving TACE combined with apatinib and camrelizumab treatment with higher TIGIT expression have shorter PFS time than those receiving TACE combined with apatinib treatment.
CONCLUSIONS: Patients with HCC that have a high TIGIT expression on their T cells exhibited poorer baseline characteristics, immunosuppressive status, and prognosis after receiving TACE combined with apatinib and camrelizumab and maybe more suited to receive TACE combined with apatinib treatment instead.

In the era of immunotherapy, lenvatinib (LEN) still holds an important position in the sequential treatment of advanced hepatocellular carcinoma (HCC). However, the sustained therapeutic effect of LEN is not sufficient, and there is a need to address the development of resistance. Neuropilin-1 (NRP1) is known to act as a co-receptor for epidermal growth factor receptor (EGFR), Met, and vascular endothelial growth factor receptor 2 (VEGFR2), which have been reported to be involved in LEN resistance. In this study, we used cell culture and in vivo transplantation models to evaluate the contribution of NRP1 in the acquisition of LEN resistance in HCC as well as the potential of NRP1 as a therapeutic target. LEN resistance increased EGF/EGFR and hepatocyte growth factor (HGF)/Met signaling in liver cancer cells and VEGFA/VEGFR2 and HGF/Met signaling in vascular endothelial cells, thereby promoting cell proliferation, cell migration, and angiogenesis. We found that activation of NRP1 is essential for the enhancement of these signaling. In addition, NRP1 inhibition combined with LEN therapy synergistically improved the antitumor effects against LEN-resistant HCC, indicating that NRP1 is an attractive therapeutic target.

BACKGROUND: Fontan-associated liver disease (FALD) encompasses hepatic complications following the Fontan procedure, ranging from fibrosis to hepatocellular carcinoma (HCC). Despite advancements in surgical techniques and perioperative care, robot-assisted laparoscopic hepatectomy (RALH) for HCC in patients with FALD has not been previously reported owing to concerns about the Fontan circulation.
METHODS: We present the first case of RALH for recurrent HCC in a 45-year-old man after the Fontan procedure. The preoperative evaluation confirmed good cardiac function. The procedure involved meticulous monitoring and management of central venous pressure and was successfully completed with minimal blood loss. Postoperative recovery was uneventful. With thorough preoperative cardiac assessment and close collaboration between cardiologists and anesthesiologists, RALH can be safely performed in selected patients with FALD.
CONCLUSIONS: Even if a patient has a history of FALD, RALH can be safely performed in selected patients under appropriate conditions.

BACKGROUND: Metabolic disorders are significant risk factors for liver cancer, particularly Hepatocellular Carcinoma (HCC). However, the molecular genetic basis of metabolic reprogramming in the liver remains largely uncertain.
OBJECTIVE: This study aimed to investigate some novel prognostic biomarkers in HCC by using proteogenomic and transcriptomic analysis and explore the potential role of specific prognostic genes in HCC.
METHODS: Here, we have presented a proteogenomic analysis of 10 pairs of HCC. Protein co-expression and pathway analysis were performed to investigate the biological characteristics of HCC. Protein and mRNA expression profiles of multi-cohorts were integrated to detect novel prognostic protein markers of HCC. The carcinogenic roles of candidate prognostic markers were further evaluated by MTS assay, colony formation, monolayer wound healing assay, and xenograft models.
RESULTS: A total of 2086 proteins with significantly different expressions were detected in HCC. Pathways related to oncogenic signaling and insulin-related metabolism have been found to be dysregulated and differentially regulated in HCC. We have identified the novel prognostic biomarkers, KIF5B, involved in liver metabolic reprogramming. The biomarkers were identified using multivariable COX regression analysis from two independent proteomic datasets (Fudan Cohort and our recruited cohort) and the TCGA mRNA database. Both the protein and mRNA up-regulation of KIF5B have been found to be associated with a poor clinical outcome in HCC. Insulin activated the protein expression of KIF5B in HCC. Knocking out KIF5B expression by sgRNA decreased the protein expression of FASN and SCD1 and the intracellular triglyceride concentration. Silencing KIF5B suppressed HCC cell proliferation and colony formation in vitro, as well as HCC growth in xenograft models.
CONCLUSIONS: Our findings have suggested KIF5B protein to function as a novel prognostic biomarker in HCC. KIF5B expression has been found to activate the AKT/mTOR pathway and reprogram triglyceride metabolism, leading to HCC development. Targeting KIF5B may be an effective strategy in the clinical treatment of HCC.