Joseph Rabbat, Boyu Yang, Hye Won Lee, Huapeng Lin, Emmanuel Tsochatzis, Salvatore Petta, Elisabetta Bugianesi, Masato Yoneda, Ming-Hua Zheng, Hannes Hagström, Jérôme Boursier, José Luis Calleja, George Boon-Bee Goh, Wah-Kheong Chan, Rocio Gallego-Durán, Arun J. Sanyal, Victor de Lédinghen, Philip N Newsome, Jian-Gao Fan, Laurent Castéra, Michelle Lai, Céline Fournier-Poizat, Grace Lai-Hung Wong, Mirko Zoncape, Grazia Pennisi, Angelo Armandi, Atsushi Nakajima, Wen-Yue Liu, Ying Shang, Marc de Saint-Loup, Elba Llop, Kevin Kim Jun Teh, Carmen Lara-Romero, Amon Asgharpour, Sara Mahgoub, Mandy Sau-Wai Chan, Clemence M Canivet, Manuel Romero-Gomez, Vincent Wai-Sun Wong, Seung Up Kim, Terry Cheuk-Fung Yip
Received August 6, 2025 Accepted November 2, 2025 Published online November 11, 2025
Background/Aims Current guidelines recommend a 2-step approach for identifying advanced fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD), using FIB-4 followed by liver stiffness measurement (LSM) via vibration-controlled transient elastography. However, some patients may exhibit discordant results. This study evaluates the histological severity and outcomes in patients with discordant FIB-4 and LSM results.
Methods This secondary analysis of the VCTE-Prognosis study included 12,950 patients evaluated for MASLD at 16 tertiary centers, of whom 2,915 underwent liver biopsy. Patients were categorized into four groups based on established FIB-4 (1.3) and LSM (8 kPa) cutoffs.
Results F3-F4 fibrosis was observed in 6.4%, 13.7%, 30.6%, and 62.4% in low-FIB-4-low-LSM (n=6,403), high-FIB-4-low-LSM (n=3,017), low-FIB-4-high-LSM (n=1,363), and high-FIB-4-high-LSM (n=2,167) groups, respectively. During a median follow-up of 47.4 months, 248 patients experienced hepatic decompensation, hepatocellular carcinoma, liver transplantation, or liver-related death. The incidence rates of liver-related events (LREs) were 0.67, 1.19, 2.58, and 21.30 per 1,000 person-years, respectively. Compared to low-FIB-4-low-LSM patients, those with low-FIB-4-high-LSM (adjusted subdistribution hazard ratio [aSHR] 4.2) and high-FIB-4-high-LSM (aSHR 21.3) had a significantly higher risk of LREs, while high-FIB-4-low-LSM patients did not. Similar findings were observed when hepatic decompensation and hepatocellular carcinoma were analyzed separately.
Conclusions Approximately 30% of patients in tertiary centers exhibit discordant FIB-4 and LSM results, with LSM more likely reflecting true severity. While some patients with discordant results may have advanced fibrosis, the overall incidence of LREs remains low.
Background/Aims The identification of factors that lead to CD8+ T cell dysfunction within the tumor microenvironment (TME) holds great promise for the development of innovative immunotherapies. However, the mechanisms underlying the exhausted phenotype of CD8+ T cells infiltrating early-stage hepatocellular carcinoma (HCC) tumors remain unclear.
Methods Single-cell RNA sequencing was performed using a murine HCC model. Flow cytometry and additional experimental approaches were employed to investigate the mechanisms of CD8+ T cell exhaustion.
Results CD8+ T cells infiltrating early-stage HCC exhibited a functionally exhausted phenotype, which escalated with HCC progression. At early stages of HCC, the TME was characterized by significant iron accumulation. Moreover, tumor-infiltrating CD8+ T cells in murine HCC exhibited higher levels of intracellular ferrous iron compared to splenic CD8+ T. This excessive iron led to increased lipid peroxide levels and impaired the effector function of CD8+ T cells. Mechanistically, CD36 upregulated the iron uptake protein transferrin receptor 1 (TfR1) by mediating the activation of oxidized low-density lipoprotein (oxLDL)-p38-CEBPB axis. Depletion of CD36 in CD8+ T cells inhibited the upregulation of TfR1 and the increase of iron levels. Furthermore, constitutively activated nuclear factor erythroid 2-related factor 2 (NRF2) effectively suppressed lipid peroxidation, thereby preserving the effector functions of intratumoral CD8+ T cells and ultimately inhibiting tumor growth.
Conclusions Our findings reveal a previously unidentified mechanism mediated by CD36 that regulates the progressive dysfunction of CD8+ T cells in early HCC TME and provide a potential novel therapeutic approach to restore T cell function.
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Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease (NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its dynamic nature and poor correlation with liver biochemical markers. Liver histology keeps its role as the standard tool, yet it is well-known for substantial sampling, intraobserver, and interobserver variability. Serum proinflammatory cytokines and apoptotic markers, namely cytokeratin-18, are well-studied with reasonable accuracy, whereas serum metabolomics and lipidomics have been adopted in some commercially available diagnostic models. Ultrasound and computed tomography imaging techniques are attractive due to their wide availability; yet their accuracies may not be comparable with magnetic resonance imaging-based tools. Machine learning and deep learning models, be they supervised or unsupervised learning, are promising tools to identify various subtypes of NAFLD, including those with dominating liver inflammation, contributing to sustainable care pathways for NAFLD.
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Background/Aims We aimed to determine the association between blood urea level and incident cirrhosis, hepatic decompensation, and hepatocellular carcinoma in chronic liver disease (CLD) patients.
Methods The association between blood urea level and liver fibrosis/liver-related events were evaluated on continuous scale with restricted cubic spline curves based on generalized additive model or Cox proportional hazards models. Then, the above associations were evaluated by urea level within intervals.
Results Among 4,282 patients who had undergone liver stiffness measurement (LSM) by transient elastography, baseline urea level had a U-shaped association with LSM and hepatic decompensation development after a median follow-up of 5.5 years. Compared to patients with urea of 3.6–9.9 mmol/L, those with urea ≤3.5 mmol/L (adjusted hazard ratio [aHR], 4.15; 95% confidence interval [CI], 1.68–10.24) and ≥10 mmol/L (aHR, 5.22; 95% CI, 1.86–14.67) had higher risk of hepatic decompensation. Patients with urea ≤3.5 mmol/L also had higher risk of incident cirrhosis (aHR, 3.24; 95% CI, 1.50–6.98). The association between low urea level and incident cirrhosis and hepatic decompensation was consistently observed in subgroups by age, gender, albumin level, and comorbidities. The U-shaped relationship between urea level and LSM was validated in another population screening study (n=917). Likewise, urea ≤3.5 mmol/L was associated with a higher risk of incident cirrhosis in a territory-wide cohort of 12,476 patients with nonalcoholic fatty liver disease at a median follow-up of 9.9 years (aHR, 1.27; 95% CI, 1.03–1.57).
Conclusions We identified a U-shaped relationship between the urea level and liver fibrosis/incident cirrhosis/hepatic decompensation in patients with CLD.
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