Hepatocellular carcinoma (HCC) is one of the most prevalent and aggressive malignant tumors globally, with a notably low five-year survival rate. Its high mortality is largely attributed to challenges in early detection. Extracellular vesicles (EVs) are naturally occurring nanoparticles secreted by nearly all cell types and carry a diverse array of bioactive molecules, including proteins, nucleic acids (particularly non-coding RNAs), and lipids. EVs play pivotal roles in remodeling the tumor microenvironment and driving cancer progression through intercellular communication. Accumulating evidence has established that EVs are critically involved in the pathogenesis of HCC and are emerging as promising biomarkers for its early detection. With advances in EV isolation technologies, these vesicles have garnered considerable attention in the field of liquid biopsy for HCC. This review provides a comprehensive overview of the diagnostic potential of EV-derived biomarkers in HCC, including DNA, RNA, proteins, and lipids. Additionally, it discusses the advantages of integrating multi-omics approaches for HCC diagnosis. Furthermore, the review highlights the technical challenges in EV isolation and characterization, as well as the crucial role of reference genes in the standardization of EV data. These insights underscore the potential of EVs as novel, minimally invasive liquid biopsy biomarkers for the early diagnosis of HCC.

The optimal management strategy for adults with immune-tolerant (IT) chronic hepatitis B infection remains undefined. This study aimed to investigate the efficacy and predictive factors of a pegylated interferon (Peg-IFN)-based treatment strategy in IT patients with chronic HBV infection.

In this pilot, open-label, prospective study, 286 patients aged 18 to 60 years with IT characteristics were enrolled and allocated to one of three groups. The combination group received Peg-IFN for 48–96 weeks, with tenofovir disoproxil fumarate (TDF) initiated at week 12 and continued through week 96 (n = 103). The monotherapy group received TDF monotherapy alone (n = 125), and the control group was monitored without therapeutic intervention (n = 58).

No patients in the control group met any predefined efficacy endpoints. Intention-to-treat analysis showed that patients in the combination group achieved significantly higher virological response rates (71.8% vs. 53.6%, p = 0.005), hepatitis B e antigen seroconversion rates (15.5% vs. 1.6%, p < 0.001), and hepatitis B surface antigen (HBsAg) loss rates (10.7% vs. 0%, p < 0.001) compared with those in the monotherapy group at week 96. In the combination group, the cumulative rate of HBsAg loss was 5.4% at week 48 and increased to 11.8% by week 96. Independent predictors of achieving either hepatitis B e antigen seroconversion or HBsAg loss were baseline age under 30 years (odds ratio = 0.217, 95% confidence interval: 0.048–0.976, p = 0.046) and a decline in HBsAg level greater than 1 log10 IU/mL by week 24 (odds ratio = 13.976, 95% confidence interval: 2.506–77.932, p = 0.003).

A Peg-IFN-based treatment strategy significantly increases response rates compared with TDF monotherapy or observation in patients with IT characteristics.

Hepatic ischemia–reperfusion (HIR) injury impairs outcomes post–liver transplantation. Therefore, we aimed to investigate the role and mechanism of miR-381-3p in HIR.

The study enrolled 150 healthy controls, 82 non-HIR-injured patients, and 68 patients with HIR injury following liver transplantation. Clinical data were analyzed. Multivariate analysis identified HIR risk factors; the predictive value of miR-381-3p was assessed via receiver operating characteristic analysis. An in vitro hypoxia/reoxygenation (H/R) model was established and employed. The cellular effects of miR-381-3p and JAK2 were evaluated using CCK-8, flow cytometry, ELISA, luciferase, RIP, and bioinformatics.

Serum miR-381-3p was significantly elevated in HIR compared with the other groups. miR-381-3p was the strongest independent HIR risk factor, which was confirmed by receiver operating characteristic analysis. H/R upregulated miR-381-3p. Inhibiting miR-381-3p counteracted H/R-induced decreased viability and increased apoptosis, inflammation, and oxidative stress. miR-381-3p directly bound to and suppressed JAK2 via its 3′ untranslated region (validated by luciferase and RIP). Transfection of si-JAK2 abolished the protective effects of miR-381-3p inhibition.

miR-381-3p exacerbates post-transplant HIR by directly targeting JAK2, amplifying inflammation and oxidative stress. Thus, our findings nominate serum miR-381-3p as a promising non-invasive biomarker and suggest its potential as a therapeutic target for mitigating HIR injury.

Predicting the malignant transformation of rectal precancerous lesions remains challenging because conventional Whole Slide Images (WSIs) capture morphological information but lack molecular insight. Multiomics data provide complementary biological signals that often precede visible morphological changes. This study aimed to develop an artificial intelligence (AI)-based multimodal framework integrating WSI and multiomics data for accurate early prediction of malignant transformation.

WSI patches (512×512 px at 20× magnification) and matched multiomics profiles were used for 450 rectal tissue samples from the publicly available The Cancer Genome Atlas dataset. A multimodal architecture was designed, employing a Vision Transformer (ViT-B/16) for WSI feature extraction and a Variational Autoencoder for multiomics representation learning. Features were fused via a cross-attention mechanism to capture inter-modality dependencies. Baseline models, including a convolutional neural network-only image model and an omics-only multilayer perceptron, were trained for comparison. Five-fold cross-validation was applied, with binary cross-entropy loss, the AdamW optimizer, early stopping, and hyperparameter tuning to ensure reproducibility.

The multimodal Vision Transformer–Variational Autoencoder fusion model outperformed unimodal baselines, achieving an accuracy of 0.892 ± 0.012 and an area under the receiver operating characteristic curve of 0.927 ± 0.009, corresponding to a 7–10% improvement over WSI-only and omics-only models. Cross-attention–based fusion improved prediction stability and classification performance, while interpretability analyses (Grad-CAM and SHAP) highlighted biologically meaningful histopathological regions and molecular feature contributions.

This study presents a robust and scalable AI-based framework for integrating WSI and multiomics data in rectal precancerous lesions. The model improves predictive precision compared with unimodal baselines and offers preliminary interpretability insights through attention mechanisms. These findings support the potential of multimodal AI for early cancer risk assessment and precision pathology.

N6-methyladenosine (m6A), the most prevalent internal RNA modification in eukaryotic cells, is a dynamic regulator of RNA metabolism and cancer biology. In colorectal cancer (CRC), dysregulated m6A reshapes transcriptomic programs that control tumor growth, metastasis, immune evasion, and therapeutic resistance. However, the context-dependent functions of individual m6A regulators remain incompletely defined, the integration of m6A with canonical oncogenic signaling remains incomplete, and its role in metabolic reprogramming lacks a systematic overview. This review aims to integrate current evidence on m6A regulatory machinery in CRC, clarify its coordination with oncogenic signaling and metabolic pathways, and highlight emerging translational implications. The key players regulating m6A in CRC progression are m6A “writers”, including methyltransferase-like 3 and methyltransferase-like 14; m6A “erasers”, including fat mass and obesity-associated protein and AlkB homolog 5; and m6A “readers”, including the YTH m6A RNA-binding protein family and the insulin-like growth factor 2 mRNA-binding protein family. m6A modification coordinates key oncogenic pathways, including Wnt/β-catenin, PI3K/Akt, MAPK, and p53 signaling. Moreover, m6A-dependent regulation of metabolic enzymes such as hexokinase 2, pyruvate kinase M2, and fatty acid synthase promotes the reprogramming of glucose, amino acid, and lipid metabolism, linking epitranscriptomic control to bioenergetic adaptation. We also discuss context-dependent and paradoxical functions of m6A regulators and advances in m6A-targeted therapies. In conclusion, m6A modification functions as a central regulatory hub in CRC by integrating signaling networks and metabolic pathways. Deeper mechanistic insights into spatiotemporal m6A regulation may accelerate the development of biomarkers and targeted therapies for precision CRC management.

Development of mixed histiocytosis (Langerhans cell histiocytosis (LCH))/Erdheim–Chester disease (ECD)) after treatment in patients with an initial skull LCH lesion has not been well recognized. An elderly woman initially developed LCH at the left temporal bone, preceded by polyuria and polydipsia five years earlier; the lesion was surgically removed. Two years thereafter, she experienced her first LCH relapse with a right parietal skull lesion, in which a BRAF V600E mutation was confirmed, and chemotherapy was initiated. After a second LCH relapse involving the left parietal bone, the patient presented with a third relapse at the L2 vertebra. This lesion was pathologically diagnosed as mixed histiocytosis (LCH/ECD), resulting in refractoriness to conventional chemotherapy, and was successfully treated with targeted therapy using BRAF and MEK inhibitors. Spinal mixed histiocytosis (LCH/ECD) may develop following relapses of skull LCH after chemotherapy, for which targeted therapy could be effective.

Early and accurate prognostic assessment is crucial to avoid serious disease progression in patients with liver failure. Thyroid hormone is an important metabolic regulator involved in hepatic function. This review examines the pathophysiological regulation in detail of the hypothalamic-pituitary-thyroid axis in patients with liver failure and emphasizes the importance of thyroid profiling (thyroid-stimulating hormone, T3, and T4) in prognostic assessment and risk stratification. T3 can enhance liver regeneration. The clinical application of thyroid hormone replacement therapy in patients with acute-on-chronic liver failure complicated by non-thyroidal illness syndrome is controversial. This review aims to inform clinical practice regarding the relevance of thyroid hormone level assessment in liver failure and to provide novel insights into the prognostic evaluation and comprehensive care of liver failure complicated by thyroid dysfunction.