❌

Normal view

Received today — 7 October 2026 ⏭ (Multiomics OR Omics) AND (Pancreatic)

Transformer-Based Multitask Framework Integrating Habitat and Deep Learning for Predicting Early Disease Control and Survival in Immunotherapy-Treated Hepatocellular Carcinoma

Adv Sci (Weinh). 2026 Sep 27:e78005. doi: 10.1002/advs.78005. Online ahead of print.

ABSTRACT

Hepatocellular carcinoma (HCC) patients show heterogeneous responses to immune checkpoint inhibitors (ICIs). This study developed ECOS-Net, a transformer-based multitask network integrating CT-derived habitat and 2.5-dimensional (2.5D) deep learning features for simultaneously predicting early disease control (DC) and overall survival (OS). Of 1,234 patients with HCC enrolled from eight institutions and public databases, 832 ICI-treated patients were used for model development. ECOS-Net fused features using multi-head attention and generated early DC probabilities and OS risk scores. ECOS-DC achieved AUCs of 0.836, 0.822, and 0.817 in training, internal validation, and external test sets, outperforming clinical models (all p values < 0.05). ECOS-OS yielded C-indices of 0.730, 0.722, and 0.720, respectively. Integrated models also showed favorable external performance (early DC AUC: 0.825; OS C-index: 0.741). Patients with higher ECOS-DC probabilities had a higher likelihood of early DC, whereas those with higher ECOS-OS risk had shorter OS, with directionally consistent associations across most subgroups. Exploratory biological analyses suggested that the higher ECOS-DC probability and lower ECOS-OS risk groups were associated with immune-active tumor microenvironment features. Therefore, ECOS-Net shows potential as a non-invasive imaging-based risk stratification framework for simultaneously predicting early DC and OS in ICI-treated HCC patients.

PMID:42801546 | PMC:PMC13616327 | DOI:10.1002/advs.78005

Inositol Metabolism Modulates Inflammatory Injury in Acute Pancreatitis via the ISYNA1-NETs Axis

J Inflamm Res. 2026 Sep 22;19:606503. doi: 10.2147/JIR.S606503. eCollection 2026.

ABSTRACT

BACKGROUND: Neutrophil extracellular traps (NETs) were key factors mediating inflammatory injury in acute pancreatitis (AP). To this end, there was an urgent need to identify precise and effective therapeutic targets that modulate NETs formation, providing new ideas for the prevention and treatment of AP pancreatitis injury.

GAP: To address this gap, we investigated the potential involvement of the myo-inositol metabolism in modulating NETs and inflammatory damage during AP.

METHODS: Multi-omics analysis identified myo-inositol metabolism as critical. We then established the in vitro NETs model using phorbol-12-myristate-13-acetate (PMA) to investigate the role and regulatory mechanism of inositol-3-phosphate synthase 1 (ISYNA1) on NETs formation. Finally, the findings were validated in the classic AP mouse model to verify the correlation between myo-inositol metabolism and AP pathogenesis.

RESULTS: Multiple omics analyses showed that the myo-inositol metabolic pathway is the most significant, and the key enzyme ISYNA1 involved in myo-inositol synthesis was significantly reduced. ISYNA1 was significantly downregulated in both the in vitro NETs model and in neutrophils infiltrating the pancreatic tissue of AP mice. Meanwhile, exogenous supplementation of ISYNA1 or myo-inositol significantly inhibited the NETs formation in vitro and inflammatory injury in AP mice. Mechanistically, downregulation of ISYNA1 led to reduced myo-inositol synthesis, thereby promoting NETs formation via modulation of the PI3K/AKT pathway.

CONCLUSION: ISYNA1 and myo-inositol metabolism were among the key links that regulated NETs formation and inflammatory injury in AP. Therefore, enhancing ISYNA1 and myo-inositol metabolism might serve as a potential intervention target for treating acute organ injury in AP.

PMID:42801157 | PMC:PMC13615823 | DOI:10.2147/JIR.S606503

❌