ABSTRACT Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths, its progression and treatment heterogeneity are mainly influenced by driver gene and tumor micro-environment (TME) interactions. Nevertheless, the mechanisms of this process at the single-cell level remain unclear. This study integrated TCGA and multi-center single-cell transcriptome data to identify a 575 genes HCC-specific core set, developing a single-cell “oncogene scoring” system to quantify individual carcinogenic activity. This score is significantly elevated in malignant and proliferative T cells and is closely associated with metabolic reprogramming, aberrant cell‒cell communication, and immunosuppressive phenotypes. Based on these characteristics, we constructed a machine learning-based Random Survival Forest (RSF) prognostic model validated in multiple independent cohorts, which classifies patients into distinct risk subtypes. The high-risk group exhibits genomic instability, increased tumor stemness, and immune evasion, while the low-risk group was more sensitive to drugs such as sorafenib. This study highlights the potential pathways by which high oncogenic activity is associated with HCC progression, suggesting a profound link with single-cell metabolic‒immune crosstalk. The constructed RSF model offers a promising computational framework for risk stratification and provides hypothesis-generating insights that may inform future personalized treatment strategies for HCC patients.
BACKGROUND
Hepatic ischemia-reperfusion injury (HIRI) remains a clinical challenge during liver surgery and transplantation, largely due to the lack of effective pharmacological interventions. Isolinderalactone (ILL), a sesquiterpene lactone, exhibits potent antioxidant and anti-inflammatory properties. However, its therapeutic potential for HIRI and its precise molecular targets, particularly regarding the SIRT1/IRE1α-mediated endoplasmic reticulum stress (ERS) pathway, remain to be elucidated.
OBJECTIVE
This study aimed to determine the hepatoprotective effects of ILL against HIRI and investigate its regulatory mechanism centered on the SIRT1/IRE1α signaling axis.
METHODS
HIRI was modeled in mice via ischemia/reperfusion (I/R) and in AML12 cells via hypoxia/reoxygenation (H/R). Cellular injury, oxidative stress, endoplasmic reticulum stress (ERS), apoptosis, and inflammatory responses were assessed using biochemical, histological, molecular, and cellular imaging techniques. The physical and functional interaction between ILL and SIRT1 was characterized through molecular docking, dynamics simulations, surface plasmon resonance, and enzymatic activity assays. The role of SIRT1 was further validated using genetic knockdown and pharmacological inhibition (EX527).
RESULTS
ILL treatment significantly attenuated liver tissue damage, restored intracellular redox homeostasis, and mitigated ERS-induced inflammation and apoptosis. Mechanistically, ILL not only upregulated SIRT1 expression but also directly bound to SIRT1 to enhance its deacetylase activity, thereby suppressing the downstream IRE1α/TRAF2/JNK signaling cascade. Notably, SIRT1 silencing or pharmacological blockade with EX527 significantly blunted, albeit did not completely abolish, the protective effects of ILL, indicating that the SIRT1/IRE1α axis serves as a primary, though not exclusive, mediator of ILL's hepatoprotective activity.
CONCLUSION
ILL attenuates HIRI by simultaneously elevating SIRT1 expression and activating its deacetylase function, thereby restraining IRE1α-dependent ERS and subsequent hepatic injury. These findings highlight ILL as a promising therapeutic candidate for the management of perioperative HIRI.
Hao Li, Zhenyu Guan, Wendong Li et al.· International Immunopharmaco...· 0 citations
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