MAIN METHODS: The effects of BChE on signaling pathways were determined by immunoblotting in a BChE knockout hepatocyte cell line. DiI-LDL probe was used to explore the effect of BChE expression on LDL internalization. Co-immunoprecipitation and LC-MS were used to explore the interacting proteins with BChE. Finally, a hepatocyte-restricted BChE silencing mouse model was established by AAV8-Tbg-shRNA, and the hypercholesterolemia was induced by 65% kcal% high-fat, high-sucrose diet feeding.
MAIN FINDINGS: Here we demonstrate that butyrylcholinesterase (BChE) governs the LDL receptor levels and LDL uptake capacity through the MEK-ERK signaling cascades to promote Ldlr transcription. BChE interacts and co-localizes with PRMT5, a protein methylation modifier controlling the ERK signaling. PRMT5 regulates LDLR-dependent LDL uptake and is a substrate of chaperone-mediated autophagy (CMA). BChE deficiency induces the PRTM5 degradation dependent on CMA activity, possibly through facilitating the HSC70 (Heat shock cognate 71 kDa) recognition of PRMT5. Remarkably, in vivo hepatocyte-restricted BChE silencing reduces plasma cholesterol levels substantially. In contrast, the BChE knockout mice are predisposed to hypercholesterolemia.
SIGNIFICANCE: Taken together, these findings outline a regulatory role for the BChE-PRMT5-ERK-LDLR axis in hepatocyte cholesterol metabolism, and suggest that targeting liver BChE is an effective therapeutic strategy to treat hypercholesterolemia.
MATERIAL AND METHODS: Differential gene expression was identified using the "limma" package in R. Prognosis-related LncRNAs were identified via univariate Cox regression analysis, while a prognostic model was crafted using multivariate Cox regression analysis. Survival analysis was conducted using Kaplan-Meier curves. The precision of the prognostic model was assessed through ROC analysis. Subsequently, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were executed on the TCGA dataset via the TIDE database. Fractions of 24 types of immune cell infiltration were obtained from NCI Cancer Research Data Commons using deconvolution techniques. The protein expression levels encoded by specific genes were obtained through the TPCA database.
RESULTS: In this research, we have identified 85 LncRNAs associated with TP53 mutations and developed a corresponding signature referred to as TP53MLncSig. Kaplan-Meier analysis revealed a lower 3-year survival rate in high-risk patients (46.9%) compared to low-risk patients (74.2%). The accuracy of the prognostic TP53MLncSig was further evaluated by calculating the area under the ROC curve. The analysis yielded a 5-year ROC score of 0.793, confirming its effectiveness. Furthermore, a higher score for TP53MLncSig was found to be associated with an increased response rate to immune checkpoint blocker (ICB) therapy (p = .005). Patients possessing high-risk classification exhibited lower levels of P53 protein expression and higher levels of genomic instability.
CONCLUSION: The present study aimed to identify and validate LncRNAs associated with TP53 mutations. We constructed a prognostic model that can predict chemosensitivity and response to ICB therapy in HCC patients. This novel approach sheds light on the role of LncRNAs in TP53 mutation and provides valuable resources for analyzing patient prognosis and treatment selection.