Sox9 mediates autophagy-dependent vascular smooth muscle cell phenotypic modulation and transplant arteriosclerosis.

Vascular smooth muscle cell (vSMC) phenotypic modulation is a dynamic pathogenesis process implicated in neointimal formation and transplant arteriosclerosis (TA). Transcription factor Sox9 functions to establish cell type and wound healing, but little is known about its transcriptional regulation in vSMCs and its roles in the development of TA. Here, we found an increased Sox9 expression in aortic allografts and in HMGB1-treated vSMCs in vitro, accompanied by the downregulation of vSMC markers. Notably, vSMC-specific Sox9 knockdown in aortic allografts attenuated neointimal formation through preventing vSMC phenotypic modulation following transplantation. We further indicated that HMGB1 induced Sox9 expression and vSMC phenotypic modulation through activating autophagy to degrade p27Kip1. Mechanistically, p27Kip1 bound to the Sox9 promoter in vSMCs together with p130/E2F4 complex, by which it restrained Sox9 transcriptional expression. These findings uncover a fundamental role of Sox9 in mediating autophagy-dependent vSMC phenotypic modulation and TA, offering a therapeutic approach for vascular pathologies.

TAK1 accelerates transplant arteriosclerosis in rat aortic allografts by inducing autophagy in vascular smooth muscle cells.

BACKGROUND AND AIMS: The proliferation and migration of vascular smooth muscle cells (VSMCs) are fundamental hallmarks of vasculopathy. Transforming growth factor ß-activated kinase-1 (TAK1) plays a crucial role in mediating cellular functions, including autophagy, which has been recently linked to the regulation of VSMC functions and the development of vasculopathy. This study aims to better dissect how TAK1 controls VSMC proliferation and migration. METHODS: A rat model of graft arteriosclerosis was employed to explore the influence of TAK1 signaling activation on VSMC proliferation, migration, autophagy, and neointima formation in vivo. Knockdown and pharmacological inhibition of TAK1 were utilized in cultured VSMCs to investigate the mechanisms underlying the progression of VSMC proliferation and migration. RESULTS: Increased phosphorylation of TAK1 (Thr-184/Thr-187) was examined in SMα-actin positive cells in the medial and neointimal lesions of aortic allografts. Lentivirus-mediated Tak1 shRNA transfection of aortic allografts robustly suppressed neointimal formation and lumen stenosis, as well as autophagy and cell proliferative responses. In cultured PDGF-BB-incubated VSMCs, genetic and pharmacological inhibition of TAK1 markedly attenuated autophagy activation, and blocked the progression of cell cycle, proliferation, and migration responses. CONCLUSIONS: Activation of TAK1 in VSMCs in the setting of aortic transplantation is an early and critical event in VSMC proliferation and migration, as well as neointima formation, because it controls autophagy activation, constituting a potential molecular mechanism and target for preventing transplant vasculopathy.

High BLM Expression Predicts Poor Clinical Outcome and Contributes to Malignant Progression in Human Cholangiocarcinoma.

Molecular mechanisms underlying the tumorigenesis of a highly malignant cancer, cholangiocarcinoma (CCA), are still obscure. In our study, the CCA expression profile data were acquired from The Cancer Genome Atlas (TCGA) database, and differentially expressed genes (DEGs) in the TCGA-Cholangiocarcinoma (TCGA-CHOL) data set were utilized to construct a co-expression network via weighted gene co-expression network analysis (WGCNA). The blue gene module associated with the histopathologic grade of CCA was screened. Then, five candidate hub genes were screened by combining the co-expression network with protein-protein interaction (PPI) network. After progression and survival analyses, bloom syndrome helicase (BLM) was ultimately identified as a real hub gene. Moreover, the receiver operating characteristic (ROC) curve analysis suggested that BLM had a favorable diagnostic and predictive recurrence value for CCA. The gene set enrichment analysis (GSEA) results for a single hub gene revealed the importance of cell cycle-related pathways in the CCA progression and prognosis. Furthermore, we detected the BLM expression in vitro, and the results demonstrated that the expression level of BLM was much higher in the CCA tissues and cells relative to adjacent non-tumor samples and normal bile duct epithelial cells. Additionally, after further silencing the BLM expression by small interfering RNA (siRNA), the proliferation and migration ability of CCA cells were all inhibited, and the cell cycle was arrested. Altogether, a real hub gene (BLM) and cell cycle-related pathways were identified in the present study, and the gene BLM may be involved in the CCA progression and could act as a reliable biomarker for potential diagnosis and prognostic evaluation.

Development of a novel lipid metabolism-based risk score model in hepatocellular carcinoma patients.

BACKGROUND: Liver cancer is one of the most common malignancies worldwide. HCC (hepatocellular carcinoma) is the predominant pathological type of liver cancer, accounting for approximately 75-85 % of all liver cancers. Lipid metabolic reprogramming has emerged as an important feature of HCC. However, the influence of lipid metabolism-related gene expression in HCC patient prognosis remains unknown. In this study, we performed a comprehensive analysis of HCC gene expression data from TCGA (The Cancer Genome Atlas) to acquire further insight into the role of lipid metabolism-related genes in HCC patient prognosis. METHODS: We analyzed the mRNA expression profiles of 424 HCC patients from the TCGA database. GSEA(Gene Set Enrichment Analysis) was performed to identify lipid metabolism-related gene sets associated with HCC. We performed univariate Cox regression and LASSO(least absolute shrinkage and selection operator) regression analyses to identify genes with prognostic value and develop a prognostic model, which was tested in a validation cohort. We performed Kaplan-Meier survival and ROC (receiver operating characteristic) analyses to evaluate the performance of the model. RESULTS: We identified three lipid metabolism-related genes (ME1, MED10, MED22) with prognostic value in HCC and used them to calculate a risk score for each HCC patient. High-risk HCC patients exhibited a significantly lower survival rate than low-risk patients. Multivariate Cox regression analysis revealed that the 3-gene signature was an independent prognostic factor in HCC. Furthermore, the signature provided a highly accurate prediction of HCC patient prognosis. CONCLUSIONS: We identified three lipid-metabolism-related genes that are upregulated in HCC tissues and established a 3-gene signature-based risk model that can accurately predict HCC patient prognosis. Our findings support the strong links between lipid metabolism and HCC and may facilitate the development of new metabolism-targeted treatment approaches for HCC.