No abstract

Coronary artery disease (CAD) is a major atherosclerotic cardiovascular disease and the leading cause of mortality globally. Long non-coding RNAs (lncRNAs) play crucial roles in CAD development. To date, the effect of lncRNA non-coding RNA activated by DNA damage (NORAD) on atherosclerosis in CAD remains unclear. The primary aim of this study was to investigate the effect of lncRNA NORAD on vascular endothelial cell injury and atherosclerosis. Here, ox-LDL-treated human umbilical vein endothelial cells (HUVECs) and high-fat-diet (HFD)-fed ApoE–/– mice were utilized as in vitro and in vivo models. The present study found that lncRNA NORAD expression was increased in ox-LDL-treated HUVECs and thoracic aorta of atherosclerotic mice, and knockdown of lncRNA NORAD alleviated vascular endothelial cell injury and atherosclerosis development in vitro and in vivo. Knockdown of lncRNA NORAD aggravated ox-LDL-reduced or atherosclerosis-decreased vascular endothelial growth factor (VEGF) expression in HUVECs and thoracic aorta of mice to ameliorate vascular endothelial cell injury and atherosclerosis development. Moreover, nucleus lncRNA NORAD suppressed VEGF gene transcription through enhancing H3K9 deacetylation via recruiting HDAC6 to the VEGF gene promoter in ox-LDL-treated HUVECs. In addition, VEGF reduced FUS (FUS RNA binding protein) expression by a negative feedback regulation in HUVECs. In summary, lncRNA NORAD enhanced vascular endothelial cell injury and atherosclerosis through suppressing VEGF gene transcription via enhancing H3K9 deacetylation by recruiting HDAC6. The findings could facilitate discovering novel diagnostic markers and therapeutic targets for CAD.

Objective: The purpose of this study was to evaluate the prognostic value of computed tomography (CT) texture features of pancreatic cancer with liver metastases. Methods: We included 39 patients with metastatic pancreatic cancer (MPC) with liver metastases and performed texture analysis on primary tumors and metastases. The correlations between texture parameters were assessed using Pearson's correlation. Univariate Cox proportional hazards model was used to assess the correlations between clinicopathological characteristics, texture features and overall survival (OS). The univariate Cox regression model revealed four texture features potentially correlated with OS (P<0.1). A radiomics score (RS) was determined using a sequential combination of four texture features with potential prognostic value that were weighted according to their β-coefficients. Furthermore, all variables with P<0.1 were included in the multivariate analysis. A nomogram,which was developed to predict OS according to independent prognostic factors, was internally validated using the C-index and calibration plots. Kaplan-Meier analysis and the log-rank test were performed to stratify OS according to the RS and nomogram total points (NTP). Results: Few significant correlations were found between texture features of primary tumors and those of liver metastases. However, texture features within primary tumors or liver metastases were significantly associated. Multivariate analysis showed that Eastern Cooperative Oncology Group performance status (ECOG PS), chemotherapy, Carbohydrate antigen 19-9 (CA19-9), and the RS were independent prognostic factors (P<0.05). The nomogram incorporating these factors showed good discriminative ability (C-index = 0.754). RS and NTP stratified patients into two potential risk groups (P<0.01). Conclusion: The RS derived from significant texture features of primary tumors and metastases shows promise as a prognostic biomarker of OS of patients with MPC. A nomogram based on the RS and other independent prognostic clinicopathological factors accurately predicts OS.