Long non-coding RNA in coronary artery disease: the role of PDXDC1-AS1 and SFI1-AS1.

This study investigates the interaction between long non-coding RNAs (lncRNAs) and metabolic risk factors that contribute to coronary artery disease (CAD). A total transcriptome high throughput sequencing study was conducted on peripheral blood mononuclear cells from five patients with CAD and five healthy controls. Validation assay by qRT-PCR was conducted among 270 patients and 47 controls. Finally, to evaluate the lncRNAs' diagnostic value for CAD, the Spearman correlation test and receiver operating characteristic curve (ROC) analysis were utilized. Additionally, univariate and multivariate logistic regression along with crossover analyses were conducted to identify the interaction between lncRNA and environmental risk factors. A total of 2149 of 26,027 lncRNAs identified by RNA sequencing were differentially expressed in CAD patients compared to controls. Validation by qRT-PCR showed significantly different relative expression levels for lncRNAs PDXDC1-AS1, SFI1-AS1, RP13-143G15.3, DAPK1-IT1, PPIE-AS1, and RP11-362A1.1 between the two groups (all P<0.05). The area under the ROC values of PDXDC1-AS1 and SFI1-AS1 is 0.645 (sensitivity=0.443 and specificity=0.920) and 0.629 (sensitivity=0.571 and specificity=0.909), especially. Multivariate logistic regression analyses showed that lncRNAs PDXDC1-AS1 (OR=2.285, 95%CI=1.390-3.754, p=0.001) and SFI1-AS1 (OR=1.163, 95%CI=1.163-2.264, p=0.004) were protective factors against CAD. Under the additive model, cross-over analyses demonstrated significant interactions between lncRNAs PDXDC1-AS1 and smoking in relation to CAD risk (S=3.871, 95%CI=1.140-6.599). PDXDC1-AS1 and SFI1-AS1 were sensitive and specific biomarkers for CAD and exhibited synergistic effects with certain environmental factors. These results highlighted their potential use as CAD diagnostic biomarkers for future research.

Characteristics of circular RNAs expression of peripheral blood mononuclear cells in humans with coronary artery disease.

Circular RNAs (circRNAs) function as promising biomarkers and therapeutic targets for coronary artery disease due to their high stability, covalently closed structure, and potential gene regulation. We aimed to identify the expression profile and role of circular RNAs (circRNAs) in coronary artery disease (CAD). We performed RNA sequence analysis of circRNAs in peripheral blood mononuclear cells of five patients with CAD and five controls. Bioinformatics analyses were adopted to explore biological functions of differentially expressed circRNAs. The miRanda and TargetScan tools were used to predict the microRNA (miRNA)-targeting interactions and to construct a triple network of differentially expressed gene-circRNA-miRNA-mRNA. In total, 13,160 downregulated and 12,905 upregulated circRNAs were identified in CAD. A gene ontology annotation analysis showed that genes in the network were involved in organelle organization, cell cycle, mitotic cycle, and cellular metabolic process. Parental genes of the 10 dysregulated circRNAs were involved in metabolism and protein modification, and these circRNAs might regulate gene expression associated with CAD via miRNA sponges. As potential competing endogenous RNAs (ceRNAs), dysregulated circRNAs may be involved in the pathogenesis of CAD, which provides new insights into the diagnosis and prognosis of coronary artery disease.

Proteomic characterization of epithelial ovarian cancer delineates molecular signatures and therapeutic targets in distinct histological subtypes.

Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicates potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.

Comprehensive Analysis of mRNA Expression Profiling and Identification of Potential Diagnostic Biomarkers in Coronary Artery Disease.

The aim of this study is to investigate mRNA expression profiling by RNA sequencing (RNA-seq) in patients with coronary artery disease (CAD) and validate differentially expressed genes (DEGs) as novel biomarkers for CAD. Transcriptome-wide mRNA expression analysis of peripheral blood mononuclear cells was performed in five CAD patients and five controls. Functional enrichment analyses, protein-protein interaction network construction, and hub gene selection were further conducted. Relative expression levels of hub genes were validated by quantitative reverse transcription PCR in larger cohorts. Spearman correlation test and multiple linear regression analysis were applied to examine the relationship between confounding factors with severity of coronary artery atherosclerosis. Receiver operating characteristic (ROC) curve analysis was adopted to identify potentially diagnostic biomarkers for CAD. A total of 527 upregulated and 653 downregulated mRNAs were identified as DEGs in CAD patients. The relative expression levels of beta-transducin repeat containing E3 ubiquitin protein ligase (BTRC), F-box and leucine-rich repeat protein 4 (FBXL4), ubiquitin conjugating enzyme E2 D2 (UBE2D2), and ankyrin repeat and SOCS box containing 1 (ASB1) were significantly different between two groups (all p ≤ 0.05). The severity of coronary artery atherosclerosis was negatively associated with the BTRC gene relative expression level (r = -0.323, p < 0.001) and positively with UBE2D2 (r = 0.285, p < 0.001). ROC analysis of BTRC and UBE2D2 genes showed that the areas under the curve were 0.782 (95% CI: 0.720-0.845, p < 0.001) and 0.753 (95% CI: 0.681-0.824, p < 0.001), respectively. We described the characteristics of mRNA expression in the peripheral blood of CAD patients and controls by RNA-seq. Combined with Spearman correlation analysis and ROC analyses, BTRC and UBE2D2 genes had significantly diagnostic values, which may have potential to act as novel diagnostic biomarkers and therapeutic targets for CAD.

Fully automated identification and quantification of five polar pesticides in groundwater by isotope dilution-online solid phase extraction coupled with high-performance liquid chromatography-quadrupole Orbitrap high-resolution mass spectrometry.

A fully automated method for identification and quantification of five polar pesticides in groundwater by isotope dilution-online solid-phase extraction (SPE) coupled with high-performance liquid chromatography-quadrupole Orbitrap high-resolution mass spectrometry was developed. After one step of filtration, an aliquot of a 7.5-ml water sample was automatedly preconcentrated and purified on a turbulent Cyclone SPE column. The analytes were eluted in backflush mode, then separated on an analytical column and acquired by full MS/dd-MS2 scan in negative and positive ions mode. The major parameters for sample loading, cleanup, and elution were optimized in detail. Preconcentration and ionization efficiency were highly improved by using 0.1% acid solution in the mobile phase. The method provided good linearity of calibration coefficients (R2 > 0.995), sensitive method limits of detection (0.5-10.0 ng/L), accurate mass spectra (within 5 ppm error), satisfactory matrix spiking recoveries (98.4% to 109%), and high precision (intraday/interday relative standard deviations 1.57-8.90%). The method was successfully applied to analyze large batch groundwater of National Groundwater Monitoring Project and suspect screening of potential pesticides in groundwater. The study provided a practical alternative for a simple, robust, sensitive, and accurate identification and qualification of five polar pesticides in groundwater.