Identification of EDNRA as the Key Biomarker for Hypercholesterolemia and Colorectal Cancer.

Some studies have investigated the role of cholesterol in the progression of colorectal cancer (CRC). However, the underlying mechanism of action is not clear. In this study, we used bioinformatics tools to elucidate the molecular mechanisms involved. We initially obtained CRC datasets from the Gene Expression Omnibus (GEO) database and hypercholesterolemia data from GeneCards and DisGeNE. Common differentially expressed genes (DEGs) were determined by using Venn diagram web tools. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The hub gene was identified through common expression pattern analysis and survival analysis. Finally, we conducted an immune regulatory point analysis and predicted target drugs based on the hub gene. The results of our analysis revealed 13 common DEGs, with endothelin receptor type A (EDNRA) identified as the hub gene linking hypercholesterolemia and CRC. The results of the GO analysis showed that the common DEGs were primarily associated with the G-protein coupled receptor signaling pathway, extracellular space, and receptor binding. The results of the KEGG pathway enrichment analysis indicated enrichment in pathways related to cancer and the phospholipase D signaling pathway. Additionally, we identified potential target drugs, including Podocarpus montanus, Diospyros kaki, Herba Salviae japoniae, sitaxentan, and ambrisentan. We found that EDNRA might be an underlying biomarker for both hypercholesterolemia and CRC. The predicted target drugs provide new strategies for treating CRC.

Establishment and assessment of a preclinical model of acute kidney injury induced by contrast media combined acute myocardial ischemia reperfusion surgery.

Acute kidney injury (AKI) is a common complication after acute myocardial infarction (AMI) in clinical practice, and the majority of previous preclinical models were induced by a single factor. The objective of the present study was to establish a stable preclinic model of AKI induced by contrast media (CM) with acute myocardial ischemia reperfusion surgery and to identify the effect of oxidative stress on kidney injury. Rats were treated individually or with CM or myocardial ischemia reperfusion surgery. Renal baseline and AKI parameters, the level of oxidative stress and histopathological images were examined along with AKI biomarkers. Results showed the incidence of AKI in the CM group and ischemia reperfusion injury (IRI) group was 40%, χ2 test (P<0.05 vs. CM-IRI) and 35%, χ2 test (P<0.05 vs. CM-IRI) and the combination group had the highest incidence rate 75%. IRI surgery combined with CM diminished kidney function and induced oxidative stress by increasing creatinine, blood urea nitrogen and reactive oxygen species levels. Western blotting showed that the early AKI biomarker of NGAL and KIM-1 increased and that the combination group had the highest value. Pathology damage exhibited severe kidney damage in the combination group compared with other control groups. The present research established a reliable preclinic model of post-AMI AKI with a stable and high postoperative AKI rate. Additionally, CM was demonstrated to exacerbate AKI caused by acute myocardial infarction through oxidative stress and, thus, oxidative stress may be a potential therapeutic target.

Elevation of hemoglobin A1c increases the risk of decline in left ventricular systolic function among patients with coronary artery disease.

AIMS: The aim of this study was to investigate the association of HbA1c and left ventricular (LV) systolic function among patients with coronary artery disease (CAD). METHODS: CAD patients from the Cardiorenal ImprovemeNt II (CIN-II, NCT05050877) registry were included in the study. They were separated into four groups based on HbA1c levels (Q1: HbA1c<5.7%; Q2: 5.7% ≤ HbA1c < 6.1%; Q3: 6.1% ≤ HbA1c < 6.9%; Q4: HbA1c ≥ 6.9%). The endpoint was decline in LV systolic function, defined as an absolute decrease in LV ejection fraction (LVEF) ≥10% from baseline to follow-up with 3-12 months. The association of HbA1c and LVEF was assessed by logistics regression models. RESULTS: CAD patients (n = 3,994) (age 62.9 ± 10.6 years; 22.2% female) were included in the final analysis. A decline in LV systolic function was recorded in 429 (11%) patients during follow-up. After fully adjusting for confounders, HbA1c was significantly associated with the high risk of decline in LV systolic function (OR 1.12 [95%CI 1.05-1.20] P = 0.001). By stratifying HbA1c as four groups, there is a significantly increased risk of decline in LV systolic function when HbA1c ≥6.1% (Q2, Q3 and Q4 vs Q1, with OR 1.22 [0.88-1.68] P = 0.235; OR 1.48 [1.07-2.05] P = 0.019; OR 1.60 [1.160-2.22] P = 0.004, respectively). Meanwhile, patients with decline in LV systolic function had a higher risk of cardiovascular death. CONCLUSIONS: Elevated HbA1c is a predictor of decline in LV systolic function in CAD patients. Clinicians should be aware of the risk of decline in LV systolic function in CAD patients with elevated HbA1c, and take measures as soon as possible.

How to Choose a Survival Period? The Impact of Antibiotic Use on OS or PFS in NSCLC Patients Treated With Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis.

BACKGROUND: The development of immunotherapy has dramatically changed the treatment of non-small-cell lung cancer. The negative association of antibiotics on the clinical activity of immune checkpoint inhibitors in patients with NSCLC is well known. METHODS: PubMed, Embase, and Medline databases were searched until January 11, 2020. We included retrospective studies of ICIs (e.g., PD-1, PD-L1, and CTLA-4). The clinical outcomes were progression-free survival (PFS) and overall survival (OS). Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated, and subgroup and sensitivity analyses were performed. RESULTS: Our results indicated that the use of antibiotics reduced the survival of NSCLC patients treated with ICIs. The pooled HRs of PFS and OS were HR = 1.41 (95% CI = 1.23-1.61; P < 0.001) and HR = 2.16 (95% CI = 1.79-2.60; P < 0.001). We divided the studies into 5 subgroups according to antibiotic exposure time. Subgroup analysis showed that the patients that were administered antibiotics [-60 days; 0 days] or [-30 days; 0 days] before the initiation of ICIs treatment had a poorer OS rate, whereas those patients that were administered antibiotics [0 days; 30 days] after the initiation of ICIs treatment had a poorer PFS rate. In summary, ATB treatment in patients [-60 days; +30 days] near the initiation of ICIs treatment significantly reduced the survival in NSCLC patients. CONCLUSION: Our results indicated that ATB use is negatively associated with survival in NSCLC patients treated with ICIs immunotherapy. Similar studies involving a larger sample of cases are still being published. This meta-analysis identified that the timing of ATB treatment in NSCLC patients receiving ICIs immunotherapy has different effects on the OS and PFS of these patients. ATB treatment prior to the initiation of ICIs treatment affects OS, whereas ATB treatment after the initiation of ICIs treatment affects PFS.

Experimental evidence and network pharmacology-based analysis reveal the molecular mechanism of Tongxinluo capsule administered in coronary heart diseases.

BACKGROUND: Tongxinluo (TXL) capsule, a polypharmacy derived from traditional Chinese medicine (TCM), has been widely used in coronary heart disease (CHD), while the underlying mechanism of TXL capsule is still unclear. The present study aimed at investigating the underlying mechanism of TXL acting on CHD patients and providing substantial evidence in molecular evidence by means of a network pharmacological analysis. METHOD: Active compounds and targeted genes of TXL were retrieved from TCM systems pharmacology (TCMSP) and TCM integrative database (TCMID). CHD and coronary artery disease were treated as search queries in GeneCards and Online Mendelian Inheritance in Man (OMIM) databases to obtain disease-related genes. Visualization of disease-targets network was performed under administration of Cytoscape software. Besides, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were administered. H9c2 cells were used to validate the predicted results in cardiomyocytes/reoxygenation model, and anti-inflammatory ability was examined. RESULTS: A network of a total of 212 nodes and 1016 edges was obtained. Peptide and ubiquitin-like protein ligase binding occupied a leading position of GO enrichment. For KEGG analysis, fluid shear stress and atherosclerosis, as well as inflammation-related pathways were enriched. Cellular validation revealed the anti-inflammatory effect of ß-sitosterol, eriodictyol, odoricarpin, and tirucallol as active compounds of TXL. CONCLUSION: Our study provided substantial molecular evidence that TXL capsule possessed the characteristics of multitargets with safe profile, and the main component is capable of regulating cytokine level in CHD patients.

A Seven-Long Non-coding RNA Signature Improves Prognosis Prediction of Lung Adenocarcinoma: An Integrated Competing Endogenous RNA Network Analysis.

Early and precise prediction is an important way to reduce the poor prognosis of lung adenocarcinoma (LUAD) patients. Nevertheless, the widely used tumor, node, and metastasis (TNM) staging system based on anatomical information only often could not achieve adequate performance on foreseeing the prognosis of LUAD patients. This study thus aimed to examine whether the long non-coding RNAs (lncRNAs), known highly involved in the tumorigenesis of LUAD through the competing endogenous RNAs (ceRNAs) mechanism, could provide additional information to improve prognosis prediction of LUAD patients. To prove the hypothesis, a dataset consisting of both RNA sequencing data and clinical pathological data, obtained from The Cancer Genome Atlas (TCGA) database, was analyzed. Then, differentially expressed RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) were identified and a lncRNA-miRNA-mRNA ceRNA network was constructed based on those differentially expressed RNAs. Functional enrichment analysis revealed that this ceRNA network was highly enriched in some cancer-associated signaling pathways. Next, lasso-Cox model was run 1,000 times to recognize the potential survival-related combinations of the candidate lncRNAs in the ceRNA network, followed by the "best subset selection" to further optimize these lncRNA-based combinations, and a seven-lncRNA prognostic signature with the best performance was determined. Based on the median risk score, LUAD patients could be well distinguished into high-/low-risk subgroups. The Kaplan-Meier survival curve showed that LUAD patients in the high-risk group had significantly shorter overall survival than those in the low-risk group (log-rank test P = 4.52 × 10-9). The ROC curve indicated that the clinical genomic model including both the TNM staging system and the signature had a superior performance in predicting the patients' overall survival compared to the clinical model with the TNM staging system only. Further stratification analysis suggested that the signature could work well in the different strata of the stage, gender, or age, rendering it to be a wide application. Finally, a ceRNA subnetwork related to the signature was extracted, demonstrating its high involvement in the tumorigenesis mechanism of LUAD. In conclusion, the present study established a lncRNA-based molecular signature, which can significantly improve prognosis prediction for LUAD patients.