The peritoneum, especially the omentum, is a common site for gastric cancer (GC) metastasis. Our aim was to expound the role and mechanisms of Piezo1 on GC omentum metastasis. A series of functional assays were performed to examine cell proliferation, clone formation, apoptosis, Ca2+ influx, mitochondrial membrane potential (MMP) and migration after overexpression or knockdown of Piezo1. A GC peritoneal implantation and metastasis model was conducted. After infection by si‐Piezo1, the number and growth of tumours were observed in abdominal cavity. Fibre and angiogenesis were tested in metastatic tumour tissues. Piezo1 had higher expression in GC tissues with omentum metastasis and metastatic lymph node tissues than in GC tissues among 110 patients. High Piezo1 expression was associated with lymph metastasis, TNM and distant metastasis. Overexpressed Piezo1 facilitated cell proliferation and suppressed cell apoptosis in GC cells. Moreover, Ca2+ influx was elevated after up‐regulation of Piezo1. Piezo1 promoted cell migration and Calpain1/2 expression via up‐regulation of HIF‐1α in GC cells. In vivo, Piezo1 knockdown significantly inhibited peritoneal metastasis of GC cells and blocked EMT process and angiogenesis. Our findings suggested that Piezo1 is a key component during GC omentum metastasis, which could be related to up‐regulation of HIF‐1α.
The proposed approach is able to accurately and quickly determine the optimal viewing angles for the online support of coronary interventions.
Background: Impairment of left ventricular (LV) longitudinal function has an important role in hypertrophic cardiomyopathy (HCM). This research investigated an association between the longitudinal strain of different myocardial layers, longitudinal rotation and the LV systolic function of HCM patients. Methods: The research was performed on 36 HCM patients and 36 healthy subjects. The peak systolic longitudinal strain of the subendocardial, midmyocardial, and subepicardial layers was measured using 2-dimensional speckle tracking echocardiography (2D-STE). The apical long-axis and 4-and 2-chamber views were acquired via 2D Doppler echocardiography. The curve of the longitudinal rotation was traced at 17 timepoints in the analysis of 2 cardiac cycles. Results: Compared with healthy subjects, in HCM patients regional LV peak systolic longitudinal strain was less, not only in hypertrophied LV myocardium, but also in non-hypertrophied myocardium. The rotational degrees of the midmyocardial-septal, apex, and lateral wall of HCM patients were significantly different from that of normal subjects, as follows. In HCM patients, clockwise longitudinal rotation was found. The interventricular septum thickness at end-diastole positively correlated with the peak longitudinal systolic strain of the subendocardial, the midmyocardial, and the subepicardial layers. The area under ROC curve values for subendocardial, midmyocardial and subepicardial layers in HCM patients were 0.923, 0.938, 0.948. Conclusion: In HCM patients, the longitudinal function was damaged, even with normal LV ejection fraction. The peak longitudinal systolic strain of the subendocardial, midmyocardial, and subepicardial layers, and the longitudinal rotation detected by 2D-STE, are very sensitive predictors of systolic function in patients with HCM.
Long non-coding RNAs (lncRNAs) play important roles in a range of different human cancers. However, the role of lncRNA solute carrier organic anion transporter family member 4A1-AS1 (SLCO4A1-AS1) in colon cancer remains enigmatic. Hence, we aimed to explore the specific role of SLCO4A1-AS1 in colon cancer stem cells. Colon cancer-related differentially expressed lncRNA and mRNA were screened using microarray-based analysis, and the expression of SLCO4A1-AS1 and SLCO4A1 in colon cancer tissues was determined using reverse transcription quantitative polymerase chain reaction and western blot analysis. The interaction among SLCO4A1-AS1, microRNA-150-3p (miR-150-3p) and SLCO4A1 was verified using dual-luciferase reporter assay, RNA immunoprecipitation and RNA pull-down. Moreover, SLCO4A1-AS1, miR-150-3p and/or SLCO4A1 were overexpressed or depleted in colon cancer cells to detect their effects on migration, invasion, sphere formation, apoptosis and tumorigenesis abilities of colon cancer stem CD133+CD44+ cells using both in vitro and in vivo assays. SLCO4A1-AS1 and SLCO4A1 were screened as the differentially expressed lncRNA and mRNA in colon cancer tissues. SLCO4A1-AS1 was confirmed to competitively bind to miR-150-3p to elevate SLCO4A1 expression. Moreover, knockdown of SLCO4A1-AS1 decreased SLCO4A1 expression, thus inhibiting cell migration, invasion, sphere formation, and tumorigenesis abilities and enhancing the apoptosis of CD133+CD44+ cells. Collectively, these findings provide evidence demonstrating that depleting SLCO4A1-AS1 competitively binds to miR-150-3p, which downregulates SLCO4A1 expression, thus hindering colon cancer progression.
Background Oral cancer (OC) is a common and dangerous malignant tumor with a low survival rate. However, the micro level mechanism has not been explained in detail. Methods Gene and miRNA expression micro array data were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and miRNAs (DE miRNAs) were identified by R software. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of genes and genomes (KEGG) pathway analysis were used to assess the potential molecular mechanisms of DEGs. Cytoscape software was utilized to construct protein–protein interaction (PPI) network and miRNA-gene network. Central genes were screened out with the participation of gene degree, molecular complex detection (MCODE) plugin, and miRNA-gene network. Then, the identified genes were checked by The Cancer Genome Atlas (TCGA) gene expression profile, Kaplan-Meier data, Oncomine, and the Human Protein Atlas database. Receiver operating characteristic (ROC) curve was drawn to predict the diagnostic efficiency of crucial gene level in normal and tumor tissues. Univariate and multivariate Cox regression were used to analyze the effect of dominant genes and clinical characteristics on the overall survival rate of OC patients. Results Gene expression data of gene expression profiling chip(GSE9844, GSE30784, and GSE74530) were obtained from GEO database, including 199 tumor and 63 non-tumor samples. We identified 298 gene mutations, including 200 upregulated and 98 downregulated genes. GO functional annotation analysis showed that DEGs were enriched in extracellular structure and extracellular matrix containing collagen. In addition, KEGG pathway enrichment analysis demonstrated that the DEGs were significantly enriched in IL-17 signaling pathway and PI3K-Akt signaling pathway. Then, we detected three most relevant modules in PPI network. Central genes (CXCL8, DDX60, EIF2AK2, GBP1, IFI44, IFI44L, IFIT1, IL6, MMP9,CXCL1, CCL20, RSAD2, and RTP4) were screened out with the participation of MCODE plugin, gene degree, and miRNA-gene network. TCGA gene expression profile and Kaplan-Meier analysis showed that high expression of CXCL8, DDX60, IL6, and RTP4 was associated with poor prognosis in OC patients, while patients with high expression of IFI44L and RSAD2 had a better prognosis. The elevated expression of CXCL8, DDX60, IFI44L, RSAD2, and RTP44 in OC was verified by using Oncomine database. ROC curve showed that the mRNA levels of these five genes had a helpful diagnostic effect on tumor tissue. The Human Protein Atlas database showed that the protein expressions of DDX60, IFI44L, RSAD2, and RTP44 in tumor tissues were higher than those in normal tissues. Finally, univariate and multivariate Cox regression showed that DDX60, IFI44L, RSAD2, and RTP44 were independent prognostic indicators of OC. Conclusion This study revealed the potential biomarkers and relevant pathways of OC from publicly available GEO database, and provided a theoretical basis for elucidating the diagnosis, treatment, and prognosis of OC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.