Joint efficacy of the three biomarkers SNCA, GYPB and HBG1 for atrial fibrillation and stroke: Analysis via the support vector machine neural network

ANK1 inhibits malignant progression of osteosarcoma by promoting ferroptosis

PURPOSE

Osteosarcoma (OS) is a primary bone tumor with high malignancy and poor prognosis. Ferroptosis plays a crucial role in OS. This study aimed to evaluate the effects of Ankyrin 1 (ANK1) on OS and to investigate its specific mechanisms.

METHODS

Microarray datasets related to "osteosarcoma" were selected for this study. Relevant hub genes in OS were identified through bioinformatics analysis. Transfected U-2OS and MG-63 cells were used for in vitro experiments. The effects of ANK1 overexpression on cell viability, migration, and invasion were determined through CCK-8, wound healing, and transwell assays. An OS mouse model was established for the in vivo experiments. Hematoxylin-eosin staining and immunohistochemistry were conducted to observe the histological effects of ANK1 overexpression on mouse tumors. TUNEL staining was performed to evaluate apoptosis in mouse.

RESULTS

There were 159 common differentially expressed genes in the GSE16088 and GSE19276 datasets. The hub genes ANK1, AHSP, GYPB, GYPA, KEL, and ALAS2 were identified. Pan-cancer analysis verified that ANK1 was closely associated with cancer prognosis and immune infiltration. Furthermore, ANK1 overexpression inhibited the proliferation, migration, and invasion of OS cells and promoted ferroptosis, while ferroptosis inhibitor (fer-1) weakened these effects. Moreover, ANK1 overexpression suppressed tumor growth, promoted apoptosis, reduced the number of Ki67 positive cells, and elevated the number of caspase-3 positive cells in vivo.

CONCLUSIONS

ANK1 is a prognosis biomarker of OS that can alleviate the progression of OS by promoting ferroptosis.

Expression profile of circulating miRNAs in patients with atrial fibrillation-dominated cardioembolic stroke: A systematic review and bioinformatics analysis

Background

Cardioembolic stroke is a type of ischemic stroke with high disability and mortality, a high recurrence rate and poor prognosis. miRNAs have been explored as potential noninvasive biomarkers in atrial fibrillation and ischemic stroke, but their expression profile in cardioembolic stroke still needs to be explored. This study will explore the differences in miRNA expression between cardioembolic stroke patients and healthy people through meta-analysis and attempt to analyze the target genes by bioinformatics analysis.

Methods

Literature databases and gene expression databases were searched from the inception date to June 2022. The study reported the circulating miRNA expression profiles in cardioembolic stroke patients and healthy controls. miRNAs with significantly differential expression and their target genes were analyzed.

Results

Three articles and one gene expression dataset were included in the analysis. The results showed that miR-21-5p (SMD: 2.16; 95 % CI: 1.57, 2.75; p < 0.001), miR-943, miR-145-3p, and miR-3148 were upregulated in cardioembolic stroke patients compared with controls. The downregulated miRNAs included miR-3136-5p, miR-2277-5p, and miR-2277-3p. The area under the receiver operating characteristic curve of miR-21-5p for cardioembolic stroke was 0.975 (0.933-0.989). For the enrichment results, the target genes of upregulated miRNAs were enriched in the MAPK signaling pathway, Ras signaling pathway, etc. The target genes of downregulated miRNAs were also enriched in the Ras signaling pathway.

Conclusions

This study suggested that circulating miR-21-5p is upregulated in cardioembolic stroke patients compared to healthy controls. The Ras signaling pathway plays an important role in pathogenesis according to enrichment analysis.

Beneficial Effect of Edoxaban on Preventing Atrial Fibrillation and Coagulation by Reducing Inflammation via HBG1/HBD Biomarkers

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia. The effectiveness and mechanism of edoxaban in preventing stroke after atrial fibrillation remain unclear. Methods: The expressions of HBG1 and HBD in red blood cells were tested in AF. Sixty C57B/6J mice were randomly divided into the following groups: the control (CON) group, atrial fibrillation (AF) group, AF + edoxaban group, and AF + rivaroxaban group. H&E staining assay and reticular fiber staining were performed. Myocardial fibrosis was evaluated by the Masson staining assay, Sirius red staining assay, and immunohistochemical assay for the expressions of α-SMA and COL1A1. ELISA and RT-PCR assay were performed for the detection of inflammatory parameters (TNF-α, IL-1β, IL-6, and IL-10). Blood lipids were detected by using the Beckman automatic biochemical analyzer. Furthermore, four items of coagulation were detected, and molecular docking among HBG1, HBD, and MASP1 (Xa) was performed by PyMOL 2.1 software. The BP neural network model, cubic spline interpolation, and support vector machine model were constructed to predict prothrombin time based on HBG1 and HBD expressions. COIP assay was performed to construct the interaction between HBG1 and HBD. The functional enrichment analysis was performed by DAVID and Metascape tools. Results: The expressions of HBG1 and HBD in red blood cells of the patients with atrial fibrillation were decreased. The results showed a lower level of hemoglobin in red blood cells with HBG1-siRNA and HBG1-siRNA. Compared with the AF group, the collagen fiber percentage in the AF + edoxaban group was decreased (p < 0.05). After using edoxaban, the expressions of TNF-α, IL-1β, IL-6, and IL-10 were significantly decreased (p < 0.05). The LDL-C, TC, and TG levels were downregulated in the AF + edoxaban group. The PT and APTT levels in the AF + edoxaban group were more increasing than in the AF mice (p < 0.05). Compared with the AF group, the expressions of HBG1 and HBD were downregulated in the AF + edoxaban group (p < 0.05). HBG1 protein matched well with HBD and MASP1(Xa) protein surfaces. There exists a significant interaction between HBG1, HBD, and PT via the BP neural network and support vector machine. Enrichment analysis showed that HBG1 and HBD were mainly enriched in blood coagulation. Conclusion: Edoxaban could prevent atrial fibrillation and coagulation by reducing inflammation, lipids, and fibrosis via HBG1/HBD biomarkers effectively, and the effect was superior to that of rivaroxaban.