CLEC3B protects H9c2 cardiomyocytes from apoptosis caused by hypoxia via the PI3K/Akt pathway

Identification of metabolism-related gene signature in lung adenocarcinoma

AIM

Lung cancer is one of the most common cancers in China and has a high mortality rate. Most patients who are diagnosed have lost the opportunity to undergo surgery. Aberrant metabolism is closely associated with tumorigenesis. We aimed to identify an effective metabolism-related prediction model for assessing prognosis based on the cancer genome atlas (TCGA) and GSE116959 databases.

METHODS

TCGA and GSE116959 datasets from Gene Expression Omnibus were used to obtain lung adenocarcinoma (LUAD) data. Additionally, we captured metabolism-related genes (MRGs) from the GeneCards database. First, we extracted differentially expressed genes using R to analyze the LUAD data. We then selected the same differentially expressed genes, including 168 downregulated and 77 upregulated genes. Finally, 218 differentially expressed MRGs (DEMRGs) were included to perform functional enrichment analysis and construct a protein-protein interaction network with the help of Cytoscape and Search Tool for the Retrieval of Interacting Genes database. Cytoscape was used to visualize the intensive intervals in the network. Then univariate and Least Absolute Shrinkage and Selection Operator Cox regression analyses, which assisted in identifying the overall survival (OS)-related DEMRGs and building a 10-DEMRG prognosis model, were performed. The prognostic values, tumor immunity relevance, and molecular mechanism were further investigated. A nomogram incorporating signature, age, gender, and TNM stage was established.

RESULTS

A 10-DEMRG model was established to forecast the OS of LUAD through Least Absolute Shrinkage and Selection Operator regression analysis. This prognostic signature stratified LUAD patients into low-risk and high-risk groups. The receiver operating characteristic curve and K-M analysis indicated good performance of the DEMRGs signature at predicting OS in the TCGA dataset. Univariate and multivariate Cox regression also revealed that the DEMRGs signature was an independent prognosis factor in LUAD. We noticed that the risk score was substantially related to the clinical parameters of LUAD patients, covering age and stage. Immune analysis results showed that risk score was associated with some immune cells and immune checkpoints. Nomogram also verified the clinical value of the DEMRGs signature.

CONCLUSION

In this study, we constructed a DEMRGs signature and established a prognostic nomogram that is robust and reliable to predict OS in LUAD. Overall, the findings could help with therapeutic customization and personalized therapies.

Identification of novel candidate biomarkers for acute myocardial infarction by the Olink proteomics platform

BACKGROUND

Both pathological and normal processes depend on proteins. In this study, plasma protein profiles were analyzed by a novel proximity extension assay (PEA) to identify potential pathogenic mechanisms and diagnostic biomarkers in patients diagnosed with acute myocardial infarction (AMI).

METHODS

In this study, we identified a total of 92 plasma proteins using the Olink Target 96 Cardiovascular III panel in a cohort consisting of 30 healthy controls (HC), 28 patients with unstable angina (UA) and 30 patients with AMI. Subsequently, we conducted a differential expression analysis to identify protein molecules that were specifically expressed in patients with AMI. To gain insights into the potential functional mechanisms of these differentially expressed molecules, we performed Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Following that, the utilization of least absolute shrinkage and selection operator (LASSO) regression facilitated the identification of potential protein biomarkers, enabling the differentiation between AMI and UA. A diagnostic model was subsequently developed through logistic regression, and the effectiveness of these markers was assessed using receiver operating characteristic (ROC) analysis. Ultimately, the diagnostic capabilities of these potential biomarkers were validated in an independent validation cohort consisting of 30 UA cases and 30 AMI cases.

RESULTS

In this study, a comprehensive analysis of plasma proteins identified a total of 92 proteins. Further analysis using analysis of variance revealed that 25 proteins exhibited specific expression in the AMI group compared to the HC and UA groups. Additionally, KEGG enrichment analysis indicated that these differentially expressed proteins were primarily associated with the activation of cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, and GnRH signaling pathway. AGRP, TGM2, IL6, GH1, and CA5A were identified through LASSO regression as prospective protein biomarkers for distinguishing between UA and AMI. The diagnostic model comprising these five proteins exhibited exceptional performance in both the discovery and validation datasets, surpassing AUC values of 0.9.

CONCLUSION

The findings of our study provide additional insights into the involvement of the inflammatory response and AKT cascade response in the development of AMI. Moreover, we have identified potential protein markers that could be utilized for the accurate diagnosis of AMI. These results offer a fresh perspective for clinical decision-making in the context of AMI.

Inhibition of GARS1-DT Protects Against Hypoxic Injury in H9C2 Cardiomyocytes via Sponging miR-212-5p

ABSTRACT

The present study aimed to elucidate the function of long noncoding RNA GARS1-DT in hypoxia-induced injury in ex-vivo cardiomyocytes and explore its underlying mechanism. Hypoxic injury was confirmed in H9C2 cells by the determination of cell viability, migration, invasion, and apoptosis. GARS1-DT expression was estimated in H9C2 cells after hypoxia. We then measured the effects of GARS1-DT knockdown on hypoxia-induced H9C2 cells. The interaction between GARS1-DT and miR-212-5p was also investigated. Hypoxia treatment led to cell damage in H9C2 cardiomyocytes, accompanied with the upregulation of GARS1-DT expression. Transfection of GARS1-DT small interfering RNA remarkably attenuated hypoxia-induced injury by enhancing cell viability, migration, and invasion, and reducing apoptosis. Furthermore, GARS1-DT served as an endogenous sponge for miR-212-5p, and its expression was negatively regulated by GARS1-DT. The effects of GARS1-DT knockdown on hypoxia-induced injury were significantly abrogated by miR-212-5p silence. Besides, suppression of GARS1-DT activated PI3K/AKT pathway in hypoxia-treated H9C2 cells, which were reversed by inhibition of miR-212-5p. Our findings demonstrated the novel molecular mechanism of GARS1-DT/miR-212-5p/PI3K/AKT axis on the regulation of hypoxia-induced myocardial injury in H9C2 cells, which may provide potential therapeutic targets for acute myocardial infarction treatment.