immune infiltration Archives

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Stress cardiomyopathy (SCM) is a reversible, self-limiting condition that manifests as left ventricular insufficiency. The incidence of stress cardiomyopathy has increased because of increasing mental and social stress, but the exact pathophysiological mechanisms remain unclear.

To elucidate the critical molecules in the pathogenesis of SCM and the functional changes that they mediate, data for a healthy control group and stress cardiomyopathy (SCM) group was downloaded from the Gene Expression Omnibus database, differential analysis was performed, and the results of GO and KEGG enrichment analysis was analysed to describe SCM-associated genes and functions. Lasso, random forest, SVM-RFM, and Friends analysis were used to screen hub genes; CIBERSORT and MCPcounter were used to explore the relationship between SCM and immunity; and an animal model of SCM was constructed to conduct bidirectional verification of the obtained results.

In total, 21 samples (6 healthy, 15 SCM) were used in this study. Overall, 39 DEGs (absolute fold change ≥ 1; P < 0.05), including 23 upregulated and 16 downregulated genes in SCM, were extracted. Three common hub genes (PLAT, SEMA6B, and CRP) were finally screened. It was further confirmed that functional changes in SCM were concentrated in immunity and coagulation functions.

Three key genes (PLAT, SEMA6B, and CRP) in SCM were identified by machine learning, and the major functional changes leading to SCM, and relationships of SCM with immunity, were identified.

https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2024.0011

CVIA is available on the ScienceOpen platform and at Cardiovascular Innovations and Applications. Submissions may be made using ScholarOne Manuscripts. There are no author submission or article processing fees. Cardiovascular Innovations and Applications is indexed in the EMBASE, EBSCO, ESCI, OCLC, Primo Central (Ex Libris), Sherpa Romeo, NISC (National Information Services Corporation), DOAJ, Index Copernicus, Research4Life and Ulrich’s web Databases. Follow CVIA on Twitter @CVIA_Journal; or Facebook.

Xuexin Jin, Xuanrui Ji and Hongpeng Yin et al. Identification of Potential Targets of Stress Cardiomyopathy by a Machine Learning Algorithm. CVIA. 2024. Vol. 9(1). DOI: 10.15212/CVIA.2024.0011

Announcing a new article publication for Cardiovascular Innovations and Applications journal. In this study, the authors identify cuproptosis-associated ferroptosis genes in the atherosclerosis microarray of the Gene Expression Omnibus (GEO) database and explored hub gene-mediated immune infiltration in atherosclerosis.

Immune infiltration plays a crucial role in atherosclerosis development. Ferroptosis is a mode of cell death caused by the iron-dependent accumulation of lipid peroxides. Cuproptosis is a recently discovered type of programmed cell death. No previous studies have examined the mechanism of cuproptosis-associated ferroptosis gene regulation in immune infiltration in atherosclerosis.

The qualified atherosclerosis gene microarray was researched in the GEO database, integrated with ferroptosis and cuproptosis genes, and calculated with the correlation coefficients. The authors then obtained the cuproptosis-associated ferroptosis gene matrix and screened differentially expressed genes. Subsequently, they performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses and protein–protein interaction network analysis of differentially expressed genes. The authors also screened hub genes according to the Matthews correlation coefficient (MCC) algorithm. The authors conducted enrichment analysis of hub genes to explore their functions and predict related microRNAs (P<0.05). The authors also used the single-sample gene set enrichment analysis (ssGSEA) algorithm to analyze the relationships between hub genes and immune infiltration, and used immune-associated hub genes to construct a risk model. Finally, the authors used the drug prediction results and molecular docking technology to explore potential therapeutic drugs targeting the hub genes.

Seventy-eight cuproptosis-associated ferroptosis genes were found to be involved in the cellular response to oxidative and chemical stress, and to be enriched in multiple pathways, including ferroptosis, glutathione metabolism, and atherosclerosis. Ten hub genes were identified with the MCC algorithm; according to the ssGSEA algorithm, these genes were closely associated with immune infiltration, thus indicating that cuproptosis-associated ferroptosis genes may participate in atherosclerosis by mediating immune infiltration. The receiver operating characteristic curve indicated that the model had a good ability to predict atherosclerosis risk. The results of drug prediction (adjusted P<0.001) and molecular docking showed that glutathione may be a potential therapeutic drug that targets the hub genes.

The conclusion was that cuproptosis-associated ferroptosis genes are associated with immune infiltration in atherosclerosis.

https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2023.0003

Article reference: Boyu Zhang, Shuhan Li and Hanbing Liu et al. Immune Infiltration in Atherosclerosis is Mediated by Cuproptosis-Associated Ferroptosis Genes. CVIA. 2023. Vol. 7(1). DOI: 10.15212/CVIA.2023.0003

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Tag: immune infiltration

Identification of Potential Targets of Stress Cardiomyopathy by a Machine Learning Algorithm

Immune Infiltration in Atherosclerosis is Mediated by Cuproptosis-Associated Ferroptosis Genes