We are analyzing https://link.springer.com/article/10.1186/s12890-023-02326-6.

Title:
Identification of biomarkers related to copper metabolism in patients with pulmonary arterial hypertension | BMC Pulmonary Medicine
Description:
Background The pathogenesis of pulmonary arterial hypertension (PAH) and associated biomarkers remain to be studied. Copper metabolism is an emerging metabolic research direction in many diseases, but its role in PAH is still unclear. Methods PAH-related datasets were downloaded from the Gene Expression Omnibus database, and 2067 copper metabolism-related genes (CMGs) were obtained from the GeneCards database. Differential expression analysis and the Venn algorithm were used to acquire the differentially expressed CMGs (DE-CMGs). DE-CMGs were then used for the coexpression network construction to screen candidate key genes associated with PAH. Furthermore, the predictive performance of the model was verified by receiver operating characteristic (ROC) analysis, and genes with area under the curve (AUC) values greater than 0.8 were selected as diagnostic genes. Then support vector machine, least absolute shrinkage and selection operator regression, and Venn diagrams were applied to detect biomarkers. Moreover, gene set enrichment analysis was performed to explore the function of the biomarkers, and immune-related analyses were utilized to study the infiltration of immune cells. The drug-gene interaction database was used to predict potential therapeutic drugs for PAH using the biomarkers. Biomarkers expression in clinical samples was verified by real-time quantitative PCR. Results Four biomarkers (DDIT3, NFKBIA, OSM, and PTGER4) were screened. The ROC analysis showed that the 4 biomarkers performed well (AUCs > 0.7). The high expression groups for the 4 biomarkers were enriched in protein activity-related pathways including protein export, spliceosome and proteasome. Furthermore, 8 immune cell types were significantly different between the two groups, including naive B cells, memory B cells, and resting memory CD4 T cells. Afterward, a gene-drug network was constructed. This network illustrated that STREPTOZOCIN, IBUPROFEN, and CELECOXIB were shared by the PTGER4 and DDIT3. Finally, the results of RT-qPCR in clinical samples further confirmed the results of the public database for the expression of NFKBIA and OSM. Conclusion In conclusion, four biomarkers (DDIT3, NFKBIA, OSM, and PTGER4) with considerable diagnostic values were identified, and a gene-drug network was further constructed. The results of this study may have significant implications for the development of new diagnostic biomarkers and actionable targets to expand treatment options for PAH patients.
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Keywords {🔍}

pah, pulmonary, article, google, scholar, biomarkers, hypertension, copper, genes, cells, expression, cas, samples, cell, fig, analysis, osm, arterial, ddit, immune, ptger, nfkbia, control, decmgs, study, database, results, patients, metabolism, role, diagnostic, gene, data, set, gse, network, drugs, identification, significantly, memory, development, based, vascular, full, metabolismrelated, model, potential, pathways, wgcna, size,

Topics {✒️}

hypoxia-induced pulmonary hypertension real-time quantitative pcr stat1/stat3-dependent pathways massive b-cell infiltration article download pdf copper metabolism-related genes pulmonary arterial pressure ≥ 20 mmhg cardiac ischaemia/reperfusion injury de-cmg expression matrices disease-related kegg pathways copper metabolism-related biomarkers drug-gene interaction database epithelial-mesenchymal transition tenfold cross-validation method bioinformatics analysis methods differentially expressed cmgs promote vascular remodeling promote pulmonary hypertension full access erj open res hypoxia-induced ph [50] anti-tumour agent [27 steroidal anti-inflammatory drugs pulmonary arterial hypertension identify de-cmg modules mct-induced ph [26] de-cmg modules significantly immune-related analyses prevents mct-ph pulmonary artery pressure copper-utilizing proteins enhanced ep4 expression privacy choices/manage cookies il-17 signaling pathway predicting pulmonary hypertension pulmonary artery aneurysm persistent pulmonary hypertension primary pulmonary hypertension functional enrichment analysis vascular pulmonary disease gene-drug network limited sample size receiver operating characteristic annu rev physiol intravenous copper sulfate specific genes related hub genes based fundamental research funds open-source package endothelial cell proliferation

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Increased serum copper in primary pulmonary hypertension: a possible pathogenic link?

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         description:The pathogenesis of pulmonary arterial hypertension (PAH) and associated biomarkers remain to be studied. Copper metabolism is an emerging metabolic research direction in many diseases, but its role in PAH is still unclear. PAH-related datasets were downloaded from the Gene Expression Omnibus database, and 2067 copper metabolism-related genes (CMGs) were obtained from the GeneCards database. Differential expression analysis and the Venn algorithm were used to acquire the differentially expressed CMGs (DE-CMGs). DE-CMGs were then used for the coexpression network construction to screen candidate key genes associated with PAH. Furthermore, the predictive performance of the model was verified by receiver operating characteristic (ROC) analysis, and genes with area under the curve (AUC) values greater than 0.8 were selected as diagnostic genes. Then support vector machine, least absolute shrinkage and selection operator regression, and Venn diagrams were applied to detect biomarkers. Moreover, gene set enrichment analysis was performed to explore the function of the biomarkers, and immune-related analyses were utilized to study the infiltration of immune cells. The drug-gene interaction database was used to predict potential therapeutic drugs for PAH using the biomarkers. Biomarkers expression in clinical samples was verified by real-time quantitative PCR. Four biomarkers (DDIT3, NFKBIA, OSM, and PTGER4) were screened. The ROC analysis showed that the 4 biomarkers performed well (AUCs > 0.7). The high expression groups for the 4 biomarkers were enriched in protein activity-related pathways including protein export, spliceosome and proteasome. Furthermore, 8 immune cell types were significantly different between the two groups, including naive B cells, memory B cells, and resting memory CD4 T cells. Afterward, a gene-drug network was constructed. This network illustrated that STREPTOZOCIN, IBUPROFEN, and CELECOXIB were shared by the PTGER4 and DDIT3. Finally, the results of RT-qPCR in clinical samples further confirmed the results of the public database for the expression of NFKBIA and OSM. In conclusion, four biomarkers (DDIT3, NFKBIA, OSM, and PTGER4) with considerable diagnostic values were identified, and a gene-drug network was further constructed. The results of this study may have significant implications for the development of new diagnostic biomarkers and actionable targets to expand treatment options for PAH patients.
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      name:Department of Rheumatism and Immunology, The First Affiliated Hospital Xi’an Jiaotong University, Xi’an, China

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