Background: Chronic Thromboembolic Pulmonary Hypertension (CTEPH) is a form of pulmonary hypertension with a high mortality rate. A new type of iron-mediated cell death is Ferroptosis, which is characterized by the accumulation of lethal iron ions and lipid peroxidation leading to mitochondrial atrophy and increased mitochondrial membrane density. Now, there is a lack of Ferroptosis-related biomarkers (FRBs) associated with pathogenic process of CTEPH.
Methods: The differentially expressed genes (DEGs) of CTEPH were obtained by GEO2R. Genes related to Ferroptosis were obtained from FerrDb database. The intersection of Ferroptosis and DEGs results in FRBs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed in Database for Annotation, Visualization and Integrated Discovery (DAVID) database. The optimal potential biomarkers for CTEPH were analyzed by least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) machine learning. The four hub genes were verified from the Gene Expression Omnibus (GEO) dataset GSE188938. Immune infiltration was analyzed by CIBERSORT. SPSS software was used to analyze the Spearman rank correlation between FRBs identified and infiltration-related immune cells, and p < 0.05 was considered as statistically significant.
Results: In this study, potential genetic biomarkers associated with Ferroptosis in CTEPH were investigated and explored their role in immune infiltration. In total, we identified 17 differentially expressed Ferroptosis-associated genes by GEOquery package. The key FRBs including ARRDC3, HMOX1, BRD4, and YWHAE were screened using Lasso and SVM-RFE machine learning methods.Through gene set GSE188938 verification, only upregulation of gene ARRDC3 showed statistical difference. In addition, immune infiltration analysis using the CIBERSORT algorithm revealed the infiltration of Eosinophils and Neutrophils in CTEPH samples was less than that in the control group. And correlation analysis revealed that ARRDC3 was positively correlated with T cells follicular helper (r = 0.554, p = 0.017) and negatively correlated with Neutrophils (r = -0.47, p = 0.049).
Conclusions: In conclusion, ARRDC3 upregulation with different immune cell infiltration were involved in the development of CTEPH. ARRDC3 might a potential Ferroptosis-related biomarker for CTEPH treatment. This study provided a new insight into pathogenesis CTEPH.
Keywords: Biomarker; CTEPH; Ferroptosis; Immune cell infiltration; Machine learning.
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