Analysis of m7G methylation modification patterns and pulmonary vascular immune microenvironment in pulmonary arterial hypertension

免疫系统 甲基化 聚类分析 下调和上调 计算生物学 生物 发病机制 基因 DNA甲基化 基因表达 免疫学 癌症研究 遗传学 计算机科学 机器学习
作者
Desheng Wang,Yanfei Mo,Dongfang Zhang,Yang Bai
出处
期刊:Frontiers in Immunology [Frontiers Media SA]
卷期号:13 被引量:3
标识
DOI:10.3389/fimmu.2022.1014509
摘要

Background M 7 G methylation modification plays an important role in cardiovascular disease development. Dysregulation of the immune microenvironment is closely related to the pathogenesis of PAH. However, it is unclear whether m 7 G methylation is involved in the progress of PAH by affecting the immune microenvironment. Methods The gene expression profile of PAH was obtained from the GEO database, and the m 7 G regulatory factors were analyzed for differences. Machine learning algorithms were used to screen characteristic genes, including the least absolute shrinkage and selection operator, random forest, and support vector machine recursive feature elimination analysis. Constructed a nomogram model, and receiver operating characteristic was used to evaluate the diagnosis of disease characteristic genes value. Next, we used an unsupervised clustering method to perform consistent clustering analysis on m 7 G differential genes. Used the ssGSEA algorithm to estimate the relationship between the m 7 G regulator in PAH and immune cell infiltration and analyze the correlation with disease-characteristic genes. Finally, the listed drugs were evaluated through the screened signature genes. Results We identified 15 kinds of m 7 G differential genes. CYFIP1, EIF4E, and IFIT5 were identified as signature genes by the machine learning algorithm. Meanwhile, two m 7 G molecular subtypes were identified by consensus clustering (cluster A/B). In addition, immune cell infiltration analysis showed that activated CD4 T cells, regulatory T cells, and type 2 T helper cells were upregulated in m 7 G cluster B, CD56 dim natural killer cells, MDSC, and monocyte were upregulated in the m 7 G cluster A. It might be helpful to select Calpain inhibitor I and Everolimus for the treatment of PAH. Conclusion Our study identified CYFIP1, EIF4E, and IFIT5 as novel diagnostic biomarkers in PAH. Furthermore, their association with immune cell infiltration may facilitate the development of immune therapy in PAH.
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