Identification of MACC1 as a potential biomarker for pulmonary arterial hypertension based on bioinformatics and machine learning

被引:0
作者
Zhou X. [1 ]
Liang B. [1 ,3 ]
Lin W. [2 ,3 ]
Zha L. [1 ,3 ]
机构
[1] Department of Cardiology, Xiangya Hospital, Central South University, Hunan, Changsha
[2] Department of Nephrology, Xiangya Hospital, Central South University, Hunan, Changsha
[3] National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Hunan, Changsha
基金
美国国家科学基金会; 中国国家自然科学基金;
关键词
Bioinformatics; Immune infiltration; MACC1; Machine learning; Pulmonary arterial hypertension;
D O I
10.1016/j.compbiomed.2024.108372
中图分类号
学科分类号
摘要
Background: Pulmonary arterial hypertension (PAH) is a life-threatening disease characterized by abnormal early activation of pulmonary arterial smooth muscle cells (PASMCs), yet the underlying mechanisms remain to be elucidated. Methods: Normal and PAH gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database and analyzed using gene set enrichment analysis (GSEA) to uncover the underlying mechanisms. Weighted gene co-expression network analysis (WGCNA) and machine learning methods were deployed to further filter hub genes. A number of immune infiltration analysis methods were applied to explore the immune landscape of PAH. Enzyme-linked immunosorbent assay (ELISA) was employed to compare MACC1 levels between PAH and normal subjects. The important role of MACC1 in the progression of PAH was verified through Western blot and real-time qPCR, among others. Results: 39 up-regulated and 7 down-regulated genes were identified by ‘limma’ and ‘RRA’ packages. WGCNA and machine learning further narrowed down the list to 4 hub genes, with MACC1 showing strong diagnostic capacity. In vivo and in vitro experiments revealed that MACC1 was highsly associated with malignant features of PASMCs in PAH. Conclusions: These findings suggest that targeting MACC1 may offer a promising therapeutic strategy for treating PAH, and further clinical studies are warranted to evaluate its efficacy. © 2024 Elsevier Ltd
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共 63 条
[1]  
Mocumbi A., Humbert M., Saxena A., Jing Z.C., Sliwa K., Thienemann F., Archer S.L., Stewart S., Pulmonary hypertension, Nat. Rev. Dis. Prim., 10, 1, (2024)
[2]  
Rabinovitch M., Molecular pathogenesis of pulmonary arterial hypertension, J. Clin. Invest., 122, 12, pp. 4306-4313, (2012)
[3]  
Rabinovitch M., Guignabert C., Humbert M., Nicolls M.R., Inflammation and immunity in the pathogenesis of pulmonary arterial hypertension, Circ. Res., 115, 1, pp. 165-175, (2014)
[4]  
Savai R., Al-Tamari H.M., Sedding D., Kojonazarov B., Muecke C., Teske R., Capecchi M.R., Weissmann N., Grimminger F., Seeger W., Schermuly R.T., Pullamsetti S.S., Pro-proliferative and inflammatory signaling converge on FoxO1 transcription factor in pulmonary hypertension, Nat. Med., 20, 11, pp. 1289-1300, (2014)
[5]  
Humbert M., Sitbon O., Simonneau G., Treatment of pulmonary arterial hypertension, N. Engl. J. Med., 351, 14, pp. 1425-1436, (2004)
[6]  
Zeng W.J., Xiong C.M., Zhao L., Shan G.L., Liu Z.H., Xue F., Gu Q., Ni X.H., Zhao Z.H., Cheng X.S., Wilkins M.R., He J.G., Atorvastatin in pulmonary arterial hypertension (APATH) study, Eur. Respir. J., 40, 1, pp. 67-74, (2012)
[7]  
Stearman R.S., Bui Q.M., Speyer G., Handen A., Cornelius A.R., Graham B.B., Kim S., Mickler E.A., Tuder R.M., Chan S.Y., Geraci M.W., Systems analysis of the human pulmonary arterial hypertension lung transcriptome, Am. J. Respir. Cell Mol. Biol., 60, 6, pp. 637-649, (2019)
[8]  
Li D., Shao N.Y., Moonen J.R., Zhao Z., Shi M., Otsuki S., Wang L., Nguyen T., Yan E., Marciano D.P., Contrepois K., Li C.G., Wu J.C., Snyder M.P., Rabinovitch M., ALDH1A3 coordinates metabolism with gene regulation in pulmonary arterial hypertension, Circulation, 143, 21, pp. 2074-2090, (2021)
[9]  
Kikuchi N., Satoh K., Kurosawa R., Yaoita N., Elias-Al-Mamun M., Siddique M.A.H., Omura J., Satoh T., Nogi M., Sunamura S., Miyata S., Saito Y., Hoshikawa Y., Okada Y., Shimokawa H., Selenoprotein P promotes the development of pulmonary arterial hypertension: possible novel therapeutic target, Circulation, 138, 6, pp. 600-623, (2018)
[10]  
Kolde R., Laur S., Adler P., Vilo J., Robust rank aggregation for gene list integration and meta-analysis, Bioinformatics, 28, 4, pp. 573-580, (2012)