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Current Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

Research Article

Identification of a Novel Diagnosis Model based on 5 Hub Genes for Chronic Thromboembolic Pulmonary Hypertension

Author(s): Feng Zhang, Xiaoming Huang, Junqi Lin, Ruilin Yu, Shaoming Lin, Guanle Shen and Wenbiao Chen*

Volume 31, Issue 13, 2024

Published on: 18 July, 2023

Page: [1754 - 1768] Pages: 15

DOI: 10.2174/0929867330666230605125512

Price: $65

Abstract

Background: As a type of precapillary pulmonary hypertension, chronic thromboembolic pulmonary hypertension (CTEPH) results from incomplete pulmonary embolism resolution. In this study, we aimed to determine biomarker genes for predicting the prognosis of CTEPH.

Methods: RNAseq of CTEPH was collected from the public database, namely Gene Expression Omnibus (GEO), including GSE84538 and GSE188938, which combined a dataset (GSE). Differentially expressed genes (DEG) or miRNA (DEM) were identified by limma package. Functional enrichment analysis was performed by the WebGestaltR package. Then, the miRNA-mRNA network was presented by Cytoscape, and the protein-protein interactions (PPI) network was constructed by STRING. MCODE was mined by mature MCODE algorithm. Immune infiltration analysis was conducted by ESTIMATER and ssGSEA analysis. A diagnosis model was established by SVM algorithm.

Results: In the GSE dataset, CTEPH samples had a lower GOBP_RESPONSE_- TO_OXIDATIVE_STRESS score. A total of 628 DEGs and 31 DEMs were identified between CTEPH and normal samples. Afterward, DEGs were intersected with genes, which correlated with the GOBP_RESPONSE_TO_OXIDATIVE_STRESS score. A 26 DEMs-152 DEGs network was constructed, and a PPI network was established based on 152 DEGs to find 149 target genes. From the above 149 target genes, 3 modules were extracted to obtain 15 core targets. Finally, 5 hub genes were obtained by the intersection of 15 core targets and genes in MCODE2. A total of 5 hub genes were positively correlated with most immune cell scores as well as GOBP_RESPONSE_TO_OXIDATIVE_ STRESS. It was found that a diagnosis model based on 5 hub genes had a well diagnostic ability for CTEPH.

Conclusion: We identified 5 hub genes associated with oxidative stress. It can be concluded that they may be beneficial in diagnosing CTEPH.

[1]
Papamatheakis, D.G.; Poch, D.S.; Fernandes, T.M.; Kerr, K.M.; Kim, N.H.; Fedullo, P.F. Chronic thromboembolic pulmonary hypertension: JACC focus seminar. J. Am. Coll. Cardiol., 2020, 76(18), 2155-2169.
[http://dx.doi.org/10.1016/j.jacc.2020.08.074] [PMID: 33121723]
[2]
Yang, S.; Yang, Y.; Zhai, Z.; Kuang, T.; Gong, J.; Zhang, S.; Zhu, J.; Liang, L.; Shen, Y.H.; Wang, C. Incidence and risk factors of chronic thromboembolic pulmonary hypertension in patients after acute pulmonary embolism. J. Thorac. Dis., 2015, 7(11), 1927-1938.
[PMID: 26716031]
[3]
Guérin, L.; Couturaud, F.; Parent, F.; Revel, M.P.; Gillaizeau, F.; Planquette, B.; Pontal, D.; Guégan, M.; Simonneau, G.; Meyer, G.; Sanchez, O. Prevalence of chronic thromboembolic pulmonary hypertension after acute pulmonary embolism. Thromb. Haemost., 2014, 112(9), 598-605.
[http://dx.doi.org/10.1160/TH13-07-0538] [PMID: 24898545]
[4]
Hoeper, M.M.; Madani, M.M.; Nakanishi, N.; Meyer, B.; Cebotari, S.; Rubin, L.J. Chronic thromboembolic pulmonary hypertension. Lancet Respir. Med., 2014, 2(7), 573-582.
[http://dx.doi.org/10.1016/S2213-2600(14)70089-X] [PMID: 24898750]
[5]
Otero, R.; Oribe, M.; Ballaz, A.; Jimenez, D.; Uresandi, F.; Nauffal, D.; Conget, F.; Rodriguez, C.; Elias, T.; Jara, L.; Cayuela, A.; Blanco, I.; Barberá, J. Echocardiographic assessment of pulmonary arterial pressure in the follow-up of patients with pulmonary embolism. Thromb. Res., 2011, 127(4), 303-308.
[http://dx.doi.org/10.1016/j.thromres.2010.12.010] [PMID: 21247617]
[6]
Lang, I.M.; Madani, M. Update on chronic thromboembolic pulmonary hypertension. Circulation, 2014, 130(6), 508-518.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.114.009309] [PMID: 25092279]
[7]
Guth, S.; Mayer, E.; Prüfer, D.; Wiedenroth, C.B. Pulmonary endarterectomy: Technique and pitfalls. Ann. Cardiothorac. Surg., 2022, 11(2), 180-188.
[http://dx.doi.org/10.21037/acs-2021-pte-185] [PMID: 35433367]
[8]
Hashemizadeh, S.; Hosseindoost, S.; Omidi, A.; Aminianfar, H.; Ebrahimi-Barough, S.; Ai, J.; Arjmand, B.; Hadjighassem, M. Novel therapeutic approach to slow down the inflammatory cascade in acute/subacute spinal cord injury: Early immune therapy with lipopolysaccharide enhanced neuroprotective effect of combinational therapy of granulocyte colony-stimulating factor and bone-marrow mesenchymal stem cell in spinal cord injury. Front. Cell. Neurosci., 2022, 16, 993019.
[http://dx.doi.org/10.3389/fncel.2022.993019] [PMID: 36505513]
[9]
Deng, Z.; Liu, S. Inflammation-responsive delivery systems for the treatment of chronic inflammatory diseases. Drug Deliv. Transl. Res., 2021, 11(4), 1475-1497.
[http://dx.doi.org/10.1007/s13346-021-00977-8] [PMID: 33860447]
[10]
Rabinovitch, M.; Guignabert, C.; Humbert, M.; Nicolls, M.R. Inflammation and immunity in the pathogenesis of pulmonary arterial hypertension. Circ. Res., 2014, 115(1), 165-175.
[http://dx.doi.org/10.1161/CIRCRESAHA.113.301141] [PMID: 24951765]
[11]
Quarck, R.; Wynants, M.; Verbeken, E.; Meyns, B.; Delcroix, M. Contribution of inflammation and impaired angiogenesis to the pathobiology of chronic thromboembolic pulmonary hypertension. Eur. Respir. J., 2015, 46(2), 431-443.
[http://dx.doi.org/10.1183/09031936.00009914] [PMID: 26113681]
[12]
Hardy, P.; Dumont, I.; Bhattacharya, M.; Hou, X.; Lachapelle, P.; Varma, D.R.; Chemtob, S. Oxidants, nitric oxide and prostanoids in the developing ocular vasculature: A basis for ischemic retinopathy. Cardiovasc. Res., 2000, 47(3), 489-509.
[http://dx.doi.org/10.1016/S0008-6363(00)00084-5] [PMID: 10963722]
[13]
Majed, B.H.; Khalil, R.A. Molecular mechanisms regulating the vascular prostacyclin pathways and their adaptation during pregnancy and in the newborn. Pharmacol. Rev., 2012, 64(3), 540-582.
[http://dx.doi.org/10.1124/pr.111.004770] [PMID: 22679221]
[14]
Sartori, C.; Allemann, Y.; Scherrer, U. Pathogenesis of pulmonary edema: Learning from high-altitude pulmonary edema. Respir. Physiol. Neurobiol., 2007, 159(3), 338-349.
[http://dx.doi.org/10.1016/j.resp.2007.04.006] [PMID: 17532272]
[15]
Panieri, E.; Santoro, M.M. ROS signaling and redox biology in endothelial cells. Cell. Mol. Life Sci., 2015, 72(17), 3281-3303.
[http://dx.doi.org/10.1007/s00018-015-1928-9] [PMID: 25972278]
[16]
Rahman, I.; Adcock, I.M. Oxidative stress and redox regulation of lung inflammation in COPD. Eur. Respir. J., 2006, 28(1), 219-242.
[http://dx.doi.org/10.1183/09031936.06.00053805] [PMID: 16816350]
[17]
Boukhenouna, S.; Wilson, M.A.; Bahmed, K.; Kosmider, B. Reactive oxygen species in chronic obstructive pulmonary disease. Oxid. Med. Cell. Longev., 2018, 2018, 1-9.
[http://dx.doi.org/10.1155/2018/5730395] [PMID: 29599897]
[18]
Liu, J.; Sun, Y.; Zhu, B.; Lin, Y.; Lin, K.; Sun, Y.; Yao, Z.; Yuan, L. Identification of a potentially novel LncRNA-miRNA-mRNA competing endogenous RNA network in pulmonary arterial hypertension via integrated bioinformatic analysis. Life Sci., 2021, 277, 119455.
[http://dx.doi.org/10.1016/j.lfs.2021.119455] [PMID: 33831428]
[19]
Wang, F.; Sun, C.; Lv, X.; Sun, M.; Si, C.; Zhen, Y.; Guo, J.; Sun, W.; Ye, Z.; Wen, J.; Liu, P. Identification of a novel gene correlated with vascular smooth muscle cells proliferation and migration in chronic thromboembolic pulmonary hypertension. Front. Physiol., 2021, 12, 744219.
[http://dx.doi.org/10.3389/fphys.2021.744219] [PMID: 34858201]
[20]
Jin, X.; Liu, L.; Wu, J.; Jin, X.; Yu, G.; Jia, L.; Wang, F.; Shi, M.; Lu, H.; Liu, J.; Liu, D.; Yang, J.; Li, H.; Ni, Y.; Luo, Q.; Jia, W.; Wang, W.; Chen, W.L. A multi-omics study delineates new molecular features and therapeutic targets for esophageal squamous cell carcinoma. Clin. Transl. Med., 2021, 11(9), e538.
[http://dx.doi.org/10.1002/ctm2.538] [PMID: 34586744]
[21]
Hänzelmann, S.; Castelo, R.; Guinney, J. GSVA: Gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics, 2013, 14(1), 7.
[http://dx.doi.org/10.1186/1471-2105-14-7] [PMID: 23323831]
[22]
Ritchie, M.E.; Phipson, B.; Wu, D.; Hu, Y.; Law, C.W.; Shi, W.; Smyth, G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res., 2015, 43(7), e47.
[http://dx.doi.org/10.1093/nar/gkv007] [PMID: 25605792]
[23]
Subramanian, A.; Tamayo, P.; Mootha, V.K.; Mukherjee, S.; Ebert, B.L.; Gillette, M.A.; Paulovich, A.; Pomeroy, S.L.; Golub, T.R.; Lander, E.S.; Mesirov, J.P. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA, 2005, 102(43), 15545-15550.
[http://dx.doi.org/10.1073/pnas.0506580102] [PMID: 16199517]
[24]
Yu, G.; Wang, L.G.; Han, Y.; He, Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS, 2012, 16(5), 284-287.
[http://dx.doi.org/10.1089/omi.2011.0118] [PMID: 22455463]
[25]
Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res., 2003, 13(11), 2498-2504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]
[26]
Szklarczyk, D.; Gable, A.L.; Nastou, K.C.; Lyon, D.; Kirsch, R.; Pyysalo, S.; Doncheva, N.T.; Legeay, M.; Fang, T.; Bork, P.; Jensen, L.J.; von Mering, C. The STRING database in 2021: Customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res., 2021, 49(D1), D605-D612.
[http://dx.doi.org/10.1093/nar/gkaa1074] [PMID: 33237311]
[27]
Guo, A.; Wang, W.; Shi, H.; Wang, J.; Liu, T. Identification of hub genes and pathways in a rat model of renal ischemia-reperfusion injury using bioinformatics analysis of the Gene Expression Omnibus (GEO) dataset and integration of gene expression profiles. Med. Sci. Monit., 2019, 25, 8403-8411.
[http://dx.doi.org/10.12659/MSM.920364] [PMID: 31699960]
[28]
Shen, W.; Song, Z.; Zhong, X.; Huang, M.; Shen, D.; Gao, P.; Qian, X.; Wang, M.; He, X.; Wang, T.; Li, S.; Song, X. Sangerbox: A comprehensive, interaction-friendly clinical bioinformatics analysis platform. iMeta, 2022, 1(3), e36.
[http://dx.doi.org/10.1002/imt2.36]
[29]
Peterson, S.M.; Thompson, J.A.; Ufkin, M.L.; Sathyanarayana, P.; Liaw, L.; Congdon, C.B. Common features of microRNA target prediction tools. Front. Genet., 2014, 5, 23.
[http://dx.doi.org/10.3389/fgene.2014.00023] [PMID: 24600468]
[30]
Miao, R.; Gong, J.; Zhang, C.; Wang, Y.; Guo, X.; Li, J.; Yang, S.; Kuang, T.; Zhong, J.; Feng, H. Hsa_circ_0046159 is involved in the development of chronic thromboembolic pulmonary hypertension. J. Thromb. Thrombolysis, 2020, 49(3), 386-394.
[http://dx.doi.org/10.1007/s11239-019-01998-4] [PMID: 31776848]
[31]
Xu, W.; Deng, M.; Meng, X.; Sun, X.; Tao, X.; Wang, D.; Zhang, S.; Zhen, Y.; Liu, X.; Liu, M. The alterations in molecular markers and signaling pathways in chronic thromboembolic pulmonary hypertension, a study with transcriptome sequencing and bioinformatic analysis. Front. Cardiovasc. Med., 2022, 9, 961305.
[http://dx.doi.org/10.3389/fcvm.2022.961305] [PMID: 35958401]
[32]
Van Gorp, H.; Delputte, P.L.; Nauwynck, H.J. Scavenger receptor CD163, a Jack-of-all-trades and potential target for cell-directed therapy. Mol. Immunol., 2010, 47(7-8), 1650-1660.
[http://dx.doi.org/10.1016/j.molimm.2010.02.008] [PMID: 20299103]
[33]
Jasiewicz, M.; Kowal, K.; Kowal-Bielecka, O.; Knapp, M.; Skiepko, R.; Bodzenta-Lukaszyk, A.; Sobkowicz, B.; Musial, W.J.; Kaminski, K.A. Serum levels of CD163 and TWEAK in patients with pulmonary arterial hypertension. Cytokine, 2014, 66(1), 40-45.
[http://dx.doi.org/10.1016/j.cyto.2013.12.013] [PMID: 24548423]
[34]
Daverey, A.; Agrawal, S.K. Curcumin alleviates oxidative stress and mitochondrial dysfunction in astrocytes. Neuroscience, 2016, 333, 92-103.
[http://dx.doi.org/10.1016/j.neuroscience.2016.07.012] [PMID: 27423629]
[35]
Vaillancourt, M.; Chia, P.; Medzikovic, L.; Cao, N.; Ruffenach, G.; Younessi, D.; Umar, S. Experimental pulmonary hypertension is associated with neuroinflammation in the spinal cord. Front. Physiol., 2019, 10, 1186.
[http://dx.doi.org/10.3389/fphys.2019.01186] [PMID: 31616310]
[36]
Nies, M.K.; Yang, J.; Griffiths, M.; Damico, R.; Zhu, J.; Vaydia, D.; Fu, Z.; Brandal, S.; Austin, E.D.; Ivy, D.D.; Hassoun, P.M.; Van Eyk, J.E.; Everett, A.D. Proteomics discovery of pulmonary hypertension biomarkers: Insulin- like growth factor binding proteins are associated with disease severity. Pulm. Circ., 2022, 12(2), e12039.
[http://dx.doi.org/10.1002/pul2.12039] [PMID: 35514776]
[37]
Boxhammer, E.; Paar, V.; Jirak, P.; Köller, C.; Demirel, O.; Eder, S.; Reiter, C.; Kammler, J.; Kellermair, J.; Hammerer, M.; Blessberger, H.; Steinwender, C.; Hoppe, U.C.; Lichtenauer, M. Main pulmonary artery diameter in combination with cardiovascular biomarkers. New possibilities to identify pulmonary hypertension in patients with severe aortic valve stenosis? Minerva Med., 2022.
[http://dx.doi.org/10.23736/S0026-4806.22.08167-8] [PMID: 35822856]

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