Verification of hub genes in the expression profile of aortic dissection

Autoři: Weitie Wang aff001;  Qing Liu aff002;  Yong Wang aff001;  Hulin Piao aff001;  Bo Li aff001;  Zhicheng Zhu aff001;  Dan Li aff001;  Tiance Wang aff001;  Rihao Xu aff001;  Kexiang Liu aff001
Působiště autorů: Department of Cardiovascular Surgery, Second Hospital of Jilin University, Changchun, Jilin, China aff001;  Graduate School of Medicine and Faculty of Medicine, University of Tokyo, Tokyo, Japan aff002
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0224922



To assess the mRNA expression profile and explore the hub mRNAs and potential molecular mechanisms in the pathogenesis of human thoracic aortic dissection (TAD).


mRNA microarray expression signatures of TAD tissues (n = 6) and non-TAD tissues (NT; n = 6) were analyzed by an Arraystar human mRNA microarray. Real-time PCR (qRT-PCR) was used to validate the results of the mRNA microarray. Bioinformatic tools, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, were utilized. Protein-protein interaction (PPI) networks were constructed based on data from the STRING database. Molecular Complex Detection (MCODE) and cytoHubba analyses were used to predict the strongest hub gene and pathway.


The top 10 hub genes were CDK1, CDC20, CCNB2, CCNB1, MAD2L1, AURKA, C3AR1, NCAPG, CXCL12 and ASPM, which were identified from the PPI network. Module analysis revealed that TAD was associated with the cell cycle, oocyte meiosis, the p53 signaling pathway, and progesterone-mediated oocyte maturation. The qRT-PCR results showed that the expression of all hub genes was significantly increased in TAD samples (p < 0.05). Immunostaining of Ki-67 and CDK1 showed a high proliferation state and high expression in TAD, respectively.


CDK1 could be used as a potential diagnostic biomarker and therapeutic target of TAD.

Klíčová slova:

Gene expression – Cell cycle and cell division – Cellular structures and organelles – Immune response – Binding analysis – Cytoskeletal proteins – Microarrays – Muscle contraction


1. Lio A, Bovio E, Nicolò F, Saitto G, Scafuri A, Bassano C, et al. Influence of Body Mass Index on Outcomes of Patients Undergoing Surgery for Acute Aortic Dissection: A Propensity-Matched Analysis.Tex Heart Inst J. 46, 7–13 (2019).

2. Nienaber CA, Clough RE. Management of acute aortic dissection. Lancet. 385, 800–811 (2015). doi: 10.1016/S0140-6736(14)61005-9 25662791

3. Zhao Z, Wang Y, Li S, Liu S, Liu Y, Yu Y, et al. HSP90 inhibitor 17-DMAG effectively alleviated the progress of thoracic aortic dissection by suppressing smooth muscle cell phenotypic switch. Am J Transl Res. 11, 509–518 (2019). 30788006

4. Cheng J, Zhou X, Jiang X, Sun T. Deletion of ACTA2 in mice promotes angiotensin II induced pathogenesis of thoracic aorticaneurysms and dissections. J Thorac Dis. 8, 4733–4740 (2018).

5. An Z, Qiao F, Lu Q, Ma Y, Liu Y, Lu F, et al. Interleukin-6 downregulated vascular smooth muscle cell contractile proteins via ATG4B-mediated autophagy in thoracic aortic dissection. Heart Vessels. 12, 1523–1535 (2017).

6. Herman AB, Autieri MV. Inflammation-regulated mRNA stability and the progression of vascular inflammatory diseases. Clin Sci (Lond). 131, 2687–2699 (2017).

7. McCoy TH Jr, Fragomen AT, Hart KL, Pellegrini AM, Raskin KA, Perlis RH. Genomewide Association Study of Fracture Nonunion Using Electronic Health Records. JBMR Plus. 20, 23–28 (2018).

8. Kimura N, Futamura K, Arakawa M, Okada N, Emrich F, Okamura H, et al. Gene expression profiling of acute type A aortic dissection combined with in vitro assessment. Eur J Cardiothorac Surg. 52, 810–817 (2017). doi: 10.1093/ejcts/ezx095 28402522

9. Li Y, Yang N, Zhou X, Bian X, Qiu G, Zhang M et al. LncRNA and mRNA interaction study based on transcriptome profiles reveals potential core genesin the pathogenesis of human thoracic aortic dissection. Mol Med Rep. 18, 3167–3176 (2018). doi: 10.3892/mmr.2018.9308 30066903

10. Ohno-Urabe S, Aoki H, Nishihara M, Furusho A, Hirakata S, Nishida N, et al. Role of Macrophage Socs3 in the Pathogenesis of Aortic Dissection. J Am Heart Assoc. 17, e007389 (2018).

11. Gawinecka J, Schönrath F, von Eckardstein A. Acute aortic dissection: pathogenesis, risk factors and diagnosis. Swiss Med Wkly. 147, 14489 (2017).

12. Berger T, Weiss G, Voetsch A, Arnold Z, Kreibich M, Rylski B, et al. Multicentre experience with two frozen elephant trunk prostheses in the treatment of acute aortic dissection. Eur J Cardiothorac Surg. 7, 037 (2019).

13. Wang F, Li B, Lan L, Li L. C596G mutation in FBN1 causes Marfan syndrome with exotropia in a Chinese family. Circ. Res. 21, 194–200 (2015).

14. Reinstein E, DeLozier CD, Simon Z, Bannykh S, Rimoin DL, Curry CJ. Ehlers‑Danlos syndrome type VIII is clinically heterogeneous disorder associated primarily with periodontal disease, and variable connective tissue features. Eur J Hum Genet. 21, 233‑236 (2013). doi: 10.1038/ejhg.2012.132 22739343

15. Mallat Z, Tedgui A, Henrion D. Role of Microvascular Tone and Extracellular Matrix Contraction in the Regulation of Interstitial Fluid: Implications for Aortic Dissection. Arterioscler Thromb Vasc Biol. 36, 1742–1746 (2016). doi: 10.1161/ATVBAHA.116.307909 27444198

16. Li Z, Zhou C, Tan L, Chen P, Cao Y, Li C, et al. Variants of genes encoding collagens and matrix metalloproteinase system increased the risk of aortic dissection.Sci China Life Sci. 60, 57–65 (2017). doi: 10.1007/s11427-016-0333-3 27975164

17. He R. Characterization of the infl ammatory and apoptotic cells in the aortas of patients with ascending thoracic aortic aneurysms and dissections. J Thorac Cardiovasc Surg. 131, 671–678 (2006). doi: 10.1016/j.jtcvs.2005.09.018 16515922

18. Luo F, Zhou XL, LI JJ, Hui RT. Inflammatory response is associated with aortic dissection. Ageing Res Rev. 8, 31–35 (2009). doi: 10.1016/j.arr.2008.08.001 18789403

19. Weis-Müller BT, Modlich O, Drobinskaya I, Unay D, Huber R, Bojar H, et al. Gene expression in acute Stanford type A dissection: a comparative microarray study. J Transl Med. 4, 29–44 (2006). doi: 10.1186/1479-5876-4-29 16824202

20. Schonbeck U, Sukhova GK, Gerdes N, Libby P. Th2 predominant immune responses prevail in human abdominal aortic aneurysm. Am J Pathol, 161, 499–506 (2002). doi: 10.1016/S0002-9440(10)64206-X 12163375

21. Schulte S, Sukhova GK, Libby P. Genetically programmed biases in Th1 and Th2 immune responses modulates atherogenesis. Am J Pathol. 172, 1500–1508. (2008). doi: 10.2353/ajpath.2008.070776 18467709

22. Lindeman JH, Abdul-Hussien H, Schaapherder AF, Van Bockel JH, Von der Thüsen JH, Roelen DL, et al. Enhanced expression and activation of pro-inflammatory transcription factors distinguish aneurysmal from atherosclerotic aorta: IL-6 and IL-8-dominated infl ammatory responses prevail in the human aneurysm. Clin Sci (Lond). 114, 687–697 (2008).

23. del Porto F, Proietta M, Tritapepe L, Miraldi F, Koverech A, Cardelli P, et al. Inflammation and immune response in acute aortic dissection. Ann Med. 42, 622–699 (2010). doi: 10.3109/07853890.2010.518156 20860543

24. Wei X, Sun Y, Wu Y, Zhu J, Gao B, Yan H, et al. Downregulation of Talin-1 expression associates with increased proliferation and migration of vascular smooth muscle cells in aortic dissection. BMC Cardiovasc Disord. 20, 162 (2017).

25. Iida Y, Tanaka H, Sano H, Suzuki Y, Shimizu H, Urano T. Ectopic Expression of PCSK9 by Smooth Muscle Cells Contributes to Aortic Dissection. Ann Vasc Surg. 48, 195–208 (2018). doi: 10.1016/j.avsg.2017.10.005 29197601

26. Fry JL, Shiraishi Y, Turcotte R, Yu X, Gao YZ, Akiki R, et al. Vascular Smooth Muscle Sirtuin-1 Protects Against Aortic Dissection During Angiotensin II-Induced Hypertension. J Am Heart Assoc, 16, e002384 (2015).

27. Liao WL, Tan MW, Yuan Y, Wang GK, Wang C, Tang H et al. Brahma-related gene 1 inhibits proliferation and migration of human aortic smooth muscle cellsby directly up-regulating Ras-related associated with diabetes in the pathophysiologic processesof aortic dissection. J Thorac Cardiovasc Surg. 150, 1292–301 (2015). doi: 10.1016/j.jtcvs.2015.08.010 26344687

28. Li Z, Wang Q, Chen G, Li X, Yang Q, Du Z, et al. Integration of Gene Expression Profile Data to Screen and Verify Hub Genes Involved in Osteoarthritis. Biomed Res Int. 14, 9482726 (2018).

29. Brown NR, Korolchuk S, Martin MP, Stanley WA, Moukhametzianov R, Noble MEM, et al. CDK1 structures reveal conserved and unique features of the essential cell cycle CDK.Nat Commun.13, 6769 (2015).

30. Diril MK, Ratnacaram CK, Padmakumar VC, Du T, Wasser M, Coppola V., et al. Cyclin-dependent kinase 1 (Cdk1) is essential for cell division and suppression of DNA re-replication but not for liver regeneration. Proc. Natl Acad. Sci. 109, 3826–3831 (2012). doi: 10.1073/pnas.1115201109 22355113

31. Hsieh TC, Lu X, Guo J, Wu JM. Differential regulation of proliferation, cell cycle control and gene expression in cultured humanaortic and pulmonary artery endothelial cells by resveratrol. Int J Mol Med. 26, 743–749 (2010). doi: 10.3892/ijmm_00000521 20878097

32. Barchiesi F, Jackson EK, Fingerle J, Gillespie DG, Odermatt B, Dubey RK. 2-Methoxyestradiol, an estradiol metabolite, inhibits neointima formation and smooth muscle cellgrowth via double blockade of the cell cycle.Circ Res. 99, 266–274 (2006). doi: 10.1161/01.RES.0000233318.85181.2e 16794187

33. Zhu L, Vranckx R, Khau Van Kien P, Lalande A, Boisset N, Mathieu F, et al. Mutations in myosin heavy chain 11 cause a syndrome associating thoracic aortic aneurysm/aortic dissection and patent ductus arteriosus. Nat Genet. 38, 343‐349 (2006). doi: 10.1038/ng1721 16444274

34. Huang DW, Sherman BT, Tan Q, Collins JR, Alvord WG, Roayaei J, et al. The DAVID gene functional classifcation tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biology. 9, R183 (2017).

35. Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks, et al.The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Research. 39, 561–568 (2011).

36. Shannon P., A. Cytoscape: a sofware Environment for integrated models of biomolecular interaction networks. Genome Research. 13, 2498–2504 (2003). doi: 10.1101/gr.1239303 14597658

37. Bader GD, Hogue CW. An automated method for fnding molecular complexes in large protein interaction networks. BMC Bioinformatics. 4, 1–2 (2003). doi: 10.1186/1471-2105-4-1

Článok vyšiel v časopise


2019 Číslo 11