A network analysis revealed the essential and common downstream proteins related to inguinal hernia


Autoři: Yimin Mao aff001;  Le Chen aff001;  Jianghua Li aff001;  Anna Junjie Shangguan aff003;  Stacy Kujawa aff004;  Hong Zhao aff004
Působiště autorů: School of Information and Technology, Jiangxi University of Science and Technology, Jiangxi, China aff001;  Applied Science Institute, Jiangxi University of Science and Technology, Jiangxi, China aff002;  Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America aff003;  Division of Reproductive Science in Medicine, Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226885

Souhrn

Although more than 1 in 4 men develop symptomatic inguinal hernia during their lifetime, the molecular mechanism behind inguinal hernia remains unknown. Here, we explored the protein-protein interaction network built on known inguinal hernia-causative genes to identify essential and common downstream proteins for inguinal hernia formation. We discovered that PIK3R1, PTPN11, TGFBR1, CDC42, SOS1, and KRAS were the most essential inguinal hernia-causative proteins and UBC, GRB2, CTNNB1, HSP90AA1, CBL, PLCG1, and CRK were listed as the most commonly-involved downstream proteins. In addition, the transmembrane receptor protein tyrosine kinase signaling pathway was the most frequently found inguinal hernia-related pathway. Our in silico approach was able to uncover a novel molecular mechanism underlying inguinal hernia formation by identifying inguinal hernia-related essential proteins and potential common downstream proteins of inguinal hernia-causative proteins.

Klíčová slova:

Centrality – Hernia – MAPK signaling cascades – Membrane receptor signaling – Protein interaction networks – Protein kinase signaling cascade – TGF-beta signaling cascade – VEGF signaling


Zdroje

1. Chung L, Norrie J, O'Dwyer PJ. Long-term follow-up of patients with a painless inguinal hernia from a randomized clinical trial. Br J Surg. 2011;98(4):596–9. doi: 10.1002/bjs.7355 21656724.

2. Primatesta P, Goldacre MJ. Inguinal hernia repair: incidence of elective and emergency surgery, readmission and mortality. International journal of epidemiology. 1996;25(4):835–9. doi: 10.1093/ije/25.4.835 8921464.

3. Matthews RD, Neumayer L. Inguinal hernia in the 21st century: an evidence-based review. Curr Probl Surg. 2008;45(4):261–312. doi: 10.1067/j.cpsurg.2008.01.002 18358264.

4. Abdeen NS, W.M. Review of Inguinal Region Hernias on MDCT. Applied Radiology. 2011;40(4):6.

5. Malangoni MR, M. The Biological Basis of Modern Surgical Practice. In: Townsend CJB, D.; Evers M.; Mattox K.; eds., editor. Sabiston Textbook of Surgery. Hernias. 18th ed. Philadelphia: Saunders Elsevier; 2008.

6. Youssef T, El-Alfy K, Farid M. Randomized clinical trial of Desarda versus Lichtenstein repair for treatment of primary inguinal hernia. International journal of surgery. 2015;20:28–34. doi: 10.1016/j.ijsu.2015.05.055 26074293.

7. Bay-Nielsen M, Perkins FM, Kehlet H, Danish Hernia D. Pain and functional impairment 1 year after inguinal herniorrhaphy: a nationwide questionnaire study. Ann Surg. 2001;233(1):1–7. doi: 10.1097/00000658-200101000-00001 11141218; PubMed Central PMCID: PMC1421158.

8. Matthews RD, Anthony T, Kim LT, Wang J, Fitzgibbons RJ Jr., Giobbie-Hurder A, et al. Factors associated with postoperative complications and hernia recurrence for patients undergoing inguinal hernia repair: a report from the VA Cooperative Hernia Study Group. Am J Surg. 2007;194(5):611–7. doi: 10.1016/j.amjsurg.2007.07.018 17936422.

9. Yang B, Jiang ZP, Li YR, Zong Z, Chen S. Long-term outcome for open preperitoneal mesh repair of recurrent inguinal hernia. International journal of surgery. 2015;19:134–6. doi: 10.1016/j.ijsu.2015.05.029 26021274.

10. Gianetta E, de Cian F, Cuneo S, Friedman D, Vitale B, Marinari G, et al. Hernia repair in elderly patients. Br J Surg. 1997;84(7):983–5. doi: 10.1002/bjs.1800840721 9240142.

11. Gilbert AI. Hernia repair in the aged and infirmed. J Fla Med Assoc. 1988;75(11):742–4. 3204359.

12. Gunnarsson U, Degerman M, Davidsson A, Heuman R. Is elective hernia repair worthwhile in old patients? Eur J Surg. 1999;165(4):326–32. doi: 10.1080/110241599750006857 10365833.

13. Kingsnorth A, LeBlanc K. Hernias: inguinal and incisional. Lancet. 2003;362(9395):1561–71. doi: 10.1016/S0140-6736(03)14746-0 14615114.

14. Burcharth J, Pommergaard HC, Rosenberg J. The inheritance of groin hernia: a systematic review. Hernia: the journal of hernias and abdominal wall surgery. 2013;17(2):183–9. doi: 10.1007/s10029-013-1060-4 23423330.

15. Zoller B, Ji J, Sundquist J, Sundquist K. Shared and nonshared familial susceptibility to surgically treated inguinal hernia, femoral hernia, incisional hernia, epigastric hernia, and umbilical hernia. J Am Coll Surg. 2013;217(2):289–99 e1. doi: 10.1016/j.jamcollsurg.2013.04.020 23870221.

16. Ringpfeil F. Selected disorders of connective tissue: pseudoxanthoma elasticum, cutis laxa, and lipoid proteinosis. Clin Dermatol. 2005;23(1):41–6. doi: 10.1016/j.clindermatol.2004.09.006 15708288.

17. Pyeritz RE, McKusick VA. The Marfan syndrome: diagnosis and management. The New England journal of medicine. 1979;300(14):772–7. doi: 10.1056/NEJM197904053001406 370588.

18. Liem MS, van der Graaf Y, Beemer FA, van Vroonhoven TJ. Increased risk for inguinal hernia in patients with Ehlers-Danlos syndrome. Surgery. 1997;122(1):114–5. doi: 10.1016/s0039-6060(97)90273-7 9225924.

19. Antoniou GA, Lazarides MK, Patera S, Antoniou SA, Giannoukas AD, Georgiadis GS, et al. Assessment of insertion/deletion polymorphism of the angiotensin-converting enzyme gene in abdominal aortic aneurysm and inguinal hernia. Vascular. 2013;21(1):1–5. doi: 10.1258/vasc.2011.oa0322 22271804.

20. Han Q, Zhang Y, Li W, Fan H, Xing Q, Pang S, et al. Functional sequence variants within the SIRT1 gene promoter in indirect inguinal hernia. Gene. 2014;546(1):1–5. doi: 10.1016/j.gene.2014.05.058 24875419.

21. Jorgenson E, Makki N, Shen L, Chen DC, Tian C, Eckalbar WL, et al. A genome-wide association study identifies four novel susceptibility loci underlying inguinal hernia. Nat Commun. 2015;6:10130. doi: 10.1038/ncomms10130 26686553; PubMed Central PMCID: PMC4703831.

22. Sezer S, Simsek N, Celik HT, Erden G, Ozturk G, Duzgun AP, et al. Association of collagen type I alpha 1 gene polymorphism with inguinal hernia. Hernia: the journal of hernias and abdominal wall surgery. 2014;18(4):507–12. doi: 10.1007/s10029-013-1147-y 23925543.

23. Zhang Y, Han Q, Fan H, Li W, Xing Q, Yan B. Genetic analysis of the TBX2 gene promoter in indirect inguinal hernia. Hernia: the journal of hernias and abdominal wall surgery. 2014;18(4):513–7. doi: 10.1007/s10029-013-1199-z 24309999.

24. Zhang Y, Han Q, Li C, Li W, Fan H, Xing Q, et al. Genetic analysis of the TBX1 gene promoter in indirect inguinal hernia. Gene. 2014;535(2):290–3. doi: 10.1016/j.gene.2013.11.012 24295890.

25. Bairoch A, Apweiler R, Wu CH, Barker WC, Boeckmann B, Ferro S, et al. The Universal Protein Resource (UniProt). Nucleic Acids Res. 2005;33(Database issue):D154–9. doi: 10.1093/nar/gki070 15608167; PubMed Central PMCID: PMC540024.

26. Wuchty S, Stadler PF. Centers of complex networks. J Theor Biol. 2003;223(1):45–53. doi: 10.1016/s0022-5193(03)00071-7 12782116.

27. Vallabhajosyula RR, Chakravarti D, Lutfeali S, Ray A, Raval A. Identifying hubs in protein interaction networks. PloS one. 2009;4(4):e5344. doi: 10.1371/journal.pone.0005344 19399170; PubMed Central PMCID: PMC2670494.

28. Maslov S, Sneppen K. Specificity and stability in topology of protein networks. Science. 2002;296(5569):910–3. doi: 10.1126/science.1065103 11988575.

29. Zhang W, Xu J, Li Y, Zou X. Detecting Essential Proteins Based on Network Topology, Gene Expression Data, and Gene Ontology Information. IEEE/ACM Trans Comput Biol Bioinform. 2018;15(1):109–16. doi: 10.1109/TCBB.2016.2615931 28650821.

30. Zhang S, Ning X, Zhang XS. Identification of functional modules in a PPI network by clique percolation clustering. Comput Biol Chem. 2006;30(6):445–51. doi: 10.1016/j.compbiolchem.2006.10.001 17098476.

31. Tew KL, Li XL, Tan SH. Functional centrality: detecting lethality of proteins in protein interaction networks. Genome Inform. 2007;19:166–77. 18546514.

32. Raman K, Damaraju N, Joshi GK. The organisational structure of protein networks: revisiting the centrality-lethality hypothesis. Syst Synth Biol. 2014;8(1):73–81. doi: 10.1007/s11693-013-9123-5 24592293; PubMed Central PMCID: PMC3933631.

33. Peng X, Wang J, Wang J, Wu FX, Pan Y. Rechecking the Centrality-Lethality Rule in the Scope of Protein Subcellular Localization Interaction Networks. PloS one. 2015;10(6):e0130743. doi: 10.1371/journal.pone.0130743 26115027; PubMed Central PMCID: PMC4482623.

34. Jeong H, Mason SP, Barabasi AL, Oltvai ZN. Lethality and centrality in protein networks. Nature. 2001;411(6833):41–2. doi: 10.1038/35075138 11333967.

35. Hahn MW, Kern AD. Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol. 2005;22(4):803–6. doi: 10.1093/molbev/msi072 15616139.

36. Yu HY, Greenbaum D, Lu HX, Zhu XW, Gerstein M. Genomic analysis of essentiality within protein networks. Trends Genet. 2004;20(6):227–31. doi: 10.1016/j.tig.2004.04.008 WOS:000223743100003. 15145574

37. Mao Y, Kuo SW, Chen L, Heckman CJ, Jiang MC. The essential and downstream common proteins of amyotrophic lateral sclerosis: A protein-protein interaction network analysis. PloS one. 2017;12(3):e0172246. doi: 10.1371/journal.pone.0172246 28282387; PubMed Central PMCID: PMC5345759.

38. Estrada E. Virtual identification of essential proteins within the protein interaction network of yeast. Proteomics. 2006;6(1):35–40. doi: 10.1002/pmic.200500209 16281187.

39. Nguyen TP, Caberlotto L, Morine MJ, Priami C. Network analysis of neurodegenerative disease highlights a role of Toll-like receptor signaling. Biomed Res Int. 2014;2014:686505. doi: 10.1155/2014/686505 24551850; PubMed Central PMCID: PMC3914352.

40. Zhong JC, Wang JX, Peng W, Zhang Z, Li M. A Feature Selection Method for Prediction Essential Protein. Tsinghua Sci Technol. 2015;20(5):491–9. doi: 10.1109/Tst.2015.7297748 WOS:000364492700007.

41. Zhang X, Xiao W, Hu X. Predicting essential proteins by integrating orthology, gene expressions, and PPI networks. PloS one. 2018;13(4):e0195410. doi: 10.1371/journal.pone.0195410 29634727; PubMed Central PMCID: PMC5892885.

42. Freeman LC. Set of Measures of Centrality Based on Betweenness. Sociometry. 1977;40(1):35–41. doi: 10.2307/3033543 WOS:A1977CZ20900004.

43. Joy MP, Brock A, Ingber DE, Huang S. High-betweenness proteins in the yeast protein interaction network. J Biomed Biotechnol. 2005;2005(2):96–103. doi: 10.1155/JBB.2005.96 16046814; PubMed Central PMCID: PMC1184047.

44. Bonacich P. Power and Centrality—a Family of Measures. Am J Sociol. 1987;92(5):1170–82. doi: 10.1086/228631 WOS:A1987G108900005.

45. Chua HN, Tew KL, Li XL, Ng SK. A Unified Scoring Scheme for Detecting Essential Proteins in Protein Interaction Networks. Proc Int C Tools Art. 2008:66–73. doi: 10.1109/Ictai.2008.107 WOS:000262215500010.

46. Ren J, Wang JX, Li M, Wang H, Liu BB. Prediction of Essential Proteins by Integration of PPI Network Topology and Protein Complexes Information. Lect N Bioinformat. 2011;6674:12–24. WOS:000296688700006.

47. Hart GT, Lee I, Marcotte ER. A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality. BMC Bioinformatics. 2007;8:236. doi: 10.1186/1471-2105-8-236 17605818; PubMed Central PMCID: PMC1940025.

48. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57. doi: 10.1038/nprot.2008.211 WOS:000265781800006. 19131956

49. Zhao H, Zhou L, Li L, Coon VJ, Chatterton RT, Brooks DC, et al. Shift from androgen to estrogen action causes abdominal muscle fibrosis, atrophy, and inguinal hernia in a transgenic male mouse model. Proc Natl Acad Sci U S A. 2018;115(44):E10427–E36. doi: 10.1073/pnas.1807765115 30327348; PubMed Central PMCID: PMC6217386.

50. Engelman JA, Luo J, Cantley LC. The evolution of phosphatidylinositol 3-kinases as regulators of growth and metabolism. Nat Rev Genet. 2006;7(8):606–19. doi: 10.1038/nrg1879 16847462.

51. Dance M, Montagner A, Salles JP, Yart A, Raynal P. The molecular functions of Shp2 in the Ras/Mitogen-activated protein kinase (ERK1/2) pathway. Cell Signal. 2008;20(3):453–9. doi: 10.1016/j.cellsig.2007.10.002 17993263.

52. Arozarena I, Aaronson DS, Matallanas D, Sanz V, Ajenjo N, Tenbaum SP, et al. The Rho family GTPase Cdc42 regulates the activation of Ras/MAP kinase by the exchange factor Ras-GRF. The Journal of biological chemistry. 2000;275(34):26441–8. doi: 10.1074/jbc.M002992200 10840034

53. Findlay GM, Smith MJ, Lanner F, Hsiung MS, Gish GD, Petsalaki E, et al. Interaction domains of Sos1/Grb2 are finely tuned for cooperative control of embryonic stem cell fate. Cell. 2013;152(5):1008–20. doi: 10.1016/j.cell.2013.01.056 23452850.

54. Ruess DA, Heynen GJ, Ciecielski KJ, Ai J, Berninger A, Kabacaoglu D, et al. Mutant KRAS-driven cancers depend on PTPN11/SHP2 phosphatase. Nat Med. 2018;24(7):954–60. doi: 10.1038/s41591-018-0024-8 29808009.

55. Chapnick DA, Warner L, Bernet J, Rao T, Liu X. Partners in crime: the TGFbeta and MAPK pathways in cancer progression. Cell Biosci. 2011;1:42. doi: 10.1186/2045-3701-1-42 22204556; PubMed Central PMCID: PMC3275500.

56. Zhang L, Zhou F, ten Dijke P. Signaling interplay between transforming growth factor-beta receptor and PI3K/AKT pathways in cancer. Trends Biochem Sci. 2013;38(12):612–20. doi: 10.1016/j.tibs.2013.10.001 24239264.

57. Cheung LW, Yu S, Zhang D, Li J, Ng PK, Panupinthu N, et al. Naturally occurring neomorphic PIK3R1 mutations activate the MAPK pathway, dictating therapeutic response to MAPK pathway inhibitors. Cancer cell. 2014;26(4):479–94. doi: 10.1016/j.ccell.2014.08.017 25284480; PubMed Central PMCID: PMC4198486.

58. Ye Y, Blaser G, Horrocks MH, Ruedas-Rama MJ, Ibrahim S, Zhukov AA, et al. Ubiquitin chain conformation regulates recognition and activity of interacting proteins. Nature. 2012;492(7428):266–70. doi: 10.1038/nature11722 23201676; PubMed Central PMCID: PMC3605796.

59. Yang WL, Wu CY, Wu J, Lin HK. Regulation of Akt signaling activation by ubiquitination. Cell Cycle. 2010;9(3):487–97. doi: 10.4161/cc.9.3.10508 20081374; PubMed Central PMCID: PMC3077544.

60. Lowenstein EJ, Daly RJ, Batzer AG, Li W, Margolis B, Lammers R, et al. The SH2 and SH3 domain-containing protein GRB2 links receptor tyrosine kinases to ras signaling. Cell. 1992;70(3):431–42. doi: 10.1016/0092-8674(92)90167-b 1322798.

61. Zhao H, Cui Y, Dupont J, Sun H, Hennighausen L, Yakar S. Overexpression of the tumor suppressor gene phosphatase and tensin homologue partially inhibits wnt-1-induced mammary tumorigenesis. Cancer research. 2005;65(15):6864–73. Epub 2005/08/03. doi: 10.1158/0008-5472.CAN-05-0181 16061670.

62. Xiao X, Wang W, Li Y, Yang D, Li X, Shen C, et al. HSP90AA1-mediated autophagy promotes drug resistance in osteosarcoma. J Exp Clin Cancer Res. 2018;37(1):201. doi: 10.1186/s13046-018-0880-6 30153855; PubMed Central PMCID: PMC6114771.

63. Gresset A, Sondek J, Harden TK. The phospholipase C isozymes and their regulation. Subcell Biochem. 2012;58:61–94. doi: 10.1007/978-94-007-3012-0_3 22403074; PubMed Central PMCID: PMC3638883.

64. Schmidt MHH, Dikic I. The Cbl interactome and its functions. Nat Rev Mol Cell Biol. 2005;6(12):907–18. doi: 10.1038/nrm1762 16227975.

65. Hossain S, Dubielecka PM, Sikorski AF, Birge RB, Kotula L. Crk and ABI1: binary molecular switches that regulate abl tyrosine kinase and signaling to the cytoskeleton. Genes Cancer. 2012;3(5–6):402–13. doi: 10.1177/1947601912460051 23226578; PubMed Central PMCID: PMC3513786.

66. Fruman DA, Chiu H, Hopkins BD, Bagrodia S, Cantley LC, Abraham RT. The PI3K Pathway in Human Disease. Cell. 2017;170(4):605–35. doi: 10.1016/j.cell.2017.07.029 28802037; PubMed Central PMCID: PMC5726441.

67. Lee YR, Park J, Yu HN, Kim JS, Youn HJ, Jung SH. Up-regulation of PI3K/Akt signaling by 17beta-estradiol through activation of estrogen receptor-alpha, but not estrogen receptor-beta, and stimulates cell growth in breast cancer cells. Biochem Biophys Res Commun. 2005;336(4):1221–6. doi: 10.1016/j.bbrc.2005.08.256 16169518.

68. Vanhaesebroeck B, Stephens L, Hawkins P. PI3K signalling: the path to discovery and understanding. Nat Rev Mol Cell Biol. 2012;13(3):195–203. doi: 10.1038/nrm3290 22358332.

69. Winnay JN, Solheim MH, Dirice E, Sakaguchi M, Noh HL, Kang HJ, et al. PI3-kinase mutation linked to insulin and growth factor resistance in vivo. The Journal of clinical investigation. 2016;126(4):1401–12. doi: 10.1172/JCI84005 26974159; PubMed Central PMCID: PMC4811129.

70. Wang J, Chu ES, Chen HY, Man K, Go MY, Huang XR, et al. microRNA-29b prevents liver fibrosis by attenuating hepatic stellate cell activation and inducing apoptosis through targeting PI3K/AKT pathway. Oncotarget. 2015;6(9):7325–38. doi: 10.18632/oncotarget.2621 25356754; PubMed Central PMCID: PMC4466688.

71. Ueki K, Algenstaedt P, Mauvais-Jarvis F, Kahn CR. Positive and negative regulation of phosphoinositide 3-kinase-dependent signaling pathways by three different gene products of the p85alpha regulatory subunit. Mol Cell Biol. 2000;20(21):8035–46. doi: 10.1128/mcb.20.21.8035-8046.2000 11027274; PubMed Central PMCID: PMC86414.

72. Barbour LA, Mizanoor Rahman S, Gurevich I, Leitner JW, Fischer SJ, Roper MD, et al. Increased P85alpha is a potent negative regulator of skeletal muscle insulin signaling and induces in vivo insulin resistance associated with growth hormone excess. The Journal of biological chemistry. 2005;280(45):37489–94. doi: 10.1074/jbc.M506967200 16166093.

73. Luo J, Sobkiw CL, Hirshman MF, Logsdon MN, Li TQ, Goodyear LJ, et al. Loss of class IA PI3K signaling in muscle leads to impaired muscle growth, insulin response, and hyperlipidemia. Cell Metab. 2006;3(5):355–66. doi: 10.1016/j.cmet.2006.04.003 16679293.


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