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Complex interaction networks of cytokines after transarterial chemotherapy in patients with hepatocellular carcinoma


Autoři: Dong Wook Jekarl aff001;  Seungok Lee aff002;  Jung Hyun Kwon aff004;  Soon Woo Nam aff004;  Myungshin Kim aff001;  Yonggoo Kim aff001;  Jeong Won Jang aff005
Působiště autorů: Department of Laboratory Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea aff001;  Laboratory for Development and Evaluation Center, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea aff002;  Department of Laboratory Medicine, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea aff003;  Department of Internal Medicine, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea aff004;  Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea aff005
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0224318

Souhrn

Treating hepatocellular carcinoma with transarterial chemoembolization (TACE) induces both local inflammation in the tumor microenvironment as well as systemic inflammation. We analyzed serum cytokine response to TACE to evaluate this. Serum samples obtained from 203 HCC patients treated with TACE were analyzed for inflammatory cytokines including interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12, IL-13, IL-17, IL-22, TNF-α, IFN-γ, and C-reactive protein (CRP) levels. Cytokine concentrations were measured at day 0 (D0, baseline, n = 203), day3 (D3, n = 156), day7 (D7, n = 147), and day 60 (D60, n = 115) after TACE. Network analysis of the cytokines was performed to understand their interactive relationship. After TACE, IL-1β, -6,-9, -12, and -22 increased by D60. IL-2, -5, -10, -17A and INF-γ decreased by D60, and IL-4, -13 and TNF-α revealed stable concentration. D0 network revealed that IL-2, -4, -5, and -10 formed a module. D3 network had the highest clustering coefficient and average degree that revealed similar pattern as CRP. D7 network revealed that IL-6, -9 and CRP were isolated from the network. D60 network had the lower network heterogeneity and lower clustering coefficient, network diameter, shortest path and characteristic path length. Degree correlation revealed that assortative network turned to disassortative network by D60 indicating that the network gained scale free feature. D60 cytokine network retained inflammatory function and these parameters indicated that the systemic inflammation induced by TACE appeared to be attenuated by D60. IL-9 at D3 and D7 seemed to be related to anti-tumor effect and IL-6 at D7 and D60, and IL-22 at D60 was related to regenerative but not pro- or anti- inflammatory function. Median survival month of patient group with high and low values of cytokine with P-values were as follows: D0 CRP, 9.5 and 54.2 months (P<0.0001); D0 IL-2, 39.9 and 56.1 months (P = 0.0084); D3 CRP, 31.3 and 55.1 months (P = 0.0056); D7 CRP, 28.7 and 50.7 months (P = 0.0065), respectively. TACE is associated with systemic inflammation which appears to peak at Day 3 and resolve by D60. Among the tested cytokines, IL-6 and IL-22 appear to play a regenerative role.

Klíčová slova:

Network analysis – Cytokines – Inflammation – Hepatocellular carcinoma – Clustering coefficients – Scale-free networks – Protein interaction networks


Zdroje

1. Bray F, Ferlay J, Soerjomataram I, Siegel R, Torre L. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424. doi: 10.3322/caac.21492 30207593

2. Kim BH, Park JW. Epidemiology of liver cancer in South Korea. Clin Mol Hepatol. 2018;24:1–9. doi: 10.3350/cmh.2017.0112 29249129

3. Llovet JM, Zucman-Rossi J, Pikarsky E, Sangro B, Schwartz M, Sherman M, et al. Hepatocellular carcinoma. Nat Rev Dis Primers. 2016;2:1–23.

4. Hernandez-Gea V, Toffanin S, Freidman SL, Llovet JM. Role of the microenvironment in the pathogenesis and treatment of hepatocellular carcinoma. Gastroenterology. 2013;144: 512–527. doi: 10.1053/j.gastro.2013.01.002 23313965

5. Aino H, Sumie S, Nizeki T, Kuromatsu R, Tajiri N, Nakano M, et al. The systemic inflammatory response as a prognostic factor for advanced hepatocellular carcinoma with extrahepatic metastasis. Mol Clin Oncol. 2016;5:83–88. doi: 10.3892/mco.2016.879 27330772

6. Liu C, Li L, Lu WS, Du H, Yan L, Wen T, et al. A novel combined systemic inflammation based score can predict survival of intermediate-to-advanced hepatocellular carcinoma patients undergoing transarterial chemoembolization. BMC Cancer. 2018;18:216–225. doi: 10.1186/s12885-018-4121-3 29466970

7. He CB, Lin XJ. Inflammation scores predict the survival of patients with hepatocellular carcinoma who were treated with transarterial chemoembolization and recombinant human type-5 adenovirus H101. PLoS One. 2017;12:e0174769. doi: 10.1371/journal.pone.0174769 28355305

8. Mantovani A, Allavena P, Sica A, Balkwill F. Cancer related inflammation. Nature. 2008;454:436–444. doi: 10.1038/nature07205 18650914

9. Estrada E. Quantifying network heterogeneity. Phys Rev. 2010;82:0660102–1–066012–8.

10. Estrada E. Evolutionary equations with application in natural sciences. Introduction to complex network: structures and dynamics. Switzerland: Springer Nature; 2015.

11. Barabasi AL, Oltvai Z. Network biology: understanding the cell’s functional organization. Nat Rev Genet. 2004;5:101–113. doi: 10.1038/nrg1272 14735121

12. Barabasi AL, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet. 2011;12:56–68. doi: 10.1038/nrg2918 21164525

13. Kim MJ, Jang JW, Oh BS, Kwon JH, Chung KW, Jung HS, et al. Change in inflammatory cytokine profiles after transarterial chemotherapy in patients with hepatocellular carcinoma. Cytokine. 2013;64:516–522. doi: 10.1016/j.cyto.2013.07.021 24035756

14. Jang JW, Oh BS, Kwon JH, You CR, Chung KW, Kay CS, et al. Serum interleukin-6 and C-reactive protein as a prognostic indicator in hepatocellular carcinoma. Cytokine. 2012;60:686–693. doi: 10.1016/j.cyto.2012.07.017 22906998

15. Jekarl DW, Kim KS, Lee S, Kim M, Kim Y. Cytokine and molecular networks in sepsis cases: A network biology approach. Eur Cytokine Netw. 2018;29:103–111. doi: 10.1684/ecn.2018.0414 30547887

16. Doncheva NT, Assenov Y, Domingues FS, Albrecht M. Topological analysis and interactive visualization of biological networks and protein structures. Nat Protoc. 2012;7:670–685. doi: 10.1038/nprot.2012.004 22422314

17. Saito R, Smoot ME, Ono K, Ruscheinski J, Wang P, Lotia S, et al. A travel guide to Cytoscape plugins. Nat Method. 2012;9:1069–1076.

18. Assenov Y, Ramirez F, Schelhorn SE, Lengauer T, Albrecht M. Computing topological parameters of biological networks. Sys Biol. 2008;24: 282.284.

19. Zhu Z, Gerstein M, Snyder M. Getting connected: analysis and principles of biological networks. Genes Dev. 2007;21:1010–1024. doi: 10.1101/gad.1528707 17473168

20. Barabasi AL. Network science. United Kingdom: Cambridge University Press; 2016.

21. Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal, Complex Systems. 2006;1695–1702.

22. Newman M. Modularity and community structure in networks. Proc Natl Acad Sci. USA. 2006;103:8577–8582. doi: 10.1073/pnas.0601602103 16723398

23. Llovet JM. Briux J. Systematic review of randomized trials for unresectable hepatocellular carcinoma: chemoembolization improves survival. Hepatology. 2003;37:429–442. doi: 10.1053/jhep.2003.50047 12540794

24. European association for the study of the liver and European organization for research and treatment of cancer. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012;56:908–943. doi: 10.1016/j.jhep.2011.12.001 22424438

25. Xue T, Jia Q, Ge N, Chen Y, Zhang B, Ye S. Imbalance in systemic inflammation and immune response following transarterial chemoembolization potential increases metastatic risk in huge hepatocellular carcinoma. Tumor Biol. 2015;36:8797–8803.

26. Dudakov JA, Hanash AM, van den Brink MRM. Interleukin-22: immunobiology and pathology. Annu Rev Immunol. 2015;33:747–785. doi: 10.1146/annurev-immunol-032414-112123 25706098

27. Ren X, Hu B, Colletti LM. IL-22 is involved in liver regeneration after hepatectomy. Am J Physiol Gastrointest Liver Physiol. 2010;298:G74–G80. doi: 10.1152/ajpgi.00075.2009 19875704

28. Pavlopoulos GA, Secrier M, Moschopoulos CN, Soldatos TG, Kossida S, Aerts J, et al. Using graph theory to analyze biological networks. BioData Mining. 2011;4:10–37. doi: 10.1186/1756-0381-4-10 21527005

29. Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang DU. Complex networks: structure and dynamics. Phys Rep. 2006;424:175–308.

30. Xu K, Bezakova I, Bunimovich L, Yi SV. Path length in protein-protein interaction network and biological complexity. Proteomics. 2011;11:1857–1867. doi: 10.1002/pmic.201000684 21480527

31. Zhang Z, Zhang J. A big world inside small-world network. PLoS One. 2009;4:1–6.

32. Jacob R, Harikrishnan KP, Misra R, Ambika G. Measure for degree heterogeneity in complex networks and its application to recurrence network analysis. R Soc Open Sci. 2017;4:160757. doi: 10.1098/rsos.160757 28280579

33. Cheng F, Liu C, Shen B, Zhao Z. Investigating cellular network heterogeneity and modularity in cancer: a network entropy and unbalanced motif approach. BMC Sys Biol. 2016;65(Suppl 3):302–311.

34. Lee HL, Jang JW, Lee SW, Yoo SH, Kwon JH, Nam SW, et al. Inflammatory cytokines and change of Th1/Th2 balance as prognostic indicators for hepatocellular carcinoma in patients treated with transarterial chemoembolization. Sci Rep. 2019;9:3260–3268. doi: 10.1038/s41598-019-40078-8 30824840

35. Gaggianesi M, Turdo A, Chinnici A, Lipari E, Apuzzo T, Benfante A, et al. IL-4 primes the dynamics of breast cancer progression via DUSP4 inhibition. Cancer Res. 2017;77:3268–3279. doi: 10.1158/0008-5472.CAN-16-3126 28400477


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2019 Číslo 11
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