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01.04.2013 | Gynecologic Oncology

Network motifs in the transcriptional regulation network of cervical carcinoma cells respond to EGF

verfasst von: Su Fang Wu, Wen Yan Qian, Jia Wen Zhang, Yong Bin Yang, Yuan Liu, Yu Dong, Zhen Bo Zhang, Ya Ping Zhu, You Ji Feng

Erschienen in: Archives of Gynecology and Obstetrics | Ausgabe 4/2013

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Abstract

Purpose

Cervical carcinoma is the second most prevalent and the fifth most deadly malignancy seen in women worldwide. Dysregulated activation of EGF ErbB system has been implicated in diverse types of human cancer; however, it is elusive how it is regulated in human cervical cancer cells. We herein aimed to explore the mechanisms of cervical carcinoma response to epidermal growth factor (EGF), with a view of the pathways activated by EGF.

Methods

Using the GSE6783 affymetrix microarray data accessible from gene expression omnibus database, we first identified the differentially expressed genes between EGF-stimulated and -unstimulated samples. Then we constructed a regulation network and identified the network motifs. We also performed biological process and pathway enrichment analyses to functionally classify the genes in the regulation network.

Results

A total of 11 network motifs were identified in the regulation network. EGF treatment could increase the risk of cancer via dysregulation of cancer-related pathways and immune response pathways.

Conclusions

Network motif analysis is useful in mining the useful information underlying the network. We hope our work could serve as a basis for further experimentation.

Armstrong EP (2010) Prophylaxis of cervical cancer and related cervical disease: a review of the cost-effectiveness of vaccination against oncogenic HPV types. J Manag Care Pharm 16(3):217–230PubMed

Jemal A, Siegel R, Ward E, Hao Y, Xu J, Thun MJ (2009) Cancer statistics. CA Cancer J Clin 59(4):225–249. doi:10.3322/caac.20006 PubMedCrossRef

Einstein MH, Schiller JT, Viscidi RP, Strickler HD, Coursaget P, Tan T, Halsey N, Jenkins D (2009) Clinician’s guide to human papillomavirus immunology: knowns and unknowns. Lancet Infect Dis 9(6):347–356. doi:10.1016/S1473-3099(09)70108-2 PubMedCrossRef

Brake T, Lambert PF (2005) Estrogen contributes to the onset, persistence, and malignant progression of cervical cancer in a human papillomavirus-transgenic mouse model. Proc Natl Acad Sci USA 102(7):2490–2495. doi:10.1073/pnas.0409883102 PubMedCrossRef

Herbst RS (2004) Review of epidermal growth factor receptor biology. Int J Radiat Oncol Biol Phys 59(2):21–26. doi:10.1016/j.ijrobp.2003.11.041 PubMedCrossRef

Levin ER (2003) Bidirectional signaling between the estrogen receptor and the epidermal growth factor receptor. Mol Endocrinol 17(3):309–317. doi:10.1210/me.2002-0368me.2002-0368 PubMedCrossRef

Vignon F, Bouton MM, Rochefort H (1987) Antiestrogens inhibit the mitogenic effect of growth factors on breast cancer cells in the total absence of estrogens. Biochem Biophys Res Commun 146(3):1502–1508, pii: 0006-291X(87)90819-9PubMedCrossRef

Yarden Y, Sliwkowski MX (2001) Untangling the ErbB signalling network. Nat Rev Mol Cell Biol 2(2):127–137. doi:10.1038/35052073 PubMedCrossRef

Hynes NE, Lane HA (2005) ERBB receptors and cancer: the complexity of targeted inhibitors. Nat Rev Cancer 5(5):341–354. doi:10.1038/nrc1609 PubMedCrossRef

10.

Mangan S, Alon U (2003) Structure and function of the feed-forward loop network motif. Proc Natl Acad Sci USA 100(21):11980–11985. doi:10.1073/pnas.21338411002133841100 PubMedCrossRef

11.

Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U (2002) Network motifs: simple building blocks of complex networks. Science 298(5594):824–827. doi:10.1126/science.298.5594.824298/5594/824 PubMedCrossRef

12.

Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M (2004) Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature 430(6995):88–93. doi:10.1038/nature02555nature02555 PubMedCrossRef

13.

Jeong H, Mason SP, Barabasi AL, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411(6833):41–42. doi:10.1038/3507513835075138 PubMedCrossRef

14.

Jaimovich A, Elidan G, Margalit H, Friedman N (2006) Towards an integrated protein–protein interaction network: a relational Markov network approach. J Comput Biol 13(2):145–164. doi:10.1089/cmb.2006.13.145 PubMedCrossRef

15.

Jeong H, Tombor B, Albert R, Oltvai ZN, Barabasi AL (2000) The large-scale organization of metabolic networks. Nature 407(6804):651–654. doi:10.1038/35036627 PubMedCrossRef

16.

Amit I, Citri A, Shay T, Lu Y, Katz M, Zhang F, Tarcic G, Siwak D, Lahad J, Jacob-Hirsch J, Amariglio N, Vaisman N, Segal E, Rechavi G, Alon U, Mills GB, Domany E, Yarden Y (2007) A module of negative feedback regulators defines growth factor signaling. Nat Genet 39(4):503–512. doi:10.1038/ng1987 PubMedCrossRef

17.

Matys V, Fricke E, Geffers R, Gossling E, Haubrock M, Hehl R, Hornischer K, Karas D, Kel AE, Kel-Margoulis OV, Kloos DU, Land S, Lewicki-Potapov B, Michael H, Munch R, Reuter I, Rotert S, Saxel H, Scheer M, Thiele S, Wingender E (2003) TRANSFAC: transcriptional regulation, from patterns to profiles. Nucl Acids Res 31(1):374–378PubMedCrossRef

18.

Jiang C, Xuan Z, Zhao F, Zhang MQ (2007) TRED: a transcriptional regulatory element database, new entries and other development. Nucl Acids Res 35:D137–D140. doi:10.1093/nar/gkl1041 PubMedCrossRef

19.

Smyth GK (2004) Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3 (3). doi:10.2202/1544-6115.1027

20.

Derrick TR, Bates BT, Dufek JS (1994) Evaluation of time-series data sets using the Pearson product-moment correlation coefficient. Med Sci Sports Exerc 26(7):919–928PubMed

21.

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504. doi:10.1101/gr.123930313/11/2498 PubMedCrossRef

22.

Wernicke S, Rasche F (2006) Fanmod: a tool for fast network motif detection. Bioinformatics 22(9):1152–1153. doi:10.1093/bioinformatics/btl038 PubMedCrossRef

23.

da Huang W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44–57. doi:10.1038/nprot.2008.211 CrossRef

24.

Brake T, Connor JP, Petereit DG, Lambert PF (2003) Comparative analysis of cervical cancer in women and in a human papillomavirus-transgenic mouse model: identification of minichromosome maintenance protein 7 as an informative biomarker for human cervical cancer. Cancer Res 63(23):8173–8180PubMed

25.

Mangan S, Zaslaver A, Alon U (2003) The coherent feedforward loop serves as a sign-sensitive delay element in transcription networks. J Mol Biol 334(2):197–204, pii: S0022283603012038PubMedCrossRef

26.

Zaslaver A, Mayo AE, Rosenberg R, Bashkin P, Sberro H, Tsalyuk M, Surette MG, Alon U (2004) Just-in-time transcription program in metabolic pathways. Nat Genet 36(5):486–491. doi:10.1038/ng1348ng1348 PubMedCrossRef

27.

Lo RS, Wotton D, Massague J (2001) Epidermal growth factor signaling via ras controls the smad transcriptional co-repressor TGIF. EMBO J 20(1–2):128–136. doi:10.1093/emboj/20.1.128 PubMedCrossRef

28.

Derynck R, Zhang YE (2003) Smad-dependent and smad-independent pathways in TGF-beta family signalling. Nature 425(6958):577–584. doi:10.1038/nature02006 PubMedCrossRef

29.

Lee HP, Seo SS (2002) The application of human papillomavirus testing to cervical cancer screening. Yonsei Med J 43(6):763–768PubMed

30.

Li L, He S, Sun JM, Davie JR (2004) Gene regulation by Sp1 and Sp3. Biochem Cell Biol 82(4):460–471. doi:10.1139/o04-045o04-045 PubMedCrossRef

31.

Wang LW, Li Q, Hua ZL, Zhou F, Keping X, Daoyan W, Yao J, Ajani J (2007) Expression of transcription factor Sp1 in human gastric cancer tissue and its correlation with prognosis. Zhonghua Zhong Liu Za Zhi 29(2):107–111PubMed

32.

Wang F, Li Y, Zhou J, Xu J, Peng C, Ye F, Shen Y, Lu W, Wan X, Xie X (2011) miR-375 is down-regulated in squamous cervical cancer and inhibits cell migration and invasion via targeting transcription factor SP1. Am J Pathol 179(5):2580–2588. doi:10.1016/j.ajpath.2011.07.037 PubMedCrossRef

33.

Cho S, Cinghu S, Yu JR, Park WY (2011) Helicase-like transcription factor confers radiation resistance in cervical cancer through enhancing the DNA damage repair capacity. J Cancer Res Clin Oncol 137(4):629–637. doi:10.1007/s00432-010-0925-5 PubMedCrossRef

34.

Leslie MC, Bar-Eli M (2005) Regulation of gene expression in melanoma: new approaches for treatment. J Cell Biochem 94(1):25–38. doi:10.1002/jcb.20296 PubMedCrossRef

35.

Papassava P, Gorgoulis VG, Papaevangeliou D, Vlahopoulos S, van Dam H, Zoumpourlis V (2004) Overexpression of activating transcription factor-2 is required for tumor growth and progression in mouse skin tumors. Cancer Res 64(23):8573–8584. doi:10.1158/0008-5472.CAN-03-0955 PubMedCrossRef

36.

Vlahopoulos SA, Logotheti S, Mikas D, Giarika A, Gorgoulis V, Zoumpourlis V (2008) The role of ATF-2 in oncogenesis. Bioessays 30(4):314–327. doi:10.1002/bies.20734 PubMedCrossRef

Titel: Network motifs in the transcriptional regulation network of cervical carcinoma cells respond to EGF
verfasst von: Su Fang Wu
Wen Yan Qian
Jia Wen Zhang
Yong Bin Yang
Yuan Liu
Yu Dong
Zhen Bo Zhang
Ya Ping Zhu
You Ji Feng
Publikationsdatum: 01.04.2013
Verlag: Springer-Verlag
Erschienen in: Archives of Gynecology and Obstetrics / Ausgabe 4/2013
Print ISSN: 0932-0067
Elektronische ISSN: 1432-0711
DOI: https://doi.org/10.1007/s00404-012-2608-8

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Network motifs in the transcriptional regulation network of cervical carcinoma cells respond to EGF