期刊论文详细信息
BMC Systems Biology
Identification of upstream regulators for prognostic expression signature genes in colorectal cancer
Sunghoon Kim1  Wankyu Kim2  Katsuhisa Horimoto6  Jin Woo Choi3  Kyoohyoung Rho4  Taejeong Bae5 
[1] World Class University Program Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul 151-742, South Korea;Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, South Korea;Department of Pharmacology and Wonkwang Institute of Dental Research, School of Dentistry, Wonkwang University, Iksan, Chonbuk 570-749, South Korea;DNA Link Inc, Seoul, South Korea;Medicinal Bioconvergence Research Center, Advanced Institutes of Convergence Technology, Suwon 443-270, South Korea;Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan
关键词: Network inference;    Transcriptional network;    Colorectal cancer;    Gene signature;   
Others  :  1142338
DOI  :  10.1186/1752-0509-7-86
 received in 2013-04-23, accepted in 2013-09-02,  发布年份 2013
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【 摘 要 】

Background

Gene expression signatures have been commonly used as diagnostic and prognostic markers for cancer subtyping. However, expression signatures frequently include many passengers, which are not directly related to cancer progression. Their upstream regulators such as transcription factors (TFs) may take a more critical role as drivers or master regulators to provide better clues on the underlying regulatory mechanisms and therapeutic applications.

Results

In order to identify prognostic master regulators, we took the known 85 prognostic signature genes for colorectal cancer and inferred their upstream TFs. To this end, a global transcriptional regulatory network was constructed with total >200,000 TF-target links using the ARACNE algorithm. We selected the top 10 TFs as candidate master regulators to show the highest coverage of the signature genes among the total 846 TF-target sub-networks or regulons. The selected TFs showed a comparable or slightly better prognostic performance than the original 85 signature genes in spite of greatly reduced number of marker genes from 85 to 10. Notably, these TFs were selected solely from inferred regulatory links using gene expression profiles and included many TFs regulating tumorigenic processes such as proliferation, metastasis, and differentiation.

Conclusions

Our network approach leads to the identification of the upstream transcription factors for prognostic signature genes to provide leads to their regulatory mechanisms. We demonstrate that our approach could identify upstream biomarkers for a given set of signature genes with markedly smaller size and comparable performances. The utility of our method may be expandable to other types of signatures such as diagnosis and drug response.

【 授权许可】

   
2013 Bae et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Sotiriou C, Piccart MJ: Taking gene-expression profiling to the clinic: when will molecular signatures become relevant to patient care? Nat Rev Cancer 2007, 7:545-53.
  • [2]Méndez E, Lohavanichbutr P, Fan W, Houck JR, Rue TC, Doody DR, Futran ND, Upton MP, Yueh B, Zhao LP, Schwartz SM, Chen C: Can a metastatic gene expression profile outperform tumor size as a predictor of occult lymph node metastasis in oral cancer patients? Clin Cancer Res 2011, 17:2466-73.
  • [3]Servant N, Bollet MA, Halfwerk H, Bleakley K, Kreike B, Jacob L, Sie D, Kerkhoven R, Hupe P, Hadhri R, Fourquet A, Bartelink H, Barillot E, Sigal-Zafrani B, Van De Vijver M: Search for a gene expression signature of breast cancer local recurrence in young women. Clin Cancer Res 2012, 45:1704-15.
  • [4]Van Veer LJ, Dai H, Van De Vijver MJ, Schreiber GJ, Kerkhoven RM, Roberts C, Bernards Â, Friend SH, Linsley PS: Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002, 415:530-6.
  • [5]Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T, Hiller W, Fisher ER, Wickerham DL, Bryant J, Wolmark N: A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004, 351:2817-26.
  • [6]Nevins JR, Potti A: Mining gene expression profiles: expression signatures as cancer phenotypes. Nat Rev Genet 2007, 8:601-9.
  • [7]Pe’er D, Hacohen N: Principles and strategies for developing network models in cancer. Cell 2011, 144:864-73.
  • [8]Carro MS, Lim WK, Alvarez MJ, Bollo RJ, Zhao X, Snyder EY, Sulman EP, Anne SL, Doetsch F, Colman H, Lasorella A, Aldape K, Califano A, Iavarone A: The transcriptional network for mesenchymal transformation of brain tumours. Nature 2010, 463:318-25.
  • [9]Margolin A, Wang K, Lim WK, Kustagi M, Nemenman I, Califano A: Reverse engineering cellular networks. Nat Protoc 2006, 1:662-71.
  • [10]Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D: Global cancer statistics. CA Cancer J Clin 2011, 61:69-90.
  • [11]Jorissen RN, Gibbs P, Christie M, Prakash S, Lipton L, Desai J, Kerr D, Aaltonen LA, Arango D, Kruhøffer M, Orntoft TF, Andersen CL, Gruidl M, Kamath VP, Eschrich S, Yeatman TJ, Sieber OM: Metastasis-associated gene expression changes predict poor outcomes in patients with Dukes Stage B and C colorectal cancer. Clin Cancer Res 2009, 15:7642-51.
  • [12]Smith JJ, Deane NG, Wu F, Merchant NB, Zhang B, Jiang A, Lu P, Johnson JC, Schmidt C, Bailey CE, Eschrich S, Kis C, Levy S, Washington MK, Heslin MJ, Coffey RJ, Yeatman TJ, Shyr Y, Beauchamp RD: Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer. Gastroenterology 2010, 138:958-68.
  • [13]Staub E, Groene J, Heinze M, Mennerich D, Roepcke S, Klaman I, Hinzmann B, Castanos-Velez E, Pilarsky C, Mann B, Brümmendorf T, Weber B, Buhr H-J, Rosenthal A: An expression module of WIPF1-coexpressed genes identifies patients with favorable prognosis in three tumor types. J Mol Med 2009, 87:633-44.
  • [14]Oh SC, Park Y-Y, Park ES, Lim JY, Kim SM, Kim S-B, Kim J, Kim SC, Chu I-S, Smith JJ, Beauchamp RD, Yeatman TJ, Kopetz S, Lee J-S: Prognostic gene expression signature associated with two molecularly distinct subtypes of colorectal cancer. Gut 2012, 61:1291-8.
  • [15]Rankin EB, Giaccia a J: The role of hypoxia-inducible factors in tumorigenesis. Cell Death Differ 2008, 15:678-85.
  • [16]Majmundar AJ, Wong WJ, Simon MC: Hypoxia-inducible factors and the response to hypoxic stress. Mol Cell 2010, 40:294-309.
  • [17]Baba Y, Nosho K, Shima K, Irahara N, Chan AT, Meyerhardt JA, Chung DC, Giovannucci EL, Fuchs CS, Ogino S: HIF1A Overexpression is associated with poor prognosis in a cohort of 731 colorectal cancers. Am J Pathol 2010, 176:2292-301.
  • [18]Pan J, Mestas J, Burdick MD, Phillips RJ, Thomas GV, Reckamp K, Belperio J a, Strieter RM: Stromal derived factor-1 (SDF-1/CXCL12) and CXCR4 in renal cell carcinoma metastasis. Mol Cancer 2006, 5:56. BioMed Central Full Text
  • [19]Erler JT, Bennewith KL, Nicolau M, Dornhöfer N, Kong C, Le Q-T, Chi J-TA, Jeffrey SS, Giaccia AJ: Lysyl oxidase is essential for hypoxia-induced metastasis. Nature 2006, 440:1222-6.
  • [20]Zhong H, Willard M, Simons J: NS398 reduces hypoxia-inducible factor (HIF)-1alpha and HIF-1 activity: multiple-level effects involving cyclooxygenase-2 dependent and independent mechanisms. Int J Cancer 2004, 112:585-95.
  • [21]Outinen PA, Sood SK, Pfeifer SI, Pamidi S, Podor TJ, Li J, Weitz JI, Austin RC: Homocysteine-induced endoplasmic reticulum stress and growth arrest leads to specific changes in gene expression in human vascular endothelial cells. Blood 1999, 94:959-67.
  • [22]Maurer B, Busch N, Jüngel A, Pileckyte M, Gay RE, Michel BA, Schett G, Gay S, Distler J, Distler O: Transcription factor fos-related antigen-2 induces progressive peripheral vasculopathy in mice closely resembling human systemic sclerosis. Circulation 2009, 120:2367-76.
  • [23]Landrette SF, Kuo Y-H, Hensen K, van Waalwijk B, van Doorn-Khosrovani S, Perrat PN, Van de Ven WJM, Delwel R, Castilla LH: Plag1 and Plagl2 are oncogenes that induce acute myeloid leukemia in cooperation with Cbfb-MYH11. Blood 2005, 105:2900-7.
  • [24]Yang Y-S, Yang M-CW, Weissler JC: Pleiomorphic adenoma gene-like 2 expression is associated with the development of lung adenocarcinoma and emphysema. Lung cancer 2011, 74:12-24.
  • [25]Zheng H, Ying H, Wiedemeyer R, Yan H, Quayle SN, Ivanova EV, Paik J-H, Zhang H, Xiao Y, Perry SR, Hu J, Vinjamoori A, Gan B, Sahin E, Chheda MG, Brennan C, Wang YA, Hahn WC, Chin L, DePinho RA: PLAGL2 regulates Wnt signaling to impede differentiation in neural stem cells and gliomas. Cancer cell 2010, 17:497-509.
  • [26]Furukawa T, Adachi Y, Fujisawa J, Kambe T, Yamaguchi-Iwai Y, Sasaki R, Kuwahara J, Ikehara S, Tokunaga R, Taketani S: Involvement of PLAGL2 in activation of iron deficient- and hypoxia-induced gene expression in mouse cell lines. Oncogene 2001, 20:4718-27.
  • [27]Mizutani A, Furukawa T, Adachi Y, Ikehara S, Taketani S: A zinc-finger protein, PLAGL2, induces the expression of a proapoptotic protein Nip3, leading to cellular apoptosis. J Biol Chem 2002, 277:15851-8.
  • [28]Hanks TS, Gauss KA: Pleomorphic adenoma gene-like 2 regulates expression of the p53 family member, p73, and induces cell cycle block and apoptosis in human promonocytic U937 cells. Apoptosis 2012, 17:236-47.
  • [29]Jubb AM, Chalasani S, Frantz GD, Smits R, Grabsch HI, Kavi V, Maughan NJ, Hillan KJ, Quirke P, Koeppen H: Achaete-scute like 2 (ascl2) is a target of Wnt signalling and is upregulated in intestinal neoplasia. Oncogene 2006, 25:3445-57.
  • [30]Zhu R, Yang Y, Tian Y, Bai J, Zhang X, Li X, Peng Z, He Y, Chen L, Pan Q, Fang D, Chen W, Qian C, Bian X, Wang R: Ascl2 knockdown results in tumor growth arrest by miRNA-302b-related inhibition of colon cancer progenitor cells. PloS one 2012, 7:e32170.
  • [31]Roose J: Synergy between tumor suppressor APC and the -catenin-Tcf4 target Tcf1. Science 1999, 285:1923-26.
  • [32]Waterman ML: Lymphoid enhancer factor/T cell factor expression in colorectal cancer. Cancer Metastasis Rev 2004, 23:41-52.
  • [33]Nakamura T, Yamazaki Y, Hatano Y, Miura I: NUP98 is fused to PMX1 homeobox gene in human acute myelogenous leukemia with chromosome translocation t(1;11)(q23;p15). Blood 1999, 94:741-7.
  • [34]Moussa O, Turner DP, Feldman RJ, Sementchenko VI, McCarragher BD, Desouki MM, Fraig M, Watson DK: PDEF is a negative regulator of colon cancer cell growth and migration. J Cell Biochem 2009, 108:1389-98.
  • [35]Steffan JJ, Koul HK: Prostate derived ETS factor (PDEF): a putative tumor metastasis suppressor. Cancer letters 2011, 310:109-17.
  • [36]Benjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 1995, 57:289-300.
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