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Interferon-inducible guanylate binding protein (GBP2) is associated with better prognosis in breast cancer and indicates an efficient T cell response

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Abstract

Background

Recently, interferon-inducible guanylate binding protein (GBP2) has been discussed as a possible control factor in tumor development, which is controlled by p53, and inhibits NF-Kappa B and Rac protein as well as expression of matrix metalloproteinase 9. However, the potential role that GBP2 plays in tumor development and prognosis has not yet been studied.

Methods

We analyzed whether GBP2 mRNA levels are associated with metastasis-free interval in 766 patients with node negative breast carcinomas who did not receive systemic chemotherapy. Furthermore, response to anthracycline-based chemotherapy was studied in 768 breast cancer patients.

Results

High expression of GBP2 in breast carcinomas was associated with better prognosis in the univariate (P < 0.001, hazard ratio 0.763, 95 % CI 0.650–0.896) as well as in the multivariate Cox analysis (P = 0.008, hazard ratio 0.731, 95 % CI 0.580–0.920) adjusted to the established clinical factors age, pT stage, grading, hormone and ERBB2 receptor status. The association was particularly strong in subgroups with high proliferation and positive estrogen receptor status but did not reach significance in carcinomas with low expression of proliferation associated genes. Besides its prognostic capacity, GBP2 also predicted pathologically complete response to anthracycline-based chemotherapy (P = 0.0037, odds ratio 1.39, 95 % CI 1.11–1.74). Interestingly, GBP2 correlated with a recently established T cell signature, indicating tumor infiltration with T cells (R = 0.607, P < 0.001).

Conclusion

GBP2 is associated with better prognosis in fast proliferating tumors and probably represents a marker of an efficient T cell response.

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References

  1. Traver MK, Henry SC, Cantillana V, Oliver T, Hunn JP, Howard JC, et al. Immunity-related GTPase M (IRGM) proteins influence the localization of guanylate-binding protein 2 (GBP2) by modulating macroautophagy. J Biol Chem. 2011;286(35):30471–80.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  2. Balasubramanian S, Fan M, Messmer-Blust AF, Yang CH, Trendel JA, Jeyaratnam JA, et al. The interferon-gamma-induced GTPase, mGBP-2, inhibits tumor necrosis factor alpha (TNF-alpha) induction of matrix metalloproteinase-9 (MMP-9) by inhibiting NF-kappaB and Rac protein. J Biol Chem. 2011;286(22):20054–64.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. Abdullah N, Balakumari M, Sau AK. Dimerization and its role in GMP formation by human guanylate binding proteins. Biophys J. 2010;99(7):2235–44.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  4. Messmer-Blust AF, Balasubramanian S, Gorbacheva VY, Jeyaratnam JA, Vestal DJ. The interferon-gamma-induced murine guanylate-binding protein-2 inhibits rac activation during cell spreading on fibronectin and after platelet-derived growth factor treatment: role for phosphatidylinositol 3-kinase. Mol Biol Cell. 2010;21(14):2514–28.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Freeman WM, Bixler GV, Brucklacher RM, Lin CM, Patel KM, VanGuilder HD, et al. A multistep validation process of biomarkers for preclinical drug development. Pharmacogenomics J. 2010;10(5):385–95.

    Article  CAS  PubMed  Google Scholar 

  6. Kobayashi S, Nagano H, Marubashi S, Hama N, Eguchi TA, Takeda Y, et al. Guanylate-binding protein 2 mRNA in peripheral blood leukocytes of liver transplant recipients as a marker for acute cellular rejection. Transpl Int. 2010;23(4):390–6.

    Article  CAS  PubMed  Google Scholar 

  7. Guimaraes DP, Oliveira IM, de Moraes E, Paiva GR, Souza DM, Barnas C, et al. Interferon-inducible guanylate binding protein (GBP)-2: a novel p53-regulated tumor marker in esophageal squamous cell carcinomas. Int J Cancer. 2009;124(2):272–9.

    Article  CAS  PubMed  Google Scholar 

  8. Wei L, Fan M, Xu L, Heinrich K, Berry MW, Homayouni R, et al. Bioinformatic analysis reveals cRel as a regulator of a subset of interferon-stimulated genes. J Interferon Cytokine Res. 2008;28(9):541–51.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Kresse A, Konermann C, Degrandi D, Beuter-Gunia C, Wuerthner J, Pfeffer K, et al. Analyses of murine GBP homology clusters based on in silico, in vitro and in vivo studies. BMC Genomics. 2008;9:158.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Ma G, Huang J, Sun N, Liu X, Zhu M, Wu Z, et al. Molecular characterization of the porcine GBP1 and GBP2 genes. Mol Immunol. 2008;45(10):2797–807.

    Article  CAS  PubMed  Google Scholar 

  11. MacMicking JD. IFN-inducible GTPases and immunity to intracellular pathogens. Trends Immunol. 2004;25(11):601–9.

    Article  CAS  PubMed  Google Scholar 

  12. Vestal DJ, Buss JE, McKercher SR, Jenkins NA, Copeland NG, Kelner GS, et al. Murine GBP-2: a new IFN-gamma-induced member of the GBP family of GTPases isolated from macrophages. J Interferon Cytokine Res. 1998;18(11):977–85.

    CAS  PubMed  Google Scholar 

  13. Gorbacheva VY, Lindner D, Sen GC, Vestal DJ. The interferon (IFN)-induced GTPase, mGBP-2. Role in IFN-gamma-induced murine fibroblast proliferation. J Biol Chem. 2002;277(8):6080–7.

    Article  CAS  PubMed  Google Scholar 

  14. Cheng YS, Colonno RJ, Yin FH. Interferon induction of fibroblast proteins with guanylate binding activity. J Biol Chem. 1983;258(12):7746–50.

    CAS  PubMed  Google Scholar 

  15. Cheng YS, Becker-Manley MF, Chow TP, Horan DC. Affinity purification of an interferon-induced human guanylate-binding protein and its characterization. J Biol Chem. 1985;260(29):15834–9.

    CAS  PubMed  Google Scholar 

  16. Giampieri S, Manning C, Hooper S, Jones L, Hill CS, Sahai E. Localized and reversible TGFbeta signalling switches breast cancer cells from cohesive to single cell motility. Nat Cell Biol. 2009;11(11):1287–96.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Ramsauer K, Farlik M, Zupkovitz G, Seiser C, Kroger A, Hauser H, et al. Distinct modes of action applied by transcription factors STAT1 and IRF1 to initiate transcription of the IFN-gamma-inducible gbp2 gene. Proc Natl Acad Sci USA. 2007;104(8):2849–54.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Schmidt M, Hasenclever D, Schaeffer M, Boehm D, Cotarelo C, Steiner E, et al. Prognostic effect of epithelial cell adhesion molecule overexpression in untreated node-negative breast cancer. Clin Cancer Res. 2008;14(18):5849–55.

    Article  CAS  PubMed  Google Scholar 

  19. Schmidt M, Bohm D, von Torne C, Steiner E, Puhl A, Pilch H, et al. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer Res. 2008;68(13):5405–13.

    Article  CAS  PubMed  Google Scholar 

  20. Schmidt M, Petry IB, Bohm D, Lebrecht A, von Torne C, Gebhard S, et al. Ep-CAM RNA expression predicts metastasis-free survival in three cohorts of untreated node-negative breast cancer. Breast Cancer Res Treat. 2011;125(3):637–46.

    Article  CAS  PubMed  Google Scholar 

  21. Schmidt M, Hellwig B, Hammad S, Othman A, Lohr M, Chen Z, et al. A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin kappa C as a compatible prognostic marker in human solid tumors. Clin Cancer Res. 2012;18(9):2695–703.

    Article  CAS  PubMed  Google Scholar 

  22. Cadenas C, Franckenstein D, Schmidt M, Gehrmann M, Hermes M, Geppert B, et al. Role of thioredoxin reductase 1 and thioredoxin interacting protein in prognosis of breast cancer. Breast Cancer Res. 2010;12(3):R44.

    Article  PubMed Central  PubMed  Google Scholar 

  23. Hellwig B, Hengstler JG, Schmidt M, Gehrmann MC, Schormann W, Rahnenfuhrer J. Comparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of high-scoring genes. BMC Bioinforma. 2010;11:276.

    Article  Google Scholar 

  24. Lee JH, Jung C, Javadian-Elyaderani P, Schweyer S, Schutte D, Shoukier M, et al. Pathways of proliferation and antiapoptosis driven in breast cancer stem cells by stem cell protein piwil2. Cancer Res. 2010;70(11):4569–79.

    Article  CAS  PubMed  Google Scholar 

  25. Petry IB, Fieber E, Schmidt M, Gehrmann M, Gebhard S, Hermes M, et al. ERBB2 induces an antiapoptotic expression pattern of Bcl-2 family members in node-negative breast cancer. Clin Cancer Res. 2010;16(2):451–60.

    Article  CAS  PubMed  Google Scholar 

  26. Brase JC, Schmidt M, Fischbach T, Sultmann H, Bojar H, Koelbl H, et al. ERBB2 and TOP2A in breast cancer: a comprehensive analysis of gene amplification, RNA levels, and protein expression and their influence on prognosis and prediction. Clin Cancer Res. 2010;16(8):2391–401.

    Article  CAS  PubMed  Google Scholar 

  27. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005;365(9460):671–9.

    Article  CAS  PubMed  Google Scholar 

  28. Yu JX, Sieuwerts AM, Zhang Y, Martens JW, Smid M, Klijn JG, et al. Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer. BMC Cancer. 2007;7:182.

    Article  PubMed Central  PubMed  Google Scholar 

  29. Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B, et al. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin Cancer Res. 2007;13(11):3207–14.

    Article  CAS  PubMed  Google Scholar 

  30. Loi S, Haibe-Kains B, Desmedt C, Lallemand F, Tutt AM, Gillet C, et al. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J Clin Oncol. 2007;25(10):1239–46.

    Article  CAS  PubMed  Google Scholar 

  31. Popovici V, Chen W, Gallas BG, Hatzis C, Shi W, Samuelson FW, et al. Effect of training-sample size and classification difficulty on the accuracy of genomic predictors. Breast Cancer Res. 2010;12(1):R5.

    Article  PubMed Central  PubMed  Google Scholar 

  32. Tabchy A, Valero V, Vidaurre T, Lluch A, Gomez H, Martin M, et al. Evaluation of a 30-gene paclitaxel, fluorouracil, doxorubicin, and cyclophosphamide chemotherapy response predictor in a multicenter randomized trial in breast cancer. Clin Cancer Res. 2010;16(21):5351–61.

    Article  CAS  PubMed  Google Scholar 

  33. Bonnefoi H, Potti A, Delorenzi M, Mauriac L, Campone M, Tubiana-Hulin M, et al. Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial. Lancet Oncol. 2007;8(12):1071–8.

    Article  CAS  PubMed  Google Scholar 

  34. Li Y, Zou L, Li Q, Haibe-Kains B, Tian R, Li Y, et al. Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer. Nat Med. 2010;16(2):214–8.

    Article  PubMed Central  PubMed  Google Scholar 

  35. Iwamoto T, Bianchini G, Booser D, Qi Y, Coutant C, Shiang CY, et al. Gene pathways associated with prognosis and chemotherapy sensitivity in molecular subtypes of breast cancer. J Natl Cancer Inst. 2011;103(3):264–72.

    Article  CAS  PubMed  Google Scholar 

  36. Desmedt C, Haibe-Kains B, Wirapati P, Buyse M, Larsimont D, Bontempi G, et al. Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res. 2008;14(16):5158–65.

    Article  CAS  PubMed  Google Scholar 

  37. Micke P, Basrai M, Faldum A, Bittinger F, Ronnstrand L, Blaukat A, et al. Characterization of c-kit expression in small cell lung cancer: prognostic and therapeutic implications. Clin Cancer Res. 2003;9(1):188–94.

    CAS  PubMed  Google Scholar 

  38. Steiner E, Pollow K, Hasenclever D, Schormann W, Hermes M, Schmidt M, et al. Role of urokinase-type plasminogen activator (uPA) and plasminogen activator inhibitor type 1 (PAI-1) for prognosis in endometrial cancer. Gynecol Oncol. 2008;108(3):569–76.

    Article  CAS  PubMed  Google Scholar 

  39. Tanner B, Hasenclever D, Stern K, Schormann W, Bezler M, Hermes M, et al. ErbB-3 predicts survival in ovarian cancer. J Clin Oncol. 2006;24(26):4317–23.

    Article  CAS  PubMed  Google Scholar 

  40. Hengstler JG, Lange J, Kett A, Dornhofer N, Meinert R, Arand M, et al. Contribution of c-erbB-2 and topoisomerase IIalpha to chemoresistance in ovarian cancer. Cancer Res. 1999;59(13):3206–14.

    CAS  PubMed  Google Scholar 

  41. Schmidt M, Hengstler JG, von Torne C, Koelbl H, Gehrmann MC. Coordinates in the universe of node-negative breast cancer revisited. Cancer Res. 2009;69(7):2695–8.

    Article  CAS  PubMed  Google Scholar 

  42. Schmidt M, Victor A, Bratzel D, Boehm D, Cotarelo C, Lebrecht A, et al. Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer—comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial. Ann Oncol. 2009;20(2):258–64.

    Article  CAS  PubMed  Google Scholar 

  43. Schmidt M, Gehrmann M, Hengstler JG, Koelbl H. New prognostic and predictive factors in breast cancer. Minerva Ginecol. 2010;62(6):599–611.

    CAS  PubMed  Google Scholar 

  44. Shedden K, Xie XT, Chandaroy P, Chang YT, Rosania GR. Expulsion of small molecules in vesicles shed by cancer cells: association with gene expression and chemosensitivity profiles. Cancer Res. 2003;63(15):4331–7.

    CAS  PubMed  Google Scholar 

  45. Raponi M, Zhang Y, Yu J, Chen G, Lee G, Taylor JM, et al. Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung. Cancer Res. 2006;66(15):7466–72.

    Article  CAS  PubMed  Google Scholar 

  46. Bild AH, Potti A, Nevins JR. Linking oncogenic pathways with therapeutic opportunities. Nat Rev. 2006;6(9):735–41.

    Article  CAS  Google Scholar 

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Acknowledgments

This study was supported by the German Federal Ministry of Education and Research (BMBF) funded National Genome Research Network (NGFN) project Oncoprofile. We thank Ms. Silke Hankinson and Ms. Susanne Lindemann for excellent bibliographical support.

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Authors and Affiliations

  1. Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 76, 44139, Dortmund, Germany

    Patricio Godoy, Cristina Cadenas, Rosemarie Marchan, Joanna Stewart, Raymond Reif & Jan G. Hengstler

  2. Fakultät Statistik, Technische Universität Dortmund, Mathematikgeb., Raum 713, 44221, Dortmund, Germany

    Birte Hellwig, Miriam Lohr & Jörg Rahnenführer

  3. Bayer Technology Services GmbH, BTS-PT-AS-AT, Leverkusen, Germany

    Matthias Gehrmann

  4. Department of Gynaecology, University of Mainz, Mainz, Germany

    Markus Schmidt

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  1. Patricio Godoy
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  2. Cristina Cadenas
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  3. Birte Hellwig
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  11. Jan G. Hengstler
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Correspondence to Patricio Godoy.

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M. Schmidt and J.G. Hengstler contributed equally as senior authors.

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Godoy, P., Cadenas, C., Hellwig, B. et al. Interferon-inducible guanylate binding protein (GBP2) is associated with better prognosis in breast cancer and indicates an efficient T cell response. Breast Cancer 21, 491–499 (2014). https://doi.org/10.1007/s12282-012-0404-8

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