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Breast Cancer Research and Treatment

, Volume 157, Issue 2, pp 329–338 | Cite as

Plasma S100P level as a novel prognostic marker of metastatic breast cancer

  • Cike PengEmail author
  • Hongda Chen
  • Markus Wallwiener
  • Caroline Modugno
  • Katarina Cuk
  • Dharanija Madhavan
  • Andreas Trumpp
  • Jörg Heil
  • Frederik Marmé
  • Juliane Nees
  • Sabine Riethdorf
  • Sarah Schott
  • Christof Sohn
  • Klaus Pantel
  • Andreas Schneeweiss
  • Rongxi Yang
  • Barbara Burwinkel
Epidemiology

Abstract

Metastasis is the main cause of death in breast cancer patients. The development of reliable and cost-effective biomarker to evaluate the prognosis of metastatic breast cancer (MBC) patients is of great importance. S100P is a member of S100 family and has been proved to be associated with metastasis establishment. Methods: We investigated the plasma S100P levels in 60 healthy controls, 48 primary and 273 metastatic breast cancer patients. The MBC patients were followed-up for disease progression and death up to 3.5 years after recruitment. Radiographic response of MBC patients were also analyzed for investigation on treatment monitoring value of plasma S100P level. We found a robust association between high plasma S100P level (>7 ng/mL) and poor prognosis of metastatic breast cancer (MBC) patients (median progression-free survival time: 5.0 vs. 8.7 months, log-rank test p < 0.001; median overall survival time: 22.5 vs. 31.6 months, log-rank test p < 0.001). The plasma S100P level added additional prognostic relevance to the conventional prognostication model with clinicopathological factors and CTC enumeration. The plasma S100P level decreased significantly after treatment, while the reduction correlated with the radiographic response of the MBC patients. This finding indicates the value of plasma S100P in dynamic evaluation of treatment outcome. We hereby suggest plasma S100P level as a simple and cost-effective marker for the prognosis of metastatic breast cancer.

Keywords

Metastatic breast cancer S100P Prognosis Plasma Biomarker 

Notes

Acknowledgments

This study was funded and supported by the Dietmar-Hopp Foundation, the University Hospital of Heidelberg, the Helmholtz Society, the German Cancer Research Center (DKFZ), Heidelberg, Germany, and the National Center for Tumor Diseases, Heidelberg, Germany (IFP-Project I.2). Cike Peng is funded by China Scholarship Council (CSC) for a 4-year PhD program.

Compliance with ethical standards

Conflict of interest

Cike Peng, Andreas Schneeweiss, Rongxi Yang, and Barbara Burwinkel are inventors of a provisional patent application relating to the subject matter of this manuscript and therefore declare a potential conflict of interests.

Supplementary material

10549_2016_3776_MOESM1_ESM.docx (15 kb)
Supplementary material 1 (DOCX 15 kb)

References

  1. 1.
    Giordano A, Cristofanilli M (2012) CTCs in metastatic breast cancer. Recent Results Cancer Res (Fortschritte der Krebsforschung Progres dans les recherches sur le cancer) 195:193–201. doi: 10.1007/978-3-642-28160-0_18
  2. 2.
    Jabbour MN, Massad CY, Boulos FI (2012) Variability in hormone and growth factor receptor expression in primary versus recurrent, metastatic, and post-neoadjuvant breast carcinoma. Breast Cancer Res Treat 135(1):29–37. doi: 10.1007/s10549-012-2047-z CrossRefPubMedGoogle Scholar
  3. 3.
    Baccelli I, Schneeweiss A, Riethdorf S, Stenzinger A, Schillert A, Vogel V, Klein C, Saini M, Bauerle T, Wallwiener M, Holland-Letz T, Hofner T, Sprick M, Scharpff M, Marme F, Sinn HP, Pantel K, Weichert W, Trumpp A (2013) Identification of a population of blood circulating tumor cells from breast cancer patients that initiates metastasis in a xenograft assay. Nat Biotechnol 31(6):539–544. doi: 10.1038/nbt.2576 CrossRefPubMedGoogle Scholar
  4. 4.
    Wallwiener M, Hartkopf AD, Baccelli I, Riethdorf S, Schott S, Pantel K, Marme F, Sohn C, Trumpp A, Rack B, Aktas B, Solomayer EF, Muller V, Janni W, Schneeweiss A, Fehm TN (2013) The prognostic impact of circulating tumor cells in subtypes of metastatic breast cancer. Breast Cancer Res Treat 137(2):503–510. doi: 10.1007/s10549-012-2382-0 CrossRefPubMedGoogle Scholar
  5. 5.
    Bidard FC, Peeters DJ, Fehm T, Nole F, Gisbert-Criado R, Mavroudis D, Grisanti S, Generali D, Garcia-Saenz JA, Stebbing J, Caldas C, Gazzaniga P, Manso L, Zamarchi R, de Lascoiti AF, De Mattos-Arruda L, Ignatiadis M, Lebofsky R, van Laere SJ, Meier-Stiegen F, Sandri MT, Vidal-Martinez J, Politaki E, Consoli F, Bottini A, Diaz-Rubio E, Krell J, Dawson SJ, Raimondi C, Rutten A, Janni W, Munzone E, Caranana V, Agelaki S, Almici C, Dirix L, Solomayer EF, Zorzino L, Johannes H, Reis-Filho JS, Pantel K, Pierga JY, Michiels S (2014) Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data. Lancet Oncol 15(4):406–414. doi: 10.1016/S1470-2045(14)70069-5 CrossRefPubMedGoogle Scholar
  6. 6.
    Riethdorf S, Wikman H, Pantel K (2008) Review: biological relevance of disseminated tumor cells in cancer patients. Int J Cancer 123(9):1991–2006. doi: 10.1002/ijc.23825 CrossRefPubMedGoogle Scholar
  7. 7.
    Lianidou ES, Markou A (2011) Circulating tumor cells in breast cancer: detection systems, molecular characterization, and future challenges. Clin Chem 57(9):1242–1255. doi: 10.1373/clinchem.2011.165068 CrossRefPubMedGoogle Scholar
  8. 8.
    FDA (2004) CellSearch™ Epithelial Cell Kit/CellSpotter™ Analyzer—K031588Google Scholar
  9. 9.
    Pantel K, Alix-Panabieres C (2010) Circulating tumour cells in cancer patients: challenges and perspectives. Trends Mol Med 16(9):398–406. doi: 10.1016/j.molmed.2010.07.001 CrossRefPubMedGoogle Scholar
  10. 10.
    Mani SA, Guo W, Liao MJ, Eaton EN, Ayyanan A, Zhou AY, Brooks M, Reinhard F, Zhang CC, Shipitsin M, Campbell LL, Polyak K, Brisken C, Yang J, Weinberg RA (2008) The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell 133(4):704–715. doi: 10.1016/j.cell.2008.03.027 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Ota I, Li XY, Hu Y, Weiss SJ (2009) Induction of a MT1-MMP and MT2-MMP-dependent basement membrane transmigration program in cancer cells by Snail1. Proc Natl Acad Sci USA 106(48):20318–20323. doi: 10.1073/pnas.0910962106 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Bonnomet A, Brysse A, Tachsidis A, Waltham M, Thompson EW, Polette M, Gilles C (2010) Epithelial-to-mesenchymal transitions and circulating tumor cells. J Mammary Gland Biol Neoplasia 15(2):261–273. doi: 10.1007/s10911-010-9174-0 CrossRefPubMedGoogle Scholar
  13. 13.
    Muller V, Riethdorf S, Rack B, Janni W, Fasching PA, Solomayer E, Aktas B, Kasimir-Bauer S, Pantel K, Fehm T, Group Ds (2012) Prognostic impact of circulating tumor cells assessed with the Cell Search System and AdnaTest Breast in metastatic breast cancer patients: the DETECT study. Breast Cancer Res 14(4):R118. doi: 10.1186/bcr3243 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Jiang H, Hu H, Tong X, Jiang Q, Zhu H, Zhang S (2012) Calcium-binding protein S100P and cancer: mechanisms and clinical relevance. J Cancer Res Clin Oncol 138(1):1–9. doi: 10.1007/s00432-011-1062-5 CrossRefPubMedGoogle Scholar
  15. 15.
    Hartman KG, McKnight LE, Liriano MA, Weber DJ (2013) The evolution of S100B inhibitors for the treatment of malignant melanoma. Future Med Chem 5(1):97–109. doi: 10.4155/fmc.12.191 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Arumugam T, Logsdon CD (2011) S100P: a novel therapeutic target for cancer. Amino Acids 41(4):893–899. doi: 10.1007/s00726-010-0496-4 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Parkkila S, Pan PW, Ward A, Gibadulinova A, Oveckova I, Pastorekova S, Pastorek J, Martinez AR, Helin HO, Isola J (2008) The calcium-binding protein S100P in normal and malignant human tissues. BMC Clin Pathol 8:2. doi: 10.1186/1472-6890-8-2 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Guerreiro Da Silva ID, Hu YF, Russo IH, Ao X, Salicioni AM, Yang X, Russo J (2000) S100P calcium-binding protein overexpression is associated with immortalization of human breast epithelial cells in vitro and early stages of breast cancer development in vivo. Int J Oncol 16(2):231–240PubMedGoogle Scholar
  19. 19.
    Beer DG, Kardia SL, Huang CC, Giordano TJ, Levin AM, Misek DE, Lin L, Chen G, Gharib TG, Thomas DG, Lizyness ML, Kuick R, Hayasaka S, Taylor JM, Iannettoni MD, Orringer MB, Hanash S (2002) Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med 8(8):816–824. doi: 10.1038/nm733 PubMedGoogle Scholar
  20. 20.
    Wang G, Platt-Higgins A, Carroll J, de Silva Rudland S, Winstanley J, Barraclough R, Rudland PS (2006) Induction of metastasis by S100P in a rat mammary model and its association with poor survival of breast cancer patients. Cancer Res 66(2):1199–1207. doi: 10.1158/0008-5472.CAN-05-2605 CrossRefPubMedGoogle Scholar
  21. 21.
    Chandramouli A, Mercado-Pimentel ME, Hutchinson A, Gibadulinova A, Olson ER, Dickinson S, Shanas R, Davenport J, Owens J, Bhattacharyya AK, Regan JW, Pastorekova S, Arumugam T, Logsdon CD, Nelson MA (2010) The induction of S100p expression by the Prostaglandin E(2) (PGE(2))/EP4 receptor signaling pathway in colon cancer cells. Cancer Biol Ther 10(10):1056–1066. doi: 10.4161/cbt.10.10.13373 CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Ohuchida K, Mizumoto K, Egami T, Yamaguchi H, Fujii K, Konomi H, Nagai E, Yamaguchi K, Tsuneyoshi M, Tanaka M (2006) S100P is an early developmental marker of pancreatic carcinogenesis. Clin Cancer Res 12(18):5411–5416. doi: 10.1158/1078-0432.CCR-06-0298 CrossRefPubMedGoogle Scholar
  23. 23.
    Li Y, St John MA, Zhou X, Kim Y, Sinha U, Jordan RC, Eisele D, Abemayor E, Elashoff D, Park NH, Wong DT (2004) Salivary transcriptome diagnostics for oral cancer detection. Clin Cancer Res 10(24):8442–8450. doi: 10.1158/1078-0432.CCR-04-1167 CrossRefPubMedGoogle Scholar
  24. 24.
    Riethdorf S, Fritsche H, Muller V, Rau T, Schindlbeck C, Rack B, Janni W, Coith C, Beck K, Janicke F, Jackson S, Gornet T, Cristofanilli M, Pantel K (2007) Detection of circulating tumor cells in peripheral blood of patients with metastatic breast cancer: a validation study of the Cell Search system. Clin Cancer Res 13(3):920–928. doi: 10.1158/1078-0432.CCR-06-1695 CrossRefPubMedGoogle Scholar
  25. 25.
    Core R, Team RC (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  26. 26.
    Jp F, Rj G (1999) A proportional hazards model for the subdistribution of a competing risk. JASA 94:496–509CrossRefGoogle Scholar
  27. 27.
    Cristofanilli M, Budd GT, Ellis MJ, Stopeck A, Matera J, Miller MC, Reuben JM, Doyle GV, Allard WJ, Terstappen LW, Hayes DF (2004) Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med 351(8):781–791. doi: 10.1056/NEJMoa040766351/8/781 CrossRefPubMedGoogle Scholar
  28. 28.
    Beslija S, Bonneterre J, Burstein H, Cocquyt V, Gnant M, Goodwin P, Heinemann V, Jassem J, Kostler WJ, Krainer M, Menard S, Petit T, Petruzelka L, Possinger K, Schmid P, Stadtmauer E, Stockler M, Van Belle S, Vogel C, Wilcken N, Wiltschke C, Zielinski CC, Zwierzina H (2007) Second consensus on medical treatment of metastatic breast cancer. Ann Oncol 18(2):215–225. doi: 10.1093/annonc/mdl155 CrossRefPubMedGoogle Scholar
  29. 29.
    Colzani E, Liljegren A, Johansson AL, Adolfsson J, Hellborg H, Hall PF, Czene K (2011) Prognosis of patients with breast cancer: causes of death and effects of time since diagnosis, age, and tumor characteristics. J Clin Oncol 29(30):4014–4021. doi: 10.1200/JCO.2010.32.6462 CrossRefPubMedGoogle Scholar
  30. 30.
    Penumutchu SR, Chou RH, Yu C (2014) Structural insights into calcium-bound S100P and the V domain of the RAGE complex. PLoS One 9(8):e103947. doi: 10.1371/journal.pone.0103947 CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Mackay A, Jones C, Dexter T, Silva RL, Bulmer K, Jones A, Simpson P, Harris RA, Jat PS, Neville AM, Reis LF, Lakhani SR, O’Hare MJ (2003) cDNA microarray analysis of genes associated with ERBB2 (HER2/neu) overexpression in human mammary luminal epithelial cells. Oncogene 22(17):2680–2688. doi: 10.1038/sj.onc.1206349 CrossRefPubMedGoogle Scholar
  32. 32.
    Bulk E, Hascher A, Liersch R, Mesters RM, Diederichs S, Sargin B, Gerke V, Hotfilder M, Vormoor J, Berdel WE, Serve H, Muller-Tidow C (2008) Adjuvant therapy with small hairpin RNA interference prevents non-small cell lung cancer metastasis development in mice. Cancer Res 68(6):1896–1904. doi: 10.1158/0008-5472.CAN-07-2390 CrossRefPubMedGoogle Scholar
  33. 33.
    Mousses S, Bubendorf L, Wagner U, Hostetter G, Kononen J, Cornelison R, Goldberger N, Elkahloun AG, Willi N, Koivisto P, Ferhle W, Raffeld M, Sauter G, Kallioniemi OP (2002) Clinical validation of candidate genes associated with prostate cancer progression in the CWR22 model system using tissue microarrays. Cancer Res 62(5):1256–1260PubMedGoogle Scholar
  34. 34.
    Diederichs S, Bulk E, Steffen B, Ji P, Tickenbrock L, Lang K, Zanker KS, Metzger R, Schneider PM, Gerke V, Thomas M, Berdel WE, Serve H, Muller-Tidow C (2004) S100 family members and trypsinogens are predictors of distant metastasis and survival in early-stage non-small cell lung cancer. Cancer Res 64(16):5564–5569. doi: 10.1158/0008-5472.CAN-04-2004 CrossRefPubMedGoogle Scholar
  35. 35.
    Ding Q, Chang CJ, Xie X, Xia W, Yang JY, Wang SC, Wang Y, Xia J, Chen L, Cai C, Li H, Yen CJ, Kuo HP, Lee DF, Lang J, Huo L, Cheng X, Chen YJ, Li CW, Jeng LB, Hsu JL, Li LY, Tan A, Curley SA, Ellis LM, Dubois RN, Hung MC (2011) APOBEC3G promotes liver metastasis in an orthotopic mouse model of colorectal cancer and predicts human hepatic metastasis. J Clin Investig 121(11):4526–4536. doi: 10.1172/JCI45008 CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Mousses S, Wagner U, Chen Y, Kim JW, Bubendorf L, Bittner M, Pretlow T, Elkahloun AG, Trepel JB, Kallioniemi OP (2001) Failure of hormone therapy in prostate cancer involves systematic restoration of androgen responsive genes and activation of rapamycin sensitive signaling. Oncogene 20(46):6718–6723. doi: 10.1038/sj.onc.1204889 CrossRefPubMedGoogle Scholar
  37. 37.
    Wang Q, Zhang YN, Lin GL, Qiu HZ, Wu B, Wu HY, Zhao Y, Chen YJ, Lu CM (2012) S100P, a potential novel prognostic marker in colorectal cancer. Oncol Rep 28(1):303–310. doi: 10.3892/or.2012.1794 PubMedGoogle Scholar
  38. 38.
    Jiang L, Lai YK, Zhang J, Wang H, Lin MC, He ML, Kung HF (2011) Targeting S100P inhibits colon cancer growth and metastasis by Lentivirus-mediated RNA interference and proteomic analysis. Mol Med 17(7–8):709–716. doi: 10.2119/molmed.2011.00008 PubMedPubMedCentralGoogle Scholar
  39. 39.
    Wallwiener M, Riethdorf S, Hartkopf AD, Modugno C, Nees J, Madhavan D, Sprick MR, Schott S, Domschke C, Baccelli I, Schonfisch B, Burwinkel B, Marme F, Heil J, Sohn C, Pantel K, Trumpp A, Schneeweiss A (2014) Serial enumeration of circulating tumor cells predicts treatment response and prognosis in metastatic breast cancer: a prospective study in 393 patients. BMC Cancer 14:512. doi: 10.1186/1471-2407-14-512 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Cike Peng
    • 1
    • 2
    Email author
  • Hongda Chen
    • 3
  • Markus Wallwiener
    • 4
    • 5
  • Caroline Modugno
    • 4
    • 5
  • Katarina Cuk
    • 1
    • 2
  • Dharanija Madhavan
    • 1
    • 2
  • Andreas Trumpp
    • 6
    • 7
  • Jörg Heil
    • 4
  • Frederik Marmé
    • 4
  • Juliane Nees
    • 4
    • 5
  • Sabine Riethdorf
    • 8
  • Sarah Schott
    • 4
  • Christof Sohn
    • 4
  • Klaus Pantel
    • 8
  • Andreas Schneeweiss
    • 4
    • 5
  • Rongxi Yang
    • 1
    • 2
    • 9
  • Barbara Burwinkel
    • 1
    • 2
    • 9
  1. 1.Molecular EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
  2. 2.Molecular Biology of Breast Cancer, Department of Gynecology and ObstetricsUniversity of HeidelbergHeidelbergGermany
  3. 3.Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
  4. 4.Department of Gynecology and ObstetricsUniversity of HeidelbergHeidelbergGermany
  5. 5.National Center for Tumor DiseasesUniversity of HeidelbergHeidelbergGermany
  6. 6.Hi-STEM-Heidelberg Institute for Stem Cell Technology and Experimental Medicine, GmbHHeidelbergGermany
  7. 7.Division of Stem Cells and CancerGerman Cancer Research Center (DKFZ)HeidelbergGermany
  8. 8.Department of Tumor BiologyUniversity Hospital Hamburg-EppendorfHamburgGermany
  9. 9.Molecular Biology of Breast CancerUniversity Women’s Clinic University HeidelbergHeidelbergGermany

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