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bc-GenExMiner: an easy-to-use online platform for gene prognostic analyses in breast cancer

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Gene prognostic meta-analyses should benefit from breast tumour genomic data obtained during the last decade. The aim was to develop a user-friendly, web-based application, based on DNA microarrays results, called “breast cancer Gene-Expression Miner” (bc-GenExMiner) to improve gene prognostic analysis performance by using the same bioinformatics process. bc-GenExMiner was developed as a web-based tool including a MySQL relational database. Survival analyses are performed with R statistical software and packages. Molecular subtyping was performed by means of three single sample predictors (SSPs) and three subtype clustering models (SCMs). Twenty-one public data sets have been included. Among the 3,414 recovered breast cancer patients, 1,209 experienced a pejorative event. Molecular subtyping by means of three SSPs and three SCMs was performed for 3,063 patients. Furthermore, three robust lists of stable subtyped patients were built to maximize reliability of molecular assignment. Gene prognostic analyses are done by means of univariate Cox proportional hazards model and may be conducted on cohorts split by nodal (N), oestrogen receptor (ER), or molecular subtype status. To evaluate independent prognostic impact of genes relative to Nottingham Prognostic Index and Adjuvant! Online, adjusted Cox proportional hazards models are performed. bc-GenExMiner allows researchers without specific computation skills to easily and quickly evaluate the in vivo prognostic role of genes in breast cancer by means of Cox proportional hazards model on large pooled cohorts, which may be split according to different prognostic parameters: N, ER, and molecular subtype. Prognostic analyses by molecular subtype may also be performed in three robust molecular subtype classifications.

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Any event


Adjuvant! Online


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Gene expression omnibus


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Molecular subtype predictor




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Robust molecular subtype predictor classification


Robust subtype clustering model classification


Robust single sample predictor classification


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Single sample predictor


  1. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lønning PE, Børresen-Dale AL, Brown PO, Botstein D (2000) Molecular portraits of human breast tumours. Nature 406:747–752

    Article  PubMed  CAS  Google Scholar 

  2. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Eystein Lønning P, Børresen-Dale AL (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98:10869–10874

    Article  PubMed  CAS  Google Scholar 

  3. Brenton JD, Carey LA, Ahmed AA, Caldas C (2005) Molecular classification and molecular forecasting of breast cancer: ready for clinical application? J Clin Oncol 23:7350–7360

    Article  PubMed  CAS  Google Scholar 

  4. R Development Core Team (2009) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  5. Lumley T (2006) rmeta: Meta-analysis. R package version 2.14.

  6. Therneau T and original R port by Thomas Lumley (2009) Survival: Survival analysis, including penalised likelihood. R package version 2.35-4.

  7. Edgar R, Domrachev M, Lash AE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30:207–210

    Article  PubMed  CAS  Google Scholar 

  8. Parkinson H, Kapushensky M, Kolesnikov N, Rustici G, Shojatalab M, Abeygunawardena N, Berube H, Dylag M, Emam I, Farne A, Holloway E, Lukk M, Malone J, Mani R, Pilicheva E, Rayner TF, Rezwan F, Sharma A, Williams E, Bradley XZ, Adamusiak T, Brandizi M, Burdett T, Coulson R, Krestyaninova M, Kurnosov P, Maguire E, Neogi SG, Rocca-Serra P, Sansone SA, Sklyar N, Zhao M, Sarkans U, Brazma A (2009) ArrayExpress update—from an archive of functional genomics experiments to the atlas of gene expression. Nucleic Acids Res 37(Database Issue):D868–D872

    Article  PubMed  CAS  Google Scholar 

  9. Hubble J, Demeter J, Jin H, Mao M, Nitzberg M, Reddy TB, Wymore F, Zachariah ZK, Sherlock G, Ball CA (2009) Implementation of GenePattern within the Stanford Microarray Database. Nucleic Acids Res 37(Database Issue):D898–D901

    Article  PubMed  CAS  Google Scholar 

  10. Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA, Booser D, Theriault RL, Buzdar AU, Dempsey PJ, Rouzier R, Sneige N, Ross JS, Vidaurre T, Gomez HL, Hortobagyi GN, Pusztai L (2006) Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol 24:4236–4244

    Article  PubMed  CAS  Google Scholar 

  11. Shabalin AA, Tjelmeland H, Fan C, Perou CM, Nobel AB (2008) Merging two gene-expression studies via cross-platform normalization. Bioinformatics 24:1154–1160

    Article  PubMed  CAS  Google Scholar 

  12. Weigelt B, Mackay A, A’hern R, Natrajan R, Tan DS, Dowsett M, Ashworth A, Reis-Filho JS (2010) Breast cancer molecular profiling with single sample predictors: a retrospective analysis. Lancet Oncol 11:339–349

    Article  PubMed  CAS  Google Scholar 

  13. Sorlie T, Tibshirani R, Parker J, Hasties T, Marron JS, Nobel A, Deng S, Johnsen H, Pesich R, Geisler S, Demeter J, Perou CM, Lonning PE, Brown PO, Borresen-Dale AL, Botstein D (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100:8418–8423

    Article  PubMed  CAS  Google Scholar 

  14. Hu Z, Fan C, Oh DS, Marron JS, He X, Qaqish BF, Livasy C, Carey LA, Reynolds E, Dressler L, Nobel A, Parker J, Ewend MG, Sawyer LR, Wu J, Liu Y, Nanda R, Tretiakova M, Ruiz Orrico A, Dreher D, Palazzo JP, Perreard L, Nelson E, Mone M, Hansen H, Mullins M, Quackenbush JF, Ellis MJ, Olopade OI, Bernard PS, Perou CM (2006) The molecular portraits of breast tumors are conserved across microarray platform. BMC Genomics 7:96

    Article  PubMed  Google Scholar 

  15. Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z, Quackenbush JF, Stijleman IJ, Palazzo J, Marron JS, Nobel AB, Mardis E, Nielsen TO, Ellis MJ, Perou CM, Bernard PS (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27:1160–1167

    Article  PubMed  Google Scholar 

  16. Haibe-Kains B, Bontempi G, Quackenbush JF et al (2010) genefu: Relevant functions for gene expression analysis, especially in breast cancer. R package version 1.0.9.

  17. Desmedt C, Haibe-Kains B, Wirapati P, Buyse M, Larsimont D, Bontempi G, Delorenzi M, Piccart M, Sotiriou C (2008) Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 14:5158–5165

    Article  PubMed  CAS  Google Scholar 

  18. Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schütz F, Goldstein DR, Piccart M, Delorenzi M (2008) Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res 10:R65

    Article  PubMed  Google Scholar 

  19. Galea MH, Blamey RW, Elston CE, Ellis IO (1992) The Nottingham prognostic index in primary breast cancer. Breast Cancer Res Treat 22:207–219

    Article  PubMed  CAS  Google Scholar 

  20. Ravdin PM, Siminoff LA, Davis GJ, Mercer MB, Hewlett J, Gerson N, Parker HL (2001) Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 19:980–991

    PubMed  CAS  Google Scholar 

  21. Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20:37–46

    Article  Google Scholar 

  22. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    Article  PubMed  CAS  Google Scholar 

  23. Kauraniemi P, Kallioniemi A (2006) Activation of multiple cancer-associated genes at the ERBB2 amplicon in breast cancer. Endocr Relat Cancer 13:39–49

    Article  PubMed  CAS  Google Scholar 

  24. Charafe-Jauffret E, Ginestier C, Monville F, Finetti P, Adélaïde J, Cervera N, Fekairi S, Xerri L, Jacquemier J, Birnbaum D, Bertucci F (2006) Gene expression profiling of breast cancer cell lines identifies new basal markers. Oncogene 25:2273–2284

    Article  PubMed  CAS  Google Scholar 

  25. Urban P, Vuaroqueaux V, Labuhn M, Delorenzi M, Wirapati P, Wight E, Senn HJ, Benz C, Eppenberger U, Eppenberger-Castori S (2006) Increased expression of urokinase-type plasminogen activator mRNA determines adverse prognosis in ErbB2-positive primary breast cancer. J Clin Oncol 24:4245–4253

    Article  PubMed  CAS  Google Scholar 

  26. Bild AH, Parker JS, Gustafson AM, Acharya CR, Hoadley KA, Anders C, Marcorn PK, Carey LA, Potti A, Nevins JR, Perou CM (2009) An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer. Breast Cancer Res 11:R55

    Article  PubMed  Google Scholar 

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This study was supported by SANOFI-AVENTIS-France, PFIZER-France and GSK. These pharmaceutical companies did not have any role in the design of this study, or in the preparation of this manuscript. We thank Franck Poiron for technical assistance. We are grateful to Pascale Hillard for English revision of this manuscript.

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Correspondence to Pascal Jézéquel.

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Jézéquel, P., Campone, M., Gouraud, W. et al. bc-GenExMiner: an easy-to-use online platform for gene prognostic analyses in breast cancer. Breast Cancer Res Treat 131, 765–775 (2012).

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