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Breast Cancer Research and Treatment

, Volume 131, Issue 3, pp 765–775 | Cite as

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

  • Pascal Jézéquel
  • Mario Campone
  • Wilfried Gouraud
  • Catherine Guérin-Charbonnel
  • Christophe Leux
  • Gabriel Ricolleau
  • Loïc Campion
Preclinical Study

Abstract

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.

Keywords

Prognostic analysis Breast cancer Genomic data Molecular subtype Web tool 

Abbreviations

AE

Any event

AOL

Adjuvant! Online

AR

Any relapse

D

Death

ER

Oestrogen receptor

GEO

Gene expression omnibus

GES

Gene-expression signature

IHC

Immunohistochemistry

MR

Metastatic relapse

MRD

Metastatic relapse or death

MSP

Molecular subtype predictor

N

Nodal

NPI

Nottingham prognostic index

RMSPC

Robust molecular subtype predictor classification

RSCMC

Robust subtype clustering model classification

RSSPC

Robust single sample predictor classification

SCM

Subtype clustering model

SSP

Single sample predictor

Notes

Acknowledgments

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.

Conflict of interest

None.

Supplementary material

10549_2011_1457_MOESM1_ESM.pdf (1.1 mb)
(PDF 1081 kb)

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Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  • Pascal Jézéquel
    • 1
    • 2
  • Mario Campone
    • 3
    • 4
  • Wilfried Gouraud
    • 1
    • 4
    • 5
  • Catherine Guérin-Charbonnel
    • 1
    • 4
    • 5
  • Christophe Leux
    • 6
  • Gabriel Ricolleau
    • 2
  • Loïc Campion
    • 4
    • 5
  1. 1.Unité Mixte de Génomique du CancerHôpital Laënnec, Bd J. MonodNantes-Saint Herblain CedexFrance
  2. 2.Département de Biologie OncologiqueCentre de Lutte Contre le Cancer René Gauducheau, Bd J. MonodNantes-Saint Herblain CedexFrance
  3. 3.Service d’Oncologie MédicaleCentre de Lutte Contre le Cancer René Gauducheau, Bd J. MonodNantes-Saint Herblain CedexFrance
  4. 4.INSERM U892, IRT-UNNantes CedexFrance
  5. 5.Unité de BiostatistiqueCentre de Lutte Contre le Cancer René Gauducheau, Bd J. MonodNantes-Saint Herblain CedexFrance
  6. 6.Service d’épidémiologie et de BiostatistiquesPôle d’information Médicale, d’évaluation et de Santé Publique, Hôpital Saint Jacques, CHU NantesNantesFrance

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