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

  • Preclinical Study
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Breast Cancer Research and Treatment Aims and scope Submit manuscript

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.

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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

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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.

Author information

Authors and Affiliations

  1. Unité Mixte de Génomique du Cancer, Hôpital Laënnec, Bd J. Monod, 44805, Nantes-Saint Herblain Cedex, France

    Pascal Jézéquel, Wilfried Gouraud & Catherine Guérin-Charbonnel

  2. Département de Biologie Oncologique, Centre de Lutte Contre le Cancer René Gauducheau, Bd J. Monod, 44805, Nantes-Saint Herblain Cedex, France

    Pascal Jézéquel & Gabriel Ricolleau

  3. Service d’Oncologie Médicale, Centre de Lutte Contre le Cancer René Gauducheau, Bd J. Monod, 44805, Nantes-Saint Herblain Cedex, France

    Mario Campone

  4. INSERM U892, IRT-UN, 8 Quai Moncousu, 44007, Nantes Cedex, France

    Mario Campone, Wilfried Gouraud, Catherine Guérin-Charbonnel & Loïc Campion

  5. Unité de Biostatistique, Centre de Lutte Contre le Cancer René Gauducheau, Bd J. Monod, 44805, Nantes-Saint Herblain Cedex, France

    Wilfried Gouraud, Catherine Guérin-Charbonnel & Loïc Campion

  6. Service d’épidémiologie et de Biostatistiques, Pôle d’information Médicale, d’évaluation et de Santé Publique, Hôpital Saint Jacques, CHU Nantes, 85 rue Saint Jacques, 44093, Nantes, France

    Christophe Leux

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  1. Pascal Jézéquel
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  2. Mario Campone
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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). https://doi.org/10.1007/s10549-011-1457-7

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  • DOI: https://doi.org/10.1007/s10549-011-1457-7

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