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 subty** 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 subty** 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.
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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