title: Predicting risk of breast cancer recurrence using gene-expression profiling.
abstract: The molecular profiling of breast tumors using the powerful microarray technology has uncovered the molecular heterogeneity of breast tumors and has offered novel insight into breast tumorigenesis. The estrogen receptor (ER) has been shown to be the most important discriminator dichotomizing breast cancer into two main subsets. At the same time, proliferation, as captured by the recently developed Genomic Grade Index (GGI) has been found to be the most important prognostic factor in breast cancer, far beyond ER status. Interestingly, this index encompasses a significant portion of the predictive power of many published prognostic signatures. The challenge now is to integrate all the prognostic gene signatures available to date towards a comprehensive genomic fingerprint of the primary tumor. In the future, we should be able to offer individualized treatment to our patients based on a clinical decision-making algorithm that takes into account the clinicopathological parameters, the genomic profile of the primary tumor, the presence of micrometastatic cells and pharmacogenetic data for drug response.
authors.affiliation: Free University of Brussels, Functional Genomics and Translational Research Unit, Jules Bordet Institute, 125 Bld de Waterloo, 1000 Brussels, Belgium. Michail.ignatiadis@bordet.be
authors.forename: Michail
authors.initials: M
authors.lastname: Ignatiadis
authors.forename: Christine
authors.initials: C
authors.lastname: Desmedt
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000235:genetics; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000517:prevention & control; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis / Q000235:genetics* / Q000517:prevention & control; D011237:Predictive Value of Tests; D012307:Risk Factors
chemical_list: D014408:Biomarkers, Tumor