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Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen

BMC Genomics · 2008 · Vol. 9(1) · pp. 239–239

Sherene Loi✉(Institut Jules Bordet)Benjamin Haibe‐Kains(Université Libre de Bruxelles)Christine Desmedt(Institut Jules Bordet)Pratyaksha Wirapati(SIB Swiss Institute of Bioinformatics)Françoise Lallemand(Institut Jules Bordet)Andrew M Tutt(Guy's Hospital)Cheryl Gillet(Guy's Hospital)Peter Ellis(Guy's Hospital)K W Ryder(Guy's Hospital)James F. Reid(FIRC Institute of Molecular Oncology)Maria Grazia Daidone(Fondazione IRCCS Istituto Nazionale dei Tumori)Marco A. Pierotti(Fondazione IRCCS Istituto Nazionale dei Tumori)Els M.J.J. Berns(Erasmus University Rotterdam)Maurice P.H.M. Jansen(Erasmus University Rotterdam)John A. Foekens(Erasmus University Rotterdam)Mauro Delorenzi(SIB Swiss Institute of Bioinformatics)Gianluca Bontempi(Université Libre de Bruxelles)Martine Piccart(Institut Jules Bordet)Christos Sotiriou(Institut Jules Bordet)

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Abstract

We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.

Estrogen and related hormone effects Gene expression and cancer classification Bioinformatics and Genomic NetworksTamoxifenBreast cancerEstrogen receptorOncologyGene expression profilingInternal medicineEstrogenBiologyEstrogen receptor alphaMicroarray

MeSH terms

Breast NeoplasmsFemaleHumansNeoplasms, Hormone-DependentPrognosisReceptors, EstrogenReceptors, ProgesteroneTamoxifenChemotherapy, AdjuvantAntineoplastic Agents, HormonalGene Expression ProfilingDatabases, Genetic