Multifactorial Approach to Predicting Resistance to Anthracyclines
Desmedt C, Di Leo A, de Azambuja E, Larsimont D, Haibe-Kains B, Selleslags J, Delaloge S, Duhem C, Kains JP, Carly B, Maerevoet M, Vindevoghel A, Rouas G, Lallemand F, Durbecq V, Cardoso F, Salgado R, Rovere R, Bontempi G, Michiels S, Buyse M, Nogaret JM, Qi Y, Symmans F, Pusztai L, D'Hondt V, Piccart-Gebhart M, Sotiriou C. Multifactorial Approach to Predicting Resistance to Anthracyclines. Journal Of Clinical Oncology 2011, 29: 1578-1586. PMID: 21422418, DOI: 10.1200/jco.2010.31.2231.Peer-Reviewed Original ResearchMeSH KeywordsAntibiotics, AntineoplasticAntigens, NeoplasmBiomarkers, TumorBiopsyBreast NeoplasmsChemotherapy, AdjuvantDNA Topoisomerases, Type IIDNA-Binding ProteinsDrug Resistance, NeoplasmEpirubicinEuropeFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedNeoadjuvant TherapyOdds RatioPatient SelectionPoly-ADP-Ribose Binding ProteinsPredictive Value of TestsProspective StudiesReceptor, ErbB-2Receptors, EstrogenReproducibility of ResultsRisk AssessmentRisk FactorsTexasTreatment FailureConceptsPathologic complete responseHuman epidermal growth factor receptor 2Neoadjuvant trialsTOP trialPredictive valueEstrogen receptor-negative tumorsEpidermal growth factor receptor 2High negative predictive valuePrimary end pointGrowth factor receptor 2Receptor-negative tumorsResponse/resistanceFactor receptor 2Negative predictive valueUseful clinical toolER-negative samplesA scoresAnthracycline monotherapyEvaluable patientsGene expression signaturesComplete responseBreast cancerImmune responseReceptor 2Patients