2017
RNA Sequencing to Predict Response to Neoadjuvant Anti-HER2 Therapy: A Secondary Analysis of the NeoALTTO Randomized Clinical Trial
Fumagalli D, Venet D, Ignatiadis M, Azim HA, Maetens M, Rothé F, Salgado R, Bradbury I, Pusztai L, Harbeck N, Gomez H, Chang TW, Coccia-Portugal MA, Di Cosimo S, de Azambuja E, de la Peña L, Nuciforo P, Brase JC, Huober J, Baselga J, Piccart M, Loi S, Sotiriou C. RNA Sequencing to Predict Response to Neoadjuvant Anti-HER2 Therapy: A Secondary Analysis of the NeoALTTO Randomized Clinical Trial. JAMA Oncology 2017, 3: 227-234. PMID: 27684533, PMCID: PMC5374044, DOI: 10.1001/jamaoncol.2016.3824.Peer-Reviewed Original ResearchEvent-free survivalAnti-HER2 therapyAnti-HER2 agentsErbB2/HER2Genomic grade indexCombination armTreatment armsGene signatureBreast cancerHER2-positive early-stage breast cancerNeoadjuvant anti-HER2 therapyPathologic complete response rateHuman epidermal growth factor receptor 2Early-stage breast cancerEpidermal growth factor receptor 2Candidate predictive markersCycles of fluorouracilDual HER2 blockadeImmune gene signaturesComplete response rateGrowth factor receptor 2Positive breast cancerLong-term outcomesRandomized clinical trialsHigh PCR
2014
Dynamic classification using case‐specific training cohorts outperforms static gene expression signatures in breast cancer
Győrffy B, Karn T, Sztupinszki Z, Weltz B, Müller V, Pusztai L. Dynamic classification using case‐specific training cohorts outperforms static gene expression signatures in breast cancer. International Journal Of Cancer 2014, 136: 2091-2098. PMID: 25274406, PMCID: PMC4354298, DOI: 10.1002/ijc.29247.Peer-Reviewed Original Research
2013
Proliferation and estrogen signaling can distinguish patients at risk for early versus late relapse among estrogen receptor positive breast cancers
Bianchini G, Pusztai L, Karn T, Iwamoto T, Rody A, Kelly C, Müller V, Schmidt M, Qi Y, Holtrich U, Becker S, Santarpia L, Fasolo A, Del Conte G, Zambetti M, Sotiriou C, Haibe-Kains B, Symmans WF, Gianni L. Proliferation and estrogen signaling can distinguish patients at risk for early versus late relapse among estrogen receptor positive breast cancers. Breast Cancer Research 2013, 15: r86. PMID: 24060333, PMCID: PMC3978752, DOI: 10.1186/bcr3481.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Agents, HormonalBiomarkers, TumorBreast NeoplasmsCell ProliferationChemoradiotherapy, AdjuvantEstrogensFemaleFollow-Up StudiesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedMitosisNeoplasm GradingNeoplasm MetastasisNeoplasm Recurrence, LocalNeoplasm StagingPrognosisReceptors, EstrogenRiskSignal TransductionTamoxifenConceptsNode-negative tumorsLate relapseNeoadjuvant letrozoleEndocrine therapyEarly relapseNegative tumorsBreast cancerEstrogen receptor-positive breast cancerProliferation markersReceptor-positive breast cancerER-positive breast cancerAdjuvant endocrine therapyAffymetrix gene expression profilesExtended endocrine therapyTamoxifen-treated patientsER-positive patientsGenomic grade indexPositive breast cancerRisk of recurrenceRisk of relapseEstrogen receptor activitySmall independent cohortEstrogen-related genesAdjuvant tamoxifenSystemic therapyA 3-gene proliferation score (TOP-FOX-67) can re-classify histological grade-2, ER-positive breast cancers into low- and high-risk prognostic categories
Szekely B, Iwamoto T, Szasz AM, Qi Y, Matsuoka J, Symmans WF, Tokes AM, Kulka J, Swanton C, Pusztai L. A 3-gene proliferation score (TOP-FOX-67) can re-classify histological grade-2, ER-positive breast cancers into low- and high-risk prognostic categories. Breast Cancer Research And Treatment 2013, 138: 691-698. PMID: 23504136, DOI: 10.1007/s10549-013-2475-4.Peer-Reviewed Original ResearchMeSH KeywordsAntigens, NeoplasmBreast NeoplasmsCell ProliferationChemotherapy, AdjuvantCohort StudiesDatabases, GeneticDNA Topoisomerases, Type IIDNA-Binding ProteinsFemaleForkhead Box Protein M1Forkhead Transcription FactorsGene Expression Regulation, NeoplasticGenome, HumanHumansKi-67 AntigenPoly-ADP-Ribose Binding ProteinsPredictive Value of TestsPrognosisReceptors, EstrogenSurvival RateTamoxifenConceptsGenomic grade indexGrade 2 cancersPrognostic valueProliferation scoreBreast cancerDistant metastasis-free survival curvesGrade 2Metastasis-free survival curvesER-positive breast cancerSystemic adjuvant therapyHigh expressionCohort of patientsHistological grade 2Intermediate-risk cancerPositive breast cancerSimilar prognostic valueGrade 2 tumorsHigh-risk groupGrade 1 cancersHistological grade groupsNon-significant trendWorse DMFSAdjuvant tamoxifenAdjuvant therapyWorse survival
2009
Genomic Grade Index Is Associated With Response to Chemotherapy in Patients With Breast Cancer
Liedtke C, Hatzis C, Symmans WF, Desmedt C, Haibe-Kains B, Valero V, Kuerer H, Hortobagyi GN, Piccart-Gebhart M, Sotiriou C, Pusztai L. Genomic Grade Index Is Associated With Response to Chemotherapy in Patients With Breast Cancer. Journal Of Clinical Oncology 2009, 27: 3185-3191. PMID: 19364972, PMCID: PMC2716940, DOI: 10.1200/jco.2008.18.5934.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsArea Under CurveBreast NeoplasmsCyclophosphamideDoxorubicinDrug Resistance, NeoplasmFemaleFluorouracilHumansMiddle AgedNeoadjuvant TherapyOligonucleotide Array Sequence AnalysisPaclitaxelReceptors, EstrogenROC CurveTreatment OutcomeConceptsGenomic grade indexER-positive patientsRelapse-free survivalPathologic responseNeoadjuvant paclitaxelCyclophosphamide chemotherapyBreast cancerWorse distant relapse-free survivalDistant relapse-free survivalSystemic adjuvant therapyPathologic complete responseFine-needle aspiration biopsyGrade 3 tumorsER-negative cancersER-positive cancersGrade 1 tumorsGrade 2 tumorsMinimal residual diseaseHistological tumor gradeAdjuvant therapyNeoadjuvant chemotherapyComplete responseWorse survivalClinical parametersResidual disease
2008
Use of genomic grade index (GGI) to predict pathologic response to preoperative chemotherapy in breast cancer
Symmans W, Hatzis C, Liedtke C, Desmedt C, Valero V, Kuerer H, Hortobagyi G, Piccart- Gebhart M, Pusztai L, Sotiriou C. Use of genomic grade index (GGI) to predict pathologic response to preoperative chemotherapy in breast cancer. Journal Of Clinical Oncology 2008, 26: 541-541. DOI: 10.1200/jco.2008.26.15_suppl.541.Peer-Reviewed Original ResearchEvaluation of biological pathways involved in chemotherapy response in breast cancer
Tordai A, Wang J, Andre F, Liedtke C, Yan K, Sotiriou C, Hortobagyi GN, Symmans WF, Pusztai L. Evaluation of biological pathways involved in chemotherapy response in breast cancer. Breast Cancer Research 2008, 10: r37. PMID: 18445275, PMCID: PMC2397539, DOI: 10.1186/bcr2088.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsChemotherapy, AdjuvantCyclophosphamideDoxorubicinDrug Resistance, NeoplasmE2F3 Transcription FactorFemaleFluorouracilGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, p53HumansKi-67 AntigenLymphatic MetastasisMiddle AgedMutationNeoadjuvant TherapyNeoplasm StagingPaclitaxelReceptors, EstrogenSignal TransductionTreatment OutcomeConceptsER-positive breast cancerPathologic complete responseER-positive cancersER-negative cancersGenomic grade indexBreast cancerChemotherapy sensitivityGene signatureER-negative breast cancerProliferation signatureER-positive patientsPositive breast cancerExpression of ERPreoperative paclitaxelProliferation gene signatureCyclophosphamide chemotherapyComplete responseResidual cancerChemotherapy responsePCR groupKi67 expressionEstrogen receptorIntroductionOur goalCancerChemotherapy