2018
CD68, CD163, and matrix metalloproteinase 9 (MMP-9) co-localization in breast tumor microenvironment predicts survival differently in ER-positive and -negative cancers
Pelekanou V, Villarroel-Espindola F, Schalper KA, Pusztai L, Rimm DL. CD68, CD163, and matrix metalloproteinase 9 (MMP-9) co-localization in breast tumor microenvironment predicts survival differently in ER-positive and -negative cancers. Breast Cancer Research 2018, 20: 154. PMID: 30558648, PMCID: PMC6298021, DOI: 10.1186/s13058-018-1076-x.Peer-Reviewed Original ResearchMeSH KeywordsAntigens, CDAntigens, Differentiation, MyelomonocyticAntineoplastic AgentsBiomarkers, TumorBreastBreast NeoplasmsDisease-Free SurvivalFemaleGene Expression Regulation, NeoplasticHumansMacrophagesMatrix Metalloproteinase 9Middle AgedPatient SelectionPrognosisReceptors, Cell SurfaceReceptors, EstrogenRetrospective StudiesSurvival AnalysisTissue Array AnalysisTumor MicroenvironmentConceptsTumor-associated macrophagesOverall survivalQuantitative immunofluorescenceMacrophage markersBreast cancerHigh expressionPan-macrophage marker CD68Triple-negative breast cancerCD163/CD68Multiplexed quantitative immunofluorescenceImproved overall survivalProtein expressionWorse overall survivalPoor overall survivalMMP-9 protein expressionSubclass of patientsMacrophage-targeted therapiesMatrix metalloproteinase-9Tissue microarray formatMMP-9 proteinBreast tumor microenvironmentModulator of responseParaffin-embedded tissuesBreast cancer biomarkersCohort BComparison of Residual Risk–Based Eligibility vs Tumor Size and Nodal Status for Power Estimates in Adjuvant Trials of Breast Cancer Therapies
Wei W, Kurita T, Hess KR, Sanft T, Szekely B, Hatzis C, Pusztai L. Comparison of Residual Risk–Based Eligibility vs Tumor Size and Nodal Status for Power Estimates in Adjuvant Trials of Breast Cancer Therapies. JAMA Oncology 2018, 4: e175092-e175092. PMID: 29372234, PMCID: PMC5885272, DOI: 10.1001/jamaoncol.2017.5092.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsChemotherapy, AdjuvantEligibility DeterminationFemaleHumansLymph NodesLymphatic MetastasisMiddle AgedNeoplasm Recurrence, LocalNeoplasm, ResidualPatient SelectionPrognosisRandomized Controlled Trials as TopicReproducibility of ResultsResearch DesignRetrospective StudiesRisk FactorsSurvival AnalysisTrastuzumabTumor BurdenWatchful WaitingYoung AdultConceptsTumor sizeAdjuvant trialsEligibility criteriaNodal statusClinical trialsResidual riskEarly-stage breast cancerAdjuvant clinical trialsBaseline prognostic riskFuture adjuvant trialsResidual risk estimatesRisk of recurrenceBreast cancer therapyRisk thresholdTrial powerClinical trial powerTrial eligibilityAdjuvant therapyCare therapyConsecutive patientsPrognostic riskPatient eligibilityTrial populationPatient cohortControl armAn integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes
Győrffy B, Pongor L, Bottai G, Li X, Budczies J, Szabó A, Hatzis C, Pusztai L, Santarpia L. An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes. British Journal Of Cancer 2018, 118: 1107-1114. PMID: 29559730, PMCID: PMC5931099, DOI: 10.1038/s41416-018-0030-0.Peer-Reviewed Original ResearchConceptsHER2-negative tumorsBreast cancer patientsCancer patientsER-positive/HER2-negative tumorsBreast cancer molecular subtypesMETABRIC data setMolecular breast cancer subtypesCox regression analysisBreast cancer subtypesCancer molecular subtypesGene expression profilesMann-Whitney U testRegression analysisMultivariate regression analysisPrognostic valueKaplan-MeierBreast cancerClinical dataDisease outcomeTCGA cohortGene expressionMolecular subtypesCancer-associated genesCancer-related genesClinical relevance
2017
Association Between Genomic Metrics and Immune Infiltration in Triple-Negative Breast Cancer
Karn T, Jiang T, Hatzis C, Sänger N, El-Balat A, Rody A, Holtrich U, Becker S, Bianchini G, Pusztai L. Association Between Genomic Metrics and Immune Infiltration in Triple-Negative Breast Cancer. JAMA Oncology 2017, 3: 1707-1711. PMID: 28750120, PMCID: PMC5824276, DOI: 10.1001/jamaoncol.2017.2140.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorCohort StudiesGene DosageGene Expression ProfilingGene Expression Regulation, NeoplasticGenetic HeterogeneityHumansImmunologic SurveillanceLymphocyte CountLymphocytes, Tumor-InfiltratingPrognosisSequence Analysis, DNASequence Analysis, RNASurvival AnalysisTriple Negative Breast NeoplasmsConceptsTriple-negative breast cancerImmune infiltrationTNBC cohortBetter prognosisPrognostic categoriesPoor prognosisInverse associationBreast cancerImmune surveillanceImmune checkpoint inhibitor therapyMore effective immunotherapy strategiesSubset of TNBCLow immune cell infiltrationClonal heterogeneityCheckpoint inhibitor therapySelection of patientsImmune cell infiltrationEffective immunotherapy strategiesIndependent validation cohortPatient survival informationLymphocyte countImmunotherapy strategiesInhibitor therapyNeoantigen loadValidation cohort
2016
Testing Violations of the Exponential Assumption in Cancer Clinical Trials with Survival Endpoints
Han G, Schell MJ, Zhang H, Zelterman D, Pusztai L, Adelson K, Hatzis C. Testing Violations of the Exponential Assumption in Cancer Clinical Trials with Survival Endpoints. Biometrics 2016, 73: 687-695. PMID: 27669414, PMCID: PMC6093291, DOI: 10.1111/biom.12590.Peer-Reviewed Original ResearchSWOG S0800 (NCI CDR0000636131): addition of bevacizumab to neoadjuvant nab-paclitaxel with dose-dense doxorubicin and cyclophosphamide improves pathologic complete response (pCR) rates in inflammatory or locally advanced breast cancer
Nahleh ZA, Barlow WE, Hayes DF, Schott AF, Gralow JR, Sikov WM, Perez EA, Chennuru S, Mirshahidi HR, Corso SW, Lew DL, Pusztai L, Livingston RB, Hortobagyi GN. SWOG S0800 (NCI CDR0000636131): addition of bevacizumab to neoadjuvant nab-paclitaxel with dose-dense doxorubicin and cyclophosphamide improves pathologic complete response (pCR) rates in inflammatory or locally advanced breast cancer. Breast Cancer Research And Treatment 2016, 158: 485-495. PMID: 27393622, PMCID: PMC4963434, DOI: 10.1007/s10549-016-3889-6.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerEvent-free survivalAddition of bevacizumabInflammatory breast cancerAdvanced breast cancerDose-dense doxorubicinNab-paclitaxelPathologic complete responseBreast cancerPCR rateOverall survivalOpen-label phase II clinical trialHormone receptor-positive diseaseImproved event-free survivalPathologic complete response ratePhase II clinical trialNeoadjuvant chemotherapy armNeoadjuvant nab-paclitaxelRole of bevacizumabWeekly nab-paclitaxelComplete response rateReceptor-positive diseaseHormone receptor statusSequence of administrationChemotherapy armRelationship between Complete Pathologic Response to Neoadjuvant Chemotherapy and Survival in Triple-Negative Breast Cancer
Hatzis C, Symmans WF, Zhang Y, Gould RE, Moulder SL, Hunt KK, Abu-Khalaf M, Hofstatter EW, Lannin D, Chagpar AB, Pusztai L. Relationship between Complete Pathologic Response to Neoadjuvant Chemotherapy and Survival in Triple-Negative Breast Cancer. Clinical Cancer Research 2016, 22: 26-33. PMID: 26286912, DOI: 10.1158/1078-0432.ccr-14-3304.Peer-Reviewed Original ResearchConceptsPathologic complete responseRecurrence-free survivalTriple-negative breast cancerSurvival benefitNeoadjuvant trialsNeoadjuvant chemotherapyTrial populationBaseline prognosisBreast cancerOverall survival benefitComplete pathologic responseSignificant survival benefitPostneoadjuvant therapyPCR rateComplete responseImproved survivalPathologic responseSurvival improvementTreatment armsPatient survivalResidual diseaseControl armPrognostic variablesPatientsTrials
2014
TP53 mutation‐correlated genes predict the risk of tumor relapse and identify MPS1 as a potential therapeutic kinase in TP53‐mutated breast cancers
Győrffy B, Bottai G, Lehmann-Che J, Kéri G, Őrfi L, Iwamoto T, Desmedt C, Bianchini G, Turner NC, de Thè H, André F, Sotiriou C, Hortobagyi GN, Di Leo A, Pusztai L, Santarpia L. TP53 mutation‐correlated genes predict the risk of tumor relapse and identify MPS1 as a potential therapeutic kinase in TP53‐mutated breast cancers. Molecular Oncology 2014, 8: 508-519. PMID: 24462521, PMCID: PMC5528634, DOI: 10.1016/j.molonc.2013.12.018.Peer-Reviewed Original ResearchConceptsBreast cancerTP53 mutation statusPrognostic valueBC cellsMutation statusER-negative breast cancerDifferent BC cell linesFuture clinical trialsSignificant prognostic markerPotential therapeutic targetBC cell linesType of treatmentNeoadjuvant chemotherapyBC patientsClinical behaviorPrognostic markerClinical trialsConventional chemotherapyEstrogen receptorPotent small molecule inhibitorsTumor relapseSmall molecule inhibitorsTherapeutic targetClinical relevanceTP53 status
2013
Influence of genomics on adjuvant treatments for pre-invasive and invasive breast cancer
Abu-Khalaf M, Pusztai L. Influence of genomics on adjuvant treatments for pre-invasive and invasive breast cancer. The Breast 2013, 22: s83-s87. PMID: 24074799, DOI: 10.1016/j.breast.2013.07.015.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAgedAntineoplastic Agents, HormonalBiopsy, NeedleBreast NeoplasmsChemotherapy, AdjuvantCost SavingsCost-Benefit AnalysisFemaleForecastingGenetic TestingGenomicsHumansImmunohistochemistryMiddle AgedNeoplasm InvasivenessNeoplasm StagingPrognosisReceptors, EstrogenRisk AssessmentSurvival AnalysisTreatment OutcomeConceptsLow-risk patientsBreast cancerRisk patientsTreatment recommendationsEarly-stage breast cancerER-positive breast cancerUse of chemotherapyInvasive breast cancerGenomic testingStage breast cancerInternational practice guidelinesMultivariate prognostic modelCost-effectiveness studiesPotential clinical valueAdjuvant treatmentBreast cancer biomarkersCurrent guidelinesPractice guidelinesClinical utilityClinical valueTumor markersStage IPrognostic modelPrognostic testClinical useComparison of molecular subtype distribution in triple-negative inflammatory and non-inflammatory breast cancers
Masuda H, Baggerly KA, Wang Y, Iwamoto T, Brewer T, Pusztai L, Kai K, Kogawa T, Finetti P, Birnbaum D, Dirix L, Woodward WA, Reuben JM, Krishnamurthy S, Symmans W, Van Laere SJ, Bertucci F, Hortobagyi GN, Ueno NT. Comparison of molecular subtype distribution in triple-negative inflammatory and non-inflammatory breast cancers. Breast Cancer Research 2013, 15: r112. PMID: 24274653, PMCID: PMC3978878, DOI: 10.1186/bcr3579.Peer-Reviewed Original ResearchConceptsInflammatory breast cancerTriple-negative breast cancerTN-IBCIBC statusTNBC subtypesBreast cancerTNBC cohortClinical outcomesNon-inflammatory breast cancerMolecular subtype distributionWorld IBC ConsortiumRecurrence-free survivalNon-inflammatory typeClinical characteristicsOverall survivalPoor prognosisClinical behaviorSubtype distributionConclusionsOur dataHeterogeneous diseaseSubtypesCancerSignificant predictorsGene expression profilesCohort
2011
Distinct p53 Gene Signatures Are Needed to Predict Prognosis and Response to Chemotherapy in ER-Positive and ER-Negative Breast Cancers
Coutant C, Rouzier R, Qi Y, Lehmann-Che J, Bianchini G, Iwamoto T, Hortobagyi GN, Symmans WF, Uzan S, Andre F, de Thé H, Pusztai L. Distinct p53 Gene Signatures Are Needed to Predict Prognosis and Response to Chemotherapy in ER-Positive and ER-Negative Breast Cancers. Clinical Cancer Research 2011, 17: 2591-2601. PMID: 21248301, DOI: 10.1158/1078-0432.ccr-10-1045.Peer-Reviewed Original ResearchConceptsER- cancersPredictive valueBreast cancerP53 signatureWorse distant metastasis-free survivalDistant metastasis-free survivalER-negative breast cancerAdjuvant tamoxifen therapyDifferent molecular subsetsMetastasis-free survivalDifferent prognostic valueNegative breast cancerHigher chemotherapy sensitivityTamoxifen therapyFree survivalBetter prognosisER-positivePoor prognosisPrognostic valuePrognostic markerMolecular subsetsChemotherapy sensitivityMutation statusP53 mutationsMultivariate analysis
2010
Molecular Anatomy of Breast Cancer Stroma and Its Prognostic Value in Estrogen Receptor–Positive and –Negative Cancers
Bianchini G, Qi Y, Alvarez RH, Iwamoto T, Coutant C, Ibrahim NK, Valero V, Cristofanilli M, Green MC, Radvanyi L, Hatzis C, Hortobagyi GN, Andre F, Gianni L, Symmans WF, Pusztai L. Molecular Anatomy of Breast Cancer Stroma and Its Prognostic Value in Estrogen Receptor–Positive and –Negative Cancers. Journal Of Clinical Oncology 2010, 28: 4316-4323. PMID: 20805453, DOI: 10.1200/jco.2009.27.2419.Peer-Reviewed Original ResearchMeSH KeywordsAmyloid beta-Protein PrecursorAntineoplastic Agents, HormonalBiopsy, Fine-NeedleB-LymphocytesBreast NeoplasmsChi-Square DistributionCollagen Type IVExtracellular Matrix ProteinsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMetagenomeNeoplasm Recurrence, LocalPhospholipid Transfer ProteinsPrognosisProportional Hazards ModelsProspective StudiesProtease NexinsProtein Serine-Threonine KinasesReceptor, Transforming Growth Factor-beta Type IIReceptors, Cell SurfaceReceptors, EstrogenReceptors, Transforming Growth Factor betaSurvival AnalysisTamoxifenConceptsER-negative cancersBreast cancer stromaER-positive cancersPrognostic valueCancer stromaNegative cancersProliferative cancersSystemic adjuvant therapyTamoxifen-treated patientsNode-negative patientsEstrogen-receptor positiveStrong prognostic valueCore needle biopsySubset of tumorsLess prognostic valueDistant relapseAdjuvant therapyHazard ratioFavorable prognosisHighest tertilePrognostic scoreCore biopsyBreast cancerImmune functionMultivariate analysisGenomic Index of Sensitivity to Endocrine Therapy for Breast Cancer
Symmans WF, Hatzis C, Sotiriou C, Andre F, Peintinger F, Regitnig P, Daxenbichler G, Desmedt C, Domont J, Marth C, Delaloge S, Bauernhofer T, Valero V, Booser DJ, Hortobagyi GN, Pusztai L. Genomic Index of Sensitivity to Endocrine Therapy for Breast Cancer. Journal Of Clinical Oncology 2010, 28: 4111-4119. PMID: 20697068, PMCID: PMC2953969, DOI: 10.1200/jco.2010.28.4273.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic Agents, HormonalAromatase InhibitorsBiomarkers, TumorBreast NeoplasmsChemotherapy, AdjuvantChi-Square DistributionDisease-Free SurvivalEstrogen Receptor alphaFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGenomicsHumansMiddle AgedNeoplasm StagingOligonucleotide Array Sequence AnalysisPatient SelectionProportional Hazards ModelsRisk AssessmentRisk FactorsSurvival AnalysisTamoxifenTime FactorsTranscription, GeneticTreatment OutcomeConceptsAdjuvant endocrine therapyEndocrine therapyBreast cancerDistant relapseER-positive breast cancerChemo-endocrine therapyDistant relapse riskYears of tamoxifenAdjuvant systemic therapyEstrogen receptor αBreast cancer samplesPrior chemotherapyNeoadjuvant chemotherapyPathologic responseSurvival benefitSystemic therapyUntreated cohortRelapse riskDeath riskTherapy indexAromatase inhibitionESR1 levelsReceptor αTamoxifenTherapy
2009
The HER-2 Receptor and Breast Cancer: Ten Years of Targeted Anti–HER-2 Therapy and Personalized Medicine
Ross JS, Slodkowska EA, Symmans WF, Pusztai L, Ravdin PM, Hortobagyi GN. The HER-2 Receptor and Breast Cancer: Ten Years of Targeted Anti–HER-2 Therapy and Personalized Medicine. The Oncologist 2009, 14: 320-368. PMID: 19346299, DOI: 10.1634/theoncologist.2008-0230.Peer-Reviewed Original ResearchMeSH KeywordsAnthracyclinesAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic Combined Chemotherapy ProtocolsBevacizumabBiomarkers, TumorBreast NeoplasmsEverolimusEvidence-Based MedicineFemaleGene Expression Regulation, NeoplasticHumansImmunohistochemistryIn Situ HybridizationLapatinibNeoplasm StagingPolymerase Chain ReactionPractice Guidelines as TopicPrognosisPyrazolesPyrimidinesQuinazolinesReceptor, ErbB-2RNA, MessengerSirolimusSurvival AnalysisTaxoidsTrastuzumabTreatment OutcomeUp-RegulationConceptsBreast cancerOverall survivalInsulin-like growth factor receptor pathwayClinical Oncology-CollegeMetastatic breast cancerInvasive breast cancerAmerican Pathologists guidelinesHER-2 receptorTyrosine kinase inhibitorsTarget of therapyGrowth factor receptor pathwayKinase inhibitor lapatinibMean relative riskReal-time polymerase chain reactionTransmembrane tyrosine kinase receptorPrediction of responseChromosome 17 polysomyHormonal therapyTyrosine kinase receptorsTherapy toxicitySitu hybridizationPrognostic significancePolymerase chain reactionPathologists guidelinesRelative risk
2007
Expression patterns and predictive value of phosphorylated AKT in early-stage breast cancer
Andre F, Nahta R, Conforti R, Boulet T, Aziz M, Yuan LX, Meslin F, Spielmann M, Tomasic G, Pusztai L, Hortobagyi GN, Michiels S, Delaloge S, Esteva FJ. Expression patterns and predictive value of phosphorylated AKT in early-stage breast cancer. Annals Of Oncology 2007, 19: 315-320. PMID: 17804473, DOI: 10.1093/annonc/mdm429.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAgedBiomarkers, TumorBreast NeoplasmsChi-Square DistributionCohort StudiesCombined Modality TherapyDisease-Free SurvivalErbB ReceptorsFemaleFollow-Up StudiesGene Expression Regulation, NeoplasticHumansImmunohistochemistryMiddle AgedNeoplasm StagingPredictive Value of TestsProbabilityProportional Hazards ModelsProto-Oncogene Proteins c-aktRandomized Controlled Trials as TopicReceptor, ErbB-2Risk AssessmentSurvival AnalysisTime FactorsTreatment OutcomeConceptsEarly breast cancerBreast cancerPredictive valuePhosphorylated AktAdjuvant chemotherapyPAkt expressionAnthracycline-based adjuvant chemotherapyEarly-stage breast cancerEpidermal growth factor receptor expressionGrowth factor receptor expressionAkt phosphorylationBreast cancer tissuesFactor receptor expressionGrowth factor receptorHER2 tumorsRandomized trialsAssessable tumorsHER2 expressionReceptor expressionPositive stainingCancer tissuesEGFR expressionHER2Tumor resistancePatientsInclusion of taxanes, particularly weekly paclitaxel, in preoperative chemotherapy improves pathologic complete response rate in estrogen receptor-positive breast cancers
Mazouni C, Kau S, Frye D, Andre F, Kuerer H, Buchholz T, Symmans W, Anderson K, Hess K, Gonzalez-Angulo A, Hortobagyi G, Buzdar A, Pusztai L. Inclusion of taxanes, particularly weekly paclitaxel, in preoperative chemotherapy improves pathologic complete response rate in estrogen receptor-positive breast cancers. Annals Of Oncology 2007, 18: 874-880. PMID: 17293601, DOI: 10.1093/annonc/mdm008.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsBridged-Ring CompoundsChemotherapy, AdjuvantCyclophosphamideDoxorubicinDrug Administration ScheduleFemaleFluorouracilHumansMiddle AgedNeoplasms, Hormone-DependentPaclitaxelPrognosisReceptors, EstrogenSurvival AnalysisTaxoidsTumor BurdenConceptsPathologic complete response rateComplete response rateER-negative tumorsPreoperative chemotherapyPCR rateER statusBreast cancerResponse rateEstrogen receptor-positive breast cancerReceptor-positive breast cancerMD Anderson Cancer CenterBreast cancer benefitER-negative statusInclusion of taxanesER-negative patientsER-positive patientsER-positive tumorsNeo-adjuvant therapyType of regimenClinical tumor sizeSubset of patientsCox regression analysisER-negative cancersPositive breast cancerAnderson Cancer Center
2005
Epidermal growth factor receptor expression correlates with poor survival in patients who have breast carcinoma treated with doxorubicin‐based neoadjuvant chemotherapy
Buchholz TA, Tu X, Ang KK, Esteva FJ, Kuerer HM, Pusztai L, Cristofanilli M, Singletary SE, Hortobagyi GN, Sahin AA. Epidermal growth factor receptor expression correlates with poor survival in patients who have breast carcinoma treated with doxorubicin‐based neoadjuvant chemotherapy. Cancer 2005, 104: 676-681. PMID: 15981280, DOI: 10.1002/cncr.21217.Peer-Reviewed Original ResearchMeSH KeywordsAntibiotics, AntineoplasticAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsClinical Trials, Phase II as TopicClinical Trials, Phase III as TopicCyclophosphamideDisease-Free SurvivalDoxorubicinErbB ReceptorsFemaleFluorouracilHumansImmunohistochemistryNeoadjuvant TherapyPrognosisRandomized Controlled Trials as TopicSurvival AnalysisConceptsEpidermal growth factor receptorBreast carcinomaEGFR expressionAnthracycline chemotherapyLymph nodesEpidermal growth factor receptor expression correlatesSurvival ratePathologic complete response ratePretreatment tumor tissue samplesDisease-free survival ratesCox regression analysis modelComplete response rateEGFR-negative tumorsEGFR-positive diseasePositive lymph nodesAdvanced breast carcinomaMore lymph nodesOutcomes of patientsOverall survival rateProgesterone receptor statusEGFR-positive tumorsTumor tissue samplesKnowledge of outcomesGrowth factor receptorCyclophosphamide chemotherapy
2004
Pharmacoproteomic analysis of prechemotherapy and postchemotherapy plasma samples from patients receiving neoadjuvant or adjuvant chemotherapy for breast carcinoma
Pusztai L, Gregory BW, Baggerly KA, Peng B, Koomen J, Kuerer HM, Esteva FJ, Symmans WF, Wagner P, Hortobagyi GN, Laronga C, Semmes OJ, Wright GL, Drake RR, Vlahou A. Pharmacoproteomic analysis of prechemotherapy and postchemotherapy plasma samples from patients receiving neoadjuvant or adjuvant chemotherapy for breast carcinoma. Cancer 2004, 100: 1814-1822. PMID: 15112261, DOI: 10.1002/cncr.20203.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBiopsy, NeedleBreast NeoplasmsCase-Control StudiesChemotherapy, AdjuvantCyclophosphamideDoxorubicinDrug Administration ScheduleFemaleFluorouracilHumansMastectomyMiddle AgedNeoadjuvant TherapyNeoplasm StagingPaclitaxelPostoperative CarePreoperative CareProteomicsRisk AssessmentSensitivity and SpecificitySurvival AnalysisTreatment OutcomeConceptsBreast carcinomaHealthy womenPreoperative chemotherapyFinal tumor responseSubset of patientsDay 3 posttreatmentAdjuvant chemotherapyPostoperative chemotherapyCyclophosphamide chemotherapyFAC chemotherapyMicrometastatic diseasePaclitaxel chemotherapyNormal womenTumor responsePlasma profilesHealthy volunteersChemotherapyPatientsStage ICarcinomaDay 0Single courseWomenPlasma samplesCandidate markersPrognostic significance of phosphorylated P38 mitogen‐activated protein kinase and HER‐2 expression in lymph node‐positive breast carcinoma
Esteva FJ, Sahin AA, Smith TL, Yang Y, Pusztai L, Nahta R, Buchholz TA, Buzdar AU, Hortobagyi GN, Bacus SS. Prognostic significance of phosphorylated P38 mitogen‐activated protein kinase and HER‐2 expression in lymph node‐positive breast carcinoma. Cancer 2004, 100: 499-506. PMID: 14745865, DOI: 10.1002/cncr.11940.Peer-Reviewed Original ResearchMeSH KeywordsAgedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBiopsy, NeedleBreast NeoplasmsCombined Modality TherapyFemaleGene Expression Regulation, NeoplasticHumansImmunohistochemistryLymph NodesMastectomyMiddle AgedMitogen-Activated Protein KinasesNeoplasm StagingP38 Mitogen-Activated Protein KinasesProbabilityPrognosisProportional Hazards ModelsReceptor, ErbB-2Risk AssessmentSensitivity and SpecificitySurvival AnalysisTreatment OutcomeConceptsLymph node positive breast carcinomaNode-positive breast carcinomaProgression-free survivalP-p38 MAPKShorter progression-free survivalHER-2 expressionP-p38 MAPK expressionBreast carcinomaAdjuvant chemotherapyMAPK expressionKi-67Phosphorylated p38 MAPK expressionInitial cancer surgeryPrimary breast carcinomaInvasive breast carcinomaP38 MAPK expressionP38 mitogen-activated protein kinase phosphorylationPhosphorylated p38 mitogen-activated protein kinaseMitogen-activated protein kinase phosphorylationBreast carcinoma cellsAdjuvant fluorouracilMedian followCyclophosphamide chemotherapyCancer surgeryPoor outcome
2003
Jun activation domain binding protein 1 expression is associated with low p27(Kip1)levels in node-negative breast cancer.
Esteva FJ, Sahin AA, Rassidakis GZ, Yuan LX, Smith TL, Yang Y, Gilcrease MZ, Cristofanilli M, Nahta R, Pusztai L, Claret FX. Jun activation domain binding protein 1 expression is associated with low p27(Kip1)levels in node-negative breast cancer. Clinical Cancer Research 2003, 9: 5652-9. PMID: 14654548.Peer-Reviewed Original ResearchMeSH KeywordsBreast NeoplasmsCell Cycle ProteinsCOP9 Signalosome ComplexCyclin-Dependent Kinase Inhibitor p27DNA-Binding ProteinsFemaleGene Expression Regulation, NeoplasticGenes, Tumor SuppressorHumansImmunohistochemistryIntracellular Signaling Peptides and ProteinsLymphatic MetastasisMiddle AgedPeptide HydrolasesReceptor, ErbB-2Receptors, EstrogenSurvival AnalysisTime FactorsTranscription FactorsTumor Suppressor ProteinsConceptsNode-negative breast cancerAdjacent normal tissuesInvasive breast carcinomaBreast cancerJab1 overexpressionNormal tissuesBreast carcinomaAdjuvant systemic therapyDisease-free survivalIndependent prognostic factorInvasive breast cancerLow nuclear gradeBreast cancer tissuesExpression levelsProtein-1 expressionBreast tumor tissuesWestern blot analysisDomain-binding protein 1Patient agePrognostic factorsSystemic therapyPrognostic significanceTumor sizeNuclear gradeInvasive tumors