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 cohortAssociation of LN Evaluation with Survival in Women Aged 70 Years or Older With Clinically Node-Negative Hormone Receptor Positive Breast Cancer
Chagpar AB, Hatzis C, Pusztai L, DiGiovanna MP, Moran M, Mougalian S, Sanft T, Evans S, Hofstatter E, Wilson LD, Lannin DR. Association of LN Evaluation with Survival in Women Aged 70 Years or Older With Clinically Node-Negative Hormone Receptor Positive Breast Cancer. Annals Of Surgical Oncology 2017, 24: 3073-3081. PMID: 28766195, DOI: 10.1245/s10434-017-5936-x.Peer-Reviewed Original ResearchConceptsBreast cancer-specific survivalLN evaluationPositive breast cancerOverall survivalBreast cancerHormone receptor-positive breast cancerWomen Aged 70 YearsReceptor-positive breast cancerLymph node evaluationCancer-specific survivalLower hazard rateLN surgeryBetter OSPatient ageSEER databasePatient selectionTumor characteristicsSEER dataPatientsNode evaluationHormone receptorsCancerSurvivalTreatment variablesNCDB
2016
Predictors of Chemosensitivity in Triple Negative Breast Cancer: An Integrated Genomic Analysis
Jiang T, Shi W, Wali VB, Pongor L, Li C, Lau R, Győrffy B, Lifton RP, Symmans WF, Pusztai L, Hatzis C. Predictors of Chemosensitivity in Triple Negative Breast Cancer: An Integrated Genomic Analysis. PLOS Medicine 2016, 13: e1002193. PMID: 27959926, PMCID: PMC5154510, DOI: 10.1371/journal.pmed.1002193.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerPathologic complete responseMD Anderson Cancer CenterNegative breast cancerBreast cancerMutation burdenExtensive residual diseaseBetter survival outcomesBRCA deficiencyImmune cell activityAnderson Cancer CenterPredictor of chemosensitivityHigh mutation burdenWhole-exome sequencingACT chemotherapyMDACC cohortTNBC cohortNeoadjuvant chemotherapyCare chemotherapyTaxane chemotherapyCancer Genome AtlasComplete responseSuch patientsImproved survivalAggressive diseasePatient preferences regarding incidental genomic findings discovered during tumor profiling
Yushak ML, Han G, Bouberhan S, Epstein L, DiGiovanna MP, Mougalian SS, Sanft TB, Abu-Khalaf MM, Chung GG, Stein SM, Goldberg SB, Pusztai L, Hofstatter EW. Patient preferences regarding incidental genomic findings discovered during tumor profiling. Cancer 2016, 122: 1588-1597. PMID: 26970385, DOI: 10.1002/cncr.29951.Peer-Reviewed Original ResearchConceptsIncidental findingTumor profilingGermline variantsAmbulatory oncology clinicsMajority of patientsStandard of careTumor profiling testsOncology clinicPreventable diseaseFamily historyPatient tumorsInformation patientsPreventable illnessPatientsDisease variablesUnpreventable diseaseUncertain significanceDisclosure preferencesCancerFrequent concernTumorsIllnessProfiling testsDiseaseCurrent study
2015
Use of neoadjuvant chemotherapy for patients with stage I to III breast cancer in the United States
Mougalian SS, Soulos PR, Killelea BK, Lannin DR, Abu-Khalaf MM, DiGiovanna MP, Sanft TB, Pusztai L, Gross CP, Chagpar AB. Use of neoadjuvant chemotherapy for patients with stage I to III breast cancer in the United States. Cancer 2015, 121: 2544-2552. PMID: 25902916, DOI: 10.1002/cncr.29348.Peer-Reviewed Original ResearchConceptsNeoadjuvant chemotherapyNAC useBreast cancerStage INational Cancer Data BaseStage III breast cancerStage IIIC cancerStage II diseaseStage III diseaseAdvanced breast cancerStandard of careLow-stage cancersLogistic regression analysisChi-square testIIIC cancersStage IIIAStage IIIBAdvanced cancerAfrican American individualsStage cancerPatterns of usePatientsAcademic centersClinical advantagesMultivariate analysisPD-L1 Expression Correlates with Tumor-Infiltrating Lymphocytes and Response to Neoadjuvant Chemotherapy in Breast Cancer
Wimberly H, Brown JR, Schalper K, Haack H, Silver MR, Nixon C, Bossuyt V, Pusztai L, Lannin DR, Rimm DL. PD-L1 Expression Correlates with Tumor-Infiltrating Lymphocytes and Response to Neoadjuvant Chemotherapy in Breast Cancer. Cancer Immunology Research 2015, 3: 326-332. PMID: 25527356, PMCID: PMC4390454, DOI: 10.1158/2326-6066.cir-14-0133.Peer-Reviewed Original ResearchConceptsTumor-infiltrating lymphocytesPD-L1 expressionPathologic complete responseNeoadjuvant chemotherapyPD-L1Breast cancerDeath 1 ligand 1PD-L1 protein expressionYale-New Haven HospitalHigh PD-L1Antitumor immune activitySubset of patientsTriple-negative patientsBreast cancer patientsTriple-negative statusImmune checkpoint proteinsImmune regulatory moleculesNew Haven HospitalSignificant multivariate modelRabbit monoclonal antibodyTILs correlateComplete responseImmune therapyCancer patientsImmune activity
2014
Differences in Gene and Protein Expression and the Effects of Race/Ethnicity on Breast Cancer Subtypes
Chavez-MacGregor M, Liu S, De Melo-Gagliato D, Chen H, Do KA, Pusztai L, Symmans W, Nair L, Hortobagyi GN, Mills GB, Meric-Bernstam F, Gonzalez-Angulo AM. Differences in Gene and Protein Expression and the Effects of Race/Ethnicity on Breast Cancer Subtypes. Cancer Epidemiology Biomarkers & Prevention 2014, 23: 316-323. PMID: 24296856, PMCID: PMC3946290, DOI: 10.1158/1055-9965.epi-13-0929.Peer-Reviewed Original Research
2013
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
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 survivalComparison 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
2012
A Systematic Evaluation of Multi-Gene Predictors for the Pathological Response of Breast Cancer Patients to Chemotherapy
Shen K, Song N, Kim Y, Tian C, Rice SD, Gabrin MJ, Symmans WF, Pusztai L, Lee JK. A Systematic Evaluation of Multi-Gene Predictors for the Pathological Response of Breast Cancer Patients to Chemotherapy. PLOS ONE 2012, 7: e49529. PMID: 23185353, PMCID: PMC3504014, DOI: 10.1371/journal.pone.0049529.Peer-Reviewed Original ResearchConceptsMulti-gene predictorsPatients' clinical outcomesClinical outcomesCancer patientsTherapeutic responseStandard combination chemotherapyBreast cancer patientsClinical outcome measurementsPatient's therapeutic responseBreast cancer cell linesCancer cell linesNegative patientsCombination chemotherapyPatient cohortPathological responseBreast cancerEstrogen receptorClinical utilityOutcome measurementsChemotherapyPatientsCell linesOutcomesPredictorsCOXENAgreement in Risk Prediction Between the 21‐Gene Recurrence Score Assay (Oncotype DX®) and the PAM50 Breast Cancer Intrinsic Classifier™ in Early‐Stage Estrogen Receptor–Positive Breast Cancer
Kelly CM, Bernard PS, Krishnamurthy S, Wang B, Ebbert MT, Bastien RR, Boucher KM, Young E, Iwamoto T, Pusztai L. Agreement in Risk Prediction Between the 21‐Gene Recurrence Score Assay (Oncotype DX®) and the PAM50 Breast Cancer Intrinsic Classifier™ in Early‐Stage Estrogen Receptor–Positive Breast Cancer. The Oncologist 2012, 17: 492-498. PMID: 22418568, PMCID: PMC3336833, DOI: 10.1634/theoncologist.2012-0007.Peer-Reviewed Original ResearchConceptsBreast cancerEstrogen receptorEarly-stage estrogen receptor-positive breast cancerRisk assignmentHuman epidermal growth factor receptor 2 (HER2) expressionEpidermal growth factor receptor 2 expressionEstrogen receptor-positive breast cancerReceptor-positive breast cancerIntermediate RS groupLuminal B cancersReceptor 2 expressionLow-risk categoryQuantitative polymerase chain reactionB cancersMore patientsPolymerase chain reactionIntermediate RSLower riskStage IRS groupCancerPAM50Risk categoriesRisk predictionChain reaction
2011
Homogeneous Datasets of Triple Negative Breast Cancers Enable the Identification of Novel Prognostic and Predictive Signatures
Karn T, Pusztai L, Holtrich U, Iwamoto T, Shiang CY, Schmidt M, Müller V, Solbach C, Gaetje R, Hanker L, Ahr A, Liedtke C, Ruckhäberle E, Kaufmann M, Rody A. Homogeneous Datasets of Triple Negative Breast Cancers Enable the Identification of Novel Prognostic and Predictive Signatures. PLOS ONE 2011, 6: e28403. PMID: 22220191, PMCID: PMC3248403, DOI: 10.1371/journal.pone.0028403.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsCohort StudiesDatabases, GeneticFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, NeoplasmHumansKaplan-Meier EstimateNeoadjuvant TherapyPredictive Value of TestsPrognosisReceptor, ErbB-2Receptors, EstrogenReceptors, ProgesteroneReproducibility of ResultsConceptsPrognostic signatureValidation cohortBreast cancerPredictive valueTriple-negative breast cancerEvent-free survivalTriple-negative cancersHigh-risk groupIndependent validation cohortNegative breast cancerModest predictive valuePrognostic gene signaturePrognostic gene setsTNBC cohortNeoadjuvant chemotherapyPrognostic predictorPoor prognosisRisk groupsMultivariate analysisPredictive signatureNovel prognosticGene signatureSmall sample sizeCohortCancerEffect of CYP2D6 polymorphisms on breast cancer recurrence
Morrow PK, Serna R, Broglio K, Pusztai L, Nikoloff DM, Hillman GR, Fontecha M, Li R, Michaud L, Hortobagyi G, Gonzalez‐Angulo A. Effect of CYP2D6 polymorphisms on breast cancer recurrence. Cancer 2011, 118: 1221-1227. PMID: 21823108, DOI: 10.1002/cncr.26407.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsCarcinomaCase-Control StudiesCohort StudiesCytochrome P-450 CYP2D6Cytochrome P-450 CYP2D6 InhibitorsEnzyme InhibitorsFemaleFollow-Up StudiesGenetic Predisposition to DiseaseHumansMastectomyMiddle AgedNeoplasm Recurrence, LocalPolymorphism, GeneticTamoxifenConceptsEarly breast cancerBreast cancer recurrenceAdjuvant tamoxifen therapyCancer recurrenceTamoxifen therapyMedical historyCYP2D6 genotypeTexas MD Anderson Cancer CenterFresh frozen tumor samplesCytochrome P450 2D6 polymorphismMD Anderson Cancer CenterBreast cancer patientsRisk of recurrenceCase-control studyAnderson Cancer CenterPatient's medical historyFrozen tumor samplesAdjuvant tamoxifenAdjuvant therapyConcomitant medicationsPatient characteristicsAmpliChip CYP450 TestCYP2D6 metabolismDisease recurrenceCancer CenterConsistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response
Li Q, Eklund AC, Birkbak NJ, Desmedt C, Haibe-Kains B, Sotiriou C, Symmans WF, Pusztai L, Brunak S, Richardson AL, Szallasi Z. Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response. BMC Bioinformatics 2011, 12: 310. PMID: 21798043, PMCID: PMC3155975, DOI: 10.1186/1471-2105-12-310.Peer-Reviewed Original ResearchConceptsEarly-stage lung cancerStage lung cancerNegative breast cancerCancer treatment decisionsHuman tumor samplesNeoadjuvant therapyChemotherapy responseLung cancerBreast cancerTreatment decisionsIndependent cohortPrognostic classifierAccurate biomarkersCancer expression profilesTumor typesPotential biomarkersTumor samplesConclusionsThese resultsSpecific predictorsStrong associationReliable predictorCohortCancerPredictorsBiomarkers
2010
Different gene expressions are associated with the different molecular subtypes of inflammatory breast cancer
Iwamoto T, Bianchini G, Qi Y, Cristofanilli M, Lucci A, Woodward WA, Reuben JM, Matsuoka J, Gong Y, Krishnamurthy S, Valero V, Hortobagyi GN, Robertson F, Symmans WF, Pusztai L, Ueno NT. Different gene expressions are associated with the different molecular subtypes of inflammatory breast cancer. Breast Cancer Research And Treatment 2010, 125: 785-795. PMID: 21153052, PMCID: PMC4109066, DOI: 10.1007/s10549-010-1280-6.Peer-Reviewed Original ResearchConceptsInflammatory breast cancerClinical subtypesBreast cancerNon-IBC patientsCase-control studyDistinct clinical subtypesDifferent molecular subtypesNon-IBC tumorsSignificant differencesNon-IBC specimensImmune system-related pathwaysLipid metabolism-related pathwaysHER2 statusReceptor phenotypeMetabolism-related pathwaysMolecular subtypesIBC tumorsSurvival curvesSubtypesTumor samplesHormone receptorsCancerPatientsT-testHER2
2008
Promises and caveats of in silico biomarker discovery
Pusztai L, Leyland-Jones B. Promises and caveats of in silico biomarker discovery. British Journal Of Cancer 2008, 99: 385-386. PMID: 18665186, PMCID: PMC2527796, DOI: 10.1038/sj.bjc.6604495.Peer-Reviewed Original Research
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 resistancePatients