2023
Neoadjuvant Immunotherapy in Early, Triple-Negative Breast Cancers: Catching Up with the Rest
Kim L, Coman M, Pusztai L, Park T. Neoadjuvant Immunotherapy in Early, Triple-Negative Breast Cancers: Catching Up with the Rest. Annals Of Surgical Oncology 2023, 30: 6441-6449. PMID: 37349612, DOI: 10.1245/s10434-023-13714-x.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerTumor mutational burdenBreast cancerAdjuvant therapyPathological complete response rateImmune checkpoint modulationComplete response rateExcellent clinical outcomesCombination immunochemotherapyNeoadjuvant immunotherapyNeoadjuvant settingNeoadjuvant chemotherapyOverall survivalPD-L1Checkpoint modulationClinical outcomesMajor trialsMutational burdenResponse rateCancer typesCancerTherapyBiomarkersOutcomesExciting advances
2022
Tumor immune microenvironment of self-identified African American and non-African American triple negative breast cancer
Marczyk M, Qing T, O’Meara T, Yagahoobi V, Pelekanou V, Bai Y, Reisenbichler E, Cole KS, Li X, Gunasekharan V, Ibrahim E, Fanucci K, Wei W, Rimm DL, Pusztai L, Blenman KRM. Tumor immune microenvironment of self-identified African American and non-African American triple negative breast cancer. Npj Breast Cancer 2022, 8: 88. PMID: 35869114, PMCID: PMC9307813, DOI: 10.1038/s41523-022-00449-3.Peer-Reviewed Original ResearchTumor immune microenvironmentImmune microenvironmentTriple-negative breast cancer tissuesTriple-negative breast cancerAfrican AmericansImmune checkpoint inhibitorsTumor mutation burdenNegative breast cancerBreast cancer tissuesImmune-related pathwaysStromal TILsCheckpoint inhibitorsImmune exclusionClinical outcomesPD-L1Self-identified African AmericansCancer patientsImmune infiltrationBreast cancerMutation burdenCancer tissuesPredictive signatureMRNA expressionTherapeutic agentsPatients
2020
Association of T- and B-cell receptor repertoires with molecular subtypes and outcome in HER2+ breast cancer: An analysis of the NeoALTTO clinical trial.
Rediti M, Venet D, Rothe F, Qing T, Maetens M, Bradbury I, Izquierdo M, Di Cosimo S, Hilbers F, Bajji M, Harbeck N, Untch M, Liu M, Saura C, Huober J, Nuciforo P, Salgado R, Loi S, Pusztai L, Sotiriou C. Association of T- and B-cell receptor repertoires with molecular subtypes and outcome in HER2+ breast cancer: An analysis of the NeoALTTO clinical trial. Journal Of Clinical Oncology 2020, 38: 511-511. DOI: 10.1200/jco.2020.38.15_suppl.511.Peer-Reviewed Original ResearchPathological complete responseBreast cancerPAM50 subtypesB cell receptorImmune responseBiomarker-driven treatment strategiesTumor-infiltrating lymphocyte levelsBaseline tumor biopsiesEvent-free survivalPhase III trialsAnti-HER2 treatmentGrade 3 tumorsEstrogen receptor statusImproved clinical outcomesProportional hazards modelIII trialsLymphocyte levelsComplete responseReceptor statusClinical outcomesClinicopathological characteristicsBC subtypesClinical trialsTreatment strategiesTumor biopsies
2019
Quantitative assessment of immune cell populations and associations with clinical outcomes in African-American (AA) versus Caucasian triple-negative breast cancer (TNBC).
O'Meara T, Yaghoobi V, Blenman K, Pelekanou V, Silber A, Rimm D, Pusztai L. Quantitative assessment of immune cell populations and associations with clinical outcomes in African-American (AA) versus Caucasian triple-negative breast cancer (TNBC). Journal Of Clinical Oncology 2019, 37: e14180-e14180. DOI: 10.1200/jco.2019.37.15_suppl.e14180.Peer-Reviewed Original ResearchTriple-negative breast cancerDisease-free survivalBetter disease-free survivalPD-L1 expressionCD68 expressionAA TNBCStromal PD-L1 expressionPD-L1 protein expressionCaucasian casesHigher TIL countsTumor immune microenvironmentImmune cell populationsHigh CD68 expressionHigh CD68Similar CD8Stromal TILsClinical characteristicsDiagnosis dateTIL countPD-L1Clinical outcomesPredictive factorsCD8 expressionClinical variablesImmune microenvironmentOn-treatment changes in tumor-infiltrating lymphocytes (TIL) during neoadjuvant HER2 therapy (NAT) and clinical outcome.
Luen S, Griguolo G, Nuciforo P, Campbell C, Fasani R, Cortes J, Untch M, Lin S, Savas P, Fox S, Di Cosimo S, Llombart Cussac A, de Azambuja E, Piccart-Gebhart M, Pusztai L, Sotiriou C, Salgado R, Prat A, Loi S. On-treatment changes in tumor-infiltrating lymphocytes (TIL) during neoadjuvant HER2 therapy (NAT) and clinical outcome. Journal Of Clinical Oncology 2019, 37: 574-574. DOI: 10.1200/jco.2019.37.15_suppl.574.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesBreast cancerPrognostic valuePoor patientsTissue-resident memory cellsEarly-stage HER2Resident memory cellsEarly breast cancerImmune cell subsetsFuture trial designPrediction of pCRHER2 therapyNeoALTTO trialImmune subsetsClinical outcomesClinicopathological variablesF patientsCell subsetsTrial designTreatment changesMultivariate analysisPatientsNeoALTTOHER2EFSPersonalizing Treatment Selection for Breast Cancer
Pusztai L, Yeoh C. Personalizing Treatment Selection for Breast Cancer. 2019, 297-324. DOI: 10.1201/9780429066504-14.Peer-Reviewed Original ResearchBreast cancerTreatment selectionClinical outcomesRisk of recurrenceMultiple treatment optionsParticular clinical outcomesCurrent treatment modalitiesCancer-related deathMore effective treatmentsProbability of benefitBreast cancer researchUnited States FoodSurgical resectionProbability of responseTrastuzumab therapyCommon malignancyTreatment optionsClinicopathologic variablesPatient preferencesSpecific therapyTreatment modalitiesMulti-gene testsDisease outcomeMolecular differencesEffective treatment
2016
Assessing cost-utility of predictive biomarkers in oncology: a streamlined approach
Safonov A, Wang S, Gross CP, Agarwal D, Bianchini G, Pusztai L, Hatzis C. Assessing cost-utility of predictive biomarkers in oncology: a streamlined approach. Breast Cancer Research And Treatment 2016, 155: 223-234. PMID: 26749360, PMCID: PMC5990969, DOI: 10.1007/s10549-016-3677-3.Peer-Reviewed Original ResearchConceptsQuality-adjusted life yearsCost-effectiveness analysisPredictive biomarkersBiomarker-guided treatmentIncremental cost-effectiveness ratioHealth-related qualityTreatment costsCost-effectiveness ratioClinical outcomesClinical efficacyPrognostic biomarkerTraditional cost-effectiveness analysisBiomarker useLife yearsBiomarker valuesBiomarker prevalenceClinical literatureBiomarkersTreatmentState transition modelDecision analytic approachMedical utilityDecision analytic toolsCrizotinibHER2
2015
A genome-wide approach to link genotype to clinical outcome by utilizing next generation sequencing and gene chip data of 6,697 breast cancer patients
Pongor L, Kormos M, Hatzis C, Pusztai L, Szabó A, Győrffy B. A genome-wide approach to link genotype to clinical outcome by utilizing next generation sequencing and gene chip data of 6,697 breast cancer patients. Genome Medicine 2015, 7: 104. PMID: 26474971, PMCID: PMC4609150, DOI: 10.1186/s13073-015-0228-1.Peer-Reviewed Original ResearchConceptsRNA-seq dataNext-generation sequencingBreast cancer patientsTranscriptomic fingerprintGenome-wide approachesGeneration sequencingClinical outcomesCancer patientsHuman gene mutationsTumor suppressor geneGene chip dataSuch genesRNA-seqGene mutationsLarge breast cancer cohortGene expressionChip dataSuppressor geneBreast cancer cohortGenesMicroarray dataMutationsSomatic mutationsClinical characteristicsCox regression
2013
DNA Repair Gene Patterns as Prognostic and Predictive Factors in Molecular Breast Cancer Subtypes
Santarpia L, Iwamoto T, Di Leo A, Hayashi N, Bottai G, Stampfer M, André F, Turner NC, Symmans WF, Hortobágyi GN, Pusztai L, Bianchini G. DNA Repair Gene Patterns as Prognostic and Predictive Factors in Molecular Breast Cancer Subtypes. The Oncologist 2013, 18: 1063-1073. PMID: 24072219, PMCID: PMC3805146, DOI: 10.1634/theoncologist.2013-0163.Peer-Reviewed Original ResearchConceptsResidual invasive cancerHER2-negative tumorsInvasive cancerER-positive/HER2-negative tumorsPredictive valueUntreated breast cancer patientsAffymetrix gene expression profilesHER2-negative subgroupMolecular breast cancer subtypesTaxane/anthracyclinePathological complete responseER-positive tumorsAnthracycline-treated patientsHER2-positive tumorsBreast cancer patientsER-negative tumorsBreast cancer subtypesAnthracycline regimensComplete responseBetter prognosisClinical outcomesBC patientsPoor prognosisPredictive factorsPrognostic valueCancer heterogeneity: implications for targeted therapeutics
Fisher R, Pusztai L, Swanton C. Cancer heterogeneity: implications for targeted therapeutics. British Journal Of Cancer 2013, 108: 479-485. PMID: 23299535, PMCID: PMC3593543, DOI: 10.1038/bjc.2012.581.Peer-Reviewed Original ResearchConceptsIntra-tumoural heterogeneityIntra-tumor heterogeneityClinical trial designCancer therapeuticsDistinct genomic alterationsClinical outcomesMalignant tumorsCurrent evidenceTrial designSolid tumorsSubpopulation of cellsSame tumorTumorsTissue collectionGenomic alterationsTherapeuticsBiomarker discoveryWidespread implementationEvidenceComparison 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 linesOutcomesPredictorsCOXENCell Line Derived Multi-Gene Predictor of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Validation Study on US Oncology 02-103 Clinical Trial
Shen K, Qi Y, Song N, Tian C, Rice SD, Gabrin MJ, Brower SL, Symmans WF, O’Shaughnessy J, Holmes FA, Asmar L, Pusztai L. Cell Line Derived Multi-Gene Predictor of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Validation Study on US Oncology 02-103 Clinical Trial. BMC Medical Genomics 2012, 5: 51. PMID: 23158478, PMCID: PMC3536618, DOI: 10.1186/1755-8794-5-51.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic AgentsAntineoplastic Combined Chemotherapy ProtocolsArea Under CurveBreast NeoplasmsCell Line, TumorClinical Trials as TopicDemographyFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, NeoplasmHumansMiddle AgedMultivariate AnalysisNeoadjuvant TherapyReproducibility of ResultsTreatment OutcomeUnited StatesConceptsMulti-gene predictorsBreast cancerNeoadjuvant chemotherapyCombination chemotherapyCyclophosphamide combination chemotherapyDocetaxel/capecitabineEpirubicin/cyclophosphamideER-negative patientsPathologic complete responseER-positive cancersReceiver-operating characteristic curveAU-ROCCell linesBlinded validation studyNeoadjuvant treatmentMost patientsComplete responseER statusPathologic responseClinical outcomesValidation studyResidual diseaseTx groupClinical trialsEstrogen receptorIntratumor Heterogeneity: Seeing the Wood for the Trees
Yap TA, Gerlinger M, Futreal PA, Pusztai L, Swanton C. Intratumor Heterogeneity: Seeing the Wood for the Trees. Science Translational Medicine 2012, 4: 127ps10. PMID: 22461637, DOI: 10.1126/scitranslmed.3003854.Peer-Reviewed Original ResearchSeventeen-gene signature from enriched Her2/Neu mammary tumor-initiating cells predicts clinical outcome for human HER2+:ERα− breast cancer
Liu JC, Voisin V, Bader GD, Deng T, Pusztai L, Symmans WF, Esteva FJ, Egan SE, Zacksenhaus E. Seventeen-gene signature from enriched Her2/Neu mammary tumor-initiating cells predicts clinical outcome for human HER2+:ERα− breast cancer. Proceedings Of The National Academy Of Sciences Of The United States Of America 2012, 109: 5832-5837. PMID: 22460789, PMCID: PMC3326451, DOI: 10.1073/pnas.1201105109.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntibodies, Monoclonal, HumanizedAntineoplastic AgentsBreast NeoplasmsCalcium-Binding ProteinsCD24 AntigenCell DifferentiationCell DivisionEstrogen Receptor alphaFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, NeoplasmHumansIntercellular Signaling Peptides and ProteinsJagged-1 ProteinMembrane ProteinsMiceNeoadjuvant TherapyNeoplastic Stem CellsPrognosisReceptor, ErbB-2Serrate-Jagged ProteinsSignal TransductionTrastuzumabTreatment OutcomeConceptsTumor-initiating cellsMammary tumor-initiating cellsBreast cancerClinical outcomesPrognostic signatureHuman epidermal growth factor receptorAnti-HER2 drugsAnti-HER2 therapyHigh-risk patientsHigh-risk subgroupsEpidermal growth factor receptorGrowth factor receptorBC cohortRisk patientsAggressive diseaseBC patientsRetrospective analysisImmune responsePrognostic powerTumor growthPatientsChemotherapyFactor receptorCancerFraction of cells
2010
PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor–positive breast cancer
Loi S, Haibe-Kains B, Majjaj S, Lallemand F, Durbecq V, Larsimont D, Gonzalez-Angulo AM, Pusztai L, Symmans WF, Bardelli A, Ellis P, Tutt AN, Gillett CE, Hennessy BT, Mills GB, Phillips WA, Piccart MJ, Speed TP, McArthur GA, Sotiriou C. PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor–positive breast cancer. Proceedings Of The National Academy Of Sciences Of The United States Of America 2010, 107: 10208-10213. PMID: 20479250, PMCID: PMC2890442, DOI: 10.1073/pnas.0907011107.Peer-Reviewed Original ResearchMeSH KeywordsAntibiotics, AntineoplasticAntineoplastic Agents, HormonalBase SequenceBreast NeoplasmsCell Line, TumorClass I Phosphatidylinositol 3-KinasesDNA PrimersFemaleGene Expression ProfilingHumansMechanistic Target of Rapamycin Complex 1Multiprotein ComplexesMutationNeoplasms, Hormone-DependentOligonucleotide Array Sequence AnalysisPhosphatidylinositol 3-KinasesPrognosisProteinsProto-Oncogene Proteins c-aktReceptor, ErbB-2Receptors, EstrogenSignal TransductionSirolimusTamoxifenTOR Serine-Threonine KinasesTranscription FactorsConceptsBreast cancerPIK3CA mutationsClinical outcomesEstrogen receptor-positive breast cancerReceptor-positive breast cancerGene signaturePIK3CA mutation statusPI3K/mTOR inhibitorBetter clinical outcomesPI3K/mTOR inhibitionHuman breast cancerBC cell linesPIK3CA mutant breast cancersCommon genetic aberrationsTamoxifen monotherapyBetter prognosisMTOR inhibitorsBetter outcomesMutation statusMTOR inhibitionPathway activationExperimental modelGenetic aberrationsPrognosisCell lines
2009
Correlation of PIK3CA mutation-associated gene expression signature (PIK3CA-GS) with deactivation of the PI3K pathway and with prognosis within the luminal-B ER+ breast cancers
Loi S, Haibe-Kains B, Lallemand F, Pusztai L, Bardelli A, Gillett C, Ellis P, Piccart-Gebhart M, Phillips W, McArthur G, Sotiriou C. Correlation of PIK3CA mutation-associated gene expression signature (PIK3CA-GS) with deactivation of the PI3K pathway and with prognosis within the luminal-B ER+ breast cancers. Journal Of Clinical Oncology 2009, 27: 533-533. DOI: 10.1200/jco.2009.27.15_suppl.533.Peer-Reviewed Original ResearchPI3K pathwayBreast cancerPIK3CA mutationsMutation statusGene expression signaturesK pathwayClinical outcomesLuminal B breast cancerLuminal BC subtypePIK3CA mutation statusBetter clinical outcomesIndependent prognostic informationB breast cancerExpression signaturesPI3K inhibitorsPI3K inhibitionBC cohortDistinct gene expression signaturesEndocrine therapyBC samplesBC subtypesPrognostic informationFavorable outcomeEstrogen receptorMutation carriersEvaluation of microtubule associated protein tau expression as prognostic and predictive marker in the NSABP-B 28 randomized clinical trial.
Pusztai L, Jeong J, Gong Y, Ross J, Kim C, Hortobagyi G, Paik S, Symmans W. Evaluation of microtubule associated protein tau expression as prognostic and predictive marker in the NSABP-B 28 randomized clinical trial. Cancer Research 2009, 69: 54. DOI: 10.1158/0008-5472.sabcs-54.Peer-Reviewed Original ResearchOverall survivalTau protein expressionTau expressionClinical trialsHormone receptor-positive tumorsMD Anderson Cancer CenterDoxorubicin/cyclophosphamideER-negative subsetNational Surgical BreastAdjuvant endocrine treatmentProtein expressionReceptor-positive tumorsPercent of tumorsAnderson Cancer CenterNormal breast epitheliumAdjuvant chemotherapyPaclitaxel efficacyBowel ProjectEndocrine therapyEndocrine treatmentPaclitaxel chemotherapyNodal statusBetter prognosisClinical outcomesPositive tumors
2008
Commercialized Multigene Predictors of Clinical Outcome for Breast Cancer
Ross JS, Hatzis C, Symmans WF, Pusztai L, Hortobágyi GN. Commercialized Multigene Predictors of Clinical Outcome for Breast Cancer. The Oncologist 2008, 13: 477-493. PMID: 18515733, DOI: 10.1634/theoncologist.2007-0248.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsCost-Benefit AnalysisDevice ApprovalFemaleGene Expression ProfilingHumansMolecular Diagnostic TechniquesParaffin EmbeddingPredictive Value of TestsPrognosisReceptors, EstrogenReverse Transcriptase Polymerase Chain ReactionUnited StatesUnited States Food and Drug AdministrationConceptsQuantitative multiplex real-time polymerase chain reactionLymph node positiveValidation clinical trialEfficacy of tamoxifenER-positive patientsPredictive testRegulatory approval statusOncotype DX testCurrent clinical utilityReal-time polymerase chain reactionCytochrome P450 CYP2D6High accrual rateMultiplex real-time polymerase chain reactionParaffin-embedded tissuesThird-party payorsProspective trialYounger patientsNode positiveClinical outcomesOncotype DXPatient eligibilityMultigene assaysPolymerase chain reactionClinical trialsBreast cancerCurrent Status of Prognostic Profiling in Breast Cancer
Pusztai L. Current Status of Prognostic Profiling in Breast Cancer. The Oncologist 2008, 13: 350-360. PMID: 18448548, DOI: 10.1634/theoncologist.2007-0216.Peer-Reviewed Original ResearchMeSH KeywordsAntigens, NeoplasmAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBreast NeoplasmsClinical Trials as TopicDNA Topoisomerases, Type IIDNA-Binding ProteinsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansOligonucleotide Array Sequence AnalysisOncogenesPredictive Value of TestsPrognosisReceptor, ErbB-2Receptors, EstrogenResearch DesignTamoxifenTaxoidsTreatment OutcomeConceptsBreast cancerClinical-pathological variablesClinical trial planningClinical courseClinical outcomesPathological variablesTreatment armsPrognostic informationClinical trialsTreatment strategiesClinicopathologic parametersHeterogeneous diseaseSpecific treatmentTherapeutic targetPrognostic profilingClinical heterogeneityGene expression fingerprintProspective tissue collectionAbnormal gene expressionIndividual tumorsPrognostic testTumorsPredictive indicatorIndividual diseasesTrial planning