2023
Molecular Characterization of HER2-Low Invasive Breast Carcinoma by Quantitative RT-PCR Using Oncotype DX Assay
Lin H, Can T, Kahn A, Flannery C, Hoag J, Akkunuri A, Bailey H, Baehner R, Pusztai L, Rozenblit M. Molecular Characterization of HER2-Low Invasive Breast Carcinoma by Quantitative RT-PCR Using Oncotype DX Assay. The Oncologist 2023, 28: e973-e976. PMID: 37656608, PMCID: PMC10546821, DOI: 10.1093/oncolo/oyad249.Peer-Reviewed Original ResearchConceptsHER2 mRNA levelsIHC 0MRNA levelsOncotype DX recurrence score resultsEstrogen receptor-positive breast cancerReceptor-positive breast cancerCurrent adjuvant chemotherapyOncotype DX assayRecurrence Score resultsPositive breast cancerInvasive breast carcinomaIHC score 0Adjuvant chemotherapyQuantitative RT-PCRBreast carcinomaPositive statusScore 0Breast cancerStage IYale cohortHigher mRNA levelsCancerRT-PCRPatientsHER2
2020
Prospective multi-institutional evaluation of pathologist assessment of PD-L1 assays for patient selection in triple negative breast cancer
Reisenbichler ES, Han G, Bellizzi A, Bossuyt V, Brock J, Cole K, Fadare O, Hameed O, Hanley K, Harrison BT, Kuba MG, Ly A, Miller D, Podoll M, Roden AC, Singh K, Sanders MA, Wei S, Wen H, Pelekanou V, Yaghoobi V, Ahmed F, Pusztai L, Rimm DL. Prospective multi-institutional evaluation of pathologist assessment of PD-L1 assays for patient selection in triple negative breast cancer. Modern Pathology 2020, 33: 1746-1752. PMID: 32300181, PMCID: PMC8366569, DOI: 10.1038/s41379-020-0544-x.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerNegative breast cancerOverall percent agreementPD-L1Intraclass correlation coefficientBreast cancerAdvanced triple-negative breast cancerPD-L1 positive casesImmune cell stainingMultiple pathologistsPD-L1 scoringMulti-institutional evaluationLung cancer studiesAtezolizumab therapySP142 assaySP263 assaysPatient selectionSP263SP142US FoodDrug AdministrationPathologist's assessmentPositive casesReal-world settingPercent agreement
2018
Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity
Shi W, Ng CKY, Lim RS, Jiang T, Kumar S, Li X, Wali VB, Piscuoglio S, Gerstein MB, Chagpar AB, Weigelt B, Pusztai L, Reis-Filho JS, Hatzis C. Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity. Cell Reports 2018, 25: 1446-1457. PMID: 30404001, PMCID: PMC6261536, DOI: 10.1016/j.celrep.2018.10.046.Peer-Reviewed Original ResearchComparison 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 arm
2016
Quantitative assessment of the spatial heterogeneity of tumor-infiltrating lymphocytes in breast cancer
Mani NL, Schalper KA, Hatzis C, Saglam O, Tavassoli F, Butler M, Chagpar AB, Pusztai L, Rimm DL. Quantitative assessment of the spatial heterogeneity of tumor-infiltrating lymphocytes in breast cancer. Breast Cancer Research 2016, 18: 78. PMID: 27473061, PMCID: PMC4966732, DOI: 10.1186/s13058-016-0737-x.Peer-Reviewed Original ResearchConceptsIntraclass correlation coefficientQuantitative immunofluorescenceBreast cancerSame cancerSingle biopsyMultiplexed quantitative immunofluorescenceTumor-infiltrating lymphocytesPotential predictive markerPrimary breast carcinomaCytokeratin-positive epithelial cellsCD20-positive lymphocytesCD8 levelsLymphocyte scoreQIF scoresLymphocyte countLymphocyte subpopulationsMultiple biopsiesSubpopulation countsPredictive markerPrognostic informationBreast carcinomaBiopsyB lymphocytesCD3Breast tumors
2015
Characterization of DNA variants in the human kinome in breast cancer
Agarwal D, Qi Y, Jiang T, Liu X, Shi W, Wali VB, Turk B, Ross JS, Fraser Symmans W, Pusztai L, Hatzis C. Characterization of DNA variants in the human kinome in breast cancer. Scientific Reports 2015, 5: 14736. PMID: 26420498, PMCID: PMC4588561, DOI: 10.1038/srep14736.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorBreast NeoplasmsFemaleGene Expression Regulation, NeoplasticGenetic Predisposition to DiseaseGenetic VariationHigh-Throughput Nucleotide SequencingHumansMiddle AgedMutationNeoplasm GradingNeoplasm MetastasisNeoplasm StagingPhosphotransferasesPolymorphism, Single NucleotideReproducibility of ResultsTranscriptomeConceptsBreast cancerHuman kinomeKinase geneGreater mutational loadNucleic acid variationPrimary cancer samplesPrimary breast cancerHistologic grade 1Major functional impactSOLiD sequencing platformIndividual breast cancersNon-synonymous variantsFine-needle biopsyGrade 3 casesCancer-related genesNucleotide variationsDNA variantsSequencing platformsMetastatic lesionsMutational loadAcid variationsCancer biologyGenesNeedle biopsyAdditional cancersReproducibility of Variant Calls in Replicate Next Generation Sequencing Experiments
Qi Y, Liu X, Liu CG, Wang B, Hess KR, Symmans WF, Shi W, Pusztai L. Reproducibility of Variant Calls in Replicate Next Generation Sequencing Experiments. PLOS ONE 2015, 10: e0119230. PMID: 26136146, PMCID: PMC4489803, DOI: 10.1371/journal.pone.0119230.Peer-Reviewed Original ResearchConceptsSingle nucleotide variantsEuropean Genome-phenome ArchiveProtein kinase geneMillions of nucleotidesSame genomic DNANext-generation sequencing experimentsVariant callsGenomic locationNext-generation sequencingSequence dataSNV callsKinase geneGenomic DNANucleotide substitutionsSequencing experimentsHigh stringencyVariant allele frequencyNucleotide variantsTrue biological changeNucleotide alterationsGeneration sequencingAllele countsSequencing errorsBreast cancer samplesAllele frequencies
2014
Combined analysis of gene expression, DNA copy number, and mutation profiling data to display biological process anomalies in individual breast cancers
Shi W, Balazs B, Györffy B, Jiang T, Symmans WF, Hatzis C, Pusztai L. Combined analysis of gene expression, DNA copy number, and mutation profiling data to display biological process anomalies in individual breast cancers. Breast Cancer Research And Treatment 2014, 144: 561-568. PMID: 24619174, DOI: 10.1007/s10549-014-2904-z.Peer-Reviewed Original ResearchConceptsDNA copy numberBiological processesIndividual molecular eventsCopy numberGene expressionMolecular eventsMulticellular organismal processGene Ontology databaseGO biological processesSignal transduction pathwaysOrganismal processesGO termsMolecular dataTransduction pathwaysSiRNA screenComplex genomic abnormalitiesIndividual cancersOntology databaseFunctional roleDriver eventsCell growthSequence abnormalitiesBreast cancer cell linesCancer cell linesGenomic abnormalities
2013
Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing
Frampton GM, Fichtenholtz A, Otto GA, Wang K, Downing SR, He J, Schnall-Levin M, White J, Sanford EM, An P, Sun J, Juhn F, Brennan K, Iwanik K, Maillet A, Buell J, White E, Zhao M, Balasubramanian S, Terzic S, Richards T, Banning V, Garcia L, Mahoney K, Zwirko Z, Donahue A, Beltran H, Mosquera JM, Rubin MA, Dogan S, Hedvat CV, Berger MF, Pusztai L, Lechner M, Boshoff C, Jarosz M, Vietz C, Parker A, Miller VA, Ross JS, Curran J, Cronin MT, Stephens PJ, Lipson D, Yelensky R. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nature Biotechnology 2013, 31: 1023-1031. PMID: 24142049, PMCID: PMC5710001, DOI: 10.1038/nbt.2696.Peer-Reviewed Original ResearchReproducibility of research and preclinical validation: problems and solutions
Pusztai L, Hatzis C, Andre F. Reproducibility of research and preclinical validation: problems and solutions. Nature Reviews Clinical Oncology 2013, 10: 720-724. PMID: 24080600, DOI: 10.1038/nrclinonc.2013.171.Peer-Reviewed Original ResearchBiomedical ResearchDrug Evaluation, PreclinicalHumansReproducibility of ResultsValidation Studies as Topic
2012
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
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 receptor
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 sizeCohortCancerEvidence for biological effects of metformin in operable breast cancer: a pre-operative, window-of-opportunity, randomized trial
Hadad S, Iwamoto T, Jordan L, Purdie C, Bray S, Baker L, Jellema G, Deharo S, Hardie DG, Pusztai L, Moulder-Thompson S, Dewar JA, Thompson AM. Evidence for biological effects of metformin in operable breast cancer: a pre-operative, window-of-opportunity, randomized trial. Breast Cancer Research And Treatment 2011, 128: 783-794. PMID: 21655990, DOI: 10.1007/s10549-011-1612-1.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBreast NeoplasmsCyclic Nucleotide Phosphodiesterases, Type 3FemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansHypoglycemic AgentsInsulinKi-67 AntigenMetforminMiddle AgedReproducibility of ResultsSignal TransductionTumor Suppressor Protein p53ConceptsTumor necrosis factor receptor 1Breast cancerCore biopsyPilot cohortOperable invasive breast cancerNon-diabetic womenOperable breast cancerInvasive breast cancerPrimary breast cancerEffect of metforminNecrosis factor receptor 1Serum insulin determinationsMessenger RNA expressionAnti-proliferative effectsFactor receptor 1Ingenuity Pathway AnalysisDiabetic womenMetformin 500Neoadjuvant chemotherapyControl patientsGastrointestinal upsetMetformin armSerum insulinTherapeutic trialsMetformin treatmentMultifactorial 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
2010
Estrogen and HER-2 Receptor Discordance Between Primary Breast Cancer and Metastasis
Pusztai L, Viale G, Kelly CM, Hudis CA. Estrogen and HER-2 Receptor Discordance Between Primary Breast Cancer and Metastasis. The Oncologist 2010, 15: 1164-1168. PMID: 21041379, PMCID: PMC3227913, DOI: 10.1634/theoncologist.2010-0059.Peer-Reviewed Original ResearchMeSH KeywordsBreast NeoplasmsDiagnosisFalse Negative ReactionsFemaleGene ExpressionHumansNeoplasm MetastasisReceptor, ErbB-2Receptors, EstrogenReproducibility of ResultsSelection BiasConceptsReceptors resultsBreast cancerHuman epidermal growth factor receptor 2 receptor statusRepeat tumor biopsiesRoutine repeat biopsyPrimary breast cancerReceptor-positive cancersReceptor-negative cancersEndocrine therapyFalse-negative resultsReceptor discordanceMetastatic diseaseReceptor statusRepeat biopsyClinical courseRecurrent cancerClinical groundsPrimary tumorTumor nestsEstrogen receptorTumor biopsiesHormone responsivenessReceptor assayCancerDiscordant results
2008
Prediction of the outcome of preoperative chemotherapy in breast cancer using DNA probes that provide information on both complete and incomplete responses
Natowicz R, Incitti R, Horta EG, Charles B, Guinot P, Yan K, Coutant C, Andre F, Pusztai L, Rouzier R. Prediction of the outcome of preoperative chemotherapy in breast cancer using DNA probes that provide information on both complete and incomplete responses. BMC Bioinformatics 2008, 9: 149. PMID: 18366635, PMCID: PMC2292140, DOI: 10.1186/1471-2105-9-149.Peer-Reviewed Original Research
2007
Limitations of pharmacogenomic predictor discovery in Phase II clinical trials
Pusztai L. Limitations of pharmacogenomic predictor discovery in Phase II clinical trials. Pharmacogenomics 2007, 8: 1443-1448. PMID: 17979517, DOI: 10.2217/14622416.8.10.1443.Peer-Reviewed Original ResearchMeSH KeywordsClinical Trials, Phase II as TopicDrug TherapyGenetic MarkersHumansPharmacogeneticsReproducibility of Results
2006
Pharmacogenomic Predictor of Sensitivity to Preoperative Chemotherapy With Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide in Breast Cancer
Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA, Booser D, Theriault RL, Buzdar AU, Dempsey PJ, Rouzier R, Sneige N, Ross JS, Vidaurre T, Gómez HL, Hortobagyi GN, Pusztai L. Pharmacogenomic Predictor of Sensitivity to Preoperative Chemotherapy With Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide in Breast Cancer. Journal Of Clinical Oncology 2006, 24: 4236-4244. PMID: 16896004, DOI: 10.1200/jco.2006.05.6861.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsCyclophosphamideDoxorubicinFemaleFluorouracilGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMicroarray AnalysisMiddle AgedNeoplasm StagingOligonucleotidesPaclitaxelPredictive Value of TestsReproducibility of ResultsROC CurveSensitivity and SpecificityReproducibility of Gene Expression Signature–Based Predictions in Replicate Experiments
Anderson K, Hess KR, Kapoor M, Tirrell S, Courtemanche J, Wang B, Wu Y, Gong Y, Hortobagyi GN, Symmans WF, Pusztai L. Reproducibility of Gene Expression Signature–Based Predictions in Replicate Experiments. Clinical Cancer Research 2006, 12: 1721-1727. PMID: 16551855, DOI: 10.1158/1078-0432.ccr-05-1539.Peer-Reviewed Original Research
2005
Nomograms to Predict Pathologic Complete Response and Metastasis-Free Survival After Preoperative Chemotherapy for Breast Cancer
Rouzier R, Pusztai L, Delaloge S, Gonzalez-Angulo AM, Andre F, Hess KR, Buzdar AU, Garbay JR, Spielmann M, Mathieu MC, Symmans WF, Wagner P, Atallah D, Valero V, Berry DA, Hortobagyi GN. Nomograms to Predict Pathologic Complete Response and Metastasis-Free Survival After Preoperative Chemotherapy for Breast Cancer. Journal Of Clinical Oncology 2005, 23: 8331-8339. PMID: 16293864, DOI: 10.1200/jco.2005.01.2898.Peer-Reviewed Original ResearchMeSH KeywordsAnthracyclinesAntibiotics, AntineoplasticAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsChemotherapy, AdjuvantDecision Making, Computer-AssistedDisease-Free SurvivalFemaleFranceHumansInternetLogistic ModelsMiddle AgedMultivariate AnalysisNeoadjuvant TherapyNomogramsPaclitaxelPredictive Value of TestsProportional Hazards ModelsReproducibility of ResultsTexasConceptsDistant metastasis-free survivalPathologic complete responseMetastasis-free survivalPreoperative chemotherapyComplete responseCox proportional hazards regression modelProportional hazards regression modelsM.D. Anderson Cancer CenterPreoperative chemotherapy cyclesSchedule of paclitaxelCombination of paclitaxelEstrogen receptor statusHazards regression modelsMultivariate logistic regressionInstitut Gustave RoussyAnderson Cancer CenterInclusion of paclitaxelClinical prediction modelChemotherapy cyclesReceptor statusClinical stageClinical variablesHistologic gradeCancer CenterPrediction nomogram