2023
Image analysis-based tumor infiltrating lymphocytes measurement predicts breast cancer pathologic complete response in SWOG S0800 neoadjuvant chemotherapy trial
Fanucci K, Bai Y, Pelekanou V, Nahleh Z, Shafi S, Burela S, Barlow W, Sharma P, Thompson A, Godwin A, Rimm D, Hortobagyi G, Liu Y, Wang L, Wei W, Pusztai L, Blenman K. Image analysis-based tumor infiltrating lymphocytes measurement predicts breast cancer pathologic complete response in SWOG S0800 neoadjuvant chemotherapy trial. Npj Breast Cancer 2023, 9: 38. PMID: 37179362, PMCID: PMC10182981, DOI: 10.1038/s41523-023-00535-0.Peer-Reviewed Original ResearchPathologic complete responseBreast cancerComplete responseTIL scoreBreast Cancer Pathologic Complete ResponseTumor-infiltrating lymphocyte scoresEvent-free survivalNeoadjuvant chemotherapy trialsLymphocyte measurementsLymphocyte scoreNeoadjuvant chemotherapyChemotherapy trialsMean pretreatmentResidual diseaseTIL quantificationPredictive valuePretreatment samplesResponse discriminationScoresStrong positive correlationPositive correlationThymidine kinase activity levels in serum can identify HR+ metastatic breast cancer patients with a low risk of early progression (SWOG S0226)
Bergqvist M, Nordmark A, Williams A, Paoletti C, Barlow W, Cobain E, Mehta R, Gralow J, Hortobagyi G, Albain K, Pusztai L, Sharma P, Godwin A, Thompson A, Hayes D, Rae J. Thymidine kinase activity levels in serum can identify HR+ metastatic breast cancer patients with a low risk of early progression (SWOG S0226). Biomarkers 2023, 28: 313-322. PMID: 36647745, PMCID: PMC10681159, DOI: 10.1080/1354750x.2023.2168063.Peer-Reviewed Original ResearchConceptsMetastatic breast cancerNegative predictive valueEndocrine therapyThymidine kinase activityLower riskSingle-agent endocrine therapyMetastatic breast cancer patientsLonger progression-free survivalHigh negative predictive valueProgression-free survivalBreast cancer patientsSerum thymidine kinase activityAdditional therapyOverall survivalSuch patientsCancer patientsBlood drawEarly progressionDisease progressionRapid progressionBreast cancerPatientsSubsequent timepointsPredictive valuePotential biomarkers
2020
Validation of an immunomodulatory gene signature algorithm to predict response to neoadjuvant immunochemotherapy in patients with primary triple-negative breast cancer.
Iwase T, Pusztai L, Blenman K, Li X, Seitz R, Nielsen T, Schweitzer B, Hout D, Bailey D, Zhang X, Shen Y, Ueno N. Validation of an immunomodulatory gene signature algorithm to predict response to neoadjuvant immunochemotherapy in patients with primary triple-negative breast cancer. Journal Of Clinical Oncology 2020, 38: 3117-3117. DOI: 10.1200/jco.2020.38.15_suppl.3117.Peer-Reviewed Original ResearchPrimary triple-negative breast cancerTriple-negative breast cancerPathological complete responsePD-L1 IHCIM subtypesPredictive valueNeoadjuvant immunochemotherapyBreast cancerPhase I/II trialPretreatment core-needle biopsiesAntigen-presenting immune cellsPossible predictive markerImmune cell populationsImmune cell processesCore needle biopsyNegative predictive valuePositive predictive valueStrong predictive valuePositive likelihood ratioNegative likelihood ratioImmunomodulatory subtypeNeoadjuvant immunotherapyII trialLikelihood ratioComplete responseEarly Modulation of Circulating MicroRNAs Levels in HER2-Positive Breast Cancer Patients Treated with Trastuzumab-Based Neoadjuvant Therapy
Di Cosimo S, Appierto V, Pizzamiglio S, Silvestri M, Baselga J, Piccart M, Huober J, Izquierdo M, de la Pena L, Hilbers FS, de Azambuja E, Untch M, Pusztai L, Pritchard K, Nuciforo P, Vincent-Salomon A, Symmans F, Apolone G, de Braud FG, Iorio MV, Verderio P, Daidone MG. Early Modulation of Circulating MicroRNAs Levels in HER2-Positive Breast Cancer Patients Treated with Trastuzumab-Based Neoadjuvant Therapy. International Journal Of Molecular Sciences 2020, 21: 1386. PMID: 32085669, PMCID: PMC7073028, DOI: 10.3390/ijms21041386.Peer-Reviewed Original ResearchConceptsPathological complete responseNeoadjuvant therapyHER2-positive breast cancer patientsTrastuzumab-based neoadjuvant therapyAvailable predictive biomarkersBreast cancer patientsEstrogen receptor statusComplete responseReceptor statusCancer patientsPredictive biomarkersTreatment responseHCC progressionPatientsPredictive valueBivariate analysisMean differencePlasma pairsTherapyEarly modulationMicroRNA levelsTrastuzumabMAPK signalingMetabolism regulationKEGG analysis
2015
Predictive and Prognostic Value of the TauProtein in Breast Cancer.
Bonneau C, Gurard-Levin ZA, Andre F, Pusztai L, Rouzier R. Predictive and Prognostic Value of the TauProtein in Breast Cancer. Anticancer Research 2015, 35: 5179-84. PMID: 26408675.Peer-Reviewed Original ResearchConceptsBreast cancerTau protein expressionTau proteinPrognostic valueTau expressionHuman epidermal growth factor receptor 2 (HER2) expressionEpidermal growth factor receptor 2 expressionLow tau expressionProtein expressionSubset of patientsReceptor 2 expressionIncreased response rateEffects of taxanesNodal statusBetter prognosisPredictive markerTaxane resistanceChemotherapy sensitivityPredictive valueResponse ratePubMed databaseDrug resistanceCancerHormone receptorsTaxanes
2013
Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients
Haibe-Kains B, Desmedt C, Di Leo A, Azambuja E, Larsimont D, 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. Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients. Data In Brief 2013, 1: 7-10. PMID: 26484051, PMCID: PMC4608867, DOI: 10.1016/j.gdata.2013.09.001.Peer-Reviewed Original ResearchBreast cancer patientsResponse/resistanceAnthracycline monotherapyNeoadjuvant trialsGene expression signaturesNegative tumorsCancer patientsBreast cancerClinical dataEstrogen receptorClinical OncologyPredictive valuePatientsAnthracyclinesGene expressionII alphaExpression signaturesGenome-wide gene expressionMonotherapyExpressionTumorsCancerOncologyTrialsBiomarkersDNA 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 value
2012
19IN Does Molecular Triage Help to Identify Highly Sensitive Disease?
Pusztai L. 19IN Does Molecular Triage Help to Identify Highly Sensitive Disease? Annals Of Oncology 2012, 23: ix29. DOI: 10.1016/s0923-7534(20)32633-8.Peer-Reviewed Original ResearchResponse markersPredictive valueEstrogen receptor expressionHigher tumor proliferationTreatment response markersClass of drugsNegative predictive valuePositive predictive valueDriver eventsAdjuvant therapyPredictive biomarkersPredictive markerTreatment modalitiesTriage patientsVariety of agentsBaseline prognosisClinical trialsReceptor expressionBreast cancerSensitive diseaseHuman epidermal growth factorClinical utilityEpidermal growth factorChemotherapy sensitivityTumor proliferation172O ER + /HER2+ and ER-/Her2+ Breast Cancers are Molecularly Distinct but Immune Gene Signatures are Prognostic and Predictive in Both Groups
Iwamoto T, Pusztai L, Matsuoka J, Callari M, Kelly C, Qi Y, Motoki T, Taira N, Santarpia L, Doihara H, Gianni L, Bianchini G. 172O ER + /HER2+ and ER-/Her2+ Breast Cancers are Molecularly Distinct but Immune Gene Signatures are Prognostic and Predictive in Both Groups. Annals Of Oncology 2012, 23: ix74-ix75. DOI: 10.1016/s0923-7534(20)32783-6.Peer-Reviewed Original ResearchPathologic complete responseER statusResidual diseaseER-/HER2HER2 cancersBetter prognosisBreast cancerHER2-positive breast cancerImmune gene signaturesSystemic adjuvant therapyPositive breast cancerEstrogen receptor statusHigher chemotherapy sensitivityDistinct molecular subtypesNeoadjuvant taxaneAdjuvant therapyImmune signaturesComplete responseReceptor statusHER2 patientsPoor prognosisMolecular subtypesChemotherapy sensitivityPredictive valueHER2Use of next-generation sequencing (NGS) to detect high frequency of targetable alterations in primary and metastatic breast cancer (MBC).
Pusztai L, Yelensky R, Wang B, Avritscher R, Symmans W, Lipson D, Palmer G, Moulder S, Stephens P, Wu Y, Cronin M. Use of next-generation sequencing (NGS) to detect high frequency of targetable alterations in primary and metastatic breast cancer (MBC). Journal Of Clinical Oncology 2012, 30: 10559-10559. DOI: 10.1200/jco.2012.30.15_suppl.10559.Peer-Reviewed Original ResearchMetastatic breast cancerClinical trialsNext-generation sequencingNeedle biopsyBreast cancerGenomic alterationsClinical treatment optionsHER2 gene amplificationPatient selection approachAdjuvant therapyTargetable alterationsTreatment optionsPIK3CA mutationsNovel agentsERBB2 alterationsInvestigational drugsTherapeutic implicationsCancer-related genesBiopsyPredictive valueProspective testingNGS profilingDriver mutationsTherapyCancerA dendritic metagene that predicts prognosis and endocrine resistance in breast cancer.
Giampaolo B, Pusztai L, Qi Y, Iwamoto T, Kelly C, Zambetti M, Symmans W, Gianni L. A dendritic metagene that predicts prognosis and endocrine resistance in breast cancer. Journal Of Clinical Oncology 2012, 30: 545-545. DOI: 10.1200/jco.2012.30.15_suppl.545.Peer-Reviewed Original ResearchHazard ratioEndocrine resistanceBreast cancerNeoadjuvant endocrine therapyProliferative breast cancersAdjuvant tamoxifenEndocrine therapyDistant relapseFree survivalUntreated patientsBetter prognosisDendritic cellsEarly relapseOncotype DXPoor prognosisClinical variablesPoor responseUntreated tumorsLower riskMetagene signaturePredictive valueMultivariate analysisTumorsRelapsePrognosis
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 sizeCohortCancerPD03-02: Prognostic and Predictive Predictors for Triple Negative Breast Cancer.
Karn T, Pusztai L, Ruckhäberle E, Liedtke C, Schmidt M, Müller V, Gätje R, Hanker L, Ahr A, Holtrich U, Rody A, Kaufmann M. PD03-02: Prognostic and Predictive Predictors for Triple Negative Breast Cancer. Cancer Research 2011, 71: pd03-02-pd03-02. DOI: 10.1158/0008-5472.sabcs11-pd03-02.Peer-Reviewed Original ResearchTriple-negative breast cancerNegative breast cancerPrognostic signatureBreast cancerResponse of TNBCER-positive cancersPrognostic gene signatureMolecular phenotypesTNBC cohortNeoadjuvant chemotherapyHazard ratioBetter prognosisPrognostic predictorTherapeutic optionsPoor prognosisIndependent cohortPredictive valuePrognostic gene expression profilesMultivariate analysisGene signatureCancer ResCohortCancerPrognosisROC analysisFirst generation prognostic gene signatures for breast cancer predict both survival and chemotherapy sensitivity and identify overlapping patient populations
Iwamoto T, Lee JS, Bianchini G, Hubbard RE, Young E, Matsuoka J, Kim SB, Symmans WF, Hortobagyi GN, Pusztai L. First generation prognostic gene signatures for breast cancer predict both survival and chemotherapy sensitivity and identify overlapping patient populations. Breast Cancer Research And Treatment 2011, 130: 155. PMID: 21833625, DOI: 10.1007/s10549-011-1706-9.Peer-Reviewed Original ResearchConceptsLong-term survivalPrognostic gene signatureClinical variablesChemotherapy responseGenomic prognostic markersPrognostic markerPredictive valueKaplan-Meir survival curvesSignificant independent predictive valuePathologic complete responseProgression-free survivalLong-term followIndependent predictive valueSame patient cohortReceiver operator characteristic curveOperator characteristic curveOverall survivalPreoperative chemotherapyComplete responseNodal statusIndependent prognosticClinicopathological variablesPatient populationHER2 statusPatient cohortDistinct 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 analysisMultifactorial 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
Use of standard markers and incorporation of molecular markers into breast cancer therapy
Kaufmann M, Pusztai L, Members T. Use of standard markers and incorporation of molecular markers into breast cancer therapy. Cancer 2010, 117: 1575-1582. PMID: 21472705, DOI: 10.1002/cncr.25660.Peer-Reviewed Original ResearchConceptsFuture clinical trialsClinical trialsBreast cancerRoutine pathological evaluationBreast cancer managementCancer Research GroupBreast cancer therapyRoutine clinical decisionImportant therapeutic targetPredictive gene signaturesPathological evaluationPatient selectionConsensus recommendationsCancer managementHeterogeneous diseaseTherapeutic targetPredictive valueBreast pathologyClinical decisionDifferent subtypesGene signatureGenomic profilingClinical levelNew molecular markersOutcome predictionPrognostic and Therapeutic Implications of Distinct Kinase Expression Patterns in Different Subtypes of Breast Cancer
Bianchini G, Iwamoto T, Qi Y, Coutant C, Shiang CY, Wang B, Santarpia L, Valero V, Hortobagyi GN, Symmans WF, Gianni L, Pusztai L. Prognostic and Therapeutic Implications of Distinct Kinase Expression Patterns in Different Subtypes of Breast Cancer. Cancer Research 2010, 70: 8852-8862. PMID: 20959472, DOI: 10.1158/0008-5472.can-10-1039.Peer-Reviewed Original ResearchConceptsPathologic complete responseBreast cancerClinical subtypesPredictive valueHigher pathologic complete responseHuman epidermal growth factor receptor 2Epidermal growth factor receptor 2Different clinical subsetsDistinct prognostic informationNode-negative patientsGrowth factor receptor 2Different clinical subtypesBreast cancer cell linesFactor receptor 2Subtype-specific inhibitionCancer cell linesNeoadjuvant chemotherapyAdjuvant therapyComplete responseClinical subsetsWorse prognosisPrognostic valuePrognostic informationClinical subgroupsExpression patternsEvaluation of a 30-Gene Paclitaxel, Fluorouracil, Doxorubicin, and Cyclophosphamide Chemotherapy Response Predictor in a Multicenter Randomized Trial in Breast Cancer
Tabchy A, Valero V, Vidaurre T, Lluch A, Gomez H, Martin M, Qi Y, Barajas-Figueroa LJ, Souchon E, Coutant C, Doimi FD, Ibrahim NK, Gong Y, Hortobagyi GN, Hess KR, Symmans WF, Pusztai L. Evaluation of a 30-Gene Paclitaxel, Fluorouracil, Doxorubicin, and Cyclophosphamide Chemotherapy Response Predictor in a Multicenter Randomized Trial in Breast Cancer. Clinical Cancer Research 2010, 16: 5351-5361. PMID: 20829329, PMCID: PMC4181852, DOI: 10.1158/1078-0432.ccr-10-1265.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, PharmacologicalBiomarkers, TumorBreast NeoplasmsCarcinoma, Ductal, BreastCyclophosphamideDoxorubicinFemaleFluorouracilGene Expression Regulation, NeoplasticHumansMiddle AgedPaclitaxelPredictive Value of TestsPrognosisTreatment OutcomeConceptsPositive predictive valuePathologic complete responseFAC armPCR rateBreast cancerPredictive valueGene expression profilingDifferent molecular subsetsFine-needle aspiration biopsyMulticenter Randomized TrialInternational clinical trialsGenomic predictorsNegative predictive valueTreatment response predictionWeekly paclitaxelNeoadjuvant chemotherapyCyclophosphamide chemotherapyFAC chemotherapyPreoperative chemotherapyComplete responseRandomized trialsTreatment armsPredictive markerClinical trialsMolecular subsetsCyclophosphamide Dose Intensification May Circumvent Anthracycline Resistance of p53 Mutant Breast Cancers
Lehmann‐Che J, André F, Desmedt C, Mazouni C, Giacchetti S, Turpin E, Espié M, Plassa L, Marty M, Bertheau P, Sotiriou C, Piccart M, Symmans WF, Pusztai L, de Thé H. Cyclophosphamide Dose Intensification May Circumvent Anthracycline Resistance of p53 Mutant Breast Cancers. The Oncologist 2010, 15: 246-252. PMID: 20228131, PMCID: PMC3227956, DOI: 10.1634/theoncologist.2009-0243.Peer-Reviewed Original ResearchConceptsPathologic complete responseBreast cancer patientsCancer patientsDose intensificationDose intensityP53 statusAnthracycline resistanceHigh-dose cyclophosphamide administrationP53-mutant breast cancersAnthracycline-based regimensTriple-negative tumorsPretreatment tumor samplesMutant breast cancerChemotherapy regimensComplete responseER expressionCyclophosphamide administrationER- tumorsTumor responsePooled resultsBreast cancerYeast functional assayPatientsPredictive valueMultivariate analysis