2023
Vitamin D Insufficiency as a Risk Factor for Paclitaxel-Induced Peripheral Neuropathy in SWOG S0221.
Chen C, Zirpoli G, Barlow W, Budd G, McKiver B, Pusztai L, Hortobagyi G, Albain K, Damaj M, Godwin A, Thompson A, Henry N, Ambrosone C, Stringer K, Hertz D. Vitamin D Insufficiency as a Risk Factor for Paclitaxel-Induced Peripheral Neuropathy in SWOG S0221. Journal Of The National Comprehensive Cancer Network 2023, 21: 1172-1180.e3. PMID: 37935109, PMCID: PMC10976748, DOI: 10.6004/jnccn.2023.7062.Peer-Reviewed Original ResearchConceptsChemotherapy-induced peripheral neuropathyVitamin D insufficiencyD insufficiencyVitamin DPaclitaxel scheduleMechanical hypersensitivityPeripheral neuropathyRisk factorsDeficient dietPaclitaxel-Induced Peripheral NeuropathyEarly-stage breast cancerPaclitaxel-containing chemotherapyVitamin D supplementationSufficient vitamin DVitamin D deficiencyBody mass indexMultiple logistic regressionSelf-reported raceD supplementationD deficiencySensitized miceProspective trialFemale patientsMass indexPredictive biomarkers
2022
Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies
Wolf DM, Yau C, Wulfkuhle J, Brown-Swigart L, Gallagher RI, Lee PRE, Zhu Z, Magbanua MJ, Sayaman R, O’Grady N, Basu A, Delson A, Coppé JP, Lu R, Braun J, Investigators I, Asare SM, Sit L, Matthews JB, Perlmutter J, Hylton N, Liu MC, Pohlmann P, Symmans WF, Rugo HS, Isaacs C, DeMichele AM, Yee D, Berry DA, Pusztai L, Petricoin EF, Hirst GL, Esserman LJ, van 't Veer LJ. Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies. Cancer Cell 2022, 40: 609-623.e6. PMID: 35623341, PMCID: PMC9426306, DOI: 10.1016/j.ccell.2022.05.005.Peer-Reviewed Original ResearchConceptsBreast cancer subtypesHormone receptorsHuman epidermal growth factor receptor 2 (HER2) statusCancer subtypesEpidermal growth factor receptor 2 statusPathologic complete response rateTreatment prioritizationComplete response ratePatient selectionPredictive biomarkersTreatment allocationPlatform trialsClinical dataLuminal phenotypeTreatment selectionResponse rateTumor biologyNew treatmentsDrug responseSubtypesCancer therapyBiomarkersProtein/phosphoproteinGene expressionDiverse biology
2021
Ganitumab and metformin plus standard neoadjuvant therapy in stage 2/3 breast cancer
Yee D, Isaacs C, Wolf DM, Yau C, Haluska P, Giridhar KV, Forero-Torres A, Jo Chien A, Wallace AM, Pusztai L, Albain KS, Ellis ED, Beckwith H, Haley BB, Elias AD, Boughey JC, Kemmer K, Yung RL, Pohlmann PR, Tripathy D, Clark AS, Han HS, Nanda R, Khan QJ, Edmiston KK, Petricoin EF, Stringer-Reasor E, Falkson CI, Majure M, Mukhtar RA, Helsten TL, Moulder SL, Robinson PA, Wulfkuhle JD, Brown-Swigart L, Buxton M, Clennell JL, Paoloni M, Sanil A, Berry S, Asare SM, Wilson A, Hirst GL, Singhrao R, Asare AL, Matthews JB, Hylton NM, DeMichele A, Melisko M, Perlmutter J, Rugo HS, Fraser Symmans W, van‘t Veer L, Berry DA, Esserman LJ. Ganitumab and metformin plus standard neoadjuvant therapy in stage 2/3 breast cancer. Npj Breast Cancer 2021, 7: 131. PMID: 34611148, PMCID: PMC8492731, DOI: 10.1038/s41523-021-00337-2.Peer-Reviewed Original ResearchBreast cancerPredictive biomarkersPathologic complete response rateStage 2/3 breast cancerHER2-negative breast cancerPhase 2 clinical trialType I insulin-like growth factor receptorDrug-induced hyperglycemiaStandard neoadjuvant therapyComplete response rateUse of metforminI insulin-like growth factor receptorInsulin-like growth factor receptorPutative predictive biomarkersGrowth factor receptorI-SPY2Neoadjuvant therapyNeoadjuvant treatmentTreatment armsClinical trialsElevated hemoglobinNovel agentsGanitumabResponse rateCare paclitaxelA Novel Immunomodulatory 27-Gene Signature to Predict Response to Neoadjuvant Immunochemotherapy for Primary Triple-Negative Breast Cancer
Iwase T, Blenman KRM, Li X, Reisenbichler E, Seitz R, Hout D, Nielsen TJ, Schweitzer BL, Bailey DB, Shen Y, Zhang X, Pusztai L, Ueno NT. A Novel Immunomodulatory 27-Gene Signature to Predict Response to Neoadjuvant Immunochemotherapy for Primary Triple-Negative Breast Cancer. Cancers 2021, 13: 4839. PMID: 34638323, PMCID: PMC8508147, DOI: 10.3390/cancers13194839.Peer-Reviewed Original ResearchPD-L1 expressionNeoadjuvant immunochemotherapyPrimary triple-negative breast cancerTriple-negative breast cancerPrecise predictive biomarkersImmunomodulatory subtypeNovel immunomodulatoryPrimary TNBCTNBC responsePCR ratePredictive biomarkersPrimary tumorIM subtypesBreast cancerImmunochemotherapyLarge cohortTNBCImmunohistochemistryPilot studySubtypesExpressionPCRDurvalumabPatientsCohort
2020
Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer
Kos Z, Roblin E, Kim RS, Michiels S, Gallas BD, Chen W, van de Vijver KK, Goel S, Adams S, Demaria S, Viale G, Nielsen TO, Badve SS, Symmans WF, Sotiriou C, Rimm DL, Hewitt S, Denkert C, Loibl S, Luen SJ, Bartlett JMS, Savas P, Pruneri G, Dillon DA, Cheang MCU, Tutt A, Hall JA, Kok M, Horlings HM, Madabhushi A, van der Laak J, Ciompi F, Laenkholm AV, Bellolio E, Gruosso T, Fox SB, Araya JC, Floris G, Hudeček J, Voorwerk L, Beck AH, Kerner J, Larsimont D, Declercq S, Van den Eynden G, Pusztai L, Ehinger A, Yang W, AbdulJabbar K, Yuan Y, Singh R, Hiley C, Bakir MA, Lazar AJ, Naber S, Wienert S, Castillo M, Curigliano G, Dieci MV, André F, Swanton C, Reis-Filho J, Sparano J, Balslev E, Chen IC, Stovgaard EIS, Pogue-Geile K, Blenman KRM, Penault-Llorca F, Schnitt S, Lakhani SR, Vincent-Salomon A, Rojo F, Braybrooke JP, Hanna MG, Soler-Monsó MT, Bethmann D, Castaneda CA, Willard-Gallo K, Sharma A, Lien HC, Fineberg S, Thagaard J, Comerma L, Gonzalez-Ericsson P, Brogi E, Loi S, Saltz J, Klaushen F, Cooper L, Amgad M, Moore DA, Salgado R. Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer. Npj Breast Cancer 2020, 6: 17. PMID: 32411819, PMCID: PMC7217863, DOI: 10.1038/s41523-020-0156-0.Peer-Reviewed Original ResearchStromal tumor-infiltrating lymphocytesEarly TNBCBreast cancerHER2-positive breast cancerTumor-infiltrating lymphocytesLymphocyte distributionStromal tumorsInflammatory cellsPredictive biomarkersTreatment selectionPrognostic toolClinical practiceOutcome estimatesLymphocytesReproducible assessmentTNBCTumorsCancerScoring guidelinesMultiple areasTumor boundariesRisk estimationImpact of discrepanciesRing studiesAssessmentEarly 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
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 framework to assess the cost effectiveness of predictive biomarkers in oncology: Test Incremental Cost Effectiveness Ratio (TICER).
Safonov A, Shi W, Platt J, Aktas B, Kurita T, Pusztai L, Hatzis C. A framework to assess the cost effectiveness of predictive biomarkers in oncology: Test Incremental Cost Effectiveness Ratio (TICER). Journal Of Clinical Oncology 2015, 33: 6621-6621. DOI: 10.1200/jco.2015.33.15_suppl.6621.Peer-Reviewed Original Research
2013
Novel Functional Assay for Spindle-Assembly Checkpoint by Cyclin-Dependent Kinase Activity to Predict Taxane Chemosensitivity in Breast Tumor Patient
Torikoshi Y, Gohda K, Davis ML, Symmans WF, Pusztai L, Kazansky A, Nakayama S, Yoshida T, Matsushima T, Hortobagyi GN, Ishihara H, Kim SJ, Noguchi S, Ueno NT. Novel Functional Assay for Spindle-Assembly Checkpoint by Cyclin-Dependent Kinase Activity to Predict Taxane Chemosensitivity in Breast Tumor Patient. Journal Of Cancer 2013, 4: 697-702. PMID: 24312139, PMCID: PMC3842438, DOI: 10.7150/jca.6248.Peer-Reviewed Original ResearchTaxane-containing chemotherapyClinical responsePreoperative chemotherapyTaxane-induced cell deathAnthracycline-based treatmentFine-needle aspiration biopsyLarge prospective studiesBreast cancer patientsCyclin-dependent kinase 1Taxane-resistant tumorsLogistic regression analysisTaxane-containing therapyBreast tumor patientsDysfunction groupTaxane therapyPathologic responseProspective studyCancer patientsPredictive biomarkersTumor patientsBreast cancerClinicopathologic parametersAspiration biopsyBiopsy samplesPatientsBiomarker Analysis of Neoadjuvant Doxorubicin/Cyclophosphamide Followed by Ixabepilone or Paclitaxel in Early-Stage Breast Cancer
Horak CE, Pusztai L, Xing G, Trifan OC, Saura C, Tseng LM, Chan S, Welcher R, Liu D. Biomarker Analysis of Neoadjuvant Doxorubicin/Cyclophosphamide Followed by Ixabepilone or Paclitaxel in Early-Stage Breast Cancer. Clinical Cancer Research 2013, 19: 1587-1595. PMID: 23340299, DOI: 10.1158/1078-0432.ccr-12-1359.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic Combined Chemotherapy ProtocolsATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1Biomarkers, TumorBreast NeoplasmsCyclophosphamideDoxorubicinEpothilonesFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMicrofilament ProteinsMicrotubule-Associated ProteinsNeoadjuvant TherapyNeoplasm ProteinsNuclear ProteinsPaclitaxelPrognosisTubulinConceptsMDR1 protein expressionNeoadjuvant doxorubicin/cyclophosphamideEarly-stage breast cancerDoxorubicin/cyclophosphamidePositive patientsProtein expressionTreatment armsBreast cancerPathologic complete response rateEfficacy of ixabepiloneInvasive breast adenocarcinomaComplete response ratePhase II trialCore needle biopsyRates of pCRΒIII-tubulin proteinNeoadjuvant settingII trialNegative patientsGene expressionPrimary cancerPredictive biomarkersPredictive markerRisk ratioNeedle biopsy
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 proliferationIntratumor 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 Research
2008
Predictive biomarkers for preoperative endocrine therapy of stage II-III breast cancer by tissue microarrays
Zoubir M, Mathieu M, Liedtke C, Bidard F, Delaloge S, Corley L, Spielmann M, Pusztai L, André F, Symmans W. Predictive biomarkers for preoperative endocrine therapy of stage II-III breast cancer by tissue microarrays. Journal Of Clinical Oncology 2008, 26: 560-560. DOI: 10.1200/jco.2008.26.15_suppl.560.Peer-Reviewed Original Research
2006
DNA arrays as predictors of efficacy of adjuvant/neoadjuvant chemotherapy in breast cancer patients: Current data and issues on study design
Andre F, Mazouni C, Hortobagyi GN, Pusztai L. DNA arrays as predictors of efficacy of adjuvant/neoadjuvant chemotherapy in breast cancer patients: Current data and issues on study design. Biochimica Et Biophysica Acta 2006, 1766: 197-204. PMID: 16962247, DOI: 10.1016/j.bbcan.2006.08.002.Peer-Reviewed Original ResearchConceptsStudy designPredictive biomarkersBreast cancer patientsPredictors of efficacyBreast cancer populationCase-control studySevere side effectsNeoadjuvant chemotherapyResistant patientsCancer patientsCancer populationBreast cancerSide effectsMolecular subclassesPredictive diagnostic toolGene signatureChemotherapyPatientsCancer pharmacogenomicsVariable benefitDiagnostic toolBiomarkersCurrent dataEfficacyPredictors