2018
A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT)
Mateo J, Chakravarty D, Dienstmann R, Jezdic S, Gonzalez-Perez A, Lopez-Bigas N, Ng CKY, Bedard PL, Tortora G, Douillard J, Van Allen EM, Schultz N, Swanton C, André F, Pusztai L. A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT). Annals Of Oncology 2018, 29: 1895-1902. PMID: 30137196, PMCID: PMC6158764, DOI: 10.1093/annonc/mdy263.Peer-Reviewed Original ResearchConceptsESMO ScaleMolecular targetsClinical actionabilityPrecision Medicine Working GroupGenomic alterationsPrecision medicineRoutine clinical decisionEvidence-based criteriaMedicine Working GroupLack of evidencePreclinical evidenceClinical benefitClinical evidencePatient populationClassification systemClinical managementCancer precision medicineInvestigational targetsPatient managementMolecular aberrationsTumor typesClinical decisionClinical targetsAvailable evidenceEuropean Society
2014
Statistical measures of transcriptional diversity capture genomic heterogeneity of cancer
Jiang T, Shi W, Natowicz R, Ononye SN, Wali VB, Kluger Y, Pusztai L, Hatzis C. Statistical measures of transcriptional diversity capture genomic heterogeneity of cancer. BMC Genomics 2014, 15: 876. PMID: 25294321, PMCID: PMC4197225, DOI: 10.1186/1471-2164-15-876.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 survival
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 sizeCohortCancerMaximizing biomarker discovery by minimizing gene signatures
Chang C, Wang J, Zhao C, Fostel J, Tong W, Bushel PR, Deng Y, Pusztai L, Symmans WF, Shi T. Maximizing biomarker discovery by minimizing gene signatures. BMC Genomics 2011, 12: s6. PMID: 22369133, PMCID: PMC3287502, DOI: 10.1186/1471-2164-12-s5-s6.Peer-Reviewed Original Research
2010
Gene Pathways Associated With Prognosis and Chemotherapy Sensitivity in Molecular Subtypes of Breast Cancer
Iwamoto T, Bianchini G, Booser D, Qi Y, Coutant C, Shiang CY, Santarpia L, Matsuoka J, Hortobagyi GN, Symmans WF, Holmes FA, O’Shaughnessy J, Hellerstedt B, Pippen J, Andre F, Simon R, Pusztai L. Gene Pathways Associated With Prognosis and Chemotherapy Sensitivity in Molecular Subtypes of Breast Cancer. Journal Of The National Cancer Institute 2010, 103: 264-272. PMID: 21191116, DOI: 10.1093/jnci/djq524.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBreast NeoplasmsChemotherapy, AdjuvantConfounding Factors, EpidemiologicCytochrome P-450 Enzyme InhibitorsCytochrome P-450 Enzyme SystemDatabases, GeneticDrug Resistance, NeoplasmFemaleGene Expression Regulation, NeoplasticGTP-Binding ProteinsHumansMiddle AgedNeoadjuvant TherapyNeoplasm StagingPredictive Value of TestsPrognosisReceptors, EstrogenSignal TransductionTreatment OutcomeConceptsER-negative breast cancerPathological complete responseER-positive cancersER-negative cancersBreast cancerChemotherapy responseComplete responseBetter prognosisChemotherapy sensitivityLymph node-negative breast cancerNode-negative breast cancerSystemic adjuvant therapyCell cycle-related gene setsBreast cancer subtypesIngenuity Pathway AnalysisAdjuvant therapyPreoperative chemotherapyPoor prognosisPooled analysisEstrogen receptorTreatment responseMolecular subtypesAdditional cohortPrognosisStage I