2021
Network propagation-based prioritization of long tail genes in 17 cancer types
Mohsen H, Gunasekharan V, Qing T, Seay M, Surovtseva Y, Negahban S, Szallasi Z, Pusztai L, Gerstein MB. Network propagation-based prioritization of long tail genes in 17 cancer types. Genome Biology 2021, 22: 287. PMID: 34620211, PMCID: PMC8496153, DOI: 10.1186/s13059-021-02504-x.Peer-Reviewed Original ResearchConceptsCancer-relevant genesTail genesMobility genesNetwork propagation approachGenome-wide RNAiNetwork propagation methodCancer developmentPotential functional impactCancer cell survivalNew genesUnreported genesFunctional screeningCancer typesFunctional importanceCancer genesNovel potential therapeutic targetDriver genesCell survivalGenesMutational distributionsBiological interactionsPotential therapeutic targetFunctional impactGenomic alterationsInfrequent mutations
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
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 receptorSeventeen-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 cellsA network-based, integrative study to identify core biological pathways that drive breast cancer clinical subtypes
Dutta B, Pusztai L, Qi Y, André F, Lazar V, Bianchini G, Ueno N, Agarwal R, Wang B, Shiang CY, Hortobagyi GN, Mills GB, Symmans WF, Balázsi G. A network-based, integrative study to identify core biological pathways that drive breast cancer clinical subtypes. British Journal Of Cancer 2012, 106: 1107-1116. PMID: 22343619, PMCID: PMC3304402, DOI: 10.1038/bjc.2011.584.Peer-Reviewed Original ResearchMeSH KeywordsBreast NeoplasmsCell Line, TumorComputer SimulationDNA Copy Number VariationsEpithelial-Mesenchymal TransitionFemaleGene ExpressionGene Expression ProfilingGene Expression Regulation, NeoplasticGene Knockdown TechniquesGene Regulatory NetworksGenes, NeoplasmHumansModels, BiologicalProtein Interaction MapsReceptor, ErbB-2Receptors, EstrogenReceptors, ProgesteroneRNA InterferenceConceptsGenome-scale dataCore biological pathwaysTriple receptor-negative breast cancerProtein-protein interactionsCell line data setsGene knockdown experimentsGene copy number dataCopy number dataCopy number variation dataNumber variation dataMember genesGene networksTranscriptional disturbancesKnockdown experimentsBiological discoveryGene expressionFunctional specificityBiological pathwaysDifferential expressionIntegrative studyFunctional relevanceVariation dataLine data setsCell linesGenes
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 sizeCohortCancerA Genomic Predictor of Response and Survival Following Taxane-Anthracycline Chemotherapy for Invasive Breast Cancer
Hatzis C, Pusztai L, Valero V, Booser DJ, Esserman L, Lluch A, Vidaurre T, Holmes F, Souchon E, Wang H, Martin M, Cotrina J, Gomez H, Hubbard R, Chacón JI, Ferrer-Lozano J, Dyer R, Buxton M, Gong Y, Wu Y, Ibrahim N, Andreopoulou E, Ueno NT, Hunt K, Yang W, Nazario A, DeMichele A, O’Shaughnessy J, Hortobagyi GN, Symmans WF. A Genomic Predictor of Response and Survival Following Taxane-Anthracycline Chemotherapy for Invasive Breast Cancer. JAMA 2011, 305: 1873-1881. PMID: 21558518, PMCID: PMC5638042, DOI: 10.1001/jama.2011.593.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlgorithmsAnthracyclinesAntineoplastic Agents, HormonalAntineoplastic Combined Chemotherapy ProtocolsBiopsy, NeedleBreast NeoplasmsBridged-Ring CompoundsDisease-Free SurvivalDrug Resistance, NeoplasmFemaleForecastingGene Expression ProfilingGenes, erbB-2Genes, NeoplasmGenomicsHumansMiddle AgedNeoadjuvant TherapyNeoplasm Recurrence, LocalOligonucleotide Array Sequence AnalysisPredictive Value of TestsPrognosisProspective StudiesReceptors, EstrogenRiskTaxoidsConceptsDistant relapse-free survivalInvasive breast cancerBreast cancerGenomic predictorsD. Anderson Cancer CenterAnthracycline-based regimensER-negative subsetExcellent pathologic responseProspective multicenter studyRelapse-free survivalAbsolute risk reductionStandard cancer treatmentPredictors of responseIndependent validation cohortAnderson Cancer CenterNegative breast cancerCancer treatment strategiesSequential taxaneNeoadjuvant chemotherapyPreoperative chemotherapyPathologic responseWorse survivalEndocrine sensitivityER statusMulticenter study