2024
Correlation of hormone receptor positive HER2-negative/MammaPrint high-2 breast cancer with triple negative breast cancer: Results from gene expression data from the ISPY2 trial.
Rios-Hoyo A, Xiong K, Marczyk M, García-Millán R, Wolf D, Huppert L, Nanda R, Yau C, Hirst G, van 't Veer L, Esserman L, Pusztai L. Correlation of hormone receptor positive HER2-negative/MammaPrint high-2 breast cancer with triple negative breast cancer: Results from gene expression data from the ISPY2 trial. Journal Of Clinical Oncology 2024, 42: 573-573. DOI: 10.1200/jco.2024.42.16_suppl.573.Peer-Reviewed Original ResearchGene expression dataGene expression analysisExpression dataExpressed genesExpression analysisTriple-negativeDistance analysisPathway analysisDifferential gene expression analysisCell cycle pathwayGene set enrichment analysisBreast cancerIngenuity Pathway AnalysisRate of pathological complete responseHigh-risk stage IIGlucocorticoid receptor signalingTriple negative breast cancerCycle pathwayPathological complete responseDNA repairEnrichment analysisOptimal treatment strategyNegative breast cancerI-SPY2 trialGenes
2023
Pan-cancer analysis of antibody-drug conjugate targets and putative predictors of treatment response
Bosi C, Bartha Á, Galbardi B, Notini G, Naldini M, Licata L, Viale G, Mariani M, Pistilli B, Ali H, André F, Piras M, Callari M, Barreca M, Locatelli A, Viganò L, Criscitiello C, Pusztai L, Curigliano G, Győrffy B, Dugo M, Bianchini G. Pan-cancer analysis of antibody-drug conjugate targets and putative predictors of treatment response. European Journal Of Cancer 2023, 195: 113379. PMID: 37913680, DOI: 10.1016/j.ejca.2023.113379.Peer-Reviewed Original ResearchConceptsGenotype-Tissue Expression (GTEx) databaseAntibody-drug conjugatesADC targetPan-cancer analysisCancer Genome AtlasExpression distributionGene expressionNew therapeutic opportunitiesTreatment responseExpression of determinantsPrimary tissuesGenome AtlasExpression levelsNormal tissuesPotential downstreamProtein expressionRelative expressionExpression databaseGenesTherapeutic opportunitiesExpressionTarget expressionMRNA levelsCancer typesInter-patient heterogeneityEvaluation of zero counts to better understand the discrepancies between bulk and single-cell RNA-Seq platforms
Zyla J, Papiez A, Zhao J, Qu R, Li X, Kluger Y, Polanska J, Hatzis C, Pusztai L, Marczyk M. Evaluation of zero counts to better understand the discrepancies between bulk and single-cell RNA-Seq platforms. Computational And Structural Biotechnology Journal 2023, 21: 4663-4674. PMID: 37841335, PMCID: PMC10568495, DOI: 10.1016/j.csbj.2023.09.035.Peer-Reviewed Original ResearchSingle-cell RNA-seq platformsSingle-cell RNA sequencingBulk RNA-seq dataRNA-seq platformsNumber of transcriptsLow-expression genesRNA-seq dataSingle-cell dataExpression levelsLow sequencing depthDiscordant genesRNA sequencingSequencing technologiesExpression shiftsPathway levelBiological pathwaysGene levelSequencing depthTranscriptomic platformsGenesIndividual cellsSingle cellsRNA integrityPathwayCells
2022
Cancer Relevance of Human Genes
Qing T, Mohsen H, Cannataro VL, Marczyk M, Rozenblit M, Foldi J, Murray M, Townsend J, Kluger Y, Gerstein M, Pusztai L. Cancer Relevance of Human Genes. Journal Of The National Cancer Institute 2022, 114: 988-995. PMID: 35417011, PMCID: PMC9275765, DOI: 10.1093/jnci/djac068.Peer-Reviewed Original ResearchConceptsCore cancer genesHuman genesFunctional importanceSomatic mutation frequencySelection pressureGene/protein networksCancer genesHigher somatic mutation frequencyNegative selection pressureGene-gene interaction networksMutation frequencyProtein-truncating variantsGenomic contextCell viabilityGenes decreasesCancer Genome AtlasInteraction networksProtein networkCancer relevanceCancer cell viabilityCell survivalGenesCancer biologyGenome AtlasSearch tools
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
2020
Multi-Omics Investigation of Innate Navitoclax Resistance in Triple-Negative Breast Cancer Cells
Marczyk M, Patwardhan GA, Zhao J, Qu R, Li X, Wali VB, Gupta AK, Pillai MM, Kluger Y, Yan Q, Hatzis C, Pusztai L, Gunasekharan V. Multi-Omics Investigation of Innate Navitoclax Resistance in Triple-Negative Breast Cancer Cells. Cancers 2020, 12: 2551. PMID: 32911681, PMCID: PMC7563413, DOI: 10.3390/cancers12092551.Peer-Reviewed Original ResearchTriple-negative breast cancer cellsCancer cellsBreast cancer cellsStress response genesMulti-omics landscapeCell population compositionDrug-induced cell deathMulti-omics investigationsCell linesBCL2 family inhibitorsSingle-cell analysisChromatin accessibilityGenome structureMDA-MB-231 triple-negative breast cancer cellsChromatin structureMethylation stateResponse genesFamily inhibitorsCell deathTNBC cell linesNumber variationsDefense mechanismsResistance mechanismsNew therapeutic strategiesGenes
2019
Immune profiling of pre- and post-treatment breast cancer tissues from the SWOG S0800 neoadjuvant trial
Li X, Warren S, Pelekanou V, Wali V, Cesano A, Liu M, Danaher P, Elliott N, Nahleh ZA, Hayes DF, Hortobagyi GN, Barlow WE, Hatzis C, Pusztai L. Immune profiling of pre- and post-treatment breast cancer tissues from the SWOG S0800 neoadjuvant trial. Journal For ImmunoTherapy Of Cancer 2019, 7: 88. PMID: 30967156, PMCID: PMC6457012, DOI: 10.1186/s40425-019-0563-7.Peer-Reviewed Original ResearchConceptsPathologic complete responseResidual diseaseTIL countGene expression levelsHigh expressionCellular stressNeoadjuvant chemotherapyImmune genesImmune-related genesStromal genesImmune functionImmune microenvironment changesMost immune functionsGenesCell typesPD-L1 protein expressionStem cellsHigher TIL countsPD-L1 expressionExpression levelsPrimary breast cancerT-cell markersImmune cell typesProtein expressionStromal function
2015
A genome-wide approach to link genotype to clinical outcome by utilizing next generation sequencing and gene chip data of 6,697 breast cancer patients
Pongor L, Kormos M, Hatzis C, Pusztai L, Szabó A, Győrffy B. A genome-wide approach to link genotype to clinical outcome by utilizing next generation sequencing and gene chip data of 6,697 breast cancer patients. Genome Medicine 2015, 7: 104. PMID: 26474971, PMCID: PMC4609150, DOI: 10.1186/s13073-015-0228-1.Peer-Reviewed Original ResearchConceptsRNA-seq dataNext-generation sequencingBreast cancer patientsTranscriptomic fingerprintGenome-wide approachesGeneration sequencingClinical outcomesCancer patientsHuman gene mutationsTumor suppressor geneGene chip dataSuch genesRNA-seqGene mutationsLarge breast cancer cohortGene expressionChip dataSuppressor geneBreast cancer cohortGenesMicroarray dataMutationsSomatic mutationsClinical characteristicsCox regressionCharacterization 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 cancers
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 ResearchBayesian Mixture Models for Assessment of Gene Differential Behaviour and Prediction of pCR through the Integration of Copy Number and Gene Expression Data
Trentini F, Ji Y, Iwamoto T, Qi Y, Pusztai L, Müller P. Bayesian Mixture Models for Assessment of Gene Differential Behaviour and Prediction of pCR through the Integration of Copy Number and Gene Expression Data. PLOS ONE 2013, 8: e68071. PMID: 23874497, PMCID: PMC3709899, DOI: 10.1371/journal.pone.0068071.Peer-Reviewed Original Research
2012
A 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
2009
Functional pathways analyses to identify candidate therapeutic targets in triple-negative breast cancer
Andre F, Dessen P, Job B, Delaloge S, Pusztai L, Lazar V. Functional pathways analyses to identify candidate therapeutic targets in triple-negative breast cancer. Journal Of Clinical Oncology 2009, 27: 569-569. DOI: 10.1200/jco.2009.27.15_suppl.569.Peer-Reviewed Original ResearchGene gainPathway analysisHigh resolution CGH arrayBRB-Array ToolsFunctional pathway analysisChromosome organizationTargetable pathwaysTriple-negative breast cancerMolecular classesGene setsCDNA arraysNotch pathwayCandidate therapeutic targetGenomic aberrationsNegative breast cancerCGH arrayHistonesPathway dysregulationPathwayGenesDifferential pathwaysVEGFA geneTherapeutic targetDysregulationHedgehog
2004
Breast cancer biomarkers and molecular medicine: part II
Ross JS, Linette GP, Stec J, Clark E, Ayers M, Leschly N, Symmans WF, Hortobagyi GN, Pusztai L. Breast cancer biomarkers and molecular medicine: part II. Expert Review Of Molecular Diagnostics 2004, 4: 169-188. PMID: 14995904, DOI: 10.1586/14737159.4.2.169.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsCell Adhesion MoleculesDNADrug Resistance, MultipleEndopeptidasesFemaleGene Expression ProfilingGenes, Tumor SuppressorHumansOncogenesPharmacogeneticsPrognosisProto-Oncogene Proteins c-bcl-2Receptors, EstrogenReceptors, ProgesteroneTelomeraseTranscription FactorsConceptsInvasion-associated proteinsMolecular medicineTumor suppressor geneTranscriptional profilingTranscription factorsDNA repairCell adhesion moleculeDrug resistance proteinsGenomic microarraysApoptosis regulatorSuppressor geneHormone receptor proteinsReceptor proteinBreast cancer biomarkersResistance proteinCancer biomarkersProteinBreast cancer prognostic factorsAdhesion moleculesCancer prognostic factorsPrognostic factorsTherapy responseGenesMethylationTelomerase
2003
Clinical Application of cDNA Microarrays in Oncology
Pusztai L, Ayers M, Stec J, Hortobágyi GN. Clinical Application of cDNA Microarrays in Oncology. The Oncologist 2003, 8: 252-258. PMID: 12773747, DOI: 10.1634/theoncologist.8-3-252.Peer-Reviewed Original ResearchConceptsHundreds of genesGene expression patternsSingle-gene markersIndividual genesTranscriptional profilingCDNA microarrayMRNA speciesDNA microarraysExpression patternsComplex biologyNovel targetImportant new toolMicroarrayClinical outcomesGenesHuman tissuesImportant clinical outcomesDiseased tissuesDrug developmentTrue clinical utilityClinical utilityClinical OncologyNew toolBiologyExciting new technology