2018
An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes
Győrffy B, Pongor L, Bottai G, Li X, Budczies J, Szabó A, Hatzis C, Pusztai L, Santarpia L. An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes. British Journal Of Cancer 2018, 118: 1107-1114. PMID: 29559730, PMCID: PMC5931099, DOI: 10.1038/s41416-018-0030-0.Peer-Reviewed Original ResearchConceptsHER2-negative tumorsBreast cancer patientsCancer patientsER-positive/HER2-negative tumorsBreast cancer molecular subtypesMETABRIC data setMolecular breast cancer subtypesCox regression analysisBreast cancer subtypesCancer molecular subtypesGene expression profilesMann-Whitney U testRegression analysisMultivariate regression analysisPrognostic valueKaplan-MeierBreast cancerClinical dataDisease outcomeTCGA cohortGene expressionMolecular subtypesCancer-associated genesCancer-related genesClinical relevance
2017
Integrated MicroRNA–mRNA Profiling Identifies Oncostatin M as a Marker of Mesenchymal-Like ER-Negative/HER2-Negative Breast Cancer
Bottai G, Diao L, Baggerly KA, Paladini L, Győrffy B, Raschioni C, Pusztai L, Calin GA, Santarpia L. Integrated MicroRNA–mRNA Profiling Identifies Oncostatin M as a Marker of Mesenchymal-Like ER-Negative/HER2-Negative Breast Cancer. International Journal Of Molecular Sciences 2017, 18: 194. PMID: 28106823, PMCID: PMC5297825, DOI: 10.3390/ijms18010194.Peer-Reviewed Original ResearchConceptsEpidermal growth factorExpression profilesMessenger RNA (mRNA) expression profilesMiRNA-regulated pathwaysAvailable gene expression profilesOncostatin M signalingMesenchymal-like breast cancer cellsGene expression profilesRNA expression profilesImmune-related pathwaysPathway regulationGlobal miRNAOncogenic networksGene expressionSpecific miRNAsPathway analysisBreast cancer cellsHuman estrogen receptorTriple-negative breast cancerEMT pathwayMesenchymal transitionMiRNAMRNA dataOncostatin MCancer cells
2013
Comparison of molecular subtype distribution in triple-negative inflammatory and non-inflammatory breast cancers
Masuda H, Baggerly KA, Wang Y, Iwamoto T, Brewer T, Pusztai L, Kai K, Kogawa T, Finetti P, Birnbaum D, Dirix L, Woodward WA, Reuben JM, Krishnamurthy S, Symmans W, Van Laere SJ, Bertucci F, Hortobagyi GN, Ueno NT. Comparison of molecular subtype distribution in triple-negative inflammatory and non-inflammatory breast cancers. Breast Cancer Research 2013, 15: r112. PMID: 24274653, PMCID: PMC3978878, DOI: 10.1186/bcr3579.Peer-Reviewed Original ResearchConceptsInflammatory breast cancerTriple-negative breast cancerTN-IBCIBC statusTNBC subtypesBreast cancerTNBC cohortClinical outcomesNon-inflammatory breast cancerMolecular subtype distributionWorld IBC ConsortiumRecurrence-free survivalNon-inflammatory typeClinical characteristicsOverall survivalPoor prognosisClinical behaviorSubtype distributionConclusionsOur dataHeterogeneous diseaseSubtypesCancerSignificant predictorsGene expression profilesCohort
2009
Correlations of estrogen receptor (ER) related genomic transcription and ER gene expression with increasing AJCC stage of ER-positive breast cancer
Andreopoulou E, Hatzis C, Booser D, Valero V, Wallace M, Sotiriou C, Hortobagyi G, Pusztai L, Symmans W. Correlations of estrogen receptor (ER) related genomic transcription and ER gene expression with increasing AJCC stage of ER-positive breast cancer. Journal Of Clinical Oncology 2009, 27: 1044-1044. DOI: 10.1200/jco.2009.27.15_suppl.1044.Peer-Reviewed Original ResearchER-positive breast cancerBreast cancerEstrogen receptorPathologic stageAJCC stageProgesterone receptorStage IIIAdvanced ER-positive breast cancerExpression levelsStage IV diseaseER gene expressionClinical samplesPatient clinical samplesPgR expression levelsInitial presentationTumor dependenceExpression of GAPDHAdvanced stageCancerGene expressionGenomic pathwayGAPDH gene expressionReceptor geneGene expression profilesFurther studies
2007
Gene expression profiling can predict pathological complete response (pCR) to anthracycline-based therapy in estrogen- receptor (ER) negative breast cancer (BC) patients
Desmedt C, André F, Azambuja E, Haibe-Kains B, Larsimont D, D'Hondt V, Di Leo A, Piccart M, Pusztai L, Sotiriou C. Gene expression profiling can predict pathological complete response (pCR) to anthracycline-based therapy in estrogen- receptor (ER) negative breast cancer (BC) patients. Journal Of Clinical Oncology 2007, 25: 10564-10564. DOI: 10.1200/jco.2007.25.18_suppl.10564.Peer-Reviewed Original ResearchPathological complete responseBreast cancerLarge seriesEstrogen receptor-negative breast cancer patientsNegative breast cancer patientsAffymetrix gene expression profilesAnthracycline-based therapyER-negative patientsBreast cancer patientsGene expression profilesOvarian suppressionComplete responseP53 signaturePrognostic valueCancer patientsSubgroup analysisMD AndersonStudent's t-test analysisTOP trialBC diseaseExpression profilesGene expression profilingTherapySignificant financial relationshipPatients
2005
Pharmacogenomics and Clinical Biomarkers in Drug Discovery and Development
Ross JS, Symmans WF, Pusztai L, Hortobagyi GN. Pharmacogenomics and Clinical Biomarkers in Drug Discovery and Development. American Journal Of Clinical Pathology 2005, 124: s29-s41. PMID: 16468416, DOI: 10.1309/xyqafanapync6x59.Peer-Reviewed Original ResearchConceptsHuman genome sequenceGene expression profilesGenome sequenceEpigenetic eventsExpression profilesProteomics researchDrug discoveryRapid evolutionComputational biologyPharmaceutical industryMolecular diagnosticsDiscoveryFurther understandingBiosensorRNABiologyAnticancerSequenceClinical biomarkersAnti-inflammatory drugsDrug efficacyToxicityPrediction of responseDevelopmentContinuous technological advancements
2003
Total RNA yield and microarray gene expression profiles from fine‐needle aspiration biopsy and core‐needle biopsy samples of breast carcinoma
Symmans WF, Ayers M, Clark EA, Stec J, Hess KR, Sneige N, Buchholz TA, Krishnamurthy S, Ibrahim NK, Buzdar AU, Theriault RL, Rosales MF, Thomas ES, Gwyn KM, Green MC, Syed AR, Hortobagyi GN, Pusztai L. Total RNA yield and microarray gene expression profiles from fine‐needle aspiration biopsy and core‐needle biopsy samples of breast carcinoma. Cancer 2003, 97: 2960-2971. PMID: 12784330, DOI: 10.1002/cncr.11435.Peer-Reviewed Original ResearchConceptsGene expression profilesTranscriptional profilesExpression profilesFine-needle aspiration biopsyGenomic databasesStromal gene expressionGene expressionTotal RNA yieldTotal RNABreast carcinomaTumor cell populationSubset of genesCDNA microarray analysisStromal cellsBiopsy samplesGene expression profilingCell populationsMicroscopic cell countsRNA yieldAspiration biopsyGenomic studiesTranscriptional profilingCDNA microarrayNonlymphoid stromal cellsExpression profiling