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 integrityPathwayCellsAssessment of stained direct cytology smears of breast cancer for whole transcriptome and targeted messenger RNA sequencing
Marczyk M, Fu C, Lau R, Du L, Trevarton A, Sinn B, Gould R, Pusztai L, Hatzis C, Symmans W. Assessment of stained direct cytology smears of breast cancer for whole transcriptome and targeted messenger RNA sequencing. Cancer Cytopathology 2023, 131: 289-299. PMID: 36650408, PMCID: PMC10614161, DOI: 10.1002/cncy.22679.Peer-Reviewed Original ResearchConceptsCytology smearsBreast cancerConcordance correlation coefficientTumor tissue samplesParaffin-embedded sectionsClinical diagnostic proceduresSurgical resectionRNA sequencingTumor stromaCytologic specimensDiagnostic proceduresLin's concordance correlation coefficientPapanicolaou stainCancerTissue samplesDNA mutation testingSmearsSimilar concordanceTranscriptome RNA-SeqDiagnostic cytologyAllele fractionExpression levelsRNA-seqExpression of genesGene expression levels
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
2014
Global gene expression changes induced by prolonged cold ischemic stress and preservation method of breast cancer tissue
Aktas B, Sun H, Yao H, Shi W, Hubbard R, Zhang Y, Jiang T, Ononye SN, Wali VB, Pusztai L, Symmans WF, Hatzis C. Global gene expression changes induced by prolonged cold ischemic stress and preservation method of breast cancer tissue. Molecular Oncology 2014, 8: 717-727. PMID: 24602449, PMCID: PMC4048748, DOI: 10.1016/j.molonc.2014.02.002.Peer-Reviewed Original ResearchConceptsGlobal gene expression changesGlobal gene expressionGene expression changesGenomic signaturesResponse genesGene expressionSensitive transcriptsExpression changesStress response genesCell cycle regulationSignificant transcriptional changesExpression levelsCycle regulationTranscriptional changesIndividual probe setsInduced transcriptsAffected transcriptsProtein processingEnrichment analysis
2012
High stearoyl-CoA desaturase 1 expression is associated with shorter survival in breast cancer patients
Holder AM, Gonzalez-Angulo AM, Chen H, Akcakanat A, Do KA, Fraser Symmans W, Pusztai L, Hortobagyi GN, Mills GB, Meric-Bernstam F. High stearoyl-CoA desaturase 1 expression is associated with shorter survival in breast cancer patients. Breast Cancer Research And Treatment 2012, 137: 319-327. PMID: 23208590, PMCID: PMC3556743, DOI: 10.1007/s10549-012-2354-4.Peer-Reviewed Original ResearchConceptsRelapse-free survivalShorter relapse-free survivalBreast cancerOverall survivalPatient ageMultivariable analysisClinical stageSCD1 levelsSCD1 expressionTumor subtypesStearoyl-CoA desaturase 1 expressionTriple-negative breast cancerMartingale residual plotsPrimary breast cancerSurvival of patientsBreast cancer patientsClinical pathologic characteristicsTumor clinical stageDesaturase 1 expressionBreast cancer subtypesBreast cancer cell linesExpression levelsRole of SCD1Fine needle aspiratesOverexpression of SCD1
2011
P4-03-04: Identification of Molecular Targets for Cancer-Initiating Cells Using a Triple-Negative Breast Cancer Mouse Model.
Kai K, Iwamoto T, Pusztai L, Hortobagyi G, Saya H, Ueno N. P4-03-04: Identification of Molecular Targets for Cancer-Initiating Cells Using a Triple-Negative Breast Cancer Mouse Model. Cancer Research 2011, 71: p4-03-04-p4-03-04. DOI: 10.1158/0008-5472.sabcs11-p4-03-04.Peer-Reviewed Original ResearchTriple-negative breast cancerTumor-initiating activityCancer-initiating cellsHuman triple-negative breast cancerTNBC mouse modelMammary fat padHigh tumor-initiating activityMouse modelTumor cellsRecipient miceClinical aggressivenessBreast cancerMouse mammary epithelial cellsFat padTriple-negative breast cancer mouse modelBackground Triple-negative breast cancerBreast cancer mouse modelAnti-HER2 agentsMouse mammary fat padMolecular profileBreast cancer subtypesCancer mouse modelEndothelin-A receptorExpression levelsCancer initiating cellsPlasma microRNA 210 levels correlate with sensitivity to trastuzumab and tumor presence in breast cancer patients
Jung E, Santarpia L, Kim J, Esteva FJ, Moretti E, Buzdar AU, Di Leo A, Le X, Bast RC, Park S, Pusztai L, Calin GA. Plasma microRNA 210 levels correlate with sensitivity to trastuzumab and tumor presence in breast cancer patients. Cancer 2011, 118: 2603-2614. PMID: 22370716, PMCID: PMC3864019, DOI: 10.1002/cncr.26565.Peer-Reviewed Original ResearchConceptsBreast cancer patientsPositive breast cancerMiR-210 levelsBreast cancerMiR-210Cancer patientsMicroRNA expression levelsTumor presenceExpression levelsPlasma samplesBT474 cellsNeoadjuvant trastuzumab-based chemotherapyHuman epidermal growth factor receptor 2Epidermal growth factor receptor 2Trastuzumab-resistant breast cancer cellsMiR expression levelsTrastuzumab-based chemotherapyPathologic complete responseGrowth factor receptor 2Cancer cellsPostoperative plasma samplesPreoperative plasma samplesReverse transcriptase-polymerase chain reactionQuantitative reverse transcriptase-polymerase chain reactionMiR-210 expression
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
Identification of predictive markers to differentiate ixabepilone from paclitaxel activity in ER-negative breast cancer patients
Wu S, Chasalow S, Lee H, Xu L, Paul B, Mokliatchouk O, Symmans W, Zerba K, Pusztai L, Clark E. Identification of predictive markers to differentiate ixabepilone from paclitaxel activity in ER-negative breast cancer patients. Journal Of Clinical Oncology 2007, 25: 2525-2525. DOI: 10.1200/jco.2007.25.18_suppl.2525.Peer-Reviewed Original ResearchBreast cancer patientsER patientsCancer patientsPredictive markerClinical trialsPaclitaxel activityER-negative breast cancer patientsComplete pathological responseER-negative patientsTaxane-containing regimensTaxane-containing therapyExpression levelsIxabepilone treatmentPatient selectionBC patientsPathological responseIxabepilonePatientsTherapeutic valueProtein 3SiRNA studiesDifferential markersROC curveTrialsCandidate markers
2003
Jun activation domain binding protein 1 expression is associated with low p27(Kip1)levels in node-negative breast cancer.
Esteva FJ, Sahin AA, Rassidakis GZ, Yuan LX, Smith TL, Yang Y, Gilcrease MZ, Cristofanilli M, Nahta R, Pusztai L, Claret FX. Jun activation domain binding protein 1 expression is associated with low p27(Kip1)levels in node-negative breast cancer. Clinical Cancer Research 2003, 9: 5652-9. PMID: 14654548.Peer-Reviewed Original ResearchMeSH KeywordsBreast NeoplasmsCell Cycle ProteinsCOP9 Signalosome ComplexCyclin-Dependent Kinase Inhibitor p27DNA-Binding ProteinsFemaleGene Expression Regulation, NeoplasticGenes, Tumor SuppressorHumansImmunohistochemistryIntracellular Signaling Peptides and ProteinsLymphatic MetastasisMiddle AgedPeptide HydrolasesReceptor, ErbB-2Receptors, EstrogenSurvival AnalysisTime FactorsTranscription FactorsTumor Suppressor ProteinsConceptsNode-negative breast cancerAdjacent normal tissuesInvasive breast carcinomaBreast cancerJab1 overexpressionNormal tissuesBreast carcinomaAdjuvant systemic therapyDisease-free survivalIndependent prognostic factorInvasive breast cancerLow nuclear gradeBreast cancer tissuesExpression levelsProtein-1 expressionBreast tumor tissuesWestern blot analysisDomain-binding protein 1Patient agePrognostic factorsSystemic therapyPrognostic significanceTumor sizeNuclear gradeInvasive tumors
1998
Cell surface density of p185(c-erbB-2) determines susceptibility to anti-p185(c-erbB-2)-ricin A chain (RTA) immunotoxin therapy alone and in combination with anti-p170(EGFR)-RTA in ovarian cancer cells.
Dean G, Pusztai L, Xu F, O'Briant K, DeSombre K, Conaway M, Boyer C, Mendelsohn J, Bast R. Cell surface density of p185(c-erbB-2) determines susceptibility to anti-p185(c-erbB-2)-ricin A chain (RTA) immunotoxin therapy alone and in combination with anti-p170(EGFR)-RTA in ovarian cancer cells. Clinical Cancer Research 1998, 4: 2545-50. PMID: 9796989.Peer-Reviewed Original ResearchConceptsOvarian cancer cellsReceptors/cellCancer cellsC-erbBSynergistic cytotoxicityCopies/cellTumor cellsSKOV3 human ovarian cancer cellsHuman ovarian cancer cellsClonogenic tumor cellsCell surface densityBreast cancerRTA immunotoxinsNude miceSame immunotoxinFirst treatmentAnchorage-independent growthAnchorage-dependent growthVivo growthClonogenic cellsImmunotoxinExpression levelsSignificant correlationCell linesNormal cells