2020
PD-L1 Protein Expression on Both Tumor Cells and Macrophages are Associated with Response to Neoadjuvant Durvalumab with Chemotherapy in Triple-negative Breast Cancer
Ahmed FS, Gaule P, McGuire J, Patel K, Blenman K, Pusztai L, Rimm DL. PD-L1 Protein Expression on Both Tumor Cells and Macrophages are Associated with Response to Neoadjuvant Durvalumab with Chemotherapy in Triple-negative Breast Cancer. Clinical Cancer Research 2020, 26: 5456-5461. PMID: 32709714, PMCID: PMC7572612, DOI: 10.1158/1078-0432.ccr-20-1303.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntibodies, MonoclonalAntigens, CDAntigens, Differentiation, MyelomonocyticAntineoplastic Combined Chemotherapy ProtocolsB7-H1 AntigenBiomarkers, TumorCell ProliferationFemaleGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingMacrophagesMiddle AgedNeoadjuvant TherapyProgrammed Cell Death 1 ReceptorTriple Negative Breast NeoplasmsConceptsTriple-negative breast cancerPD-L1 expressionNeoadjuvant durvalumabTumor cellsImmune cellsBreast cancerPretreatment core-needle biopsiesPhase I/II clinical trialsPD-L1 protein expressionIMpassion 130 trialCore needle biopsyAmount of CD68Neoadjuvant settingMetastatic settingPD-L1Clinical trialsNeedle biopsyInsufficient tissuePatientsCD68Stromal compartmentQuantitative immunofluorescenceChemotherapyFinal analysisProtein expressionEarly Modulation of Circulating MicroRNAs Levels in HER2-Positive Breast Cancer Patients Treated with Trastuzumab-Based Neoadjuvant Therapy
Di Cosimo S, Appierto V, Pizzamiglio S, Silvestri M, Baselga J, Piccart M, Huober J, Izquierdo M, de la Pena L, Hilbers FS, de Azambuja E, Untch M, Pusztai L, Pritchard K, Nuciforo P, Vincent-Salomon A, Symmans F, Apolone G, de Braud FG, Iorio MV, Verderio P, Daidone MG. Early Modulation of Circulating MicroRNAs Levels in HER2-Positive Breast Cancer Patients Treated with Trastuzumab-Based Neoadjuvant Therapy. International Journal Of Molecular Sciences 2020, 21: 1386. PMID: 32085669, PMCID: PMC7073028, DOI: 10.3390/ijms21041386.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedBreast NeoplasmsCell Line, TumorCirculating MicroRNAFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansLogistic ModelsMiddle AgedMultivariate AnalysisNeoadjuvant TherapyReceptor, ErbB-2TrastuzumabConceptsPathological complete responseNeoadjuvant therapyHER2-positive breast cancer patientsTrastuzumab-based neoadjuvant therapyAvailable predictive biomarkersBreast cancer patientsEstrogen receptor statusComplete responseReceptor statusCancer patientsPredictive biomarkersTreatment responseHCC progressionPatientsPredictive valueBivariate analysisMean differencePlasma pairsTherapyEarly modulationMicroRNA levelsTrastuzumabMAPK signalingMetabolism regulationKEGG analysis
2019
The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues
Marczyk M, Fu C, Lau R, Du L, Trevarton AJ, Sinn BV, Gould RE, Pusztai L, Hatzis C, Symmans WF. The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues. BMC Cancer 2019, 19: 1189. PMID: 31805884, PMCID: PMC6896723, DOI: 10.1186/s12885-019-6363-0.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBreast NeoplasmsExome SequencingFemaleFormaldehydeGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedParaffin EmbeddingRNASequence Analysis, RNATissue FixationConceptsBreast cancerFresh frozenParaffin-embedded tumor samplesFF samplesFFPE samplesConcordance correlation coefficientMixed-effects model analysisBreast cancer signaturesQiagen RNeasy kitWhole transcriptome RNA sequencingParaffin-embedded tissuesTranscriptome RNA sequencingLinear mixed-effects model analysisGene expression signaturesDifferent kitsClinical trialsGene signatureTumor samplesGene expressionTranslational researchCancerTissue samplesExpression signaturesArchival formalinSimilar concordanceImmune 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 ResearchMeSH KeywordsAntineoplastic Agents, ImmunologicalB7-H1 AntigenBevacizumabBreast NeoplasmsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingNeoadjuvant TherapyTreatment OutcomeTumor MicroenvironmentConceptsPathologic 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 functionImmune microenvironment of triple-negative breast cancer in African-American and Caucasian women
O’Meara T, Safonov A, Casadevall D, Qing T, Silber A, Killelea B, Hatzis C, Pusztai L. Immune microenvironment of triple-negative breast cancer in African-American and Caucasian women. Breast Cancer Research And Treatment 2019, 175: 247-259. PMID: 30725384, PMCID: PMC6666415, DOI: 10.1007/s10549-019-05156-5.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerCaucasian breast cancersER-positive cancersBreast cancerTIL countImmune microenvironmentCaucasian patientsMolecular subtypesAA TNBCHuman epidermal growth factor receptor 2Epidermal growth factor receptor 2Pathologic complete responseGrowth factor receptor 2Immune cell distributionImmune cell populationsCancer Genome Atlas (TCGA) databaseConsistent racial differencesFactor receptor 2Immune gene expressionImmune attenuationNeoadjuvant chemotherapyLymphocyte countLymphocyte infiltrationComplete responseTNBC cases
2018
CD68, CD163, and matrix metalloproteinase 9 (MMP-9) co-localization in breast tumor microenvironment predicts survival differently in ER-positive and -negative cancers
Pelekanou V, Villarroel-Espindola F, Schalper KA, Pusztai L, Rimm DL. CD68, CD163, and matrix metalloproteinase 9 (MMP-9) co-localization in breast tumor microenvironment predicts survival differently in ER-positive and -negative cancers. Breast Cancer Research 2018, 20: 154. PMID: 30558648, PMCID: PMC6298021, DOI: 10.1186/s13058-018-1076-x.Peer-Reviewed Original ResearchMeSH KeywordsAntigens, CDAntigens, Differentiation, MyelomonocyticAntineoplastic AgentsBiomarkers, TumorBreastBreast NeoplasmsDisease-Free SurvivalFemaleGene Expression Regulation, NeoplasticHumansMacrophagesMatrix Metalloproteinase 9Middle AgedPatient SelectionPrognosisReceptors, Cell SurfaceReceptors, EstrogenRetrospective StudiesSurvival AnalysisTissue Array AnalysisTumor MicroenvironmentConceptsTumor-associated macrophagesOverall survivalQuantitative immunofluorescenceMacrophage markersBreast cancerHigh expressionPan-macrophage marker CD68Triple-negative breast cancerCD163/CD68Multiplexed quantitative immunofluorescenceImproved overall survivalProtein expressionWorse overall survivalPoor overall survivalMMP-9 protein expressionSubclass of patientsMacrophage-targeted therapiesMatrix metalloproteinase-9Tissue microarray formatMMP-9 proteinBreast tumor microenvironmentModulator of responseParaffin-embedded tissuesBreast cancer biomarkersCohort BTumor infiltrating lymphocytes and PD-L1 expression in pre- and post-treatment breast cancers in the SWOG S0800 Phase II neoadjuvant chemotherapy trial
Pelekanou V, Barlow WE, Nahleh Z, Wasserman B, Lo YC, von Wahlde MK, Hayes D, Hortobagyi GN, Gralow J, Tripathy D, Porter P, Szekely B, Hatzis C, Rimm DL, Pusztai L. Tumor infiltrating lymphocytes and PD-L1 expression in pre- and post-treatment breast cancers in the SWOG S0800 Phase II neoadjuvant chemotherapy trial. Molecular Cancer Therapeutics 2018, 17: molcanther.1005.2017. PMID: 29588392, PMCID: PMC6548451, DOI: 10.1158/1535-7163.mct-17-1005.Peer-Reviewed Original ResearchConceptsPD-L1 expressionPathologic complete responseTIL countPosttreatment tissuePD-L1Estrogen receptorImmune checkpoint inhibitor therapyPD-L1 positivity rateTumor-infiltrating lymphocyte countsDoxorubicin/cyclophosphamideCheckpoint inhibitor therapyPD-L1 levelsMol Cancer TherNab-paclitaxelLymphocyte countResidual cancerComplete responseER statusImmune changesInhibitor therapyCox regressionPatient populationControl armClinical trialsPositivity rateAn 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
Association Between Genomic Metrics and Immune Infiltration in Triple-Negative Breast Cancer
Karn T, Jiang T, Hatzis C, Sänger N, El-Balat A, Rody A, Holtrich U, Becker S, Bianchini G, Pusztai L. Association Between Genomic Metrics and Immune Infiltration in Triple-Negative Breast Cancer. JAMA Oncology 2017, 3: 1707-1711. PMID: 28750120, PMCID: PMC5824276, DOI: 10.1001/jamaoncol.2017.2140.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorCohort StudiesGene DosageGene Expression ProfilingGene Expression Regulation, NeoplasticGenetic HeterogeneityHumansImmunologic SurveillanceLymphocyte CountLymphocytes, Tumor-InfiltratingPrognosisSequence Analysis, DNASequence Analysis, RNASurvival AnalysisTriple Negative Breast NeoplasmsConceptsTriple-negative breast cancerImmune infiltrationTNBC cohortBetter prognosisPrognostic categoriesPoor prognosisInverse associationBreast cancerImmune surveillanceImmune checkpoint inhibitor therapyMore effective immunotherapy strategiesSubset of TNBCLow immune cell infiltrationClonal heterogeneityCheckpoint inhibitor therapySelection of patientsImmune cell infiltrationEffective immunotherapy strategiesIndependent validation cohortPatient survival informationLymphocyte countImmunotherapy strategiesInhibitor therapyNeoantigen loadValidation cohortEffect of neoadjuvant chemotherapy on tumor-infiltrating lymphocytes and PD-L1 expression in breast cancer and its clinical significance
Pelekanou V, Carvajal-Hausdorf DE, Altan M, Wasserman B, Carvajal-Hausdorf C, Wimberly H, Brown J, Lannin D, Pusztai L, Rimm DL. Effect of neoadjuvant chemotherapy on tumor-infiltrating lymphocytes and PD-L1 expression in breast cancer and its clinical significance. Breast Cancer Research 2017, 19: 91. PMID: 28784153, PMCID: PMC5547502, DOI: 10.1186/s13058-017-0884-8.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedB7-H1 AntigenBreast NeoplasmsCD8-Positive T-LymphocytesDisease-Free SurvivalFemaleGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingMiddle AgedNeoadjuvant TherapyPrognosisConceptsStromal tumor-infiltrating lymphocytesPD-L1 expressionTumor-infiltrating lymphocytesRecurrence-free survivalNeoadjuvant chemotherapyResidual cancer tissueTIL countBreast cancerCancer tissuesDeath ligand 1 (PD-L1) protein expressionNode-positive breast cancerImproved recurrence-free survivalPD-L1 protein expressionHigher TIL countsPD-L1 statusProtein expressionBreast cancer patientsBreast cancer tissuesPost-treatment samplesPrechemotherapy samplesTIL infiltrationResidual cancerImmune markersResidual diseasePatient cohortIntegrated 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 ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsCell Line, TumorCluster AnalysisFemaleGene Expression Regulation, NeoplasticHumansMesodermMicroRNAsOncostatin MReceptor, ErbB-2Receptors, EstrogenRNA, MessengerTranscriptomeTriple Negative Breast NeoplasmsConceptsEpidermal 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
2015
Prospective assessment of the decision-making impact of the Breast Cancer Index in recommending extended adjuvant endocrine therapy for patients with early-stage ER-positive breast cancer
Sanft T, Aktas B, Schroeder B, Bossuyt V, DiGiovanna M, Abu-Khalaf M, Chung G, Silber A, Hofstatter E, Mougalian S, Epstein L, Hatzis C, Schnabel C, Pusztai L. Prospective assessment of the decision-making impact of the Breast Cancer Index in recommending extended adjuvant endocrine therapy for patients with early-stage ER-positive breast cancer. Breast Cancer Research And Treatment 2015, 154: 533-541. PMID: 26578401, PMCID: PMC4661200, DOI: 10.1007/s10549-015-3631-9.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAntineoplastic Agents, HormonalAnxietyBreast NeoplasmsChemotherapy, AdjuvantDecision MakingFemaleGene Expression Regulation, NeoplasticGenetic TestingHumansMiddle AgedNeoplasm Recurrence, LocalPrognosisProspective StudiesReceptors, EstrogenSurveys and QuestionnairesTamoxifenConceptsBreast Cancer IndexExtended endocrine therapyER-positive breast cancerAdjuvant endocrine therapyEndocrine therapyDecisional Conflict ScaleBreast cancerCancer indexPhysician recommendationRisk/benefit discussionEarly-stage estrogen receptorEndocrine therapy trialsYale Cancer CenterPositive breast cancerState-Trait Anxiety Inventory FormMean STAIExtended therapyLate recurrenceAbsolute benefitCancer CenterPatient satisfactionPrognostic informationTreatment recommendationsPatient anxietyImproved outcomesCharacterization 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 cancersThe cell cycle regulator 14-3-3σ opposes and reverses cancer metabolic reprogramming
Phan L, Chou PC, Velazquez-Torres G, Samudio I, Parreno K, Huang Y, Tseng C, Vu T, Gully C, Su CH, Wang E, Chen J, Choi HH, Fuentes-Mattei E, Shin JH, Shiang C, Grabiner B, Blonska M, Skerl S, Shao Y, Cody D, Delacerda J, Kingsley C, Webb D, Carlock C, Zhou Z, Hsieh YC, Lee J, Elliott A, Ramirez M, Bankson J, Hazle J, Wang Y, Li L, Weng S, Rizk N, Wen YY, Lin X, Wang H, Wang H, Zhang A, Xia X, Wu Y, Habra M, Yang W, Pusztai L, Yeung SC, Lee MH. The cell cycle regulator 14-3-3σ opposes and reverses cancer metabolic reprogramming. Nature Communications 2015, 6: 7530. PMID: 26179207, PMCID: PMC4507299, DOI: 10.1038/ncomms8530.Peer-Reviewed Original ResearchMeSH Keywords14-3-3 ProteinsAdultAgedAged, 80 and overBiomarkers, TumorBreast NeoplasmsCell Line, TumorDisease-Free SurvivalEnergy MetabolismExoribonucleasesFemaleGene Expression Regulation, NeoplasticGene Knockout TechniquesGlutamineGlycolysisHCT116 CellsHumansMiddle AgedOrganelle BiogenesisPrognosisProteolysisProto-Oncogene Proteins c-mycUbiquitinationYoung AdultConceptsCancer metabolic reprogrammingMetabolic reprogrammingRecurrence-free survival ratesMetabolic gene expressionBreast cancer patientsCellular energy metabolismHallmarks of cancerMajor metabolic processesTumor glucose uptakeExtensive reprogrammingMetabolic programsMitochondrial biogenesisGene expressionTumorigenic transformationCancer glycolysisMolecular mechanismsReprogrammingCancer patientsMetabolic processesMetabolic shiftMeasurement of Domain-Specific HER2 (ERBB2) Expression May Classify Benefit From Trastuzumab in Breast Cancer
Carvajal-Hausdorf DE, Schalper KA, Pusztai L, Psyrri A, Kalogeras KT, Kotoula V, Fountzilas G, Rimm DL. Measurement of Domain-Specific HER2 (ERBB2) Expression May Classify Benefit From Trastuzumab in Breast Cancer. Journal Of The National Cancer Institute 2015, 107: djv136. PMID: 25991002, PMCID: PMC4554192, DOI: 10.1093/jnci/djv136.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntibodies, Monoclonal, HumanizedAntineoplastic AgentsAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBreast NeoplasmsChemotherapy, AdjuvantClinical Trials as TopicDisease-Free SurvivalExtracellular SpaceFemaleFluorescent Antibody TechniqueGene Expression Regulation, NeoplasticHumansIntracellular SpaceKaplan-Meier EstimateMiddle AgedPredictive Value of TestsPrognosisReceptor, ErbB-2Sensitivity and SpecificityTissue Array AnalysisTrastuzumabTreatment OutcomeConceptsHuman epidermal growth factor receptor 2ECD expressionICD statusLonger DFSQuantitative immunofluorescenceTrastuzumab therapyPrognostic valueBreast cancerTissue microarrayEpidermal growth factor receptor 2Adjuvant trastuzumab therapyDisease-free survival analysisTrastuzumab-treated patientsGrowth factor receptor 2High positive predictive valueHER2-positive tumorsKaplan-Meier estimatesFactor receptor 2ERBB2 gene amplificationHER2 protein expressionPositive predictive valueExtracellular domainAdjuvant chemotherapyHER2-ICDBetter DFS
2014
Metabolic isoenzyme shifts in cancer as potential novel therapeutic targets
Ononye SN, Shi W, Wali VB, Aktas B, Jiang T, Hatzis C, Pusztai L. Metabolic isoenzyme shifts in cancer as potential novel therapeutic targets. Breast Cancer Research And Treatment 2014, 148: 477-488. PMID: 25395317, DOI: 10.1007/s10549-014-3194-1.Peer-Reviewed Original ResearchMeSH KeywordsDatabases, ProteinEnergy MetabolismEnzyme InhibitorsGene Expression Regulation, NeoplasticGlycolysisHumansIsoenzymesMetabolic Networks and PathwaysMolecular Targeted TherapyNeoplasmsConceptsIsoform-specific inhibitorsMetabolic isoenzymesCancer cellsNeoplastic transformationMetabolic enzyme expressionFunctional redundancyEnzymatic functionIsoenzyme diversityAdditional isoformsCancer metabolismMetabolic enzymesSingle isoformMetabolic pathwaysPotential novel therapeutic targetNovel therapeutic targetMetabolic precursorsEnzyme expressionNormal cellsNew therapeutic strategiesStages of developmentIsoformsTherapeutic targetExpressionIsoenzyme expressionTreatment of cancerCancer cell–autonomous contribution of type I interferon signaling to the efficacy of chemotherapy
Sistigu A, Yamazaki T, Vacchelli E, Chaba K, Enot DP, Adam J, Vitale I, Goubar A, Baracco EE, Remédios C, Fend L, Hannani D, Aymeric L, Ma Y, Niso-Santano M, Kepp O, Schultze JL, Tüting T, Belardelli F, Bracci L, La Sorsa V, Ziccheddu G, Sestili P, Urbani F, Delorenzi M, Lacroix-Triki M, Quidville V, Conforti R, Spano JP, Pusztai L, Poirier-Colame V, Delaloge S, Penault-Llorca F, Ladoire S, Arnould L, Cyrta J, Dessoliers MC, Eggermont A, Bianchi ME, Pittet M, Engblom C, Pfirschke C, Préville X, Uzè G, Schreiber RD, Chow MT, Smyth MJ, Proietti E, André F, Kroemer G, Zitvogel L. Cancer cell–autonomous contribution of type I interferon signaling to the efficacy of chemotherapy. Nature Medicine 2014, 20: 1301-1309. PMID: 25344738, DOI: 10.1038/nm.3708.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Vesicular TransportAnimalsAnthracyclinesBreast NeoplasmsChemokine CXCL10DoxorubicinFemaleGene Expression Regulation, NeoplasticHumansImmunocompetenceInterferon Type IMice, Inbred C57BLMyxovirus Resistance ProteinsNeoadjuvant TherapyNeoplasm MetastasisReceptor, Interferon alpha-betaReceptors, Pattern RecognitionRNARNA, MessengerSignal TransductionToll-Like Receptor 3Treatment OutcomeStatistical 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 ResearchIn Situ Tumor PD-L1 mRNA Expression Is Associated with Increased TILs and Better Outcome in Breast Carcinomas
Schalper KA, Velcheti V, Carvajal D, Wimberly H, Brown J, Pusztai L, Rimm DL. In Situ Tumor PD-L1 mRNA Expression Is Associated with Increased TILs and Better Outcome in Breast Carcinomas. Clinical Cancer Research 2014, 20: 2773-2782. PMID: 24647569, DOI: 10.1158/1078-0432.ccr-13-2702.Peer-Reviewed Original ResearchB7-H1 AntigenBreast NeoplasmsCell Line, TumorFemaleFluorescent Antibody TechniqueGene Expression Regulation, NeoplasticHumansIn Situ HybridizationKaplan-Meier EstimateLymphatic MetastasisLymphocytes, Tumor-InfiltratingMiddle AgedMultivariate AnalysisNeoplasm Recurrence, LocalPrognosisReceptor, ErbB-2Receptors, EstrogenRNA, MessengerTissue Array AnalysisCombined analysis of gene expression, DNA copy number, and mutation profiling data to display biological process anomalies in individual breast cancers
Shi W, Balazs B, Györffy B, Jiang T, Symmans WF, Hatzis C, Pusztai L. Combined analysis of gene expression, DNA copy number, and mutation profiling data to display biological process anomalies in individual breast cancers. Breast Cancer Research And Treatment 2014, 144: 561-568. PMID: 24619174, DOI: 10.1007/s10549-014-2904-z.Peer-Reviewed Original ResearchConceptsDNA copy numberBiological processesIndividual molecular eventsCopy numberGene expressionMolecular eventsMulticellular organismal processGene Ontology databaseGO biological processesSignal transduction pathwaysOrganismal processesGO termsMolecular dataTransduction pathwaysSiRNA screenComplex genomic abnormalitiesIndividual cancersOntology databaseFunctional roleDriver eventsCell growthSequence abnormalitiesBreast cancer cell linesCancer cell linesGenomic abnormalities