2023
Validation of the Prognostic Usefulness of the Gene Expression Profiling Test in Patients with Uveal Melanoma
Miguez S, Lee R, Chan A, Demkowicz P, Jones B, Long C, Abramson D, Bosenberg M, Sznol M, Kluger H, Goldbaum M, Francis J, Pointdujour-Lim R, Bakhoum M. Validation of the Prognostic Usefulness of the Gene Expression Profiling Test in Patients with Uveal Melanoma. Ophthalmology 2023, 130: 598-607. PMID: 36739981, PMCID: PMC10619207, DOI: 10.1016/j.ophtha.2023.01.020.Peer-Reviewed Original ResearchConceptsMetastasis-free survivalRisk of metastasisClass 2 tumorsAdditional prognostic valueRate of metastasisPrognostic usefulnessTumor sizeTumor characteristicsPrognostic valueUveal melanomaGene expression profile testingMemorial Sloan-Kettering Cancer CenterGEP classificationCox hazard regression analysisYale-New Haven HospitalHazards regression analysisGene expression profiling testsNew Haven HospitalClass 1 tumorsGEP class 2Class 1AMean followTumor thicknessCancer CenterSurveillance protocol
2019
Closed system RT-qPCR as a potential companion diagnostic test for immunotherapy outcome in metastatic melanoma
Gupta S, McCann L, Chan YGY, Lai EW, Wei W, Wong PF, Smithy JW, Weidler J, Rhees B, Bates M, Kluger HM, Rimm DL. Closed system RT-qPCR as a potential companion diagnostic test for immunotherapy outcome in metastatic melanoma. Journal For ImmunoTherapy Of Cancer 2019, 7: 254. PMID: 31533832, PMCID: PMC6751819, DOI: 10.1186/s40425-019-0731-9.Peer-Reviewed Original ResearchMeSH KeywordsAgedAntineoplastic Agents, ImmunologicalB7-H1 AntigenBiomarkers, TumorCD8 AntigensFemaleFollow-Up StudiesGene Expression ProfilingHumansInterferon Regulatory Factor-1MaleMelanomaMiddle AgedMonitoring, ImmunologicPrognosisProgrammed Cell Death 1 Ligand 2 ProteinProgression-Free SurvivalReal-Time Polymerase Chain ReactionRetrospective StudiesReverse Transcriptase Polymerase Chain ReactionRNA, MessengerSkin NeoplasmsConceptsCompanion diagnostic testsImmunotherapy outcomesMelanoma patientsClinical benefitAnti-PD-1 therapyImmune checkpoint inhibitor therapyMRNA expressionQuantitative immunofluorescenceDiagnostic testsCheckpoint inhibitor therapyReal-time quantitative reverse transcription polymerase chain reactionMetastatic melanoma patientsQuantitative reverse transcription polymerase chain reactionReverse transcription-polymerase chain reactionTranscription-polymerase chain reactionYale Pathology archivesParaffin-embedded tissue sectionsAdjuvant settingICI therapyOS associationInhibitor therapyBaseline variablesMetastatic melanomaPredictive biomarkersPolymerase chain reaction
2015
PLEKHA5 as a Biomarker and Potential Mediator of Melanoma Brain Metastasis
Jilaveanu LB, Parisi F, Barr ML, Zito CR, Cruz-Munoz W, Kerbel RS, Rimm DL, Bosenberg MW, Halaban R, Kluger Y, Kluger HM. PLEKHA5 as a Biomarker and Potential Mediator of Melanoma Brain Metastasis. Clinical Cancer Research 2015, 21: 2138-2147. PMID: 25316811, PMCID: PMC4397107, DOI: 10.1158/1078-0432.ccr-14-0861.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorBrain NeoplasmsCell Line, TumorFemaleFluorescent Antibody TechniqueGene Expression ProfilingHumansImage Processing, Computer-AssistedIntracellular Signaling Peptides and ProteinsMaleMelanomaMiddle AgedNeoplasm InvasivenessTissue Array AnalysisTranscriptomeYoung AdultConceptsCell line modelsBlood-brain barrierBrain metastasesGene expression profilesGene expression profilingExpression profilingExpression profilesPLEKHA5Brain metastasis-free survivalA375P cellsQuantitative immunofluorescenceEarly brain metastasisMelanoma brain metastasesMetastasis-free survivalProfile of patientsPotential mediatorsProtein levelsMetastatic melanoma casesEarly developmentMelanoma cellsKnockdownDecrease proliferationBBB transmigrationExtracerebral sitesMetastatic sitesCombination Therapy with Anti–CTLA-4 and Anti–PD-1 Leads to Distinct Immunologic Changes In Vivo
Das R, Verma R, Sznol M, Boddupalli CS, Gettinger SN, Kluger H, Callahan M, Wolchok JD, Halaban R, Dhodapkar MV, Dhodapkar KM. Combination Therapy with Anti–CTLA-4 and Anti–PD-1 Leads to Distinct Immunologic Changes In Vivo. The Journal Of Immunology 2015, 194: 950-959. PMID: 25539810, PMCID: PMC4380504, DOI: 10.4049/jimmunol.1401686.Peer-Reviewed Original ResearchMeSH KeywordsAntibodies, MonoclonalAntigens, SurfaceAntineoplastic Combined Chemotherapy ProtocolsCTLA-4 AntigenCytokinesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunophenotypingIpilimumabLymphocytes, Tumor-InfiltratingNeoplasmsNivolumabProgrammed Cell Death 1 ReceptorSignal TransductionT-Lymphocyte SubsetsConceptsPD-1T cellsCTLA-4Checkpoint blockadeCombination therapyReceptor occupancyCombination immune checkpoint blockadeCTLA-4 immune checkpointsPD-1 receptor occupancyTransitional memory T cellsAnti-PD-1 therapyAnti CTLA-4Immune-based combinationsPD-1 blockadeSoluble IL-2RImmune checkpoint blockadeNK cell functionMemory T cellsTherapy-induced changesT cell activationTumor T cellsHuman T cellsRemarkable antitumor effectImmunologic changesImmunologic effects
2012
Integrated analysis of tumor samples sheds light on tumor heterogeneity.
Parisi F, Micsinai M, Strino F, Ariyan S, Narayan D, Bacchiocchi A, Cheng E, Xu F, Li P, Kluger H, Halaban R, Kluger Y. Integrated analysis of tumor samples sheds light on tumor heterogeneity. The Yale Journal Of Biology And Medicine 2012, 85: 347-61. PMID: 23012583, PMCID: PMC3447199.Peer-Reviewed Original ResearchMeSH KeywordsCell Line, TumorChromosome MappingChromosomes, HumanDNA Copy Number VariationsEvolution, MolecularGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, NeoplasmHumansIntercellular Signaling Peptides and ProteinsKaryotypingMelanomaMutationOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideProto-Oncogene Proteins B-rafConceptsHigh-throughput profilingGene expression levelsExpression levelsDifferent gene expression levelsGene expression profilingCopy number analysisExpression profilingSNP arrayPathway analysisCopy number statusWnt pathwayTumor samplesNumber alteration profilesTumor heterogeneityTumor evolutionCopy number alteration profilesGenomic aberrationsIntegrated analysisCell linesTumor subclonesNumber analysisNumber statusProfilingDriver mutationsRecurrent association
2008
Assessing Expression of Apoptotic Markers Using Large Cohort Tissue Microarrays
Pick E, McCarthy MM, Kluger HM. Assessing Expression of Apoptotic Markers Using Large Cohort Tissue Microarrays. Methods In Molecular Biology 2008, 414: 83-93. PMID: 18175814, DOI: 10.1007/978-1-59745-339-4_8.Peer-Reviewed Original ResearchConceptsLarge cohortApoptotic markersParaffin-embedded specimensHundreds of patientsAnti-apoptotic elementsTissue microarray technologySitu protein expressionApoptotic marker expressionTissue microarrayMarker expressionBenign cellsImmunohistochemistryProtein expressionExtrinsic pathwayExpression levelsCohortMarkersExpressionCellsPatients
2006
Characterizing disease states from topological properties of transcriptional regulatory networks
Tuck DP, Kluger HM, Kluger Y. Characterizing disease states from topological properties of transcriptional regulatory networks. BMC Bioinformatics 2006, 7: 236. PMID: 16670008, PMCID: PMC1482723, DOI: 10.1186/1471-2105-7-236.Peer-Reviewed Original ResearchConceptsTranscriptional regulatory networksRegulatory networksTranscription factorsTranscriptional networksRegulated genesGene deregulationExpression profilesDiseased statesGene regulatory networksCentrality of genesGene expression experimentsGene expression profilesGene expression studiesGene centralityRegulatory linkExpression experimentsExpression studiesGene linksGenesCell typesExpression datasetsGene subsetsDifferential activityNormal cellsRemarkable degree
2005
Evaluating the Expression and Prognostic Value of TRAIL-R1 and TRAIL-R2 in Breast Cancer
McCarthy MM, Sznol M, DiVito KA, Camp RL, Rimm DL, Kluger HM. Evaluating the Expression and Prognostic Value of TRAIL-R1 and TRAIL-R2 in Breast Cancer. Clinical Cancer Research 2005, 11: 5188-5194. PMID: 16033835, DOI: 10.1158/1078-0432.ccr-05-0158.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBreast NeoplasmsCase-Control StudiesFemaleFollow-Up StudiesGene Expression ProfilingHumansMiddle AgedMultivariate AnalysisOligonucleotide Array Sequence AnalysisPrognosisReceptors, TNF-Related Apoptosis-Inducing LigandReceptors, Tumor Necrosis FactorSurvival AnalysisConceptsEarly-stage breast cancerTRAIL-R2 expressionBreast cancerPrognostic valueTRAIL-R2TRAIL-R1Normal breast specimensTumor necrosis factor-related apoptosis-inducing ligand receptor 1Lymph node involvementSubset of patientsBreast cancer patientsIndependent prognostic markerTRAIL-R1 expressionNormal breast epitheliumTRAIL receptor expressionLigand receptor 1Apoptosis-inducing ligand receptor 1Adjuvant treatmentNode involvementNodal statusPathologic variablesTumor sizeCancer patientsClinical trialsPrognostic markerUsing a Xenograft Model of Human Breast Cancer Metastasis to Find Genes Associated with Clinically Aggressive Disease
Kluger HM, Lev D, Kluger Y, McCarthy MM, Kiriakova G, Camp RL, Rimm DL, Price JE. Using a Xenograft Model of Human Breast Cancer Metastasis to Find Genes Associated with Clinically Aggressive Disease. Cancer Research 2005, 65: 5578-5587. PMID: 15994930, DOI: 10.1158/0008-5472.can-05-0108.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBreast NeoplasmsCell AdhesionCell Growth ProcessesCell Line, TumorDisease Models, AnimalFemaleGene Expression ProfilingHumansImmunohistochemistryMiceMice, NudeMultivariate AnalysisNeoplasm InvasivenessNeoplasm MetastasisNeoplasm TransplantationOligonucleotide Array Sequence AnalysisPredictive Value of TestsReproducibility of ResultsTissue Array AnalysisTransplantation, HeterologousConceptsBreast cancerXenograft modelHuman breast cancer metastasisLymph node involvementLymph node metastasisChemokine ligand 1Human breast cancer cell linesBreast cancer metastasisLeukocyte protease inhibitorBreast cancer cell linesBreast cancer tissuesHSP-70 expressionHeat shock protein 70Cancer cell linesShock protein 70Identification of genesNode involvementNode metastasisAggressive diseaseClinicopathologic variablesPrimary tumorPrognostic markerNovel therapiesCDNA microarray analysisCancer tissues
2004
Expression Profiling Reveals Novel Pathways in the Transformation of Melanocytes to Melanomas
Hoek K, Rimm DL, Williams KR, Zhao H, Ariyan S, Lin A, Kluger HM, Berger AJ, Cheng E, Trombetta ES, Wu T, Niinobe M, Yoshikawa K, Hannigan GE, Halaban R. Expression Profiling Reveals Novel Pathways in the Transformation of Melanocytes to Melanomas. Cancer Research 2004, 64: 5270-5282. PMID: 15289333, DOI: 10.1158/0008-5472.can-04-0731.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBiomarkers, TumorCell Transformation, NeoplasticCohort StudiesDown-RegulationGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLymphatic MetastasisMelanocytesMelanomaMiceNuclear ProteinsOligonucleotide Array Sequence AnalysisPrognosisSignal TransductionSkin NeoplasmsSurvival RateTranscription FactorsTransfectionTwist-Related Protein 1Ubiquitin ThiolesteraseConceptsGlobal differential gene expressionMembrane trafficking eventsNovel pathwayNormal melanocytesHelix protein TwistAdditional transcriptional regulatorsDifferential gene expressionMelanoma cellsTransformation of melanocytesCpG promoter methylationNormal human melanocytesTrafficking eventsTranscriptional regulatorsEmbryonic developmentGrowth suppressorChromosomal regionsExpression profilingGene expressionNotch pathwayOligonucleotide microarraysMelanoma tissue microarrayDifferential expressionGenesHuman melanocytesGrowth advantagecDNA microarray analysis of invasive and tumorigenic phenotypes in a breast cancer model
Kluger HM, Kluger Y, Gilmore-Hebert M, DiVito K, Chang JT, Rodov S, Mironenko O, Kacinski BM, Perkins AS, Sapi E. cDNA microarray analysis of invasive and tumorigenic phenotypes in a breast cancer model. Laboratory Investigation 2004, 84: 320-331. PMID: 14767486, DOI: 10.1038/labinvest.3700044.Peer-Reviewed Original ResearchConceptsAutophosphorylation sitesHC11 mammary epithelial cellsMAP kinase phosphatase-1SNARE protein Ykt6Macrophage colony-stimulating factor receptorK cDNA microarrayColony-stimulating factor receptorCDNA microarray analysisKinase phosphatase-1Effects of mutationsMammary epithelial cellsTransmembrane tyrosine kinase receptorTyrosine kinase receptorsPhosphatase 1HC11 cellsCDNA microarrayTumorigenic phenotypeChaperonin 10Gene expressionFms oncogeneMicroarray analysisInvasive phenotypeMetastatic competenceKinase receptorsVivo tumorigenesis