2024
Prognostic and therapeutic insights into MIF, DDT, and CD74 in melanoma
Valdez C, Sánchez-Zuno G, Osmani L, Ibrahim W, Galan A, Bacchiocchi A, Halaban R, Kulkarni R, Kang I, Bucala R, Tran T. Prognostic and therapeutic insights into MIF, DDT, and CD74 in melanoma. Oncotarget 2024, 15: 507-520. PMID: 39028303, PMCID: PMC11259151, DOI: 10.18632/oncotarget.28615.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAntigens, Differentiation, B-LymphocyteBiomarkers, TumorFemaleHistocompatibility Antigens Class IIHumansImmune Checkpoint InhibitorsIntramolecular OxidoreductasesMacrophage Migration-Inhibitory FactorsMaleMelanomaMiddle AgedMutationPrognosisRetrospective StudiesSkin NeoplasmsConceptsMacrophage migration inhibitory factorImmune checkpoint inhibitionD-dopachrome tautomeraseExpression of macrophage migration inhibitory factorDrivers of tumor progressionInflammatory cell markersPatient tumor samplesPatient survival outcomesMigration inhibitory factorStatistically significant differenceCheckpoint inhibitionImmune therapyPrognostic valueSurvival outcomesResistant melanomaGene expressionImproved survivalRetrospective studyInflammatory markersTumor progressionCell markersTumor samplesClinical evidenceMelanomaBulk RNA sequencing
2018
Early B cell changes predict autoimmunity following combination immune checkpoint blockade
Das R, Bar N, Ferreira M, Newman AM, Zhang L, Bailur JK, Bacchiocchi A, Kluger H, Wei W, Halaban R, Sznol M, Dhodapkar MV, Dhodapkar KM. Early B cell changes predict autoimmunity following combination immune checkpoint blockade. Journal Of Clinical Investigation 2018, 128: 715-720. PMID: 29309048, PMCID: PMC5785243, DOI: 10.1172/jci96798.Peer-Reviewed Original ResearchConceptsCombination checkpoint blockadeB cell changesB cellsCheckpoint blockadeCell changesCombination immune checkpoint blockadeB-cell receptor sequencingRisk of irAEsImmune checkpoint blockadeCell receptor sequencingB cell activationTreatment-induced changesCCB therapyAdverse eventsPD1 expressionPD1 receptorGrade 3PatientsCell activationEarly changesSingle-cell RNA sequencingTherapyPreemptive strategyCancer therapyIrAEsA Serum Protein Signature Associated with Outcome after Anti–PD-1 Therapy in Metastatic Melanoma
Weber JS, Sznol M, Sullivan RJ, Blackmon S, Boland G, Kluger HM, Halaban R, Bacchiocchi A, Ascierto PA, Capone M, Oliveira C, Meyer K, Grigorieva J, Asmellash SG, Roder J, Roder H. A Serum Protein Signature Associated with Outcome after Anti–PD-1 Therapy in Metastatic Melanoma. Cancer Immunology Research 2018, 6: 79-86. PMID: 29208646, DOI: 10.1158/2326-6066.cir-17-0412.Peer-Reviewed Original ResearchConceptsAcute phase reactantsCheckpoint inhibitorsOverall survivalPhase reactantsIpilimumab-treated patientsPD-1 blockadeTrials of nivolumabBetter overall survivalIndependent patient cohortsPretreatment serumPD-1Melanoma patientsValidation cohortMetastatic melanomaMultipeptide vaccinePatient cohortPooled analysisWorse outcomesClinical dataPatientsMultivariate analysisComplement cascadeMass spectrometry analysisNivolumabCohort
2017
Changes in serum interleukin-8 (IL-8) levels reflect and predict response to anti-PD-1 treatment in melanoma and non-small-cell lung cancer patients
Sanmamed MF, Perez-Gracia JL, Schalper KA, Fusco JP, Gonzalez A, Rodriguez-Ruiz ME, Oñate C, Perez G, Alfaro C, Martín-Algarra S, Andueza MP, Gurpide A, Morgado M, Wang J, Bacchiocchi A, Halaban R, Kluger H, Chen L, Sznol M, Melero I. Changes in serum interleukin-8 (IL-8) levels reflect and predict response to anti-PD-1 treatment in melanoma and non-small-cell lung cancer patients. Annals Of Oncology 2017, 28: 1988-1995. PMID: 28595336, PMCID: PMC5834104, DOI: 10.1093/annonc/mdx190.Peer-Reviewed Original ResearchConceptsSerum IL-8 levelsIL-8 levelsCell lung cancer patientsLung cancer patientsNSCLC patientsCancer patientsMelanoma patientsPD1/PD-L1 therapyAnti-PD-1 treatmentAnti-PD-1 blockadeSerum interleukin-8 levelsPD-L1 therapyImmune checkpoint blockadeInterleukin-8 levelsLonger overall survivalBiomarkers of responseMann-Whitney testCheckpoint blockadeFirst doseOverall survivalStrength of associationClinical benefitReceiver operation characteristic curveMetastatic melanomaSurrogate biomarkerSpitz nevi and Spitzoid melanomas: exome sequencing and comparison with conventional melanocytic nevi and melanomas
Lazova R, Pornputtapong N, Halaban R, Bosenberg M, Bai Y, Chai H, Krauthammer M. Spitz nevi and Spitzoid melanomas: exome sequencing and comparison with conventional melanocytic nevi and melanomas. Modern Pathology 2017, 30: 640-649. PMID: 28186096, PMCID: PMC5413430, DOI: 10.1038/modpathol.2016.237.Peer-Reviewed Original Research
2016
A generic, cost-effective, and scalable cell lineage analysis platform
Biezuner T, Spiro A, Raz O, Amir S, Milo L, Adar R, Chapal-Ilani N, Berman V, Fried Y, Ainbinder E, Cohen G, Barr H, Halaban R, Shapiro E. A generic, cost-effective, and scalable cell lineage analysis platform. Genome Research 2016, 26: 1588-1599. PMID: 27558250, PMCID: PMC5088600, DOI: 10.1101/gr.202903.115.Peer-Reviewed Original ResearchConceptsLineage analysisSingle cell lineage analysisSingle-cell sequencing dataSingle-cell genomicsCurrent sequencing-based methodsIndividual cellsCell lineage analysisSingle-cell sequencingSequencing-based methodsLineage treesSequencing dataLineage relationsCellsTreesGenomicsAnalysis platformInput cellsSequencingBulk analysisVivoDiscoveryLandscapeGermline MC1R status influences somatic mutation burden in melanoma
Robles-Espinoza CD, Roberts ND, Chen S, Leacy FP, Alexandrov LB, Pornputtapong N, Halaban R, Krauthammer M, Cui R, Timothy Bishop D, Adams DJ. Germline MC1R status influences somatic mutation burden in melanoma. Nature Communications 2016, 7: 12064. PMID: 27403562, PMCID: PMC4945874, DOI: 10.1038/ncomms12064.Peer-Reviewed Original ResearchMeSH KeywordsAgedAllelesCohort StudiesFemaleGenetic Predisposition to DiseaseGenetic VariationGerm-Line MutationHair ColorHead and Neck NeoplasmsHumansMaleMelanomaMelanosisMiddle AgedMutationMutation AccumulationNeoplasm InvasivenessPolymorphism, Single NucleotideReceptor, Melanocortin, Type 1Skin NeoplasmsSkin PigmentationConceptsR allelePhenotypic risk factorsCutaneous melanoma riskYears of ageSomatic mutation burdenRisk factorsMutation burdenSun exposureGeneral populationMelanoma riskMutational burdenSun sensitivityMC1R statusMajor genetic determinantMelanoma developmentReceptor geneT mutationMelanomaRed hairGenetic determinantsMutation classesDisruptive variantsBurdenAllelesMelanocortin 1 receptor (MC1R) gene
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 sites
2012
Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma
Krauthammer M, Kong Y, Ha BH, Evans P, Bacchiocchi A, McCusker J, Cheng E, Davis MJ, Goh G, Choi M, Ariyan S, Narayan D, Dutton-Regester K, Capatana A, Holman EC, Bosenberg M, Sznol M, Kluger HM, Brash DE, Stern DF, Materin MA, Lo RS, Mane S, Ma S, Kidd KK, Hayward NK, Lifton RP, Schlessinger J, Boggon TJ, Halaban R. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nature Genetics 2012, 44: 1006-1014. PMID: 22842228, PMCID: PMC3432702, DOI: 10.1038/ng.2359.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCase-Control StudiesDNA Mutational AnalysisExomeFemaleGene FrequencyGenetic Predisposition to DiseaseHumansMaleMelanomaMiddle AgedModels, MolecularMutationProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)Rac1 GTP-Binding ProteinSequence Analysis, DNASkin NeoplasmsUveal NeoplasmsConceptsSun-exposed melanomasPreexisting MEK1 Exon 3 Mutations in V600E/KBRAF Melanomas Do Not Confer Resistance to BRAF Inhibitors
Shi H, Moriceau G, Kong X, Koya RC, Nazarian R, Pupo GM, Bacchiocchi A, Dahlman KB, Chmielowski B, Sosman JA, Halaban R, Kefford RF, Long GV, Ribas A, Lo RS. Preexisting MEK1 Exon 3 Mutations in V600E/KBRAF Melanomas Do Not Confer Resistance to BRAF Inhibitors. Cancer Discovery 2012, 2: 414-424. PMID: 22588879, PMCID: PMC3594852, DOI: 10.1158/2159-8290.cd-12-0022.Peer-Reviewed Original ResearchConceptsBRAF inhibitorsActivating mutationsObjective tumor responseMEK1/2 inhibitorMEK1 mutationsP-ERK1/2 levelsBRAF-mutant melanomaMelanoma cell linesAdvanced melanomaAntitumor responseExon 3 mutationsTumor responseDisease progressionMelanomaBRAFi resistanceDrug sensitivitySignificant alterationsPatientsCell linesInhibitorsBaselineMutationsExon 3Widespread use
2011
Integrated NY-ESO-1 antibody and CD8+ T-cell responses correlate with clinical benefit in advanced melanoma patients treated with ipilimumab
Yuan J, Adamow M, Ginsberg BA, Rasalan TS, Ritter E, Gallardo HF, Xu Y, Pogoriler E, Terzulli SL, Kuk D, Panageas KS, Ritter G, Sznol M, Halaban R, Jungbluth AA, Allison JP, Old LJ, Wolchok JD, Gnjatic S. Integrated NY-ESO-1 antibody and CD8+ T-cell responses correlate with clinical benefit in advanced melanoma patients treated with ipilimumab. Proceedings Of The National Academy Of Sciences Of The United States Of America 2011, 108: 16723-16728. PMID: 21933959, PMCID: PMC3189057, DOI: 10.1073/pnas.1110814108.Peer-Reviewed Original ResearchConceptsNY-ESO-1-seropositive patientsNY-ESO-1 antibodyT cell responsesClinical benefitImmune responseIpilimumab treatmentNY-ESO-1 immune responsesNY-ESO-1 serum antibodyTumor antigen-specific immune responsesCytotoxic T-lymphocyte antigen-4NY-ESO-1 immunityT-lymphocyte antigen-4Antigen-specific immune responsesIpilimumab-treated patientsAdvanced melanoma patientsAdvanced metastatic melanomaCancer/testis antigensSubset of patientsNY-ESO-1Significant survival advantageCD8 responsesAdoptive transferClinical outcomesMelanoma patientsProspective studyPlasma Markers for Identifying Patients with Metastatic Melanoma
Kluger HM, Hoyt K, Bacchiocchi A, Mayer T, Kirsch J, Kluger Y, Sznol M, Ariyan S, Molinaro A, Halaban R. Plasma Markers for Identifying Patients with Metastatic Melanoma. Clinical Cancer Research 2011, 17: 2417-2425. PMID: 21487066, PMCID: PMC3415234, DOI: 10.1158/1078-0432.ccr-10-2402.Peer-Reviewed Original ResearchMeSH KeywordsAgedAntigens, CDBiomarkers, TumorCell Adhesion MoleculesEnzyme-Linked Immunosorbent AssayExtracellular Matrix ProteinsFemaleGlycoproteinsGrowth Differentiation Factor 15HumansIntercellular Adhesion Molecule-1L-Lactate DehydrogenaseMaleMelanomaMiddle AgedNeoplasm MetastasisNeoplasm ProteinsNeoplasm Recurrence, LocalNeoplasm StagingNerve Growth FactorsPrognosisReproducibility of ResultsS100 Calcium Binding Protein beta SubunitS100 ProteinsSensitivity and SpecificityTissue Inhibitor of Metalloproteinase-1ConceptsGenome-wide gene expression dataGene expression dataHigh expression levelsLevels of proteinExpression dataExpression levelsProteinMelanoma cellsStage I/II diseaseEqual-sized trainingMarkersGenesDisease recurrencePlasma markersMetastatic melanomaTIMP-1Lactate dehydrogenaseCEACAMsStage I/II patientsDehydrogenaseOsteopontinStage IV diseaseStage IV patientsMetastatic melanoma patientsGender-matched patients
2010
Genome-wide methylation and expression profiling identifies promoter characteristics affecting demethylation-induced gene up-regulation in melanoma
Rubinstein JC, Tran N, Ma S, Halaban R, Krauthammer M. Genome-wide methylation and expression profiling identifies promoter characteristics affecting demethylation-induced gene up-regulation in melanoma. BMC Medical Genomics 2010, 3: 4. PMID: 20144234, PMCID: PMC2843643, DOI: 10.1186/1755-8794-3-4.Peer-Reviewed Original ResearchMeSH KeywordsAgedAntimetabolites, AntineoplasticAzacitidineCell Line, TumorCpG IslandsDecitabineDNA MethylationDNA Modification MethylasesEnzyme InhibitorsEpigenesis, GeneticFemaleGene Expression ProfilingGenome, HumanHumansMaleMelanomaMiddle AgedPromoter Regions, GeneticTumor Suppressor ProteinsUp-RegulationConceptsHigh CpG contentCpG contentGenome-wide gene expression dataMethylation levelsPromoter CpG contentUp-regulates gene expressionGenome-wide methylationGenome-wide dataLow CpG contentMelanoma cell strainsGene expression dataTumor suppressor geneCytosine analog 5Lower methylation levelsTranscriptional silencingMethylated promotersHigher methylation levelsBisulfite sequencingDNA methylationCpG methylationDNA methyltransferaseGenomic hypomethylationPromoter characteristicsSpecific genesGene expression
2009
Genome-wide screen of promoter methylation identifies novel markers in melanoma
Koga Y, Pelizzola M, Cheng E, Krauthammer M, Sznol M, Ariyan S, Narayan D, Molinaro AM, Halaban R, Weissman SM. Genome-wide screen of promoter methylation identifies novel markers in melanoma. Genome Research 2009, 19: 1462-1470. PMID: 19491193, PMCID: PMC2720187, DOI: 10.1101/gr.091447.109.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Signal TransducingAdultAgedBiomarkers, TumorCells, CulturedCluster AnalysisCollagenCollagen Type IDNA MethylationFemaleGene Expression ProfilingGenome-Wide Association StudyGenome, HumanHSP20 Heat-Shock ProteinsHumansInfant, NewbornMaleMelanomaMetallothioneinMiddle AgedMolecular ChaperonesNuclear ProteinsNucleoplasminsOligonucleotide Array Sequence AnalysisPhosphoproteinsPromoter Regions, GeneticProteinsReproducibility of ResultsReverse Transcriptase Polymerase Chain ReactionSequence Analysis, DNATumor Cells, CulturedConceptsDifferential gene expressionGene expressionPromoter methylationGenome-wide promoter methylationGenome-wide integrative analysisPromoter CpG contentMethylation markersGenome-wide screenSequencing of bisulfiteTranscription start siteMelanoma cell strainsCell strainsTranscriptional machineryNovel genesEpigenetic modificationsDNA methylationIdentifies novel markersStart siteSnap-frozen tissuesCpG contentAdult melanocytesIntegrative analysisReal-time reverse transcriptase PCRHuman diseasesMethylation
2004
Automated Quantitative Analysis of HDM2 Expression in Malignant Melanoma Shows Association with Early-Stage Disease and Improved Outcome
Berger AJ, Camp RL, DiVito KA, Kluger HM, Halaban R, Rimm DL. Automated Quantitative Analysis of HDM2 Expression in Malignant Melanoma Shows Association with Early-Stage Disease and Improved Outcome. Cancer Research 2004, 64: 8767-8772. PMID: 15574789, DOI: 10.1158/0008-5472.can-04-1384.Peer-Reviewed Original ResearchConceptsMurine double minute 2Double minute 2Protein expressionMalignant melanomaMinute 2Early-stage diseaseTissue microarray cohortPotential tissue biomarkersCutaneous malignant melanomaValuable prognostic toolNormal skin samplesSkin cancer deathsMicroarray cohortAdvanced melanomaMetastatic lesionsCancer deathPrimary melanomaImproved outcomesExpression of HDM2Tissue biomarkersPrognostic toolBetter outcomesMelanoma lesionsAggressive natureMelanomaNovel tyramide‐based tyrosinase assay for the detection of melanoma cells in cytological preparations
Angeletti C, Khomitch V, Halaban R, Rimm DL. Novel tyramide‐based tyrosinase assay for the detection of melanoma cells in cytological preparations. Diagnostic Cytopathology 2004, 31: 33-37. PMID: 15236262, DOI: 10.1002/dc.20051.Peer-Reviewed Original Research
1993
Altered Metabolism of Mast-Cell Growth Factor (c-kit Ligand) in Cutaneous Mastocytosis
Longley B, Morganroth G, Tyrrell L, Ding T, Anderson D, Williams D, Halaban R. Altered Metabolism of Mast-Cell Growth Factor (c-kit Ligand) in Cutaneous Mastocytosis. New England Journal Of Medicine 1993, 328: 1302-1307. PMID: 7682288, DOI: 10.1056/nejm199305063281803.Peer-Reviewed Original ResearchConceptsMast cell growth factorMessenger RNAGrowth factorC-kit proto-oncogeneProduction of melaninSoluble formGrowth factor geneFactor genesProteolytic processingProto-oncogeneSequence abnormalitiesExtracellular spaceAltered metabolismAltered distributionGrowth factor messenger RNASkin of patientsDermal cellsCellsPolymerase chain reactionCutaneous mastocytosisMast cells
1988
Cytogenetic Analysis of Melanocytes From Premalignant Nevi and Melanomas2
Cowan J, Halaban R, Francka U. Cytogenetic Analysis of Melanocytes From Premalignant Nevi and Melanomas2. Journal Of The National Cancer Institute 1988, 80: 1159-1164. PMID: 3166071, DOI: 10.1093/jnci/80.14.1159.Peer-Reviewed Original Research
1986
Human Melanocytes Cultured from Nevi and Melanomas
Halaban R, Ghosh S, Duray P, Kirkwood J, Lerner A. Human Melanocytes Cultured from Nevi and Melanomas. Journal Of Investigative Dermatology 1986, 87: 95-101. PMID: 2425008, DOI: 10.1111/1523-1747.ep12523594.Peer-Reviewed Original ResearchConceptsPresence of mitogensHuman melanocytesNeonatal melanocytesRate of proliferationPrimary melanomaCongenital neviMalignant transformationTransformation of melanocytesCholera toxinIsobutylmethyl xanthineHuman placentaGrowth factorProliferative rateMelanomaNewborn foreskinUnidentified factorsCell linesMelanocytesMitogenNeviHuman neonatal melanocytesPopulation doublingsMonthsLate eventProliferation