2021
Outcomes of Stereotactic Radiosurgery and Immunotherapy in Renal Cell Carcinoma Patients With Brain Metastases
Uezono H, Nam D, Kluger HM, Sznol M, Hurwitz M, Yu JB, Chiang VL. Outcomes of Stereotactic Radiosurgery and Immunotherapy in Renal Cell Carcinoma Patients With Brain Metastases. American Journal Of Clinical Oncology 2021, 44: 495-501. PMID: 34432667, DOI: 10.1097/coc.0000000000000849.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsRCC brain metastasesBrain metastasesRenal cell carcinomaStereotactic radiosurgeryOverall survivalUse of ICIsCentral nervous system toxicityRenal cell carcinoma patientsImpact of immunotherapyLocal control outcomesMedian overall survivalCell carcinoma patientsKaplan-Meier curvesNervous system toxicityBetter median OSLog-rank testMann-Whitney U testMargin doseMedian OSNonimmunotherapy groupSRS doseCheckpoint inhibitorsImmunotherapy groupCarcinoma patientsAutomated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma
Moore MR, Friesner ID, Rizk EM, Fullerton BT, Mondal M, Trager MH, Mendelson K, Chikeka I, Kurc T, Gupta R, Rohr BR, Robinson EJ, Acs B, Chang R, Kluger H, Taback B, Geskin LJ, Horst B, Gardner K, Niedt G, Celebi JT, Gartrell-Corrado RD, Messina J, Ferringer T, Rimm DL, Saltz J, Wang J, Vanguri R, Saenger YM. Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma. Scientific Reports 2021, 11: 2809. PMID: 33531581, PMCID: PMC7854647, DOI: 10.1038/s41598-021-82305-1.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiopsyChemotherapy, AdjuvantClinical Decision-MakingDeep LearningFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedKaplan-Meier EstimateLymphocytes, Tumor-InfiltratingMaleMelanomaMiddle AgedNeoplasm StagingPatient SelectionPrognosisRetrospective StudiesRisk AssessmentROC CurveSkinSkin NeoplasmsYoung AdultConceptsTumor-infiltrating lymphocytesDisease-specific survivalEarly-stage melanomaOpen-source deep learningCutoff valueMultivariable Cox proportional hazards analysisCox proportional hazards analysisDeep learningLow-risk patientsProportional hazards analysisKaplan-Meier analysisAccurate prognostic biomarkersEosin imagesAccuracy of predictionAdjuvant therapyRisk patientsSpecific survivalPrognostic valueValidation cohortReceiver operating curvesTraining cohortTIL analysisClinical trialsPrimary melanomaPrognostic biomarker
2020
Regulation of eIF2α by RNF4 Promotes Melanoma Tumorigenesis and Therapy Resistance
Avitan-Hersh E, Feng Y, Oknin Vaisman A, Abu Ahmad Y, Zohar Y, Zhang T, Lee JS, Lazar I, Sheikh Khalil S, Feiler Y, Kluger H, Kahana C, Brown K, Ruppin E, Ronai ZA, Orian A. Regulation of eIF2α by RNF4 Promotes Melanoma Tumorigenesis and Therapy Resistance. Journal Of Investigative Dermatology 2020, 140: 2466-2477. PMID: 32360601, PMCID: PMC8081033, DOI: 10.1016/j.jid.2020.04.008.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCarcinogenesisCell Line, TumorDrug Resistance, NeoplasmEukaryotic Initiation Factor-2FemaleGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMelanomaMiceMitogen-Activated Protein KinasesNuclear ProteinsOncogenesPrognosisProtein Kinase InhibitorsProtein StabilityProto-Oncogene Proteins B-rafSkinSkin NeoplasmsTranscription FactorsUbiquitinationXenograft Model Antitumor AssaysConceptsUbiquitin ligase RNF4Elongation factor alphaPatient-derived melanomasIntegrated stress responseTherapy resistancePositive feed-forward loopTranscription factor 4Feed-forward loopOncogenic translationMolecular machineryMajor clinical challengePhosphorylated eIF2αHallmark of melanomaXenograft mouse modelHomologous proteinsStress responseMAPK inhibitorProtein stabilizationMelanoma tumorigenesisTumorigenic propertiesPoor prognosisFactor alphaClinical challengeMouse modelRNF4
2019
Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes and Immunotherapy Outcome in Metastatic Melanoma
Wong PF, Wei W, Smithy JW, Acs B, Toki MI, Blenman K, Zelterman D, Kluger HM, Rimm DL. Multiplex Quantitative Analysis of Tumor-Infiltrating Lymphocytes and Immunotherapy Outcome in Metastatic Melanoma. Clinical Cancer Research 2019, 25: 2442-2449. PMID: 30617133, PMCID: PMC6467753, DOI: 10.1158/1078-0432.ccr-18-2652.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAntineoplastic Agents, ImmunologicalBiomarkersBiomarkers, TumorFemaleFluorescent Antibody TechniqueHumansImmunohistochemistryImmunotherapyKaplan-Meier EstimateLymphocytes, Tumor-InfiltratingMaleMelanomaMiddle AgedMolecular Targeted TherapyNeoplasm StagingROC CurveT-Lymphocyte SubsetsConceptsCell countTIL activationQuantitative immunofluorescenceLymphocytic infiltrationMelanoma patientsMetastatic melanomaAnti-PD-1 responseAnti-PD-1 therapyCell death 1 (PD-1) inhibitionAbsence of immunotherapyDeath-1 (PD-1) inhibitionDisease control rateProgression-free survivalCD8 cell countsTumor-Infiltrating LymphocytesNew predictive biomarkersWhole tissue sectionsRECIST 1.1Progressive diseaseDurable responsesObjective responsePartial responseImmunotherapy outcomesLymphocyte profilesMultivariable analysis
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
2015
Exome sequencing identifies recurrent mutations in NF1 and RASopathy genes in sun-exposed melanomas
Krauthammer M, Kong Y, Bacchiocchi A, Evans P, Pornputtapong N, Wu C, McCusker JP, Ma S, Cheng E, Straub R, Serin M, Bosenberg M, Ariyan S, Narayan D, Sznol M, Kluger HM, Mane S, Schlessinger J, Lifton RP, Halaban R. Exome sequencing identifies recurrent mutations in NF1 and RASopathy genes in sun-exposed melanomas. Nature Genetics 2015, 47: 996-1002. PMID: 26214590, PMCID: PMC4916843, DOI: 10.1038/ng.3361.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic AgentsBenzimidazolesDNA Mutational AnalysisDrug Resistance, NeoplasmExomeGenetic Association StudiesGenetic Predisposition to DiseaseHumansInhibitory Concentration 50Kaplan-Meier EstimateLoss of HeterozygosityMaleMelanomaMutation, MissenseNeurofibromin 1Ras ProteinsSequence Analysis, RNASkin NeoplasmsSunlightTumor Cells, CulturedCharacterization of PD-L1 Expression and Associated T-cell Infiltrates in Metastatic Melanoma Samples from Variable Anatomic Sites
Kluger HM, Zito CR, Barr ML, Baine MK, Chiang VL, Sznol M, Rimm DL, Chen L, Jilaveanu LB. Characterization of PD-L1 Expression and Associated T-cell Infiltrates in Metastatic Melanoma Samples from Variable Anatomic Sites. Clinical Cancer Research 2015, 21: 3052-3060. PMID: 25788491, PMCID: PMC4490112, DOI: 10.1158/1078-0432.ccr-14-3073.Peer-Reviewed Original ResearchConceptsPD-L1 expressionT-cell contentPD-1/PD-L1 inhibitorsHigher T-cell contentT-cell infiltratesPD-L1 inhibitorsAnatomic sitesBrain metastasesMetastatic melanomaTissue microarrayHigh PD-L1 expressionLess PD-L1 expressionLow PD-L1 expressionTumor PD-L1 expressionHigher TIL contentImproved overall survivalT cell infiltrationLess T cellsMetastatic melanoma samplesExtracerebral metastasesCerebral metastasesOverall survivalDermal metastasesImproved survivalPD-L1
2014
MEK targeting in N-RAS mutated metastatic melanoma
Thumar J, Shahbazian D, Aziz SA, Jilaveanu LB, Kluger HM. MEK targeting in N-RAS mutated metastatic melanoma. Molecular Cancer 2014, 13: 45. PMID: 24588908, PMCID: PMC3945937, DOI: 10.1186/1476-4598-13-45.Peer-Reviewed Original ResearchConceptsN-RASShort-term cultureMelanoma patientsMelanoma culturesYale Cancer CenterMetastatic melanoma patientsTime of presentationOngoing clinical trialsProtein kinase pathway activationN-RAS mutationsB-RafPan-RAF inhibitorTerm cultureKinase pathway activationConclusionsThe prognosisBrain metastasesClinical characteristicsMetastatic diseasePathologic dataWorse prognosisCancer CenterMetastatic melanomaClinical trialsMutant melanomaMelanoma cell culturesSurvival, Durable Tumor Remission, and Long-Term Safety in Patients With Advanced Melanoma Receiving Nivolumab
Topalian SL, Sznol M, McDermott DF, Kluger HM, Carvajal RD, Sharfman WH, Brahmer JR, Lawrence DP, Atkins MB, Powderly JD, Leming PD, Lipson EJ, Puzanov I, Smith DC, Taube JM, Wigginton JM, Kollia GD, Gupta A, Pardoll DM, Sosman JA, Hodi FS. Survival, Durable Tumor Remission, and Long-Term Safety in Patients With Advanced Melanoma Receiving Nivolumab. Journal Of Clinical Oncology 2014, 32: 1020-1030. PMID: 24590637, PMCID: PMC4811023, DOI: 10.1200/jco.2013.53.0105.Peer-Reviewed Original ResearchConceptsLong-term safetyOverall survivalToxicity ratesTumor regressionResponse durationOngoing randomized clinical trialsDurable tumor remissionNivolumab-treated patientsMedian overall survivalMedian response durationPD-1 blockadeObjective tumor regressionMaintenance of responseCell death 1Randomized clinical trialsSimilar patient populationsActivated T cellsDrug discontinuationIntravenous nivolumabNivolumab therapyNivolumab treatmentTreatment discontinuationObjective responseAdvanced melanomaDeath-1
2013
Expression of Drug Targets in Patients Treated with Sorafenib, Carboplatin and Paclitaxel
Jilaveanu LB, Zhao F, Zito CR, Kirkwood JM, Nathanson KL, D'Andrea K, Wilson M, Rimm DL, Flaherty KT, Lee SJ, Kluger HM. Expression of Drug Targets in Patients Treated with Sorafenib, Carboplatin and Paclitaxel. PLOS ONE 2013, 8: e69748. PMID: 23936348, PMCID: PMC3735539, DOI: 10.1371/journal.pone.0069748.Peer-Reviewed Original ResearchConceptsProgression-free survivalOverall survivalVEGF-R1FGF-R1Paclitaxel-based therapyVEGF-R1 expressionPre-treatment tumorsPredictive biomarker signaturesMultitarget kinase inhibitorPDGF-RβSitu protein expressionTherapeutic ratioTaxane sensitivityMitogen-activated protein kinase pathwayPatientsVEGF-R3CarboplatinSorafenibVEGF-R2C-kitKinase inhibitorsTherapyProtein expressionPhase IIISorafenib targets
2008
Expression of Aurora A (but Not Aurora B) Is Predictive of Survival in Breast Cancer
Nadler Y, Camp RL, Schwartz C, Rimm DL, Kluger HM, Kluger Y. Expression of Aurora A (but Not Aurora B) Is Predictive of Survival in Breast Cancer. Clinical Cancer Research 2008, 14: 4455-4462. PMID: 18628459, PMCID: PMC5849429, DOI: 10.1158/1078-0432.ccr-07-5268.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAurora Kinase BAurora KinasesBiomarkers, TumorBlotting, WesternBreast NeoplasmsCell Line, TumorFemaleHistory, 17th CenturyHumansImage Processing, Computer-AssistedImmunohistochemistryKaplan-Meier EstimatePrognosisProtein Serine-Threonine KinasesTissue Array AnalysisConceptsBreast cancerB expressionAurora B expressionBreast tumorsHigh AuroraEarly-stage breast cancerHER-2/neuProgesterone receptor expressionSubset of patientsPopulation of patientsIndependent prognostic markerHigh nuclear gradePrimary breast tumorsCy5-conjugated antibodiesPathologic variablesPrognostic roleMultivariable analysisProspective studyNuclear gradePrognostic markerReceptor expressionClinical developmentPatientsPredictive roleCancerExpression patterns and prognostic value of Bag-1 and Bcl-2 in breast cancer
Nadler Y, Camp RL, Giltnane JM, Moeder C, Rimm DL, Kluger HM, Kluger Y. Expression patterns and prognostic value of Bag-1 and Bcl-2 in breast cancer. Breast Cancer Research 2008, 10: r35. PMID: 18430249, PMCID: PMC2397537, DOI: 10.1186/bcr1998.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic AgentsBiomarkers, TumorBreast NeoplasmsDNA-Binding ProteinsDrug Resistance, NeoplasmFemaleFluorescent Antibody TechniqueFollow-Up StudiesGene Expression Regulation, NeoplasticHumansImmunohistochemistryKaplan-Meier EstimateLymphatic MetastasisMiddle AgedPredictive Value of TestsPrognosisProportional Hazards ModelsProtein Array AnalysisProto-Oncogene Proteins c-bcl-2Receptors, EstrogenReceptors, ProgesteroneTranscription FactorsTreatment OutcomeConceptsNode-positive subsetHER2/neuProgesterone receptorBreast cancerEstrogen receptorBcl-2 expressionBAG-1 expressionImproved survivalBcl-2Anti-apoptotic mediator Bcl-2Breast tumorsSteroid receptor positivitySubset of patientsBAG-1Antihormonal therapyFavorable prognosisReceptor positivityMultivariable analysisPathological variablesEntire cohortPrognostic valuePrognostic markerImproved outcomesLarge cohortClinical development