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 sequencingDigital spatial proteomic profiling reveals immune checkpoints as biomarkers in lymphoid aggregates and tumor microenvironment of desmoplastic melanoma
Su D, Schoenfeld D, Ibrahim W, Cabrejo R, Djureinovic D, Baumann R, Rimm D, Khan S, Halaban R, Kluger H, Olino K, Galan A, Clune J. Digital spatial proteomic profiling reveals immune checkpoints as biomarkers in lymphoid aggregates and tumor microenvironment of desmoplastic melanoma. Journal For ImmunoTherapy Of Cancer 2024, 12: e008646. PMID: 38519058, PMCID: PMC10961546, DOI: 10.1136/jitc-2023-008646.Peer-Reviewed Original ResearchConceptsCTLA-4 expression levelsCancer-associated fibroblastsAssociated with worse survivalExpression of immune checkpointsLAG-3 expressionDesmoplastic melanomaLymphoid aggregatesCTLA-4PD-1Immune checkpointsIntratumoral leukocytesLAG-3Tumor compartmentsWorse survivalCD20+B cellsIncreased expression of immune checkpointsProgrammed cell death protein 1Macrophage/monocyte markerSentinel lymph node positivityCell death protein 1Associated with poor prognosisLymph node positivityDense fibrous stromaPotential prognostic significanceCore of tumors
2023
Dynamic changes of circulating soluble PD-1/PD-L1 and its association with patient survival in immune checkpoint blockade-treated melanoma
Lu L, Risch E, Halaban R, Zhen P, Bacchiocchi A, Risch H. Dynamic changes of circulating soluble PD-1/PD-L1 and its association with patient survival in immune checkpoint blockade-treated melanoma. International Immunopharmacology 2023, 118: 110092. PMID: 37004344, DOI: 10.1016/j.intimp.2023.110092.Peer-Reviewed Original ResearchMeSH KeywordsB7-H1 AntigenHumansImmune Checkpoint InhibitorsImmunotherapyMelanomaRetrospective StudiesConceptsImmune checkpoint blockadeSoluble PD-L1 (sPD-L1) levelsPD-L1 ratioPD-L1 levelsSoluble PD-1Soluble PD-L1PD-L1PD-1Patient survivalSurvival statusPD-1/PD-L1Immune checkpoints PD-1T cell exhaustionPatients' survival statusSolid tumor typesInitial immunotherapyCheckpoint blockadeMelanoma patientsPoor prognosisRetrospective studyPatient responseCell exhaustionTumor typesMelanomaSurvival
2022
Integrative molecular and clinical profiling of acral melanoma links focal amplification of 22q11.21 to metastasis
Farshidfar F, Rhrissorrakrai K, Levovitz C, Peng C, Knight J, Bacchiocchi A, Su J, Yin M, Sznol M, Ariyan S, Clune J, Olino K, Parida L, Nikolaus J, Zhang M, Zhao S, Wang Y, Huang G, Wan M, Li X, Cao J, Yan Q, Chen X, Newman AM, Halaban R. Integrative molecular and clinical profiling of acral melanoma links focal amplification of 22q11.21 to metastasis. Nature Communications 2022, 13: 898. PMID: 35197475, PMCID: PMC8866401, DOI: 10.1038/s41467-022-28566-4.Peer-Reviewed Original ResearchConceptsAcral melanomaMelanoma subtypesClinical profilingCommon melanoma subtypeImmune checkpoint blockadeCheckpoint blockadeInferior survivalMelanoma cell linesKey molecular driversPoor prognosisTherapeutic targetAnchorage-independent growthImmunomodulatory genesNon-white individualsHotspot mutationsMolecular driversCandidate oncogeneMelanomaApoptotic cell deathLZTR1Focal amplificationTumor promoterCell linesMetastasisTumor suppressorT cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanoma
Lozano AX, Chaudhuri AA, Nene A, Bacchiocchi A, Earland N, Vesely MD, Usmani A, Turner BE, Steen CB, Luca BA, Badri T, Gulati GS, Vahid MR, Khameneh F, Harris PK, Chen DY, Dhodapkar K, Sznol M, Halaban R, Newman AM. T cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanoma. Nature Medicine 2022, 28: 353-362. PMID: 35027754, PMCID: PMC8866214, DOI: 10.1038/s41591-021-01623-z.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsImmune-related adverse eventsT-cell characteristicsIrAE developmentBlood samplesSevere immune-related adverse eventsAnti-PD-1 monotherapyCombination immune checkpoint inhibitorsT-cell receptor sequencingT cell abundanceCell receptor sequencingOrgan system involvementPeripheral blood samplesIrAE onsetCheckpoint inhibitorsAdverse eventsCheckpoint blockadeRNA sequencingTCR clonalityCombination therapyPatient cohortSystem involvementClinical managementTCR diversityImmunological state
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
Future perspectives in melanoma research “Melanoma Bridge”, Napoli, November 30th–3rd December 2016
Ascierto PA, Agarwala SS, Ciliberto G, Demaria S, Dummer R, Duong CPM, Ferrone S, Formenti SC, Garbe C, Halaban R, Khleif S, Luke JJ, Mir LM, Overwijk WW, Postow M, Puzanov I, Sondel P, Taube JM, Thor Straten P, Stroncek DF, Wargo JA, Zarour H, Thurin M. Future perspectives in melanoma research “Melanoma Bridge”, Napoli, November 30th–3rd December 2016. Journal Of Translational Medicine 2017, 15: 236. PMID: 29145885, PMCID: PMC5691855, DOI: 10.1186/s12967-017-1341-2.Peer-Reviewed Original ResearchConceptsT-cell therapyCombination therapyMetastatic melanomaChemokine receptorsT cellsHoming capacitySurvival rateTumor-Infiltrating Lymphocyte TherapyStage IV melanoma patientsAdoptive T-cell therapyCell therapyBRAF inhibitor monotherapyImmune checkpoint blockersSetting of treatmentIdentification of patientsChimeric antigen receptorEfficient combination therapyEmpowerment of patientsOptimize treatment regimensDifferent therapeutic agentsMelanoma BridgeImmunotherapy agentsOutcome enhancementCheckpoint blockadeCheckpoint blockersChanges 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
Germline 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) geneRASopathy Gene Mutations in Melanoma
Halaban R, Krauthammer M. RASopathy Gene Mutations in Melanoma. Journal Of Investigative Dermatology 2016, 136: 1755-1759. PMID: 27236105, PMCID: PMC4992636, DOI: 10.1016/j.jid.2016.05.095.Peer-Reviewed Original ResearchConceptsRASopathy mutationsRAS/mitogen-activated protein kinaseRAS/mitogen-activated protein kinase (MAPK) pathwayMitogen-activated protein kinase pathwayMitogen-activated protein kinaseProtein kinase pathwayAmino acid substitutionsNext-generation sequencingProtein kinasePathway genesKinase pathwaySequencing dataDriver genesAcid substitutionsGenomic abnormalitiesMutationsLegius syndromeGenesAbundant mutationsGermline mutationsGene mutationsPathwaySignificant overlapKinaseMelanomagenesisAMPK promotes tolerance to Ras pathway inhibition by activating autophagy
Sanduja S, Feng Y, Mathis RA, Sokol ES, Reinhardt F, Halaban R, Gupta PB. AMPK promotes tolerance to Ras pathway inhibition by activating autophagy. Oncogene 2016, 35: 5295-5303. PMID: 27041569, PMCID: PMC6086350, DOI: 10.1038/onc.2016.70.Peer-Reviewed Original ResearchConceptsCellular energy sensor AMPEnergy sensor AMPPathway inhibitorTargeted inhibitorsRas-Raf pathwayDrug-tolerant cellsPathway inhibitionOncogenic RasProtein kinaseRaf signalingRas pathway inhibitionReduced growthAMPKAutophagyPathway mutationsCancer cellsResistant cellsKey mechanismPathwayInhibitorsCellsToleranceKinaseSignalingInhibition
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, CulturedGenomic Classification of Cutaneous Melanoma
Network T, Akbani R, Akdemir K, Aksoy B, Albert M, Ally A, Amin S, Arachchi H, Arora A, Auman J, Ayala B, Baboud J, Balasundaram M, Balu S, Barnabas N, Bartlett J, Bartlett P, Bastian B, Baylin S, Behera M, Belyaev D, Benz C, Bernard B, Beroukhim R, Bir N, Black A, Bodenheimer T, Boice L, Boland G, Bono R, Bootwalla M, Bosenberg M, Bowen J, Bowlby R, Bristow C, Brockway-Lunardi L, Brooks D, Brzezinski J, Bshara W, Buda E, Burns W, Butterfield Y, Button M, Calderone T, Cappellini G, Carter C, Carter S, Cherney L, Cherniack A, Chevalier A, Chin L, Cho J, Cho R, Choi Y, Chu A, Chudamani S, Cibulskis K, Ciriello G, Clarke A, Coons S, Cope L, Crain D, Curley E, Danilova L, D’Atri S, Davidsen T, Davies M, Delman K, Demchok J, Deng Q, Deribe Y, Dhalla N, Dhir R, DiCara D, Dinikin M, Dubina M, Ebrom J, Egea S, Eley G, Engel J, Eschbacher J, Fedosenko K, Felau I, Fennell T, Ferguson M, Fisher S, Flaherty K, Frazer S, Frick J, Fulidou V, Gabriel S, Gao J, Gardner J, Garraway L, Gastier-Foster J, Gaudioso C, Gehlenborg N, Genovese G, Gerken M, Gershenwald J, Getz G, Gomez-Fernandez C, Gribbin T, Grimsby J, Gross B, Guin R, Gutschner T, Hadjipanayis A, Halaban R, Hanf B, Haussler D, Haydu L, Hayes D, Hayward N, Heiman D, Herbert L, Herman J, Hersey P, Hoadley K, Hodis E, Holt R, Hoon D, Hoppough S, Hoyle A, Huang F, Huang M, Huang S, Hutter C, Ibbs M, Iype L, Jacobsen A, Jakrot V, Janning A, Jeck W, Jefferys S, Jensen M, Jones C, Jones S, Ju Z, Kakavand H, Kang H, Kefford R, Khuri F, Kim J, Kirkwood J, Klode J, Korkut A, Korski K, Krauthammer M, Kucherlapati R, Kwong L, Kycler W, Ladanyi M, Lai P, Laird P, Lander E, Lawrence M, Lazar A, Łaźniak R, Lee D, Lee J, Lee J, Lee K, Lee S, Lee W, Leporowska E, Leraas K, Li H, Lichtenberg T, Lichtenstein L, Lin P, Ling S, Liu J, Liu O, Liu W, Long G, Lu Y, Ma, Ma Y, Mackiewicz A, Mahadeshwar H, Malke J, Mallery D, Manikhas G, Mann G, Marra M, Matejka B, Mayo M, Mehrabi S, Meng S, Meyerson M, Mieczkowski P, Miller J, Miller M, Mills G, Moiseenko F, Moore R, Morris S, Morrison C, Morton D, Moschos S, Mose L, Muller F, Mungall A, Murawa D, Murawa P, Murray B, Nezi L, Ng S, Nicholson D, Noble M, Osunkoya A, Owonikoko T, Ozenberger B, Pagani E, Paklina O, Pantazi A, Parfenov M, Parfitt J, Park P, Park W, Parker J, Passarelli F, Penny R, Perou C, Pihl T, Potapova O, Prieto V, Protopopov A, Quinn M, Radenbaugh A, Rai K, Ramalingam S, Raman A, Ramirez N, Ramirez R, Rao U, Rathmell W, Ren X, Reynolds S, Roach J, Robertson A, Ross M, Roszik J, Russo G, Saksena G, Saller C, Samuels Y, Sander C, Sander C, Sandusky G, Santoso N, Saul M, Saw R, Schadendorf D, Schein J, Schultz N, Schumacher S, Schwallier C, Scolyer R, Seidman J, Sekhar P, Sekhon H, Senbabaoglu Y, Seth S, Shannon K, Sharpe S, Sharpless N, Shaw K, Shelton C, Shelton T, Shen R, Sheth M, Shi Y, Shiau C, Shmulevich I, Sica G, Simons J, Sinha R, Sipahimalani P, Sofia H, Soloway M, Song X, Sougnez C, Spillane A, Spychała A, Stretch J, Stuart J, Suchorska W, Sucker A, Sumer S, Sun Y, Synott M, Tabak B, Tabler T, Tam A, Tan D, Tang J, Tarnuzzer R, Tarvin K, Tatka H, Taylor B, Teresiak M, Thiessen N, Thompson J, Thorne L, Thorsson V, Trent J, Triche T, Tsai K, Tsou P, Van Den Berg D, Van Allen E, Veluvolu U, Verhaak R, Voet D, Voronina O, Walter V, Walton J, Wan Y, Wang Y, Wang Z, Waring S, Watson I, Weinhold N, Weinstein J, Weisenberger D, White P, Wilkerson M, Wilmott J, Wise L, Wiznerowicz M, Woodman S, Wu C, Wu C, Wu J, Wu Y, Xi R, Xu A, Yang D, Yang L, Yang L, Zack T, Zenklusen J, Zhang H, Zhang J, Zhang W, Zhao X, Zhu J, Zhu K, Zimmer L, Zmuda E, Zou L. Genomic Classification of Cutaneous Melanoma. Cell 2015, 161: 1681-1696. PMID: 26091043, PMCID: PMC4580370, DOI: 10.1016/j.cell.2015.05.044.Peer-Reviewed Original ResearchConceptsGenomic classificationProtein-based analysesComplex structural rearrangementsImmune gene expressionMutant RASGene expressionIntegrative analysisFocal amplificationGenomic alterationsStructural rearrangementsProtein expressionMutant BRAFCell markersExpressionGenesRNADNAMutationsCutaneous melanomaKIT mutationsNF1RASRearrangementEnrichmentLandscapeDownregulation of the Ubiquitin Ligase RNF125 Underlies Resistance of Melanoma Cells to BRAF Inhibitors via JAK1 Deregulation
Kim H, Frederick DT, Levesque MP, Cooper ZA, Feng Y, Krepler C, Brill L, Samuels Y, Hayward NK, Perlina A, Piris A, Zhang T, Halaban R, Herlyn MM, Brown KM, Wargo JA, Dummer R, Flaherty KT, Ronai Z. Downregulation of the Ubiquitin Ligase RNF125 Underlies Resistance of Melanoma Cells to BRAF Inhibitors via JAK1 Deregulation. Cell Reports 2015, 11: 1458-1473. PMID: 26027934, PMCID: PMC4681438, DOI: 10.1016/j.celrep.2015.04.049.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCell Line, TumorChromatography, LiquidDown-RegulationDrug Resistance, NeoplasmEnzyme InhibitorsFemaleHeterograftsHumansImmunoblottingImmunohistochemistryImmunoprecipitationJanus Kinase 1Mass SpectrometryMelanomaMiceMice, NudeProto-Oncogene Proteins B-rafRNA, Small InterferingTransfectionUbiquitin-Protein LigasesConceptsBRAF inhibitorsRTK expressionReceptor tyrosine kinasesRemarkable clinical responsesBRAFi-resistant melanomasInhibition of JAK1BRAFi-resistant tumorsClinical responseCombination therapyMost tumorsBRAF mutationsTumor specimensVivo xenograftsBRAFi resistanceMelanoma cellsElevated expressionMelanomaEGFRAdaptive resistanceTumorsRNF125MITF expressionTyrosine kinaseJAK1DownregulationPLEKHA5 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 sitesPDK1 and SGK3 Contribute to the Growth of BRAF-Mutant Melanomas and Are Potential Therapeutic Targets
Scortegagna M, Lau E, Zhang T, Feng Y, Sereduk C, Yin H, De SK, Meeth K, Platt JT, Langdon CG, Halaban R, Pellecchia M, Davies MA, Brown K, Stern DF, Bosenberg M, Ronai ZA. PDK1 and SGK3 Contribute to the Growth of BRAF-Mutant Melanomas and Are Potential Therapeutic Targets. Cancer Research 2015, 75: 1399-1412. PMID: 25712345, PMCID: PMC4383687, DOI: 10.1158/0008-5472.can-14-2785.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBenzoatesBridged Bicyclo Compounds, HeterocyclicCell Line, TumorDrug Screening Assays, AntitumorG1 Phase Cell Cycle CheckpointsHumansImmediate-Early ProteinsIndazolesLymphatic MetastasisMelanomaMice, KnockoutMolecular Targeted TherapyProtein Kinase InhibitorsProtein Serine-Threonine KinasesProto-Oncogene Proteins B-rafPyrimidinesPyruvate Dehydrogenase Acetyl-Transferring KinaseSkinSkin NeoplasmsConceptsPDK1 inhibitionAGC kinase familySynthetic lethal screenCell cycle arrestPhase cell cycle arrestPigmentation genesPDK1 activityG1 phase cell cycle arrestSuppress melanoma growthKinase familyTherapeutic targetMelanoma growthPDK1PTEN genotypePI3KMelanoma developmentPotential therapeutic targetK inhibitionPharmacologic inhibitionDevelopment of melanomaPan-PI3K inhibitionBRAF-mutant melanomaSGK3GenesMelanoma cellsChemiexcitation of melanin derivatives induces DNA photoproducts long after UV exposure
Premi S, Wallisch S, Mano CM, Weiner AB, Bacchiocchi A, Wakamatsu K, Bechara EJ, Halaban R, Douki T, Brash DE. Chemiexcitation of melanin derivatives induces DNA photoproducts long after UV exposure. Science 2015, 347: 842-847. PMID: 25700512, PMCID: PMC4432913, DOI: 10.1126/science.1256022.Peer-Reviewed Original ResearchConceptsDark cyclobutane pyrimidine dimersExcited electronic statesUltraviolet photonsUV photonsElectronic statesTriplet stateSunlight-induced melanomaCytosine-containing cyclobutane pyrimidine dimersEnergy transferPhotonsPicosecondsElectronsUV exposureRadiationChemiexcitationEnergyStatePhotoproducts
2014
RAC1 and Melanoma
Halaban R. RAC1 and Melanoma. Clinical Therapeutics 2014, 37: 682-685. PMID: 25465943, PMCID: PMC4415501, DOI: 10.1016/j.clinthera.2014.10.027.Peer-Reviewed Original Research