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
Unannotated microprotein EMBOW regulates the interactome and chromatin and mitotic functions of WDR5
Chen Y, Su H, Zhao J, Na Z, Jiang K, Bacchiocchi A, Loh K, Halaban R, Wang Z, Cao X, Slavoff S. Unannotated microprotein EMBOW regulates the interactome and chromatin and mitotic functions of WDR5. Cell Reports 2023, 42: 113145. PMID: 37725512, PMCID: PMC10629662, DOI: 10.1016/j.celrep.2023.113145.Peer-Reviewed Original ResearchConceptsG2/M phaseWD40-repeat protein WDR5Mitotic spindle lengthMultiple interaction partnersM phaseOff-target genesLate G1 phaseWDR5 interactionMitotic functionsH3K4me3 levelsWDR5Interaction partnersMultiple proteinsExpression maximaCell cycleSpindle lengthG1 phaseGenesCell proliferationOff-target bindingBindingInteractomeChromatinTranscriptionKIF2A.CD4 T cells and toxicity from immune checkpoint blockade
Earland N, Zhang W, Usmani A, Nene A, Bacchiocchi A, Chen D, Sznol M, Halaban R, Chaudhuri A, Newman A. CD4 T cells and toxicity from immune checkpoint blockade. Immunological Reviews 2023, 318: 96-109. PMID: 37491734, PMCID: PMC10838135, DOI: 10.1111/imr.13248.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsIrAE developmentHigh-dose corticosteroid treatmentT-cell receptor sequencingT cell abundanceImmune checkpoint blockadeCD4 T cellsICI discontinuationCheckpoint inhibitorsCorticosteroid treatmentAdverse eventsCheckpoint blockadeAdvanced melanomaHospital admissionTreatment initiationRNA sequencingSafety profileCancer patientsTCR diversityT cellsBulk RNA sequencingSingle-cell RNA sequencingOrgan systemsPatientsBaseline featuresDynamic 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 ResearchConceptsImmune 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
2021
Retrospective cell lineage reconstruction in humans by using short tandem repeats
Tao L, Raz O, Marx Z, Ghosh MS, Huber S, Greindl-Junghans J, Biezuner T, Amir S, Milo L, Adar R, Levy R, Onn A, Chapal-Ilani N, Berman V, Arie A, Rom G, Oron B, Halaban R, Czyz ZT, Werner-Klein M, Klein CA, Shapiro E. Retrospective cell lineage reconstruction in humans by using short tandem repeats. Cell Reports Methods 2021, 1: 100054. PMID: 34341783, PMCID: PMC8313865, DOI: 10.1016/j.crmeth.2021.100054.Peer-Reviewed Original ResearchConceptsLineage reconstructionShort tandem repeatsCell lineagesTandem repeatsCell lineage reconstructionCell lineage analysisSingle cellsLineage tracing methodHuman cell lineagesGenome editingLineage analysisMolecular inversion probesReconstructed lineagesLineagesDU145 cellsSomatic mutationsDiscovery platformCell of originRepeatsHealthy cellsCellsImportant insightsTissue formationOrganismsDevelopmental history
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
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 analysisVivoDiscoveryLandscapeGNA14 Somatic Mutation Causes Congenital and Sporadic Vascular Tumors by MAPK Activation
Lim YH, Bacchiocchi A, Qiu J, Straub R, Bruckner A, Bercovitch L, Narayan D, Genomics Y, McNiff J, Ko C, Robinson-Bostom L, Antaya R, Halaban R, Choate KA. GNA14 Somatic Mutation Causes Congenital and Sporadic Vascular Tumors by MAPK Activation. American Journal Of Human Genetics 2016, 99: 443-450. PMID: 27476652, PMCID: PMC4974082, DOI: 10.1016/j.ajhg.2016.06.010.Peer-Reviewed Original ResearchMeSH KeywordsCells, CulturedChild, PreschoolEnzyme ActivationGTP-Binding Protein alpha SubunitsGTP-Binding Protein alpha Subunits, Gq-G11Human Umbilical Vein Endothelial CellsHumansInfantInfant, NewbornIntercellular Signaling Peptides and ProteinsMaleMAP Kinase Signaling SystemMelanocytesMitogen-Activated Protein KinasesMutationProto-Oncogene Proteins c-aktVascular NeoplasmsConceptsLobular capillary hemangiomaVascular tumorsKaposiform hemangioendotheliomaMonths of lifeYears of ageSomatic activating mutationsGNA14 mutationsHuman endothelial cellsPharmacologic interventionsSignificant complicationsCommon neoplasmCapillary hemangiomaInfantile hemangiomasLCH lesionsPrimary human endothelial cellsTherapeutic interventionsActivating mutationsGNA11 mutationsTumorsEndothelial cellsLesionsPotential targetHemangiomaGNA14Somatic mutationsGermline 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 mutationsNF1RASRearrangementEnrichmentLandscape