Featured Publications
Analyses of non-coding somatic drivers in 2,658 cancer whole genomes
Rheinbay E, Nielsen MM, Abascal F, Wala JA, Shapira O, Tiao G, Hornshøj H, Hess JM, Juul RI, Lin Z, Feuerbach L, Sabarinathan R, Madsen T, Kim J, Mularoni L, Shuai S, Lanzós A, Herrmann C, Maruvka YE, Shen C, Amin SB, Bandopadhayay P, Bertl J, Boroevich KA, Busanovich J, Carlevaro-Fita J, Chakravarty D, Chan CWY, Craft D, Dhingra P, Diamanti K, Fonseca NA, Gonzalez-Perez A, Guo Q, Hamilton MP, Haradhvala NJ, Hong C, Isaev K, Johnson TA, Juul M, Kahles A, Kahraman A, Kim Y, Komorowski J, Kumar K, Kumar S, Lee D, Lehmann KV, Li Y, Liu EM, Lochovsky L, Park K, Pich O, Roberts ND, Saksena G, Schumacher SE, Sidiropoulos N, Sieverling L, Sinnott-Armstrong N, Stewart C, Tamborero D, Tubio JMC, Umer HM, Uusküla-Reimand L, Wadelius C, Wadi L, Yao X, Zhang CZ, Zhang J, Haber JE, Hobolth A, Imielinski M, Kellis M, Lawrence MS, von Mering C, Nakagawa H, Raphael BJ, Rubin MA, Sander C, Stein LD, Stuart JM, Tsunoda T, Wheeler DA, Johnson R, Reimand J, Gerstein M, Khurana E, Campbell PJ, López-Bigas N, Weischenfeldt J, Beroukhim R, Martincorena I, Pedersen J, Getz G. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature 2020, 578: 102-111. PMID: 32025015, PMCID: PMC7054214, DOI: 10.1038/s41586-020-1965-x.Peer-Reviewed Original ResearchMeSH KeywordsDatabases, GeneticDNA BreaksGene Expression Regulation, NeoplasticGenome, HumanGenome-Wide Association StudyHumansINDEL MutationMutationNeoplasmsConceptsInternational Cancer Genome ConsortiumStructural variantsPoint mutationsDriver discoveryProtein-coding genesNon-coding genesNon-coding regionsPan-cancer analysisDriver point mutationsSomatic driversCancer Genome AtlasRegulatory sequencesCancer genomesUntranslated regionGenome ConsortiumFocal deletionsGenesGenome AtlasGenomeNovel candidatesMutationsRecurrent breakpointsRegion of TP53DiscoveryVariants
2020
KMT2D Deficiency Impairs Super-Enhancers to Confer a Glycolytic Vulnerability in Lung Cancer
Alam H, Tang M, Maitituoheti M, Dhar S, Kumar M, Han C, Ambati C, Amin S, Gu B, Chen T, Lin Y, Chen J, Muller F, Putluri N, Flores E, DeMayo F, Baseler L, Rai K, Lee M. KMT2D Deficiency Impairs Super-Enhancers to Confer a Glycolytic Vulnerability in Lung Cancer. Cancer Cell 2020, 37: 599-617.e7. PMID: 32243837, PMCID: PMC7178078, DOI: 10.1016/j.ccell.2020.03.005.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma of LungAnimalsAntimetabolitesApoptosisBiomarkers, TumorCell ProliferationDeoxyglucoseDNA-Binding ProteinsEnhancer Elements, GeneticGene Expression Regulation, NeoplasticGlycolysisHistone-Lysine N-MethyltransferaseHistonesHumansLung NeoplasmsMiceMice, KnockoutMice, NudeMutationMyeloid-Lymphoid Leukemia ProteinNeoplasm ProteinsPeriod Circadian ProteinsPrognosisTumor Cells, CulturedXenograft Model Antitumor AssaysConceptsLung cancerLung-specific lossHuman lung cancer cellsExpression of Per2Lung cancer cellsHistone methyltransferase KMT2DLung tumor suppressorTumor suppressive roleMultiple glycolytic genesLung tumorigenesisEpigenetic modifiersPharmacological inhibitionTherapeutic vulnerabilitiesGlycolytic inhibitorCancerCancer cellsKMT2DFunction mutationsTumor suppressorPer2GlycolysisGlycolytic genesMutationsMice
2019
p53 Is a Master Regulator of Proteostasis in SMARCB1-Deficient Malignant Rhabdoid Tumors
Carugo A, Minelli R, Sapio L, Soeung M, Carbone F, Robinson F, Tepper J, Chen Z, Lovisa S, Svelto M, Amin S, Srinivasan S, Del Poggetto E, Loponte S, Puca F, Dey P, Malouf G, Su X, Li L, Lopez-Terrada D, Rakheja D, Lazar A, Netto G, Rao P, Sgambato A, Maitra A, Tripathi D, Walker C, Karam J, Heffernan T, Viale A, Roberts C, Msaouel P, Tannir N, Draetta G, Genovese G. p53 Is a Master Regulator of Proteostasis in SMARCB1-Deficient Malignant Rhabdoid Tumors. Cancer Cell 2019, 35: 204-220.e9. PMID: 30753823, PMCID: PMC7876656, DOI: 10.1016/j.ccell.2019.01.006.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntineoplastic AgentsAutophagyCell Line, TumorCyclin-Dependent Kinase Inhibitor p16Endoplasmic Reticulum StressFemaleGene Expression Regulation, NeoplasticHumansMaleMice, 129 StrainMice, Inbred C57BLMice, KnockoutProteasome InhibitorsProteostasisProto-Oncogene Proteins c-mycRhabdoid TumorSignal TransductionSMARCB1 ProteinTumor Cells, CulturedTumor Suppressor Protein p53Unfolded Protein ResponseConceptsMalignant rhabdoid tumorRhabdoid tumorUnfolded protein responseClinical pathological featuresAggressive pediatric malignancyCombination of agentsPediatric malignanciesMouse modelP53 axisMosaic mouse modelChromatin remodeling genesER stress responseTumorsHuman oncogenesisBiallelic inactivationMalignancyProtein responseDramatic activationHuman diseasesMaster regulatorExquisite sensitivityAutophagic machineryAgentsDiseaseStress response
2018
An in vivo screen identifies PYGO2 as a driver for metastatic prostate cancer
Lu X, Pan X, Wu C, Zhao D, Feng S, Zang Y, Lee R, Khadka S, Amin S, Jin E, Shang X, Deng P, Luo Y, Morgenlander W, Weinrich J, Lu X, Jiang S, Chang Q, Navone N, Troncoso P, DePinho R, Wang Y. An in vivo screen identifies PYGO2 as a driver for metastatic prostate cancer. Cancer Research 2018, 78: canres.3564.2017. PMID: 29769196, PMCID: PMC6381393, DOI: 10.1158/0008-5472.can-17-3564.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBiomarkers, TumorCarcinogenesisCell Line, TumorDisease ProgressionGene Expression Regulation, NeoplasticHEK293 CellsHumansIntracellular Signaling Peptides and ProteinsLymph NodesMaleMiceMice, NudeNeoplasm GradingOncogenesPC-3 CellsProstatic NeoplasmsTranscriptional ActivationUp-RegulationWnt Signaling PathwayConceptsProstate cancer progressionDepth functional analysisCancer progressionWnt/β-catenin signalingCancer cell invasionΒ-catenin signalingFunctional genomicsProstate cancerTranscriptional activationCopy number aberrationsTranscriptomic datasetsFinger 2New oncogenePygo2's functionFunctional driversFunctional analysisLymph nodesImpairs tumor progressionChromosomal instabilityPutative oncogeneCell invasionNumber aberrationsPositive hitsAmplification/overexpressionOncogene
2017
TumorFusions: an integrative resource for cancer-associated transcript fusions
Hu X, Wang Q, Tang M, Barthel F, Amin S, Yoshihara K, Lang F, Martinez-Ledesma E, Lee S, Zheng S, Verhaak R. TumorFusions: an integrative resource for cancer-associated transcript fusions. Nucleic Acids Research 2017, 46: gkx1018-. PMID: 29099951, PMCID: PMC5753333, DOI: 10.1093/nar/gkx1018.Peer-Reviewed Original ResearchMeSH KeywordsDatabases, GeneticDNA Copy Number VariationsGene Expression Regulation, NeoplasticGene FusionHumansNeoplasmsOncogene Proteins, FusionPolymorphism, Single NucleotideReproducibility of ResultsUser-Computer InterfaceWhole Genome SequencingConceptsTranscript fusionsGene fusionsWhole-genome sequencing dataSomatic DNA rearrangementsTranscript-level expressionGenome sequencing dataGene annotationCopy number levelsCancer samplesCancer Genome AtlasDNA rearrangementsUniform pipelineFunctional fusionSequencing dataIntegrative resourceLevel expressionPartner genesGenome AtlasChromosomal alterationsMutational patternsCancer typesFusion transcriptsNon-neoplastic samplesMolecular aberrationsNumber levels
2015
The Molecular Taxonomy of Primary Prostate Cancer
Network T, Abeshouse A, Ahn J, Akbani R, Ally A, Amin S, Andry C, Annala M, Aprikian A, Armenia J, Arora A, Auman J, Balasundaram M, Balu S, Barbieri C, Bauer T, Benz C, Bergeron A, Beroukhim R, Berrios M, Bivol A, Bodenheimer T, Boice L, Bootwalla M, dos Reis R, Boutros P, Bowen J, Bowlby R, Boyd J, Bradley R, Breggia A, Brimo F, Bristow C, Brooks D, Broom B, Bryce A, Bubley G, Burks E, Butterfield Y, Button M, Canes D, Carlotti C, Carlsen R, Carmel M, Carroll P, Carter S, Cartun R, Carver B, Chan J, Chang M, Chen Y, Cherniack A, Chevalier S, Chin L, Cho J, Chu A, Chuah E, Chudamani S, Cibulskis K, Ciriello G, Clarke A, Cooperberg M, Corcoran N, Costello A, Cowan J, Crain D, Curley E, David K, Demchok J, Demichelis F, Dhalla N, Dhir R, Doueik A, Drake B, Dvinge H, Dyakova N, Felau I, Ferguson M, Frazer S, Freedland S, Fu Y, Gabriel S, Gao J, Gardner J, Gastier-Foster J, Gehlenborg N, Gerken M, Gerstein M, Getz G, Godwin A, Gopalan A, Graefen M, Graim K, Gribbin T, Guin R, Gupta M, Hadjipanayis A, Haider S, Hamel L, Hayes D, Heiman D, Hess J, Hoadley K, Holbrook A, Holt R, Holway A, Hovens C, Hoyle A, Huang M, Hutter C, Ittmann M, Iype L, Jefferys S, Jones C, Jones S, Juhl H, Kahles A, Kane C, Kasaian K, Kerger M, Khurana E, Kim J, Klein R, Kucherlapati R, Lacombe L, Ladanyi M, Lai P, Laird P, Lander E, Latour M, Lawrence M, Lau K, LeBien T, Lee D, Lee S, Lehmann K, Leraas K, Leshchiner I, Leung R, Libertino J, Lichtenberg T, Lin P, Linehan W, Ling S, Lippman S, Liu J, Liu W, Lochovsky L, Loda M, Logothetis C, Lolla L, Longacre T, Lu Y, Luo J, Ma Y, Mahadeshwar H, Mallery D, Mariamidze A, Marra M, Mayo M, McCall S, McKercher G, Meng S, Mes-Masson A, Merino M, Meyerson M, Mieczkowski P, Mills G, Shaw K, Minner S, Moinzadeh A, Moore R, Morris S, Morrison C, Mose L, Mungall A, Murray B, Myers J, Naresh R, Nelson J, Nelson M, Nelson P, Newton Y, Noble M, Noushmehr H, Nykter M, Pantazi A, Parfenov M, Park P, Parker J, Paulauskis J, Penny R, Perou C, Piché A, Pihl T, Pinto P, Prandi D, Protopopov A, Ramirez N, Rao A, Rathmell W, Rätsch G, Ren X, Reuter V, Reynolds S, Rhie S, Rieger-Christ K, Roach J, Robertson A, Robinson B, Rubin M, Saad F, Sadeghi S, Saksena G, Saller C, Salner A, Sanchez-Vega F, Sander C, Sandusky G, Sauter G, Sboner A, Scardino P, Scarlata E, Schein J, Schlomm T, Schmidt L, Schultz N, Schumacher S, Seidman J, Neder L, Seth S, Sharp A, Shelton C, Shelton T, Shen H, Shen R, Sherman M, Sheth M, Shi Y, Shih J, Shmulevich I, Simko J, Simon R, Simons J, Sipahimalani P, Skelly T, Sofia H, Soloway M, Song X, Sorcini A, Sougnez C, Stepa S, Stewart C, Stewart J, Stuart J, Sullivan T, Sun C, Sun H, Tam A, Tan D, Tang J, Tarnuzzer R, Tarvin K, Taylor B, Teebagy P, Tenggara I, Têtu B, Tewari A, Thiessen N, Thompson T, Thorne L, Tirapelli D, Tomlins S, Trevisan F, Troncoso P, True L, Tsourlakis M, Tyekucheva S, Van Allen E, Van Den Berg D, Veluvolu U, Verhaak R, Vocke C, Voet D, Wan Y, Wang Q, Wang W, Wang Z, Weinhold N, Weinstein J, Weisenberger D, Wilkerson M, Wise L, Witte J, Wu C, Wu J, Wu Y, Xu A, Yadav S, Yang L, Yang L, Yau C, Ye H, Yena P, Zeng T, Zenklusen J, Zhang H, Zhang J, Zhang J, Zhang W, Zhong Y, Zhu K, Zmuda E. The Molecular Taxonomy of Primary Prostate Cancer. Cell 2015, 163: 1011-1025. PMID: 26544944, PMCID: PMC4695400, DOI: 10.1016/j.cell.2015.10.025.Peer-Reviewed Original ResearchMeSH KeywordsDNA RepairEpigenesis, GeneticGene Expression Regulation, NeoplasticGene FusionHumansMaleMutationNeoplasm MetastasisPhosphatidylinositol 3-KinasesProstatic NeoplasmsRas ProteinsReceptors, AndrogenSignal TransductionConceptsPrimary prostate cancerProstate cancerVariable clinical courseAndrogen receptor activityPrimary prostate carcinomasSubtype-specific mannerSubstantial heterogeneityMolecular taxonomyCancer Genome AtlasClinical courseSpecific gene fusionsProstate carcinomaMutant tumorsReceptor activityComprehensive molecular analysisMolecular abnormalitiesCancerDNA repair genesMethylator phenotypeActionable lesionsGenome AtlasPI3KRepair genesEpigenetic profilesTumors
2012
Investigational agent MLN9708/2238 targets tumor-suppressor miR33b in MM cells
Tian Z, Zhao J, Tai Y, Amin S, Hu Y, Berger A, Richardson P, Chauhan D, Anderson K. Investigational agent MLN9708/2238 targets tumor-suppressor miR33b in MM cells. Blood 2012, 120: 3958-3967. PMID: 22983447, PMCID: PMC3496955, DOI: 10.1182/blood-2012-01-401794.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntineoplastic AgentsBoron CompoundsCell DeathCell Line, TumorCell MovementCell SurvivalCluster AnalysisDrug Resistance, NeoplasmGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, Tumor SuppressorGlycineHumansImidazolesMiceMicroRNAsMultiple MyelomaProto-Oncogene Proteins c-pim-1PyridazinesSignal TransductionXenograft Model Antitumor AssaysConceptsMultiple myelomaMM cellsPim-1Tumor suppressor geneTranscriptional regulationPim-1 overexpressionBiochemical inhibitorsApoptotic signalingRole of miRTumor suppressorMiR33bMM cell viabilityCell deathPatient MM cellsMM xenograft modelNovel therapeutic strategiesLuciferase activityColony formationOverexpressionMiR profilingTumor pathogenesisInvestigational agentsCritical roleRegulationCell viabilityIntegrative analysis of gene and miRNA expression profiles with transcription factor–miRNA feed-forward loops identifies regulators in human cancers
Yan Z, Shah P, Amin S, Samur M, Huang N, Wang X, Misra V, Ji H, Gabuzda D, Li C. Integrative analysis of gene and miRNA expression profiles with transcription factor–miRNA feed-forward loops identifies regulators in human cancers. Nucleic Acids Research 2012, 40: e135-e135. PMID: 22645320, PMCID: PMC3458521, DOI: 10.1093/nar/gks395.Peer-Reviewed Original ResearchMeSH KeywordsFeedback, PhysiologicalGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMicroRNAsNeoplasmsTranscription FactorsTranscriptomeConceptsFeed-forward loopTranscription factorsMiRNA expression profilesExpression profilesNovel feed-forward loopCancer-related transcription factorsExpression dataTF target genesMiRNA-mRNA interactionsCommon target genesMiR-15/miRMiRNA expression dataMiRNA partnersTranscriptome changesTarget genesDifferential genesIntegrative analysisMultiple cancer typesGenesMiRNA expressionHuman cancersLiterature validationBiological conditionsMiRNAsRegulator
2010
Elevated IL-17 produced by T h 17 cells promotes myeloma cell growth and inhibits immune function in multiple myeloma
Prabhala R, Pelluru D, Fulciniti M, Prabhala H, Nanjappa P, Song W, Pai C, Amin S, Tai Y, Richardson P, Ghobrial I, Treon S, Daley J, Anderson K, Kutok J, Munshi N. Elevated IL-17 produced by T h 17 cells promotes myeloma cell growth and inhibits immune function in multiple myeloma. Blood 2010, 115: 5385-5392. PMID: 20395418, PMCID: PMC2902136, DOI: 10.1182/blood-2009-10-246660.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCell ProliferationCytokinesGene Expression Regulation, NeoplasticHumansInterleukin-17Leukocytes, MononuclearMaleMiceMice, SCIDMultiple MyelomaReceptors, Interleukin-17Th1 CellsT-Lymphocytes, Helper-InducerConceptsPeripheral blood mononuclear cellsHealthy donor peripheral blood mononuclear cellsDonor peripheral blood mononuclear cellsIL-17Multiple myelomaBM mononuclear cellsMyeloma cell growthBone marrowBone marrow stromal cellsIL-22Mononuclear cellsHealthy donorsImmune functionT helper 17 (Th17) cellsElevated IL-17Observed immune dysfunctionSerum IL-17IL-23 productionBlood mononuclear cellsAnti-MM activityIL-17 receptorHuman multiple myelomaMurine xenograft modelImportant therapeutic targetMM pathobiology