Featured Publications
Truncating PREX2 mutations activate its GEF activity and alter gene expression regulation in NRAS-mutant melanoma
Lissanu Deribe Y, Shi Y, Rai K, Nezi L, Amin S, Wu C, Akdemir K, Mahdavi M, Peng Q, Chang Q, Hornigold K, Arold S, Welch H, Garraway L, Chin L. Truncating PREX2 mutations activate its GEF activity and alter gene expression regulation in NRAS-mutant melanoma. Proceedings Of The National Academy Of Sciences Of The United States Of America 2016, 113: e1296-e1305. PMID: 26884185, PMCID: PMC4780599, DOI: 10.1073/pnas.1513801113.Peer-Reviewed Original ResearchConceptsPREX2 mutationsCross-species gene expression analysisGuanine nucleotide exchange factor activityNucleotide exchange factor activityGene expression regulationPI3K/PTEN/Akt pathwayExchange factor activityMelanoma developmentPTEN/AKT pathwayCell cycle regulatorsGene expression analysisExpression regulationGEF activityCytoskeleton organizationCDKN1C geneRegulatory regionsExpression analysisGene expressionCycle regulatorsDNA hypomethylationCell cycleChromosome 11Tumor suppressorBiological pathwaysMechanistic basisIntegrating Gene and Mir Expression Profiles and Regulatory Network Structures to Define Aberrent Feed Forward Loops with Functional and Clinical Implications in Myeloma.
Fulciniti M, Li Y, Wang X, Samur M, Yan Z, Amin S, Li C, Anderson K, Munshi N. Integrating Gene and Mir Expression Profiles and Regulatory Network Structures to Define Aberrent Feed Forward Loops with Functional and Clinical Implications in Myeloma. Blood 2012, 120: 2386. DOI: 10.1182/blood.v120.21.2386.2386.Peer-Reviewed Original ResearchFeed-forward loopRegulatory network structureGene/sGene expressionExpression profilesMiR expression profilesGene expression profile analysisNormal plasma cellsLarge regulatory networkExpression profile analysisOncogenic effectsExpression profile dataMaster TFsNegative feedback regulationRegulatory networksOncogenomic analysisDifferential genesRegulatory loopMolecular impactHeterogeneous genetic backgroundMiRNA expressionFeedback regulationMiR profilesGenetic backgroundMalignant phenotype
2019
The effects of MicroRNA deregulation on pre-RNA processing network in multiple myeloma
Adamia S, Abiatari I, Amin S, Fulciniti M, Minvielle S, Li C, Moreau P, Avet-Loiseau H, Munshi N, Anderson K. The effects of MicroRNA deregulation on pre-RNA processing network in multiple myeloma. Leukemia 2019, 34: 167-179. PMID: 31182781, PMCID: PMC6901818, DOI: 10.1038/s41375-019-0498-5.Peer-Reviewed Original ResearchConceptsMultiple myelomaPlasma cellsOvert multiple myelomaPatient outcomesMM cellsMM pathogenesisLet-7fMicroRNA deregulationRegulation of microRNAsCD138Certain miRsMyelomaMiRDependent gene expressionDeregulated expressionMiR-mediated regulationSignificant numberEpigenetic lesionsTarget genesMM genomesExpressionGene expressionEarly stagesCellsPatients
2015
Genomic 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
2011
The dChip survival analysis module for microarray data
Amin S, Shah P, Yan A, Adamia S, Minvielle S, Avet-Loiseau H, Munshi N, Li C. The dChip survival analysis module for microarray data. BMC Bioinformatics 2011, 12: 72. PMID: 21388547, PMCID: PMC3068974, DOI: 10.1186/1471-2105-12-72.Peer-Reviewed Original ResearchConceptsAnalysis moduleUser-friendly wayDemonstration dataMicroarray data analysisAnalysis functionsFast computationSoftware packageSoftwareSignificant chromosome regionsMicroarray dataMinimal learning curveGene expressionDChip softwareModuleGenome-wide copy number alterationsData analysisSNP array dataSurvival gene signaturesCopy number dataChromosome displayContext of genesUsersCopy number alterationsChromosome regionsClustering