2024
Artificial-Intelligence, Data-Driven, Comprehensive Classification of Myeloid Neoplasms Based on Genomic, Morphological and Histological Features
Lanino L, D'Amico S, Maggioni G, Al Ali N, Wang Y, Gurnari C, Gagelmann N, Bewersdorf J, Ball S, Guglielmelli P, Meggendorfer M, Hunter A, Kubasch A, Travaglino E, Campagna A, Ubezio M, Russo A, Todisco G, Tentori C, Buizza A, Sauta E, Zampini M, Riva E, Asti G, Delleani M, Ficara F, Santoro A, Sala C, Dall'Olio D, Dall'Olio L, Kewan T, Casetti I, Awada H, Xicoy B, Vucinic V, Hou H, Chou W, Yao C, Lin C, Tien H, Consagra A, Sallman D, Kern W, Bernardi M, Chiusolo P, Borin L, Voso M, Pleyer L, Palomo L, Quintela D, Jerez A, Cornejo E, Martin P, Díaz-Beyá M, Pita A, Roldan V, Suarez D, Velasco E, Calabuig M, Garcia-Manero G, Loghavi S, Platzbecker U, Sole F, Diez-Campelo M, Maciejewski J, Kröger N, Fenaux P, Fontenay M, Santini V, Haferlach T, Germing U, Padron E, Robin M, Passamonti F, Solary E, Vannucchi A, Castellani G, Zeidan A, Komrokji R, Della Porta M. Artificial-Intelligence, Data-Driven, Comprehensive Classification of Myeloid Neoplasms Based on Genomic, Morphological and Histological Features. Blood 2024, 144: 1005. DOI: 10.1182/blood-2024-204826.Peer-Reviewed Original ResearchGenomic featuresSplicing mutationBiallelic inactivationAnalysis of genomic profilesBiallelic inactivation of TP53Clinical phenotypeGene expression profilesCNV analysisMorphological featuresInactivation of TP53Myeloid neoplasmsGenomic characterizationRNAseq dataMorphological dataMutation screeningExpression profilesMutationsJAK/STATGenomic profilingGenomeHierarchical importanceHeterogeneous phenotypesIntegrated analysisPhenotypeHematological phenotypeIntegrated mutational landscape analysis of poorly differentiated high-grade neuroendocrine carcinoma of the uterine cervix
Bellone S, Jeong K, Halle M, Krakstad C, McNamara B, Greenman M, Mutlu L, Demirkiran C, Hartwich T, Yang-Hartwich Y, Zipponi M, Buza N, Hui P, Raspagliesi F, Lopez S, Paolini B, Milione M, Perrone E, Scambia G, Altwerger G, Ravaggi A, Bignotti E, Huang G, Andikyan V, Clark M, Ratner E, Azodi M, Schwartz P, Quick C, Angioli R, Terranova C, Zaidi S, Nandi S, Alexandrov L, Siegel E, Choi J, Schlessinger J, Santin A. Integrated mutational landscape analysis of poorly differentiated high-grade neuroendocrine carcinoma of the uterine cervix. Proceedings Of The National Academy Of Sciences Of The United States Of America 2024, 121: e2321898121. PMID: 38625939, PMCID: PMC11046577, DOI: 10.1073/pnas.2321898121.Peer-Reviewed Original ResearchConceptsWhole-exome sequencingPatient-derived-xenograftsBase excision repairCopy number lossMultiregion whole-exome sequencingCopy number gainHigh-grade neuroendocrine carcinomaCNV analysisPhylogenetic analysisEvolutionary historyNeuroendocrine cervical cancerHuman papillomavirus DNAMutator phenotypeSensitivity to afatinibGenetic landscapeRecurrent mutationsRNA sequencingGene fusionsMutational landscape analysisExcision repairGenesMutationsPan-HERConsistent with deficiencyNeuroendocrine carcinoma
2019
NIMG-09. NONINVASIVE PERFUSION IMAGING BIOMARKER OF MALIGNANT GENOTYPE IN ISOCITRATE DEHYDROGENASE MUTANT GLIOMAS
Mureb M, Jain R, Poisson L, Littig I, Neto L, Wu C, Ng V, Patel S, Patel S, Serrano J, Kurz S, Cahill D, Bendszus M, von Deimling A, Placantonakis D, Golfinos J, Kickingereder P, Snuderl M, Chi A. NIMG-09. NONINVASIVE PERFUSION IMAGING BIOMARKER OF MALIGNANT GENOTYPE IN ISOCITRATE DEHYDROGENASE MUTANT GLIOMAS. Neuro-Oncology 2019, 21: vi163-vi163. PMCID: PMC6847952, DOI: 10.1093/neuonc/noz175.681.Peer-Reviewed Original ResearchCDKN2A/B homozygous deletionCopy number variationsHomozygous deletionHigher rCBVGenomic alterationsRelative cerebral blood volumeImmediate postoperative settingHigh perfusion areaCopy number statusCerebral blood volumeNon-invasive imaging biomarkerInformed treatment decisionsMalignant genotypePostoperative settingIDHwt glioblastomasRCBVCDKN2A/BIDHmutCNV analysisAstrocytomaBlood volumeTreatment decisionsPerfusion areaImaging biomarkersDNA hypomethylation
2016
Chromosomal microarray analysis in clinical evaluation of neurodevelopmental disorders-reporting a novel deletion of SETDB1 and illustration of counseling challenge
Xu Q, Goldstein J, Wang P, Gadi IK, Labreche H, Rehder C, Wang WP, McConkie A, Xu X, Jiang YH. Chromosomal microarray analysis in clinical evaluation of neurodevelopmental disorders-reporting a novel deletion of SETDB1 and illustration of counseling challenge. Pediatric Research 2016, 80: 371-381. PMID: 27119313, PMCID: PMC5382808, DOI: 10.1038/pr.2016.101.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAlgorithmsAutistic DisorderChildChild, PreschoolChromatinComparative Genomic HybridizationCounselingDevelopmental DisabilitiesDNA Copy Number VariationsFemaleGene DeletionGene RearrangementHistone-Lysine N-MethyltransferaseHumansInfantIntellectual DisabilityMaleMicroarray AnalysisNeurodevelopmental DisordersPedigreeProtein MethyltransferasesConceptsNeurodevelopmental disordersAutism spectrum disorderIntellectual disabilityDevelopmental disabilitiesCopy number variationsChromosomal microarray analysisEtiological evaluationClinical evaluationClinical significanceUnknown significanceCNV analysisGenetics clinicEtiology of ASDCounseling familiesDisordersVariable penetranceClinicMicroarray analysisNovel deletionSpectrum disorderDisabilityCounseling challengesFurther supportEtiologyCohort
2014
Exome sequencing and genome-wide copy number variant mapping reveal novel associations with sensorineural hereditary hearing loss
Haraksingh RR, Jahanbani F, Rodriguez-Paris J, Gelernter J, Nadeau KC, Oghalai JS, Schrijver I, Snyder MP. Exome sequencing and genome-wide copy number variant mapping reveal novel associations with sensorineural hereditary hearing loss. BMC Genomics 2014, 15: 1155. PMID: 25528277, PMCID: PMC4367882, DOI: 10.1186/1471-2164-15-1155.Peer-Reviewed Original ResearchConceptsHearing lossHereditary hearing lossExome sequencingSensorineural hearing lossType II myosinGenome-wide CNV analysisCase-control cohortNon-syndromic sensorineural hearing lossStrong candidate geneLoss patientsDirect clinical applicationGenetic diversityNovel lociClinical settingCytoskeletal proteinsCandidate genesCandidate lociVariants mappingDistinct familiesChromosome 16Loss phenotypeClinical applicationNovel regionLociCNV analysis
2011
Rare Copy Number Variants in Tourette Syndrome Disrupt Genes in Histaminergic Pathways and Overlap with Autism
Fernandez TV, Sanders SJ, Yurkiewicz IR, Ercan-Sencicek AG, Kim YS, Fishman DO, Raubeson MJ, Song Y, Yasuno K, Ho WS, Bilguvar K, Glessner J, Chu SH, Leckman JF, King RA, Gilbert DL, Heiman GA, Tischfield JA, Hoekstra PJ, Devlin B, Hakonarson H, Mane SM, Günel M, State MW. Rare Copy Number Variants in Tourette Syndrome Disrupt Genes in Histaminergic Pathways and Overlap with Autism. Biological Psychiatry 2011, 71: 392-402. PMID: 22169095, PMCID: PMC3282144, DOI: 10.1016/j.biopsych.2011.09.034.Peer-Reviewed Original ResearchConceptsCopy number variationsRare copy number variationsNovel risk regionsEnrichment of genesGamma-aminobutyric acid receptor genesNervous system developmentEtiology of TSParent-child triosRare copy number variantsCopy number variantsGene mappingPathway analysisDe novo eventsAxon guidanceCell adhesionMolecular pathwaysNumber variationsRelevant pathwaysCNV analysisNumber variantsGenesReceptor geneDe novoNovo eventsPathway
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