2022
Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota
Petrone ME, Rothman JE, Breban MI, Ott IM, Russell A, Lasek-Nesselquist E, Badr H, Kelly K, Omerza G, Renzette N, Watkins AE, Kalinich CC, Alpert T, Brito AF, Earnest R, Tikhonova IR, Castaldi C, Kelly JP, Shudt M, Plitnick J, Schneider E, Murphy S, Neal C, Laszlo E, Altajar A, Pearson C, Muyombwe A, Downing R, Razeq J, Niccolai L, Wilson MS, Anderson ML, Wang J, Liu C, Hui P, Mane S, Taylor BP, Hanage WP, Landry ML, Peaper DR, Bilguvar K, Fauver JR, Vogels CBF, Gardner LM, Pitzer VE, St. George K, Adams MD, Grubaugh ND. Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota. Communications Biology 2022, 5: 439. PMID: 35545661, PMCID: PMC9095641, DOI: 10.1038/s42003-022-03347-3.Peer-Reviewed Original ResearchCenters for Mendelian Genomics: A decade of facilitating gene discovery
Baxter SM, Posey JE, Lake NJ, Sobreira N, Chong JX, Buyske S, Blue EE, Chadwick LH, Coban-Akdemir ZH, Doheny KF, Davis CP, Lek M, Wellington C, Jhangiani SN, Gerstein M, Gibbs RA, Lifton RP, MacArthur DG, Matise TC, Lupski JR, Valle D, Bamshad MJ, Hamosh A, Mane S, Nickerson DA, Consortium C, Adams M, Aguet F, Akay G, Anderson P, Antonescu C, Arachchi H, Atik M, Austin-Tse C, Babb L, Bacus T, Bahrambeigi V, Balasubramanian S, Bayram Y, Beaudet A, Beck C, Belmont J, Below J, Bilguvar K, Boehm C, Boerwinkle E, Boone P, Bowne S, Brand H, Buckingham K, Byrne A, Calame D, Campbell I, Cao X, Carvalho C, Chander V, Chang J, Chao K, Chinn I, Clarke D, Collins R, Cummings B, Dardas Z, Dawood M, Delano K, DiTroia S, Doddapaneni H, Du H, Du R, Duan R, Eldomery M, Eng C, England E, Evangelista E, Everett S, Fatih J, Felsenfeld A, Francioli L, Frazar C, Fu J, Gamarra E, Gambin T, Gan W, Gandhi M, Ganesh V, Garimella K, Gauthier L, Giroux D, Gonzaga-Jauregui C, Goodrich J, Gordon W, Griffith S, Grochowski C, Gu S, Gudmundsson S, Hall S, Hansen A, Harel T, Harmanci A, Herman I, Hetrick K, Hijazi H, Horike-Pyne M, Hsu E, Hu J, Huang Y, Hurless J, Jahl S, Jarvik G, Jiang Y, Johanson E, Jolly A, Karaca E, Khayat M, Knight J, Kolar J, Kumar S, Lalani S, Laricchia K, Larkin K, Leal S, Lemire G, Lewis R, Li H, Ling H, Lipson R, Liu P, Lovgren A, López-Giráldez F, MacMillan M, Mangilog B, Mano S, Marafi D, Marosy B, Marshall J, Martin R, Marvin C, Mawhinney M, McGee S, McGoldrick D, Mehaffey M, Mekonnen B, Meng X, Mitani T, Miyake C, Mohr D, Morris S, Mullen T, Murdock D, Murugan M, Muzny D, Myers B, Neira J, Nguyen K, Nielsen P, Nudelman N, O’Heir E, O’Leary M, Ongaco C, Orange J, Osei-Owusu I, Paine I, Pais L, Paschall J, Patterson K, Pehlivan D, Pelle B, Penney S, Chavez J, Pierce-Hoffman E, Poli C, Punetha J, Radhakrishnan A, Richardson M, Rodrigues E, Roote G, Rosenfeld J, Ryke E, Sabo A, Sanchez A, Schrauwen I, Scott D, Sedlazeck F, Serrano J, Shaw C, Shelford T, Shively K, Singer-Berk M, Smith J, Snow H, Snyder G, Solomonson M, Son R, Song X, Stankiewicz P, Stephan T, Sutton V, Sveden A, Sánchez D, Tackett M, Talkowski M, Threlkeld M, Tiao G, Udler M, Vail L, Valivullah Z, Valkanas E, VanNoy G, Wang Q, Wang G, Wang L, Wangler M, Watts N, Weisburd B, Weiss J, Wheeler M, White J, Williamson C, Wilson M, Wiszniewski W, Withers M, Witmer D, Witzgall L, Wohler E, Wojcik M, Wong I, Wood J, Wu N, Xing J, Yang Y, Yi Q, Yuan B, Zeiger J, Zhang C, Zhang P, Zhang Y, Zhang X, Zhang Y, Zhang S, Zoghbi H, van den Veyver I, Rehm H, O’Donnell-Luria A. Centers for Mendelian Genomics: A decade of facilitating gene discovery. Genetics In Medicine 2022, 24: 784-797. PMID: 35148959, PMCID: PMC9119004, DOI: 10.1016/j.gim.2021.12.005.Peer-Reviewed Original ResearchConceptsGene discoveryMendelian GenomicsUnderstanding of genesGene-phenotype relationshipsGenome variationWorldwide data sharingCandidate genesMendelian phenotypesGenomic researchGenome sequencingMatchmaker ExchangeGenomicsGenesSequencingBiomedical researchMajor roleDiscoveryExomePhenotypeRoleGenotypesCommunityImplications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies
Brown S, Lavery J, Shen R, Martin A, Kehl K, Sweeney S, Lepisto E, Rizvi H, McCarthy C, Schultz N, Warner J, Park B, Bedard P, Riely G, Schrag D, Panageas K, Sweeney S, Foti M, Khotskaya Y, Fiandalo M, Gross B, Schultz N, Mastrogiacomo B, Sarmardy M, Li M, Resnick A, Waanders A, Lilly J, Carvajal R, Rabadan R, Ingham M, Hsaio S, Abraham J, Brenton J, Rueda O, Caldas C, Valgañón M, Silva D, Boursnell C, Garcia R, Rodriguez E, Nimmervoll B, Cerami E, Ducar M, Kumari P, Lindeman N, MacConnaill L, Orechia J, Schrag D, Shivdasani P, Van Allen E, Johnson J, Jänne P, Lepisto E, Hassett M, Pimentel S, Sripakdeevong P, Janeway K, Johnson J, Meyerson M, Quinn D, Cushing O, Haigis K, Miller D, Kehl K, Gustav A, Tramontano A, Baquero S, Bell J, Green M, McCall S, Datto M, Calvo F, Andre F, Guillaume M, Dogan S, Ludovic L, Scoazec J, Ardenos M, Vassal G, Michels S, Velculescu V, Baras A, Gocke C, Brahmer J, Sawyers C, Solit D, Gardos S, Berger M, Ladanyi M, Riely G, Sirintrapun J, Panageas K, Caroline A, Thomas S, Zarski A, Zehir A, Iasonosa A, Philip J, Brown S, Kung A, Kundra R, Rudolph J, Lavery J, Rivzi H, Schwartz J, McCarthy C, Bhuiya M, Martin A, Chu C, DuBois R, van de Velde T, Meijer G, Horlings H, van Tinteren H, Lolkema M, Nijman L, Bierkens M, Hoeve J, Voest E, Hiemstra A, Sonke G, Craenmehr J, Hudecek J, Monkhorst K, Urba W, Bernard B, Piening B, Bifulco C, Tittel P, Cramer J, Guinney J, Yu T, Guo X, Acebedo A, Gold P, Bailey N, Kadri S, Segal J, Pankhuri W, Wang P, George S, Christine M, Van't Veer L, Talevich E, Wren A, Sweet-Cordero A, Turski M, Bedard P, KamelReid S, Lu Z, Pugh T, Siu L, Watt S, Leighl N, Yu C, Ahmed L, Krishna G, Virtaenen C, Chow H, Plagianakos D, Del Rossi S, Singaravelan N, Hakgor S, Qazi N, Nguyen A, Stickle N, Stricker T, Micheel C, Anderson I, Jones L, Wang L, Lovly C, LeNoue Newton M, Park B, Warner J, Fabbri D, Coco J, Ye C, Chaugai S, Mishra S, Yang Y, Wen L, Dienstmann R, Aguilar Izquierdo S, Viaplana Donato C, Mancuso F, Topaloglu U, Liu L, Guan M, Zhang W, Jin G, Knight J, D'Eletto M, Ormay E, Mane S, Bilguvar K, Zenta W, Dykas D. Implications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies. JAMA Oncology 2022, 8: 287-291. PMID: 34734967, PMCID: PMC9190030, DOI: 10.1001/jamaoncol.2021.5153.Peer-Reviewed Original ResearchConceptsOverall survivalStage IV non-small cell lung cancerNon-small cell lung cancerStage IV colorectal cancerUnadjusted median survivalCell lung cancerMedian survivalStudy entryCancer outcomesColorectal cancerLung cancerMolecular testingSurvival analysisGeneralizable research findingsClinical genomic studiesSurvivalCancerSelection biasAppropriate statistical methodsDiagnosisAmerican Association
2021
Correlation Between Surrogate End Points and Overall Survival in a Multi-institutional Clinicogenomic Cohort of Patients With Non–Small Cell Lung or Colorectal Cancer
Kehl K, Riely G, Lepisto E, Lavery J, Warner J, LeNoue-Newton M, Sweeney S, Rudolph J, Brown S, Yu C, Bedard P, Schrag D, Panageas K, Sweeney S, Foti M, Khotskaya Y, Fiandalo M, Gross B, Schultz N, Mastrogiacomo B, Sarmardy M, Li M, Resnick A, Waanders A, Lilly J, Carvajal R, Rabadan R, Ingham M, Hsaio S, Abraham J, Brenton J, Rueda O, Caldas C, Valgañón M, Silva D, Boursnell C, Garcia R, Rodriguez E, Nimmervoll B, Cerami E, Ducar M, Kumari P, Lindeman N, MacConnaill L, Orechia J, Schrag D, Shivdasani P, Van Allen E, Johnson J, Jänne P, Lepisto E, Hassett M, Pimentel S, Sripakdeevong P, Janeway K, Johnson J, Meyerson M, Quinn D, Cushing O, Haigis K, Miller D, Kehl K, Gustav A, Tramontano A, Baquero S, Bell J, Green M, McCall S, Datto M, Calvo F, Andre F, Guillaume M, Dogan S, Ludovic L, Scoazec J, Ardenos M, Vassal G, Michels S, Velculescu V, Baras A, Gocke C, Brahmer J, Sawyers C, Solit D, Gardos S, Berger M, Ladanyi M, Riely G, Sirintrapun J, Caroline A, Thomas S, Zarski A, Zehir A, Iasonosa A, Philip J, Brown S, Kung A, Kundra R, Rudolph J, Lavery J, Rivzi H, Schwartz J, McCarthy C, Bhuiya M, Martin A, Chu C, DuBois R, van de Velde T, Meijer G, Horlings H, van Tinteren H, Lolkema M, Nijman L, Bierkens M, Hoeve J, Voest E, Hiemstra A, Sonke G, Craenmehr J, Hudecek J, Monkhorst K, Urba W, Bernard B, Piening B, Bifulco C, Tittel P, Cramer J, Guinney J, Yu T, Guo X, Acebedo A, Gold P, Bailey N, Kadri S, Segal J, Pankhuri W, Wang P, George S, Christine M, Van't Veer L, Talevich E, Wren A, Sweet-Cordero A, Turski M, Bedard P, KamelReid S, Lu Z, Pugh T, Siu L, Watt S, Leighl N, Yu C, Ahmed L, Krishna G, Virtaenen C, Chow H, Plagianakos D, Del Rossi S, Singaravelan N, Hakgor S, Qazi N, Nguyen A, Stickle N, Stricker T, Micheel C, Anderson I, Jones L, Wang L, Lovly C, LeNoue Newton M, Park B, Warner J, Fabbri D, Coco J, Ye C, Chaugai S, Mishra S, Yang Y, Wen L, Dienstmann R, Aguilar Izquierdo S, Viaplana Donato C, Mancuso F, Topaloglu U, Liu L, Guan M, Zhang W, Jin G, Knight J, D'Eletto M, Ormay E, Mane S, Bilguvar K, Zenta W, Dykas D. Correlation Between Surrogate End Points and Overall Survival in a Multi-institutional Clinicogenomic Cohort of Patients With Non–Small Cell Lung or Colorectal Cancer. JAMA Network Open 2021, 4: e2117547. PMID: 34309669, PMCID: PMC8314138, DOI: 10.1001/jamanetworkopen.2021.17547.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerCandidate surrogate end pointsProgression-free survivalSurrogate end pointsOverall survivalTreatment discontinuationColorectal cancerEnd pointCohort studyNext treatmentNon-small cell lungRetrospective cohort studyAlternative end pointsCell lung cancerKey end pointsAdvanced diseasePrimary outcomeSystemic therapyCell lungLung cancerProlonged survivalMAIN OUTCOMEProgression eventsAcademic centersPatientsSequential filtering for clinically relevant variants as a method for clinical interpretation of whole exome sequencing findings in glioma
Ülgen E, Can Ö, Bilguvar K, Akyerli Boylu C, Kılıçturgay Yüksel Ş, Erşen Danyeli A, Sezerman OU, Yakıcıer MC, Pamir MN, Özduman K. Sequential filtering for clinically relevant variants as a method for clinical interpretation of whole exome sequencing findings in glioma. BMC Medical Genomics 2021, 14: 54. PMID: 33622343, PMCID: PMC7903763, DOI: 10.1186/s12920-021-00904-3.Peer-Reviewed Original ResearchConceptsTumor mutational burdenSomatic copy number alterationsWhole-exome sequencing findingsMicrosatellite instabilityGermline variantsClinical interpretationIndividual brain tumorsShort variantRecurrent tumorsMSI incidenceMutational burdenBrain tumorsLoss of heterozygosityPathway enrichment analysisPrimary gliomasClinical settingTumorsWES analysisCopy number alterationsTumor samplesSequencing findingsDiffuse gliomasClinical analysisGliomasChr10 loss
2020
Alternative genomic diagnoses for individuals with a clinical diagnosis of Dubowitz syndrome
Dyment DA, O'Donnell‐Luria A, Agrawal PB, Akdemir Z, Aleck KA, Antaki D, Al Sharhan H, Au P, Aydin H, Beggs AH, Bilguvar K, Boerwinkle E, Brand H, Brownstein CA, Buyske S, Chodirker B, Choi J, Chudley AE, Clericuzio CL, Cox GF, Curry C, de Boer E, de Vries B, Dunn K, Dutmer CM, England EM, Fahrner JA, Geckinli BB, Genetti CA, Gezdirici A, Gibson WT, Gleeson JG, Greenberg CR, Hall A, Hamosh A, Hartley T, Jhangiani SN, Karaca E, Kernohan K, Lauzon JL, Lewis MES, Lowry RB, López‐Giráldez F, Matise TC, McEvoy‐Venneri J, McInnes B, Mhanni A, Minaur S, Moilanen J, Nguyen A, Nowaczyk MJM, Posey JE, Õunap K, Pehlivan D, Pajusalu S, Penney LS, Poterba T, Prontera P, Doriqui MJR, Sawyer SL, Sobreira N, Stanley V, Torun D, Wargowski D, Witmer PD, Wong I, Xing J, Zaki MS, Zhang Y, Consortium C, Genomics C, Boycott KM, Bamshad MJ, Nickerson DA, Blue EE, Innes AM. Alternative genomic diagnoses for individuals with a clinical diagnosis of Dubowitz syndrome. American Journal Of Medical Genetics Part A 2020, 185: 119-133. PMID: 33098347, PMCID: PMC8197629, DOI: 10.1002/ajmg.a.61926.Peer-Reviewed Original ResearchConceptsGenome sequencingExtensive locus heterogeneityCopy number variationsGenomic analysisMolecular diagnosisSingle geneDe novo variantsNext-generation sequencingDisease genesWide sequencingGenesGenomic diagnosisLocus heterogeneityNovo variantsSequencingPhenotypeAdditional familiesBiallelic variantsHDAC8FamilyVariant filteringDistinctive facial appearanceClinical phenotypeVariantsUncertain significanceAssociations of meningioma molecular subgroup and tumor recurrence
Youngblood MW, Miyagishima DF, Jin L, Gupte T, Li C, Duran D, Montejo JD, Zhao A, Sheth A, Tyrtova E, Özduman K, Iacoangeli F, Peyre M, Boetto J, Pease M, Avşar T, Huttner A, Bilguvar K, Kilic T, Pamir MN, Amankulor N, Kalamarides M, Erson-Omay EZ, Günel M, Moliterno J. Associations of meningioma molecular subgroup and tumor recurrence. Neuro-Oncology 2020, 23: 783-794. PMID: 33068421, PMCID: PMC8099468, DOI: 10.1093/neuonc/noaa226.Peer-Reviewed Original ResearchConceptsDivergent clinical coursesMolecular subgroupsClinical courseClinical outcomesProgression-free survivalExtent of resectionKaplan-Meier analysisLong-term outcomesLow-grade tumorsCox proportional hazardsDistinct clinical outcomesPostoperative radiationIndependent predictorsMale sexRecurrence rateSurveillance imagingTumor recurrencePrevious recurrencesClinical prognosticationKi-67Outcome dataAggressive subgroupRecurrenceElevated recurrenceProportional hazards
2017
Integrated genomic analyses of de novo pathways underlying atypical meningiomas
Harmancı AS, Youngblood MW, Clark VE, Coşkun S, Henegariu O, Duran D, Erson-Omay EZ, Kaulen LD, Lee TI, Abraham BJ, Simon M, Krischek B, Timmer M, Goldbrunner R, Omay SB, Baranoski J, Baran B, Carrión-Grant G, Bai H, Mishra-Gorur K, Schramm J, Moliterno J, Vortmeyer AO, Bilgüvar K, Yasuno K, Young RA, Günel M. Integrated genomic analyses of de novo pathways underlying atypical meningiomas. Nature Communications 2017, 8: 14433. PMID: 28195122, PMCID: PMC5316884, DOI: 10.1038/ncomms14433.Peer-Reviewed Original ResearchMeSH KeywordsBinding SitesBrain NeoplasmsCell Transformation, NeoplasticChromosomal InstabilityCluster AnalysisDNA MethylationE2F2 Transcription FactorEnhancer of Zeste Homolog 2 ProteinEpigenomicsExomeForkhead Box Protein M1Gene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksGene SilencingGenes, Neurofibromatosis 2GenomeGenomicsGenotyping TechniquesHuman Embryonic Stem CellsHumansJumonji Domain-Containing Histone DemethylasesMeningeal NeoplasmsMeningiomaMolecular Probe TechniquesMutationPhenotypePolycomb Repressive Complex 2Promoter Regions, GeneticRNA, MessengerSequence AnalysisSignal TransductionSMARCB1 ProteinTranscriptomeConceptsPolycomb repressive complex 2Human embryonic stem cellsRepressive complex 2Integrated genomic analysisEmbryonic stem cellsDe novo pathwayH3K27me3 signalsTranscriptional networksPRC2 complexEpigenomic analysisCellular statesCatalytic subunitGenomic analysisGenomic instabilityHypermethylated phenotypeGenomic landscapeNovo pathwayDisplay lossStem cellsPotential therapeutic targetExhibit upregulationPromoter mutationsTherapeutic targetMutationsComplexes 2Longitudinal analysis of treatment-induced genomic alterations in gliomas
Erson-Omay EZ, Henegariu O, Omay SB, Harmancı AS, Youngblood MW, Mishra-Gorur K, Li J, Özduman K, Carrión-Grant G, Clark VE, Çağlar C, Bakırcıoğlu M, Pamir MN, Tabar V, Vortmeyer AO, Bilguvar K, Yasuno K, DeAngelis LM, Baehring JM, Moliterno J, Günel M. Longitudinal analysis of treatment-induced genomic alterations in gliomas. Genome Medicine 2017, 9: 12. PMID: 28153049, PMCID: PMC5290635, DOI: 10.1186/s13073-017-0401-9.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic AgentsChromosome AberrationsCombined Modality TherapyDisease ProgressionDNA Mismatch RepairDNA Mutational AnalysisDNA, NeoplasmExomeFemaleGeneral SurgeryGenome, HumanGenomicsGlioblastomaHumansImmunotherapyLongitudinal StudiesMiddle AgedMutationNeoplasm Recurrence, LocalPrecision MedicineRadiotherapyTreatment OutcomeConceptsWhole-exome sequencingMismatch repair deficiencyImmune checkpoint inhibitionMalignant brain tumorsMolecular changesLongitudinal analysisMedian survivalCheckpoint inhibitionSubsequent recurrenceMaximal resectionStandard treatmentBackgroundGlioblastoma multiformeBrain tumorsTumor-normal pairsFavorable responsePrimary GBMIndividual tumorsConclusionsOur studyPrecision therapyPersonalized treatmentGenomic profilingRepair deficiencyGenomic alterationsGenomic profilesTherapy
2013
Genomic Analysis of Non-NF2 Meningiomas Reveals Mutations in TRAF7, KLF4, AKT1, and SMO
Clark VE, Erson-Omay EZ, Serin A, Yin J, Cotney J, Özduman K, Avşar T, Li J, Murray PB, Henegariu O, Yilmaz S, Günel JM, Carrión-Grant G, Yılmaz B, Grady C, Tanrıkulu B, Bakırcıoğlu M, Kaymakçalan H, Caglayan AO, Sencar L, Ceyhun E, Atik AF, Bayri Y, Bai H, Kolb LE, Hebert RM, Omay SB, Mishra-Gorur K, Choi M, Overton JD, Holland EC, Mane S, State MW, Bilgüvar K, Baehring JM, Gutin PH, Piepmeier JM, Vortmeyer A, Brennan CW, Pamir MN, Kılıç T, Lifton RP, Noonan JP, Yasuno K, Günel M. Genomic Analysis of Non-NF2 Meningiomas Reveals Mutations in TRAF7, KLF4, AKT1, and SMO. Science 2013, 339: 1077-1080. PMID: 23348505, PMCID: PMC4808587, DOI: 10.1126/science.1233009.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBrain NeoplasmsChromosomes, Human, Pair 22DNA Mutational AnalysisFemaleGenes, Neurofibromatosis 2Genomic InstabilityGenomicsHumansKruppel-Like Factor 4Kruppel-Like Transcription FactorsMaleMeningeal NeoplasmsMeningiomaMiddle AgedMutationNeoplasm GradingProto-Oncogene Proteins c-aktReceptors, G-Protein-CoupledSmoothened ReceptorTumor Necrosis Factor Receptor-Associated Peptides and Proteins