Featured Publications
Extrachromosomal DNA is associated with oncogene amplification and poor outcome across multiple cancers
Kim H, Nguyen N, Turner K, Wu S, Gujar A, Luebeck J, Liu J, Deshpande V, Rajkumar U, Namburi S, Amin S, Yi E, Menghi F, Schulte J, Henssen A, Chang H, Beck C, Mischel P, Bafna V, Verhaak R. Extrachromosomal DNA is associated with oncogene amplification and poor outcome across multiple cancers. Nature Genetics 2020, 52: 891-897. PMID: 32807987, PMCID: PMC7484012, DOI: 10.1038/s41588-020-0678-2.Peer-Reviewed Original ResearchConceptsOncogene amplificationPoor outcomeCancer typesEcDNA amplificationShorter survivalCancer patientsMost cancer typesExtrachromosomal DNA amplificationsClinical impactMultiple cancersPatientsNormal tissuesCancerTranscript fusionsEnhanced chromatin accessibilityIntratumoral genetic heterogeneityOncogene transcriptionChromosomal amplificationOutcomesGenetic heterogeneityHigh levelsDNA amplificationTissue typesBloodLongitudinal molecular trajectories of diffuse glioma in adults
Barthel FP, Johnson KC, Varn FS, Moskalik AD, Tanner G, Kocakavuk E, Anderson KJ, Abiola O, Aldape K, Alfaro KD, Alpar D, Amin SB, Ashley DM, Bandopadhayay P, Barnholtz-Sloan JS, Beroukhim R, Bock C, Brastianos PK, Brat DJ, Brodbelt AR, Bruns AF, Bulsara KR, Chakrabarty A, Chakravarti A, Chuang JH, Claus EB, Cochran EJ, Connelly J, Costello JF, Finocchiaro G, Fletcher MN, French PJ, Gan HK, Gilbert MR, Gould PV, Grimmer MR, Iavarone A, Ismail A, Jenkinson MD, Khasraw M, Kim H, Kouwenhoven MCM, LaViolette PS, Li M, Lichter P, Ligon KL, Lowman AK, Malta TM, Mazor T, McDonald KL, Molinaro AM, Nam DH, Nayyar N, Ng HK, Ngan CY, Niclou SP, Niers JM, Noushmehr H, Noorbakhsh J, Ormond DR, Park CK, Poisson LM, Rabadan R, Radlwimmer B, Rao G, Reifenberger G, Sa JK, Schuster M, Shaw BL, Short SC, Smitt PAS, Sloan AE, Smits M, Suzuki H, Tabatabai G, Van Meir EG, Watts C, Weller M, Wesseling P, Westerman BA, Widhalm G, Woehrer A, Yung WKA, Zadeh G, Huse JT, De Groot JF, Stead LF, Verhaak RGW. Longitudinal molecular trajectories of diffuse glioma in adults. Nature 2019, 576: 112-120. PMID: 31748746, PMCID: PMC6897368, DOI: 10.1038/s41586-019-1775-1.Peer-Reviewed Original ResearchConceptsAdult patientsDiffuse gliomasRecurrent gliomaOverall survivalPoor outcomeCurrent therapiesChromosome arms 1p/19qAcquired alterationsMajor subtypesTherapeutic resistanceGliomasGlioma developmentGene alterationsIDH mutationsGlioma subtypesPatientsHypermutator phenotypeDriver genesSubtypesClinical annotationSurvivalSubclonal selectionCell cycleAlterationsLittle evidence
2024
A brave new framework for glioma drug development
Hotchkiss K, Karschnia P, Schreck K, Geurts M, Cloughesy T, Huse J, Duke E, Lathia J, Ashley D, Nduom E, Long G, Singh K, Chalmers A, Ahluwalia M, Heimberger A, Bagley S, Todo T, Verhaak R, Kelly P, Hervey-Jumper S, de Groot J, Patel A, Fecci P, Parney I, Wykes V, Watts C, Burns T, Sanai N, Preusser M, Tonn J, Drummond K, Platten M, Das S, Tanner K, Vogelbaum M, Weller M, Whittle J, Berger M, Khasraw M. A brave new framework for glioma drug development. The Lancet Oncology 2024, 25: e512-e519. PMID: 39362262, DOI: 10.1016/s1470-2045(24)00190-6.Peer-Reviewed Original ResearchConceptsBrain tumorsBenefits of biopsyBrain tumor therapyLiquid biopsy technologiesTissue samplesPostoperative deficitsBiopsy techniqueBiopsy technologyEffective therapySurgical trialsClinical trialsTumor therapyResistance mechanismsTumorTherapyPatientsDrug developmentTissue analysisBrainTrialsTissueBiopsyGliomaRegulatory agenciesOncogenic composite mutations can be predicted by co‐mutations and their chromosomal location
Küçükosmanoglu A, van der Borden C, de Boer L, Verhaak R, Noske D, Wurdinger T, Radonic T, Westerman B. Oncogenic composite mutations can be predicted by co‐mutations and their chromosomal location. Molecular Oncology 2024, 18: 2407-2422. PMID: 38757376, PMCID: PMC11459034, DOI: 10.1002/1878-0261.13636.Peer-Reviewed Original ResearchComposite mutationCo-mutationsMutation-specific drugsCell line dataChromosomal locationSub-clonal populationsGenetic heterogeneitySub-clonesTherapy resistanceSelection pressureGenetic eventsStratify patientsKRAS geneResistance-causing mutationsCancer patientsBiopsy samplesMutationsPatientsGenesPrecision medicineTherapyRiskChromosomeBiopsyBRAF
2023
CTNI-23. SINGLE CELL TRANSCRIPTOMICS, PHARMACOKINETICS, AND PHARMACODYNAMICS OF COMBINED CDK4/6 AND MTOR INHIBITION IN A PHASE 0 TRIAL OF RECURRENT HIGH-GRADE GLIOMA
Johnson K, Tien A, Jiang J, McNamara J, Chang Y, Montgomery C, DeSantis A, Elena L, Fujita Y, Kim S, Tovmasyan A, Li J, Mehta S, Verhaak R, Sanai N. CTNI-23. SINGLE CELL TRANSCRIPTOMICS, PHARMACOKINETICS, AND PHARMACODYNAMICS OF COMBINED CDK4/6 AND MTOR INHIBITION IN A PHASE 0 TRIAL OF RECURRENT HIGH-GRADE GLIOMA. Neuro-Oncology 2023, 25: v78-v79. PMCID: PMC10639373, DOI: 10.1093/neuonc/noad179.0305.Peer-Reviewed Original ResearchHigh-grade gliomasRecurrent high-grade gliomaPhase 0 trialsStandard therapyPharmacodynamic effectsSurgical specimensMTOR inhibitionAdult high-grade gliomasCDKN2A/B deletionsDose-escalation cohortsIDH wild-type tumorsPharmacokinetics/pharmacodynamicsUnbound drug concentrationsGlioma cell linesRibociclib treatmentCell cycle inhibitionPIK3CA mutationsPreoperative MRIGlioma patientsRibociclibEverolimus concentrationsUnbound concentrationsPatientsSurgical tissuesB deletion
2019
GENE-28. LONGITUDINAL MOLECULAR TRAJECTORIES OF DIFFUSE GLIOMA IN ADULTS
Barthel F, Johnson K, Varn F, Moskalik A, Tanner G, Kocakavuk E, Anderson K, Abiola O, Consortium G, Huse J, DeGroot J, Stead L, Verhaak R. GENE-28. LONGITUDINAL MOLECULAR TRAJECTORIES OF DIFFUSE GLIOMA IN ADULTS. Neuro-Oncology 2019, 21: vi103-vi103. PMCID: PMC6847692, DOI: 10.1093/neuonc/noz175.430.Peer-Reviewed Original ResearchAdult patientsOverall survivalDisease recurrencePoor outcomeCurrent therapiesInitial diseaseTreatment optionsTherapy resistanceNeoantigen profilesTherapeutic interventionsPatientsPathway alterationsTumor progressionGlioma Longitudinal Analysis ConsortiumTargeted inhibitorsCancer typesGlioma developmentGliomasDiffuse gliomasGlioma subtypesTime pointsUnderstanding of mechanismsRecurrenceGlioma datasetsHypermutator phenotype