2023
Mammalian SWI/SNF chromatin remodeling complexes promote tyrosine kinase inhibitor resistance in EGFR-mutant lung cancer
de Miguel F, Gentile C, Feng W, Silva S, Sankar A, Exposito F, Cai W, Melnick M, Robles-Oteiza C, Hinkley M, Tsai J, Hartley A, Wei J, Wurtz A, Li F, Toki M, Rimm D, Homer R, Wilen C, Xiao A, Qi J, Yan Q, Nguyen D, Jänne P, Kadoch C, Politi K. Mammalian SWI/SNF chromatin remodeling complexes promote tyrosine kinase inhibitor resistance in EGFR-mutant lung cancer. Cancer Cell 2023, 41: 1516-1534.e9. PMID: 37541244, PMCID: PMC10957226, DOI: 10.1016/j.ccell.2023.07.005.Peer-Reviewed Original ResearchConceptsMammalian SWI/SNF chromatinSWI/SNF chromatinMSWI/SNF complexesGenome-wide localizationGene regulatory signaturesNon-genetic mechanismsEpithelial cell differentiationEGFR-mutant cellsChromatin accessibilitySNF complexCellular programsRegulatory signaturesTKI-resistant lung cancerGene targetsKinase inhibitor resistanceCell differentiationMesenchymal transitionTKI resistancePharmacologic disruptionTyrosine kinase inhibitor resistanceCell proliferationChromatinInhibitor resistanceEGFR-mutant lungKinase inhibitors
2021
Spatial Analysis and Clinical Significance of HLA Class-I and Class-II Subunit Expression in Non–Small Cell Lung Cancer
Datar IJ, Hauc SC, Desai S, Gianino N, Henick B, Liu Y, Syrigos K, Rimm DL, Kavathas P, Ferrone S, Schalper KA. Spatial Analysis and Clinical Significance of HLA Class-I and Class-II Subunit Expression in Non–Small Cell Lung Cancer. Clinical Cancer Research 2021, 27: 2837-2847. PMID: 33602682, PMCID: PMC8734284, DOI: 10.1158/1078-0432.ccr-20-3655.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerNK cell infiltrationReduced T cellCell lung cancerHLA class IIT cellsLung cancerHLA classClinical significanceSubunit expressionHLA class II downregulationΒ2MClass IIHLA genesHuman leukocyte antigen classShorter overall survivalTumor microenvironment compositionClass II β chainImmune contextureOverall survivalLung malignancyNatural killerPatient survivalCell infiltrationClinicopathologic variables
2020
Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images
Noorbakhsh J, Farahmand S, Foroughi pour A, Namburi S, Caruana D, Rimm D, Soltanieh-ha M, Zarringhalam K, Chuang JH. Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images. Nature Communications 2020, 11: 6367. PMID: 33311458, PMCID: PMC7733499, DOI: 10.1038/s41467-020-20030-5.Peer-Reviewed Original ResearchConceptsConvolutional neural networkWhole slide imagesPower of CNNsNormal convolutional neural networkImage data miningColon cancer imagesData miningCNN accuracyCancer imagesNeural networkHistopathological imagesManual inspectionSlide imagesData typesClassifier comparisonSignificant accuracyHistological imagesImage analysisSpatial similarityImagesClassifier pairsClassificationMutation classificationAccuracyMining
2019
Performance Comparison of Different Analytic Methods in Proficiency Testing for Mutations in the BRAF, EGFR, and KRAS Genes: A Study of the College of American Pathologists Molecular Oncology Committee
Moncur JT, Bartley AN, Bridge JA, Kamel-Reid S, Lazar AJ, Lindeman NI, Long TA, Merker JD, Rai AJ, Rimm DL, Rothberg PG, Vasalos P, Kim AS. Performance Comparison of Different Analytic Methods in Proficiency Testing for Mutations in the BRAF, EGFR, and KRAS Genes: A Study of the College of American Pathologists Molecular Oncology Committee. Archives Of Pathology & Laboratory Medicine 2019, 143: 1203-1211. PMID: 30969158, DOI: 10.5858/arpa.2018-0396-cp.Peer-Reviewed Original Research
2018
Immune Marker Profiling and Programmed Death Ligand 1 Expression Across NSCLC Mutations
Toki MI, Mani N, Smithy JW, Liu Y, Altan M, Wasserman B, Tuktamyshov R, Schalper K, Syrigos KN, Rimm DL. Immune Marker Profiling and Programmed Death Ligand 1 Expression Across NSCLC Mutations. Journal Of Thoracic Oncology 2018, 13: 1884-1896. PMID: 30267840, PMCID: PMC6251746, DOI: 10.1016/j.jtho.2018.09.012.Peer-Reviewed Original ResearchConceptsPD-L1 expressionPD-L1TIL activationHigh PD-L1 levelsDeath ligand 1 (PD-L1) expressionActivation statusKRAS wild-type tumorsKRAS mutantEGFR mutantsHigh PD-L1Multiplexed quantitative immunofluorescenceUnique immune profilePD-L1 levelsLigand 1 expressionDeath-1/EGFR-mutant tumorsImmunotherapy response ratesKRAS mutant tumorsWild-type tumorsHigher CD4NSCLC patientsImmune profileClinical efficacyKRAS WTLymphocyte populationsA dormant TIL phenotype defines non-small cell lung carcinomas sensitive to immune checkpoint blockers
Gettinger SN, Choi J, Mani N, Sanmamed MF, Datar I, Sowell R, Du VY, Kaftan E, Goldberg S, Dong W, Zelterman D, Politi K, Kavathas P, Kaech S, Yu X, Zhao H, Schlessinger J, Lifton R, Rimm DL, Chen L, Herbst RS, Schalper KA. A dormant TIL phenotype defines non-small cell lung carcinomas sensitive to immune checkpoint blockers. Nature Communications 2018, 9: 3196. PMID: 30097571, PMCID: PMC6086912, DOI: 10.1038/s41467-018-05032-8.Peer-Reviewed Original ResearchMeSH KeywordsAmino Acid SequenceAnimalsAntibodies, BlockingCarcinogenesisCarcinoma, Non-Small-Cell LungCell ProliferationCytotoxicity, ImmunologicHistocompatibility Antigens Class IHumansLung NeoplasmsLymphocyte ActivationLymphocytes, Tumor-InfiltratingMaleMice, Inbred NODMice, SCIDMutant ProteinsMutationPeptidesPhenotypeProgrammed Cell Death 1 ReceptorReproducibility of ResultsSurvival AnalysisTobaccoConceptsImmune checkpoint blockersCheckpoint blockersQuantitative immunofluorescenceNon-small cell lung carcinoma patientsCell lung carcinoma patientsNon-small cell lung carcinomaPatient-derived xenograft modelsIntratumoral T cellsMultiplexed quantitative immunofluorescencePD-1 blockadeLevels of CD3Lung carcinoma patientsCell lung carcinomaT cell proliferationPre-treatment samplesTIL phenotypeSurvival benefitCarcinoma patientsEffector capacityLung carcinomaT cellsWhole-exome DNA sequencingXenograft modelFavorable responseBlockersExceptional Response to Pembrolizumab in a Metastatic, Chemotherapy/Radiation-Resistant Ovarian Cancer Patient Harboring a PD-L1-Genetic Rearrangement
Bellone S, Buza N, Choi J, Zammataro L, Gay L, Elvin J, Rimm DL, Liu Y, Ratner E, Schwartz PE, Santin AD. Exceptional Response to Pembrolizumab in a Metastatic, Chemotherapy/Radiation-Resistant Ovarian Cancer Patient Harboring a PD-L1-Genetic Rearrangement. Clinical Cancer Research 2018, 24: 3282-3291. PMID: 29351920, PMCID: PMC6050068, DOI: 10.1158/1078-0432.ccr-17-1805.Peer-Reviewed Original ResearchMeSH KeywordsAged, 80 and overAntibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalB7-H1 AntigenBiomarkers, TumorBiopsyComputational BiologyDrug Resistance, NeoplasmExome SequencingFemaleGene RearrangementHLA AntigensHumansMolecular Targeted TherapyMutationOvarian NeoplasmsPositron Emission Tomography Computed TomographyProgrammed Cell Death 1 ReceptorReceptors, Cell SurfaceRetreatmentT-LymphocytesTreatment OutcomeConceptsImmune checkpoint inhibitor pembrolizumabCheckpoint inhibitor pembrolizumabComplete clinical responseClinical responsePD-L1Ovarian carcinomaAberrant PD-L1 expressionPD-L1 surface expressionAnti-PD1 inhibitorsPD-L1 expressionRemarkable clinical responsesHigh-grade ovarian carcinomaStandard treatment modalityAlternative therapeutic optionClear cell featuresNovel treatment optionsSignificant side effectsT-cell lymphocytesWhole exome sequencing techniqueClin Cancer ResMetastatic human tumorsRecurrent diseaseComplete responseHeavy infiltrationTherapeutic options
2017
Worldwide Frequency of Commonly Detected EGFR Mutations
Graham RP, Treece AL, Lindeman NI, Vasalos P, Shan M, Jennings LJ, Rimm DL. Worldwide Frequency of Commonly Detected EGFR Mutations. Archives Of Pathology & Laboratory Medicine 2017, 142: 163-167. PMID: 29106293, DOI: 10.5858/arpa.2016-0579-cp.Peer-Reviewed Original ResearchConceptsEGFR mutationsResistance mutationsEpidermal growth factor receptor (EGFR) mutationsProficiency testing programEGFR inhibitor therapyAmerican Pathologists Proficiency Testing ProgramCommon resistance mutationsT790M mutationClinical laboratoriesCalendar year 2013Mutation frequencyInhibitor therapyCommon mutation sitesLung cancerPulmonary adenocarcinomaL858R mutationReceptor mutationsFrequency of mutationsActivating mutationsEGFR inhibitorsM mutationAsian femalesExon 18Exon 20Ethnic differencesPathway level alterations rather than mutations in single genes predict response to HER2-targeted therapies in the neo-ALTTO trial
Shi W, Jiang T, Nuciforo P, Hatzis C, Holmes E, Harbeck N, Sotiriou C, Peña L, Loi S, Rosa DD, Chia S, Wardley A, Ueno T, Rossari J, Eidtmann H, Armour A, Piccart-Gebhart M, Rimm DL, Baselga J, Pusztai L. Pathway level alterations rather than mutations in single genes predict response to HER2-targeted therapies in the neo-ALTTO trial. Annals Of Oncology 2017, 28: 128-135. PMID: 28177460, PMCID: PMC5834036, DOI: 10.1093/annonc/mdw434.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic Combined Chemotherapy ProtocolsBiopsy, Fine-NeedleBreast NeoplasmsClass I Phosphatidylinositol 3-KinasesDNA, NeoplasmExome SequencingFemaleHumansLapatinibMolecular Targeted TherapyMutationProportional Hazards ModelsProtein Kinase InhibitorsQuinazolinesReceptor, ErbB-2RhoA GTP-Binding ProteinTrastuzumabConceptsPathologic complete responseWhole-exome sequencing and immune profiling of early-stage lung adenocarcinoma with fully annotated clinical follow-up
Kadara H, Choi M, Zhang J, Parra ER, Rodriguez-Canales J, Gaffney SG, Zhao Z, Behrens C, Fujimoto J, Chow C, Yoo Y, Kalhor N, Moran C, Rimm D, Swisher S, Gibbons DL, Heymach J, Kaftan E, Townsend JP, Lynch TJ, Schlessinger J, Lee J, Lifton RP, Wistuba II, Herbst RS. Whole-exome sequencing and immune profiling of early-stage lung adenocarcinoma with fully annotated clinical follow-up. Annals Of Oncology 2017, 28: 75-82. PMID: 27687306, PMCID: PMC5982809, DOI: 10.1093/annonc/mdw436.Peer-Reviewed Original ResearchConceptsRecurrence-free survivalPoor recurrence-free survivalWhole-exome sequencingEarly-stage lung adenocarcinomaMutant lung adenocarcinomaLung adenocarcinomaImmune markersClinical outcomesExact testNatural killer cell infiltrationProportional hazards regression modelsGranzyme B levelsImmune marker analysisImmune profiling analysisPD-L1 expressionImmune-based therapiesTumoral PD-L1Hazards regression modelsKRAS mutant tumorsNormal lung tissuesMajority of deathsFisher's exact testHigh mutation burdenAnalysis of immunophenotypeRelevant molecular markersMutation profiles in early-stage lung squamous cell carcinoma with clinical follow-up and correlation with markers of immune function
Choi M, Kadara H, Zhang J, Parra ER, Rodriguez-Canales J, Gaffney SG, Zhao Z, Behrens C, Fujimoto J, Chow C, Kim K, Kalhor N, Moran C, Rimm D, Swisher S, Gibbons DL, Heymach J, Kaftan E, Townsend JP, Lynch TJ, Schlessinger J, Lee J, Lifton RP, Herbst RS, Wistuba II. Mutation profiles in early-stage lung squamous cell carcinoma with clinical follow-up and correlation with markers of immune function. Annals Of Oncology 2017, 28: 83-89. PMID: 28177435, PMCID: PMC6246501, DOI: 10.1093/annonc/mdw437.Peer-Reviewed Original ResearchConceptsLung squamous cell carcinomaEarly stage lung squamous cell carcinomaNon-small cell lung cancerSquamous cell carcinomaWhole-exome sequencingImmune markersClinical outcomesCell carcinomaPIK3CA mutationsExact testPoor recurrence-free survivalProportional hazards regression modelsTumoral PD-L1 expressionPD-L1 expressionRecurrence-free survivalCell lung cancerComprehensive immune profilingTP53 mutant tumorsHazards regression modelsNormal lung tissuesFisher's exact testLUSC cohortAdjuvant therapyImmune profilingPoor prognosis
2016
Non-malignant respiratory epithelial cells preferentially proliferate from resected non-small cell lung cancer specimens cultured under conditionally reprogrammed conditions
Gao B, Huang C, Kernstine K, Pelekanou V, Kluger Y, Jiang T, Peters-Hall JR, Coquelin M, Girard L, Zhang W, Huffman K, Oliver D, Kinose F, Haura E, Teer JK, Rix U, Le AT, Aisner DL, Varella-Garcia M, Doebele RC, Covington KR, Hampton OA, Doddapaneni HV, Jayaseelan JC, Hu J, Wheeler DA, Shay JW, Rimm DL, Gazdar A, Minna JD. Non-malignant respiratory epithelial cells preferentially proliferate from resected non-small cell lung cancer specimens cultured under conditionally reprogrammed conditions. Oncotarget 2016, 5: 11114-11126. PMID: 28052041, PMCID: PMC5355251, DOI: 10.18632/oncotarget.14366.Peer-Reviewed Original ResearchMeSH KeywordsA549 CellsAdultAgedAged, 80 and overBase SequenceCarcinoma, Non-Small-Cell LungCell Line, TumorCell ProliferationCells, CulturedCoculture TechniquesDNA Copy Number VariationsDNA Mutational AnalysisEpithelial CellsFemaleGene Expression ProfilingGenetic Predisposition to DiseaseHumansLung NeoplasmsMaleMiddle AgedMutationRespiratory MucosaTumor Cells, CulturedConceptsNon-small cell lung cancerRespiratory epithelial cellsNon-malignant lungCell lung cancerCRC culturesLung cancerEpithelial cellsResected non-small cell lung cancerPrimary lung cancerNon-malignant samplesLung epithelial cellsRho-kinase inhibitorNon-malignant cellsPrimary NSCLCPrimary tumorDiploid patternOriginal tumorTumor specimensTumor tissueTumorsKinase inhibitorsCancerCancer cellsMRNA expression profilesSmall subpopulationEGFR-GRB2 Protein Colocalization Is a Prognostic Factor Unrelated to Overall EGFR Expression or EGFR Mutation in Lung Adenocarcinoma
Toki MI, Carvajal-Hausdorf DE, Altan M, McLaughlin J, Henick B, Schalper KA, Syrigos KN, Rimm DL. EGFR-GRB2 Protein Colocalization Is a Prognostic Factor Unrelated to Overall EGFR Expression or EGFR Mutation in Lung Adenocarcinoma. Journal Of Thoracic Oncology 2016, 11: 1901-1911. PMID: 27449805, PMCID: PMC5075503, DOI: 10.1016/j.jtho.2016.06.025.Peer-Reviewed Original ResearchConceptsEGFR pathway activationSeries of patientsLung adenocarcinomaMutation statusEGFR expressionPathway activationProximity ligation assayKRAS wild-type tumorsEGFR-mutant patientsKRAS-mutant casesCohort of patientsWild-type tumorsInteraction of EGFREGFR expression levelsEGFR protein expressionMAPK/ERK pathwayGrowth factor receptorActive EGFRPrognostic factorsDifferent mutation statusPatient groupPrognostic valueLonger survivalEGFR mutationsPrognostic markerDual CCNE1/PIK3CA targeting is synergistic in CCNE1-amplified/PIK3CA-mutated uterine serous carcinomas in vitro and in vivo
Cocco E, Lopez S, Black J, Bellone S, Bonazzoli E, Predolini F, Ferrari F, Schwab CL, Menderes G, Zammataro L, Buza N, Hui P, Wong S, Zhao S, Bai Y, Rimm DL, Ratner E, Litkouhi B, Silasi DA, Azodi M, Schwartz PE, Santin AD. Dual CCNE1/PIK3CA targeting is synergistic in CCNE1-amplified/PIK3CA-mutated uterine serous carcinomas in vitro and in vivo. British Journal Of Cancer 2016, 115: 303-311. PMID: 27351214, PMCID: PMC4973158, DOI: 10.1038/bjc.2016.198.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntineoplastic AgentsCell Line, TumorClass I Phosphatidylinositol 3-KinasesCyclin EDNA Copy Number VariationsFemaleGene Knockdown TechniquesHeterograftsHumansIn Situ Hybridization, FluorescenceIn Vitro TechniquesMiceMutationOncogene ProteinsPhosphatidylinositol 3-KinasesRNA, MessengerTissue Array AnalysisUterine NeoplasmsConceptsUterine serous carcinomaSerous carcinomaTumor growthCyclin E1 (CCNE1) gene amplificationRecurrent uterine serous carcinomaPrimary USC cell linesNovel therapeutic optionsSingle-agent treatmentIdeal therapeutic targetUSC cell linesCyclin E1 expressionUSC patientsUSC xenograftsInhibited cell growthCell cycle analysisAggressive variantTherapeutic optionsCCNE1 amplificationEndometrial tumorsCYC065Therapeutic targetClinical optionPIK3CA driver mutationsDriver mutationsXenograftsOncogenic EGFR Represses the TET1 DNA Demethylase to Induce Silencing of Tumor Suppressors in Cancer Cells
Forloni M, Gupta R, Nagarajan A, Sun LS, Dong Y, Pirazzoli V, Toki M, Wurtz A, Melnick MA, Kobayashi S, Homer RJ, Rimm DL, Gettinger SJ, Politi K, Dogra SK, Wajapeyee N. Oncogenic EGFR Represses the TET1 DNA Demethylase to Induce Silencing of Tumor Suppressors in Cancer Cells. Cell Reports 2016, 16: 457-471. PMID: 27346347, PMCID: PMC4945411, DOI: 10.1016/j.celrep.2016.05.087.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAdenocarcinoma of LungAntineoplastic AgentsBrain NeoplasmsCCAAT-Enhancer-Binding ProteinsCell Line, TumorCpG IslandsDNA MethylationDrug Screening Assays, AntitumorErbB ReceptorsGene Expression Regulation, NeoplasticGene SilencingGlioblastomaHumansLung NeoplasmsMAP Kinase Signaling SystemMixed Function OxygenasesMutationOncogenesProtein Kinase InhibitorsProto-Oncogene ProteinsTranscription, GeneticTumor Suppressor ProteinsUp-RegulationConceptsOncogenic epidermal growth factor receptorMethylation-mediated transcriptional silencingEpidermal growth factor receptorTumor suppressorTranscriptional silencingActive DNA demethylationCancer cellsFamily member 1TET1 knockdownDNA demethylaseDNA demethylationTranscription factorsGrowth factor receptorEctopic expressionCytoplasmic localizationGlioblastoma tumor growthLung cancer cellsTET1 expressionFunctional roleSuppressorFactor receptorMember 1TET1SilencingLung cancer samplesEarly and multiple origins of metastatic lineages within primary tumors
Zhao ZM, Zhao B, Bai Y, Iamarino A, Gaffney SG, Schlessinger J, Lifton RP, Rimm DL, Townsend JP. Early and multiple origins of metastatic lineages within primary tumors. Proceedings Of The National Academy Of Sciences Of The United States Of America 2016, 113: 2140-2145. PMID: 26858460, PMCID: PMC4776530, DOI: 10.1073/pnas.1525677113.Peer-Reviewed Original ResearchConceptsMetastatic lineagesGenetic changesEarly genetic divergenceMolecular evolutionary modelsSingle genetic changeDivergent lineagesTumor phylogeneticsDivergence timesAncestral stateGenetic divergenceCancer lineagesPhylogenetic analysisEvolutionary processesLineagesCancer evolutionMultiple originsDriver genesCancer biologyCancer progressionSomatic mutationsTumor developmentEvolutionary modelsDriver mutationsChronogramMutationsCopy Number Changes Are Associated with Response to Treatment with Carboplatin, Paclitaxel, and Sorafenib in Melanoma
Wilson MA, Zhao F, Khare S, Roszik J, Woodman SE, D'Andrea K, Wubbenhorst B, Rimm DL, Kirkwood JM, Kluger HM, Schuchter LM, Lee SJ, Flaherty KT, Nathanson KL. Copy Number Changes Are Associated with Response to Treatment with Carboplatin, Paclitaxel, and Sorafenib in Melanoma. Clinical Cancer Research 2016, 22: 374-382. PMID: 26307133, PMCID: PMC4821426, DOI: 10.1158/1078-0432.ccr-15-1162.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic Combined Chemotherapy ProtocolsCarboplatinDisease-Free SurvivalDNA Copy Number VariationsDNA Mutational AnalysisDouble-Blind MethodGenes, rasHumansMelanomaMutationNeoplasm StagingNiacinamidePaclitaxelPhenylurea CompoundsProto-Oncogene Proteins B-rafProto-Oncogene Proteins c-metSorafenibTreatment OutcomeConceptsProgression-free survivalGene copy gainOverall survivalImproved progression-free survivalCopy gainImproved overall survivalGenomic alterationsCancer Genome Atlas (TCGA) datasetImproved treatment responseClinical outcomesMET amplificationV600KCCND1 amplificationTreatment responseMelanoma pathogenesisV600E mutationCurrent FDAPretreatment samplesBRAF geneTumor samplesPatientsSorafenibTherapyTumorsAtlas dataset
2015
Characterization of the mutational landscape of anaplastic thyroid cancer via whole-exome sequencing
Kunstman JW, Juhlin CC, Goh G, Brown TC, Stenman A, Healy JM, Rubinstein JC, Choi M, Kiss N, Nelson-Williams C, Mane S, Rimm DL, Prasad ML, Höög A, Zedenius J, Larsson C, Korah R, Lifton RP, Carling T. Characterization of the mutational landscape of anaplastic thyroid cancer via whole-exome sequencing. Human Molecular Genetics 2015, 24: 2318-2329. PMID: 25576899, PMCID: PMC4380073, DOI: 10.1093/hmg/ddu749.Peer-Reviewed Original Research
2014
Whole-Exome Sequencing Characterizes the Landscape of Somatic Mutations and Copy Number Alterations in Adrenocortical Carcinoma
Juhlin CC, Goh G, Healy JM, Fonseca AL, Scholl UI, Stenman A, Kunstman JW, Brown TC, Overton JD, Mane SM, Nelson-Williams C, Bäckdahl M, Suttorp AC, Haase M, Choi M, Schlessinger J, Rimm DL, Höög A, Prasad ML, Korah R, Larsson C, Lifton RP, Carling T. Whole-Exome Sequencing Characterizes the Landscape of Somatic Mutations and Copy Number Alterations in Adrenocortical Carcinoma. The Journal Of Clinical Endocrinology & Metabolism 2014, 100: e493-e502. PMID: 25490274, PMCID: PMC5393505, DOI: 10.1210/jc.2014-3282.Peer-Reviewed Original ResearchConceptsAdrenocortical carcinomaSomatic mutationsCopy number alterationsNumber alterationsNonsynonymous somatic mutationsWnt pathway dysregulationHomozygous deletionMajority of casesPotential disease-causing mutationsWhole-exome sequencingUnderlying somatic mutationsLethal malignancyPathway dysregulationTumorsExome sequencingFocal CNAsDisease-causing mutationsCarcinomaTERT locusZNRF3Recurrent CNAsAlterationsNormal samplesTP53Unknown roleCorrelation of Somatic Mutations and Clinical Outcome in Melanoma Patients Treated with Carboplatin, Paclitaxel, and Sorafenib
Wilson MA, Zhao F, Letrero R, D'Andrea K, Rimm DL, Kirkwood JM, Kluger HM, Lee SJ, Schuchter LM, Flaherty KT, Nathanson KL. Correlation of Somatic Mutations and Clinical Outcome in Melanoma Patients Treated with Carboplatin, Paclitaxel, and Sorafenib. Clinical Cancer Research 2014, 20: 3328-3337. PMID: 24714776, PMCID: PMC4058354, DOI: 10.1158/1078-0432.ccr-14-0093.Peer-Reviewed Original ResearchMeSH KeywordsAdultAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorCarboplatinDouble-Blind MethodFemaleFollow-Up StudiesGenotypeGTP PhosphohydrolasesHumansMaleMelanomaMembrane ProteinsMiddle AgedMutationNeoplasm StagingNiacinamidePaclitaxelPhenylurea CompoundsPrognosisProto-Oncogene Proteins B-rafSkin NeoplasmsSorafenibSurvival RateConceptsProgression-free survivalNRAS-mutant melanomaPlatelet-derived growth factor receptorPerformance statusClinical outcomesNRAS mutationsCox proportional hazards modelVEGF receptorsSomatic mutationsWorse performance statusGood performance statusImproved clinical responseKaplan-Meier methodClinical trial populationsPretreatment tumor samplesSite of diseaseProportional hazards modelEffect of sorafenibBRAF-mutant melanomaFisher's exact testGrowth factor receptorClinical responseOverall survivalClinicopathologic featuresMelanoma patients