2022
SYK and ZAP70 kinases in autoimmunity and lymphoid malignancies
Leveille E, Chan LN, Mirza AS, Kume K, Müschen M. SYK and ZAP70 kinases in autoimmunity and lymphoid malignancies. Cellular Signalling 2022, 94: 110331. PMID: 35398488, DOI: 10.1016/j.cellsig.2022.110331.Peer-Reviewed Original ResearchConceptsChronic lymphocytic leukemiaB-cell malignanciesT cell receptorB cell receptorB-cell chronic lymphocytic leukemiaPathological B-cellsPoor clinical outcomeAcute lymphoblastic leukemiaExpression of SykT lymphocyte developmentClinical outcomesAggressive diseaseActivation of NFATAutoimmune diseasesLymphoblastic leukemiaT lymphocytesLymphocytic leukemiaCell lymphomaLymphoid malignanciesB cellsPI3K-pathwayOncogenic driversMalignancyNegative selectionPremalignant cells
2021
Developmental partitioning of SYK and ZAP70 prevents autoimmunity and cancer
Sadras T, Martin M, Kume K, Robinson ME, Saravanakumar S, Lenz G, Chen Z, Song JY, Siddiqi T, Oksa L, Knapp AM, Cutler J, Cosgun KN, Klemm L, Ecker V, Winchester J, Ghergus D, Soulas-Sprauel P, Kiefer F, Heisterkamp N, Pandey A, Ngo V, Wang L, Jumaa H, Buchner M, Ruland J, Chan WC, Meffre E, Martin T, Müschen M. Developmental partitioning of SYK and ZAP70 prevents autoimmunity and cancer. Molecular Cell 2021, 81: 2094-2111.e9. PMID: 33878293, PMCID: PMC8239336, DOI: 10.1016/j.molcel.2021.03.043.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntigens, CD19AutoimmunityB-LymphocytesCalciumCell DifferentiationCell Transformation, NeoplasticEnzyme ActivationHumansImmune ToleranceLymphoma, B-CellMiceModels, GeneticNeoplasm ProteinsNeoplasmsNFATC Transcription FactorsPhosphatidylinositol 3-KinasesProtein BindingReceptors, Antigen, B-CellSignal TransductionSyk KinaseZAP-70 Protein-Tyrosine KinasePON2 subverts metabolic gatekeeper functions in B cells to promote leukemogenesis
Pan L, Hong C, Chan LN, Xiao G, Malvi P, Robinson ME, Geng H, Reddy ST, Lee J, Khairnar V, Cosgun KN, Xu L, Kume K, Sadras T, Wang S, Wajapeyee N, Müschen M. PON2 subverts metabolic gatekeeper functions in B cells to promote leukemogenesis. Proceedings Of The National Academy Of Sciences Of The United States Of America 2021, 118: e2016553118. PMID: 33531346, PMCID: PMC7896313, DOI: 10.1073/pnas.2016553118.Peer-Reviewed Original ResearchConceptsTransplant recipient miceDNA double-strand breaksNormal B cell developmentDouble-strand breaksB cell developmentGenetic deletionB cellsLymphoid transcription factorsGlucose transporter GLUT1Gatekeeper functionGlucose uptakeRecipient miceTranscription factorsSomatic recombinationSynthetic lethalityB-cell acute lymphoblastic leukemiaCell developmentMetabolic gatekeeperRefractory B-ALLDeficient murineCell acute lymphoblastic leukemiaPoor clinical outcomeCell typesAcute lymphoblastic leukemiaGlucose transport
2020
IFITM3 functions as a PIP3 scaffold to amplify PI3K signalling in B cells
Lee J, Robinson ME, Ma N, Artadji D, Ahmed MA, Xiao G, Sadras T, Deb G, Winchester J, Cosgun KN, Geng H, Chan LN, Kume K, Miettinen TP, Zhang Y, Nix MA, Klemm L, Chen CW, Chen J, Khairnar V, Wiita AP, Thomas-Tikhonenko A, Farzan M, Jung JU, Weinstock DM, Manalis SR, Diamond MS, Vaidehi N, Müschen M. IFITM3 functions as a PIP3 scaffold to amplify PI3K signalling in B cells. Nature 2020, 588: 491-497. PMID: 33149299, PMCID: PMC8087162, DOI: 10.1038/s41586-020-2884-6.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntigens, CD19B-LymphocytesCell Transformation, NeoplasticFemaleGerminal CenterHumansIntegrinsMembrane MicrodomainsMembrane ProteinsMiceMice, Inbred C57BLMice, Inbred NODModels, MolecularPhosphatidylinositol 3-KinasesPhosphatidylinositol PhosphatesPhosphorylationReceptors, Antigen, B-CellRNA-Binding ProteinsSignal TransductionConceptsPI3KCell leukemiaAntiviral effector functionsAntigen-specific antibodiesInterferon-induced transmembrane proteinsIFITM3 functionDevelopment of leukemiaCell surfacePoor outcomeOncogenic PI3KClinical cohortEffector functionsGerminal centersMouse modelB cellsExpression of IFITM3Malignant transformationAccumulation of PIP3PI3K signalsCell receptorNormal numbersLeukemiaDefective expressionEndosomal proteinIFITM3Signalling input from divergent pathways subverts B cell transformation
Chan LN, Murakami MA, Robinson ME, Caeser R, Sadras T, Lee J, Cosgun KN, Kume K, Khairnar V, Xiao G, Ahmed MA, Aghania E, Deb G, Hurtz C, Shojaee S, Hong C, Pölönen P, Nix MA, Chen Z, Chen CW, Chen J, Vogt A, Heinäniemi M, Lohi O, Wiita AP, Izraeli S, Geng H, Weinstock DM, Müschen M. Signalling input from divergent pathways subverts B cell transformation. Nature 2020, 583: 845-851. PMID: 32699415, PMCID: PMC7394729, DOI: 10.1038/s41586-020-2513-4.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsB-LymphocytesCell Line, TumorCell Transformation, NeoplasticEnzyme ActivationExtracellular Signal-Regulated MAP KinasesFemaleHumansLeukemia, B-CellMiceProtein Tyrosine Phosphatase, Non-Receptor Type 6Proto-Oncogene Proteins c-bcl-6Proto-Oncogene Proteins c-mycSignal TransductionSTAT5 Transcription FactorConceptsPre-B cell receptorPrincipal oncogenic driverDivergent pathwaysSignal transduction proteinsPro-B cell stageSingle-cell mutationTranscription factor MYCOncogenic driversDivergent signaling pathwaysSingle oncogenic pathwayCentral oncogenic driverMore mature cellsGenetic reactivationTranscriptional programsB-cell transformationProtein kinasePathway componentsERK activationIndividual mutationsOncogenic STAT5Signaling pathwaysCell transformationCytokine receptorsGenetic lesionsDivergent circuits
2019
RPPAs for Cell Subpopulation Analysis
Kume K, Nishizuka SS. RPPAs for Cell Subpopulation Analysis. Advances In Experimental Medicine And Biology 2019, 1188: 227-237. PMID: 31820391, DOI: 10.1007/978-981-32-9755-5_12.ChaptersConceptsDrug-tolerant persistersStem cell-associated proteinsReverse phase protein arrayTolerant cell linesCell linesPhase protein arrayDifferent cell typesCell-associated proteinsGastric cancer cell linesCell biologyProteomic profilingProteomic profilesTolerant linesCellular heterogeneityClonal populationsCancer biologyPI3KCell typesCancer cell linesProtein arraysStem cellsIndividual subpopulationsProliferative conditionsBiologyProteinRecurrence risk evaluation in T1N1M0/T2N0M0/T3N0M0 gastric cancer with TP53 codon 72 polymorphisms
Ohmori Y, Nomura T, Fukushima N, Takahashi F, Iwaya T, Koeda K, Nishizuka S, Consortium M. Recurrence risk evaluation in T1N1M0/T2N0M0/T3N0M0 gastric cancer with TP53 codon 72 polymorphisms. Journal Of Surgical Oncology 2019, 120: 1154-1161. PMID: 31578743, DOI: 10.1002/jso.25718.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAdultAgedAged, 80 and overCodonFemaleFollow-Up StudiesGastrectomyGenetic Predisposition to DiseaseGenotypeHumansIncidenceJapanMaleMiddle AgedNeoplasm Recurrence, LocalNeoplasm StagingPolymorphism, Single NucleotideRisk AssessmentStomach NeoplasmsSurvival RateTumor Suppressor Protein p53ConceptsRelapse-free survivalTP53 codon 72 polymorphismArg/ArgCodon 72 polymorphismGastric cancerOverall survivalHazard ratioHigh-risk patient groupsPostoperative adjuvant chemotherapyRecurrence risk evaluationArg/ProPro/Pro groupAdjuvant chemotherapyT3N0M0 patientsCurative intentStudy cohortPatient groupPro polymorphismEntire observation periodPolymorphism statusPRO groupPatientsArg/CancerPro/
2017
Colony Lysate Arrays for Proteomic Profiling of Drug-Tolerant Persisters of Cancer Cell
Kume K, Nishizuka SS. Colony Lysate Arrays for Proteomic Profiling of Drug-Tolerant Persisters of Cancer Cell. Analytical Chemistry 2017, 89: 8626-8631. PMID: 28753272, DOI: 10.1021/acs.analchem.7b01215.Peer-Reviewed Original ResearchConceptsDrug-tolerant persistersCancer cellsTranscription factorsProteomic profilingProteomic profilesLevels of proteinIndividual coloniesProtein array systemNumber of assaysSingle cellsProtein levelsCritical mechanismFunctional informationAlternative therapeutic targetsProteinTherapeutic targetFunctional heterogeneityCellsInitiation of relapseProfilingPersistersAgarose gelOct4ASTAT3ColoniesInhibition of PI3K suppresses propagation of drug-tolerant cancer cell subpopulations enriched by 5-fluorouracil
Ishida K, Ito C, Ohmori Y, Kume K, Sato KA, Koizumi Y, Konta A, Iwaya T, Nukatsuka M, Kobunai T, Takechi T, Nishizuka SS. Inhibition of PI3K suppresses propagation of drug-tolerant cancer cell subpopulations enriched by 5-fluorouracil. Scientific Reports 2017, 7: 2262. PMID: 28536445, PMCID: PMC5442158, DOI: 10.1038/s41598-017-02548-9.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntimetabolites, AntineoplasticCell Line, TumorCell ProliferationClass I Phosphatidylinositol 3-KinasesCodonDisease Models, AnimalDose-Response Relationship, DrugDrug Resistance, NeoplasmFluorouracilGenetic VariationHeterograftsHumansMiceNeoplasmsPhenotypePhosphatidylinositol 3-KinasesPhosphoinositide-3 Kinase InhibitorsPhosphorylationProteomeProteomicsRibosomal Protein S6 Kinases, 90-kDaSignal TransductionConceptsOrthotopic xenograftsCancer cell subpopulationsCell subpopulationsGastric cancer cell line MKN45Gastric cancer chemotherapyRibosomal S6 kinase phosphorylationPI3K inhibitorsDisease relapseSequential administrationS6 kinase phosphorylationNude miceTumor propagationCancer chemotherapyK inhibitorsXenograftsPI3KChemotherapyRelapseTolerant subpopulationSubpopulationsKinase phosphorylationAdministrationCellsPhosphorylated phosphatidylinositidesMice
2016
Downregulation of ST6GALNAC1 is associated with esophageal squamous cell carcinoma development
Iwaya T, Sawada G, Amano S, Kume K, Ito C, Endo F, Konosu M, Shioi Y, Akiyama Y, Takahara T, Otsuka K, Nitta H, Koeda K, Mizuno M, Nishizuka S, Sasaki A, Mimori K. Downregulation of ST6GALNAC1 is associated with esophageal squamous cell carcinoma development. International Journal Of Oncology 2016, 50: 441-447. PMID: 28035351, DOI: 10.3892/ijo.2016.3817.Peer-Reviewed Original ResearchMeSH KeywordsAgedCarcinogenesisCarcinoma, Squamous CellChromosomes, Human, Pair 17Down-RegulationEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLoss of HeterozygosityMaleReal-Time Polymerase Chain ReactionSialyltransferasesTranscriptomeConceptsQuantitative real-time reverse transcription PCRSporadic esophageal squamous cell carcinomasResponsible geneRNA sequence analysisClinical ESCC samplesPutative tumor suppressor geneCell linesTumor suppressor geneChromosome 17q25.1Esophageal squamous cell carcinoma (ESCC) developmentReal-time reverse transcription PCREsophageal squamous cell carcinomaMultiple genesCandidate genesExpression patternsChromosome 17q25Reverse transcription-PCRSequence analysisSuppressor geneGenesMethylation analysisCorresponding normal tissuesST6GALNAC1Transcription-PCRESCC developmentα-Amanitin Restrains Cancer Relapse from Drug-Tolerant Cell Subpopulations via TAF15
Kume K, Ikeda M, Miura S, Ito K, Sato KA, Ohmori Y, Endo F, Katagiri H, Ishida K, Ito C, Iwaya T, Nishizuka SS. α-Amanitin Restrains Cancer Relapse from Drug-Tolerant Cell Subpopulations via TAF15. Scientific Reports 2016, 6: 25895. PMID: 27181033, PMCID: PMC4867652, DOI: 10.1038/srep25895.Peer-Reviewed Original ResearchMeSH KeywordsAlpha-AmanitinAnimalsCell Line, TumorCisplatinDown-RegulationDrug ResistanceEnzyme InhibitorsGene Expression Regulation, NeoplasticHCT116 CellsHeLa CellsHT29 CellsHumansMCF-7 CellsMicePeritoneal NeoplasmsProteomicsSecondary PreventionTATA-Binding Protein Associated FactorsTranscription, GeneticXenograft Model Antitumor AssaysConceptsΑ-amanitinRNA polymerase II inhibitorProtein expression patternsTranscriptional machineryRNA processingProteomic characterizationFunctional screeningTranscriptional levelExpression patternsTAF15II inhibitorsCancer cellsSubstantial frequencyDTC formationCancer relapseCell subpopulationsSubpopulationsTranscriptionMouse modelMachineryRNAPresence of drugsStemnessColoniesExpressionIndividualized Mutation Detection in Circulating Tumor DNA for Monitoring Colorectal Tumor Burden Using a Cancer-Associated Gene Sequencing Panel
Sato KA, Hachiya T, Iwaya T, Kume K, Matsuo T, Kawasaki K, Abiko Y, Akasaka R, Matsumoto T, Otsuka K, Nishizuka SS. Individualized Mutation Detection in Circulating Tumor DNA for Monitoring Colorectal Tumor Burden Using a Cancer-Associated Gene Sequencing Panel. PLOS ONE 2016, 11: e0146275. PMID: 26727500, PMCID: PMC4699643, DOI: 10.1371/journal.pone.0146275.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAdultAgedAllelesCell Line, TumorColorectal NeoplasmsDNA Mutational AnalysisDNA PrimersDNA, NeoplasmFemaleGenes, NeoplasmHumansLeukocytes, MononuclearMaleMiddle AgedMultiplex Polymerase Chain ReactionPoint MutationPolymorphism, Single NucleotideSequence Analysis, DNATumor BurdenConceptsPeripheral blood mononuclear cellsTumor burdenColorectal tumorsVariant allele frequencyCurative resectionDroplet digital PCRPlasma DNACancer-associated genesTumor DNATumor burden monitoringUtility of ctDNABlood mononuclear cellsSingle nucleotide variantsGene sequencing panelAllele frequenciesMutation spectrumCancer patientsMononuclear cellsPrimary tumorCtDNA markersClinical utilityHealthy individualsSequencing panelGene point mutationsTumors
2015
Systematic Protein Level Regulation via Degradation Machinery Induced by Genotoxic Drugs
Kume K, Ishida K, Ikeda M, Takemoto K, Shimura T, Young L, Nishizuka SS. Systematic Protein Level Regulation via Degradation Machinery Induced by Genotoxic Drugs. Journal Of Proteome Research 2015, 15: 205-215. PMID: 26625007, DOI: 10.1021/acs.jproteome.5b00759.Peer-Reviewed Original ResearchConceptsDegradation machineryGenotoxic drugsProtein dynamicsProtein-level regulationProtein degradation systemProtein levelsDistinct proteinsApoptosis-related proteinsDegradation systemProtein arraysProteinLevel regulationProteasome inhibitorsMachineryComprehensive insightRegulationMG132Similar dynamicsPairsInhibitorsDynamicsDifferent concentrationsResponseSimilarityLevelsA Distinct Subpopulation of Bone Marrow Mesenchymal Stem Cells, Muse Cells, Directly Commit to the Replacement of Liver Components
Katagiri H, Kushida Y, Nojima M, Kuroda Y, Wakao S, Ishida K, Endo F, Kume K, Takahara T, Nitta H, Tsuda H, Dezawa M, Nishizuka SS. A Distinct Subpopulation of Bone Marrow Mesenchymal Stem Cells, Muse Cells, Directly Commit to the Replacement of Liver Components. American Journal Of Transplantation 2015, 16: 468-483. PMID: 26663569, DOI: 10.1111/ajt.13537.Peer-Reviewed Original ResearchConceptsLiver componentsBone marrow mesenchymal stem cellsMarrow mesenchymal stem cellsLiver regenerationBM-MSCsMuse cellsMesenchymal stem cellsLiving-donor liver transplantationSinusoidal endothelial cellsMultilineage-differentiating stress-enduring (Muse) cellsPartial hepatectomy modelStem cellsGraft liverLiver transplantationPolymerase chain reactionCell involvementImmunodeficient miceKupffer cellsSinusoidal cellsPeriportal areasExtrahepatic originHepatectomy modelSpecific subpopulationsEndothelial cellsProgenitor markers
2014
A Compensatory Role of NF-κB to p53 in Response to 5-FU–Based Chemotherapy for Gastric Cancer Cell Lines
Endo F, Nishizuka SS, Kume K, Ishida K, Katagiri H, Ishida K, Sato K, Iwaya T, Koeda K, Wakabayashi G. A Compensatory Role of NF-κB to p53 in Response to 5-FU–Based Chemotherapy for Gastric Cancer Cell Lines. PLOS ONE 2014, 9: e90155. PMID: 24587255, PMCID: PMC3937424, DOI: 10.1371/journal.pone.0090155.Peer-Reviewed Original ResearchMeSH KeywordsAntimetabolites, AntineoplasticCell Line, TumorCodonDrug Resistance, NeoplasmFluorouracilGene Expression ProfilingGene Expression Regulation, NeoplasticGene Knockdown TechniquesHumansNF-kappa BProtein BindingProtein TransportStomach NeoplasmsTranscription Factor RelATumor Suppressor Protein p53ConceptsGastric cancer cell linesCancer cell linesNF-κBAdjuvant chemotherapyPrediction markersCell linesNF-κB-dependent mannerGastric cancer patientsKnockdown of RelANF-κB bindingArg homozygosityCurative resectionRelapse rateCancer patientsGastric cancerPrediction biomarkersChemotherapyP65 subunitTP53 knockdownChemotherapeutic efficacyProtein levelsCompensatory roleP53Target protein levelsTreatment
2013
Contrasting Expression Patterns of Histone mRNA and microRNA 760 in Patients with Gastric Cancer
Iwaya T, Fukagawa T, Suzuki Y, Takahashi Y, Sawada G, Ishibashi M, Kurashige J, Sudo T, Tanaka F, Shibata K, Endo F, Katagiri H, Ishida K, Kume K, Nishizuka S, Iinuma H, Wakabayashi G, Mori M, Sasako M, Mimori K. Contrasting Expression Patterns of Histone mRNA and microRNA 760 in Patients with Gastric Cancer. Clinical Cancer Research 2013, 19: 6438-6449. PMID: 24097871, DOI: 10.1158/1078-0432.ccr-12-3186.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAgedBiomarkers, TumorBone MarrowCell Line, TumorFemaleGastric MucosaGene Expression Regulation, NeoplasticHistonesHumansKaplan-Meier EstimateLymphatic MetastasisMaleMicroRNAsMiddle AgedMultivariate AnalysisNeoplasm StagingOligonucleotide Array Sequence AnalysisPrognosisProportional Hazards ModelsRNA InterferenceRNA, MessengerSequence Analysis, RNAStomach NeoplasmsTranscriptomeConceptsGastric cancer patientsStage IV patientsStage I patientsCancer patientsBone marrow samplesIV patientsBone marrowMiR-760 expressionPrimary tumor samplesPrimary tumorGastric cancerMiR-760I patientsPeripheral bloodMarrow samplesStage IV gastric cancer patientsAdvanced gastric cancer patientsTumor samplesLuciferase reporter assaysNoncancerous cellsRNA-seq analysisPrognostic markerMicroRNA-760Noncancerous mucosaPatientsEvaluation of chemosensitivity prediction using quantitative dose–response curve classification for highly advanced/relapsed gastric cancer
Matsuo T, Nishizuka SS, Ishida K, Endo F, Katagiri H, Kume K, Ikeda M, Koeda K, Wakabayashi G. Evaluation of chemosensitivity prediction using quantitative dose–response curve classification for highly advanced/relapsed gastric cancer. World Journal Of Surgical Oncology 2013, 11: 11. PMID: 23339659, PMCID: PMC3562164, DOI: 10.1186/1477-7819-11-11.Peer-Reviewed Original ResearchConceptsDose-response curveChemosensitivity testGastric cancerResistant cancer cell populationsStandard chemotherapy regimensPeak plasma concentrationDose-response patternDrug dose-response curvesPrimary chemotherapyChemotherapy regimensRecurrent diseaseStandard chemotherapyResultsA totalChemosensitivity evaluationPlasma concentrationsChemosensitivity patternsChemoresistant tumorsResistant patternChemotherapyDrug resistanceDrug sensitivityCancer cell populationsConclusionsThese resultsCisplatinCell populations
2012
Molecular Marker Identification for Relapse Prediction in 5-FU-Based Adjuvant Chemotherapy in Gastric and Colorectal Cancers
Ishida K, Nishizuka SS, Chiba T, Ikeda M, Kume K, Endo F, Katagiri H, Matsuo T, Noda H, Iwaya T, Yamada N, Fujiwara H, Takahashi M, Itabashi T, Uesugi N, Maesawa C, Tamura G, Sugai T, Otsuka K, Koeda K, Wakabayashi G. Molecular Marker Identification for Relapse Prediction in 5-FU-Based Adjuvant Chemotherapy in Gastric and Colorectal Cancers. PLOS ONE 2012, 7: e43236. PMID: 22905237, PMCID: PMC3419205, DOI: 10.1371/journal.pone.0043236.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAntimetabolites, AntineoplasticBiomarkers, TumorCell Line, TumorChemotherapy, AdjuvantCluster AnalysisColorectal NeoplasmsFluorouracilGene Expression Regulation, NeoplasticHumansImmunohistochemistryMAP Kinase Kinase 4Middle AgedPrognosisRecurrenceRNA, Small InterferingStomach NeoplasmsConceptsAdjuvant chemotherapyNF-κBCancer patientsTissue microarrayProtein expressionColorectal cancer patientsOverall survival rateGastrointestinal tract cancerGastric cancer patientsGastric cancer cell linesCell linesCancer cell linesJNK protein expressionR0 resectionTract cancerColorectal cancerImmunohistochemical examinationClinical significanceSurvival rateRelapse predictionBaseline expressionChemotherapyChemosensitivity markerPatientsGastric