2019
Recurrence 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/
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 developmentIndividualized 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
A 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
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