2021
Targeting Pyruvate Kinase M2 Phosphorylation Reverses Aggressive Cancer Phenotypes
Apostolidi M, Vathiotis IA, Muthusamy V, Gaule P, Gassaway BM, Rimm DL, Rinehart J. Targeting Pyruvate Kinase M2 Phosphorylation Reverses Aggressive Cancer Phenotypes. Cancer Research 2021, 81: 4346-4359. PMID: 34185676, PMCID: PMC8373815, DOI: 10.1158/0008-5472.can-20-4190.Peer-Reviewed Original ResearchMeSH KeywordsActive Transport, Cell NucleusAnimalsBiomarkers, TumorCarrier ProteinsCell Line, TumorCollagenCyclic N-OxidesDrug CombinationsGenome, HumanHumansIndolizinesLamininMCF-7 CellsMembrane ProteinsMiceNeoplasm InvasivenessNeoplasm TransplantationNeoplasmsOxidation-ReductionPhenotypePhosphorylationProtein IsoformsProteoglycansProteomicsPyridazinesPyridinium CompoundsPyrrolesPyruvate KinaseThyroid HormonesTriple Negative Breast NeoplasmsConceptsTriple-negative breast cancerPyruvate kinase M2TEPP-46Breast cancerAggressive breast cancer cell phenotypesCharacteristic nuclear staining patternAggressive breast cancer subtypeAggressive breast cancer phenotypeBreast cancer cell phenotypeCDK inhibitor dinaciclibCombination of dinaciclibLack of biomarkersEffective therapeutic approachBreast cancer phenotypeBreast cancer subtypesCancer phenotypePhosphorylation of PKM2Cyclin-dependent kinase (CDK) pathwayMouse xenograft modelAggressive cancer phenotypeNuclear staining patternLower survival rateImpaired redox balancePrognostic valueCancer cell phenotypeSTING enhances cell death through regulation of reactive oxygen species and DNA damage
Hayman TJ, Baro M, MacNeil T, Phoomak C, Aung TN, Cui W, Leach K, Iyer R, Challa S, Sandoval-Schaefer T, Burtness BA, Rimm DL, Contessa JN. STING enhances cell death through regulation of reactive oxygen species and DNA damage. Nature Communications 2021, 12: 2327. PMID: 33875663, PMCID: PMC8055995, DOI: 10.1038/s41467-021-22572-8.Peer-Reviewed Original Research
2019
Quantitative Assessment of CMTM6 in the Tumor Microenvironment and Association with Response to PD-1 Pathway Blockade in Advanced-Stage Non–Small Cell Lung Cancer
Zugazagoitia J, Liu Y, Toki M, McGuire J, Ahmed FS, Henick BS, Gupta R, Gettinger S, Herbst R, Schalper KA, Rimm DL. Quantitative Assessment of CMTM6 in the Tumor Microenvironment and Association with Response to PD-1 Pathway Blockade in Advanced-Stage Non–Small Cell Lung Cancer. Journal Of Thoracic Oncology 2019, 14: 2084-2096. PMID: 31605795, PMCID: PMC6951804, DOI: 10.1016/j.jtho.2019.09.014.Peer-Reviewed Original ResearchConceptsPD-L1CMTM6 expressionPathway blockadeAdvanced stage non-small cell lung cancerNon-small cell lung cancerPD-1 pathway blockadeTumor cellsAbsence of immunotherapyMultiplexed quantitative immunofluorescencePD-L1 coexpressionStromal immune cellsPD-L1 expressionT cell infiltrationLonger overall survivalCell lung cancerIndependent retrospective cohortsKRAS mutational statusExpression of CMTM6MARVEL transmembrane domainNSCLC cohortOverall survivalRetrospective cohortAxis blockadeClinical featuresImmunotherapy outcomesMultiplex quantitative analysis of cancer-associated fibroblasts and immunotherapy outcome in metastatic melanoma
Wong PF, Wei W, Gupta S, Smithy JW, Zelterman D, Kluger HM, Rimm DL. Multiplex quantitative analysis of cancer-associated fibroblasts and immunotherapy outcome in metastatic melanoma. Journal For ImmunoTherapy Of Cancer 2019, 7: 194. PMID: 31337426, PMCID: PMC6651990, DOI: 10.1186/s40425-019-0675-0.Peer-Reviewed Original ResearchConceptsProgression-free survivalBest overall responseSmooth muscle actinOverall survivalCell countQuantitative immunofluorescenceImmune markersImmunotherapy outcomesMelanoma patientsSignificant progression-free survivalAnti-PD-1 therapyAbsence of immunotherapyPretreatment tumor specimensImmune checkpoint blockadeCell death 1Cancer-associated fibroblast (CAF) populationNegative prognostic biomarkerCancer-associated fibroblastsWhole tissue sectionsOverall responseOS associationCAF parametersCheckpoint blockadeImmune dysregulationDeath-1Siglec-15 as an immune suppressor and potential target for normalization cancer immunotherapy
Wang J, Sun J, Liu LN, Flies DB, Nie X, Toki M, Zhang J, Song C, Zarr M, Zhou X, Han X, Archer KA, O’Neill T, Herbst RS, Boto AN, Sanmamed MF, Langermann S, Rimm DL, Chen L. Siglec-15 as an immune suppressor and potential target for normalization cancer immunotherapy. Nature Medicine 2019, 25: 656-666. PMID: 30833750, PMCID: PMC7175920, DOI: 10.1038/s41591-019-0374-x.Peer-Reviewed Original ResearchConceptsNormalization cancer immunotherapyTumor microenvironmentSiglec-15Antibody blockadeCancer immunotherapyImmune suppressorMyeloid cellsAntigen-specific T cell responsesB7-H1/PDTumor-infiltrating myeloid cellsB7-H1 moleculesAnti-tumor immunityT cell responsesPotential targetImmune evasion mechanismsInhibits tumor growthMacrophage colony-stimulating factorColony-stimulating factorB7-H1Evasion mechanismsMouse modelHuman cancer cellsTumor growthCell responsesGenetic ablation
2014
Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error
Shipitsin M, Small C, Choudhury S, Giladi E, Friedlander S, Nardone J, Hussain S, Hurley AD, Ernst C, Huang YE, Chang H, Nifong TP, Rimm DL, Dunyak J, Loda M, Berman DM, Blume-Jensen P. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. British Journal Of Cancer 2014, 111: 1201-1212. PMID: 25032733, PMCID: PMC4453845, DOI: 10.1038/bjc.2014.396.Peer-Reviewed Original ResearchMeSH KeywordsActininAgedAlkyl and Aryl TransferasesArea Under CurveBiomarkers, TumorBiopsy, Fine-NeedleCullin ProteinsDNA-Binding ProteinsFollow-Up StudiesHSP70 Heat-Shock ProteinsHumansImage Processing, Computer-AssistedMaleMembrane ProteinsMiddle AgedMitochondrial ProteinsNeoplasm GradingNeoplasm StagingPhosphorylationProstateProstatic NeoplasmsProteomicsRibosomal Protein S6RNA-Binding Protein FUSROC CurveSelection BiasSmad2 ProteinSmad4 ProteinTissue Array AnalysisVoltage-Dependent Anion Channel 1Y-Box-Binding Protein 1ConceptsProstate cancer aggressivenessCancer aggressivenessLarge patient cohortLow Gleason gradePatient cohortTumor microarrayLethal outcomeProstatectomy samplesGleason gradeSignificant overtreatmentBiopsy interpretationProstatectomy tissuePatient samplesBiopsy testsProteomic biomarkersCancer biomarker discoveryExpert pathologistsMarker signaturesTumor heterogeneityBiomarkersAggressivenessProtein biomarkersBiomarker discoveryQuantitative proteomics approachCorrelation 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
2009
Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features
Creighton CJ, Li X, Landis M, Dixon JM, Neumeister VM, Sjolund A, Rimm DL, Wong H, Rodriguez A, Herschkowitz JI, Fan C, Zhang X, He X, Pavlick A, Gutierrez MC, Renshaw L, Larionov AA, Faratian D, Hilsenbeck SG, Perou CM, Lewis MT, Rosen JM, Chang JC. Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features. Proceedings Of The National Academy Of Sciences Of The United States Of America 2009, 106: 13820-13825. PMID: 19666588, PMCID: PMC2720409, DOI: 10.1073/pnas.0905718106.Peer-Reviewed Original ResearchConceptsBreast cancerConventional treatmentHigh tumor-initiating potentialResidual breast cancerBreast cancer patientsCell surface antigen profileLong-term survivalHuman breast tumorsBreast cancer cellsTumor-initiating cellsTumor-initiating potentialEndocrine therapyGene expression signaturesCancer patientsTumor cell populationClinical significanceMolecular subtypesTherapeutic strategiesMesenchymal markersMetalloproteinase-2Breast tumorsSubpopulation of cellsAntigen profileMesenchymal featuresTumor tissueGOLPH3 modulates mTOR signalling and rapamycin sensitivity in cancer
Scott KL, Kabbarah O, Liang MC, Ivanova E, Anagnostou V, Wu J, Dhakal S, Wu M, Chen S, Feinberg T, Huang J, Saci A, Widlund HR, Fisher DE, Xiao Y, Rimm DL, Protopopov A, Wong KK, Chin L. GOLPH3 modulates mTOR signalling and rapamycin sensitivity in cancer. Nature 2009, 459: 1085-1090. PMID: 19553991, PMCID: PMC2753613, DOI: 10.1038/nature08109.Peer-Reviewed Original ResearchConceptsTarget of rapamycinTrans-Golgi networkHuman cancersGenome-wide copy number analysisCopy number analysisRetromer complexGolgi proteinsHuman cancer cellsRapamycin sensitivityNew oncogeneGOLPH3Integrative analysisPotent oncogeneGenomic profilesBiochemical dataCancer cellsFunction studiesNumber analysisYeastSolid tumor typesCell sizeOncogeneMTORRapamycinMTOR inhibitors
2007
Quantitative Analysis of Breast Cancer Tissue Microarrays Shows High Cox-2 Expression Is Associated with Poor Outcome
Zerkowski MP, Camp RL, Burtness BA, Rimm DL, Chung GG. Quantitative Analysis of Breast Cancer Tissue Microarrays Shows High Cox-2 Expression Is Associated with Poor Outcome. Cancer Investigation 2007, 25: 19-26. PMID: 17364553, DOI: 10.1080/07357900601128825.Peer-Reviewed Original ResearchConceptsCOX-2 expressionCOX-2Tissue microarrayBreast cancerEstrogen receptorPrognostic factorsWorse survivalProgesterone receptorX-tileOptimal cutpointHigh COX-2 expressionBreast cancer tissue microarrayX-tile analysisSignificant prognostic factorsPrimary breast cancerCOX-2 inhibitorsCancer tissue microarrayHER2/neuClinicopathologic factorsNodal statusPoor outcomePoor prognosisTumor sizePredictive biomarkersClinical trials
1995
Receptor protein tyrosine phosphatase PTPmu associates with cadherins and catenins in vivo.
Brady-Kalnay SM, Rimm DL, Tonks NK. Receptor protein tyrosine phosphatase PTPmu associates with cadherins and catenins in vivo. Journal Of Cell Biology 1995, 130: 977-986. PMID: 7642713, PMCID: PMC2199947, DOI: 10.1083/jcb.130.4.977.Peer-Reviewed Original ResearchMeSH KeywordsAlpha CateninAnimalsBeta CateninBinding SitesBrainCadherinsCell LineCytoskeletal ProteinsImmunoblottingImmunohistochemistryIntercellular JunctionsLungMembrane ProteinsMinkMyocardiumPhosphorylationPrecipitin TestsProtein BindingProtein Tyrosine PhosphatasesRatsReceptor-Like Protein Tyrosine Phosphatases, Class 2Receptor-Like Protein Tyrosine Phosphatases, Class 8Receptors, Cell SurfaceTissue DistributionTrans-ActivatorsVanadatesConceptsIntracellular segmentIntracellular domainCellular tyrosine phosphatase activityCadherin/catenin complexDynamic tyrosine phosphorylationImmunoglobulin domainFibronectin type III repeatsTyrosine phosphatase activityTyrosine-phosphorylated formType III repeatsCell-cell contactJuxtamembrane segmentPTP domainPervanadate treatmentMAM domainActin cytoskeletonCatenin complexPTPmuTyrosine phosphorylationExtracellular segmentCadherinEndogenous substratesMink lung cellsPhosphatase activityCatenin