2023
Spatial characterization and quantification of CD40 expression across cancer types
Bates K, Vathiotis I, MacNeil T, Ahmed F, Aung T, Katlinskaya Y, Bhattacharya S, Psyrri A, Yea S, Parkes A, Sadraei N, Roychoudhury S, Rimm D, Gavrielatou N. Spatial characterization and quantification of CD40 expression across cancer types. BMC Cancer 2023, 23: 220. PMID: 36894898, PMCID: PMC9996913, DOI: 10.1186/s12885-023-10650-7.Peer-Reviewed Original ResearchConceptsCD40 expressionSolid tumorsTumor cellsQuantitative immunofluorescencePatient cohortPancreatic cancerCancer typesExpression of CD40Large patient cohortOvarian cancer populationTissue microarray formatDifferent solid tumorsInnate immune responseTNF receptor family membersAvailable patient cohortNSCLC populationOverall survivalPrognostic impactReceptor family membersCancer populationAdenocarcinoma populationImmune cellsOvarian cancerPancreatic adenocarcinomaPositivity rate
2017
Effect of neoadjuvant chemotherapy on tumor-infiltrating lymphocytes and PD-L1 expression in breast cancer and its clinical significance
Pelekanou V, Carvajal-Hausdorf DE, Altan M, Wasserman B, Carvajal-Hausdorf C, Wimberly H, Brown J, Lannin D, Pusztai L, Rimm DL. Effect of neoadjuvant chemotherapy on tumor-infiltrating lymphocytes and PD-L1 expression in breast cancer and its clinical significance. Breast Cancer Research 2017, 19: 91. PMID: 28784153, PMCID: PMC5547502, DOI: 10.1186/s13058-017-0884-8.Peer-Reviewed Original ResearchConceptsStromal tumor-infiltrating lymphocytesPD-L1 expressionTumor-infiltrating lymphocytesRecurrence-free survivalNeoadjuvant chemotherapyResidual cancer tissueTIL countBreast cancerCancer tissuesDeath ligand 1 (PD-L1) protein expressionNode-positive breast cancerImproved recurrence-free survivalPD-L1 protein expressionHigher TIL countsPD-L1 statusProtein expressionBreast cancer patientsBreast cancer tissuesPost-treatment samplesPrechemotherapy samplesTIL infiltrationResidual cancerImmune markersResidual diseasePatient cohortCalcium Sensor, NCS-1, Promotes Tumor Aggressiveness and Predicts Patient Survival
Moore LM, England A, Ehrlich BE, Rimm DL. Calcium Sensor, NCS-1, Promotes Tumor Aggressiveness and Predicts Patient Survival. Molecular Cancer Research 2017, 15: 942-952. PMID: 28275088, PMCID: PMC5500411, DOI: 10.1158/1541-7786.mcr-16-0408.Peer-Reviewed Original ResearchConceptsBreast cancer cellsNCS-1Breast cancer patient cohortsNCS-1 expressionLymph node statusCancer cellsShorter survival rateIndependent breast cancer cohortsCancer patient cohortsBreast cancer cohortMB-231 breast cancer cellsPaclitaxel-induced cell deathAggressive tumor phenotypeNeuronal model systemClinical outcomesClinicopathologic featuresNeuronal calcium sensor-1Node statusPatient cohortProgesterone receptorWorse outcomesBreast cancerCalcium-binding proteinsCancer cohortEstrogen receptor
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 approach
2010
Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models
Parisi F, González A, Nadler Y, Camp RL, Rimm DL, Kluger HM, Kluger Y. Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models. Breast Cancer Research 2010, 12: r66. PMID: 20809974, PMCID: PMC3096952, DOI: 10.1186/bcr2633.Peer-Reviewed Original ResearchConceptsNottingham Prognostic IndexClinico-pathological variablesPrognostic indexCox modelPrognostic modelMultivariate Cox regression modelEarly-stage breast cancerBreast cancer patient cohortsAdjuvant chemotherapy decisionsMultivariate Cox modelStage breast cancerCox regression modelCancer patient cohortsTime-dependent areaBreast cancer prognostic modelsCancer prognostic modelsNPI groupOncotype DXPatient cohortChemotherapy decisionsPrognostic markerBackward selection procedureBreast cancerQuantitative immunofluorescence methodImmunofluorescence method
2004
Automated Quantitative Analysis of Tissue Microarrays Reveals an Association between High Bcl-2 Expression and Improved Outcome in Melanoma
DiVito KA, Berger AJ, Camp RL, Dolled-Filhart M, Rimm DL, Kluger HM. Automated Quantitative Analysis of Tissue Microarrays Reveals an Association between High Bcl-2 Expression and Improved Outcome in Melanoma. Cancer Research 2004, 64: 8773-8777. PMID: 15574790, DOI: 10.1158/0008-5472.can-04-1387.Peer-Reviewed Original ResearchConceptsBcl-2 expressionHigh Bcl-2 expressionTissue microarrayMetastatic specimensResponse rateSmall cohortProgression-free survivalImproved response ratesLarge patient cohortMelanoma patientsClark levelEntire cohortBreslow depthClinical variablesPatient cohortMetastatic melanomaContinuous index scoreBetter outcomesIndex scoreMelanoma specimensCohortMelanomaBcl-2PatientsOutcomes