2021
What if the future of HER2‐positive breast cancer patients was written in miRNAs? An exploratory analysis from NeoALTTO study
Pizzamiglio S, Cosentino G, Ciniselli CM, De Cecco L, Cataldo A, Plantamura I, Triulzi T, El‐abed S, Wang Y, Bajji M, Nuciforo P, Huober J, Ellard SL, Rimm DL, Gombos A, Daidone MG, Verderio P, Tagliabue E, Di Cosimo S, Iorio MV. What if the future of HER2‐positive breast cancer patients was written in miRNAs? An exploratory analysis from NeoALTTO study. Cancer Medicine 2021, 11: 332-339. PMID: 34921525, PMCID: PMC8729061, DOI: 10.1002/cam4.4449.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsFemaleHumansMicroRNAsMiddle AgedNeoadjuvant TherapyPrognosisProportional Hazards ModelsReceptor, ErbB-2TrastuzumabTreatment OutcomeTumor BurdenConceptsHER2-positive breast cancer patientsEvent-free survivalBreast cancer patientsNeoadjuvant therapyCancer patientsPathological complete response rateSingle-agent trastuzumabTwo-miRNA signatureComplete response rateDifferential clinical outcomesPredictive miRNA signatureTrastuzumab armBaseline biopsiesClinical outcomesPathological variablesPrognostic valueUnivariate analysisAgent trastuzumabPrognostic signatureResponse ratePatientsTissue miRNAsMiRNA expression profilesMiRNA signatureMultivariate modelBRCA1 Protein Expression Predicts Survival in Glioblastoma Patients from an NRG Oncology RTOG Cohort
Vassilakopoulou M, Won M, Curran WJ, Souhami L, Prados MD, Langer CJ, Rimm DL, Hanna JA, Neumeister VM, Melian E, Diaz AZ, Atkins JN, Komarnicky LT, Schultz CJ, Howard SP, Zhang P, Dicker AP, Knisely JPS. BRCA1 Protein Expression Predicts Survival in Glioblastoma Patients from an NRG Oncology RTOG Cohort. Oncology 2021, 99: 580-588. PMID: 33957633, PMCID: PMC8491475, DOI: 10.1159/000516168.Peer-Reviewed Original ResearchConceptsBRCA1 protein expressionTensin homolog (PTEN) tumor suppressor geneProtein expressionTumor suppressor geneQuantitative protein analysisDNA repairGenetic profiling studiesMolecular markersSuppressor geneProtein analysisProfiling studiesBRCA1 expressionSitu hybridizationExpression levelsTumor formationCommon malignant brain tumorCancer cellsTissue microarrayGlioblastoma tumorsExpressionPre-temozolomide eraGlioblastoma patients
2020
A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
Lu C, Bera K, Wang X, Prasanna P, Xu J, Janowczyk A, Beig N, Yang M, Fu P, Lewis J, Choi H, Schmid RA, Berezowska S, Schalper K, Rimm D, Velcheti V, Madabhushi A. A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study. The Lancet Digital Health 2020, 2: e594-e606. PMID: 33163952, PMCID: PMC7646741, DOI: 10.1016/s2589-7500(20)30225-9.Peer-Reviewed Original ResearchMeSH KeywordsAgedCarcinoma, Non-Small-Cell LungDatabases, FactualFemaleHumansMaleMiddle AgedNeoplasm StagingPrognosisProportional Hazards ModelsRetrospective StudiesSurvival AnalysisConceptsNon-small cell lung carcinomaEarly-stage non-small cell lung carcinomaOverall survivalRetrospective studyEarly-stage non-small cell lung cancerNon-small cell lung cancerMultivariable Cox regression analysisCell differentiation pathwayCox proportional hazards modelLung squamous cell carcinomaEarly-stage LUADOverall survival informationCox regression analysisPrognosis of patientsCell lung cancerRisk stratification modelSquamous cell carcinomaLung cancer pathogenesisIndependent validation cohortCell lung carcinomaProportional hazards modelComputer-extracted featuresAdjuvant therapyDifferentiation pathwayValidation cohort
2019
High-Plex Predictive Marker Discovery for Melanoma Immunotherapy–Treated Patients Using Digital Spatial Profiling
Toki MI, Merritt CR, Wong PF, Smithy JW, Kluger HM, Syrigos KN, Ong GT, Warren SE, Beechem JM, Rimm DL. High-Plex Predictive Marker Discovery for Melanoma Immunotherapy–Treated Patients Using Digital Spatial Profiling. Clinical Cancer Research 2019, 25: 5503-5512. PMID: 31189645, PMCID: PMC6744974, DOI: 10.1158/1078-0432.ccr-19-0104.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic Agents, ImmunologicalBiomarkers, TumorFemaleFluorescent Antibody TechniqueHumansImmunohistochemistryImmunotherapyLymphocytes, Tumor-InfiltratingMaleMelanomaMolecular Diagnostic TechniquesMolecular Targeted TherapyPrognosisProportional Hazards ModelsTissue Array AnalysisTreatment OutcomeConceptsNon-small cell lung cancerProlonged progression-free survivalDigital spatial profilingOverall survivalPD-L1Predictive markerPD-L1 expressionProgression-free survivalProtein expressionCell lung cancerNovel predictive markerCD68-positive cellsStromal CD3Melanoma immunotherapyImmune markersImmune therapyPrognostic valueLung cancerAntibody cocktailTissue microarrayQuantitative fluorescenceOutcome assessmentTumor cellsHigh concordanceMultiple biomarkersSpatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non–Small Cell Lung Cancer
Corredor G, Wang X, Zhou Y, Lu C, Fu P, Syrigos K, Rimm DL, Yang M, Romero E, Schalper KA, Velcheti V, Madabhushi A. Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non–Small Cell Lung Cancer. Clinical Cancer Research 2019, 25: 1526-1534. PMID: 30201760, PMCID: PMC6397708, DOI: 10.1158/1078-0432.ccr-18-2013.Peer-Reviewed Original ResearchMeSH KeywordsAgedCarcinoma, Non-Small-Cell LungFemaleHumansLung NeoplasmsLymphocytes, Tumor-InfiltratingMaleMiddle AgedNeoplasm MetastasisNeoplasm StagingPrognosisProportional Hazards ModelsRecurrence
2017
Pathway 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 markers
2016
Evaluation of PD-L1 Expression and Associated Tumor-Infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma
Vassilakopoulou M, Avgeris M, Velcheti V, Kotoula V, Rampias T, Chatzopoulos K, Perisanidis C, Kontos CK, Giotakis AI, Scorilas A, Rimm D, Sasaki C, Fountzilas G, Psyrri A. Evaluation of PD-L1 Expression and Associated Tumor-Infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma. Clinical Cancer Research 2016, 22: 704-713. PMID: 26408403, DOI: 10.1158/1078-0432.ccr-15-1543.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overB7-H1 AntigenBiomarkers, TumorCarcinoma, Squamous CellFemaleFollow-Up StudiesGene ExpressionHumansImmunohistochemistryKaplan-Meier EstimateLaryngeal NeoplasmsLymphocytes, Tumor-InfiltratingMaleMiddle AgedNeoplasm GradingNeoplasm MetastasisNeoplasm StagingPrognosisProportional Hazards ModelsRetrospective StudiesRisk FactorsRNA, MessengerConceptsLaryngeal squamous cell carcinomaSquamous cell carcinomaPrimary laryngeal squamous cell carcinomaPD-L1 expressionTumor-infiltrating lymphocytesPD-L1 mRNA expressionTIL densityCell carcinomaAssessment of TILsLaryngeal squamous cell cancerStromal tumor-infiltrating lymphocytesSuperior disease-free survivalTumor PD-L1 expressionMRNA expressionPD-L1 protein expressionPD-L1 mRNA levelsHigher TIL densityImmune checkpoint inhibitorsPD-L1 levelsDisease-free survivalT cell infiltrationSquamous cell cancerSecond independent cohortAdjacent tissue specimensFresh-frozen tumors
2015
Characterization of PD-L1 Expression and Associated T-cell Infiltrates in Metastatic Melanoma Samples from Variable Anatomic Sites
Kluger HM, Zito CR, Barr ML, Baine MK, Chiang VL, Sznol M, Rimm DL, Chen L, Jilaveanu LB. Characterization of PD-L1 Expression and Associated T-cell Infiltrates in Metastatic Melanoma Samples from Variable Anatomic Sites. Clinical Cancer Research 2015, 21: 3052-3060. PMID: 25788491, PMCID: PMC4490112, DOI: 10.1158/1078-0432.ccr-14-3073.Peer-Reviewed Original ResearchConceptsPD-L1 expressionT-cell contentPD-1/PD-L1 inhibitorsHigher T-cell contentT-cell infiltratesPD-L1 inhibitorsAnatomic sitesBrain metastasesMetastatic melanomaTissue microarrayHigh PD-L1 expressionLess PD-L1 expressionLow PD-L1 expressionTumor PD-L1 expressionHigher TIL contentImproved overall survivalT cell infiltrationLess T cellsMetastatic melanoma samplesExtracerebral metastasesCerebral metastasesOverall survivalDermal metastasesImproved survivalPD-L1
2014
Quantitative assessment of miR34a as an independent prognostic marker in breast cancer
Agarwal S, Hanna J, Sherman ME, Figueroa J, Rimm DL. Quantitative assessment of miR34a as an independent prognostic marker in breast cancer. British Journal Of Cancer 2014, 112: 61-68. PMID: 25474246, PMCID: PMC4453614, DOI: 10.1038/bjc.2014.573.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsCohort StudiesFemaleHumansMicroRNAsPrognosisProportional Hazards ModelsProspective StudiesSurvival AnalysisTreatment OutcomeConceptsDisease-specific survivalBreast cancer cohortPoor disease-specific survivalDisease-specific deathIndependent breast cancer cohortsBreast cancerCancer cohortPoor outcomeCohort 1Multivariate Cox proportional hazards analysisCox proportional hazards analysisNode-positive populationX-tile softwareNode-negative patientsProportional hazards analysisTumor suppressorBreast cancer patientsIndependent prognostic markerExpression of miR34aReceptor statusNode statusPreclinical observationsTumor sizeCancer patientsCohort 2Prognostic Biomarkers in Phase II Trial of Cetuximab-Containing Induction and Chemoradiation in Resectable HNSCC: Eastern Cooperative Oncology Group E2303
Psyrri A, Lee JW, Pectasides E, Vassilakopoulou M, Kosmidis EK, Burtness BA, Rimm DL, Wanebo HJ, Forastiere AA. Prognostic Biomarkers in Phase II Trial of Cetuximab-Containing Induction and Chemoradiation in Resectable HNSCC: Eastern Cooperative Oncology Group E2303. Clinical Cancer Research 2014, 20: 3023-3032. PMID: 24700741, PMCID: PMC4049169, DOI: 10.1158/1078-0432.ccr-14-0113.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntibodies, Monoclonal, HumanizedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorCarboplatinCarcinoma, Squamous CellCetuximabChemoradiotherapyDisease-Free SurvivalDrug Resistance, NeoplasmFemaleFluorescent Antibody TechniqueHead and Neck NeoplasmsHumansInduction ChemotherapyKaplan-Meier EstimateMaleMiddle AgedMitogen-Activated Protein Kinase KinasesPaclitaxelPhosphatidylinositol 3-KinasesPrognosisProportional Hazards ModelsProto-Oncogene Proteins c-aktRas ProteinsSignal TransductionSquamous Cell Carcinoma of Head and NeckTissue Array AnalysisConceptsProgression-free survivalEvent-free survivalPhase II trialOverall survivalII trialTissue microarrayStage III/IV headMultivariable Cox proportional hazards modelsMultivariable Cox regression analysisNeck squamous cell cancerRAS/MAPK/ERKCox proportional hazards modelInsulin-like growth factor 1 receptorLarge prospective studiesCox regression analysisInferior overall survivalKaplan-Meier methodSquamous cell cancerLog-rank testGrowth factor 1 receptorProportional hazards modelPI3K/Akt pathwayFactor 1 receptorPI3K/AktEGF receptorMarkers of Epithelial to Mesenchymal Transition in Association with Survival in Head and Neck Squamous Cell Carcinoma (HNSCC)
Pectasides E, Rampias T, Sasaki C, Perisanidis C, Kouloulias V, Burtness B, Zaramboukas T, Rimm D, Fountzilas G, Psyrri A. Markers of Epithelial to Mesenchymal Transition in Association with Survival in Head and Neck Squamous Cell Carcinoma (HNSCC). PLOS ONE 2014, 9: e94273. PMID: 24722213, PMCID: PMC3983114, DOI: 10.1371/journal.pone.0094273.Peer-Reviewed Original ResearchMeSH KeywordsAutomationBiomarkers, TumorCarcinoma, Squamous CellCohort StudiesEpithelial-Mesenchymal TransitionFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHead and Neck NeoplasmsHumansImage Processing, Computer-AssistedImmunohistochemistryKaplan-Meier EstimateMaleMultivariate AnalysisNeoplasm MetastasisPhenotypePrognosisProportional Hazards ModelsSquamous Cell Carcinoma of Head and NeckTreatment OutcomeConceptsProgression-free survivalSquamous cell carcinomaOverall survivalCell carcinomaE-cadherinPrimary squamous cell carcinomaNeck squamous cell carcinomaHigh-risk HNSCCKaplan-Meier analysisNovel therapeutic approachesMesenchymal transition phenotypeHigh metastatic potentialLow E-cadherinImproved OSInferior OSIndependent predictorsPoor prognosisCarcinoma prognosisClinicopathological parametersInclusion criteriaTherapeutic approachesTransition phenotypeMetastatic potentialMesenchymal transitionProtein expression analysis
2013
High Frequency of Putative Ovarian Cancer Stem Cells With CD44/CK19 Coexpression Is Associated With Decreased Progression-Free Intervals In Patients With Recurrent Epithelial Ovarian Cancer
Liu M, Mor G, Cheng H, Xiang X, Hui P, Rutherford T, Yin G, Rimm DL, Holmberg J, Alvero A, Silasi DA. High Frequency of Putative Ovarian Cancer Stem Cells With CD44/CK19 Coexpression Is Associated With Decreased Progression-Free Intervals In Patients With Recurrent Epithelial Ovarian Cancer. Reproductive Sciences 2013, 20: 605-615. PMID: 23171677, PMCID: PMC3635069, DOI: 10.1177/1933719112461183.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAnalysis of VarianceBiomarkers, TumorCarcinoma, Ovarian EpithelialDisease ProgressionDisease-Free SurvivalDrug Resistance, NeoplasmFemaleHumansHyaluronan ReceptorsKaplan-Meier EstimateKeratin-19Middle AgedMultivariate AnalysisNeoplasm Recurrence, LocalNeoplasm StagingNeoplasms, Glandular and EpithelialNeoplastic Stem CellsOvarian NeoplasmsProportional Hazards ModelsRetrospective StudiesRisk FactorsTime FactorsTreatment OutcomeConceptsPutative ovarian cancer stem cellsOvarian cancer stem cellsProgression-free intervalCancer stem cellsRecurrent epithelial ovarian cancerShorter disease-free intervalShorter progression-free intervalDisease-free intervalResidual tumor volumeEpithelial ovarian cancerLog-rank testEpithelial ovarian cancer cellsIndependent significant predictorsAdvanced stage EOCOvarian cancer cellsStem cellsMean followObstetrics stageUnivariable analysisClinicopathologic featuresMultivariable analysisRetrospective studyPrognostic valueOvarian cancerTumor volume
2012
Stathmin expression and its relationship to microtubule‐associated protein tau and outcome in breast cancer
Baquero MT, Hanna JA, Neumeister V, Cheng H, Molinaro AM, Harris LN, Rimm DL. Stathmin expression and its relationship to microtubule‐associated protein tau and outcome in breast cancer. Cancer 2012, 118: 4660-4669. PMID: 22359235, PMCID: PMC3391341, DOI: 10.1002/cncr.27453.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAnalysis of VarianceBiomarkers, TumorBlotting, WesternBreastBreast NeoplasmsCell Line, TumorCohort StudiesFemaleFluorescent Antibody TechniqueGene Expression Regulation, NeoplasticHumansImmunohistochemistryKaplan-Meier EstimateLymphatic MetastasisMiddle AgedNeoplasm GradingNeoplasm StagingOdds RatioPredictive Value of TestsPrognosisProportional Hazards ModelsRisk AssessmentRisk FactorsRNA, Small InterferingStathminTau ProteinsTissue Array AnalysisTreatment OutcomeConceptsHigh stathmin expressionDisease-free survivalMAP-tauOverall survivalStathmin expressionBreast cancerHuman epidermal growth factor receptor 2 (HER2) expressionEpidermal growth factor receptor 2 expressionMultivariate analysisCox proportional hazards modelWorse overall survivalReceptor 2 expressionTissue microarray formatMicrotubule-associated protein tauProportional hazards modelBreast cancer cohortIndependent predictorsMenopausal statusNodal statusBetter prognosisPrognostic valueTumor sizePathological characteristicsProgesterone receptorNuclear grade
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 ResearchMeSH KeywordsBiomarkers, TumorBreast NeoplasmsFemaleGene ExpressionHumansPrognosisProportional Hazards ModelsROC CurveConceptsNottingham 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 methodHigh expression of BCL-2 predicts favorable outcome in non-small cell lung cancer patients with non squamous histology
Anagnostou VK, Lowery FJ, Zolota V, Tzelepi V, Gopinath A, Liceaga C, Panagopoulos N, Frangia K, Tanoue L, Boffa D, Gettinger S, Detterbeck F, Homer RJ, Dougenis D, Rimm DL, Syrigos KN. High expression of BCL-2 predicts favorable outcome in non-small cell lung cancer patients with non squamous histology. BMC Cancer 2010, 10: 186. PMID: 20459695, PMCID: PMC2875218, DOI: 10.1186/1471-2407-10-186.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAgedBiomarkers, TumorCarcinoma, Large CellCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellCell DifferentiationCohort StudiesConnecticutFemaleGreeceHumansKaplan-Meier EstimateLung NeoplasmsMaleMiddle AgedNeoplasm StagingPredictive Value of TestsProportional Hazards ModelsProto-Oncogene Proteins c-bcl-2Reproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeUp-RegulationConceptsNon-small cell lung cancer patientsCell lung cancer patientsNon-squamous tumorsLung cancer patientsBcl-2 expressionNSCLC patientsCancer patientsBcl-2Favorable outcomeIndependent cohortSmall cell lung cancer patientsIndependent lower riskNon-squamous histologySubgroup of patientsHigh expressersSquamous cell carcinomaHigh Bcl-2 expressionBcl-2 protein levelsSquamous histologyMedian survivalPrognostic factorsValidation cohortCell carcinomaPathological characteristicsPrognostic stratificationMultiplexed Assessment of the Southwest Oncology Group-Directed Intergroup Breast Cancer Trial S9313 by AQUA Shows that Both High and Low Levels of HER2 Are Associated with Poor Outcome
Harigopal M, Barlow WE, Tedeschi G, Porter PL, Yeh IT, Haskell C, Livingston R, Hortobagyi GN, Sledge G, Shapiro C, Ingle JN, Rimm DL, Hayes DF. Multiplexed Assessment of the Southwest Oncology Group-Directed Intergroup Breast Cancer Trial S9313 by AQUA Shows that Both High and Low Levels of HER2 Are Associated with Poor Outcome. American Journal Of Pathology 2010, 176: 1639-1647. PMID: 20150438, PMCID: PMC2843456, DOI: 10.2353/ajpath.2010.090711.Peer-Reviewed Original ResearchConceptsDisease-free survivalEstrogen receptorContinuous variablesSouthwest Oncology GroupAQUA methodAC chemotherapyMenopausal statusNegative patientsOncology GroupNode statusSequential doxorubicinPoor outcomeTumor sizeProgesterone receptorPrognostic informationWorse outcomesTissue biomarkersTissue microarrayBiphasic effectP53 expressionPatientsHER2Low expressersDiagnostic approachMultiplexed assessment
2009
Quantitative expression of VEGF, VEGF-R1, VEGF-R2, and VEGF-R3 in melanoma tissue microarrays
Mehnert JM, McCarthy MM, Jilaveanu L, Flaherty KT, Aziz S, Camp RL, Rimm DL, Kluger HM. Quantitative expression of VEGF, VEGF-R1, VEGF-R2, and VEGF-R3 in melanoma tissue microarrays. Human Pathology 2009, 41: 375-384. PMID: 20004943, PMCID: PMC2824079, DOI: 10.1016/j.humpath.2009.08.016.Peer-Reviewed Original ResearchBlotting, WesternCell LineDisease ProgressionHumansImage Processing, Computer-AssistedImmunohistochemistryMelanomaNevusProportional Hazards ModelsRegression AnalysisSeverity of Illness IndexSkin NeoplasmsStatistics, NonparametricTissue Array AnalysisVascular Endothelial Growth Factor AVascular Endothelial Growth Factor Receptor-1Vascular Endothelial Growth Factor Receptor-2Vascular Endothelial Growth Factor Receptor-3
2008
Estrogen receptor co-activator (AIB1) protein expression by automated quantitative analysis (AQUA) in a breast cancer tissue microarray and association with patient outcome
Harigopal M, Heymann J, Ghosh S, Anagnostou V, Camp RL, Rimm DL. Estrogen receptor co-activator (AIB1) protein expression by automated quantitative analysis (AQUA) in a breast cancer tissue microarray and association with patient outcome. Breast Cancer Research And Treatment 2008, 115: 77-85. PMID: 18521745, DOI: 10.1007/s10549-008-0063-9.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAutomationBiomarkers, TumorBreast NeoplasmsFemaleGene Expression Regulation, NeoplasticHumansMultivariate AnalysisNuclear Receptor Coactivator 3Oligonucleotide Array Sequence AnalysisPrognosisProportional Hazards ModelsReceptors, EstrogenReceptors, ProgesteroneRegression AnalysisTranscription FactorsTreatment OutcomeConceptsHigh AIB1 expressionTranscription intermediary factor 2Poor patient outcomesAIB1 expressionTissue microarrayPatient outcomesHER2/neu statusBreast cancer tissue microarrayFluorescent immunohistochemical stainingWorse overall survivalUnivariate survival analysisBreast cancer specimensCancer tissue microarrayHER2/neuCoregulatory proteinsCox univariate survival analysesBreast tissue microarraysOverall survivalER statusPR statusPrognostic significanceIndependent associationBreast cancerPrognostic biomarkerImmunohistochemical stainingExpression patterns and prognostic value of Bag-1 and Bcl-2 in breast cancer
Nadler Y, Camp RL, Giltnane JM, Moeder C, Rimm DL, Kluger HM, Kluger Y. Expression patterns and prognostic value of Bag-1 and Bcl-2 in breast cancer. Breast Cancer Research 2008, 10: r35. PMID: 18430249, PMCID: PMC2397537, DOI: 10.1186/bcr1998.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic AgentsBiomarkers, TumorBreast NeoplasmsDNA-Binding ProteinsDrug Resistance, NeoplasmFemaleFluorescent Antibody TechniqueFollow-Up StudiesGene Expression Regulation, NeoplasticHumansImmunohistochemistryKaplan-Meier EstimateLymphatic MetastasisMiddle AgedPredictive Value of TestsPrognosisProportional Hazards ModelsProtein Array AnalysisProto-Oncogene Proteins c-bcl-2Receptors, EstrogenReceptors, ProgesteroneTranscription FactorsTreatment OutcomeConceptsNode-positive subsetHER2/neuProgesterone receptorBreast cancerEstrogen receptorBcl-2 expressionBAG-1 expressionImproved survivalBcl-2Anti-apoptotic mediator Bcl-2Breast tumorsSteroid receptor positivitySubset of patientsBAG-1Antihormonal therapyFavorable prognosisReceptor positivityMultivariable analysisPathological variablesEntire cohortPrognostic valuePrognostic markerImproved outcomesLarge cohortClinical development