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 ResearchConceptsNon-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
Multiplex 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-1
2018
CD68, CD163, and matrix metalloproteinase 9 (MMP-9) co-localization in breast tumor microenvironment predicts survival differently in ER-positive and -negative cancers
Pelekanou V, Villarroel-Espindola F, Schalper KA, Pusztai L, Rimm DL. CD68, CD163, and matrix metalloproteinase 9 (MMP-9) co-localization in breast tumor microenvironment predicts survival differently in ER-positive and -negative cancers. Breast Cancer Research 2018, 20: 154. PMID: 30558648, PMCID: PMC6298021, DOI: 10.1186/s13058-018-1076-x.Peer-Reviewed Original ResearchMeSH KeywordsAntigens, CDAntigens, Differentiation, MyelomonocyticAntineoplastic AgentsBiomarkers, TumorBreastBreast NeoplasmsDisease-Free SurvivalFemaleGene Expression Regulation, NeoplasticHumansMacrophagesMatrix Metalloproteinase 9Middle AgedPatient SelectionPrognosisReceptors, Cell SurfaceReceptors, EstrogenRetrospective StudiesSurvival AnalysisTissue Array AnalysisTumor MicroenvironmentConceptsTumor-associated macrophagesOverall survivalQuantitative immunofluorescenceMacrophage markersBreast cancerHigh expressionPan-macrophage marker CD68Triple-negative breast cancerCD163/CD68Multiplexed quantitative immunofluorescenceImproved overall survivalProtein expressionWorse overall survivalPoor overall survivalMMP-9 protein expressionSubclass of patientsMacrophage-targeted therapiesMatrix metalloproteinase-9Tissue microarray formatMMP-9 proteinBreast tumor microenvironmentModulator of responseParaffin-embedded tissuesBreast cancer biomarkersCohort BUtility of CD8 score by automated quantitative image analysis in head and neck squamous cell carcinoma
Hartman DJ, Ahmad F, Ferris R, Rimm D, Pantanowitz L. Utility of CD8 score by automated quantitative image analysis in head and neck squamous cell carcinoma. Oral Oncology 2018, 86: 278-287. PMID: 30409313, PMCID: PMC6260977, DOI: 10.1016/j.oraloncology.2018.10.005.Peer-Reviewed Original ResearchConceptsCD8 T cellsImmune cell densityOropharyngeal HNSCCT cellsNeck squamous cell carcinomaCD8 cell densityImmune cell infiltratesSquamous cell carcinomaWhole tissue sectionsEntire tumor sectionHPV infectionMedian survivalCell infiltrateHNSCC patientsCell carcinomaHNSCC casesClinicopathologic parametersOnly predictorTumor sectionsBetter outcomesClinical practiceTumor microenvironmentCell densityClinical validationCells/A dormant TIL phenotype defines non-small cell lung carcinomas sensitive to immune checkpoint blockers
Gettinger SN, Choi J, Mani N, Sanmamed MF, Datar I, Sowell R, Du VY, Kaftan E, Goldberg S, Dong W, Zelterman D, Politi K, Kavathas P, Kaech S, Yu X, Zhao H, Schlessinger J, Lifton R, Rimm DL, Chen L, Herbst RS, Schalper KA. A dormant TIL phenotype defines non-small cell lung carcinomas sensitive to immune checkpoint blockers. Nature Communications 2018, 9: 3196. PMID: 30097571, PMCID: PMC6086912, DOI: 10.1038/s41467-018-05032-8.Peer-Reviewed Original ResearchMeSH KeywordsAmino Acid SequenceAnimalsAntibodies, BlockingCarcinogenesisCarcinoma, Non-Small-Cell LungCell ProliferationCytotoxicity, ImmunologicHistocompatibility Antigens Class IHumansLung NeoplasmsLymphocyte ActivationLymphocytes, Tumor-InfiltratingMaleMice, Inbred NODMice, SCIDMutant ProteinsMutationPeptidesPhenotypeProgrammed Cell Death 1 ReceptorReproducibility of ResultsSurvival AnalysisTobaccoConceptsImmune checkpoint blockersCheckpoint blockersQuantitative immunofluorescenceNon-small cell lung carcinoma patientsCell lung carcinoma patientsNon-small cell lung carcinomaPatient-derived xenograft modelsIntratumoral T cellsMultiplexed quantitative immunofluorescencePD-1 blockadeLevels of CD3Lung carcinoma patientsCell lung carcinomaT cell proliferationPre-treatment samplesTIL phenotypeSurvival benefitCarcinoma patientsEffector capacityLung carcinomaT cellsWhole-exome DNA sequencingXenograft modelFavorable responseBlockers
2017
Objective measurement and clinical significance of IDO1 protein in hormone receptor-positive breast cancer
Carvajal-Hausdorf DE, Mani N, Velcheti V, Schalper KA, Rimm DL. Objective measurement and clinical significance of IDO1 protein in hormone receptor-positive breast cancer. Journal For ImmunoTherapy Of Cancer 2017, 5: 81. PMID: 29037255, PMCID: PMC5644103, DOI: 10.1186/s40425-017-0285-7.Peer-Reviewed Original ResearchMeSH KeywordsBreast NeoplasmsFemaleHumansLymphocytes, Tumor-InfiltratingMiddle AgedRetrospective StudiesSurvival AnalysisConceptsHormone receptor-positive breast cancerReceptor-positive breast cancerIDO1 expressionBreast cancerIndependent negative prognostic markerB cell infiltrationImmune suppressive pathwaysAdvanced solid tumorsTumor-infiltrating lymphocytesT cell responsesClinico-pathological featuresClinico-pathological characteristicsProportional hazards modelNegative prognostic markerDegradation of tryptophanMann-Whitney testFoxp3 levelsIDO1 blockadeIDO1 levelsEffector CD4Durable responsesOverall survivalImmune toleranceMultivariable analysisPrognostic marker
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 ResearchConceptsDisease-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 2
2013
Programmed death ligand-1 expression in non-small cell lung cancer
Velcheti V, Schalper KA, Carvajal DE, Anagnostou VK, Syrigos KN, Sznol M, Herbst RS, Gettinger SN, Chen L, Rimm DL. Programmed death ligand-1 expression in non-small cell lung cancer. Laboratory Investigation 2013, 94: 107-116. PMID: 24217091, PMCID: PMC6125250, DOI: 10.1038/labinvest.2013.130.Peer-Reviewed Original ResearchMeSH KeywordsAgedB7-H1 AntigenBiomarkers, TumorCarcinoma, Non-Small-Cell LungCell Line, TumorChi-Square DistributionCohort StudiesConnecticutFemaleGreeceHumansImmunohistochemistryLung NeoplasmsLymphocytes, Tumor-InfiltratingMalePrognosisReproducibility of ResultsRNA, MessengerSurvival AnalysisTissue Array AnalysisConceptsNon-small cell lung cancerPD-L1 expressionCell lung cancerPD-L1Tissue microarrayBetter outcomesNSCLC casesLung cancerDeath ligand 1 (PD-L1) expressionCell death ligand 1PD-L1 protein expressionEarly phase clinical trialsLigand 1 expressionTumor-infiltrating lymphocytesDeath ligand 1Significant better outcomePD-L1 mRNAPD-L1 proteinPhase clinical trialsNormal human placentaPrediction of responseQuantitative fluorescence approachesFrequency of expressionPD-1Prognostic valueHigh SOX2 Levels Predict Better Outcome in Non-Small Cell Lung Carcinomas
Velcheti V, Schalper K, Yao X, Cheng H, Kocoglu M, Dhodapkar K, Deng Y, Gettinger S, Rimm DL. High SOX2 Levels Predict Better Outcome in Non-Small Cell Lung Carcinomas. PLOS ONE 2013, 8: e61427. PMID: 23620753, PMCID: PMC3631238, DOI: 10.1371/journal.pone.0061427.Peer-Reviewed Original ResearchConceptsSquamous cell carcinomaLonger survivalTissue microarrayMultivariate analysisIndependent lung cancer cohortsIndependent positive prognostic markerSOX2 levelsNon-small cell lung carcinomaQuantitative immunofluorescenceLung squamous cell carcinomaSecond independent validation cohortSOX2 expressionHigh SOX2 levelsLog rank pSOX2 overexpressionPositive prognostic markerRisk of deathClinico-pathological characteristicsClinico-pathological variablesCox univariate analysisIndependent validation cohortCell lung carcinomaLung cancer cohortNSCLC patientsOverall survival
2012
Lin28 regulates HER2 and promotes malignancy through multiple mechanisms
Feng C, Neumeister V, Ma W, Xu J, Lu L, Bordeaux J, Maihle NJ, Rimm DL, Huang Y. Lin28 regulates HER2 and promotes malignancy through multiple mechanisms. Cell Cycle 2012, 11: 2486-2494. PMID: 22713243, DOI: 10.4161/cc.20893.Peer-Reviewed Original ResearchConceptsHuman epidermal growth factor receptor 2HER2 expressionLin28 expressionEpidermal growth factor receptor 2Growth factor receptor 2Primary breast tumorsFactor receptor 2Cancer cell growthMajor therapeutic targetMultiple mechanismsAdvanced human malignanciesClinical outcomesPoor prognosisBreast cancerReceptor 2Therapeutic targetBreast tumorsNovel mechanistic insightsHuman malignanciesLin28 overexpressionReceptor tyrosine kinasesCancerCell proliferationHuman cancersPowerful predictorQuantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer
Agarwal S, Gertler FB, Balsamo M, Condeelis JS, Camp RL, Xue X, Lin J, Rohan TE, Rimm DL. Quantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer. Breast Cancer Research 2012, 14: r124. PMID: 22971274, PMCID: PMC3962029, DOI: 10.1186/bcr3318.Peer-Reviewed Original ResearchConceptsBreast cancer cohortBreast cancerPoor outcomeTumor cellsCancer cohortPoor disease-specific survivalDisease-specific deathDisease-specific survivalBreast cancer patientsIndependent prognostic markerIndependent breast cancer cohortsNon-invasive tumor cellsInvasive tumor cellsReceptor statusNode statusTumor sizeCancer patientsPrognostic markerSignificant associationCohortCancerIsoform expressionPatientsMetastasisOutcomes
2011
Loss of Nuclear Localized and Tyrosine Phosphorylated Stat5 in Breast Cancer Predicts Poor Clinical Outcome and Increased Risk of Antiestrogen Therapy Failure
Peck AR, Witkiewicz AK, Liu C, Stringer GA, Klimowicz AC, Pequignot E, Freydin B, Tran TH, Yang N, Rosenberg AL, Hooke JA, Kovatich AJ, Nevalainen MT, Shriver CD, Hyslop T, Sauter G, Rimm DL, Magliocco AM, Rui H. Loss of Nuclear Localized and Tyrosine Phosphorylated Stat5 in Breast Cancer Predicts Poor Clinical Outcome and Increased Risk of Antiestrogen Therapy Failure. Journal Of Clinical Oncology 2011, 29: 2448-2458. PMID: 21576635, PMCID: PMC3675698, DOI: 10.1200/jco.2010.30.3552.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAntineoplastic Agents, HormonalBreast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, Intraductal, NoninfiltratingCohort StudiesDisease ProgressionDisease-Free SurvivalDrug Resistance, NeoplasmEstrogen Receptor ModulatorsFemaleHumansLymphatic MetastasisMiddle AgedNeoplasm ProteinsNuclear ProteinsPhosphorylationPhosphotyrosinePrognosisProtein Processing, Post-TranslationalSTAT5 Transcription FactorSurvival AnalysisTreatment FailureTumor Suppressor ProteinsYoung AdultConceptsNode-negative breast cancerCancer-specific survivalIndependent prognostic markerBreast cancerWhole tissue sectionsTherapy failurePrognostic markerTissue microarrayPathologist scoringMultivariate analysis patientsSystemic adjuvant therapyAdjuvant hormone therapyMarker of prognosisPoor clinical outcomeUseful predictive markerPredictors of responseNormal breast epitheliumTissue sectionsCohort IVAdjuvant therapyHormone therapyAnalysis patientsClinical outcomesDuctal carcinomaProspective studyComparative Prognostic Value of Epidermal Growth Factor Quantitative Protein Expression Compared with FISH for Head and Neck Squamous Cell Carcinoma
Pectasides E, Rampias T, Kountourakis P, Sasaki C, Kowalski D, Fountzilas G, Zaramboukas T, Rimm D, Burtness B, Psyrri A. Comparative Prognostic Value of Epidermal Growth Factor Quantitative Protein Expression Compared with FISH for Head and Neck Squamous Cell Carcinoma. Clinical Cancer Research 2011, 17: 2947-2954. PMID: 21355076, DOI: 10.1158/1078-0432.ccr-10-2040.Peer-Reviewed Original ResearchCarcinomaCarcinoma, Squamous CellEpidermal Growth FactorFemaleGene DosageGene Expression Regulation, NeoplasticHead and Neck NeoplasmsHumansIn Situ Hybridization, FluorescenceMaleNeoplasms, Squamous CellPredictive Value of TestsPrognosisProteinsSquamous Cell Carcinoma of Head and NeckSurvival AnalysisTissue Array AnalysisDifferential expression of arrestins is a predictor of breast cancer progression and survival
Michal AM, Peck AR, Tran TH, Liu C, Rimm DL, Rui H, Benovic JL. Differential expression of arrestins is a predictor of breast cancer progression and survival. Breast Cancer Research And Treatment 2011, 130: 791-807. PMID: 21318602, PMCID: PMC3156829, DOI: 10.1007/s10549-011-1374-9.Peer-Reviewed Original ResearchConceptsBreast cancer progressionBreast cancerCancer progressionArrestin2 expressionLuminal linesMyoepithelial cellsNormal human breast tissueMetastatic breast cancerLymph node metastasisPoor clinical outcomeIndependent prognostic markerPrimary breast tumorsBreast cancer cell linesG protein-coupled receptorsArrestin2 levelsPositive lymphCancer cell linesHazard ratioHuman breast tissueProtein-coupled receptorsNode metastasisClinical outcomesDuctal carcinomaTumor sizeNuclear grade
2009
Tissue Biomarkers for Prognosis in Cutaneous Melanoma: A Systematic Review and Meta-analysis
Rothberg BE, Bracken MB, Rimm DL. Tissue Biomarkers for Prognosis in Cutaneous Melanoma: A Systematic Review and Meta-analysis. Journal Of The National Cancer Institute 2009, 101: 452-474. PMID: 19318635, PMCID: PMC2720709, DOI: 10.1093/jnci/djp038.Peer-Reviewed Original ResearchConceptsCohort studyCutaneous melanomaMelanoma cell adhesion moleculeSystematic reviewEarly-stage cutaneous melanomaPotential prognostic valueMatrix metalloproteinase-2Cell nuclear antigenREMARK criteriaAdjuvant therapyMultivariable analysisREMARK guidelinesRisk stratificationPrognostic valueSurvival outcomesIncomplete adherenceMelanoma outcomesClinical managementImmunohistochemical expressionCell adhesion moleculeInclusion criteriaKi-67Tissue biomarkersClinical practiceMetalloproteinase-2Activated Wnt/ß-catenin signaling in melanoma is associated with decreased proliferation in patient tumors and a murine melanoma model
Chien AJ, Moore EC, Lonsdorf AS, Kulikauskas RM, Rothberg BG, Berger AJ, Major MB, Hwang ST, Rimm DL, Moon RT. Activated Wnt/ß-catenin signaling in melanoma is associated with decreased proliferation in patient tumors and a murine melanoma model. Proceedings Of The National Academy Of Sciences Of The United States Of America 2009, 106: 1193-1198. PMID: 19144919, PMCID: PMC2626610, DOI: 10.1073/pnas.0811902106.Peer-Reviewed Original ResearchConceptsBeta-catenin signalingNormal melanocyte developmentTranscriptional profiling revealsWnt/beta-catenin signalingMelanoma cellsUp-regulates genesWnt/ß-cateninMelanoma progressionSmall molecule activatorsRole of WntMelanocyte developmentCell fateTranscriptional changesB16 murine melanoma cellsCellular differentiationProfiling revealsMelanocyte differentiationMelanoma cell linesMurine melanoma cellsß-cateninHuman melanoma cell linesWnt3aMurine melanoma modelCell linesReduced expression
2008
Prognostic Significance of Cadherin-Based Adhesion Molecules in Cutaneous Malignant Melanoma
Kreizenbeck GM, Berger AJ, Subtil A, Rimm DL, Rothberg BE. Prognostic Significance of Cadherin-Based Adhesion Molecules in Cutaneous Malignant Melanoma. Cancer Epidemiology Biomarkers & Prevention 2008, 17: 949-958. PMID: 18398036, PMCID: PMC3312613, DOI: 10.1158/1055-9965.epi-07-2729.Peer-Reviewed Original Research
2007
Quantitative Measurement of Epidermal Growth Factor Receptor Is a Negative Predictive Factor for Tamoxifen Response in Hormone Receptor–Positive Premenopausal Breast Cancer
Giltnane JM, Rydén L, Cregger M, Bendahl PO, Jirström K, Rimm DL. Quantitative Measurement of Epidermal Growth Factor Receptor Is a Negative Predictive Factor for Tamoxifen Response in Hormone Receptor–Positive Premenopausal Breast Cancer. Journal Of Clinical Oncology 2007, 25: 3007-3014. PMID: 17634479, DOI: 10.1200/jco.2006.08.9938.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedBiomarkersBiopsy, NeedleBreast NeoplasmsDrug Resistance, NeoplasmErbB ReceptorsEstrogen AntagonistsFemaleHumansImmunohistochemistryMiddle AgedMultivariate AnalysisPredictive Value of TestsPremenopauseProbabilityProportional Hazards ModelsReceptors, EstrogenRisk AssessmentSensitivity and SpecificitySurvival AnalysisTamoxifenConceptsEpidermal growth factor receptorER-positive patientsEGFR expressionBreast cancerEstrogen receptorTamoxifen-treated patientsEarly breast cancerRecurrence-free survivalRandomized clinical trialsLow EGFR expressionSignificant beneficial effectAdjuvant tamoxifenGrowth factor receptorEndocrine therapyTamoxifen responseTamoxifen treatmentClinical trialsSitu protein expressionUntreated groupTissue microarrayPatientsBeneficial effectsProtein expressionFactor receptorTreatment effectsPhosphorylation of Akt (Ser473) Predicts Poor Clinical Outcome in Oropharyngeal Squamous Cell Cancer
Yu Z, Weinberger PM, Sasaki C, Egleston BL, Speier WF, Haffty B, Kowalski D, Camp R, Rimm D, Vairaktaris E, Burtness B, Psyrri A. Phosphorylation of Akt (Ser473) Predicts Poor Clinical Outcome in Oropharyngeal Squamous Cell Cancer. Cancer Epidemiology Biomarkers & Prevention 2007, 16: 553-558. PMID: 17372251, DOI: 10.1158/1055-9965.epi-06-0121.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedBiomarkers, TumorCarcinoma, Squamous CellChi-Square DistributionFemaleHumansImmunoenzyme TechniquesMaleMiddle AgedNeoplasm Recurrence, LocalOropharyngeal NeoplasmsPhosphorylationPredictive Value of TestsPrognosisProportional Hazards ModelsProtein Array AnalysisProto-Oncogene Proteins c-aktPTEN PhosphohydrolaseSurvival AnalysisConceptsNuclear p-AktAkt activationP-AktOropharyngeal squamous cell cancerSquamous cell carcinoma progressionPhosphorylated AktCohort of patientsLocal recurrence rateOverall survival rateSquamous cell cancerPoor clinical outcomeAdverse patient outcomesP-AKT levelsPromising molecular targetP-AKT expressionProtein expression levelsPhosphorylation of AktDisease recurrenceLocal recurrenceCell cancerClinical outcomesAdjusted analysisPrognostic significanceRecurrence ratePatient outcomes
2006
Classification of Breast Cancer Using Genetic Algorithms and Tissue Microarrays
Dolled-Filhart M, Rydén L, Cregger M, Jirström K, Harigopal M, Camp RL, Rimm DL. Classification of Breast Cancer Using Genetic Algorithms and Tissue Microarrays. Clinical Cancer Research 2006, 12: 6459-6468. PMID: 17085660, DOI: 10.1158/1078-0432.ccr-06-1383.Peer-Reviewed Original ResearchConceptsBreast cancerPatient outcomesTissue microarraySubset of patientsBreast cancer patientsTissue microarray platformInternal validation setRoutine pathology laboratoriesCancer patientsEstrogen receptorTissue biomarkersIndependent cohortTumor subtypesPredictive valueAcid-base analysisPathology laboratoryRNA expression studiesCancerTissue sectionsPatientsCohortOutcomesFurther validationObjective quantitative analysisBiomarker discovery