2021
BRCA1 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 patientsComparison of programmed death-ligand 1 protein expression between primary and metastatic lesions in patients with lung cancer
Moutafi MK, Tao W, Huang R, Haberberger J, Alexander B, Ramkissoon S, Ross JS, Syrigos K, Wei W, Pusztai L, Rimm DL, Vathiotis IA. Comparison of programmed death-ligand 1 protein expression between primary and metastatic lesions in patients with lung cancer. Journal For ImmunoTherapy Of Cancer 2021, 9: e002230. PMID: 33833050, PMCID: PMC8039214, DOI: 10.1136/jitc-2020-002230.Peer-Reviewed Original ResearchConceptsPD-L1 expressionMetastatic lesionsLung cancer casesLung cancerCancer casesAdvanced stage non-small cell lung cancerNon-small cell lung cancerNon-squamous histologyCell lung cancerFuture patient managementDefinite diagnostic testSquamous histologyFoundation MedicineLymph nodesRoutine careHistologic subtypeMetastatic sitesPrimary lesionRetrospective studyAdrenal glandPrimary tumorPleural fluidPatient managementTrial designDrug AdministrationAutomated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma
Moore MR, Friesner ID, Rizk EM, Fullerton BT, Mondal M, Trager MH, Mendelson K, Chikeka I, Kurc T, Gupta R, Rohr BR, Robinson EJ, Acs B, Chang R, Kluger H, Taback B, Geskin LJ, Horst B, Gardner K, Niedt G, Celebi JT, Gartrell-Corrado RD, Messina J, Ferringer T, Rimm DL, Saltz J, Wang J, Vanguri R, Saenger YM. Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma. Scientific Reports 2021, 11: 2809. PMID: 33531581, PMCID: PMC7854647, DOI: 10.1038/s41598-021-82305-1.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiopsyChemotherapy, AdjuvantClinical Decision-MakingDeep LearningFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedKaplan-Meier EstimateLymphocytes, Tumor-InfiltratingMaleMelanomaMiddle AgedNeoplasm StagingPatient SelectionPrognosisRetrospective StudiesRisk AssessmentROC CurveSkinSkin NeoplasmsYoung AdultConceptsTumor-infiltrating lymphocytesDisease-specific survivalEarly-stage melanomaOpen-source deep learningCutoff valueMultivariable Cox proportional hazards analysisCox proportional hazards analysisDeep learningLow-risk patientsProportional hazards analysisKaplan-Meier analysisAccurate prognostic biomarkersEosin imagesAccuracy of predictionAdjuvant therapyRisk patientsSpecific survivalPrognostic valueValidation cohortReceiver operating curvesTraining cohortTIL analysisClinical trialsPrimary melanomaPrognostic biomarker
2019
An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
Acs B, Ahmed FS, Gupta S, Wong P, Gartrell RD, Sarin Pradhan J, Rizk EM, Gould Rothberg BE, Saenger YM, Rimm DL. An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma. Nature Communications 2019, 10: 5440. PMID: 31784511, PMCID: PMC6884485, DOI: 10.1038/s41467-019-13043-2.Peer-Reviewed Original ResearchConceptsOpen sourceOpen source softwareSource softwareTIL scoreTraining setDisease-specific overall survivalHigh TIL scorePoor prognosis cohortsSubset of patientsAlgorithmIndependent prognostic markerBroad adoptionAssessment of tumorOverall survivalFavorable prognosisMelanoma patientsMultivariable analysisValidation cohortIndependent associationPrognostic markerSeparate patientsPrognostic variablesIndependent cohortRetrospective collectionMelanomaDeep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death
Kulkarni PM, Robinson EJ, Pradhan J, Gartrell-Corrado RD, Rohr BR, Trager MH, Geskin LJ, Kluger HM, Wong PF, Acs B, Rizk EM, Yang C, Mondal M, Moore MR, Osman I, Phelps R, Horst BA, Chen ZS, Ferringer T, Rimm DL, Wang J, Saenger YM. Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death. Clinical Cancer Research 2019, 26: 1126-1134. PMID: 31636101, PMCID: PMC8142811, DOI: 10.1158/1078-0432.ccr-19-1495.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAlgorithmsArea Under CurveBiopsyDeep LearningDisease ProgressionFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedMaleMelanomaMiddle AgedNeoplasm Recurrence, LocalNeural Networks, ComputerRetrospective StudiesRisk FactorsStaining and LabelingSurvival RateYoung AdultConceptsDeep neural network architectureNeural network architectureDeep learningNetwork architectureComputational modelImage sequencesDigital imagesVote aggregationDisease-specific survivalDSS predictionPractical advancesComputational methodsIHC-based methodsImagesGeisinger Health SystemNovel methodGHS patientsArchitectureLearningKaplan-Meier analysisPrimary melanoma tumorsEarly-stage melanomaClinical trial designModelAdjuvant immunotherapy
2018
Immunological differences between primary and metastatic breast cancer
Szekely B, Bossuyt V, Li X, Wali VB, Patwardhan GA, Frederick C, Silber A, Park T, Harigopal M, Pelekanou V, Zhang M, Yan Q, Rimm DL, Bianchini G, Hatzis C, Pusztai L. Immunological differences between primary and metastatic breast cancer. Annals Of Oncology 2018, 29: 2232-2239. PMID: 30203045, DOI: 10.1093/annonc/mdy399.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAntineoplastic Agents, ImmunologicalB7-H1 AntigenBiomarkers, TumorBiopsyBreast NeoplasmsDisease ProgressionDrug Resistance, NeoplasmFemaleGene Expression RegulationHumansImmunologic SurveillanceLymphocyte CountLymphocytes, Tumor-InfiltratingMiddle AgedMutation RateTumor EscapeTumor MicroenvironmentYoung AdultConceptsMetastatic breast cancerBreast cancerTherapeutic targetToll-like receptor pathway genesImmuno-oncology therapeutic targetsBreast cancer evolvesImmune proteasome expressionPD-L1 positivityCorresponding primary tumorsPotential therapeutic targetMHC class IImmune-related genesMetastatic cancer samplesLigand/receptor pairLymphocyte countT helperT-regsPD-L1Immune microenvironmentCytotoxic TPrimary tumorMastoid cellsDisease progressionTherapeutic combinationsMacrophage markers
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-L1PLEKHA5 as a Biomarker and Potential Mediator of Melanoma Brain Metastasis
Jilaveanu LB, Parisi F, Barr ML, Zito CR, Cruz-Munoz W, Kerbel RS, Rimm DL, Bosenberg MW, Halaban R, Kluger Y, Kluger HM. PLEKHA5 as a Biomarker and Potential Mediator of Melanoma Brain Metastasis. Clinical Cancer Research 2015, 21: 2138-2147. PMID: 25316811, PMCID: PMC4397107, DOI: 10.1158/1078-0432.ccr-14-0861.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorBrain NeoplasmsCell Line, TumorFemaleFluorescent Antibody TechniqueGene Expression ProfilingHumansImage Processing, Computer-AssistedIntracellular Signaling Peptides and ProteinsMaleMelanomaMiddle AgedNeoplasm InvasivenessTissue Array AnalysisTranscriptomeYoung AdultConceptsCell line modelsBlood-brain barrierBrain metastasesGene expression profilesGene expression profilingExpression profilingExpression profilesPLEKHA5Brain metastasis-free survivalA375P cellsQuantitative immunofluorescenceEarly brain metastasisMelanoma brain metastasesMetastasis-free survivalProfile of patientsPotential mediatorsProtein levelsMetastatic melanoma casesEarly developmentMelanoma cellsKnockdownDecrease proliferationBBB transmigrationExtracerebral sitesMetastatic sites
2014
Whole-Exome Sequencing Characterizes the Landscape of Somatic Mutations and Copy Number Alterations in Adrenocortical Carcinoma
Juhlin CC, Goh G, Healy JM, Fonseca AL, Scholl UI, Stenman A, Kunstman JW, Brown TC, Overton JD, Mane SM, Nelson-Williams C, Bäckdahl M, Suttorp AC, Haase M, Choi M, Schlessinger J, Rimm DL, Höög A, Prasad ML, Korah R, Larsson C, Lifton RP, Carling T. Whole-Exome Sequencing Characterizes the Landscape of Somatic Mutations and Copy Number Alterations in Adrenocortical Carcinoma. The Journal Of Clinical Endocrinology & Metabolism 2014, 100: e493-e502. PMID: 25490274, PMCID: PMC5393505, DOI: 10.1210/jc.2014-3282.Peer-Reviewed Original ResearchConceptsAdrenocortical carcinomaSomatic mutationsCopy number alterationsNumber alterationsNonsynonymous somatic mutationsWnt pathway dysregulationHomozygous deletionMajority of casesPotential disease-causing mutationsWhole-exome sequencingUnderlying somatic mutationsLethal malignancyPathway dysregulationTumorsExome sequencingFocal CNAsDisease-causing mutationsCarcinomaTERT locusZNRF3Recurrent CNAsAlterationsNormal samplesTP53Unknown roleMacrophage expression of tartrate-resistant acid phosphatase as a prognostic indicator in colon cancer
How J, Brown JR, Saylor S, Rimm DL. Macrophage expression of tartrate-resistant acid phosphatase as a prognostic indicator in colon cancer. Histochemistry And Cell Biology 2014, 142: 195-204. PMID: 24429833, PMCID: PMC4101067, DOI: 10.1007/s00418-014-1181-6.Peer-Reviewed Original ResearchMeSH KeywordsAcid PhosphataseAdenocarcinomaAdultAgedAged, 80 and overAntigens, CDAntigens, Differentiation, MyelomonocyticBiomarkers, TumorColonic NeoplasmsFemaleHumansIsoenzymesMacrophagesMaleMiddle AgedReceptors, Cell SurfaceTartrate-Resistant Acid PhosphataseTissue Array AnalysisTreatment OutcomeYoung AdultConceptsColorectal cancer patientsMacrophage expressionResistant acid phosphataseColon cancerCancer patientsTRAP expressionYale-New Haven HospitalDisease-specific deathPan-macrophage markerRisk reductionPrognostic indicatorCancer survivalColorectal adenocarcinomaM2 markersImproved outcomesTissue microarrayImmunohistochemical analysisSecond cohortSurvival analysisPatientsPotential biomarkersQuantitative immunofluorescenceCancerAcid phosphataseOld cases
2013
Marginal and Joint Distributions of S100, HMB-45, and Melan-A Across a Large Series of Cutaneous Melanomas
Viray H, Bradley WR, Schalper KA, Rimm DL, Rothberg BE. Marginal and Joint Distributions of S100, HMB-45, and Melan-A Across a Large Series of Cutaneous Melanomas. Archives Of Pathology & Laboratory Medicine 2013, 137: 1063-73. PMID: 23899062, PMCID: PMC3963468, DOI: 10.5858/arpa.2012-0284-oa.Peer-Reviewed Original ResearchConceptsHMB-45Primary tumorCutaneous melanomaLarge seriesMelanoma-specific survivalMelanoma primary tumorsGroup of antigensLarge tissue microarrayClinicopathologic covariatesClinicopathologic criteriaPrognostic relevanceHistopathologic profileClinicopathologic correlatesAntigen expressionClinicopathologic parametersMelanoma markersTissue microarrayPositive expressionSurvival analysisMelanomaMelanS100Melanoma cellsBivariate associationsSignificant differences
2012
Association between the nuclear to cytoplasmic ratio of p27 and the efficacy of adjuvant polychemotherapy in early breast cancer
Andre F, Conforti R, Moeder CB, Mauguen A, Arnedos M, Berrada N, Delaloge S, Tomasic G, Spielmann M, Esteva FJ, Rimm DL, Michiels S. Association between the nuclear to cytoplasmic ratio of p27 and the efficacy of adjuvant polychemotherapy in early breast cancer. Annals Of Oncology 2012, 23: 2059-2064. PMID: 22241898, DOI: 10.1093/annonc/mdr569.Peer-Reviewed Original ResearchConceptsAnthracycline-based chemotherapyEarly breast cancerNuclear/cytoplasmic (N/C) ratioCytoplasmic ratioAdjuvant chemotherapyHazard ratioBreast cancerP27 expressionNuclear expressionAdjusted hazard ratioNuclear p27 expressionAdjuvant polychemotherapyUntreated armPrognostic parametersTissue microarrayChemotherapyPatientsPredictive valueImmunofluorescence assaysQuantitative immunofluorescence assaysEfficacyP27CancerExpressionPolychemotherapy
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 study
2009
C-Raf Is Associated with Disease Progression and Cell Proliferation in a Subset of Melanomas
Jilaveanu LB, Zito CR, Aziz SA, Conrad PJ, Schmitz JC, Sznol M, Camp RL, Rimm DL, Kluger HM. C-Raf Is Associated with Disease Progression and Cell Proliferation in a Subset of Melanomas. Clinical Cancer Research 2009, 15: 5704-5713. PMID: 19737955, PMCID: PMC2763114, DOI: 10.1158/1078-0432.ccr-09-0198.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overBenzenesulfonatesCell Line, TumorCell ProliferationCell SurvivalCohort StudiesDisease ProgressionFemaleGene SilencingHumansIndolesMaleMelanomaMiddle AgedNevusNiacinamidePhenolsPhenylurea CompoundsProtein Kinase InhibitorsProto-Oncogene Proteins c-rafPyridinesRNA, Small InterferingSensitivity and SpecificitySkin NeoplasmsSorafenibYoung AdultConceptsExtracellular signal-regulated kinaseC-RafC-Raf expressionSubset of melanomasPhospho-c-RafSignal-regulated kinaseCell linesProtein kinase inhibitionMitogen-activated protein kinase inhibitionDecreased viabilityDecreased Bcl-2 expressionProtein kinaseCell signalingBcl-2 inhibitionRaf kinaseB-RafMelanoma cell linesPhospho-MEKSpecific siRNAsSitu protein expressionGW5074Major isoformsKinasePhospho-ERKBcl-2 expressionGrowth factor receptor-bound protein-7 (Grb7) as a prognostic marker and therapeutic target in breast cancer
Nadler Y, González AM, Camp RL, Rimm DL, Kluger HM, Kluger Y. Growth factor receptor-bound protein-7 (Grb7) as a prognostic marker and therapeutic target in breast cancer. Annals Of Oncology 2009, 21: 466-473. PMID: 19717535, PMCID: PMC2826097, DOI: 10.1093/annonc/mdp346.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorBlotting, WesternBreast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, LobularFemaleFluorescent Antibody TechniqueFollow-Up StudiesGRB7 Adaptor ProteinHumansImage Processing, Computer-AssistedMiddle AgedPrognosisReceptor, ErbB-2Survival RateTissue Array AnalysisTumor Cells, CulturedYoung AdultConceptsHER2/neuBreast cancerPrognostic markerHER2/neu-positive breast cancerGRB7 expressionHigh HER2/neuNeu-positive breast cancerHER2/neu overexpressionPrimary breast cancerBreast cancer patientsIndependent prognostic markerNode-positive subsetValuable prognostic markerProtein 7Cy5-conjugated antibodiesMultivariable analysisWorse prognosisEntire cohortCancer patientsNeu overexpressionTissue microarrayTherapeutic targetCancerNeuPatients
2008
High levels of vascular endothelial growth factor and its receptors (VEGFR-1, VEGFR-2, neuropilin-1) are associated with worse outcome in breast cancer
Ghosh S, Sullivan CA, Zerkowski MP, Molinaro AM, Rimm DL, Camp RL, Chung GG. High levels of vascular endothelial growth factor and its receptors (VEGFR-1, VEGFR-2, neuropilin-1) are associated with worse outcome in breast cancer. Human Pathology 2008, 39: 1835-1843. PMID: 18715621, PMCID: PMC2632946, DOI: 10.1016/j.humpath.2008.06.004.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorBreast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, LobularConnecticutFemaleFluorescent Antibody Technique, IndirectHumansImage Processing, Computer-AssistedImmunoenzyme TechniquesKaplan-Meier EstimateMiddle AgedNeuropilin-1Receptors, Vascular Endothelial Growth FactorSurvival RateTissue Array AnalysisVascular Endothelial Growth Factor AVascular Endothelial Growth Factor Receptor-1Vascular Endothelial Growth Factor Receptor-2Young AdultConceptsVascular endothelial growth factorEndothelial growth factorBreast cancerVEGFR-1Growth factorNeuropilin-1VEGFR-2Kaplan-Meier survival analysisBreast cancer tissue microarrayVascular endothelial growth factor receptorPrimary breast cancerStandard prognostic factorsEndothelial growth factor receptorPrimary breast adenocarcinomaCancer tissue microarrayTumor-specific expressionGrowth factor receptorPrognostic factorsPrognostic significancePrognostic valueWorse outcomesLarge cohortTissue microarraySurvival analysisSignificant association