2021
Automated 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
2020
Prospective multi-institutional evaluation of pathologist assessment of PD-L1 assays for patient selection in triple negative breast cancer
Reisenbichler ES, Han G, Bellizzi A, Bossuyt V, Brock J, Cole K, Fadare O, Hameed O, Hanley K, Harrison BT, Kuba MG, Ly A, Miller D, Podoll M, Roden AC, Singh K, Sanders MA, Wei S, Wen H, Pelekanou V, Yaghoobi V, Ahmed F, Pusztai L, Rimm DL. Prospective multi-institutional evaluation of pathologist assessment of PD-L1 assays for patient selection in triple negative breast cancer. Modern Pathology 2020, 33: 1746-1752. PMID: 32300181, PMCID: PMC8366569, DOI: 10.1038/s41379-020-0544-x.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerNegative breast cancerOverall percent agreementPD-L1Intraclass correlation coefficientBreast cancerAdvanced triple-negative breast cancerPD-L1 positive casesImmune cell stainingMultiple pathologistsPD-L1 scoringMulti-institutional evaluationLung cancer studiesAtezolizumab therapySP142 assaySP263 assaysPatient selectionSP263SP142US FoodDrug AdministrationPathologist's assessmentPositive casesReal-world settingPercent agreement
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 B
2011
Quantification of Hormone Receptors to Guide Adjuvant Therapy Choice in Early Breast Cancer: Better Methods Required for Improved Utility
Bartlett J, Rea D, Rimm DL. Quantification of Hormone Receptors to Guide Adjuvant Therapy Choice in Early Breast Cancer: Better Methods Required for Improved Utility. Journal Of Clinical Oncology 2011, 29: 3715-3716. PMID: 21810678, DOI: 10.1200/jco.2011.37.3704.Peer-Reviewed Original Research