2023
Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases
Chatziioannou E, Roßner J, Aung T, Rimm D, Niessner H, Keim U, Serna-Higuita L, Bonzheim I, Cuellar L, Westphal D, Steininger J, Meier F, Pop O, Forchhammer S, Flatz L, Eigentler T, Garbe C, Röcken M, Amaral T, Sinnberg T. Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases. EBioMedicine 2023, 93: 104644. PMID: 37295047, PMCID: PMC10363450, DOI: 10.1016/j.ebiom.2023.104644.Peer-Reviewed Original ResearchConceptsTumor-infiltrating lymphocytesMultiple Cox regressionMelanoma-specific survivalCox regressionTumor thicknessCutaneous melanomaPrimary melanomaAssessment of TILsPD-1 checkpoint inhibitionSignificant unfavourable prognostic factorLonger progression-free survivalDistant metastasis-free survivalSimple Cox regressionUnfavourable survival outcomeFirst-line therapyProgression-free survivalUnfavourable prognostic factorCutaneous melanoma patientsMetastasis-free survivalPresence of ulcerationPrimary cutaneous melanomaCox regression modelPrimary melanoma samplesPrimary tissuesOverall survival
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
2012
In situ measurement of miR-205 in malignant melanoma tissue supports its role as a tumor suppressor microRNA
Hanna JA, Hahn L, Agarwal S, Rimm DL. In situ measurement of miR-205 in malignant melanoma tissue supports its role as a tumor suppressor microRNA. Laboratory Investigation 2012, 92: 1390-1397. PMID: 22890556, PMCID: PMC3460033, DOI: 10.1038/labinvest.2012.119.Peer-Reviewed Original ResearchMeSH KeywordsAgedAnalysis of VarianceBiomarkers, TumorCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGp100 Melanoma AntigenHumansIn Situ HybridizationMaleMelanomaMicroRNAsMiddle AgedPrognosisRetrospective StudiesReverse Transcriptase Polymerase Chain ReactionRNA, NeoplasmS100 ProteinsSkin NeoplasmsTissue Array AnalysisConceptsMiR-205 levelsMiR-205 expressionMiR-205Shorter melanoma-specific survivalMelanoma-specific survivalMalignant melanoma tissuesPrimary melanoma specimensTypes of cancerImmunofluorescent assessmentBreslow depthAggressive tumorsWorse outcomesPrimary melanomaTumor suppressor miRNADiscovery cohortMelanoma specimensMultivariate analysisMelanoma tissuesQuantitative immunofluorescenceTumorsLow expressionHuman tumorsUse of miRNAsSuppressor miRNAAQUA method
2005
Automated Quantitative Analysis of Activator Protein-2α Subcellular Expression in Melanoma Tissue Microarrays Correlates with Survival Prediction
Berger AJ, Davis DW, Tellez C, Prieto VG, Gershenwald JE, Johnson MM, Rimm DL, Bar-Eli M. Automated Quantitative Analysis of Activator Protein-2α Subcellular Expression in Melanoma Tissue Microarrays Correlates with Survival Prediction. Cancer Research 2005, 65: 11185-11192. PMID: 16322269, DOI: 10.1158/0008-5472.can-05-2300.Peer-Reviewed Original ResearchConceptsAP-2 expressionM.D. Anderson Cancer CenterCytoplasmic expression levelsAnderson Cancer CenterAP-2 levelsProgression of melanomaMelanoma tissue microarrayClinicopathologic factorsRetrospective cohortMetastatic groupPrognostic significanceBreslow depthCancer CenterNevi groupPoor prognosisMetastatic melanomaPrimary tumorPrimary melanomaDiagnosis groupsTissue microarrayTumor growthMelanoma specimensMalignant transformationHuman melanomaMelanoma progression
2004
Automated Quantitative Analysis of HDM2 Expression in Malignant Melanoma Shows Association with Early-Stage Disease and Improved Outcome
Berger AJ, Camp RL, DiVito KA, Kluger HM, Halaban R, Rimm DL. Automated Quantitative Analysis of HDM2 Expression in Malignant Melanoma Shows Association with Early-Stage Disease and Improved Outcome. Cancer Research 2004, 64: 8767-8772. PMID: 15574789, DOI: 10.1158/0008-5472.can-04-1384.Peer-Reviewed Original ResearchConceptsMurine double minute 2Double minute 2Protein expressionMalignant melanomaMinute 2Early-stage diseaseTissue microarray cohortPotential tissue biomarkersCutaneous malignant melanomaValuable prognostic toolNormal skin samplesSkin cancer deathsMicroarray cohortAdvanced melanomaMetastatic lesionsCancer deathPrimary melanomaImproved outcomesExpression of HDM2Tissue biomarkersPrognostic toolBetter outcomesMelanoma lesionsAggressive natureMelanoma