2021
An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy
Perincheri S, Levi AW, Celli R, Gershkovich P, Rimm D, Morrow JS, Rothrock B, Raciti P, Klimstra D, Sinard J. An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy. Modern Pathology 2021, 34: 1588-1595. PMID: 33782551, PMCID: PMC8295034, DOI: 10.1038/s41379-021-00794-x.Peer-Reviewed Original ResearchConceptsMemorial Sloan-Kettering Cancer CenterCore biopsyPredictive valueDiagnostic accuracyProstate core needle biopsiesCore needle biopsySurgical pathology practiceNegative predictive valueProstate core biopsiesPositive predictive valueProstate cancer detectionStrong diagnostic accuracyPoor quality scansCancer detectionCancer CenterProstate biopsyLeading causeNeedle biopsyTransrectal approachProstate cancerProstatic adenocarcinomaProstate carcinomaBiopsyPathology practiceProstate
2015
Development and Clinical Validation of an In Situ Biopsy-Based Multimarker Assay for Risk Stratification in Prostate Cancer
Blume-Jensen P, Berman DM, Rimm DL, Shipitsin M, Putzi M, Nifong TP, Small C, Choudhury S, Capela T, Coupal L, Ernst C, Hurley A, Kaprelyants A, Chang H, Giladi E, Nardone J, Dunyak J, Loda M, Klein EA, Magi-Galluzzi C, Latour M, Epstein JI, Kantoff P, Saad F. Development and Clinical Validation of an In Situ Biopsy-Based Multimarker Assay for Risk Stratification in Prostate Cancer. Clinical Cancer Research 2015, 21: 2591-2600. PMID: 25733599, DOI: 10.1158/1078-0432.ccr-14-2603.Peer-Reviewed Original ResearchConceptsBiomarker risk scoreRisk scoreRisk groupsPredictive valueNational Comprehensive Cancer NetworkComprehensive Cancer NetworkCurrent risk stratification systemsIndependent prognostic informationRisk stratification systemProstate cancer aggressivenessRisk classification groupsAccurate risk predictionCoprimary endpointsFavorable pathologyAppropriate therapyCurative therapyRisk stratificationPathologic parametersPrognostic informationProstate biopsyProstate pathologyProstate cancerBlinded studyProstatectomy specimensCancer Network
2014
Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error
Shipitsin M, Small C, Choudhury S, Giladi E, Friedlander S, Nardone J, Hussain S, Hurley AD, Ernst C, Huang YE, Chang H, Nifong TP, Rimm DL, Dunyak J, Loda M, Berman DM, Blume-Jensen P. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. British Journal Of Cancer 2014, 111: 1201-1212. PMID: 25032733, PMCID: PMC4453845, DOI: 10.1038/bjc.2014.396.Peer-Reviewed Original ResearchMeSH KeywordsActininAgedAlkyl and Aryl TransferasesArea Under CurveBiomarkers, TumorBiopsy, Fine-NeedleCullin ProteinsDNA-Binding ProteinsFollow-Up StudiesHSP70 Heat-Shock ProteinsHumansImage Processing, Computer-AssistedMaleMembrane ProteinsMiddle AgedMitochondrial ProteinsNeoplasm GradingNeoplasm StagingPhosphorylationProstateProstatic NeoplasmsProteomicsRibosomal Protein S6RNA-Binding Protein FUSROC CurveSelection BiasSmad2 ProteinSmad4 ProteinTissue Array AnalysisVoltage-Dependent Anion Channel 1Y-Box-Binding Protein 1ConceptsProstate cancer aggressivenessCancer aggressivenessLarge patient cohortLow Gleason gradePatient cohortTumor microarrayLethal outcomeProstatectomy samplesGleason gradeSignificant overtreatmentBiopsy interpretationProstatectomy tissuePatient samplesBiopsy testsProteomic biomarkersCancer biomarker discoveryExpert pathologistsMarker signaturesTumor heterogeneityBiomarkersAggressivenessProtein biomarkersBiomarker discoveryQuantitative proteomics approach
2004
Quantitative Determination of Expression of the Prostate Cancer Protein α-Methylacyl-CoA Racemase Using Automated Quantitative Analysis (AQUA) A Novel Paradigm for Automated and Continuous Biomarker Measurements
Rubin MA, Zerkowski MP, Camp RL, Kuefer R, Hofer MD, Chinnaiyan AM, Rimm DL. Quantitative Determination of Expression of the Prostate Cancer Protein α-Methylacyl-CoA Racemase Using Automated Quantitative Analysis (AQUA) A Novel Paradigm for Automated and Continuous Biomarker Measurements. American Journal Of Pathology 2004, 164: 831-840. PMID: 14982837, PMCID: PMC1613273, DOI: 10.1016/s0002-9440(10)63171-9.Peer-Reviewed Original ResearchConceptsProstate cancerProstate tissue samplesAMACR protein expressionTissue samplesProtein expressionProstate tissueZ-scoreAcinar prostate cancerLow AMACR expressionΑ-Methylacyl-CoA racemaseTissue microarray samplesTissue microarray slidesBenign prostate tissueProgression tissue microarrayMetastatic tumor samplesTissue-based markersMost tissue samplesProstate tissue biomarkersProstate cancer biomarkersBenign prostate tissue samplesImmunohistochemical evaluationSeparation of tumorAMACR expressionTissue biomarkersTissue microarray