2021
Impact of a randomized weight loss trial on breast tissue markers in breast cancer survivors.
Dieli-Conwright C, Harrigan M, Cartmel B, Chagpar A, Bai Y, Rimm D, Pusztai L, Lu L, Sanft T, Irwin M. Impact of a randomized weight loss trial on breast tissue markers in breast cancer survivors. Journal Of Clinical Oncology 2021, 39: e12501-e12501. DOI: 10.1200/jco.2021.39.15_suppl.e12501.Peer-Reviewed Original ResearchBreast cancer survivorsWeight loss interventionSerum insulin levelsCancer survivorsLoss interventionPercent body fatSerum levelsSerum biomarkersTissue biomarkersBody compositionMonth 6Insulin levelsBreast tissueBreast cancerInsulin receptorBody fatStage I breast cancerBreast tissue levelsI breast cancerWeight loss trialBreast tissue markersLevels of CD163Breast tissue biopsiesUsual careLifestyle intervention
2011
Quantitative assessment shows loss of antigenic epitopes as a function of pre-analytic variables
Bai Y, Tolles J, Cheng H, Siddiqui S, Gopinath A, Pectasides E, Camp RL, Rimm DL, Molinaro AM. Quantitative assessment shows loss of antigenic epitopes as a function of pre-analytic variables. Laboratory Investigation 2011, 91: 1253-1261. PMID: 21519325, PMCID: PMC3145004, DOI: 10.1038/labinvest.2011.75.Peer-Reviewed Original ResearchConceptsCore needle biopsyCold ischemic timePre-analytic variablesNeedle biopsyEstrogen receptorIschemic timeTumor resectionTumor resection specimensAntigenic lossResection specimensTissue biomarkersTotal AktBiopsyPhospho-AktQuantitative immunofluorescencePhospho-ERKPhospho-S6K1Antigenic epitopesTotal ERKResectionTotal proteinCytokeratinImmunological methodsAntigenicitySignificant changes
2010
Multiplexed Assessment of the Southwest Oncology Group-Directed Intergroup Breast Cancer Trial S9313 by AQUA Shows that Both High and Low Levels of HER2 Are Associated with Poor Outcome
Harigopal M, Barlow WE, Tedeschi G, Porter PL, Yeh IT, Haskell C, Livingston R, Hortobagyi GN, Sledge G, Shapiro C, Ingle JN, Rimm DL, Hayes DF. Multiplexed Assessment of the Southwest Oncology Group-Directed Intergroup Breast Cancer Trial S9313 by AQUA Shows that Both High and Low Levels of HER2 Are Associated with Poor Outcome. American Journal Of Pathology 2010, 176: 1639-1647. PMID: 20150438, PMCID: PMC2843456, DOI: 10.2353/ajpath.2010.090711.Peer-Reviewed Original ResearchConceptsDisease-free survivalEstrogen receptorContinuous variablesSouthwest Oncology GroupAQUA methodAC chemotherapyMenopausal statusNegative patientsOncology GroupNode statusSequential doxorubicinPoor outcomeTumor sizeProgesterone receptorPrognostic informationWorse outcomesTissue biomarkersTissue microarrayBiphasic effectP53 expressionPatientsHER2Low expressersDiagnostic approachMultiplexed assessment
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-2
2008
Quantitative Assessment of Tissue Biomarkers and Construction of a Model to Predict Outcome in Breast Cancer Using Multiple Imputation
Emerson JW, Dolled-Filhart M, Harris L, Rimm DL, Tuck DP. Quantitative Assessment of Tissue Biomarkers and Construction of a Model to Predict Outcome in Breast Cancer Using Multiple Imputation. Cancer Informatics 2008, 7: cin.s911. PMID: 19352457, PMCID: PMC2664700, DOI: 10.4137/cin.s911.Peer-Reviewed Original ResearchLymph node statusProtein expression levelsNode statusBreast cancerBaseline clinical modelCohort of patientsLack of tumorTissue microarray studyLarge independent cohortsExpression levelsMultiple imputationPatient survivalTraining cohortTissue biomarkersIndependent cohortClinical modelSelect markersCohortSimilar improvementsBiomarker analysisCancerClinical annotationProtein markersBiomarkersFuture studies
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
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 natureMelanomaQuantitative 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