2024
Spatially Informed Gene Signatures for Response to Immunotherapy in Melanoma.
Aung T, Warrell J, Martinez-Morilla S, Gavrielatou N, Vathiotis I, Yaghoobi V, Kluger H, Gerstein M, Rimm D. Spatially Informed Gene Signatures for Response to Immunotherapy in Melanoma. Clinical Cancer Research 2024, 30: 3520-3532. PMID: 38837895, PMCID: PMC11326985, DOI: 10.1158/1078-0432.ccr-23-3932.Peer-Reviewed Original ResearchGene signatureResistance to immunotherapyResponse to immunotherapyPrediction of treatment outcomeResistant to treatmentAccurate prediction of treatment outcomePredictive of responseImmunotherapy outcomesMelanoma patientsMelanoma specimensValidation cohortPatient stratificationDiscovery cohortTreatment outcomesImmunotherapyMelanomaTumorPatientsCohortS100BOutcomesGene expression dataGenesCD68+macrophagesExpression data
2012
Quantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer
Agarwal S, Gertler FB, Balsamo M, Condeelis JS, Camp RL, Xue X, Lin J, Rohan TE, Rimm DL. Quantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer. Breast Cancer Research 2012, 14: r124. PMID: 22971274, PMCID: PMC3962029, DOI: 10.1186/bcr3318.Peer-Reviewed Original ResearchConceptsBreast cancer cohortBreast cancerPoor outcomeTumor cellsCancer cohortPoor disease-specific survivalDisease-specific deathDisease-specific survivalBreast cancer patientsIndependent prognostic markerIndependent breast cancer cohortsNon-invasive tumor cellsInvasive tumor cellsReceptor statusNode statusTumor sizeCancer patientsPrognostic markerSignificant associationCohortCancerIsoform expressionPatientsMetastasisOutcomes
2010
PMCA2 regulates apoptosis during mammary gland involution and predicts outcome in breast cancer
VanHouten J, Sullivan C, Bazinet C, Ryoo T, Camp R, Rimm DL, Chung G, Wysolmerski J. PMCA2 regulates apoptosis during mammary gland involution and predicts outcome in breast cancer. Proceedings Of The National Academy Of Sciences Of The United States Of America 2010, 107: 11405-11410. PMID: 20534448, PMCID: PMC2895115, DOI: 10.1073/pnas.0911186107.Peer-Reviewed Original ResearchConceptsPMCA2 expressionBreast cancerT47D breast cancer cellsIntracellular calcium levelsBreast cancer progressionBreast cancer cellsEpithelial cell apoptosisPoor outcomeIntracellular calciumCalcium levelsMammary gland involutionCancer progressionCell apoptosisCancer cellsMammary involutionApoptosisGland involutionCancerMammary epithelial cell apoptosisOutcomesPMCA2Triggers apoptosisApical surfaceExpressionOverexpression
2007
Melanophages reside in hypermelanotic, aberrantly glycosylated tumor areas and predict improved outcome in primary cutaneous malignant melanoma
Handerson T, Berger A, Harigopol M, Rimm D, Nishigori C, Ueda M, Miyoshi E, Taniguchi N, Pawelek J. Melanophages reside in hypermelanotic, aberrantly glycosylated tumor areas and predict improved outcome in primary cutaneous malignant melanoma. Journal Of Cutaneous Pathology 2007, 34: 679-686. PMID: 17696914, DOI: 10.1111/j.1600-0560.2006.00681.x.Peer-Reviewed Original ResearchConceptsCutaneous malignant melanomaPrimary cutaneous malignant melanomaImproved outcomesMalignant melanomaMelanoma cellsAnti-tumor roleMelanoma tissue microarrayFollow-upWorse outcomesPatient outcomesPoor survivalTissue microarrayBetter outcomesMyeloid cellsImmune systemMelanophagesTumor areaMelanomaCancer cellsMelanoma biologyOutcomesAberrant glycosylationCell typesCellsTumor region
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 Tissue Microarrays Reveals an Association between High Bcl-2 Expression and Improved Outcome in Melanoma
DiVito KA, Berger AJ, Camp RL, Dolled-Filhart M, Rimm DL, Kluger HM. Automated Quantitative Analysis of Tissue Microarrays Reveals an Association between High Bcl-2 Expression and Improved Outcome in Melanoma. Cancer Research 2004, 64: 8773-8777. PMID: 15574790, DOI: 10.1158/0008-5472.can-04-1387.Peer-Reviewed Original ResearchConceptsBcl-2 expressionHigh Bcl-2 expressionTissue microarrayMetastatic specimensResponse rateSmall cohortProgression-free survivalImproved response ratesLarge patient cohortMelanoma patientsClark levelEntire cohortBreslow depthClinical variablesPatient cohortMetastatic melanomaContinuous index scoreBetter outcomesIndex scoreMelanoma specimensCohortMelanomaBcl-2PatientsOutcomesX-TileA New Bio-Informatics Tool for Biomarker Assessment and Outcome-Based Cut-Point Optimization
Camp RL, Dolled-Filhart M, Rimm DL. X-TileA New Bio-Informatics Tool for Biomarker Assessment and Outcome-Based Cut-Point Optimization. Clinical Cancer Research 2004, 10: 7252-7259. PMID: 15534099, DOI: 10.1158/1078-0432.ccr-04-0713.Peer-Reviewed Original Research
2003
JAKs and STATs as Biomarkers of Disease
Dolled-Filhart M, Rimm D. JAKs and STATs as Biomarkers of Disease. 2003, 697-720. DOI: 10.1007/978-94-017-3000-6_44.Peer-Reviewed Original ResearchClinical practice todayPathways of tumorigenesisPrecise disease classificationPrognosticate outcomesClinical trialsDisease progressionDisease outcomeLarge cohortTumor specimensBiomarkers of diseaseSmall studyNew biomarkersPredictive valueBiomarker expressionHuman malignanciesPatient samplesLevel of expressionTherapeutic agentsTumor biomarkersTherapyProtein expressionBiomarkersPatientsOutcomesDisease
2002
Tissue microarray‐based analysis shows phospho‐β‐catenin expression in malignant melanoma is associated with poor outcome
Kielhorn E, Provost E, Olsen D, D'Aquila TG, Smith BL, Camp RL, Rimm DL. Tissue microarray‐based analysis shows phospho‐β‐catenin expression in malignant melanoma is associated with poor outcome. International Journal Of Cancer 2002, 103: 652-656. PMID: 12494474, DOI: 10.1002/ijc.10893.Peer-Reviewed Original ResearchConceptsMalignant melanomaTissue microarray-based studyTissue microarray-based analysisWorse overall survivalDepth of invasionImmuno-histochemical analysisPhospho-specific antibodiesPhospho-β-catenin expressionOverall survivalMetastatic lesionsPrimary lesionPoor outcomePrognostic markerMelanomaUnique subsetNuclear stainingAntibodiesCatenin antibodyMicroarray-based analysisLesionsOutcomesCatenin expressionSer33/37/Thr41Microarray-based studiesHuman tissuesSubjective Differences in Outcome Are Seen as a Function of the Immunohistochemical Method Used on a Colorectal Cancer Tissue Microarray
Chung GG, Kielhorn EP, Rimm DL. Subjective Differences in Outcome Are Seen as a Function of the Immunohistochemical Method Used on a Colorectal Cancer Tissue Microarray. Clinical Colorectal Cancer 2002, 1: 237-242. PMID: 12450422, DOI: 10.3816/ccc.2002.n.005.Peer-Reviewed Original ResearchConceptsTissue microarrayTissue sectionsColorectal cancer tissue microarraySemiquantitative grading systemColorectal cancer specimensCancer tissue microarrayPatient outcomesLarge cohortSubjective assessmentCancer specimensImmunohistochemical methodsGrading systemNuclear stainingPathology literatureProtein expressionTissue samplesCell preparationsExpression levelsBeta-catenin antibodyCurrent standardImmunohistochemistryCohortOutcomesApparent increaseExpression