2017
Calcium Sensor, NCS-1, Promotes Tumor Aggressiveness and Predicts Patient Survival
Moore LM, England A, Ehrlich BE, Rimm DL. Calcium Sensor, NCS-1, Promotes Tumor Aggressiveness and Predicts Patient Survival. Molecular Cancer Research 2017, 15: 942-952. PMID: 28275088, PMCID: PMC5500411, DOI: 10.1158/1541-7786.mcr-16-0408.Peer-Reviewed Original ResearchConceptsBreast cancer cellsNCS-1Breast cancer patient cohortsNCS-1 expressionLymph node statusCancer cellsShorter survival rateIndependent breast cancer cohortsCancer patient cohortsBreast cancer cohortMB-231 breast cancer cellsPaclitaxel-induced cell deathAggressive tumor phenotypeNeuronal model systemClinical outcomesClinicopathologic featuresNeuronal calcium sensor-1Node statusPatient cohortProgesterone receptorWorse outcomesBreast cancerCalcium-binding proteinsCancer cohortEstrogen receptor
2012
Can primary tumor markers of cancer-initiating cells predict lymph node positivity in breast cancer patients?
Chagpar A, Neumeister V, Lannin D, Rimm D. Can primary tumor markers of cancer-initiating cells predict lymph node positivity in breast cancer patients? Journal Of Clinical Oncology 2012, 30: 1121-1121. DOI: 10.1200/jco.2012.30.15_suppl.1121.Peer-Reviewed Original ResearchBreast cancer patientsLN statusCancer patientsLymphovascular invasionTumor sizeTumor markersPositive LNsPoor prognosisMedian numberPrimary tumor markersMedian patient ageMedian tumor sizeLymph node positivityLN-positive patientsLymph node statusOnly factorCancer initiating cellsCancer-initiating cellsLevels of CD44Axillary surgeryLN positivityNode positivityPatient agePositive patientsClinicopathologic data
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
2004
αB‐crystallin as a marker of lymph node involvement in breast carcinoma
Chelouche‐Lev D, Kluger HM, Berger AJ, Rimm DL, Price JE. αB‐crystallin as a marker of lymph node involvement in breast carcinoma. Cancer 2004, 100: 2543-2548. PMID: 15197794, DOI: 10.1002/cncr.20304.Peer-Reviewed Original ResearchConceptsLymph node involvementBreast carcinoma cell linesBreast carcinomaNode involvementCarcinoma cell linesHuman breast carcinoma cell lineLymph node negative breast carcinomaPrimary breast carcinoma specimensLymph node positive breast carcinomaNode-positive breast carcinomaNode-negative breast carcinomaCell linesAdvanced breast carcinomaLymph node statusPredictors of survivalAlphaB-crystallinClinical prognostic markersLymph node metastasisHigh nuclear gradePrimary breast carcinomaBreast carcinoma specimensNovel tumor markerHuman breast carcinomaAlphaB-crystallin expressionIntensity of expression
1998
Expression of c‐met is a strong independent prognostic factor in breast carcinoma
Ghoussoub R, Dillon D, D'Aquila T, Rimm E, Fearon E, Rimm D. Expression of c‐met is a strong independent prognostic factor in breast carcinoma. Cancer 1998, 82: 1513-1520. PMID: 9554529, DOI: 10.1002/(sici)1097-0142(19980415)82:8<1513::aid-cncr13>3.0.co;2-7.Peer-Reviewed Original ResearchConceptsBreast carcinomaIndependent predictorsStrong independent prognostic factorCox proportional hazards modelGrowth factorIndependent prognostic factorLymph node statusSubset of patientsInvasive ductal carcinomaUseful prognostic markerProportional hazards modelBreast tumor specimensHepatocyte growth factorNegative patientsPrognostic factorsAggressive diseaseDuctal carcinomaNode statusPrognostic valuePrognostic markerTumor specimensHazards modelPatientsPredictive valueSurvival rate