2019
An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
Acs B, Ahmed FS, Gupta S, Wong P, Gartrell RD, Sarin Pradhan J, Rizk EM, Gould Rothberg BE, Saenger YM, Rimm DL. An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma. Nature Communications 2019, 10: 5440. PMID: 31784511, PMCID: PMC6884485, DOI: 10.1038/s41467-019-13043-2.Peer-Reviewed Original ResearchConceptsOpen sourceOpen source softwareSource softwareTIL scoreTraining setDisease-specific overall survivalHigh TIL scorePoor prognosis cohortsSubset of patientsAlgorithmIndependent prognostic markerBroad adoptionAssessment of tumorOverall survivalFavorable prognosisMelanoma patientsMultivariable analysisValidation cohortIndependent associationPrognostic markerSeparate patientsPrognostic variablesIndependent cohortRetrospective collectionMelanoma
2006
Evaluation of the Prognostic Value of Cellular Inhibitor of Apoptosis Protein in Epithelial Ovarian Cancer Using Automated Quantitative Protein Analysis
Psyrri A, Yu Z, Bamias A, Weinberger PM, Markakis S, Kowalski D, Camp RL, Rimm DL, Dimopoulos MA. Evaluation of the Prognostic Value of Cellular Inhibitor of Apoptosis Protein in Epithelial Ovarian Cancer Using Automated Quantitative Protein Analysis. Cancer Epidemiology Biomarkers & Prevention 2006, 15: 1179-1183. PMID: 16775178, DOI: 10.1158/1055-9965.epi-06-0120.Peer-Reviewed Original ResearchConceptsEpithelial ovarian cancerOvarian cancerPrognostic valuePaclitaxel-based combination chemotherapyOnly significant prognostic factorAdvanced stage ovarian cancerSignificant prognostic factorsOvarian cancer patientsProtein levelsImportant prognostic biomarkerMean followSurgical debulkingCombination chemotherapyOverall survivalPrognostic factorsClinical outcomesMultivariable analysisEntire cohortCancer patientsPrognostic biomarkerPrognostic variablesMembranous expressionApoptosis proteinSurvival rateCellular inhibitor
2005
Subcellular Localization and Protein Levels of Cyclin-Dependent Kinase Inhibitor p27 Independently Predict for Survival in Epithelial Ovarian Cancer
Psyrri A, Bamias A, Yu Z, Weinberger PM, Kassar M, Markakis S, Kowalski D, Efstathiou E, Camp RL, Rimm DL, Dimopoulos MA. Subcellular Localization and Protein Levels of Cyclin-Dependent Kinase Inhibitor p27 Independently Predict for Survival in Epithelial Ovarian Cancer. Clinical Cancer Research 2005, 11: 8384-8390. PMID: 16322299, DOI: 10.1158/1078-0432.ccr-05-1270.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorCell DifferentiationCohort StudiesCombined Modality TherapyCyclin-Dependent Kinase Inhibitor p27Cystadenocarcinoma, SerousFemaleHumansMiddle AgedNeoplasm StagingNeoplasms, Glandular and EpithelialOvarian NeoplasmsPrognosisSubcellular FractionsSurvival RateTissue Array AnalysisConceptsNuclear p27 expressionOvarian cancerP27 expression levelsOverall survivalP27 expressionPlatinum-paclitaxel combination chemotherapyAdvanced stage ovarian cancerDisease-free survivalSignificant prognostic factorsStage ovarian cancerEpithelial ovarian cancerValuable prognostic biomarkerExpression levelsP27 protein expressionCyclin-dependent kinase inhibitor p27Mean followSurgical debulkingCombination chemotherapyPrognostic factorsMultivariable analysisPrognostic valueImmunohistochemical assessmentPrognostic biomarkerPrognostic variablesImmunofluorescence-based method