2019
BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis
Prasse A, Binder H, Schupp JC, Kayser G, Bargagli E, Jaeger B, Hess M, Rittinghausen S, Vuga L, Lynn H, Violette S, Jung B, Quast K, Vanaudenaerde B, Xu Y, Hohlfeld JM, Krug N, Herazo-Maya JD, Rottoli P, Wuyts WA, Kaminski N. BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2019, 199: 622-630. PMID: 30141961, PMCID: PMC6396865, DOI: 10.1164/rccm.201712-2551oc.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisAirway basal cellsChronic obstructive pulmonary diseaseObstructive pulmonary diseasePulmonary diseaseBAL cellsBasal cellsPulmonary fibrosisControl subjectsCell gene expressionIndependent IPF cohortsNine-gene signatureIPF cohortDerivation cohortClinical parametersRetrospective studyUnivariate analysisUnpredictable courseCell involvementDiscovery cohortGene expressionHealthy volunteersCox modelStage IIIFatal diseaseLCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data
Sun J, Herazo-Maya JD, Wang JL, Kaminski N, Zhao H. LCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data. Statistical Applications In Genetics And Molecular Biology 2019, 18: 20170060. PMID: 30759070, DOI: 10.1515/sagmb-2017-0060.Peer-Reviewed Original Research
2018
Gene correlation network analysis to identify regulatory factors in idiopathic pulmonary fibrosis
McDonough JE, Kaminski N, Thienpont B, Hogg JC, Vanaudenaerde BM, Wuyts WA. Gene correlation network analysis to identify regulatory factors in idiopathic pulmonary fibrosis. Thorax 2018, 74: 132. PMID: 30366970, PMCID: PMC6467239, DOI: 10.1136/thoraxjnl-2018-211929.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisLung functionPulmonary fibrosisExtensive pathological changesSevere lung diseaseLung Tissue Research ConsortiumCorrelation network analysisIPF cohortIPF groupLung diseaseControl subjectsUpregulated modulesT cellsImmune responsePathological changesLeucocyte activationB cellsClinical relevanceSurfactant metabolismDisease pathologyInterferon responseFibrosisBlood vesselsPathological processesGene correlation network analysisRegularized Latent Class Model for Joint Analysis of High-Dimensional Longitudinal Biomarkers and a Time-to-Event Outcome
Sun J, Herazo-Maya J, Molyneaux PL, Maher TM, Kaminski N, Zhao H. Regularized Latent Class Model for Joint Analysis of High-Dimensional Longitudinal Biomarkers and a Time-to-Event Outcome. Biometrics 2018, 75: 69-77. PMID: 30178494, DOI: 10.1111/biom.12964.Peer-Reviewed Original ResearchConceptsJoint latent class modelLongitudinal biomarkersExtensive simulation studyLatent class modelLongitudinal submodelJoint modeling methodSurvival submodelLikelihood approachSimulation studyClass modelEvent outcomesLatent classesModeling methodMembership modelRandom effectsModeling approachClassSubmodelsJoint analysisModelBootstrapUnique trajectoriesNovel biological insightsInference
2017
Lung Endothelial MicroRNA-1 Regulates Tumor Growth and Angiogenesis
Korde A, Jin L, Zhang JG, Ramaswamy A, Hu B, Kolahian S, Guardela BJ, Herazo-Maya J, Siegfried JM, Stabile L, Pisani MA, Herbst RS, Kaminski N, Elias JA, Puchalski JT, Takyar SS. Lung Endothelial MicroRNA-1 Regulates Tumor Growth and Angiogenesis. American Journal Of Respiratory And Critical Care Medicine 2017, 196: 1443-1455. PMID: 28853613, PMCID: PMC5736970, DOI: 10.1164/rccm.201610-2157oc.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerMiR-1 levelsLewis lung carcinoma xenograftsLung carcinoma xenograftsTransgenic miceEndothelial cellsNSCLC tumorsCarcinoma xenograftsLung endotheliumMiR-1Tumor growthTumor progressionVascular endothelial cadherin promoterMicroRNA-1Cohort of patientsTumor-bearing lungsCell lung cancerVascular endothelial growth factorCancer-free tissuesEndothelial growth factorInducible transgenic miceMiR-1 overexpressionKP miceOverall survivalTumor burdenModified mesenchymal stem cells using miRNA transduction alter lung injury in a bleomycin model
Huleihel L, Sellares J, Cardenes N, Álvarez D, Faner R, Sakamoto K, Yu G, Kapetanaki MG, Kaminski N, Rojas M. Modified mesenchymal stem cells using miRNA transduction alter lung injury in a bleomycin model. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2017, 313: l92-l103. PMID: 28385811, PMCID: PMC5538868, DOI: 10.1152/ajplung.00323.2016.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBiomarkersBleomycinBone Marrow CellsCollagenCytokinesDisease Models, AnimalFemaleGene Expression RegulationGene Regulatory NetworksHumansInterleukin-6Leukocyte Common AntigensLung InjuryMesenchymal Stem Cell TransplantationMesenchymal Stem CellsMice, Inbred C57BLMicroRNAsRNA, MessengerSurvival AnalysisTransduction, GeneticTransfectionWeight LossConceptsBone marrow-derived mesenchymal stem cellsMesenchymal stem cellsLung fibrosisLate administrationBleomycin modelMiR-154Different preclinical modelsStem cellsCD45-positive cellsMurine bleomycin modelMarrow-derived mesenchymal stem cellsInitial weight lossLower survival rateAshcroft scoreLung injuryBleomycin instillationFibrotic changesCytokine expressionMice groupsLung tissueOH-prolinePreclinical modelsProtective effectTreatment groupsSurvival rate
2015
A functional genomic model for predicting prognosis in idiopathic pulmonary fibrosis
Huang Y, Ma SF, Vij R, Oldham JM, Herazo-Maya J, Broderick SM, Strek ME, White SR, Hogarth DK, Sandbo NK, Lussier YA, Gibson KF, Kaminski N, Garcia JG, Noth I. A functional genomic model for predicting prognosis in idiopathic pulmonary fibrosis. BMC Pulmonary Medicine 2015, 15: 147. PMID: 26589497, PMCID: PMC4654815, DOI: 10.1186/s12890-015-0142-8.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisPrognostic indexIPF patientsPulmonary fibrosisValidation cohortTraining cohortMultivariate Cox regression survival analysisPrognostic modelPeripheral blood mononuclear cellsUnivariate Cox regression analysisCox regression survival analysisLow-risk patientsWeighted gene co-expression network analysisCox regression analysisBlood mononuclear cellsCourse of diseaseIndependent validation cohortRegression survival analysisNovel prognostic modelPredictor genesT cell biologyT cell receptorCurrent prognostic toolsFunctional pathway analysisFold change
2014
T-RECS: STABLE SELECTION OF DYNAMICALLY FORMED GROUPS OF FEATURES WITH APPLICATION TO PREDICTION OF CLINICAL OUTCOMES
Altman R, Dunker A, Hunter L, Ritchie M, Murray T, Klein T, HUANG G, TSAMARDINOS I, RAGHU V, KAMINSKI N, BENOS P. T-RECS: STABLE SELECTION OF DYNAMICALLY FORMED GROUPS OF FEATURES WITH APPLICATION TO PREDICTION OF CLINICAL OUTCOMES. Biocomputing 2014, 20: 431-42. PMID: 25592602, PMCID: PMC4299881, DOI: 10.1142/9789814644730_0041.Peer-Reviewed Original ResearchConceptsTraditional feature selection methodsFeature selection methodCohort of patientsPersonalized medicine strategiesReal expression dataFeature selectionClassification accuracyCluster selectionBiological datasetsClinical outcomesCluster featuresLung diseaseBreast cancerSelection methodPatient classificationStructured natureMedicine strategiesSurvival dataTarget variablesEfficient selectionCohortStable selectionImportant features
2013
Association Between the MUC5B Promoter Polymorphism and Survival in Patients With Idiopathic Pulmonary Fibrosis
Peljto AL, Zhang Y, Fingerlin TE, Ma SF, Garcia JG, Richards TJ, Silveira LJ, Lindell KO, Steele MP, Loyd JE, Gibson KF, Seibold MA, Brown KK, Talbert JL, Markin C, Kossen K, Seiwert SD, Murphy E, Noth I, Schwarz MI, Kaminski N, Schwartz DA. Association Between the MUC5B Promoter Polymorphism and Survival in Patients With Idiopathic Pulmonary Fibrosis. JAMA 2013, 309: 2232-2239. PMID: 23695349, PMCID: PMC4545271, DOI: 10.1001/jama.2013.5827.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisChicago cohortPulmonary fibrosisImproved survivalPromoter polymorphismInterstitial lung disease clinicMUC5B Promoter PolymorphismPrimary end pointNumber of patientsTT genotype groupCommon risk polymorphismsChicago patientsIPF mortalityMedian followCause mortalityCumulative incidenceMechanisms of diseaseDisease clinicRetrospective studyVital capacityClinical trialsBlood concentrationsClinical covariatesMAIN OUTCOMETreatment status
2012
Peripheral Blood Proteins Predict Mortality in Idiopathic Pulmonary Fibrosis
Richards TJ, Kaminski N, Baribaud F, Flavin S, Brodmerkel C, Horowitz D, Li K, Choi J, Vuga LJ, Lindell KO, Klesen M, Zhang Y, Gibson KF. Peripheral Blood Proteins Predict Mortality in Idiopathic Pulmonary Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2012, 185: 67-76. PMID: 22016448, PMCID: PMC3262037, DOI: 10.1164/rccm.201101-0058oc.Peer-Reviewed Original ResearchMeSH KeywordsAgedBiomarkersCell Adhesion MoleculesCohort StudiesEnzyme-Linked Immunosorbent AssayFemaleHumansIdiopathic Pulmonary FibrosisIntercellular Adhesion Molecule-1Interleukin-8MaleMatrix Metalloproteinase 1Matrix Metalloproteinase 7Matrix MetalloproteinasesPredictive Value of TestsProportional Hazards ModelsS100 ProteinsS100A12 ProteinSurvival AnalysisVascular Cell Adhesion Molecule-1ConceptsIdiopathic pulmonary fibrosisTransplant-free survivalPoor transplant-free survivalPoor progression-free survivalProgression-free survivalDerivation cohortIL-8ICAM-1MMP-7Overall survivalPulmonary fibrosisValidation cohortCox proportional hazards modelVascular cell adhesion moleculeAdhesion moleculesLethal lung diseaseBead-based multiplex assayPoor overall survivalRisk prediction scoreMultiplex bead-based immunoassayAssociation of biomarkersProportional hazards modelIntercellular adhesion moleculePrioritization of patientsPlasma proteins