2024
Gene trajectory inference for single-cell data by optimal transport metrics
Qu R, Cheng X, Sefik E, Stanley III J, Landa B, Strino F, Platt S, Garritano J, Odell I, Coifman R, Flavell R, Myung P, Kluger Y. Gene trajectory inference for single-cell data by optimal transport metrics. Nature Biotechnology 2024, 43: 258-268. PMID: 38580861, PMCID: PMC11452571, DOI: 10.1038/s41587-024-02186-3.Peer-Reviewed Original ResearchGene dynamicsGene programTrajectory inferenceBiological processesCell-cell graphDynamics of genesCell trajectory inferenceSingle-cell RNA sequencingSingle-cell dataCell state transitionsMyeloid lineage maturationDynamics of biological processesGene distributionRNA sequencingPseudotemporal orderingGene processingTrajectories of cellsGenesActivity of biological processesTechnical noiseGroups of cellsLineage maturationCellsConstruct cellsSequence
2023
IL-6 trans-signaling in a humanized mouse model of scleroderma
Odell I, Agrawal K, Sefik E, Odell A, Caves E, Kirkiles-Smith N, Horsley V, Hinchcliff M, Pober J, Kluger Y, Flavell R. IL-6 trans-signaling in a humanized mouse model of scleroderma. Proceedings Of The National Academy Of Sciences Of The United States Of America 2023, 120: e2306965120. PMID: 37669366, PMCID: PMC10500188, DOI: 10.1073/pnas.2306965120.Peer-Reviewed Original ResearchConceptsBone marrow-derived immune cellsIL-6Human hematopoietic stem cellsImmune cellsT cellsScleroderma skinSoluble IL-6 receptorCD8 T cellsHumanized mouse modelPathogenesis of sclerodermaMesenchymal cellsFibroblast-derived IL-6IL-6 receptorIL-6 signalingT cell activationHuman IL-6Human T cellsExpression of collagenFibrosis improvementPansclerotic morpheaHuman endothelial cellsHumanized miceReduced markersSkin graftsHuman CD4Humanized mouse liver reveals endothelial control of essential hepatic metabolic functions
Kaffe E, Roulis M, Zhao J, Qu R, Sefik E, Mirza H, Zhou J, Zheng Y, Charkoftaki G, Vasiliou V, Vatner D, Mehal W, AlcHepNet, Kluger Y, Flavell R. Humanized mouse liver reveals endothelial control of essential hepatic metabolic functions. Cell 2023, 186: 3793-3809.e26. PMID: 37562401, PMCID: PMC10544749, DOI: 10.1016/j.cell.2023.07.017.Peer-Reviewed Original ResearchConceptsMetabolic functionsSpecies-specific interactionsKey metabolic functionsCell-autonomous mechanismsNon-alcoholic fatty liver diseaseMajor metabolic hubNon-parenchymal cellsMetabolic hubHuman hepatocytesMicroenvironmental regulationHuman diseasesHuman-specific aspectsHuman pathologiesHomeostatic processesSpecies mismatchCholesterol uptakeFatty liver diseaseParacrine mannerHuman immuneBile acid conjugationSinusoidal endothelial cellsHepatic metabolic functionMouse liverEndothelial cellsCellsAutologous humanized PDX modeling for immuno-oncology recapitulates features of the human tumor microenvironment
Chiorazzi M, Martinek J, Krasnick B, Zheng Y, Robbins K, Qu R, Kaufmann G, Skidmore Z, Juric M, Henze L, Brösecke F, Adonyi A, Zhao J, Shan L, Sefik E, Mudd J, Bi Y, Goedegebuure S, Griffith M, Griffith O, Oyedeji A, Fertuzinhos S, Garcia-Milian R, Boffa D, Detterbeck F, Dhanasopon A, Blasberg J, Judson B, Gettinger S, Politi K, Kluger Y, Palucka K, Fields R, Flavell R. Autologous humanized PDX modeling for immuno-oncology recapitulates features of the human tumor microenvironment. Journal For ImmunoTherapy Of Cancer 2023, 11: e006921. PMID: 37487666, PMCID: PMC10373695, DOI: 10.1136/jitc-2023-006921.Peer-Reviewed Original ResearchConceptsHuman tumor microenvironmentTumor microenvironmentTumor-immune interactionsSolid tumorsAdaptive immune activationAdaptive immune populationsIndividual tumor microenvironmentsPatient's hematopoietic systemPatient-derived xenograft tissuesVascular endothelial growth factorBone marrow hematopoietic stemBone marrow aspiratePreclinical drug testingEndothelial growth factorHematopoietic systemAutologous tumorPDX modelingPDX miceImmune activationImmune populationsMarrow aspiratesAutologous systemIndividual patientsLittermate controlsPreclinical predictions
2021
Detection of differentially abundant cell subpopulations in scRNA-seq data
Zhao J, Jaffe A, Li H, Lindenbaum O, Sefik E, Jackson R, Cheng X, Flavell RA, Kluger Y. Detection of differentially abundant cell subpopulations in scRNA-seq data. Proceedings Of The National Academy Of Sciences Of The United States Of America 2021, 118: e2100293118. PMID: 34001664, PMCID: PMC8179149, DOI: 10.1073/pnas.2100293118.Peer-Reviewed Original ResearchMeSH KeywordsAgingB-LymphocytesBrainCell LineageCOVID-19CytokinesDatasets as TopicDendritic CellsGene Expression ProfilingGene Expression RegulationHigh-Throughput Nucleotide SequencingHumansMelanomaMonocytesPhenotypeRNA, Small CytoplasmicSARS-CoV-2Severity of Illness IndexSingle-Cell AnalysisSkin NeoplasmsT-LymphocytesTranscriptomeConceptsDA subpopulationsIll COVID-19 patientsImmune checkpoint therapyCOVID-19 patientsSingle-cell RNA sequencing analysisCheckpoint therapyBrain tissueCell subpopulationsRNA sequencing analysisTime pointsSubpopulationsDiseased individualsDistinct phenotypesOriginal studyCell typesAbundant subpopulationSequencing analysisCellsDA measuresPhenotypeImportant differencesNonrespondersPatientsTherapy
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