2025
Transcriptomic landscape of Kaposi sarcoma: Insights into therapeutic targeting of KSHV.
Fei Y, Costa P, Junejo M, Li M, Perry C, Damsky W, Ishizuka J. Transcriptomic landscape of Kaposi sarcoma: Insights into therapeutic targeting of KSHV. Journal Of Clinical Oncology 2025, 43 DOI: 10.1200/jco.2025.43.16_suppl.e23526.Peer-Reviewed Original ResearchKaposi's sarcoma herpesvirusKaposi's sarcomaTranscripts Per MillionKSHV genomeHIV statusPresence of Kaposi’s sarcoma herpesvirusDisease progressionLatency-associated regionExpressed genesHistory of organ transplantationVirus-associated tumorsTherapeutic targetFormalin-fixed paraffin-embedded (FFPEGene expressionParaffin-embedded (FFPEHuman herpesvirus 8Differential gene expression analysisDisseminated diseaseViral eradicationViral gene expressionHIV-positiveBaseline characteristicsHHV-8Gene expression analysisTumor morphologyThe dynamic role of ufmylation in endothelium
Lee C, Sibley J, Dai C, Li H, Su H, Li J. The dynamic role of ufmylation in endothelium. Physiology 2025, 40: 0746. DOI: 10.1152/physiol.2025.40.s1.0746.Peer-Reviewed Original ResearchUbiquitin-fold modifier 1Bulk RNA sequencingHuman umbilical vein endothelial cellsEndothelial cellsUbiquitin-like proteinDisrupt blood vessel formationCdh5-Cre miceAssociated with coronary artery diseaseVascular developmentCoronary artery diseaseProtein substratesRegulate vascular toneGene setsUFL1UfmylationExpressed genesBulk-RNAEnzymatic cascadeModifier 1Umbilical vein endothelial cellsCell cycleECKO miceCell homeostasisImpaired cell viabilityEndothelial cell homeostasisInfection-relevant conditions dictate differential versus coordinate expression of Salmonella chaperones and cochaperones
Chan C, Mukai K, Groisman E. Infection-relevant conditions dictate differential versus coordinate expression of Salmonella chaperones and cochaperones. MBio 2025, 16: e00227-25. PMID: 40162747, PMCID: PMC12077118, DOI: 10.1128/mbio.00227-25.Peer-Reviewed Original ResearchConceptsInfection-relevant conditionsJ-domainProtein homeostasisChaperone DnaKCytoplasmic MgMolecular chaperonesNucleotide exchange factor GrpEChaperone trigger factorSigma factor RpoHProteins co-translationallyExpression of molecular chaperonesPreventing protein aggregationIncreased mRNA amountsPerturb protein homeostasisMRNA amountsCochaperone DnaJRpoH proteinCo-translationallyPost-translationallyCochaperoneExpressed genesFolded proteinsDnaKCoordinated expressionChaperoneProspective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma
Biswas D, Liu Y, Herrero J, Wu Y, Moore D, Karasaki T, Grigoriadis K, Lu W, Veeriah S, Naceur-Lombardelli C, Magno N, Ward S, Frankell A, Hill M, Colliver E, de Carné Trécesson S, East P, Malhi A, Snell D, O’Neill O, Leonce D, Mattsson J, Lindberg A, Micke P, Moldvay J, Megyesfalvi Z, Dome B, Fillinger J, Nicod J, Downward J, Szallasi Z, Hackshaw A, Jamal-Hanjani M, Kanu N, Birkbak N, Swanton C. Prospective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma. Nature Cancer 2025, 6: 86-101. PMID: 39789179, PMCID: PMC11779643, DOI: 10.1038/s43018-024-00883-1.Peer-Reviewed Original ResearchConceptsLung adenocarcinomaStage I diseaseClinicopathological risk factorsSurvival of patientsResponse to treatmentRNA sequencing dataI diseaseSequence dataMetastatic clonesNeedle biopsyIndividual tumorsLung expressionTranscription signalsPrognostic informationWhole exomeExpressed genesChemotherapy sensitivityProspective validationSurvival associationsTranscriptomic heterogeneityHuman tumorsEvolutionary measuresChromosomal instabilityRisk factorsNatural history
2024
Single-cell transcriptomic and proteomic analysis of Parkinson’s disease brains
Zhu B, Park J, Coffey S, Russo A, Hsu I, Wang J, Su C, Chang R, Lam T, Gopal P, Ginsberg S, Zhao H, Hafler D, Chandra S, Zhang L. Single-cell transcriptomic and proteomic analysis of Parkinson’s disease brains. Science Translational Medicine 2024, 16: eabo1997. PMID: 39475571, PMCID: PMC12372474, DOI: 10.1126/scitranslmed.abo1997.Peer-Reviewed Original ResearchConceptsProteomic analysisAlzheimer's diseasePrefrontal cortexBrain cell typesGenetics of PDParkinson's diseaseCell-cell interactionsChaperone expressionSingle-nucleus transcriptomesExpressed genesTranscriptional changesPostmortem human brainPostmortem brain tissueDiseased brainSynaptic proteinsSingle-cellDown-regulationBrain cell populationsBrain regionsCell typesNeurodegenerative disordersLate-stage PDParkinson's disease brainsDisease etiologyNeuronal vulnerabilityComparative Analysis of Fecal Microbiota Between Adolescents with Early-Onset Psychosis and Adults with Schizophrenia
Nuncio-Mora L, Nicolini H, Lanzagorta N, García-Jaimes C, Sosa-Hernández F, González-Covarrubias V, Cabello-Rangel H, Sarmiento E, Glahn D, Genis-Mendoza A. Comparative Analysis of Fecal Microbiota Between Adolescents with Early-Onset Psychosis and Adults with Schizophrenia. Microorganisms 2024, 12: 2071. PMID: 39458380, PMCID: PMC11510430, DOI: 10.3390/microorganisms12102071.Peer-Reviewed Original ResearchEarly-onset psychosisPsychiatric disordersAtypical antipsychotic treatmentNon-psychotic individualsTreated with sertralineAntipsychotic treatmentSchizophrenia groupSchizophrenia patientsSchizophreniaGut-brain axisPsychosisGene orthology analysisPotential metabolic functionsAssociated with gut dysbiosisFunctional prediction analysisValproate treatmentPharmacological treatmentOscillospiraceae familiesOrthology analysisDecreased levelsFatty acid metabolismGut microbiomeExpressed genesMicrobial communitiesMicrobial compositionPredicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs
Song T, Cosatto E, Wang G, Kuang R, Gerstein M, Min M, Warrell J. Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs. Bioinformatics 2024, 40: ii111-ii119. PMID: 39230702, PMCID: PMC11373608, DOI: 10.1093/bioinformatics/btae383.Peer-Reviewed Original ResearchConceptsGene expressionSpatial gene expressionSpatial transcriptomics technologiesTissue histology imagesExpressed genesGene activationTranscriptomic technologiesMolecular underpinningsGraph neural networksState-of-the-artSpatial expressionGenesTissue architectureExpressionHistological imagesNeural networkExpression and prognostic value of cell‐cycle‐associated genes in lung squamous cell carcinoma
Xu X, Jin K, Xu X, Yang Y, Zhou B. Expression and prognostic value of cell‐cycle‐associated genes in lung squamous cell carcinoma. The Journal Of Gene Medicine 2024, 26: e3735. PMID: 39171952, DOI: 10.1002/jgm.3735.Peer-Reviewed Original ResearchConceptsCell cycle-associated genesLung squamous carcinomaCell cycleMRNA expression dataGene expression profilesAssociated with positive prognosisCause of cancer-related deathExpression dataCancer Genome AtlasExpressed genesSquamous cell carcinomaLung squamous cell carcinomaTargeted therapy trialsGroup of patientsCancer-related deathsExpression of CDK4GenesExpression trendsExpression profilesMolecular studiesGenome AtlasSquamous carcinomaCell carcinomaPathological stagePrognostic valueLung Transcriptomics Links Emphysema to Barrier Dysfunction and Macrophage Subpopulations.
Lu R, Gregory A, Suryadevara R, Xu Z, Jain D, Morrow J, Hobbs B, Yun J, Lichtblau N, Chase R, Curtis J, Sauler M, Bartholmai B, Silverman E, Hersh C, Castaldi P, Boueiz A. Lung Transcriptomics Links Emphysema to Barrier Dysfunction and Macrophage Subpopulations. American Journal Of Respiratory And Critical Care Medicine 2024, 211: 75-90. PMID: 38935868, PMCID: PMC11755365, DOI: 10.1164/rccm.202305-0793oc.Peer-Reviewed Original ResearchRNA sequencing dataAlternative splicingExpressed genesFunctional pathwaysCell typesBiological pathwaysGene expressionTranscriptomic featuresGene regulatory processesDysregulated pathwaysSingle-cell RNA sequencing dataRNA-seq analysisLung cell typesLung Tissue Research ConsortiumTranscriptome analysisGenesCell-typeDifferential expressionMultiple lung cell typesPathway activationTranscriptomic signaturesPathway dysregulationRegulatory processesSplicingPathwayZika virus exists in enterocytes and enteroendocrine cells of the Aedes aegypti midgut
Chen T, Raduwan H, Marín-López A, Cui Y, Fikrig E. Zika virus exists in enterocytes and enteroendocrine cells of the Aedes aegypti midgut. IScience 2024, 27: 110353. PMID: 39055935, PMCID: PMC11269924, DOI: 10.1016/j.isci.2024.110353.Peer-Reviewed Original ResearchAedes aegypti midgutEnteroendocrine cellsSingle-cell RNA sequencingIntestinal stem cellsVirus infectionPathogen interactionsExpressed genesRNA sequencingCopy numberTranscriptomic changesFunctional studiesInfected cellsZika virus infectionEnteroendocrineBlood digestionRNA copy numberCellular levelCell processesGenesMidgutPotential targetCell clustersCellsEnterocytesViral infectionCorrelation of hormone receptor positive HER2-negative/MammaPrint high-2 breast cancer with triple negative breast cancer: Results from gene expression data from the ISPY2 trial.
Rios-Hoyo A, Xiong K, Marczyk M, García-Millán R, Wolf D, Huppert L, Nanda R, Yau C, Hirst G, van 't Veer L, Esserman L, Pusztai L. Correlation of hormone receptor positive HER2-negative/MammaPrint high-2 breast cancer with triple negative breast cancer: Results from gene expression data from the ISPY2 trial. Journal Of Clinical Oncology 2024, 42: 573-573. DOI: 10.1200/jco.2024.42.16_suppl.573.Peer-Reviewed Original ResearchGene expression dataGene expression analysisExpression dataExpressed genesExpression analysisTriple-negativeDistance analysisPathway analysisDifferential gene expression analysisCell cycle pathwayGene Set Enrichment AnalysisBreast cancerIngenuity Pathway AnalysisRate of pathological complete responseHigh-risk stage IIGlucocorticoid receptor signalingTriple negative breast cancerCycle pathwayPathological complete responseDNA repairEnrichment analysisOptimal treatment strategyNegative breast cancerI-SPY2 trialGenesEzrin drives adaptation of monocytes to the inflamed lung microenvironment.
Gudneppanavar R, Di Pietro C, Oez H, Zhang P, Huang P, Braga C, Tebaldi T, Biancon G, Kim C, Gonzalez A, Halene S, Krause D, Egan M, Gupta N, Murray T, Bruscia E. Ezrin drives adaptation of monocytes to the inflamed lung microenvironment. The Journal Of Immunology 2024, 212: 0078_5418-0078_5418. DOI: 10.4049/jimmunol.212.supp.0078.5418.Peer-Reviewed Original ResearchRNA-seqActin-binding protein ezrinF-actin distributionImmune response to bacteriaCystic fibrosisIn vitro functional studiesResponse to bacteriaIncreased expression of pro-inflammatory markersCytoskeleton rearrangementF-actinResponse to lung infectionExpressed genesProtein ezrinTranscriptional profilesExpression of pro-inflammatory markersPlasma membranePro-inflammatory markersFunctional studiesEzrinLung extracellular matrixCF miceExtracellular matrixWT micePI3K/Akt signalingLung infectionInterleukin-7-based identification of liver lymphatic endothelial cells reveals their unique structural features
Yang Y, Jeong J, Su T, Lai S, Zhang P, Garcia-Milian R, Graham M, Liu X, McConnell M, Utsumi T, Pereira J, Iwakiri Y. Interleukin-7-based identification of liver lymphatic endothelial cells reveals their unique structural features. JHEP Reports 2024, 6: 101069. PMID: 38966234, PMCID: PMC11222939, DOI: 10.1016/j.jhepr.2024.101069.Peer-Reviewed Original ResearchCell surface structuresLymphatic endothelial cellsPublished single-cell RNA-sequencingRNA-seq analysisScRNA-seq analysisSingle-cell RNA sequencingLymphatic systemEndothelial cellsInterleukin-7RNA-seqScRNA-seqExpressed genesRNA sequencingTranscriptomic changesLow abundanceI/R liver injuryGenesIsolation protocolLiver cell typesCell typesIsolation methodLiver of miceHuman liver specimensHeterozygous miceMouse liver
2022
Transcription factor antagonism regulates heterogeneity in embryonic stem cell states
Hu S, Metcalf E, Mahat D, Chan L, Sohal N, Chakraborty M, Hamilton M, Singh A, Singh A, Lees J, Sharp P, Garg S. Transcription factor antagonism regulates heterogeneity in embryonic stem cell states. Molecular Cell 2022, 82: 4410-4427.e12. PMID: 36356583, PMCID: PMC9722640, DOI: 10.1016/j.molcel.2022.10.022.Peer-Reviewed Original ResearchConceptsGene expression heterogeneityMurine embryonic stem cellsCell statesGeneration of diverse cell typesExpression heterogeneityCell-type identityDiverse cell typesEmbryonic stem cell stateChromatin programmingStem cell stateTranscribed enhancersDevelopmental robustnessTranscription factor KLF4Expressed genesTranscription processDampened variationsGene expressionEmbryonic stem cellsGenesRegulatory programsPositive feedback networkCell typesZfp281CO bindingKinetics of switching
2018
CTCF maintains regulatory homeostasis of cancer pathways
Aitken S, Ibarra-Soria X, Kentepozidou E, Flicek P, Feig C, Marioni J, Odom D. CTCF maintains regulatory homeostasis of cancer pathways. Genome Biology 2018, 19: 106. PMID: 30086769, PMCID: PMC6081938, DOI: 10.1186/s13059-018-1484-3.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBreast NeoplasmsCCCTC-Binding FactorCell LineChromatinDNA, NeoplasmEnhancer Elements, GeneticFemaleFibroblastsGene Expression Regulation, NeoplasticGenomeHemizygoteHomeostasisHumansLiver Neoplasms, ExperimentalMiceMice, Inbred C57BLMice, TransgenicProtein BindingSignal TransductionUterine NeoplasmsConceptsTranscriptional regulationIntra-TAD interactionsSteady-state gene expressionCancer-related pathwaysMammalian genomesCTCF occupancyGenome functionChromatin loopsEvolutionary conservationChromatin structureGenomic dysregulationRegulatory domainHemizygous cellsEpigenomic profilingCTCFCTCF expressionMammalian cellsExpressed genesAffinity binding eventsTranscriptional alterationsGene expressionMouse lineagesCancer pathwaysMouse model systemHuman cancers
2017
Transcriptomic Analysis of Octanoic Acid Response in Drosophila sechellia Using RNA-Sequencing
Lanno S, Gregory S, Shimshak S, Alverson M, Chiu K, Feil A, Findley M, Forman T, Gordon J, Ho J, Krupp J, Lam I, Lane J, Linde S, Morse A, Rusk S, Ryan R, Saniee A, Sheth R, Siranosian J, Sirichantaropart L, Sternlieb S, Zaccardi C, Coolon J. Transcriptomic Analysis of Octanoic Acid Response in Drosophila sechellia Using RNA-Sequencing. G3: Genes, Genomes, Genetics 2017, 7: 3867-3873. PMID: 29021218, PMCID: PMC5714484, DOI: 10.1534/g3.117.300297.Peer-Reviewed Original ResearchConceptsQuantitative trait lociOA resistanceGene expression analysisGene OntologyResistance genesRNA sequencingRNA interferenceExpression analysisConsistent with previous functional studiesFunctional studiesGene family membersAnnotated orthologsDrosophila sechelliaEffect lociRNA-seqLevels of octanoic acidTrait lociCuticle developmentDefense responsesExpressed genesToxic fruitsTranscriptome analysisDownregulated genesUpregulated genesGenes
2007
Different Evolutionary Histories of the Two Classical Class I Genes BF1 and BF2 Illustrate Drift and Selection within the Stable MHC Haplotypes of Chickens
Shaw I, Powell T, Marston D, Baker K, van Hateren A, Riegert P, Wiles M, Milne S, Beck S, Kaufman J. Different Evolutionary Histories of the Two Classical Class I Genes BF1 and BF2 Illustrate Drift and Selection within the Stable MHC Haplotypes of Chickens. The Journal Of Immunology 2007, 178: 5744-5752. PMID: 17442958, DOI: 10.4049/jimmunol.178.9.5744.Peer-Reviewed Original ResearchConceptsClass I genesI geneChicken MHCChicken MHC haplotypesResistance to infectious pathogensLong-distance PCRMHC haplotypesPatterns of descentGenome organizationBF2 genesEvolutionary historyClass II BExpressed genesSite deletionHaplotypesNeutral changesB12 haplotypeGenesDendrogramWell-expressedChickenInfectious pathogensBF1Response to vaccinationClass I molecules
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply