Featured Publications
5‐Fluorouracil efficacy requires anti‐tumor immunity triggered by cancer‐cell‐intrinsic STING
Tian J, Zhang D, Kurbatov V, Wang Q, Wang Y, Fang D, Wu L, Bosenberg M, Muzumdar MD, Khan S, Lu Q, Yan Q, Lu J. 5‐Fluorouracil efficacy requires anti‐tumor immunity triggered by cancer‐cell‐intrinsic STING. The EMBO Journal 2021, 40: embj2020106065. PMID: 33615517, PMCID: PMC8013832, DOI: 10.15252/embj.2020106065.Peer-Reviewed Original ResearchConceptsAnti-tumor immunityTumor burdenSubsequent type I interferon productionHigh STING expressionIntratumoral T cellsT-cell depletionType I interferon productionI interferon productionLoss of STINGImmunocompetent hostsColorectal specimensT cellsSTING expressionBetter survivalHigh doseTherapeutic effectivenessHuman colorectal specimensMelanoma tumorsInterferon productionChemotherapeutic drugsMurine colonImmunityEfficacyStingsColonSingle-cell microRNA-mRNA co-sequencing reveals non-genetic heterogeneity and mechanisms of microRNA regulation
Wang N, Zheng J, Chen Z, Liu Y, Dura B, Kwak M, Xavier-Ferrucio J, Lu YC, Zhang M, Roden C, Cheng J, Krause DS, Ding Y, Fan R, Lu J. Single-cell microRNA-mRNA co-sequencing reveals non-genetic heterogeneity and mechanisms of microRNA regulation. Nature Communications 2019, 10: 95. PMID: 30626865, PMCID: PMC6327095, DOI: 10.1038/s41467-018-07981-6.Peer-Reviewed Original ResearchConceptsSame single cellMicroRNA-mRNASingle cellsGenome-scale analysisNon-genetic cellNon-genetic heterogeneityMultiple omic profilesGenomic approachesMicroRNA regulationMolecular regulationTarget mRNAsExpression variabilityCellular pathwaysRegulatory relationshipsLevels of microRNAsIntercellular heterogeneityOmics profilesIntercellular variabilityCell heterogeneityMRNA profilesMicroRNAsMRNACellsRegulationExpressionThe DNA Methylcytosine Dioxygenase Tet2 Sustains Immunosuppressive Function of Tumor-Infiltrating Myeloid Cells to Promote Melanoma Progression
Pan W, Zhu S, Qu K, Meeth K, Cheng J, He K, Ma H, Liao Y, Wen X, Roden C, Tobiasova Z, Wei Z, Zhao J, Liu J, Zheng J, Guo B, Khan SA, Bosenberg M, Flavell RA, Lu J. The DNA Methylcytosine Dioxygenase Tet2 Sustains Immunosuppressive Function of Tumor-Infiltrating Myeloid Cells to Promote Melanoma Progression. Immunity 2017, 47: 284-297.e5. PMID: 28813659, PMCID: PMC5710009, DOI: 10.1016/j.immuni.2017.07.020.Peer-Reviewed Original ResearchConceptsImmunosuppressive functionMyeloid cellsIntratumoral myeloid cellsNon-hematologic malignanciesMyeloid-specific deletionTumor-associated macrophagesReduced tumor growthTumor-promoting functionsProinflammatory onesMyD88 pathwayMelanoma patientsCell depletionEffector TRole of TET2Methylcytosine dioxygenase TET2Mouse modelIL-1RMelanoma growthTherapeutic targetTumor growthTET2 expressionMelanoma progressionHematopoietic malignanciesMalignancyTET2Novel determinants of mammalian primary microRNA processing revealed by systematic evaluation of hairpin-containing transcripts and human genetic variation
Roden C, Gaillard J, Kanoria S, Rennie W, Barish S, Cheng J, Pan W, Liu J, Cotsapas C, Ding Y, Lu J. Novel determinants of mammalian primary microRNA processing revealed by systematic evaluation of hairpin-containing transcripts and human genetic variation. Genome Research 2017, 27: 374-384. PMID: 28087842, PMCID: PMC5340965, DOI: 10.1101/gr.208900.116.Peer-Reviewed Original ResearchConceptsPri-miRNA processingHuman genetic variationGenetic variationPrimary sequence motifsPrimary microRNA processingMiRNA biogenesisDisease-causing mutationsPrimary miRNAsPri-miRNAsSequence motifsMiRNA hairpinsMicroRNA processingMature microRNAsSequence featuresRNA hairpinsComputational pipelineNovel determinantStem lengthUnpaired basesHairpinTranscriptsStemBiogenesisGenomeMiRNAsA Molecular Chipper technology for CRISPR sgRNA library generation and functional mapping of noncoding regions
Cheng J, Roden CA, Pan W, Zhu S, Baccei A, Pan X, Jiang T, Kluger Y, Weissman SM, Guo S, Flavell RA, Ding Y, Lu J. A Molecular Chipper technology for CRISPR sgRNA library generation and functional mapping of noncoding regions. Nature Communications 2016, 7: 11178. PMID: 27025950, PMCID: PMC4820989, DOI: 10.1038/ncomms11178.Peer-Reviewed Original ResearchAnimalsBacterial ProteinsCell LineChromosome MappingCloning, MolecularClustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Associated Protein 9DNADNA Restriction EnzymesEndonucleasesGene LibraryGenomeHumansMiceMicroRNAsOligonucleotide Array Sequence AnalysisRNA, Guide, CRISPR-Cas SystemsUntranslated Regions
2023
Ten-Eleven-Translocation Genes in Cancer
Wang Y, Wang X, Lu J. Ten-Eleven-Translocation Genes in Cancer. Cancer Treatment And Research 2023, 190: 363-373. PMID: 38113007, DOI: 10.1007/978-3-031-45654-1_11.Peer-Reviewed Original ResearchConceptsTET mutationsTen-ElevenBiochemical functionsTranslocation (TET) familyTranslocation geneHematopoietic malignanciesHematopoietic expansionGenesHuman cancersMutationsCritical roleImmune responseTET2Clonal hematopoiesisSolid cancersEpigenomeTET1TET3RNABiologyUnanswered questionsDNAHematopoiesisCooperateTETs
2022
Bile acid distributions, sex-specificity, and prognosis in colorectal cancer
Cai Y, Shen X, Lu L, Yan H, Huang H, Gaule P, Muca E, Theriot CM, Rattray Z, Rattray NJW, Lu J, Ahuja N, Zhang Y, Paty PB, Khan SA, Johnson CH. Bile acid distributions, sex-specificity, and prognosis in colorectal cancer. Biology Of Sex Differences 2022, 13: 61. PMID: 36274154, PMCID: PMC9590160, DOI: 10.1186/s13293-022-00473-9.Peer-Reviewed Original ResearchConceptsLeft-sided colon tumorsRight-sided colon tumorsColon cancer patientsColorectal cancerTumor locationBile acidsColon tumorsCancer patientsQuantitative immunofluorescencePrimary tumor locationImmune regulatory cellsRecurrence-free survivalBile acid metabolismSecondary bile acidsBile acid distributionBile acid analysisBackgroundBile acidsOverall survivalRegulatory cellsCRC patientsMale patientsPatient sexImmune cellsPatient prognosisImmune response
2021
Tet2 Controls the Responses of β cells to Inflammation in Autoimmune Diabetes
Rui J, Deng S, Perdigoto AL, Ponath G, Kursawe R, Lawlor N, Sumida T, Levine-Ritterman M, Stitzel ML, Pitt D, Lu J, Herold KC. Tet2 Controls the Responses of β cells to Inflammation in Autoimmune Diabetes. Nature Communications 2021, 12: 5074. PMID: 34417463, PMCID: PMC8379260, DOI: 10.1038/s41467-021-25367-z.Peer-Reviewed Original ResearchConceptsImmune cellsΒ-cellsNOD/SCID recipientsDiabetogenic immune cellsDiabetogenic T cellsBone marrow transplantType 1 diabetesExpression of TET2Human β-cellsIslet infiltratesSCID recipientsMarrow transplantInflammatory pathwaysTransfer of diseaseT cellsInflammatory genesImmune killingPathologic interactionsReduced expressionDiabetesInflammationTET2MiceRecipientsCells
2020
The mir181ab1 cluster promotes kras-driven oncogenesis and progression in lung and pancreas
Valencia K, Erice O, Kostyrko K, Hausmann S, Guruceaga E, Tathireddy A, Flores NM, Sayles LC, Lee AG, Fragoso R, Sun TQ, Vallejo A, Roman M, Entrialgo-Cadierno R, Migueliz I, Razquin N, Fortes P, Lecanda F, Lu J, Ponz-Sarvise M, Chen CZ, Mazur PK, Sweet-Cordero EA, Vicent S. The mir181ab1 cluster promotes kras-driven oncogenesis and progression in lung and pancreas. Journal Of Clinical Investigation 2020, 130: 1879-1895. PMID: 31874105, PMCID: PMC7108928, DOI: 10.1172/jci129012.Peer-Reviewed Original ResearchConceptsPotential therapeutic targetNew molecular targetsPancreatic cancerMouse modelTherapeutic targetHuman cancer cellsDownstream effector pathwaysKRASMolecular targetsCancerCancer cellsEffector pathwaysKey modulatorNonredundant roleLungProliferative advantageProgressionUnknown roleOncogenesisPhenotypePatientsTherapyPancreasMicroRNA cluster
2019
Digital Inference of Immune Microenvironment Reveals Low-Risk Subtype of Early Lung Adenocarcinoma
Kurbatov V, Balayev A, Saffarzadeh A, Heller DR, Boffa DJ, Blasberg JD, Lu J, Khan SA. Digital Inference of Immune Microenvironment Reveals Low-Risk Subtype of Early Lung Adenocarcinoma. The Annals Of Thoracic Surgery 2019, 109: 343-349. PMID: 31568747, DOI: 10.1016/j.athoracsur.2019.08.050.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinoma of LungAdultAgedCohort StudiesDatabases, FactualDisease-Free SurvivalFemaleHumansImmunotherapyKaplan-Meier EstimateLung NeoplasmsMaleMiddle AgedNeoplasm InvasivenessNeoplasm StagingPneumonectomyPrognosisProportional Hazards ModelsRetrospective StudiesRisk AssessmentSurvival AnalysisTumor MicroenvironmentConceptsTumor immune microenvironmentImmune microenvironmentLung adenocarcinomaOverall survivalRisk groupsMast cellsCox proportional hazard modelingEarly-stage lung adenocarcinomaLow-risk subtypesKaplan-Meier analysisPathological staging systemProportional hazard modelingImproved clinical outcomesCancer immune microenvironmentImmune cell typesEarly lung adenocarcinomaActivation stateClinical outcomesValidation cohortMacrophage contentStaging systemMultivariable modelCIBERSORT analysisPatientsClinical decisionSfold Tools for MicroRNA Target Prediction
Rennie W, Kanoria S, Liu C, Carmack CS, Lu J, Ding Y. Sfold Tools for MicroRNA Target Prediction. Methods In Molecular Biology 2019, 1970: 31-42. PMID: 30963486, DOI: 10.1007/978-1-4939-9207-2_3.Peer-Reviewed Original Research
2017
The cationic small molecule GW4869 is cytotoxic to high phosphatidylserine‐expressing myeloma cells
Vuckovic S, Vandyke K, Rickards DA, Winter P, Brown SHJ, Mitchell TW, Liu J, Lu J, Askenase PW, Yuriev E, Capuano B, Ramsland PA, Hill GR, Zannettino ACW, Hutchinson AT. The cationic small molecule GW4869 is cytotoxic to high phosphatidylserine‐expressing myeloma cells. British Journal Of Haematology 2017, 177: 423-440. PMID: 28211573, DOI: 10.1111/bjh.14561.Peer-Reviewed Original ResearchConceptsMyeloma cell linesMyeloma cellsMyeloma plasma cellsCell linesPlasma cellsPrimary myeloma samplesMalignant cellsMyeloma samplesGW4869Surface phosphatidylserine exposurePhosphatidylserine expressionPhosphatidylserine exposureCell surface phosphatidylserine exposureCellsBiochemical analysisCytotoxicSmall cationic moleculesIntracellular sidePhosphatidylserineCancerCell membraneSmall moleculesBrefeldin A
2016
Regulation of the DNA Methylation Landscape in Human Somatic Cell Reprogramming by the miR-29 Family
Hysolli E, Tanaka Y, Su J, Kim KY, Zhong T, Janknecht R, Zhou XL, Geng L, Qiu C, Pan X, Jung YW, Cheng J, Lu J, Zhong M, Weissman SM, Park IH. Regulation of the DNA Methylation Landscape in Human Somatic Cell Reprogramming by the miR-29 Family. Stem Cell Reports 2016, 7: 43-54. PMID: 27373925, PMCID: PMC4945581, DOI: 10.1016/j.stemcr.2016.05.014.Peer-Reviewed Original ResearchConceptsDNA methylation stateEmbryonic stem cellsInduced pluripotent stem cellsHuman somatic cell reprogrammingSomatic cell reprogrammingMethylation stateCell reprogrammingMiR-29 familyDNA methylation landscapeImportant epigenetic regulatorsStem cellsOverexpression of Oct4Global DNA methylationMiRNA-based approachesPluripotent stem cellsMethylation landscapeHistone modificationsDNA demethylationEpigenomic changesEarly reprogrammingEpigenetic regulatorsEpigenetic differencesDNA methylationHydroxymethylation analysisReprogrammingIncreased miR-155-5p and reduced miR-148a-3p contribute to the suppression of osteosarcoma cell death
Bhattacharya S, Chalk AM, Ng AJ, Martin TJ, Zannettino AC, Purton LE, Lu J, Baker EK, Walkley CR. Increased miR-155-5p and reduced miR-148a-3p contribute to the suppression of osteosarcoma cell death. Oncogene 2016, 35: 5282-5294. PMID: 27041566, DOI: 10.1038/onc.2016.68.Peer-Reviewed Original ResearchConceptsMiR-148aCell deathCell biological impactMiR-155-5p inhibitionCross-species comparisonsMiR-155-5pApoptosis/necroptosisNormal osteoblastsOS cellsOsteosarcoma cell deathMurine primary osteoblastsMiRNA expression patternsMiRNA-based therapiesCell fateMiR-155-5p overexpressionExpression patternsMolecular geneticsTractable targetsPrimary osteoblastsCandidate targetsBiological impactOsteoblast culturesRIPK1MiRNAsMiRNAThe microRNA miR-148a functions as a critical regulator of B cell tolerance and autoimmunity
Gonzalez-Martin A, Adams BD, Lai M, Shepherd J, Salvador-Bernaldez M, Salvador JM, Lu J, Nemazee D, Xiao C. The microRNA miR-148a functions as a critical regulator of B cell tolerance and autoimmunity. Nature Immunology 2016, 17: 433-440. PMID: 26901150, PMCID: PMC4803625, DOI: 10.1038/ni.3385.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsApoptosisApoptosis Regulatory ProteinsAutoimmunityBcl-2-Like Protein 11B-LymphocytesBone Marrow TransplantationCell Cycle ProteinsCell ProliferationDisease Models, AnimalHEK293 CellsHumansImmune ToleranceImmunoblottingLupus Erythematosus, SystemicMembrane ProteinsMiceMice, Inbred MRL lprMicroRNAsNuclear ProteinsProto-Oncogene ProteinsPTEN PhosphohydrolaseReverse Transcriptase Polymerase Chain ReactionSequence Analysis, RNAmiR-126 Regulates Distinct Self-Renewal Outcomes in Normal and Malignant Hematopoietic Stem Cells
Lechman ER, Gentner B, Ng SW, Schoof EM, van Galen P, Kennedy JA, Nucera S, Ciceri F, Kaufmann KB, Takayama N, Dobson SM, Trotman-Grant A, Krivdova G, Elzinga J, Mitchell A, Nilsson B, Hermans KG, Eppert K, Marke R, Isserlin R, Voisin V, Bader GD, Zandstra PW, Golub TR, Ebert BL, Lu J, Minden M, Wang JC, Naldini L, Dick JE. miR-126 Regulates Distinct Self-Renewal Outcomes in Normal and Malignant Hematopoietic Stem Cells. Cancer Cell 2016, 29: 214-228. PMID: 26832662, PMCID: PMC4749543, DOI: 10.1016/j.ccell.2015.12.011.Peer-Reviewed Original ResearchConceptsLeukemia stem cellsMiR-126Human acute myeloid leukemia stem cellsAcute myeloid leukemia stem cellsMyeloid leukemia stem cellsPI3K/Akt/mTORMiR-126 expressionAkt/mTORMalignant hematopoietic stem cellsMiR-126 regulationStem cellsMiR-126 targetsLSC activityLSC quiescenceAML samplesChemotherapy resistanceHematopoietic stem cellsHematopoietic stem cell cyclingMiRNA signatureCell cycle progressionLSC functionCycle progressionStem cell cyclingSignature miRNAsCell cycling
2015
Hyperglycemia repression of miR-24 coordinately upregulates endothelial cell expression and secretion of von Willebrand factor
Xiang Y, Cheng J, Wang D, Hu X, Xie Y, Stitham J, Atteya G, Du J, Tang WH, Lee SH, Leslie K, Spollett G, Liu Z, Herzog E, Herzog RI, Lu J, Martin KA, Hwa J. Hyperglycemia repression of miR-24 coordinately upregulates endothelial cell expression and secretion of von Willebrand factor. Blood 2015, 125: 3377-3387. PMID: 25814526, PMCID: PMC4447857, DOI: 10.1182/blood-2015-01-620278.Peer-Reviewed Original ResearchConceptsVon Willebrand factorDiabetes mellitusMiR-24Diabetic patientsAdverse thrombotic eventsThrombotic cardiovascular eventsVWF expressionWillebrand factorDiabetic mouse modelNovel therapeutic targetHistamine H1 receptorsEndothelial cell expressionHyperglycemia-induced activationCardiovascular eventsThrombotic eventsH1 receptorsMouse modelVWF levelsTherapeutic targetCell expressionMellitusPatientsEndothelial cellsElevated levelsReactive oxygen speciesPharmacological modulation of the AKT/microRNA-199a-5p/CAV1 pathway ameliorates cystic fibrosis lung hyper-inflammation
Zhang PX, Cheng J, Zou S, D'Souza AD, Koff JL, Lu J, Lee PJ, Krause DS, Egan ME, Bruscia EM. Pharmacological modulation of the AKT/microRNA-199a-5p/CAV1 pathway ameliorates cystic fibrosis lung hyper-inflammation. Nature Communications 2015, 6: 6221. PMID: 25665524, PMCID: PMC4324503, DOI: 10.1038/ncomms7221.Peer-Reviewed Original ResearchConceptsCF macrophagesMiR-199aMicroRNA-199aHyper-inflammatory responseCFTR-deficient miceCystic fibrosis patientsCystic fibrosis lungLung destructionDisease morbidityPharmacological modulationCF miceCF lungFibrosis patientsInnate immunityLungMacrophagesCAV1 expressionDrug celecoxibReduced levelsTLR4CelecoxibMiceCav1PathwayMorbidityCharacterization of the mammalian miRNA turnover landscape
Guo Y, Liu J, Elfenbein SJ, Ma Y, Zhong M, Qiu C, Ding Y, Lu J. Characterization of the mammalian miRNA turnover landscape. Nucleic Acids Research 2015, 43: 2326-2341. PMID: 25653157, PMCID: PMC4344502, DOI: 10.1093/nar/gkv057.Peer-Reviewed Original ResearchConceptsMiRNA turnoverStable small RNAsMammalian cell typesCultured mammalian cellsSubset of miRNAsTurnover kineticsMiRNA biogenesisMost miRNAsMiR-222-5pNucleotide biasSmall RNAsMiRNA maturationMammalian cellsSame miRNAMiRNA poolExpression profilingHsp90 associationSequence determinantsDeep sequencingHsp90 inhibitionTurnover rateMiRNA isoformsDifferent turnover ratesSequence featuresCell typesmicroRNA Expression Profiling: Technologies, Insights, and Prospects
Roden C, Mastriano S, Wang N, Lu J. microRNA Expression Profiling: Technologies, Insights, and Prospects. Advances In Experimental Medicine And Biology 2015, 888: 409-421. PMID: 26663195, DOI: 10.1007/978-3-319-22671-2_21.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBase SequenceCell Line, TumorDisease Models, AnimalGene Expression ProfilingGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansMicroRNAsMolecular Sequence DataNeoplasmsReverse Transcriptase Polymerase Chain ReactionSequence Homology, Nucleic AcidSignal TransductionConceptsLong small noncoding RNAsExpression profilingMiRNA isoformsMiRNA expressionProfiling technologiesDiverse biological processesSingle-cell variabilitySmall noncoding RNAsMiRNA profiling technologiesGlobal miRNA expressionNext-generation sequencingNoncoding RNAsCell variabilitySingle-molecule measurementsBiological functionsBiological processesTumor suppressorMicroRNA researchQuantitative RT-PCRCareful experimental designMiRNAsIsoformsRT-PCRProfilingExpression