2024
Circulating tumor-reactive KIR+CD8+ T cells suppress anti-tumor immunity in patients with melanoma
Lu B, Lucca L, Lewis W, Wang J, Nogueira C, Heer S, Rayon-Estrada V, Axisa P, Reeves S, Buitrago-Pocasangre N, Pham G, Kojima M, Wei W, Aizenbud L, Bacchiocchi A, Zhang L, Walewski J, Chiang V, Olino K, Clune J, Halaban R, Kluger Y, Coyle A, Kisielow J, Obermair F, Kluger H, Hafler D. Circulating tumor-reactive KIR+CD8+ T cells suppress anti-tumor immunity in patients with melanoma. Nature Immunology 2024, 26: 82-91. PMID: 39609626, DOI: 10.1038/s41590-024-02023-4.Peer-Reviewed Original ResearchCD8+ T cellsAnti-tumor immunityRegulatory T cellsT cellsSubpopulation of CD8+ T cellsCytotoxic CD8+ T cellsHuman CD8+ T cellsTumor antigen-specific CD8Impaired anti-tumor immunityTumor antigen-specificPoor overall survivalTumor rejectionKIR expressionOverall survivalTumor antigensImmune evasionCellular mediatorsHuman cancersCD8MelanomaTumorTranscriptional programsFunctional heterogeneityImmunityPatients
2023
A bedside to bench study of anti-PD-1, anti-CD40, and anti-CSF1R indicates that more is not necessarily better
Djureinovic D, Weiss S, Krykbaeva I, Qu R, Vathiotis I, Moutafi M, Zhang L, Perdigoto A, Wei W, Anderson G, Damsky W, Hurwitz M, Johnson B, Schoenfeld D, Mahajan A, Hsu F, Miller-Jensen K, Kluger Y, Sznol M, Kaech S, Bosenberg M, Jilaveanu L, Kluger H. A bedside to bench study of anti-PD-1, anti-CD40, and anti-CSF1R indicates that more is not necessarily better. Molecular Cancer 2023, 22: 182. PMID: 37964379, PMCID: PMC10644655, DOI: 10.1186/s12943-023-01884-x.Peer-Reviewed Original ResearchConceptsStable diseasePartial responseMacrophage populationsThree-drug regimenUnconfirmed partial responsePhase I trialLimited treatment optionsMonocyte/macrophage populationNon-classical monocytesMurine melanoma modelTreatment-related changesResultsThirteen patientsWorse survivalI trialInflammatory tumorPatient populationTreatment optionsImmune cellsDisease progressionMurine studiesPreclinical modelsResistant melanomaAntigen presentationMurine modelCyTOF analysis
2022
Longitudinal single-cell analysis of a patient receiving adoptive cell therapy reveals potential mechanisms of treatment failure
Qu R, Kluger Y, Yang J, Zhao J, Hafler D, Krause D, Bersenev A, Bosenberg M, Hurwitz M, Lucca L, Kluger H. Longitudinal single-cell analysis of a patient receiving adoptive cell therapy reveals potential mechanisms of treatment failure. Molecular Cancer 2022, 21: 219. PMID: 36514045, PMCID: PMC9749221, DOI: 10.1186/s12943-022-01688-5.Peer-Reviewed Original ResearchConceptsAdoptive cell therapySingle-cell analysisDepth single-cell analysisSingle-cell RNAACT productsDisease progressionT-cell receptor sequencingCell therapyFamily genesFeatures of exhaustionMultiple tumor typesCell expansionGenesNew clonotypesTIL preparationsClonal cell expansionCytokine therapyTreatment failureSerial bloodClonesEffector functionsSerial samplesTumor typesCellular therapyTherapy
2020
19. PLEKHA5 REGULATES TUMOR GROWTH IN METASTATIC MELANOMA
Oria V, Zhang H, Zhu H, Deng G, Zito C, Rane C, Zhang S, Weiss S, Tran T, Adeniran A, Zhang F, Zhou J, Kluger Y, Bosenberg M, Kluger H, Jilaveanu L. 19. PLEKHA5 REGULATES TUMOR GROWTH IN METASTATIC MELANOMA. Neuro-Oncology Advances 2020, 2: ii3-ii3. PMCID: PMC7401364, DOI: 10.1093/noajnl/vdaa073.009.Peer-Reviewed Original ResearchMelanoma brain metastasesBrain metastasesTumor growthPI3K/Akt/mTORCell cycle transitionAkt/mTORGrowth of tumorsS cell cycle transitionPhosphorylation of AktMelanoma patientsPoor prognosisNovel drug targetsPatient populationRegulation of PDCD4Metastatic melanomaUnique cohortXenograft modelClinical relevanceNude miceMetastasisCycle transitionMelanomaBrain developmentKey mediatorMelanoma cells
2006
Characterizing disease states from topological properties of transcriptional regulatory networks
Tuck DP, Kluger HM, Kluger Y. Characterizing disease states from topological properties of transcriptional regulatory networks. BMC Bioinformatics 2006, 7: 236. PMID: 16670008, PMCID: PMC1482723, DOI: 10.1186/1471-2105-7-236.Peer-Reviewed Original ResearchConceptsTranscriptional regulatory networksRegulatory networksTranscription factorsTranscriptional networksRegulated genesGene deregulationExpression profilesDiseased statesGene regulatory networksCentrality of genesGene expression experimentsGene expression profilesGene expression studiesGene centralityRegulatory linkExpression experimentsExpression studiesGene linksGenesCell typesExpression datasetsGene subsetsDifferential activityNormal cellsRemarkable degree
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply