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, 1-10. 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
Corrigendum to “Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: results from the IMPACC study” [eBioMedicine 83 (2022) 104208]
Ozonoff A, Schaenman J, Jayavelu N, Milliren C, Calfee C, Cairns C, Kraft M, Baden L, Shaw A, Krammer F, van Bakel H, Esserman D, Liu S, Sesma A, Simon V, Hafler D, Montgomery R, Kleinstein S, Levy O, Bime C, Haddad E, Erle D, Pulendran B, Nadeau K, Davis M, Hough C, Messer W, Higuita N, Metcalf J, Atkinson M, Brakenridge S, Corry D, Kheradmand F, Ehrlich L, Melamed E, McComsey G, Sekaly R, Diray-Arce J, Peters B, Augustine A, Reed E, Altman M, Becker P, Rouphael N, Members T. Corrigendum to “Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: results from the IMPACC study” [eBioMedicine 83 (2022) 104208]. EBioMedicine 2023, 98: 104860. PMID: 37918220, PMCID: PMC10643088, DOI: 10.1016/j.ebiom.2023.104860.Peer-Reviewed Original ResearchMicrofluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection (Small Methods 10/2023)
Kim D, Biancon G, Bai Z, VanOudenhove J, Liu Y, Kothari S, Gowda L, Kwan J, Buitrago‐Pocasangre N, Lele N, Asashima H, Racke M, Wilson J, Givens T, Tomayko M, Schulz W, Longbrake E, Hafler D, Halene S, Fan R. Microfluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection (Small Methods 10/2023). Small Methods 2023, 7 DOI: 10.1002/smtd.202370057.Peer-Reviewed Original ResearchMicrofluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection
Kim D, Biancon G, Bai Z, VanOudenhove J, Liu Y, Kothari S, Gowda L, Kwan J, Buitrago‐Pocasangre N, Lele N, Asashima H, Racke M, Wilson J, Givens T, Tomayko M, Schulz W, Longbrake E, Hafler D, Halene S, Fan R. Microfluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection. Small Methods 2023, 7: e2300594. PMID: 37312418, PMCID: PMC10592458, DOI: 10.1002/smtd.202300594.Peer-Reviewed Original ResearchConceptsB cell depletion therapyAcute COVID infectionAnti-spike IgGHigh-risk patientsCoronavirus disease-19COVID-19 pathologyDepletion therapyVaccine protectionAntibody responseCOVID infectionHematologic malignanciesImmune protectionDisease-19Healthy donorsMultiple time pointsSerology assaysBlood samplesSoluble markersB cellsImmunization strategiesPatientsFunctional deficiencySerological analysisTime pointsClonotype diversity
2021
Immunophenotyping assessment in a COVID-19 cohort (IMPACC): A prospective longitudinal study
, , Rouphael N, Maecker H, Montgomery R, Diray-Arce J, Kleinstein S, Altman M, Bosinger S, Eckalbar W, Guan L, Hough C, Krammer F, Langelier C, Levy O, McEnaney K, Peters B, Rahman A, Rajan J, Sigelman S, Steen H, van Bakel H, Ward A, Wilson M, Woodruff P, Zamecnik C, Augustine A, Ozonoff A, Reed E, Becker P, Higuita N, Altman M, Atkinson M, Baden L, Becker P, Bime C, Brakenridge S, Calfee C, Cairns C, Corry D, Davis M, Augustine A, Ehrlich L, Haddad E, Erle D, Fernandez-Sesma A, Hafler D, Hough C, Kheradmand F, Kleinstein S, Kraft M, Levy O, McComsey G, Melamed E, Messer W, Metcalf J, Montgomery R, Nadeau K, Ozonoff A, Peters B, Pulendran B, Reed E, Rouphael N, Sarwal M, Schaenman J, Sekaly R, Shaw A, Simon V. Immunophenotyping assessment in a COVID-19 cohort (IMPACC): A prospective longitudinal study. Science Immunology 2021, 6: eabf3733. PMID: 34376480, PMCID: PMC8713959, DOI: 10.1126/sciimmunol.abf3733.Peer-Reviewed Original ResearchConceptsCOVID-19 cohortProspective longitudinal studyHost immune responseLongitudinal studyCOVID-19Identification of biomarkersHospitalized patientsRespiratory secretionsClinical criteriaDisease progressionImmune responseRadiographic dataImmunologic assaysEffective therapeuticsOptimal timingStudy designBiologic samplingSuch interventionsCohortSeveritySample collectionAssay protocolsPatientsCutting Edge: Distinct B Cell Repertoires Characterize Patients with Mild and Severe COVID-19
Hoehn KB, Ramanathan P, Unterman A, Sumida TS, Asashima H, Hafler DA, Kaminski N, Dela Cruz CS, Sealfon SC, Bukreyev A, Kleinstein SH. Cutting Edge: Distinct B Cell Repertoires Characterize Patients with Mild and Severe COVID-19. The Journal Of Immunology 2021, 206: 2785-2790. PMID: 34049971, PMCID: PMC8627528, DOI: 10.4049/jimmunol.2100135.Peer-Reviewed Original ResearchConceptsSevere COVID-19Mild COVID-19B cell responsesMemory B cellsB cell repertoireB cellsCell repertoireCOVID-19Cell responsesExtrafollicular B cell responsesLong-term immunitySymptomatic COVID-19Onset of symptomsB cell populationsGerminal center reactionProtective immunityPlasma cellsSingle-cell RNA sequencingCenter reactionPatientsCell populationsImmunityRNA sequencingCellsPostvaccinationImmune dysregulation and autoreactivity correlate with disease severity in SARS-CoV-2-associated multisystem inflammatory syndrome in children
Ramaswamy A, Brodsky NN, Sumida TS, Comi M, Asashima H, Hoehn KB, Li N, Liu Y, Shah A, Ravindra NG, Bishai J, Khan A, Lau W, Sellers B, Bansal N, Guerrerio P, Unterman A, Habet V, Rice AJ, Catanzaro J, Chandnani H, Lopez M, Kaminski N, Dela Cruz CS, Tsang JS, Wang Z, Yan X, Kleinstein SH, van Dijk D, Pierce RW, Hafler DA, Lucas CL. Immune dysregulation and autoreactivity correlate with disease severity in SARS-CoV-2-associated multisystem inflammatory syndrome in children. Immunity 2021, 54: 1083-1095.e7. PMID: 33891889, PMCID: PMC8043654, DOI: 10.1016/j.immuni.2021.04.003.Peer-Reviewed Original ResearchConceptsMIS-C patientsDisease severityInflammatory syndromeTCR repertoireSARS-CoV-2-associated multisystem inflammatory syndromeAsymptomatic SARS-CoV-2 infectionSARS-CoV-2 infectionAdult COVID-19Post-infectious complicationsMultisystem inflammatory syndromeCytotoxicity genesHealthy pediatricImmune dysregulationMemory TActive infectionMyeloid dysfunctionPatientsSingle-cell RNA sequencingFlow cytometrySerum proteomicsRepertoire analysisElevated expressionSeverityAlarminsCOVID-19Oleic acid restores suppressive defects in tissue-resident FOXP3 regulatory T cells from patients with multiple sclerosis
Pompura SL, Wagner A, Kitz A, Laperche J, Yosef N, Dominguez-Villar M, Hafler D. Oleic acid restores suppressive defects in tissue-resident FOXP3 regulatory T cells from patients with multiple sclerosis. Journal Of Clinical Investigation 2021, 131 PMID: 33170805, PMCID: PMC7810477, DOI: 10.1172/jci138519.Peer-Reviewed Original ResearchConceptsMultiple sclerosisAdipose tissueFoxp3 regulatory T cellsExpression of Foxp3Regulatory T cellsTreg suppressive functionProinflammatory arachidonic acidHuman adipose tissuePhosphorylation of STAT5Treg homeostasisFatty acidsPeripheral bloodTissue residencyHealthy donorsInflammatory signalsT cellsTregsFree fatty acidsSuppressive functionArachidonic acidPatientsOleic acidOxidative phosphorylationTranscriptomic programsFoxp3
2020
Transcriptomic and clonal characterization of T cells in the human central nervous system
Pappalardo JL, Zhang L, Pecsok MK, Perlman K, Zografou C, Raddassi K, Abulaban A, Krishnaswamy S, Antel J, van Dijk D, Hafler DA. Transcriptomic and clonal characterization of T cells in the human central nervous system. Science Immunology 2020, 5 PMID: 32948672, PMCID: PMC8567322, DOI: 10.1126/sciimmunol.abb8786.Peer-Reviewed Original ResearchConceptsCentral nervous systemCSF of patientsT cellsCerebrospinal fluidMultiple sclerosisImmune surveillanceNervous systemCSF T cellsHuman central nervous systemHealthy human donorsT cell activationImmune dysfunctionNeuroinflammatory diseasesCytotoxic capacityHealthy donorsHealthy individualsCell activationHuman donorsTissue adaptationPatientsClonal characterizationExpression of genesCellsSurveillanceFurther characterizationDifferential expression of the T-cell inhibitor TIGIT in glioblastoma and MS
Lucca LE, Lerner BA, Park C, DeBartolo D, Harnett B, Kumar VP, Ponath G, Raddassi K, Huttner A, Hafler DA, Pitt D. Differential expression of the T-cell inhibitor TIGIT in glioblastoma and MS. Neurology Neuroimmunology & Neuroinflammation 2020, 7: e712. PMID: 32269065, PMCID: PMC7188477, DOI: 10.1212/nxi.0000000000000712.Peer-Reviewed Original ResearchConceptsTumor-infiltrating T cellsT cellsPD-1/PD-L1Anti-TIGIT therapyExpression of CD226Expression of TIGITPostmortem CNS tissueLymphocytes of patientsFresh surgical resectionsLigand CD155TIGIT expressionSurgical resectionPD-1PD-L1CNS diseaseHealthy controlsHealthy donorsLymphocytic expressionImmune responseCNS tissueMS lesionsTIGITImmune pathwaysPatientsGlioblastoma multiforme
2019
Siponimod Chips Away at Progressive MS
Longbrake EE, Hafler DA. Siponimod Chips Away at Progressive MS. Cell 2019, 179: 1440. PMID: 31951523, PMCID: PMC8023412, DOI: 10.1016/j.cell.2019.11.034.Peer-Reviewed Original ResearchConceptsProgressive multiple sclerosisGadolinium-enhancing MRI lesionsInflammatory disease activityImmunomodulatory medicationsDisability progressionDisease activityMRI lesionsProgressive MSNeurologic disabilityPMS patientsMultiple sclerosisSiponimodMedicationsSclerosisPatientsLesionsBedsideProgressionOcrelizumab treatment reduced levels of neurofilament light chain and numbers of B cells in the cerebrospinal fluid of patients with relapsing multiple sclerosis in the OBOE study (S56.008)
Cross A, Bennett J, von Büdingen H, Carruthers R, Edwards K, Fallis R, Fiore D, Gelfand J, Giacomini P, Greenberg B, Hafler D, Harp C, Assman B, Herman A, Ionete C, Kaunzner U, Lock C, Ma X, Musch B, Pardo G, Piehl F, Weber M, Ziemssen T, Bar-Or A. Ocrelizumab treatment reduced levels of neurofilament light chain and numbers of B cells in the cerebrospinal fluid of patients with relapsing multiple sclerosis in the OBOE study (S56.008). Neurology 2019, 92 DOI: 10.1212/wnl.92.15_supplement.s56.008.Peer-Reviewed Original Research
2018
Chapter 46 Multiple sclerosis
Cotsapas C, Mitrovic M, Hafler D. Chapter 46 Multiple sclerosis. Handbook Of Clinical Neurology 2018, 148: 723-730. PMID: 29478610, DOI: 10.1016/b978-0-444-64076-5.00046-6.Peer-Reviewed Original ResearchConceptsMultiple sclerosisCentral nervous system white matterNervous system white matterAutoimmune neurologic disordersDisease-modifying therapiesImmune function modulationSpecific immune subsetsCentral nervous systemGenetic variantsImmune subsetsNeurologic symptomsAutoimmune attackLeading causeNeurologic disordersNervous systemWhite matterCommon genetic variantsOverall riskSclerosisYoung adultsEnvironmental exposuresRiskSymptomsDiseasePatients
2016
Evaluation of KIR4.1 as an Immune Target in Multiple Sclerosis
Chastre A, Hafler DA, O'Connor KC. Evaluation of KIR4.1 as an Immune Target in Multiple Sclerosis. New England Journal Of Medicine 2016, 374: 1495-1496. PMID: 27074083, PMCID: PMC4918464, DOI: 10.1056/nejmc1513302.Peer-Reviewed Original Research
2015
CBM-06IMMUNE BIOMARKER RESULTS FROM A TRIAL OF NIVOLUMAB ± IPILIMUMAB IN PATIENTS WITH RECURRENT GLIOBLASTOMA: CHECKMATE-143
Lowther D, Weinhold K, Reap E, Vlahovic G, Omuro A, Sahebjam S, Baehring J, Voloschin A, Cloughesy T, Lim M, Coric V, Latek R, Simon J, Lerner B, Raddassi K, Hafler D, Sampson J. CBM-06IMMUNE BIOMARKER RESULTS FROM A TRIAL OF NIVOLUMAB ± IPILIMUMAB IN PATIENTS WITH RECURRENT GLIOBLASTOMA: CHECKMATE-143. Neuro-Oncology 2015, 17: v70-v70. PMCID: PMC4638710, DOI: 10.1093/neuonc/nov211.06.Peer-Reviewed Original ResearchCBM-05FUNCTIONAL DIFFERENCES BETWEEN PD-1+ AND PD-1– CD4+ T EFFECTOR CELLS IN HEALTHY DONORS AND PATIENTS WITH GLIOBLASTOMA
Goods B, Lowther D, Lucca L, Hernandez A, Lerner B, Gunel M, Raddassi K, Simon J, Coric V, Love J, Hafler D. CBM-05FUNCTIONAL DIFFERENCES BETWEEN PD-1+ AND PD-1– CD4+ T EFFECTOR CELLS IN HEALTHY DONORS AND PATIENTS WITH GLIOBLASTOMA. Neuro-Oncology 2015, 17: v70-v70. PMCID: PMC4638709, DOI: 10.1093/neuonc/nov211.05.Peer-Reviewed Original ResearchProspects of immune checkpoint modulators in the treatment of glioblastoma
Preusser M, Lim M, Hafler DA, Reardon DA, Sampson JH. Prospects of immune checkpoint modulators in the treatment of glioblastoma. Nature Reviews Neurology 2015, 11: 504-514. PMID: 26260659, PMCID: PMC4782584, DOI: 10.1038/nrneurol.2015.139.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsCheckpoint inhibitorsGlioblastoma patientsMultiple immunosuppressive mechanismsMedian overall survivalImmune checkpoint modulatorsBlood-brain barrierTreatment of glioblastomaOverall survivalImmunosuppressive mechanismsAdvanced tumorsClinical benefitImmunotherapeutic agentsConventional therapyCheckpoint modulatorsLung cancerImmune systemPatientsCancerInhibitorsCurrent understandingImmunotherapyPrognosisLymphocytesTherapyMultiple sclerosis—a quiet revolution
Ransohoff RM, Hafler DA, Lucchinetti CF. Multiple sclerosis—a quiet revolution. Nature Reviews Neurology 2015, 11: 134-142. PMID: 25686758, PMCID: PMC4556342, DOI: 10.1038/nrneurol.2015.14.Peer-Reviewed Original ResearchConceptsTreatment optionsMajor unmet medical needMultiple sclerosis susceptibilityUnmet medical needNeural tissue injuryGenetic variantsMS therapeuticsAcetate therapyMS riskInflammatory aspectsMultiple sclerosisAutoimmune diseasesTreatable diseaseTissue injuryIndividual patientsDisease evolutionClinical phenotypeMedical needPatientsDisease susceptibilityDiseaseGenetic componentSclerosisIFNOptions
2014
Identification of Pathogenic IL-17 Producing FOXP3+ Tregs in Patients With De Novo Autoimmune Hepatitis.
Ekong U, Hill M, Edmunds C, Han G, Bhela S, Hafler D, Kleinewietfeld M. Identification of Pathogenic IL-17 Producing FOXP3+ Tregs in Patients With De Novo Autoimmune Hepatitis. Transplantation 2014, 98: 872-873. DOI: 10.1097/00007890-201407151-02977.Peer-Reviewed Original Research
2013
Protein array–based profiling of CSF identifies RBPJ as an autoantigen in multiple sclerosis
Querol L, Clark PL, Bailey MA, Cotsapas C, Cross AH, Hafler DA, Kleinstein SH, Lee JY, Yaari G, Willis SN, O'Connor KC. Protein array–based profiling of CSF identifies RBPJ as an autoantigen in multiple sclerosis. Neurology 2013, 81: 956-963. PMID: 23921886, PMCID: PMC3888197, DOI: 10.1212/wnl.0b013e3182a43b48.Peer-Reviewed Original ResearchConceptsCSF of patientsMultiple sclerosisNeurologic diseaseEpstein-Barr virus infectionImmunoglobulin GElevated immunoglobulin GInflammatory neurologic diseasesSubset of patientsLarger validation cohortRecombination signal binding proteinImmunoglobulin kappa J regionCSF autoantibodiesValidation cohortControl subjectsSerum reactivityAutoantigen candidatesHigh prevalenceVirus infectionPatientsAutoantibodiesCSFSclerosisArray-based profilingDiseaseELISA