Featured Publications
Differential richness inference for 16S rRNA marker gene surveys
Kumar M, Slud E, Hehnly C, Zhang L, Broach J, Irizarry R, Schiff S, Paulson J. Differential richness inference for 16S rRNA marker gene surveys. Genome Biology 2022, 23: 166. PMID: 35915508, PMCID: PMC9344657, DOI: 10.1186/s13059-022-02722-x.Peer-Reviewed Original ResearchConceptsMarker gene surveysRRNA marker gene surveysGene surveysMicrobial assemblagesSpecies discoveryMicrobial taxaMicrobial communitiesMicrobiome surveysRichness estimationSequencing readsDiversity measuresTaxaGenus abundanceMicrobiome dataR packageAbundanceRichnessDiscoveryDiversityReadsAssemblagesObserved numberExperimental evidenceAccumulationInferencePaenibacillus infection with frequent viral coinfection contributes to postinfectious hydrocephalus in Ugandan infants
Paulson J, Williams B, Hehnly C, Mishra N, Sinnar S, Zhang L, Ssentongo P, Mbabazi-Kabachelor E, Wijetunge D, von Bredow B, Mulondo R, Kiwanuka J, Bajunirwe F, Bazira J, Bebell L, Burgoine K, Couto-Rodriguez M, Ericson J, Erickson T, Ferrari M, Gladstone M, Guo C, Haran M, Hornig M, Isaacs A, Kaaya B, Kangere S, Kulkarni A, Kumbakumba E, Li X, Limbrick D, Magombe J, Morton S, Mugamba J, Ng J, Olupot-Olupot P, Onen J, Peterson M, Roy F, Sheldon K, Townsend R, Weeks A, Whalen A, Quackenbush J, Ssenyonga P, Galperin M, Almeida M, Atkins H, Warf B, Lipkin W, Broach J, Schiff S. Paenibacillus infection with frequent viral coinfection contributes to postinfectious hydrocephalus in Ugandan infants. Science Translational Medicine 2020, 12 PMID: 32998967, PMCID: PMC7774825, DOI: 10.1126/scitranslmed.aba0565.Peer-Reviewed Original ResearchConceptsPostinfectious hydrocephalusCSF samplesPIH casesPotential causative organismsCerebrospinal fluid accumulationCytomegalovirus coinfectionUgandan infantsNeonatal sepsisSurgical palliationNeonatal infectionInfant casesOptimal treatmentInfant cohortCommon causeCausative organismPediatric hydrocephalusFluid accumulationHydrocephalusAnaerobic bacterial isolatesControl casesInfectionFacultative anaerobic bacterial isolatesInfantsParasitic DNADiseaseNeoantigens in Patients with De Novo Follicular Lymphoma: Results from the PRIMA Study
Henneges C, Jin D, Venstrom J, Trabucco S, Nielsen T, Penuel E, Huet S, Salles G, Paulson J. Neoantigens in Patients with De Novo Follicular Lymphoma: Results from the PRIMA Study. Blood 2020, 136: 25-26. DOI: 10.1182/blood-2020-134795.Peer-Reviewed Original ResearchDiffuse large B-cell lymphomaDe novo diffuse large B-cell lymphomaProgression-free survivalTumor mutational burdenComprehensive genomic profilingCurrent equity holderAssociated with progression-free survivalFollicular lymphomaF. Hoffmann-La RocheFoundation MedicinePrognostic valueClinical outcomesMedian tumor mutation burdenProgression-free survival eventsPooled analysis of patientsLarge B-cell lymphomaResponse to induction treatmentCalculate tumor mutational burdenAssociated with clinical outcomesEZH2 mutation statusComprehensive genomic profiling dataB-cell lymphomaGenetic mutational landscapeAnalysis of patientsProportion of patientsDifferential abundance analysis for microbial marker-gene surveys
Paulson J, Stine O, Bravo H, Pop M. Differential abundance analysis for microbial marker-gene surveys. Nature Methods 2013, 10: 1200-1202. PMID: 24076764, PMCID: PMC4010126, DOI: 10.1038/nmeth.2658.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsArea Under CurveCluster AnalysisComputer SimulationDatabases, GeneticGene Expression ProfilingGenetic MarkersGenetic VariationHumansIntestinesMetagenomicsMiceMicrobiotaModels, GeneticModels, StatisticalNormal DistributionPhenotypeRNA, Ribosomal, 16SSequence Analysis, DNASoftware
2024
Lubricating gel influence on vaginal microbiome sampling
Amitai Komem D, Hadar R, Paulson J, Mordechai Y, Eskandarian H, Efroni G, Amir A, Haberman Y, Tsur A. Lubricating gel influence on vaginal microbiome sampling. Scientific Reports 2024, 14: 18223. PMID: 39107405, PMCID: PMC11303677, DOI: 10.1038/s41598-024-68948-w.Peer-Reviewed Original ResearchConceptsMicrobial compositionVaginal samplesVaginal microbiome samplesBeta diversityVaginal microbiome studiesMicrobiome studiesMicrobiome samplesTaxa abundanceGynecological examinationPregnant womenLubricant gelReduce painMicrobial dataGel exposureEmergency roomSterile swabsEffect of gelMicrobial analysisPrediction of Benefit From Adjuvant Pertuzumab by 80-Gene Signature in the APHINITY (BIG 4-11) Trial
Krop I, Mittempergher L, Paulson J, Andre F, Bonnefoi H, Loi S, Loibl S, Gelber R, Caballero C, Bhaskaran R, Dreezen C, Menicucci A, Bernards R, van ’t Veer L, Piccart M. Prediction of Benefit From Adjuvant Pertuzumab by 80-Gene Signature in the APHINITY (BIG 4-11) Trial. JCO Precision Oncology 2024, 8: e2200667. PMID: 38237097, DOI: 10.1200/po.22.00667.Peer-Reviewed Original ResearchConceptsInvasive disease-free survivalHER2 typeLuminal typeInvasive disease-free survival eventsHazard ratioEarly-stage breast cancerLuminal-type tumorsMolecular subtype signaturesAnti-HER2 therapyHER2-positive tumorsDisease-free survivalStandard adjuvant chemotherapyBasal-type tumorsBasal typePredictive of benefitAdjuvant pertuzumabAPHINITY trialHER2-typeHER2-positiveInferior prognosisAdjuvant chemotherapyTumor subtypesNo significant differenceAnti-HER2Breast tumors
2023
Transcriptional immunogenomic analysis reveals distinct immunological clusters in paediatric nervous system tumours
Nabbi A, Beck P, Delaidelli A, Oldridge D, Sudhaman S, Zhu K, Yang S, Mulder D, Bruce J, Paulson J, Raman P, Zhu Y, Resnick A, Sorensen P, Sill M, Brabetz S, Lambo S, Malkin D, Johann P, Kool M, Jones D, Pfister S, Jäger N, Pugh T. Transcriptional immunogenomic analysis reveals distinct immunological clusters in paediatric nervous system tumours. Genome Medicine 2023, 15: 67. PMID: 37679810, PMCID: PMC10486055, DOI: 10.1186/s13073-023-01219-x.Peer-Reviewed Original ResearchConceptsChimeric antigen receptorNervous system tumorsImmune clustersImmunogenomic analysisSystem tumorsCancer typesImmune checkpoint inhibitorsT-cell therapyPaediatric solid tumoursTumor mutational burdenImmune cell frequenciesPotential immune biomarkersImmune infiltration levelsB cell repertoireDeterminants of immune responseVariable response ratesBackgroundCancer immunotherapyImmunogenomic profilingMyeloid predominanceCheckpoint inhibitorsImmunotherapeutic strategiesImmunotherapy approachesImmune compositionImmune neutralizationImmune desertmbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
Movassagh M, Schiff S, Paulson J. mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation. Bioinformatics 2023, 39: btad565. PMID: 37707523, PMCID: PMC10516520, DOI: 10.1093/bioinformatics/btad565.Peer-Reviewed Original ResearchConceptsSingle nucleotide variationsRNA sequencingMicrobial abundance dataQuantitative trait lociSingle nucleotide polymorphism dataRibosomal RNA sequencingField of genomicsWhole-genome sequencingEvidence of interplayMutational profileTrait lociMicrobial communitiesMicrobial abundancePolymorphism dataMicrobial populationsGenome sequencingAbundance dataFirst R packageHuman geneticsBioconductor packageGenetic variantsMicrobiome dataSequencingR packageAbundanceTranscriptomic profiles and 5-year results from the randomized CLL14 study of venetoclax plus obinutuzumab versus chlorambucil plus obinutuzumab in chronic lymphocytic leukemia
Al-Sawaf O, Zhang C, Jin H, Robrecht S, Choi Y, Balasubramanian S, Kotak A, Chang Y, Fink A, Tausch E, Schneider C, Ritgen M, Kreuzer K, Chyla B, Paulson J, Pallasch C, Frenzel L, Peifer M, Eichhorst B, Stilgenbauer S, Jiang Y, Hallek M, Fischer K. Transcriptomic profiles and 5-year results from the randomized CLL14 study of venetoclax plus obinutuzumab versus chlorambucil plus obinutuzumab in chronic lymphocytic leukemia. Nature Communications 2023, 14: 2147. PMID: 37072421, PMCID: PMC10113251, DOI: 10.1038/s41467-023-37648-w.Peer-Reviewed Original ResearchConceptsProgression-free survivalChronic lymphocytic leukemiaUntreated chronic lymphocytic leukemiaLymphocytic leukemiaAssociated with longer progression-free survivalParallel-group phase 3 studyProgression-free survival ratesTreatment of chronic lymphocytic leukemiaLonger progression-free survivalDepth of remissionMedian follow-upPhase 3 studyAssociated with increased expressionLong-term efficacyLong-term outcomesExploratory post hoc analysisPost hoc analysisMRD statusBCL2 inhibitionOverall survivalPrimary endpointSecondary endpointsInflammatory response pathwaysVenetoclax-obinutuzumabFollow-upMultimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab
Nabbi A, Danesh A, Espin-Garcia O, Pedersen S, Wellum J, Fu L, Paulson J, Geoerger B, Marshall L, Trippett T, Rossato G, Pugh T, Hutchinson K. Multimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab. Nature Cancer 2023, 4: 502-515. PMID: 37038005, PMCID: PMC10132976, DOI: 10.1038/s43018-023-00534-x.Peer-Reviewed Original ResearchConceptsPediatric patientsAssociated with progression-free survivalCD8+ T cellsT cell receptor repertoireProgression-free survivalImmune-checkpoint inhibitionB cell infiltrationTertiary lymphoid structuresBiomarker analysisAtezolizumab therapyAntitumor immunityStable diseasePD-L1Partial responseTumor neoantigensRefractory tumorsPatient tumorsLymphoid structuresT cellsB cellsReceptor repertoireClinical trialsClinical activityTumorImmune responseThe Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks
Ben Guebila M, Wang T, Lopes-Ramos C, Fanfani V, Weighill D, Burkholz R, Schlauch D, Paulson J, Altenbuchinger M, Shutta K, Sonawane A, Lim J, Calderer G, van IJzendoorn D, Morgan D, Marin A, Chen C, Song Q, Saha E, DeMeo D, Padi M, Platig J, Kuijjer M, Glass K, Quackenbush J. The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks. Genome Biology 2023, 24: 45. PMID: 36894939, PMCID: PMC9999668, DOI: 10.1186/s13059-023-02877-1.Peer-Reviewed Original Research
2022
A tumor volume and performance status model to predict outcome before treatment in diffuse large B-cell lymphoma
Thieblemont C, Chartier L, Dührsen U, Vitolo U, Barrington S, Zaucha J, Vercellino L, Silva M, Patrocinio-Carvalho I, Decazes P, Viailly P, Tilly H, Berriolo-Riedinger A, Casasnovas O, Hüttmann A, Ilyas H, Mikhaeel N, Dunn J, Cottereau A, Schmitz C, Kostakoglu L, Paulson J, Nielsen T, Meignan M. A tumor volume and performance status model to predict outcome before treatment in diffuse large B-cell lymphoma. Blood Advances 2022, 6: 5995-6004. PMID: 36044385, PMCID: PMC9691911, DOI: 10.1182/bloodadvances.2021006923.Peer-Reviewed Original ResearchConceptsLarge B-cell lymphomaAggressive large B-cell lymphomaB-cell lymphomaRisk factorsTumor volumePerformance statusDiffuse large B-cell lymphomaInternational Prognostic IndexMetabolic tumor volumeProgression-free survivalReal-world seriesReal-world clinicsREMARC trialOverall survivalRefractory diseaseECOG-PSPrognostic indexIntermediate riskInitial treatmentTreatment initiationRisk stratificationC-indexOlder patientsPrognostic toolClinical trialsType IV Pili Are a Critical Virulence Factor in Clinical Isolates of Paenibacillus thiaminolyticus
Hehnly C, Shi A, Ssentongo P, Zhang L, Isaacs A, Morton S, Streck N, Erdmann-Gilmore P, Tolstoy I, Townsend R, Limbrick D, Paulson J, Ericson J, Galperin M, Schiff S, Broach J. Type IV Pili Are a Critical Virulence Factor in Clinical Isolates of Paenibacillus thiaminolyticus. MBio 2022, 13: e02688-22. PMID: 36374038, PMCID: PMC9765702, DOI: 10.1128/mbio.02688-22.Peer-Reviewed Original ResearchConceptsPostinfectious hydrocephalusClinical isolatesVirulence factorsCritical virulence factorPotential virulence factorsPoor long-term outcomesPrevention of hydrocephalusLong-term outcomesBacterial pathogensDevastating sequelaeNeonatal sepsisMiddle-income countriesNeonatal infectionSurgical interventionReference strainsNovel bacterial pathogensAfrican cohortBeta-lactamase genesChildhood mortalityHydrocephalusTherapeutic targetInfectionVirulent strainDevastating diseaseWhole-genome sequencingFull automation of total metabolic tumor volume from FDG-PET/CT in DLBCL for baseline risk assessments
Jemaa S, Paulson J, Hutchings M, Kostakoglu L, Trotman J, Tracy S, de Crespigny A, Carano R, El-Galaly T, Nielsen T, Bengtsson T. Full automation of total metabolic tumor volume from FDG-PET/CT in DLBCL for baseline risk assessments. Cancer Imaging 2022, 22: 39. PMID: 35962459, PMCID: PMC9373298, DOI: 10.1186/s40644-022-00476-0.Peer-Reviewed Original ResearchConceptsDiffuse large B-cell lymphomaProgression-free survivalOverall survivalFDG-PETUntreated diffuse large B-cell lymphomaHazard ratioHigh-risk DLBCL patientsCentral nervous system relapseLarge B-cell lymphomaMetabolic tumor volumeImaging-based risk factorsB-cell lymphomaEnhanced risk stratificationHigh-risk populationImaging metricsRisk increaseDLBCL patientsFDG-PET/CTSystemic relapseTumor volumeOrgan involvementPrognostic improvementRisk stratificationInvasive proceduresClinical dataGameRank: R package for feature selection and construction
Henneges C, Paulson J. GameRank: R package for feature selection and construction. Bioinformatics 2022, 38: 4840-4842. PMID: 35951761, PMCID: PMC9563696, DOI: 10.1093/bioinformatics/btac552.Peer-Reviewed Original ResearchDisentangling the genetic basis of rhizosphere microbiome assembly in tomato
Oyserman B, Flores S, Griffioen T, Pan X, van der Wijk E, Pronk L, Lokhorst W, Nurfikari A, Paulson J, Movassagh M, Stopnisek N, Kupczok A, Cordovez V, Carrión V, Ligterink W, Snoek B, Medema M, Raaijmakers J. Disentangling the genetic basis of rhizosphere microbiome assembly in tomato. Nature Communications 2022, 13: 3228. PMID: 35710629, PMCID: PMC9203511, DOI: 10.1038/s41467-022-30849-9.Peer-Reviewed Original ResearchConceptsMicrobiome assemblyGenetic basisRhizosphere microbiome assemblyMetagenome-assembled genomesGene content analysisQuantitative trait lociDomestication sweepsDomesticated tomatoRhizosphere microbiomePutative plantPlant geneticsTrait lociBacterial genesPlant growthHybrid populationsQuantitative traitsBreeding programsMbp regionGenetic variation associatesPlant polysaccharidesDifferential recruitmentTomatoStreptomycesTraitsPivotal rolemirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis
Movassagh M, Morton S, Hehnly C, Smith J, Doan T, Irizarry R, Broach J, Schiff S, Bailey J, Paulson J. mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis. BMC Genomics 2022, 23: 439. PMID: 35698050, PMCID: PMC9191533, DOI: 10.1186/s12864-022-08558-w.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionLung epithelial cellsEpithelial cellsHuman lung epithelial cellsSARS-CoV-2NK cellsStatistical PackageEBV miRNAsT cellsImmune pathwaysB cellsClinical relevanceSample cohortCD34 cellsStomach adenocarcinomaEndothelial cellsTime pointsInfectionCOVID-19CellsCD4AdenocarcinomaPatientsCD19CytokinesOutcomes by BCL2 and MYC expression and rearrangements in untreated diffuse large B-cell lymphoma (DLBCL) from the POLARIX trial.
Morschhauser F, Jiang Y, Jardin F, Herrera A, Sehn L, Herbaux C, Flowers C, Phillips T, Guillermo A, Diefenbach C, Gregory G, Kim A, Barbui A, Balasubramanian S, Harris W, Hirata J, Paulson J, Lee C, Lenz G. Outcomes by BCL2 and MYC expression and rearrangements in untreated diffuse large B-cell lymphoma (DLBCL) from the POLARIX trial. Journal Of Clinical Oncology 2022, 40: 7517-7517. DOI: 10.1200/jco.2022.40.16_suppl.7517.Peer-Reviewed Original ResearchDiffuse large B-cell lymphomaPola-R-CHPProgression-free survivalR-CHOPPrognostic impactMultivariate analysisBCL6-RUntreated diffuse large B-cell lymphomaProgression-free survival eventsProgression-free survival estimatesLarge B-cell lymphomaMultivariate Cox regression modelDouble expressor lymphomaSubgroups of ptsTranslocation of MYCTriple-hit lymphomaAssociated with poor outcomesB-cell lymphomaMYC protein expressionResults of univariate analysisCox regression modelsBCL2+Cell of originOverexpression of BCL2Fluorescence in situ hybridizationP1268: DELINEATING THE NEOANTIGEN BURDEN AND TUMOUR MICROENVIRONMENT IN PATIENTS WITH DIFFUSE LARGE B CELL LYMPHOMA (DLBCL).
Jiang Y, Jin D, Henneges C, Penuel E, Hiew H, Paulson J, Bazeos A. P1268: DELINEATING THE NEOANTIGEN BURDEN AND TUMOUR MICROENVIRONMENT IN PATIENTS WITH DIFFUSE LARGE B CELL LYMPHOMA (DLBCL). HemaSphere 2022, 6: 1153-1154. PMCID: PMC9429719, DOI: 10.1097/01.hs9.0000847936.41396.29.Peer-Reviewed Original ResearchPatient‐reported outcomes provide prognostic information for survival in patients with diffuse large B‐cell lymphoma: Analysis of 1239 patients from the GOYA study
Huang H, Datye A, Fan M, Knapp A, Nielsen T, Bottos A, Paulson J, Trask P, Efficace F. Patient‐reported outcomes provide prognostic information for survival in patients with diffuse large B‐cell lymphoma: Analysis of 1239 patients from the GOYA study. Cancer Medicine 2022, 11: 3312-3322. PMID: 35322932, PMCID: PMC9468432, DOI: 10.1002/cam4.4692.Peer-Reviewed Original ResearchConceptsDiffuse large B-cell lymphomaInternational Prognostic IndexProgression-free survivalLarge B-cell lymphomaB-cell lymphomaOverall survivalPrognostic valuePatient-reported outcomesPrognostic informationCox regression analysis of overall survivalClinical variablesAnalysis of overall survivalPhase III studyFifty-nine patientsCox regression analysisPatient risk stratificationPopulation of patientsEuropean Organization for Research and Treatment of Cancer Quality of LifeEuropean Organization for Research and TreatmentPlus chemotherapyIII studiesPrognostic indexTreatment of Cancer Quality of LifeGlobal health status/quality of lifeGlobal health status/quality