2024
Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines
Kovalchik K, Hamelin D, Kubiniok P, Bourdin B, Mostefai F, Poujol R, Paré B, Simpson S, Sidney J, Bonneil É, Courcelles M, Saini S, Shahbazy M, Kapoor S, Rajesh V, Weitzen M, Grenier J, Gharsallaoui B, Maréchal L, Wu Z, Savoie C, Sette A, Thibault P, Sirois I, Smith M, Decaluwe H, Hussin J, Lavallée-Adam M, Caron E. Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines. Nature Communications 2024, 15: 10316. PMID: 39609459, PMCID: PMC11604954, DOI: 10.1038/s41467-024-54734-9.Peer-Reviewed Original ResearchConceptsT cell epitopesT cellsCD8+ T cell epitopesT cell immunityT cell epitope discoverySARS-CoV-2T-cell-directed vaccinationDesigning effective vaccinesB7 supertypePatient's proteomesSARS-CoV-2 variantsVaccine epitopesViral antigensSpike antigenVaccine developmentEffective vaccineEpitope discoveryCOVID-19 vaccineVaccineEpitopesAntigenic featuresOmicron variantAntigenCOVID-19CD8
2023
The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics
Huang X, Gan Z, Cui H, Lan T, Liu Y, Caron E, Shao W. The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics. Nucleic Acids Research 2023, 52: d1062-d1071. PMID: 38000392, PMCID: PMC10767952, DOI: 10.1093/nar/gkad1068.Peer-Reviewed Original ResearchIntroduction to the Special Issue: The Immunopeptidome
Caron É, Perreault C. Introduction to the Special Issue: The Immunopeptidome. Seminars In Immunology 2023, 69: 101798. PMID: 37348326, DOI: 10.1016/j.smim.2023.101798.Peer-Reviewed Original Research
2021
Generation of HLA Allele-Specific Spectral Libraries to Identify and Quantify Immunopeptidomes by SWATH/DIA-MS
Kovalchik K, Hamelin D, Caron E. Generation of HLA Allele-Specific Spectral Libraries to Identify and Quantify Immunopeptidomes by SWATH/DIA-MS. Methods In Molecular Biology 2021, 2420: 137-147. PMID: 34905171, DOI: 10.1007/978-1-0716-1936-0_11.Peer-Reviewed Original ResearchMhcVizPipe: A Quality Control Software for Rapid Assessment of Small- to Large-Scale Immunopeptidome Datasets
Kovalchik K, Ma Q, Wessling L, Saab F, Duquette J, Kubiniok P, Hamelin D, Faridi P, Li C, Purcell A, Jang A, Paramithiotis E, Tognetti M, Reiter L, Bruderer R, Lanoix J, Bonneil É, Courcelles M, Thibault P, Caron E, Sirois I. MhcVizPipe: A Quality Control Software for Rapid Assessment of Small- to Large-Scale Immunopeptidome Datasets. Molecular & Cellular Proteomics 2021, 21: 100178. PMID: 34798331, PMCID: PMC8717601, DOI: 10.1016/j.mcpro.2021.100178.Peer-Reviewed Original ResearchConceptsModern web browsersLarge-scale datasetsQuality control softwareWeb browserHTML formatControl softwareSoftware toolsProteomics core facilitiesConsolidated viewDatasetImmunopeptidomic datasetsHigh-throughput technologiesDecision-making processData interpretationBrowserInstrument operatorsComputerAssurance systemAlgorithmQuality controlSoftwareCore facilitiesFormatServicesTechnologyRHybridFinder: An R package to process immunopeptidomic data for putative hybrid peptide discovery
Saab F, Hamelin D, Ma Q, Kovalchik K, Sirois I, Faridi P, Li C, Purcell A, Kubiniok P, Caron E. RHybridFinder: An R package to process immunopeptidomic data for putative hybrid peptide discovery. STAR Protocols 2021, 2: 100875. PMID: 34746858, PMCID: PMC8551247, DOI: 10.1016/j.xpro.2021.100875.Peer-Reviewed Original Research
2020
The SysteMHC Atlas: a Computational Pipeline, a Website, and a Data Repository for Immunopeptidomic Analyses
Shao W, Caron E, Pedrioli P, Aebersold R. The SysteMHC Atlas: a Computational Pipeline, a Website, and a Data Repository for Immunopeptidomic Analyses. Methods In Molecular Biology 2020, 2120: 173-181. PMID: 32124319, DOI: 10.1007/978-1-0716-0327-7_12.Peer-Reviewed Original Research
2018
Minimal Information About an Immuno‐Peptidomics Experiment (MIAIPE)
Lill J, van Veelen P, Tenzer S, Admon A, Caron E, Elias J, Heck A, Marcilla M, Marino F, Müller M, Peters B, Purcell A, Sette A, Sturm T, Ternette N, Vizcaíno J, Bassani‐Sternberg M. Minimal Information About an Immuno‐Peptidomics Experiment (MIAIPE). Proteomics 2018, 18: 1800110. PMID: 29791771, PMCID: PMC6033177, DOI: 10.1002/pmic.201800110.Peer-Reviewed Original Research
2016
Contribution of Mass Spectrometry-Based Proteomics to the Understanding of TNF‑α Signaling
Ciuffa R, Caron E, Leitner A, Uliana F, Gstaiger M, Aebersold R. Contribution of Mass Spectrometry-Based Proteomics to the Understanding of TNF‑α Signaling. Journal Of Proteome Research 2016, 16: 14-33. PMID: 27762135, DOI: 10.1021/acs.jproteome.6b00728.Peer-Reviewed Original ResearchConceptsTNF-α signalingProteomics researchDimeric transcription factorsComplex signaling cascadesSystems-level understandingProteome levelProteomic landscapeCellular processesTranscription factorsSignaling cascadesNF-κBSignalingLevel understandingMass spectrometryProteomeActivationProteomicsSpite of decadesCytokines IL-1βDifferentiationLimited knowledgePathwayCascadeFamilyTNF
2015
Epigenetics and Proteomics Join Transcriptomics in the Quest for Tuberculosis Biomarkers
Esterhuyse M, Weiner J, Caron E, Loxton A, Iannaccone M, Wagman C, Saikali P, Stanley K, Wolski W, Mollenkopf H, Schick M, Aebersold R, Linhart H, Walzl G, Kaufmann S. Epigenetics and Proteomics Join Transcriptomics in the Quest for Tuberculosis Biomarkers. MBio 2015, 6: 10.1128/mbio.01187-15. PMID: 26374119, PMCID: PMC4600108, DOI: 10.1128/mbio.01187-15.Peer-Reviewed Original ResearchConceptsTB patientsPilot studyActive tuberculosis diseaseLarge-scale studiesSpread of TBLTBI controlLTBI participantsTuberculosis infectionTuberculosis diseaseDisease progressionHealthy controlsPrognostic biomarkerImmune responseBiologic mechanismsHealthy individualsPatientsHost responseInfected individualsBetter careInfectious diseasesMycobacterium tuberculosisSmall sample sizeBiomarker developmentRegulation of functionDNA methylation
2014
A repository of assays to quantify 10,000 human proteins by SWATH-MS
Rosenberger G, Koh CC, Guo T, Röst HL, Kouvonen P, Collins BC, Heusel M, Liu Y, Caron E, Vichalkovski A, Faini M, Schubert OT, Faridi P, Ebhardt HA, Matondo M, Lam H, Bader SL, Campbell DS, Deutsch EW, Moritz RL, Tate S, Aebersold R. A repository of assays to quantify 10,000 human proteins by SWATH-MS. Scientific Data 2014, 1: 140031. PMID: 25977788, PMCID: PMC4322573, DOI: 10.1038/sdata.2014.31.Peer-Reviewed Original Research
2011
The MHC I immunopeptidome conveys to the cell surface an integrative view of cellular regulation
Caron E, Vincent K, Fortier M, Laverdure J, Bramoullé A, Hardy M, Voisin G, Roux P, Lemieux S, Thibault P, Perreault C. The MHC I immunopeptidome conveys to the cell surface an integrative view of cellular regulation. Molecular Systems Biology 2011, 7: msb201168. PMID: 21952136, PMCID: PMC3202804, DOI: 10.1038/msb.2011.68.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCD8-Positive T-LymphocytesCell Line, TumorCell MembraneGene Expression ProfilingHigh-Throughput Screening AssaysHistocompatibility Antigens Class IImmunityMajor Histocompatibility ComplexMass SpectrometryMetabolic Networks and PathwaysMiceOligonucleotide Array Sequence AnalysisPeptidesProteomicsSignal TransductionSirolimusSystems BiologyTandem Mass SpectrometryTOR Serine-Threonine KinasesConceptsCell surfaceMass spectrometry-based approachSystems-level evidenceSelf/non-self discriminationCellular regulationPredictive biologyCellular metabolic activityCellular metabolismNon-self discriminationRapamycin resultsMammalian targetMHC IBiochemical networksCD8 T lymphocytesSystems immunologyMajor histocompatibility complex (MHC) class I moleculesMetabolic eventsExtrinsic factorsMetabolic activityIntegrative viewClass I moleculesImmunotherapeutic interventionsT lymphocytesEssence of selfSystem-level perspective