2025
Turnover atlas of proteome and phosphoproteome across mouse tissues and brain regions
Li W, Dasgupta A, Yang K, Wang S, Hemandhar-Kumar N, Chepyala S, Yarbro J, Hu Z, Salovska B, Fornasiero E, Peng J, Liu Y. Turnover atlas of proteome and phosphoproteome across mouse tissues and brain regions. Cell 2025, 188: 2267-2287.e21. PMID: 40118046, PMCID: PMC12033170, DOI: 10.1016/j.cell.2025.02.021.Peer-Reviewed Original ResearchConceptsMouse tissuesNeurodegeneration-related proteinsPost-translational modificationsImpact of phosphorylationStable isotope labelingLong-lived proteinsPeroxisomal proteinsProtein lifetimeProteomic propertiesProtein phosphorylationProtein stabilityInteractive web-based portalProtein abundanceProtein turnoverPhosphorylationMammalian tissuesComprehensive resourceProteinIsotope labelingProteomicsA-synucleinAbundanceTurnoverTurnover changesPhosphositesHuman and mouse proteomics reveals the shared pathways in Alzheimer’s disease and delayed protein turnover in the amyloidome
Yarbro J, Han X, Dasgupta A, Yang K, Liu D, Shrestha H, Zaman M, Wang Z, Yu K, Lee D, Vanderwall D, Niu M, Sun H, Xie B, Chen P, Jiao Y, Zhang X, Wu Z, Chepyala S, Fu Y, Li Y, Yuan Z, Wang X, Poudel S, Vagnerova B, He Q, Tang A, Ronaldson P, Chang R, Yu G, Liu Y, Peng J. Human and mouse proteomics reveals the shared pathways in Alzheimer’s disease and delayed protein turnover in the amyloidome. Nature Communications 2025, 16: 1533. PMID: 39934151, PMCID: PMC11814087, DOI: 10.1038/s41467-025-56853-3.Peer-Reviewed Original ResearchConceptsAlzheimer's diseaseProtein turnoverMouse model of amyloidosisMulti-omics analysisMurine model of Alzheimer's diseaseModel of Alzheimer's diseaseModel of amyloidosisProteome turnoverMouse proteomeGenetic incorporationAD pathwayAmyloid formationBrain proteomeMulti-OmicsProteomic strategyAD progressionProteomicsProtein alterationsProteinDisease mechanismsAmyloidPathwayPotential targetMouse brainTurnover
2024
Multiscale modeling uncovers 7q11.23 copy number variation–dependent changes in ribosomal biogenesis and neuronal maturation and excitability
Mihailovich M, Germain P, Shyti R, Pozzi D, Noberini R, Liu Y, Aprile D, Tenderini E, Troglio F, Trattaro S, Fabris S, Ciptasari U, Rigoli M, Caporale N, D’Agostino G, Mirabella F, Vitriolo A, Capocefalo D, Skaros A, Franchini A, Ricciardi S, Biunno I, Neri A, Kasri N, Bonaldi T, Aebersold R, Matteoli M, Testa G. Multiscale modeling uncovers 7q11.23 copy number variation–dependent changes in ribosomal biogenesis and neuronal maturation and excitability. Journal Of Clinical Investigation 2024, 134: e168982. PMID: 39007270, PMCID: PMC11245157, DOI: 10.1172/jci168982.Peer-Reviewed Original ResearchConceptsCopy number variationsWilliams-Beuren syndromeRibosome biogenesisP-RPS6Neurodevelopmental disordersRibosomal genesP-4EBPNumber variationsTranslation factorsMicroduplication syndromeMolecular mechanismsGenesNeuronal differentiationPatient-derivedIntrinsic excitabilityMTOR pathwayBiogenesisNeuronal maturationPhosphorylated rpS6Neuronal transmissionWilliams-BeurenPathophysiological relevanceNeurocognitive featuresIntellectual disabilityDisease models
2020
Strategies to enable large-scale proteomics for reproducible research
Poulos R, Hains P, Shah R, Lucas N, Xavier D, Manda S, Anees A, Koh J, Mahboob S, Wittman M, Williams S, Sykes E, Hecker M, Dausmann M, Wouters M, Ashman K, Yang J, Wild P, deFazio A, Balleine R, Tully B, Aebersold R, Speed T, Liu Y, Reddel R, Robinson P, Zhong Q. Strategies to enable large-scale proteomics for reproducible research. Nature Communications 2020, 11: 3793. PMID: 32732981, PMCID: PMC7393074, DOI: 10.1038/s41467-020-17641-3.Peer-Reviewed Original ResearchGerm‐free and microbiota‐associated mice yield small intestinal epithelial organoids with equivalent and robust transcriptome/proteome expression phenotypes
Hausmann A, Russo G, Grossmann J, Zünd M, Schwank G, Aebersold R, Liu Y, Sellin ME, Hardt W. Germ‐free and microbiota‐associated mice yield small intestinal epithelial organoids with equivalent and robust transcriptome/proteome expression phenotypes. Cellular Microbiology 2020, 22: e13191. PMID: 32068945, PMCID: PMC7317401, DOI: 10.1111/cmi.13191.Peer-Reviewed Original Research
2019
Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma
Gao Q, Zhu H, Dong L, Shi W, Chen R, Song Z, Huang C, Li J, Dong X, Zhou Y, Liu Q, Ma L, Wang X, Zhou J, Liu Y, Boja E, Robles A, Ma W, Wang P, Li Y, Ding L, Wen B, Zhang B, Rodriguez H, Gao D, Zhou H, Fan J. Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma. Cell 2019, 179: 561-577.e22. PMID: 31585088, DOI: 10.1016/j.cell.2019.08.052.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsbeta CateninCarcinoma, HepatocellularCell ProliferationCohort StudiesFemaleFructose-Bisphosphate AldolaseGene Expression ProfilingGene Expression Regulation, NeoplasticHep G2 CellsHepatitis B virusHepatitis B, ChronicHumansLiver NeoplasmsMaleMiceMice, Inbred BALB CMiddle AgedProteogenomicsTumor MicroenvironmentConceptsHepatitis B virus (HBV)-related hepatocellular carcinomaHBV-related HCCMetabolic reprogrammingHepatocellular carcinomaProteogenomic characterizationHBV-related hepatocellular carcinomaCell proliferationAdjacent liver tissuesIntegrative proteogenomic analysisMicroenvironment dysregulationBenefit clinical practiceTumor thrombusPatient survivalPaired tumorPrognostic biomarkerMetabolic profileActivation statusClinical practiceGenetic profileCarcinomaLiver tissueTumorSignaling pathwayPromote glycolysisPatientsComparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins
Shao W, Guo T, Toussaint N, Xue P, Wagner U, Li L, Charmpi K, Zhu Y, Wu J, Buljan M, Sun R, Rutishauser D, Hermanns T, Fankhauser C, Poyet C, Ljubicic J, Rupp N, Rüschoff J, Zhong Q, Beyer A, Ji J, Collins B, Liu Y, Rätsch G, Wild P, Aebersold R. Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins. Nature Communications 2019, 10: 2524. PMID: 31175306, PMCID: PMC6555818, DOI: 10.1038/s41467-019-10513-5.Peer-Reviewed Original ResearchConceptsProtein degradationMass spectrometric methodDegradation of mRNAAnalysis of mRNASpectrometric methodStability of proteinsMass spectrometryRNA-seqIndicator of sample qualitySWATH mass spectrometryDegree of protein degradationMRNA degradationClinical sample cohortsProteomic analysisClinical tissuesProteinMRNAMolecular measurementsConfounding conclusions
2017
Impact of Alternative Splicing on the Human Proteome
Liu Y, Gonzàlez-Porta M, Santos S, Brazma A, Marioni JC, Aebersold R, Venkitaraman AR, Wickramasinghe VO. Impact of Alternative Splicing on the Human Proteome. Cell Reports 2017, 20: 1229-1241. PMID: 28768205, PMCID: PMC5554779, DOI: 10.1016/j.celrep.2017.07.025.Peer-Reviewed Original ResearchConceptsProteomic diversityAlternative splicingAlternative splicing eventsDifferential transcript usageIntron retentionSplicing eventsHuman transcriptomeHuman proteomeTranscript usageRNA sequencingProtein abundanceTranscript levelsHuman diseasesProteomeSWATH-MSSplicingQuantitative snapshotIntegrative approachCritical determinantDiversityTranscriptomeSequencingAbundanceMRNAQuantitative manner
2016
Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity
Zhong Q, Rüschoff JH, Guo T, Gabrani M, Schüffler PJ, Rechsteiner M, Liu Y, Fuchs TJ, Rupp NJ, Fankhauser C, Buhmann JM, Perner S, Poyet C, Blattner M, Soldini D, Moch H, Rubin MA, Noske A, Rüschoff J, Haffner MC, Jochum W, Wild PJ. Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity. Scientific Reports 2016, 6: 24146. PMID: 27052161, PMCID: PMC4823793, DOI: 10.1038/srep24146.Peer-Reviewed Original ResearchAgedComputational BiologyDNA Copy Number VariationsEndometrial NeoplasmsFemaleGenetic HeterogeneityGenetic Predisposition to DiseaseHumansImmunohistochemistryIn Situ Hybridization, FluorescenceKaplan-Meier EstimateMaleMiddle AgedMutationNeoplasm StagingNeoplasmsOvarian NeoplasmsProstatic NeoplasmsPTEN PhosphohydrolaseReceptor, ErbB-2Stomach Neoplasms
2015
Multiplexed Targeted Mass Spectrometry-Based Assays for the Quantification of N‑Linked Glycosite-Containing Peptides in Serum
Thomas SN, Harlan R, Chen J, Aiyetan P, Liu Y, Sokoll LJ, Aebersold R, Chan DW, Zhang H. Multiplexed Targeted Mass Spectrometry-Based Assays for the Quantification of N‑Linked Glycosite-Containing Peptides in Serum. Analytical Chemistry 2015, 87: 10830-10838. PMID: 26451657, PMCID: PMC4708883, DOI: 10.1021/acs.analchem.5b02063.Peer-Reviewed Original ResearchConceptsGlycosite-containing peptidesClinical Proteomic Tumor Analysis ConsortiumParallel reaction monitoringNational Cancer Institute's Clinical Proteomic Tumor Analysis ConsortiumCommon protein modificationsProtein glycosylationProtein modificationBiological functionsAnalysis ConsortiumRelative abundanceTargeted Mass SpectrometryPRM assaysRobust assayPeak area ratioRelative peak area ratiosGlycoproteinReaction monitoringAssaysHuman serumMass spectrometryDisease statesPeptidesProstate cancer patient seraMS assayGlycosylation
2014
Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness*
Liu Y, Chen J, Sethi A, Li QK, Chen L, Collins B, Gillet LC, Wollscheid B, Zhang H, Aebersold R. Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness*. Molecular & Cellular Proteomics 2014, 13: 1753-1768. PMID: 24741114, PMCID: PMC4083113, DOI: 10.1074/mcp.m114.038273.Peer-Reviewed Original ResearchConceptsN-acylethanolamine acid amidaseProtein tyrosine kinase 7Non-aggressive prostate cancerTyrosine kinase 7Prostate cancerKinase 7N-glycositesDiverse biological processesPotential tissue biomarkersAggressive prostate cancerPCa tumor tissuesSWATH mass spectrometryTissue microarray analysisProstate cancer tissuesUrgent clinical needIdentification of biomarkersHuman proteomePCa aggressivenessMicroarray analysisBiological processesPCa casesTissue biomarkersTumor aggressivenessNormal prostateCancer tissues
2013
Quantitative measurements of N‐linked glycoproteins in human plasma by SWATH‐MS
Liu Y, Hüttenhain R, Surinova S, Gillet L, Mouritsen J, Brunner R, Navarro P, Aebersold R. Quantitative measurements of N‐linked glycoproteins in human plasma by SWATH‐MS. Proteomics 2013, 13: 1247-1256. PMID: 23322582, DOI: 10.1002/pmic.201200417.Peer-Reviewed Original Research
2011
A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer
Luo X, Liu Y, Wang R, Hu H, Zeng R, Chen H. A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer. Journal Of Proteomics 2011, 74: 528-538. PMID: 21262398, DOI: 10.1016/j.jprot.2011.01.011.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerCellular proteomeCell lung cancerCancer secretomeLung cancerOne-dimensional gel electrophoresisA549 cellsBiomarker discoveryProteomic dataGene expressionSecretory proteinsIntracellular contaminationNovel promising biomarkerNovel serum biomarkersEnzyme-linked immunosorbent assaySecretomeProteinSerum proteomic dataClinical stagingProteomeSerum biomarkersGel electrophoresisC4BP levelsPromising biomarkerImmunosorbent assay
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