2024
Subtyping strokes using blood‐based protein biomarkers: A high‐throughput proteomics and machine learning approach
Misra S, Singh P, Sengupta S, Kushwaha M, Rahman Z, Bhalla D, Talwar P, Nath M, Chakraborty R, Kumar P, Kumar A, Aggarwal P, Srivastava A, Pandit A, Mohania D, Prasad K, Mishra N, Vibha D. Subtyping strokes using blood‐based protein biomarkers: A high‐throughput proteomics and machine learning approach. European Journal Of Clinical Investigation 2024, 55: e14372. PMID: 39655799, DOI: 10.1111/eci.14372.Peer-Reviewed Original ResearchHigh-throughput proteomicsExpressed proteinsSWATH-MSInteraction networkPathway analysisProteomicsProtein biomarkersBlood-based protein biomarkersIntracerebral haemorrhageDifferentiate ISIschemic strokeProteinApo C1Clinical variablesDiscovery phaseMMP-9Multivariate logistic regression analysisLogistic regression analysisCut-off pointCytoscapeProtein Biomarkers in Lung Cancer Screening: Technical Considerations and Feasibility Assessment
Orive D, Echepare M, Bernasconi-Bisio F, Sanmamed M, Pineda-Lucena A, de la Calle-Arroyo C, Detterbeck F, Hung R, Johansson M, Robbins H, Seijo L, Montuenga L, Valencia K. Protein Biomarkers in Lung Cancer Screening: Technical Considerations and Feasibility Assessment. Archivos De Bronconeumología 2024, 60: s67-s76. PMID: 39079848, PMCID: PMC12172408, DOI: 10.1016/j.arbres.2024.07.007.Peer-Reviewed Original ResearchLung cancer screeningLung cancerCancer screeningManagement of lung cancerLDCT-based lung cancer screeningSurgically resected tumorsPresence of metastasesEarly lung cancerCancer-related deathsLung cancer patientsContext of lung cancer screeningDiagnosis to earlier stagesProtein biomarkersResected tumorProtein-based biomarkersTherapeutic optionsAdjuvant strategiesLate diagnosisCancer patientsRecommended management strategiesEarly managementLung cancer detectionRobust biomarkersBenefit patientsCancerPrognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms
Misra S, Kawamura Y, Singh P, Sengupta S, Nath M, Rahman Z, Kumar P, Kumar A, Aggarwal P, Srivastava A, Pandit A, Mohania D, Prasad K, Mishra N, Vibha D. Prognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms. PLOS ONE 2024, 19: e0296616. PMID: 38829877, PMCID: PMC11146689, DOI: 10.1371/journal.pone.0296616.Peer-Reviewed Original ResearchConceptsIntracerebral hemorrhagePoor outcomePrognostic biomarker of ICHBiomarker of intracerebral hemorrhageHazard ratioOdds ratioShort-term poor outcomePrognostic of patient outcomeMMP-2Multivariate Cox regression modelICH prognosisInternal validation of prediction modelsModified Rankin Scale scoreIntracerebral hemorrhage patientsRankin Scale scoreUCH-L1Confidence intervalsCox regression modelsMultivariate logistic regressionProtein biomarkersIGFBP-3Regression modelsPrognostic outcomesSerum biomarkersClinical variables
2021
Exosomes as Emerging Biomarker Tools in Neurodegenerative and Neuropsychiatric Disorders—A Proteomics Perspective
Mathew B, Mansuri MS, Williams KR, Nairn AC. Exosomes as Emerging Biomarker Tools in Neurodegenerative and Neuropsychiatric Disorders—A Proteomics Perspective. Brain Sciences 2021, 11: 258. PMID: 33669482, PMCID: PMC7922222, DOI: 10.3390/brainsci11020258.Peer-Reviewed Original ResearchProtein dynamic rangeDifferent cell typesProteomic perspectiveRNA speciesExosome proteomicsDisease biomarker discoveryIsolation of exosomesProteomics researchCell typesPhysiological statusExosomesCell of originNovel reservoirVariable tissueBiomarker discoveryProteinProtein detectionProtein biomarkersCurrent progressProteomicsBiomarker toolSpeciesLow amountsRapid rateNeuropsychiatric disorders
2020
Associations between Genetically Predicted Blood Protein Biomarkers and Pancreatic Cancer Risk
Zhu J, Shu X, Guo X, Liu D, Bao J, Milne RL, Giles GG, Wu C, Du M, White E, Risch HA, Malats N, Duell EJ, Goodman PJ, Li D, Bracci P, Katzke V, Neale RE, Gallinger S, Van Den Eeden SK, Arslan AA, Canzian F, Kooperberg C, Freeman L, Scelo G, Visvanathan K, Haiman CA, Le Marchand L, Yu H, Petersen GM, Stolzenberg-Solomon R, Klein AP, Cai Q, Long J, Shu XO, Zheng W, Wu L. Associations between Genetically Predicted Blood Protein Biomarkers and Pancreatic Cancer Risk. Cancer Epidemiology Biomarkers & Prevention 2020, 29: 1501-1508. PMID: 32439797, PMCID: PMC7334065, DOI: 10.1158/1055-9965.epi-20-0091.Peer-Reviewed Original ResearchConceptsPancreatic ductal adenocarcinomaProtein quantitative trait lociQuantitative trait lociRisk variantsBlood protein biomarkersPathway enrichment analysisPotential target genesCancer-related pathwaysPDAC riskProtein biomarkersTrait lociTarget genesPancreatic Cancer Case-Control ConsortiumPancreatic Cancer Cohort ConsortiumEnrichment analysisProteinGenetic instrumentsPancreatic cancer riskProtein levelsGenesPDAC developmentProtein biomarker candidatesRisk factorsDuctal adenocarcinomaLethal malignancy
2017
Use of a Targeted Urine Proteome Assay (TUPA) to identify protein biomarkers of delayed recovery after kidney transplant
Williams KR, Colangelo CM, Hou L, Chung L, Belcher JM, Abbott T, Hall IE, Zhao H, Cantley LG, Parikh CR. Use of a Targeted Urine Proteome Assay (TUPA) to identify protein biomarkers of delayed recovery after kidney transplant. Proteomics Clinical Applications 2017, 11 PMID: 28261998, PMCID: PMC5549272, DOI: 10.1002/prca.201600132.Peer-Reviewed Original ResearchConceptsImmediate graft functionKidney transplantGraft functionLong-term graft outcomeMore effective treatmentsProtein biomarkersIGF patientsGraft outcomeIGF levelsPoor outcomeEffective treatmentKidney implantationClinical relevanceBiomarker panelPotential biomarkersUrine proteomeDGFTransplantBiomarkersPatientsOutcomesTreatmentEarly stagesAssaysPrognosisReaching the limits of prognostication in non-small cell lung cancer: an optimized biomarker panel fails to outperform clinical parameters
Grinberg M, Djureinovic D, Brunnström H, Mattsson J, Edlund K, Hengstler J, La Fleur L, Ekman S, Koyi H, Branden E, Ståhle E, Jirström K, Tracy D, Pontén F, Botling J, Rahnenführer J, Micke P. Reaching the limits of prognostication in non-small cell lung cancer: an optimized biomarker panel fails to outperform clinical parameters. Modern Pathology 2017, 30: 964-977. PMID: 28281552, DOI: 10.1038/modpathol.2017.14.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorCarcinoma, Non-Small-Cell LungCell Adhesion Molecule-1Enhancer of Zeste Homolog 2 ProteinGlucose Transporter Type 1HumansImmunohistochemistryIntracellular Signaling Peptides and ProteinsLung NeoplasmsNuclear ProteinsPrognosisThyroid Nuclear Factor 1Tissue Array AnalysisConceptsNon-small cell lung cancerCell lung cancerNon-small cell lung cancer patientsCell lung cancer patientsLung cancer patientsLung cancerBiomarker panelClinical parametersCancer patientsPrognostic associationClinicopathological parametersClinical practicePrognostic modelSurvival predictionProtein expressionBest prognostic modelPrognostic biomarker panelBetter prognostic performanceImmunohistochemistry-based assessmentCorresponding concordance indexProtein biomarkersClinicopathological dataConcordance indexPrognostic performanceTissue microarray
2015
Development of a Targeted Urine Proteome Assay for kidney diseases
Cantley LG, Colangelo CM, Stone KL, Chung L, Belcher J, Abbott T, Cantley JL, Williams KR, Parikh CR. Development of a Targeted Urine Proteome Assay for kidney diseases. Proteomics Clinical Applications 2015, 10: 58-74. PMID: 26220717, PMCID: PMC5003777, DOI: 10.1002/prca.201500020.Peer-Reviewed Original ResearchConceptsKidney diseaseUrinary proteinGraft functionImmediate graft functionDelayed graft functionKidney transplant patientsMultiple kidney diseasesTransplant patientsKidney transplantClinical relevancePotential biomarkersUrine proteomeDiseaseAvailable biofluidBiomarkersPatientsProtein biomarkersAssaysSingle assayProteome changesHuman urineQuantifiable proteinsTransplantProteinPeptidesPrediction of colorectal cancer diagnosis based on circulating plasma proteins
Surinova S, Choi M, Tao S, Schüffler PJ, Chang CY, Clough T, Vysloužil K, Khoylou M, Srovnal J, Liu Y, Matondo M, Hüttenhain R, Weisser H, Buhmann JM, Hajdúch M, Brenner H, Vitek O, Aebersold R. Prediction of colorectal cancer diagnosis based on circulating plasma proteins. EMBO Molecular Medicine 2015, 7: 1166-1178. PMID: 26253081, PMCID: PMC4568950, DOI: 10.15252/emmm.201404873.Peer-Reviewed Original ResearchConceptsColorectal cancer diagnosisBlood-based markersColorectal cancer detectionPatient's systemic circulationColorectal cancerSystemic circulationIndependent cohortCritical clinical needNon-invasive detectionDiagnostic valueClinical needTissue epitheliumCancer diagnosisPlasma samplesBiomarker signaturesPlasma proteinsBlood plasmaProtein biomarkersCancer detectionCandidate glycoproteinsClinical datasetsMass spectrometry-based approachCohortCancerDiagnosis
2014
Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error
Shipitsin M, Small C, Choudhury S, Giladi E, Friedlander S, Nardone J, Hussain S, Hurley AD, Ernst C, Huang YE, Chang H, Nifong TP, Rimm DL, Dunyak J, Loda M, Berman DM, Blume-Jensen P. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. British Journal Of Cancer 2014, 111: 1201-1212. PMID: 25032733, PMCID: PMC4453845, DOI: 10.1038/bjc.2014.396.Peer-Reviewed Original ResearchMeSH KeywordsActininAgedAlkyl and Aryl TransferasesArea Under CurveBiomarkers, TumorBiopsy, Fine-NeedleCullin ProteinsDNA-Binding ProteinsFollow-Up StudiesHSP70 Heat-Shock ProteinsHumansImage Processing, Computer-AssistedMaleMembrane ProteinsMiddle AgedMitochondrial ProteinsNeoplasm GradingNeoplasm StagingPhosphorylationProstateProstatic NeoplasmsProteomicsRibosomal Protein S6RNA-Binding Protein FUSROC CurveSelection BiasSmad2 ProteinSmad4 ProteinTissue Array AnalysisVoltage-Dependent Anion Channel 1Y-Box-Binding Protein 1ConceptsProstate cancer aggressivenessCancer aggressivenessLarge patient cohortLow Gleason gradePatient cohortTumor microarrayLethal outcomeProstatectomy samplesGleason gradeSignificant overtreatmentBiopsy interpretationProstatectomy tissuePatient samplesBiopsy testsProteomic biomarkersCancer biomarker discoveryExpert pathologistsMarker signaturesTumor heterogeneityBiomarkersAggressivenessProtein biomarkersBiomarker discoveryQuantitative proteomics approachAutomated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality
Shipitsin M, Small C, Giladi E, Siddiqui S, Choudhury S, Hussain S, Huang YE, Chang H, Rimm DL, Berman DM, Nifong TP, Blume-Jensen P. Automated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality. Proteome Science 2014, 12: 40. PMID: 25075204, PMCID: PMC4114438, DOI: 10.1186/1477-5956-12-40.Peer-Reviewed Original ResearchProtein levelsPost-translational modificationsProtein-based approachGene-based approachesIntact tissue specimensProtein activityProtein signaturesHuman prostate cancerMolecular informationPredictive protein biomarkersProtein biomarker levelsPhospho-PRAS40Phospho-S6Prostate cancer lethalityTissue lysisSPP1PTENIntact tissueSmad4Cancer lethalityPhenotypeCCND1Morphological featuresProtein biomarkersFunctional activity
2009
Proteomic-Based Detection of a Protein Cluster Dysregulated during Cardiovascular Development Identifies Biomarkers of Congenital Heart Defects
Nath AK, Krauthammer M, Li P, Davidov E, Butler LC, Copel J, Katajamaa M, Oresic M, Buhimschi I, Buhimschi C, Snyder M, Madri JA. Proteomic-Based Detection of a Protein Cluster Dysregulated during Cardiovascular Development Identifies Biomarkers of Congenital Heart Defects. PLOS ONE 2009, 4: e4221. PMID: 19156209, PMCID: PMC2626248, DOI: 10.1371/journal.pone.0004221.Peer-Reviewed Original ResearchConceptsCardiovascular developmentMass spectrometry-based proteomicsSpectrometry-based proteomicsNormal cardiovascular developmentAdhesion/migrationHuman CHDsProteomic datasetsHeart developmentProtein clustersMurine embryosProtein pathwayMolecular pathwaysFunctional roleProteinEmbryonic survivalYolk sacProtein levelsIdentifies biomarkersCardiovascular defectsWestern blottingPathwayNovel avenuesEmbryosComplete understandingProtein biomarkers
2007
Proteomics: A Novel Methodology to Complement Prenatal Diagnosis of Chromosomal Abnormalities and Inherited Human Diseases
Bahtiyar M, Copel J, Mahoney M, Buhimschi I, Buhimschi C. Proteomics: A Novel Methodology to Complement Prenatal Diagnosis of Chromosomal Abnormalities and Inherited Human Diseases. American Journal Of Perinatology 2007, 24: 167-181. PMID: 17372862, DOI: 10.1055/s-2007-972927.Peer-Reviewed Original ResearchMeSH KeywordsAneuploidyChromosome AberrationsElectrophoresis, Polyacrylamide GelFemaleGene Expression ProfilingGenetic Diseases, InbornHumansMass SpectrometryNuchal Translucency MeasurementPregnancyPregnancy Trimester, FirstPregnancy Trimester, SecondPrenatal DiagnosisProtein Processing, Post-TranslationalProteomicsRisk AssessmentSensitivity and Specificity
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