个体化医疗的现状与未来-生物标志物1

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个体化医疗的现状与未来四.生物标志物研究吕林莉M.D.,Ph.D.东南大学医学院 Outline生物标志物的概念如何评价生物标志物？生物标志物的研究方法？ 生物标志物的概念 什么是生物标志物(biomarker)？“measurableandquantifiablebiologicalparameters”--aMedicalSubjectHeading(MeSH)term,1989“Acharacteristicthatisobjectivelymeasuredandevaluatedasanindicatorofnormalbiologicalprocesses,pathogenicprocessesorpharmacologicalresponsestoatherapeuticintervention.”--BiomarkerDefinitionsWorkingGroup,2001,NIH FeaturesofaUsefulBiomarkerHighsensitivityandspecificityEasyaccessiblesampleCorrelationwithhistologicalscoringChangeinadvanceofclinicalsignsTranslationalfromresearchtoclinicaluse 不同水平生物标志物DNAPrimarytranscriptmRNATranscriptionproteinTranslationRNAprocessingNucleus BiomarkerExamplesCholesterolisoneofthemostwell-knownbiomarkersofcardiovascularhealthPhysicalmeasurements:bodytemperature(fever);bloodpressure(strokerisk)Otherbiomarkers:•bloodsugarlevel(diabetes)•antigens(hepatitis)•proteins(heartattack)•geneticvariations(Huntington’sdisease) 生物标志物的临床应用LudwigJAetal.Naturereviews2005,5:845-856 目前临床很多疾病的诊断依赖病理诊断，但不能作为常规筛查、监测手段众多疾病缺乏早期、特异性生物标志物治疗缺乏个体化方案生物标志物应用现状 ClinJAmSocNephrol3:1895–1901,2008.Biomarkersforchronickidneydisease Arewetreatingsub-populations?疾病药物无反应率抑郁SSRIs,SNRIs,TCAs40-60%哮喘ß-adrenergics,LTD44-75%糖尿病Sulfonylurea,Biguanides,Glitazones50-75%肿瘤(乳腺癌肺癌)Various70-100%FromKalow,Tyndale&Meyer,Pharmacogenomics,2001 NovelbiomarkersareneededEarly,accuratediagnosis-IndividualizedtherapyandimprovedtreatmentoutcomesBetterdefinedpopulationswillallowmorespecificdrugs-Betterefficacy-Fewersideeffects “Theuseofbiomarkerswillchangemedicalpracticefromapopulation-basedapproachtoanindividualizedapproach”FelixFrueh,AssociateDirectorofGenomicsatCDER,FDA Evolutionofthebiomarkersresearch HighplasmacholesterolandcardiovasculardiseasesNearly50percentofallfuturemyocardialinfarctionandstrokeeventsoccurinthosewithnormalorbelownormallipidlevels.EUROASPIREStudyGroup,1997%ofMI Additionalbiomarkers(inflammation)Hs-CRPandcardiovascularriskHs-CRPisthemostwidelystudiedbiomarkerofinflammationincardiovascularrisk.Sincetheearly1990swiththedevelopmentofhighlysensitiveassaysforitsmeasurement,correlationsofhs-CRPwithbothcardiovascularriskfactorsandfuturecardiovasculareventshasbeenpossible. CRPandLDL–ClevelsandtheriskofcardiovasculardiseasesC-ReactiveProtein(mg/L)<1.01.0-3.0>3.0<130130-160>160LDL-cholesterol(mg/dL)3.02.01.00.0MultivariableRelativeRiskIncreasedCRPlevelsareassociatedwithincreasedriskofcardiovasculareventsindependentlyofLDL-ClevelsRidkerPMetal.,200227,939women HighCRP-highLDLHighCRP-lowLDLLowCRP-lowLDLLowCRP-highLDLPorbabilityofEvent-freeSurvivalYearsofFollow-up0.990.980.970.960.001.0002468Evolutionofthebiomarkersresearch:CRPandLDL-Clevelsandevent-freesurvivalamongwomen27,939womenThemedianvalueswereasfollows:C-reactiveprotein:1.52mg/LLDLcholesterol:123.7mg/dLor:3.20mmol/LCRPandLDL-Ccouldgivebetterprognosticinformationthanthetwomarkersseparately.RidkerPMetal.,2002 如何评价生物标志物？ 常用评价指标（一）敏感性（二）特异性（三）Youden指数（四）阳性似然比（五）阴性似然比（六）阳性预报值（七）阴性预报值（八）ROC曲线 ECG诊断试验的结果ECG诊断结果心肌梗塞合计出现不出现阳性阴性合计416(TP)9（FP）425104(FN)171（TN）275520180700(N)一、敏感性（Sensitivity):TP/(TP+FN)=TPR(truepositiverate)TRP=Sen=416/(416+104)=0.8该指标只与病例组有关，反映了诊断试验检出病例的能力 ECG诊断试验的结果ECG诊断结果心肌梗塞合计出现不出现阳性阴性合计416(TP)9（FP）425104(FN)171（TN）275520180700(N)二、特异性（Specificity)Spe=Truenegativerate(TNR)=TN(FP+TN)=171/(171+9)=0.95该指标只与对照组有关，反映了诊断试验排除非病例的能力。 灵敏度与特异度的优缺点优点：灵敏度与特异度不受患病率的影响，其取值范围均在（0,1）之间，其值越接近于1，说明其诊断准确性越好。缺点：当比较两个诊断试验时，单独使用灵敏度或特异度，可能出现矛盾。解决办法：将两指标结合：Youden指数、阳性似然比、阴性似然比等 ECG诊断试验的结果ECG诊断结果心肌梗塞合计出现不出现阳性阴性合计416(TP)9（FP）425104(FN)171（TN）275520180700(N)三、Youden指数，=Sen+Spe-1=TPR-FPR=0.8-0.05=0.75Youden指数取值范围在（0，1）之间，其值越接近1，诊断准确性越好。 ECG诊断试验的结果ECG诊断结果心肌梗塞合计出现不出现阳性阴性合计416(TP)9（FP）425104(FN)171（TN）275520180700(N) ECG诊断试验的结果ECG诊断结果心肌梗塞合计出现不出现阳性阴性合计416(TP)9（FP）425104(FN)171（TN）275520180700(N) 医生最关心的问题：1.试验阳性时患病的概率多大？2.试验阴性时不患病的概率多大？ 阳性预测值是在诊断试验阳性的受试者中，标准诊断有病的病例（真阳性）所占的比例 阴性预测值则是在诊断试验为阴性的受试者中，标准诊断证实无病的受试者（真阴性）所占的比例。 ECG诊断结果心肌梗塞合计出现不出现阳性阴性合计416(TP)9（FP）425104(FN)171（TN）275520180700(N) 阳性预报值与阴性预报值 ROC曲线 ROC（receiveroperatingcharacteristic的缩写，译为“接受者工作特征”）ROC曲线研究历史1950’s雷达信号观测能力评价1960’s中期实验心理学、心理物理学1970’s末与1980’s初诊断医学ROC的涵义与起源 不同诊断界值时灵敏度与特异度间的平衡(tradeoff)0204060801005060708090100特异度灵敏度百分率（％） ReceiverOperatingCharacteristiccurveAreaUnderCurve(AUC)-GraphedCurve1=.50Purechance…nobetterthanrandomguessCurve3isbetterthanCurve2Curve4=1.0TotallySensitivecompletelyaccurateclassificationofeffectivelyandless-effectivelyinstructedstudents 完美与无用的ROC曲线真阳性率即灵敏度假阳性率即1－特异度机率线(chanceline)(diagonalreferenceline) 诊断准确度较低（<0.7）0.00.20.40.60.81.00.00.20.40.60.81.0FPRTPRA＝0.664A＝0.830诊断准确度较高（>0.9）0.00.20.40.60.81.00.00.20.40.60.81.0FPRTPRA＝0.938ROC曲线下面积（Area）与诊断准确度高低高0.90-1.00=excellent(A)中0.80-0.90=good(B)0.70-0.80=fair(C)低0.60-0.70=poor(D)0.50-0.60=fail(F) ROC曲线小结ROC曲线反映了灵敏度与特异度间的平衡(增加灵敏度将降低特异度；增加特异度将降低灵敏度)。在ROC曲线空间，如果曲线沿着左边线，然后沿着上边线越紧密，则试验准确度越高。在ROC曲线空间，如果曲线沿着机会线（45度对角线）越紧密，则试验准确度越低。ROC曲线下面积是重要的试验准确度指标。 生物标志物研究方法 phasePhase1PreclinicalExploratoryPhase2ClinicalAssayandValidationPhase3RetrospectiveLongitudinalPhase4ProspectiveScreeningPhase5DiseasecontrolObjectiveTargetbiomarkeridentification,feasibilityStudyassayinpeoplewithandwithoutdiseaseCase-controlstudiesusingspecimensLongitudinalstudiestopredictdiseaseClinicaluseSiteBiomarkerdevelopmentlabBiomarkervalidationlabClinicalepidemiologiccentersCohortstudiesCommunityDesignCross-sectionalCross-sectionalCase-controlprospectiveRCTSamplesizesmallsmallmodestmediumlargeVasanRS.Circulation.2006;113:2335-2362. TheAgendiaMammaPrintTest首个FDA批准的基因组检测试验--Feb.2007 Howtheygotthere？2002–Discoveryof70genesignature(117patients)2002–Duplicationofresults(inanothersampleset:295patients)2006–Assayperformance2006–Optimizedarrayformat:reproducibility;backtooriginalsampleset2006–Externalconfirmation(307patients,5hospitals)2007–ApprovalbyFDA 生物标志物研究技术传统研究方法：PCR,Westernblotting,ELISA,etal新型研究方法：基因组学技术蛋白质组学技术：2-DIGE/MS,蛋白质芯片 生物标志物研究方法Question1.Whathumansamplesshouldbecollected,andhowshouldtheybeused?Doesthisvarybetweendiscovery,validationandimplementation? Answer1.AllbiologicalsamplesareeligibleforcollectionCollectedbiologicalmaterialdependsonanalyteandtissuesourceExamples–Biologicalfluids•Serum,plasma,urine,csf•Secretions•Saliva,seminalfluid–Bodycavityfluids•Pleuralfluid,peritonealfluid,etc–Specifictissuematerial•Specializedcells–reproductivecells–Non-cellular Ideal–Biomarkerdiscoverysamplesshouldbeidenticaltotheprojectedtestingsituation–(e.g.Donotstudyplasmafordiscovery,andthenvalidateorimplementassayusingserum)Practical–setupstudywithsamplesthatareasclosetothetestingsituationaspossible Question2.Whatistheroleofroutinelyaccessiblebiofluidssuchasplasma,serum,andurine?Whatistheroleof“proximal”fluidslikeCSF,synovialfluid,ascites,pancreaticductalfluid,etc?Whatistheroleofsolidtissues? RoleofroutinelyaccessiblebiofluidsVeryimportantinthediscoveryofbiomarkersofdiseases(systemicvs.organspecific/local)Importantfor:–earlydetection–diseaseseverity–tumorburden–prognosis–monitoringofresponsetotherapy “Proximalfluids”–CanreflectdiseaseperturbationsintheorgansortissuesfromwhichtheyaresecretedSolidtissues–Veryimportantforthedevelopmentofnovelinsitubiomarkers•Immunofluorescence,immunocytochemistry•Imagingmassspectrometry Question3.Musthumansamplecollectionbeprospective,orcanexistingrepositoriesbeused?Whatconsiderationsareimportantindeterminingtheadequacyofrepositorysamples? Answer3:UltimateconfirmationofthevalidityofabiomarkerhastobeproveninaprospectivestudyNevertheless,welldesignedretrospectivestudiesusingwellcharacterizedsamplesinrepositoriescanbeperformedandfrequentlyyieldviablecandidates 生物标志物研究面临的挑战Themultidisciplinarynatureofbiomarkerdiscovery&developmentComplexMultipledisciplinesHeterogeneouspopulationsStandardsnotestablishedExpensiveHumanresourcesMultipletechnologies