1、Thank you for viewing this presentation.We would like to remind you that this material is the property of the author.It is provided to you by the ERS for your personal use only,as submitted by the author.2008 by the authorHarvesting Biomarkers for Early Risk Assessment Pan-Chyr Yang MD,PhD National
2、Taiwan University Institute of Biomedical SciencesNational Research Health InstituteWhy Lung Cancer?Why Need Biomarker?nEarly metastasis,poor treatment outcome nEast and West are different nPharmacogenomics of EGFR mutationsnPrognostic and predictive biomarkersnNovel treatment targetsnTowards person
3、alized therapyLung Cancer with Early MetastasisnFemale,nonsmoker,adenocanDiagnosis late,operable 30%nPoor treatment outcomenEarly metastasisEarly Relapse in Stage I Lung Cancer PatientMr.Tseng,67 year-old Adenocarcinoma IBTumor recur 6 months after operationMarch 2007Oct 2007Gefitnib 250mg 4 weeksPr
4、etreatmentTarget Therapy of Lung Cancer Delayed Diagnosis and Early MetastasisSource:American Cancer Society 2006Lung Cancer Natural History and Personalized TherapyTime(m)Tumor Size(cm)DiagnosisHigh RiskLow RiskQuality of Life and Lung Cancer TherapyTime(m)Quality of LifeTarget TherapyChemotherapyB
5、iomarkersDiagnostic:Disease diagnosis,classification,monitoringPrognostic:Estimating patients outcome independent of therapeutic decisionPredictive:Markers useful to make therapeutic decision Four Levels of BiomarkersGeneGenomeEpigenomeDNA MethylationProteomeProteinTranscriptomeTranscript(Glyco-,Pho
6、spho-)Modified from SEQUENOM Lung Cancer in East Asia A Unique DiseaseThe EastThe WestEtiology Smoker in male pts Smoker in female pts Female Adenocarcinoma50-60%10%60-80%80-90%80%30-40%Objective Chemotherapy Response40-70%20-40%Median Survival for Advanced Disease (IIIB+IV)12-24 m 8-12 mResponse Ra
7、te to EGFR-TKI Unselected patients First line30-40%50-70%10%(Chang A,J Thoracic Oncol 2006)18192120 C-helixP-loopA-loopDeletions 46%L858R(39%)Duplications/insertions(9%)N-lobeC-lobeTransmembraneregionExtracellular domainRegulatorydomainATP binding cleftTKdomainDistribution of Mutations in EGFR TK Do
8、main:Meta-analysis (n=1256)Lung Adenoca is not just one cancer-East and West are Different-CaucasiansEast AsiaEGFR(10%)KRAS(30%)ERBB2(10%)MET(10%)Unknown(Others)EML4-ALKEGFR(30-40%)KRAS(5%)ERBB2(10%)MET(10%)Unknown(Others)EML4-ALKPhase II Trials of First-line EGFR-TKI Monotherapy in NSCLCPatientsaNo
9、.evaluable ORR,%DCR,%GefitinibEast AsianLee et al 2005Suzuki et al 2005Kasahara et al 2005Yang et al 2008N-smokers,adenoPS 0-1PS 0-1Enriched54343010661.126.533.350.972.2NR63.382.1CaucasianSpiegel et al 2005Reck et al 2006DAddario 2007PS 2-3PS 0-1725863458504524ErlotinibGiaccone et al 2005Jackman et
10、al 200770 years old535522.71052.851a All patients were CT nave;patients had stage III/IV NSCLC,PS 02 unless specified otherwise;NR,not reported N mutR RR PFS OSSutani et al.BJC 2006 2738%78%9.4M 15.4MInoue et al.JCO 20061633%75%9.7MAsahina et al.BJC 2006 1624%75%8.9MYoshida JTO 20072141%90.5%7.7MSeq
11、uist et al.JCO 20083135%58%8.9M 17.5MYang et al.JCO 20085561%69%8.9M 24.0MGefitinib in NSCLC with EGFR Mutation PFS=progression-free survival;OS=overall survivalPFS in EGFR mutation-positive and wild-type patients(IPASS)EGFR mutation-positiveEGFR wild-typeProbability of PFS1.00.80.60.40.20Probabilit
12、y of PFS1.00.80.60.40.200481216202404812162024MonthsMonths1321087131113012910337 7 210At risk:GefitinibC/P9121 421008558141000Gefitinib(n=132)Carboplatin/paclitaxel(n=129)HR(95%CI)=0.48(0.36,0.64)p0.0001Gefitinib(n=91)Carboplatin/paclitaxel(n=85)HR(95%CI)=2.85(2.05,3.98)p0.0001IPASS Study GroupT790M
13、:Primary Resistance to Gefitinib(Shih JY,et al.N Engl J Med 2005)Exon 21Exon 20L858RT790MLymphocyte DNATumorDNAAcquired Resistance in NTUHnT790M:14/24(58%)8/11:L858R 6/13:Del 19nC-Met amplification:5/24(21%)2/11:L858R 3/13:Del19nBoth T790M+Met amplification:3(Bean J et al.PNAS 2007)C-Met amplificati
14、onL858R(2573 TG)2573 2573 G TT790M(2369 CT)unextend2369 2369 C TT/GC/TunextendSensitivity:10copies,QuantifiableSu KY et al 2008Genome-Wide Identification of Novel Marker for Cancer MetastasisEstablish in vitro metastasis cell line modelProteomic identification of novel markers Genome-wide profiling
15、of differentially expressed metastasis related genesCharacterize novel metastasis-related genesBiomarkers for diagnosis,prognosis prediction and therapyLung Cancer Invasion Cell Line ModelNo.Invaded Cells050010001500CL1CL1-1CL1-2CL1-3CL1-4CL1-5(Chen JJW et al.Cancer Res 2001)Medium 1Medium 2Membrane
16、 Invasion Culture IV Metastasis Assay in SCID MiceNM23CL1-0CL1-5Microarray and Pathway Analysis192325413476(CRSD:Liu CC et al.NAR 2006)Risk scoreHigh riskgeneRelative expression level;Low riskgene2.3-2.3Risk Score=0.47NF1+0.51HGF+0.52HMMR+0.52IRF4+0.55ZNF264+0.55ErbB3+0.59STAT2+0.59CPEB4+0.65RNF4+0.
17、75DUSP6+0.92MMD+1.32DLG2-1.09ANXA5-0.84LCK-0.77FRAP1-0.58STAT1(Chen HY et al.NEJM 2007)Microarray Gene Signature and Lung Cancer Outcome(Yu SL et al.Cancer Cell 2008)miR-137miR-182*miR-372miR-221Let-7aMicroRNA Signature Predicts NSCLC Outcome Low riskN=31High riskN=16All N=47Overall survivalLow risk
18、N=15High riskN=13All N=28Low riskN=12High riskN=25All N=37MonthsMonthsMonthsRelapse-free survivalMonthsMonthsMonthsLow riskN=31High riskN=16All N=47Low riskN=15High riskN=13All N=28Low riskN=12High riskN=25All N=37P=0.044P=0.047P=0.004P=0.031P=0.046P=0.076Stage IStage IIStage IIIMicroRNA Signature o
19、f NSCLC:Subgroup Analysis(Yu SL et al.Cancer Cell 2008)Gene Signature for Lung AdenocarcinomanGene signatures for outcome prediction (Beer D.Nature Med 2002,Bianchi F.JCI 2007,Sun Z.JCO 2008,Lau SK.JCO 2007,Potti A.NEJM 2006,Chen HY.NEJM 2007,etc)nMinimal overlap,non-cell type specific,different sta
20、tistical method,lack of independent validationnLarge,training-testing,multi-site,blind validation Molecular information useful for risk prediction of early stage lung cancer(Shedden K et al.Nature Med 2008)nCombine multiple levels of biomarkers DNA,mRNA biomarkers microRNA(Yu SL et al.Cancer Cell 20
21、08)DNA methylation(Brock M et al.NEJM 2008)Proteomics,Glycoproteome Interaction Networks of Independent Prognostic Gene Sets(Lau SK et al.JCO 2007)Combination of Gene Expression and MicroRNA Signatures and Lung Cancer OutcomeNone(n=24)Two signatures(n=30)Any one signature(n=39)P0.0001Three-year surv
22、ival:nNone:0.91nAny one signature:0.61nTwo signatures:0.16MonthsOverall survivalSignatures:Gene:Chen HY et al,NEJM 2007microRNA:Yu SL et al,Cancer Cell 2008CLDN1 IHC stainingAdenocarcinoma CLDN1 positive stainingNormal bronchial epitheliumSquamous cell carcinomaAdenocarcinoma negative staining(Chao
23、YC et al,AJRCCM 2008)Low CLDN1 (n=32)Time(month)Overall Survivalp=0.027 High CLDN1(n=32)Overall SurvivalTime(month)CLDN1 Negative(n=34)CLDN1 Positive(n=33)p=0.024CLDN1 protein:IHC stainingCLDN1 mRNA:Real time PCR(an independent cohort)(Chao YC et al,AJRCCM 2008)CL1-5/GFP-CLDN1 EGFPCL1-5/EGFP Phase(C
24、hao YC et al,AJRCCM 2008)Strategy Towards Personalized Therapy of Lung Cancer ScreeningEarly detectionDiagnosisstagingInoperableOperableRisk genes,SNPsClinical trial,Spiral CT,othersNew staging system:TNMCMicrometastasisnPredict outcome&metastasisnChemopreventionnClinical trialnPredict chemotherapy
25、response(ERCC1,RRM1)nTarget therapy(EGFR)nClinical trialClinical networkBiomarkersNew methodsGene Signature BiomarkersConclusionnGenomic and proteomic tools facilitate the identification of novel lung cancer biomarkers nLung adenocarcinoma is a distinct disease group with specific pharmacogenomicsnP
26、rognostic and predictive markers are useful for personalized therapy of lung cancernTranslational research to validate biomarkers for clinical application5-Gene Signature for NSCLCnSTAT1:Growth arrest and apoptosisnLCK:lymphocyte-specific protein tyrosine kinase,regulate cancer cell motility and T cell activationnERBB3:v-erb-b2 avain erythroblastic leukemia viral oncogene homolog 3,member of EGFR-TKnMMD:Monocyte-to-macrophage differentiation proteinnDUSP6:Dual-specificity phosphatase 6 Inactivate ERK2,suppress tumor and apoptosis
