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Pharmacogenetics in the treatment of breast and ovarian cancer patients. Peter A. Fasching. UCLA. David Geffen School of Medicine Div. Hem/Onc. Concepts of science. Therapy A. Therapy B. Therapy A must be better. Pitfalls with this approach. Will this patient have a recurrence?.
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Pharmacogenetics in the treatment of breast and ovarian cancer patients Peter A. Fasching UCLA David Geffen School of Medicine Div. Hem/Onc
Concepts of science Therapy A Therapy B Therapy A must be better 2
Pitfalls with this approach Will this patient have a recurrence? Therapie A A: Therapy helped, and the patient has no recurrence. B: Patient would not have gotten a recurrence anyway 3
AimA priori identification of patients with a benefit from the offered therapy Test Therapy will improve outcome Therapy will NOT improve outcome 4
Biomaterials that could be helpful Gene expressions From stromal cells SNP Chips (Germline-DNA) Gene copy variations Gene expression Profiling (WBC) Gene expression profiles Epigentic Profiling Epigenetic Profiling (circulating nucleic acids) miRNA Profiling miRNA Profiling Mutation Profiling Proteomics 5
Biomaterials that could be helpful SNP Chips (Germline-DNA) Can predict: -Efficacy -Toxicity Can discover: -functional explanation of differential response to chemotherapy 6
CYP2D6 Genotypingas a predictivemarker(Schroth, Goetz, Hamann, Fasching et al. JAMA 2009) • N=1325 ER positive Breast Cancer Patients • All treatedwith Tamoxifen • Genotyping CYP2D6 • *3, *4, *5, *10, *41 • Metabolizing Groups • EM=extensive Metabolizers • IM=Intermediate Metabolizers • PM=Poor Metabolizers 8
How many Single nucleodide Polymorphisms are out there? About 3.3 Billion basepairs about 24,000 genes
How many Single nucleodide Polymorphisms are out there? 2001 Image Source: The Sanger Institute >1,000,000 SNPs tobeanalyzedbychiptechnology on onechip 2006 2009/ 2010
How to analyze and present 1,000,000 associations between genetic variations and the phenotype? P=0,0000001 P=0,9 P=0,001
P=0,00001 P=0,0001 P=0,001 P=0,01 P=0,1 P=1
Conditional Logistic Regression Analyses* -log10(p-value) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 22 23 Chromosome Position Ingle et al. San Antonio 2010
How to do the work? • Clinical collaborators with well designed studies(!!!) • Biosampling infrastructure • Genotyping Facility • Biostatistics/Bioinformatics • Functional Explanation • Clinical collaborators for clinical validation
SUCCESS A Study: Simultaneous Study ofGemcitabine-DocetaxelCombinationadjuvanttreatmentSurveillance-Trial (n=3725) (PI: Prof. Dr. W. Janni) F F F DcT DcT DcT Zoledronate 2 years E E E C C C R R F F F DcT DcT DcT Zoledronate 5 years E E E G G G C C C Primary Objective Disease free Survival Secondary Objectives Overall Survival, Toxicity, Quality of Life C E =Epirubicin =Cyclophosphamide DcT F G =Docetaxel = 5-Flourouracil =Gemcitabine 21
Pre-planned Pharmacogenetic subprotocol • 3602 out of 3754 patients (96%) provided DNA Samples (just one blood tube!!) • Collaborative application of Mayo Clinics (PI Dr. Weinshilboum) and SUCCESS Study Group (Co-PI Dr. Fasching) for NIH funding • NHGRI HG01 granted as part of a funding program for genome wide association studies for randomized trials
Structures for this collaboration Clinical Collaborators SUCCESS A Study (GeparQuinto Study) NIH NHGRI GARNET (www.garnetstudy.org) Mayo Collaborators PGRN Biostatistics Molecular Pharmacology Hematology / Oncology Genotype Core Facility Blood Processing DNA Extraction DNA Normalization DNA Plating Genotyping Plate Map Design Genotype Quality Control DNA Storage DNA Analysis SNP Chip Processing • Coordination • Collborationwithother Groups • Working groups on • PhenotypeHarmonization • GenotypeHarmonization • Statistical Methology • EthicalConsiderations • Cross Validation • Further Clinical Validation Biostatistics Phenotype Quality Control Gx and Phx Data Cleaning Provision of Analysis Data Management Data entry Data Monitoring Data updates Cell Line Program Human Variation Panel BC Panel (UCLA)
Structures for this collaboration Clinical Collaborators SUCCESS A Study (GeparQuinto Study) NIH NHGRI GARNET (www.garnet.org) Mayo Collaborators Biostatistics Molecular Pharmacology Hematology / Oncology Genotype Core Facility Blood Processing DNA Extraction DNA Normalization DNA Plating Genotyping Plate Map Design Genotype Quality Control DNA Storage DNA Analysis SNP Chip Processing • Coordination • Collborationwithother Groups • Working groups on • PhenotypeHarmonization • GenotypeHarmonization • Statistical Methology • EthicalConsiderations • Cross Validation • Further Clinical Validation Biostatistics Phenotype Quality Control Gx and Px Data Cleaning Provision of Analysis Data Management Data entry Data Monitoring Data updates Cell Line Program Human Variation Panel BC Panel (UCLA)
Mayo PGRN - “Human Variation Panel” Cell Lines UCLA – Human Individual Breast Cancer Cell Lines MAYO - 300 lymphoblastoidCelllines (Dr Wang) UCLA - 52 BreastCancerCelllines (Dr Finn) • Genome-wide SNPs: Affy 6.0 and Illumina 550S and 510S. 1.3 million SNPs • Expression array: Affy U133 Plus2.0, 54,000 probe sets • Exon array • microRNA • CNV data • In-depth gene resequencing data • Genome-wide SNPs: Illumina 610K • Expression array: Agilent Human 44k • CNV Data 25
Where do we stand with Ovarian Cancer?The Ovarian Cancer Association Consortium 8 US Sites 12 European Sites Coordinating Centers Duke University, USA, USC (L.A.), USA Cambridge, UK 1 South American Site 4 Australian Sites 1 African Site 1 Asian Site • 26,000 Ovariancancerpatientswithgermline DNA • Epidemiologicaldata • Clinical data, Therapydata • Follow Updata • TissueMicroarraywith >9,000 Samples • 31,000 Healthy Controls • Epidemiological Data
Call for Data and sample pooling for drug/genotype Interactions • MiliaryDisase • Residual Disease • First Line Chemotherapy • Duration Chemotherapy • Dose Chemotherapy • Progression (RECIST OR GCIG) • Death • Behaviour • Primary Site • Sub Type • Stage • Histopathological grade
What would be future questions • Dramatically increase sample size for genomewide studies • Important Questions within randomized clinical trials