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 ATherapy 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

Aim A priori identification of patients with a benefit from the offered therapy Test Therapy will improve outcome Therapy will NOT improve outcome 4

Gene expressions From stromal cells Gene expression profiles SNP Chips (Germline-DNA) Gene expression Profiling (WBC) Epigenetic Profiling (circulating nucleic acids) Gene copy variations Epigentic Profiling Mutation Profiling Proteomics Biomaterials that could be helpful miRNA Profiling 5 miRNA Profiling

SNP Chips (Germline-DNA) Biomaterials that could be helpful 6 Can predict: -Efficacy -Toxicity Can discover: -functional explanation of differential response to chemotherapy

Tamoxifen-Metabolism 7

CYP2D6 Genotyping as a predictive marker (Schroth, Goetz, Hamann, Fasching et al. JAMA 2009) N=1325 ER positive Breast Cancer Patients All treated with Tamoxifen Genotyping CYP2D6 *3, *4, *5, *10, *41 Metabolizing Groups EM=extensive Metabolizers IM=Intermediate Metabolizers PM=Poor Metabolizers 8

The genome wide approach

How many Single nucleodide Polymorphisms are out there? About 3.3 Billion base pairs about 24,000 genes

Persons genotyped SNPsPolymorphic 1(20) + 2 or so??? 24010,000,0003,100, >15,000,000>???? / 2010 How many Single nucleodide Polymorphisms are out there? Image Source: The Sanger Institute >1,000,000 SNPs to be analyzed by chip technology on one chip

How to analyze and present 1,000,000 associations between genetic variations and the phenotype? SNP1 (Chr1) Genotype 1Genotype 2 Phenotype 110%50% Phenotype 290%50% SNP2 (Chr1) Genotype 1Genotype 2 Phenotype 110% Phenotype 290% SNP3 (Chr1) Genotype 1Genotype 2 Phenotype 110%20% Phenotype 290%80% P=0, P=0,9 P=0,001

How can I present a million associations?

P=1 P=0,1 P=0,0001 P=0,001 P=0,01 P=0,00001

-log10(p-value) Conditional Logistic Regression Analyses* Ingle et al. San Antonio 2010 Chromosome Position

How to do the work?  Clinical collaborators with well designed studies(!!!)  Biosampling infrastructure  Genotyping Facility  Biostatistics/Bioinformatics  Functional Explanation  Clinical collaborators for clinical validation

R E C DcT SUCCESS A Study: Simultaneous Study of Gemcitabine-Docetaxel Combination adjuvant treatment Surveillance-Trial (n=3725) (PI: Prof. Dr. W. Janni) DcT E C =Docetaxel =Epirubicin =Cyclophosphamide F E C F E C F E C DcT F E C F E C F GGG G =Gemcitabine F = 5-Flourouracil Primary Objective Disease free Survival Secondary Objectives Overall Survival, Toxicity, Quality of Life R Zoledronate 2 years Zoledronate 5 years 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 Blood Processing DNA Extraction DNA Normalization DNA Plating Data Management Data entry Data Monitoring Data updates Genotyping Plate Map Design Genotype Quality Control DNA Storage Biostatistics Phenotype Quality Control Gx and Phx Data Cleaning Provision of Analysis DNA Analysis SNP Chip Processing Coordination Collboration with other Groups Working groups on Phenotype HarmonizationPhenotype Harmonization Genotype HarmonizationGenotype Harmonization Statistical MethologyStatistical Methology Ethical ConsiderationsEthical Considerations Cross ValidationCross Validation Further Clinical ValidationFurther Clinical Validation Clinical Collaborators SUCCESS A Study (GeparQuinto Study) Mayo Collaborators PGRN Biostatistics Molecular Pharmacology Hematology / Oncology Genotype Core Facility Cell Line Program Human Variation Panel BC Panel (UCLA) NIH NHGRI GARNET (

Structures for this collaboration Blood Processing DNA Extraction DNA Normalization DNA Plating Data Management Data entry Data Monitoring Data updates Genotyping Plate Map Design Genotype Quality Control DNA Storage Biostatistics Phenotype Quality Control Gx and Px Data Cleaning Provision of Analysis DNA Analysis SNP Chip Processing Coordination Collboration with other Groups Working groups on Phenotype HarmonizationPhenotype Harmonization Genotype HarmonizationGenotype Harmonization Statistical MethologyStatistical Methology Ethical ConsiderationsEthical Considerations Cross ValidationCross Validation Further Clinical ValidationFurther Clinical Validation Clinical Collaborators SUCCESS A Study (GeparQuinto Study) Mayo Collaborators Biostatistics Molecular Pharmacology Hematology / Oncology Genotype Core Facility Cell Line Program Human Variation Panel BC Panel (UCLA) NIH NHGRI GARNET (

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 Mayo PGRN - “Human Variation Panel” Cell Lines UCLA – Human Individual Breast Cancer Cell Lines MAYO lymphoblastoid Cell lines (Dr Wang) UCLA - 52 Breast Cancer Cell lines (Dr Finn) 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 CoordinatingCenters Duke University, USA, USC (L.A.), USA Cambridge, UK 8 US Sites 4 Australian Sites 1 Asian Site 12 European Sites 1 South American Site 1 African Site 26,000 Ovarian cancer patients with germline DNA26,000 Ovarian cancer patients with germline DNA Epidemiological dataEpidemiological data Clinical data, Therapy dataClinical data, Therapy data Follow Up dataFollow Up data Tissue Microarray with >9,000 SamplesTissue Microarray with >9,000 Samples 31,000 Healthy Controls31,000 Healthy Controls Epidemiological DataEpidemiological Data

Call for Data and sample pooling for drug/genotype Interactions Behaviour Primary Site Sub Type Stage Histopathological grade Miliary Disase Residual Disease First Line Chemotherapy  Duration Chemotherapy  Dose Chemotherapy Progression (RECIST OR GCIG) Death

SiteCountryCasesChemo AOCSAustralia600Platinum/taxane MALOVADenmark680Mostly pre-taxanes LOS ANGELESUSA360Platinum/taxane MAYOUSA466Platinum/taxane BAVARIAGermany271Platinum/taxane LEUVENBelgium296Platinum/taxane RPC235Platinum/taxane YALEUSA96Platinum/taxane PVD203Platinum/taxane SCOTROC1GB950Platinum/taxane GOGUSA493Platinum/taxane TOTAL3970Platinum/taxane Work in Progress: Sets for analysis of PFS and Genotype

What would be future questions Dramatically increase sample size for genomewide studies Important Questions within randomized clinical trials