pharmacogenetics in the treatment of breast and ovarian cancer patients peter a. fasching ucla david...
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Pharmacogenetics in the treatment of breast and ovarian cancer patients
Peter A. Fasching
UCLUCLAA
David Geffen School of Medicine
Div. Hem/Onc
Concepts of science
Therapy A Therapy B
Therapy A must be better2
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 expressionsFrom stromal cells
Gene expression profiles
SNP Chips (Germline-DNA)
Gene expression Profiling (WBC)
Epigenetic Profiling(circulating nucleic acids)
Gene copy variations
EpigenticProfiling
MutationProfiling
Proteomics
Biomaterials that could be helpful
miRNA Profiling
5
miRNAProfiling
SNP Chips (Germline-DNA)
Biomaterials that could be helpful
6
Can predict:
-Efficacy-Toxicity
Can discover:-functional explanation of differential response to chemotherapy
Tamoxifen
4-Hydroxy-Tamoxifen
N-Desmethyl-Tamoxifen
Endoxifen (N-Desmethyl-4-Hydroxy-Tamoxifen)
CYP3A4CYP3A5CYP2D6CYP2C9
CYP2C19CYP1A2
CYP2D6CYP3A4CYP2C9
CYP2C19CYP2B6
CYP2D6CYP2C9
CYP2C19CYP2B6
CYP3A4
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 pairsabout 24,000 genes
Persons genotyped
SNPs Polymorphic
1(20) + 2 or so ??? ???
240 10,000,000 3,100,000
1000 >15,000,000 >????
2001
2006
2009/2010
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 1 Genotype 2
Phenotype 1 10% 50%
Phenotype 2 90% 50%
SNP2 (Chr1)
Genotype 1 Genotype 2
Phenotype 1 10% 10%
Phenotype 2 90% 90%
SNP3 (Chr1)
Genotype 1 Genotype 2
Phenotype 1 10% 20%
Phenotype 2 90% 80%
P=0,0000001
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
-lo
g1
0(p
-va
lue)
Conditional Logistic Regression Analyses*
Ingle et al. San Antonio 2010Chromosome Position
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 22 23
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
DcTDcTDcT
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
DcTDcTDcTF
E
C
F
E
C
F
G G G
G =GemcitabineF = 5-Flourouracil
Primary Objective
Disease free Survival
Secondary Objectives
Overall Survival, Toxicity, Quality of Life
R
Zoledronate2 years
Zoledronate5 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 ProcessingBlood ProcessingDNA ExtractionDNA ExtractionDNA NormalizationDNA NormalizationDNA PlatingDNA Plating
Data ManagementData ManagementData entryData entryData MonitoringData MonitoringData updatesData updates
GenotypingGenotypingPlate Map DesignPlate Map DesignGenotype Quality ControlGenotype Quality ControlDNA StorageDNA Storage
BiostatisticsBiostatisticsPhenotype Quality ControlPhenotype Quality ControlGx and Phx Data CleaningGx and Phx Data CleaningProvision of AnalysisProvision of Analysis
DNA AnalysisDNA AnalysisSNP Chip ProcessingSNP Chip Processing
CoordinationCoordinationCollboration with other GroupsCollboration with other GroupsWorking groups onWorking groups on•Phenotype HarmonizationPhenotype Harmonization•Genotype HarmonizationGenotype Harmonization•Statistical MethologyStatistical Methology•Ethical ConsiderationsEthical Considerations•Cross ValidationCross Validation•Further Clinical ValidationFurther Clinical Validation
Clinical CollaboratorsSUCCESS A
Study(GeparQuinto
Study)
Mayo Collaborators PGRN
BiostatisticsMolecular
PharmacologyHematology /
OncologyGenotype Core Facility
Cell Line ProgramCell Line ProgramHuman Variation PanelHuman Variation PanelBC Panel (UCLA)BC Panel (UCLA)
NIHNHGRI
GARNET (www.garnetstudy.org
)
Structures for this collaboration
Blood ProcessingBlood ProcessingDNA ExtractionDNA ExtractionDNA NormalizationDNA NormalizationDNA PlatingDNA Plating
Data ManagementData ManagementData entryData entryData MonitoringData MonitoringData updatesData updates
GenotypingGenotypingPlate Map DesignPlate Map DesignGenotype Quality ControlGenotype Quality ControlDNA StorageDNA Storage
BiostatisticsBiostatisticsPhenotype Quality ControlPhenotype Quality ControlGx and Px Data CleaningGx and Px Data CleaningProvision of AnalysisProvision of Analysis
DNA AnalysisDNA AnalysisSNP Chip ProcessingSNP Chip Processing
CoordinationCoordinationCollboration with other GroupsCollboration with other GroupsWorking groups onWorking groups on•Phenotype HarmonizationPhenotype Harmonization•Genotype HarmonizationGenotype Harmonization•Statistical MethologyStatistical Methology•Ethical ConsiderationsEthical Considerations•Cross ValidationCross Validation•Further Clinical ValidationFurther Clinical Validation
Clinical CollaboratorsSUCCESS A
Study(GeparQuinto
Study)
Mayo CollaboratorsBiostatistics
Molecular PharmacologyHematology /
OncologyGenotype Core Facility
Cell Line ProgramCell Line ProgramHuman Variation PanelHuman Variation PanelBC Panel (UCLA)BC Panel (UCLA)
NIHNHGRI
GARNET (www.garnet.org)
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 LinesUCLA – Human Individual Breast Cancer Cell Lines
MAYO - 300 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
Coordinating Coordinating CentersCenters
Duke University, USA,Duke University, USA,USC (L.A.), USAUSC (L.A.), USACambridge, UKCambridge, UK
8 US 8 US SitesSites
4 Australian 4 Australian SitesSites
1 Asian 1 Asian SiteSite
12 European 12 European SitesSites
1 South American 1 South American SiteSite
1 African 1 African SiteSite
•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
Site Country Cases ChemoAOCS Australia 600 Platinum/taxane
MALOVA Denmark 680 Mostly pre-taxanes
LOS ANGELES USA 360 Platinum/taxane
MAYO USA 466 Platinum/taxane
BAVARIA Germany 271 Platinum/taxane
LEUVEN Belgium 296 Platinum/taxane
RPC 235 Platinum/taxane
YALE USA 96 Platinum/taxane
PVD 203 Platinum/taxane
SCOTROC1 GB 950 Platinum/taxane
GOG USA 493 Platinum/taxane
TOTAL 3970 Platinum/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
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