Download presentation
Presentation is loading. Please wait.
Published byGwenda Blair Modified over 9 years ago
1
CCEB Pharmacogenetics of Leukemia Treatment Response Richard Aplenc May 2 nd, 2008
2
CCEB Pediatric Leukemia Most common pediatric malignancy Four types ALL AML CML JMML
4
CCEB Leukemia Treatment Varies both by disease and treating group Generally curable ~80% in ALL ~60% in AML Toxicity important Long term effects in ALL Infection and cardiac toxicity in AML
5
CCEB Leukemia Treatment Multi-agent Over time Substantial impact on patient and family Accurate response prediction is clinically very important
6
CCEB Induction ALL Therapy Consolidation Maintenance InterimMaintenance DelayedIntensification MTX Steroids 6-MP/6-TG DoxorubicinCyclophosphamide L-Asp VCRAraC
7
CCEB Predicting Treatment Response Leukemic blast characteristics Morphology Cytogenetics Molecular alterations (BCR-ABL) Patient characteristics Age Gender Genetic information?
8
CCEB Genetic Information Variation in DNA sequence throughout the genome Types of variation include Gene deletions (GSTT1) Duplications of DNA regions (TS 28 bp) Changes in single base pairs (SNPs) Allele, genotype, haplotype
9
CCEB Allele/Genotype/Haplotype/CNV SNP: Single Nucleotide Polymorphism An allele is a single value for a single marker A genotype is a pair of alleles for a given marker and both chromosomes in a single person A haplotype is an ordered series of alleles for many markers on a single chromosome Copy number variation (CNV) of DNA sequences Chromosome from one parent Chromosome from other parent SNP 2... Allele Genotype Haplotype SNP 1 G T GGGCGGGATGTACGTTCG SNP example:
10
CCEB Impact of Genetic Variability Loss of gene = loss of function Duplication of DNA segments and single base pair changes may have different effects depending on position Gain of function, loss of function, no change
11
Our Dream One Genotype Would Explain Treatment Response
12
CCEB Why Did We Have This Dream? Thiopurine methylatransferase (TPMT) Low frequency variants have complete loss of thiopurine metabolizing abilities
13
That Dream Has Ended Why Is That?
14
CCEB
16
TPMT One Gene, One Pathway, One Exposure Mercaptopurine TIMP TXMPTGMP TPMT 6-MMP TX TU XO Allopurinol TPMT Deficiency HGPRT
17
CCEB Two Remaining Questions
18
Can we utilize data on host genetic variability in a clinically meaningful way? Question 1:
19
Question 2: Is Theo Zaoutis really Neo?
20
Lisa Z looks like Trinity This Makes Sense Because…
21
And Because… Paul Offit is clearly Morpheus
22
CCEB Now That Everyone is Awake… Return to Question 1
23
CCEB Moving Towards the Answer Decide on the question Understand the complex phenotype issues Host genetics Environment Address the genetic epidemiology issues
24
CCEB What is the Question? Does the genotype inform us of the biology underlying a clinical outcome? Etiology Does the genotype predict a clinical outcome? Prediction
25
CCEB One Conceptual Approach Etiology Sensitivity Probability of positive test given disease Prediction Positive predictive value Probability of disease given positive test Seems obvious but impacts analysis
26
CCEB Complex Phenotype: Host Genetics Common SNPs will have modest effects Potentially large impact for the population Rare SNPs may have bigger effects Small population impact SNP frequency and the effect size determine sample size SNP frequency varies by ethnicity
27
CCEB Complex Phenotype: Environment Identify and measure relevant covariates Genotype does not matter if the patient doesn’t take the medication Concomitant medications Drug-drug interactions Alternative medications Folic acid supplimentation Other environmental exposures
28
CCEB What are the Genetic Epidemiology Issues? Population stratification Variation of SNP frequency by ethnicity High dimensional data Gene-environment interactions Interaction of host genetics with environment Gene-gene interactions Interaction of different SNPs Multiple comparisons
29
CCEB Some Examples from Our Data Methotrexate interrupts the folate cycle ALL blasts are sensitive to folate depletion Polymorphisms in genes in the folate cycle may impact methotrexate efficacy
31
CCEB MTHFR C677T Cox Model CovariateHRp95% CI C677T variant1.930.0041.2293.037 Day 7 BM1.770.0131.1252.773 Age1.110.0161.0201.220 Race1.710.3070.6104.798 Gender1.370.2380.8112.323 Rx Arm1.180.2140.9081.535 WBC0.990.3350.9711.010 Phenotype0.950.7760.6611.362
32
CCEB
33
MTHFR C677T and Infection Risk
34
CCEB MTHFR Conclusions The MTHFR C677T variant allele seems to impact relapse risk Dose adjustment of methotrexate for toxicity/infection does not ameliorate this effect Dose adjustment based on genotype may be clinically useful Replication in anther sample set is ongoing
35
CCEB MTFHR Issues Allele versus genotype versus haplotype Clinically meaningful analysis Positive predictive value
39
CCEB PPV with Time to Relapse Data This is the metric of interest to oncologists Moscowitz and Pepe defined positive predictive value in survival time data PPV Xk (t) = P(T ≤ t | X k = 1)
42
CCEB PPV Conclusions Although statistically significant, the MTHFR C677T allele has a PPV of 35% This is worse than flipping a coin Important question is the increased predictive value above baseline
43
CCEB TS 28 bp as Example NRFSHRCIp 2R/2R8380%1-- 2R/3R19679%1.680.863-3.2550.13 3R/3R10373%1.870.942-3.7210.074 3R/4R2060%3.691.436-9.4810.007
45
CCEB TS 28 bp Bootstrapping Does knowledge of TS genotype improve prediction of relapse? Bootstrap comparison of relapse free survival of all patients with those with particular TS polymorphisms No additional predictive value from knowing TS genotype Caveat of sample size issues
46
CCEB Other Genetic Epidemiology Issues Multiple comparisons Gene-gene and gene-environment interactions
47
CCEB Multiple Comparisons Probability of finding a false association by chance = 1 - 0.95 n n = 10, p = 40% n = 100, p = 99.4% Our data: 19 genotypes, 2 genders, 3 different relapse sites N = 228, p = 99.99959%
48
CCEB Methods for Multiple Comparisons Ignore it Validation sample set Adjust p-values Bonferroni False discovery rate (FDR) Benjamini et al 2001 Use Bayesian methods False positive report probability (FPRP) Wacholder et al 2004
49
CCEB High Dimensional Data The number of cells (N) needed to split R variables into X partitions: N = X R A single 2-way combination R = 2, X= 3, N= 9 We have evaluated 19 genotypes All 2-way combinations of our genotypes R = 19, X = 3, N = 1,162,261,467
50
CCEB High Dimensional Data Methods Several methods in current use We have used patterning with recursive partitioning (CART) Create groups as uniform as possible Use with genotype and other covariates No p-values Confirmation by cross-validation within the sample set
51
CCEB
52
CART Caveats No p-values Need to validate in a separate sample Often difficult to interpret results, particularly of higher order interactions i.e. 2 genotypes and 1 environmental factor
53
CCEB Future Directions Validate and extend genotyping in another ALL sample set Incorporate drug dose data Investigate the impact of genetic variability on infection risk in pediatric myeloid leukemia R01 resubmission with Theo Zaoutis
54
CCEB The End…. Thanks to everyone who makes it safe to swim with the sharks. Bev Lange, Tim Rebbeck,Jinbo Chen, Theo Zaoutis, Tom McWilliams, Peggy Han, Shannon Smith, Michelle Horn, Melanie Doran. Funded by RO1 CA108862-01.
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.