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    • 1. Pharmacogenomics: The Promise of Personalized Medicine Christina Aquilante, Pharm.D. Assistant Professor Department of Pharmaceutical Sciences School of Pharmacy University of Colorado at Denver and Health Sciences Center
    • 2. Objectives
      • Provide an overview of pharmacogenomics and its clinical relevance
      • Discuss clinically-relevant examples of:
        • Drug metabolism pharmacogenomics
        • Drug target pharmacogenomics
      • Discuss the challenges facing pharmacogenomic studies and the movement of pharmacogenomics into clinical practice
      • Discuss pharmacogenomics from the FDA and pharmaceutical industry perspective
    • 3. Interindividual Variability in Drug Response
      • Disease Drug Class Rate of Poor Response
      • Asthma Beta-agonists 40-75%
      • Hypertension Various 30%
      • Solid Cancers Various 70%
      • Depression SSRIs, tricyclics 20-40%
      • Diabetes Sulfonylureas, others 50%
      • Arthritis NSAIDs, COX-2 inhibitors 30-60%
      • Schizophrenia Various 25-75%
    • 4. Factors Contributing to Interindividual Variability in Drug Disposition and Action
      • Age
      • Race/ethnicity
      • Weight
      • Gender
      • Concomitant Diseases
      • Concomitant Drugs
      • Social factors
      • GENETICS
    • 5. “ We wish to suggest a structure for the salt of [DNA]. This structure has novel features which are of considerable biological interest.”
    • 6. Human Genome Project
      • Determine the sequence of the 3 billion nucleotides that make up human DNA
      • Characterize variability in the genome
      • Identify all the genes in human DNA
      • The Era of Genomic Medicine:
        • Improve prediction of drug efficacy or toxicity
        • Improve the diagnosis of disease
        • Earlier detection of genetic predisposition to disease
    • 7. Newsweek June 25, 2001 “… pharmacogenetics promises to target treatment to a patient’s genetic profile…”
    • 8. Genetics or Genomics?
      • Pharmacogenetics
        • Study of how genetic differences in a SINGLE gene influence variability in drug response (i.e., efficacy and toxicity)
      • Pharmacogenomics
        • Study of how genetic (genome) differences in MULTIPLE genes influence variability in drug response (i.e., efficacy and toxicity)
    • 9. Current Concept of Pharmacogenomics Roden DM et al. Ann Intern Med 2006; 145:749-57
    • 10. Potential of Pharmacogenomics All patients with same diagnosis 1 2 Responders and patients not predisposed to toxicity Non-responders and toxic responders Treat with alternative drug or dose Treat with conventional drug or dose
    • 11. Clinical Relevance
      • Can we predict who will derive an optimal response?
      • Can we predict who will have a toxicity?
        • Host (patient) genotype determines optimal drug therapy approach
        • Disease (pathogen) genotype determines optimal drug therapy approach
    • 12. DNA is Information
      • DNA
      • A, T, G, C
      • Codon
      • Gene
      • Chromosome
      • Genome
      • ENGLISH
      • Abcdefg….xyz
      • Word
      • Sentence
      • Chapter
      • Book
    • 13. Composition of the Human Genome
      • Mutation/Polymorphism 1 bp
      • Unit of genetic code 3 bp
      • Coding sequence (exons) 3,000 bp
      • Gene (exons and introns) 50,000 bp
      • Chromosome 150,000,000 bp
      • Human genome 3,000,000,000 bp
    • 14. The Foundation of Pharmacogenomics: Differences in the Genetic Code Between People
      • Mutation: difference in the DNA code that occurs in less than 1% of population
        • Often associated with rare diseases
          • Cystic fibrosis, sickle cell anemia, Huntington’s disease
      • Polymorphism: difference in the DNA code that occurs in more than 1% of the population
        • A single polymorphism is less likely to be the main cause of a disease
        • Polymorphisms often have no visible clinical impact
    • 15. Single Nucleotide Polymorphisms (SNP)
      • Pronounced “snip”
      • Single base pair difference in the DNA sequence
        • Over 2 million SNPs in the human genome
      • Other polymorphisms:
        • Insertion/deletion polymorphisms
        • Gene duplications
        • Gene deletions
    • 16.  
    • 17. Consequences of Polymorphisms
      • May result in a different amino acid or stop codon
      • May result in a change in protein function or quantity
      • May alter stability of mRNA
      • No consequence
    • 18. Genetics Terminology
      • Alleles = different DNA sequences at a locus
        • Codon 389  1 -AR
          • Arg (0.75)
          • Gly (0.25)
      • Genotype = pair of alleles a person has at a region of the chromosome
        • Codon 389  1 -AR
          • Arg389Arg
          • Arg389Gly
          • Gly389Gly
    • 19. Genetics Terminology
      • Phenotype: outward manifestation of a trait
      • Linkage: measure of proximity of 2 or more polymorphisms on a single chromosome
        • Polymorphisms in close proximity tend to be co-inherited
        • Regions of linked polymorphisms are known as haplotypes
    • 20. Haplotype Map
      • For specific locations in the genome, a small number of SNP patterns (haplotypes) can account for 80-90% of entire human population
      • International HapMap Project:
        • Identifying common haplotypes in four populations from different parts of the world
        • Identifying “tag” SNPs that uniquely identify these haplotypes
    • 21. Pharmacogenomics DRUG TARGETS DRUG METABOLIZING ENZYMES DRUG TRANSPORTERS PHARMACOKINETICS PHARMACODYNAMICS Variability in Efficacy/Toxicity Johnson JA. Trends in Genetics 2003: 660-666
    • 22. Drug Metabolism Pharmacogenomics
      • Evidence of an inherited basis for drug response dates back in the literature to the 1950s
        • Succinylcholine: 1 in 3000 patients developed prolonged muscle relaxation
      • Monogenic
      • Phenotype to genotype approach
    • 23. Drug Metabolizing Enzymes
    • 24. Examples of Drug Metabolism Pharmacogenomics NEJM 2003; 348: 529-537
    • 25. Examples of Drug Metabolism Pharmacogenomics NEJM 2003; 348: 529-537
    • 26. Warfarin and CYP2C9
      • Widely prescribed anticoagulant drug used to prevent blood clots
      • Narrow range between efficacy and toxicity
      • Large variability in the dose required to achieve therapeutic anticoagulation
        • Doses vary 10-fold between people
      • CYP2C9 is the enzyme responsible for the metabolism of warfarin
      • SNPs exist in CYP2C9 gene that decrease the activity of the CYP2C9 metabolizing enzyme
    • 27. CYP2C9 Polymorphisms and Warfarin Dose
      • Warfarin dose is affected by CYP2C9 genotype
      Gage BF et al. Thromb Haemost 2004; 91: 87-94 *2 and *3 are SNPs
    • 28. CYP2C9 Genotype and Bleeding Events
      • Compared to wild-type, CYP2C9 variants had a higher risk of serious or life-threatening bleeds
      • Hazard Ratio of 3.94 during the first 3 months of follow-up
      • Hazard Ratio of 2.39 for the entire follow-up period
      Higashi et al. JAMA 2002; 287 WT Variant
    • 29. Challenges Facing Warfarin Pharmacogenomics
      • Despite the strong association between CYP2C9 genotype and warfarin dose, CYP2C9 genotype accounts for only a small portion of the total variability in warfarin doses (~10-20%)
      • Need to determine other genetic and non-genetic factors that contribute to interindividual variability in warfarin doses
    • 30. CYP2D6 Polymorphisms
      • CYP2D6 is responsible for the metabolism of a number of different drugs
        • Antidepressants, antipsychotics, analgesics, cardiovascular drugs
      • Over 100 polymorphisms in CYP2D6 have been identified
      • Based on these polymorphisms, patients are phenotypically classified as:
        • Ultrarapid metabolizers (UMs)
        • Extensive metabolizers (EMs)
        • Poor metabolizers (PMs)
    • 31. CYP2D6 Phenotypes NEJM 2003; 348:529 Roden DM et al. Ann Intern Med 2006; 145:749-57
    • 32. CYP2D6 Polymorphisms and Psychiatric Drug Response
      • Increased rate of adverse effects in poor metabolizers due to increased plasma concentrations of drug:
        • Fluoxetine (Prozac  ) death in child attributed to CYP2D6 poor metabolizer genotype
        • Side effects of antipsychotic drugs occur more frequently in CYP2D6 poor metabolizers
        • CYP2D6 poor metabolizers with severe mental illness had more adverse drug reactions, increased cost of care, and longer hospital stays
    • 33. CYP2D6 and Codeine
      • Codeine requires activation by CYP2D6 in order to exert its analgesic effect
      • Due to genetic polymorphisms, 2-10% of the population cannot metabolize codeine and are resistant to the analgesic effects
      • Interindividual variability exists in the adequacy of pain relief when uniform doses of codeine are given
    • 34. Strattera ® (Atomoxetine)
      • Treatment of attention deficit hyperactivity disorder
        • CYP2D6 poor metabolizers have 10-fold higher plasma concentrations to a given dose of STRATTERA compared with extensive metabolizers
        • Approximately 7% of Caucasians are poor metabolizers
        • Higher blood levels in poor metabolizers may lead to a higher rate of some adverse effects of STRATTERA
    • 35. CYP2C19 and Proton Pump Inhibitors
      • Proton pump inhibitors are used to treat acid reflux and stomach ulcers
      • Ulcer cure rates using omeprazole and amoxicillin by CYP2C19 phenotype:
      • Cure Rate
        • Rapid metabolizers 28.6%
        • Intermediate metabolizers 60%
        • Poor metabolizers 100%
      Furuta, T. et. al. Ann Intern Med 1998;129:1027-1030
    • 36. Roche AmpliChip: FDA-Approved
    • 37. Roche AmpliChip P450 Test
      • The Roche AmpliChip CYP450 Test is intended to identify a patient's CYP2D6 and CYP2C19 genotype from genomic DNA extracted from a whole blood sample.
      • Information about CYP2D6 and CYP2C19 genotype may be used as an aid to clinicians in determining therapeutic strategy and treatment dose for therapeutics that are metabolized by the CYP2D6 or CYP2C19 gene product.
    • 38. Thiopurine-S-Methyltransferase (TPMT)
      • Thiopurine drugs are used to treat cancer
        • Acute lymphoblastic leukemia
      • TPMT is important for metabolizing thiopurines
        • azathioprine, mercaptopurine (6-MP)
      • Polymorphisms in the TPMT gene result in decreased TPMT enzyme activity
      • Decreased TPMT activity predisposes individuals to severe, life-threatening toxicities from these drugs
    • 39. Variability in TPMT Activity
    • 40. Genotype-Guided 6-MP Dosing Pharmacogenomics 2002;3(1):89-98.
    • 41. 6-Mercaptopurine Prescribing Information
      • There are individuals with an inherited deficiency
      • of the enzyme thiopurine methyltransferase
      • (TPMT) who may be unusually sensitive to the
      • myelosuppressive effects of mercaptopurine and
      • prone to developing rapid bone marrow
      • suppression following the initiation of treatment.
      • Substantial dosage reductions may be required to
      • avoid the development of life-threatening bone
      • marrow suppression in these patients.
    • 42. Imuran Prescribing Information
      • TPMT genotyping or phenotyping can be used to identify patients with absent or reduced TPMT activity.
      • Patients with low or absent TPMT activity are at an increased risk of developing severe, life-threatening myelotoxicity from IMURAN if conventional doses are given.
      • Physicians may consider alternative therapies for patients who have low or absent TPMT activity (homozygous for non-functional alleles). IMURAN should be administered with caution to patients having one non-functional allele (heterozygous) who are at risk for reduced TPMT activity that may lead to toxicity if conventional doses are given. Dosage reduction is recommended in patients with reduced TPMT activity.
    • 43. TPMT and Thioguanines
      • Clinical implications:
        • Genetic testing for TPMT is routine practice at some cancer centers for protocols involving thiopurine drugs
        • CLIA approved test available
        • Implications for cancer, transplant, rheumatoid arthritis, lupus, dermatology, and Crohn’s disease treatment
    • 44. Drug Target Pharmacogenomics
    • 45. Drug Target Pharmacogenomics
      • Direct protein target of drug
        • Receptor
        • Enzyme
      • Proteins involved in pharmacologic response
        • Signal transduction proteins or downstream proteins
      • Polymorphisms associated with
      • disease risk
        • “ Disease-modifying” polymorphisms
        • “ Treatment-modifying” polymorphisms
    • 46. Complexity of Drug Effect
    • 47. Assessing Phenotype in Drug Target Pharmacogenomics
      • Depression—Symptom rating scales
        • Indirect measure of drug response
        • Inter-rater reliability
      • Hypertension—Blood pressure
        • Minute to minute and diurnal variability
        • Influence of environmental factors (e.g. lack of rest before measurement)
      • Diabetes—Blood glucose
        • Diurnal variation in blood glucose
        • Influence of environmental factors (e.g. diet/exercise)
    • 48. Comparison
      • Drug Metabolism Pgx
      • Polymorphisms often lead to non-functional or absent proteins
      • Distinct phenotypes
        • Bimodal/trimodal distribution
      • Phenotypes are easily measured
        • Drug concentration
        • In vitro catalytic activity
      • Drug Target Pgx
      • Polymorphisms usually don’t result in lack of protein function
        • “ Subtle” effects
      • Differences in phenotypes are smaller
      • Measurement of phenotypes is difficult
        • Imprecise and variable
      • Failure to consider haplotypes
      Johnson JA and Lima JJ. Pharmacogenetics 2003; 13:525-534
    • 49. Examples of Drug Target Pharmacogenomics Evans WE. NEJM 2003; 348:538-48
    • 50. Examples of Disease or Treatment Modifying Pharmacogenomics Evans WE. NEJM 2003; 348:538-48
    • 51. Beta-blockers and Hypertension (HTN)
      • HTN is the most prevalent chronic disease in the US and a contributor to morbidity and mortality
      • Beta-blockers are first-line agent in the treatment of HTN
      • Marked variability in response to beta-blockers
        • 30-60% of patients fail to achieve adequate blood pressure lowering with beta-blockers
      • Common beta-blockers used in HTN:
        • Metoprolol
        • Atenolol
    • 52. Beta-1 Adrenergic Receptor Podlowski, et al. J Mol Med 2000;78:90. Codon 49 Ser  Gly Codon 389 Arg  Gly
    • 53. Beta-1 Receptor Polymorphisms and Response to Metoprolol Johnson JA et al. Clin Pharmacol Ther 2003; 74:44-52
    • 54. Beta-2 Adrenergic Receptor Polymorphisms and Response to Albuterol in Asthma
      • Hyperreactivity of the airways is the hallmark of asthma
      • Airway smooth muscle contains beta-2 receptors that produce broncodilation
      • Albuterol is a beta-2 agonist that is used in the treatment of asthma
        • Produces smooth muscle cell relaxation and bronchodilation
      • Forced expiratory volume in 1 second (FEV 1 )
        • Phenotypic measure of response
    • 55. Beta-2 Polymorphisms and Response to Albuterol Lima JJ. Clin Pharmacol Ther 1999; 65:519-25
      • Single 8 mg albuterol dose
      • Albuterol-evoked increases in FEV 1 were higher and more rapid in Arg16 homozyotes compared with Gly carriers
      • Codon 16 polymorphism is a determinant of bronchodilator response to albuterol
      • Lima JJ et al. Clin Pharmacol Ther 1999; 65: 519-25
    • 56. VKOR and Warfarin
      • Warfarin works by inhibiting Vitamin K Epoxide Reductase (VKOR)
      • VKOR helps recycle vitamin K which is important in proper functioning of clotting factors
      • By inhibiting VKOR, warfarin alters the vitamin K cycle and results in the production of inactive clotting factors
      • Polymorphisms exist in the gene for VKOR (VKORC1)
    • 57. VKORC1 Genotype and Warfarin Dose Requirements 33 mg/wk 46 mg/wk 21 mg/wk G/G G/A A/A
    • 58. Warfarin Pharmacogenomics
      • CYP2C9 SNPs account for a small amount of variability in warfarin doses (~10%)
      • VKORC1 SNPs explain a larger portion of variability in warfarin doses (~20-25%)
      • Almost 50% of variability in warfarin doses can be explained by a combination of factors:
        • VKORC1 SNPs
        • CYP2C9 SNPs
        • Non-genetic factors (age, weight, concomitant drugs, concomitant disease states)
    • 59. Warfarin Pharmacogenomics
      • Current Status:
        • Develop and validate dosing algorithms to that include VKORC1 genetic information, CYP2C9 genetic information, and non-genetic factors (e.g., age, weight, concomitant drugs, concomitant disease states)
        • Test if dosing warfarin based on genotype is better than the “usual” care approach
    • 60. Abacavir Hypersensitivity
      • Antiretroviral used for treatment of HIV
      • 5% of patients experience hypersensitivity reactions to the drug
        • Hypersensitivity is fatal in rare cases
      • Hypersensitivity reaction starts with severe GI symptoms, followed by fever and rash
      • Discontinuation of drug reverses symptoms
      • Re-challenge of abacavir in hypersensitive individuals can result in life-threatening low blood pressure or death
      Lancet 2002;359:727-32.
    • 61. Abacavir Hypersensitivity
      • Hypersensitivity typically believed to be an immunologic reaction
      • Hypersensitivity might be genetically linked, and thus predictable
      • Major histocompatibility proteins (MHC) investigated because of known links in other immune responses and allergic reactions
    • 62. Genetics of Abacavir Hypersensitivity
      • Patients with the HLA-B*5701 variant were 117 times more likely to be hypersensitive to abacavir than those who did not have the variant
      • 13 patients had 3 linked genetic variants (*5701, DR7, DQ3) and all patients were abacavir hypersensitive
      • All abacavir hypersensitive patients were Caucasian, therefore
      • studies in other racial groups are needed
      Western HIV Australia HIV Cohort Study
    • 63. Disease Risk Polymorphisms Polymorphisms can predispose individuals to a disease or increase the risk for disease If a drug with a known adverse effect is given to a person with a genetic susceptibility to that adverse effect, there is an increased likelihood for that adverse effect
    • 64. Clotting Factor Polymorphisms, Blood Clots, and Oral Contraceptive Pills
      • Polymorphisms exist in clotting factor genes
      • Oral contraceptive pills alone are associated with an increased risk of blood clots
      • Women who have clotting factor polymorphisms are at an even greater risk for blood clots if they receive oral contraceptive pills
    • 65. Oral Contraceptive Pills and Blood Clots Martinelli I. Pharmacogenetics 2003; 13:589-594 Patients on OCP who are homozygous for Factor V Leiden have 50 to100-fold increased risk of VTE Heterozygotes
    • 66. A Different Aspect of Drug Target Pharmacogenomics
      • In all of the examples thus far, the drug target has been a human protein
      • The gene encoding that human protein has generally NOT undergone mutation during the patient’s life
      • However, in the areas of infectious diseases and cancer, the drug target is often a non-human protein
        • Cancer: Tumor DNA
        • Infectious Diseases: Viral genotype
          • e.g., HIV, HBV, HCV
    • 67. HER-2 Protein and Herceptin
      • Herceptin (trastuzumab):
        • Metastatic breast cancer
        • Targets tumor cells that over-express the human epidermal growth factor receptor 2 (HER2) protein
        • Best response attained in women who over-express the HER2 protein
        • HER-2 over-expression in breast cancer cells should be done before patients receive the drug
    • 68. Herceptin: Prescribing Information
      • HERCEPTIN (Trastuzumab) as a single agent is indicated for the treatment of patients with metastatic breast cancer whose tumors overexpress the HER2 protein and who have received one or more chemotherapy regimens for their metastatic disease.
      • HERCEPTIN should be used in patients whose tumors have been evaluated with an assay validated to predict HER2 protein overexpression
    • 69. Hepatitis C
      • Interferon-  -2b and ribavirin are used to treat patients with hepatitis C virus
      • Different mutations exist in the hepatitis C virus
      • Knowledge of a person’s hepatitis C genotype may help play a role in the therapeutic decision-making process
    • 70. HIV and Antiretroviral Drugs
      • Resistance to antiretroviral agents hinders the management of HIV disease
      • In the virus, mutations occur which confer drug resistance
      • Knowledge of viral genotype (or phenotype) can help guide the selection of antiretroviral therapy
    • 71. Challenges Facing the Field of Pharmacogenomics
      • Multiple studies, but literature is inconclusive in some instances
      • Genetics accounts for an insufficient percentage of response variability for a given drug
      • Few studies documenting genotype-guided therapy is better than the “usual care” approach
      • Few “point-of-care” tests available to determine a person’s genetic make-up or protein expression
    • 72. Potential Reasons for Discrepancies
      • Inadequately powered studies
      • Studying different drug response phenotypes
      • Studying different patient populations (differences in allele frequencies)
      • Problems precisely measuring phenotype
      • Subtlety of functional effects of polymorphisms
      • Focus on single SNPs instead of haplotypes
      • Failure to consider the complexity of drug response
      Johnson JA and Lima JJ. Pharmacogenetics 2003; 13:525-534
    • 73.  
    • 74.  
    • 75. Pharmacogenetics and Pharmacogenomics Knowledge Base (PharmGKB)
      • Publicly accessible knowledge base
      • Goal: establish the definitive source of information about the interaction of genetic variability and drug response
        • Store and organize primary genotyping data
        • Correlate phenotypic measures of drug response with genotypic data
        • Curate major findings of the published literature
        • Provide information about complex drug pathways
        • Highlight genes that are critical for understanding pharmacogenomics
    • 76. Role of Pharmacogenomics in the Drug Development Process
      • 80% of products that enter the development pipeline FAIL to make it to market
      • Pharmacogenomics may contribute to a “smarter” drug development process
        • Allow for the prediction of efficacy/toxicity during clinical development
        • Make the process more efficient by decreasing the number of patients required to show efficacy in clinical trials
        • Decrease costs and time to bring drug to market
    • 77. Pharmacogenomic Paradigm in the Drug Development Process Current Options Options with Pharmacogenomics Proportion of patients showing poor or no response Low High Continue clinical trials to market Abandon drug before market Optimize clinical trials, making them smaller and shorter Continue trials safely by excluding at-risk pts
    • 78. Personalized Medicine and the Pharmaceutical Industry
      • Targeted Therapies:
        • Herceptin: treatment of HER2 positive metastatic breast cancer
        • Gleevec: treatment for patients with Philadelphia chromosome-positive chronic myeloid leukemia
        • Erlotinib: treatment for non-small cell lung cancer
          • Most effective in epidermal growth factor receptor positive tumors
        • Maraviroc (not approved): treatment for HIV
          • Studies have incorporated a screening process for different receptors that HIV uses to gain access to cells
        • Iloperidone (not approved): schizophrenia treatment
          • Company identified a genetic marker that predicts a good response to the drug
    • 79. Pharmacogenomic Paradigm in the Pharmaceutical Industry Rare side effect prediction Efficacy prediction Market expansion Common side effect prediction
    • 80. FDA and Pharmacogenomics
      • Traditionally, industry has been hesitant to submit pharmacogenomic data due to fears of:
        • Delays in drug development
        • Request for additional clinical studies
        • Potentially put clinical trials on hold
      • FDA published: “Draft Guidance for Industry: Pharmacogenomic Data Submission” in 2003. (currently under revision)
      • Set criteria for Voluntary Genomic Data Submission (VGDS)
    • 81. Pharmacogenomics Information in the Published Literature Zineh I et al. Ann Pharmacother. 2006; 40: 639-44
    • 82. Pharmacogenomics Information in FDA-Approved Prescribing Information Zineh I et al. Pharmacogenomics J; 2004: 1-5
    • 83. Moving Pharmacogenomics to Clinical Practice Identify sequence variability in candidate genes In vitro functional studies Proof-of-concept clinical studies Studies that mimic clinical practice Documenting sufficient variability to predict clinical utility Document Pgx superiority: Pgx-guided versus usual care Johnson JA. Trends in Genetics 2003; 19: 660-66
    • 84. The Future of Pharmacogenomics
      • Genome wide approach versus candidate gene approach
      • Thousands of SNPs
      • Thousands of patients
      • Replication studies
      • Sophisticated databases housing pharmacogenomic information
      • Drug selection and dosing algorithms incorporating non-genetic and genetic information
      • Point of care genetic testing
    • 85. "Here's my sequence..." The New Yorker
    • 86. “ Personalized medicine: elusive dream or imminent reality ? In summary: it is both.” Larry Lesko, Director of the FDA Office of Clinical Pharmacology and Biopharmaceutics Clin Pharmacol Ther; 2007: 807-816