1 / 18

Cancer Pharmacogenomics From Bench to Bedside

Pharmacogenomics. The study of the role of inheritance in individual variation in drug response phenotypes.A major component of

Olivia
Download Presentation

Cancer Pharmacogenomics From Bench to Bedside

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. Cancer Pharmacogenomics From Bench to Bedside Liewei Wang M.D.,PhD. Assistant Professor Department or Molecular Pharmacology & Experimental Therapeutics Mayo Clinic Rochester

    2. Pharmacogenomics The study of the role of inheritance in individual variation in drug response phenotypes. A major component of “Personalized Medicine”.

    3. Clinical Goals Avoid adverse drug reactions Maximize drug efficacy Select responsive patients Pharmacogenomics

    4. Scientific Goals Link variation in genotype to variation in phenotype Determine mechanisms responsible for that link Translate the link into enhanced understanding, treatment and prevention of disease Pharmacogenomics

    6. Classical pharmacogenomic examples FDA Hearings Pharmacogenetics and Drug Labeling Thiopurines – TPMT Irinotecan – UGT1A1 Warfarin – CYP2C9 and VKORC1 Tamoxifen – CYP2D6

    8. Genome-wide association study Clinical GWAS GWAS using model systems (hypothesis generating and hypothesis testing)

    9. Human Variation Panel cell line A model system Publically available, widely used for genetic studies Ethnic diversity (100 CA, 100 AA and 100 HCA) Represent common genetic variation among individuals A good model system for pharmacogenomic studies

    10. Genome-wide SNP data 1.3 million SNPs/cell line Expression array data 54,000 probe sets/cell line MicroRNA 800 probe sets/cell line 2,000,000 genomic data points/cell line 576,000,000 genomic data points total for 288 cell lines

    15. Potential clinical implication Two genes were identified to be significantly associated with response to gemcitabine and AraC (NT5C3 and FKBP5) (Li et.al. Cancer Research 2008; 68: (17). Sept. 1, 2008; Cancer Cell, in press) These genes can be potentially used as biomarkers for prediction of patients who might respond better to theses treatments.

    17. Pharmacogenomics Ethical Challenges Confidentiality Insurance Therapeutic “activism”

More Related