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Pathology in the Genome Era: Challenges to Diagnosis, Prognosis, Therapeutics, and Implications for Training Programs Mark E. Sobel, M.D., Ph.D. Executive Officer American Society for Investigative Pathology [email protected] Temple University School of Medicine October 29, 2010 This presentation will be available at http://www.asip.org/about/exec.htm No relevant financial relationships to disclose Goals Understand the future capabilities and changes to pathology practice in the genome era Recognize the impact of whole genome sequence analysis on pathology practice. What are the potential benefits and pitfalls? Describe approaches to training of medical students, residents and fellows in training, and practicing pathologists to meet the challenges of the genome era. Dark Matter is 96% of the mass of the universe The New Genetics: The Human Genome 3.1 x 109 bp 500,000 stretches of DNA that are conserved through evolution 22,000 genes based on current algorithms = 5% of genome 30% have instructions to make proteins 70% have instructions to regulate the protein-coding genes © The American Society for Investigative Pathology Complexity of the Human Genome The other 70% (regulating) Ribosomal (rRNA) Transfer RNA (tRNA) Small nucleolar RNA (snoRNA) Micro RNA (miRNA) 95% “Junk DNA” Pseudogenes Other functions? © American Society for Investigative Pathology The Human Genome is NOT “Green” Inefficiencies can be an advantage Adapt quickly to rare, life-threatening circumstances Fill up your gas tank and have it ready at all times for a long trip Bleeding Starvation Extreme heat or cold © American Society for Investigative Pathology Human Genome Data: DNA Methods PCR Sequencing FISH Microarrays Data SNPs (single nucleotide polymorphisms) Insertions/Deletions/Rearrangements Gene copy number Whole Genome Sequence variants © American Society for Investigative Pathology Human Genome Data: Sequencing the Genome ProgressToward Whole Genome Sequencing (WGS) Time Period Turn-around Time FTEs Cost per genome 1990 – 2003 ~ 5 years ~5,000 ~ $3 billion 2003-2009 ~ 6 months <50 2010-2014 < 1 month 4 + bioinformatics analysts 2015 15 minutes <1 $300,000 $3,800/exome $20,000/WGS $100 © American Society for Investigative Pathology Whole Genome Analysis Gene Expression OncotypeDx, Mammaprint Whole transcriptome analysis (cells, tissues) Direct to Consumer Whole Genome SNP Analysis 23andMe Navigenics DeCode How do we help patients interpret? © American Society for Investigative Pathology Whole Genome Sequencing The New Microscope? Beckman Coulter Genomics Applied Biosystems Complete Genomics 454 Sequencing Helicos Illumina Pacific Biosciences © American Society for Investigative Pathology Human Genome Data: RNA Methods RT-PCR qPCR Microarrays In situ Hybridization Data Whole transcriptome analysis Sequence variants, copy number Expression: increased, decreased, absent © American Society for Investigative Pathology Human Genome Data: Protein Methods Immunohistochemistry Gel analysis (1D, 2D) Mass spectrometry Data Presence and amount Size Modifications- phosphorylation, glycosylation Whole cell and tissue expression © American Society for Investigative Pathology Current Practice of Molecular Pathology Disease-specific tests and HLA typing Centralized laboratories Cost of a single test: $100 - $5,000 Individual test validation and performance Troubleshooting Interpretation Clinical consultation © American Society for Investigative Pathology Genomic Pathology: Whole Genome Sequencing Replace current single and multi-gene tests at a lower cost and faster turn-around time Delineation of Signaling Pathways Interpretative Dilemma – what is clinically relevant? © American Society for Investigative Pathology Genomic Pathology: Issues in Whole Genome Sequencing Validation of testing method Quality control Validation of interpretative algorithm Archive complete sequence? Consent? Confidentiality? Patent and licensing restrictions? © American Society for Investigative Pathology The New Genetics and Personalized Medicine Personalized Medicine is the use of human genome data to optimize patient care Treatments based on genomics Subcategorize diseases based on genomics Use disease susceptibility for prevention Use disease susceptibility to direct early monitoring Improve outcomes Faster diagnosis More precise prognosis Effective therapy Reduce healthcare costs The New Genetics and Personalized Medicine Personalized Medicine is the use of human genome data to optimize patient care Pharmacogenetics The Study of Variations in Genes that Affect Responses to Drugs 50% of first treatments do not work Optimize treatment for individual patients Minimize adverse drug events Maximize drug efficacy Develop more targeted drugs The right drug at the right dose Application to Oncology Determine the preferred therapeutic agent for each tumor Ascertain which patients are most likely to benefit from a given therapy Patients with same diagnosis Adapted, Courtesy Slide from Howard L. McLeod Institute for Pharmacogenomics and Individualized Therapy UNC – Chapel Hill, NC All patients with same diagnosis Toxic Responder: Lower dose or alternate drug All patients with same diagnosis Non-Responder: higher dose or alternate drug Pharmacogenetics: The Study of Variations in Genes that Affect Responses to Drugs Genetic changes specifically within malignant tumor cells Inherited genetic variability in a targeted gene or group of functionally-related genes affecting response to drugs Pharmacogenetics: The Study of Variations in Genes that Affect Responses to Drugs Genetic changes specifically within malignant tumor cells Estrogen Receptor Status Treatment with SERMs- selective ER modulators Tamoxifen Raloxifene Multigene analysis: OncoType DX assay (21 genes) MammaPrint assay (70 genes) Epidermal growth factor receptor (EGFR) Status HER2/neu (Herceptin therapy) Pharmacogenetics: The Study of Variations in Genes that Affect Responses to Drugs Genetic changes specifically within malignant tumor cells Inherited genetic variability in a targeted gene or group of functionally-related genes affecting response to drugs Pharmacokinetics: What the Body Does to the Drug Absorption – substance enters the body Distribution – drug disperses to fluids and tissues Metabolism – transform parent compound into daughter compounds Excretion – elimination of parent drug and daughter compounds from the body Pharmacokinetic Metabolism: transform parent compound into daughter metabolites Parent compounds are converted to metabolites that are more water soluble so they can be more easily excreted Bioactivation: Prodrugs are converted into therapeutically active compounds Cytochrome P450 Enzymes Supergene family Active in the liver and small intestine Named for the characteristic absorption spectra of the protein products (450 nm) Human genome: 57 CYP genes 15 genes involved in metabolism of xenobiotics 75% of total metabolism of drugs 14 genes involved in metabolism of sterols 4 genes oxidize fat-soluble vitamins 9 involved in metabolism of fatty acids and eicosanoids 15 unknown function CYP Nomenclature CYP 2 D 6 *1 *1 is usually wild-type Supergene family Family Subfamily Isoenzyme Allelic variant Tamoxifen Approved by the US FDA for the treatment and prevention of breast cancer Anti-estrogen SERM: selective estrogen receptor modulator CYP2D6 and Tamoxifen At least 70 CYP2D6 allelic variants Reduced activity of CYP2D6 → reduced metabolism of tamoxifen → poor response to tamoxifen Classification of alleles Poor metabolizers Intermediate metabolizers Extensive metabolizers Ultrarapid metabolizers Ethnic variation – CYP2D6*4 – poor metabolizer 12% - 21% Northern Europeans 1% - 2% Asians and Black Africans CYP2D6*10 – intermediate metabolizer Most common allele in Asians Tamoxifen: A Prodrug Requiring Extensive Metabolism Tamoxifen 4-hydroxyTAM CYP2D6 MINOR METABOLITE 100X POTENCY CYP3A4/5 CYP3A4/5 CYP2D6 N-desmethylTAM MAJOR METABOLITESAME POTENCY Endoxifen MODERATE METABOLITE100X POTENCY Genetic variants of CYP2D6 and drugs that modulate this enzyme significantly affect outcome in tamoxifen-treated patients Adapted from Goetz, M. P. et al. J Clin Oncol; 23:9312-9318 2005 Side effects of Tamoxifen and Treatment with Antidepressants Hot flashes most common side effect Treated with antidepressants: SSRIs (selective serotonin reuptake inhibitors) Inhibit CYP2D6 activity Potent inhibitors (paroxetene, fluoxetine) reduce endoxifen levels Less potent inhibitors (venlafaxine) have little effect Patients with decreased metabolism: Shorter time to recurrence Worse relapse-free survival Potent CYP2D6 inhibitors such as certain SSRIs are contraindicated in tamoxifen-treated patients CYP2D6 Poor Metabolizers •Patients diagnosed with breast cancer should be treated with alternatives to tamoxifen (e.g. aromatase inhibitors) •For breast cancer prevention, raloxifene is a viable alternative to tamoxifen Recommended reading: Snozek CLH, O’Kane DJ, and Algeciras-Schimnich A.: Pharmacogenetics of Solid Tumors: Directed Therapy in Breast, Lung, and Colorectal Cancer. J Mol Diagn 2009, 11:381-389, DOI: 10.2353/jmoldx.2009.090003 Training and Education Haspel A et al. A Call to Action: Training Pathology Residents in Genomics and Personalized Medicine. Am J Clin Pathol 2010;133:832-834 Didactic presentations Personalized Medicine Teaching Set of Genomic Cases Voluntary commercial genome SNP analysis Disease-gene investigation and presentation- each resident investigates, interprets and discusses a case Encourage translational research © American Society for Investigative Pathology Didactic Presentations Haspel A et al. A Call to Action: Training Pathology Residents in Genomics and Personalized Medicine. Am J Clin Pathol 2010;133:832-834 Current state of genome analysis Basics of next-generation sequencing technologies and potential diagnostic applications Genetic counselors: Use of genetic information to guide and counsel patients and physicians Use of variation databases and linked literature review HGVbaseG2P, DGV, dbSNP, … © American Society for Investigative Pathology Personalized Medicine Teaching Set of Genomic Cases Haspel A et al. A Call to Action: Training Pathology Residents in Genomics and Personalized Medicine. Am J Clin Pathol 2010;133:832-834 Multiple theoretical genomic cases, each consisting of: Clinical case and family history for a patient Genome sequence variations for patient compared to a reference sequence © American Society for Investigative Pathology