Transcript No Slide Title

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