A non confidential corporate presentation of "Manteia Predictive Médicine" as of September 2003. Présents DNA colony sequencing resutls, instrument, DNA preparation for genotyping.
3. Tomorrow:
Patient DNA is fully genotyped one time only
A database is consulted in order to
oDevelop a molecular diagnosis of specific disease
oPredict responses to each of the available treatmentsDiagnosis and treatment
Today’s medical practice is for the most part:
Imprecise in diagnosis
Selecting treatment by trial-and-error
4. Tomorrow: the Personal Genome Card is available.
The database is consulted whenever necessary
oGenetic susceptibility to specific diseases is assessed
Preventive measures are taken in consultation with a family physician, including:
oLife style changes
oRoutine screenings for those at elevated risk, allowing for early diagnosis and better prognosis
oPersonalized preventive treatment
Today’s medical practice is for the most part reactive to diseasePrevention
5. Bridging the gap
Need to decipher the genetic basis of common complex diseases and responses to treatment
Today’s technologies are not up to the task:
Too complex (e.g., procedures are SNP specific)
Too expensive (> 0.1€per SNP)
6. Drug Responses are Multigenic
Pharmacokinetics Pharmacodynamics
individual
metabolism
individual
action
Molecular sub-types
Drug Individual responses
individual
pathways
Individual response to medicines is likely a
consequence of many low-effect genetic variants
7. sporadic
Combinations of many low-effect
gene variants
(eg: AD, Migraine, NID- Diabetes, Psoriasis)
Most disease is the result of combinations of low- effect genetic variantsCommon Diseases are Multigenicfamilial
Moderate-penetrance
gene variants
(eg: BRCA1,2)
Single high- penetrance
gene variants
(eg: CF, Huntington Disease)
8. ABCDEFG
ABCDEFG ABCDEFG
ABCDEFG ABCDEFG
ABCDEFG ABCDEFG ABCDEFG ABCDEFG
Over Generations
A combination of many subtle
genetic variants may tip the balance
in favor of disease
ABCDEFG ABCDEFG
Combinations of low-effect variants
9. Finding low effect variants will require high density genotyping of large populations
“…a density of SNPs of one every 10,000 –30,000 bp can rapidly narrow the search for susceptibility genes*.” Roses. Nature, 405 (2000) pp862. (SVP, Genetics Research, GSK)
“…roughly 500,000 SNPs will be required for whole-genome association studies in samples drawn from large outbred populations.” (pp139). “…efficient technologies are needed for genotyping hundreds of thousands of SNPs in thousands of individuals” (pp143). Kruglyak. Nature Genetics, 22 (1999).(Fred Hutchinson Cancer Research Center & HHMI)
*100,000 –300,000 SNPs
10. Multigenic Diseases: Gene Hunting
Genome-wide / hypothesis-free approach
Using very high density markers
At least 300,000 SNPs/genome
Large numbers of subjects
At least 2,000 per disease/treatment
Totaling at least 600 million SNPs typed/disease
Today cost/SNP = 10-20¢
Tractable when cost falls below 1¢/SNP
12. SNPtyping with Manteia technology
No SNP map needed
Not SNP-specific
“One” tube per patient
Readily scalable
Detection method: sequencing genome fragments
Below 0.1¢ per SNP
13. Manteia Technology: PAS( Parallel Amplification and Sequencing )
Four basic steps
1: Isolate genomic DNA from blood or cheek-swab
2: Cut up the DNA and collect the fragments
3: Amplify all the fragments in parallel on a solid surface
4: Sequence all the fragments in parallel
14. Patient 1
Patient n
Isolate
Genomic DNA
Cut DNA with
Restriction Endonuclease Enzyme
1
2
3
4
5
1
2
3
4
5
15. Type IIs
recognition site
n
Genomicfragment
n
Ligation
Type IIs
digest
Short genomic
fragment
n
Linker 1
16. Restriction site
Type IIs
recognition sites
n
Genomicfragment
n
Ligation
n
Type IIs
digest
Short genomic
fragmentsPAS2
17. n
n
Ligation
Linearized
Colony Template
Linker 2
5
4
3
2
1
DNA fragment sizes
normalized
Each restriction endonuclease=> ~1.5 million fragments
18. 5
4
3
2
1
Clone DNA fragments
Into “DNA Colony Vectors”
5
4
3
2
1
DNA fragment sizes
normalized
n
Variable region
Constant region
Constant region
19. n
Colony vectors
Short primers
n
n
Functionalization
Chemically functionalized surface
20. PAS Array
Density = f([template],[primer],t)
ss DNA Colony Vector(107/cm2)
ss Oligonucleotide
Primers (4x104/μm2)
Glass surface
1
2
5’ endscovalently attached
3’ endsfree in solution
23. 1-2 μm
DNA
Colonies
(1000-2000 copies in each)
1
2
100 μm
24. Sequencing primers
Added to the array
DNA:DNA
Hybrids
C
A
C
T
G
C
T
G
A
Sequencing primer
Anonymous
Fragment of genomic
DNA (Variable region)
Colony Vector (Constant region)
Colony Vector (Constant region)
25. Cycle 3
C
A
C
T
G
C
T
G
A
G
T
0
1
2
3
4
Signal
A
G
T
C
C
A
C
T
G
C
T
G
A
A
0
1
2
3
4
Signal
A
G
T
C
Cycle 1
Wash
Add
C
A
C
T
G
C
T
G
A
Cycle 2
G
0
1
2
3
4
Signal
A
G
T
C
30. Genetic variability in the human population:
Between 2 individuals: 1 SNP every 1331 bp
(SNP consortium, Nature 409,928)
In the population (Krugliak, Nature Genetics 27,234 ):
Frequency >= 10% : 1 SNP every 600bp
Frequency >= 1% : 1 SNP every 290bp
Frequency >= 0.1%: 1 SNP every 200 bp
31. The same stretches of DNA are sequenced in each patient
patient #1
patient #47
patient #125
patient #571
....
....
Sequenced fragments
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
acgtaggtgcaggtcagt
…
tagcgtAtcgtaggtagat
tagcgtAtcgtaggtagat
tagcgtAtcgtaggtagat
tagcgtAtcgtaggtagat
tagcgtGtcgtaggtagat
tagcgtAtcgtaggtagat
tagcgtAtcgtaggtagat
tagcgtAtcgtaggtagat
tagcgtGtcgtaggtagat
tagcgtAtcgtaggtagat
…
SNP
Making SNP identification possible
Each restriction endonuclease: => 1.5 million fragments
=> 25 million bases sequenced
=> 1% of the genome scanned
=> 100,000 SNPs scored
32. Mega-SNP data analysis: “genetic” approach
Classical frequent SNP problem:
-number SNP >> population
-distance between SNP > linkage range
-moderate population (50~300)
=> How to differentiate real linkage signal from false positives/negatives
Manteia’s Mega-SNP approach:
-distance between SNP < linkage range
-moderately frequent SNPs
-large population (1,000~10,000)
=>SNP clusters of high statistical signifcance
1 Mbp
Linkage
Signal
1 Mbp
Linkage
Signal
2~4 LD range
“running average”
33. SNPtyping with Manteia technology
No dependent on SNP maps
Not SNP-specific
“One” tube per patient
Readily scalable
Detection method: sequencing genome fragments
Tracktable biostatistics and bioinformatics
Below 0.1¢ per SNP (Q1-2006)
34. Business Model
Identify Gene Variant Associations
Alone or in partnerships
Retain rights to these associations for application to:
Therapeutic response prediction
Disease risk assessments
License out rights for application to:
Drug discovery
Develop and market a Personal Genome Card in conjunction with access to a database of clinical and genetic associations.
35. Collaborations with biopharmaceutical companies
Clinical partnerships
Clinical trials assessment & recruitment
Drug revival
Development of marketed Companion Tests
Discovery partnerships
Target discovery in diseased populations
Transcriptome analysisCollaborations
36. Collaborations
Clinical
Studies
Association Studies
Gene Variants
Disease
Causation
Progression
Drug Targets
Response to Therapy
Drug Discovery
Predictive Tests
Marketing
Manteia
Technology
Individual
Patterns
37. Personal Genome Card
Internal Programs:
Personal Treatment Guidelines
In conjunction with Personal Genome Cards
Predict patient responses to therapy
Efficacy and side-effects
Personal Risk Profiles
In conjunction with Personal Genome Cards
Predict lifetime risk of sporadic cases of common diseases.
Permit appropriate interventions and monitoring for those at risk. Business Model
38. Treatment Guidelines
Single Disease Clinical Populations
Association Studies
Patterns ofGene Variants
Manteia
Technology
Therapy 1
Responders
Non
Responders
Therapy 2
Responders
Non
Responders
Therapy 3
Responders
Non
Responders
Pharmacokinetics
Pharmacodynamics
Disease subgrouping
Genotypes
Personal
Genotype
Card
Treatment
Guideline
PRODUCT
39. Disease Selection
Serious diseases
High incidence
Several treatments available
Each treatments works for only a fraction of patients
Treatments are expensive
Treatments have serious side effects
Delaying effective treatments leads to poorer prognosis
All frequent diseases where sub-optimal treatment has a high cost
40. Personal Treatment Guidelines
Market example: Breast Cancer
200,000 new diagnoses each year in US; 300,000 in EU.
$2,500 per comprehensive Treatment Guideline
Potential US+EU market: $1.25B/year
Maximal penetration @ 30% = $375MM/year
Net income @ 20% = $75MM/year
Personal Genome Card
41. Risk Profiles
Association Studies
Patterns ofGene Variants
Manteia
Technology
Genotypes
Personal
Genotype
Card
Risk Profile
PRODUCT
Single Disease Clinical Populations
Disease
Subgroups
Matched Populations
42. Disease Selection
High incidence
Prevention is possible
Preventive treatment is available
Early diagnosis leads to much better prognosis
Where there is either no available screen
Where screening is expensive or unpleasant
43. Personal Risk Profiles
Market example: Colorectal cancer
4,000,000 turn 50 each year in the US
8,000,000 target population US+EU
$500 Risk Profile for colorectal cancers
Potential US+EU market: $4B per year
Maximal penetration @ 10% = $400MM/year
Net income @ 10% = $40MM/year
Personal Genome Card