2015 bioinformatics personal_genomics_wim_vancriekinge

FBW
15-12-2015
Wim Van Criekinge

Examen
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Who does practical exam 5th of january (8u30 – 11u30)?

Lab for Bioinformatics and computational genomics
107 106 105 104 103 102 101 1108109
Full genome bp
G
E
N
E
T
I
C
Whole-genome
sequencing
Enrichment seq
(Exome)
PCR
Enrichment
Targeted Panels
Instrument and Assay providers
CLIA Lab service providers

Personalized Medicine
• The use of diagnostic tests (aka biomarkers) to identify in advance
which patients are likely to respond well to a therapy
• The benefits of this approach are to
– avoid adverse drug reactions
– improve efficacy
– adjust the dose to suit the patient
– differentiate a product in a competitive market
– meet future legal or regulatory requirements
• Potential uses of biomarkers
– Risk assessment
– Initial/early detection
– Prognosis
– Prediction/therapy selection
– Response assessment
– Monitoring for recurrence

Biomarker
First used in 1971 … An objective and
« predictive » measure … at the molecular
level … of normal and pathogenic processes
and responses to therapeutic interventions
Characteristic that is objectively measured and
evaluated as an indicator of normal biologic
or pathogenic processes or pharmacologic
response to a drug
A biomarker is valid if:
– It can be measured in a test system with well
established performance characteristics
– Evidence for its clinical significance has been
established

Rationale 1:
Why now ? Regulatory path becoming more clear
There is more at stake than
efficient drug
development. FDA
« critical path initiative »
Pharmacogenomics
guideline
Biomarkers are the
foundation of « evidence
based medicine » - who
should be treated, how
and with what.
Without Biomarkers
advances in targeted
therapy will be limited and
treatment remain largely
emperical. It is imperative
that Biomarker
development be
accelarated along with
therapeutics

Why now ?
First and maturing second generation molecular
profiling methodologies allow to stratify clinical
trial participants to include those most likely to
benefit from the drug candidate—and exclude
those who likely will not—pharmacogenomics-
based
Clinical trials should attain more specific results
with smaller numbers of patients. Smaller
numbers mean fewer costs (factor 2-10)
An additional benefit for trial participants and
internal review boards (IRBs) is that
stratification, given the correct biomarker, may
reduce or eliminate adverse events.

Molecular Profiling
The study of specific patterns (fingerprints) of proteins,
DNA, and/or mRNA and how these patterns correlate
with an individual's physical characteristics or
symptoms of disease.

Generic Health advice
• Exercise (Hypertrophic Cardiomyopathy)
• Drink your milk (MCM6 Lactose intolarance)
• Eat your green beans (glucose-6-phosphate
dehydrogenase Deficiency)
• & your grains (HLA-DQ2 – Celiac disease)
• & your iron (HFE - Hemochromatosis)
• Get more rest (HLA-DR2 - Narcolepsy)

Generic Health advice (UNLESS)
• Drink your milk (MCM6 Lactose intolarance)

Generic Health advice (UNLESS)
• Drink your milk (MCM6 Lactose intolerance)

Overview
Personalized Medicine,
Biomarkers …
… Molecular Profiling
First Generation Molecular Profiling
Next Generation Molecular Profiling
Next Generation Epigenetic Profiling
Concluding Remarks

Before molecular profiling …

• Flow cytometry correlates surface markers,
cell size and other parameters
• Circulating tumor cell assays (CTC’s)
quantitate the number of tumor cells in the
peripheral blood.
• Exosomes are 30-90 nm vesicles secreted by
a wide range of mammalian cell types.
• Immunohistochemistry (IHC) measures
protein expression, usually on the cell
surface.

• Gene sequencing for mutation detection
• Microarray for m-RNA message detection
• RT-PCR for gene expression
• FISH analysis for gene copy number
• Comparative Genome Hybridization (CGH) for
gene copy number

Basics of the “old” technology
• Clone the DNA.
• Generate a ladder of labeled (colored)
molecules that are different by 1 nucleotide.
• Separate mixture on some matrix.
• Detect fluorochrome by laser.
• Interpret peaks as string of DNA.
• Strings are 500 to 1,000 letters long
• 1 machine generates 57,000 nucleotides/run
• Assemble all strings into a genome.

Genetic Variation
Among People
0.1% difference among
people
GATTTAGATCGCGATAGAG
GATTTAGATCTCGATAGAG
Single nucleotide polymorphisms
(SNPs)

The genome fits as an e-mail attachment

The Technical Feasibility Argument
The Quality Argument
The Price Argument
The Logistics Argument

Recreational genomics

• Experimental designs are outdated by technological advances
• Genetic background (reference genome) as a concept will need to be
updated
• Traits dependent on multiple loci are “complicated”: educate and
provide tools to deal with it

• Eye color … why not the ear wax/asparagus or unibrown example
• … metabolize nutrients (newborns ?)
• … metabolize drugs in case you need it urgently ?

“several 23andMe users have reported taking the FDA’s
advice of reviewing their genetic results with their
physicians, only to find the doctors unprepared, unwilling,
or downright hostile to helping interpret the data”

my genome is too important (for me)
to leave it (only) to doctors

NXTGNT biohackerspace …

PGMv2: Personal Genomics Manifesto

Everyone should have the power and legitimacy to
be able to discover, develop and find new things
about their own genome data.
Intelligent exploration, experimentation and trial to
push the boundaries of knowledge are a basic
human right.

Personal genome data access should be
affordable to all irrespective of nationality, gender,
social background or any other circumstance.
Not having access to a personal genetic test is in
itself a new kind of discrimination.

Whether one wants to share genome data or keep it
private should be a matter of personal choice.
Whatever attitude a person has towards personal
genome privacy, it should be utterly respected.
Corporate interest can never compromise any human
right. Laws must fully protect individual human rights of
equality for every person, irrespective of predicted risks
from genetic data.

Stating that genetic tests merely provide non-
clinical information misses the point of what
personal genomics is all about.
Most genomic information is uninterpretable and
may well be meaningless. But those are not
reasons to deny it to people.
Genetic test results are not unrelated to
someone’s health, one’s ability to respond to
certain drugs and one’s ethnic ancestry.

Education in risks and opportunities for personal
genetic testing should be the primary aim of
policy makers.
Restricting access to interested people makes
no sense and it is virtually impossible to ensure.
Access to personal genomics data and tools for
its interpretation should become accessible to
everyone.

Translational Medicine: An inconvenient truth
• 1% of genome codes for proteins, however
more than 90% is transcribed
• Less than 10% of protein experimentally
measured can be “explained” from the
genome
• 1 genome ? Structural variation
• > 200 Epigenomes ??
• Space/time continuum …

Translational Medicine: An inconvenient truth
• 1% of genome codes for proteins, however
more than 90% is transcribed
• Less than 10% of protein experimentally
measured can be “explained” from the
genome
• 1 genome ? Structural variation
• > 200 Epigenomes …
• “space/time” continuum

Epigenetic (meta)information = stem cells
Cellular programming

Cellular reprogramming
Tumor
Epigenetically
altered, self-
renewing cancer
stem cells
Tumor
Development
and
Growth

Gene-specific
Epigenetic
reprogramming
Cellular reprogramming

2015 bioinformatics personal_genomics_wim_vancriekinge

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2015 bioinformatics personal_genomics_wim_vancriekinge