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Lab for Bioinformatics and computational genomics
107 106 105 104 103 102 101 1108109
Full genome bp
GENETIC
Whole-genomesequencing
Enrichment seq(Exome) PCREnrichment
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)
• 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)
• Exercise (Hypertrophic Cardiomyopathy)• Drink your milk (MCM6 Lactose intolerance)• 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)
• Exercise (Hypertrophic Cardiomyopathy)• Drink your milk (MCM6 Lactose intolerance)• 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)
Overview
Personalized Medicine, Biomarkers … … Molecular Profiling
First Generation Molecular ProfilingNext Generation Molecular ProfilingNext Generation Epigenetic Profiling
Concluding Remarks
First Generation 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.
First Generation Molecular Profiling
• 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
GATTTAGATCGCGATAGAGGATTTAGATCTCGATAGAG
Single nucleotide polymorphisms(SNPs)
Lab for Bioinformatics and computational genomics
The Technical Feasibility Argument
The Quality Argument
The Price Argument
The Logistics Argument
Lab for Bioinformatics and computational genomics
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
Lab for Bioinformatics and computational genomics
Recreational genomics
• Eye color … why not the ear wax/asparagus or unibrown example
• … metabolize nutrients (newborns ?)• … metabolize drugs in case you need it urgently ?
Lab for Bioinformatics and computational genomics
Recreational genomics
“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”
Lab for Bioinformatics and computational genomics
my genome is too important (for me) to leave it (only) to doctors
Lab for Bioinformatics and computational genomics
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 topush the boundaries of knowledge are a basic human right.
PGMv2: Personal Genomics Manifesto
Lab for Bioinformatics and computational genomics
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.
PGMv2: Personal Genomics Manifesto
Lab for Bioinformatics and computational genomics
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.
PGMv2: Personal Genomics Manifesto
Lab for Bioinformatics and computational genomics
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.
PGMv2: Personal Genomics Manifesto
Lab for Bioinformatics and computational genomics
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.
PGMv2: Personal Genomics Manifesto
First Generation Molecular Profiling
• 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
First Generation Molecular Profiling
• 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
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
Cellular reprogramming
Tumor
Epigenetically altered, self-renewing cancer stem cells
Tumor Development and Growth