Microarrays, SNPs and ApplicationsMicroarrays, SNPs and Applications
DNADNA
mRNAmRNA ProteinProtein
MicroarraysMicroarrays
What is a microarray?
A microarray is a compact device that contains a large number of well-defined immobilized capture molecules (e.g. synthetic oligos, PCR products, proteins, antibodies) assembled in an addressable format.
You can expose an unknown (test) substance on it and then examine where the molecule was captured.
You can then derive information on identity and amount of captured molecule.
Microscope slideMicroscope slide DNAmicroarray
ActinDNA
CyclinDDNA
DHFRDNA
RBDNA
E2F1DNA
tubulinDNA
controlDNA
MycDNA
Src1DNA
16 17 18
7
8
9
Microarray Technology
Manufacture or Purchase Microarray
Hybridize
Detect
Data Analysis
Advantages of MicroarraysAdvantages of Microarrays
Small volume deposition (nL)
Minimal wasted reagents
Access many genes / proteins simultaneously
Can be automated
Potentially quantitative
Limitations of MicroarraysLimitations of Microarrays Relatively new technology (10 years old)
Still has technical problems (background)
Poor reproducibility between investigators
Still mostly manual procedure
Relatively expensive
Applications of MicroarraysApplications of Microarrays Gene expression patterns
Single nucleotide polymorphism (SNP) detection
Sequence by hybridization / genotyping / mutation detection
Study protein expression (multianalyte assay) Protein-protein interactions
Provides: Massive parallel information
If Microarrays Are So Good Why If Microarrays Are So Good Why Didn’t We Use Them Before??Didn’t We Use Them Before??
Not all genes were available No SNPs known No suitable bioinformatics New proteins now becoming available
Microarrays and associated technologies should be regarded as by-products of the Human Genome Initiative,Nanotechnology and Bioinformatics
Reviews on MicroarraysReviews on Microarrays
A whole issue on Microarray Technology has been published by Nature Genetics, Dec. 2002 (Vol. 32)
Books: Bowtell D. Sambrook J. DNA Microarrays. Cold Spring
Harbor Laboratory Press, 2003
Schena M. Microarray Analysis. Wiley Liss, 2003
HistoryHistory
1991 - Photolithographic printing (Affymetrix)
1994 - First cDNA collections are developed at Stanford.
1995 - Quantitative monitoring of gene expression patterns with a complementary DNA microarray
1996 - Commercialization of arrays (Affymetrix) 1997- Genome-wide expression monitoring in S. cerevisiae (yeast) 2000 – Portraits/Signatures of cancer
2003 - Introduction to clinical practice
2004-Whole human genome on one microarray
Microarray FabricationMicroarray Fabrication
Two Major Methods:Two Major Methods:
[a] Affymetrix Photolithography (400,000 spots in 1.25 x 1.25 cm area!)
[b] Everybody else Mechanical deposition (printing) [0.5 - 2nL] on
glass slides, membranes,etc
Principles of DNA Microarrays Principles of DNA Microarrays (printing oligos by photolithography) (printing oligos by photolithography)
(Fodor et al.(Fodor et al. Science 1991;251:767-773)Science 1991;251:767-773)
Microarrays, such as Affymetrix’s GeneChip, now include all 50,000 known human genes.
Science, 302:211, 10 October, 2003
Affymetrix Expression ArraysAffymetrix Expression Arrays
They immobilize oligonucleotides (de novo synthesis; 25 mers)
For specificity and sensitivity, they array 22 oligos per gene
Latest version covers 50,000 genes (whole human genome) in one array (Agilent Technologies has the same density array; G4112A)
They label-test RNA with biotin and detect with streptavidin-fluor conjugates
Preparation of Labeled mRNAPreparation of Labeled mRNAfor Hybridizationfor Hybridization
Use oligo-dT with a T7 RNA polymerase promoter for reverse transcription of extracted mRNA
(procedure makes cDNA)
Use T7 RNA polymerase and biotin-labeled ribonucleotides for in vitro transcription (produces biotinylated, single-stranded cRNA)
Alternatively: You can directly label cRNA with Cy-3 and Cy-5 fluors using T7 RNA polymerase
Microarray ApplicationsMicroarray Applications
Differential Gene ExpressionDifferential Gene Expression
Cy3-UTPgreen fluorescence
reverse transcriptase,T7 RNA polymerase
Cy5-UTPred fluorescence
cRNA
sample 2(reference)
RNAcDNA
sample 1(tumortissue)
RNAcDNA
cRNA
RNA extraction and labelingRNA extraction and labelingto determine expression levelto determine expression level
sample of interestcompared tostandard reference
12345678910
Reference tissuecRNA (green)
Tumor tissuecRNA (red)
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10Human genes
on a microarray slide
Differential Gene ExpressionDifferential Gene Expression(Budding vs Non-Budding Yeast)(Budding vs Non-Budding Yeast)
Normal vs. NormalNormal vs. Normal
Normal vs. TumorNormal vs. Tumor
Lung Tumor: Up-RegulatedLung Tumor: Up-Regulated
Lung Tumor: Down-RegulatedLung Tumor: Down-Regulated
Lung Tumor: Up-RegulatedLung Tumor: Up-Regulated
Signal transduction Cytoskeleton
Proteases/Inhibitors Kinases
Lung Tumor: Up-RegulatedLung Tumor: Up-Regulated
Signal transduction Cytoskeleton
Proteases/Inhibitors Kinases
Cyclin B1Cyclin B1
Cyclin-dependentCyclin-dependentkinasekinase
Tumor expression-Tumor expression-related proteinrelated protein
Lung Tumor: Down-RegulatedLung Tumor: Down-RegulatedSignal transduction Cytoskeleton
Proteases/Inhibitors Kinases
Lung Tumor: Down-RegulatedLung Tumor: Down-RegulatedSignal transduction Cytoskeleton
Proteases/Inhibitors Kinases
Tumor necrosisTumor necrosisfactor-related proteinfactor-related protein
Genes Common to Many TumorsGenes Common to Many Tumors(e.g.Kidney; Liver; Lung)(e.g.Kidney; Liver; Lung)
Up-regulated
Down-regulated
Microarray ApplicationsMicroarray Applications
Whole Organism BiologyWhole Organism Biology
Whole Genome Biology With MicroarraysWhole Genome Biology With Microarrays
Cell cycle in yeastStudy of all yeast genessimultaneously!RedRed: High expressionBlueBlue: Low expression
Lockhart and Winzeler Nature 2000;405:827-836
Microarray ApplicationsMicroarray Applications
Single Nucleotide Polymorphism (SNP) AnalysisSingle Nucleotide Polymorphism (SNP) Analysis
Single Nucleotide Polymorphisms (SNP)Single Nucleotide Polymorphisms (SNP)
DNA variation at one base pair level; found at a frequency of 1 SNP per 1,000 - 2,000 bases
A map of 9 x 106 SNPs has been described in humans (by the International SNP map working group (HapMap)
60,000 SNPs fall within exons; the rest are in introns
Why Are SNPs Useful?Why Are SNPs Useful? Human genetic diversity depends on SNPs between
individuals (these are our major genetic differences, plus micro/minisatellites)
Specific combinations of alleles (called “Haplotypes”) seem to play a major role in our genetic diversity
How does this genotype affect the phenotype
Disease predisposition?Disease predisposition?
Why Are SNPs Useful?Why Are SNPs Useful? Diagnostic Application
Determine somebody’s haplotype (sets of SNPs) and assess disease risk.
Be careful: These disease-related haplotypes are not as yet known!
NatureNature 2003 426: 789-796 2003 426: 789-796
Genotyping: SNP MicroarrayGenotyping: SNP Microarray Immobilized allele-specific oligo probes Hybridize with labeled PCR product Assay multiple SNPs on a single array
TTAGCTAGTCTGGACATTAGCCATGCGGATGACCTGTAATCG
Many other methodsMany other methodsFor SNP analysis have For SNP analysis have
been developedbeen developed
TTAGCTAGTCTGGACATTAGCCATGCGGAT
GACCTATAATCG
SNP Analysis by MicroarraySNP Analysis by Microarray
GeneChip® HuSNPGeneChip® HuSNPTMTM Mapping Assay (Affymetrix) Mapping Assay (Affymetrix)
More than 10,000 single nucleotide polymorphisms (SNPs) covering all 22 autosomes and the X chromosome in a single experiment (soon to move to 100,000 SNPs per experiment).
Coverage:1 SNP per 210 kb of DNA
Needs:250 ng of genomic DNA-1 PCR reaction
Commercial Microarray for Clinical Use Commercial Microarray for Clinical Use (Pharmacogenomics)(Pharmacogenomics)
Roche Product
CYP 450 Genotyping(drug metabolizing system)
FDA ConfusionClass 1 medical device? (no PMA)
Class 2 or 3 medical device?(requires pre-market approval)
From: Nature Biotechnology 2003 21:959-60
“The US government has blocked the sale of a new kind of DNA diagnostic test, putting up an
unexpected barrier to the marketing of technology to distinguish genetic differences in how patients
metabolize certain drugs.”
Science Science 2003 302: 11342003 302: 1134
SNP Detection by Mass SpectrometrySNP Detection by Mass Spectrometry
High throughput detection of SNPs can be achieved by mass spectrometry
SNP Center in Toronto (PMH) runs a Sequenom Mass Spectrometry system
Microarray ApplicationsMicroarray Applications
Sequencing by HybridizationSequencing by Hybridization
Sequencing By HybridizationSequencing By Hybridization
Address the need for high-speed, low-cost sequencing of large sequences in parallel.
Example:Consider examining 50Kb of sequence for 1,000 individuals.
Conventional MethodConventional Method MicroarrayMicroarray
50Kb x 1,000 = 50 Mb of sequence. At a rate of 500 bases per lane and 30 sequencing lanes, you can produce 15 Kb of sequence per day. You need 10 years for the project.
With one microarray of 1.25 x 1.25 cm dimension, you can scan 50 Kb of sequence at once. You need 1,000 microarrays to complete task. This may be completed in a few days.
Sequencing by Microarray TechnologySequencing by Microarray Technology
GeneChip p53 Assay ReagentsGeneChip p53 Assay Reagents
p53 Primer Set: PCR primer pairs of exons 2-11 optimized for a single-tube multiplex reaction
Fragment Reagent: DNase 1 for DNA fragmentation
Control Oligonucleotide F1: Positive hybridization control
p53 Reference DNA: Human placental DNA
GeneChip p53 Assay GeneChip p53 Assay Performance CharacteristicsPerformance Characteristics
Bases of genomic DNA analyzed 1262 bp
Base calling accuracy for missense > 99.9%mutations
Time from purified DNA to data 4.5 hrs
Maximum steady state throughout equivalent to 6310 bp/hr
As validated on a set of 60 human p53 genomic DNA samples. “Maximum steady state through-put based on one GeneChip analysis system.
Microarray Applications-Non Human - Chips Microarray Applications-Non Human - Chips Avaliable Now (2004)Avaliable Now (2004)
Pathogens (detection of Bird-Flu Virus strains)
Smallpox (bioterrorism)
Malaria (Plasmodium anopheles)
Zebrafish/Xenopus laevis (model organisms)
SARS Virus sequencing
Microarray ApplicationsMicroarray Applications
Food Expert-ID (available by Bio-Merieux;2004)
DNA chip can verify quickly the animal species composition and the authenticity of raw or processed food and animal feed
By providing multi-species identification, FoodExpert-ID will help to improve safety of food for human and animal consumption, thereby contributing to consumer health protection
Microarray ApplicationsMicroarray Applications
Protein MicroarraysProtein Microarrays
Protein MicroarraysProtein Microarrays Protein microarrays are lagging behind DNA microarrays
Same idea but immobilized elements are proteins instead of nucleic acids
Number of elements (proteins) on current protein microarrays are limited (approx. 500)
Antibodies for high density microarrays have limitations (cross-reactivities)
Aptamers or engineered antibodies/proteins may be viable alternatives
(Aptamers:RNAs that bind proteins with high specificity and affinity)
ApplicationsApplications
Screening for:Screening for: Small molecule targets Post-translational
modifications Protein-protein
interactions Protein-DNA
interactions Enzyme assays Epitope mapping
High-throughput proteomic analysisHigh-throughput proteomic analysis
Haab et al. Haab et al. Genome BiologyGenome Biology 2000;1:1-22 2000;1:1-22Protein array now commerciallyProtein array now commerciallyavailable by BD Biosciences(2002)available by BD Biosciences(2002)
Label all Proteins in Mixture
marker proteinmarker protein
cytokine cytokine
VEGFIL-10IL-6IL-1 MIX
BIOTINYLATED MAb
CAPTURE MAb
ANTIGEN
Detection system
Cytokine Specific Microarray Cytokine Specific Microarray (Microarray version of ELISA)(Microarray version of ELISA)
Competing High Throughput Protein TechnologiesCompeting High Throughput Protein Technologies
Bead-Based Technologies Luminex-flow cytometry Illumina-bead chips
Microfluidics Zyomyx
Mass spectrometry Ciphergen-protein chips
Microarray Clinical ApplicationsMicroarray Clinical Applications
Cancer DiagnosticsCancer Diagnostics
Molecular Portraits of CancerMolecular Portraits of Cancer
Rationale:Rationale:The phenotypic diversity of breast and other tumors The phenotypic diversity of breast and other tumors
might be accompanied by a corresponding diversity in might be accompanied by a corresponding diversity in gene expression patterns that can be captured by using gene expression patterns that can be captured by using
cDNA microarrayscDNA microarraysThenThen
Systematic investigation of gene expressionSystematic investigation of gene expressionpatterns in human tumors might provide the basispatterns in human tumors might provide the basis
of an of an improved taxonomyimproved taxonomy of breast cancers of breast cancers
Perou et al. Nature 2000;406:747-752
Molecular Portraits of CancerMolecular Portraits of Cancer
Breast CancerBreast CancerPerou et al. Nature 2000;406:747-752
GreenGreen: UnderexpressionBlackBlack: Equal expressionRedRed: Overexpression
Left Panel: Cell LinesRight Panel: Breast Tumors
Figure Represents 1753 GenesFigure Represents 1753 Genes
Differential Diagnosis ofDifferential Diagnosis of Childhood Malignancies Childhood Malignancies
Ewing Sarcoma: YellowYellow Rhabdomyosarcoma: RedRed
Burkitt Lymphoma: BlueBlue
Neuroblastoma: GreenGreen
Khan et al. Nature Medicine 2001;7:673-679
Differential Diagnosis of Childhood MalignanciesDifferential Diagnosis of Childhood Malignancies(small round blue-cell tumors, SRBCT)(small round blue-cell tumors, SRBCT)
EWS = Ewing SarcomaEWS = Ewing SarcomaNB = NeuroblastomaNB = NeuroblastomaRMS = RhabdomyosarcomaRMS = RhabdomyosarcomaBL = Burkitt’s LymphomaBL = Burkitt’s Lymphoma
Note the relatively small number of genes necessary for completediscrimination
Khan et al. Nature Medicine 2001;7:673-679
Microarray Milestone: Microarray Milestone: June 2003 June 2003
Nature 2002; 415: 530-536
NEJM 2002; 347: 1999-2009
Van’t Veer and colleagues are using microarray profiling as a routine tool for breast cancer management (administration of adjuvant chemotherapy after surgery).
Their profile is based on expression of 70 genes
Question:Can microarray profiling be used in clinical practice?Prognosis/Prediction of therapy/Selection of patients who should be treated aggressively?
premenopausal, lymph node negativepremenopausal, lymph node negative
Gene Expression profiling
Treatment Tailoring by ProfilingTreatment Tailoring by Profiling
Adjuvant chemo- andAdjuvant chemo- andhormonal therapyhormonal therapy
No adjuvant therapy No adjuvant therapy or hormonal therapy onlyor hormonal therapy only
Poor signaturePoor signature~~ 56 % metastases at 10 yrs 56 % metastases at 10 yrs
~ 50 % death at 10 yrs~ 50 % death at 10 yrs
60%60%
Good signatureGood signature~~ 13 % metastases at 10 yrs 13 % metastases at 10 yrs
~ 4 % death at 10 yrs~ 4 % death at 10 yrs
40%40%
295 patients295 patientsKaplan-Meier Survival CurvesKaplan-Meier Survival Curves
surv
ival
meta
stase
s-fr
ee
time (years) time (years)
Profiling in Clinical PracticeProfiling in Clinical Practice
Metastatic potential is an early and inherent ability rather than late and acquired
Predictive power of prognostic signature confirmed in validation series
Prognostic profile outperforms clinical parameters
~30-40% reduction of unnecessary treatment and avoidance of undertreatment (LN0 and LN+)
Therapeutic ImplicationsTherapeutic Implications
Who to treat:Who to treat: Prognostic profile as diagnostic tool
improvement of accurate selection for adjuvant therapy (less under- and over-treatment)
Prognostic profile implemented in clinical trials reduction in number of patients & costs (select only
patients that are at metastatic risk)
How to treat:How to treat: Predictive profile for drug response
selection of patients who benefit
Commercial ClashesCommercial Clashes
Oncotype DX by “Genomic Health Inc”, Redwood City, CA
A prognostic test for breast cancer metastasis based on profiling 250 genes; 16 genes as a group have predictive value; $3,400 per test
215,000 breast cancer cases per year (potential market value > $500 million!)
No validation of test; No FDA approval Test has no value for predicting response to treatment
Science 2004;303:1754-5
Commercial ClashesCommercial Clashes
Mammaprint marketed by Agendia, Amsterdam, The Netherlands
Based on L.Van’t Veer publications Test costs Euro 1650; based on 70 gene
signature Prospective trials underway Celera and Arcturus developing similar tests
(prognosis/prediction of therapy)
Science 2004;303:1754-5
Tissue MicroarraysTissue Microarrays
Printing on a slide tiny amounts of tissue
Array many patients in one slide (e.g. 500)
Process all at once (e.g. immunohistochemistry)
Works with archival tissue (paraffin blocks)
Gene Expression Analysis of TumorsGene Expression Analysis of Tumors
cDNA MicroarraycDNA Microarray
Lakhani and Ashworth Nature Reviews Cancer 2001;1:151-157
Tissue MicroarrayTissue Microarray
Alizadeh et al. J Pathol 2001;195:41-52
Microarray Future: ConclusionsMicroarray Future: Conclusions Differential gene experssion studies will continue(robusness)
Inexpensive, high-throughput, genome-wide scans for clinical applications
Protein microarrays are now being deployed (may take over)
Focus on biology and improved technology
SNP analysis-Disease predisposition
Pharmacogenomics
Diagnostics-Multiparametric analysis
Replacement of single-gene experiments(paradigm shift)
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