Microarrays, SNPs and ApplicationsMicroarrays, SNPs and Applications

Eleftherios P. Diamandis MD,Ph.DEleftherios P. Diamandis MD,Ph.D

(ediamandis@mtsinai.on.ca) (ediamandis@mtsinai.on.ca) Website:www.acdclab.org

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)