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Microarrays, SNPs and Applications : 

Microarrays, SNPs and Applications Eleftherios P. Diamandis MD,Ph.D (ediamandis@mtsinai.on.ca) Website:www.acdclab.org

Microarrays : 

Microarrays 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.

Slide3: 

Microscope slide DNA microarray

Microarray Technology Manufacture or Purchase Microarray Hybridize Detect Data Analysis : 

Microarray Technology Manufacture or Purchase Microarray Hybridize Detect Data Analysis

Advantages of Microarrays: 

Advantages of Microarrays Small volume deposition (nL) Minimal wasted reagents Access many genes / proteins simultaneously Can be automated Potentially quantitative

Limitations of Microarrays: 

Limitations 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 Microarrays : 

Applications 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 Didn’t We Use Them Before??: 

If Microarrays Are So Good Why 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 Microarrays: 

Reviews 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

History: 

History 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 Fabrication 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 : 

Microarray Fabrication 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 (printing oligos by photolithography): 

Principles of DNA Microarrays (printing oligos by photolithography) (Fodor et al. Science 1991;251:767-773)

Slide13: 

Microarrays, such as Affymetrix’s GeneChip, now include all 50,000 known human genes. Science, 302:211, 10 October, 2003

Affymetrix Expression Arrays : 

Affymetrix 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 mRNA for Hybridization: 

Preparation of Labeled mRNA for 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 Applications: 

Microarray Applications Differential Gene Expression

Slide17: 

Cy3-UTP green fluorescence reverse transcriptase, T7 RNA polymerase Cy5-UTP red fluorescence cRNA cRNA RNA extraction and labeling to determine expression level sample of interest compared to standard reference

Differential Gene Expression (Budding vs Non-Budding Yeast): 

Differential Gene Expression (Budding vs Non-Budding Yeast)

Normal vs. Normal: 

Normal vs. Normal

Normal vs. Tumor: 

Normal vs. Tumor

Lung Tumor: Up-Regulated: 

Lung Tumor: Up-Regulated

Lung Tumor: Down-Regulated: 

Lung Tumor: Down-Regulated

Lung Tumor: Up-Regulated: 

Lung Tumor: Up-Regulated Signal transduction Cytoskeleton Proteases/Inhibitors Kinases

Lung Tumor: Up-Regulated: 

Lung Tumor: Up-Regulated Signal transduction Cytoskeleton Proteases/Inhibitors Kinases Cyclin B1 Cyclin-dependent kinase Tumor expression- related protein

Lung Tumor: Down-Regulated: 

Lung Tumor: Down-Regulated Signal transduction Cytoskeleton Proteases/Inhibitors Kinases

Lung Tumor: Down-Regulated: 

Lung Tumor: Down-Regulated Signal transduction Cytoskeleton Proteases/Inhibitors Kinases Tumor necrosis factor-related protein

Genes Common to Many Tumors (e.g.Kidney; Liver; Lung): 

Genes Common to Many Tumors (e.g.Kidney; Liver; Lung) Up-regulated Down-regulated

Microarray Applications: 

Microarray Applications Whole Organism Biology

Whole Genome Biology With Microarrays: 

Whole Genome Biology With Microarrays Cell cycle in yeast Study of all yeast genes simultaneously! Red: High expression Blue: Low expression Lockhart and Winzeler Nature 2000;405:827-836

Microarray Applications: 

Microarray Applications Single 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?

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!

Slide35: 

Nature 2003 426: 789-796

Genotyping: SNP Microarray: 

Genotyping: SNP Microarray Immobilized allele-specific oligo probes Hybridize with labeled PCR product Assay multiple SNPs on a single array Many other methods For SNP analysis have been developed

SNP Analysis by Microarray: 

SNP Analysis by Microarray GeneChip® HuSNPTM 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 (Pharmacogenomics): 

Commercial Microarray for Clinical Use (Pharmacogenomics) Roche Product CYP 450 Genotyping (drug metabolizing system) FDA Confusion Class 1 medical device? (no PMA) Class 2 or 3 medical device? (requires pre-market approval) From: Nature Biotechnology 2003 21:959-60

Slide40: 

“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 2003 302: 1134

SNP Detection by Mass Spectrometry: 

SNP 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 Applications: 

Microarray Applications Sequencing by Hybridization

Sequencing By Hybridization: 

Sequencing 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 Method Microarray 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 Technology: 

Sequencing by Microarray Technology

GeneChip p53 Assay Reagents : 

GeneChip 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 Performance Characteristics: 

GeneChip p53 Assay Performance 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 Avaliable Now (2004): 

Microarray Applications-Non Human - Chips Avaliable Now (2004) Pathogens (detection of Bird-Flu Virus strains) Smallpox (bioterrorism) Malaria (Plasmodium anopheles) Zebrafish/Xenopus laevis (model organisms) SARS Virus sequencing

Microarray Applications: 

Microarray 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 Applications: 

Microarray Applications Protein Microarrays

Protein Microarrays: 

Protein 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)

Applications: 

Applications Screening for: Small molecule targets Post-translational modifications Protein-protein interactions Protein-DNA interactions Enzyme assays Epitope mapping

Slide52: 

High-throughput proteomic analysis Haab et al. Genome Biology 2000;1:1-22 Protein array now commercially available by BD Biosciences(2002)

Cytokine Specific Microarray (Microarray version of ELISA): 

BIOTINYLATED MAb CAPTURE MAb ANTIGEN Detection system Cytokine Specific Microarray (Microarray version of ELISA)

Competing High Throughput Protein Technologies: 

Competing High Throughput Protein Technologies Bead-Based Technologies Luminex-flow cytometry Illumina-bead chips Microfluidics Zyomyx Mass spectrometry Ciphergen-protein chips

Microarray Clinical Applications: 

Microarray Clinical Applications Cancer Diagnostics

Molecular Portraits of Cancer: 

Molecular Portraits of Cancer Rationale: The phenotypic diversity of breast and other tumors might be accompanied by a corresponding diversity in gene expression patterns that can be captured by using cDNA microarrays Then Systematic investigation of gene expression patterns in human tumors might provide the basis of an improved taxonomy of breast cancers Perou et al. Nature 2000;406:747-752

Molecular Portraits of Cancer: 

Molecular Portraits of Cancer Breast Cancer Perou et al. Nature 2000;406:747-752 Green: Underexpression Black: Equal expression Red: Overexpression Left Panel: Cell Lines Right Panel: Breast Tumors Figure Represents 1753 Genes

Differential Diagnosis of Childhood Malignancies: 

Differential Diagnosis of Childhood Malignancies Ewing Sarcoma: Yellow Rhabdomyosarcoma: Red Burkitt Lymphoma: Blue Neuroblastoma: Green Khan et al. Nature Medicine 2001;7:673-679

Differential Diagnosis of Childhood Malignancies (small round blue-cell tumors, SRBCT): 

Differential Diagnosis of Childhood Malignancies (small round blue-cell tumors, SRBCT) EWS = Ewing Sarcoma NB = Neuroblastoma RMS = Rhabdomyosarcoma BL = Burkitt’s Lymphoma Note the relatively small number of genes necessary for complete discrimination Khan et al. Nature Medicine 2001;7:673-679

Microarray Milestone: June 2003 : 

Microarray Milestone: 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?

Slide61: 

premenopausal, lymph node negative Treatment Tailoring by Profiling

295 patients: 

295 patients Kaplan-Meier Survival Curves survival metastases-free time (years) time (years)

Profiling in Clinical Practice: 

Profiling 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 Implications: 

Therapeutic Implications 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: Predictive profile for drug response selection of patients who benefit

Commercial Clashes: 

Commercial 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 Clashes: 

Commercial 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 Microarrays : 

Tissue 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 Tumors: 

Gene Expression Analysis of Tumors cDNA Microarray Lakhani and Ashworth Nature Reviews Cancer 2001;1:151-157

Tissue Microarray: 

Tissue Microarray Alizadeh et al. J Pathol 2001;195:41-52

Microarray Future: Conclusions: 

Microarray 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)