DNA arrays for early disease detection

DNA arrays for early disease DNA arrays for early disease detectiondetectionChem 395Chem 395

Bioanalytical chemistryBioanalytical chemistry

InstructorInstructorProf.James F.RuslingProf.James F.Rusling

Presented byPresented byVigneshwaran ManiVigneshwaran Mani

OutlineOutline

What is a Microarray?What is a Microarray? Types of MicroarrayTypes of Microarray Steps involved in Microarray Steps involved in Microarray

fabricationfabrication What happens to the Genes in What happens to the Genes in

disease state?disease state? Application of MicroarrayApplication of Microarray SummarySummary

Why Microarrays?????Why Microarrays?????

Small volume- miniaturizationSmall volume- miniaturization High throughput analysisHigh throughput analysis Large information generatedLarge information generated Less time required to analyzeLess time required to analyze

What is a Microarray?What is a Microarray?

A microarray is a A microarray is a spatially orderedspatially ordered, , minituarizedminituarized arrangement of arrangement of multitude of multitude of immobilizedimmobilized reagents reagents

Types of MicroarraysTypes of Microarrays

cDNA and Oligonucleotide cDNA and Oligonucleotide MicroarraysMicroarrays

Probe: Probe: ssDNA,OligonucleotidessDNA,Oligonucleotide

Target: ssDNA,ssRNATarget: ssDNA,ssRNA Principle: HybridizationPrinciple: Hybridization

Protein MicroarraysProtein Microarrays Probe: AntibodyProbe: Antibody Target: AntigenTarget: Antigen Principle: peptide chemistryPrinciple: peptide chemistry

OthersOthers Tissue arraysTissue arrays

Gene expressionGene expression

RNA POLYMERASE

RIBOSOMES

Nucleus

Cytoplasm

cDNA ARRAYScDNA ARRAYS

Marketed By: Agilent technologies

Steps Involved in MicroarraysSteps Involved in Microarrays

Microarray Microarray printingprinting

HybridizationHybridization

DetectionDetection

DNA-Microarray printingDNA-Microarray printing

100-10000 spots100-10000 spots Glass slide used as Glass slide used as

substratesubstrate DNA is attached covalently DNA is attached covalently

to glass slideto glass slide 96-384 well microtitre 96-384 well microtitre

plates usedplates used Spot Volume 0.25-1nl.Spot Volume 0.25-1nl. Spot size 100-150Spot size 100-150µm in µm in

diameterdiameter

• 1,2,3-X,Y,Z 1,2,3-X,Y,Z directiondirection

• 4-print head4-print head• 5-glass slide5-glass slide• 6-Microtitre 6-Microtitre

plateplate• 7-Distilled 7-Distilled

waterwater• 8- Drying8- Drying

A C U G

T G AC

A C U G

T G AC

mRNA Control mRNA Diseased

Reverse transcriptase Reverse transcriptase

Fluorescent labeling Fluorescent labeling

Cy3 Cy5

cDNA

T G AC T G A

C

Hybridize target to microarray

HybridizationHybridization

HybridizationHybridization

Detection:Detection:

The slide is scanned The slide is scanned twicetwice-Once to measure -Once to measure red red intensityintensity-Once to measure -Once to measure green green intensityintensity The images are The images are overlayed to produce overlayed to produce one imageone image

ScanningScanning

M = logM = logRR//GG = log = logRR – log – logGG

M<0M<0: gene is over-: gene is over-expressed in green-labeled expressed in green-labeled sample compared to red-sample compared to red-labeled sample.labeled sample.

M=0M=0: gene is equally : gene is equally expressed in both expressed in both samples.samples.

M>0M>0: gene is over-: gene is over-expressed in red-labeled expressed in red-labeled sample compared to sample compared to green-labeled sample.green-labeled sample.

What happens to Genes in What happens to Genes in (Cancer) Disease State(Cancer) Disease State

Certain genes undergo Certain genes undergo overexpression.overexpression.

No. of copies of particular genes may No. of copies of particular genes may increase.increase.

Gene mutation.Gene mutation.

Gene is overexpressed in a certain Gene is overexpressed in a certain disease state,disease state, More cDNA(target) will hybridizes to probe, as More cDNA(target) will hybridizes to probe, as

compared to control cDNA, compared to control cDNA,

In turn, the spot will fluorescence red with In turn, the spot will fluorescence red with greater intensity than it will be with green. greater intensity than it will be with green.

Expression patterns of various genes is Expression patterns of various genes is characterized involved in many diseases,characterized involved in many diseases,

Compare expression pattern of the gene from the Compare expression pattern of the gene from the

individual with the expression pattern of a known individual with the expression pattern of a known disease.disease.

Changes in gene expression levelsChanges in gene expression levels

Number of copies of a particular target gene has Number of copies of a particular target gene has

increased.increased.

Large amount of (Disease) sample DNA will hybridize to Large amount of (Disease) sample DNA will hybridize to those spots on the microarray compared to (normal) those spots on the microarray compared to (normal) control DNA hybridizing to those same spots. control DNA hybridizing to those same spots.

Those spots containing the sample DNA will fluoresce Those spots containing the sample DNA will fluoresce red with greater intensity than they will fluoresce green, red with greater intensity than they will fluoresce green, indicating that the number of copies of the gene indicating that the number of copies of the gene involved in the disease has gone up.  involved in the disease has gone up. 

Genomic gains and lossesGenomic gains and losses

Gene Expression profile analysis in Gene Expression profile analysis in Human hepatocellular carcinoma by Human hepatocellular carcinoma by

cDNA microarraycDNA microarray

Eun Jung Chung,Young Kwan Eun Jung Chung,Young Kwan Sung,MohammadFarooq,Younghee Kim, Sanguk Sung,MohammadFarooq,Younghee Kim, Sanguk Im,Won Young Tak,Yoon Jin Hwang, Yang Il Kim, Im,Won Young Tak,Yoon Jin Hwang, Yang Il Kim, Hyung Soo Han, Jung-Chul Kim, and Moon Kyu Hyung Soo Han, Jung-Chul Kim, and Moon Kyu Kim.,Mol.Cells,Vol.14,pp382-387,2002Kim.,Mol.Cells,Vol.14,pp382-387,2002

HCC (Hepatocellular carcinoma)HCC (Hepatocellular carcinoma)

Primary liver cancer (HCC)Primary liver cancer (HCC) Somatic mutations and activation of certain Somatic mutations and activation of certain

oncogenes.oncogenes. These events Lead to expression changes in These events Lead to expression changes in

genes.genes. cDNA arrays are used to analyze expression cDNA arrays are used to analyze expression

patternspatterns

cDNA arrayscDNA arrays

3063 human cDNA8 different samples of HCC

Computer analysis

Gene expression patterns of 8 hepatocellular Gene expression patterns of 8 hepatocellular carcinomas.carcinomas.The genes were primarily classified into three The genes were primarily classified into three groups, based on their clustering pattern.groups, based on their clustering pattern.

Up-regulated genes in HCCUp-regulated genes in HCC Galectin-3Galectin-3 Serine/threonine kinase Serine/threonine kinase Fibroblast growth factor Fibroblast growth factor

receptorreceptor Ribosomal protein L35ARibosomal protein L35A

Down-regulated genes in Down-regulated genes in HCCHCC

mRNAs of Nip3mRNAs of Nip3 DecorinDecorin Insulin-like growth factor Insulin-like growth factor

binding protein-3binding protein-3

Application of MicroarraysApplication of Microarrays

ApplicationApplication

cDNA array.cDNA array. Tumor classification, risk Tumor classification, risk assessment, and prognosis assessment, and prognosis

prediction.prediction.

Expression Expression analysis.analysis.

Drug development, drug response, Drug development, drug response, and therapy developmentand therapy development

SummarySummary

Data can be generated in a high throughput, Data can be generated in a high throughput, parallel fashion.parallel fashion.

Less time required for analysis.Less time required for analysis. If gene expression data is already known for If gene expression data is already known for

a certain disease. Then we can compare the a certain disease. Then we can compare the gene expression data of the individual with gene expression data of the individual with the known, and predict the diseasethe known, and predict the disease

ReferencesReferences

David J. Duggan, Michael Bittner, Yidong Chen, Paul Meltzer & Jeffrey M. Trent, Nature genetics supplement, volume 21, january 1999.

Sunil R. Lakhani, Michael J.O’hare & Alan ashworth, Nature medicine,volume 7,number 4,april 2001.

Vivian G. Cheung, Michael Morley, Francisco Aguilar, Aldo Massimi,Raju Kucherlapati & Geoffrey Childs, Nature genetics supplement,volume 21,january 1999.

http://www.ncbi.nlm.nih.gov/

AcknowledgementAcknowledgement

Prof. James F. RuslingProf. James F. Rusling Chem 395 studentsChem 395 students