dna microarray /expressionkaim.or.kr/pds/files/hmo/hmo_200601.pdfdna microarray-total rna target...
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DNA Microarray /Expression
안성환
(주)지노믹트리
Genomictree GeneTrack Human DNA microarray
DNA Microarray
Intron
Exon: 4만gene- PCR product- Oligo DNA
. Methylation assay
AAAA
RNAProtein
CGCGAT
GCGCTACGCGATCG
GCGCTAAC
CH3 SNP증폭
결실 C
DNAChromosome
LOH
자극전달
반응
MSI
expression
Methylation
Genetic and Epigenetic alteration through second hitaffects on gene expression
miRNA
환경
유전자1
유전자2
유전자3
Central Dogma ?Central Dogma ?
DNAmRNA Protein
근육세포 피부세포 신경세포
유전자1
유전자2
유전자3
Normal Cell Cancer Cell어떻게 차이를구분할 것인가?
정상세포와 암세포 : 유전자 활동차이
RNA identification and differential detectionin molecular level
Northern blotPrimer extensionRNase ProtectionRT-PCRDD-PCR
Real time –PCR
Microarray
Profile of Differential Expression
Single gene
To
Genomic level
P32* Probe (gene)
Target(total RNA)
C T C T
C T
Test
Control
2
6
Probe (gene)
Cy3 Cy5
Target(total RNA)
C T
Test
Control
6
23X
6
23X
Northern Blot Array-based Blot
2 6
N
N
N
N
N
N
Individual AmplificationRT-PCR
Individual detectionGel-based assay Microarray-based Assay
Hybridization
RNA
From low to High throughput AssayMultiplex amplificationRT or PCR
Gelelectrophoresis
Human 35KRow 27 x Column 27 x 48 blocks = 34,992genesPrinting Area : 54 mm x 18 mm
Hybridization image 2.5 cm
7.5 cm
Printing area: 5.4 X 1.8 cm
Genomictree
Each gene in each well of plate
Robotic machine
Pin head
Open slotPin : capillary
DNA microarray
-Total RNA
Target labeled
Reference(N) Test(T)
Cy5-dUTPCy3-dUTP
Scan
microarray experiment
=Hybridization
Level ⇒ Cy5
Cy3
NormalTissue
cancerTissue
Competitive hybridization
Equal mix
Reverse transcription
DATA MINING
control Test
Probe
Up regulated gene Down regulated geneNo change
Competitive hybridization
Ratio of intensity
Noncompetitive hybridization
Control RNA Test RNA
1. Scanning 30분전에 scanner를 power-on하여 pre-warming.
2. GT-microarray hybridization method에 의해 실험이 수행된 microarray를GenePix 4000(Axon) scanner로 가지고 온다.
4. Scanner의 덮개를 좌측으로 미끄러지듯이 열고, microarray를 넣는다.
5. Cassette 좌측의 lever를 움직여, microarray를 고정시킨다.
6. Scanner 덮개를 닫으면, scan할 준비가 된다.
9. “Prescan ” icon을 click한다.
- 전체 microarray의 대략적인 실험 결과, scan하기 위한 spot 위치등의 파악.
10. Spot의 위치가 파악되면, “stop ” icon을 click하여, prescan을 멈춘다.
② Prescan으로 spot의위치가 파악된다.
③ “Stop” icon을 clickPrescan
진행 방향
① “Prescan” 시작
18. Gridding file을 선택하면 각 spot(feature)에 맞게 제작된 grid box가 나온다. Mouse와 keyboard를 사용하여, 모든 grid box를 각 spot(feature)에 알맞게 위치시킨다. (자동으로 alignment하므로, 정확하게 맞출 필요는 없다.)
크게 확대하여 작업하면 더욱 정확하게위치 시킬 수 있다.
20. Alignment가 완료된 후, “Analyze ” icon을 click.
→ 모든 data가 excel의 형식으로 나타난다.
① “Analyze” icon을click.
② Data가 analysis 되는진행상황이 보인다.
Alignment가 된 feature Data로 쓸 수 없어 flag-out된 feature
21. Data analysis가 끝난 후, excel과 scatterplot 형식으로 output되는 data.
Result panel Scatter-plot panel
2X up-regulated genes
2X down-regulated genes
22. “Results” panel에서, Sum of Median 값이 <1000인 feature를 제거(flag-
out)하여, false-positive를 최대한 감소시킨다.
① “sum of median”을click하면, 자동으로sorting이 된다.
② mouse와 shift+mouse를 사용하여 flag-out할 범위를 지정한다.
③ 범위가 지정된 후,mouse 오른쪽 click하여, “Flag-bad”를선택하면, 지정된범위는 삭제된다.
Flag-out된 feature는Scatter-plot에서 사라진다.
Profiling Patterns of Gene expression to HCV core protein in Hepatocytes
Unsuitable spots flaggedand excluded
Gridding
GeneClustering
net signal
Average pixel intensity of each spotminus local background intensity equals net signal of each spot
Up-regulated genes
Down-regulated genes
Test : core expression ( Tet-minus ) Cy5
Reference : no core expression (Tet plus) Cy3vs
3h6h
48hrs
465 gene > 2 fold on at least one array > 80% good spot > 50 Ch1 and Ch2 net norm
Clustering 465 genes selected
Down- Up-
Insufficient
TreeView
200 10000 50.00 5.644800 4800 1.00 0.009000 300 0.03 -4.91
Cy3 Cy5Cy5Cy3
Cy5Cy3log2
Gen
es
Experiments
DNA microarray 분석 system
Up
Down
Clustering
Data Submit
Data Extract
Graphical displayGT DB
Experimentsn-1
Tree View
Down-regulated
Up-regulated
normal cancer
oncogene
Tumor surppressor
Target discovery and development via expression profiling
Low grade lesions
high grade lesions
Normaltissue
CancerHSIL CIS SCCASCUS LSIL
SIL : Squamous intraepithelial lesionCIS : Carcinoma in situSCC : Squamous cell carcinoma
Low SIL High SIL
Development of Cervical Cancer
Phenotype--- host molecular classification
HPV genotype
Expression Kinetics during disease progression
Low grade: Group A
High grade: Group B
Diff
eren
t ial ly
exp
res s
ed g
e nes
Normal LSIL HSIL CIS Cancer
Selection for genes gradually down-regulated in cancer formation
Expression profile of cervical biopsy sample
(ANOVA, p < 0.01)
Gene expression signature as PredictorOf Survival in Breast Cancer
-Inkjet-synthesized oligonucleotide microarrays, 25000 oligos-70-gene prognosis profile,98 patients-295 consecutive breast cancer patients-Gene-expression profile is a more powerful predictor of-Disease outcome in young breast cancer patients thanStandard systems
Van de Vijver MJ, et al. NEJM2002. Van’t Veer LJ, et al. Nature 2002
MammaPrint R Test Technologyprovides the means for selecting patients who would benefit from adjuvant therapy and those who can be spared the serious impact of these treatments
-Regulating cell cycle-Invasion-Metastasis-angiogenesis
Primary breast tumorSupervised classification70gene selectedStrongly predict poor prognosis
Agendia,Inc
Personalized approach and classification to Cancer through Genomics and Epigenomics
Phenotype
Genotype
Early detection and right classification
New generation of in-vitroDiagnosis and prognosis-> better treatment
Diagnostics move towards earlier detection and differential diagnostics for unmet medical needs
utilizing Nucleic Acid-based Molecular markerstumormass(cell)
108
104
GeneticPredisposition
tests
dysplasia Early cancer
Cancer screening test
Tumor diagnostics
Timeline of carcinogenesisCancer in-situ Clinically overt cancer Relapse/metastasis
Early detection( non or less invasive))
Theranostics(differential)
MonitoringTherapyrecurrences
DNA-based DNA or RNA- based
Tumor
Control vs
Tumor
SNPs
CGH, cDNA
Oligonucleotide
Antibody chip
Analysis
TumorclassificationIdentification ofclusters orIndividual markergenes
Clinicalvalidation with
tissuemicroarrays
General scheme of the procedure used in tumor expression profiling for target identification and validation
Microarrayhybridization
Methylation
Genetic
Epigenetic
We need clinical research collaboration
Novel markersClinical assessment of
predictive valuediscovery
Standard of care
Pilot studies &Assay development
Phase I
Retrospective clinicalanalysis
Phase II
Prospective confirmatoryanalysis
Phase III
Phase IVMulti-institutionalValidation trials
SNPs
CGH, cDNA
Oligonucleotide
Antibody
Methylation
Eearly detectionprognosis
Thank you