PD Dr. rer. nat. Holger Sültmann dpt. of Molecular Genome Analysis head: Prof. Dr. Annemarie Poustka DKFZ Heidelberg cDNA microarrays for gene expression studies in complex disease
PD Dr. rer. nat. Holger Sültmann
dpt. of Molecular Genome Analysishead: Prof. Dr. Annemarie PoustkaDKFZ Heidelberg
cDNA microarrays for gene expression studies in complex disease
Hanahan and WeinbergCell 100, 57-70 (2000)
genome projects: change of paradigms
hypothesis-driven research
high throughput
gene-driven research
cDNA expression profiling - goals
! target genes for new therapeutic approaches! identification of pathways associated with
disease development and progression! classification of disease (sub)types! disease diagnosis, prognosis,
and treatment response
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Promotor
DNA(gene)
Exon 1 Exon 2 Exon n
hn-mRNA
poly A tailprotein coding region
translation
AAAAAAAAAmRNA
protein
nucleus
cytoplasm
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5` 3`
PCR for cDNA clone amplification(A)n
cDNA clone
(A)n
vector PCR
DNA array
genespecific PCR
DNA array 31500 clones
QC: M13-primed PCR amplification
doublebands no product
low product amount
spotting robot forcDNA nylon filters
tumor/normal-tissue
33P-labelledcDNA
AAAAAATTTT
RNA
signal intensities(31500-cDNA-clone filter)
cDNA expression profilingusing 31500-clone nylon filters
DNA-DNA-hybridization
data analysisratio of RNA abundance in normal/tumor samples
T98-08850
N98-08850
kidney cancer (renal cell carcinoma, RCC)! types:• clear cell (75%)• chromophilic (10%)• chromophobe (5%)• oncocytoma (5%)• duct-Bellini (1%)
! epidemiology: • 95000 deaths p.a. worldwide• risk increased by 43% since 1973 (USA)• males have 2-3x higher risk than females• risk is associated with genetic (VHL gene),
metabolic (obesity, blood pressure), environmental (cadmium) factors, and age
! genetic markers:• 3p deletion or translocation (clear cell and chromophilic)• VHL, VEGF, EGFR, TGFA, VIM, GAPDH, LDHA
! medical treatment:• surgery, immunotherapy
clear cell carcinoma
! ratio 3.5, percentile threshold 30%
! sign (-1/0/1) statisticDKFZ HeidelbergMolecular Genome AnalysisDr. Holger Sültmann
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data analysis
gene expression changes in kidney cancer
X
X
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up: 1025 genes/ESTs; down: 717 genes/ESTs (37 samples)
Boer et al., Genome Research 11(11), 1861-1870, 2001
mathematics/informatics: data visualization (ββββ2m)
frequency
log ratio
37 patients
glucose 6-phosphatase
ATPADPphosphofructokinase
fructose 1,6-bisphosphatase
aldolase
Pi
ATPADP
Pi
triosephosphate isomerase
Glycolysisupregulated
Gluconeogenesisdownregulatedphosphoglycerate kinase
enolase
ADP
ATP
pyruvate kinase PEP carboxykinase
ATP
GDP
GTP
NAD+ +PiNADH + H+GAP-DH
ADP
ATPADP
Pi
pyruvate carboxylase
PEP
pyruvate
glucose
Glc-6-P
oxalo acetate
2-P-glycerate
DHAP
Frc-6-P
Frc-6-Bis-P
GA-3-P
Bis-P-glycerate
3-P-glycerate
pathway identification
comprehensive31500 (70000) elements
indication-specific3000-8000 elements
cDNA arrays at MGA (DKFZ)
kidney cancerbreast cancerbrain cancerGIS tumors
tumor tissue
RNA
normal tissue
cDNA-Chip
higher in tumor
lower in tumor
balanced expression
RNA
cDNA
cDNA
cDNA expression profiling on glass arrays
Omnigrid (Genemachines) Arrayer
slide spottingexperiences
robot stopped during spotting
some pins temporarilynon-functional
384-well spotting plate deformed
04/05/2001
27/04/2001
11/05/2001
slide surfaces before spotting
AS3 (300301) Lys5 (300301)
spotting pin quality decline
after delivery of 5x105 spots
after delivery of 3x105 spots
cDNA array experiments and analysis
PCR products: PCR product control on agarose gels purification (precipitation, chromatography)
slide spotting: spotting solutions (3xSSC, +/- betaine, commercial ...)slide surfaces (non-treated, AS, poly-L-Lys, AL, ...)pre- and post-spotting slide treatment
RNA QC: agarose gel electrophoresis, Agilent RNA chipsRNA labelling: amount of RNA required (10 µg/slide/channel)
amount of fluorescent dye requiredreaction conditions (enzyme, temperature, duration ...)
hybridization: commercial, DIG-easy with Cot/Denhardt`sunder coverslides, hyb-machinein closed humidified hyb-chambers submerged in water
post-hyb-treatment of slides: SSC/SDS, water, ethanol-dilutions, dryingimage analysis: Arrayvision, self-defined grids data: handling and storagedata analysis: QC, normalization, statistical evaluation
+ 5q
5q
prognosis of RCCC correlates with chr. 5q amplification(cytogenetic data; Gunawan et al., Cancer Research, in press)
50 marker genes/ESTs correlating with 5q amplif."""" molecular classification of clear cell renal cancer[gene expression data; 21 (10 vs. 11) patients]
diagnosis/prognosis
highest expressed genes
595652
EC vs. A DocER (+) vs. ER (-)PR (+) vs. PR (-)
2074pre vs. post chemotherapy
65response vs. no response276pre vs. post chemotherapy
differentially expressed genes(p-value < 0.001)
breast cancer samples on 31500 clones:neoadjuvant chemotherapy:- inn--vivo sensibility testvivo sensibility test-- visualization of therapy success visualization of therapy success -- better conditions for surgerybetter conditions for surgery-- early therapy for early therapy for micrometastasesmicrometastases
(12 patients)
biopsy
indication-specific arrays at DKFZ/MGA! kidney cancer: 2200 differentially expressed genes/ESTs
+ 1800 oncologically relevant genes ! brain cancer: 2950 highly expressed genes/ESTs
+ 520 differentially expressed genes/ESTs+ 580 genes from literature searches+ 1150 oncologically relevant genes
! breast cancer: 3300 highly expressed genes/ESTs+ 1900 genes from literature searches+ 550 differentially expressed genes/ESTs+ 1150 oncologically relevant genes
! GIS tumors: 1200 highly expressed genes/ESTs+ 600 differentially expressed genes/ESTs+ 1150 oncologically relevant genes
immunohistochemistry
CMN TIII
N TIII
N TI
N TI
N TIII
Northern blot hybridization
quantitive PCR
additional experimental evidence
the challenge: complex systems
Annemarie PoustkaHolger SültmannWolfgang HuberMarkus VogtFrank BergmannPatrick HerdeKlaus SteinerJörg SchneiderFlorian HallerKatharina FinisStephanie SüßYvonne KeßlerKai DobersteinAnne Dörsam
Judith BoerFriederike Wilmer
Martin VingronAnja von HeydebreckMPI for molecular genetics, Berlin
Günter SawitzkiStatlab, university ofHeidelberg
Laszlo FüzesiBastian Gunawandpt. of pathology, university of Göttingen
Molecular Genome AnalysisCollaborations
Bernhard KornMatthias SchickRZPD Heidelberg
Stefan WiemannUte ErnstSara Burmester
Daniel Göttel
http://www.dkfz.de/abt0840/