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Patterns in expression profiles point to mode of action
in drug discovery
© 2001,Pharmacia, Inc. - All Rights Reserved.
Antifungal therapy:
Opportunistic systemic infections: candidiasis and aspergillosis
Candida albicans is 4th most-frequently infectious hospital isolateNosocomial fungal infections affect > 2 million patient / year
Available therapies: Polyenes (Amphotericin B): effective but with side effects Azoles (Fluconazole, Itraconazole): safe but less effective Candins (Cancidas): just approved
Model organism: Saccharomyces cerevisiae, aka baker’s yeast
Characterization of novel agents
Have we seen this type of agent before?
What biological processes does it impact?
Are improvements making it better or different?
How can we measure activity?
Drug discovery objectives:
Transcript profiles with Affymetrix microarrays
Microarray profiles within an experimental class
Relationships between experiments
Identification of functional patterns
Relationships among responsive genes
Topics:
Transcript profiles:
Transcript profile = snapshot of all mRNA species in sample
Yeast: Profile =>unstressed, normal growth
Profile => response to agent? target pathway? “secondary” response? surrogate expression marker
Stress:
Affymetrix Gene Chip Hybridization:
Result: intensity value for each mRNA represented on chip
Measures of [mRNA] agree:
log(Chip Intensity)
2
3
4
5
6
7
8
9
2 2.5 3 3.5 4
ketoconazole
itraconazole
clotrimazolePNU-144248E
amorolfine
fluconazole
voriconazole
terbinafine
untreated
ketoconazole
itraconazole
clotrimazole
PNU-144248Eamorolfine
fluconazole
voriconazoleterbinafine
untreated
PCR
cyc
le n
umbe
r
GeneChip ~ [mRNA] log (Chip Intensity)
Taqman ~ 1 / [mRNA] (PCR cycle number)
Experimental design:
Agents X Exposure = Treatment1357
Aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
1111111111111111111111111111111111111111111111111111111111111111111111111111111111111
111111111111111111111111111111111111111111111111111111111111111111111111111
1111111111111111111111111111111111111111111111111111111111111111111111
11111111111111111111111111111111111111111111111111111111111111111
1 2 3 4
gene
s
Treatments Treatment profiles:
Measure of similarity between biological response to different treatments
Treatment profiles reveal similarity in response:
Signal from chip
Identify common biological response:
Distinguish a compound with distinct effect:
Correlation:
Pairwise Pearsoncorrelation coefficientbetween each pair oftreatments
Correlations between experiments:
Biological effects, proof of concept:
8 chemical agents:
ergosterol
ERG9ERG1ERG7ERG11ERG24ERG25ERG26ERG6ERG2ERG3ERG5ERG24
allylamine
morpholine5 azoles
Novel imidizole PNU-144248E
3 genetic changes:
ERG6ERG2
ERG5Define method to identify responsive transcripts
farnesyl pyrophosphate
Expressed above background
Significantly changed from untreated
Changed in multiple related treatments
Responsive genes:
XXXXXX
Responsive genes in blue
112 transcripts related to ergosterol 59 genes of unknown function 52 “other” changed transcripts
AcylCoA-> -> ERG19 -> farnesyl pyrophosphate ERG9 ERG1 ERG7 ERG11, NCP1 ERG24 ERG25/ERG26 ERG6 ERG2 ERG3 ERG5 ERG4
ergosterol
Response to ergosterol perturbation:
5
20 stress-response
36 mito
16 membrane -assoc.
5 vesicular transport
13 heme-responsive
29 lipid, fatty-acid29 lipid, fatty-acidsterol associatedsterol associated
ergosterol ergosterol plasma membraneplasma membrane inner mito membraneinner mito membrane
Erg11p contains hemeErg11p contains heme
12 hypoxic
5 cell wall
Facets of response:
Signal transduction
MajorFacilitatorSuperfamily
TransportersProtein processing
Translation
Lipid, sterol andfatty acid, biosynthesis
Cell wallbiosynthesis
Stress responses
Amino acid metabolism
Carbohydrate metabolism
Mitochondrial: metabolismenergy productiontranslation
Nucleoside, etc. metabolism
RNA synthesisand processing
Structure
DNA synthesis /repair / recombination
Global patterns of responsive genes:
Each row is histogram of responsive genes in given treatment
Second dimension -- gene profiles:
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1111111111111111111111111111111111111111111111111111111111111111111111111111111111111
111111111111111111111111111111111111111111111111111111111111111111111111111
1111111111111111111111111111111111111111111111111111111111111111111111
11111111111111111111111111111111111111111111111111111111111111111
1 2 3 4
gene
s
treatments
=> biologicalsimilarity
=> gene families co-regulated in response to treatment
Gene profiles:
Treatment profiles:
Treatment profiles / gene profiles
profiles
Heat Map
A1 D1 B1 C1 B3 A3 D3 C3 A5 B5 A7 B7 D7 C5 C7
Treatment profiles / gene profiles
Treatments
Gen
es
Heat Map
Rows 1 Rows 12 Rows 23 Rows 34 Rows 45 Rows 56 Rows 67 Rows 78 Rows 89 Rows 100 Rows 111 Rows 122
Gene correlations
Pairwise Pearson correlation coefficients forgene profiles
Conclusions:
Expression profiles:
identify responsive genesfind significant pathway(s) in responsefind unanticipated responsive pathwaysidentify surrogate expression markers
identify agents eliciting similar responses
distinguish biological response to apparently similar agents
Acknowledgements:
Pharmacia:Gary Bammert, ID GenomicsChad Storer, ID GenomicsMark Johnson, Computer-Aided Drug DiscoveryTom Vidmar, Biostatistics
Affymetrix: Mike Lelivelt
Proteome: Everyone supporting YPD
Spotfire: Bill Ladd Shawn Kenner