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

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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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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