BETWEEN CF HUMAN AIRWAYAND NORMAL CELLS

Institute for Research in Immunology and Cancer,

Department of Computer Science and Operation Research, Research Center, CHUM, Université de

Montréal,

Montréal, QC, Canada.

Massé, André Dagenais, Sébastien Lemieux

DIFFERENTIAL EXPRESSION

Breathe Project

Grégory Voisin, Chantal

EPITHELIAL CELL LINES

and Yves Berthiaume

Previous microarray studies in CF have been conducted in :Primary cells (ΔF508/ ΔF508): Zabner, Wright.Transgenic mouse model (CFTR(-/-)): Xu,

Radzioch.Human Airway Epithelial (HAE) cell lines

(ΔF508/W1282X): Virella-Lowell.

• Although all of these models are heterogeneous, these studies come to the same global conclusion : There is a modulation of inflammatory actors in CF cells. So far, no relation has been shown between possible metabolic pathways and modulated genes.

1-Introduction

2-Hypothesis

CFTR deficiency in HAE cells triggers specific pathways involved in the inflammatory response.

Goal of the present microarray study:

Carry out a differential expression analysis on a CF (ΔF508/ ΔF508) and a non-CF human airway epithelial cell lines.Determine the biological processes modulated in CF.Determine the metabolic pathways modulated in CF.

3-Specific Objectives

2 cell lines•immortalized byDr. Joseph Zabner.•The study was carried out on cell lines to reduce biological variability and allows a higher confidence in microarray analysisand interpretation.

Nuli cells:Normal Lung, University of Iowa Derived from HAE of normal genotype.

Cufi cells:

Cystic Fibrosis, University of Iowaderived from HAE of CF genotype (homozygote ∆F508)

RNA extraction

hybridation

EXPERIMENT DESIGN

3 biological replicates2 experimental conditions: Cufi and Nuli

GeneChip® Affymetrix

Pangenomic Chips HGU133.plus.2.054,000 probesets47,000 transcrits ( 38,500 well-known genes)

4-Methology

Scanning by bioanalyzer

Data acquisition

Normalizationby RMA express

Statistical analysiswith Bioconductor (AffyLM package)

Bioconductor version 1.8Statistical analysis based on a linear model.Differential Expressed Genes (DEGs) orderedby Bayesian statistic,which represents theprobability of expressionin the context of ourexperiment.

CEL files

Pathway Analysis:Determine the overexpressed

Signaling Pathway in an interest group of DEGs

List of DEGs

Global observation:Number of DEGs UP and DOWN

Confidence levelAdjusted Pvalues

Ontological Analysis:Determine the overexpressed

Gene Ontology (GO) in an interest group of DEGs

Pathway-express

Onto-express

Selection ofinteresting DEGs

Confirmation of expression by qPCRValidation of over/under expression

obtained by microarray analysis

Confirmation of protein expression

Pathway inhibition

Confirmation of pathway activation

In progress...

5-Results2335 PROBESETS

differentially expressed

1659 annotated differentially

expressed GENES

788 DEGs UP-regulated

871 DEGs DOWN-regulated 202 genes NA

+

474 duplicate gene annotations

+

Range values:0.01<Adjusted Pvalues<10℮-130.5<Expression probability<10.006<Expression Ratio <19

Results: Gene ontology and Pathway analysis.

Gene Ontology:UP-regulation of inflammatory response, immune response, celladhesion, chemotaxis: IL6, IL8, SPINK5, CXCL10,CXCL11,2,3,5,6, IFIT1,3,IL1R2,TNFAIP6,S100A12, MCAM, SRPX,AREG, CD36..

UP-regulation of transport: SLC6A14, CLCA2,4, CYP24A1,KCNE3,VIM

Modulation of protein biosynthesis:EIF1AY, RPS23

lipid metabolism: ACOX1, ACOX2

Down-regulation of the transport electron: ALOX5,15B, CLCN4,KCNK5

Pathway analysis:Activation of Toll-Like Receptor pathway

Res

ults

: Mod

ulat

ed g

enes

in th

e T

oll-l

ike

Sig

nalin

g P

athw

ay

Res

ults

: mic

roar

ray

mod

ulat

ed g

enes

in T

oll-l

ike

Sig

nalin

g P

athw

ay.

0

1

2

3

4

5

6

7

Nuli Cufi Nuli Cufi Nuli Cufi Nuli Cufi Nuli Cufi

IL8 IL1B IL6 CXCL10 (IP-10) CXCL11(ITAC)

RATIO qPCR 3,6

EXPRES.PROBAB.MICROARRAY

0,002RATIO

MICROARRAY

P-value qPCR

4

>95 %

4,7

0,0004

2

>95 %

5,4

0,01

17

>95 %

5,5

0,028

9

>95 %

4,9

0,02

18

>50%

Results: Confirmation by qPCR of gene expression .

STAT1Pvalue = 0.006, ratio= 2.1

0,0

0,5

1,0

1,5

2,0

2,5

3,0

Nuli-CTL Cufi-CTL

CLCA4pvalue = 0.0001 , ratio = 4,7

00,5

11,5

22,5

33,5

44,5

5

Nuli-CTL Cufi-CTL

CLCA4:The protein encoded by this genebelongs to the calcium sensitive chloride conductance protein family.The exact function of this protein isnot known.

STAT1:This protein can be activated by various ligands including interferon-alpha, interferon-gamma, EGF, PDGF and IL6. This protein mediates the expressionof a variety of genes, which is thought to be important for cell viability in response to different cell stimuli and pathogens.

Results: Other interesting genes modulated in Cufi confirmed by qPCR.

Conclusion• In the absence of pathogen agents, we

observe an up-regulation of several inflammatory actors in Cufi cells.

• CFTR deficiency could be responsible for an excessive immune and inflammatory response.

• The highest regulated genes are implicated in the TLR signaling pathway, therefore there could be a dysregulation of this pathway in CF cells.