the transcriptome of corresponding cumulus and granulosa cells

The transcriptome of corresponding cumulus and granulosa cellsDo differences in genetic markers of cumulus andgranulosa cells reflect the implantation potentialof the oocyte?

Marie Louise Grøndahl, DVM, PhD

Laboratory of Reproductive Biology and Fertility Clinic, University Hospital of Copenhagen, Rigshospitalet, Copenhagen, Denmark.

e-mail: [email protected]

1. Gene expression profile and gene function analysis in cumulus and granulosa cells from individual human follicle just prior to ovulation

Overall data; LH receptor

2. Genes in cumulus and granulosa cells which expressions have been suggested to reflect the quality of the oocyte. Methodological considerations

Cumulus cells, CC

30-40 pre-granulosa cells

Mural granulosa cells, MGC

FolliculogenesisFrom pre-granulosa to cumulus and granulosa cells

Review: Zuccotti et al., 2011

Activators

•LIF

•GDF9

•Kit ligand

•BMP4/7/15

•

Suppressors

•AMH

•P27

•FOXO3a

•PTEN

•

•TGF-b

•BMP15

•GDF9

•Activins

•

•

~ 50,000,000

~ 500-1000

Gene expression profile - TranscriptomeA snapshot of the activity in the cells

A: Picopure RNA Isolation kit

B: Double amplification protocol for small RNAsamples. Affymetrix

C: HG-U133plus2 GeneChip array. Affymetrix

D: Scanning, data handling software, analysis

E: Confirmation af array dataRT-PCR. TaqMan® Probes

Microarray analysis

Gene expression profile and gene function analysis of cumulus and granulosa cells from individual human follicle just prior to ovulation

Overall data, LH receptor

1

•12 women aged 27-39 years in IVF / ICSI treatment

•Controlled ovarian hyperstimulation

•Short antagonist protocol

•rFSH and hCG (10.000 IU)

Corresponding cumulus and granulosa cells

from 12 large (mean: 3.5 ml) pre-ovulatory follicles

containing a MII oocyte

•RT-PCR confirmation in additional 6 independent women

Materials and Methods

Flash frozen -196 °C Storage -80 °C

RNAse inhibitor RNAse inhibitor

within 30 minutes after OPU

Materials and MethodsIsolation of granulosa and cumulus cells

Flash frozen -196 °C Storage -80 °C

•CD45 (leucocyte marker)

negative

•CYP17 (theca cell marker)

negative

Average 50 ng and 90 ng of total RNA extracted from the cumulus and mural granulosa cells, respectively

Grøndahl et al., 2009, 2010, 2011

DCHIP

Homogeneous cell populations

Cumulus cells

11,100 unique genes present

(in at least 10 of 12 samples)

Granulosa cells

11,739 unique genes present

(in at least 10 of 12 samples)

85 61

The transcriptome of MGC and CC-genes expressed just prior to ovulation

Selectively expressed in MGC-expressed in at least 10 out of 12 in MGC-expressed in 0 of CC

Selectively expressed in CC-expressed in at least 10 out of 12 in CC-expressed in 0 of MGC

Paired t-test with Benjamini Hochberg multiple testing corrections with p-value below 0.01, fold-change larger than 2 and difference of means larger than 50

1542 unique genes were differentially expressed by more than 2 fold

489 genes differentially expressed227 overlap with present dataSamples represent cohort of folliclesCC isolated in connection to ICSICC up-to 4 hours in vitroMGC cells isolated by centrifugationMGC CYP17 (theca cell) positiveKôks et al. 2009

Differentially expressed genes in CC and MCG

CC MGC

1542 differentially expressed genes

Lower (2-8) fold changed1377 genes

High (>8) fold changed165 genes

Gene function enrichment analysis ofthe differentially expressed genes

Number of genes

Gene function enrichment of differentially expressedlower (2-8) fold changed genes (p<0.001)

Number of genes

Gene function enrichment of differentially expressed high (>8) fold changed genes (p<0.001)

85 61

0 5 10 15 20

cell communication

signal transduction

multicellular organismal process

extracellular region

cell surface receptor linked signal transduction

nervous system development

substrate specific channel activity

gated channel activity

proteinaceous extracellular matrix

enzyme linked receptor protein signaling pathway

0 10 20 30 40 50

catalytic activity

hydrolase activity

mitochondrion

lipid metabolic process

carboxylic acid metabolic process

organic acid metabolic process

monocarboxylic acid metabolic process

protein serine/threonine phosphatase activity

metallocarboxypeptidase activity

Series1

Number of genes Number of genes

RYR2: Ryanodine Receptor 2

AMH: Anti-Mullerian Hormone

Gene function enrichment (p<0.001) of selectively expressed genes

Cholesterol Synthesiso24-dehydrocholesterolreductaseoCYP51

Cholesterol deliveryScarb1

Transfer of substrate cholesterol to the inner mitochondrial membranefor steroidogenesis.StAR

CYP11A / P450scc

Wikipedia, 2010

CY

P1

9A

/ Aro

ma

tase

•CYP19A1 expression significantly higher in cumulus cells as compared to floating granulosa cells(Kôks et al. 2009) Human

•Mature COC in culture express high aromatase activity and produce estradiol when androgen is present in the culture media. (Bar-Ami et al., 1997) Human

Steroidogenic genes in MGC and CC

Top 10 in both the CC and MGCExpression of genes for cholesterol

availability for steroidogenesis

• FSH receptor was not expressed in appreciable levels in neither

CC nor MGC

• LH receptor was moderately expressed at the same level in both

CC and MGC

Xu et al.,

2010

Ovulatory dose of

hCG induces

abolishment of the

gonadotrophinreceptor

expression, where

after the LH receptor

mRNA reappear

(Eyster and Stouffer,

1985, Xu et al., 2010).

Gonadotropin receptors

• These findings may reflect that LH receptor expression levels in the

somatic cell compartment are correlated to patients or more likely

correlated to the individual follicle

• Variation in LH receptor expression in MGC

and CC: up-to 10 fold difference in expression

level

(Haouzi et al., 2009)

LH receptor expression

0,00

500,00

1000,00

1500,00

2000,00

2500,00

3000,00

3500,00

4000,00

4500,00

0,00 500,00 1000,00 1500,00 2000,00

Cumulus

Mu

ral

gra

nu

los

a

Pearson correlation coefficient = 0.72

p-value = 0.003

Variarion in LH expression in Cumulus cells

0,00

500,00

1000,00

1500,00

2000,00

0 2 4 6 8 10 12 14

Sample number

Exp

ressio

n v

alu

es ,

Mic

ro

array

Strong correlation between LH receptor expressionin corresponding CC and MGC

Gene name Symbol Pearson correlation coefficient

P-value

Steroidogenic acute regulatory protein StAR 0,75 <0.01

Cholesterol side chain cleavage cytochrome P450

CYP11A 0,46 <0.01

Hydroxy-delta-5-steroid dehydrogenase, 3 beta- and steroid delta-isomerase 1

HSD3b 0.63 <0.001

Cytochrome P450, family 19, subfamilyA, polypeptide 1, Aromatse

CYP19A 0.27 0.12

Liver receptor homolog-1/

Nuclear receptor 5A2

LRH-1/

NR5A2

0.45 <0.05

Epiregulin EREG 0.55 <0.01

Amphiregulin AREG 0.52 <0.01

Ryanodine receptor 2 RYR2 0.780 <0.001

Anti Müllerian Hormone AMH -0.170 P=0.23

Associations between LH receptor expression and expression of central steroidogenic genes


P-value


Cholesterol side chain cleavagecytochrome P450

CYP11A 0,46 <0.01


HSD3b 0.63 <0.001

Cytochrome P450, family 19, subfamily A, polypeptide 1, Aromatse

CYP19A 0.27 0.12

Liver receptor homolog-1/

Nuclear receptor 5A2

LRH-1/

NR5A2

0.45 <0.05

Epiregulin EREG 0.55 <0.01


Ryanodine receptor 2 RYR2 0.780 <0.001

Anti Müllerian Hormone AMH -0.170 P=0.23

Associations between LH receptor expression and expression of central steroidogenic genes

The paired analysis within individual follicle gives a unique picture of the two

somatic cell compartments

Functional enrichment analysis of selectively expressed genes provided

list of genes describing a metabolic ‘phenotype’ of MGC and cell communication

‘phenotype’ of CC

High steroidogenic capacity was present in both cell-types with differences in

levels of genes encoding for enzymes involved in steroidogenesis

Correlation between LH receptor expression in corresponding CC and MGC

Association between both LH expression and central steroidogenic and growth

factor genes.

Confirmation of substantial inter follicle variation / unique milieu

Conclusion

Genes in cumulus and granulosa cells which expressions have been suggested to reflect the quality of the oocyte

Methodological considerations

2

Quality markers -increase the outcome of ART -reduce the multiple pregnancies

ESHRE, dec 2010

Sample TechniqueOocyte

competenceMGC CC

McKenzie et al.,

2004

Individual RT-PCR Embryo

morphology

(day 3)

PTGS2,

GREM1,

HAS2

Zhang et al.,

2005

Pooled Array,

RT-PCR

8-cell day 3 vs

non fertilised

after IVF

Ptx3

Cillo et al.,

2007


morphology

HAS2,

GREM1

Feuerstein et al.,

2007


morphology

(day 3)

STAR,

PTGS2,

AREG, CX43,

SCDI, SCD5

Assou et al.,

2008

Individual Array,

RT-PCR

Pregnancy

(pos hCG)

BCL2L11,

PCK1, NFIB

Hamel et al.,

2008

Pooled Array

RT-PCR

Pregnancy

(pos hCG)

CYP19A1

CDC42,

HSD3B1,

FDX1,

SERPINEA2

Hamel et al,

2009

Individual RT-PCR Pregnancy

(ongoing)

PGK1, RGS2

Hamel et al.,

2010

Individual Array Pregnancy

(ongoing)

UGP2,

PHLDA2

Adriaenssens et al.,

2010

Pooled RT-PCR Oocyte

maturity

Embryo

morphology

VCAN,

GREM1

RPS6KA2,

ALCAM

Gebhardt et al.,

2011

Individual RT-PCR Birth VCAN

PTGS2

Genes in CC or MGC suggested to relate to qualityof the correspondent oocyte

ESHRE, dec 2010

Sample TechniqueOocyte

competenceMGC CC

McKenzie et al.,

2004


morphology

(day 3)

PTGS2,

GREM1,

HAS2

Zhang et al.,

2005

Pooled Array,

RT-PCR

8-cell day 3 vs

non fertilised

after IVF

Ptx3

Cillo et al.,

2007


morphology

HAS2,

GREM1

Feuerstein et al.,

2007


morphology

(day 3)

STAR,

PTGS2,

AREG, CX43,

SCDI, SCD5

Assou et al.,

2008

Individual Array,

RT-PCR

Pregnancy

(pos hCG)

BCL2L11,

PCK1, NFIB

Hamel et al.,

2008

Pooled Array

RT-PCR

Pregnancy

(pos hCG)

CYP19A1

CDC42,

HSD3B1,

FDX1,

SERPINEA2

Hamel et al,

2009

Individual RT-PCR Pregnancy

(ongoing)

PGK1, RGS2

Hamel et al.,

2010

Individual Array Pregnancy

(ongoing)

UGP2,

PHLDA2

Adriaenssens et al.,

2010

Pooled RT-PCR Oocyte

maturity

Embryo

morphology

VCAN

GREM1

RPS6KA2,

ALCAM

Gebhardt et al.,

2011

Individual RT-PCR Birth VCAN

PTGS2

Genes in CC or MGC suggested to relate to qualityof the correspondent oocyte

• Lack of consistent markers in published studies

- no common standard for developmental competence

- difference in sampling (time)

- analysis on individual or pooled follicles

• Studies where MGC and CC are collected and embryoescultured individually

-sampling immediately after OPU

-analysis on cells for individual follicles

-well defined developmental competence (ongoing

pregnancy / birth)

Current statusfor identifying gene expression quality markers

Cell adhesion

Inflammation

Response to wounding

Electron transport chain

Cell-to-cell signalling

Signal transduction

Regulation of proteolysis

Cell cycle regulation

Growth factor

Fatty acid biosynthesis

Lipid metabolic process

Carbohydrate metabolic process

Extracellular matrix

Gene ontology functions/process of suggested marker genes

Ongoing study

No pregnancy

X

•Marker expression profile based on pregnant and non-

pregnant classification

1) Cumulus cells

2) Granulosa cells

3) Cumulus:Granulosa ratio

Classification of the gene expression profileCorrelation between somatic cell gene-expression and competence of the oocytes

Lack of consistent gene expression markers in CC and MGC

Difference in sampling competence measure may be the explanation

Classification of CC and MGC in ‘pregnant’ and ‘non pregnant’ expression profile may provide us a tool to prospectively select and de-select oocytes/embryoes

Conclusion

Acknowledgement

Rehannah BorupMicroarray Centre

Rigshospitalet

Claus Yding AndersenRigshospitalet

Jeanette Bogstad, VibekeBoujida Hartvig, Jens IngemanssenAnita Elverdal, Pernille AndersenKirsten Langbøl,Marianne Pedersen,Mette Villads Nielsen, Tanja SchrøderFertility ClinicHvidovre Hospital

MSD, Denmark

-50

-40

-30

-20

-10

0

10

20

30

AMH CYP11a1 ESR GHR

Microarray(n= 12)

RT-PCR (n= 6)

AMH

BP

β-actin

Grøndahl et al., 2011

RT-PCR confirmation of array analysis

•The AR was 3 fold higher expressed (p<0.01) in CC as compared to MGC

•The AR signalling pathway was significantly enriched (p<0.001) in the CC compartment while it was not present in the MGCs indicating a sustained function signalling through AR in the cumulus cells in the preovulatory follicle

Androgen receptor expression has been suggetsted to be assosiated with follicle health Weil et al., 1998; 1999 (primate); Nielsen et al., 2010 (human)

Androgen receptor (AR) expression is higher in CC than in MGC

•Higher expression in CC than MGC (Kôks et al., 2010). Human.•Immuno-localization of AR found to by mainly located in COC

(Szoltys et al., 2010). Murine.•AR activity in granulosa cells in the proximity of the oocyte was found in the porcine ovary (Hickey et al., 2004).


P-value



CYP11A 0,565 <0.02


HSD3b 0.071 P=0.42


CYP19A 0.44 P=0.07

Epiregulin EREG 0.034 P=0.45


Ryanodine receptor 2 RYR2 0.513 P=0.04

Anti Müllerian Hormone AMH 0.566 P=0.02

Associations between AR expression and expression of central steroidogenic genes


P-value



CYP11A 0,565 <0.02


HSD3b 0.071 P=0.42


CYP19A 0.44 P=0.07

Epiregulin EREG 0.034 P=0.45


Ryanodine receptor 2 RYR2 0.513 P=0.04

Anti Müllerian Hormone AMH 0.566 P=0.02

Associations between AR expression and expression of central steroidogenic genes

•Positive correlation between AMH and AR expression

Catteau-Jonard et al., 2008, Human

Grøndahl et al., 2011

the transcriptome of corresponding cumulus and granulosa cells

Documents