COPHES/DEMOCOPHES Workshop, Copenhagen 12 March 2012

Zdenko Herceg,

Head, Section of Mechanisms of Carcinogenesis

International Agency for Research on Cancer (IARC)

Epigenetic biomarkers for assessing environmental exposures and cancer risk

Genomes

Epigenomes Courtesy of Peter Jones

Definitions

Epigenetics defines all heritable changes in gene

expression that are not coded in the DNA sequence

itself

Semantic debate…

Epigenetics, interface between genome and environment

Normal cells Tumour cells

Fundamental role of genetic and epigenetic events and environment in cancer

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Point mutation

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Rearrangement

Epigenetic changes occur more frequently than genetic

changes Deletion

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CMet

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Epimutation

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Normal

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Duplication

F r e q u e n c y

Epigenetic carcinogens – “Epimutagens”

1. Environmental agents or toxic drugs:

- tobacco

- cadmium

- arsenic

- ionizing radiation (plutonium)

2. Diet:

- alcohol consumption - colorectal cancer

- diet

3. Infectious agents:

- EB virus in human lymphomas

- HPV genome in cervical cancer

- HBV/HCV in human hepatocellular carcinoma

Identification of environmental factors associated with

epigenetic changes

Previous studies

• Qualitative assays

• Small sample size

• Lack of statistical power

• Tissues/cells analyzed

• False positives

• Publication bias

Ideal approach

• Quantitative and genome-wide analysis

• Large sample size

• High quality of environmental/lifestyle exposures

• Choice of tissues and cells (cell heterogeneity and averaging?)

• Reliable biomarkers of exposure

Three types of epigenetic information

Sawan, Vaissiere and Herceg 2008

Me

Me

Me

Me

G

C

C

G

Me

G

C

C

G

DNMT 3A/B

Maintenance of

methylation

de novo methylation

DNMT 1

Me

G

C

C

G

Me

G

C

C

G

Me

G

C

C

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G

DNA replication

DNA methylation is a universal epigenetic modification

Tissue-specific and tumour-specific epigenetic

signatures

DNA methylation patterns in normal human tissues

Christensen et al., PLoS Genetics 2009

Placenta Blood other solid tissues

Adult Infant

Aberrant DNA methylation is a gradual and reversible process

DNMTi HDACi

“Normal”

Pre-neoplastic

Tumour

CHRNα3 expression can be re-expressed by DNA

demethylating treatment

Paliwal et al. Cancer Research 2010

Methylation within a gene region is NOT « all or none »

Introns

Alus

LINEs

Retroelements

miRNAs

(53%)

Coding regions (3%)

Promoter regions (3%)

Chromosomes 20, 21, and 22

(127 MB bp containing 2,122 genes)

Satellites

Alus

LINEs

Retroelements

(41%)

CH3

CH3

CH3

CH3

CH3

CH3

CH3

CH3

CH3

1 kb 1 kb

CH3

CH3

CH3

CH3

CH3

CH3

CH3

CH3

Coding regions (3%)

Promoter regions (3%)

Courtesy of Peter Jones

Methylation of “junk” DNA

Current developments

• new emerging concepts involving epigenetic mechanisms in

critical cellular processes and disease

• remarkable technological advances in epigenetics and

epigenomics that allow powerful screening of large series of

samples

• the availability of large case-control studies and

population-based cohorts

Recent advances that have resulted in exciting opportunities

for cancer epigenetics in understanding the causes of

cancers:

Methodologies and approaches to study

epigenetic states in tissues and cells?

Tumor samples

Analysis of DNA

methylation

Global 5-meC

content

Technologies for epigenetic profiling of cancer

Analysis of histone

modifications

ChIP-

on-

chip

ChIP

candidate

gene IHC

mRNAs

Genome-wide

approaches

RLGS Methyl-DNA

IP with MBDs ChIP-on-chip

DMH with

CpG-island

tiling array

CpG-island

Bead-Array

NGS

MethylC-seq

RRBS

MeDIP-seq

MBD-seq

Mass-spec

LINE-1

LUMA

Gene-specific approaches

MSP Sanger Pyro MALDI-

TOF/Sequ

enom

Pyrosequencing assays established at IARC

Additional pyrosequencing assays for larger panel of cancer-associated genes

are being established

DNA methylation changes in liver cancer

Lambert et al., J. Hepatol 2010

Cell lines HCC samples N BC EC Blood

DNA methylation profiling in HCC (Illumina arrays)

Hernandez-Vargas et al., PLoS One, 2010

66 genes were found differentially methylated in HCC tumours compared with paired surrounding tissues.

P< 0.001 FDR 0.15

Specific DNA methylation signature in liver cancer

Parametricp-value FDR UniqueID Name Location Status Expressed Allele

0.0044384 0.0274 GFI1_P208_ 4071 1:92702908- Predicted paternal

0.0003924 0.00591 GFI1_E136_ 607 1:92702908- Predicted paternal

0.0019333 0.0157 HOXA5_E18 3470 7:27137520- Predicted maternal

0.0011385 0.0111 HOXA11_P6 1066 7:27177300- Predicted maternal

0.0002617 0.00433 GLI3_E148_ 630 7:41957071- Predicted maternal

0.002281 0.017 ASB4_P52_R 87 7:94943219- Unknown Unknown

0.0047648 0.029 ASB4_E89_F 3011 7:94943219- Unknown Unknown

0.0002987 0.00478 CPA4_P1265 377 7:129710229- Imprinted maternal

0.001986 0.016 MEST_P4_F 1390 7:129903281- Imprinted paternal

2.02E-05 0.000859 MEST_P62_ 1392 7:129903281- Imprinted paternal

0.0014373 0.0127 FASTK_P598 4874 7:150394640- Predicted maternal

0.0047203 0.0289 H19_P541_F 949 11:1962981-1985640 Imprinted maternal

0.0001402 0.00274 INS_P804_R 1203 11:2127584-2148999 Imprinted paternal

0.0011466 0.0111 ASCL2_P360 103 11:2236303-2258757 Conflicting maternal

6.60E-06 0.000394 TRPM5_P97 2155 11:2372335-2410850 Provisional paternal

0.0001076 0.00225 TRPM5_P72 2153 11:2372335-2410850 Provisional paternal

4.50E-06 0.000294 TRPM5_E87 3986 11:2372335-2410850 Provisional paternal

0.0029305 0.0198 KCNQ1_P54 1267 11:2412796-2836915 Imprinted maternal

0.0011178 0.0109 CDKN1C_P6 240 11:2851440-2873550 Imprinted maternal

0.001211 0.0115 DCN_P1320 3592 12:90053165- Unknown Unknown

0.0021316 0.0167 DIO3_P674_ 636 14:101087440- Unknown Unknown

0.0006213 0.00795 PWCR1_P81 1790 15:260567-280661 Imprinted paternal

1.00E-06 0.000107 PWCR1_E81 3846 15:260567-280661 Imprinted paternal

0.0041615 0.0261 SNRPN_seq 6124 15:1443610-1616684 Imprinted paternal

0.0027452 0.0188 SNRPN_E14 3936 15:1443610-1616684 Imprinted paternal

0.0001198 0.00244 SNRPN_P23 2029 15:1443610-1616684 Imprinted paternal

8.00E-07 1.00E-04 MKRN3_E14 3676 15:21351546- Imprinted paternal

2.00E-07 5.02E-05 MKRN3_P10 1439 15:21351546- Imprinted paternal

0.0026996 0.0187 MAGEL2_E1 3624 15:21429787- Imprinted paternal

0.0016337 0.0141 MAGEL2_P1 1339 15:21429787- Imprinted paternal

0.0013901 0.0126 NDN_P1110 1595 15:21471646- Imprinted paternal

1.00E-06 0.000107 GABRA5_P8 840 15:24732695- Conflicting paternal

1.14E-05 0.000618 GABRA5_P1 844 15:24732695- Conflicting paternal

4.00E-07 6.69E-05 GABRA5_E4 3295 15:24732695- Conflicting paternal

2.10E-06 0.000158 GABRG3_E1 3303 15:24787860- Conflicting paternal

0.0039607 0.0252 USP29_P205 2184 19:62313320- Unknown Unknown

< 1e-07 < 1e-07 USP29_E274 4004 19:62313320- Unknown Unknown

4.42E-05 0.00136 ZIM3_P451_ 2204 19:62327275- Unknown Unknown

4.00E-07 6.69E-05 ZIM3_P718_ 2205 19:62327275- Unknown Unknown

2.00E-07 5.02E-05 ZIM3_E203_ 4010 19:62327275- Unknown Unknown

0.0023747 0.0175 NNAT_P544 1634 20:35573020- Imprinted paternal

0.0021678 0.0167 GNAS_E58_ 3330 20:56838189- Imprinted maternal

0.0017671 0.0148 GNAS_P86_ 915 20:56838189- Imprinted maternal15 11 7

chr7

chr11

chr15

Identification of genes and pathways that are differentially methylated in HCC

DNA methylation and tumor stage

Predictive value of DNA methylation signature

Epigenetic changes as signatures of environmental

exposures to risk factors

- In tumour cells

- In non-tumour (target or surrogate) tissues

Distinct DNA Methylation Profiles In HCC Of Different Etiologies

Epigenetic signatures in peripheral blood predicts ovarian cancer

Teschendorff et al., 2009 PLoS One

Cancer and age appear to elicit a common methylation changes in

blood cells that may reflect changes in the cellular composition

Schembri et al. 2009 PNAS

Smoking-dependent changes in microRNA expression profiles in normal lung epithelium

All three diet groups pooled together (at T0 and T4)

Randomized trial with flavonoid rich diet

Scoccianti et al., 2011in press

Alterations in DNA methylation status during development

Skinner & Jirtle Nature Rev/Genet. 2007

Birth Gametes Childhood Adulthood

Epigenome reprogramming Cancer Leukemia

Parental exposures Maternal diet/lifestyle C

on

cep

tio

n

In utero life

Epigenetic profiling Cancer risk Exposure markers

Impact of early life exposure on epigenome and cancer risk in childhood and adulthood

Windows of susceptibility

Pregnant women Pregnant women

Dry season (high aflatoxin)

Wet season (low aflatoxin)

Aflatoxin-albumin biomarker analysis in maternal plasma

Newborn babies Newborn babies

Infant blood samples taken at birth

DNA methylation profiling (Illumina 450K Arrays)

Bioinformatics analysis

Technical validation

Identification of epigenetic biomarkers of aflatoxin exposures

and dietary deprivation

Identification of epigenetic biomarkers of growth impairment

and dietary interventions

Validation of top hits in an independent cohort

HumanMethylation450K arrays provide coverage throughout gene regions

Every requested content category is included on the array

Comprehensive gene coverage

450K arrays (Illumina)

Bioinformatic analysis

Normalization

Probes filtering

Unsupervised clustering

Clustering Class comparison Class prediction

Survival prediction Gene ontology

HCC T vs S tumor stages risk factors

High aflatoxin

Differentially methylated CpG sites between high vs low aflatoxin

Low aflatoxin

low

me

thyla

tio

n h

igh

me

thyla

tio

n

Distribution of all CpG sites

Distribution of differentially

methylated CpG sites

Hernandez-Vargas and Herceg, unpublished results

116

20

15

31

Absolute number of differentially methylated CpG sites in CpG

islands, shores, shelves and open sea between high vs low

aflatoxin

Differentially methylated genes between aflatoxin exposure

groups

Toward DNA Methylomes at single base

resolution

Quantitative and genome-wide analysis of DNA methylation

1) MethC-seq - Arabidopsis DNA methylome at base resolution - Genomic

DNA is treated with sodium bisulphite subjected to Illumina Genetic

Analyser (GA) - (Lister et al., Cell 2008)

2) BS-seq - Arabidopsis DNA methylome at base resolution - Genomic DNA

is treated with sodium bisulphite subjected to Illumina Genetic Analyser

and Solexa technology for Shotgun sequencing (Cokus et al., Cell 2008)

3) MethC-seq - Human DNA methylome at base resolution - Genomic DNA

from human ES and fibroblasts is treated with sodium bisulphite subjected

to Illumina GA - 94% of all cytosines covered (Lister et al., Nature 2009)

Lister et al. Nature 2009

Human DNA methylome at base resolution show

widespread epigenomic differences

Embryo Fibroblasts

ES cells

One-quarter of cytosine methylation in ES cells occurs in non-CG context and non-CG methylation is restored in iPS cells

ChIP-seq of Trrap and Oct4 binding in ES cells and MEFs

Sawan and Herceg, 2012, manuscript in revision

Genome-wide redistribution of Trrap and Oct4 following cell

differentiation

Sawan and Herceg, 2012, manuscript in revision

Summary and perspectives

- The fields of epigenetics has become “mainstream” and a

new branch (Environmental Epigenetics) is now emerging

- Epigenome is profoundly altered in cancer cells (driver vs

functionally inert « passenger » changes)

- Epigenetic changes in tumours and surrogate tissues as

biomarkers of environmental exposures and cancer risk

- Mechanisms by which environmental factors influence the

epigenome

- Effects of in utero and early life conditions on epigenetic

states and disease risk in childhood and adulthood

Epigenetics Group (IARC)

Cyrille Cuenin

Hector Hernandez

Marie-Pierre Lambert

Rabih Murr (now at FMI, Basel)

Maria Ouzounova

Anupam Paliwal

Carla Sawan

Thomas Vaissière (now at Scripps)

Sheila Lima

Joanna Loizou (now at CR UK)

Vivek Shukla (now at MD Anderson)

Pushpinder Kaur

Karen Balassiano

Anastas Gospodinov

Marion Martin

Gabriel Ichim

Ho-Sun Lee

Pierre-Benoit Ancey

Acknowledgments

Joanna Rabih Vivek

Epigenetics Group

Karen Balassiano

Marie-Pierre Cros

Cyrille Cuenin

Marion Essig

Hector Hernandez

Anastas Gospodinov

Gabriel Ichim

Marie-Pierre Lambert

Pushpinder Kaur

Vladimir Krutovskikh

Maria Ouzounova

Anupam Paliwal

Carla Sawan

Thomas Vaissière

Cat Int Oncol Barcelona

Carlos González

FLI-Jena, Germany

Zhao-Qi Wang

CRC Cambridge, UK

Steve Jackson

INSERM, Lyon

Jean-Yves Scoazec

Isabelle Chemin

Christian Trepo

Fabien Zoulim

LIGHT, Leeds

Yun Yun Gong

INCA, Rio de Janeiro

Luis Felipe Ribeiro Pinto

External Collaborators

Acknowledgments IARC

IGBMC, Strasbourg

Laszlo Tora

IEO, Milan

Bruno Amati

CNG, Paris

Jorg Tost

Univ. Ottawa

Chantal Matar

ICL London

Paolo Vineis

ISREC, Lausanne

Andreas Trumpp

Ohio State Univ.

Carlo Croce

IARC collaborators

Pierre Hainaut

Paul Brennan

Florence Le Calvez

James McKay

Bakary Sylla

Massimo Tommasino

Mazda Janeb

Research supported by:

European Network of Excellence

(ECNIS)

La Ligue National Contre le Cancer,

France

Institut National du Cancer

(Cancéropôle “EpiPro - Epigenetic

Network”)

European Molecular Biology

Organisation (EMBO)

Association for International Cancer

Research (AICR), UK

NIH - National Cancer Institute, USA

Swiss Bridge Award 2006

Association pou la Recheche sur le

Cancer (ARC)

International Agency for Research on Cancer (IARC)

Education and Training at IARC

Postdoctoral fellowships to junior scientists from …

Visiting Scientist Award is also offered for a qualified and experienced investigator …

Expertise Transfer Fellowship to enable an established investigator to spend from six…

http://www.iarc.fr/en/education-training/index.php

La passerelle Saint-Vincent, Lyon

Cell fate switching in epigenetic landscape

Waddington, 1956

Epigenetic gene regulation during mammalian development

Reik, Nature 2007

Aberrant DNA methylation and cancer

Promoter-specific hypermethylation

- inactivation of tumour suppressors and other

cancer associated genes

Global hypomethylation

- activation of cellular proto-oncogenes

- genomic instability

Loss of imprinting (LOI)

- abnormal biallelic expression of critical cellular

and developmental regulators

DNA methylation profiles in ESCCs

Lima et al., 2011

“Healthy” smokers were recruited and randomly assigned to

3 groups:

1.normal isocaloric diet (adequate administration of fruit and

vegetables)

2. flavonoid rich diet (cruciferous vegetables: cauliflower,

cabbage, broccoli…)

3. flavonoid supplementation diet (green tea and soy

products)

Randomized trial with flavonoid rich diet

Experimental strategy for identification of

molecular changes associated with HCC

RNA signatures

DNA methylation

profiling (Illumina

arrays and NGS)

microRNA, lncRNA, RNA expression

analysis

Identification of

candidate genes

Mechanistic

studies

Human liver

samples

Validation of

biomarkers

Isolation of DNA Isolation of non-coding RNAs

DNA sequencing

DNA methylation states in tumour vs surrounding tissues (liver cancer)

1257 genes were found significantly differentially expressed between Tumour and Surrounding tissues from HBV positive patients with HCC.

Tumour Surrounding

Hernandez and Herceg, in preparation Illumina arrays

DNA methylation changes in HCC (Illumina arrays)

Hernandez-Vargas et al. 2010 PLoS ONE

DNA methylation profiles in HCCs vs ESCCs

Liver cancer (HCC) Oesophageal squamous cell carcinoma

Hernandez Vargas et al., PLoS One 2010 Lima et al., 2011 submitted

Correlation analysis

Specific DNA methylation signature in HCC

INSERT OUR JIA’s Study (Faseb J) Epigenetic signatures in

peripheral blood predicts ovarian cancer

Teschendorff et al., 2009 PLoS One

Cancer and age appear to elicit a common methylation changes in

blood cells that may reflect changes in the cellular composition

Birth Childhood Adulthood

Epigenetic reprogramming Disease Impaired growth

In utero life Windows of susceptibility

Altered epigenetic states at birth

Biomarkers for disease risk

and dietary interventions

Epigenetic biomarkers of exposure

Environmental factors Aflatoxin exposure Dietary deprivation

Frequent infections Impaired mental development

Higher mortality rate