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Epigenetic programming in chronic lymphocytic leukemia Christopher Oakes 10 th Canadian CLL Research Meeting September 18-19 th , 2014

Christopher Oakes 10th September 18-19 · Epigenetic programming in chronic lymphocytic leukemia Christopher Oakes 10th Canadian CLL Research Meeting September 18-19th, 2014

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Epigenetic programming in chronic lymphocytic leukemia

Christopher Oakes

10th Canadian CLL Research MeetingSeptember 18-19th, 2014

Epigenetics and DNA methylation programming in normal and tumor cells:

Epigenetic = a modification of DNA or chromatin that alters its function that is heritable

Epigenetic states are programmed in early cell lineage development and become fixed in mature, differentiated cells and thus define cellular identity

CpG methylation

enhancer promoterProgramming

Cancer cells acquire aberrant epigenetic marks that are important to the malignant phenotype

450K array (Illumina) analysis of 29 CLLs at 2 timepoints:Pe

arso

n co

rrel

atio

n m

atrix

, 450

K C

pGs

50x

CpG

s

samples samples

(Oakes et al., Cancer Discovery, 2014)

Remarkable stability of DNA methylation in CLL revealed by 450K array profiling:

Tim

e =

Year

s

HighStability

Summary I – High longitudinal stability of DNA methylation patterns in CLL:

CLL cellpopulation:

++

+

+++

++

+

Instability/Evolution

Co-evolution of genetic &epigenetic alterations

Oakes et al., Cancer Discovery, 2014

Low methylation heterogeneity reveals clonal orgins of epigenetic patterns in CLL:

0

5

10

15

20

25

30

35

40

healthy donor

B(LN)

T CLLB(PB)

Met

hyla

tion

hete

roge

neity

(arb

itrar

y un

its)

CLL(ICGC)

AML

Ren

al

Col

on

Lung

Glio

blas

tom

a

Global Heterogeneity assessment (450K):

Oakes et al., Cancer Discovery, 2014

Low methylation heterogeneity reveals clonal orgins of epigenetic patterns in CLL:

Targeted bisulfite sequencing:

Allele‘A’

Allele‘G’

CLL86 CLL44CLL21

Sequ

ence

read

s

CpG: 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

Allele‘A’

Allele‘G’

Healthy B cellsCLL32 CLL36

methylatedunmethylated

Sequ

ence

read

s

CpG: 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

LowMethylationHeterogeneity,

HighMethylationStability

++

+

+++

++

+

Summary II – High longitudinal stability of DNA methylation patterns in CLL:

CLL:

Instability/Evolution

Co-evolution of genetic &epigenetic alterations

Tim

e =

Year

s to

Dec

ades

CLL foundercell:

MBL:

High epigenetic stability in CLL permits the elucidation of the methylation patterns present in the founder cell at the time of malignant transformation

cluster 3cluster 2cluster 1

CLL patients cluster into three distinct epigenetic subgroups:

139 CLL profiles downloaded from the ICGC Data Portal (http://dcc.icgc.org/web)

met

hyla

tion

%

100

50

0

450k array (Illumina) analysis of 249 CLLsUnsupervised analysis displaying the 500 most discriminating CpGs

DNA methylation clusters versus IGHV mutation status:

Num

ber o

f cas

es0123456789

0

2

4

6

8

10

12

020406080100120140160180

100   98   96  94    92   90  88   86

100   98   96  94    92    90  88   86

100   98   96  94    92    90  88   86

% mutation of IGHV sequence

IGHV mutation status:

cluster 1 cluster 2 cluster 3

DNA methylation clusters versus clinical outcome:Independent, clinically-annotated sample set (n = 349):

cluster 3cluster 2cluster 1

Summary III – Three epigenetic subgroups derive from distinct cell poulations:

CLL:

Tim

e =

Year

s to

Dec

ades

CLL foundercell:

MBL:

LowMethylationHeterogeneity,

HighMethylationStability

cluster 1 cluster 2 cluster 3

IGHV (% germline): 100 ~99.9 - 95 <95Clinical outcome: poor intermediate favorable

Mutation spectrum: adverse mixed low risk

Are methylationclusters relatedto B cell maturation?

How/why 3 clusters?

Phylo(epi)genetic analysis of the development of blood cell types:

(10,000 most variable probes)

HSCs

Myeloid

T/NK lymphocytes

B lymphocytes

Profiles downloaded from: ICGC Data Portal (http://dcc.icgc.org/web)GEO Database (http://www.ncbi.nlm.nih.gov/geo)

Illumina 450K analysis:

Example of DNA methylation programming during B cell maturation:

%GCCpG islandsGene (EBF1)

CD5- NBCCD5+ NBCCD5- MBCCD5+ MBC

TFsDNaseH

H3K4me3H3K27ac

H3K4me1Conservation

EBF1: (chromosome 5)

EBF1

Isolation of B cells at various stages of maturation (naïve→memory):

DNA methylation programming during B cell maturation:

DNA methylation programming during B cell maturation:

Top 1000 programmed CpGs (naïve→memory):hy

pom

ethy

late

dhy

perm

ethy

late

d

Genomic features associated with B cell methylation programming:

NBC→csMBC:

Chromatin state segmentation analysis:

:Transcription factor motif & association analysis:

NBC GCF csMBCncsMBCencsMBC MGZ

AP-1 EBF Oct NF-kB MYC

Hypomethylation ofenhancers & promoters

HOXA9

Hypermethylation ofPRC-marked regions

Ag(αIgM)

+++

(CD40L)

DC(IL15)

TH

Summary IV - Normal B cell DNA methylation programming:

How do the CLL methylation clusters relate to normal B cells at various stages of maturation?

Comparison of Normal B cell and CLL DNA methylation programming:

HP-CLL(Highly Programmed)

IP-CLL(Intermediate Programmed)

LP-CLL(Less Programmed)

Phylo(epi)genetic analysis of individual CLL samples with normal B cells:

Top 1000 most variable CpGs in both CLL & B cells:

Comparison of B cell programming in CLL and global gene expression:

Total RNA-seq:

Summary V – CLL clusters derive from various stages of B cell maturation:

CLL:

Tim

e =

Year

s to

Dec

ades

CLL foundercell:

MBL:HighMethylationStability

NBC GCF csMBCncsMBCencsMBC MGZ

AP-1 EBF Oct NF-kB MYC HOXA9Time = Hours to Days

Normal B cell DNA methylation programming

cluster: IP-CLL HP-CLLLP-CLL

↑TCL1A↑ZAP70↑BTK↓miR-29↓IRF4

↓TCL1A↓ZAP70↓BTK↑miR-29↑IRF4

Global geneexpression: transition from an aggressive

to an indolent gene expressionsignature

How/why do normal cells become malignant? Aggressive vs. indolent?

CLL-specific methylation reveals a transcription factor signature of aggressive disease:

Summary VI – Deregulation of transcription factors enact malignant transformation in CLL:

CLL:

Tim

e =

Year

s to

Dec

ades

CLL foundercell:

MBL:HighMethylationStability

NBC GCF csMBCncsMBCencsMBC MGZ

AP-1 EBF Oct NF-kB MYC HOXA9Time = Hours to Days

Normal B cell DNA methylation programming

cluster: IP-CLL HP-CLLLP-CLL↑TCL1A↑ZAP70↑BTK↓miR-29↓IRF4

↓TCL1A↓ZAP70↓BTK↑miR-29↑IRF4

Global geneexpression: transition from an aggressive

to an indolent gene expressionsignature

CLL initiatingmutation(s), BCRactivation

↑NFAT↑EGR2

↓c-FOS↓EBF1

↑E2A↑OCT2

Conclusions:

The vast majority of differences between U vs M CLL occur between normal B cell subsets (epigenome & transcriptome)

All comparisons of CLL to crude CD19+ B cells should be interpreted very cautiously

DNA methylation programming is continual and driven by signaling pathway activation and enacted by specific transcription factors.

The CLL founder cell can arise from within a broad window of development and in-turn each CLL patients’ clone is unique.

The degree of DNA methylation programming achieved strongly impacts on the clonal phenotype (gene expression & clinical course)

CLL-specific changes are linked to aberrant activity of NFAT & EGR transcription factor families and loss of AP-1 and EBF1

The mechanisms governing extreme flexibility vs. stability is key to understanding the cause and evolution of the disease

Acknowledgements:

Clinical collaborations:

Bioinformatics/statistics:

John C. ByrdDavid LucasAmy Stark(The Ohio State University)

Laura RassentiThomas Kipps(CLL Research Consortium)

Thorsten ZenzLeo SellnerJennifer Hüllein(Nationales Centrum furTumorerkrankungenHeidelberg)

Yassen AssenovLei GuManuela ZucknickOlga Bogatyrova

Marc SeifertRalf KuppersDaniel MertensPeter LichterChristoph Plass

Hartmut DöhnerStephan StilgenbauerEugen TauschJohannes Bloehdorn(University of Ulm)

met

hyla

tion

%

100

50

0

HP-CLLIP-CLLLP-CLL

n=7 P=0.011

NOTCH1* BRAF* TP53*

SF3B1* MYD88*

del 11q* del 17p*

trisomy 12

events:Fisher’s exact test:

bidel 13q

n=6 P=0.018

n=23 P=0.001

n=17 P=0.027

n=15 P=0.0003

n=14 P=0.003

n=18 P=0.001

n=17 P=0.39

n=16 P=0.064

*P<0.05

events:Fisher’s exact test:

del 13q*(sole) 

n=21P=0.016

HP-CLL

LP-CLL

IP-CLL

The distribution of genetic aberrations within CLL methylation clusters:

TP5317p‐11q‐

SF3B1NOTCH1

BRAF12+

MYD8813q‐

Examples of DNA methylation programming during B cell maturation:

%GCCpG islandsGene (EBF1)

CD5- NBCCD5+ NBCCD5- MBCCD5+ MBC

TFsDNaseH

H3K4me3H3K27ac

H3K4me1Conservation

EGR2: (chromosome 10)

EGR2