Next generation epigenetic profiling

2. Next Generation
Epigenetic Profiling
Wim Van Criekinge
10th octobre 2013, Lille (FR)

3. Overview
Epigenetics
– Introduction
– Methylation & Oncology
– Biomarkers
MDxHealth
–NEXT-GENeration Epigenetic Biomarkers
–PharmacoDX: Methylation Based Biomarkers
for Predictive and Prognostic Use

4. Actionable
Epigenome

5. Outside
Oncology ?

6. Historically,
Cancer Was Considered
to be Driven Mostly by Genetic Changes
Example:
Replication errors
GENETIC
Altered
DNA/mRNA/proteins
Altered
DNA sequence
X X
Oncogenesis
Tumor
 Mutations in p53
 Activating mutations in RAS
 Mutations or amplifications of the
HER-2 gene
 Chromosomal translocations in
myeloid cells and the generation of
the BCR-ABL fusion protein

7. Epigenetic Changes are
Important in Causing Cancer
Example:
Replication errors
GENETIC EPIGENETIC
Example:
Chromatin modification errors
Altered
DNA/mRNA/proteins
Altered
DNA sequence
Altered levels of
mRNA/proteins
Altered
chromatin structure
X X
Oncogenesis
Tumor

8. Source: Schuebel et al 2007
0
20
40
60
80
100
120
Methylated Mutated
76-100 51-75 21-50 1-20
Dx
CDx
Example of Methylation
vs Mutation: Colon & Breast Cancer

9. MGMT Biology
O6 Methyl-Guanine
Methyl Transferase
Essential DNA Repair Enzyme
Removes alkyl groups from damaged
guanine bases
Healthy individual:
- MGMT is an essential DNA repair enzyme
Loss of MGMT activity makes individuals susceptible
to DNA damage and prone to tumor development
Glioblastoma patient on alkylator chemotherapy:
- Patients with MGMT promoter methylation show
have longer PFS and OS with the use of alkylating
agents as chemotherapy

10. MGMT Promoter
Methylation Predicts
Benefit form DNA-Alkylating Chemotherapy
Post-hoc subgroup analysis of Temozolomide Clinical trial with primary
glioblastoma patients show benefit for patients with MGMT promoter methylation
0
5
10
15
20
25
Median Overall Survival
21.7 months
12.7 months
radiotherapy
plus
temozolomide
Methylated
MGMT Gene
Non-Methylated
MGMT Gene
radiotherapy
Adapted from Hegi et al.
NEJM 2005
352(10):1036-8.
Study with 207 patients

11. Overview
Epigenetics
– Introduction
– Methylation & Oncology
– Biomarkers
MDxHealth
–NEXT-GENeration Epigenetic Biomarkers
Can we rediscover MGMT ?
What does the epigenome look like ?
….

12. MBD_Seq
DNA Sheared
Immobilized
Methyl Binding Domain
Condensed Chromatin
DNA Sheared

13. Immobilized
Methyl binding domain
MgCl2
Next Gen Sequencing
GA Illumina: 100 million reads
MBD_Seq

14. Confidential Information | ©2013 MDxHealth Inc. All rights reserved.
Quality evaluation of Methyl Binding Domain
based kits for enrichment DNA-methylation
sequencing
De Meyer et al (2013)
Plos One

15. Confidential Information | ©2013 MDxHealth Inc. All rights reserved.
Quality evaluation of Methyl Binding Domain based
kits for enrichment DNA-methylation sequencing

16. MBD_Seq
MGMT = dual core

17. # samples
# markers
MBD_Seq
Genome-wide methylation
…. by next generation sequencing
Discovery
1-2 million
methylation
cores

18. BRCA1,
a bidirectional promoter
18

19. 19
Splice variants

20. Zooming into
Exon 1
20

21. Zooming into
Exon 1
21

22. Zooming into
Exon 1
22

23. GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
Where is the mC ?

24. GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT

25. GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
25% 50% 25%
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT

26. GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
25% 50% 25%
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
Dense methylated needed for transcriptional silencing
Are there alleles with all three positions methylated ?

27. GCATCGTGACTTACGACTGATCGATGGATGCTA
unmethylated alleles
less methylationmethylated alleles
more methylation
Deep Sequencing

28. Deep Sequencing MGMT Heterogenic complexity

29. Data integration with
DEEP Sequencing, Infinium, Reactivation, (directional) Expression …

30. Data integration
Correlation tracks
methylation methylation
expression expression
Corr =-1 Corr = 1

31. Correlation track
in GBM @ MGMT
+1
-1

32. BRCA1
32
1 T47D
2 BT549
3 MCF7
4 MDAMB231
5 HS578T
6 NORMAL
7 NORMAL
8 NORMAL

33. 9 BI T21 (BRCA1 MUT)
10 BI T22 (BRCA1 MUT)
11 BLC
12 BLC
13 BLC
14 BLC
15 BLC
16 BLC
17 BLC

34. 13 BLC
14 BLC
15 BLC
16 BLC
17 BLC
18 BLC
19 IVM
20 DKO

35. # samples
# markers
MBD_Seq
BT_Seq
MSP
Genome-wide methylation
…. by next generation sequencing
Discovery
Verification
Validation

36. Confidential Information | ©2013 MDxHealth Inc. All rights reserved.
Genetics
107 106 105 104 103 102 101 1108109
Full genome bp
Whole-genome
Bisulphite seq
MSP
Probes
(450-27K)
Enrichment
Targeted Panels

37. Confidential Information | ©2013 MDxHealth Inc. All rights reserved.
Genetics
107 106 105 104 103 102 101 1108109
Full genome bp
G
E
N
E
T
I
C
Whole-genome
sequencing
Enrichment seq
(Exome)
PCR
Enrichment
Targeted Panels
Instrument and Assay providers
CLIA Lab service providers

38. Sequencing
Deep
Seq
Molecular Unification
107 106 105 104 103 102 101 1108109
Full genome bp
Whole-genome
Bisulphite seq
RUO Clinical
E
P
I
G
E
N
E
T
I
C
Whole-genome
sequencing
Enrichment seq
(MBD, RRBS)
Enrichment seq
(Exome)
Probes
(450-27K)
Enrichment
Targeted Panels
Enrichment
Targeted Panels
Ultra
Deep

39. Confidential Information | ©2013 MDxHealth Inc. All rights reserved.
236 cancer-related genes
(3,769 exons) plus 47 introns
from 19 genes often
rearranged or altered in
cancer. These genes are
known to be somatically
altered in human solid
cancers based on recent
scientific and clinical
literature.

40. Confidential Information | ©2013 MDxHealth Inc. All rights reserved.
PubMeth.org
Reviewed methylation database in cancer

41. Epigenetic Alterations
Associated with Cancer Therapy Response
PCFT – folate
transport (MTX)
WRN

42. Confidential Information | ©2013 MDxHealth Inc. All rights reserved.
440 cancer-related genes genes are known to
be epigenetically altered in human solid
cancers based on recent scientific and clinical
literature.

43. Sequencing
Deep
Seq
Molecular Unification
107 106 105 104 103 102 101 1108109
Full genome bp
Whole-genome
Bisulphite seq
RUO Clinical
E
P
I
G
E
N
E
T
I
C
Whole-genome
sequencing
Enrichment seq
(MBD, RRBS)
Enrichment seq
(Exome)
Probes
(450-27K)
Enrichment
Targeted Panels
Enrichment
Targeted Panels
Ultra
Deep

44. Acknowledgments
44
Geert Trooskens
Simon Denil
Klaas Mensaert
Jean-Pierre Renard
Sarah De Keulenaer
Ellen De Meester
Tim De Meyer
Olivier Thas
Wim van den Berghe
Manon Van Engeland
Jurgen Veeck
Monika Hegi
Pierre Bady
Sebastian Kurscheid

45. 45
biobix
wvcrieki
biobix.be
bioinformatics.be