Bob Brown: New challenges in using biological endpoints for epigenetic therapies in clinical trials

Same genotype, different phenotype

Same genome, different epigenome

Same genotype, different phenotype

High Grade Serous Ovarian Cancer: Similar genome, very different epigenome (TCGA)

Many important genes are epigenetically silenced in malignant cells

• Cell cycle: Rb, p16INK4a, p15INK4a, p14ARF

• Signal transduction: RASSF1, APC

• Apoptosis: DAPK, Caspase 8

• DNA repair: MLH1, MGMT, BRCA1

• Senescence: TERT, TERC

• Invasion/metastasis: TIMP-3, E-cadherin

APC = adenomatous polyposis coliDAPK = death-associated protein kinaseMGMT = O-6-methylguanine-DNA methyltransferase  

1. Jones & Baylin. Cell 2007;128:683–922. Teodoridis JM, et al. Drug Resistance Updates

2004;7:267–78

MBD protein

Me Me Me

Acetyl Acetyl

DNAHistone Histone

HDAC

MBD protein

Me Me Me

Acetyl

DNAHistone Histone

HDAC

MBD protein

Me Me Me

DNAHistone Histone

HMT MeMe+ Me

MBD protein

Me Me Me

DNA

HMTMe Me Me

Epigenetic Therapies

• DNA Methyltransferase (DNMT) Inhibitors– Azacytidine: approved in the EU for the treatment of

patients with higher-risk MDS, CMML and AML– Decitabine: approved in the USA for the treatment of

patients with all FAB classifications of MDS

• Histone Deacetylase (HDAC) Inhibitors– Vorinostat: approval in US for treatment of advanced

cutaneous T-cell lymphoma

Challenges with current epigenetic therapies

• Toxicity

• Delivery

• Short plasma half-life (although long pharmacodynamic half-life)

• Lack of targeting

• Do they work by epigenetic mechanism?

• What are the chemotherapeutic epigenetic target?

• Lack of predictive biomarkers

• Do they target subpopulations of tumour stem cells?

• How to design early clinical trials if only targeting subpopulation

• Is the maximum biological dose the same as the maximum tolerated dose?

CR-UK Phase I dose escalation trial of decitabine and carboplatin in

patients with advanced solid tumours (Appleton et al 2007)

Ratio 5-methylcytosine: cytosinein PBMC DNA (CRUK Phase I trial of Decitabine &

carboplatin in advanced solid tumours)

1.5

2.0

2.5

3.0

3.5

4.0

4.5

0 5 10 15 20 25Days

Rat

io45mg/m2

90mg/m2

135mg/m2Decitabine induces

demethylation several days after treatment that reverses over time

Decitabine PK vs PD in PBCs

0

20

40

60

80

100

120

140

5 10 15 20

Methycytosine AAC

Decit

ab

ine A

UCPeak plasma levels of

decitabine correlate with demethylation in PBMCs

Proof of Mechanism: Do they do what they say on the tin?

Proof of Concept:Gene expression

(but not for all genes)

HbF

Actin

CP

70

K5

62

Da

y 1

Da

y 8

Da

y 1

0

Da

y 1

2

Da

y 1

5

Cycle 1

222018161412108642050

100

150

200 4590135non-epithelial

Day

CK

18

(%

of

da

y 1

)Proof of Concept:

Apoptosis(normal or tumour?)

Proof of Concept: Do they biologically do what they should?

Combination of DNMT and HDAC inhibitor enhances gene re-expression and chemosensitisation

65432100

1

2

3

4

5ControlCisplatinDAC

DAC+CisplatinPXD101DAC+PXD101+Cisplatin

Time (Days)

Rela

tive t

umou

r vol

ume

DAC

Day 6 Day 9 Day 12 Day 16

DAC+PXD101

Steele et al 2010

Origin of Cancer – Role of Cancer Stem Cells (CSC)?

Ovarian cancer cell lines & primary ascites contain Side Population cells

Specimen_001_23 Verapamil.fcs

HOECHST RED-A

HO

EC

HS

T B

LUE

-A

0 256 512 768 10240

256

512

768

1024

SP

Specimen_001_23.fcs

HOECHST RED-A

HOEC

HST

BLUE

-A

0 256 512 768 10240

256

512

768

1024

SP

Ascites010509_CD45 FITC.fcs

670nmLP (L3)-A42

4/44

nm (L

3)-A

0 256 512 768 10240

256

512

768

1024

SP 45neg live

Patient AscitesSP 0.021%

PEO23:

SP 6.90%

PEO23 +verapamil:

SP 0.00%

Rizzo et al, 2011

Patient ascites SP: increases following treatment

Cell lines derived from matched patient ascites

Primary patient ascites

Rizzo et al, 2011

IGROV1 SP cells have tumour stem cell like properties

(a) Tumour Initiation (b) Spheroid growth

(d) Repopulation(c) 2D colony formation

Rizzo et al, 2011

Group Gene setGene set

namep value FDR Source

ES Expressed Es exp2 ES2 0.39 0.7313overexpressed in hES cells according

to a meta-analysis

NOS targets

Nanog targets

nanog 0.128 0.32ChIP array of Nanog in hES cells:

activated genes

Oct4 targets

oct4 <10-6 <10-4 ChIP array of Oct4 in hES cells; activated genes

Sox2 targets

sox2 0.128 0.32ChIP array of Sox2 in hES cells;

activated genes

NOS targets

Nos <10-6 <10-4 overlap of above three sets

polycomb targets

Suz12 targets

suz12 0.128 0.64 ChIP array of Suz12 in hES cells

Eed targets

eed 0.388 0.7313 ChIP array of Eed in hES cells

H3K27 bound

h3k27 0.254 0.645ChIP array of trimethylated H3K27 in

hES cells

PRC2 targets

prc2_targets1 0.128 0.64 overlap of three above sets

PRC2 targets

prc2_targets2 <10-6 <10-4 PRC2 repressed targets transcriptionally reactivated by DZNep

polycomb complex

PRC1polycomb complex1

0.258 0.645 polycomb complex1 genes

PRC2polycomb complex2

<10-6 <10-4 polycomb complex2 genes

EZH2 and ABCB1 expression is increased in Side Population from patient ascites

Patient Ascites sample number

Ratio of expression of ABCB1 mRNA SP:non-SP

Ratio of expression of EZH2 mRNA SP:non-SP

6 12.9 14.5*

7 3.1 4.2*

9 8.4 1.3

10 16.9 1.3

14 2.9 2.1*

16 3.7 5.9*

17 57.6 8.6*

18 10.3 1.6*

19 51.8 1.1

21 36.8 3.4*

PRC2 is a protein complex that catalyses the protein methylation of lysines on histones (H3K27me3)

24 48 72 96 24 48 72 96 24 48 72 96 24 48 72 96

IGROV1

Control siRNA

PEO14

H3K27me3

EZH2 siRNA EZH2 siRNA

h.

Control siRNA

Histone H3

(b) EZH2 compounds (Chapman-Rothe, Shasaei, Rizzo, Cherblanc, Fuchter)

(a) EZH2 knock-down using SiRNA (Rizzo et al., 2011)

Does targeting EZH2 reduce sustaining/ stem cells?

Beta-actin

EZH2

H3K27me3

untre

ated

TG3-

178-

2TG

3-17

8-1

TG3-

213-

2TG

3-21

4-1

TG3-

179-

1

EZH2 as a potential anti-cancer target ?

• Many genes in cancer, including tumour suppressor genes, are epigentically silenced by mechanisms associated with H3K27me3 which can be independent of DNA methylation (Kondo et al Nat Genet, 2008; 40: 741-750)

• H3K27me3 is somatically inherited during cell division (Margueron et al Nature, 2009. 461: 762-7)

• Repressive chromatin marks in tumour stem cells may make genes vulnerable to CpG island DNA methylation (Ohm et al 2007, Nat Genet, 39; 237-242)

• EZH2 is frequently over-expressed in a wide variety of tumour types and is driver of metastasis (Min et al Nature Medicine 2010, 16: 286-94)

• EZH2 is essential for Glioblastoma cancer stem cell maintenance (Suvà et al, Cancer Res 2009 69:921)

23

GOG 218 and ICON-7: results• both trials are positive, with highly significant

improvements in progression-free survival

• overall survival analysis immature (too few events)

• no new safety concerns (hypertension in >20%; bowel perforation in <2%)

• and yet ....

• both trials are positive, with highly significant improvements in progression-free survival

• overall survival analysis immature (too few events)

• no new safety concerns (hypertension in >20%; bowel perforation in <2%)

• and yet ....

↑Burger et al. GOG study - presented at ASCO, Chicago, 2010.

Perren T et al. (ICON-7) – presented at ESMO, Milan 2010.

GOG investigator analysis used CA125/RECIST-determined progression. If data censored for CA125, median PFS for Arm I and III increase to 12.0 m and 18.2 m, respectively.

GOG investigator analysis used CA125/RECIST-determined progression. If data censored for CA125, median PFS for Arm I and III increase to 12.0 m and 18.2 m, respectively.

→

CpG island methylation as a biomarker

• Stable in vivo and ex vivo

• Sensitive PCR based assays for single loci

• Array based methods for genome wide patterns

• Aberrant tumour methylation can be detected in tumour DNA in accessible body fluids

DNA Methylation Prognostic Biomarkers in Wnt signalling pathway

Red: SGCTG cohort & TCGA cohortBlue: SGCTG cohort onlyOrange: Absent in TCGA cohort

Dai et al 2011

Systematic analysis of other pathways

Pathway/ family

genes

  Multivariate PFS analysis (n=111)

  HR 95% CI adjusted p value

AKT/mTOR

VEGFA   13.8 (0.9, 210.8) 0.06+

AKT1   27.2 (2.2, 329.1) 0.009**

VEGFB||DNAJC4 16.2 (1.6, 162.1) 0.018*

p53

BAI1 33.8 (1.3, 866.5) 0.033*BAX 1.7 (0.7, 4.3) 0.234

LRDD 21.2 (1.8, 250.5) 0.016*CCND1 4.6 (0.5, 37.9) 0.161

BRCA1/2HDAC4   4.7 (0.7, 32) 0.110HDAC11 7 (1, 47.8) 0.048*

RedoxPRDX2 2.8 (1.5, 5.5) 0.002**TR2IT1 28.4 (2.3, 352.4) 0.009**

MMRLIG1   1.8 (1.0, 3.5) 0.644MLH3   218.6 (7.7, 6.2x103) 0.002***

HRLRRC14||RECQL 45.4 (0.4, 4.6x103) 0.105

Table 3: Multivariate progression free survival analysis of loci significantly associated with Progression-free survival in univariate analysis

Dai, Zeller, et al

Epigenetics Unit Teams & support

Imperial College:

Tumour DNA Methylation Profiling

• Constanze Zeller

• Elizabeth Evans

• Jenny Quinn

• Jens Teodoridis

• Janet Graham

• James Flanagan

Chromatin targets

• Nadine Chapman-Rothe

• Ely Shamsaei

• Fanny Cherblanc

• Matt Fuchter

Bioinformatics• Wei Dai

Tissue collection• Sadaf Ghaem-Maghami, Nona

Rama, Amy Ford, Nicole Martin

Institute of Cancer Research:

Epigenetics (stem cell) team

• Sian Rizzo

• Alessandra Silva

• Jenny Quinn

• Louisa Luk

• Prof. Stan Kaye

• Gary Box, Sue Eccles

• Ian Titley, Gowri Vijayaraghavan

• Craig Carden, Debbie Tandy