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Predictive DNA methylation markers for
platinum response in cancer
Dr. Inmaculada Ibáñez de Cáceres
Experimental therapies and biomarkers in cancer.
Group 33 IdiPAZ
Going to the origins
La Paz University Hospital (HULP)
1964
Hospital with the best reputation in Spain in 2014 and 2015
Referral Center
Other, national reference
H Cruz Roja
H Infanta Sofia
H. Carlos III
Daily turnover
Total: 27.000 people
6.000 Patients (in- and out-patients, emergencies)
7.000 staff
12.000 Relatives and Visitors
2.000 external (providers, contractors…)
500 Students
H. Cantoblanco
Going to the origins
La Paz University Hospital (HULP)
1964
IdiPAZ
UAM
2009
The Institute for Health Research of La Paz University Hospital (IdiPAZ)
The first one to be accredited by National Health System ISCIII in Madrid
Re-accredited May 2015
Internationalization
IdiPAZ participates in the National strategy for
internationalization that is based on the ESFRI (European
Strategy Forum on Research Infrastructures) roadmap
promoted by the European Union for generate initiatives
of scientific facilities.
With in this European strategy, IdiPAZ participates in:
•ECRIN –The European Clinical Research Infrastructure Network for Clinical Trials
and Biotherapy.
•EATRIS– The European Advanced Translational Research Infrastructure in
Medicine.
•BBMRI –Biobanking and Biomolecular Resources Research Infrastructure.
Applications from Postdoctoral Researches with 4 years experience are Welcome
based in an Institutional Internationalization Strategy----
Scientific structure of IdiPAZ
49 groups and 6 strategic areas
Cancer Epigenetics group
Epigenetic Mechanisms
2008: Cold Spring Harbor meeting. Epigenetics is the study of heritable changes in
gene activity which are not caused by changes in the DNA sequence.
Molecular Biology Dogma
Epigenetic mechanisms
Epigenetic mechanisms
•DNA Methylation
DNMTs
Expresión del gen reprimida
Isla CpG
CpG
Isla
gen
TET
citosina
5-metilcitosina
Human genome has only 10% expected CpGs, 70-80% of these are
methylated
Small CpG-rich regions of DNA, 1-2%, CpG islands protected against
methylation & associated w/transcription in 50% of human genes
Two cases of healthy cell regulation:
Female X Chr. inactivation, genomic imprinting
Methylation patterns altered in cancer cells, hypo- and hyper-methylation
Aberrant changes in the methylation pattern
Aberrant hypermethylation on promoter CpG islands:
Appears:
Early stage
Aggressive phenotype
“De novo”: -radiation
-smoking
-drugs exposure
Induces TSG transcriptional
repression ≈ mutations and LOH
DNA methylation markers
-Early in carcinogenesis, even when samples are histologically negative for cancer.
N. lymph nodes—show positive methylation for p16
-Ubiquity of aberrant methylated DNA
-Reversibility of epigenetic changes through pharmacological manipulation:
FDA: DNA methyltransferase inhibitors: *5-azacytidine (Vidaza)
*decitabine (2-deoxy-5-azacytidine, Dacogen)
HDAC inhibitors: *suberoylanilide hydroxamic acid (SAHA, Zolinza)
*romidepsin (Istodax)
Blood, Broch. f
-Technologies able to detect DNA methylation in body fluids
sputum, saliva
ed in our laboratory
T
Bisulfite
Sequencing
NimbleGen
SeqCap Epi
qMSP
Gene vs End.
NGS
WGBS
2002
2005
2012
MSP
qMSP
Methylight
2013
2015
H-methylation
450k
2016
Epigenetic biomarkers predicting chemotherapy response
•CDK10
Breast
Sensitivity to tamoxifen
•CHFR
Gastric
Sensitivity to microtubule
polymerization inhibitors
•FANCF
Ovarian
Sensitivity to CDDP and mitomycin C
•hMLH
Colon/ovarian
Resistance to 5-fluoracilo and CDDP
•IGFBP-3
Lung
Resistance to CDDP
•MGMT
Glioma
Sensitivity to alkylating agents
Methylation and chemotherapy
response prediction in cancer:
-mIGFBP-3 and Lung cancer
-A miRNA approach
Cisplatin Treatment
Pt
Pt
Pt
Pt
Extracelular matrix
MDR
Pt
Pt
Cytoplasm
Pt
Pt
- DNA damage
- DNA repair inhibition
- Oxidative stress
Nucleus
Platinum
First-line
Ac
Me
Me
Ac
Aberrant histonemodifying enzymes
regulation/expression:
Me
Ac
Aberrant expression of
miRNAs targeting
epigenetic regulators:
- HDACs
- H Demethyl
Me
-KATs
Aberrant gene
expression
- KMTs and PRMTs
E.g.: DNMTs,
E.g. miRNAs:- miR29, miR-101, miR-138,
miR-181, etc
E.g. target mRNAs:
DNMTs, KMTs, Bax,
Bal,
M. Cortés-Sempere et al.
NSCLC
Ovarian
Testicular
bladder
Experimental model: Cisplatin-Resistant NSCLC
Cell lines
Gene selection strategy
5-Aza-dC
H23
H460
W.T.
Inhib.
H23R
H460R
H23R
H460R
Resistant
Resistant
Reexpres.
TSA
Resistance-specific-methylation-gene: IGFBP-3
IGFBP-3 Methylation is causative and not a
consequence of CDDP-resistance
IGFBP-3 methylation status correlates
with CDDP-response in primary samples
N
Methylate Unmethylat
d
ed
P
Sensitiv Resista
e
nt
p
Stage
Stage I
22
(61.1)
Stage II
13
(36.1)
Stage Unknown 1 (2.8)
12
10
4
0.172
7
15
9
9
4
0
1
1
0
0
9
0.04
3
TNM
T1
9 (25)
6
3
T2
22
(61.1)
4 (11.1)
9
13
13
9
1
3
3
1
1 (2.8)
0
1
1
0
26
(72.2%)
9 (25%)
13
13
10
16
3
6
6
3
1 (2.8)
0
1
1
0
9
13
11
11
4
6
5
5
3
1
1
3
T3
T Unknown
N0
N1
N Unknown
0.288
0.460
0.00
5
0.24
5
Histology
Epidermoid
22
(61.1)
Adenocarcinom 10
a
(27.8)
Large Cell
4 (11.1)
0.427
0.64
In vitro resistance to cisplatin
Resistant
Sensitive
19
(52.8)
17
(47.2)
14
5
2
15
<0.00
1
Ibanez de Caceres I, et al. Oncogene 2010; 29(11):1681-90.cited12. (3 Nature)
AKT phosphorylation: 41S/R, H460S/R, H23S/R
41
p-AKT
IGFBP-3
AKT
PTEN
tubulin
IGF-I
IGF-I
IGF-I
H460
IGF-I
IGF-I
IGFBP3
IGFIR
R
K
K
IGFBP-3
AKT
R
PI3-K
p
p-AKT
CDDP
PIP2
PIP3
p
PIP2
PTEN
AKT
p
PTEN
p
tubulin
H23
Survival
p-AKT
IGFBP-3
AKT
PTEN
tubulin
CDDP
(µg/ml)
0 0.5 1 1.5 2 3
S
0 0.5 1 1.5 2
R
3
IGFBP-3 expression, pAKT and CDDP response
bp
bp
41S
ø
41R-IGFBP-3
41R-pCMV5
300
300
IGFBP-3
IGFBP-3
200
200
GAPDH
0
41R-pCMV5
1
2
3
0
1
2
3
41S-pCMV5
41R-IGFBP-3
41R
pAKT
AKT
pTEN
41R+pMCV5 (ø)
100
41R+IGFBP-3
41S+pCMV5 (ø)
75
50
25
0
tubulin
1
2
3
0
1
2
3
0
1
GAPDH
100
Cell viability
% of Untreated Controls
100
CDDP
(µg/ml)
CDDP
0
(µg/ml)
41R 41S
41R
ø IGFBP-3 ø
ø IGFBP-3
2
3
0
0.5
1
1.5
CDDP (µg/ml)
2
IGFIR is active only in CDDP resistant cells
IGF-I
IGF-I
IGF-I
IGF-I
IGF-I
CDDP
IGFBP3
IGFIR
R
R
PI3-K
p
K
K
PIP2
PIP3
p
PIP2
PTEN
AKT
p
p
Survival
Cortés-Sempere M, et al. Oncogene 2013; 32(10):1274-1283
Platinum
NSCLC (80% LC)
Ovarian
Testicular
bladder
•
Stage III with affected nodes
•
It is not possible to predict the
response
• There are not molecular markers
Radiotherapy
IDEA GENER
CONCEPT
DEVELOPMENT
TESTING
ATION
3
2
4
PRODUCT LIFE-CYCLE
1
5
RESEARCH &
ANALYZE
2
Based in our previous
results
3
IGFBP-3m and
Radiotherapy
DEPLOYMENT &
MAINTENANCE
RT reactivates the IGFBP-3 expression
Survival Functions
Methylation status=Methylated
Cumulative Survival
RT
NO-RT
RT-censored
NO-RT-censored
OS (days)
Pernia, et al. Epigenetics. 2014 Nov;9(11):1446-53.
Methylation status of IGFBP-3 as a useful clinical tool for deciding on a
concomitant radiotherapy
Pernia, et al. Epigenetics. 2014 Nov;9(11):1446-53.
Intellectual property strategy
Commercialization
Patent
Cooperation Treaty
(PCT)
May 2014
Application filing
• Licenced to a
National Company
•Developing Kit
for clinical Use
National Phases
(EEUU/EU)
Nov & Dec 2015
Commercialization
Funding at a national level:
Pre-commercial public
purchasing.
Horizon 2020
Validation steps
National Health System-Company
Extending the study to other tumor types treated with platinum and RT:
Colorectal, ovarian
Methylation and chemotherapy
response prediction in cancer:
A miRNA approach
Epigenetic mechanisms: Non coding RNAs
-Short ~22nucleotide long non coding RNA mol. encoded in the genome.
-Posttranscriptional regulation by targeting the 3´UTR of specific RNA: Direct mRNA degradation
Translational inhibition.
-Little is know about regulation of their expression: DNA-methylation
microRNAs
Intergenic
miARN
Unmethylated
Isla CpG
exón
miARN
Isla CpG
Methylated
miARN
exón
intragenic
or intronic
miARN
Isla CpG
exón
miARN
exón
miRNAs: Exponential biological sense
miRNA
Chemoresponse prediction: miRNAs
miRNAs under epigenetic regulation in cancer
miRNAs and chemotherapy response
Cortés-Sempere M, et al. Clin Transl Oncol. 2011; 13(6):357-62
Cancers 2011, 3, 1426-1453; doi:10.3390/cancers3011426
Chen Y et al. Mol Med Rep. 2013 May;7(5):1579-84
Experimental mode and strategy for miRNA selection
NGS
RNA-seq
miRNA-seq
WGBS
Validation on selected miRNA candidates
Relative expression (Log10)
1
a
RT
-1
-2
-3
1
miR-7
miR-132
miR-335
miR-B
miR-148a
miR-C
b
miR-9
miR-D
miR-E
miR-124
miR-F
H460
0
-1
miR-7
miR-A
1
c
miR-132
miR-B
miR-335
miR-C
miR-148a
miR-D
miR-9
A2780
1
0
-1
-2
miR-7
miR-A
miR-132
miR-B
miR-124
miR-C
miR-10a
miR-D
miR-124
miR-E
Relative expression (Log10)
Relative expression (Log10)
R
0
miR-A
Relative expression (Log10)
S
H23
miR-F
d
miR-10a
miR-G
OVCAR3
0
-1
miR-132
miR-E
miR-124
miR-F
miR-X methylation can play a role in the early establishment of NSCLC tumorigenesis
36 and 39 NSCLC cohorts
985 samples from TCGA
A. Emphysemas (10)
117
U M
118
120
122
124
U M U M U M U M
L.N
U M + H20
B. PBMCs (10)
238
U M
476-CpG-1
+
4762
-C3p9
G-2
240
241 47264-C2pG-3-7 L.N
U M U M U M U M U M H20
C. Normal lung tissue (10) + bronchioalveolar c. line
+
U
LC1
M
U
LC2
M
U
BCLM H20
miR-X methylation appears to play an important platinum-predictive role in ovarian cancer
86 ovarian samples, H. del Mar
Barcelona
31
7
82
U M U M U M
29
46
O.N
H20
U M U M U M +
Normal ovarian tissue (4)
+
OC1
U M
OC2
U M
OC3
U M
OC4
U M H20
miR-X methylation appears to play an important platinum-predictive role in ovarian cancer
47 IdiCHUS. Galicia
mRNA-miRNA candidate validation
Mimic del miR-4
3
’
5’
3
’
5’
Expresión luciferasa/renilla/proteína
1.5
**p<0.01
*p<0.05
1
*
**
0.5
0
Mimic 74
Mimic CN
Mimic 74
Mimic CN
15nM
30nM
Luciferi
na
L
U
Z
Luciferi
na
L
U
Z
Log10 de RQ miR-4
3'UTR MAFG
4
3
2
1
0
-1
Mimic
CN
Mimic 47
Mimic
CN
15nM
Mimic 47
30nM
3'UTR control
Mimic
CN
Mimic 47
Mimic
CN
15nM
Mimic 47
30nM
3'UTR MAFG
miRNAs as therapeutics
-Candidate miRNA with a potential therapeutic role in cancer for further experimental approaches
-Advantages of miRNAs & anti-miRNA as therapeutics:
-organic composition,
-natural metabolism,
-lower toxicity and immune reactions
-The development of carriers for selective and efficient
delivery of those biotherapeutics.
Intellectual property strategy
•Priority patent filed in
OEPM on 07/09/2015
•Authors and
applicants assessment
•Co-ownership
contract
Invention disclosure
Prior art search
• Preliminary search
done in-house
•
Patent Cooperation
Treaty (PCT)
ES2016/070516
07/07/2016
• Patent agent
Application filing
Commercialization
• Validation,
development and
distribution
• Searching
for
licensees
Other basic and translational strategies
RNA-seq
microRNA-seq
Ovarian
Ovarian
LUNG
5 NORMAL
Lung
5 NORMAL
5 TUMOR
5 NORMAL
9 TUMOR
Lung
RNA-seq
GBS
W
2 SENSITIVE CELLS
32
Ovarian
RNA-seq
450K (Methylation MICROAR
microRNA-seq
24
Methyl-seq
6
Ovarian
2 RESISTANT CELLS
7+5 TUMOR
Bioinformatics Scoring Matrix
9 TUMOR
Lung
1+5 NORMAL
2 RESISTANT CELLS
microRNA-seq
Methyl-seq
Ovarian
1 NORMAL
SENSITIVE CELLS
4 TUMOR
RAYS)
MOF
Albert
Cris
Fernando López-Ríos
Dpt. Cancer
Dpt. Molecular Oncology
Thomas A. Sellers
Jin Q. Cheng
CNIC
Dpt. Genomics
Ana Dopazo
Fátima Sánchez
FCCC, USA
Dpt. Surgical Oncology
Paul Cairns
H. La Paz
Dpt. Medical Oncology
Dpt. Pathology
Javier de Castro
Virginia Martínez
Isabel Estéban
H. Del Mar//Fundación Jiménez Díaz
Dpt. Medical Oncology
Dpt. Pathology
Joan Albanell
Ana Rovira
Federico Rojo
41M/R
H460S/R
H23S/R
A2780S/R
OVCAR3S/R
microRNA-seq
RNA-seq
Ovarian-18
Ovarian-10s
5 NORMAL
Lung-14s
5 NORMAL
5 TUMOR
WGBS
2 Sensitive Cell lines
12 TUMOR
450K methylation Arrays
Ovarian-4 samples
2 Resistant Cell lines
5 NORMAL
9 TUMOR
9 TUMOR
Lung-4 samples
6 NORMAL
Lung-14
2 Resistant cell lines
Ovarian-5 samples
1 NORMAL
2 Sensitive Cell lines
4 TUMOR
A
A2780
100
Viabilidad (%)
100
ViabilidaD (%)
S-Ø
S-MAFG
R-Ø
H23
75
50
S-Ø
S-MAFG
R-Ø
75
25
0
0
1
2
3
4
Concentración de CDDP (μg/ml)
Log10 de RQ
0.40
RNAm
1.20
0.70
0.20
0.20
0.00
S-Ø
R-Ø
S-MAFG
-0.30
-0.20
C
Log10 de RQ
B
A2780 (72h)
1.70
H23 (72h)
0.60
Proteína
S-Ø
R-Ø
S-MAFG