Discovery of two identities of neuroblastoma cells via the...
Transcript of Discovery of two identities of neuroblastoma cells via the...
Discovery of two identities of neuroblastoma cells via the analysis of super-enhancer
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Valentina BOEVA
Computational (Epi-)Genetics of Cancer Institut Cochin, Inserm U1016 / CNRS UMR 8104 / Université Paris Descartes UMR-S1016
Introduction in neuroblastoma
NB = Pediatric cancer (avg. age 18 months)
Neuroblastoma may be found in the adrenal glands and paraspinal nerve
tissue from the neck to the pelvis
MYCN amplification
Acetylation H3K27 modifications
NB cells with MYCN may be sensitive to “epigenetic” drugs: • CDK7 inhibitor (THZ1) – MYCN amplified
tumors
• BRD4 inhibitors (I-Bet726, I-Bet151, JQ1)
Initial aim: Profile super-enhancers in neuroblastoma cell lines and discover core transcriptional regulatory circuitries
• Neuroblastoma: 25 cell lines
& 6 patient-derived xenografts
• Normal control: Neural crest cells
• ChIP-seq data
– H3K27ac
• Gene expression: RNA-seq data
Active promoters, enhancers and super-enhancers
Model for aggressive neuroblastoma
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Collaboration with the team of Isabelle Janoueix
• Caroline Louis
• Simon Durand
• Agathe Peltier
Bioinformatics methods to work with histone modification data:
• Peak calling from ChIP-seq data
• Calling of super-enhancers based on H3K27ac peaks
Copy number
HMCan
MACS
SICER
Without copy number correction With copy number correction
LILY ROSE
http://boevalab.com/tools.html
H. Ashoor…V. Boeva, Bioinformatics, 2013 V. Boeva* … I. Janoueix-Lerosey*, Nature Genetics, 2017
Principal component analysis (PCA) based on the SE signal determines 2 groups of cell lines
Group II
Group I
V. Boeva* … I. Janoueix-Lerosey*, Nature Genetics, 2017
The two groups of neuroblastoma are driven by different transcriptional master regulators
Analysis: Motif enrichment, core-regulatory circuitries, gene expression correlation analysis in cell lines and 498 primary tumors, experimental ChIP-seq validation
Group II
Group I
PHOX2B
GATA3
HAND2
PHOX2B
GATA3
HAND2
SE
SE
SE
Super-enhancers of MYC, BCOR, MECOM, PTPRJ, etc.
FOSL1
FOSL2
RUNX1
FOSL1
FOSL2
RUNX1
SE
SE
SE
RUNX2 RUNX2 SE
PRRX1 PRRX1 SE
IRF2 IRF2 SE
… … SE
Super-enhancers of MYCN, ALK, RET, LMO1, PRKCE, EYA1, BCL11A, etc.
drive
drive
V. Boeva* … I. Janoueix-Lerosey*, Nature Genetics, 2017
Group I cells are more sensitive to chemotherapy
“Intermediate” cell lines contain cells of both types
Group II
Group I
V. Boeva* … I. Janoueix-Lerosey*, Nature Genetics, 2017
SK-N-AS (intermediate) cell line
Cell ID
1 2
The two cell types can co-exist within the same tumor
van Groningen et al, Nat Genetics, 2017
IHC for MAML3 (blue) and PRRX1 (red) in a stage 4 neuroblastoma. MAML3=the pan-neuroblastoma marker PRRX1=marker of module 2
Module 1 cells
Module 2 cells
stage 4 neuroblastoma tumor
Acknowledgements
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Emmanuel Barillot
Alban Lermine
Amira Kramdi
Isabelle Janoueix-Lerosey
Caroline Louis
Simon Durand
Tatiana Popova
Olivier Delattre
Gudrun Schleiermacher
Institut Curie, Paris
Vladimir Bajic Haitham Ashoor
KAUST, Saudi Arabia
Irina Medvedeva
Institut Cochin, Paris
1. Detection of regions enriched in H3K27ac (peak calling)
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H. Ashoor et al, Bioinformatics, 2013
Hidden Markov Model
Peaks predicted by HMCan do not show copy number bias
H. Ashoor et al, Bioinformatics, 2013 13
Copy number
HMCan
MACS
SICER
2. Detection of Super-Enhancers in cancer cells: correction for GC-content bias and variation in copy
number
Without copy number correction
2. Detection of Super-Enhancers in cancer cells: correction for GC-content bias and variation in copy
number
Without copy number correction With copy number correction
LILY: http://boevalab.com/LILY/
3. Motif detection in Super-enhancers
Super-enhancers are too large to look for enriched motifs
Better approach: Discovery of enriched motifs in valley regions of H3K27ac peaks in super-enhancers
Valleys
H3K27ac
Motif hits
NB cell line
3. Motif detection in Super-enhancers
Super-enhancers are too large to look for enriched motifs
Better approach: Discovery of enriched motifs in valley regions of H3K27ac peaks in super-enhancers
Valleys
TF binding (ChIP-seq)
H3K27ac
Motif hits
NB cell line
LILY: http://boevalab.com/LILY/
Some maths for SE score normalization 1. Real SE in a diploid region:
ChIP signal: X1 reads
Corresponding input signal for this diploid region: X2 reads.
ROSE score: X1-X2
our score: ~(X1/1-X2/1)=(X1-X2)/1 = X1-X2
correction of 1 corresponds to a diploid region (copy number is equal to the main ploidy)
2. an enhancer in a diploid region (here I suppose that there are k times less signal compared to SE:
ChIP signal: X1/k reads
Corresponding input signal for this diploid region: X2 reads.
ROSE score: X1/k -X2
our score: ~( X1/3/1 -X2/1)= X1/k -X2
3. SE in the MYCN region present in 100 copies instead of 2:
ChIP signal: X1*50 reads
Corresponding input signal for this diploid region: X2*50 reads.
ROSE score: X1*50 -X2*50 = 50*(X1-X2)
our score: ~(X1*50/50-X2*50/50)= X1-X2
4. No SE/enhancer in the MYCN region present in 100 copies instead of 2:
ChIP signal: X1*50/k reads
Corresponding input signal for this diploid region: X2*50 reads.
ROSE score: X1*50/k -X2*50 = 50*(X1/k-X2)
Our score: ~(X1*50/50/k-X2*50/50)= X1/k-X2
The same with values X1=400, X2=40 and k=4: 1. ROSE: 360 Our score: 360 2. ROSE: 60 Our score: 60 3. ROSE: 18000 Our score: 360 4. ROSE: 3000 Our score: 60
Neuroblastoma Super-Enhancers defined by H3K27ac peaks are occupied by PHOX2B, HAND2 and GATA3
• Top SE sorted according to the average SE score
• Intersection with TF binding sites defined in CLB-GA
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Perc
enta
ge
Top super-enhancers
Binding by
HAND2, PHOX2B and GATA3 bind closely located regions within enhancers and SEs
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10,000 strongest HAND2 binding sites (ChIP-seq)
HAND2, PHOX2B and GATA3 bind to a MYCN enhancer
MYCN
HAND2
PHOX2B
GATA3
H3K27ac
enhancer FANTOM5 MYCN and DDX1 enhancer
Gene expression linearly correlates with SE score (in Log scale): examples
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NB cell lines
Control samples
Other cancer cell lines
DNMT expression can be a CIMP driver in ACC
• DNMT1 and DNMT3A expression is increased in CIMP-high patients
DNMT1, but not DNMT3A expression, is correlated with proliferation
TCGA
Proliferation score
Ge
ne
exp
ress
ion
Cochin
We are hiring post-docs
Cancer epigenetics research projects
• Method development
• High-throughput data analysis and data mining
• Experimental validation
NB genes with super-enhancers tend to associate with neuronal differentiation
• Functional annotation of neuroblastoma Super-Enhancers:
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GO:0030182 neuron differentiation GO:0022008 neurogenesis GO:0048483 autonomic nervous system development GO:0045664 regulation of neuron differentiation GO:0045202 synapse
Gene expression linearly correlates with SE score (in Log scale): examples
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NB cell lines
Control samples
Other cancer cell lines
Gene expression linearly correlates with SE score (in Log scale): for 1003 SE regions detected in at least 2 NB samples
P-value<0.05
Pearson correlation test on 20 NB cell lines + 2 hNCC
Is there any difference in CRCs in MYCN amplified NB?
35 Chipumuro et al, Cell, 2014
Cancer cells with a specific SV have a specific epigenetic profile (super-enhancers)
These cells are sensitive to a specific drug (CDK7-enhibitor)
SH-S
Y5Y
Kel
ly
Normalization by HMCan does not suggest any “significant” difference in SEs between MYCN-amplified and MYCN non-amplified NBs
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MYCN-amplified (top) vs MYCN non-amplified (bottom) cell lines: SE in GATA2
Normalization by HMCan does not suggest any “significant” difference in SEs between MYCN-amplified and MYCN non-amplified NBs
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SE score
Super-enhancers with differential score between MYCN-amplified and MYCN non-amplified NBs
38 With FDR adjustment: no significant regions (Wilcoxon rank test)
P-value <0.01
ChIP-seq technique can provide information about modifications of histone tails
+ Control (e.g., input DNA)
35-100bp
A cluster of reads (peak) in the UCSC genome browser
ChIP-seq = chromatin immunoprecipitation + sequencing
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Mains steps of ChIP-Seq technique:
PHOX2B is critical for the growth of neuroblastoma cells of noradrenergic type
PHOX2B expressed
PHOX2B inhibited with shRNA
CLB-GA cell line Caroline Louis
Analysis of ChIP-seq data: density profile calculation
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chromosome
reads
density
4 2 binned density
We calculate the density both for the ChIP and control sample
0 .wig file
Nebula: web-service for analysis of ChIP-seq data
Statistics for external connections to Curie
Nebula Nebula
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Nebula: web-service for analysis of ChIP-seq data
• Peak calling
• Calculation of the density and cumulative distribution of peak locations relative to gene transcription start sites
• Annotation of peaks with genomic features and genes with peak information
0.0
0.2
0.4
0 0.5 1 1.5 2
down-regulated
no-response
up-regulated
Distance from TSS (Kb)
Pro
port
ion o
f genes w
ith a
peak
at
a g
iven d
ista
nce (
cum
ula
tive)
-2000 -1000 0 1000 2000
2e-0
76e-0
7 ChIPControl
Distance from TSS (bp)
Pro
port
ion o
f genes w
ith a
peak
at
a g
iven d
ista
nce (
density)
Enh. Prom. Imm.Down. Intrag. GeneDown. F.Intron Exons 2,3,etc.Introns E.I.Junctions
Pro
port
ion o
f genes w
ith a
peak
0.0
0.1
0.2
0.3
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0.5
down-regulated
no-response
up-regulated
Control
10 20 30 40 50
1100
10000
Peak height
Peak c
ount
ChIPControl
GeneDown. Enh. Imm.Down. Interg. Intrag. Prom.
Pro
port
ion o
f peaks
0.0
0.1
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0.3
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ChIP
Control
D E
C B A
Some graphs produced produced by Nebula
V. Boeva, A. Lermine et al, Bioinformatics, 2012 43
Disruption of the genomic sequence in cancer can affect epigenetic profiles
• Mutations and structural variants (SVs) in cancer genomes
– Disruption of epigenetic profiles by mutation of epigenome-regulatory proteins (readers, writers or erasers)
– Disruption of regulatory elements
– Disruption of interactions between genes and regulatory elements
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What transcription factors may be involved in the formation of NB-specific super-enhancers?
• Likely candidates: TCF12 (that interacts with Hand2), PBX3, JUND, GATA2 and GATA3 together with many others TFs (ChIP-seq experiments are ongoing)
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CTCF JUND PBX3 TCF12 GATA2 GATA3 H3K27ac (SK-N-SH) H3K27ac (SHSY-5Y) Super enhancer Genes
ENCODE DATA
• CDK7 inhibitor (THZ1) – MYCN amplified tumors
Neuroblastoma cells have been shown to be sensitive to CDK7 inhibitor
Chipumuro et al., Cell, 2014
Suggested mechanism: desactivation of super-enhancers created by MYCN
• CDK7 inhibitor (THZ1) – MYCN amplified tumors
Neuroblastoma cells have been shown to be sensitive to CDK7 inhibitor
Chipumuro et al., Cell, 2014
Suggested mechanism: desactivation of super-enhancers created by MYCN
HMCan normalization of the same data
• MYCN high or MYCN amplified tumors
• MYCN low or MYCN WT tumors
• 650 cancer cell lines
Neuroblastoma cells have been shown to be sensitive to BRD4 inhibitor JQ1
Puissant et al., Cancer Discov. 2013
Molecule Mechanism Cancer
JQ1, I-Bet151, I-Bet762 – BRD4 multiple myeloma, Merkel cell carcinoma, castration-resistant prostate cancer, ER+ breast cancers, ovarian carcinoma, human osteosarcoma (+rapamycin)
THZ – CDK7 T-ALL, basal breast cancer, neuroblastoma, AML
Pivanex, Valproate, TSA, Vorinostat, Romidepsin
– HDAC prostate, endometrial and cervical carcinomas, leukemias and lymphomas
Suramin, Cambinol – SIRT1 & SIRT2 lymphomas, prostate, lung and breast cancer
5-Azacitidine, Zebularine, RG108
– DNMT1 hepatocellular carcinoma, breast cancer, prostate cancer, renal carcinoma (+ interferon α-2β)
DZNep, EPZ-6433 GSK126, EI1 – PRC2 prostate cancer, neuroblastoma
A variety of compounds reverse epigenetic changes
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