The Chromatin-Looping Factor ZNF143 is Genetically Altered ... · Furthermore, we show that the overexpression of looping-factors within ESR-1 positive BrCa patients associates with
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The Chromatin-Looping Factor ZNF143 is Genetically Altered and Promotes the Oestrogen Response in Breast
Cancer
by
Aislinn Treloar
A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Medical Biophysics
(H3K4me3), H3K4me1, H3K27me3, H3K9me3 and H3K36me3 generated in E2-stimulated MCF-7
cells (Joseph et al. 2010; Magnani et al. 2013; Li et al. 2013). We applied a 12-state chromatin model
to segment the genome and then grouped predicted functional elements as promoters, enhancers,
transcribed, repressed, CTCF or no signal regions (Supplementary Figure 2). In agreement with reports
revealing a strong enrichment for ZNF143 binding at promoters in other cell types (Bailey et al. 2015),
we find 38,320 (43%) ZNF143 bound sites at promoters (Figure 1A, lower panel). An additional
16,232 sites (18%) map to enhancers, 3,173 sites (3.6%) to transcribed regions, 2,073 sites (2.3%) to
10
repressed regions, 7,410 (8.3%) to CTCF regions, and the remaining 22,486 sites (26%) fall in regions
with no signal in our ChromHMM segmentation model (Figure 1A, lower panel). The bias of ZNF143
binding at promoters is further highlighted by its significantly increased binding intensity at promoters
over other genomic regions (Figure 1B).
ESR1 recruitment to the chromatin following E2-stimulation in MCF-7 cells has previously been
reported to occur primarily away from promoters (Carroll et al. 2006; Lin et al. 2007; Welboren et al.
2009). These assessments were performed based on the position of annotated genes across the
reference human genome as opposed to chromatin states. Indeed, using this approach, we map less than
5% (1,168) ESR1 binding sites to promoters (Figure 1C, upper panel). However, the proportion of
ESR1-bound promoters increases to 27.4% (6,406 sites) when using chromatin state to define genomic
elements in MCF-7 cells (Figure 1C, lower panel). ESR1 binding is still predominantly (33.8%; 7,907
sites) found at enhancers (Figure 1C) and further assessment of ESR1 called peaks indicates that only
10% of binding sites are within ±2.5kb from the TSS of coding genes; this is in line with reports of a
subset of ESR1 binding sites that are called in proximity of promoters when co-localized with CTCF
(Ross-Innes et al. 2011). The majority of ESR1 sites that are called in promoter regions are so far un-
annotated and do not fall within ±2.5kb of TSS of lncRNAs or coding genes.
Comparing ZNF143 and ESR1 binding profiles reveals over 8,671 shared binding sites (Supplementary
Figure 3). This translates into 72% of ESR1-bound promoter regions occupied by ZNF143 prior to and
after E2-stimulation (4,782 of 6,647 ESR1 promoter bound regions)(Figure 1D). Over 36% of ESR1-
bound enhancers are also occupied by ZNF143 binding in MCF-7 cells but transcribed, CTCF and
repressed ESR1-bound regions show minimal overlap with ZNF143 binding sites (15%, 4% and 18%
of ESR1 sites, respectively) (Figure 1D). We find that ESR1 binding is significantly stronger at
enhancer regions than promoters occupied by ZNF143 (p=1x10-3). In contrast, ZNF143 binds the
ESR1–bound promoters with greater affinity (p<1x10-3) compared to enhancers (Figure 1E). These
results are in line with primary ESR1 binding occurring at enhancers, while primary ZNF143 binding
occurs at promoters.
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Figure 1
Figure 1: Genome-Wide Binding of ZNF143 Suggests a Role in E2-Induced ESR1 Recruitment to Promoter Elements
Scatterplot comparing read count for ZNF143 binding in MCF-7 breast cancer cells treated with vehicle or E2 (10µM) for 45 minutes. Scatterplot was generated with SeqMonk (http:/www.bioinformatics.babraham.ac.uk/projects/seqmonk/) from ZNF143 ChIP-sequencing data. R, Pearson’s correlation, was calculated from all data points (Upper Panel). Genomic distribution of ZNF143 binding events in MCF-7 cells. Chromatin states were annotated by the ChromHMM algorithm (Supplemental Figure S2) (Ernst et al. 2012) (Lower Panel) (A) . Boxplots representing the signal intensity (MACS score) for ZNF143 at promoter, enhancer, transcribed, CTCF ad no-signal regions of the genome. P-value was calculated using the Mann-Whitney test (B) . Global genomic distribution of ESR1 binding events called in MCF-7 cells under E2 stimulation. Genomic elements were annotated by the Cis-Regulatory Element Annotation System (CEAS) web application (cistrome.org/ap) or by the ChromHMM algorithm (Supplemental Figure S2 (C) . Histogram illustrating the proportion of ESR1-bound sites that are occupied by ZNF143 at promoters, enhaners, transcribed, repressed and CTCF regions(D) . Boxplots showing the signal intensity of ZNF143 and ESR1 at shared binding sites called in promoters or enhancers, as defined by ChromHMM. P-values were calculated using the Mann-Whitney test (E). (*p<0.05; ** p<0.01; *** p<0.001)
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3.2 ZNF143 directly regulates oestrogen-target gene transcription in ESR1-positive breast cancer cells
To determine how ZNF143 occupancy relates to chromatin interactions at E2-regulated promoters, we
first defined E2-responsive genes as genes whose expression, measured by RNA-sequencing (RNA-
seq), is significantly altered following E2-stimulation for three hours (FC > 1.5; p=0.05). This
identified 194 E2-regulated genes (Supplementary Table 1). We then mined the RNA Polymerase II
(RNA Pol II) Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) dataset (Li
et al. 2012) to identify E2-upregulated gene promoters that form chromatin interactions. A total of 223
promoters ascribed to the 194 E2-regulated genes were assessed in this analysis. We identified 137
(61%) E2-upregulated genes with at least one chromatin interaction anchored at the promoter (±2.5
kilobases (kb) from the Transcription Start Site (TSS)) (Figure 2A, upper panel). ZNF143 binds to 110
(80%) of the 137 E2-regulated gene promoters, a significantly higher proportion (P<1.0x10-4) than
expected by chance (Figure 2A, lower panel). These results indicate ZNF143 binding is enriched at E2-
regulated gene promoters involved in chromatin interactions, supporting a direct contribution of
ZNF143 to chromatin interactions associated with the E2-response in breast cancer.
We then further delineated the requirement for ZNF143 in the E2 response, specifically in the
regulation of E2 target gene expression. We performed RNA-seq following E2-stimulation in MCF-7
cells depleted of ZNF143 using siRNAs. We found that 91(47%) of the 194 E2-regulated genes were
no longer responsive to E2-stimulation following ZNF143 depletion (Figure 2B-C). Among the genes
whose expression remained responsive to E2-stimulation, 32 genes (16%) showed significantly reduced
expression (p<0.05) following ZNF143 depletion compared to control cells (Figure 2B-C). The impact
of ZNF143 depletion on E2-target gene regulation relates to ZNF143 binding intensity at promoters;
we found that genes unaffected by the loss of ZNF143 (No Change gene category) showed weak
ZNF143 binding at their promoters whereas genes that showed reduced expression or loss of induction
to E2-stimulation following ZNF143 depletion harboured significantly stronger ZNF143 binding at
their promoters in control conditions (p= 4.0x10-3; p=7.1x10-3) (Figure 2D). These findings suggest that
the genes that are unaffected by the loss of ZNF143 do not require ZNF143 at their promoters to
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regulate expression whereas the genes that exhibit either loss of induction or reduced expression when
ZNF143 is lost do rely on ZNF143 occupancy at their promoters. We further interrogated patterns of
mRNA expression in MCF-7 cells depleted of ZNF143 by performing Gene Set Enrichment Analysis
(GSEA) for genes whose expression was significantly down-regulated upon ZNF143 depletion (FC
>1.5, p <0.05) under E2-stimulated conditions. This revealed enrichment for early and late oestrogen
MCF-7 cells rely on E2-stimulation to activate the ESR1-regulated gene expression program, which
mediates their re-entry into cell cycle and drives proliferation. We therefore assessed the requirement
for ZNF143 in the E2-induced growth of MCF-7 luminal breast cancer cells following its siRNA-based
depletion (Figure 2E). ZNF143 depletion significantly impaired growth of MCF-7 cells under E2-
stimulation (Figure 2F), supporting its central role in the oestrogen response. Overall, these results
show that ZNF143 is required for the ESR1-mediated transcriptional response and for the E2-induced
growth response of luminal breast cancer cells.
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Figure 2
Figure 2: ZNF143 is Required for the E2-Induced Transcriptional Response
Proportion of E2-responsive gene promoters (±2.5kb from TSS) that are involved in chromatin interactions associated with RNA polymerase II in E2-stimulated MCF-7 cells (upper panel). Scatterplot illustrating the proportion of these promoters that exhibit ZNF143 binding (lower panel) (A). Volcano plot showing changes in gene expression of E2-responsive genes upon E2 stimulation in cells depleted of ZNF143 (pink) or transfected with scrambled siRNA (green).Each circle represents one gene. The log fold change in gene expression in E2-stimulated versus vehicle treated conditions is represented on the x-axis. The y-axis shows the -log10 of the pvalue. A p-value of 0.05 and a fold change of 1.5 are indicated by grey lines. Quadrants 1-6 are indicated (B). Case examples of genes that fall within quadrants 1 and 5 that illustrate gene expression changes under vehicle and E2-stimulated conditions. (RPKM: reads per kilobase per million). P-value calculated using student’s t-test. (C). Boxplots illustrating signal intensity of ZNF143 at promoters of genes that show no change, reduced expression or loss of E2-induction upon ZNF143 depletion. P-value calculated using Kruskal-Wallis test (D). ZNF143 depletion via siRNA significantly reduces its mRNA levels 48hrs post-transfection. P-value calculated using student’s unpaired t-test (E). MCF-7 breast cancer cells depleted of ZNF143 fail to grow in response to E2 stimulation compared to control cells. P-value calculated using student’s unpaired t-test (F) (*p<0.05; ** p<0.01; *** p<0.001; NS = Not Significant)
Figure 2: ZNF143 is Required for the E2-Induced Transcriptional Response
Proportion of E2-responsive gene promoters (±2.5kb from TSS) that are involved in chromatininteractions associated with RNA polymerase II in E2-stimulated MCF-7 cells (upper panel).Scatterplot illustrating the proportion of these promoters that exhibit ZNF143 binding (lowerpanel) (A). Volcano plot showing changes in gene expression of E2-responsive genes upon E2stimulation in cells depleted of ZNF143 (pink) or transfected with scrambled siRNA (green).Each circle represents one gene. The log fold change in gene expression in E2-stimulated versusvehicle treated conditions is represented on the x-axis. The y-axis shows the -log10 of the pvalue.A p-value of 0.05 and a fold change of 1.5 are indicated by grey lines. Quadrants 1-6 areindicated (B). Case examples of genes that fall within quadrants 1 and 5 that illustrate geneexpression changes under vehicle and E2-stimulated conditions. (RPKM: reads per kilobase permillion). P-value calculated using student’s t-test. (C). Boxplots illustrating signal intensity of ZNF143 at promoters of genes that show no change, reduced expression or loss of E2-induction upon ZNF143 depletion. P-value calculated using Kruskal-Wallis test (D). ZNF143 depletion via siRNA significantly reduces its mRNA levels 48hrs post-transfection. P-value calculated using student’s unpaired t-test (E). MCF-7 breast cancer cells depleted of ZNF143 fail to grow in response to E2 stimulation compared to control cells. P-value calculated using student’s unpaired t-test (F) (*p<0.05; ** p<0.01; *** p<0.001; NS = Not Significant)
15
3.3 Genetic alterations in chromatin looping factors are frequently occurring and tend towards mutual exclusivity
Pan-cancer analyses led by The Cancer Genome Atlas (TCGA) have revealed that CTCF is
significantly mutated in several cancers, including breast (Lawrence et al. 2014). Having established a
role for ZNF143 in ESR1 signalling in luminal breast cancer cells, these reports prompted us to assess
the extent of genetic alterations to the known chromatin looping factors in breast cancer. We
investigated the frequency of genetic alterations in CTCF, ZNF143 and the cohesin complex subunits
(Rad21, STAG1, STAG2, SMCA1 and SMC3) in the published and provisional breast cancer datasets
from TCGA as well as in the Primary Derived Xenograft (PDX) populations from the British Columbia
Cancer Research Centre (BCCRC) (TCGA 2012; Eirew et al. 2014). Collectively, the chromatin-
looping factors harbour genetic alterations (amplification, deletion or somatic mutation) in at least 22%
of primary breast tumours and up to 65% of PDXs derived from primary and metastatic breast tumours
(Figure 3A-B). Although we observe a trend towards mutual exclusivity between genetic alterations in
the chromatin-looping factors across samples from the TCGA provisional and published datasets, 3
gene pairs do show significant co-occurrence in the TCGA provisional dataset (Figure 1C,
Supplementary Table 3-4).
Finally, we assessed the relevance for these genetic alterations to breast cancer subtype as defined by
the PAM50 gene expression classifier (Parker et al. 2009) in the TCGA published and provisional data
sets. Although genetic alterations to ZNF143 and CTCF seem to enrich in luminal cancers (3/3 and
15/18, respectively) in the published data set, this observation is not reproduced in the provisional
dataset; genetic alterations in each of the chromatin looping factors are found in the other breast cancer
subtypes. These results suggest that in addition to the chromatin looping machinery being altered in
luminal cancers, where it is contributes to ESR1 signalling, the dysregulation of these factors may also
contribute to disease in the other breast cancer subtypes.
16
Figure 3
Figure 3: Chromatin-Looping Factors are Genetically Altered in Breast Cancer
Copy number alterations and somatic mutations in CTCF, ZNF143 and five members of the cohesin complex were analyzed in three separate breast cancer datasets. DNA amplification, deletion, mutation or multiple alterations are indicated (A). Overall frequency of genetic alterations in the chromatin looping factors specified in A, in three breast cancer data sets (B). For each breast cancer data set, the proportion of samples with genetic alterations in a single factor versus in multiple factors is indicated by the strength of colour (C). Breast cancer subtype of tumours harbouring a genetic alteration in a chromatin looping factor; subtype determined by gene expression of 50 genes (PAM50) (D). (*p<0.05; ** p<0.01; *** p<0.001)
ZNF143CTCF
Rad21
STAG1
STAG2
SMC1ASMC3
0
20
40
60
AmplificationMutationDeletionMultiple Alterations
Alte
ratio
n Fr
eque
ncy
(%)
TCGA Pub
TCGA Prov
BCCRC Xen
ograf
t0
20
40
60
80
n = 29
n = 962
n = 482
Ove
rall A
ltera
tion
Freq
uenc
y (%
)
A
BCCRC Xenograft
B
ZNF143CTCF
Rad21
STAG1
STAG2
SMC1ASMC3
0
5
10
15
20
25
AmplificationMutationDeletionMultiple Alterations
Alte
ratio
n Fr
eque
ncy
(%)
ZNF143CTCF
Rad21
STAG1
STAG2
SMC1ASMC3
0
5
10
15
20
AmplificationMutationDeletionMultiple Alterations
Alte
ratio
n Fr
eque
ncy
(%)
TCGA Prov
TCGA PubD
C
★★
★★★
★★★
★★
Co-occurence
ZNF143 (
n=3)
CTCF (n=1
8)
RAD21 (n
=67)
STAG1 (n=
8)
STAG2 (n=
6)
SMC1A (n
=4)
SMC3 (n=
1)
All Sam
ples (
n=48
2)0
20
40
60
80
100
LuminalHER2-EnrichedBasal-LikeNormal-Like
PAM50 (TCGA Published Data Set)
Tum
ours
(%)
ZNF143 (
n=13
)
CTCF (n=2
9)
RAD21 (n
=195
)
STAG1 (n=
64)
STAG2 (n=
18)
SMC1A (n
=21)
SMC3 (n=
12)
All Sam
ples (
n=96
3)0
20
40
60
80
100
LuminalHER2-EnrichedBasal-LikeNormal-LikeNA
PAM50 (TCGA Provisional Data Set)
Tum
ours
(%)
LuminalHER2-EnrichedBasal-LikeNormal-LikeNA
Copy number alterations and somatic mutations in CTCF, ZNF143 and five members of the
cohesin complex were analyzed in three separate breast cancer datasets. DNA amplification,
deletion, mutation or multiple alterations are indicated (A). Overall frequency of genetic
alterations in the chromatin looping factors specified in A, in three breast cancer data sets (B). For
each breast cancer data set, the proportion of samples with genetic alterations in a single factor
versus in multiple factors is indicated by the strength of colour (C). Breast cancer subtype of
tumours harbouring a genetic alteration in a chromatin looping factor; subtype determined by
Figure 3: Chromatin-Looping Factors are Genetically Altered in Breast Cancer
17
3.4 Differential gene expression of the chromatin looping machinery is clinically relevant and relates to genetic alterations in breast cancer
We determined the relevance of genetic alterations in chromatin looping factors to their expression by
segregating breast tumour samples based on the GISTIC-based copy-number alteration score (Mermel
et al. 2011). We observe a significant decrease in ZNF143 expression in tumours harbouring
heterozygous and homozygous deletions compared to diploid cases (p=2.0x10-3 and p<1.0x10-3
respectively) (Figure 4A), while copy number gains correlate with significantly increased ZNF143
expression (p<1.0x10-3). Similar results were obtained for all other chromatin-looping factors with the
exception of STAG2 (Figure 4A; Supplementary Table 5). These results suggest that that copy number
variations in the chromatin looping factors directly impacts their expression.
To address the clinical relevance of differential expression of looping factors in luminal breast cancer
we performed Kaplan-Meier analysis using the METABRIC dataset consisting of close to 2,000
expression profiles from independent, clinically annotated breast cancer samples (Curtis et al. 2012).
Using the KMplot tool (http://kmplot.com/private/) (Györffy et al. 2010) we segregated samples based
on low versus high levels for each chromatin looping factor. Kaplan-Meier curves focused on overall
survival reveal that ESR1-positive breast cancer patients with elevated ZNF143 expression do worse
than those with low expression levels (p=1.1x10-3) (Figure 4B). This observation is valid across all
ESR1-positive breast cancer patients as well as within luminal A or B subtypes (p=4.3x10-2 &
p=7.0x10-4, respectively)(Figure 4B). This suggests that ZNF143 expression does not simply
discriminate luminal A from Luminal B cancers, but that high expression correlates with more
aggressive disease within each subtype. The association of elevated gene expression with more
aggressive breast cancers is also observed for other chromatin-looping factors. For instance, the overall
survival of breast cancer patients whose tumours expressed high levels of CTCF or the cohesin subunit
Rad21 is worse than for patients whose tumours express these factors at lower levels (p=6.3x10-6 &
p=1.3x10-3, respectively across all ESR1-positive breast cancer patients). CTCF expression
discriminates poor outcome within both Luminal A and Luminal B subtypes (p=4.3x10-4 & p=7.7x10-4,
respectively) (Figure 4B), while RAD21’s expression is only predictive in the more aggressive Luminal
B subtype (p=0.027) (Supplementary Figure 5). These results suggest that the expression levels of
18
these chromatin-looping factors are relevant to the clinical outcome of ESR1-positive breast cancers
patients.
19
Figure 4
Figure 4: Chromatin Looping Factor Expression is affected by Genetic Alterations and is Clinically Relevant in Luminal Breast Cancer
Box-and-whisker plots showing mRNA expression for the chromatin looping factors assessed in A-C that have altered copy number status, as determined from GISTIC. Gene mutation status and mRNA expression were analyzed using publically available data obtained through the cBioPortal for Cancer Genomics. P-value is calculated using Mann-Whitney test (*p<0.05; ** p <0.01; *** p <0.001) (A). . Kaplan-Meier plots derived from the METABRIC data set (Curtis et al. 2012) evaluating overall survival in ESR1-positive breast cancer patients (n=1486), Luminal A patients (n=825) and Luminal B (n=668) patients, stratified by ZNF143 or CTCF expression. Data were obtained from the Kaplan-Meier plotter breast cancer survival analysis database (Györffy 2010). Hazard ratios (HR) and logrank P-values are displayed (B).
ZNF143
0.0
0.2
0.4
0.6
0.8
1.0
Expressionlowhigh
HR = 1.4 (1.1 − 1.7)logrank P = 0.0011
Prob
abilit
y0.
00.
20.
40.
60.
81.
0
Time (years)0 5 10 15 20 25
HR = 1.4P-val = 0.0011
Expressionlowhigh
0.0
0.2
0.4
0.6
0.8
1.0
Expressionlowhigh
HR = 1.4 (1.0 − 1.9)logrank P = 0.043
Prob
abilit
y0.
00.
20.
40.
60.
81.
0
Time (years)0 5 10 15 20 25
HR = 1.4P-val = 0.043
Expressionlowhigh
0.0
0.2
0.4
0.6
0.8
1.0
Expressionlowhigh
HR = 1.5 (1.2 − 1.9)logrank P = 0.00077
Prob
abilit
y0.
00.
20.
40.
60.
81.
0
Time (years)0 5 10 15 20 25
HR = 1.5P-val = 0.00077
Expressionlowhigh
0.0
0.2
0.4
0.6
0.8
1.0
Expressionlowhigh
HR = 1.6 (1.3 − 2.0)logrank P = 6.3e−06
Prob
abilit
y0.
00.
20.
40.
60.
81.
0
Time (years)0 5 10 15 20 25
HR = 1.6P-val = 6.3e-6
Expressionlowhigh
0.0
0.2
0.4
0.6
0.8
1.0
Expressionlowhigh
HR = 1.6 (1.2 − 2.2)logrank P = 0.0043
Prob
abilit
y0.
00.
20.
40.
60.
81.
0
Time (years)0 5 10 15 20 25
HR = 1.6P-val = 0.0043
Expressionlowhigh
0.0
0.2
0.4
0.6
0.8
1.0
Expressionlowhigh
HR = 1.5 (1.2 − 1.9)logrank P = 0.0013
Prob
abilit
y0.
00.
20.
40.
60.
81.
0
Time (years)0 5 10 15 20 25
HR = 1.5P-val = 0.013
Expressionlowhigh
CTCF
A
B Luminal BLuminal AERα Positive
Box-and-whisker plots showing mRNA expression for the chromatin looping factors assessed in
A-C that have altered copy number status, as determined from GISTIC. Gene mutation status and
mRNA expression were analyzed using publically available data obtained through the cBioPortal
for Cancer Genomics. P-value is calculated using Mann-Whitney test (*p<0.05; ** p <0.01; *** p
<0.001) (A). . Kaplan-Meier plots derived from the METABRIC data set (Curtis et al. 2012)
evaluating overall survival in ESR1-positive breast cancer patients (n=1486), Luminal A patients
(n=825) and Luminal B (n=668) patients, stratified by ZNF143 or CTCF expression. Data were
obtained from the Kaplan-Meier plotter breast cancer survival analysis database (Györffy 2010).
Hazard ratios (HR) and logrank P-values are displayed (B).
Figure 4: Chromatin Looping Factor Expression is Affected by Genetic Alterations and is Clinically Relevant in Luminal Breast Cancer
HomDel
(n=1)
HetLos
s (n=
165)
Diploid
(n=6
55)
Gain (n
=134
)
Amp (n=
4)6
8
10
12
14
STAG2
««
NS NS
mR
NA
Expr
essi
on (l
og2)
HomDel
(n=3)
HetLos
s (n=
151)
Diploid
(n=6
39)
Gain (n
=155
)
Amp (n=
10)
10
12
14
SMC1A
« «««
««««
mR
NA
Expr
essi
on (l
og2)
HomDel
(n=4)
HetLos
s (n=
292)
Diploid
(n=5
77)
Gain (n
=85)
Amp (n=
1)7
8
9
10
11
12
13
SMC3
««« «««
««
mR
NA
Expr
essi
on (l
og2)
HomDel
(n=6)
HetLos
s (n=
263)
Diploid
(n=5
61)
Gain (n
=124
)
Amp (n=
5)
7
8
9
10
ZNF143
««« «««
««
mR
NA
Expr
essi
on (l
og2)
NS
HomDel
(n=10
)
HetLos
s (n=
598)
Diploid
(n=2
70)
Gain (n
=79)
Amp (n=
3)8
9
10
11
12
CTCF
«««
««
mR
NA
Expr
essi
on (l
og2)
««
«
HomDel
(n=0)
HetLos
s (n=
23)
Diploid
(n=3
38)
Gain (n
=407
)
Amp (n=
190)
9
10
11
12
13
14
15
16
17
Rad21
«««
«««
mR
NA
Expr
essi
on (l
og2)
«««
HomDel
(n=1)
HetLos
s (n=
89)
Diploid
(n=6
31)
Gain (n
=227
)
Amp (n=
11)
5
6
7
8
9
10
11
12
13
STAG1
««« «««
NS
mR
NA
Expr
essi
on (l
og2)
20
Discussion & Future Directions 4
Chromatin interactions regulate transcriptional networks that drive differentiation and cell-specific
responses to stimuli (Fraser et al. 2009; Sanyal et al. 2012; Jin et al. 2013; Rao et al. 2014).
Dysregulation of transcriptional regulation mechanisms and consequent changes to gene expression
networks are central to tumourigenesis and disease progression (Kolch et al. 2015). Using three
different studies characterizing genetic alterations in breast tumours, we show that the chromatin
interaction factors that are known to regulate chromatin loops (ZNF143, CTCF and the subunits of the
cohesin complex) are frequently genetically altered. Furthermore, using an independent dataset, we
show that elevated expression of these factors typifies aggressive ESR1-positive breast tumours. These
results expand on the reported significant mutational load in CTCF and the subunits of the cohesin
complex in some solid and haematological cancers (Lawrence et al. 2014). We find that genetic
alterations in chromatin-looping factors tend towards mutual exclusivity in breast cancer, an
Supplementary Figure 1: ZNF143 ChIP-sequencing replicates show a high degree of reproducibility
Scatterplots depicting read count for ZNF143 binding in MCF-7 breast cancer cells treated with vehicle or E2 (10µM) for 45 minutes in two separate experiments. Plot was generated with SeqMonk from ZNF143 ChIP-sequencing data. R, Pearson’s correlations, were calculated from all data points.
R = 0.884 R = 0.928
35
Supplementary Figure 2
36
Supplementary Figure 3
37
Supplementary Figure 4
siScr
siZNF14
30
2
4
6
8
FC = 1.1NS
FC = 1.0NS
FC = 3.6!!!
FC = 3.1!!!
VehicleE2
FPK
M
siScr
siZNF14
30
10
20
30
40
50 FC = 1NS
FC = 1NS
FC = 1.1NS
FC = 1.1NS
VehicleE2
FPK
M
siScr
siZNF14
30
20
40
60
80
100
VehicleE2
FC = 1.1NS
FC = 1NS
FC = 1.2NS
FC = 1.2NS
FPK
M
Supplementary Figure 4: Depletion of ZNF143 mRNA does not affect ESR1 or FOXA1 expression under vehicle or E2-stimulated conditions
Gene expression changes in cells transfected with siZNF143 or scrambled siren under vehicle and E2-stimulated conditions (RPKM: reads per kilobase per million). (*p<0.05; ** p<0.01; *** p<0.001; NS = Not Significant)
ZNF143 ESR1 FOXA1
38
Supplementary Figure 5
0.0
0.2
0.4
0.6
0.8
1.0
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HR = 1.4 (1.1 − 1.6)logrank P = 0.0013
Prob
abilit
y0.
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HR = 1.4P-val = 0.0013
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0.0
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HR = 1.23 (0.91 − 1.67)logrank P = 0.18
Prob
abilit
y0.
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Time (years)0 5 10 15 20 25
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Expressionlowhigh
0.0
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HR = 1.3 (1.0 − 1.7)logrank P = 0.027
Prob
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Rad21
Luminal BLuminal AERα Positive
Supplemementary Figure 5: Rad21 expression is relevant to clinical outcome of luminal breast cancer patients
Kaplan-Meier plots derived from the METABRIC data set (Curtis et al. 2012) evaluating overall survival in ESR1-positive breast cancer patients (n=1486), Luminal A patients (n=825) and Luminal B (n=668) patients, stratified by RAD21 expression. Data were obtained from the Kaplan-Meier plotter breast cancer survival analysis database (Györffy 2010). Hazard ratios (HR) and logrank P-values are displayed
39
Supplementary Figure 6
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Supplementary Figure 3: Chromatin Looping Factors are Genetically Altered in Many CancersOverall frequency of genetic alterations in the chromatin looping factors (ZNF143, CTCF and the cohesion
subunits) in datasets available through the CBioPortal database (http://www.cbioportal.org).
40
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