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Excess Polθ functions in response to replicative stress in homologous
recombination-proficient cancer cells
Goullet de Rugy T1., Bashkurov M.2, Datti A.2,3, Betous R.1, L. Guitton-Sert, C. Cazaux1†,
Durocher D.2 and Hoffmann J.S.*,1
1UMR1037, Le Centre de Recherches en Cancérologie de Toulouse (CRCT), 2 avenue Hubert
Curien CS 53717, 31037 TOULOUSE CEDEX 1 FRANCE; UMR1037, CRCT, Université
Toulouse
III-Paul Sabatier, F-31000 Toulouse, France; Equipe Labellisée Ligue Contre le Cancer, F-31000
Toulouse, France;
2The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, 600 University Avenue,
Toronto, Ontario M5G 1X5, Canada.
3Department of Agricultural, Food and Environmental Sciences, University of Perugia, Perugia,
Italy.
† In memoriam
Corresponding author: Jean-Sebastien.hoffmann@inserm.fr
Keywords: Polθ, DNA polymerase Theta, synthetic lethality, high throughput screen
Biology Open • Advance article
Abstract
DNA polymerase theta (Polθ) is a specialized A-family DNA polymerase that functions in
processes such as translesion synthesis (TLS), DNA double-strand break repair and DNA
replication timing. Overexpression of POLQ, the gene encoding Polθ, is a prognostic marker for
an adverse outcome in a wide range of human cancers. While increased Polθ dosage was recently
suggested to promote survival of homologous recombination (HR)-deficient cancer cells, it remains
unclear whether POLQ overexpression could be also beneficial to HR-proficient cancer cells.
By performing a short interfering (si) RNA screen in which genes encoding druggable proteins
were knocked down in Polθ-overexpressing cells as a means to uncover genetic vulnerabilities
associated with POLQ overexpression, we could not identify genes that were essential for viability
in Polθ-overexpressing cells in normal growth conditions. We also showed that, upon external
DNA replication stress, Polθ expression promotes cell survival and limits genetic instability.
Finally, we report that POLQ expression correlates with the expression of a set of HR genes in
breast, lung and colorectal cancers. Collectively, our data suggest that Polθ upregulation, besides
its importance for survival of HR deficient cancer cells, may be crucial also for HR-proficient cells
to better tolerate DNA replication stress, as part of a global gene deregulation response, including
HR genes.
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Introduction
The human genome contains 15 genes that encode DNA polymerases. Three of them, namely α, ε,
and δ, have been extensively studied for their role in the error-free replication of the human
genome. The twelve other “non-replicative” or “specialized” DNA polymerases have been mostly
described as involved in mechanisms allowing the DNA to be repaired or replicated through DNA
insults that block the progression of replicative polymerases, a process referred to as translesional
synthesis (TLS). More recently, different studies including our own, supported the idea that the so-
called “TLS” polymerases may also be involved in other DNA-related events at the crossroad of
DNA replication, repair and recombination (Bergoglio et al., 2013; Bétous et al., 2013; Fernandez-
Vidal et al., 2014), and, for review, see (Boyer et al., 2013; Hoffmann and Cazaux, 2010).
Within the TLS network, the DNA polymerase theta (Polθ) shows unique features, for example the
existence of an N-terminal ATPase domain predicted to function as a DNA helicase, and a specific
ability to function during DNA double-strand break repair (DSB) via a Microhomology-Mediated
End Joining (MMEJ) process (Kent et al., 2015; Mateos-Gomez et al., 2015; Zahn et al., 2015).
We and others have previously shown that Polθ is the most frequently overexpressed DNA
polymerase in cancers and this overexpression is associated with an adverse clinical outcome
However, it is not yet clear whether Polθ overexpression is a bystander event occurring in
aggressive tumour development or, more importantly, Polθ plays a driving role in tumour
development and progression.
It has been recently proposed that high abundance of Polθ may result in an increased activity of
the Polθ-mediated MMEJ pathway to compensate a defective homologous recombination (HR)
repair and might represent an adaptive mechanism favouring the survival of HR repair defective
tumours like approximately half of the epithelial ovarian cancers. Indeed, Polθ can mediate the
repair of DSB through the error-prone alternative MMEJ DNA break repair pathway by inhibiting
the recruitment of RAD51, an early step of HR (Ceccaldi et al., 2015; Newman et al., 2015).
However, we recently reported that among the 101 breast tumours overexpressing POLQ analyzed
(Lemée et al., 2010), the majority did not present any alterations in HR. This prompted us to
speculate here that POLQ overexpression might give a selective advantage of growth/proliferation
also to HR-proficient tumours. We therefore explore in this work whether we could find genetic
vulnerabilities associated with POLQ overexpression of HR-proficient cancer cells and if up-
regulation of Polθ could be selected during tumorigenesis in order to adapt to high levels of
endogenous or external replicative stress. We also analysed whether POLQ deregulation in cancer
could be part of a global deregulation of genes involved in the response of replicative stress in vivo
by datamining gene expression data from published cancer studies. To the best of our knowledge
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this is the first study to demonstrate that POLQ overexpression confers a significant resistance to a
general replication stress.
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Materials and methods
Cell lines and plasmid
MRC5 is the parental cell line from lung fibroblastic origin and is immortalized by SV40.
MRC5-Q1 and Q2 were transfected with plasmid coding for human Polθ labelled with Flag tag and
overexpressing clone were selected as previously described (Lemée et al., 2010) using hygromycin
B as selective pressure. RKO were obtained from ATCC (CRL2577™) and MRC5-SV parental
cell line from ECACC (MRC5-SV2, catalogue number: 84100401)
siRNA and transfection reaction:
The "kinome" (n=720) and "druggable" (n=4440) siRNA subsets used for this study were obtained
from the human, SMARTpool library from Dharmacon. siRNAs were transfected to yield a final
concentration of 40 nM. For transfection, 103 MRC5 cells were seeded in 384-well plates. After 24
hours, transfection reactions were performed using MRC5 cell Avalanche reagent (EZbiosystem)
in antibiotic-free medium. After 6 hours of incubation, the medium was changed to reintroduce
antibiotic and selective pressure for Polθ overexpression.
Screening:
Following a 72h incubation with siRNAs, cells were fixed using fresh 2% PFA for 15 min and then
permeabilized with Triton 0.1% for 30 min. Cells were then incubated with DAPI 5mg/mL for 15
min and washed with PBS. High capacity acquisition of fluorescent cells nuclei images was
obtained with an InCell analyser 6000 (Ge Healthcare) with a ×20 objective lens. Image analyses
were carried out with the Columbus software (Perkin Elmer).
MTS Viability assay
Cells were reverse-transfected in triplicate in 96 well plates with siRNA targeting candidate genes.
Medium was changed 6 h post transfection and hygromycin B was added to restore selection
pressure when needed. MTS was added 72 h or 96 h after transfection of cells and incubated 3 h at
37 °C. Viability was measured using a spectrophotometer at 590 nm.
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Neutral comet assay
Cells were mixed with low melting agarose and then spread on microscopic slides (kit Trevigen).
Slides were brought to 4°C for about 10 min to allow solidification of the gel. Samples were lysed
for 1 h at 4°C and then rinsed in electrophoresis buffer for 30min. Electrophoresis was then run at
20V for about 50 min at 4°C, after which slides were incubated in precipitation buffer at room
temperature for 35 min, rinsed in 70% ethanol under agitation and dried at 37°C for 15 min before
incubation with SYBR®Gold. Finally, slides were dried again before imaging.
Immunofluorescence
Cells were grown on glass coverslips and pre-extracted with NP-40-based buffer for 15min (20
mM HEPES pH 7.4, 0.5% NP40, 20 mM NaCl, 5 mM MgCl2, 1 mM DTT and 1× Halt TM
protease/phosphatase inhibitors [ThermoFisher Scientific]) followed by fixation with 4%
paraformaldehyde (PFA) incubated for 15 min at RT. After fixation, cells were washed in PBS and
blocked with 5% BSA (Euromedex) in PBS. Cells were incubated overnight at 4°C with primary
antibodies against BrdU (BD bioscience 347583) or RPA34 (Clabiochem NA18) in PBS (1/100
and 1/200 respectively). Then coverslips were washed with PBS, and then incubated with Alexa
Fluor 488 or 555 goat anti–mouse or anti–rabbit (1:1,000; Molecular Probes) for 1 h at RT in PBS.
DNA was counterstained with DAPI and coverslips mounted on microscopy-slides using ProLong
Diamond (Thermofisher).
DNA combing:
Cells were successively labeled for 15 minutes with 50 µM IdU (Sigma-Aldrich) and 100 µM CldU
(ICN) and incubated 3 h with 200 mM thymidine. Genomic DNA was prepared in agarose plugs
(0.5×105 cells/plug), and DNA combing was performed as described previously (Fernandez-Vidal
et al., 2014). IdU and CldU were detected with monoclonal mouse (347580 1:20 Becton Dickinson)
and rat anti-BrdU antibodies (Abc117–7513, 1:20, Seralab), respectively. Signals were captured
with a CoolSNAP HQ camera (Photometrics) on a Leica DM IRB equipped with a 63x/1.4 PL APO
objective. Measurements were performed with MetaMorph (Universal Imaging Corp.). Fork speed
was calculated by dividing the median track size by the labeling time and the non-parametric test
of Mann-Whitney was used to data sets from different cell lines.
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Statistical and bioinformatics analysis of gene expression from tumour cohorts:
RT-qPCR data from human tumour samples were retrieved from 221 breast, 94 NSCLC and 52
colorectal cancer samples previously (Allera-Moreau et al., 2012; Lemée et al., 2010; Pillaire et al.,
2010). Correlation with POLQ gene expression was assessed using Pearson test with a p=0.65
cutoff. For each cancer type, total gene set and POLQ-correlating genes were analysed for pathway
enrichment using the KEGG database (Kanehisa et al., 2014). Co-occurrence of correlation among
different tumour types was assessed using Venny (http://bioinfogp.cnb.csic.es/tools/venny/).
Heatmaps of gene expression correlations were designed with Plotly (https://plot.ly/).
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Results
Lack of genetic robust vulnerabilities associated with POLQ overexpression in HR-proficient
cells under normal growth conditions.
In order to explore whether and how POLQ overexpression could be beneficial in HR-proficient
cancer cells, we first investigated if we could find genetic vulnerabilities associated with POLQ
overexpression of HR-proficient cancer cells under normal growth conditions. We carried out a
siRNA screen in two MRC5-SV-clones overexpressing Polθ and compared it to their isogenic
parental cell line. We established immortalized fibroblasts overexpressing Polθ (Fig. 1A) (Lemée
et al., 2010) that were then transfected in 384-well format with siRNAs derived from the
Dharmacon siGenome druggable and kinome libraries targeting a total of 5520 genes. After 72 h
incubation following transfection, cells were fixed and stained with DAPI in order to identify nuclei
and exclude dying cells. Plates were imaged with an automated microscope and viability was
derived by counting cells in each well. The siTOX siRNA from Dharmacon, which efficiently kills
cells, was used as a positive control. In each screen plate, the transfection efficiency was calculated
as the percentage of cell death induced by siTOX as compared to mock condition. siRNA plates
with a transfection efficiency below the 70% cut off were re-transfected until a transfection
efficiency above 70% was achieved (Fig. 1B).
To determine potential hit candidates in the primary screen, we calculated, for each siRNA pool,
the ratio of cell viability of each overexpressing clone compared to that of the parental cell line
(Fig. 1C-D). SiRNA pools that caused a cell survival ratio lower than 0.6 were considered as hits.
Considering the high number of hits, we selected 80 candidates enriched in genes coding for
proteins involved in DNA metabolism (about 1.5 % of the genes tested in the primary screen).
These candidates were then cherry-picked and retested for cell viability by the MTS assay (Fig. 1E,
Supp. Fig. 1). The hits from this secondary screen (0.1 % of primary screen) are presented in Figure
2A. However, upon further validation, none of these siRNAs led to a significant decrease in
viability of the POLQ-overexpressing cell lines (Fig. 2A). Since apoptosis in culture cells can take
place 24 to 48 h following a genotoxic treatment, we extended the time frame of our assay, and
monitored viability 96 h post transfection (Fig. 2B). While some siRNAs, under this condition,
significantly increased cell death at 96 h post-transfection, we did not observe any significant
difference between Polθ-overexpressing clones and the control cell line. Given that cancer cells are
known to host disparate genetic rearrangements and rely on pathways involved in DNA
checkpoints or repair (López-Contreras et al., 2012; Murga et al., 2011), we then decided to explore,
by siRNA technology, the possibility of a functional relationship between up-regulated Polθ levels
and the expression of specific genes within a tumorigenic phenotype. As a model, we chose the
RKO colorectal cell line, which express high levels of endogenous Polθ, and knocked down Polθ
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prior to, 24 h later, a second knock-down round by the siRNA candidates previously selected as
putative hits in fibroblasts (Fig. 2C). The cellular viability was then assessed 72 h later by the MTS
assay. While some candidate genes induced enhanced cell death in a tumorigenic background
compared to fibroblast (Fig. 2B-C), no statistically significant difference correlated with Polθ
levels. We therefore failed to uncover strong synthetic lethal relationships between POLQ gene
overexpression and genes coding for kinases and druggable enzymes under normal growth
conditions.
Polθ overexpression promotes cell survival in response to DNA replication stress
Since POLQ over-expression might not provide a selective advantage for HR-proficient cells
survival in the absence of external stress, we postulated that up-regulation of Polθ could be selected
during tumorigenesis in order to adapt to high levels of endogenous or external replicative stress, a
condition that characterizes many cancers (Macheret and Halazonetis, 2015). We therefore
compared cell survival of mock- and Polθ- depleted cells following treatment with replication
stress-inducing agents. Thus, we treated RKO cells, that naturally overexpress Pol, with
hydroxyurea (HU) and cytarabine (Ara-C), two drugs that inhibit the DNA replication fork
progression by depleting the nucleotide pool or chain termination, respectively (Galmarini et al.,
2001; Krakoff et al.). Our results show that Polθ depletion by siRNA (Fig. 3A) reduced cell
survival, as monitored by the MTS viability test, in response to Ara-C and HU (Fig. 3B and 3C).
Also, we performed the mirror experiment by monitoring the survival of Pol-overexpressing
MRC5 cells upon HU treatment. We found that high abundance of Pol increased cell survival, as
compared to the control isogenic cells (Fig. 3D), confirming that the abundance of Pol can
modulate resistance to replicative stress.
In order to better understand the mechanism by which Polθ-depleted cells can be sensitized to DNA
replication stress, we used a neutral comet assay to analyse formation of HU-induced DSBs (Fig.
4A). Quantification of comet tail moments revealed that Polθ loss causes higher levels of DSBs
following HU treatment, suggesting that Polθ prevents DSB formation in response to DNA
replication stress. In addition, we monitored accumulation of ssDNA by detecting ssDNA-bound
protein RPA by immunofluorescence after HU treatment. We found that the percentage of cells
with strong RPA signal significantly increased following Polθ knockdown (Fig. 4B). To confirm
this result, immortalized cells were grown in a culture medium containing the BrdU nucleotide
analogue (BrdU) to detect ssDNA formation through a native BrdU labelling assay (Raderschall et
al., 1999). This assay enables the visualization of exposed ssDNA, notably following uncoupling
of DNA replication forks and the replicative helicase. We observed that a significant increase of
Biology Open • Advance article
cells positive for BrdU staining was detected in the absence of Polθ upon HU treatment (Fig. 4C-
D). Collectively, these findings demonstrating an accumulation of ssDNA when Polθ is knocked-
down, further support a role of Polθ in the response to replicative stress.
Finally, we analyzed the DNA replication forks in cellulo both at the whole genome and at the
single molecule levels by performing a DNA fiber combing technique, a method for labeling tracts
of new DNA synthesis in vivo enabling us to monitor replication fork progression as nascent DNA
at the level of individual replicating DNA molecules. This technique relies on two consecutive
incorporations of different halogenated nucleotides which can label two subsequent periods of
DNA synthesis. The DNA molecules that have incorporated these analogs can be visualized by
fluorescence microscopy and DNA track lengths can be quantified (see the Methods section). We
found a mild but significant reduction of the replication track length in Pol-depleted cells
compared to control cells (Fig. 4E), suggesting that the role of Pol in the response to replicative
stress may occur in unstressed cells directly at natural replication barriers.
POLQ overexpression strongly correlates with HR gene expression in cancer
To explore whether POLQ deregulation in cancer could be part of a global deregulation of genes
involved in the response of replicative stress, we thought to go back to our previously reported real-
time PCR data related to DNA samples from breast, colorectal or lung cancer patients (Allera-
Moreau et al., 2012; Lemée et al., 2010; Pillaire et al., 2010), and address whether the expression
of POLQ was correlated with the expression of other genes. By using Pearson coefficient of
correlation with a threshold of p=0.65, we searched for genes that significantly correlated with
POLQ expression. Indeed, the Pearson coefficient is a statistical tool indicating the strength of a
linear correlation. A Pearson coefficient of 0 being the absence of correlation and a coefficient of
1 a perfect positive correlation. Interestingly, we found that POLQ expression in breast, colorectal
and lung cancers is positively correlated with the expression of 15 out of 64, 9 out of 61 and 15 out
of 92 genes respectively (Fig. 5A-B, Supplemental Fig. 2). Next, we investigated, by KEGG
mapping, the molecular pathways relevant to such correlated genes (Kanehisa et al., 2014). KEGG
(Kyoto Encyclopedia of Genes and Genomes) is a bioinformatics resource allowing to quantify
from a list of gene the potential enrichment in some biological processes and pathways. Notably,
our analysis consistently revealed gene networks associated with the cell cycle and homologous
recombination in the three cancers studied. Indeed, 2 out of 15, 4 out of 9 and 2 out of 15 correlated
genes were identified as HR genes in 103 lung, 52 colorectal and 221 breast tumour samples
respectively. This analysis showed an enrichment of the HR pathway in genes positively correlating
with POLQ expression (p-values of hypergeometric test: 1.25x10-5, 1.46x10-5, and 1.25x10-5).
While it is possible that the original real-time PCRs, performed on a set of genes involved in DNA
Biology Open • Advance article
repair and DNA replication, may arguably have led to biased conclusions, further data analysis
revealed that the percentage of HR-related genes that correlated with POLQ overexpression was
consistently higher than in the gene population subject to PCR analysis. Moreover, the expression
of FANCD2, an HR gene not referenced in the KEGG “HR” pathway, also correlates with POLQ
(Fig. 5B). Furthermore, 6 genes correlate with POLQ expression in the three different cancer types.
Of these genes, three of them are have previously been described in the literature shown to be
involved in HR mechanism (BLM, FANCD2 and RAD51), while the others (CDT1, CDC6 and
CDC45) are well described regulators of DNA replication origins, a molecular pathway in which
we recently implicated Polθ (Fernandez-Vidal et al., 2014).
Although Polθ was recently described as a key factor of MMEJ (Kent et al., 2015; Mateos-Gomez
et al., 2015), POLQ expression did not correlate with the expression of several genes encoding for
core MMEJ factors (PARP1, XRCC1 and LIG3) (Fig. 5C). POLQ expression did not correlate either
with the expression of genes involved in NHEJ or with genes involved in DNA end resection, a
step shared by MMEJ and HR (coefficient<0.5) (Truong et al., 2013). Then, we calculated a
Pearson coefficient for each pair of gene involved in HR and POLQ. Strikingly, HR genes
expression strongly correlated with each other with the exception of BRCA1 in breast and colorectal
cancer and BRCA2 in colorectal cancer (Fig. 5D).
Importantly, the three HR genes whose expression most strongly correlated with POLQ expression
(Fig. 5B), namely RAD51, FANCD2 and BLM, have been shown to be major actors in response to
replicative stress (Chaudhury et al., 2013; Chen et al., 2016; Zellweger et al., 2015). Therefore,
these data collectively support the notion that POLQ overexpression is part of a global gene
expression reprogramming that specifically integrates HR genes to respond to endogenous and/or
external-induced replication stress.
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Discussion
We and others have demonstrated that, Polθ expression is a strong prognostic factor in different
types of cancers (Allera-Moreau et al., 2012; Lemée et al., 2010; Pillaire et al., 2010). Recent
studies have demonstrated the important role of Polθ in DNA repair under stress conditions and
suggest that Polθ overexpression may play a key role in mechanisms of protection against
genotoxic therapies (Yousefzadeh et al., 2014), especially when other repair pathways are no longer
functional (Ceccaldi et al., 2015; Mateos-Gomez et al., 2015). Indeed, in a HR-deficient
background, Polθ becomes essential for cancer cells by promoting MMEJ and preventing toxic
RAD51 structures. However, the frequency of Polθ overexpression, especially in sporadic breast
cancer, suggests that Polθ is not only involved in a compensatory mechanism that rescues HR
deficiency, but is likely to provide HR-proficient tumours with a growth advantage. Indeed, while
proportion of HR-proficiency in sporadic cancers is difficult to quantify, somatic mutations in
BRCA genes in sporadic breast cancer is estimated to be around 10% (Futreal et al., 1994; De
Leeneer et al., 2012). To obtain new insights regarding the contextual relevance of Polθ
overexpression in tumours, and identify possible mechanisms associated with its mode-of-action,
we initially studied the correlation between the expression of POLQ and that of the genes involved
either in DNA repair or replication. Surprisingly, the expression of genes coding for MMEJ factors
did not correlate with POLQ expression. However, the HR pathway was significantly enriched in
genes that were correlated with POLQ. In this regard, BLM, FANCD2 and RAD51 show a very
strong correlation, which, interestingly, was already reported for FANCD2 and RAD51 in ovarian
cancer (Ceccaldi et al., 2015). However, in our dataset BRCA1/2 genes show a weaker correlation
with Polθ expression in lung cancer and no correlation in colorectal and breast cancer. MRE11 and
NBS1, two genes coding for proteins of the MRN complex involved in primary resection, an early
step in the HR pathway, do not instead correlate with Polθ expression. Notably, published work
has repeatedly suggested that a number of proteins involved in the HR pathway play a role in the
management of stalled replication fork under replicative stress (Carr and Lambert, 2013).
Moreover, RAD51 and BLM have been described to be involved in remodelling stalled replication
fork in a mechanism described as “fork reversal” (Neelsen and Lopes, 2015). These observations
prompted us to evaluate the role of Polθ in the response to chemotherapeutic agent that mediate
replicative stress. We used Ara-C, a drug currently used in the clinics, and HU to treat cells depleted
for Polθ. Interestingly, our findings show that Polθ depletion sensitizes cells to both agents. This
phenotype was accompanied with an increase of DNA DSB and an increase in ssDNA upon HU
treatment (Fig. 4A, B and C). In this regard, one possible explanation could be that the absence of
Polθ decreases fork restarts and increases fork stalling or fork collapse. The fact that Polθ is
frequently overexpressed in a wide range of malignant tumours highlight the importance to design
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new therapeutic strategies. One possibility might be to target Polθ and thus, resensitize cancer cells
to chemotherapeutic agents that induce replicative stress. However, while this strategy may appear
attractive, it must be noted that Polθ contains several catalytic domains that may both contribute to
chemo resistance, thereby ruling out conventional drug discovery rationales based on the
development of enzymatic inhibitors (Li et al., 2011). Another strategy would be to target a cognate
pathway that is engaged within the dynamic context of Polθ overexpression. This strategy was
explored in the past by targeting kinases involved in mitotic processes in cells with endogenous
replicative stress (Luo et al., 2009). In this regard, we attempted to unveil potential targets by means
of a systematic siRNA-based screen using cells that overexpressed Polθ and, in parallel, cells
displaying basal levels of polymerase expression. Despite good transfection efficiencies and a high
dynamic range (i.e. positive control siTOX induces at least 80% cell mortality), our attempt of
targeting 5550 different genes did not reveal any statistically significant hits and, therefore, any
evidence for synthetic lethal relationships between excess Polθ and a given metabolic pathway in
unstressed cells. This, in turn, supports the notion that there is no overt metabolic dependency in
Polθ overexpressing cells in these conditions. Recent studies have demonstrated that Polθ is a bona
fide MMEJ protein and revealed insights concerning its biological roles toward DNA repair in
cancer cells. However, taken together, our results support a potential role of this protein in DNA
replication stress response, which may also be essential in an HR-deficient background. The role
of Polθ in response to replicative stress could therefore represent a pharmacological target in cancer
sensitization to chemotherapy in both HR-proficient and HR-deficient tumours.
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Acknowledgement
This work is dedicated to Christophe Cazaux, who died accidentally during the preparation of the
manuscript.
The authors would like to thank members of the Durocher lab for fruitful discussions, especially
Jordan Young for his help with the high-throughput screen strategy.
Competing interests
The authors have no competing interest to declare
Authors’ contributions
G.R.T., B.M., Datti A., B.R., D.D., C.C. and H.J.S conceived and designed the experiments, G.R.T.
performed the experiments, G.R.T., B.M. and B.R. analysed the data, G.R.T., D.D. and H.J.S. wrote
the paper.
Funding
G.R.T. is funded by « Ministère de l’enseignement supérieur et de la Recherche » and « Ligue
Nationale contre le Cancer ». This project was in part founded by Cancer Grand Sud-Ouest
emergence. JSH is supported by grants from la Ligue Nationale Contre le Cancer (Labellisation),
INCA (PLBIO) and ANR (PCR).
Biology Open • Advance article
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Figures
Figure 1: siRNA based high throughput screen. A) Analysis of Polθ protein levels in stably
transfected clones and parental cell line. B) Transfection efficiencies for plates from the primary
screen. Transfection efficiency was calculated for each screened plate and for each of the cell line
as follows: Efficiency=100-(average (siTOX)/average (mock)). Each dot represents the efficiency
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calculated for a 384 well plate of the screen. C) And D): Results obtained from kinome (C) and
druggable (D) primary screens. SiRNA from Dharmacon kinome and druggable library subsets
were normalized to their negative siRNA control. Signals under the 0.6 threshold were considered
potential synthetic lethal hits, and signals above as negative results. E) Results from cherry-picked
genes screened by MTS assay. The 80 best siRNA candidates obtained in the primary screen were
retested in duplicate under similar conditions. Average of viability ratio compared to parental cell
line for both experimental replicates is presented. SiRNA leading to a 20% decrease or more in the
two clones as compared to MRC5 cells are highlighted in red.
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Figure 2: Absence of synthetic lethality between Polθ and candidate genes A) & B) potential
hits were transfected in low throughput and cell viability was assessed by MTS test at the indicated
times C) RKO cells were transfected with siRNA against Polθ, and then seeded after 24 h
incubation in 96well plate prior to transfection with the indicated siRNAs. Cell viability was
assessed 96 h later by MTS test.
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Figure 3: Polθ is important for cell survival upon replicative stress.
A) Validation of Polθ expression and knockdown in RKO cells. RKO were transfected with siRNA
pools directed against Polθ and protein levels were estimated by Western blot after 72 h B) and C)
Polθ deficiency leads to sensitisation of cancer cells to Hydroxyurea and Ara-C treatments. RKO
cells were transfected with siRNA targeting Luciferase and Polθ. On the following day, cells were
treated with the indicated doses of drug for 4 h. As in B), cell viability was assessed 48 h after
treatment. D) Polθ overexpression leads to resistance of cells to Hydroxyurea treatment. MRC5-
SV or MRC5-Q cells were treated with the indicated doses of drug for 4 h. Cell viability was
assessed 48h after treatment.
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Figure 4: Polθ prevents genomic instability induced by replicative stress.
A) Replication induced DNA DSBs in Polθ-depleted cells after HU. RKO cells were treated with
4 mM of HU prior to resuspension in low-melting agarose and electrophoresis required to perform
the neutral comet assay. At least 100 nuclei were quantified per condition. Two tailed t-test was
used to assess statistical significance. The graph shows the mean and standard deviation from three
independent experiments. B) Increased ssDNA in nuclei from Polθ depleted cells. Left panel: RKO
were treated with indicated doses of HU 48h after transfection cells with control siRNA (siLuc) or
siRNAs targeting Polθ. RPA34 intensity was detected in nuclei after nuclear pre-extraction (a
minimum of 900 nuclei per condition was quantified). Right panel: transfected MRC5-SV were
cultivated during 36h with BrdU in culture medium before treatment with HU. BrdU was detected
by immunofluorescence microscopy (a minimum of 350 nuclei per condition was quantified). Two
tailed Mann Whitney tests were performed to assess statistical relevance of populations (**:
pvalues<0.01; ***: pvalues<0.001). Results of two independent experiments are shown.
Representative images are shown in D). E) Polθ depletion influences fork velocity. Twenty-four
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hours after transfection of the RKO cell line with control (siLuc) or Polθ siRNA, RKO cells were
labelled successively with 50µM IdU (Sigma-Aldrich) for 15 min, 100µM CldU for 15 min and 3
h 200mM thymidine. DNA combing was performed as described previously (Fernandez-Vidal et
al., 2014). The number of bi-colour forks analysed in this experiment are 74 and 64 for siLuc and
siPOLQ conditions respectively.
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Figure 5: Polθ expression positively correlates with HR but not MMEJ genes in solid
tumours. A) Pearson test was used to compare POLQ mRNA expression and expression of any
other analyzed gene within each cohort. The number of patients analysed for lung, breast and
colorectal cancer was 103, 221, and 52, respectively (Lemee, Bergoglio et al. 2010, Pillaire, Selves
et al. 2010, Allera-Moreau, Rouquette et al. 2012). A coefficient superior to 0.65 was considered
associated to a positive correlation. Pathway enrichment analysis was performed using the KEGG
pathway database. Pie charts report the pathways detected by KEGG analysis in relation to the
number of genes in each pathway. B) Venn diagram representing different correlating genes shared
by the different tumour types. C) Heatmap of the Pearson coefficients for correlation of expression
between POLQ and genes involved in different DSB repair pathways. A white block is indicative
of unavailable data. D) Heatmap showing correlation between different genes involved in HR. A
more intense colour indicates a stronger positive correlation.
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