dna damage signaling factors protecting cancer cells against replication stress · 2017-12-07 ·...

DNA damage signaling factors protecting cancer cells against replication stress

Tine Therese Henriksen Raabe

Master thesis in Molecular Bioscience

Department of Biosciences

Faculty of Mathematics and Natural Sciences

UNIVERSITY OF OSLO

June 2016

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© Tine Therese Henriksen Raabe

2016

DNA damage signaling factors protecting cancer cells against replication stress


http://www.duo.uio.no/

Print: Reprosentralen, University of Oslo

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Abstract

DNA damage signaling is important for maintaining genomic stability of human cells. In response to

DNA damage, the cell can activate a network of signaling pathways that coordinates DNA repair and

cell cycle progression. This helps the cell to survive. Cancer cells often have increased levels of

replication stress, seen as replication arrest and DNA breakage in S-‐phase. Therefore, cancer cells

may likely depend more on DNA damage signaling compared to normal cells in order to survive. It is

therefore important to find factors of these signaling pathways that can be used for targets in

cancer treatment. The WEE1 and ATR kinases are two such factors, and inhibitors selectively

targeting them, MK1775 and VE822 respectively, are currently in clinical trials as anti-‐cancer drugs.

Among other effects, inhibition of WEE1 and ATR can cause massive replication stress and DNA

damage leading to cancer cell death. Hypoxia is a common trait of cancer cells that is caused by

rapid growth of cancer cells that outgrows its´ blood supply, resulting in inadequate oxygen delivery

to tumor cells. This can cause resistance to radiation-‐ and chemotherapy. It is previously shown that

severe hypoxia can activate DNA damage signaling and replication stress in S-‐phase.

In this thesis, we wanted to investigate the effects of inhibiting DNA damage signaling factors in

U2OS cancer cells experiencing hypoxia-‐induced replication stress. We found increased levels of the

DNA damage marker γH2AX after hypoxic exposure when WEE1 or ATR was depleted by siRNA

transfection. Furthermore, the WEE1 and ATR inhibitors MK1775 and VE822 also caused more DNA

damage in S-‐phase cells in hypoxia-‐exposed compared to normoxic cells. Interestingly, we saw a

synergistic increase of S-‐phase DNA damage upon combined inhibition of WEE1 and ATR. This effect

was also seen in cancer cells without hypoxic exposure, and was accompanied by a synergistic

reduction of clonogenic survival. We subsequently examined some mechanisms behind this

synergistic effect, and found that the synergy unlikely can be explained by elevated CDK (Cyclin

Dependent Kinase) activity. Our results indicate that combining ATR and WEE1 inhibitors may be a

possible option to be considered for future cancer treatment.

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Table of content

ABSTRACT ................................................................................................................................... 3

TABLE OF CONTENT ..................................................................................................................... 4

1 INTRODUCTION ........................................................................................................................ 7 1.1 GENERAL INTRODUCTION ................................................................................................................. 7 1.2 THE DNA DAMAGE AND REPLICATION STRESS RESPONSE ........................................................................ 8 1.2.1 DNA damage response ...................................................................................................... 8 1.2.2 Replication stress ............................................................................................................... 9 1.2.3 DDR kinases ..................................................................................................................... 10 1.2.4 Phosphatases ................................................................................................................... 16 1.2.5 DNA damage induced cell cycle checkpoints ................................................................... 16 1.2.7 DNA repair ....................................................................................................................... 18

1.4 HYPOXIA .................................................................................................................................... 19 1.4.1 Hypoxia in human tumors ............................................................................................... 19 1.4.2 Hypoxia-‐induced genomic instability and replication stress ............................................ 20 1.4.3 Targeting hypoxic cells for cancer therapy ...................................................................... 21 1.4.4 Desferrioxamine (DFO) as a hypoxia-‐mimetic agent ....................................................... 22

2 AIM ........................................................................................................................................ 23

3 MATERIALS ............................................................................................................................. 25 3.1 CELL CULTURE ............................................................................................................................. 25 3.2 SIRNA TRANSFECTION .................................................................................................................. 25 3.3 FLOW CYTOMETRY ....................................................................................................................... 26 3.4 IMMUNOFLUORESCENCE MICROSCOPY ............................................................................................. 26 3.5 SDS-‐PAGE AND WESTERN BLOT .................................................................................................... 27 3.6 CLONOGENIC SURVIVAL ASSAY ........................................................................................................ 28 3.7 BUFFERS AND SOLUTIONS .............................................................................................................. 29

4 METHODS ............................................................................................................................... 31 4.1 CELL CULTURE AND CELL SEEDING .................................................................................................... 31 4.2 WEE1-‐ AND ATR-‐INHIBITION ........................................................................................................ 32 4.3 SIRNA TRANSFECTION .................................................................................................................. 32 4.4 HYPOXIA TREATMENTS .................................................................................................................. 33 4.5 FLOW CYTOMETRY ....................................................................................................................... 33 4.6 IMMUNOFLUORESCENCE MICROSCOPY ............................................................................................. 36 4.7 SDS-‐PAGE ................................................................................................................................ 37 4.8 WESTERN BLOT ........................................................................................................................... 37 4.9 CLONOGENIC SURVIVAL ASSAY ........................................................................................................ 38

5 RESULTS ................................................................................................................................. 39 5.1 VALIDATE CANDIDATE HITS WITH SIRNA SCREEN ................................................................................ 39 5.2 DETERMINE CONCENTRATION OF ATR-‐INHIBITOR VE822 .................................................................... 42

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5.3 EFFECTS OF MK1775 AND VE822 TREATMENT IN COMBINATION WITH HYPOXIA ..................................... 43 5.4 EFFECTS OF MK1775 AND VE822 TREATMENT AFTER HYPOXIA ............................................................ 46 5.5 MEASUREMENT OF CELL SURVIVAL ................................................................................................... 51 5.6 FLUORESCENCE IMAGING OF MK1775 AND VE822 TREATED CELLS ....................................................... 52 5.7 EXPLORING THE MECHANISM BEHIND THE SYNERGISTIC EFFECT BETWEEN MK1775 AND VE822 ................. 54 5.8 DESFERRIOXAMINE AS A REPLACEMENT FOR HYPOXIA CHAMBER ............................................................. 59

6 DISCUSSION ............................................................................................................................ 61 6.1 GENERAL DISCUSSION ................................................................................................................... 61 6.2 VALIDATION OF SIRNA SCREEN ....................................................................................................... 61 6.3 COMBINED WEE1 AND ATR INHIBITION LEADS TO SYNERGISTIC INCREASE OF S-‐PHASE DNA DAMAGE. ......... 63 6.4 DO BOTH WEE1 AND ATR INHIBITION LEAD TO ELEVATED CDK ACTIVITY? .............................................. 63 6.5 COMBINATION TREATMENT WITH MK1775 AND VE822 AS A POTENTIAL ANTI-‐CANCER STRATEGY ............... 64 6.6 MICRONUCLEI IN RESPONSE TO ATR INHIBITION ................................................................................. 65 6.7 EXPERIMENTAL CONSIDERATION ...................................................................................................... 65 6.7.1 Cell culture ....................................................................................................................... 65 6.7.2 siRNA transfection ........................................................................................................... 66 6.7.3 WEE1 and ATR inhibition ................................................................................................. 67 6.7.4 Hypoxia treatments ......................................................................................................... 67 6.7.5 Measuring protein levels by flow cytometry ................................................................... 68 6.7.6 Measuring protein levels by western blotting ................................................................. 69

6.8 CONCLUDING REMARKS ................................................................................................................. 70

7 SUPPLEMENT .......................................................................................................................... 71

8 ACKNOWLEDGEMENTS ........................................................................................................... 73

9 LIST OF ABBREVIATIONS ......................................................................................................... 75

10 REFERENCES ......................................................................................................................... 79

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1 Introduction

1.1 General introduction The risk of getting cancer is known to increase with age, but people of all ages can get the disease,

and there is also increased number of people that get cancer at earlier ages. Only in 2014, there

were 31651 new cases of cancer in Norway, and some of the most common cancer types are linked

to lifestyle, such as melanoma, colorectal, and lung cancer (www.kreftregisteret.no). A paradox is

that these cancer types can be prevented, but are the ones that have the highest increased rates.

Even though more people with diagnosed cancer survive, current cancer treatment has severe side

effects and more cancer-‐specific therapy is needed, leading to the focus onto targeting cancer

treatment or personalized medicine. The idea is to exploit phenotypic or genotypic characteristics

of individual tumors and to target properties of cancer cells that are not shared in normal and

healthy cells, giving high cancer cell destruction but minimal side effects.

DNA replication is a vulnerable cellular process, where defects in the DNA damage response and

hypoxia can lead to genomic instability, an important hallmark of cancer (Gaillard et al., 2015;

Hanahan and Weinberg, 2011). Conditions that increase levels of DNA damage can cause

replication stress, a major source for genomic instability. The negative aspects of replication stress,

is that it can cause tumorgenesis, but the positive aspect is that it is a potential target for cancer

therapy. Several therapeutic drugs targeting the DNA damage response and hypoxia are in clinical

trials, but as cancer is a heterogeneous disease, this is not a straightforward process. In this project,

we will focus on the effect of inhibiting some DNA damage response targets, with or without

hypoxic conditions.

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1.2 The DNA damage and replication stress response 1.2.1 DNA damage response

To maintain genomic integrity, the cell has developed mechanisms to detect and repair DNA

damage. DNA damage can cause cancer, but is also a main mechanism of cancer cell death during

treatment with radiotherapy or chemotherapy, and is responsible for side effects of this treatment

(Kastan and Bartek, 2004). Every day the cell faces 105 of spontaneously arised DNA lesions that are

caused by internal processes or environmental agents, such as metabolic byproducts like free

radicals, replication errors, ionizing radiation (IR), ultraviolet (UV) light and chemical agents. These

lesions can create single-‐stranded DNA (ssDNA) or double-‐strand breaks (DSBs) which can cause

genomic instability. Therefore, mechanisms to repair DNA damage are critical (Ciccia and Elledge,

2010; Zhou and Elledge, 2000).

The cell has developed a network of interacting pathways, called the DNA damage response (DDR),

to coordinate DNA repair and cell cycle progression (Figure 1). DNA damage is detected by sensor

proteins, which send information signals to transducers, which again activate protein kinase

cascades, involving posttranslational modifications such as phosphorylation (Ciccia and Elledge,

2010). Downstream of transducers are the effector proteins, that regulate DNA repair, cell cycle,

transcription, and cell death pathways such as apoptosis or senescence at severe damage (Jackson

and Bartek, 2009; Zhou and Elledge, 2000). The DDR can also induce other cellular responses like

replisome stability, chromatin remodeling, RNA processing, and energy production (Jackson and

Bartek, 2009). The outcome of DDR depends on the type of DNA lesions, the severity of the lesion,

and the signaling repertoire of the cell (Ciccia and Elledge, 2010; Zhou and Elledge, 2000).

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Figure 1. The DNA damage response. Sensors react to stalled replication forks and DNA damage, and can be induced by chemicals or radiation. Sensors can then activate or inhibit downstream transducer, which pass on signals to different effectors that leads to different DNA damage responses. Figure adapted from (Jackson and Bartek, 2009).

1.2.2 Replication stress Replication stress can be defined as slowing and stalling of the replication fork progression, which

can lead to replication fork collapse and DNA breaks. This can, as mentioned, induce genomic

instability and possible cell death (Zeman and Cimprich, 2014). Replication stress can be caused by

both external agents and internal factors, which damage the DNA template or inhibit replication

proteins. For instance, several cancer therapies target replicating cells and cause replication stress,

such as the nucleoside analog gemcitabine or topoisomerase inhibitor camptotechin (Kotsantis et

al., 2015). Replication fork stalling is crucial for the action of these treatments because small lesions

can be converted into DNA double strand breaks (DBS) (Saintigny et al., 2001). Replication stress

can also be due to abnormal initiation of genomic replication origins. In human cells, replication can

start from thousands of defined sites along the chromosome at the so-‐called replication origins, and

form bidirectional replication forks (Zeman and Cimprich, 2014). The origins are licensed in G1

phase when binding of the origin recognition complex (ORC) recruits MCM2-‐7 helicase to form the

prereplicative complex (pre-‐RC). In early S-‐phase, this pre-‐RC initiates replication by recruitment of

CDC45 and the GIN-‐S complex. These will, together with MCM2-‐7, form the active replicative

helicase that unwinds the DNA helix, finally allowing activation of the DNA polymerase (Reviewed in

(Kotsantis et al., 2015)).

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The origins are activated at different times during S-‐phase. However, only a fraction of the origins

fire under normal S-‐phase, the rest serves as back up under DNA damage and replication stress

(Zeman and Cimprich, 2014). Upon overexpression of oncogenes like Ras, Myc and Cyclin-‐E (Di

Micco et al., 2006), origin firing can therefore be increased abnormally. Furthermore, certain

agents, such as inhibitors of the checkpoint kinases Chk1, Wee1 and ATR (see §1.2.3) can also

increase origin firing. The increased replication initiation leads to nucleotide shortage and stalled

forks. The stalled forks may continue to unwind the DNA helix by MCM2-‐7, creating single-‐stranded

DNA (ssDNA) that is covered with RPA (Zeman and Cimprich, 2014). This will lead to induction of the

intra-‐S checkpoint that halts the cell cycle and suppresses the origin firing (see §1.2.5). However, if

the cell does not manage to restart replication, the fork will eventually collapse, creating DNA

breakage (Magdalou et al., 2014)). Collisions between the replication and transcription machineries

may further contribute to replication stress. During S-‐phase replication and transcription operate

on the same DNA template, can lead to collisions that cause replication stalling. When more origins

are fired, due to for example oncogene expression, the number of such collisions is increased (Jones

et al., 2013; Petermann et al., 2010).

1.2.3 DDR kinases Upon DNA damage and replication stress, the DDR is activated to protect the cell. As mentioned

above, phosphorylation events are central in the DDR signaling cascades. Several kinases are

therefore highly important. ATM, DNA-‐PK and ATR are three fundamental kinases of the PIKK

(phospho-‐inositide3-‐kinase related kinases) family that act relatively upstream in the DDR

(Figure 2). ATM and DNA-‐PK are activated by DNA damaging agents that create DSBs (Reviewed in

(Ciccia and Elledge, 2010)). ATR is activated when recruited to RPA-‐coated ssDNA at stalled

replication forks or at resected (processed) DSBs (Zou and Elledge, 2003). All three kinases can

phosphorylate histone H2AX at the C-‐terminal Ser139 (γH2AX) (Stucki and Jackson, 2006). Chk1 and

Wee1 are two other important kinases, which act downstream in the DDR in induction of cell cycle

checkpoints.

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Figure 2. Model of activation of the main DDR kinases ATM, ATR and DNA-‐PK, and their downstream response. Figure modified from (Xiaofei and Kowalik, 2014).

ATM ATM (Ataxia Telangiectasia Mutated) kinase is named after the disease Ataxia Telangiectasia (A-‐T)

caused by mutations in the ATM gene, giving hypersensitivity to radiation, genomic instability ,

increased risk of cancer, immunodeficiency and neurodegeneration (Lavin, 2008). ATM is recruited

to DSBs by interacting with Nbs1 in the MRN (Mre11-‐Rad50-‐Nbs1) complex (Lee and Paull, 2004)

(Figure 2). Activated ATM can phosphorylate itself on Ser1981, allowing ATM to dissociate from an

inactive dimer complex into an active monomer. Freed ATM can then phosphorylate other

substrates, included H2AX on Ser139 (Bakkenist and Kastan, 2003). γH2AX recruits mediator protein

MDC1 (mediator of DNA damage checkpoint protein 1) which has a BRCT-‐domain that can bind

directly to γH2AX (Lukas et al., 2004). MDC1 can form a bridge between ATM an γH2AX, and

together they form a positive feedback loop, which accumulate ATM activation at DNA damage

sites. This facilitates further ATM phosphorylation on H2AX and amplifies DNA damage signals.

H2AX and MDC1 are also responsible for accumulation of DNA damage factors, like MRN, BRCA1,

and 53BP1 (Lou et al., 2006). Full ATM activation however, is shown to require ATM acetylation,

mediated by Tip60 histone acetyltransferase (Sun et al., 2005). ATM phosphorylates and activates a

number of downstream substrates, such as p53 (Canman et al., 1998) and Chk2 (Matsuoka et al.,

1998).

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DNA-‐PK DNA dependent protein kinase (DNA-‐PK) is a key enzyme in the non-‐homologous end-‐joining

(NHEJ), one of the DSB repair pathways (see § 1.2.7). DNA-‐PK is brought to DSB by Ku heterodimer,

which consists of Ku70 and Ku80 (Figure 2). Activation of DNA-‐PK kinase at the DSBs then support

NHEJ repair (Davis et al., 2014). DNA-‐PK has a lower affinity than ATM to the DSBs and normally

does not activate downstream proteins in the checkpoint response, but it can phosphorylate γH2AX

in the absence of ATM (Stiff et al., 2004).

ATR activation Ataxia telangiectasia and Rad3-‐related (ATR) protein kinase is a third members of the

phosphoinositide 3-‐kinase related kinase (PIKK) family and is a key enzyme in the DDR that activates

Checkpoint kinase 1 (Chk1) (Engelman et al., 2006). ATR is activated by ssDNA during S-‐phase to

promote genomic stability in response to DNA damage, this includes cell cycle arrest, stabilization

and repair of replication forks, inhibition of replication origin firing (reviewed in (Cimprich and

Cortez, 2008). RPA-‐coated ssDNA recruits ATRIP, a regulatory partner of ATR, which directly allows

ATR to bind to the RPA covered ssDNA (Zou and Elledge, 2003) (Figure 2). RPA also recruits the 9-‐1-‐

1 (Rad9-‐Rad1-‐Hus1) complex which is loaded onto the ssDNA by clamp-‐loading complex containing

Rad17 (Maréchal and Zou, 2013). 9-‐1-‐1 complex allows TOPBP1-‐binding to the damaged sites and

to stimulate kinase activity of ATR-‐ATRIP (Kumagai et al., 2006). Once activated, ATR can activate

checkpoints in response to DNA damage or replication stress. The best studied ATR-‐target is Chk1.

With the help of mediator proteins, such as CLASPIN, ATR recognizes and phosphorylates Chk1

(Kumagai and Dunphy, 2000). ATR is also shown to signal DNA damage to p53. This can be done

either directly (Lakin ND, 1999), or via Chk1 or Chk2 (Shieh et al., 2000). P53 is then phosphorylated

and stabilized, which leads to upregulation of CDK inhibitor p21 and cell cycle arrest (AJ, 1997).

ATR-‐inhibition as an anti-‐cancer strategy ATR is important for cell survival in normal cells. Inactivation of ATR in mouse embryo is shown to

be lethal (Cimprich and Cortez, 2008). In adult mice tissue, inactivation of ATR has shown to cause

premature aging, defects in tissue homeostasis, and depletion of progenitor cells in rapidly

proliferating tissues (Ruzankina et al., 2007). In tumor cells, ATR is however more important than it

is in normal cells. Multiple events drive tumorgenesis and can cause a synthetic lethality for ATR

inhibition. Oncoproteins, such as Ras, Myc and Cyclin-‐E, disrupt normal cell cycle regulations and

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cause genomic instability and replication stress. The ATR pathway is critical for the tumor cells to

survive, and in cells with high levels of oncogene-‐induced replication stress, inhibition of ATR

pathway has been shown to be selectively toxic (Gilad et al., 2010; Toledo et al., 2011). ATR

inhibition leads to increased replication stress causing lethal damage and cancer cell death (López-‐

Contreras Aé and Fernandez-‐Capetillo, 2010). In addition, tumor cell lines become more sensitive to

ATR inhibition when they lack specific DNA repair proteins, such as XRCC1 and ERCC1 (Mohni et al.,

2014; Sultana et al., 2013). Furthermore, since hypoxia is shown to cause replication stress, hypoxic

cells are also sensitive to ATR inhibition (Hammond et al., 2004; Pires et al., 2010; Pires et al., 2012).

In addition, some tumor cells rely on the alternative lengthening of telomeres (ALT) pathway. ATR

has a role in the homologous recombination reaction that maintains these telomeres, so that these

tumor cells are also more sensitive to ATR inhibition (Flynn et al., 2015).

Moreover, a common feature of cancer cells is loss of the G1 checkpoint, because of deficient pRB

(Retinoblastoma protein), ATM and/or p53. Therapeutic inhibition of ATR can therefore selectively

sensitize cancer cells and increase tumor cell killing (Reviewed in (Fokas et al., 2014)). Both G1 and

S/G2 cell cycle checkpoints are intact in normal cells, were genotoxic stimuli activate the

checkpoints via ATM and ATR-‐dependent pathways. Since cancer cells often have loss of G1/S

checkpoint control, they are dependent on the ATR/Chk1 pathway to repair DNA damage. This gives

specificity for ATR inhibition in cancerous cells. Normal cells with intact G1 checkpoint control are

less affected (Fokas et al., 2014). (See also discussion about Wee1 inhibition and mitotic

catastrophe below). The first ATR inhibitor discovered was caffeine that disrupted DNA damage

induced cell cycle arrest and sensitized cells to DNA damage. It is not very specific for ATR and very

toxic (Sarkaria et al., 1999). In 2011 the first selective inhibitor of ATR was discovered, called VE821,

that was 100 times more selective for ATR than the other PIKK-‐kinases (Charrier et al., 2011).

Recently its analog, VE822 (VX-‐970), has been proved to have higher solubility, potency, selectively,

and pharmacodynamics properties. VE822 is currently in clinical trials (Asmal et al., 2015). VE822

elevates the levels of DNA damage markers, like γH2AX, and causes checkpoint abrogation and cell

death (Hall et al., 2014). VE822 is also used in the experiments in this master project.

Chk1 Chk1 was initially identified as a Serine/Threonine protein kinase that controls the G2/M phase

transition in response to DNA damage in fission yeast (Walworth et al., 1993). Later it has been

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shown that Chk1 impacts various stages of the cell cycle that also includes S-‐phase and G2/M-‐phase

(Bartek and Lukas, 2003; Zhang and Hunter, 2014).

Chk1 is regulated by ATR through phosphorylation, creating the ATR-‐Chk1 pathway. Activation of

Chk1 occurs primarily through phosphorylation of Ser317 and Ser345 (Zhang and Hunter, 2014),

and after activation, Chk1 can phosphorylate a number of substrates that have several functions.

One major substrate downstream of Chk1 is the cdc25A phosphatase (Furnari et al., 1997; Sanchez

et al., 1997) that regulates cell cycle progression by activation of the cyclin-‐dependent kinases

(CDKs) (Sanchez et al., 1997). The ATR-‐Chk1 pathway in shown not only to be activated in response

to DNA damage, but also is important during normal cell cycle progression, for instance in S-‐phase

(Syljuåsen et al., 2005).

WEE1 WEE1 tyrosine kinase is an important regulator of the G2/M checkpoint (Domingo-‐Sananes et al.,

2011), as it negatively regulates entry into mitosis by catalyzing inhibitory phosphorylation on CDK1.

This gives an inactivation of CDK1/cyclin B complex, and leads to G2/M checkpoint arrest. Such

checkpoint arrest is also mediated by Chk1 inhibition of CDC25 phosphatase, which removes

inhibitory phosphorylation on CDK1 (Domingo-‐Sananes et al., 2011; Mueller and Haas-‐Kogan,

2015). Recently it was shown that WEE1 also is important during S-‐phase, and controls both CDK1

and CDK2 by an inhibitory phosphate on Tyr15. This means that WEE1 and also Chk1 both control

CDK activity during DNA replication in S-‐phase to avoid DNA damage and maintain genomic stability

(Beck et al., 2010; Sørensen and Syljuåsen, 2012). WEE1 inhibition increases CDK activity that can

increase replication initiation and lead to depletion of the nucleotide pool. This can result in

replication stalling and endonuclease Mus81 cleavage of stalled replication forks that eventually

creates DNA damage (Beck et al., 2012; Domínguez-‐Kelly et al., 2011). Forced CDK activity after

WEE1 inhibition can also lead to DNA damage through causing impaired homologous

recombination (HR) repair in interphase cells (Krajewska et al., 2013).

WEE1 activity is increased during S and G2 phase but is inactivated and degraded during mitosis,

suggesting that there are mechanisms for regulating WEE1 (McGowan and Russell, 1995; Watanabe

et al., 1995). Polo-‐like kinase 1 (PLK1) and CDK1 itself can negatively regulate WEE1 by

phosphorylating Ser53 and Ser123, respectively, promoting ubiquitination and subsequent

proteasomal degradation. CDK1 can also activate CDC25 by phosphorylation, and by this create a

positive feedback-‐loop that increase CDK activity when entering mitosis (Watanabe et al., 2005;

Watanabe et al., 2004; Watanabe et al., 1995).

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WEE1-‐inhibition as an anti-‐cancer strategy As mentioned above, common traits of human cancer cells are that they have mutations in p53 or

the pRB that leads to malfunction of the G1/S checkpoint. Because of this, the cancer cells become

more reliant of the G2/M checkpoint for DNA damage survival (AJ, 1997). Since inhibition of WEE1

causes abrogation of the G2/M checkpoint, cells that already lack the G1/S checkpoint would not be

able to halt the cell cycle for repair of DNA damage (Figure 3). Cells will start to divide with

unrepaired DNA lesions, leading to abnormal chromosome segregation and apoptosis, a process

often termed mitotic catastrophe (Castedo et al., 2004; Kawabe, 2004). WEE1 inhibition can cause

mitotic catastrophe when combined with conventional DNA damaging therapy, such as radiation

and different cytostatics (De Witt Hamer et al., 2011; Hirai et al., 2009). Recently the cytotoxic

effects WEE1 inhibitors have on cancer cell survival as single agents have also gained more

attention (Kreahling et al., 2012). Oncogene activity and elevated CDK activity can result in

replication stress in cancer cells (Halazonetis et al., 2008), and by inhibiting WEE1, CDK activity

becomes too high and results in DNA damage, and eventually cancer cell death (Sørensen and

Syljuåsen, 2012). The selective WEE1 small molecule inhibitor, MK1775, inhibits CDK

phosphorylation on Tyr15, which leads to abrogation of the G2/M checkpoint and subsequent

mitotic catastrophe. This is shown to be a possible anti-‐cancer strategy in p53-‐defective cancer cells

(De Witt Hamer et al., 2011; Hirai et al., 2009), but can also can cause significant cell death in

sarcoma cells with wild-‐type p53, suggesting that mitotic catastrophe can also occur independent

of p53 status (Kreahling et al., 2012). MK1775 is also shown to abrogate S phase arrest and cause

more cell death in combination with the cytostatic drug, Gemcitabine (Kreahling et al., 2013).

Figure 3. Principle behind the selectively targeted cancer cells, taking advantage of the lost DNA damage response pathway. When targeting G2/M checkpoint, a normal, healthy cell can survive DNA damage because it still has the compensatory G1/S checkpoint, that will arrest the cell for DNA repair. In cancer cells, where this compensatory pathway is abrogated, the cells will die because of massive DNA damage that will not be abled to be repaired. Modified from (Curtin, 2012).

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1.2.4 Phosphatases DNA damage and replication stress activate DDR, and as discussed, serine/threonine kinases are the

key players for phosphorylating a wide range of substrates that execute DDR. However, this

response needs to be inactivated when the damage has been resolved. (Harper and Elledge, 2007;

Zhou and Elledge, 2000).

Phosphatases are therefore important for dephosphorylating these substrates.

Reversible protein phosphorylation at serine (Ser), threonine (Thr), and tyrosine (Tyr) residues is the

most common post-‐translational modification in eukaryotic cells (Rebelo et al., 2015).

Protein phosphatases are divided into three families based on sequence, structure, and catalytic

mechanisms, and whether they can dephosphorylate Ser/Thr residues alone, Tyr residues alone, or

have dual specificity. The Ser/Thr family can be further divided into three families. One of them is

the large phosphoprotein phosphatase (PPP), including proteinphosphatase-‐1 (PP1), which is

involved in many cellular functions, including DNA repair and checkpoint activation. However, there

are more than ten times more Ser/Thr kinases than phosphatases. (Moorhead et al., 2007). PP1 is

therefore associated with different regulatory subunits. PP1 can form as many as 650 distinct

complexes with PP1-‐ interacting proteins (PIPs), which bind to the targeting RVxF motif (Bollen et

al., 2010; Lee and Chowdhury, 2011). In addition to DDR, PP1 is also involved in regulation of

metabolic processes by inactivating the cAMP response element (CREB), a transcriptional regulator

of metabolic genes and processes. Under hypoxic conditions, Nuclear inhibitor of PP1 (NIPP1) can

bind to the isoform PP1γ. This leads to degradation of CREB. It is suggested that NIPP1, by binding

to PP1γ, may be important in helping the cell adapt metabolically in order to survive under hypoxic

conditions (Comerford et al., 2006).

1.2.5 DNA damage induced cell cycle checkpoints The cell cycle is divided into four phases: The first gap (G1) phase, Synthesis (S) phase, second gap

(G2) phase, and the Mitotic (M) phase. The different phase-‐transitions are thoroughly controlled by

ordered activation of different CDKs that bind to specific cyclins to create cyclin/CDK complexes

(Figure 4A). These complexes activate multiple targets that are specific for the next cell cycle phase

to drive the cell cycle forward, and this is tightly regulated to ensure that each process in one phase

is completed before the cell can enter the next phase (Malumbres and Barbacid, 2009).

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There are three different DNA-‐damage induced cell cycle checkpoints in mammalian cells. The two

main checkpoints are at the G1/S and G2/M transitions, which halt the cell cycle progression before

S-‐ and M-‐phase. In addition, the Intra-‐S checkpoint can slow down the replication (Figure 4B).

Figure 4. Regulation pathways of the cell cycle and DNA damage checkpoint pathways. A) The cell cycle phases and the corresponding CDK-‐cyclin complexes that derived the cell cycle progression. Modified from (Verbon et al., 2012). B) Induction of G1/S, intra S, and G2/M checkpoints. G1/S and G2/M checkpoints induce cell cycle arrest that allow time for DNA repair (stop), while intra-‐S checkpoint leads to slowing of replication and decreased initiation of origin firing (slow). Modified from (Kastan and Bartek, 2004).

G1/S checkpoint The G1/S checkpoint is important to prevent damaged cells to enter S-‐phase. This is mainly

mediated by the ATM-‐Chk2-‐cdc25 pathway and the ATM-‐p53-‐p21 pathway. Targeting of cdc25 is a

rapid response after DNA damage (Deckbar et al., 2011). Activated ATM recruits and activates Chk2

by phosphorylation and the active Chk2 will phosphorylate cdc25 phosphatase that will be

degraded. Cdc25 is necessary for CDK2 activation and upon degradation it can no longer remove

inhibitory phosphorylation on CDKs. CDK activity is decreased which leads to rapid G1/S arrest. The

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activation of p53 is slower than the cdc25 response. Prolonged G1/S arrest is dependent on p53

and p21 (Bartek and Lukas, 2001). Increased p53 activation transcriptionally upregulates p21, which

binds to and inactivate cyclin-‐E/CDK2, preventing the cell to enter S-‐phase (Sherr and Roberts,

1999).

Intra-‐S checkpoint Activation of the intra-‐S phase checkpoint can only delay cell cycle progression and not induce

permanent arrest. This delay is mediated by ATM and ATR that, as mentioned, phosphorylate and

activate Chk2 and Chk1 kinases, which in turn phosphorylate and inactivate CDC25. This leads to

degradation of CDC25 and decreased CDK activity (Sørensen et al., 2003). Decreased CDK activity

will prevent firing of new replication origins, and slow down replication fork progression (Bartek and

Lukas, 2001). Increased CDK activity is induced by WEE1 inhibition in the cyclin-‐A/CDK2 complex

(Enders, 2010).

G2/M checkpoint The G2 to M phase is mediated by the cyclin-‐B/CDK1 complex. The G2/M checkpoint prevent cells

from entering into mitosis with DNA damage. The damage may have occurred either in the G2

phase or be a result of unrepaired damage occurred in S-‐phase (Kastan and Bartek, 2004;

Malumbres and Barbacid, 2009). Cell cycle arrest is dependent on either ATR-‐Chk1-‐CDC25 pathway

or ATM-‐p53-‐p21 pathway. Unrepaired damage from S-‐phase activates ATR, which phosphorylates

Chk1 and thereby inactivate CDC25. This inactivation leads to cyclin-‐B/CDK1 inhibition. DSBs in G2

activate ATM that can directly phosphorylate p53, or indirectly through Chk2, and upregulate p21,

leading to CDK1 inhibition (Medema and Macurek, 2012). Similar to in S-‐phase, WEE1 can also

inhibit CDK1 in G2 phase and thereby lead to G2/M cell cycle arrest (Watanabe et al., 2004).

1.2.7 DNA repair The cell is facing different types of DNA damage and has developed several types of repair systems

according to cell cycle phases and lesion types. For instance, Base excision repair (BER) deals with

damaged nucleotides and ssDNA, Mismatch repair (MMR) deals with damage under replication, like

insertion/deletion of the wrong base, and nucleotide excision repair (NER) deals with various types

of lesions. DSBs have two main pathways for DNA repair: homologous recombination (HR) and non-‐

homologous end-‐joining (NHEJ) (Ciccia and Elledge, 2010; Dexheimer, 2013).

19

Homologous recombination repair HR is dependent on a sister chromatid that that is used as a template for break repair. The

requirement of a homologous sequence restricts this repair mechanism to S-‐ and G2-‐phase, and

makes this repair pathway to be error-‐free. HR is initiated by binding of the MRN complex to the

DSB and Mre11 in cooperation with CtBP-‐interaction protein (CtIP) create short stretches of ssDNA

(resection) (Reviewed in (Stracker and Petrini, 2011)). This process also depends on BRCA1 (breast

cancer 1 susceptibility protein) (Yun and Hiom, 2009). Further resection is carried out by Exo1,

DNA2, and BLM (Stracker and Petrini, 2011). This results in long stretches of 3´-‐ended ssDNA, that

are quickly coated by RPA. RPA is then replaced with Rad51, in a manner dependent on BRCA2

(breast cancer 2 susceptibility protein) and PALB2 (partner and localizer of BRCA2) (Holloman,

2011). Rad51 forms a nucleoprotein filament, and initiates strand invasion and DNA synthesis by a

DNA polymerase. This forms Holliday junction that is cut and ligated at crossover points

(Holthausen et al., 2010).

Non-‐homologous end joining NHEJ is more error-‐prone but also more efficient than HR, and is initiated in all phases in the cell

cycle. This repair mechanism is initiated by a Ku complex that binds to DSBs. As previously

mentioned, the Ku complex is a heterodimer which consists of Ku70 and Ku80. Ku complex quickly

recruit DNA-‐PK to the damaged site (Davis et al., 2014). After activation of DNA-‐PK, the

endonuclease Artemis is recruited together with repair proteins (Polymerase µ and γ) and ligase

complex (DNA ligase IV with XLF and XRCC4) that ligate the ends together (Mahaney et al., 2009).

1.4 Hypoxia 1.4.1 Hypoxia in human tumors All cells need blood supply for delivery of oxygen and nutrients, including cancer cells. As the solid

tumor grows, it outgrows its oxygen and nutrient supply, and it needs to induce formation of new

blood vessels from pre-‐existing blood-‐vessels in order to grow further, called tumor angiogenesis.

The new blood vessels are usually quickly formed and often have structural abnormalities. This

leads to unstable blood flow and thereby oxygen levels to parts of the tumor, causing

subpopulations of the cancer cells to experience hypoxia (Bristow and Hill, 2008; Vaupel et al.,

1989). Hypoxia is defined as an oxygen range between normal levels (approximately 6%), mild

20

hypoxia (0,5-‐3%), and anoxia (0%) (Vaupel et al., 1989). Tumor hypoxia can be divided into two

main subgroups, acute or chronic hypoxia (Pires et al., 2010). Acute hypoxia, or cycling hypoxia, is

repeated periods of hypoxia with subsequent reoxygenation that last from minutes to a few hours.

It is caused by temporary occlusions of blood and oxygen (Bristow and Hill, 2008; Dewhirst et al.,

2008). Chronic hypoxia is found in regions deep inside the tumor, far from blood vessels. Extreme

chronic hypoxia often has O2 levels close to anoxia (Bristow and Hill, 2008). Hypoxic cells are more

resistant to chemotherapeutics than normal, well-‐oxygenated cells, because rich blood supply is

necessary for delivery of oxygen and thereby better drug transport (Bussink et al., 2003). In

addition, hypoxic cells are resistant to radiotherapy and hypoxia is an important factor for

development of angiogenesis and tumor aggressiveness (Overgaard, 2007; Tatum et al., 2006). Due

to this, hypoxia is generally related to poor outcome for cancer patients. Since hypoxia affects many

basic cellular processes, including metabolism, cell cycle progression, and translation and

transcription, cells have developed three response pathways: the stabilization of hypoxia-‐inducible

factors (HIFs), the mammalian target of rapamycin (mTOR) pathway, and the unfolded protein

response (UPR) (Ebbesen et al., 2009; Wouters and Koritzinsky, 2008).

HIFs are transcription factors that form a heterodimer composed of an α-‐ and a β-‐ subunit when

active. These transcription factors are critical regulators of cellular responses in hypoxia (Semenza,

1998). In the presence of oxygen, HIF1-‐α is hydroxylated by oxygen-‐activated propylhydroxylases

(PHDs), which is leads to ubiquitination and degradation of HIF1-‐α by interaction of von Hippel-‐

Lindau complex (vHL). Hypoxia leads to stabilization and accumulation of HIF1-‐α by inactivation of

PHDs, which leads to activation of downstream target genes of HIF1 inducing factors. This is

involved in promoting pathways, such as angiogenesis by vascular endothelial growth factor (VEGF),

metastasis, and glycolysis (Bristow and Hill, 2008; Semenza, 2012). UPR and mTOR are two other

pathways that are important for tumor cell behavior and are working independently to influence

gene expression. They help regulating energy consumption in hypoxic cells by inhibition of mRNA

translation, which is a highly energy-‐consuming process (Wouters and Koritzinsky, 2008).

1.4.2 Hypoxia-‐induced genomic instability and replication stress In addition to causing resistance to radiation and chemotherapy, hypoxia represses many essential

components of the DNA repair pathways (Bristow and Hill, 2008). Hypoxic conditions have been

shown to induce less effective HR, MMR, and possibly NHEJ repair (Bindra et al., 2007; Bristow and

Hill, 2008; Kumareswaran et al., 2012). The key members of HR pathway, Rad51 and BRCA1, are

21

shown to be downregulated in hypoxia (Bindra and Glazer, 2006). MLH1 and MLH2, both

components of the MMR pathway are also repressed under hypoxic conditions (Chen et al., 2006;

Olcina et al., 2010). It is suggested that repression of genes involved in DNA repair causes increased

genomic instability in hypoxia, and may contribute to aggressive tumor development (Bristow and

Hill, 2008).

Severe levels of hypoxia (<0.02% O2) also induces several hypoxic responses, including DDR, that

induce rapid S-‐phase or replication arrest (Green et al., 2001). The oxygen-‐dependent enzyme

ribonucleotide reductase (RNR) is responsible for production of the four deoxyribonucleotide

triphosphates (dNTPs) that are required for DNA replication and DNA repair. In response to severe

hypoxia this enzyme is severely repressed (Nordlund and Reichard, 2006), and this gives a rapid and

significant decrease of nucleotides (Pires et al., 2010). In response to replication arrest, ATRIP can

recognize RPA complexes that bind to ssDNA and lead to activation of ATR. Severe hypoxia results in

regions of ssDNA within S-‐phase (Zou and Elledge, 2003), but hypoxia does not always lead to DNA

breaks directly. It has been suggested that reoxygenation creates reactive oxygen species (ROS) that

will genereate SSBs and possibly DSBs, and elicits ATM-‐Chk2-‐dependent G2 checkpoint arrest for

DNA repair. In tumor cells lacking Chk2, a reduced reoxygenation-‐induced cell cycle arrest and

increased apoptosis was shown (Freiberg et al., 2006).

1.4.3 Targeting hypoxic cells for cancer therapy Since hypoxic cells are known to cause negative prognosis, it is important to target these cells

during cancer therapy. In the last years, there have been developed several treatment strategies for

targeting hypoxic cells specifically. One strategy is to use fractionated radiotherapy, where radiation

is given in a series of small doses rather than one large dose, which allows reoxygenation between

therapy (Reviewed in (Horsman, 2009; Overgaard, 2007)). Other strategies involved are inhibitors of

DDR, as hypoxia affects DDR and induces genomic instability. There are several performed and

ongoing studies with the use of different inhibitors. During and after chronic hypoxia the decreased

HR repair can resensitize tumor cells to IR and some chemotherapeutic drugs (Chan et al., 2008).

HR-‐defected cells are shown to be synthetically lethal with poly (ADP-‐ribose) polymerase 1 (PARP1),

involved in base excision repair pathway of SSBs. Inhibition of PARP1 results in accumulation of SSBs

that may eventually lead to DSBs in encounter with replication fork. These breaks require HR for

DNA repair and replication (Chan et al., 2010). Therefore, PARP1 inhibitors can increase clonogenic

killing in HR-‐deficient hypoxic cells.

22

The key roles of ATR and ATM during hypoxia-‐induced replication stress and reoxygenation, are

suggesting these kinases as potential therapeutic targets (Hammond et al., 2007). By using potent

and specific inhibitors of cellular ATR activity, such as VE821 and VE822, promising sensitizing

effects were found for a variety of cancer cells (Fokas et al., 2012; Pires et al., 2012). Furthermore,

inhibition of Chk1 is also reported to selectively sensitize cancer cells after being exposed to

prolonged hypoxia and reoxygenation (Hasvold et al., 2013). Especially ATR and Chk1 inhibitors play

critical roles in the cellular response to hypoxia followed by reoxygenation, and represent new

hypoxic cell cytotoxins (Hammond et al., 2004).

1.4.4 Desferrioxamine (DFO) as a hypoxia-‐mimetic agent The iron chelator desferrioxamine (DFO) is a commonly used hypoxia-‐mimetic agent, and like

hypoxia, it can block the degradation and induce accumulation of hypoxia-‐inducible factor-‐1alpha

(HIF-‐1α) (An et al., 1998). DFO has been shown to induce cell death with features of an apoptotic

cell, like shrinking, chromatin condense, and nuclear fragmentation inside the cell wall (Guo et al.,

2006). DFO can also cause genetic instability by inducing replication arrest similar to hypoxia

(Hammond et al., 2002).

23

2 Aim The overall aim of this master project was to identify some factors protecting cancer cells against

replication stress, and investigate whether hypoxia influenced the DNA damage in S-‐phase cells

caused by WEE1 inhibitor MK1775 and ATR inhibitor VE822.

Specific aims of this project are:

(I) To validate candidate hits from a previous performed siRNA screen

(II) To investigate the effect of WEE1 and ATR inhibition in combination with hypoxia

(III) To examine some of the mechanisms behind the synergistic effect after combined

treatment of WEE1 and ATR inhibitors

25

3 Materials

3.1 Cell culture Material Product Vendor Cat. #

Medium DMEM, high glucose, GlutaMAX™ Supplement, pyruvate Life Technologies 31966-‐047

FBS Fetal Bovine Serum Origin: EU Approved (South American) Life Technologies 10270-‐106

Antibiotic Penicillin-‐Streptomycin (10,000 U/ml) Life Technologies 15140-‐122

PBS Phosphate-‐Buffered Saline (1x), pH 7.2 Life Technologies 20012-‐068

Trypsin Trypsin-‐EDTA (0.25%), phenol red Life Technologies 25200-‐056

Wee1-‐inhibitor MK1775 Axon Axon 1494

ATR-‐inhibitor VE822 Selleck

Chemicals S7102

Hypoxia treatment

Invivo2 200 hypoxia chamber

Ruskinn

3.2 siRNA transfection Material Product Vendor Cat. #

Transfection reagent Lipofectamine™ RNAiMAX Life Technologies 13778075

Medium Opti-‐MEM® in Reduced Serum Medium, GlutaMAX™ supplement Life Technologies 51985-‐026

Buffer 5x siRNA buffer Thermo Scientific B-‐002000-‐UB-‐100

siRNA (control) Non-‐targeting siRNA #4 GE Dharmacon

siRNA siATR, sense sequence: 5´GAACAACACUGCUGGUUUGUU(dT)(dT) Sigma

siRNA siNIPP1, sense sequence: 5´GGAACCUCACAAGCCUCAGCAAAUU(dT)(dT) Sigma

siRNA siNIPP1, sense sequence: 5´GGGUUGAAAUAGCCCAUAA(dT)(dT) GE Dharmacon

siRNA siRAD17, sense sequence: 5´CAACAAAGCCCGAGGAUAU(dT)(dT) Sigma

siRNA siWEE1, sense sequence: 5´GGAAAAAGGGAAUUUGAUG(dT)(dT) Sigma

26

3.3 Flow cytometry

3.4 Immunofluorescence microscopy

Material Product Vendor Cat. #

Primary antibody Mouse anti-‐phospho-‐Histone H2AX (S139), 1:500 Millipore 05-‐636

Secondary antibody

Alexa Fluor® 488 conjugated donkey Anti-‐mouse IgG, 1:1000 Life Technologies A-‐21202

Fixing agent Ethanol, absolute VWR 20821.310


Fixing agent Formalin solution 10%, neutral buffered with 4% formaldehyde SIGMA-‐ALDRICH HT501128

DNA dye VECTASHIELD Mounting medium with DAPI Vector Laboratories H-‐1200

Coverslips Coverslips, 13 mm diameter Thermo Scientific 13100

Glass slides Microscope slides, 76x26 mm Thermo Scientific 51101



FBS Fetal Bovine Serum Origin: EU Approved (South American) Life Technologies 10270-‐106

Non-‐ionic detergent Igepal CA630 SIGMA-‐ALDRICH 13021


Milk Powder Skim milk powder for microbiology SIGMA-‐ALDRICH/Fluka 70166-‐500G

DNA stain Hoechst 33258 SIGMA-‐ALDRICH 94403-‐1ML

Primary antibody Mouse anti-‐phospho-‐Histone H2AX (S139), 1:500 Millipore 05-‐636

Primary antibody Rabbit anti-‐phospho-‐Histone H3 (S10), 1:500 Millipore 06-‐570

Secondary antibody Alexa Fluor® 647 conjugated goat Anti-‐mouse IgG, 1:250 Life Technologies A-‐21235

Secondary antibody Alexa Fluor® 488 conjugated donkey Anti-‐rabbit IgG, 1:250 Life Technologies A-‐21026

Flow tubes BD Falcon Round bottomed test tubes, polystyrene, cell strainer cap, 5 ml VWR 734-‐0001

27

3.5 SDS-‐PAGE and Western blot


Acrylamide gel 4-‐15% Mini-‐PROTEAN® TGX™ precast gel, 15 well, 15µl Bio-‐Rad 456-‐1086

Acrylamide gel 4-‐20% Mini-‐PROTEAN® TGX™ precast gel, 15 well, 15µl Bio-‐Rad 456-‐1096

Acrylamide gel 4-‐15% Criterion™ TGX™ precast gel, 26 well, 15µl Bio-‐Rad 567-‐1085

Running buffer 10x Tris/glycine/SDS Bio-‐Rad 161-‐0772

Transfer buffer 5x Trans-‐Blot® Turbo™ Bio-‐Rad 10026938

Marker Full-‐Range Rainbow Molecular Weight Marker VWR RPN800E

Sample buffer Lane marker reducing Sample Buffer VWR PIER39000

Nitrocellulose membrane Trans-‐Blot® Turbo™ RTA Mini Nitrocellulose Transfer Kit Bio-‐Rad 170-‐4270

Transfer stacks Trans-‐Blot® Turbo™ RTA Mini Nitrocellulose Transfer Kit Bio-‐Rad 170-‐4270

Transfer buffer Trans-‐Blot® Turbo™ RTA Mini Nitrocellulose Transfer Kit Bio-‐Rad 170-‐4270

Nitrocellulose membrane Trans-‐Blot® Turbo™ RTA Midi Nitrocellulose Transfer Kit Bio-‐Rad 170-‐4271

Transfer stacks Trans-‐Blot® Turbo™ RTA Midi Nitrocellulose Transfer Kit Bio-‐Rad 170-‐4271

Transfer buffer Trans-‐Blot® Turbo™ RTA Midi Nitrocellulose Transfer Kit Bio-‐Rad 170-‐4271

Ponceau stain Ponceau S solution SIGMA-‐ALDRICH P7170-‐1L


Tween 10% Tween 20 Bio-‐Rad 161-‐0781

Milk Powder Skim milk powder for microbiology SIGMA-‐ALDRICH/Fluka

70166-‐500G

Primary antibody Rabbit anti-‐ATR, 1:1000 Cell Signaling 2790

Primary antibody Mouse anti-‐CDK1, 1:400 Santa Cruz

Biotechnology sc-‐54

Primary antibody Rabbit anti-‐CDK1 pY15, 1:1000 Cell Signaling 9111

Primary antibody Rabbit anti-‐CDK2, 1:400 Santa Cruz


Primary antibody Rabbit anti-‐CDK2 pY15, 1:5000 AbCam Ab76146

Primary antibody Mouse anti-‐CHK1, 1:400 Santa Cruz

Biotechnology DCS310.1

Primary antibody Mouse anti-‐CHK1 pS317, 1:400 Cell Signaling 2344

28

Primary antibody Mouse anti-‐CHK2, 1:50 Santa Cruz

Biotechnology DCS270.1

Primary antibody Rabbit anti-‐CHK2 pT68, 1:400 Cell Signaling 2197

Primary antibody Rabbit anti-‐DNApk pS2056, 1:400 Abcam ab18192

Primary antibody Mouse anti-‐NIPP1, 1:400 Santa Cruz


Primary antibody Mouse anti-‐ATM pS1981, 1:1000 Cell Signaling 4526

Primary antibody Mouse anti-‐PNUTS, 1:1000 BD Biosciences BD 611060

Primary antibody Rabbit anti-‐RPA pS33, 1:1000 Nordic Biosite A300-‐

246A Primary antibody Rabbit anti-‐RPA pS4/S8, 1:1000 Nordic Biosite A300-‐245

Primary antibody Mouse anti-‐𝛾Tubulin, 1:1000 SIGMA-‐ALDRICH T6557

Secondary antibody

Horseradish-‐peroxidase conjugated donkey anti-‐mouse IgG, 1:10 000

Jackson ImmunoResearch

715-‐035-‐150

Secondary antibody

Horseradish-‐peroxidase conjugated goat anti-‐rabbit IgG, 1:10 000

Jackson ImmunoResearch

111-‐035-‐144

ECL SuperSignal® West Pico Chemiluminescent Substrate VWR PIER34080

ECL SuperSignal® West Dura Extended Duration Substrate VWR PIER34075

ECL SuperSignal® West Femto Maximum Sensitivity Substrate VWR PIER34095

3.6 Clonogenic survival assay Material Product Vendor Cat. #

Colony counter pen

E-‐Count Colony Counter with pen

Heathrow Scientific 120000


Staining Methylene blue-‐2-‐hydrat KEBOlab 1.1283-‐100

Staining Sodium hydroxide (NaOH) SIGMA-‐ALDRICH S8045

29

3.7 Buffers and solutions

Buffer Content

Lysis Buffer 2 % SDS 10 mM TrisHCL, pH 7.5 100 µM Na3VO4 (added before use)

Transfer Buffer 200 mL 5x Transfer buffer 600 mL distilled H2O 200 mL ethanol

Running Buffer 10x TGS (25 mM Tris, 192 mM Glycine, 0.1% SDS) pH 8.3 following dilution to 1x with distilled H2O

Flow Staining Buffer

6.5 mM Na2HPO4 1.5 mM KH2PO4 2.7 mM KCl 137 mM NaCl 0.5 mM EDTA Giving pH 7.5 100 µL Igepal per 100 ml buffer

Extraction Buffer

0.5 % TritonX-‐100 20 mM Hepes, pH 7.4 50 mM NaCl 3 mM MgCl2 300 mM Sucrose

Staining solution 30-‐part saturated Methylene blue solution 70-‐part distilled H2O 1-‐part 1% NaOH

31

4 Methods

4.1 Cell culture and cell seeding In this study, all experiments were done using the human osteosarcoma U2OS cell line, derived in

1964 from a tumor of the tibia from a 15-‐year-‐old girl (Niforou, 2008). This cell line has both wild

type RB and TP53 genes (Diller et al., 1990). However, the proteins p16(INK4a) and p14(ARF)

promoters in the INK4a/ARF locus were inhibited by methylation in this cell line (Park et al., 2002).

The p14 protein stabilized p53 by inhibiting MDM2 and induce cell cycle arrest in G1 and G2/M.

MDM2 is a E3 ubiquitin-‐protein ligase and a negative regulator of the p53 tumor suppressor, and is

blocked by p14 (Stott et al., 1998). p16 is a tumor suppressor, which can induce G1 arrest by

inhibiting the phosphorylation of pRb that is facilitated by CDK4/CDK6 (Hara, 1996). Inactivation of

both p14 and p16, and thereby pRB and p53, appears to be essential for the development of

osteosarcoma (Park et al., 2002).

Cells were grown in tissue culture flasks containing Dulbecco´s Modified Eagle Medium (DMEM),

complemented with 10% Fetal Bovine Serum (FBS) and 50 U/mL Penicillin/Streptomycin. Cells were

kept in a humidified incubator at 37°C with 5% CO2.

Mycoplasma tests were performed regularly (by R.G. Syljuåsen using Mycoalert Mycoplasma kit)

and cell line verified by short tandem repeat assay, which is a rapid, PCR-‐based assay for forensic

DNA profiling.

For subculturing the cells, they were first examined with a microscope for estimation of confluence.

The growth medium was then aspirated and the cells were first washed with 10 ml 1% phosphate

buffered saline (PBS), then 2 ml Trypsin/EDTA. Following 5 minutes incubation at 37°C, cell

detachment from the bottom of the flask was examined with a microscope. Cells were re-‐

suspended in fresh medium, and a fraction of this cell suspension was retained in the flask before

adding additional fresh medium. Subculturing was done twice a week.

Cell seeding was done by trypsination and re-‐suspension, following the same procedure as

subculturing. Cell density in the suspension was assessed using a hemacytometer, a glass slide used

for counting cells manually. The cell suspension was diluted in medium to a desired concentration

32

and seeded on polystyrene dishes. Cell density of 2⋅105 cells per 3 ml medium was used for this

purpose.

4.2 WEE1-‐ and ATR-‐inhibition WEE1-‐ and ATR inhibition was obtained by using the small nuclear inhibitors MK1775 and VE822

respectively. These are both ATP-‐competitive compounds that bind the active site of the kinases.

MK1775 inhibits WEE1-‐activity in an ATP-‐competitive manner and with an IC50 of 5.2 nM

(www.selleckchem.com). In this thesis, concentrations of 50nM to 300nM were used.

VE822 inhibits ATR activity and phosphorylation of H2AX. It as an IC50 of 19 nM

(www.selleckchem.com). It is a modified, and more ATR-‐specific homolog of VE821, also a potent

and selective ATP-‐competitive inhibitor of ATR. VE821 has a minimal cross-‐reactivity against related

PIKKs, such as ATM (inhibitor concentration of 16µM), DNA-‐PK (2.2µM), mTOR (>1µM), and PI3K

(3.9µM). I used VE822 concentrations of 50nM to 500nM, and it has an IC50 of 19 nM.

4.3 siRNA transfection RNA interference (RNAi) is a process that can lead to mRNA degradation or transcriptional silencing.

In response to double-‐stranded RNA (dsRNA), the enzyme DICER is activated and cuts the dsRNA

into small fragments (-‐21-‐23 nt), resulting in small interfering RNAs (siRNAs) (Reviewed in (Rana,

2007)). These siRNAs can form part of a multi-‐protein siRNA complex called RISC (RNA-‐induced

silencing complex). This complex binds to complementary mRNA, resulting in knockdown of gene

expression. SiRNA delivery into the cell is performed by a lipid based transfection reagent called

Lipofectamine® RNAiMAX (Invitrogen). Cationic lipids and negatively charged siRNA forms

lipoplexes, lipid and plasmid-‐based complexes, that can be added to the cell medium. Lipoplexes

are then transported into the cell by endocytosis. The siRNA is released into the cytoplasm, and is

then further trafficked into nucleus where siRNA is incorporated into the RNAi pathway (Unciti-‐

Broceta et al., 2010).

SiRNA oligos were dissolved in 1x siRNA buffer with RNase-‐free H2O, to create a stock solution of

20µM, which was aliquoted and stored at -‐20°C.

For optimal transfection, 2⋅105 cells were seeded in 3ml growth medium on 6 cm polystyrene

dishes the day before transfection. The Lipofectamine RNAiMAX transcription protocol from

InVitrogen was used as described below.

33

4µl Lipofectamine was added to 500µl Opti-‐MEM per siRNA (2 dishes) to prepare a mastermix.

Then 4µl of 20µM stock oligos was added to 500µl Opti-‐MEM in separate tubes. 500µl of master

mix was added to 500µl of stock oligo solution and mixed together before incubating at room

temperature for 20 minutes. Cells were given 1,5ml freshly medium and then 500µl of siRNA

solution. The cells were then split after 24 hours and fixated after 62-‐75 hours.

4.4 Hypoxia treatments Hypoxia treatments were performed in an Invivo2 hypoxia chamber (Ruskinn). The chamber

functions as a humidified CO2 incubator for the cells, but in contrast to a normal incubator, it is

airtight. Settings of temperature, humidity, CO2 levels and O2 levels can be strictly controlled. The

chamber has a cuff and sleeve system that allows direct access to the samples, and an interlock

function that allows you to insert and take out materials during the experiment without disrupting

the hypoxic atmosphere. O2 levels can be set as low as 0.1% with N2 gas flushed into the chamber.

With use of H2N2 gas in combination with a palladium catalyst, further reduction of O2 levels to 0.0%

(anoxia) can be achieved. The hypoxia chamber measured O2 levels every minute and these data

were checked after every experiment.

4.5 Flow cytometry Principles Flow cytometry can be used to measure properties of individual cells in a sample, by using laser

light of specific wavelengths focused onto a fluid stream of single cells. Several detectors measure

light changes (e.g. wavelength and direction) from the stream of cells, and these changes are

transformed into information about cell properties by computer software.

In order to analyze one cell at a time, flow cytometry is based on the principles behind fluid

mechanics ((Rahman, 2006) page 4). A solution, containing the sample, is injected into the center of

a faster flowing sheath stream in the cytometer, where movement of the sheath fluid creates a

drag effect on the sample inside the narrowing central chamber. This drag effect initiate changes of

the sample fluid velocity, and creates a single flow of cells that will not mix with the sheath fluid

(laminar flow). Light that hits the cell will be deflected and change direction (scatter) ((Rahman,

2006) page 5). Forward scatter channel (FSC) collect light that is scattered forwards, and gives

information about cell size, while side scatter channel (SSC) gives information about the inner

complexities of the cell, like granular content. Every cell has a unique FSC and SSC.

34

In addition to light scatter detectors, the flow cytometer may also have several fluorescence

detectors ((Rahman, 2006) page 9-‐11). These detectors can measure fluorescent light with different

wavelengths to give qualitative and quantitative information about fluorochrome-‐labeled cell

surface receptors or intracellular molecules, such as DNA. The fluorochromes, or fluorescent dye,

can absorb fluorescent light at a given wavelength and re-‐emit fluorescent light with a longer

wavelength (lower energy). This shift in energy, absorbed versus emitted light, is called the Stokes

shift. The fluorescent detectors detect light emitted from fluorophores at the cells, and the specific

detection is controlled by optical filters, which can block light of certain wavelengths while

transmitting others. By using multiple fluorochromes we can measure several parameters of the

sample simultaneously, but it is important that the emission light of one fluorochromes does not

overlap too much with the absorbed light to another, as that could give us misleading information

((Rahman, 2006) page 14).

Staining with Hoechst and antibodies The fluorescent dye Hoechst, which binds to the minor groove in DNA, can be used to measure DNA

content of cells. In the experiments we have used Hoechst 33258, which has an absorption

maximum at 346 nm and an emission maximum at 460 nm (www.sigmaaldrich.com). Information

about cell distribution of a sample according to cell cycle phase, can be viewed in a DNA histogram

where number of cells are plotted against Hoechst signal (Figure 5A). Normal cells in G1 or G0

phase can contain 2N DNA, G2 or M phase cells can contain 4N DNA, and S phase cells can contain

between 2N and 4N DNA. Two or more cells can clump together and be measured as a single event,

which will deviate from the actual cell cycle events (Wersto, 2001). These clumps need to be

excluded from data analysis and this can be done by gating based on width and area of the Hoechst

signal, since a doublet will be wider than a singlet with the same area (Figure 5B). Then we can gate

out only single events and only include these in futher analysis (Figure 5C).

Two primary antibodies have been used in this project. One is from rabbit, specific against the

phosphorylated Ser10 residue of Histone H3, a mitotic marker (Pérez-‐Cadahía et al., 2009). The

other from mouse, against the phosphorylated Ser139 residue of Histone H2AX, a marker for DNA

damage (Bakkenist and Kastan, 2003). Additional secondary Alexa-‐fluorophore conjugated

antibodies are used: Alexa Fluor 488 (donkey anti-‐rabbit IgG) with maximum absorption at 496 nm

and maximum emission at 519 nm, and Alexa Fluor 647 (goat anti-‐mouse IgG) with maximum

absorption at 650 nm and maximum emission at 665 nm (www.lifetechnologies.com).

35

Figure 5. DNA profile and gating based on Hoechst staining. A) Among the singlets, the G1/G0 phase cells contain 2N DNA and G2/M phase cells contain 4N DNA. Cells with an intermediate DNA content are considered as S phase cells. The DNA stain Hoechst is used to produce the cell cycle profile of the sample, and gives information about the distribution of cell cycle phase versus cell population. B) These signals have the same area, but width can differ and is used to distinguish singlets from doublets. C) Picture showing singlets that are being separated from doublets that adhered together in the sample and registered as one cell. Singlets are gated out from can be analyzed further. When the area is plotted against width in the DNA signal, we can separate G2/M singlets that have 4N DNA and G1/G0 doublets that also have 4N DNA by measuring width.

Sample preparation Cells were harvested by trypsination and fixed in 70% EtOH. Samples were stored at -‐20°C until

staining. On the day of experiment, the samples were washed with 5 ml PBS with 1% FBS, spun

down for 5 minutes, and supernatant was aspirated. The pellet was blocked by re-‐suspending with

50 µl of flow staining buffer with 4% milk for 5 minutes, before 50 µl primary antibody solution with

antibody and flow staining buffer with 4% milk was added and incubated for 1 hour. The pellet was

then again washed with 5 ml PBS with 1% FBS as described above. The new pellet was now re-‐

36

suspended in a secondary antibody solution and incubated in a dark place for 1 hour, and the

washed again with 5 ml PBS with 1% FBS. Pellet was then re-‐suspended in 0.5 ml PBS with 1.5 µl

Hoechst per 1 ml of PBS. The samples were wrapped in aluminum foil and stored at 4°C overnight.

The day after the samples were transferred into 5 ml flow tubes and all the samples were vortexed

briefly before running them on the flow cytometer. Gating was set after the untreated sample.

4.6 Immunofluorescence microscopy Immunofluorescent (IF) microscopy shares some of the basic principles with flow cytometry analysis

regarding fluorophores, light absorption and fluorescent light emission. In a fluorescent

microscope, the cells are illuminated with light of a specific wavelength that can be absorbed by

fluorophores and subsequently emit light with longer wavelength, which can be detected by

florescence detectors ((Shapiro, 2003) page 8). There can be several excitation filters in a

microscope that each is specific for different wavelengths that can be used in combination with

different fluorophores to examine several cell properties of a sample. Immunofluorescence can be

a useful technique to label proteins and other molecules because of highly specific binding of an

antibody to an antigen.

2⋅105 cells per 2ml medium were plated out on sterile glass coverslips in 35mm polystyrene dishes.

After 24 hours the coverslips were washed with PBS, fixed by adding 10% formalin solution for 15

minutes at room temperature, and then washed with PBS again (3x2mL). The cells were then

permeabilized in PBS with 0.5% Triton X-‐100, a nonionic detergent, for 5 minutes to dissolve lipids

from the cell membrane making them permeable to antibodies. Following another step of washing

with PBS (3x2mL) and incubated for 1 hour at room temperature with a γH2AX-‐specific antibody

diluted 1:250 in DMEM with FBS and PBS . This was followed by washing and 30 minutes’ incubation

with Alexa Fluor anti-‐mouse 488 antibody (diluted 1:1000). Coverslips were again washed with PBS,

rinsed with milliQ-‐H2O and left on paper towel to dry. Dried coverslips were mounted onto glass

slides using DAPI in Vectashield medium, and sealed using nail polish around the edges of the

coverslips. Samples were then imaged in an Axio Imager Z1-‐microscope, using Axio Vision release

4.8 Software.

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4.7 SDS-‐PAGE Sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-‐PAGE) is a method used for

separating proteins in response to an electric field. Proteins will migrate trough pores in the gel

according to size. Larger proteins have greater resistance and will migrate slower through the gel

than smaller proteins. In preparation of SDS-‐PAGE the proteins are added loading sample buffer

(LSB) that contains SDS (sodium dodecylsulfate), DTT (dithiothreitol), and glycerol. SDS is a

denaturing detergent that binds to the protein and gives them a uniform negative charge. DTT

reduces disulfide bonds. Glycerol increases the density of the samples so they sink to the bottom of

the wells (Gallagher, 2001).

Cells in dishes were washed with PBS and lysed by adding 150µl lysis buffer with Na3VO4 (sodium

orthovanadate) per dish. The lysate was gathered using a rubber scrape and transferred to an

Eppendorf tube. The lysates were kept in -‐20°C until use.

The lid of the tube was pierced using a needle and samples were boiled at 95°C for 5 minutes

before they were spun down. New lysates were made by adding 15 to 22.5 µl LSB, and boiled again

at 95°C. The samples were pipetted up and down several times before being loaded to a

polyacrylamide gel with either 4-‐15% or 4-‐20% acrylamide content. Rainbow molecular weight

marker was loaded as a guide for proteins. Gels were placed in Bio-‐Rad´s mini chambers with Tris-‐

Glycine running buffer containing SDS. The gel was first run at 70V for 30 minutes and then 200V

for another 40-‐60 minutes, depending on the size of protein of interest.

4.8 Western blot After separating proteins by gel electrophoresis, they were transferred onto a nitrocellulose

membrane so that the proteins of interest could be detected by immunoblotting with specific

antibodies. The gel and membrane were stacked between filter paper wetted with transfer buffer,

put into a gel holder cassette, and placed into a chamber between two electrodes. When applied

current, the proteins were pulled from the gel towards the anode and onto the membrane.

Ponceau S was used for rapid detection of protein bands on the membrane, and the membrane

was cut into smaller pieces containing the different proteins. Blocking was done in PBS with 0.1%

Tween (PBS-‐T) and 5% milk for 1 hour at a shaker to reduce non-‐specific binding. All antibodies

were diluted in PBS-‐T with 5% milk. The primary antibodies were added to their respective

membrane pieces, and incubated overnight at 4°C. The day after, membrane pieces were washed in

38

PBS-‐T 3x5 minutes. HRP (Horseradish peroxidase)-‐conjugated secondary antibodies were diluted in

PBS-‐T with 5% milk, applied to membrane pieces and left in room temperature for 1 hour. They

were again washed in PBS-‐T 3x5 minutes, before adding Supersignal ECL (Enhanced

Chemiluminescent) and placed between two clear plastic films. The HRP converts the ECL into a

chemiluminescent signal which can be detected and then imaged using Chemidoc.

4.9 Clonogenic survival assay Clonogenic survival assay is used to estimate cell survival and ability to continue proliferation after

treatment (Franken et al., 2006). In this project, the cells were treated with WEE1-‐inhibitor MK1775

and ATR-‐inhibitor VE822 both alone and in combination, and it was investigated for decreased

cellular response to the inhibitors.

U2OS cells can be plated out directly in the medium with the kinase inhibitors.

At day 1, medium was prepared with inhibitor and 3ml was added to 6cm dishes. Then the cell

dilutions were prepared, using 150 cells per dish for low toxic treatments, and 300 cells per dish for

more toxic treatments. 100µl of cell dilution was added to the medium containing inhibitors. The

dishes were placed in the incubator at 37°C with 5% CO2 for 24 hours. At day 2, medium was

sucked out from the dishes and replaced with 4 ml of fresh medium, and were continued stored in

the incubator. Additionally, 1 ml of fresh medium was added after one week. After two weeks the

dishes was ready to be fixed. Medium was sucked off and 2 ml of 70% EtOH was added and left in

the dishes for 30 minutes. The dishes were then washed with distilled water and left to dry up-‐side

down with the lid off. When dried, the dishes were stained with methylene blue staining solution

and again washed with distilled water and left to dry. When the dishes were dry, the colonies could

be counted. Only the colonies composed of at least 50 cells were counted.

39

5 Results Before I started with my thesis, the previous master student in our group (Håve, 2015) had

performed a siRNA screening test with multiple DNA damage signaling factors. These factors could

potentially protect cancer cells from hypoxia-‐induced replication stress. Different siRNA oligos were

used and changes in replication stress response were measured after hypoxia treatment. S-‐phase

levels of the DNA damage marker γH2AX were compared before and after hypoxia treatment. A

good candidate hit should show a low percentage of γH2AX positive cells in the normoxic sample,

similar to the percentage of γH2AX positive cells in the control transfected cells, and a significantly

higher percentage of γH2AX positive cells in hypoxic sample (Håve (2015). My validation of the

siRNA screen is presented in paragraph 5.1. The results of the effect of WEE1 and ATR inhibition are

presented in paragraphs 5.2-‐5.6. The result of using the iron chelator desferrioxamine as a hypoxia

mimetic agent is presented in paragraph 5.7.

5.1 Validate candidate hits with siRNA screen In the master project by T. Håve, it was performed a siRNA screen that identified several potential

candidate hits that were suggested to selectively targeting hypoxic cancer cells. Some of these

potential candidates were selected for further validation in this project, as they showed an increase

of γH2AX positive cells in hypoxia-‐treated cells compared to normoxic samples. The reason for

repeating some candidate hits was because the previous screen was performed with cells grown in

glass dishes that further increased γH2AX signaling, and we wanted to repeat it with polystyrene

dishes. The proteins in focus in this validation experiment were ATR, NIPP1, Rad17, and WEE1. An

additional non-‐targeting siRNA was used as a negative control. For each siRNA transfection, U2OS

cells were seeded out in dishes the first day (see experimental procedure Figure 6A). At day 2, cells

were transfected with siRNAs (see § 4.3) and the next day the cells were split into three dishes,

each for different analysis. At day 4, one dish from each siRNA transfected triplicates were placed

into a hypoxic chamber for a 20 hours´ incubation at 0.0% O2, and then continued with another 3

hours´ reoxygenation at 21% O2 before fixation for flow cytometry. The other two dishes were

incubated at 21% O2 in a humidified incubator for 23 hours before they were fixed and harvested

for flow cytometry and western blotting. An untreated Mock sample was always fixed inside the

hypoxic chamber after 20 hours (Figure 6E) to confirm that the cells have γH2AX levels consistent

with hypoxia-‐induced replication stress, and an increase in γH2AX is shown in these cells. Normal,

40

untreated Mock cells were also fixed for flow cytometry and western blotting analysis. SDS-‐PAGE

followed by western blotting was used to check knockdown of proteins and flow cytometry for

measuring DNA damage. All of the proteins tested showed good knockdown after transfection with

their specific siRNAs (Figure 6B). γ-‐Tubulin was used as a loading control. The flow cytometry

analysis shows an increase of γH2AX positive cells in ATR, NIPP1 and WEE1 siRNA-‐transfected cells

after hypoxia followed by reoxygenation, but not in Rad17 transfected cells (Figure 6B). DNA cell

cycle profiles in Figure 6C show that there is more stalling of cells in early S-‐phase after hypoxia

treatment. As there was no Mock fixed after reoxygenation, the non-‐targeted siRNA (Figure 6C)

serves as a negative control equally to the untreated sample and shows a decrease in γH2AX in

reoxygenated cells compared to cells fixed inside the hypoxic chamber.

Figure 6. Experiment 1. Validation of siRNA screen. A) Experimental setup for siRNA transfection. B) Western blot showing measurement of protein downregulation. U2OS cells were transfected with the indicated siRNAs and split into 3 dishes after 24 hours, and incubated at 21% O2 until cell harvest at 72 hours. C) Flow cytometry dot plots showing γH2AX versus DNA content for parallel samples in the same experiment as in B. Gates and numbers indicate γH2AX positive cells. D) Cell cycle profiles of transfected cells incubated at 21% O2 (upper panel) or 20 hours at 0.0% O2 followed by 3 hours 21% O2 (lower panel). Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown. E) Untreated Mock cells showing an increase of γH2AX when fixed in hypoxia chamber after 20 hours incubation. γH2AX versus DNA content in dot plot (left panel), and histogram of DNA cell cycle profile (right panel) is shown.

41

The experiments with ATR and NIPP1 siRNAs were repeated (Figure 7). Figure 2A shows a small

increase of γH2AX in the cells fixed in hypoxic conditions before it decreases after reoxygenation, as

we indicated in experiment 1. The DNA cell cycle profile shows accumulation of cells in late G1 or

early S-‐phase after treatment of hypoxia and reoxygenation, indicating that cells are arrested at the

G1/S checkpoint and prevented from progressing further in the cell cycle. The flow cytometry

analysis in this experiment only shows a small increase of γH2AX after transfection with siATR and

none with siNIPP1 (Figure 7B). It is difficult to know if this is due to poor protein knockdown or

other errors, since protein knockdown with western blot is missing due to technical problems. In

Figure 7C we can again see accumulation in early S-‐phase in NIPP1 siRNA transfected cells after

hypoxia treatment, indicating cell cycle arrest.

Figure 7. Experiment 2. Validation of siRNA screen. A) Untreated Mock cells showing γH2AX versus DNA content (left panel) and histogram of DNA cell cycle profile (right panel). Mock cells were fixed after incubation in normoxia, hypoxia, and hypoxia and reoxygenation. B) Dot plots showing γH2AX versus DNA content for same cells shown in B. Gates and numbers indicate percentage of γH2AX positive cells. C) Cell cycle profiles of transfected cells and incubated at 21% O2 (upper panel) or 20 hours at 0.0% O2 followed by 3 hours 21% O2 (lower panel). Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown.

42

5.2 Determine concentration of ATR-‐inhibitor VE822 Since ATR was shown to be a potential candidate hit several times (Figure 6 and 7), we wanted to

investigate how ATR inhibition would affect cell cycle progression. The ATR inhibitor VE821 has

previously been used in our lab, but we wanted to examine a new inhibitor currently in clinical

trials, VE822, which is a homolog of VE821. One reason for this is the need for rather high

concentrations of VE821 to achieve full inhibition of ATR (10µM), so we wanted to see if lower

concentration of VE822 could give the same inhibitory effect on ATR. One way to do this is to check

the levels of ATR-‐dependent phosphorylations after irradiation with 6Gy, using different

concentrations of the VE822 and comparing it to the concentration that we use in our lab for VE821

(10µM). One sample without inhibitor was also harvested after irradiation, and one control-‐sample

with VE822 was harvested without irradiation. In figure 8 we see that both 500nM and 1µM of

VE822 gave equal inhibition of phosphorylation of Chk1 on Ser317 (pChk1 S317) as 10µM VE821

did. The ATR-‐dependent RPA phosphorylation at Ser33 is also inhibited at these concentrations.

Higher inhibitor concentrations than needed can lead to increased toxicity and unspecific effects,

which we want to avoid, so we continued to use 500nM in the next experiments for inhibition of

ATR.

Figure 8. Measuring ATR inhibition with VE822. Western blot showing measurement of protein phosphorylations and levels. Cells with different inhibitor concentrations were irradiated with 6 Gy and harvested 1.5 hours later.

43

5.3 Effects of MK1775 and VE822 treatment in combination with hypoxia Next we wanted to test the effect of ATR inhibition after treatment with hypoxia and also in

combination with the WEE1 inhibitor MK1775, since WEE1 was also a candidate hit in the siRNA

screen (Figure 6). There has recently been shown synergy between MK1775 and Chk1 inhibitors,

and this could potentially be a useful anti-‐cancer strategy in therapy (Carrassa et al., 2012; Chilà et

al., 2015; Hasvold et al., 2013; Russell et al., 2013). Since Chk1 is one of the substrates downstream

from ATR it could be interesting to see whether inhibition of ATR, alone and in combination with

MK1775, gives increased DNA damage during S-‐phase. This can be measured by flow cytometry

after inhibition treatment (see § 4.2) using γH2AX as a marker for DNA damage in S-‐phase. The

experimental setup is showed in Figure 9A. Cells were given medium containing each of the

inhibitors, MK1775 (300nM) and VE822 (500nM), or both in combined treatment. One set of dishes

were incubated at 0.0% O2 in the hypoxia chamber for 20 hours followed by 3 hours reoxygenation

at 21% O2 before the cells were fixed (Figure 9B, lower panel). Normoxic samples, the other set,

were also treated simultaneously with inhibitors for 23 hours at 21% O2 before the cells were fixed

(Figure 9B, upper panel). Untreated Mock cells were also fixed. In response to Wee1 inhibition,

there is a significant increase of γH2AX in both the hypoxic-‐ and normoxic-‐treated samples,

indicating increased DNA damage. The effect does however appear to be even greater in the

hypoxia/reoxygenation-‐treated cells than in the cells grown in normoxia, consistent with the siRNA

experiments for WEE1 (Figure 6C). ATR inhibition gives a smaller increase of γH2AX after hypoxic

treatment than WEE1 inhibition, but again the response is greater in the hypoxic/reoxygenated

samples than in the normoxic ones. However, the most interesting result is the massive synergistic

effect of the combined treatment with MK1775 and VE822, particularly seen in normoxic samples

(Figure 9B). The cell cycle profiles are shown in Figure 9C, where we can see a large amount of cells

that are stalled or accumulate in S-‐phase upon the combined treatment.

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Figure 9. Experiment 1. S-‐phase DNA damage after inhibitors. A) Experimental setup. B) Dot plots showing γH2AX versus DNA content. Cells were treated with inhibitors for 23 hours either at 0.0% O2 for 20 hours followed by 3 hours at 21% O2(Lower panel) or at 21% O2 (Upper panel). Gates and numbers indicate γH2AX positive cells. C) Cell cycle profiles of inhibitor-‐treated cells. Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown with percentage cells in G1, S, and G2-‐phase.

The effects of MK1775 and VE822 were also measured when the inhibitors were administered for 3

hours after hypoxic incubation . The experimental setup is shown in Figure 10A. Cells were

incubated at 0.0%O2 in the hypoxic chamber for 20 hours before treatment with the inhibitors

immediately after reoxygenation at 21% O2 , and fixed 3 hours later (Figure 10B, Lower panel).

Normoxic samples were also collected, and were treated simultaneously with inhibitors for 3 hours

(Figure 10B, Upper panel). Compared to the results observed in Figure 9B, we see lower γH2AX in

the samples with MK1775, but higher levels in samples with VE822. Again, we can see the

synergistic effect of the combined treatment with both inhibitors. The cell cycle profile (Figure 10C)

shows less accumulation of cells in S-‐phase than Figure 9C, but there is a higher percentage of cells

45

both in G1 and S phase in the hypoxia samples, indicating cell cycle arrest. In the next sections we

wanted to further examine this synergistic effect between MK1775 and VE822 treatment.

Figure 10. Experiment 2. S-‐phase DNA damage after inhibitors. A) Experimental setup. B) Dot plots showing γH2AX versus DNA content. Cells were treated with inhibitors for 3 hours after incubation in 0.0% O2 (Lower panel) or 21% O2

(Upper panel). Gates and numbers indicate γH2AX positive cells. C) Cell cycle profiles of inhibitor-‐treated cells. Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown with percentage of cells in G1, S, and G2-‐phase.

46

5.4 Effects of MK1775 and VE822 treatment after hypoxia After seeing the synergistic effect of combination treatment for 3 hours with MK1775 and VE822

(Figure 10), we wanted to verify this effect by repeating the 3 hours´ treatment with inhibitors both

after hypoxic incubation and in normoxic cells. The Mock samples in Figure 11A show a small

increase of γH2AX in cells fixed inside hypoxic chamber at 0.0% O2 that decreases again after

reoxygenation, as seen in previous sections. The flow cytometry analysis in Figure 11B also show

the same synergistic effect, after combined MK1775 and VE822 inhibition (as in § 5.3). The S-‐phase

DNA damage is slightly more severe in the hypoxia exposed cells, yet with less effect than in Figure

10. The effect of MK1775 after hypoxia was neither not enhanced as much as in Figure 10.

In addition to repeating the flow cytometry analysis-‐experiment, we also wanted to find out

whether inhibition of WEE1 and/or ATR activates or inhibits other cell cycle or DNA damage

response regulators. We therefore collected both normoxic and hypoxic samples for Western

blotting simultaneously with the samples analyzed with flow cytometry. Western blotting was used

with antibodies towards the component of interest, as shown in Figure 11D. In the combination

treatment with both inhibitors, we see highly increased DNA-‐PK phosphorylation in both normoxic

and hypoxic samples. With loss of ATR activity in S-‐phase, cells will compensate by activating ATM

and DNA-‐PK to induce DNA repair (Buisson et al., 2015). Activation of ATM was measured by

autophosphorylate on Ser1981 (Bakkenist and Kastan, 2003) (Figure 11D). RPA S4/S8

phosphorylation is a marker for ssDNA and is also highly increased after combination treatment

with both inhibitors. Activated ATM also phosphorylates its downstream substrate Chk2 at

threonine 68, as we also see after combination treatment. However, Chk1 phosphorylation is

suppressed when inhibiting ATR, as expected, since Chk1 is activated by ATR by phosphorylation.

This experiment was repeated twice (Figure 12 and 13) with the same results, showing synergistic

effects after combined treatment with inhibitors. In the western blotting seen in Figure 12D we also

examined phosphorylation of CDK1, where it shows decreased inhibitory phosphorylation on

tyrosine 15 on CDK1 after WEE1 inhibition. We will examine CDK activity more closely in § 5.7, as

this is a possible mechanism behind the synergistic effect between MK1775 and VE822. Since the

combination treatment also gives a synergistic effect on the DNA damage response in normoxic

cells, we repeated the inhibition only in normoxic samples to further verify the effects (Figure 14).

When searching for the mechanisms behind the synergistic effect, it is easier to perform such

experiments without hypoxia.

47

Figure 11. Verification of synergistic effect. A) Untreated Mock cells showing γH2AX versus DNA content (left panel) and histogram of DNA cell cycle profile (right panel) with percentage cell distribution in G1, S, and G2 phase. Mock cells were fixed after incubation in normoxia, hypoxic, and hypoxia and reoxygenation. B) Dot plots showing γH2AX versus DNA content. Cells were treated with inhibitors for 3 hours after incubation in 0.0% O2 (Lower panel) or 21% O2

(Upper panel). Gates and numbers indicate γH2AX positive cells. C) Cell cycle profiles of inhibitor-‐treated cells. Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown with percentage of cells in G1, S, and G2-‐phase. D) Western blot showing how combined inhibition of WEE1 and ATR effects on different DDR components. Cells were treated with WEE1 and ATR inhibitors, incubated for 3 hours and harvested. “Mock fix” is the sample fixed inside hypoxia chamber.

48

Figure 12. Verification of synergistic effect. A) Untreated Mock cells showing γH2AX versus DNA content (left panel) and histogram of DNA cell cycle profiles (right panel) with percentage cell distribution in G1, S, and G2 phase. Mock cells were fixed after normoxic, hypoxic, and hypoxic and reoxygenated incubation. B) Dot plots showing γH2AX versus DNA content. Cells were treated with inhibitors for 3 hours after incubation in 0.0% O2 (Lower panel) or 21% O2 (Upper panel). Gates and numbers indicate γH2AX positive cells. C) Cell cycle profiles of inhibitor-‐treated cells. Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown with percentage of cells in G1, S, and G2-‐phase. D) Western blot showing how combined inhibition of WEE1 and ATR effects on different DDR components. Cells were given WEE1 and ATR inhibitors, incubated for 3 hours and harvested. “Mock fix” is the sample fixed inside hypoxia chamber.

49

Figure 13. Verification of synergistic effect. A) Untreated Mock cells showing γH2AX versus DNA content (left panel) and histogram of DNA cell cycle profiles (right panel) with percentile cell distribution in G1, S, and G2 phase. Mock cells were fixed after normoxic, hypoxic, and hypoxic and reoxygenated incubation. B) Dot plots showing γH2AX versus DNA content. Cells were treated with inhibitors for 3 hours after incubation in 0.0% O2 (Lower panel) or 21% O2 (Upper panel). Gates and numbers indicate γH2AX positive cells. C) Cell cycle profiles of inhibitor-‐treated cells. Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown with percentage of cells in G1, S, and G2-‐phase.

Figure 14. Verification of synergistic effect. A) Dot plots showing γH2AX versus DNA content. Cells were treated with inhibitors for 3 hours in normoxia and harvested. Gates and numbers indicate γH2AX positive cells. B) Cell cycle profiles of inhibitor-‐treated cells. Flow cytometric analysis of cell count versus DNA content (Hoechst staining) is shown with percentage of cells in G1, S, and G2 phase.

50

Figure 15. Verification of synergistic effect. Experiment 1 and 2. Western blot showing effects after inhibition. Experiment 1 with flow analysis in Figure 14, and experiment 2 are western blot for the experiment in Figure 13. Both experiment show western blots from normoxic samples. Cells were given WEE1 and ATR inhibitors, incubated for 3 hours and harvested.

51

5.5 Measurement of cell survival We wanted to examine whether treatment with WEE1 and ATR inhibitors influences the survival of

cells. This was done by performing clonogenic survival assays in normoxic conditions. Cells were

seeded with both MK1775 and VE822 with different concentrations, on their own and in

combination, and incubated for 24 hours before replacing the medium with inhibitors with fresh

medium, and the cells were grown for 14 days before the colonies were counted. Figure 16A shows

dishes with surviving cell colonies fixed and stained, ready to be counted. The resulting survival

curve shown in Figure 16B suggests that cells treated with the highest concentration of inhibitors

(200nM) in combination have very poor survival outcome. Cells treated with MK1775 alone show

little inhibitor-‐induced cell death.

Figure 16. Clonogenic assay to measure cell survival. A) Picture of polystyrene dishes with cell colonies ready to be counted. B) Survival of U2OS cells treated with MK1775 and/or VE822, at concentrations 0, 50, 100 and 200nM for 24 hours. Medium with inhibitors was then replaced with fresh medium, and cell colonies grown for 14 days before fixation. The experiment was repeated 3 times and in all experiments there were triplicates for each sample condition. Error bars indicate standard error of mean (SEM).

52

5.6 Fluorescence imaging of MK1775 and VE822 treated cells Since we see a synergistic increase of DNA damage with combination treatment with the inhibitors,

we wanted to visualize the damage using immunofluorescence. Cells were stained for γH2AX and

viewed in a fluorescence microscope. In Figure 17 we see a strong increase of γH2AX in the

combination treatment sample. This correlates with the flow cytometry results, that WEE1 and ATR

inhibitors in combination gives high increase of γH2AX in S-‐phase. Another interesting result that

we discovered was that inhibition with VE822 results in visual micronuclei around the cells (Figure

18). This was also observed in the combination treatment.

Figure 17. S-‐phase effects of inhibitors. Images taken by IF microscopy of U2OS cells given MK1775 and VE822 with both a concentration of 200nM, fixed after 24 hours, and stained for γH2AX to measure DNA damage, and DNA stain DAPI.

53

Figure 18. DAPI stained DNA with inhibitors. Black and white picture of DAPI stained cells, showing that VE822 causes micronuclei outside of the cells. Some of them are shown with arrows.

54

5.7 Exploring the mechanism behind the synergistic effect between MK1775 and VE822 After finding that MK1775 and VE822 synergistically increase DNA damage in S-‐phase, and that they

synergistically decrease clonogenic survival, we wanted to investigate if CDK1 and CDK2 activity

correlates with the DNA damage induction as a possible mechanism behind this effect. WEE1 and

ATR are normal regulators of the cell cycle progression (see § 1.2.3). Activated WEE1 can inactivate

CDK1 or CDK2 by inhibitory phosphorylation at tyrosine 15 (Beck et al., 2010; Sørensen and

Syljuåsen, 2012), while active ATR phosphorylates and activates Chk1, leading to CDC25

degradation (Furnari et al., 1997; Sanchez et al., 1997). When degraded, CDC25 will not be able to

remove inhibitory phosphorylation on tyrosine 15. By inhibiting both WEE1 and ATR, we would thus

expect less inhibitory phosphorylation of CDKs and thereby higher CDK activation. In order to show

the phosphorylation effect of WEE1 and ATR inhibition, and most importantly inhibitory

phosphorylation of CDK, cells were treated with MK1775 and VE822, and phosphorylation analyzed

by using SDS-‐PAGE and western blotting (Figure 19A). Flow cytometry verified the synergy between

the inhibitors (Figure 19B). Figure 19A shows the same activation of DNA-‐PK, ATM, Chk2, as well as

RPA as seen in § 5.4, however only after inhibition with MK1775 and/or VE822 for 3 hours with the

combined treatment and not after 1 hour. We also see, as in § 5.4, that pChk1 is suppressed when

ATR is inhibited (Figure 19A). The interesting result is that inhibitory phosphorylation of CDK1 is only

downregulated after WEE1 inhibition and not after ATR inhibition. This experiment was repeated

(Figure 20 and 21) and the same tendency is shown with inhibitory phosphorylation at tyrosine 15

on CDK2 (Figure 20A and 21A) as with CDK1. Quantifications of western blot analysis from Figure 20

are shown in Figure 22, these correlate with the results described further up in this section. Figure

21A however, shows activation of these proteins also after 1-‐hour incubation with the inhibitors.

The low activation seen after 3 hours in experiment 3, is likely due to uneven distribution when

performing SDS-‐PAGE or blotting with antibodies. Figure 23A indicates the average γH2AX signaling

from flow cytometry analysis from § 5.3, § 5.4 and here in § 5.7, and shows the high increased

γH2AX after combination treatment with MK1775 and VE822. These results can be calculated

relative to S phase cell distribution, seen in Figure 23B, and correlate well with results seen in Figure

23A.

55

Figure 19. Experiment 1. Analysis of synergistic mechanism. A) Western blot analysis for samples collected 1 and 3 hours after treatment. U2OS cells were exposed to MK1775 (300nM) and VE822 (500nM) for 1 and 3 hours. 12.5%, 25%, 50% and 100% of the untreated sample Mock was loaded in the four first lanes to create a standard curve for each antibody. B) Flow cytometry analysis of the inhibitors for measuring γH2AX in S-‐phase cells after 3 hours treatment with inhibitors. C) Cell cycle profiles after treatment with MK1775 and/or VE822, indicating distributions in G1, S and G2 phase.

56

Figure 20. Experiment 2. Analysis of synergistic mechanism. A) Western blot analysis for samples collected after 1 and 3 hours’ treatment. U2OS cells were exposed to MK1775 (300nM) and VE822 (500nM) for 1 and 3 hours. 12.5%, 25%, 50% and 100% of the untreated sample Mock were loaded in the four first lines to create a standard curve for each antibody for quantification. B) Flow cytometry analysis of the inhibitors for measuring γH2AX in S-‐phase cells after 3 hours treatment with inhibitors. C) Cell cycle profiles after treatment with MK1775 and/or VE822, indicating distributions in G1, S and G2 phase.

57

Figure 21. Experiment 3. Analysis of synergistic mechanism. A) Western blot analysis for samples collected after 1 and 3 hours´ treatment. U2OS cells were exposed to MK1775 (300nM) and VE822 (500nM) for 1 and 3 hours. 12.5%, 25%, 50% and 100% of the untreated sample Mock were loaded in the four first lanes to create a standard curve for each antibody. B) Flow cytometry analysis for measuring γH2AX in S-‐phase cells after 3 hours treatment with inhibitors. C) Cell cycle profile after treatment with MK1775 and/or VE822, indicating distributions of cells in G1, S and G2 phase.

58

Figure 22. Quantifications of western blotting analysis of DNA damage response and cell cycle regulators. Experiment 2. Quantification analysis of western blotting from experiment 2. Histograms shows phosphorylated kinases relative to Chk1.

Figure 23. A) Histogram of average γH2AX positive fractions from experiments in 5.3, 5.4, and 5.7. Normoxic samples shown as the darkest bars (n=8), and hypoxic samples as the lightest bars (n=4). B) Average γH2AX fractions from A relative to fraction of S phase cells in the same experiments. Error bars indicate standard error of mean (SEM).

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5.8 Desferrioxamine as a replacement for hypoxia chamber Due to technical problems, the hypoxic chamber did not always function properly, and to prevent

delay performing experiments, there could be time saved by having an alternative experimental

setup for whenever it is out of order. Desferrioxamine (DFO) has been shown to induce replication

arrest that can cause genetic instability similar to hypoxic conditions (As mentioned in §1.4.4), and

it is a commonly used hypoxia-‐mimetic agent. To find the proper concentration of DFO to induce

the same amount of DNA damage as the hypoxic incubator, we tested different concentrations of

DFO in comparison to untreated Mock cells. Half of the dishes were fixed 20 hours after adding

DFO, and the other half were treated with DFO for 20 hours, washed, and given fresh medium for

another 3 hours before fixation, to mimic the experiments with reoxygenation after hypoxia

treatment. As we can see in Figure 24, there is an increase of γH2AX in S-‐phase cells after DFO

treatment when we fixed the cells after 20 hours. After washing with fresh medium and letting the

cells incubate for additional 3 hours, we see a reversible effect in γH2AX in the cells treated with

10µM DFO, whereas the cells treated with higher concentrations continued to have the high levels

of γH2AX. This indicates that DFO caused too much DNA damage or replication stress with the

higher concentrations for the cells to repair it within these three hours. If we were going to use DFO

as a substitute for hypoxia chamber, we want to have a reversible effect of the DNA damage,

indicating that 10µM of DFO is a potentially usable concentration for the hypoxia-‐mimetic agent.

Figure 24. Cells treated with different DFO concentrations. Flow cytometry analysis of γH2AX versus DNA content. Cells were treated with DFO for 20 hours before fixation or treated with DFO for 20 hours before washing and incubation for a further 3 hours, before fixation.

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6 Discussion

6.1 General discussion

The initial purpose of this study was to examine the effect of hypoxia-‐induced replication stress

after siRNA knockdown or inhibition of key elements involved in cell cycle progression and DDR.

First, we did a validation of a previously performed siRNA screen test, with candidate hits involved

in the DDR. We examined recovery of the cells after hypoxia-‐induced replication stress and

reoxygenation, and showed that ATR, NIPP1 and WEE1 are potential targets for inhibiting this

recovery in hypoxic cells.

Both WEE1 inhibitor MK1775 and ATR inhibitor VE822 are two targeting drugs in clinical trials, and

further study was to investigate the role of MK1775 and VE822 and examine how they influence the

S phase effect with or without hypoxia. As they showed high degree of synergy of γH2AX signals in

S-‐phase cells, we also wanted to examine some of the potential mechanisms behind this effect.

6.2 Validation of siRNA screen

In this project, we started to transfect cells with some candidate siRNAs for protein knockdown for

validation of previous studies (Håve, 2015). A good candidate siRNA would, as mentioned, show low

percentage of γH2AX positive cells in normoxic samples, and high percentage of γH2AX positive cells

after hypoxia treatment. As ATR, NIPP1, Rad17, and WEE1 all have been shown to be potential

candidate hits, we repeated the siRNA screen with these proteins. Based on the criteria for elevated

γH2AX positive cells after hypoxia, we saw that ATR, NIPP1, and WEE1 fulfilled the criteria, whereas

Rad17 did not because of already high levels of γH2AX in normoxic cells (Figure 6B). In the repeated

experiment (Figure 7B), only siATR transfected cells had an increase of γH2AX after hypoxia

treatment, which was smaller than in the first experiment. However, as mentioned, protein

knockdown was not measured in the repeated experiment. In the first experiment we have seen

almost complete knockdown of ATR (Figure 6B), and it would have been interesting to see if poor

protein knockdown in the second experiment could explain the poor increase of γH2AX. To further

validate the siRNA screen, these experiments could be repeated with additional siRNA oligos

towards NIPP1, ATR and Wee1, due to the possibility of off-‐target effects. A siRNA oligo could

potentially hit and knock down other target proteins because of partial sequence overlap. In

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addition to the siNIPP1 used in §5.1, we have tested knockdown with another siNIPP1, and they

both gave highly reduced protein levels after transfection (Figure 25, Supplement). The next step

would be to use both siNIPP1 oligos in a hypoxia experiment with flow cytometry analysis to see

whether they both increase γH2AX.

Our result that siRNA depletion of ATR caused increased γH2AX in the hypoxia exposed cells, is

consistent with a previous study where siRNA knockdown of ATR caused sensitization of cells to

hypoxic condition and promoted cell death of cancer cells (Hammond et al., 2004). Knockdown of

ATR has also been associated with poor recovery after hypoxia-‐induced replication stress.

Furthermore, the ATR inhibitor VE822, has also been shown to promote cancer cell death after

hypoxia, both alone or in combination with other DNA damaging agents (Hall et al., 2014). A

homolog precursor of VE822, VE821, has been shown to decrease levels of HIF-‐1α mediated

signaling (Pires et al., 2012). It would be interesting to examine levels of HIF-‐1α in our experiments,

which could potentially be done by harvesting lysate after ATR knockdown in hypoxic condition.

To our knowledge, the impact of hypoxia on the effects of Wee1 depletion by siRNA has not been

previously reported. However, the Wee1 inhibitor MK1775 was added during hypoxic incubation

and after reoxygenation in a previous master project in our group (Hauge, 2013). In the previous

master project, the responses to MK1775 were not much influenced by hypoxia. However, in the

previous study MK1775 was washed off immediately after reoxygenation, or added after

reoxygenation but present for longer times than in our study. The differences between our studies

may therefore be due to different experimental setup.

As mentioned before, NIPP1 was reported to alter the activity of PP1 in response to hypoxia, and it

has been proposed that this altered activity leads to changes in metabolic pathway that potentially

favor cancer cells survival during hypoxia (Comerford et al., 2006). We do not see a clear

connection how this potentially could be linked mechanistically to the enhanced γH2AX signaling

after hypoxia observed in Figure 6. However, it could have been interesting to explore this further

after successful validation of NIPP1 by the additional siRNAs.

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6.3 Combined WEE1 and ATR inhibition leads to synergistic increase of S-‐phase DNA damage. In this project, we also wanted to address the effect of combined WEE1 and ATR inhibition in U2OS

cells. Treatment with MK1775 combined with VE822 caused strong increase of γH2AX in S-‐phase,

compared to the inhibitors as single agents (First shown in Figure 9B and 10B). The increase in

γH2AX upon the combined treatment was clearly higher than the additive effects of the increases in

γH2AX after MK1775 and VE822 as single agents, particularly in the normoxic samples (Figure 23).

The combined inhibition also gave strongly reduced clonogenic survival (Figure 16B) when exposed

for 24 hours with the inhibitors, consistent with a synergistic effect. This indicates that high S-‐phase

DNA damage seen after combination treatment results in cell death. S-‐phase cells with high γH2AX

also shows high levels of phosphorylated RPA S4/S8 after 3 hours combined inhibitor-‐treatment

(First shown in Figure 11D), indicating presence of ssDNA. Together these data argue that combined

treatment with MK1775 and VE822 give synergistic increase of S-‐phase DNA damage and

replication catastrophe.

6.4 Do both WEE1 and ATR inhibition lead to elevated CDK activity? Since both WEE1 and ATR negatively regulate CDK activity, we wanted to address how the

combined treatment affects this activity by examining the inhibitory phosphorylation tyrosine 15 on

CDK1 and CDK2. We performed western blotting of the samples harvested 1 or 3 hours after

treatment, and detected a reduction in inhibitory phosphorylation on CDK1 after inhibition of WEE1

and WEE1/ATR, but not after ATR inhibition alone (Figure 19A). The same tendency was seen with

inhibitory phosphorylation of CDK2, as it was slightly decreased after inhibition of WEE1 and

WEE1/ATR, but not as obvious as with CDK1 (Figure 20A). To further investigate CDK2 activity, we

could have examined cyclin-‐E levels. Cyclin-‐E is degraded in S-‐phase in a CDK2 dependent manner,

but was not examined in this project. ATR inhibition surprisingly did not decrease inhibitor

phosphorylation on CDKs, suggesting that the synergistic induction of DNA damage in S-‐phase is not

only due to higher CDK1 and CDK2 activation upon inhibition with MK1775 and VE822. Since high

CDK activity can lead to unscheduled replication initiation, and is known to cause major replication

catastrophe (Petermann et al., 2010; Sørensen and Syljuåsen, 2012), our research group has done

an examination of loading of the replication initiation factor CDC45 after inhibition of WEE1 and

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ATR (Sissel Hauge, unpublished results). These experiments showed that there is a high increase of

CDC45 loading after inhibition of ATR and even higher after WEE1/ATR, indicating that the

synergistic effect between inhibition of WEE1 and ATR is not only due to elevated CDK activity, but

also to a CDK-‐independent increase of CDC45 loading after ATR inhibition.

6.5 Combination treatment with MK1775 and VE822 as a potential anti-‐cancer strategy There are several different studies on combined treatment of checkpoint kinase inhibitors and

other types of drugs (Kotsantis et al., 2015). Synergistic effect has been shown several times with

combined treatment of WEE1 and Chk1 inhibitors (Carrassa et al., 2012; Chilà et al., 2015; Mueller

and Haas-‐Kogan, 2015; Russell et al., 2013), and also combination of ATR and Chk1 inhibitors (Sanjiv

et al., 2016). To our knowledge, synergy between WEE1 and ATR inhibitors has not been previously

reported. Recently, our group has done a project to investigate the mechanisms behind the

synergistic effect between WEE1 and Chk1 inhibitors (Hauge et al., 2016). It was shown that WEE1

inhibition alone caused higher CDK activity, while Chk1 inhibition induced more DNA damage

correlating with higher CDC45 loading. When WEE1 alone was inhibited, Chk1 suppressed CDC45

loading and thereby limited the degree of unscheduled replication initiation even with high CDK

activity. This indicates a protection mechanism of the cells, and can explain why combined

treatment of WEE1 and Chk1 inhibitors give synergistic anti-‐cancer effect.

ATR inhibition is a relative new approach in cancer treatment, and VE822 is one of the first selective

inhibitor of ATR that reached clinical trials (Weber and Ryan, 2015). ATR is upstream of Chk1 and

may have a broader clinically utility. It was recently shown that ATR inhibition more selectively kills

cancer cells under high levels of replication stress than Chk1 inhibitors, because Chk1-‐inhibitors are

more cytotoxic and kill cells under moderate replication stress (Buisson et al., 2015). However,

upon moderate replication stress, DNA-‐PK phosphorylates Chk1 in a backup pathway when ATR is

inhibited, which could protect normal cells. But this pathway is not yet fully understood.

The approach of combined inhibition with MK1775 and VE822 may potentially be clinically relevant

in the future. Our group has recently started to look for this synergistic effect in other cancer cell

lines including lung cancer, and also in normal cells. Some cell lines appear to be very resistant to

MK1775 as measured by clonogenic survival assays, where VE822 treatment alone kills the cells but

not much more death is seen in combination with MK1775. Therefore, the combined approach may

65

not be effective in all cell lines, and more work is needed to understand the effects. The synergy

effect must be explored in additional cancer cell lines and with the use of additional inhibitors of

WEE1 and ATR, and it would also be interesting to examine this effect in in vivo studies, but much is

yet unknown about the synergistic effect of WEE1 and ATR inhibition.

6.6 Micronuclei in response to ATR inhibition

When we visualized the cells in IF microscopy, we saw that the cells formed micronuclei after

inhibiting ATR with VE822 (Figure 18). Micronuclei can derive either from a whole chromosome,

due to errors of the mitotic apparatus, or from broken chromosomes (Xu et al., 2011), and they are

commonly observed in cells with intrinsic genomic instability. ATR is the key player of maintenance

of stalled replication forks in S-‐phase (See ATR activation §1.2.3). Experiments with knockdown of

ATR have shown that cells with incomplete DNA replication can enter mitosis, and do so with

chromosome breaks, and induce chromosome bridges and micronuclei (Jardim et al., 2009). ATR is

also important for avoiding chromosome breaks during mitosis, and thereby cell death known as

“mitotic catastrophe” (Brown and Baltimore, 2003). Our result that VE822 causes micronuclei is

therefore consistent with previous reports that ATR can protect cells against micronuclei formation.

6.7 Experimental consideration

6.7.1 Cell culture In this study, all our experiments have been performed on human cells in culture. Using cell lines as

a model system have many advantages in research compared to lower class organisms or other

animal model systems. Even though they have been useful for studying cell biology, other model

systems are not always relevant for humans. Cultured cancer cells are relatively inexpensive, are

easy to work with, easy to store, and provide fewer ethnical issues compared to, for instance,

mouse models. Furthermore, many approaches for manipulating protein expression in cancer cells

by different transfection methods are developed. However, most human cell lines are immortalized

cancer cells that can have different genetic alterations, and most importantly, the conditions for

storage of cells in culture may not reflect normal physiologic conditions. The cells are kept in

conditions with much higher oxygen levels than for normal tissues in the body, and they divide

indefinitely in a monolayer in medium with highly enriched glucose. After continued cell cycle

divisions and accumulated mutations, the cells will no longer resemble the original cells. It is

66

therefore important to keep aliquots of cells with low passage number stored in liquid nitrogen, and

change the cells at a regular basis. As with all other model systems, we need to be aware of the

limitations of one cell line, and new findings need to be tested with additional cell lines.

We chose to perform all the experiments with U2OS cells, as this cell line is well known and is

involved in many studies involving hypoxia and DDR (Beck et al., 2010; Beck et al., 2012; Buisson et

al., 2015; Hasvold et al., 2013; Syljuåsen et al., 2005). The behavior of these cells is well studied,

both in response to hypoxia-‐induced replication stress and in response to inhibition of different

DDR factors in hypoxia or normoxia. There has been done much more work with WEE1 inhibition

with this cell line (Beck et al., 2012; Domínguez-‐Kelly et al., 2011; Hirai et al., 2009), compared to

ATR inhibition which is a relative new approach. Despite having wild-‐type p53, U2OS cells do not

have fully functional G1/S checkpoint (Petersen et al., 2010), which is one example of a cancer-‐

specific trait this cell line has acquired. Cell lines in general and cancer cell lines in particular can

vary a lot in their responses to different treatments, so to fully understand mechanisms involved in

cell cycle checkpoints and other DNA damage responses, as well as other cellular responses, it will

be necessary to perform experiments on other cell lines. Preferably, this should be done both with

other cancer cell lines as well as with normal cell lines, such as BJ fibroblasts. The microenvironment

involved in cancer development is also lost in cell line systems, and it would be necessary to

perform in vivo experiments for clinical trials.

6.7.2 siRNA transfection SiRNA transfection is a powerful technique to manipulate cells and to study phenotypes of cells that

have been depleted with different siRNAs. This will reduce levels of a protein when siRNA interfere

with protein expression at the mRNA level. Both qPCR (quantitative PCR) and western blotting can

measure SiRNA-‐induced knockdown, but qPCR will only give information about levels of mRNA

expression and not protein levels. We have therefore only used western blotting in this study when

we wanted to examine the effect of knockdown. Since unspecific changes in gene expression may

be induced by siRNA, it is important to use non-‐targeting siRNA as a control, rather than non-‐

transfected cells (Mock) to reflect a baseline cellular response. This baseline can be compared to

the response in cells treated with target-‐specific siRNA. We achieved good knockdown to protein

levels of 25% or less of that in untransfected cells when samples were harvested 72 hours after

siRNA transfection (Figure 6B). As mentioned in §6.2, siRNA depletion can potentially give off-‐target

effects, and it is important to use additional siRNAs with different sequences for one particular

67

protein, as we have done for NIPP1. However, interfering RNA techniques, as siRNA transfection,

are more target-‐specific than using inhibitors, but are a much more time consuming process.

6.7.3 WEE1 and ATR inhibition For inhibition of WEE1 and ATR we have used the small molecule inhibitors MK1775 and VE822

respectively. In experiments with hypoxia treatments, we have used a MK1775 concentration of

300nM (Hauge, 2013). The experimental concentration of the ATR inhibitor, VE822, was found by

checking the decrease in the levels of phosphorylations on Chk1 and RPA, as they are activated by

ATR. By using 500nM of VE822, we saw that the levels of ATR-‐dependent Chk1 phosphorylation

were undetectable compared to those in the uninhibited sample (Figure 8). As mentioned, we only

saw a decrease in CDK inhibitory phosphorylation after WEE1 inhibition, and not after ATR

inhibition. This was surprising, since we would expect Chk1 inactivation and then upregulated

CDC25 activity, caused by ATR inhibition, to give increased CDK activity (Cimprich and Cortez, 2008;

Fokas et al., 2014). MK1775 is a highly specific inhibitor of WEE1 and is useful to examine specific

effects of WEE1 inhibition. VE822 is also shown to be highly specific for ATR (Hall et al., 2014), but

as with siRNA transfection and off-‐target effects, it is important to use additional inhibitors for

further validation.

6.7.4 Hypoxia treatments In this project, we wanted to find out whether or not low oxygen levels can influence the S-‐phase

effect after both siRNA transfection and inhibition with MK1775 and VE822. As mentioned, we

detected a hypoxia-‐dependent increase of γH2AX signaling after siRNA knockdown, but most

interesting was the observed synergistic effect induced by the combination treatment with MK1775

and VE822. There were some differences in the results, but this may be due to experimental setups

and variations in the oxygen levels, and the fact that cellular responses might vary between cells.

The untreated cells fixed inside the hypoxia chamber also varied between experiments, but this

might be because of time spent inside the chamber doing the fixation, and the possibility for oxygen

leakage during this step. At the end of the project, we also performed a hypoxic-‐mimetic

experiment with DFO. We experienced an issue with gas leakage from the hypoxia chamber during

this project, one of several things that can go wrong with a device that is dependent on stable

conditions of oxygen, temperature, and humidity. Treatment with DFO has been shown to mimic

hypoxia-‐induced replication stress (Hammond et al., 2002), and we saw an increase of γH2AX when

68

adding DFO to the cells. However, after replacing the DFO-‐containing medium with new medium

(mimicking reoxygenation), we observed high levels of irreversible DNA damage at high

concentrations of DFO (Figure 24). At lower concentrations, we saw reversible γH2AX after

removing DFO that is the expected behavior, since we know that γH2AX levels decrease in Mock

cells from the moment they are removed from the hypoxia chamber until 3 hours after

reoxygenation. DFO can therefore serve as a useful substitute for hypoxia treatment, even though it

cannot recreate all sides of a hypoxic experiment. Moderate hypoxia is more difficult to recreate

than anoxic effect, because DFO inhibits cell respiration, and they become suffocated.

Several of the experiments in this project were performed in hypoxic conditions to induce

replication stress. A hypoxia chamber was used for this purpose. Oxygen consumption is influenced

by cell density (Jorjani, 1999), and for cells growing in dishes in a hypoxia chamber, high density

growth can lead to more severe hypoxia for the cells, and this is important to have in mind when

we knock down proteins involved in cell cycle progression. Knockdown can inhibit proliferation, and

even though samples were seeded with similar densities, the cells may have different densities

after several days with protein knockdown. Another consideration is that there are major

differences of reoxygenation in vivo and in vitro. Our experimental reoxygenation was performed at

atmospheric oxygen levels (21% O2) that do not correspond to the physiological reoxygenation of a

tumor that have much lower oxygen levels (3-‐7.4% O2) (McKeown, 2014). We have performed

experiments with the most severe levels for of hypoxia (0.02% O2), since previous studies show

hypoxia-‐dependent induction of γH2AX signals after prolonged exposure to severe levels of hypoxia

and not with more moderate levels of hypoxia (0.2% O2) (Hasvold et al., 2013). These anoxic

settings are only one of several possible hypoxic conditions, and it could be interesting in the future

to examine different levels of hypoxia for validating the results, or even examine the effects of

cycling hypoxia.

6.7.5 Measuring protein levels by flow cytometry Flow cytometry was used to detect S-‐phase replication stress. By DNA and antibody staining this

method can measure multiple parameters simultaneously and thousands of cells are analyzed in a

short amount of time. For every sample, we analyzed 10000 cells to increase result reliability.

Another advantage is that subpopulations of cells in a sample can be analyzed by gating, and flow

data can be stored and re-‐gated to get new information at a later time point. Quantification of

replication stress in S-‐phase is measured by γH2AX signaling as a function of cell cycle phase. Flow

69

cytometry can measure signals in each single cell individually of the S-‐phase population, and it has

an advantage over western blotting that only can measure mean value of the population in a

sample, including all phases of the cell cycle. Mean value can be misleading compared to median

value or percentage of positive γH2AX signals. Even though γH2AX is not specific for replication

stress (Liu et al., 2008), hypoxia-‐induced replication stress has been shown to increase γH2AX in S-‐

phase cells after severe hypoxia (Olcina et al., 2010). With this method, samples are stained with

fluorescent antibodies and one of the main issues when with such staining is that differences in the

number of cells in each sample can result in variations in antibody staining per cell, and thus

variations in γH2AX signaling detected. Differences in cell number can be minimized by discarding

some of the densest samples before staining. Another way to reduce sample-‐to-‐sample variations

and reduce staining errors is by barcoding of samples, a useful method when there is a need for a

high degree of accuracy. Each of a set of four samples is stained with a certain concentration of a

fluorescent dye before they are combined and stained together for the antibodies of interest. This

will simplify staining, reduce antibody consumption, and minimize sample-‐to-‐sample variation. Our

samples were stained one by one, but barcoding could be an option for further studies. Cells were

plated at the same cell density in order to prevent them from growing too dense, which can

influence oxygen consumption and cell cycle progression, as mentioned in §6.6.4.

6.7.6 Measuring protein levels by western blotting When measuring specific proteins in a sample, western blotting is a useful method to give a rough

estimation of protein knockdown by comparing strength of the bands of sample lysates to a control.

A dilution series of 10 or 12.5%, 25%, 50%, and 100% of the untreated control lysate was loaded

into the first wells in every gel to measure linearity of the antibody signal. This series also provides

an idea whether the antibody dilution has been optimal or not. When using western blotting for

quantification, it is important to have successfully transferred proteins from the SDS-‐gel to the

membrane. Uneven transfer can be checked by staining the membrane with Ponceau S, a rapid

reversible stain to protect protein bands, before proceeding with antibody detection. To examine

the mechanisms behind the synergy of MK1775 and VE822 in §5.7, we quantified the signals (Figure

20A) with a loading control to normalize the results (Figure 22). As an alternative to such

normalization against a loading control, we could have measured protein concentration before

performing SDS-‐PAGE in order to load an even amount of protein in each well. The BioRad

ChemiDoc we used, allowed us to quantify our results with great degree of certainty, as it is much

70

more sensitive and has a greater linear range that traditional photographic film, and it can control

saturation of signals better due to enhanced detection system. Western blotting can be used to

examine a lot of proteins, phosphorylations, etc., and because proteins is sorted by size, unspecific

signal is not as big a problem as it can be with flow cytometry analysis or IF. The selection of

antibodies is also greater compared to the selection of antibodies available for usage in flow

cytometry. Even though western blotting is an easy method to measure knockdown of proteins, it is

difficult to measure protein levels and modifications relative to cell cycle phase, which is better

measured with flow cytometry.

6.8 Concluding remarks Targeted cancer therapy is currently in high focus as a procedure for anti-‐cancer drug development.

These drugs can block growth and spread of cancer by interfering with specific molecules. Studying

molecules of the DDR is important for several reasons. DDR is important in normal cells as it

preserve genomic stability. Alterations in cell cycle pathways can drive carcinogenesis and due to

such alterations, cancer cells often lack some pathways and must rely on others to survive. This can

make cancer cells vulnerable for therapy that targets such alterations, without damaging normal

cells.

In this project, we have focused on factors of the DDR and in particular one of the main factors of

these responses, ATR. Inhibitors of both ATR and WEE1 are currently in clinical trials, and

combination treatment with both inhibitors has shown synergistic effects with highly increased

S-‐phase replication stress, DNA damage and cell death. We know that WEE1 inhibition causes

elevated CDK activity that leads to more DNA damage, but further studies are needed to examine

the mechanisms behind this synergy, and thereby the possibility of this combination treatment as

an anti-‐cancer strategy.

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7 Supplement

Figure 25. Knockdown of NIPP1 with two siRNA oligos. Western blotting showing siNIPP1 transfected cells with two different siRNA oligos towards NIPP1. U2OS cells were transfected with siRNAs and then split after 24 hours. The cells were harvested 72 hours after transfection. γ-‐Tubulin was used as loading control.

73

8 Acknowledgements The work performed during this master project was carried out at the Department of Radiation

Biology at the Norwegian Radium hospital, Oslo University Hospital.

First, I would like to thank my two wonderful supervisors Randi (group leader) and Grete (post doc.)

for all your help and support. Thank you for sharing your knowledge, taking time to teach me at the

lab and discuss my results. You have always been approachable and I could not have gotten better

supervisors than you two.

Second, I want to thank my group members for always being helpful, for guidance and for always

being positive. Thank you for all the laughter, dancing and singing. I also want to thank the rest of

the department for being social and friendly. I have really enjoyed my time working in the lab.

Finally, I want to thank my friends and fellow students for always being there and be interested in

my work.

But most of all I want to thank my family and my boyfriend for all your help and support. You have

all made it possible for me to focus on my studies and to get me trough these though years. I would

never have been where I am today without you.

Oslo, May 2016


75

9 List of abbreviations 53BP1 Tumor suppressing p53-‐binding protein 1

9-‐1-‐1 Rad9-‐Hus1-‐Rad1

ARF Alternative Reading Frame

ATM Ataxia-‐telangiectasia mutated

ATR Ataxia-‐telangiectasia and Rad3-‐related

ATRIP ATR-‐interacting protein

BER Base excision repair

BRCA1/2 Breast cancer type 1/2 susceptibility

CDC25 Cell division cycle 25

CHK Checkpoint kinase

CDK Cyclin-‐dependent kinase

DAPI 4´,6-‐diamidino-‐2-‐phenylindole

DDR DNA damage response

DMEM Dulbecco´s modified eagle medium

DNA Deoxyribonucleic acid

DNA-‐PK DNA protein kinase

DSB Double strand break

dsDNA double-‐stranded DNA

dsRNA double-‐stranded RNA

DTT Dithiothreitol

ECL Enhanced chemiluminescent

EDTA Ethylenediaminetetraacetic acid

ERCC1 Excision repair cross-‐complementing group 1

EtOH Ethanol

FBS Fetal bovine serum

H3P Phospho-‐Histone H3

HIF1 Hypoxia-‐inducible factor 1

HR Homologous recombination

HRP Horseradish peroxidase

Hus1 Checkpoint protein Hus1

76

IC50 Half maximal inhibitory concentration

IF Immunofluorescent

IgG Immunoglobulin G

INK4a Cyclin-‐dependent kinase inhibitor 2A isoform p16INK4A

IR Ionizing radiation

MCM2-‐7 Minichromosome maintenance proteins 2–7

MDM2 Mouse double minute 2 homolog

MMR Mismatch repair

Mre11 Meiotic recombination 11 homolog A

MRN Mre11-‐Rad50-‐Nbs1

mTOR mammalian target of rapamycin

MUS81 MUS81 structure-‐specific endonuclease

Nbs1 Nijmegen breakage syndrome proten 1

NER Nucleotide excision repair

NHEJ Non-‐homologous end-‐joining

NIPP1 Nuclear inhibitor of Protein Phosphatase-‐1

PAGE Polyacrylamide gel electrophoresis

PALB2 Partner and localizer of BRCA2

PARP Poly(ADP-‐ribose) polymerase

PBS Phosphate-‐buffered serum

PIKK Phospho-‐inositide3-‐kinase related kinases

PIP PP1 interaction protein

PP1 Protein Phosphatase-‐1

PPP Phosphoprotein phosphatase

Rad Cell cycle control protein

RB Retinoblastoma

RNA Ribonucleic acid

RNR Ribonucleotide reductase

ROS Reactive oxygen species

RPA Replication Protein A

SDS Sodium dodecyl sulfate

siRNA Small interfering RNA

SSB Single stranded break

77

ssDNA Single-‐stranded DNA

TOPBP1 DNA topoisomerase 2-‐binding protein-‐1

WEE1 Wee1-‐like protein kinase

XLF XRCC4-‐like factor 1

XRCC4 X-‐ray repair cross-‐complementing protein 4

γH2AX Gamma-‐Histone H2AX

79

10 References

AJ, L. 1997. p53, the cellular gatekeeper for growth and division. Cell. 88:323-‐331. An, W.G., M. Kanekal, M.C. Simon, E. Maltepe, M.V. Blagosklonny, and L.M. Neckers. 1998.

Stabilization of wild-‐type p53 by hypoxia-‐inducible factor 1[alpha]. Nature. 392:405-‐408. Asmal, M., E. Dean, J. Evans, M. Middleton, and R. Plummer. 2015. O6.4VX-‐970, selective inhibitor

of ataxia telangiectasia and Rad3-‐related (ATR) protein. Annals of Oncology. 26:ii8. Bakkenist, C.J., and M.B. Kastan. 2003. DNA damage activates ATM through intermolecular

autophosphorylation and dimer dissociation. Nature. 421:499-‐506. Bartek, J., and J. Lukas. 2001. Mammalian G1-‐ and S-‐phase checkpoints in response to DNA

damage. Current Opinion in Cell Biology. 13:738-‐747. Bartek, J., and J. Lukas. 2003. Chk1 and Chk2 kinases in checkpoint control and cancer. Cancer Cell.

3:421-‐429. Beck, H., V. Nähse, M.S.Y. Larsen, P. Groth, T. Clancy, M. Lees, M. Jørgensen, T. Helleday, R.G.

Syljuåsen, and C.S. Sørensen. 2010. Regulators of cyclin-‐dependent kinases are crucial for maintaining genome integrity in S phase. J Cell Biol. 188:629-‐638.

Beck, H., V. Nähse-‐Kumpf, M.S.Y. Larsen, K.A. O'Hanlon, S. Patzke, C. Holmberg, J. Mejlvang, A. Groth, O. Nielsen, R.G. Syljuåsen, and C.S. Sørensen. 2012. Cyclin-‐Dependent Kinase Suppression by WEE1 Kinase Protects the Genome through Control of Replication Initiation and Nucleotide Consumption. Molecular and Cellular Biology. 32:4226-‐4236.

Bindra, R.S., M.E. Crosby, and P.M. Glazer. 2007. Regulation of DNA repair in hypoxic cancer cells. Cancer Metastasis Rev. 26:249-‐260.

Bindra, R.S., and P.M. Glazer. 2006. Repression of RAD51 gene expression by E2F4//p130 complexes in hypoxia. Oncogene. 26:2048-‐2057.

Bollen, M., W. Peti, M.J. Ragusa, and M. Beullens. 2010. The extended PP1 toolkit: designed to create specificity. Trends in biochemical sciences. 35:450-‐458.

Bristow, R.G., and R.P. Hill. 2008. Hypoxia and metabolism: Hypoxia, DNA repair and genetic instability. Nat Rev Cancer. 8:180-‐192.

Brown, E.J., and D. Baltimore. 2003. Essential and dispensable roles of ATR in cell cycle arrest and genome maintenance. Genes & Development. 17:615-‐628.

Buisson, R., Jessica L. Boisvert, Cyril H. Benes, and L. Zou. 2015. Distinct but Concerted Roles of ATR, DNA-‐PK, and Chk1 in Countering Replication Stress during S Phase. Molecular Cell. 59:1011-‐1024.

Bussink, J., J.H.A.M. Kaanders, and A.J. van der Kogel. 2003. Tumor hypoxia at the micro-‐regional level: clinical relevance and predictive value of exogenous and endogenous hypoxic cell markers. Radiotherapy and Oncology. 67:3-‐15.

Canman, C.E., D.-‐S. Lim, K.A. Cimprich, Y. Taya, K. Tamai, K. Sakaguchi, E. Appella, M.B. Kastan, and J.D. Siliciano. 1998. Activation of the ATM Kinase by Ionizing Radiation and Phosphorylation of p53. Science (New York, N.Y.). 281:1677-‐1679.

Carrassa, L., R. Chila, M. Lupi, F. Ricci, C. Celenza, M. Mazzoletti, M. Broggini, and G. Damia. 2012. Combined inhibition of Chk1 and Wee1: in vitro synergistic effect translates to tumor growth inhibition in vivo. Cell Cycle. 11:2507-‐2517.

Castedo, M., J.L. Perfettini, T. Roumier, K. Andreau, R. Medema, and G. Kroemer. 2004. Cell death by mitotic catastrophe: a molecular definition. Oncogene. 23:2825-‐2837.

Chan, N., M. Koritzinsky, H. Zhao, R. Bindra, P.M. Glazer, S. Powell, A. Belmaaza, B. Wouters, and R.G. Bristow. 2008. Chronic Hypoxia Decreases Synthesis of Homologous Recombination Proteins to Offset Chemoresistance and Radioresistance. Cancer Research. 68:605-‐614.

80

Chan, N., I.M. Pires, Z. Bencokova, C. Coackley, K.R. Luoto, N. Bhogal, M. Lakshman, P. Gottipati, F.J. Oliver, T. Helleday, E.M. Hammond, and R.G. Bristow. 2010. Contextual Synthetic Lethality of Cancer Cell Kill Based on the Tumor Microenvironment. Cancer Res. 70:8045-‐8054.

Charrier, J.-‐D., S.J. Durrant, J.M.C. Golec, D.P. Kay, R.M.A. Knegtel, S. MacCormick, M. Mortimore, M.E. O'Donnell, J.L. Pinder, P.M. Reaper, A.P. Rutherford, P.S.H. Wang, S.C. Young, and J.R. Pollard. 2011. Discovery of Potent and Selective Inhibitors of Ataxia Telangiectasia Mutated and Rad3 Related (ATR) Protein Kinase as Potential Anticancer Agents. Journal of Medicinal Chemistry. 54:2320-‐2330.

Chen, H., Y. Yan, T.L. Davidson, Y. Shinkai, and M. Costa. 2006. Hypoxic Stress Induces Dimethylated Histone H3 Lysine 9 through Histone Methyltransferase G9a in Mammalian Cells. Cancer Research. 66:9009-‐9016.

Chilà, R., A. Basana, M. Lupi, F. Guffanti, E. Gaudio, A. Rinaldi, L. Cascione, V. Restelli, C. Tarantelli, F. Bertoni, G. Damia, and L. Carrassa. 2015. Combined inhibition of Chk1 and Wee1 as a new therapeutic strategy for mantle cell lymphoma. Oncotarget. 6:3394-‐3408.

Ciccia, A., and S.J. Elledge. 2010. The DNA Damage Response: Making it safe to play with knives. Mol Cell. 40:179-‐204.

Cimprich, K.A., and D. Cortez. 2008. ATR: An Essential Regulator of Genome Integrity. Nature reviews. Molecular cell biology. 9:616-‐627.

Comerford, K.M., M.O. Leonard, E.P. Cummins, K.T. Fitzgerald, M. Beullens, M. Bollen, and C.T. Taylor. 2006. Regulation of protein phosphatase 1γ activity in hypoxia through increased interaction with NIPP1: Implications for cellular metabolism. Journal of Cellular Physiology. 209:211-‐218.

Curtin, N.J. 2012. DNA repair dysregulation from cancer driver to therapeutic target. Nat Rev Cancer. 12:801-‐817.

Davis, A.J., B.P.C. Chen, and D.J. Chen. 2014. DNA-‐PK: a dynamic enzyme in a versatile DSB repair pathway. DNA Repair (Amst). 17:21-‐29.

De Witt Hamer, P.C., S.E. Mir, D. Noske, C.J.F. Van Noorden, and T. Würdinger. 2011. WEE1 Kinase Targeting Combined with DNA-‐Damaging Cancer Therapy Catalyzes Mitotic Catastrophe. Clinical Cancer Research. 17:4200-‐4207.

Deckbar, D., P.A. Jeggo, and M. Lobrich. 2011. Understanding the limitations of radiation-‐induced cell cycle checkpoints. Critical Reviews in Biochemistry and Molecular Biology. 46:271-‐283.

Dewhirst, M.W., Y. Cao, and B. Moeller. 2008. Cycling hypoxia and free radicals regulate angiogenesis and radiotherapy response. Nat Rev Cancer. 8:425-‐437.

Dexheimer, T.S. 2013. DNA Repair Pathways and Mechanisms.19-‐32. Di Micco, R., M. Fumagalli, A. Cicalese, S. Piccinin, P. Gasparini, C. Luise, C. Schurra, M. Garre, P.

Giovanni Nuciforo, A. Bensimon, R. Maestro, P. Giuseppe Pelicci, and F. d/'Adda di Fagagna. 2006. Oncogene-‐induced senescence is a DNA damage response triggered by DNA hyper-‐replication. Nature. 444:638-‐642.

Diller, L., J. Kassel, C.E. Nelson, M.A. Gryka, G. Litwak, M. Gebhardt, B. Bressac, M. Ozturk, S.J. Baker, and B. Vogelstein. 1990. p53 functions as a cell cycle control protein in osteosarcomas. Molecular and Cellular Biology. 10:5772-‐5781.

Domingo-‐Sananes, M.R., O. Kapuy, T. Hunt, and B. Novak. 2011. Switches and latches: a biochemical tug-‐of-‐war between the kinases and phosphatases that control mitosis. Philosophical Transactions of the Royal Society B: Biological Sciences. 366:3584-‐3594.

Domínguez-‐Kelly, R., Y. Martín, S. Koundrioukoff, M.E. Tanenbaum, V.A.J. Smits, H. Medema Ré, M. Debatisse, and R. Freire. 2011. Wee1 controls genomic stability during replication by regulating the Mus81-‐Eme1 endonuclease. J Cell Biol. 194:567-‐579.

81

Ebbesen, P., E.O. Pettersen, T.A. Gorr, G. Jobst, K. Williams, J. Kieninger, R.H. Wenger, S. Pastorekova, L. Dubois, P. Lambin, B.G. Wouters, T. Van Den Beucken, C.T. Supuran, L. Poellinger, P. Ratcliffe, A. Kanopka, A. Görlach, M. Gasmann, A.L. Harris, P. Maxwell, and A. Scozzafava. 2009. Taking advantage of tumor cell adaptations to hypoxia for developing new tumor markers and treatment strategies. Journal of Enzyme Inhibition and Medicinal Chemistry. 24:1-‐39.

Enders, G.H. 2010. Gauchos and ochos: a Wee1-‐Cdk tango regulating mitotic entry. Cell Division. 5:1-‐7.

Engelman, J.A., J. Luo, and L.C. Cantley. 2006. The evolution of phosphatidylinositol 3-‐kinases as regulators of growth and metabolism. Nat Rev Genet. 7:606-‐619.

Flynn, R.L., K.E. Cox, M. Jeitany, H. Wakimoto, A.R. Bryll, N.J. Ganem, F. Bersani, J.R. Pineda, M.L. Suvà, C.H. Benes, D.A. Haber, F.D. Boussin, and L. Zou. 2015. Alternative Lengthening of Telomeres Renders Cancer Cells Hypersensitive to ATR Inhibitors. Science (New York, N.Y.). 347:273-‐277.

Fokas, E., R. Prevo, E.M. Hammond, T.B. Brunner, W.G. McKenna, and R.J. Muschel. 2014. Targeting ATR in DNA damage response and cancer therapeutics. Cancer Treatment Reviews. 40:109-‐117.

Fokas, E., R. Prevo, J.R. Pollard, P.M. Reaper, P.A. Charlton, B. Cornelissen, K.A. Vallis, E.M. Hammond, M.M. Olcina, W. Gillies McKenna, R.J. Muschel, and T.B. Brunner. 2012. Targeting ATR in vivo using the novel inhibitor VE-‐822 results in selective sensitization of pancreatic tumors to radiation. Cell Death & Disease. 3:e441-‐.

Franken, N.A.P., H.M. Rodermond, J. Stap, J. Haveman, and C. van Bree. 2006. Clonogenic assay of cells in vitro. Nat. Protocols. 1:2315-‐2319.

Freiberg, R.A., E.M. Hammond, M.J. Dorie, S.M. Welford, and A.J. Giaccia. 2006. DNA Damage during Reoxygenation Elicits a Chk2-‐Dependent Checkpoint Response. Molecular and Cellular Biology. 26:1598-‐1609.

Furnari, B., N. Rhind, and P. Russell. 1997. Cdc25 Mitotic Inducer Targeted by Chk1 DNA Damage Checkpoint Kinase. Science (New York, N.Y.). 277:1495-‐1497.

Gaillard, H., T. Garcia-‐Muse, and A. Aguilera. 2015. Replication stress and cancer. Nat Rev Cancer. 15:276-‐289.

Gallagher, S.R. 2001. One-‐Dimensional SDS Gel Electrophoresis of Proteins. In Current Protocols in Molecular Biology. John Wiley & Sons, Inc.

Gilad, O., B.Y. Nabet, R.L. Ragland, D.W. Schoppy, K.D. Smith, A.C. Durham, and E.J. Brown. 2010. Combining ATR suppression with oncogenic Ras synergistically increases genomic instability, causing synthetic lethality or tumorigenesis in a dosage-‐dependent manner. Cancer Res. 70:9693-‐9702.

Green, S.L., R.A. Freiberg, and A.J. Giaccia. 2001. p21(Cip1) and p27(Kip1) Regulate Cell Cycle Reentry after Hypoxic Stress but Are Not Necessary for Hypoxia-‐Induced Arrest. Molecular and Cellular Biology. 21:1196-‐1206.

Guo, M., L.P. Song, Y. Jiang, W. Liu, Y. Yu, and G.Q. Chen. 2006. Hypoxia-‐mimetic agents desferrioxamine and cobalt chloride induce leukemic cell apoptosis through different hypoxia-‐inducible factor-‐1alpha independent mechanisms. Apoptosis. 11:67-‐77.

Halazonetis, T.D., V.G. Gorgoulis, and J. Bartek. 2008. An Oncogene-‐Induced DNA Damage Model for Cancer Development. Science (New York, N.Y.). 319:1352-‐1355.

Hall, A.B., D. Newsome, Y. Wang, D.M. Boucher, B. Eustace, Y. Gu, B. Hare, M.A. Johnson, S. Milton, C.E. Murphy, D. Takemoto, C. Tolman, M. Wood, P. Charlton, J.D. Charrier, B. Furey, J. Golec, P.M. Reaper, and J.R. Pollard. 2014. Potentiation of tumor responses to DNA damaging therapy by the selective ATR inhibitor VX-‐970. Oncotarget. 5:5674-‐5685.

82

Hammond, E.M., N.C. Denko, M.J. Dorie, R.T. Abraham, and A.J. Giaccia. 2002. Hypoxia Links ATR and p53 through Replication Arrest. Molecular and Cellular Biology. 22:1834-‐1843.

Hammond, E.M., M.J. Dorie, and A.J. Giaccia. 2004. Inhibition of ATR Leads to Increased Sensitivity to Hypoxia/Reoxygenation. Cancer Research. 64:6556-‐6562.

Hammond, E.M., M.R. Kaufmann, and A.J. Giaccia. 2007. Oxygen sensing and the DNA-‐damage response. Current Opinion in Cell Biology. 19:680-‐684.

Hanahan, D., and Robert A. Weinberg. 2011. Hallmarks of Cancer: The Next Generation. Cell. 144:646-‐674.

Hara, E., Smith, R., Parry, D., Tahara, H., Stone S., and Peters, G. 1996. Regulation of p16CDKN2 expression and its implications for cell immortalization and senescence. Molecular and Cellular Biology. 16:859–867.

Harper, J.W., and S.J. Elledge. 2007. The DNA Damage Response: Ten Years After. Molecular Cell. 28:739-‐745.

Hasvold, G., V. Nähse-‐Kumpf, K. Tkacz-‐Stachowska, E.K. Rofstad, and R.G. Syljuåsen. 2013. The Efficacy of CHK1 Inhibitors Is Not Altered by Hypoxia, but Is Enhanced after Reoxygenation. Molecular Cancer Therapeutics. 12:705-‐716.

Hauge, S. 2013. WEE1-‐inhibition and hypoxia: The impact of hypoxia and reoxygenation on the S-‐phase effects of the WEE1-‐inhibitor MK-‐1775.

Hauge, S., C. Naucke, G. Hasvold, M. Joel, G.E. Rødland, P. Juzenas, T. Stokke, and R. Syljuåsen. 2016. Combined inhibition of Wee1 and Chk1 gives synergistic DNA damage in S-‐phase due to distinct regulation of CDK activity and CDC45 loading. Institute for Cancer Research, Norwegian Radium Hospital.

Hirai, H., Y. Iwasawa, M. Okada, T. Arai, T. Nishibata, M. Kobayashi, T. Kimura, N. Kaneko, J. Ohtani, K. Yamanaka, H. Itadani, I. Takahashi-‐Suzuki, K. Fukasawa, H. Oki, T. Nambu, J. Jiang, T. Sakai, H. Arakawa, T. Sakamoto, T. Sagara, T. Yoshizumi, S. Mizuarai, and H. Kotani. 2009. Small-‐molecule inhibition of Wee1 kinase by MK-‐1775 selectively sensitizes p53-‐deficient tumor cells to DNA-‐damaging agents. Molecular Cancer Therapeutics. 8:2992-‐3000.

Holloman, W.K. 2011. Unraveling the mechanism of BRCA2 in homologous recombination. Nat Struct Mol Biol. 18:748-‐754.

Holthausen, J.T., C. Wyman, and R. Kanaar. 2010. Regulation of DNA strand exchange in homologous recombination. DNA Repair. 9:1264-‐1272.

Horsman, M.R., Kogel, A.v.d. 2009. Therapeutic approaches to tumour hypoxia. In Basic clinical radiobiology. Hodder Arnold.

Håve, T. 2015. DNA damage signalling factors protecting cancer cells against hypoxia-‐induced replication stress.

Jackson, S.P., and J. Bartek. 2009. The DNA-‐damage response in human biology and disease. Nature. 461:1071-‐1078.

Jardim, M.J., Q. Wang, R. Furumai, T. Wakeman, B.K. Goodman, and X.-‐F. Wang. 2009. Reduced ATR or Chk1 Expression Leads to Chromosome Instability and Chemosensitization of Mismatch Repair–deficient Colorectal Cancer Cells. Molecular Biology of the Cell. 20:3801-‐3809.

Jones, R.M., O. Mortusewicz, I. Afzal, M. Lorvellec, P. Garcia, T. Helleday, and E. Petermann. 2013. Increased replication initiation and conflicts with transcription underlie Cyclin E-‐induced replication stress. Oncogene. 32:3744-‐3753.

Jorjani, P., Ozturk, S.S. 1999. Effects of cell density and temperature on oxygen consumption rate for different mammalian cell lines. Biotechnology and Bioengineering. 64:349-‐356.

Kastan, M.B., and J. Bartek. 2004. Cell-‐cycle checkpoints and cancer. Nature. 432:316-‐323. Kawabe, T. 2004. G2 checkpoint abrogators as anticancer drugs. Molecular Cancer Therapeutics.

3:513-‐519.

83

Kotsantis, P., R.M. Jones, M.R. Higgs, and E. Petermann. 2015. Chapter Three -‐ Cancer Therapy and Replication Stress: Forks on the Road to Perdition. In Advances in Clinical Chemistry. Vol. Volume 69. S.M. Gregory, editor. Elsevier. 91-‐138.

Krajewska, M., A.M. Heijink, Y.J.W.M. Bisselink, R.I. Seinstra, H.H.W. Sillje, E.G.E. de Vries, and M.A.T.M. van Vugt. 2013. Forced activation of Cdk1 via wee1 inhibition impairs homologous recombination. Oncogene. 32:3001-‐3008.

Kreahling, J.M., P. Foroutan, D. Reed, G. Martinez, T. Razabdouski, M.M. Bui, M. Raghavan, D. Letson, R.J. Gillies, and S. Altiok. 2013. Wee1 Inhibition by MK-‐1775 Leads to Tumor Inhibition and Enhances Efficacy of Gemcitabine in Human Sarcomas. PLoS One. 8.

Kreahling, J.M., J.Y. Gemmer, D. Reed, D. Letson, M. Bui, and S. Altiok. 2012. MK1775, A Selective Wee1 Inhibitor, Shows Single-‐Agent Antitumor Activity Against Sarcoma Cells. Mol Cancer Ther. 11:174-‐182.

Kumagai, A., and W.G. Dunphy. 2000. Claspin, a Novel Protein Required for the Activation of Chk1 during a DNA Replication Checkpoint Response in <em>Xenopus</em> Egg Extracts. Molecular Cell. 6:839-‐849.

Kumagai, A., J. Lee, H.Y. Yoo, and W.G. Dunphy. 2006. TopBP1 Activates the ATR-‐ATRIP Complex. Cell. 124:943-‐955.

Kumareswaran, R., O. Ludkovski, A. Meng, J. Sykes, M. Pintilie, and R.G. Bristow. 2012. Chronic hypoxia compromises repair of DNA double-‐strand breaks to drive genetic instability. Journal of Cell Science. 125:189-‐199.

Lakin ND, H.B., Jackson SP. 1999. The ataxia-‐telangiectasia related protein ATR mediates DNA-‐dependent phosphorylation of p53. Oncogene. 18:3989-‐3995.

Lavin, M.F. 2008. Ataxia-‐telangiectasia: from a rare disorder to a paradigm for cell signalling and cancer. Nature reviews. Molecular cell biology. 9:759-‐769.

Lee, D.-‐H., and D. Chowdhury. 2011. What goes on must come off: phosphatases gate-‐crash the DNA damage response. Trends in biochemical sciences. 36:569-‐577.

Lee, J.-‐H., and T.T. Paull. 2004. Direct Activation of the ATM Protein Kinase by the Mre11/Rad50/Nbs1 Complex. Science (New York, N.Y.). 304:93-‐96.

Liu, Y., J.A. Parry, A. Chin, S. Duensing, and A. Duensing. 2008. Soluble histone H2AX is induced by DNA replication stress and sensitizes cells to undergo apoptosis. Molecular Cancer. 7:61.

López-‐Contreras Aé, J., and O. Fernandez-‐Capetillo. 2010. The ATR barrier to replication-‐born DNA damage. DNA Repair (Amst). 9:1249-‐1255.

Lou, Z., K. Minter-‐Dykhouse, S. Franco, M. Gostissa, M.A. Rivera, A. Celeste, J.P. Manis, J. van Deursen, A. Nussenzweig, T.T. Paull, F.W. Alt, and J. Chen. 2006. MDC1 Maintains Genomic Stability by Participating in the Amplification of ATM-‐Dependent DNA Damage Signals. Molecular Cell. 21:187-‐200.

Lukas, C., F. Melander, M. Stucki, J. Falck, S. Bekker-‐Jensen, M. Goldberg, Y. Lerenthal, S.P. Jackson, J. Bartek, and J. Lukas. 2004. Mdc1 couples DNA double-‐strand break recognition by Nbs1 with its H2AX-‐dependent chromatin retention. The EMBO Journal. 23:2674-‐2683.

Magdalou, I., B.S. Lopez, P. Pasero, and S.A.E. Lambert. 2014. The causes of replication stress and their consequences on genome stability and cell fate. Seminars in Cell & Developmental Biology. 30:154-‐164.

Mahaney, B.L., K. Meek, and S.P. Lees-‐Miller. 2009. Repair of ionizing radiation-‐induced DNA double strand breaks by non-‐homologous end-‐joining. Biochemical Journal. 417:639-‐650.

Malumbres, M., and M. Barbacid. 2009. Cell cycle, CDKs and cancer: a changing paradigm. Nat Rev Cancer. 9:153-‐166.

Maréchal, A., and L. Zou. 2013. DNA Damage Sensing by the ATM and ATR Kinases. Cold Spring Harbor Perspectives in Biology. 5.

84

Matsuoka, S., M. Huang, and S.J. Elledge. 1998. Linkage of ATM to Cell Cycle Regulation by the Chk2 Protein Kinase. Science (New York, N.Y.). 282:1893-‐1897.

McGowan, C.H., and P. Russell. 1995. Cell cycle regulation of human WEE1. The EMBO Journal. 14:2166-‐2175.

McKeown, S.R. 2014. Defining normoxia, physoxia and hypoxia in tumours—implications for treatment response. The British Journal of Radiology. 87.

Medema, R.H., and L. Macurek. 2012. Checkpoint control and cancer. Oncogene. 31:2601-‐2613. Mohni, K.N., G.M. Kavanaugh, and D. Cortez. 2014. ATR pathway inhibition is synthetically lethal in

cancer cells with ERCC1 deficiency. Cancer Res. 74:2835-‐2845. Moorhead, G.B.G., L. Trinkle-‐Mulcahy, and A. Ulke-‐Lemee. 2007. Emerging roles of nuclear protein

phosphatases. Nature reviews. Molecular cell biology. 8:234-‐244. Mueller, S., and D.A. Haas-‐Kogan. 2015. WEE1 Kinase As a Target for Cancer Therapy. Journal of

Clinical Oncology. 33:3485-‐3487. Niforou, K.M., A. K. Anagnostopoulos, K. Vougas, C. Kittas, V. G. Gorgoulis and G. T. Tsangaris.

2008. The proteome profile of the human osteosarcoma U2OS cell line. Cancer Genomics Proteomics. 5:63-‐78.

Nordlund, P., and P. Reichard. 2006. Ribonucleotide Reductases. Annual Review of Biochemistry. 75:681-‐706.

Olcina, M., P.S. Lecane, and E.M. Hammond. 2010. Targeting hypoxic cells through the DNA damage response. Clinical cancer research : an official journal of the American Association for Cancer Research. 16:5624-‐5629.

Overgaard, J. 2007. Hypoxic Radiosensitization: Adored and Ignored. Journal of Clinical Oncology. 25:4066-‐4074.

Park, Y.-‐B., M.J. Park, K. Kimura, K. Shimizu, S.H. Lee, and J. Yokota. 2002. Alterations in the INK4a/ARF locus and their effects on the growth of human osteosarcoma cell lines. Cancer Genetics and Cytogenetics. 133:105-‐111.

Pérez-‐Cadahía, B., B. Drobic, and J.R. Davie. 2009. H3 phosphorylation: dual role in mitosis and interphaseThis paper is one of a selection of papers published in this Special Issue entitled 30th Annual International Asilomar Chromatin and Chromosomes Conference and has undergone the Journal’s usual peer review process. Biochemistry and Cell Biology. 87:695-‐709.

Petermann, E., M. Woodcock, and T. Helleday. 2010. Chk1 promotes replication fork progression by controlling replication initiation. Proc Natl Acad Sci U S A. 107:16090-‐16095.

Petersen, L., G. Hasvold, J. Lukas, J. Bartek, and R.G. Syljuåsen. 2010. p53-‐dependent G1 arrest in 1st or 2nd cell cycle may protect human cancer cells from cell death after treatment with ionizing radiation and Chk1 inhibitors. Cell Proliferation. 43:365-‐371.

Pires, I.M., Z. Bencokova, M. Milani, L.K. Folkes, J.L. Li, M.R. Stratford, E.M. Hammond, and A.L. Harris. 2010. Effects of acute versus chronic hypoxia on DNA damage responses and genomic instability. 70:925-‐935.

Pires, I.M., M.M. Olcina, S. Anbalagan, J.R. Pollard, P.M. Reaper, P.A. Charlton, W.G. McKenna, and E.M. Hammond. 2012. Targeting radiation-‐resistant hypoxic tumour cells through ATR inhibition. British Journal of Cancer. 107:291-‐299.

Rahman, M. 2006. Introduction to flow cytometry. Serotec Ltd. Rana, T.M. 2007. Illuminating the silence: understanding the structure and function of small RNAs.

Nature reviews. Molecular cell biology. 8:23-‐36. Rebelo, S., M. Santos, F. Martins, E.F. da Cruz e Silva, and O.A.B. da Cruz e Silva. 2015. Protein

phosphatase 1 is a key player in nuclear events. Cellular Signalling. 27:2589-‐2598. Russell, M.R., K. Levin, J.A. Rader, L. Belcastro, Y. Li, D. Martinez, B. Pawel, S.D. Shumway, J.M.

Maris, and K.A. Cole. 2013. COMBINATION THERAPY TARGETING THE CHK1 AND WEE1

85

KINASES DEMONSTRATES THERAPEUTIC EFFICACY IN NEUROBLASTOMA. Cancer Res. 73:776-‐784.

Ruzankina, Y., C. Pinzon-‐Guzman, A. Asare, T. Ong, L. Pontano, G. Cotsarelis, V.P. Zediak, M. Velez, A. Bhandoola, and E.J. Brown. 2007. Deletion of the Developmentally Essential Gene ATR in Adult Mice Leads to Age-‐Related Phenotypes and Stem Cell Loss. Cell stem cell. 1:113-‐126.

Saintigny, Y., F. Delacôte, G. Varès, F. Petitot, S. Lambert, D. Averbeck, and B.S. Lopez. 2001. Characterization of homologous recombination induced by replication inhibition in mammalian cells. The EMBO Journal. 20:3861-‐3870.

Sanchez, Y., C. Wong, R.S. Thoma, R. Richman, Z. Wu, H. Piwnica-‐Worms, and S.J. Elledge. 1997. Conservation of the Chk1 Checkpoint Pathway in Mammals: Linkage of DNA Damage to Cdk Regulation Through Cdc25. Science (New York, N.Y.). 277:1497-‐1501.

Sanjiv, K., A. Hagenkort, José M. Calderón-‐Montaño, T. Koolmeister, Philip M. Reaper, O. Mortusewicz, Sylvain A. Jacques, Raoul V. Kuiper, N. Schultz, M. Scobie, Peter A. Charlton, John R. Pollard, Ulrika W. Berglund, M. Altun, and T. Helleday. 2016. Cancer-‐Specific Synthetic Lethality between ATR and CHK1 Kinase Activities. Cell Reports. 14:298-‐309.

Sarkaria, J.N., E.C. Busby, R.S. Tibbetts, P. Roos, Y. Taya, L.M. Karnitz, and R.T. Abraham. 1999. Inhibition of ATM and ATR Kinase Activities by the Radiosensitizing Agent, Caffeine. Cancer Research. 59:4375-‐4382.

Semenza, G.L. 1998. Hypoxia-‐inducible factor 1: master regulator of O2 homeostasis. Current Opinion in Genetics & Development. 8:588-‐594.

Semenza, G.L. 2012. Hypoxia-‐Inducible Factors in Physiology and Medicine. Cell. 148:399-‐408. Shapiro, H.M. 2003. Practical Flow Cytometry. John Wiley & Sons, Inc., Hoboken, New Jersey. Sherr, C.J., and J.M. Roberts. 1999. CDK inhibitors: positive and negative regulators of G1-‐phase

progression. Genes & Development. 13:1501-‐1512. Shieh, S.Y., J. Ahn, K. Tamai, Y. Taya, and C. Prives. 2000. The human homologs of checkpoint

kinases Chk1 and Cds1 (Chk2) phosphorylate p53 at multiple DNA damage-‐inducible sites. Genes & Development. 14:289-‐300.

Stiff, T., M. O’Driscoll, N. Rief, K. Iwabuchi, M. Löbrich, and P.A. Jeggo. 2004. ATM and DNA-‐PK Function Redundantly to Phosphorylate H2AX after Exposure to Ionizing Radiation. Cancer Research. 64:2390-‐2396.

Stott, F.J., S. Bates, M.C. James, B.B. McConnell, M. Starborg, S. Brookes, I. Palmero, K. Ryan, E. Hara, K.H. Vousden, and G. Peters. 1998. The alternative product from the human CDKN2A locus, p14(ARF), participates in a regulatory feedback loop with p53 and MDM2. The EMBO Journal. 17:5001-‐5014.

Stracker, T.H., and J.H.J. Petrini. 2011. The MRE11 complex: starting from the ends. Nature reviews. Molecular cell biology. 12:90-‐103.

Stucki, M., and S.P. Jackson. 2006. γH2AX and MDC1: Anchoring the DNA-‐damage-‐response machinery to broken chromosomes. DNA Repair. 5:534-‐543.

Sultana, R., T. Abdel-‐Fatah, C. Perry, P. Moseley, N. Albarakti, V. Mohan, C. Seedhouse, S. Chan, and S. Madhusudan. 2013. Ataxia Telangiectasia Mutated and Rad3 Related (ATR) Protein Kinase Inhibition Is Synthetically Lethal in XRCC1 Deficient Ovarian Cancer Cells. PLoS ONE. 8:e57098.

Sun, Y., X. Jiang, S. Chen, N. Fernandes, and B.D. Price. 2005. A role for the Tip60 histone acetyltransferase in the acetylation and activation of ATM. Proceedings of the National Academy of Sciences of the United States of America. 102:13182-‐13187.

Syljuåsen, R.G., C.S. Sørensen, L.T. Hansen, K. Fugger, C. Lundin, F. Johansson, T. Helleday, M. Sehested, J. Lukas, and J. Bartek. 2005. Inhibition of Human Chk1 Causes Increased Initiation of DNA Replication, Phosphorylation of ATR Targets, and DNA Breakage. Molecular and Cellular Biology. 25:3553-‐3562.

86

Sørensen, C.S., and R.G. Syljuåsen. 2012. Safeguarding genome integrity: the checkpoint kinases ATR, CHK1 and WEE1 restrain CDK activity during normal DNA replication. Nucleic Acids Research. 40:477-‐486.

Sørensen, C.S., R.G. Syljuåsen, J. Falck, T. Schroeder, L. Rönnstrand, K.K. Khanna, B.-‐B. Zhou, J. Bartek, and J. Lukas. 2003. Chk1 regulates the S phase checkpoint by coupling the physiological turnover and ionizing radiation-‐induced accelerated proteolysis of Cdc25A. Cancer Cell. 3:247-‐258.

Tatum, J.L., G.J. Kelloff, R.J. Gillies, J.M. Arbeit, J.M. Brown, K.S. Chao, J.D. Chapman, W.C. Eckelman, A.W. Fyles, A.J. Giaccia, R.P. Hill, C.J. Koch, M.C. Krishna, K.A. Krohn, J.S. Lewis, R.P. Mason, G. Melillo, A.R. Padhani, G. Powis, J.G. Rajendran, R. Reba, S.P. Robinson, G.L. Semenza, H.M. Swartz, P. Vaupel, D. Yang, B. Croft, J. Hoffman, G. Liu, H. Stone, and D. Sullivan. 2006. Hypoxia: importance in tumor biology, noninvasive measurement by imaging, and value of its measurement in the management of cancer therapy. Int J Radiat Biol. 82:699-‐757.

Toledo, L.I., M. Murga, R. Zur, R. Soria, A. Rodriguez, S. Martinez, J. Oyarzabal, J. Pastor, J.R. Bischoff, and O. Fernandez-‐Capetillo. 2011. A cell-‐based screen identifies ATR inhibitors with synthetic lethal properties for cancer-‐associated mutations. Nat Struct Mol Biol. 18:721-‐727.

Unciti-‐Broceta, A., M.N. Bacon, and M. Bradley. 2010. Strategies for the Preparation of Synthetic Transfection Vectors. 296:15-‐49.

Vaupel, P., F. Kallinowski, and P. Okunieff. 1989. Blood Flow, Oxygen and Nutrient Supply, and Metabolic Microenvironment of Human Tumors: A Review. Cancer Research. 49:6449-‐6465.

Verbon, E.H., J.A. Post, and J. Boonstra. 2012. The influence of reactive oxygen species on cell cycle progression in mammalian cells. Gene. 511:1-‐6.

Walworth, N., S. Davey, and D. Beach. 1993. Fission yeast chkl protein kinase links the rad checkpoint pathway to cdc2. Nature. 363:368-‐371.

Watanabe, N., H. Arai, J. Iwasaki, M. Shiina, K. Ogata, T. Hunter, and H. Osada. 2005. Cyclin-‐dependent kinase (CDK) phosphorylation destabilizes somatic Wee1 via multiple pathways. Proc Natl Acad Sci U S A. 102:11663-‐11668.

Watanabe, N., H. Arai, Y. Nishihara, M. Taniguchi, N. Watanabe, T. Hunter, and H. Osada. 2004. M-‐phase kinases induce phospho-‐dependent ubiquitination of somatic Wee1 by SCF(β-‐TrCP). Proc Natl Acad Sci U S A. 101:4419-‐4424.

Watanabe, N., M. Broome, and T. Hunter. 1995. Regulation of the human WEE1Hu CDK tyrosine 15-‐kinase during the cell cycle. The EMBO Journal. 14:1878-‐1891.

Weber, A.M., and A.J. Ryan. 2015. ATM and ATR as therapeutic targets in cancer. Pharmacology & Therapeutics. 149:124-‐138.

Wersto, R.P., Chrest, F. J, et al. 2001. Doublet discrimination in DNA cell-‐cycle analysis. Cytometry. 46:296-‐306.

Wouters, B.G., and M. Koritzinsky. 2008. Hypoxia signalling through mTOR and the unfolded protein response in cancer. Nat Rev Cancer. 8:851-‐864.

Xiaofei, E., X., and T.F. Kowalik. 2014. The DNA Damage Response Induced by Infection with Human Cytomegalovirus and Other Viruses. Viruses. 6:2155-‐2185.

Xu, B., Z. Sun, Z. Liu, H. Guo, Q. Liu, H. Jiang, Y. Zou, Y. Gong, J.A. Tischfield, and C. Shao. 2011. Replication Stress Induces Micronuclei Comprising of Aggregated DNA Double-‐Strand Breaks. PLoS ONE. 6:e18618.

Yun, M.H., and K. Hiom. 2009. CtIP-‐BRCA1 modulates the choice of DNA double-‐strand break repair pathway throughout the cell cycle. Nature. 459:460-‐463.

87

Zeman, M.K., and K.A. Cimprich. 2014. Causes and consequences of replication stress. Nat Cell Biol. 16:2-‐9.

Zhang, Y., and T. Hunter. 2014. Roles of Chk1 in Cell Biology and Cancer Therapy. International journal of cancer. Journal international du cancer. 134.

Zhou, B.-‐B.S., and S.J. Elledge. 2000. The DNA damage response: putting checkpoints in perspective. Nature. 408:433-‐439.

Zou, L., and S.J. Elledge. 2003. Sensing DNA Damage Through ATRIP Recognition of RPA-‐ssDNA Complexes. Science (New York, N.Y.). 300:1542-‐1548.

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