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Differential effects of starvation in normal and cancer cells: from EGR1-dependent protection to p53-mediated apoptosis

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Differential effects of starvation in normal and cancer cells: from EGR1-dependent protection to p53-mediated apoptosis

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DIFFERENTIAL EFFECTS OF STARVATION
IN NORMAL AND CANCER CELLS:
FROM EGR1-DEPENDENT PROTECTION
TO p53-MEDIATED APOPTOSIS

by

Hong Seok Shim
______________________________________________________________________

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
Integrative and evolutionary biology

May 2015

Copyright 2015 Hong Seok Shim
ii

To my loving family,
iii

Acknowledgments

It has been my privilege to work in Dr. Longo’s lab. Thank my advisor, Dr. Valter Longo,
for his guidance and trust in me. Thank Dr. Min Wei for all your priceless discussion and
inputs. Thank Dr. Sebastian Brandhorst for sharing your great animal works. Thank all
the lab members for giving me valuable experience.

Special thanks to my committee members:
Amy Lee, Ph.D.
John Tower, Ph.D.

Finally, I thank my family, my lovely honey Min-Young and adorable daughters Mary
and Claire for your perpetual encouragement and support, and for all they are. I would
never have made it without you.

iv

Table of Contents
Dedication ii
Acknowledgements iii
List of Figures vi
Abstract viii

Chapter 1 The Theories of Aging 1
1.1 The Evolutionary Theories of Aging 2
1.2 The Mechanistic Theories of Aging 4
1.3 Dietary and Calorie Restriction in Aging 8
1.4 Nutrient Signal Transduction Pathways 10
1.5 Clinical Applications 13
1.6 References 16

Chapter 2 Short-term starvation induces the post-translational modification
of REV1 through oxidative stress.

21
2.1 Introduction 21
2.2 Results 25
2.3 Discussion 39
2.4 Experimental Procedures 41
2.5 References 45
v

Chapter 3 The interplay between p53 and REV1 in cancer therapy.

51
3.1 Introduction 51
3.2 Results 53
3.3 Discussion 68
3.4 Experimental Procedures 75
3.5 References 81

Chapter 4 Short-term starvation induces cardioprotection via AMPK/PKA-
EGR1 pathway.

85
4.1 Introduction 85
4.2 Results 90
4.3 Discussion 108
4.4 Experimental Procedures 111
4.5 References 116

Chapter 5 Conclusions and Future Directions

123
5.1 Basic and Clinical Implications 124
5.2 Future Directions 126
5.3 References 130

Bibliography 132

vi

List of Figures
1.1 Longevity pathways in yeast, worms, flies and mammals ……………… 11
2.1 Short-term starvation leads to REV1 modification. …………………… 26
2.2 ROS induces REV1 modification under STS. ………………………… 27
2.3 REV1’s effect on STS-induced sensitization of MCF7 cells to DXR. … 28
2.4 SUMO2/3 modification of REV1 in response to ROS. ……………… 29
2.5 The conjugation of SUMO2 and SUMO3 to REV1 protein. …………… 30
2.6 Confirmation of REV1 modification by SUMO2/3. …………………… 31
2.7 SENPs de-conjugate SUMO from REV1. …………………………… 33
2.8 PIASy functions as a SUMO E3 ligase for REV1. …………………… 34
2.9 Mouse REV1 protein is SUMO2-modified at the K119 residue in vivo. 35
2.10 SUMOylation stabilizes REV1 protein. ……………………………… 36
2.11 SUMOylation increases the stability of endogenous REV1. …………… 37
3.1 REV1 interacts with p53 via its N-terminal BRCT domain. …………… 54
3.2 The C-terminal region of p53 is sufficient for REV1 interaction. ……… 55
3.3 REV1 negatively modulates p53 transcription activity. ……………… 57
3.4 REV1 regulates p53 stability. ………………………………………… 58
3.5 REV1 modulates p53 activity and its downstream in response to
starvation. ………………………………………………………………

59
3.6 REV1 SUMOylation affects p53 transactivation. ……………………… 60
3.7 REV1’s effects on colony formation ability of cancer cells. …………… 61
3.8 STS sensitizes cancer cells to chemotherapy in vivo. ………………… 62
3.9 Effect of fasting and chemotreatment on body weight, food intake, and
tumor volume in allografted mouse model. ……………………………

63
3.10 STS and H2O2 treatment disrupt REV1-p53 interaction. ……………… 64
vii

3.11 STS alone or combined with chemotherapy induces p53
phosphorylation and acetylation in cancer cells. ………………………

65
3.12 STS activates p53-dependent apoptotic pathway in cancer cells. ……… 66
3.13 A model for the regulation of p53 by REV1 SUMOylation in response
to short-term starvation. ………………………………………………

69
3.14 REV1 SUMOylation upon starvation and chemotreatment. …………… 70
3.15 The effect of REV1 SUMOylation in normal cells. …………………… 71
3.16 REV1 associates with PCNA and REV7, an accessory subunit of Polζ. 73
4.1 Glucose restriction induces Egr1 expression in primary cardiomyocytes. 91
4.2 The induction of EGR1 via AMPK activation in cardiomyocytes. …… 92
4.3 A model of the regulation of longevity pathways in yeast. …………… 93
4.4 PKA inhibition triggers Egr1 expression and protective effects in
cardiomyocytes. ………………………………………………………

95
4.5 Confirmation of Egr1-knockout cells by Western blot. ………………… 96
4.6 GR- and inhibited PKA-mediated EGR1 activation. …………………… 97
4.7 The regulation of MnSOD and FOXO responsive genes in Egr1-
dependent manner. ……………………………………………………

98
4.8 Egr1 regulates energy metabolism. …………………………………… 99
4.9 FMD induces Egr1 expression in the hearts. …………………………… 101
4.10 FMD promotes the expression of antioxidant genes in the hearts. ……… 102
4.11 Metformin and its analog phenformin treatment induce Egr1 expression
in primary cardiomyocytes. ……………………………………………

103
4.12 Body weight and blood glucose level of metformin-treated mice. …… 104
4.13 Metformin-induced stress resistance in vivo. ………………………… 105
4.14 AMPK activator metformin has protective effects in DXR-induced
toxicity through Egr1. …………………………………………………

107
4.15 A model for the starvation/metformin-mediated AMPK/PKA-EGR1
pathways. ………………………………………………………………

109
viii

Abstract
Dietary or calorie restriction has been a well-studied strategy for increasing survival and
preventing carcinogenesis in mammals. Short-term starvation, an extreme form of dietary
restriction, can augment cancer treatment efficacy and can be effective in delaying cancer
progression in the absence of chemotherapy. However, the underlying molecular
mechanisms of these dietary interventions remain elusive.
Here I describe REV1, a specialized DNA polymerase involved in DNA repair,
as an important signaling node linking nutrient sensing and metabolic control to cell fate
in cancer cells. I have identified that REV1 is a novel binding partner of the tumor
suppressor p53 and regulates its activity, and that short-term starvation facilitates the
modifications of these proteins. Under starvation, REV1 is modified by SUMO2/3,
resulting in consequent relief of REV1’s inhibition of p53 and enhancing p53 activation,
pro-apoptotic genes expression and in turn p53-mediated apoptosis in breast cancer and
melanoma cells. Thus, fasting through its effect on REV1 is a promising non-toxic
strategy to increase p53-dependent cell death and to enhance the efficacy of cancer
therapies.
In addition, my study reveals that AMPK, PKA, and EGR1 are the molecular
components of functional signaling pathway that allows cardiomyocytes to sense and
react to nutrient availability. AMPK activation and PKA inhibition under glucose
restriction and metformin treatment are required to promote the induction of EGR1, an
immediately early response gene, and the expression of antioxidant and stress resistance
ix

genes in cardiomyocytes. EGR1 has a consequent cardioprotective function following
doxorubicin treatment. This study provides that short-term starvation and metformin have
a protective role in doxorubicin-induced cardiotoxicity through AMPK/PKA-EGR1
pathway.
In conclusion, this thesis provides molecular evidence for short-term starvation as
the promising intervention to exert differential effects in normal and cancer cells,
contributing to their protection and death in response to stress, respectively. These data
describe REV1 and EGR1 as the important signaling nodes linking nutrient sensing and
metabolic control under starvation conditions.
1

Chapter 1
The Theories of Aging

Aging is defined as an overall decline in performance and fitness with age (Hughes
and Reynolds, 2005). Aging is a universal features of virtually all organisms
manifested as the progressive accumulation of irreversible developmental and
reproductive defects and the gradual loss of function, leading to increased
susceptibility to diseases and eventually death of organisms (Harman, 1981; Longo
and Finch, 2003). Aging is highly complex and may result from multiple converging
mechanisms. Aging is associated with or responsible for the decline in protection and
repair mechanisms, the accumulation of damage and consequently the high incidence
of many cancers, degenerative diseases, inflammatory diseases, somatic mutations,
and other age-related diseases (Hung et al., 2011).
The molecular pathways that modulate aging process are shared in the most
model organisms including yeast, worms, flies and mice. However, aging is quite
complex and multiple mechanisms are involved at different levels (Kirkwood, 2005).
The intrinsic complexity of the aging process poses a significant challenge for
understanding why and how aging occurs (Kirkwood, 2005). Different theories of
aging have been proposed to provide distinct but overlapping views why aging exists,
2

what causes aging, and how aging affects the structure and function of an organism.
To understand the nature of aging at the cellular and molecular levels will be a great
help to unravel the complexity of mechanisms causing aging process and age-related
diseases.

1.1 The Evolutionary Theories of Aging
The evolutionary theories of aging were based on the genetics and genomic discoveries
on aging. These theories attempted to explain the resource allocation during organism
development and reproduction based on the interplay between genetic mutations and
natural selection. Moreover, these theories provide predictions which can be tested in
experiments.
The first formal theory was the theory of programmed death developed by
August Weismann (Weismann et al., 1891). It postulated that aging is advantageous
to the species by preventing over-crowding and/or securing a turnover of generations.
Weismann’s concept inspired the germ plasm theory and the disposable soma theory.
The germ plasm theory states that the multicellular organism’s cells are divided into
soma cells, which make up the body, and germ cells, which produce the gametes and
then transmit hereditary information into the offspring. This theory proposed that the
3

newly acquired characteristic cannot be passed from one generation to the next and
implicated the chromosomal basis of inheritance.
The two contemporary evolutionary theories of aging were proposed in 1950s.
The theory of mutation accumulation was proposed by Peter Medawar (Medawar,
1952). According to this theory, aging is considered as a by-product of natural
selection and mutations. The harmful mutations accumulate over time and selective
forces decline with age in parallel. The deleterious mutations which act late in life
would not be subjected to natural selection, consequently leading to an increase in
mortality rate at late ages. This theory suggested that aging is inevitable results from
natural selection declines with time in an organism.
The antagonistic pleiotropic theory introduced the existence of pleiotropic
genes that could explain the aging process. George Williams proposed that some genes
may have an effect on several traits and also pleiotropic effects at different ages in
opposite (antagonistic) ways (Williams, 1957). For instance, if there are some
mutations which are beneficial at young age but detrimental at old age, these mutations
will be in favor for selection. In Williams’ model, aging is caused by the combined
effects of the pleiotropic effects of these genes. Compared to the mutation
accumulation theory, these genes are actively kept in the gene pool by selection in the
antagonistic pleiotropic theory. It also provides the basic explanation for the
development of many age-related diseases.
4

Thomas Kirkwood proposed the disposable soma theory of aging (Kirkwood,
1977). The idea was that organisms have limited energy and resources which have to
be divided between the organism (soma) maintenance and reproductive activity. The
intracellular processes for repair and maintenance are essential for keeping cellular
homeostasis, but the overall maintenance cost is substantial. So, the optimum course
is to invest fewer resources in the maintenance and repair of older individuals with
limited resources and to invest more efforts and resources for reproduction to secure
the continuance of its genes. Under this model, the progressive accumulation of
somatic damage during life contributes to aging.
It is clear that aging is not simply caused by the positive selection and
programmed death processes. The intensive aging research have identified many
conserved genes and mechanisms altering the age-related mortality in model
organisms including yeast, nematode worms, flies and rodents. These mechanistic
explanations for aging will be discussed below.

1.2 The Mechanistic Theories of Aging
The recent studies on aging have focused on identifying aging mechanisms and taken
approach to understand the key regulators of aging and to identify interventions to
improve the length and quality of life. Molecular, cellular and systems analysis have
5

allowed scientists to uncover that single-mutations and transgenes can modulate
longevity. In addition, the discovery of highly conserved stress-resistance and cellular
signaling mechanisms with dietary restriction also support the concept of the
mechanistic theories of aging.
Harman first proposed the free radical theory of aging in the 1950s (Harman,
1956). The free radical theory is now one of the widely accepted theories of aging and
has provided new insights into the aging process and age-associated phenomena. In
the mid 20
th
century, it was discovered that the oxygen free radicals are formed
endogenously from metabolic processes and exist in vivo. This theory proposes that
the reactive oxygen species from the constant biological reactions are responsible for
damage associated with aging and play an essential role in the aging process. The free
radical theory of aging also suggests that the organismal lifespan can be extended by
minimizing deleterious harmful free radicals.
Mitochondria are the primary organelles generating a large amount of reactive
oxygen species in most eukaryotic cells. Thus, the mitochondrial theory of aging was
proposed in 1970s (Harman, 1972). Oxidative phosphorylation is an efficient
metabolism to generate the energy, adenosine 5´-triphosphate (ATP), required for
cellular processes. During this process, however, reactive oxygen species are also
continuously produced as byproducts of aerobic metabolism in mitochondria as well
as of various metabolic mechanisms in different cellular components (Apel and Hirt,
2004; Vander Heiden et al., 2009). The free radicals cause further oxidative damage
6

to diverse macromolecules and other organelles, and the continuous oxidative damage
are accumulated during their lifetime, resulting in a progressive loss and age-
dependent decline in all physiologic systems.
Increasing experimental evidence have been supporting this theory. Most
experimental attention has focused on the antioxidant defense system containing
multiple components. The discovery of superoxide dismutases and the existence of
hydrogen peroxide in vivo gave more credibility and firmly supported this hypothesis
(Chance et al., 1979; McCord and Fridovich, 1969). All eukaryotic cells also have
various anti-oxidative defense components and under physiological conditions most
of these molecules can be detoxified immediately by the scavenging and defense
systems. Therefore, the balance between ROS producing and scavenging mechanisms
will be crucial for suppressing toxic ROS levels in cells and must be tightly controlled.
More relevant evidence including the discovery of oxidative stress-induced
mitochondrial DNA deletions and the accumulation of mitochondrial DNA damage
with age supported this theory. Knockout mouse models lacking the major antioxidant
enzymes have been generated and shown that the ablation of antioxidant genes, Sod1
and Sod2, shortens the life span of mice, and the overexpression of these genes
increases the life span (Landis and Tower, 2005; Muller et al., 2007).
However, the data in mice remain inconclusive on whether oxidative stress is
a life-span determinant. In some mouse models, elevated oxidative stress by genetic
manipulations, in cases of Sod1
+/-
, Sod2
+/-
, and Prxd1
+/-
, does not actually decrease
7

the life span of mice (Muller et al., 2007). Recent studies demonstrated that ROS are
not the only limiting factor in determining lifespan and that it can be important
signaling molecules as well. Although it has been widely accepted that free radicals
are important mediators of aging, it remains to be addressed whether free radicals or
other reactive species are the major cause of aging (Longo et al., 2005).
Many studies provide the coupling between lifespan and stress resistance. Heat
shock proteins can be induced by not only mild temperature changes but protein
damage which can accumulate with aging and have positive effects on longevity
(Longo and Finch, 2003; Smith, 1958). Long-lived strains were more resistant to
oxidative and heat stress and have the increased expression levels of antioxidant genes
including Sod1, Sod2 and catalase. A forkhead transcription factor DAF-16 was
identified as a key regulator of heat and oxidative stress resistance and an essential
regulator of longevity. However, there are substantial variation in longevity and stress
resistance in experimental data. Not only diverse genetic and environmental factors
but the crosstalk between these factors regulating longevity add more complexity of
our understanding of aging.

8

1.3 Dietary and Calorie Restriction in Aging
Dietary restriction (DR) is a robust intervention to increase healthspan and lifespan in
many species, including yeast, nematode worms, flies and mammals (Fontana et al.,
2010; Hughes and Reynolds, 2005; Kirkwood, 2005). Although the underlying
mechanisms are not fully understood, the restriction of dietary and calorie intake has
remarkably broad and beneficial effects on increasing the lifespan and attenuating
chronic diseases of aging in model organisms (Colman et al., 2014; Fontana et al.,
2010).
Calorie restriction (CR) has also been shown to attenuate or delay the onset of
multiple age-associated diseases by increasing cellular protection systems and
reducing the accumulation of oxidative stress (Hughes and Reynolds, 2005; Longo
and Finch, 2003). Substantial data have supported that dietary or calorie restriction is
the promising and practical strategies to promote longevity and prevent the onset of
many age-dependent disorders, including cancers, inflammation responses,
neurodegenerative diseases and vascular diseases. Dietary or calorie restriction acts
similarly in many organisms without adverse side effects.
DR or CR triggers cellular responses that boost stress resistance and reduce
cellular damage. DR/CR has diverse effects on gene expression, antioxidant status,
and many other metabolic alterations. In model organisms, DR/CR protects against
diabetes, cancer, heart disease and neurodegenerative diseases. Experimental evidence
from genetic studies points to the important role of insulin/insulin-like growth factor-
9

1 (IGF-1) pathways in the regulation of aging by CR (Fontana et al., 2010; Longo and
Finch, 2003; Longo and Mattson, 2014). CR reduces plasma insulin and IGF-1 levels
and the down-regulation of insulin/IGF-1 signaling pathway induces the expression of
antioxidant and heat shock proteins (Longo and Fabrizio, 2002). The reduced activity
and mutations of insulin/IGF-1 pathway also decrease the risk of cancer,
neurodegenerative diseases and inflammation, and extend lifespan in various
organisms (Longo and Finch, 2003).
Accumulating evidence show that lifespan extension and beneficial effects by
DR/CR are mediated through the signaling of TOR-Sch9 and Ras-PKA which are key
components of the insulin/IGF-1-dependent signaling. These pathways primarily
control cellular nutrient sensing and utilization (Longo and Mattson, 2014). Both
pathways play a central role in controlling growth, metabolism, and stress resistance
and are responsible for the effects of DR/CR on aging. These pathways are also
conserved in other organisms from yeast to human and play a similar role in
modulating protective mechanism and longevity. Moreover, mutations and down-
regulation of these signaling pathways promote healthspan and resistance to oxidative
stress and other types of stress (Fontana et al., 2010).
CR also has significant anti-inflammatory effects of aging (Fontana et al., 2010;
Longo and Finch, 2003). Aging is associated with increased inflammatory activity and
inflammatory mechanisms are involved in several age-related disorders such as
Alzheimer’s disease, diabetes, and osteoporosis and enhanced mortality risk
10

(Bruunsgaard et al., 2001). The inflammatory molecular factor interleukin-6 (IL-6)
and tumor necrosis factor-α (TNF-α) commonly increase with age in rodents and
humans and these pro-inflammatory shift is known to promote inflammation in aging.
CR attenuates the expression of inflammatory genes in the body, and anti-
inflammatory effects may be one of the important parts for lifespan extension
following CR.

1.4 Nutrient Signal Transduction Pathways
Nutrient-sensing signaling pathways play a pivotal role in regulating cellular
protection and lifespan in a wide range of organisms (Fontana et al., 2010). Dietary
restriction has been the most well studied strategy for increasing survival and
preventing carcinogenesis in mammals. Insulin/IGF-1 signaling transduction has been
identified as a central regulator of aging. Reduced signaling of this pathway appears
to extend the lifespan of yeast, flies and rodents. The down-regulation by genetic
mutations in this signaling pathway also increases stress resistance and lifespan.
In yeast, lifespan extension is mediated by TOR-Sch9 or Ras-PKA (Fontana et
al., 2010; Longo and Mattson, 2014). Both pathways are involved in sensing and
controlling the availability and utilization of nutrients. Glucose can primarily activate
Ras-PKA pathway, and amino acids can turn on TOR-S6K pathway. These nutrient
11

sensing pathways converge onto the stress resistance regulation which includes protein
kinase Rim15 and transcription factors Msn2/4 and Gis1. Therefore, the major effects
of CR appear to be mediated by the down-regulation of these pathways and consequent
activation of Rim15-Msn2/4-Gis1 stress resistance pathways (Fig. 1.1). In fact, dietary
restriction in the growth medium or mutations in nutrient signaling pathways decreases
metabolic rates, up-regulates stress resistance pathways, and eventually promotes
lifespan extension.

Figure 1.1 Longevity pathways in yeast, worms, flies and mammals. Adapted from
Fontana, Partridge, and Longo (Fontana et al., 2010)
12

The similar pathways appear to regulate longevity in the worm C. elegans. The
chronogical longevity in worms is also extended by inactivation of IGF-1-like
signaling pathways through TOR-S6K and AGE1-AKT pathways. The down-
regulation of DAF-2, AGE-1, and/or AKT increases antioxidant defense mechanisms
and survival (Fig. 1.1). Dietary restriction also protects against age-related damage
and extends lifespan in worms. The forkhead transcription factor DAF-16 is required
for cellular protections and anti-aging effects of DR.
In flies, conserved genes are also involved in regulating stress resistance and
longevity. The down-regulation of both IGF-1-like and TOR-S6K pathways promotes
lifespan extension in flies (Fig. 1.1). Mutation in Drosophila insulin-like receptor (INR)
yields dwarf flies that extend lifespan up to 85% (Tatar et al., 2001). The reduction of
dietary amino acids also extends fly lifespan via IGF-1-like pathway (Grandison et al.,
2009).
Insulin/IGF-1 pathway also regulates longevity in rodents. Reduced calorie
intake has been suggested to determine longevity extension. The significant decrease
in blood glucose, insulin, and IGF-1 by restricting food intake is responsible for the
beneficial effects of DR/CR. Growth hormone (GH) and IGF-1 have been identified
to lower cellular stress response and antioxidant defense mechanisms and insulin/IGF-
1 pathways are inactivated by DR/CR. On the contrary, elevated GH or IGF-1 levels
cause severe kidney lesions and shorten lifespan of mice (Longo and Finch, 2003).
13

Clinical evidence has also supported that high levels of growth hormone (GH)
and/or IGF-1 are associated with increased risk of developing various types of cancer
and diseases in human (Galluzzi et al., 2013). Long-term dietary restriction can reduce
the risks for age-related diseases, including cancer and neurodegeneration. Short-term
starvation or prolonged fasting has been shown to be an effective intervention
augmenting cancer treatment in humans (Fontana et al., 2010; Lee et al., 2012; Longo
et al., 2008; Raffaghello et al., 2008). DR/CR can enhance the treatment efficacy of
chemotherapy and reduce the chemo-toxic side effects in mice and possibly humans
(Lee et al., 2012; Safdie et al., 2012).

1.5 Clinical Applications
DR/CR is a remarkably potent intervention to extend lifespan in numerous species. It
also has beneficial effects on the prevention of multiple age-related diseases. One of
the great challenge is to develop drugs that delay aging and age-related diseases. Up
to date, there are several clinically approved drugs that mimic DR/CR and prevent or
slow down the aging process and multiple age-related diseases (Blagosklonny, 2014).
For this purpose, the National Institute on Aging (NIA)’s Intervention and
Testing Program was established to test the effects of compounds on lifespan and
diseases. Rapamycin has been turned out to be the first candidate extending lifespan
14

in mice, even when administered relatively late in the lifespan (Harrison et al., 2009).
Rapamycin inhibits the activity of the rapamycin target kinase TOR, a key nutrient
sensing component. Genetic inhibition of TOR and downstream TOR target, S6 kinase
1, also mimics the rapamycin’s effects. Moreover, physiological studies show that
rapamycin treatments exert anti-tumor property and delays the incidence of
neurodegenerative diseases, age-related heart disease, and others (Blagosklonny,
2014). The accumulation of data suggest that both dietary restriction and rapamycin-
mediated TOR inhibition extend lifespan through overlapping effects (Kennedy and
Pennypacker, 2014).
Metformin, the front-line treatment of antidiabetic therapy, has been reported
to increase healthspan and lifespan in mouse model (Martin-Montalvo et al., 2013).
Metformin administration lowers blood glucose and lipid contents by reducing hepatic
glucose production and increasing glucose utilization in skeletal muscles (Zhou et al.,
2001). Metformin is also a well-known AMPK activator, and AMPK pathway is
thought to be responsible for its therapeutic benefits, including lower cancer incidence
and mortality, anti-inflammatory and cardioprotective effects (Apaijai et al., 2012;
Hirsch et al., 2013; Zakikhani et al., 2006).
Aspirin is a nonsteroidal anti-inflammatory drug (NSAID) and also has anti-
oxidant and anti-aging properties (Miller et al., 2007). Treatment of aspirin has been
shown to have a significant effect on lifespan extension in a mouse model (Strong et
al., 2008). Aspirin decreases pro-inflammation via suppression of the expression of
15

TNF-α, a central regulator of inflammation and inhibition of COX-1 and COX-2
activities (Shackelford et al., 1997; Strong et al., 2008). The inhibition of TNF-α and
COXs accounts for aspirin’s beneficial effects on the prevention of multiple age-
associated diseases and the extension of lifespan.
Clinical and pre-clinical research suggest that several clinically approved drugs
have shown significant promise as anti-aging agents for treating age-related diseases.
However, long-term side effects limit their applications in humans. More
comprehensive studies will allow for more definitive conclusions to determine
whether any drug could prove beneficial for human longevity and prevent age-related
diseases without adverse side effects.

16

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Harman, D. (1972). The biologic clock: the mitochondria? Journal of the American
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21

Chapter 2
Short-term starvation induces the post-
translational modification of REV1
through oxidative stress.

2.1 Introduction
DNA is the important heredity materials which carry genetic information in all living
organisms. However, DNA is highly vulnerable and subject to continuous damage
from exogenous environmental sources as well as from spontaneous cellular reactive
metabolism (Prakash et al., 2005; Simpson and Sale, 2003). DNA damage by intrinsic
and extrinsic damaging agents can lead to harmful consequences, such as genetic
mutations, genomic instability, aging, cancer, or cell death, so cells also employ DNA
repair mechanism to restore or remove DNA damage. The eukaryotic cells have
evolved robust DNA repairing mechanisms. To prevent transmission of this damage
to daughter cells, the cells typically first arrest cell cycles and recover after repairs are
22

completed. Although abasic lesions can be repaired or removed by the several repair
mechanisms, unrepaired DNA lesions which escape repair pathways can block
replication progression (Kannouche et al., 2004; Schlacher and Goodman, 2007). One
of the major pathways to deal with such blocks uses the specialized low-fidelity DNA
polymerases that are capable of replicating over the DNA lesions, a translesion DNA
synthesis (TLS) (Bomar et al., 2010; Kannouche et al., 2004). DNA damage tolerance
mechanisms allow the cells to continue replication despite the presence of lesions in
DNA. DNA damage, thus, results in either DNA repair or damage tolerance processes.
Several strategies have been provided to allow cells to repair or tolerate DNA damage,
allowing progressive replication to be continued, eventually for increased probability
of cell survival at the cost of increased mutagenesis. Therefore, TLS is also an essential
cellular strategy to promote cell survival by restarting DNA replication, but
accompanied by an increase in mutations.
The majority of TLS polymerases belong to the Y family polymerases
(Friedberg, 2003). The Y family polymerases do not have proofreading exonuclease
activity, so are able to replicate template DNA damage by bypassing DNA lesions.
REV1 was originally characterized as a member of specialized Y-family DNA
polymerases, which exhibit low replication fidelity that can overcome lesion-induced
DNA replication arrest, a process known as translesion synthesis (TLS) (Kosarek et
al., 2008). Since most mutations from DNA damage are the consequence of error-
prone translesion DNA synthesis, TLS polymerases could be responsible for the
tumorigenesis and chemoresistance (Dumstorf et al., 2009; Xie et al., 2010; Xu et al.,
23

2013). REV1 has been shown to contribute to genomic instability during yeast aging
and under genotoxic stress (Madia et al., 2009; Sharma et al., 2012a), and to be partly
responsible for carcinogen-induced mutagenesis, tumor formation and
chemoresistance in mammals (Dumstorf et al., 2009; Xie et al., 2010). On the other
hand, REV1 deficiency led to hypersensitivity to multiple DNA damaging agents and
reduced cell viability (Madia et al., 2009; Pages et al., 2009). Our previous findings
point to the pivotal role of REV1 in promoting point mutations while preventing gross
chromosomal rearrangements and cell death under genotoxic stress (Madia et al.,
2009). Interestingly, recent studies have indicated that REV1's polymerase activity
may not be required for TLS, and that REV1 may play more important roles in genome
maintenance through its non-catalytic functions (Sharma et al., 2012b). REV1 protein
can interact with multiple specialized DNA polymerases, such as Polκ, Polι, Polη, and
Polζ, as well as with the critical regulators of DNA replication and repair processes,
such as proliferating cell nuclear antigen (PCNA) (Guo et al., 2003; Guo et al., 2006a).
The elucidation of REV1’s non-catalytic functions is central to gain a better
understanding of its involvement of maintaining genomic stability.
Post-translational modification by the small ubiquitin-like modifier (SUMO)
has emerged as an essential regulatory mechanism for diverse cellular processes
(Bergink and Jentsch, 2009; Dou et al., 2010; Jackson and Durocher, 2013).
SUMOylation regulates the subcellular localization, activity, interaction, and stability
of target proteins. Mammalian cells express three major SUMO isoforms, SUMO1 and
the highly-related SUMO2 and SUMO3 (SUMO2/3). These small proteins are
24

covalently conjugated to lysine residues of target proteins via an enzymatic cascade
involving E1 (activating), E2 (conjugating), and E3 (ligating) enzymes and can also
be reversely deconjugated by several SUMO cleaving enzymes (Deshaies and
Joazeiro, 2009). Interestingly, SUMOylation plays important roles in DNA repair and
the preservation of genomic integrity, and has been implicated in the regulation of the
key regulatory proteins, such as p53, PCNA, BRCA1, and 53BP1 (Galanty et al., 2009;
Hoege et al., 2002; Morris et al., 2009; Rodriguez et al., 1999). The accumulated data
have also supported that protein modification is directly involved in modulating tumor
cell sensitivity to the chemotherapeutic agents by altering the regulatory pathways and
cellular responses critical to drug response (Dai and Gu, 2010; Shen et al., 2012).
In this chapter, I show that REV1 is rapidly modified by SUMO2/3 conjugation
in cancer cells via ROS under starvation conditions. PIASy E3 SUMO ligase
modulates REV1 SUMOylation. The SUMO modification at the lysine 119 residue
stabilizes REV1 protein itself. These findings support an important new role for REV1
as an important signaling node linking nutrient sensing to metabolic control in cancer
cells in response to starvation conditions.

25

2.2 Results
Short-term starvation induces REV1 modification.
Our previous studies have recently shown that short-term starvation or fasting can
promote sensitization of a variety of cancer cells to chemotherapeutic agents but can
also delay cancer progression independently of chemotherapy (Lee et al., 2012a;
Safdie et al., 2012). In agreement with our previous studies, STS had a potent effect
on sensitizing human MCF7 breast carcinoma cells to the chemotherapeutic drug
doxorubicin (DXR) (Fig. 2.1A).
Our previous findings have previously shown that REV1, an error-prone DNA
repair enzyme, is a major contributor to age-dependent genomic instability and to cell
survival in response to genotoxic stress in S. cerevisiae (Madia et al., 2009). Since
recent studies have also shown that mammalian REV1 is implicated in cancer drug-
induced mutagenesis and drug resistance (Xie et al., 2010; Xu et al., 2013), I have
sought to determine the role of REV1 in cancer cells in response to starvation.
Interestingly, STS of human MCF7 breast cancer cells and of mouse B16 melanoma
cells resulted in the generation of slower-migrating forms (the upper bands) of
endogenous REV1 proteins in SDS-PAGE (Figs 2.1B and D). However, no significant
change in REV1 mRNA levels was observed during the same time period (Fig. 2.1C).

26

Figure 2.1 Short-term starvation leads to REV1 modification. (A) Doxorubicin dose-
response curves in MCF7 cells upon normal or starvation conditions. Starvation was applied
to cells 24 h before and 24 h during DXR treatment. Cytotoxicity values were obtained by
evaluation of LDH release to assess cell viability. (B, D) MCF7 and B16 cells were fed
complete or starvation medium for the indicated times, lysed and immunoblotted with anti-
REV1 antibody. A tubulin blot was presented as a loading control (bottom panel). (C) Relative
mRNA expression level of REV1 in MCF7 cells was measured after 48 h of starvation
condition.

27

Figure 2.2 ROS induces REV1 modification under STS. (A) ROS levels under STS were
examined by carboxy-H2DCFDA. Cells were incubated with starvation medium for the indicate
times, and the fluorescence intensity of carboxy-H2DCFDA was analyzed by fluorescence
microscopy. (B) Cells were starved for 24 h, followed by treatment with 10 or 25 mM NAC for
additional 24 h. The cell extracts were separated by SDS-PAGE and blotted with anti-REV1
antibody.

Nutrient starvation can induce the accumulation of intracellular reactive
oxygen species (ROS) which contributes to cell death selectively in cancer cells (Lee
et al., 2012a; Raffaghello et al., 2008). In agreement with previous results, I observed
that the ROS levels were elevated at 24 h and increased further at 48 h of STS (Fig.
2.2A). Since ROS operate in cellular signaling events (D'Autreaux and Toledano,
2007), I next determined their effect on REV1 response to starvation. Treatment of
starved cells with the ROS scavenger N-acetyl cysteine (NAC) significantly attenuated
REV1 modification (Fig. 2.2B), indicating a ROS-induced REV1 modification upon
STS.
28

Figure 2.3 REV1’s effect on STS-induced sensitization of MCF7 cells to DXR. (A, B)
Confirmation of siRNA-mediated depletion of endogenous REV1. MCF7 cells were transfected
with non-targeting control or REV1 siRNAs. 48 h following siRNA transfection, cell extracts
were prepared and analyzed by qRT-PCR (A) and Western blot (B). (C) MCF7 cells were
transfected with non-targeting control or REV1 siRNAs. 24 h following siRNA transfection,
cells were incubated in normal or starvation conditions for additional 24 h. After DXR treatment
for 24 h, cells were prepared and analyzed by LDH assay. Data are shown as average ± SD.

I next investigated REV1’s effect on cancer chemotherapy. I used short-
interfering RNA (siRNA) to knock down REV1 expression (Fig. 2.3A and B). I tested
the cytotoxicity of MCF7 cells after exposure to different combinations of DXR and
STS treatments. Before DXR treatment, cells were transfected with siRNA for 48 h to
achieve reduced REV1 expression. Whereas siREV1 did not affect DXR toxicity,
29

Figure 2.4 SUMO2/3 modification of REV1 in response to ROS. (A) HEK293 cells were
treated with 200 µM H2O2 for 15 min. Equal amounts of total cellular proteins were
immunoblotted with anti-REV1 antibody. A tubulin blot was presented as a loading control
(bottom panel). (B) Cell extracts from HEK293 cells treated with or without 200 µM H2O2 for
15 min were immunoprecipitated with anti-SUMO2/3 or anti-Ubiquitin antibody under
denaturing conditions and immunoblotted with anti-REV1 antibody. IgG heavy chain is shown
as loading control.

the combination of REV1-knockdown and STS doubled the killing of MCF7 cells by
DXR treatment (Fig. 2.3C), providing evidence that REV1 suppression combined with
STS can enhance chemosensitization of cancer cells.

REV1 is post-translationally modified by SUMO2/3 in response to ROS.
I investigated further the molecular mechanisms underlying REV1 modification by
STS-induced ROS. Consistent with our previous data, slower-migrating forms of
endogenous REV1 protein in SDS-PAGE were also observed in response to hydrogen
peroxide treatment (Fig. 2.4A).

30

Figure 2.5 The conjugation of SUMO2 and SUMO3 to REV1 protein. (A) Either HA-
SUMO2 or HA-SUMO3 was transiently co-expressed with Myc-REV1 in HEK293 cells, and
cell extracts were immunoblotted with anti-Myc antibody.

Post-translational modification with SUMO, especially SUMO2/3, has recently been
established as a key step in cellular stress response (Bergink and Jentsch, 2009).
SUMO conjugation is a rapid and reversible process which regulates numerous protein
functions. To determine whether REV1 protein is modified by SUMO, cell extracts
treated with H2O2 were immunoprecipitated with anti-SUMO2/3 antibody under
denaturing conditions. Immunoprecipitated SUMO2/3 also pulled down REV1, and
the anti-SUMO2/3 signal overlapped with the slower-migrating bands of REV1 (Fig.
2.4B, upper panel). Although REV1 can also be modified by ubiquitin (Guo et al.,
2006b), the ubiquitination level of REV1 was not affected by H2O2 (Fig. 2.4B, lower
panel). These data indicate that endogenous REV1 is modified by endogenous
SUMO2/3 in response to both exogenous and endogenous ROS.

31

Figure 2.6 Confirmation of REV1 modification by SUMO2/3. (A) HEK293 cells were co-
transfected with Myc-REV1 and HA-SUMO3, and extracted under denaturing conditions.
SUMOylation of REV1 was determined by reciprocal immunoprecipitation and immunoblot
analyses. Whole cell lysates were immunoblotted for Myc-REV1 as input control, and IgG
heavy chain as loading control. (B) Cells were co-transfected with Myc-REV1 and HA-SUMO2,
treated with H2O2 (200 µM) or IGF-1 (200 ng/ml) for 15 min, and immunoblotted with anti-Myc
antibody. Arrowheads indicate the SUMOylated form (filled) and the unmodified form (open).

SUMOylation of REV1 was further confirmed by co-transfection assay with Myc-
tagged REV1 and HA-tagged SUMO2 or SUMO3 expression constructs. The slower-
migrating forms of REV1 were detected in immunoblots of whole cell lysates from
co-transfected cells, but not from cells expressing Myc-REV1 alone (Fig. 2.5A).
Moreover, reciprocal immunoprecipitation and immunoblot analyses confirmed that
the slower-migrating forms corresponded to SUMO-conjugated forms of REV1 (Fig.
2.6A). H2O2 treatment also led to an increase in REV1 SUMOylation, but introduction
of insulin-like growth factor 1 (IGF-1), whose decreased levels are central in the
effects of STS in cancer treatment (Lee et al., 2012a), reversed the ROS-induced REV1
32

SUMOylation (Fig. 2.6B). These data provide direct evidence that endogenous, as well
as ectopically expressed, REV1 is SUMOylated in vivo via ROS.

PIASy E3 SUMO ligase modulates REV1 SUMOylation.
SUMOylation is a reversible and dynamic process (Dou et al., 2010). SUMO can be
removed from targets by a family of SUMO-specific peptidases (SENPs), and at least
six members (SENP1-3 and SENP5-7) have been identified in mammalian cells. To
examine whether SUMO proteases act on SUMO-modified REV1, HEK293 cells were
co-transfected with REV1, SUMO2, and either SENP1 or SENP6. Over-expression of
either SENP1 or SENP6 resulted in SUMO deconjugation from REV1 (Fig. 2.7A).

33

Figure 2.7 SENPs de-conjugate SUMO from REV1. (A) HEK293 cells were co-transfected
with Myc-REV1 and HA-SUMO2, together with either Flag-SENP1 or Flag-SENP6. Cell
extracts were immunoblotted with the indicated antibodies.

Recently, PIAS (protein inhibitor of activated STAT) proteins have been
reported to be specific E3 SUMO ligases in DNA damage response (Morris et al.,
2009). In an attempt to examine whether a PIAS can serve as a SUMO E3 ligase for
REV1, HEK293 cells were transfected with REV1 and PIASy and cell extracts were
subjected to co-immunoprecipitation (Co-IP) assay. PIASy co-precipitated with REV1
in vivo and REV1-PIASy interaction was markedly increased by ROS (Fig. 2.8A).
Furthermore, co-expression of PIASy enhanced REV1 modification, although E2
conjugating enzyme UBC9 did not exhibit any obvious effect (Fig. 2.8B), suggesting
that PIASy acts as an E3 SUMO ligase for REV1 SUMOylation.

34

Figure 2.8 PIASy functions as a SUMO E3 ligase for REV1. (A) Cells expressing Myc-
REV1 and Flag-PIASy were treated with H2O2 for 15 min. Equal amounts of total cellular
proteins were co-immunoprecipitated with anti-Myc antibody, and analyzed by immunoblot
with anti-Flag antibody. Whole cell lysates were immunoblotted for Flag-PIASy as input
control. (B) Cells were co-transfected with Myc-REV1 and HA-SUMO2 together with HA-UBC9
or Flag-PIASy, and cell extracts were immunoblotted with the indicated antibodies.

SUMO modification promotes the stability of REV1 protein.
SUMO is covalently bound to lysine residues in target proteins (Bergink and Jentsch,
2009). Sequence analysis identified twelve putative SUMOylation sites in REV1 (Fig.
2.9A).
35

Figure 2.9 Mouse REV1 protein is SUMO2-modified at the K119 residue in vivo. (A)
Schematic of mouse REV1 protein and its putative SUMOylation motifs predicted by Abgent
SUMOplot (www.abgent.com/ sumoplot) and SUMOsp 2.0 (Ren et al., 2009). (B) HEK293
cells were co-transfected with wild-type or mutated Myc-REV1 and HA-SUMO2, and cell
extracts were immunoblotted with anti-Myc antibody. Arrowheads indicate the SUMOylated
form (filled) and the unmodified form (open).

Substitutions of the lysine (K) residues for arginines (R) by site-directed mutagenesis
demonstrated that K119 is the major SUMOylation site of REV1 (Fig. 2.9B).

36

Figure 2.10 SUMOylation stabilizes REV1 protein. (A) Sequence alignment of REV1
SUMOylation sites using ClustalW2 web tool indicating that SUMOylation site of murine REV1,
lysine 119 (K119), is highly conserved in vertebrates. (B) Stability of wild-type REV1 and the
K119R mutant. HEK293 cells expressing Myc-tagged wild-type REV1 or the K119R mutant
were treated with CHX (30 µg/ml) alone or together with MG132 (50 µM) for the indicated
times. REV1 protein level was analyzed by immunoblot with anti-Myc antibody and quantified
using ImageJ (http://imagej.nih.gov/ij/).

Sequence comparison revealed that this SUMOylation site is highly conserved in
vertebrates (Fig. 2.10A).
37

Figure 2.11 SUMOylation increases the stability of endogenous REV1. B16 cells were
transfected with different amounts of HA-SUMO2 expressing vectors for 18 h, lysed and
immunoblotted with anti-REV1 antibody. A tubulin blot was presented as a loading control.

A recent yeast study showed that REV1 is regulated by proteasomal
degradation and that its stability may be modulated by protein modifications (Wiltrout
and Walker, 2011). Prior studies have also shown that SUMO contributes to regulating
the stability of SUMO target proteins, including NF-κB inhibitor IκBα, transcription
factor Oct4 and Huntingtin (Hay, 2005; Steffan et al., 2004; Ulrich, 2005; Wei et al.,
2007). To test whether SUMOylation would affect REV1 stability in mammalian cells,
I analyzed the stability of wild-type REV1 and the SUMOylation-deficient mutant
(K119R) by blocking de novo protein synthesis with cycloheximide. Wild-type REV1
was found to be stable with an estimated half-life of ~ 10 h, but mutant REV1
displayed a markedly reduced half-life of ~ 3 h. The stability of both forms was
significantly increased in cells treated with MG132, a specific inhibitor of 26S
proteasome (Fig. 2.10B). These data are consistent with the previous observations that
the abundance of wild-type REV1 when co-expressed with SUMO or PIASy was
higher than that of REV1 when expressed alone (Figs 2.1, 2.5-2.9). Furthermore, the
38

ectopic expression of SUMO also enhanced the stability of endogenous REV1 protein
(Fig. 2.11), indicating that SUMOylation controls REV1 stability.

39

2.3 Discussion
Short-term starvation or fasting has been shown to have beneficial effects in cancer
treatment by augmenting the efficacy of chemotherapy, but its mechanism of action
remain poorly understood (Fontana et al., 2010; Lee et al., 2012a; Safdie et al., 2012).
REV1 plays an important regulatory role in DNA damage response and depletion of
REV1 leads to an increase in sensitivity to DNA-damaging agents, genomic instability
and tumorigenesis (Dumstorf et al., 2009; Wei et al., 2009). Although emerging
evidence has indicated that REV1 is required for maintaining genomic integrity and
cell viability, the underlying mechanism of REV1 function remains elusive. Here, my
study demonstrates that REV1 is a novel target of SUMOylation and this modification
has an important role in the stabilization of REV1 protein.
The depletion of nutrients causes ROS production and leads to apoptotic cell
death in cancer cells (Lee et al., 2012b; Raffaghello et al., 2008). ROS also act as
signaling molecules which can regulate a number of cellular activities. My findings
reveal that REV1 protein is post-translationally modified by SUMO2/3 through ROS
in response to STS. Recently, SUMOylation has been shown to be involved in various
DNA repair mechanisms (Dou et al., 2011). SUMO E3 ligase PIASy is required for
modulating the activity of target proteins in DNA repair mechanisms and cell fate
determinations in response to various stresses (Bischof et al., 2006; Galanty et al.,
2009). I found that PIASy is a SUMO E3 ligase for REV1 and ROS which are induced
by STS increase their interaction while IGF-1 treatment decreases it. Besides its role
40

in REV1 SUMOylation, the interplay between SUMOylation and other modification
or protein-protein interaction may be important for understanding the precise nature
of the non-catalytic function of REV1. Although lysine 119 residue is identified as the
major SUMOylation site of REV1 protein, I was not able to exclude the possibility
that REV1 have multiple lysine residues which can be SUMOylated.
My data show that N terminus of REV1, containing the BRCT domain which
is critical for protein-protein interaction, was involved in the post-translational
modification. The C-terminal domain of REV1 has been shown to be required for the
interaction with other DNA polymerases, including Polκ, Polι and Polη, and the B
family TLS polymerase Polζ (Guo et al., 2003; Sale et al., 2012). The novel interaction
between REV1 and other interacting partners as well as their SUMOylation-dependent
roles in DNA damage response will provide new clues on the role of specific DNA
repair protein in the regulation of multiple cellular processes.
In conclusion, this study identifies that REV1 is a novel target of SUMOyaltion
in cancer cells under stress conditions. The REV1 knockdown enhances the short-term
starvation-induced sensitization of cancer cell to chemotherapy. Further studies on the
relationship between REV1 SUMOylation and cancer cell fate have the potential to
provide important insights into the precise regulatory mechanism of short-term
starvation in cancer cells.

41

2.4 Experimental Procedures
Cell culture and transfection
MCF7 human breast carcinoma cells, B16 mouse melanoma cells and human
embryonic kidney (HEK) 293 cells were maintained in Dulbecco’s modified Eagle’s
medium (DMEM) with 10% fetal bovine serum (FBS) and 100 units/mL penicillin
plus 100 µg/mL streptomycin (Invitrogen). Cells were all maintained in a humidified
incubator at 37°C under 5% CO2. Transient transfection was carried out using the X-
tremeGENE HP Transfection Reagent (Roche Applied Science) according to the
manufacturer’s instructions. For RNAi experiments, SMART Pool siRNAs
(Dharmacon) against mouse or human REV1 (M-041898-01 and M-008234-01) or
non-targeting siRNA (D-001210-01) were transfected into the cells using
Lipofectamine RNAiMAX reagent (Invitrogen), according to the manufacturer’s
protocols.
Plasmid expressing Myc-REV1 (Guo et al., 2003) was gifted from Dr. Errol C.
Friedberg (University of Texas Southwestern Medical Center, USA). Expression
vectors for HA-SUMO2 (Kamitani et al., 1998) (17360), HA-SUMO3 (Kamitani et
al., 1998) (17361), HA-Ubc9 (Yasugi and Howley, 1996) (14438), Flag-PIASy (Liu
et al., 2001) (15208), Flag-SENP1 (Cheng et al., 2007) (17357) and Flag-SENP6 (Dou
et al., 2010) (18065) have been described previously and were obtained from Addgene.
A series of deletion constructs of Myc-REV1 were generated by ExoIII-S1 nuclease
digestion (Promega). Mutations of lysine residues to arginine were generated by PCR-
42

based site-directed mutagenesis using the Quik Change II XL Site-Directed
Mutagenesis Kit (Stratagene). All mutants were verified by DNA sequencing.

LDH cytotoxicity assay
At 24 h following siRNA introduction, MCF7 cells were incubated in normal or
starvation media for additional 24 h. Chemotherapeutic agent was treated the
following day and cell cytotoxicity was measured 24 h later by LDH release assay
(Promega).

Immunoprecipitation and immunoblot analysis
Immunoprecipitation and immunoblot analyses were performed as previously
described (Shim et al., 2007), with minor modifications. For co-immunoprecipitation
assay, mouse tissues or cells were lysed on ice in a modified RIPA buffer containing
50 mM HEPES at pH 7.4, 150 mM NaCl, 1% NP 40, 1 mM EDTA, 1X phosphatase
and phosphatase inhibitor cocktail (Pierce), and the whole lysates were clarified by
centrifugation. The supernatants were incubated overnight at 4°C with 2 µg of
indicated antibody; and the protein A/G plus agarose beads (Pierce) were then added
and incubated for an additional hour at 4°C. Co-immunoprecipitation of transfected
Flag-p53 and Myc-REV1 was carried out using anti-Flag M2 affinity gel (Sigma) and
anti-c-Myc-agarose beads (Pierce) according to manufacturers’ instructions in order
43

to minimize interference by IgG heavy chain with p53. Immunoprecipitates were
recovered with SDS sample buffer and subjected to Western blot analysis.
For analysis of SUMO-modified REV1 protein, immunoprecipitation was
performed under denaturing conditions in the presence of NEM, a deSUMOylation
inhibitor, as described previously (Yu et al., 2009), with minor modification. The cells
were washed with ice-cold PBS, lysed by adding SUMO lysis buffer (62.5 mM Tris
at pH 6.8, 2% SDS), and boiled for 10 min. The samples were centrifuged for 20 min
at full speed and the supernatant was diluted 1/20 with NEM-RIPA buffer
supplemented with 20 mM N-ethylmaleimide (NEM; Calbiochem). The same amount
of total protein was used for immunoprecipitation, followed by Western blot analysis.
Antibodies against Myc (9E10; Santa Cruz Biotechnology), Flag (M2; Sigma-
Aldrich), HA (F-7; Santa Cruz Biotechnology), REV1 (H-300; Santa Cruz
Biotechnology), SUMO2/3 (Zymed Laboratories Inc), Ubiquitin (P4D1; Santa Cruz
Biotechnology) and Tubulin (Cell Signaling Technology) were obtained from
commercial sources.

RNA isolation and quantitative RT-PCR
Total RNA was isolated using TRI Reagent (Invitrogen), reverse-transcribed with M-
MLV Reverse Transcriptase (Promega), and amplified with SYBR Green PCR maser
mix (Invitrogen) according to the manufacturer’s recommendation. The following
44

PCR primers were used: human REV1 forward 5'-TTG TGA TGA AGC GCT GGT
AG-3', REV1 reverse 5'-TTG GTC ACT AGC TGG CCT CT-3', and β-ACTIN forward
5'- GGA CTT CGA GCA AGA GAT GG -3', β-ACTIN reverse 5'- AGC ACT GTG
TTG GCG TAC AG -3'. The expression levels were normalized with β-ACTIN mRNA
in each sample.

Starvation treatment
Short-term starvation (STS) in a cell culture model was performed by glucose and
serum restriction. The culture media were supplemented with 0.5 g/L or 2.0 g/L
glucose to match blood glucose levels in starved and normally fed mice, respectively
(Lee et al., 2012a). FBS was supplemented at 1% for starvation conditions as
compared to the normal 10%. For STS in vivo, mice were fasted for 24-48 h by
complete deprivation of food, but with free access to water.

Detection of cellular reactive oxygen species (ROS) level
Cells were treated as indicated, stained with fluorescent indicator 5-(and-6)-carboxy-
2´,7´-dichlorodihydrofluorescein diacetate (carboxy-H2DCFDA) for 30 min, and then
analyzed by fluorescence microscopy according to the manufacturer’s instructions
(Invitrogen).
45

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51

Chapter 3
The interplay between p53 and REV1
in cancer therapy.

3.1 Introduction
Nutrient-sensing signaling pathways play a pivotal role in regulating cellular
protection and lifespan in a wide range of organisms (Fontana et al., 2010). A chronic
20~30% reduction in calorie intake, or calorie restriction, has been a well-studied
strategy for increasing survival and preventing carcinogenesis in mammals. However,
its application in the treatment of existing tumors has been hindered by a lack of
consistent and potent effects in animal studies and the incompatibility of the resulting
chronic reduction in weight with cancer treatment in humans. Our previous studies
have recently shown that short-term starvation (STS) or prolonged fasting (PF) is an
effective intervention enhancing the treatment of a wide variety of tumors in mice but
possibly also protecting human against chemotherapy toxicity (Fontana et al., 2010;
Lee et al., 2012a; Longo et al., 2008; Raffaghello et al., 2008).
52

The tumor suppressor p53 plays a key role in multiple signaling pathways in
response to genotoxic and cellular stresses (Beckerman and Prives, 2010). In response
to a broad array of stimuli, p53 is activated and regulates the expression of hundreds
of target genes involved in cellular processes including cell growth arrest, DNA repair
or apoptotic cell death. The p53-dependent responses are regulated by p53 abundance,
cellular localization and activity, all of which are affected by p53’s post-translational
modifications and its interactions with various binding partners, such as BRCA1,
ATM, NFκB, MDM2, PML, and p300/CBP (Beckerman and Prives, 2010). In fact,
the development of small molecule activators of the p53 network holds the promise to
advance current cancer therapy.
In this chapter, I show that REV1 interacts with p53 and regulates its stability
and transactivation. Under starvation conditions, REV1 is rapidly modified by
SUMO2/3, resulting in increased REV1 stability with a consequent relief of its
inhibition of p53 activation. Starvation simultaneously causes p53
phosphorylation/acetylation and its activation, leading to the death of cancer cells.
Thus, my data support an important new role for REV1 as a regulator of p53-dependent
death of cancer cells in response to starvation conditions.

53

3.2 Results
REV1 is a novel interacting partner of p53 in vivo.
The eukaryotic REV1 protein has also been shown to function as a scaffold protein
that interacts with multiple DNA metabolic and repair proteins (Guo et al., 2003; Guo
et al., 2006a). The p53 tumor suppressor is a key molecule in genomic maintenance
and cell fate in mammals (Vousden and Lu, 2002). Recent studies indicated that p53
and REV1 participate in overlapping cellular processes (Lin and Howell, 2006; Monti
et al., 2008; Tsaalbi-Shtylik et al., 2009). I have sought to study whether REV1 may
interact with p53. I found that full-length REV1 was able to interact with full-length
p53 in vivo (Fig. 3.1A). To characterize the minimal p53 binding domain of REV1, I
generated truncated REV1 mutants and performed co-immunoprecipitation assays
with full-length p53 in HEK293 cells. Progressive deletion constructs revealed that the
N-terminal domain (residues 1-190) of REV1, which contains the BRCA1 C-terminal
(BRCT) domain, was sufficient for p53 binding (Figs 3.1B and C). Other truncated
mutants (residues 1-887 and 1-1043) of REV1 were also immunoprecipitated with p53
(Fig. 3.1D).

54

Figure 3.1 REV1 interacts with p53 via its N-terminal BRCT domain. (A) Myc-tagged full-
length REV1 was transiently co-expressed with Flag-tagged full-length p53 in HEK 293 cells,
and cell lysates were immunoprecipitated with anti-Myc-agarose beads. The immune
complexes were analyzed by immunoblotting with anti-Myc and anti-Flag antibodies. The
asterisk indicates IgG heavy chain. (B) Schematic of REV1 protein and the deletion mutants.
(C) The N-terminal BRCT domain of REV1 is sufficient for its interaction with p53. Full-length
or truncated (residues 1-190) Myc-REV1 was co-expressed with full-length Flag-p53 in
HEK293 cells, and cell lysates were immunoprecipitated with anti-Myc conjugated beads,
followed by Western blot analysis with anti-Flag antibody. Whole cell lysates were
immunoblotted for Flag-p53 and Myc-REV1 as input control. (D) Pull-down assays of the
interaction between p53 and deletion mutants of REV1. Myc-tagged full-length or deletion
mutants (residues 1-1043 and 1-887) of REV1 were co-transfected with Flag-tagged full-length
p53 in HEK293 cells. 24 h after transfection, cell lysates were immunoprecipitated with anti-
Myc-agarose beads. The immune complexes were subjected to immunoblot with the indicated
antibodies.
55

Figure 3.2 The C-terminal region of p53 is sufficient for REV1 interaction. (A) Schematic
of Flag-tagged p53 and its fragments. (B) The C-terminal domain of p53 is sufficient for the
interaction with REV1. Full-length or fragments of Flag-p53 were overexpressed with Myc-
REV1. Cell lysates were immunoprecipitated with anti-Flag antibody-conjugated agarose. (C)
Endogenous p53 and REV1 interact. The liver lysates from C57BL/6 mouse were
immunoprecipitated with either normal rabbit IgG or anti-p53 antibody. Immunoprecipitates
were then analyzed by immunoblotting with anti-REV1 antibody. Whole tissue lysates were
immunoblotted for REV1 and p53 as input control.

56

The p53 protein is composed of several discrete functional domains, such as
an N-terminal transactivation domain, a DNA binding domain, and a C-terminal
region (Beckerman and Prives, 2010). To further define the REV1 interaction domain
in p53, I generated p53 fragments and expressed full-length or variant p53 with wild-
type REV1 in HEK293 cells. Co-IP assays revealed that REV1 can interact with the
C-terminal domain as well as full-length p53 (Figs 3.2A and B), indicating that C-
terminal region of p53 is sufficient for REV1 interaction. More importantly, I also
examined the interaction between p53 and REV1 at the endogenous level in mouse
liver (Fig. 3.2C), suggesting that REV1 can form a complex with p53 in vivo.

REV1 modulates p53 transactivation and stability in response to STS.
The p53 protein is a well-known transcription factor, and has been shown to mediate
cellular response to metabolic stress (Vousden and Lu, 2002). Because REV1 and p53
interact in vivo, I examined the effects of REV1 on the transcriptional activity of p53
under stress conditions. MCF7 control and REV1-knockdown cells were transfected
with the p53-responsive reporter, PG13-luc, and subjected to STS. The transcriptional
ability of p53 was enhanced with increasing duration of STS (Fig. 3.3A). Furthermore,
REV1-knockdown significantly induced p53 transactivation upon starvation. Similar
results were obtained with the promoter of p21, a well-known p53 target (Fig. 3.3B).
In addition, REV1 over-expression markedly reduced the p21 promoter activity (Fig.
3.3C), in agreement with a negative effect of REV1 in regulating p53.
57

Figure 3.3 REV1 negatively modulates p53 transcription activity. (A, B) PG13-luc (A) or
p21-luc (B) was transfected in both MCF7 control and REV1-knockdown cells. 24 h
posttransfection, STS was carried out for indicated time points followed by luciferase assay.
(C) p21-luc was co-transfected with Myc-REV1 and/or Flag-p53 as indicated. Luciferase assay
was carried out 24 h posttransfection.

p53 is an unstable protein and presents at low levels in normal cells, and its
activity is influenced by its interaction (Kruse and Gu, 2009). I therefore tested
whether REV1 regulates p53 stability. REV1 was able to enhance the steady-state
levels of p53 in both p53-null MEFs and H1299 cells (Fig. 3.4A).
58

Figure 3.4 REV1 regulates p53 stability. (A) p53-null MEFs (left panel) or human H1299
cells (right panel) were co-transfected with Flag-p53 and increasing amounts of Myc-REV1.
The level of p53 was analyzed by Western blot analysis with anti-Flag antibody. A tubulin blot
was presented as a loading control (bottom panel).

To further assess the contribution of REV1 in p53 transactivation during
starvation response, real-time PCR was carried out and the levels of p53 target genes
were analyzed in the presence and absence of REV1 suppression. STS moderately
increased the expression of pro-apoptotic and metabolic target genes, including BAX,
NOXA, PUMA, KILLER, TIGAR, and SESTRIN2. Furthermore, REV1 suppression
increased the basal levels of gene expressions, and dramatically enhanced the
expression levels upon STS (Fig. 3.5A). These data are consistent with the reporter
assays (Fig. 3.3), supporting the involvement of REV1 in the regulation of p53 activity
in response to starvation.
59

Figure 3.5 REV1 modulates p53 activity and its downstream in response to starvation.
(A) MCF7 control and REV1-knockdown cells were subjected to STS for 48 h. Total RNA was
isolated and relative mRNA levels were analyzed by qRT-PCR for the indicated genes. Results
shown are reported as average ± SD.

REV1 modulates p53-mediated starvation response in vivo.
The post-translational modifications of p53 and its interacting proteins are the subject
of intense research due to their profound effects on p53’s overall activity and stability
(Kruse and Gu, 2009). I therefore examined whether the modification status of REV1
could affect p53 function in in vitro and in vivo cancer models.
60

Figure 3.6 REV1 SUMOylation affects p53 transactivation. (A) MCF7 cells were introduced
with siREV1 for 48 h, and then transfected with p21-luc, HA-SUMO3, and wild-type Myc-REV1
or K119R mutant. After additional 24 h, cells were harvested and luciferase assay was
performed as described earlier. Data are shown as average ± SD.

To assess the role of REV1 SUMOylation on p53 transactivation, MCF-7 cells were
transfected with p21-luc reporter in combination with wild-type or mutant REV1 and
SUMO3. Co-expression of wild-type REV1 relieved its inhibitory effect on p53 when
compared with SUMOylation-deficient K119R mutant (Fig. 3.6A). Moreover, SUMO
over-expression increased overall p53 activity, suggesting that as long as REV1 is
modified by SUMOylation, p53 remains highly activated under starvation conditions.

61

Figure 3.7 REV1’s effects on colony formation ability of cancer cells. (A, B) Colony-
formation assay of MCF7 cells transfected with siCTL or siREV1 under normal or starvation
conditions. MCF7 cells were transfected with control or REV1 siRNA. 24 h following siRNA
transfection, cells were incubated in normal or starvation conditions for additional 48 h, and
then split and subjected to colony-formation assay visualized by crystal violet staining (A) and
quantification (B) of colonies formed in MCF7 cells. Values are shown as average percentage
±SD.

I further tested whether REV1 is able to affect colony formation ability of
cancer cells. Knockdown of REV1 decreased the ability of MCF7 cells to form
colonies (Figs 3.7A and B). Notably, colony formation was markedly suppressed by
STS, and further reduced by knockdown of REV1. These results indicate that REV1
negatively influences clonogenicity and may mediate part of the effects of STS on
colony formation.

62

Figure 3.8 STS sensitizes cancer cells to chemotherapy in vivo. (A) Tumor progression
of allografted B16 melanoma cells treated with fasting and/or chemotherapeutic agents.
C57BL/6J mice with subcutaneously implanted B16 melanoma cells were fed Ad lib or fasted
with or without chemotherapy (DXR, 8 mg/kg, i.v.; CP, 100 mg/kg, i.p., as indicated by red
dash line). Two cycles of fasting (48 h) and/or chemotreatment were performed. Tumor
progression was presented as percentage change in tumor size. Data expressed as means
±S.E.M. (n = 5).

To further study the role of STS in sensitization of cancer cells to chemotherapy in
vivo, I employed a subcutaneous allograft model. Murine melanoma B16 cells were
injected subcutaneously and allowed to form palpable tumors, and mice bearing these
tumors were subjected to fasting cycles with chemotherapy. In agreement with our
previous findings, two fasting cycles not only retarded tumor growth and were as
effective as treatment with DXR or CP (cyclophosphamide), but also augmented the
efficacy of chemotherapy drugs (Fig. 3.8A). Notably, the greatest therapeutic effect
was observed when fasting was combined with chemotreatment.
63

Figure 3.9 Effect of fasting and chemotreatment on body weight, food intake, and tumor
volume in allografted mouse model. (A, B) Effect of fasting on body weight (A) and food
intake values (B). Body weight and food intake of tumor-bearing mice were determined
periodically, and points and bars represent the mean ±S.E.M (n = 5). (C) Tumor volumes on
day 38 were measured. Data shown are the mean +/- S.E.M. *, P < 0.05, ANOVA with Tukey’s
multiple comparison test; #, P < 0.05, t test, two tailed, compared to chemotreatment alone.
64

Figure 3.10 STS and H 2O 2 treatment disrupt REV1-p53 interaction. (A) B16 cells from
48h-starved mice were harvested, and subjected to Co-IP with anti-p53 antibody, followed by
immunoblot with anti-REV1 antibody. Whole cell lysates were immunoblotted for p53 and
REV1 as input control. (B) The cells co-transfected with Flag-p53 and Myc-REV1 expression
vectors were treated with H2O2 (200 µM) for 30 min. The whole cell lysates were subjected to
Co-IP assay.

To further investigate the molecular mechanisms underlying STS-induces
sensitization of cancer cells, I examined whether the REV1-p53 pathway might be
involved in sensitizing cancer cells in response to fasting. In allografted tumors, Co-
IP assay revealed that STS led to the disruption of REV1-p53 interaction (Fig. 3.10A).
Consistent with this in vivo data, ROS, which can be induced by STS (Fig. 3.10A),
also disrupted REV1-p53 interaction in cultured cells (Fig. 3.10B).
65

Figure 3.11 STS alone or combined with chemotherapy induces p53 phosphorylation
and acetylation in cancer cells. (A) Mice bearing B16 cells were starved for the indicated
time, and the melanoma cells were harvested for immunoblots with anti-phospho-p53 (Ser18),
anti-acetyl-p53 (Lys379) and anti-p53 antibodies. (B) Allografted B16 treated with STS and/or
chemotherapeutic agents were harvested for immunoblots with anti-phospho-p53 (Ser18),
anti-acetyl-p53 (Lys379) and anti-p53 antibodies. A tubulin blot was presented as a loading
control.

On the basis of these observations, I reasoned that fasting might cause
disruption of an inhibitory REV1 binding, and activate p53 and its downstream
effectors. I therefore examined whether fasting can activate p53 and induce the
expression of the downstream genes. Phosphorylation of endogenous p53 at Ser18
(corresponding to Ser15 of human p53) as well as acetylation at Lys379 (Lys382 of
human p53), which correlate with its activation (Xu, 2003), were increased in tumors
of mice either after starvation and/or upon chemotherapy treatment (Figs 3.11A).
Furthermore, the combination of fasting and chemotherapy exerted the strongest
effects on p53 phosphorylation and acetylation (Fig. 3.11B).
66

Figure 3.12 STS activates p53-dependent apoptotic pathway in cancer cells. (A) Total
RNA was isolated from tumors and the relative mRNA levels were analyzed by real-time PCR
for the indicated genes. Results shown are reported as average ± SD.

With such a dramatic increase in the levels of p53 post-translational
modifications, I ascertained whether fasting and/or chemotreatment could influence
p53 transactivation. Using real-time PCR, I observed that fasting up-regulated
expression of p53-dependent pro-apoptotic target genes, including Puma, Bax, and
Noxa, and chemotreatment also significantly induced their expressions (Fig. 3.12A).
More importantly, the combination of fasting and chemotherapy dramatically
increased the expression of these genes in implanted tumors, indicating that fasting
can sensitize cancer cells to chemotherapy and induce apoptosis in a p53-dependent
manner. Recent finding has previously shown that both STS and reduced IGF-1 levels
67

retard melanoma growth in mice (Lee et al., 2012a). This study indicates that these
effects are mediated in part by REV1 modification and the consequent p53 activation,
leading to cancer cell death.

68

3.3 Discussion
STS or fasting has been shown to have wide and positive effects in cancer treatment
by augmenting the efficacy of chemotherapy and in some cases by matching the
efficacy of chemotherapy, but its mechanism of action remain poorly understood
(Fontana et al., 2010; Lee et al., 2012a; Safdie et al., 2012). This study provides
evidence for a role of REV1 as a novel modulator of p53 and for REV1-p53 interaction
in STS-induced enhancement of cancer cell death. According to my model, REV1 is
capable of regulating p53 stability and activity via their physical interaction. STS
promotes REV1 SUMOylation, which contributes to its dissociation from p53,
suggesting that starvation relieves REV1-dependent repression of p53 transactivation
(Fig. 3.13). Starvation also promotes p53 modifications, such as phosphorylation and
acetylation, which correlate well with its key function. Indeed, under DNA damage
and oxidative stress, p53 and its negative regulators are post-translationally modified,
leading to p53 activation by disrupting their interaction (Vazquez et al., 2008). My
results indicate that REV1 is acting as both a scaffold and a modulator in p53 signaling
cascades in response to starvation.

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Figure 3.13 A model for the regulation of p53 by REV1 SUMOylation in response to
short-term starvation. Short-term starvation induces not only REV1 SUMOylation, which is
catalyzed by E3 SUMO ligase PIASy, but p53 transactivation via the changes in its
modification and interaction with REV1.

Nutrient depletion causes the accumulation of ROS in cancer cells, which can
lead to apoptotic cell death (Lee et al., 2012a; Raffaghello et al., 2008). ROS also
function as intracellular signaling molecules regulating multiple cellular processes.
Our data reveal that REV1 protein is SUMOylated in cancer cells in response to STS
and ROS. DXR treatment, which can induce reactive oxygen species (ROS) through
redox cycling (Lyu et al., 2007), also induced REV1 SUMOylation, but the
modification level was similar or less than that caused by STS (Fig. 3.14).

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Figure 3.14 REV1 SUMOylation upon starvation and chemotreatment. B16 cells were
incubated with starvation medium or treated with doxorubicin (1 µM) for 24 h, lysed and
immunoblotted with anti-REV1 antibody. A tubulin blot was presented as a loading control.

Moreover, we investigated the role of REV1 in normal cells in response to STS
and chemotreatment. In contrast to its effects on cancer cells, STS had protective
effects in normal cells and enhanced the resistance of primary MEFs against
chemotoxicity (Fig. 3.15). Cytotoxicity assays revealed that knockdown of Rev1 had
no significant effects on chemotherapy-induced cytotoxicity of primary MEFs. Taken
together, these data indicate that REV1 contributes to cell death selectively in cancer
cells and that REV1 may be a key mediator of STS-dependent effects on cancer cells.

71

Figure 3.15 The effect of REV1 SUMOylation in normal cells. (A) Primary MEFs were
treated with starvation medium for 24 h, lysed and immunoblotted with anti-REV1 antibody. A
tubulin blot was presented as a loading control. (B) The cytotoxicity of primary MEFs after
exposure to DXR treatments. Primary MEFs were transfected with siCTL or siRev1. 24 h
following siRNA transfection, cells were incubated in normal or starvation conditions for
additional 24 h. Cytotoxicity were analyzed 24 h treatment of 10 µM DXR. Data was plotted
as the percentage of siCTL-transfected cells treated with DXR. Results represent mean ±SD
from three independent experiments.

These results are consistent with our Differential Stress Resistance (DSR)
hypothesis proposing that fasting protects normal but not cancer cells from
chemotherapy and the Differential Stress Sensitization (DSS) hypothesis suggesting
that fasting will sensitize cancer cells by generating a complex and hostile environment
to which only normal cells can adapt (Cheng et al., 2014; Lee et al., 2012a; Lee et al.,
2012b; Raffaghello et al., 2008).
72

In recent years, SUMO modification has been shown to play prominent roles
in controlling the function of a large number of proteins involved in signal
transduction, genome maintenance and DNA repair (Polo and Jackson, 2011).
Previous studies have shown that REV1 is modified by phosphorylation in yeast and
by ubiquitination in mammalian cells (Guo et al., 2006b; Sabbioneda et al., 2007), but
its SUMOylation had not been described. Thus, the related studies of possible cross-
talk between SUMOylation and other modifications have the potential to provide
important insights into the mechanism regulating REV1 function. In addition,
SUMOylation at K119 contributes to REV1 stability, although other putative
SUMOylation sites in REV1 may be also important. In light of the fact that K119 is in
the REV1 N-terminal domain, required for p53 interaction, and that PIASy is also
required for p53 modification (Bischof et al., 2006), the precise interaction among
REV1, PIASy, and p53 requires further investigation.
p53 has been previously proposed to regulate error-prone DNA repair process
(Avkin et al., 2006), but the precise mechanism by which these pathways are linked
remains largely unknown. Our data indicate that the N terminus of REV1, which
contains the BRCT domain, is sufficient for p53 interaction and to control p53 activity.
The BRCT domain is involved in regulating DNA TLS (Jansen et al., 2005). REV1
interacts with PCNA and the B family TLS polymerase Polζ via accessory subunit
REV7 (Fig. 3.16) (Guo et al., 2003; Guo et al., 2006a). However, ROS and its induced
REV1 SUMOylation did not affect REV1 interaction with PCNA or REV7 (Fig. 3.16).
73

Figure 3.16 REV1 associates with PCNA and REV7, an accessory subunit of Polζ. (A)
Myc-REV1 was transiently expressed in HEK293 cells, and cell lysates were
immunoprecipitated with anti-Myc antibody, and the immune complex were analyzed by
immunoblotting with anti-Myc and anti-PCNA antibodies. Whole cell lysates were
immunoblotted for PCNA as input control. (B) Mouse REV7 tagged with HA epitope was
expressed in HEK293 cells and immunoblot analysis using anti-HA antibody confirmed the
expression of HA-REV7 construct. (C) Cells were co-transfected with Myc-REV1 and HA-
REV7, and cell lysates were immunoprecipitated with anti-Myc antibody, followed by Western
blot with anti-Myc and anti-HA antibodies. (D, E) Cells transiently transfected with Myc-REV1
and/or HA-REV7 were treated with H2O2 (200 µM) for the indicated time and
immunoprecipitated with anti-Myc antibody. The immune complex were analyzed by
immunoblotting with anti-Myc, anti-PCNA, and anti-HA antibodies.
74

How modification of REV1 releases p53 is unclear. Modification of the
internal lysine may simply lead to masking of existing binding site or a conformational
change in the REV1 structure, interfering with its interaction with p53. Indeed, Lys119
of REV1 SUMOyaltion site is located in the BRCT domain which has been identified
as an important node in p53 binding (Fig. 3.1). It is also possible that the post-
translational modification either reduces p53 affinity for REV1 or disrupts p53
oligemerization, resulting in dissociation of this complex.
In conclusion, this study provides evidence for a role of REV1 and its
SUMOylation in modulating p53-dependent cancer cell death in response to starvation
conditions and the consequent increase in oxidative stress. The combination of
starvation with other treatments has promising therapeutic potential as an intervention
to promote differential REV1 and p53 regulation in normal and cancer cells,
contributing to their protection and death, respectively.

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3.4 Experimental Procedures
Cell culture and transfection
MCF7 human breast carcinoma cells, B16 mouse melanoma cells, human embryonic
kidney (HEK) 293 cells, and p53-null mouse embryonic fibroblasts (MEFs) were
maintained in Dulbecco’s modified Eagle’s medium (DMEM) with 10% fetal bovine
serum (FBS) and 100 units/mL penicillin plus 100 µg/mL streptomycin (Invitrogen).
p53-null MEFs were obtained from Dr. Shengkan Jin at University of Medicine and
Dentistry of New Jersey. Non-small cell lung cancer H1299 cells were obtained from
Dr. Deborah Johnson at University of Southern California and cultured in RPMI-1640
medium with 10% FBS. Cells were all maintained in a humidified incubator at 37°C
under 5% CO2. Transient transfection was carried out using the X-tremeGENE HP
Transfection Reagent (Roche Applied Science) according to the manufacturer’s
instructions. For RNAi experiments, SMART Pool siRNAs (Dharmacon) against
mouse or human REV1 (M-041898-01 and M-008234-01) or non-targeting siRNA (D-
001210-01) were transfected into the cells using Lipofectamine RNAiMAX reagent
(Invitrogen), according to the manufacturer’s protocols.
Plasmid expressing Myc-REV1 (Guo et al., 2003) was gifted from Dr. Errol C.
Friedberg (University of Texas Southwestern Medical Center, USA). Expression
vectors for Flag-p53 (Gjoerup et al., 2001) (10838), HA-SUMO2 (Kamitani et al.,
1998) (17360), HA-SUMO3 (Kamitani et al., 1998) (17361), Flag-PIASy (Liu et al.,
2001) (15208), pG13-luc (el-Deiry et al., 1993) (16442) and p21/WAF1-luc (Dumstorf
76

et al., 2009) (16451) have been described previously and were obtained from Addgene.
The full length cDNA of REV7 was cloned into pcDNA3-HA (Invitrogen) using
standard techniques. A series of deletion constructs of Myc-REV1 were generated by
ExoIII-S1 nuclease digestion (Promega). Mutations of lysine residues to arginine were
generated by PCR-based site-directed mutagenesis using the Quik Change II XL Site-
Directed Mutagenesis Kit (Stratagene). All mutants were verified by DNA sequencing.

LDH cytotoxicity assay
At 24 h following siRNA introduction, MCF7 cells were incubated in normal or
starvation media for additional 24 h. Chemotherapeutic agent was treated the
following day and cell cytotoxicity was measured 24 h later by LDH release assay
(Promega).

Luciferase assays
Cells were transfected with the reporter plasmids with the indicated expression
constructs using X-tremeGENE HP Transfection Reagent following the protocol
provided by Roche Applied Science. At the indicated time, cells were harvested and
assayed for luciferase activity using the dual-luciferase reporter assay system
according to the manufacturer’s instructions (Promega).
77

Immunoprecipitation and immunoblot analysis
Immunoprecipitation and immunoblot analyses were performed as previously
described (Shim et al., 2007), with minor modifications. For co-immunoprecipitation
assay, mouse tissues or cells were lysed on ice in a modified RIPA buffer containing
50 mM HEPES at pH 7.4, 150 mM NaCl, 1% NP 40, 1 mM EDTA, 1X phosphatase
and phosphatase inhibitor cocktail (Pierce), and the whole lysates were clarified by
centrifugation. The supernatants were incubated overnight at 4°C with 2 µg of
indicated antibody; and the protein A/G plus agarose beads (Pierce) were then added
and incubated for an additional hour at 4°C. Co-immunoprecipitation of transfected
Flag-p53 and Myc-REV1 was carried out using anti-Flag M2 affinity gel (Sigma) and
anti-c-Myc-agarose beads (Pierce) according to manufacturers’ instructions in order
to minimize interference by IgG heavy chain with p53. Immunoprecipitates were
recovered with SDS sample buffer and subjected to Western blot analysis.
Antibodies against Myc (9E10; Santa Cruz Biotechnology), Flag (M2; Sigma-
Aldrich), HA (F-7; Santa Cruz Biotechnology), REV1 (H-300; Santa Cruz
Biotechnology), p53 (FL-393; Santa Cruz Biotechnology), phospho-p53 (Ser18, Cell
Signaling Technology), acetyl-p53 (Lys379, Cell Signaling Technology), PCNA
(NCL-PCNA; Novocastra Laboratories) and Tubulin (Cell Signaling Technology)
were obtained from commercial sources.
78

RNA isolation and quantitative RT-PCR
Total RNA was isolated using TRI Reagent (Invitrogen), reverse-transcribed with M-
MLV Reverse Transcriptase (Promega), and amplified with SYBR Green PCR maser
mix (Invitrogen) according to the manufacturer’s recommendation. The following
PCR primers were used: human BAX forward 5'- TTT TGC TTC AGG GTT TCA TC
-3', BAX reverse 5'- CAG TTG AAG TTG CCG TCA GA -3', human NOXA forward
5'- AGA GCT GGA AGT CGA GTG T -3', NOXA reverse 5'- GCA CCT TCA CAT
TCC TCT C -3', human PUMA forward 5'- TCA ACG CAC AGT ACG AGC G -3',
PUMA reverse 5'- TGG GTA AGG GCA GGA GTC C -3', human KILLER/DR5
forward 5'- TGC AGC CGT AGT CTT GAT TG -3', KILLER/DR5 reverse 5'- TCC
TGG ACT TCC ATT TCC TG -3', human TIGAR forward 5'- TCC AAG CAA CTG
TCT GGA AA -3', TIGAR reverse 5'- ATC TGC TCA GAG TGG CTG GT -3', human
SESTRIN2 forward 5'- TCA AGG ACT ACC TGC GGT TC -3', SESTRIN2 reverse
5'- GTT GTC TAC TCG CCC AGA GG -3', mouse Puma forward 5'- GCC CAG CAG
CAC TTA GAG TC -3', Puma reverse 5'- TGT CGA TGC TGC TCT TCT TG -3',
mouse Noxa forward 5'- GGC AGA GCT ACC ACC TGA GT -3', Noxa reverse 5'-
TTG AGC ACA CTC GTC CTT CA -3', mouse Bax forward 5'- TGG AGA TGA ACT
GGA CAG CA -3', Bax reverse 5'- GAT CAG CTC GGG CAC TTT AG -3', and β-
ACTIN forward 5'- GGA CTT CGA GCA AGA GAT GG -3', β-ACTIN reverse 5'-
79

AGC ACT GTG TTG GCG TAC AG -3'. The expression levels were normalized with
β-ACTIN mRNA in each sample.

Starvation treatment
Short-term starvation (STS) in a cell culture model was performed by glucose and
serum restriction. The culture media were supplemented with 0.5 g/L or 2.0 g/L
glucose to match blood glucose levels in starved and normally fed mice, respectively
(Lee et al., 2012a). FBS was supplemented at 1% for starvation conditions as
compared to the normal 10%. For STS in vivo, mice were fasted for 24-48 h by
complete deprivation of food, but with free access to water.

Mouse allografts
Twelve-week-old female C57BL/6J mice were purchased from The Jackson
Laboratory (Bar Harbor, Maine). 2×10
5
B16 cells suspended in PBS were injected
subcutaneously in the right flank of mice. Implanted melanoma cells were allowed to
form palpable tumors, and mice bearing these tumors were subjected to fasting for 48
h with chemotreatment (Lee et al., 2012a). Two cycles of fasting and chemotreatment
were performed, and body weights and tumor size were measured periodically. All of
the experiments were approved by University of Southern California’s Institutional
Animal Care and Use Committee before the experiments were started.
80

Clonogenic colony assay
MCF7 cells were transfected with either siCTL or siREV1 RNAi. The next day, cells
were incubated in normal or starvation medium. After 48 h, cells were split and seeded
at equal densities in triplicate into 6-well plates (Franken et al., 2006). After 10-14
days, colonies were fixed and stained using a crystal violet solution, and visible
colonies were counted.

81

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Chapter 4
Short-term starvation induces
cardioprotection via AMPK/PKA-
EGR1 pathway.

4.1 Introduction
Doxorubicin is a widely used anticancer chemotherapy drug and given to treat
a variety of cancer types, including bladder, breast, leukemia, lung, liver and ovarian
cancer (Gabizon et al., 2003). A doxorubicin-based combination with other
medications is commonly used in the first-line chemotherapy regimens in the
treatment of breast cancer. Like many other chemotherapy drugs, however, the side
effects limit their clinical uses. It is well recognized that doxorubicin is also able to
cause serious problems in heart (Zhang et al., 2012). The most common side-effects
of doxorubicin is dose-dependent cardiotoxicity. High doses of doxorubicin may injure
86

heart muscle and develop cardiac dysfuction and eventually can cause congestive heart
failure of patients either during or after treatment.
A restriction of dietary or calorie intake is among the most effective
interventions to protect organisms and to improve both lifespan and healthspan
(Fontana et al., 2010). Short-term dietary restriction or starvation is also shown to be
an effective and a non-toxic intervention to enhance chemotherapy treatment efficacy
with the reduction of common chemo-toxic side effects in mice and humans. A
differential stress resistance (DSR) hypothesis proposes that fasting or starvation
protects normal tissues but not cancer cells from chemotherapy (Lee et al., 2012b;
Raffaghello et al., 2008). Dietary restriction decreases the activity of nutrient-sensing
signalings, such as growth hormone (GH) and insulin/IGF-1 (insulin-like growth
factor 1) signaling (IIS) pathways, which play critical roles not only in the control of
aging process and longevity but also of cellular protection systems of diverse
organisms. A multimodality approach with genetic and chemical manipulation has
revealed that targeted disruption of GH and/or IIS pathways enhances cellular
protection against diverse cytotoxic stresses and extends lifespan in yeast, worms, flies
and rodents. For instance, high nutritional intakes are associated with an increase of
IGF-1 levels and its downstream mediators of the Ras-PKA and TOR (target of
rapamycin) pathways in mice. Although the effects of GH on longevity is still
controversial (Bartke, 2005; Berryman et al., 2008), deficiency in IIS is strongly
implicated in lifespan extension in most organisms. In yeast, glucose activates RAS-
PKA pathway and in turn induces pro-aging pathways (Fontana et al., 2010). Glucose
87

restriction is also shown to increase cellular protection against thermal and oxidative
stress and to slow aging process and extend lifespan (Wei et al., 2008; Wei et al., 2009).
Although glucose restriction can induce DSR in mice (Raffaghello et al., 2008), the
connection between GH/IIS signaling cascade and longevity is much more
complicated. The orthologs of key mediators of the yeast GH/IIS signalings need to
be addressed in vertebrates.
Adenosine monophosphate (AMP)-activated protein kinase (AMPK) is the key
energy sensor that regulates energy homeostasis in most eukaryotic cells (De Haes et
al., 2014; Hardie, 2014). AMPK senses cellular energy status by monitoring the
metabolic changes, such as AMP:ATP and ADP:ATP ratios, and have acute and long-
term effects on central metabolic pathways as well as important cellular functions. The
mammalian AMPK is activated by various metabolic stresses, such as ischemia,
hypoxia or hypoglycemia. AMPK and its orthologs are found in the genomes of almost
all eukaryotes and also required for regulating cellular energy response to maintain
energy homeostasis. The complex of Snf1, a yeast ortholog of mammalian AMPK, is
activated by the starvation response and required for growth in this condition.
Although Snf1 is repressed in high glucose concentrations, growth slows and Snf1 is
derepressed when glucose runs out (Hardie, 2014; Hardie et al., 1998). Under
starvation condition, a functional Snf1 complex is required for the derepression of
genes for metabolism of other carbon sources and for the activation of more energy-
efficient pathways to generate ATP efficiently. In C. elegans, AMPK is also required
88

for lifespan extension in response to dietary restriction (Apfeld et al., 2004; Greer and
Brunet, 2009).
Metformin is the front-line treatment of antidiabetic therapy and currently
prescribed to a majority of patients with type 2 diabetes worldwide (Zhou et al., 2001).
It lowers blood glucose and lipid contents by reducing hepatic glucose production and
increasing glucose utilization in skeletal muscles. AMPK is activated by clinical drugs
and natural plant products, and metformin is also a well-known AMPK activator.
Although it activates AMPK indirectly, AMPK pathway is thought to be responsible
for its therapeutic benefits, including lower cancer incidence and mortality, anti-
inflammatory and cardioprotective effects (Apaijai et al., 2012; Hirsch et al., 2013;
Zakikhani et al., 2006). It is also associated with the extension of healthspan and
lifespan in mice (Martin-Montalvo et al., 2013).
Early growth response protein 1 (EGR1) is a key transcription factor involved
in diverse cellular processes, such as development, proliferation, DNA repair and
apoptosis (Sukhatme et al., 1988; Yu et al., 2009). EGR1 containing zinc finger motifs
in the C-terminal region binds to specific GC-rich consensus sequence and activates
transcription of various target genes (Cao et al., 1993). It also has tumor suppressor
activity which can directly regulate multiple tumor suppressors including p53, PTEN,
TGFβ1 and fibronection (Baron et al., 2006; Yu et al., 2009). Indeed, EGR1 is down-
regulated in many tumor cell lines and its re-introduction suppresses transformation
and tumorigenicity. Our previous studies have identified that yeast Msn2/4, which is
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highly homologous to EGR1 zinc finger region (Estruch and Carlson, 1993; Josefsen
et al., 1999), is a stress response transcription factor and mediates CR-dependent stress
resistance and life span extension (Wei et al., 2008; Wei et al., 2009). Msn2/4
positively regulates genes involved in cellular protection and deletion of this gene
causes a major reversion of the beneficial effects of calorie restriction on lifespan
extension in yeast. However, the role of mammalian EGR1 in stress resistance and
lifespan related to calorie restriction has not been identified.
In this chapter, I show that EGR1 is important for the protective mechanism of
doxorubicin-induced heart damage in response to short-term starvation. STS has a
protective effect on doxorubicin-induced cardiotoxicity, and EGR1 mediates its
regulatory mechanism. STS as well as glucose starvation induce EGR1 expression in
cardiomyocytes through the activation of AMPK and the inhibition of PKA pathways.
Starvation-induced EGR1 transactivates antioxidant and FOXO downstream genes
and subsequently protects cardiomyocytes from doxorubicin treatment. Metformin, a
widely used AMPK activator, also mimics the benefits of STS in heart tissues, such as
inducing AMPK and reducing PKA pathways and improving stress resistance in
EGR1-dependent manner. These data provide EGR1 as an important signaling node
linking glucose nutrient sensing and metabolic control in response to STS.

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4.2 Results
Glucose starvation induces Egr1 expression through AMPK pathway in
cardiomyocytes.
Short-term starvation promotes cellular and organismal protection from the harmful
side effects of a variety of chemotherapy drugs (Lee et al., 2012a; Longo and Mattson,
2014; Raffaghello et al., 2008). To investigate whether STS can reduce cardiotoxic
side effects of doxorubicin treatment, I employed the primary culture of
cardiomyocytes. STS significantly reduced doxorubicin-induced cardiotoxicity (Fig.
4.1A). Stress resistance transcription factors are required for the major protective
effects by calorie restriction, such as stress resistance and lifespan extension. In yeast,
Msn2/4 genes, which is highly homologous to mammalian Egr1 zinc finger motifs,
mediate CR-mediated cellular protection systems and lifespan extension (Fontana et
al., 2010; Wei et al., 2008; Wei et al., 2009). Thus, I evaluated whether mammalian
Egr1 can sense nutrient availability and mediate corresponding effects on stress
resistance. To gain the insight the relationship between Egr1 and starvation, I measured
its expression levels in response to glucose restriction. I observed that EGR1 was
rapidly induced by glucose starvation in cardiomyocytes (Fig. 4.1B). However, serum
deprivation did not exhibit any obvious effect (Fig. 4.1C).

91

Figure 4.1 Glucose restriction induces Egr1 expression in primary cardiomyocytes. (A)
STS’s effect on doxorubicin-induced cardiotoxicity in primary rat cardiomyocytes. Primary rat
cardiomyocytes were incubated with STS or normal medium for 24 h, and then treated with
DXR (1 µM) for additional 24 h. Cytotoxicity were measured after by LDH release to assess
cell viability. (B) GR induces EGR1 expression. Primary rat cardiomyocytes were incubated
with GR medium for the indicated time, lysed, and immunoblotted with anti-EGR1 antibody. A
tubulin blot was presented as a loading control. (C) Cells were treated with serum-free medium
for 1 h, and immunoblotted with anti-EGR1 antibody.

92

Figure 4.2 The induction of EGR1 via AMPK activation in cardiomyocytes. (A, B) Cells
were pre-treated with or without compound C (20 µM) and then incubated with GR or normal
medium. Whole cell extracts were prepared and analyzed by Western blot analysis with anti-
EGR1 antibody (A) and by qRT-PCR (B). (C) Protection of cardiomyocytes by overexpression
of Egr1. H9c2 cardiomyocytes transfected Flag-Egr1 expression vector were treated with DXR
(1 µM) for 24 h. Cytotoxicity were measured by LDH release. The results present the mean
value ± SEM.

93

Figure 4.3 A model of the regulation of longevity pathways in yeast. (A) Nutrient-sensing
pathways controlled by Sch9, Tor and Ras/PKA converge on the downstream protein kinase
Rim15. Transcription factors Msn2/4 and Gis1 through transactivation of stress response
genes enhance cellular protection, leading to life span extension.

AMPK is a crucial cellular energy sensor in most eukaryotic cells (Hardie et
al., 2012). AMPK can be activated by starvation and exert an important role in the
cellular protection in response to nutrient starvation (Kroemer et al., 2010; Shaw et al.,
2004). To test the possibility that starvation-induced EGR1 is through AMPK pathway,
I co-treated cardiomyocytes with the AMPK-specific inhibitor compound C (C.C.).
EGR1 induction was completely abolished by C.C. treatment (Fig. 4.2A). mRNAs are
similarly regulated (Fig. 4.2B), indicating the transcriptional regulation contributing
94

to EGR1 induction in response to glucose restriction via AMPK activation in
cardiomyocytes. Furthermore, over-expression of Egr1 protected cardiomyocytes
from doxorubicin cytotoxicity (Fig. 4.2C). These findings are consistent with our
previous studies that yeast Msn2/4 controls cellular protection mechanisms and
mediates CR-mediate stress resistance (Fig. 4.3A).

PKA pathway modulates Egr1 expression and its protective effects.
Prolonged fasting or starvation reduces PKA signaling and the consequent reduction
of PKA activity enhances the protective effects of starvation, such as lifespan and
resistance, in yeast and mice (Cheng et al., 2014; Fontana et al., 2010; Wei et al., 2008).
Further experiments were performed to determine if PKA is involved in starvation-
mediated EGR1 induction. Similar to glucose restriction, the inhibition of PKA
activity with the selective PKA inhibitors, H-89 and PKI 14-22 amide (PKI), is
sufficient to induce the expression of Egr1 gene in primary cardiomyocytes (Fig.
4.4A). I next investigated the effects of PKA in regulating cardiomyocytes and used
short-interfering RNA (siRNA) against Pkaα (also called Prkaca), the main catalytic
subunit of PKA (Almeida et al., 2011). siRNA-based depletion of endogenous PKA
activity dramatically reduced the cytotoxic effects of doxorubicin in cardiomyocytes
(Fig. 4.4B) and its combination with starvation further abolished the doxorubicin
cytotoxicity, indicating that the inhibition of PKA is involved in starvation-induced
cardioprotective mechanism.
95

Figure 4.4 PKA inhibition triggers Egr1 expression and protective effects in
cardiomyocytes. (A) Primary rat cardiomyocytes were treated with PKA inhibitors, H89 or
PKI (myristoylated PKA inhibitor 14-22 amide) for 1 h. Total RNA was isolated and the relative
mRNA expression level of Egr1 was measured. (B) H9c2 cardiomyocytes were transfected
with siCTL or siPKA at day 1. Cells were treated with GR or normal medium at day 2 and then
DXR (1 µM) at day 3. Cytotoxicity were measured to assess cell viability.

To understand the molecular mechanisms underlying EGR1 action and how
EGR1 and PKA regulate starvation response, I examined the effects of GR and PKA
inhibition in response to starvation using wild-type and Egr1-null MEFs. The
genotypes of MEF cells were assessed by Western blot. Wild-type MEFs expressed
EGR1 proteins and its levels were rapidly induced by GR treatment, but Egr1
-/-
MEFs
did not (Fig. 4.5A).

96

Figure 4.5 Confirmation of Egr1-knockout cells by Western blot. (A) The parental Egr1
+/+

and Egr1
-/-
MEFs were treated with GR media for 1 h. The expression level of EGR1 protein
was measured by Western blot.

I employed the reporter constructs EGR1-SEAP and EGR1-dependent gene
transcription was evaluated using a reporter gene expression assay. To examine the
effect of glucose restriction on EGR1 activity, I transfected EGR1-SEAP into wild-
type and Egr1-null MEFs and treated the cells with glucose-restricted medium.
Glucose restriction led to the induction and accumulation of EGR1-dependent SEAP
expression over the time period to 48 h (Fig. 4.6A). Similarly, the inhibition of PKA
using H-89 also increased EGR1 activity (Fig. 4.6B). However, PKA inhibition was
about 5 times less potent than GR, suggesting that GR can enhance EGR1-dependent
transcription activity possibly in part through PKA inhibition.

97

Figure 4.6 GR- and inhibited PKA-mediated EGR1 activation. (A, B) Egr1
+/+
and Egr1
-/-

MEFs transiently transfected with EGR1-SEAP reporter were incubated with GR (A) or H89
(B). SEAP activity was measured and quantitated by using a chemiluminescent assay.

Starvation and fasting enhance cellular protection against oxygen radical
challenge and reduce oxidative damage to cellular macromolecules (Longo and
Mattson, 2014). Previous studies have reported that the antioxidant enzymes are
required for stress resistance and longevity extension in yeast (Fabrizio et al., 2003;
Fontana et al., 2010). The manganese superoxide dismutase (MnSOD) has been shown
to have EGR1 binding sites in its 5´ promoter region (Porntadavity et al., 2001). I
hypothesized that EGR1 may control the regulation of MnSOD gene in glucose-
restricted conditions. To examine if MnSOD expression is involved in response to
glucose restriction, I transfected wild-type and Egr1
-/-
MEFs with MnSOD-luc reporter
construct.
98

Figure 4.7 The regulation of MnSOD and FOXO responsive genes in Egr1-dependent
manner. (A-C) Cells were transfected with MnSOD-luc (A), MnSOD-mt-luc (B), or FHRE-luc
(C), and treated with GR medium. Luciferase activity was carried out 18 h after treatment.

Luciferase gene expression was effectively increased in response to glucose
restriction, however its expression was significantly reduced in both basal and glucose
restriction-induced levels of luciferase activities in Egr1
-/-
MEFs (Fig. 4.7A). The
Forkhead transcription factor (FOXO) was also shown to bind MnSOD promoter and
regulate its expression (Kops et al., 2002), however, transfection of MnSOD-mt-luc
with a mutation in two FOXO-binding sites (DBE) in MnSOD promoter did not show
the reduced luciferase activity (Fig. 4.7B).
99

Figure 4.8 Egr1 regulates energy metabolism. (A-C) OCR to ECAR ratios (A), ATP
production (B), and proton leak (C) measured by the XF96 extracellular flux analyzer is shown.
Values reported are mean ± SEM.

These indicate that expression of MnSOD is transcriptionally up-regulated in response
to glucose restriction through EGR1 activity. In addition, glucose restriction also
significantly increased the expression of the Forkhead responsive element (FHRE)-luc
reporter gene containing three copies of FHRE in wide-type MEFs, but its effect on
luciferase expression was much weaker in Egr1
-/-
cells (Fig. 4.7C), supporting that
glucose restriction can also activate other signal transduction arms downstream of
FOXO via EGR1.
100

Glucose restriction and AMPK has been shown to modulate mitochondrial
metabolism (Fulco et al., 2008; Schulz et al., 2007). To identify whether EGR1 can
regulate mitochondrial metabolic activity, I measured basal mitochondrial oxygen
consumption rate (OCR; as a measure of mitochondrial respiration), extracellular
acidification rate (ECAR; as a measure of glycolysis) and cellular APT levels. The
parental Egr1
+/+
MEFs showed elevated basal OCR/ECAR ratio when compared to
Egr1
-/-
cells (Fig. 4.8A). This would indicate that EGR1 is preferentially involved in
the regulation of mitochondrial respiration. Although there was no significant change
in the amount of ATP production (Fig. 4.8B), Egr1
+/+
cells had higher proton leak
across the mitochondrial inner membrane (Fig. 4.8C), suggesting that EGR1 is
required to induce proton leak (the level of non-ATP-linked oxygen consumption) to
control mitochondrial ROS production. These data indicate that EGR1 may contribute
to regulate both OCR and proton leak without decreasing mitochondrial efficiency.
These also suggest that the increased OCR and proton leak in the Egr1-proficient cells
can be sufficient to lower the intracellular oxygen concentration and substantially
protect against cellular damage and cytotoxicity from reactive oxygen species relative
to that in the Egr1-deficient cells.

101

Figure 4.9 FMD induces Egr1 expression in the hearts. (A, B) The heart tissue from FMD-
treated mice were collected and the level of Egr1 expression was measured by Western blot
(A) and qRT-PCR (B).

Fasting-mimicking diet induces EGR1 and antioxidant gene expression in hearts.
Not only fasting cycles, but also alternative fasting-mimicking regimes have been
shown to be as effective as the fasting regimens and to have beneficial effects on aging
and cancer treatments by lowering glucose and IGF1 levels (Longo and Mattson,
2014). Because EGR1 and SODs have been found to respond to glucose restriction
(Figs 4.2 and 4.7), I examined the effects of fasting-mimicking diet (FMD) in the
expression of Egr1 and antioxidants in the heart. I found that EGR1 is highly expressed
at RNA and protein levels in FMD-treated heart (Fig. 4.9).

102

Figure 4.10 FMD promotes the expression of antioxidant genes in the hearts. (A-E) Total
RNA was isolated from the heart of FMD-treated mice and the relative mRNA levels were
analyzed by real-time PCR for the indicated genes. The results present the mean value ±
SEM.

FMD diet resulted in a strongly increased expression of anti-oxidant enzymes,
CuZnSOD, MnSOD and catalase (Figs 4.10A-C). It also induced the expression of
FOXO1 and FOXO3 which are the key regulators of stress resistance and adaptive
metabolic responses (Figs 4.10D and E).

103

Figure 4.11 Metformin and its analog phenformin treatment induce Egr1 expression in
primary cardiomyocytes. (A) Primary rat cardiomyocytes were treated with metformin or
phenformin and the expression levels of EGR1 were analyzed by Western blot with anti-EGR1
antibody.

Metformin is the front-line drug for the treatment of type 2 diabetes which has
the robust glucose-lowering effect by glucose contents by reducing glucose production
in liver and increasing glucose utilization in skeletal muscles (Zhou et al., 2001). It has
also been shown to activate AMPK in intact cells and in vivo, and the activation of
AMPK is required for the metformin-mediated beneficial effects (Onken and Driscoll,
2010). I sought to determine whether metformin may contribute to regulate EGR1
expression and activation via AMPK activation. Treatment of AMPK activators,
metformin and its analog phenformin, induced EGR1 expression in primary
cardiomyocytes (Fig. 4.11A).
104

Figure 4.12 Body weight and blood glucose level of metformin-treated mice. (A-C) Effect
of metformin treatment on body weight (A, B) and blood glucose levels (C). Body weight of
mice were determined periodically, and blood glucose levels are measured right after
metformin treatment.

105

Figure 4.13 Metformin-induced stress resistance in vivo. (A) C57BL6 mice were injected
(i.p.) with metformin (50 mg/kg) for 2 weeks prior to DXR injection (i.v.). Survival was followed
for 25 days, after which the remaining mice were considered survivors. (B) Total RNA was
isolated from heart tissues from metformin-treated mice and the relative mRNA levels were
analyzed by real-time PCR for the indicated genes.

EGR1 mediates GR/metformin-induced stress resistance in vivo.
The finding that GR induced not only expression of Egr1 but also that of antioxidant
genes in Egr1-dependent manner led us consider the possibility that Egr1 could
modulate stress resistance to chemotherapy. I further examined EGR1’s effects on
stress resistance in vivo. Treatment of mice with metformin (50 mg/kg/day for 2 weeks,
106

i.p.) significantly reduced blood glucose levels without weight loss (Fig. 4.12) and
improved stress resistance to doxorubicin (Fig. 4.13A). Metformin treatment also
induced the expression of Egr1 and antioxidant genes in the hearts (Fig. 4.13B).
Metformin as well as nutrient restriction were shown to disrupt PKA activity
and induce AMPK pathway (Fontana et al., 2010; Pernicova and Korbonits, 2014). To
explore the interplay between these signaling pathways in stress resistance, I examined
the combined effect of AMPK activation and PKA inhibition on doxorubicin
cardiotoxicity. Metformin potently protected cardiomyocytes from DXR toxicity (Fig.
4.14A). In addition, the combined treatment of metformin and PKA knockdown
resulted in more effective protection against doxorubicin-induced cardiotoxicity.
To further investigate the role of EGR1 in GR/Met-induced cardioprotective
mechanism, I measured DXR-induced cardiotoxicity in cardiomyocytes following
Egr1 knockdown in combination with STS or metformin. Egr1 knockdown led to
increased cell death of cardiomyocytes in response to DXR treatment (Fig. 4.14B).
Consistent with previous observation, treatment of STS and metformin reversed the
cytotoxic effect of DXR. This suggests that EGR1 enhances cardiac protection
following DXR treatment through activation of AMPK and inhibition of PKA.

107

Figure 4.14 AMPK activator metformin has protective effects in DXR-induced toxicity
through Egr1. (A) H9c2 cells were transfected with siCTL or siPKA at day 1. Cells were
treated with metformin (20 mM) at day 2 and then DXR (1 µM) at day 3. Cytotoxicity were
measured to assess cell viability. (B) Primary rat cardiomyocytes transfected with siCTL or
siEgr1 were incubated with STS or metformin, then treated with DXR. At 24 h after DXR
treatment, cell viability was measured by LDH release.

108

4.3 Discussion
Chemotherapy has long been a cornerstone of cancer therapy and a major treatment
for a wide range of malignancies over the past half-century (Conklin, 2000).
Doxorubicin is generally considered as the most effective agent in human breast, lung,
thyroid and ovarian carcinomas (Lee et al., 2010; Vasey et al., 1999), but its therapeutic
applications have been restricted by its dose-limiting side effects, such as cardiac
toxicity. The results of this study indicate that EGR1 can contribute to starvation-
mediated protective mechanism against doxorubicin-induced cardiotoxicity.
According to my model, glucose restriction and metformin not only activate AMPK
but inhibit PKA pathways, resulting in Egr1 induction and Egr1-mediated
cardioprotection through the expression of antioxidant and stress resistance genes (Fig.
4.15). My data suggested the existence of a defined pathway that boost cardiac injury
protection from chemotherapy in response to low nutrients. AMPK, PKA, and Egr1
are the molecular components of this signaling cascade. RNA interference and
pharmacological inhibition of the single component allow cardiac cells highly
sensitive to doxorubicin treatment.

109

Figure 4.15 A model for the starvation/metformin-mediated AMPK/PKA-EGR1
pathways. Glucose restriction and metformin activate AMPK and inhibit PKA pathways,
converging on EGR1 induction. Transcription factors Egr1 transactivates the expression of
antioxidant and stress response genes and enhance cellular protection.

The detailed molecular mechanism of AMPK- and PKA-mediated regulations
of Egr1 and its downstream genes also remain to be clarified. AMPK and PKA may
directly regulate the expression of Egr1 and its regulatory genes. In response to
metabolic stress, AMPK can translocate to chromatin, trigger the modification of
histone H2B, and eventually contribute to the chromatin remodeling (Lu and
Thompson, 2012). AMPK can also activate stress-induced transcription via its histone
modification. The extracellular signal-regulated kinase/mitogen-activated protein
kinase (ERK/MAPK), the key critical effector kinases downstream of PKA, are also
required for chromatin remodeling and regulation of gene expression (Chwang et al.,
110

2007). Multiple histone modifications can be integrated together and drive gene
expression by altering the structure of chromatin structure or by recruiting signaling
complexes. Therefore, understanding the molecular connection between
starvation/metformin treatment and epigenetic modifications of chromatin will
provide insights for gaining a deeper comprehension on the control of several signaling
pathways upon nutrient restriction.
In this study, metformin activates Egr1 induction and its beneficial effects in
cardiac protection and stress resistance. Metformin has been shown to preserve the
cardiac functions through AMPK activation (Xie et al., 2011). However, the molecular
mechanisms by which AMPK and metformin regulate cardiac functions are poorly
understood. My results provide evidence that metformin induces Egr1 accumulation
and consequent expression of antioxidant and stress resistance genes via AMPK
activation, resulting in the reduction of stress-induced cardiac damage.
Taken together, my findings demonstrate that the reduced nutrient availability
and the hypoglycemic agent metformin may activate AMPK/PKA-Egr1 pathway and
subsequently prevent doxorubicin-induced cardiac toxicity. I conclude that Egr1 plays
a significant role in the mechanism of cardiac protection as a nutrient sensor and
mediator downstream of PKA and AMPK signaling. The combination of starvation or
metformin treatment with other treatments has promising therapeutic potentials as an
intervention to enhance the efficacy and safety of chemotherapy.

111

4.4 Experimental Procedures
Starvation, fasting, and FMD treatment
For STS in vivo, mice were fasted for 24 to 72 h by complete deprivation of food, but
with free access to water. In order to avoid dehydration, the mice were fed a low caloric
hydrogel which encouraged water consumption, and body weight was measured
immediately before, during and after fasting. For a cell culture model, STS was
performed by glucose and serum restriction. The culture media were supplemented
with 0.5 g/L or 2.0 g/L glucose to match blood glucose levels in starved and normally
fed mice, respectively (Lee et al., 2012a). FBS was supplemented at 1% for starvation
conditions as compared to the normal 10%. In FMD condition, mice were provided by
less than 50% of the normal calorie intake for 4 days bi-monthly, followed by
60~100% of the normal caloric intake.

Cell culture and transfection
Primary rat cardiomyocytes was isolated from day 1~3 neonatal rat hearts using
primary cardiomyocyte isolation kit (Pierce), according to the manufacturer’s
protocols. H9c2 rat cardiomyoblasts derived from embryonic rat heart was purchased
from ATCC (CRL-1446). Cells were maintained in DMEM with 10% fetal bovine
serum. Cells were all maintained in a humidified incubator at 37°C under 5% CO 2.
Transient transfection was performed using the X-tremeGENE HP Transfection
Reagent (Roche Applied Science) according to the manufacturer’s instructions. For
112

RNAi experiments, SMART Pool siRNAs (Dharmacon) against mouse or rat Egr1 (M-
100247-01), rat PKA (M-093299-02) or non-targeting siRNA (D-001210-01) were
transfected into the cells using Lipofectamine RNAiMAX reagent (Invitrogen),
according to the manufacturer’s protocols. Compound C (Sigma), H-89 (Sigma) and
PKI (protein kinase A inhibitor 14-22 amide, EMD Millipore) were purchased from
commercial sources.
Plasmid expressing Flag-Egr1 (Yu et al., 2004) has been described previously
and obtained from Addgene. Egr1-SEAP reporter construct was generated by inserting
two repeats of Egr1-binding consensus sequence GCG GGG GCG into pTAL-SEAP
(secreted alkaline phosphatase) vector (Clontech) and verified by DNA sequencing.
Wild-type and DBE (DAF-16 family protein-binding element)-mt MnSOD-luc
constructs (Kops et al., 2002) were gifted from Boudewijn M.T. Burgering at
University Medical Center Utrecht, Utrecht, The Netherlands. FHRE-luc (#1789)
(Brunet et al., 1999) was purchased from Addgene.
For EGR1-SEAP assay, two repeats of EGR1 consensus binding sites (GCG
GGG GCG) (Swirnoff and Milbrandt, 1995) were cloned into pTAL-SEAP (secreted
alkaline phosphatase) vector plasmid (Clontech). Wild-type and Egr1-null MEFs (7 ×
10
3
cells/well) were plated in 12-well plates and transiently transfected with the
reporter vectors by XtremeGENE HP transfection reagent (Roche). At 24 h post-
transfection, cells were treated with the indicated conditions and the cell culture
medium was harvested and analyzed for SEAP activity using the Great EscAPe SEAP
Chemiluminescence Detection Kit (Clontech).
113

Mouse model
C57BL6 female mice were purchased from Charles River Laboratories International
Inc. Mice were maintained in a 12 h light/dark cycle at constant temperature and
humidity. Following doxorubicin injection, the survival was recorded daily. All of the
experiments were approved by University of Southern California’s Institutional
Animal Care and Use Committee before the experiments were started.

Blood glucose measurements
Briefly, the tip of the tail was cut and 5µl of blood were drawn directly in the glucose
strip for the measurement (Precision Xtra, Abbott Diabetes Care Inc.).

Bioenergetic measurements
Cells were seeded onto an XF96 cell culture microplate (Seahorse Bioscience) at 2˗3
× 10
4
cells/well. Metabolic rates were measured using an XF96 Extracellular Flux
Analyzer (Seahorse Bioscience). XF Cell Mito Stress and XF Glycolysis Stress Test
kits were used to measure the key parameters of mitochondrial functions and cellular
glycolysis, respectively, according to the manufacturer’s instructions (Seahorse
Bioscience).

114

LDH cytotoxicity assay
At 24 h following siRNA introduction, cells were incubated in normal or starvation
media for additional 24 h. Cells were treated the following day and cytotoxicity was
measured 24 h later by LDH release assay (Promega).

Immunoblot analysis
Immunoblot analysis was performed as previously described (Shim et al., 2007). The
same amount of total protein was used for Western blot analysis. Antibodies against
EGR1 (C-19; Santa Cruz Biotechnology), Tubulin (Cell Signaling Technology) were
obtained from commercial sources.

RNA isolation and quantitative RT-PCR
Total RNA was isolated using TRIzol Reagent (Invitrogen), reverse-transcribed with
M-MLV Reverse Transcriptase (Promega), and amplified with SYBR Green PCR
maser mix (Invitrogen) according to the manufacturer’s recommendation. The
following PCR primers were used: mouse Egr1 forward; 5'- GAC GAG TTA TCC
CAG CCA AA -3', reverse 5'- GGC AGA GGA AGA CGA TGA AG -3', mouse
Catalaze forward; CCT GAC ATG GTC TGG GAC TT, reverse; CAA GTT TTT GAT
GCC CTG GT, mouse CuZnSOD forward; CCA GTG CAG GAC CTC ATT TT,
reverse; TTG TTT CTC ATG GAC CAC CA, mouse MnSOD forward; GCC CCC
TGA GTT GTT GAA TA, reverse; AGA CAG GCA AGG CTC TAC CA, mouse
FOXO1 forward; TAA CTG TGC CCC AGG ACT CT, reverse; AGC TGG GGT TCA
115

TCA TTT TG, mouse FOXO3 forward; GGG GAG TTT GGT CAA TCA GA, reverse;
GCC TGA GAG AGA GTC CGA GA. The expression levels were normalized with β-
ACTIN mRNA in each sample. The expression levels were normalized with β-ACTIN
mRNA in each sample.

116

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123

Chapter 5
Conclusions and Future Directions

Dietary or calorie restriction is a moderate reduction in food intake without
malnutrition (Fontana et al., 2010; Longo and Mattson, 2014). Long-term dietary or
calorie restriction has been reported to be able to reduce the risks for age-related
diseases, including diabetes, cardiovascular disease, cancer and neurodegenerative
diseases. Short-term starvation or fasting has been known as an effective intervention
enhancing cancer treatment in humans. However, the molecular mechanisms
underlying dietary or calorie restrictions remain largely unknown.
Here I demonstrate that REV1, a specialized DNA polymerase involved in
DNA repair, is an important signaling node linking nutrient sensing to cell fate in
cancer cells. I also show the importance of the interplay between p53 and REV1 in
short-term starvation response through REV1’s post-translational modification. In
addition, EGR1 is one of the key signaling components in dietary restrictions. EGR1
can sense the glucose availability and act as an important signaling component in
short-term starvation and fasting-mimicking conditions.
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5.1 Basic and Clinical Implications
This thesis provides insights into the novel molecular mechanisms underlying
dietary interventions. First, I have identified that mammalian REV1 protein can
undergo the post-translational modification by the small ubiquitin-related modifier
(SUMO). SUMOylation is a dynamic and reversible process in which SUMO
conjugation to target proteins occurs via a series of enzymatic reactions. SUMO
conjugation has received more attentions due to its essential roles in regulating diverse
cellular processes, including activity, interaction, stability and subcellular localization
of target proteins (Bergink and Jentsch, 2009; Dou et al., 2010; Jackson and Durocher,
2013).
In chapter 2, I demonstrate that SUMO2/3 covalently conjugates to REV1
protein in response to short-term starvation via ROS. Short-term starvation induces
ROS and in turn REV1 SUMOylation in cancer cells. PIASy acts as an E3 SUMO
ligase for REV1 and their interaction is increased in response to short-term starvation
and ROS. Its modification can also modulate the stability of REV1 protein. Wild-type
REV1 proteins are more stable than SUMOylation-deficient mutant REV1.
Furthermore, the ectopic over-expression of SUMO2/3 isoforms also enhances the
stability of endogenous REV1 protein in cells.
125

In chapter 3, I show that REV1 interacts with p53, the guardian of the genome,
and its interaction regulates cancer cell fate in response to short-term starvation. REV1
interaction regulates both p53’s stability and transcriptional activity. In normal
condition, REV1 negatively regulates p53 transactivation. Under starvation condition,
REV1 protein is rapidly modified by SUMO2/3 and this modification results in a
consequent relief of REV1’s inhibition of p53 activity. Moreover, starvation
simultaneously causes p53 activation through phosphorylation and acetylation and
leads to the induction of apoptosis in cancer cells. These findings demonstrate that
fasting, in part through its effect on REV1, can be a promising nontoxic strategy to
increase p53-dependent cell death and enhance the efficacy of cancer therapies.
In chapter 4, I identify the pivotal role of AMPK/PKA-EGR1 pathway in
starvation- and metformin-induced protection against chemotherapy’s side effects.
Doxorubicin is a widely used anticancer chemo drug used for treating a variety of
cancer types. Like many other chemotherapy drugs, however, its side effects limit their
clinical uses and heart problems are the well-known adverse effects of doxorubicin. I
show that fasting and glucose restriction can induce EGR1 expression through AMPK
activation and PKA inhibition in cardiomyocytes. EGR1 triggers the expression of
antioxidant and FOXO responsive genes and exerts the protective effects against
doxorubicin-induced cardiotoxicity. Metformin, an AMPK activator, also mimics the
beneficial effects of short-term starvation and fasting in heart tissues and enhances
stress resistance to doxorubicin in EGR1-dependent manner. These data provide that
EGR1 is an important molecular component of the signaling pathway that allows
126

cardiomyocytes to sense and react to nutrient availability through AMPK/PKA
pathways and that fasting and metformin reverse glucose-dependent cardiotoxicity
against doxorubicin through EGR1.
These REV1-p53 and AMPK/PKA-EGR1 pathways provide the molecular
targets for the development of novel therapeutics mimicking dietary or calorie
restriction in combating age-related disorders.

5.2 Future Directions
Dietary and calorie restriction have been reported as a remarkably potent
intervention to extend lifespan and prevent multiple age-related diseases in numerous
species (Fontana et al., 2010; Kennedy and Pennypacker, 2014). Therefore, a better
understanding of cellular and molecular mechanisms of nutrient signaling cascades
will be critical to develop the therapeutic applications to the prevention and treatment
of age-related disorders.
This study show that REV1 and EGR1 are the important and novel mediators
sensing and reacting to nutrient availability in cancer and normal cells, respectively.
REV1 and its SUMOylation have been shown to modulate p53-dependent
transactivation and cancer cell death under stress conditions. The knockdown of REV1
promotes the short-term starvation-induced sensitization of cancer cell to
127

chemotherapy. And, the combination of starvation and REV1 inhibition has the
potential as a therapeutic intervention to enhance cancer cell death in the absence of
chemotreatment.
These findings show that the N terminus of REV1, containing the BRCT
domain critical for protein interaction, is sufficient for p53 binding and that its
interaction regulates p53’s stability and transcription activity. REV1 is also known to
be interact with other Y family polymerases, Polκ, Polι and Polη (Guo et al., 2003;
Sale et al., 2012) and with PCNA and the B family TLS polymerase Polζ via accessory
subunit REV7 (Guo et al., 2003; Guo et al., 2006), it is tempting to speculate that
REV1 could be a scaffold bridging between p53 and other DNA repair proteins. How
modification of REV1 releases p53, however, is unclear. Reversible modification of
internal lysine residue(s) within REV1 may lead to a conformational change of REV1
structure, allowing p53 disruption. It is also possible that post-translational
modification leads to either reduced p53 affinity for REV1 or disruption of p53
oligemerization, resulting in dissociation in REV1-p53 complex. Therefore, further
study on the relationship among REV1 modifications, p53 complex regulation, and
cell fate will provide important insights into the precise regulatory mechanism of
short-term starvation in cancer cells.
My data also provide evidence that EGR1 mediates the protective effects of
short-term starvation and fasting in heart tissues against chemotherapy. My findings
support that short-term starvation or fasting effectively reduces doxorubicin-induced
128

toxicity in cardiomyocytes. Short-term starvation or fasting induces the expression of
EGR1 in cardiomyocytes and EGR1 induction has a protective effect against
doxorubicin-induced cardiotoxicity. Both AMPK activation and PKA inhibition in
response to short-term starvation are identified as the upstream regulators of EGR1
induction in cardiomyocytes. Thus, the further studies on a cross-talk between AMPK
and PKA kinases have the potential to provide insight into the precise regulatory
mechanisms of cardiac protection under starvation conditions.
In addition, my findings demonstrate that AMPK activator, metformin, also
induces EGR1 induction and confers cardiac protection against doxorubicin treatment.
Small molecules such as metformin and rapamycin have been identified that mimic
the beneficial effects of dietary intervention, such as improved healthspan and lifespan
(Blagosklonny, 2014; Harrison et al., 2009; Kennedy and Pennypacker, 2014;
Lamming et al., 2013; Martin-Montalvo et al., 2013). However, the underlying
mechanism of action remain unclear. My data suggest that EGR1 can be a mediator of
protective role of dietary restriction as well as metformin treatment.
Short-term starvation and metformin trigger the expression of antioxidants and
stress responsive genes, leading to increased stress resistance in EGR1-dependent
manner. Further studies are needed to assess the specific role of EGR1 in response to
starvation and metformin in combination with doxorubicin treatment. Gene expression
patterns can be examined in heart tissues using gene expression analysis. To
investigate the role of EGR1 in heart failure by doxorubicin, the expression patterns
129

of atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) can be measured
as the diagnostic markers of heart failure. Analysis of pro-inflammatory and pro-
apoptotic gene expression will also be useful to take a closer look at the metformin
and starvation’s protective effects against doxorubicin.
Furthermore, knockout mouse model will provide important insights into the
physiological significance of EGR1 in stress responses. Egr1
-/-
mice are viable and
normal in size, but exhibit impaired inflammatory response and tissue repair (Lee et
al., 1996). The heart function, such as the left ventricular systolic and diastolic
pressures, can be measured and compared in wild-type and knockout mice before and
after starvation and/or doxorubicin treatment. Glucose tolerance tests can be
performed to characterize a metabolic phenotype of wild-type and Egr1
-/-
mice. In
addition, the quantitative measurement of mouse IGF-1 and IGF1-BP1 in serum using
an enzyme-linked immunosorbent assay (ELISA) will be useful to investigate the role
of EGR1 in the physiological systems. Finally, in vivo stress resistance to doxorubicin
and histology studies will provide direct evidence that EGR1 can mediate the
beneficial effects of dietary restriction and metformin treatment under chemotherapy.

130

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Abstract (if available)

Abstract Dietary or calorie restriction has been a well‐studied strategy for increasing survival and preventing carcinogenesis in mammals. Short‐term starvation, an extreme form of dietary restriction, can augment cancer treatment efficacy and can be effective in delaying cancer progression in the absence of chemotherapy. However, the underlying molecular mechanisms of these dietary interventions remain elusive. ❧ Here I describe REV1, a specialized DNA polymerase involved in DNA repair, as an important signaling node linking nutrient sensing and metabolic control to cell fate in cancer cells. I have identified that REV1 is a novel binding partner of the tumor suppressor p53 and regulates its activity, and that short‐term starvation facilitates the modifications of these proteins. Under starvation, REV1 is modified by SUMO2/3, resulting in consequent relief of REV1’s inhibition of p53 and enhancing p53 activation, pro‐apoptotic genes expression and in turn p53‐mediated apoptosis in breast cancer and melanoma cells. Thus, fasting through its effect on REV1 is a promising non‐toxic strategy to increase p53‐dependent cell death and to enhance the efficacy of cancer therapies. ❧ In addition, my study reveals that AMPK, PKA, and EGR1 are the molecular components of functional signaling pathway that allows cardiomyocytes to sense and react to nutrient availability. AMPK activation and PKA inhibition under glucose restriction and metformin treatment are required to promote the induction of EGR1, an immediately early response gene, and the expression of antioxidant and stress resistance genes in cardiomyocytes. EGR1 has a consequent cardioprotective function following doxorubicin treatment. This study provides that short‐term starvation and metformin have a protective role in doxorubicin‐induced cardiotoxicity through AMPK/PKA-EGR1 pathway. ❧ In conclusion, this thesis provides molecular evidence for short‐term starvation as the promising intervention to exert differential effects in normal and cancer cells, contributing to their protection and death in response to stress, respectively. These data describe REV1 and EGR1 as the important signaling nodes linking nutrient sensing and metabolic control under starvation conditions.

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Creator Shim, Hong Seok (author)

Core Title Differential effects of starvation in normal and cancer cells: from EGR1-dependent protection to p53-mediated apoptosis

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Integrative and Evolutionary Biology

Publication Date 10/29/2016

Defense Date 03/16/2015

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag AMPK,EGR1,OAI-PMH Harvest,p53,PKA,REV1,Starvation,SUMOylation

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Language English

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Advisor Longo, Valter D. (committee chair), Lee, Amy S. (committee member), Tower, John G. (committee member)

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