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CHARACTERIZATION OF IMMUNE RESPONSE AND EFFECTS OF ENERGY
BALANCE ON SEVERITY OF COLITIS AFTER INFECTION WITH
HELICOBA CTER HEPA HCUS IN THE SMAD3-/- MOUSE MODEL

By

Sarah Josephine McCaskey, RD

A THESIS

Submitted to
Michigan State University
in partial ﬁllﬁllment Of the requirements
for the degree of

MASTER OF SCIENCE
Human Nutrition

2010

ABSTRACT
CHARACTERIZATION OF IMMUNE RESPONSE AND EFFECTS OF ENERGY
BALANCE ON SEVERITY OF COLITIS AFTER INFECTION WITH
HELICOBAC'IER HEPA TICUS IN THE SMAD3-/- MOUSE MODEL
By
Sarah Josephine McCaskey, RD

The SMAD3-/- mouse model is used study the pathogenesis of ulcerative colitis
and colon cancer development in humans. The absence of SMAD3 causes dysregulation
in TGF-B signaling and impairment of T regulatory cell development; however, current
information regarding alterations in immune cell populations in this model is lacking.
Therefore, we designed a study to identify and characterize SMAD3-dependent changes
in immune cell populations in response to infection with the pathogenic bacteria H.
hepaticus. We found signiﬁcant alterations in NK cells, T cells and T cell subsets in
SMAD3-l- mice, indicating that these mice have an inherently increased susceptibility to
colitis due to a decreased ability to respond infection with Helicobacter hepaticus. These
novel data provide potential immunological changes by which genetic alterations can
affect the severity of colitis and subsequent tumorigenesis.

We then used the SMAD3-/- model to examine potential effects of energy balance
on the severity of colitis and dysplasia following infection. We found that calorie-
restricted mice died shortly aﬁer infection, and that there was no difference in severity of
colitis between high-fat and control mice. These results are likely due to the fact that we
were unable to achieve signiﬁcantly increased body weight or fat percentages in the high-

fat mice compared to control, especially after 18 weeks of age. Future studies will be

designed to account for age-related changes in body composition prior to infection.

ACKNOWLEDGMENTS

The completion of this thesis would not have been possible if not for the guidance
and encouragement of many extraordinary people who have assisted me throughout my
graduate career. First and foremost, I would like to thank Dr. Jenifer Fenton for her
continuous support of my research, and for the knowledge, experience, patience and
advice she has provided to me time and time again. I am most grateful to have Dr.
Fenton as an adviser, a mentor and a ﬁiend.

I would also like to thank Dr. Norman Hord and Dr. Laura McCabe for serving on
my advisory committee. My research and writing were made stronger through each of
their unique perspectives and expertise, and I am grateful for their assistance.

My sincere appreciation goes to the members of both Dr. F enton’s and Dr.
Elizabeth Gardner’s laboratories, who have provided countless hours of technical
assistance and support during our many experiments.

Last but not least, I would like to thank the many family and friends who have
continually supported me throughout all Of my endeavors, both personal and professional.
I give special thanks to my parents, Mark and Eleanor McCaskey, for all they have done

for me, and to Zoe, who is my ultimate inspiration.

iii

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................. vi
LIST OF FIGURES .......................................................................................................... vii
KEY TO SYMBOLS ....................................................................................................... viii
Chapter 1 — Literature Review ............................................................................................ 1
Obesity and Cancer ......................................................................................................... 1
Adipokines and Cancer ................................................................................................... 3
Insulin/IGF-l and cancer. . .......................................................................................... 3
Leptin and cancer. ....................................................................................................... 5
IL-6 and cancer. .......................................................................................................... 6
Adiponectin and cancer ............................................................................................... 7
Colon Cancer .................................................................................................................. 9
Ulcerative Colitis and Colon Cancer ............................................................................ 13
Macrophages and ulcerative colitis. .......................................................................... 13
Natural killer cells and ulcerative colitis ................................................................... 14
T cells and ulcerative colitis ...................................................................................... 15
IBD, Chronic Inﬂammation and Colon Cancer ............................................................ 17
Altered cell signaling in colon cancer. ...................................................................... 18
Hypothesis and Speciﬁc Aims ...................................................................................... 21
Bibliography ................................................................................................................. 22
Chapter 2 - Identiﬁcation of kinetic and tissue-speciﬁc changes in natural killer cell and T
cell populations during Helicobacter hepaticus infection in SMAD3-l- mice ................. 33
Introduction ................................................................................................................... 33
Materials and Methods .................................................................................................. 35
Murine model. ........................................................................................................... 35
Bacteria] culture and infection. ................................................................................. 35
Experimental Design. ................................................................................................ 35
Body composition. .................................................................................................... 36
Tissue ﬁxation and histopathology. .......................................................................... 36
Lymphocyte isolation ................................................................................................ 37
Flow cytometry. ........................................................................................................ 37
Statistics. ................................................................................................................... 38
Results ........................................................................................................................... 38
Weight and body fat percentage change throughout course of infection .................. 38
Histological scoring of colitis and dysplasia. ........................................................... 39
Differences in lymphocyte populations between SMAD3-/- and SMAD3+/- mice at
baseline (pm-infection). ............................................................................................ 39

iv

Lymphocyte population changes in SMAD3-/- and SMAD3+/— mice following

infection with H. hepaticus. ...................................................................................... 4O
Treg cell populations differ between genotypes and across time in MsLN. ............. 41
Discussion ..................................................................................................................... 42
Appendix ....................................................................................................................... 48
Bibliography ................................................................................................................. 54
Chapter 3 - Effect of energy balance on severity of colitis and dysplasia after infection
with Helicobacter hepaticus in SMAD3-l— mice. ............................................................. 59
Introduction ................................................................................................................... 59
Materials and Methods .................................................................................................. 62
Mice. ......................................................................................................................... 62
Genotyping. ............................................................................................................... 62
Induction of lean, control and Obese body weight phenotypes. ................................ 63
Preparation of blood agar plates ................................................................................ 63
Helicobacter hepaticus culture and infection. ........................................................... 64
Body composition analysis. ...................................................................................... 64
Sample collection at necropsy. ................................................................................. 64
Pathology. ................................................................................................................. 65
Results ........................................................................................................................... 66

Changes in weight distribution and body fat composition between diet treatments. 66
Effect of diet treatment on colitis and dysplasia scores at 28 days post-infection.... 67

Discussion ..................................................................................................................... 67
Appendix ....................................................................................................................... 71
Bibliography ................................................................................................................. 75

LIST OF TABLES

Table 2.1. Total baseline lymphocyte cell population as percentage of live cells by tissue
and genotype, SMAD3+/- or -/-, prior to infection (MeaniSEM). .................................. 49

Table 2.2. NK cell populations as percentage of live cells by tissue and genotype through
the course of infection (MeaniSD) ................................................................................... 51

LIST OF FIGURES

Figure 2.1. Average weight (A) and body fat percentage (B) of SMAD3-/- and
SMAD3+/- mice throughout course Of infection. (C) Average combined colitis and
dysplasia scores of control (Broth) and infected mice through 8 weeks post-infection. .. 48

Figure 2.2. Total NK cell population changes throughout the course of infection in the
spleen, expressed as both (A) percentage of live cells and (B) total NK cell number ...... 50

Figure 2.3. Total T lymphocyte cell number changes in the MsLN of SMAD3+/- and -/-
mice at baseline and at 3, 7, and 28 days post infection. (A) Total CD3+ T cells. (B) Total
CD4+/CD3+ T cells. (C) Total CD8+/CD3+ T cells. ...................................................... 52

Figure 2.4. (A) Total FoxP3+ T regulatory lymphocyte cell number in the MsLN of
SMAD3+/- and -/- mice post infection. (B) Total FoxP3+ T regulatory cells expressing
CD62L lo. ......................................................................................................................... 53

Figure 3.1. Average body weight (g) for HF, CON and CR diet groups throughout the
course of diet treatment for (A) Group 1 and (B) Group 2. .............................................. 71

Figure 3.2. Survival curve of HF, CON and CR mice after infection with H. hepaticus. 72

Figure 3.3. (A) Average body weight (g) of HF and CON diet groups throughout course
of diet treatment. (B) Average body fat percentages of HF and CON diet groups .......... 73

Figure 3.4. (A) Average combined colitis and dysplasia scores between diet groups at 4
weeks post-infection. (B) Average combined colitis and dysplasia scores between diet
groups at 4, 5 and 6 weeks post-infection to assess potential effect of time. ................... 74

Images in this thesis are presented in color.

vii

KEY TO SYMBOLS

 

 

 

 

 

 

Symbol Meaning

* Signiﬁcant effect Of genotype within each time point following infection
(p<0.05)

** Signiﬁcant effect Of genotype within each time point following infection
(p<0.01)

A Signiﬁcant effect of time in SMAD3+/- infected mice compared to
control (p<0.05)

# Signiﬁcant effect of time in SMAD3-/- infected mice compared to

 

control (p<0.05)

 

viii

 

Chapter 1 — Literature Review
Obesity and Cancer

Obesity, deﬁned as a Body Mass Index (BMI) greater than 30, is the result of
complex interactions between a variety of factors, including lifestyle (diet and physical
activity), biological (genetics, metabolism) and environmental attributes, such as culture
and socioeconomic status. Excess weight is gained via sustained energy imbalance, in
that too many calories are consumed and/or not enough calories are expended through
physical activity. The prevalence of obesity in adults, as well as the frequency of
overweight in children and adolescents, has increased dramatically in the United States
over the past several decades. Data Obtained as a part of National Health and Nutrition
Examination Survey in 2003-2004 indicated that 32.2% of adults in the United States
were obese, as compared to 23% in 1988-1994 and 15% in 1976-1980 [1, 2]. At the
same time, 17.1% of American children and adolescents were overweight [1, 2]. These
trends are of particular concern due to the subsequent increase in comorbidities and
related health consequences. Obesity increases the risk of heart disease, stroke, and many
types of cancer, which are the leading three causes of death for Americans, and also
increases risk Of hypertension, osteoarthritis, dyslipidemia, diabetes mellitus type 2,
gallbladder diseases, sleep apnea and respiratory difﬁculties [2]. In a global, systematic
review, total adiposity was associated with increased risk of cancer in the esophagus,
pancreas, colorectum (CRC), breast (postmenopausal), endometrium, and kidney. The
association between obesity and cancer risk are increased when measured by and
increased waist-tO-hip ratio, as abdominal adiposity is also speciﬁcally associated with

colorectal cancer risk [3-5].

One of the connections between Obesity and increased risk of cancer involves the
altered production of adipokines, cell-signaling peptides produced by adipose tissue.
Historically, adipose tissue was primarily considered to be an organ used to store energy
in the form Of triacylglycerols, with secondary functions of insulation and shock
absorption [6]. Now, adipose tissue is recognized as a functional endocrine organ with
the ability to secrete a number of adipokines. These adipokines act both locally and
distally in tissues, and have effects on a large number of bodily functions, including lipid
metabolism, inﬂammation, atherosclerosis, insulin resistance, reproduction, vascular
homeostasis, food intake, therrnoregulation, angiogenesis and immune function [7].
Unlike other secretory organs, adipose tissue can be located in multiple areas throughout
the entire body, with the contributions of metabolic secretions depending upon the
location and size of fat pads [8]. Furthermore, because fat cells have the ability to
“networ ” with other tissues and organs such as skeletal muscle and the brain via
hormone circulation and sympathetic nervous system activation, adipose tissue is highly
integrated into overall metabolism and physiological processes of the body [9].

Adipose tissue is unique as an organ because of its nearly limitless potential to
grow, even throughout adulthood after all other developmental growth has ended. In the
obese state, adipose tissue also becomes dysregulated as a result Of an abnormal
interaction between energy balance, vasculature and immune cell inﬁltration, which is
associated with the progression of chronic inﬂammation [10]. All adipose tissue releases
adipokines regardless of body fat percentage of the individual, thus the inference can be
made that the release of adipokines will increase along with increases in amounts of

adipose tissue. As a result, production and excretion of several adipokines and other

adipose tissue-related hormones, including insulin, leptin and interleukin-6, are
signiﬁcantly increased in obesity [6]. Several Of these are pro-inﬂammatory cytokines
that are released from adipose tissue even in the absence of acute injury or inﬂammation,
supporting the characterization of obesity as a disorder of chronic mild inﬂammation.
Intra-abdominal adipose tissue appears to produce many of the adipokines in amounts
greater than that Of fat deposits elsewhere in the body, causing android obesity to be both
a symptom of and a diagnostic indicator for metabolic syndrome [11]. Metabolic
syndrome in turn is a risk factor for the development of cardiovascular disease, diabetes
mellitus, peripheral vascular disease and stroke. Multiple studies have also found
circulating adipokines to be contributing factors for increased risk Of many types of
cancer, including cancers of the breast, colon, kidney and esophagus [12]. The inﬂuence
of adipokines on insulin sensitivity, glucose metabolism, inﬂammation and
atherosclerosis may provide the molecular link between increased adiposity and
development of obesity-related cancers [13]. Therefore, adipokines may be useﬁll as
clinical biomarkers to assess increased risk of cancer associated with increased adiposity
and related comorbidities.

Adipokines and Cancer

Insulin/[GE] and cancer.

Insulin is a hormone produced and released by the pancreas and is therefore not
an adipokine by deﬁnition; however, obesity is known to cause insulin resistance, thereby
leading to an increase in serum levels of insulin as a compensatory response to the
resistance [14]. As such, insulin is included as a hormone that is markedly increased in

conditions of Obesity. Chronic hyperinsulinemia and insulin resistance has been found to

increase risk for many types of cancer, although it is unclear whether the tumor-
proliferating results are due to the direct effect of insulin on pre-neoplastic cells or the
indirect stimulation of insulin-like growth factor (IGF) and other hormones [15]. Aside
ﬁom its role in the metabolism of glucose, insulin also increases serum levels of the
structurally similar but more potent IGF, thereby acting indirectly through the IGF/IGF
receptor system that is present on most cells throughout the body, which may also
explain in part the relationship between obesity-related hyperinsulinemia and cancer risk
[16]. IGF can be produced by the liver, brain, kidney, pancreas and muscle, and affects
nearly every cell type in the human body, including liver, kidney, nerves, skin, lungs,
muscle and bone [17]. When ﬁmctioning normally, a signal transduced through IGF
receptor leads to activation of several intracellular pathways to maintain cell growth and
survival, and these pathways are tightly controlled. However, overexpression of IGF
receptors may lead to neoplastic transformation, inhibition of apoptosis, metastasis and
angiogenesis, all of which are cell alterations conducive to the development Of tumors
[18]. Downstream targets of IGF receptor comprise a signaling network that regulates
cell growth, proliferation, survival and metabolism via energy availability and supply of
growth factor [15].

Increased expression of IGF/IGFR is Observed in carcinomas and malignancies,
including cancers of the breast, colon, stomach, pancreas, liver, lung, thyroid and ovaries
[19]. Although the exact role of IGF in the disease progression of some cancers (e.g.
breast, prostate) remains controversial, multiple studies have found that higher levels of
IGF are predictive of both stage and risk of metastasis for several types of tumors,

including colorectal, gastric, liver, lung and gallbladder [20-24]. As a whole, these

studies suggest the signiﬁcance of IGF/IGF R expression as a possible indicator of tumor
progression and outcome, although the data varies somewhat between speciﬁc types of
cancers.

Leptin and cancer.

The development that ﬁrst established adipose tissue to be an endocrine organ
was the discovery of the adipokine leptin in 1994 [6]. A product of the ob gene, leptin
was discovered as a hypothalamic regulator of body weight and energy balance by
promoting a sensation of satiety upon adequate nourishment [25]. Research has shown
that mice with mutations in the gene encoding leptin become morbidly Obese, infertile,
hyperphagic, hyperthermic and diabetic due to an insatiable appetite caused by a lack of
leptin production, but human obesity is in fact related to increased levels of leptin,
leading to leptin resistance [26, 27]. Although leptin may also be secreted from other
sources, such as gastric mucosa and mammary epithelia, plasma concentrations of leptin
are largely inﬂuenced by adipose tissue stores [28]. Increased concentrations of leptin in
obese individuals is associated with both greater amounts of adipose tissue as well as
increased leptin release ﬁ'om adipocytes, these levels are higher in women than in men,
and synthesis of leptin correlates with the presence of other hormonal factors, including
insulin.

The association between leptin and cancer risk is a multifaceted relationship, as
leptin is shown to have effects on several tumorigenic pathways. Leptin has been
suggested to play a role vascular remodeling via angiogenesis, both by itself and coupled
with vascular endothelial growth factor (V EGF) and ﬁbroblast growth factor (F GF ), a

necessary trait in the survival of tumors [29]. Leptin also increases endothelial cell

hyperplasia and suppresses apoptosis, both of which are contributing factors in
tumorigenesis [30]. The stimulation of several types of pre-neoplastic and neoplastic
cells in vitro and in animal models appears to promote angiogenesis and tumor invasion
[31, 32]. Leptin has also been found to play more speciﬁc roles in vitro depending in the
location of the cancer and type of tumors: increased cell proliferation has been associated
with leptin in cancers of the breast, prostate, ovary and lung, suppression of apoptosis by
leptin is seen. in colorectal and prostate cancer, and increased pathway activation (e. g.
ERK, STAT, PKC-a) in breast, colorectal, pancreatic, ovarian and lung cancers [28].
Because leptin can be secreted by both adipose tissue as well as tumors themselves, local
concentrations Of leptin are crucial for tumor development, and may prove to become a
useful target for inhibition in cancer treatment and prevention.

IL-6 and cancer.

Interleukin-6 (IL-6) is a cytokine that is produced by many tissues in the body,
including adipose tissue, thereby also being classiﬁed as an adipokine. Previous studies
have demonstrated that IL-6 is secreted by subcutaneous adipose tissue and therefore
triggers systemic effects, particularly in Obese subjects [33]. IL-6 is also secreted from
perivascular adipose tissue, which decreases the protective vasodilation Of small arteries
in Obese subjects [34]. Adipose tissue has been found to contribute up to 35% of
circulating levels of IL-6, leading to systemic effects as well as tissue-speciﬁc pleiotropic
functions [35]. One of these effects is an increase in serum C-reactive protein (CRP), a
blood protein released in response to inﬂammation, serving as a ﬁrrther indication that
obesity is a disease of chronic inﬂammation. Park et al. found that IL-6 and CRP

concentrations are signiﬁcantly correlated with weight, BMI, waist/hip circumference

and waist/hip ratio [36]. IL-6 also has direct central actions, as evidenced by the
discovery of IL-6 receptors on the hypothalamus, making IL-6 a possible vehicle of
information transfer ﬁom adipocytes to the hypothalamus with respect to regulation of
energy balance [6].

The mechanism of action for IL-6 begins with binding of the molecule to a
hexarnetric receptor that includes an IL-6 receptor and a signal transducer; the attachment
of IL-6 and its receptor causes phosphorylation of ST AT3 proteins that directly bind to
target genes, mediating the expression of a variety of genes that affect cellular processes
such as cell growth and apoptosis [37]. The link between IL-6 and tumorigenesis has
been proposed to involve the activation of this pathway [3 8-40]. A previous study of IL-6
and its implications speciﬁcally for colon cancer concluded that tumor-inﬁltrating
macrophages have the ability to release IL-6, increasing levels of intratumor IL-6 that
condition the cancer cells to secrete IL-6 themselves, thereby perpetuating a favorable
environment for tumor growth and inﬁltration [41]. IL-6 is also been implicated in
several other types of cancer; serum IL—6 levels were found in patients with advanced
stage or metastatic cancers of the breast, gastrointestinal tract, lymph nodes, lung, skin,
ovary, pancreas, prostate and kidney [42-51]. Conversely, other evidence in the literature
indicates that IL-6 also acts as an inhibitor of cancer progression, for example, exhibiting
the anti-cancer function of growth inhibition for some cancers of the prostate, colon and
breast [52-54].

Adiponectin and cancer.
Adiponectin is another adipokine; however, unlike the previously aforementioned

pro-inﬂammatory adipokines, adiponectin functions as an anti-inﬂammatory hormone by

suppressing the migration of inﬂammatory mediators, such as monocytes and
macrophages, to inhibit inﬂammation [55]. Although it is secreted both as an active
high-molecular weight (HMW) complex and a low-molecular weight (LMW) complex,
the HMW complex is primarily associated with the known beneﬁcial physiological and
metabolic effects [56]. Adiponectin reduces plasma concentrations of triglycerides and
fatty acids while increasing expression of proteins necessary for lipid metabolism,
leading to an overall improvement of fatty acid catabolism, particularly in skeletal
muscles [57]. Adiponectin may be involved in increased insulin sensitivity, possibly as a
result of its roles in increased lipid oxidation, improvement of insulin signaling,
inhibition of gluconeogenesis, or inhibition of TNF-a [55]. The combination of increased
insulin sensitivity and improved lipid catabolism indicates that adiponectin has a strong
effect on regulation of energy balance and body weight, similar to that of leptin.
Although most other adipokines, including leptin, are upregulated and found in increased
circulating levels in obesity, adiponectin expression and concentration is markedly
reduced in overweight and Obese subjects [58]. Therefore, the diminished synthesis of
adiponectin as a result of Obesity may lead to dysregulation of the production of pro-
inﬂarnmatory cytokines, thereby leading to increased insulin resistance and inﬂammation
[55]. A negative correlation between circulating levels of adiponectin and Obesity
(particularly android obesity), insulin resistance and type 2 diabetes has already been well
established, and has been propagated by evidence that serum adiponectin levels increase
when loss of adipose tissue occurs [59].

High circulating levels of adiponectin have several protective effects against the

development Of cancer. Adiponectin also negatively regulates hematopoiesis,

downregulates immune system response, induces apoptosis in certain cancer cell lines in
vitro, and modulates expression of apoptosis-related genes [60]. Adiponectin exhibits an
antiproliferative effect by binding several mitogenic grth factors, inhibiting superoxide
production, and negatively regulating angiogenesis [61-63]. Given these protective
effects, there are also strong indications that decreased adiponectin may have a causal
role in the development of several types of cancer. Kelesidis et al. reported that
adiponectin levels are inversely associated in vivo with increased risk of cancers
associated with Obesity and insulin resistance, including cancers of the endometrium,
breast (particularly post-menopausal), colon, stomach and prostate, as well as leukemia
[59]. This may be due in part to the relationship between adiponectin and insulin, in that
hyperinsulinemia associated with decreased adiponectin may lead to an increase in
circulating IGFl, which in turn promotes cellular proliferation, inhibition Of apoptosis
and increased secretion of VEGF, all of which are necessary components of
tumorigenesis [64].
Colon Cancer

Colon cancer is the fourth most common cancer in the United States; it is
estimated that 142,570 adults (72,090 men and 70,480 women) will be diagnosed with
and 51,370 men and women will die of cancer of the colon and rectum in 2010 [65]. The
rates of incidence and mortality of colon cancer vary by race and ethnicity as well, with
the highest incidence of colon cancer in Aﬁican Americans, followed by Caucasians,
Native Americans, Asian/Paciﬁc Islander and Hispanic Americans. Several migrant
studies regarding cancer and mortality rates found that a migrant person’s risk of many

cancers, including colorectal cancer, changes to match that of the country to which

migration occurred, particularly those with Westernized cultures [66, 67]. Ethnic and
racial differences in development of colon cancer indicate that environmental factors may
heavily inﬂuence etiology of colon cancer and is therefore avoidable in theory. Although
colon cancer is widely believed to be an environmental disease, risk may include a
complex interaction Of genetic, cultural, social and lifestyle practices [68].

Although the aforementioned “environmental factors” that are widely believed to
contribute to colon cancer are less well-deﬁned, there are several risk factors that are
common throughout populations with a high incidence of colon cancer. Countries that
are more developed, afﬂuent and Westernized have much higher rates of colon cancer
that are often attributed to greater ﬁ'equency of Obesity, physical inactivity, alcohol
consumption and tobacco use, especially as compared to less-developed countries.
Dietary risk factors include the consumption of a diet high in red and/or processed meats,
saturated and trans fats, low intake of dietary ﬁber, and may include ingested carcinogens
(e. g. heterocyclic amines from charred meat) [69, 70].

A majority Of colon cancers (estimated at about 80%) develop from the
transformation of sporadic adenomatous polyps [71]. Polyp formation is often caused by
one or more mutations of the adenomatous polyposis coli (APC) gene, a known tumor
suppressor. Mutations in this gene may cause dysfunction of the proteins produced by
APC, rendering them ineffective in the suppression of uncontrolled cellular growth, and
lead to the development of familial adenomatous polyposis (FAP). Individuals with FAP
may develop anywhere from several hundred to several thousand polyps lining the large
intestine; these polyps develop as benign growths, but eventually become malignant

unless the colon is removed. In cases of classic FAP, the average age at which an

10

individual is diagnosed with colon cancer is 39 years [72]. Family history of colon
cancer ampliﬁes lifetime risk of death by colon cancer anywhere from a 2-4 fold
increase, depending on number of ﬁrst-degree relatives affected and at what age(s) the
cancer presented.

A model for molecular determinants of colorectal tumorigenesis was ﬁrst
proposed by F earon and Vogelstein in 1990 and outlined the successive genetic changes
and the speciﬁc genes involved in the development of colorectal cancer, including APC,
k-Ras, DCC and p53 [73]. Normal epithelial tissue becomes mutated to form regions of
hyperproliferative monoclonal epithelial cells. This neoplastic tissue results in the
successive formation Of early, intermediate and late stage adenomas, and ﬁnally mutate
into carcinomas. Although Fearon and Vogelstein stressed that the overall accumulation
of genetic alterations was more important than the order in which the changes occurred,
subsequent research revealed more information on the functions Of key molecules in the
original model.

In a 2000 review, Arends outlined the ﬁndings about the speciﬁc role of certain
genes in the Vogelstein model. APC, originally thought to be involved in cell adhesion
via binding with B-catenin, is bound to other molecules such as EB], and was also shown
to induce apoptosis in APC-deﬁcient cell lines [74]. The k-Ras oncogene is a signal
transduction molecule that becomes activated when paired with GTP and is inactivated in
the presence of GTPase-activating proteins (GAPS). If the Ras product mutates, it
becomes less sensitive to hydrolysis by GAPS, induces greater cellular proliferation, and
inhibits apoptosis, all Of which are factors essential to the growth of tumors. The cell

adhesion-like molecule DCC (Deleted in Colorectal Cancer), an oncosuppressor gene that

11

was believed to have been involved in 18q deletions and inﬂuenced negatively on
prognosis, was determined to be involved in axon guidance rather than deletions [75].
These genetic alterations, however, are much more conducive of the development Of
polypoid rather than nonpolypoid lesions.

A remaining minority of colon cancers are not attributable to polyp formation.
Roughly 1-7% of all diagnosed cases of colon cancer are attributable to hereditary
nonpolyposis colorectal cancer (HNPCC), also known as Lynch syndrome [76]. The
most common hereditary cause of colon cancer, HNPCC is caused by mutations in ﬁve
speciﬁc genes that are involved in DNA mismatch repair: MLHl, MLH2, MSH6, PMS
and PMSZ. A hallmark implication in most cancers, microsatellite instability occurs
when repeated sequences of DNA (rrricrosatellites), normally of a set length, become
longer or shorter than usual. These altered-length sequences are usually corrected via
mismatch repair; however, if these genes become defective, stability Of the genome is
severely compromised. DNA replication errors may further alter major tumor suppressor
genes or activate oncogenes, thereby greatly increasing the risk of developing
malignancies. Individuals with HNPCC have roughly an 80% lifetime risk for colon
cancer, compared to a less than 5% lifetime risk for those without HNPCC.

Furthermore, there is a clear association between inﬂammatory bowel diseases
(such as Crohn’s disease or ulcerative colitis [UC]) and colon cancer, indicating that
patients with IBD, particularly UC, have up to a 20-fold higher risk of developing colon
cancer than the general population. Eaden et al. conducted a meta-analysis of 116 studies

and found that the prevalence of colon cancer in patients with UC is approximately 3.7%

12

(95% CI 3.2—4.2, p<0.0001), with the cumulative probability reaching 18% by 30 years,
regardless of disease severity [77].
Ulcerative Colitis and Colon Cancer

Although the etiology of ulcerative colitis is uncertain, there are indications that
the immune systems of individuals with UC react abnormally to bacteria in the digestive
tract, and that these immune mechanisms are important in the pathogenesis of the disease
and potential for subsequent dysplasia and tumor development [78-80]. In a manner
similar to that in which it responds to bacterial and viral pathogens, the immune system
also reacts to cancer cells, in that such cells are recognized as an invading foreign entity
against which the body must be defended. The changes that occur to the surface of a cell
during malignant transformation cause the antigens present on that cell to change as well,
which in turn trigger the immune system into recognizing the cancerous cell as “non-self”
and mounting an immune response. The theory of immunosurveillance suggests that
lymphocytes, including macrophages, natural killer cells and cytotoxic T cells, constantly
patrol the body and eliminate mutated cells [81]. When this surveillance system is either
overwhelmed or dysfunctional, the cancerous cells can evade the immune system and
tumors may develop.

Macrophages and ulcerative colitis.

Immune system dysregulation associated with UC includes dysfunction and/or
imbalances of several types of inrrnune cells. Macrophages are phagocytic white blood
cells that play a role in both innate (non-speciﬁc) and humoral (speciﬁc) immunity by
acting as antigen presenting cells. In an innate immune capacity, macrophages work to

engulf and digest invading pathogens as well as the cellular debris remaining from other

13

immune cell response. The role of macrophages in humoral immunity stems ﬁ'om the
release of chemokines to stimulate other lymphocytes to respond to the pathogen. The
histopathological characterization of UC involves inﬁltration of activated macrophages
within the colonic mucosa, and these cells are responsible for the release of inﬂammatory
cytokines TNF-a, IL-IB, and IL-6, implicating pathogenesis Of the disease [82]. In
speciﬁc response to cancer cells, around which macrophages have been found to cluster,
they partake in antitumor activity mediated by lytic enzymes and reactive oxygen or
nitrogen intermediates, as well as the production of tumor necrosis factor (TNF), a
chemokine that activates cytolysis of tumor cells [83].

Natural killer cells and ulcerative colitis.

Natural killer (NK) cells are capable of destroying foreign and dysﬁmctional cells
via degranulation and induction of cell lysis. Unlike other lymphocytes, however, natural
killer cells can recognize infected and cancerous cells non-speciﬁcally and without
previous exposure or antigen presentation. Because NK cells have such marked cytolytic
abilities as well as the potential for self-reactivity, the action of NK cells is strongly
regulated. An NK cell must receive an activating signal, such as the binding of an
antibody to its Fc receptor molecule, before it becomes fully activated and functional.
The levels of NK cytotoxicity in UC are related to the clinical activity of the disease; in
an active disease state, NK cells are present in normal numbers but are functionally
defective, whereas NK cells exhibit normal cytotoxic activity in an inactive disease state
[84]. The inﬂammation and damage caused by increased secretion of inﬂammatory
cytokines during an active disease state may be triggered by false recognition and

processing of the natural gut commensal bacteria by NK cells [85]. Neither macrophages

14

nor NK cells are MHC restricted and both express F c receptors, indicating that these cells
can bind antibody directly on the tumor cells through antibody-dependent cell-mediated

cytotoxicity [83]. Recent studies have identiﬁed a speciﬁc population of NK cells that

express the transcription factor RORyt+NKp46+; these cells provide an innate source of

IL-22 and play a protective role in mucosal inﬂammation, in that a reduction or absence
of this cell type results in worsened colitis [86-89].

T cells and ulcerative colitis.

Cytotoxic T cells, also known as TC or killer T cells, are capable of killing cells
that are infected, damaged or otherwise dysfunctional, including cancerous cells. TC

cells are particularly important in the pathogenesis of UC, as evidenced by extensive TC

cell inﬁltration within intestinal lesions and contribution to epithelial cell damage [90,

91]. In order to function, Tc cells must ﬁrst be activated, a process that requires two

signals to occur between an antigen presenting cell (APC) and the TC cell. Peptide

fragments (antigens) from a dysfunctional cell bind to MHC class I molecules on the

surface of the APC. This antigen-bound MHC class I molecule must bind to the TC cell

antigen receptor (TCR) to provide the ﬁrst signal of activation. The second signal arises

from costimulation of the CD28 molecule on the TC cell and either the CD80 or CD86

molecules on the AFC [92]. After the second signal is received and the TC cell becomes

activated, it uses IL-2 as a growth and differentiation factor to commence clonal

expansion, exponentially increasing the number of TC cells that will speciﬁcally target

15

cells that express the same antigen [92]. Once bound to a target cell, the TC cell releases

perforin and granulysin, enzymes that perforate the membrane of the target cell and
trigger caspase cascades that lead to apoptosis.

After the irmnune response has taken place and the invading or threatening cells
are destroyed, regulatory T cells (Treg) work to suppress immune activation, prevent self-
reactivity and maintain homeostasis of the immune system by inhibiting the proliferation
and effector functions of other T cell populations [93]. Treg cells are uniquely deﬁned

from other thymus-derived immune cells by the transcription factor F oxP3, which

controls the development and function of the regulatory cell [94]. Treg cells also

identiﬁed by the expression of CD25, a high-afﬁnity IL-2 receptor a-chain that is also

present on the surface of activated TH cells [93]. The role of the Treg cell in immune

regulation is especially important in the pathology of inﬂammatory bowel diseases, as the

loss of homeostasis between Treg cells and proinﬂarnmatory T helper l7 (TH17) cells is

thought to trigger inﬂammation associated with these diseases. Speciﬁcally in the case of

UC, there is a decrease in Treg cells and an increase in TH17 effector cells in peripheral

blood, and consequently a signiﬁcant decrease in the ratio Of Treg/T H17 cells, which is

associated with an increased proinﬂarnmatory state [93].

UC has historically been thought to be mediated by the TH2 immune response, in

which there is high antibody production relative to the activity of cytotoxic T cells,

however recent studies strongly suggest that TH17 cells play a more pivotal role in the

16

propagation of immune-mediated tissue damage [78, 95, 96]. There is not yet a clear

consensus regarding the cytokines involved in the development of TH17 cells; however

initial in vivo mouse and in vitro human studies have identiﬁed IL-6, TGF-B, IL-1, IL-21

and IL-23 as differentiating factors [95, 97-99]. Developmentally distinct from other T

helper cells, TH17 cells are a unique subset of TH cells that are deﬁned by the production

of IL-17A and IL-17F, cytokines implicated in the induction and mediation of
proinﬂarnmatory responses, as well as IL-22 and IL-26.
IBD, Chronic Inﬂammation and Colon Cancer

The chronic inﬂammatory damage to intestinal epithelial cells that is
characteristic of IBD is believed to make an individual more susceptible to cancer via
accumulating mutations in rapidly dividing cells. If the mistake causes the dividing cell
to experience microsatellite instability and become dysplastic, the cell may become
cancerous. Histological differences between polypoid and nonpolypoid lesions render the
latter to be more difﬁcult to detect; rather than an obvious polyp, lesions are ﬂat and
more difﬁcult to identify. Because these dysplastic cells do not develop in polyp form,
rather in tissue that appears otherwise normal, an IBD-related ﬂat lesion may only be
found at later stages of cancer progression, thereby reducing the rate of survival [100].
Associated carcinomas are Often inﬁltrative without obvious protruding masses;
therefore, early screening for colon cancer is of utmost importance for patients with long-
terrn IBD [101].

Patients with a family history of colon cancer (presenting at an early age), chronic
UC or primary sclerosing cholangitis-associated neoplasia have an increased risk of

developing colon cancer. Due to the fact that most colon cancers develop ﬁom a

17

malignant change in colon epithelial cells that may have developed decades prior, regular
screening of asymptomatic individuals is a necessary measure to ensure that any
potentially threatening lesions are identiﬁed as early as possible so as to improve
treatment and prognosis. Screening techniques include fecal occult blood tests, stool
tests, barium enemas, sigrnoidoscopy and colonoscopy. Screening is conducted on
patients who present with suspicious signs and symptoms, but is also necessary for
people older than 40 and those with family history of colon cancer, as age and familial
risk are the two most common risk factors for the development of colon cancer [102].

Symptoms of colon cancer depend on location and type of lesion(s), extent of
lesion formation, and any complications associated with polyp formation. Initial signs
and symptoms include bleeding upon defecation, abdominal pain, and fatigue and
weakness, likely caused by anemia due to intestinal blood loss [103]. Patients may also
experience changes in bowel habits, often alternating between constipation and diarrhea
or increased stools. Some may ﬁrst experience symptoms associated with metastatic
disease, including ascites, swollen supraclavicular lymph nodes, and enlarged liver.
Those with non-polypoid cancer may only experience gastrointestinal symptoms (pain,
change in bowel habits) and weight loss from inadequate absorption of nutrients in the
gut.
Altered cell signaling in colon cancer.

A shared attribute of both polypoid and nonpolypoid lesions is that of
microsatellite instability, although it is more frequent in nonpolypoid cancers [104, 105].
As in the case of chronic inﬂammation in IBD, damaged cells develop defects in the

DNA repair mechanism and thereby develop microsatellite instabilities. These

18

instabilities can either alter or inactivate tumor suppressor genes and signaling pathways
that inﬂuence regulation of the cell cycle, ultimately affecting cell proliferation.

TGF-B is one such signaling pathway that is especially important in the process
of tumorigenesis because it controls proliferation, differentiation, apoptosis, homeostasis
and other functions of cells [106]. The process by which this control occurs, known as
the TGF-B signaling pathway, takes place when one or more TGF-B superfamily ligands
bind to a type II receptor, in turn phosphorylating a type I receptor. The phosphorylated
type I receptor itself phosphorylates complexes SMAD2, SMAD3 and SMAD4, which
accumulate in the nucleus, acting as transcription factors for the regulation of speciﬁc
gene expression in the cell. When functioning normally, TGF-B decreases the likelihood
of cell proliferation in all forms, most importantly cancer cells. Recent research has
indicated that development of cancerous intestinal epithelial cells can be attributed to the
loss of growth-inhibiting response to TGF-B due to one or more of three possible
pathways: 1) the cancerous cells have lost expression of TGF-B receptors entirely, 2) the
cells may only express a nonsignaling TGF-B receptor, or 3) the postreceptor signal-
transducing mechanism in the cell may be defective [107].

Multiple studies of inactivating mutations in the TGF-B ligands, the TGF-B
receptor, SMAD2 or SMAD4 complexes resulted in either no development of colon
cancer (in heterozygous mice) or premature death Of mice in uterO or shortly after birth
(in homozygous mice); nonetheless, the function of SMAD3 was not addressed in these
studies [108]. Zhu et al. studied the potential role of SMAD3 in the development and
progression of tumors by inactivating the SMAD3 gene in homologous recombination.

As opposed to homozygous SMAD2 or SMAD4 mice, homozygous SMAD3 -/- mice

19

were found to be viable, but spontaneously presented with invasive colorectal
adenocarcinomas throughout all layers of the intestinal wall that metastasized to lymph
nodes. This spontaneous tumorigenesis demonstrated a clear role of SMAD3 in the
development of nonpolypoid colorectal cancer, and provided a strong animal model for
continued research. Recent epidemiologic and genetic studies in IBD-related animal
models suggest that a combination of genetic susceptibility factors and altered immune
response driven by microbial factors in the enteric environment contributes to the
initiation and duration Of inﬂammatory bowel diseases [109]. As previously reported by
Maggio-Price et al, TGF-B dysregulation is involved in the development of colitis in
Helicobacter-infected SMAD3-/- mice as well as humans with inﬂammatory bowel
disease, conferring an increased risk for colon cancer; therefore, the induction of colon
cancer in SMAD3 -/- mice with Helicobacter is a relevant model to investigate the role of
bacteria and inﬂammation in colon cancer in humans with disrupted TGF-B signaling
[110]. The previous successes with the SMAD3-/- mouse model have established the
ability of this model to investigate the relationship of diet and body composition to

inﬂammation and the development of colon cancer.

20

Hypothesis and Speciﬁc Aims
We will use this model address the hypothesis that energy balance inﬂuences
inﬂammatory bowel disease severity and subsequent colon cancer in the SMAD3-/-
susceptible model. However, the model is poorly characterized. Therefore, we propose
the following speciﬁc aims:
1. We will characterize the model for the following parameters a) weight, body
composition and severity of colitis post-infection, and b) immune response
after infection with H. hepaticus. We will assess immune response at 0, 3, 7
and 28 days post-infection by identifying alterations in baseline immune cell
populations between SMAD3-/- and SMAD3+/- (control) mice, and
determining how these populations change throughout the course of infection.
2. We will determine the effect of energy balance on the development of colitis
and subsequent progression of colon cancer. Mice from each diet group
(calorie-restricted, control and high-fat) will be infected with H. hepaticus and
we will collect a) weight and body composition data, and b) colons and ceca
at 4, 5, and 6 weeks post-infection for histopathological analysis.
These studies may be used as a basis of research upon which to investigate effective

preventative measures against development of colon cancer.

21

10.

11.

BIBLIOGRAPHY

Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM:
Prevalence of overweight and Obesity in the United States, 1999-2004. Jama
2006, 295(13):]549-1555.

National Health and Nutrition Examination Survey 111.: National Center for Health
Statistics, CDC, http://www.cdc.gov/nchs/; 2003-2004.

WCRF/AICR: Food, Nutrition, Physical Activity, and the Prevention of Cancer: a
Global Perspective. In Washington DC; 2007.

Moayyedi P: The epidemiology of obesity and gastrointestinal and other diseases:
an overview. Dig Dis Sci 2008, 53(9):2293-2299.

Nam SY, Kim BC, Han KS, Ryu KH, Park BJ, Kim HB, Nam BH: Abdominal
visceral adipose tissue predicts risk of colorectal adenoma in both sexes. Clin
Gastroenterol Hepatol 201 O, 8(5):443-450 e441-442.

Trayhum P, Wood 1: Adipokines: inﬂammation and the pleiotropic role of white
adipose tissue. Br J Nutr 2004, 92(3):347-3 55.

Ronti T, Lupattelli G, Mannarino E: The endocrine function of adipose tissue: an
update. Clin Endocrinol (Oxf) 2006, 64(4):355-365.

Guerre-Millo M: Adipose tissue and adipokines: for better or worse. Diabetes
Metab 2004, 30(1):13-19.

Rayner D, Trayhum P: Regulation of leptin production: sympathetic nervous
system interactions. J Mol Med 2001, 79(1):8-20.

Suganami T, Ogawa Y: Adipose tissue macrophages: their role in adipose tissue
remodeling. J Leukoc Biol 2010.

Grundy SM, Brewer HB, Jr., Cleeman JI, Smith SC, Jr., Lenfant C: Deﬁnition of
metabolic syndrome: report of the National Heart, Lung, and Blood

22

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

Institute/American Heart Association conference on scientiﬁc issues related to
deﬁnition. Arterioscler Thromb Vasc Biol 2004, 24(2):e1 3-1 8.

Vainio H, Bianchini F: IARC handbooks of cancer prevention. Volume 6: Weight
control and physical activity., vol. 6. Lyon, France: IARC Press; 2002.

Inadera H: The usefulness of circulating adipokine levels for the assessment of
Obesity-related health problems. Int J Med Sci 2008, 5(5):248-262.

Kahn B, Flier J: Obesity and insulin resistance. J Clin Invest 2000, 106(4):473-
481.

Hursting S, Lashinger L, Wheatley K, Rogers C, Colbert L, Nunez N, Perkins S:
Reducing the weight of cancer: mechanistic targets for breaking the obesity-
carcinogenesis link. Best Pract Res Clin Endocrinol Metab 2008, 22(4):659-669.

Boyd D: Insulin and cancer. Integr Cancer T her 2003, 2(4):315-329.

LeROith D, Bondy C: Insulin-like growth factors. In: Growth Factors and
Cytokines in Health and Disease. Edited by Derek L, Carolyn B, vol. Volume 1,
Part 1: JAI; 1996: 1-26.

Moschos SJ, Mantzoros CS: The role of the IGF system in cancer: from basic to
clinical studies and clinical applications. Oncology 2002, 63(4):317-332.

Samani A, Yakar S, LeRoith D, Brodt P: The role of the IGF system in cancer
growth and metastasis: overview and recent insights. Endocr Rev 2007, 28(1):20-
47. Epub 2006 Aug 2024.

Hakam A, Yeatman TJ, Lu L, Mora L, Marcet G, Nicosia SV, Karl RC, Coppola
D: Expression of insulin-like growth factor-1 receptor in human colorectal cancer.
Hum Pathol 1999, 30(10):1 128-1133.

Jiang Y, Wang L, Gong W, Wei D, Le X, Yao J, Ajani J, Abbruzzese J, Huang S,
Xie K: A high expression level of insulin-like growth factor I receptor is
associated with increased expression of transcription factor Spl and regional

lymph node metastasis of human gastric cancer. Clin Exp Metastasis 2004,
21(8):755-764.

23

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

Komprat P, Rehak P, Ruschoff J, Langrrer C: Expression of IGF—I, IGF-II, and
IGF-IR in gallbladder carcinoma. A systematic analysis including primary and
corresponding metastatic tumours. J Clin Pathol 2006, 59(2):202-206.

Xie Y, Skytting B, Nilsson G, Brodin B, Larsson 0: Expression of insulin-like
growth factor-1 receptor in synovial sarcoma: association with an aggressive
phenotype. Cancer Res 1999, 59(15):3588-3591.

All-Ericsson C, Gimita L, Seregard S, Bartolazzi A, Jager M, Larsson O: Insulin-
like growth factor-1 receptor in uveal melanoma: a predictor for metastatic
disease and a potential therapeutic target. Invest Ophthalmol Vis Sci 2002,

43(1):1-8.

Aloulou N, Bastuji-Garin S, Le Gouvello S, Abolhassani M, Chaumette M,
Charachon A, Leroy K, Sobharri I: Involvement of the leptin receptor in the
immune response in intestinal cancer. Cancer Res 2008, 68(22):9413-9422.

Huang L, Li C: Leptin: a multifunctional hormone. Cell Res 2000, 10(2):81-92.

Mark A, Correia M, Rahmouni K, Haynes W: Loss of leptin actions in obesity:
two concepts with cardiovascular implications. Clin Exp Hypertens 2004, 26(7-
8):629-636.

Garofalo C, Sunnacz E: Leptin and cancer. J Cell Physiol 2006, 207(1):12-22.

Cao R, Brakenhielrn E, Wahlestedt C, Thyberg J, Cao Y: Leptin induces vascular
permeability and synergistically stimulates angiogenesis with FGF-2 and VEGF.
Proc Natl Acad Sci U S A 2001, 98(11):6390-6395. Epub 2001 May 6398.

Artwohl M, Roden M, Holzenbein T, Freudenthaler A, Waldhausl W,
Baumgartner-Parzer S: Modulation by leptin of proliferation and apoptosis in
vascular endothelial cells. Int J Obes Relat Metab Disord 2002, 26(4):577-580.

Fenton J I, Hord NG, Lavigrre JA, Perkins SN, Hursting SD: Leptin, insulin-like
growth factor-1 , and insulin-like growth factor-2 are mitogens in ApcMin/+ but

not Apc+/+ colonic epithelial cell lines. Cancer Epidemiol Biomarkers Prev 2005,
14(7):]646-1652.

24

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

Boulournie A, Drexler H, Lafontan M, Busse R: Leptin, the product of Oh gene,
promotes angiogenesis. Circ Res 1998, 83(10):1059-1066.

Moharned-Ali V, Goodrick S, Rawesh A, Katz D, Miles J, Yudkin J, Klein S,
Coppack S: Subcutaneous adipose tissue releases interleukin-6, but not tumor
necrosis factor-alpha, in vivo. J Clin Endocrinol Metab 1997, 82(12):4196-4200.

Greenstein AS, Khavandi K, Withers SB, Sonoyama K, Clancy O, J eziorska M,
Laing I, Yates AP, Pemberton PW, Malik RA et a]: Local inﬂammation and
hypoxia abolish the protective anticontractile properties of perivascular fat in
obese patients. Circulation 2009, l 19(12):1661-1670.

Kim J, Bachmann R, Chen J: Interleukin-6 and insulin resistance. Vitam Harm
2009, 80:613-633.

Park H, Park J, Yu R: Relationship of obesity and visceral adiposity with serum
concentrations of CRP, TNF-alpha and IL-6. Diabetes Res Clin Pract 2005,
69(1):29-35. Epub 2004 Dec 2030.

Akira S: Roles of STAT3 deﬁned by tissue-speciﬁc gene targeting. Oncogene
2000, 19(21):2607-261 1.

Syed V, Ulinski G, Mok SC, Ho SM: Reproductive horrnone-induced, STAT3-
mediated interleukin 6 action in normal and malignant human ovarian surface
epithelial cells. J Natl Cancer Inst 2002, 94(8):617-629.

Sriuranpong V, Park J I, Amomphirnoltharn P, Patel V, Nelkin BD, Gutkind J S:
Epidermal growth factor receptor-independent constitutive activation of STAT3
in head and neck squamous cell carcinoma is mediated by the autocrine/paracrine
stimulation of the interleukin 6/gpl30 cytokine system. Cancer Res 2003,

63(1 1):2948-2956.

Giri D, Ozen M, Ittrnann M: Interleukin-6 is an autocrine growth factor in human
prostate cancer. Am J Pathol 2001, 159(6):2159-2165.

Li YY, Hsieh LL, Tang RP, Liao SK, Yeh KY: Interleukin-6 (IL-6) released by
macrophages induces IL-6 secretion in the human colon cancer HT-29 cell line.
Hum Immunol 2009, 70(3): 151-158.

25

42.

43.

45.

46.

47.

48.

49.

50.

51.

Tempfer C, Zeisler H, Sliutz G, Haeusler G, Hanzal E, Kainz C: Serum evaluation
of interleukin 6 in ovarian cancer patients. Gynecol Oncol 1997, 66(1):27-30.

Yokoe T, Iino Y, Takei H, Horiguchi J, Koibuchi Y, Maemura M, Ohwada S,
Morishita Y: Changes of cytokines and thyroid function in patients with recurrent
breast cancer. Anticancer Res 1997, 17(1B):695-699.

Goydos J, Brumﬁeld A, Frezza E, Booth A, Lotze M, Carty S: Marked elevation
of serum interleukin-6 in patients with cholangiocarcinoma: validation of utility
as a clinical marker. Ann Surg 1998, 227(3):398-404.

Preti H, Cabanillas F, Talpaz M, Tucker S, Seymour J, Kurzrock R: Prognostic
value of serum interleukin-6 in diffuse large-cell lymphoma. Ann Intern Med
1997, 127(3):186-194.

Dowlati A, Levitan N, Remick S: Evaluation of interleukin-6 in bronchoalveolar
lavage ﬂuid and serum of patients with lung cancer. J Lab Clin Med 1999,
134(4):405-409.

Mouawad R, Benharnmouda A, Rixe 0, Antoine E, Borel C, Wei] M, Khayat D,
Soubrane C: Endogenous interleukin 6 levels in patients with metastatic

malignant melanoma: correlation with tumor burden. Clin Cancer Res 1996,
2(8): 1405-1409.

Wierzbowska A, Urbanska-Rys H, Robak T: Circulating IL-6-type cytokines and
sIL-6R in patients with multiple myeloma. Br J Haematol 1999, 105(2):412-419.

Okada S, Okusaka T, Ishii H, Kyogoku A, Yoshimori M, Kajirnura N, Yamaguchi
K, Kakizoe T: Elevated serum interleukin-6 levels in patients with pancreatic
cancer. Jpn J Clin Oncol 1998, 28(1):]2-15.

Nakashima J, Tachibana M, Horiguchi Y, Oya M, Ohigashi T, Asakura H, Murai
M: Serum interleukin 6 as a prognostic factor in patients with prostate cancer.
Clin Cancer Res 2000, 6(7):2702-2706.

Blay J, Rossi J, Wijdenes J, Menetrier-Caux C, Schemann S, Negrier S, Philip T,
Favrot M: Role of interleukin-6 in the paraneoplastic inﬂammatory syndrome
associated with renal-cell carcinoma. Int J Cancer 1997, 72(3):424-430.

26

52.

53.

54.

55.

56.

57.

58.

59.

60.

61.

Wang Q, Horiatis D, Pinski J: Interleukin-6 inhibits the growth of prostate cancer
xenograﬁs in mice by the process of neuroendocrine differentiation. Int J Cancer
2004, 111(4):508-513.

Poppenborg H, Knupfer M, Galla H, Wolff J: In vitro modulation of cisplatin
resistance by cytokines. Cytokine 1999, 1 1(9):689-695.

Honma S, Shimodaira K, Shimizu Y, Tsuchiya N, Saito H, Yanaihara T, Okai T:
The inﬂuence of inﬂammatory cytokines on estrogen production and cell
proliferation in human breast cancer cells. Endocr J 2002, 49(3):371-3 77.

Beltowski J: Adiponectin and resistin--new hormones of white adipose tissue.
Med Sci Monit 2003, 9(2):RA55-61.

Plaisance E, Grandjean P, Brunson B, Judd R: Increased total and high—molecular
weight adiponectin after extended-release niacin. Metabolism 2008, 57(3):404-
409.

Yarnauclri T, Karnon J, Waki H, Terauchi Y, Kubota N, Hara K, Mori Y, Ide T,
Murakarrri K, Tsuboyama-Kasaoka N et al: The fat-derived hormone adiponectin
reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med
2001, 7(8):941-946.

Hu E, Liang P, Spiegelman BM: AdipoQ is a novel adipose-speciﬁc gene
dysregulated in obesity. J Biol Chem 1996, 271(18): 10697-10703.

Kelesidis I, Kelesidis T, Mantzoros CS: Adiponectin and cancer: a systematic
review. Br J Cancer 2006, 94(9):]221-1225.

Yokota T, Oritarri K, Takahashi I, Ishikawa J, Matsuyarna A, Ouchi N, Kihara S,
F unahashi T, Tenner AJ, Torrriyarna Y et al: Adiponectin, a new member of the
family of soluble defense collagens, negatively regulates the growth of
myelomonocytic progenitors and the functions of macrophages. Blood 2000,
96(5):]723-1732.

Goldstein BJ, Scalia R: Adiponectin: A novel adipokine linking adipocytes and
vascular function. J Clin Endocrinol Metab 2004, 89(6):2563-2568.

27

62.

63.

65.

66.

67.

68.

69.

70.

71.

72.

Brakenhielrn E, Veitonmaki N, Cao R, Kihara S, Matsuzawa Y, Zhivotovsky B,
Funahashi T, Cao Y: Adiponectin-induced antiangiogenesis and antitumor
activity involve caspase-mediated endothelial cell apoptosis. Proc Natl Acad Sci
U S A 2004, 101(8):2476-2481.

Wang Y, Lam KS, Xu JY, Lu G, Xu LY, Cooper GJ, Xu A: Adiponectin inhibits
cell proliferation by interacting with several grth factors in an oligomerization-
dependent manner. J Biol Chem 2005, 280(18):] 8341-18347.

Calle EE, Kaaks R: Overweight, obesity and cancer: epidemiological evidence
and proposed mechanisms. Nat Rev Cancer 2004, 4(8):579-591.

Altekruse S, Kosary C, Krapcho M, Neyman N, Aminou R, Waldron W, Ruhl J,
Howlader N, Tatalovich Z, Cho H et al: SEER Cancer Statistics Review 1975-
2007 . In Bethesda, MD: National Cancer Institute; 2010.

Keys A, Menotti A, Karvonen MJ, Aravanis C, Blackburn H, Buzina R,
Djordjevic BS, Dontas AS, Fidanza F, Keys MH et al: The diet and 15-year death
rate in the seven countries study. Am J Epidemiol 1986, 124(6):903-915.

Kune S, Kune GA, Watson L: The Melbourne colorectal cancer study: incidence
ﬁndings by age, sex, site, rrrigrants and religion. Int J Epidemiol 1986, 15(4):483-
493.

Boyle P, Langrnan J S: ABC of colorectal cancer: Epidemiology. ij 2000,
321(7264):805-808.

Singh P, Fraser G: Dietary risk factors for colon cancer in a low-risk population.
Am J Epidemiol 1998, 148(8):761-774.

Park Y, Hunter D, Spiegelman D, Bergkvist L, Berrino F, van den Brandt P,
Buring J, Colditz G, Freudenheirn J, Fuchs C et al: Dietary ﬁber intake and risk of

colorectal cancer: a pooled analysis of prospective cohort studies. JAMA 2005,
294(22):2849-2857.

Livstone E: Colorectal Cancer. In: Merck Manuals. 2008.

Gordon PH NS: Principles and Practice of Surgery for the Colon, Rectum and
Anus, 2nd edn. New York, NY: Inforrna Health Care; 2007.

28

73.

74.

75.

76.

77.

78.

79.

80.

81.

82.

83.

Fearon ER, Vogelstein B: A genetic model for colorectal tumorigenesis. Cell
1990, 61(5):759-767.

Arends J: Molecular interactions in the Vogelstein model of colorectal carcinoma.
J Pathol 2000, 190(4):412-416.

Keino-Masu K, Masu M, Hinck L, Leonardo E, Chan S, Culotti J, Tessier-
Lavigne M: Deleted in Colorectal Cancer (DCC) encodes a netrin receptor. Cell
1996, 87(2):]75-185.

Silva F C, Valentin Nﬂ), Ferreira F de 0, Carraro DM, Rossi BM: Mismatch repair
genes in Lynch syndrome: a review. Sao Paulo Med J 2009, 127(1):46-51.

Eaden JA, Abrams KR, Mayberry J F : The risk of colorectal cancer in ulcerative
colitis: a meta-analysis. Gut 2001, 48(4):526-535.

Monteleone I, Pallone F, Monteleone G: Interleukin-23 and Thl7 cells in the
control of gut inﬂammation. Mediators Inflamm 20092297645.

Yeung MM, Melgar S, Baranov V, Oberg A, Danielsson A, Hammarstrom S,
Hammarstrom ML: Characterisation of mucosal lymphoid aggregates in
ulcerative colitis: immune cell phenotype and TcR-gammadelta expression. Gut
2000, 47(2):215-227.

Tlaskalova-Hogenova H, Tuckova L, Stepankova R, Hudcovic T, Palova-

J elinkova L, Kozakova H, Rossmann P, Sanchez D, Cinova J, Hmcir T et al:
Involvement of innate immunity in the development of inﬂammatory and
autoimmune diseases. Ann N Y Acad Sci 2005, 1051 :787-798.

Dunn GP, Bruce AT, Ikeda H, Old LJ, Schreiber RD: Cancer irnmunoediting:
from immunosurveillance to tumor escape. Nat Immunol 2002, 3(11):991-998.

Murakami H, Akbar SM, Matsui H, Onji M: Macrophage migration inhibitory
factor in the sera and at the colonic mucosa in patients with ulcerative colitis:
clinical implications and pathogenic signiﬁcance. Eur J Clin Invest 2001,
31(4):337-343.

Kindt T, Goldsby R, Osborne B: Kuby Immunology, 6th edn. New York: W.H.
Freeman; 2006.

29

84.

85.

86.

87.

88.

89.

90.

91.

92.

93.

Manzano L, Alvarez-Mon M, Abreu L, Antonio Vargas J, de la Morena E,
Corugedo F, Durantez A: Functional impairment of natural killer cells in active
ulcerative colitis: reversion of the defective natural killer activity by interleukin 2.

Gut 1992, 33(2):246-251.

Baumgart D, Carding S: Inﬂammatory bowel disease: cause and irnmunobiology.
Lancet 2007 , 369(9573): 1627-1640.

Cella M, Fuchs A, Vermi W, Facchetti F, Otero K, Lennerz J, Doherty J, Mills J,
Colonna M: A human natural killer cell subset provides an innate source of IL-22
for mucosal immunity. Nature 2009, 457(7230):722-725. Epub 2008 Nov 2002.

Sanos S, Bui V, Mortha A, Oberle K, Heners C, Johner C, Diefenbach A:
RORgammat and commensal microﬂora are required for the differentiation of
mucosal interleukin 22-producing NKp46+ cells. Nat Immunol 2009, 10(1):83-91.
Epub 2008 Nov 2023.

Luci C, Reynders A, Ivanov I, Cogrret C, Chiche L, Chasson L, Hardwigsen J,
Anguiano E, Banchereau J, Chaussabel D et al: Inﬂuence of the transcription
factor RORgammat on the development of NKp46+ cell populations in gut and
skin. Nat Immunol 2009, 10(1):75-82. Epub 2008 Nov 2023.

Zenewicz L, Yancopoulos G, Valenzuela D, Murphy A, Stevens S, Flavell R:
Innate and adaptive interleukin-22 protects mice from inﬂammatory bowel
disease. Immunity 2008, 29(6):947-957.

Ueyarna H, Kiyohara T, Sawada N, Isozaki K, Kitarnura S, Kondo S, Miyagawa
J, Kanayama S, Shinomura Y, Ishikawa H et al: High Fas ligand expression on
lymphocytes in lesions of ulcerative colitis. Gut 1998, 43(1):48-55.

Yonamine Y, Watanabe M, Kinjo F, Hibi T: Generation of MHC class I-restricted
cytotoxic T cell lines and clones against colonic epithelial cells from ulcerative
colitis. J Clin Immunol 1999, 19(1):77-85.

Lefrancois L, Obar JJ: Once a killer, always a killer: from cytotoxic T cell to
memory cell. Immunol Rev 2010, 23 5(1):206-21 8.

Eastaff-Leung N, Mabarrack N, Barbour A, Crunmins A, Barry S: Foxp3(+)
Regulatory T Cells, Th17 Effector Cells, and Cytokine Environment in
Inﬂammatory Bowel Disease. J Clin Immunol 2009.

30

94.

95.

96.

97.

98.

99.

100.

101.

102.

103.

Zhang L, Zhao Y: The regulation of Foxp3 expression in regulatory
CD4(+)CD25(+)T cells: multiple pathways on the road. J Cell Physiol 2007,
211(3):590—597.

Wilson NJ, Boniface K, Chan JR, McKenzie BS, Blumenschein WM, Mattson
JD, Basharn B, Smith K, Chen T, Morel F et al: Development, cytokine proﬁle
and function of human interleukin 17-producing helper T cells. Nat Immunol
2007, 8(9):950—957.

Bamias G, Cominelli F: Immunopathogenesis of inﬂammatory bowel disease:
current concepts. Curr Opin Gastroenter012007, 23(4):365-369.

Veldhoen M, Hocking RJ, Atkins CJ, Locksley RM, Stockinger B: TGFbeta in
the context of an inﬂammatory cytokine milieu supports de novo differentiation
ofIL-17-producing T cells. Immunity 2006, 24(2): 179-1 89.

Acosta-Rodriguez EV, Napolitani G, Lanzavecchia A, Sallusto F: Interleukins
lbeta and 6 but not transforming growth factor-beta are essential for the

differentiation of interleukin 17-producing human T helper cells. Nat Immunol
2007, 8(9):942-949.

Sutton CE, Lalor SJ, Sweeney CM, Brereton CF, Lavelle EC, Mills KH:
Interleukin-1 and IL-23 induce innate IL-17 production from garnmadelta T cells,
amplifying Th17 responses and autoimmunity. Immunity 2009, 31(2):331-341.

Soetikno R, Kaltenbach T, Rouse R, Park W, Maheshwari A, Sato T, Matsui S,
Friedland S: Prevalence of nonpolypoid (ﬂat and depressed) colorectal neoplasms
in asymptomatic and symptomatic adults. JAMA 2008, 299(9):1027-1035.

Kumar V AA, F austo N: Robbins & Cotran Pathological Basis of Disease. In, 7th
edn: Saunders; 2004.

Burt R: Inheritance of Colorectal Cancer. Drug Discov Today Dis Mech 2007,
4(4):293-300.

Gund S: Colon Cancer. In: MedlinePlus Medical EnLyCIOpedia. NIH; 2008.

31

104.

105.

106.

107.

108.

109.

110.

Korff S, Woemer S, Yuan Y, Bork P, von Knebel Doeberitz M, Gebert J:
Frameshift mutations in coding repeats of protein tyrosine phosphatase genes in
colorectal tumors with microsatellite instability. BMC Cancer 2008, 8:329.

Grady WM, Carethers JM: Genomic and epi genetic instability in colorectal
cancer pathogenesis. Gastroenterology 2008, 135(4): 1079-1099.

Munoz N, Baek J, Grady W: TGF—beta has paradoxical and context dependent
effects on proliferation and anoikis in human colorectal cancer cell lines. Growth
Factors 2008, 26(5):254-262.

MacKay S, Yaswen L, Tarnuzzer R, Moldawer L, Bland KI, Copeland Er, Schultz
G: Colon cancer cells that are not growth inhibited by TGF—beta lack functional
type I and type II TGF-beta receptors. Ann Surg 1995, 221(6):767-776; discussion
776-767.

Zhu Y, Richardson JA, Parada LF, Graff J M: Smad3 mutant mice develop
metastatic colorectal cancer. Cell 1998, 94(6):703-714.

Wirtz S, Neufert C, Weigrnann B, Neurath MF: Chemically induced mouse
models of intestinal inﬂammation. Nat Protoc 2007, 2(3):541-546.

Maggio-Price L, Treuting P, Zeng W, Tsang M, Bielefeldt-Ohmann H, Iritani
BM: Helicobacter infection is required for inﬂammation and colon cancer in
SMAD3-deﬁcient mice. Cancer Res 2006, 66(2):828-838.

32

Chapter 2 - Identification of kinetic and tissue-specific changes in natural killer cell
and T cell populations during Helicobacter hepaticus infection in SMAD3-l- mice
Introduction

Individuals with inﬂammatory bowel disease (IBD), particularly ulcerative colitis
(UC), are at a higher risk of developing colon cancer than the general population [1]. A
meta-analysis ﬁ'om 116 studies indicated that the prevalence of colon cancer in patients
with UC is approximately 3.7% (95% CI 3.2—4.2, p<0.0001), with the cumulative
probability reaching 18% by 30 years regardless of disease severity [2]. Although the
etiology of ulcerative colitis is poorly understood, there are indications that the immune
system of individuals with UC react abnormally to bacteria in the digestive tract. This
altered immune response is important in the pathogenesis of IBD and of dysplastic
epithelial changes leading to tumor development [3-5].

Irnbalances in both innate and adaptive immune cells, such as natural killer cells

(N K) and T cell subsets, including CD4+ T helper (T H), T regulatory (Treg) cells and

CD8+ cytotoxic (TC) cells, are associated with UC [2]. The inﬂammation and damage

caused by increased secretion of inﬂammatory cytokines during an active disease state is
thought to be triggered by false recognition and processing of the natural gut commensal
bacteria by NK cells [6]. The levels of NK cytotoxicity in UC are related to the clinical
activity of the disease [7]. In active disease states, NK cells are present in normal
numbers, but are functionally defective, whereas NK cells exhibit normal cytotoxic

activity in an inactive disease state [7]. Induction of inﬂammatory cytokines can also

result ﬁ'om the disruption of the homeostatic balance between Treg and effector TH cells.

33

Elevated levels of proinﬂammatory CD4+ T cells lead to excess cytokine/chemokine

production, thereby recruiting additional leukocytes and inﬂuencing the severity of the

inﬂammatory response [2]. Under normal conditions, Treg cells differentiate in the

Peyer’s patches (PP) and mesenteric lymph nodes (MsLN) via action of the cytokine

transforming growth factor B (TGF-ﬁ). Defects in the TGF-B pathway affect the

development and/or function of Treg cells resulting in intestinal inﬂammation in mice [2,
8]. TC cells are also important in the pathogenesis of UC in humans, as evidenced by

extensive TC cell inﬁltration within intestinal lesions contributing to mucosal damage [9,

10].

The SMAD3-/- mouse model was recently developed as an animal model of
human UC due to similar histological and immune cell changes present during the course
of colitis [ll-14]. In previous studies, the absence of SMAD3 caused a signiﬁcant

reduction in the ability of TGF-B to induce expression of Forkhead box P3 (FoxP3) on

naive T cells, which is required for the development and function of Treg cells [15].

However, there is currently insufﬁcient data describing changes in immune cell
populations during the course of infection or between infection-prone (SMAD3 -/-) and
resistant (SMAD3+/-) mice. Understanding differential responses to infection may lead
to future targets for treating human disease. Therefore, the current study was conducted
to characterize SMAD3-dependent alterations in immune cell populations (T, B and NK

cells) at baseline and throughout the course of infection with Helicobacter hepaticus.

34

Materials and Methods
Murine model

SMAD3+/- and SMAD3-/- breeder pairs of 129Sva background were
generously donated by Dr. Lillian Maggio-Price at the University of Washington.
Homozygous males and heterozygous females were mated to obtain SMAD3-/- pups.
Genotypes were conﬁrmed by PCR. Animals were housed under speciﬁc pathogen-free
conditions in 60 square inch plastic cages (maximum of 5 adult mice per cage) with
microisolator lids in an AAALAC approved facility at Michigan State University.
Animal rooms were maintained at 23.3i2.2°C with a 12-hour light-dark cycle. Mice were
fed Harlan Teklad 7913 rodent chow and sterile water ad libitum. Animal protocols were
approved by the Michigan State University Institutional Animal Care and Use
Committee.
Bacterial culture and infection.

The wild-type H. hepaticus strain 3B1 (ATCC 51488) was kindly donated by Dr.

Vince Young at the University of Michigan. Isolates were aseptically streaked onto

sheep blood agar and incubated at 36°C for 24-48 hrs inside GasPakTM gas generating

pouch systems (BD Diagnostic Systems, Sparks, MD). Mice were infected as previously
described [12]. Brieﬂy, bacteria were collected and resuspended in tryptic soy broth at an
optical density 2 1.8 (600nm wavelength). Animals were then gavaged with 0.3 mL
dosages of fresh bacterial suspension on two consecutive days.
Experimental Design.

In study 1, SMAD3-/- mice (n = 50) at 8-10 weeks of age were infected with H.

hepaticus to determine onset and duration of colitis. Colons and ceca were collected and

35

processed for histOpathology at 2, 3, 4, 5, 6, 7, and 8 wks post infection. In study 2,
SMAD3+/- (n = 24) and -/- mice (n = 19) at 8-10 weeks Of age were infected with H.
hepaticus. Weights (g) were taken daily and body composition was assessed at days 0, 3,
7, 14, 21 and 28. Spleen, PP and MsLN were collected at sacriﬁce at day 28 post-
infection and processed for lymphocyte isolation as described below. Colons and ceca
were collected and regularly processed for histopathology.

Body composition.

Body composition was analyzed using an EchoMRI-IOOTM quantitative nuclear

magnetic resonance machine (Echo Medical Systems, Houston, TX).
T issue ﬁxation and histopathology.

At the time of necropsy, rrrice were asphyxiated with CO2 and exsanguinated via
cardiac puncture. Intact colons and ceca were removed and ﬂushed with PBS. Tissues
were ﬁxed in 10% formalin overnight, embedded in parafﬁn, then sectioned and stained
with hematoxylin and eosin (H&E). Longitudinal sections were graded for inﬂammation
and dysplasia by pathologist using a blinded scoring system adapted from Dr. Maggio-
Price [16]. Ceca and colons were scored on a 1 to 4 scale both for inﬂammation (1, no
inﬂammation; 2, mild inﬂammation; 3, moderate inﬂammation; 4, marked inﬂammation)
and dysplasia (1, no dysplasia; 2, low grade dysplasia; 3, high grade dysplasia; 4, high
grade dysplasia with invasion/adenocarcinoma). The two scores for colon and two scores
for cecum tissue in each animal were combined such that a score of 4 indicated no
inﬂammation or dysplasia and a score of 16 reﬂected maximal inﬂammation and

neOplasia.

36

Lymphocyte isolation.

Spleens, PP and MsLN were removed and placed in ice cold RPMI at the time of
necropsy. Spleens were processed with a dounce homogenizer, pelleted, and washed in
RPMI. Cells were resuspended in ACK lysing buffer (Invitrogen, Carlsbad, CA) and
washed twice in RPMI. PP were treated with 5 mL enzymatic digest (5% FBS,
0.5mg/mL collagenase, 0.05mg/mL DNase I) for 30 minutes at 37°C. PP and MsLN
were passed through a 70 um ﬁlter and washed with RPMI. Cell counts were performed
with a hernocytometer using trypan blue exclusion and resuspended to a concentration of
one million cells per mL Of media.

Flow cytometry.

Lymphocytes were resuspended in FACS buffer (0.1% sodium azide, 1% PBS, in
dPBS) blocked with anti-Fe receptor yII/III [CDl6/CD32 (puriﬁed from clone 2.4G2
hybridoma, ATCC, Manassas, VA)] for 10 min on ice, and subsequently incubated with
combinations of the following ﬂuorochrome-conjugated antibodies (E-bioscience, San
Diego, CA; or BD Bioscience, San José, CA) at concentrations ranging from 1:100 to
1:300 in FACS buffer: CD3 (PerCP-Cy5.5), CD4 (eFluor450), CD8 (PE-Cy7), CD25
(PE), FoxP3 (FITC or Alexa Fluor488), CD62 (APC), Nkp46 (FITC), DX5 (APC) and
CD19 (PerCP-Cy5.5). Cells were incubated in staining cocktails (one million cells per
cocktail) on ice in the dark for 30 min. Intracellular staining was performed using FoxP3
staining buffer set as per the manufacturer’s instructions (eBioscience). Brieﬂy, after
surface staining, cells were washed twice in FACS buffer, ﬁxed in 4% paraforrnaldehyde
for 25 min, and permeabilized for 30 min. Perrneabilization was followed by incubation

for 30 min with the appropriate antibodies diluted in permeabilization diluent. Samples

37

were then acquired on a LSR 11 (BD Bioscience) and analyzed using FlowJo software
(Tree Star Inc., Ashland, OR).
Statistics.

Data analysis was performed using GraphPad Prism (GraphPad Software, La
Jolla, CA). Data were represented as mean :1: SEM unless otherwise noted. Two-way
AN OVA was performed with Bonferroni's Multiple Comparison Test to determine
differences between two groups within a parameter unless noted otherwise. P values <
0.05 were considered signiﬁcant.

Results
Weight and body fat percentage change throughout course of infection.

SMAD3-/- mice weighed less than aged-matched heterozygous mice (SMAD3+/-)
at the beginning of the study (16.4 :1: 1.7g versus 24.6 i 2.1g, respectively). These
differences remained signiﬁcant during the course of infection with H. hepaticus
(P<0.05; Figure 2.1A). There were no signiﬁcant changes in body weights within
genotypes.

Average body fat percentages of SMAD3-/- mice were signiﬁcantly lower than
heterozygous mice at days 14, 21 and 28 after infection (Figure 2.1B). By day 28,
control and infected SMAD3-l- mice lost body fat (-4% d: 5% and -2% :h 2%,
respectively) compared to baseline values. No changes in percent body fat were observed
in uninfected SMAD3+/- mice whereas SMAD3 +/- mice regained body fat by 28 days

following infection (Figure 2.13).

38

Histological scoring of colitis and dysplasia.

Histopathology scores in infected SMAD3-/- mice (Figure 2.1C) were
dramatically increased at week 4 post-infection, with an average colitis score of 7.5 i
0.49. This value was signiﬁcant compared to samples taken at all other time points;
colitis scores returned to baseline values in SMAD3-l- mice by 8 weeks post-infection.
No signiﬁcant changes in colitis or dysplasia scores were observed in SMAD3+/- mice at
any time point (data not shown).

Differences in lymphocyte populations between SAIAD3-l- and SMAD3+/- mice at
baseline (pm-infection).

B cell percentages were similar between SMAD3-/- and SMAD3+/- mice at
baseline in all tissues examined (Table 2.1). However, when calculated based upon the

number of live cells, B cell numbers differed signiﬁcantly between genotypes (P<0.05).

SMAD3-l- had average B cell numbers of 1.8 i 0.4x104, 1.6 i 0.2x104, and 1.5 :i:
0.1x104, compared to heterozygote values of 2.1 i 1.2x107, 2.7 i 1.7x106, and 1.9 :l:

1.3x106 in the spleen, MsLN, and PP, respectively (data not shown). The percentage of

natural killer (NK) cells in the lymphocyte populations from all three tissues were
signiﬁcantly lower at baseline in SMAD3-/- compared to heterozygous mice in all three

tissues (Table 2.1). However, the total numbers of NK cells were reduced in only the

spleen of SMAD3-/- mice compared to heterozygous mice (2.1 d: 0.4x105 vs 5.0 :L-

1.0x105, data not shown).

There were no signiﬁcant differences between the two genotypes in percentages

of CD3+ T cells in spleens at baseline (Table 2.1). The percentage of CD3+ T cells in

39

both MsLN and PP of SMAD3-l- mice were signiﬁcantly lower than SMAD3+/- mice at
baseline. However, there were no differences in total number of T cells in any of the
tissues analyzed (data not shown). SMAD3-/- mice had higher percentages of
CD4+/CD3+ T cells in spleens at baseline compared with SMAD3+/- mice (Table 2.1).
There was no signiﬁcant difference in percentages of CD8+/CD3+ T cells between
genotypes in any tissue. Differences in CD3+ T cell subset populations at baseline in
MsLN and PP were not statistically signiﬁcant (Table 2.1).

Lymphocyte population changes in SMAD3-ﬂ and SAMD3+/- mice following infection
with H. hepaticus.

There were no signiﬁcant differences in B cell populations of spleen, MsLN or PP
between SMAD3-/- and SMAD3+/- mice during the course of infection. In all three
tissues, signiﬁcant differences (P<0.05) in the percentage of NK cells were observed
between genotypes during at least one of the four time points in the study (Figure 2.2).
While the percentage of NK cells in the spleens of SMAD3+/- mice were signiﬁcantly
greater at days 3 and 28 post-infection (Figure 2.2A), the total number of NK cells was
signiﬁcantly higher only on day 28 (Figure 2.28). By comparison, the percentages of
NK cells in SMAD3-/- mice were signiﬁcantly lower on day 3 compared to all other time
points. In MsLN, SMAD3+/- mice had increased NK cell percentages at day 28
compared to SMAD3-/- mice, and decreased percentages of NK cells at days 3 and 7
within the genotype (Table 2.2); however there were no other signiﬁcant differences
related to total NK cell counts (data not shown). SMAD3-/- mice had both decreased
percentages (Table 2.2) and total numbers of NK cells (data not shown) that did not

change signiﬁcantly throughout the course of infection in MsLN. SMAD3+/- mice also

40

had greater percentages of NK cells in PP than SMAD3-/- at all time points. This was
only signiﬁcant at baseline and at day 28 post infection (Table 2.2).

CD3+ T cell population changes were not signiﬁcant in the spleen or PP (data not
shown); however, SMAD3—l- mice had signiﬁcantly reduced T cell numbers in the MsLN
at all time points during infection. Total CD3+ T cells were lower in SMAD3-/- mice

compared to SMAD3+/- at days 3, 7 and 28 (P<0.05; Figure 2.3A). There were

signiﬁcantly fewer TH cells (CD4+/CD3+) throughout infection, whereas cytotoxic T

cells (CD8+/CD3+) were only signiﬁcantly lower at days 3 and 7 (Figure 2.3B and C).
In all three tissues, the SMAD3+/- mice displayed a uniform increase in T cells and
subset populations, with a signiﬁcant peak at 7 days post-infection. Populations of T
cells in SMAD3-/- mice were largely unchanged throughout infection, increasing slightly

after infection (day 7) with no differences across time within the group.

T ,eg cell populations differ between genotypes and across time in MsLN.

Total numbers of activated Treg cells (F oxP3+/CD25+/CD4+) in the MsLN were

signiﬁcantly lower in SMAD3-/- mice than in SMAD3+/- mice at days 3 and 7 post-

infection (Figure 2.4A). There were no signiﬁcant changes in numbers of Treg cells in
SMAD3-/- mice across time, whereas total numbers of Tmg cells in SMAD3+/- were
signiﬁcantly increased at day 7. Treg populations throughout course of infection mirrored
that which was seen in overall T cell populations, in that SMAD3+/- Treg populations

increased through day 7 and decreased at day 28, whereas SMAD3-/- Treg populations

41

increased through day 7 with no further changes. Treg populations were not signiﬁcantly

different in the spleen or PP at any time point.

Expression of CD62L10 on Treg cells was signiﬁcantly higher in SMAD3+/- than

in SMAD3-/- mice throughout infection (Figure 2.4B). CD62L10+ Treg cells in

SMAD3+/- were, on average, 9.4% higher in MsLN, 13.9% higher in spleens, and 34.7%

higher in PP than in SMAD3-/- mice (data not shown). These increased percentages did

not translate into signiﬁcantly different total CD62L10+ cells in spleens or PP; however,
total CD62L10+ cells in MsLN averaged 3.2 times higher in heterozygous rrrice (Figure
2.48). Within the SMAD3+/- mice, total CD62L10+ cells were signiﬁcantly increased at

day 7 post-infection; within the SMAD3-/- mice, total CD62L10+ cells were signiﬁcantly

increased at day 28 post-infection.
Discussion

Chronic inﬂammation associated with UC causes damage to intestinal epithelial
cells and is thought to make an individual more susceptible to cancer by altering or
inactivating tumor suppressor genes and signaling pathways that inﬂuence regulation of
the cell cycle [17]. TGF-B is an important growth factor in the process of colon
tumorigenesis because it controls proliferation, differentiation, and apoptosis [18]. When
functioning normally, TGF-B decreases the likelihood of cell proliferation [19]. TGF-B
dysregulation is involved in the development of colitis in helicobacter-infected SMAD3-

/- mice as well as humans with inﬂammatory bowel disease. Therefore, SMAD3-/-

42

mouse model of colitis is highly relevant to investigate the role of bacteria and
inﬂammation in the pathogenesis of colon cancer.

In the present study, we demonstrate for the ﬁrst time signiﬁcant alterations in
NK cells, T cells and T cell subsets between SMAD3-/- and SMAD3+/- mice, both at
baseline and throughout the course of infection. The differences in lymphocyte
populations in SMAD3 -/- mice, as a percentage of total lymphocytes and total cell
number, indicate that these mice have an inherently increased susceptibility to colitis due
to a decreased ability to respond infection of H. hepaticus. Total numbers of B cells in
SMAD3+/- mice at baseline were at least 127-fold higher in PP and up to 1200-fold

higher in the spleen than in SMAD3-/- mice. B cells have been implicated in the
suppression of colitis through interaction with Treg cell subsets in other murine models of
IBD [20—24]. B cells possess a number of immunological functions, such as
irnmunoglobulin (1g) secretion, antigen presentation and cytokine production. Therefore,
B cells or products thereof may play a regulatory role in the pathogenesis of colitis, likely
via rapid removal of apoptotic cells, maintenance of epithelial barrier and/or control of

enteric bacterial colonization [20, 22]. Studies by Mizoguchi et al. indicate that B cells

directly suppress proliferation of CD4+ T cells through CD40/CD154 interactions

suggesting the existence of a novel B cell phenotype (CDldhlgh) in MsLN and colonic

lamina propria that suppresses the severity of colitis by down-regulating pro-
inﬂarnmatory cascades associated with IL-IB and IL-6 [22, 25]. In addition, Wei et al.

found that MsLN B cells contribute to immunoregulation and protect mice from CD4+ T

cell colitis through recruitrnent-of Tmg cell subsets to the site of infection [24]. Because

43

the SMAD3-/- mice in our study had such drastically reduced populations of B cells at
baseline, it is possible that these mice have an inability to respond to infection and
effectively control colitis, either from inadequate production of irnmunoglobulins and
cytokines or through reduced capacity to recruit necessary T cell subset populations.

Similar differences were observed in NK cell populations in our study. We found
that the percentage of NK cells in spleen, MsLN and PP were all signiﬁcantly reduced in
SMAD3-/- compared to SMAD3+/-, however the total NK cell numbers only differed in
the spleen. NK cells have an important role in the eradication of bacterial infections via
NK cell-derived IFN-y production, which has been demonstrated in multiple in viva
models [26-32]. Our results support ﬁndings from other murine models in which
immunosuppressed animals with depleted populations of NK cells develop colitis more
rapidly and with increased severity than controls [33, 34]. Fort et al. suggested that the
NK cells play an inhibitory role in development of colitis by lysing inﬂammatory effector
T cells via a perforin-dependent mechanism [34]. Other studies provide evidence that
NK cells are in fact an innate source of IL-22 in the colon, a cytokine that has
proinﬂammatory properties but is also proposed to protect tissues during
inﬂammation.[35-37] Taken together, these mechanisms consistent with our ﬁndings
suggest that a depleted population of NK cells at baseline may result in an inherent
inability to properly respond to bacterial infection, leading to colitis.

We were particularly interested in the differences in T cell subset populations
between SMAD3 -/- mice and controls, and how these subsets changed throughout the
course of infection. We found that the most remarkable changes in lymphocyte

populations occurred in the MsLN. All three T cell populations examined in SMAD3+/-

mice increased in number up to 7 days post-infection and returned to baseline levels by
day 28. SMAD3-/- mice did not elicit a comparable response to these T cell populations,
remaining close to baseline values throughout the course of infection. These data are
consistent with a previous study by MaggiO-Price et al., in which there was no signiﬁcant
T cell response to infection with Helicobacter in vitro, although it is important to note
that only splenic lymphocytes were assessed and that both H. hepaticus and H. bilis were
used for infection [12]. These data indicate that SMAD3-/- mice are unable to mount a

sufﬁcient T cell response to bacterial infection, either by failing to increase the total

population of T lymphocytes or, more speciﬁcally, CD4+ TH cells and CD8+ TC cells,

thus exacerbating the effect of H. hepaticus infection on colitis.

Data are lacking regarding immune cell population changes throughout the course
of H. hepaticus infection and colitis in SMAD3-/- mice. Wang et al. investigated the
changes of lymphocyte subpopulations, particularly CD4+/CD25+ T regulatory cells in
SMAD3-/- mice. They reported signiﬁcantly reduced levels of B cells in peripheral
blood and spleen, as well as decreased population of CD8+ T cells in the thymus,
compared to SMAD3+/+ littermate controls [13]. Our ﬁndings are somewhat consistent
with this study, in that we also showed signiﬁcantly decreased populations of B cells in
SMAD3-/- mice at baseline as well as increased CD4+/CD25+ T cells. However, we did
not ﬁnd similar effects on T cell subsets through the course of infection, nor did Wang et
al. observe any differences in MsLN, which was the site of most signiﬁcant population
differences in our study. The inconsistent ﬁndings between studies may reﬂect
differences in experimental design: we compared SMAD3-/- to SMAD3+/- mice rather

than wild type controls and we did not examine lymphocyte changes in blood or thymus

45

tissues. Furthermore, Wang et al. described the CD4+/CD25+ T cell subset population as

Treg cells, whereas we identiﬁed Treg cells by using intracellular expression of FoxP3+

in addition to surface expression of CD4 and CD25, which better deﬁnes this population

according to the recent literature. Treg cells serve to reduce inﬂammation during

infection, which is beneﬁcial to the host [38]. Several studies Show that depletion of Treg

cells in rodent models leads to an inﬂammatory colitis similar to human UC [39-42].

Furthermore, recent human studies have demonstrated reduced Treg populations in

patients with UC compared to controls both at baseline and during active stages of the

disease, consistent with the patterns of immune response found in our studies [43, 44].

We also examined L-selectin (CD62L) expression on Tmg cells, which is required
for the migration of Treg cells and is cleaved from the surface upon activation [45, 46].
We found that, in addition to decreased numbers of Treg cells, SMAD3-l- mice also had
signiﬁcantly decreased number of Treg cells expressing CD62L in MsLN throughout

infection. Our data suggests that absence of SMAD3 may decrease the ability of Treg

cells to migrate to lymph nodes in close proximity to the site of infection because L-
selectin is important in lymphocyte migration to MsLN and PP [46]. Future studies will
examine expression of homing receptors and on these lymphocytes and functional assays
to further elucidate any differences in immune cell migration in SMAD3-/- mice during

colitis.

46

In conclusion, we have characterized immune cell populations at baseline and
during infection with H. hepaticus, as well as changes in colitis in the SMAD3 knockout
model. We ﬁnd that the changes in immune cells across time parallel the progression of
the disease and are consistent with innate immune response to an acute infection.
hrrportantly, baseline NK cells were lower in the SMAD3-/- and are a key part of the
very early innate immune response to a pathogen, which may explain, in part, the

exacerbation of colitis in this mouse model. The combination of signiﬁcantly reduced

Treg populations and increased colitis and dysplasia scores in our model are consistent

with previous ﬁndings and underscore the importance of elucidating potential alterations
in the function of these immune cells. Our study indicates that it is imperative to
determine if the difference in the timing of changes in immune cell populations between
the SMAD3+/- vs SMAD3-/- contributes signiﬁcantly to the impaired immune response
and subsequent development of colitis in SMAD3-/- mice. Future studies will address
these questions by evaluating temporal changes along with functional changes of these
cell populations. These studies underscore the need to understand differential responses

to infection in an effort to identify ﬁrture targets for treating human disease.

47

APPENDIX

Figure 2.1.

>
or
O

+ +/- control

25 W -v +/-infected

 

Average weights (9)
N

 

 

 

 

 

 

 

 

 

 

 

0
+-/- control
-0- -/- infected
1c I I I I I I I I I I
4 7 10 13 16 19 22 25 28
B Days post-infection
25- ** ** *1:
3f . i 1 ++/— control
.3 2-. f ---------- w—ﬂ -v-+/- infected
8 r ‘i- "
n " ‘:
3,15! -- i -i +-/-control
g 10? '“ -- __ I\f '0--/-infected
< .
"o i 1'4 2? 28
Days post-infection
C.
Q10
8 9
(D 8 *
>
8’ f CON
g 7
g 6 I I
,3 5 4weeks
':E 4 5 Post infection

  

Broth2345678

Time post infection (wks)

Average weight (A) and body fat percentage (B) of SMAD3-/- and SMAD3+/- mice
throughout course of infection. (C) Average combined colitis and dysplasia scores of
control (Broth) and infected mice through 8 weeks post-infection.

48

Table 2.1. Total baseline lymphocyte cell population as percentage of live cells by
tissue and genotype, SMAD3+I- or -/-, prior to infection (MeaniSEM).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Spleen MsLN PP
Bcell +/- 55i3.9 32i1.1 57:1: 1.6
-/- 41 :1: 3.1 36 :1: 2.6 63 d: 2.3
NK cell +/- 0.8 :1: 0.02* 0.25 :1: 0.02* 0.22 :1: 0.02*
-/- 0.53 :1: 0.07 0.07 i 0.02 0.03 :1: 0.01
CD3+ +/- 33 :E 1.3 63 :1: 1.2 21 :1: 1.0
-/- 28 :1: 6.3 53 :1: 5.2* 15 :1: 1.0*
CD4+ of CD3+ +/- 52 :1: 15.0 67 i 0.8 50 :1: 2.7
-/- 63 :1: 2.5* 65 :h 2.5 57 i 1.2
CD8+ of CD3+ +/- 33 d: 0.8 29 :t 1.8 27 d: 3.6
-/- 32 :1: 1.9 31 i 2.0 25 :1: 4.8

 

* Signiﬁcant effect of genotype within each time point following infection (p<0.05)

49

 

Figure 2.2.

p

NK cell % of live cells '
OOOOOOOOOO-A—I—x

-+/-
DJ-

bl-sixrtulh'cn'cn'xlbo'tobL-xiv

Control Day3 Day? Day 28

Period post-infection

 

5 1”
Total NK cell count (x10 )
4:.

Control Day3 Day7 Day 28

Period post-infection

Total NK cell population changes throughout the course of infection in the spleen,
expressed as both (A) percentage of live cells and (B) total NK cell number.

Table 2.2. NK cell populations as percentage of live cells by tissue and genotype
through the course of infection (MeaniSD).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Control Day 3 Day 7 Day 28
genotype Mean SD Mean SD Mean SD Mean SD
MsLN +/- 0.176 0.091 0.075 0.057 0.066 0.033 0.280 0.206
-/- 0.065 0.025 0.066 0.030 0.034 0.014 0.042 0.018*
PP +/- 0.264 0.052 0.072 0.014 0.072 0.012 0.372 0.164
-/- 0.030 0.011* 0.024 0.005 0.016 0.008 0.016 0.007*

 

 

 

* Signiﬁcant effect of genotype within each time point following infection (p<0.05)

51

 

Figure 2.3.

) .

3.5-
3.0-
2.5-
2.01
1 .5-
1 .o-
0.5-
0.0-

7

- +/-
III-I-

Total CD3+ cells (x10

 

 

CON 3 day 7 day 28 day
Period post-infection

7 1”
Total CD4+ cells (x10 )

 

 

CON 3 day 7 day 28 day
Period post-infection

 

Total CDB+ cells (x10

 

CON 3 day 7 day 28 day
Period post-infection

Total T lymphocyte cell number changes in the MsLN of SMAD3+/- and -/- mice at
baseline and at 3, 7, and 28 days post infection. (A) Total CD3+ T cells. (B) Total
CD4+/CD3+ T cells. (C) Total CD8+/CD3+ T cells.

52

Figure 2.4.

A.

Total FoxP3+lCDZ5+lCD4+

 

 

CON 3 day 7 day 28 day
Period post-infection

144::

  

 

 

 

CON 3 day 7 day 28 day
Period post-infection

Total coezL lo+ of
FoxP3+lCDZ5+ICD4+ cells (x105)
.b

(A) Total FoxP3+ T regulatory lymphocyte cell number in the MsLN of SMAD3+/- and
-/- mice post infection. (B) Total F oxP3+ T regulatory cells expressing CD62L lo.

53

BIBLIOGRAPHY

Clevers H: At the crossroads of inﬂammation and cancer. Cell 2004, 118(6):671-
674.

Eaden JA, Abrams KR, Mayberry J F: The risk of colorectal cancer in ulcerative
colitis: a meta-analysis. Gut 2001, 48(4):526-535.

Monteleone I, Pallone F, Monteleone G: Interleukin-23 and Thl7 cells in the
control of gut inﬂammation. Mediators Inﬂamm 2009:297645.

Yeung MM, Melgar S, Baranov V, Oberg A, Danielsson A, Hammarstrom S,
Hammarstrom ML: Characterisation of mucosal lymphoid aggregates in
ulcerative colitis: immune cell phenotype and TcR-garnmadelta expression. Gut
2000, 47(2):215-227.

Tlaskalova-Hogenova H, Tuckova L, Stepankova R, Hudcovic T, Palova-

J elinkova L, Kozakova H, Rossmann P, Sanchez D, Cinova J, Hmcir T et al:
Involvement of innate immunity in the development of inﬂammatory and
autoimmune diseases. Ann N Y Acad Sci 2005, 1051:787-798.

Baumgart D, Carding S: Inﬂammatory bowel disease: cause and irnmunobiology.
Lancet 2007, 369(9573):]627-1640.

Manzano L, Alvarez-Mon M, Abreu L, Antonio Vargas J, de la Morena E,
Corugedo F, Durantez A: Functional impairment of natural killer cells in active
ulcerative colitis: reversion of the defective natural killer activity by interleukin 2.
Gut 1992, 33(2):246-251.

Nedjic J, Aichinger M, Emmerich J, Mizushima N, Klein L: Autophagy in thymic
epithelium shapes the T-cell repertoire and is essential for tolerance. Nature 2008,
455(721 1):396-400.

Ueyarna H, Kiyohara T, Sawada N, Isozaki K, Kitamura S, Kondo S, Miyagawa
J, Kanayama S, Shinomura Y, Ishikawa H et al: High Fas ligand expression on
lymphocytes in lesions of ulcerative colitis. Gut 1998, 43(1):48-55.

54

10.

11.

12.

l3.

14.

15.

16.

17.

18.

Yonarrrine Y, Watanabe M, Kinjo F, Hibi T: Generation of MHC cla
cytotoxic T cell lines and clones against colonic epithelial cells from
colitis. J Clin Immunol 1999, 19(1):77-85.

Zanninelli G, Vetuschi A, Sferra R, D'Angelo A, Fratticci A, Contin
Chiararnonte M, Gaudio E, Caprilli R, Latella G: Smad3 knock-outl
useful model to study intestinal ﬁbrogenesis. World J Gastroenterol
12(8):1211-1218.

Maggio-Price L, Treuting P, Zeng W, Tsang M, Bielefeldt-Ohmann
BM: Helicobacter infection is required for inﬂammation and colon l
SMAD3-deﬁcient mice. Cancer Res 2006, 66(2):828-838.

Wang ZB, Cui YF, Liu YQ, Jin W, Xu H, Jiang ZJ, Lu YX, Zhang
Dong B: Increase of CD4(+)CD25(+) T cells in Smad3(-/-) mice. VJ
Gastroenterol 2006, 12(15):2455-2458.

Martinez G, Zhang Z, Chung Y, Reynolds J, Lin X, J etten A, Feng
Smad3 Differentially Regulates the Induction of Regulatory and Inl
Cell Differentiation. Journal of Biological Chemistry 2009, 284(51'
35286.

Zhang L, Zhao Y: The regulation of Foxp3 expression in regulator:
CD4(+)CD25(+)T cells: multiple pathways on the road. J Cell Phy.
211(3):590-597.

Maggio-Price L, Bielefeldt-Ohmann H, Treuting P, Iritani BM, Zel
Tsang M, Shows D, Morrissey P, Viney J L: Dual infection with Hi
and Helicobacter hepaticus in p-glycoprotein-deﬁcient mdrl a-/- m'
colitis that progresses to dysplasia. Am J Pathol 2005, 166(6):]793

O'Connor P, Lapointe T, Beck P, Buret A: Mechanisms by which i
may increase intestinal cancer risk in inﬂammatory bowel disease.
Dis 2010.

Munoz N, Baek J, Grady W: TGF-beta has paradoxical and come)
effects on proliferation and anoikis in human colorectal cancer cel
Factors 2008, 26(5):254—262.

55

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

MacKay S, Yaswen L, Tarnuzzer R, Moldawer L, Bland KI, Copeland Er, Schultz
G: Colon cancer cells that are not growth inhibited by TGF-beta lack functional
type I and type II TGF-beta receptors. Ann Surg 1995, 221(6):767-776; discussion
776-767.

Mizoguchi A, Mizoguchi E, Bhan AK: Immune networks in animal models of
inﬂammatory bowel disease. Inﬂamm Bowel Dis 2003, 9(4):246-259.

Strober W, Ehrhardt RO: Chronic intestinal inﬂammation: an unexpected
outcome in cytokine or T cell receptor mutant mice. Cell 1993, 75(2):203-205.

Mizoguchi A, Mizoguchi E, Smith RN, Preffer F I, Bhan AK: Suppressive role of
B cells in chronic colitis of T cell receptor alpha mutant mice. J Exp Med 1997,
l86(10):1749-1756.

Davidson NJ, Leach MW, Fort MM, Thompson-Snipes L, Kuhn R, Muller W,
Berg DJ, Rennick DM: T helper cell l-type CD4+ T cells, but not B cells,
mediate colitis in interleukin 10-deﬁcient mice. J Exp Med 1996, 184(1):241-251.

Wei B, Velazquez P, Turovskaya O, Spricher K, Aranda R, Kronenberg M,
Birnbaurner L, Braun J: Mesenteric B cells centrally inhibit CD4+ T cell colitis
through interaction with regulatory T cell subsets. Proc Natl Acad Sci U S A 2005,
102(6):2010-2015.

Mizoguchi E, Mizoguchi A, Preffer FI, Bhan AK: Regulatory role of mature B
cells in a murine model of inﬂammatory bowel disease. Int Immunol 2000,
12(5):597-605.

Byme P, McGuirk P, Todryk S, Mills KH: Depletion ofNK cells results in
disseminating lethal infection with Bordetella pertussis associated with a

reduction of antigen-speciﬁc Th1 and enhancement of Th2, but not Trl cells. Eur
J Immunol 2004, 34(9):2579-2588.

Dunn PL, North RJ: Early gamma interferon production by natural killer cells is
important in defense against murine listeriosis. Infect Immun 1991, 59(9):2892-
2900.

Harty JT, Bevan MJ : Speciﬁc immunity to Listeria monocytogenes in the absence
of IFN gamma. Immunity 1995, 3(1):109-117.

56

29.

30.

31.

32.

33.

34.

35.

36.

37.

38.

Huang S, Hendriks W, Althage A, Hernmi S, Bluethmann H, Karnijo R, Vilcek J,
Zinkemagel RM, Aguet M: Immune response in mice that lack the interferon-
garnma receptor. Science 1993, 259(5102): 1742-1 745.

Le-Barillec K, Magalhaes JG, Corcuff E, Thuizat A, Sansonetti PJ, Phalipon A,
Di Santo JP: Roles for T and NK cells in the innate immune response to Shigella
ﬂexneri. J Immunol 2005, 175(3): 1 735-1 740.

Sponi R, J oller N, Albers U, Hilbi H, Oxenius A: MyD88-dependent IFN-gamma
production by NK cells is key for control of Legionella pneumophila infection. J
Immunol 2006, 176(10):6162-6171.

Way SS, Borczuk AC, Dorrrinitz R, Goldberg MB: An essential role for gamma
interferon in innate resistance to Shigella ﬂexneri infection. Infect Immun 1998,
66(4):1342-1348.

Takeda K, Dennert G: The development of autoimmunity in C57BL/6 lpr mice
correlates with the disappearance of natural killer type l-positive cells: evidence
for their suppressive action on bone marrow stem cell proliferation, B cell
irnmunoglobulin secretion, and autoimmune symptoms. J Exp Med 1993,

177(1):155-164.

Fort MM, Leach MW, Rennick DM: A role for NK cells as regulators of CD4+ T
cells in a transfer model of colitis. J Immunol 1998, 161(7):3256-3261.

Zenewicz LA, Yancopoulos GD, Valenzuela DM, Murphy AJ, Stevens S, F lavell
RA: Innate and adaptive interleukin-22 protects mice ﬁ'om inﬂammatory bowel
disease. Immunity 2008, 29(6):947-957.

Radaeva S, Sun R, Pan HN, Hong F, Gao B: Interleukin 22 (IL-22) plays a
protective role in T cell-mediated murine hepatitis: IL-22 is a survival factor for
hepatocytes via STAT3 activation. Hepatalagy 2004, 39(5):1332-1342.

Zenewicz LA, Yancopoulos GD, Valenzuela DM, Murphy AJ, Karow M, Flavell
RA: Interleukin-22 but not interleukin-17 provides protection to hepatocytes
during acute liver inﬂammation. Immunity 2007, 27(4):647-659.

Essence of harmony. Nat Immunol 2005, 6(4):325.

57

39.

40.

41.

42.

43.

45.

46.

Powrie F, Read S, Mottet C, Uhlig H, Maloy K: Control of immune pathology by
regulatory T cells. Navartis F aund Symp 2003, 252:92-98; discussion 98-105,
106-1 14.

Liu H, Hu B, Xu D, Liew FY: CD4+CD25+ regulatory T cells cure murine
colitis: the role of IL-10, TGF-beta, and CTLA4. J Immunol 2003, 171(10):5012-
501 7.

Fahlen L, Read S, Gorelik L, Hurst SD, Coffman RL, Flavell RA, Powrie F: T
cells that cannot respond to TGF-beta escape control by CD4(+)CD25(+)
regulatory T cells. J Exp Med 2005, 201(5):737-746.

Singh B, Read S, Assernan C, Malmstrom V, Mottet C, Stephens LA, Stepankova
R, Tlaskalova H, Powrie F: Control of intestinal inﬂammation by regulatory T
cells. Immunol Rev 2001, 182:190-200.

Yokoyama Y, Fukunaga K, Fukuda Y, Tozawa K, Karnikozuru K, Ohnishi K,
Kusaka T, Kosaka T, Hida N, Ohda Y et al: Demonstration of low-regulatory
CD25High+CD4+ and high-pro-inﬂammatory CD28-CD4+ T-Cell subsets in
patients with ulcerative colitis: modiﬁed by selective granulocyte and monocyte
adsorption apheresis. Dig Dis Sci 2007, 52(10):2725-2731.

Karnikozuru K, Fukunaga K, Hirota S, Hida N, Ohda Y, Yoshida K, Yokoyama
Y, Tozawa K, Kawa K, Iimuro M et al: The expression proﬁle of functional
regulatory T cells, CD4+CD25high+/forkhead box protein P3+, in patients with
ulcerative colitis during active and quiescent disease. Clin Exp Immunol 2009,
156(2):320-327.

Venturi GM, Conway RM, Steeber DA, Tedder TF: CD25+CD4+ regulatory T
cell migration requires L-selectin expression: L-selectin transcriptional regulation
balances constitutive receptor turnover. J Immunol 2007, 178(1):291-300.

Grailer J J , Kodera M, Steeber DA: L-selectin: role in regulating homeostasis and
cutaneous inﬂammation. J Dermatol Sci 2009, 56(3): 141-147.

58

Chapter 3 - Effect of energy balance on severity of colitis and dysplasia after
infection with Helicobacter hepaticus in SMAD3-l- mice.

Introduction

Obesity increases the risk of many diseases and conditions, including
cardiovascular disease, stroke, hypertension, osteoarthritis, dyslipidemia, diabetes
mellitus type 2, and also increases risk of many types of cancer [1]. Total adiposity is
associated with increased risk of cancer in the esophagus, pancreas, colon/rectum (CRC),
breast (postmenopausal), endometrium, and kidney [2]. Some associations between
obesity and cancer risk are even more pronounced when measured by waist-to-hip ratio
(a marker of visceral adiposity), particularly the risk of colorectal cancer [3-5]. A
potential connection between obesity and increased risk of cancer involves the altered
production of adipokines. Adipokines are cell-signaling peptides produced by adipose
tissue (AT) that have effects on a large number of bodily ﬁrnctions, including lipid
metabolism, inﬂarrunation, atherosclerosis, insulin resistance, vascular homeostasis,
angiogenesis and immune function [6].

AT dysregulation that occurs during obesity is characterized by an atypical
interaction between energy balance, adipocyte size and number, eXtracellular matrix
balance, vasculature and immune cell inﬁltration, which is associated with the
progression of chronic inﬂammation [7]. Several pro-inﬂammatory cytokines are
released ﬁom adipose tissue even in the absence of acute injury or inﬂammation, and
production is increased in proportion to greater AT mass; therefore, the elevated
circulating levels of these cytokines in obesity supports the characterization of Obesity as
a disorder of chronic inﬂammation [8]. In visceral AT, CD8+ cytotoxic T cells

accmnulate and cooperate with AT to recruit and induce macrophage differentiation,

59

initiating an inﬂammatory cascade [9]. Mast cells are also elevated in AT to produce
interleukin-6 (IL-6) and interferon-y (IFN-y), thereby contributing to angio genesis by

stimulating the release of proangiogenic peptides by adipocytes [10]. There is also a

decrease in proportions of anti-inﬂarnmatory T regulatory (Treg) cells compared to

proinﬂarnmatory T helper l (THl) cells in visceral AT, although it is unclear as to

whether or not this decrease is a cause or consequence of AT inﬂammation [11]. These
ﬁndings are consistent with known comorbidities of obesity associated particularly with
visceral adiposity [12-14].

Visceral adiposity is an important component of metabolic syndrome, in that it is
strongly associated with the other symptoms of the syndrome, including elevated blood
pressure, insulin resistance and dyslipidemia (increased triglycerides and decreased HDL
cholesterol) [15-17]. Obesity is also an important risk factor for colon cancer,
speciﬁcally visceral obesity, as evidenced by increased risk associated more so with
greater waist-tO-hip ratio as opposed to overall BMI [18, 19]. It is unknown as to what
impact an obesity-related proinﬂammatory state has on populations already at higher risk
for cancer due to other inﬂammatory conditions, such as inﬂammatory bowel disease
(IBD).

Individuals with IBD, particularly ulcerative colitis (UC), are at a higher risk of
developing colon cancer than the general population [20]. A meta-analysis from 116
studies indicated that the prevalence of colon cancer in patients with UC is approximately
3.7% (95% CI 3.2—4.2, p<0.0001), with the cumulative probability reaching 18% by 30
years regardless of disease severity [21]. There is currently insufﬁcient evidence to

support a causal relationship between obesity and IBD; however, the conditions share

60

similar inﬂammatory characteristics, providing a potential link between excessive
adiposity and pathogenesis of IBD.

Recent studies indicate that the constant low-grade inﬂammation associated with
excess adipose tissue, as evidenced by elevated serum levels of C-reactive protein (CRP),
IL-6 and TNF-a, may also contribute to the severity of IBD. A study of the phenotypic
characteristics of individuals with IBD who had persistently lower levels of CRP found
that these individuals also had signiﬁcantly lower body mass indices than those with
elevated CRP [22]. These data indicate a pathophysiologic triad between inﬂamed AT,
liver and the colon.

Alternative theories that link obesity with IBD inﬂammation include increased
oxidative stress and a decrease in the anti-inﬂammatory effects of insulin (e. g.
suppression of inﬂammatory markers and attenuation of cytokine stimulation of acute-
phase protein gene expression) caused by obesity-associated insulin resistance [23-26].
From an epidemiological perspective, there have been no studies to investigate a link
between increasing rates of obesity and the rising incidence of IBD, but there is some
evidence for the inﬂuence of obesity on the clinical course of IBD, indicating that obese
patients have more severe disease activity as compared to lean patients [27]. In this
study, we examine the effect of energy balance on severity of colitis and dysplasia
following infection with Helicobacter hepaticus in the SMAD3-/- mouse model of colon

cancer.

61

Materials and Methods

Mice.

Specimens of 129-Smad3ml/Par/J (referred to hereafter as SMAD3 -/-) mice were

generously donated by Lillian Maggio-Price at the University of Washington. The mouse
colony was developed by pairing SMAD3-/- males with SMAD3+/- females; breeding
cages contained one male and up to three females per breeding guidelines. Weaning and
genotyping of subsequent litters was performed as described below at approximately 21
days after birth. Those pups determined to be SMAD3 -/- were separated by sex into
cages with mice of similar age; all mice were housed in 60 square inch plastic cages with
nricroisolator lids. Standard diet for breeding pairs and weaned pups was Harlan Teklad
22/5 Rodent Diet 8640 (22% crude protein, 5% crude fat). Genotyped heterozygous
mouse pups were euthanized by C02 asphyxiation and cervical dislocation as stipulated
by the AVMA Panel on Euthanasia. All mouse procedures were approved by the
Michigan State University Institutional Animal Care and Use Comrrrittee.
Genotyping.

2 millimeter ear tissue samples were obtained and DNA extracted with

REDExtract-N-ArinM Tissue PCR Kits (Sigma-Aldrich, St. Louis, MO) according to

manufacturer’s recommendations. Four primers were used for polymerase chain
reaction: 1271 (GGA TGG TCG GCT GCA GGT GTC C) and 1272 (1‘ GT TGA AGG
CAA ACT CAC AGA GC) to recognize SMAD sequences at give a 130 bp product, and
506 (CGG CGA GGA TCT CGT CGT GAC CCA) and 507 (GCG ATA CCG TAA
AGC ACG AGG AAG) to recognize vector sequences and give a 200 bp product.

Thermal cycling of the samples was conducted with an initial denaturation at 94°C for 3

62

 

minutes, 40 cycles of denaturation-annealing-extension (respectively 20 seconds at 94°C,
30 seconds at 58°C, and 1 minute at 70°C), a ﬁnal extension of 72°C for 3 minutes, and
holding at 4°C. Ampliﬁed DNA was immediately loaded onto a 2% agarose gel and
separated via electrophoresis at 130-140V for 30-60 minutes.
Induction of lean, control and obese body weight phenotypes.

Weaned SMAD3-/- mice were randomly assigned to one of three OpenSource
diets (Research Diets Inc, New Brunswick, NJ): control (CON; formula D12450B: 20%
protein, 70% carbohydrate, 10% fat), 30% calorie-restricted (CR; formula D03020702B:
27% protein, 54% carbohydrate, 6% fat) or calorie dense (HF; formula D12492: 20%
protein, 20% carbohydrate, 60% fat). Dietary fat in the diets was composed of 9.3%
soybean oil and 90.7% lard. Three separate body weight phenotype induction studies
were conducted: Group 1 included a total of 73 mice (24 HF, 29 CON, and 20 CR);
Group 2 included 57 mice (20 HF, 18 CON, and 19 CR); Group 3 included 35 mice (16
HF and 19 CON) and excluded any CR subjects. All mice were fed ad libitum, and were
weighed weekly to assess body weight changes between each diet formula. Mice were
kept on assigned diets for a minimum of 20 weeks.
Preparation of blood agar plates.

Blood agar plates were prepared by autoclaving 500 mL of tryptic soy agar broth
to sterilize and adding 25 mL of sheep’s blood. 15 mL of the blood agar mixture was
pippetted into sterile Petri dishes and left to dry overnight in the chemical fume hood.

Prepared blood agar plates were stored at 4°C.

63

Helicobacter hepaticus culture and infection.
Isolates of H. hepaticus (strain 3B1, ATCC 51449) were kindly donated by Vince
Young at University of Michigan. Bacteria were streaked onto blood agar plates and

incubated at 36°C for 24-48 hours. Optimal environmental conditions for H. hepaticus

growth were sustained using GasPakTM gas generating pouch systems (BD, Franklin

Lakes, NJ) to produce an anaerobic atmosphere. After incubation, up to 2.5 m1 of broth
was added to each agar plate, and the broth/culture rrrixture was collected and optical
density was assessed using a Bio-Tek Synergy HT multi-mode rrricroplate reader (Bio-
Tek, Winooski, VT) to ensure adequate bacterial population (21.8 at 600nm wavelength)

Mice were gavaged with two separate 0.3mL dosages of either bacteria-free control

BactoTM Tryptic Soy Broth (BD, Franklin Lakes, NJ) or the H. hepaticus-broth mixture,

one dosage per day on two consecutive days. Continued weight monitoring was
conducted on the gavaged mice; any mice that exhibited a weight loss of >20% ﬁ'om one
week to the next was euthanized following the aforementioned procedures.

Body composition analysis.

Body composition of Group 3 mice, including total fat mass and lean tissue mass,
was analyzed using an EchoMRI-100TM quantitative nuclear magnetic resonance
machine (Echo Medical Systems, Houston, TX).

Sample collection at necropsy.
At necropsy, mice were euthanized via carbon dioxide asphyxiation. Terminal

bleeds were performed via cardiac puncture and blood was collected with a heparin-

coated syringe. Blood samples were centrifuged at 1500 xg for 15 minutes at 4°C, and

64

plasma was isolated and frozen at -80°C. The entire lower gastrointestinal tract was
isolated and removed. Ceca were incised and cleared of fecal material with ice-cold
phosphate buffered saline (PBS). Colons were similarly cleared, rinsed with PBS and
sectioned. Cecum and colon samples were placed into tissue biopsy cassettes and ﬁxed
for 24 hrs in a 10% formalin solution. Samples were then transferred to a 70% ethanol
solution and processed for histological examination and scoring of colitis and
adenocarcinomas.

Pathology.

Colon and cecum slides were scored by a blinded pathologist (Dr. Ingeborg
Langohr) for degree of colitis and dysplasia adapted ﬁ'om Dr. Maggio-Price [28]. Grades
were on a 1 to 4 scale both for inﬂammation (1, no inﬂammation; 2, mild inﬂammation;
3, moderate inﬂammation; 4, marked inﬂammation) and dysplasia (1, no dysplasia; 2,
low grade dysplasia; 3, high grade dysplasia; 4, high grade dysplasia with
invasion/adenocarcinoma). Brieﬂy, low-grade dysplasia was characterized by thickened
mucosa with branching and elongated crypts with normal epithelial differentiation
including goblet cells, maintenance of polarity, and nuclear morphology. High-grade
dysplasia was characterized by thickened mucosa with elongated, irregularly branching
glands, cytological and nuclear atypia including loss of differentiation and polarity,
bunched and enlarged nuclei, and numerous mitotic ﬁgures. The two scores for colon
and two scores for cecum tissue in each animal were combined such that a score of 4
indicated no inﬂammation or dysplasia and a score of 16 reﬂected maximal inﬂarrrrnation

and neoplasia.

65

Results
Changes in weight distribution and body fat composition between diet treatments.

Group 1 mice were kept on their respective diet treatments for longer than 20
weeks, as planned in the study design, due to insufﬁcient weight gain compared to
expected gains and a lack of signiﬁcant differentiation in weights between groups
receiving different diet treatments. HF mice in this group did have signiﬁcantly
increased body weight compared to CON and CR at week 14 and during weeks 16-27,
however no difference was observed at week 28 (Figure 3.1A). There was no difference
in weight between CON and CR diets at any point during the study. Group 2 mice were
kept on diet for 20 weeks; HF mice had signiﬁcantly higher average body weight at
weeks 14, 15, 18 and 19, however there was no difference at the end of diet treatment
(Figure 3.1B). There was no signiﬁcant difference in weight between CON and CR mice
in group 2 at any point during the study.

After at least 20 weeks on diet, selected mice ﬁ'om each diet treatment in groups 1
and 2 were infected with H. hepaticus (as described above) for a pilot examination of
differences in histology scores at 28 days post-infection; however, CR mice had
unexpectedly decreased survival before the end of the infection period (Figure 3.2).
Because CR mice were unable to survive the full 28-day infection, the CR group was
excluded from further study.

Group 3 HF and CON mice were fed respective diets for 20 weeks, with no
signiﬁcant difference in weights between groups at any point during diet treatment
(Figure 3.3A). These mice were also assessed for body fat composition every other week -

beginning at week 8 on diet. Although there were no signiﬁcant differences in weight,

66

HF mice had signiﬁcantly greater body fat percentages at weeks 8, 11, 13 and 17 on diet
(Figure 3.33). There was no signiﬁcance in body fat percentage between groups by the
end of diet treatment and at the time of infection.

Effect of diet treatment on colitis and dysplasia scores at 28 days post-infection.

HF and CON mice were sacriﬁced 28 days after infection with H. hepaticus to
assess differences in colitis and dysplasia scores between diet groups. There was no
difference between combined colitis and dysplasia scores between CON (7.9 :l: 1.9) and
HF (7.8 :l: 2.1) mice at 28 days post-infection (Figure 3.4A). In order to examine the
potential effect of time, we allowed some mice to remain infected for up to 6 weeks, and
compared combined colitis scores between diet groups at weeks 4, 5 and 6 post-infection.
There was no difference between diet treatments at any time point, nor were there
differences within diet treatment groups across time (Figure 3.4B).

Discussion

The results of this study indicate that there is no effect of HF diet on colitis or
dysplasia in the SMAD3-/- mouse model. However, caloric restriction increased
mortality of mice infected with H. hepaticus, similar to previous observations with CR
mice infected with inﬂuenza [29-31]. Although CR without malnutrition is known to
extend lifespan and postpone age-related changes in immunity in mice, multiple studies
have found that CR mice exhibit increased mortality, decreased viral clearance and
impaired innate immune response, particularly reduced natural killer (NK) cell
cytotoxicity [29, 30, 32, 33]. CR and increased mortality post-infection represents a

highly novel and important observation meriting further study. Future collaborations

67

between the Fenton and Gardner laboratories will investigate potential mechanisms for
this signiﬁcant observation.

Obesity increases cancer risk through a promotional inﬂuence on transformed
cells compared to other models of diet-induced obesity (DIO). The mice in our studies
were not obese, nor were we able to induce increased adiposity or weight gain compared
to controls, possibly explaining the lack of effect on colitis scoring. SMAD3 is part of a
family of proteins that serve as signal transduction intermediates for transforming growth
factor beta (TGF-B), a family of ligands that inﬂuences a variety of cellular ﬁmctions,
including adipocyte differentiation [34-36]. Although TGF-B expression is increased in
both cultured adipocytes and in adipose tissue, TGF-B has been shown to impede
adipogenesis by inhibiting differentiation of preadipocytes both, in vitro and in viva [3 7-
39]. SMAD3 mediates these adipocyte differentiation/inhibition and proliferation
responses because it is activated by and acts as an effector of TGF-B signaling [40].
Interference with SMAD3 signaling enhances both rate and extent of differentiation and
inhibits cell proliferation, while the blockage of endogenous TGF-B signaling (via
inhibition of SMAD3) increases adipogenesis [39, 40]. Given this information, we
expected to see increased adiposity in the SMAD3-/- rrrice, especially those on HF diet,
due to disrupted TGF-B functioning leading to increased adipocyte accumulation;
however, any signiﬁcant gains in body weight or fat percentage in these mice were lost
by the end of diet treatment prior to infection with H. hepaticus.

Previous studies of DIO models report signiﬁcant increases in weights and body
fat percentages of high-fat fed mice compared to controls, and have identiﬁed a number

of speciﬁc inbred mouse strains that are particularly prone to obesity with high-fat

68

feeding, including C57BL/6, AKR/J, DBA/2J, C57L/J, NJ, and C3H/HeJ [41, 42]. Of
these models, C57BL/6 mice have been used routinely to study the effect of DIO on a
number of conditions. Recently, Guo et al. able to achieve signiﬁcant DIO in a C57BL/6
mouse model, with hi gh-fat fed mice reaching body weights of approximately 55g and up
to 40% body fat percentage, with obesity persisting after removal of obesigenic diet [43].
Furthermore, obesity in C57BL/6 mice fed a high-fat diet is not a product of hyperphagia
or reduced activity, but of increased feed efﬁciency, accompanied by metabolic
abnormalities such as altered inﬂammatory cytokine proﬁles, hyperglycemia and
adipocyte hyperplasia and hypertrophy [44-50].

The lack of signiﬁcant gains in body weight or fat percentage in our SMAD3-/-
model may be due to the 129 genetic background of the colony. Multiple studies have
shown that the 129 strain is resistant to DIO [51-53]. Our data is consistent with these
studies, in that HF diet mice presented with body compositions similar to CON and CR

mice, even after long term HF feeding. As such, we can surmise that the 129-

Smad3 ar/J mrce In our study may have also been resrstant to srgruﬁcant Increases 1n

body weight or fat percentage when placed on HF diet.

A phenotypical assessment of SMAD3-/- mice was ﬁrst described by Zhu et al. to
illustrate inherent physical differences between knockout mice and controls [54].
Notably, SMAD3-/- mice are 20-30% smaller than controls, with males exhibiting a
greater size reduction than females, which may explain why we did not observe weight
gains similar to those in other DIO studies with different mouse strains. Furthermore,
SMAD3-/- mice Show evidence of distress as they age beyond 18 weeks, and exhibit

decreased life span and premature death, particularly in the 129 background [54].

69

Because our mice were started on respective diet treatments at 6-8 weeks of age and kept
on diet for at least 20 weeks, the animals would have been a minimum of 26 weeks of age
at the end of diet treatment. The observed plateaus and/or losses in body weight and fat
percentage appear to coincide with the onset of age-related distress in the SMAD3-/-,
which is another possible explanation for lack of signiﬁcant differences between diet
treatment groups after 20 weeks.

In the present study, we were only able to induce a maximum body fat percentage
of roughly 25% in the SMAD3-/- mice. This percentage body fat may be insufﬁcient to
induce the chronic inﬂammation associated with obesity that promotes colon
carcinogenesis, such as in other animal models of DIO in which animals with 40-50%
body fat exhibit obesity-associated inﬂammation and tumor proliferation. It remains
unclear as to why we were unable to induce a higher percentage of body fat consistent
with DIO in the SMAD3-/- mice. Although the 129 strain background is DIO-resistant,
the deletion of SMAD3-/-, as well as subsequent TGF-B disruption and increased
adipogenesis, should be sufﬁcient to supersede any strain-associated resistance to DIO.
Pilot DIO studies with the SMAD3-l- mice conducted by Dr. Fenton were able to achieve
greater levels of obesity; however, those mice were started on diet treatments
immediately post-wean at 21 days of age as opposed to 6-8 weeks of age in the present
study. As such, future DIO studies will be designed so that SMAD3-/- mice are placed
on diet immediate after weaning, thereby allowing for an additional 3 to 5 weeks for mice

to become obese before age-related distress and weight loss presents at 18 weeks of age.

70

APPENDIX

E!
E
3
U.)
p—r

+HF

+CON
,2. . . ‘ +CR
r"‘<?' ~ /’\‘

 

Group 1 average weights (9) E“
N
01

IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII

15 20 25
weeks on diet

-I-HF
+CON
+CR

 

Group 2 average weights (9) P

 

I I I I I I I I I I I I I I

1G I I I I I I
5 15 20

weeks on diet

Average body weight (g) for HF, CON and CR diet groups throughout the course of diet
treatment for (A) Group 1 and (B) Group 2.

71

 

90. + HF
80- + CON
70- + CR

Percent Survival
()1
O
l

 

c I I I I
0 1 2 3 4

weeks post-infection

 

Survival curve of HF, CON and CR mice after infection with H. hepaticus.

72

Figure 3.3.

A.
27.5-

1115 (9)

+ HF
25.0- + CON

Q},llti5’

'9

22.5-
20.0-
17.51

 

 

15.0 I I I I I I I I I I I I I I I I I I I I

15 20

Group 3 average we

weeks on diet

5'
co

NNNNNNNQ
NGCDO-‘NOO-AU'IODNCDCDO-F

Group 3 body fat %

A—t—hNNN

 

1'1 1'3 1'5 1'7 2'0
weeks on diet

m.

(A) Average body weight (g) of HF and CON diet groups throughout course of diet
treatment. (B) Average body fat percentages of HF and CON diet groups.

73

Figure 3.4.

A.

Colitis Scores
JSU'ICDNCDCDO—th-bmm

 

c'ON l-'lF
diet treatment

10' -HF
9' l l I:ICON

Histology Scores
9’

 

 

 

 

 

 

 

 

 

o. _
4 5 6

weeks post-infection

(A) Average combined colitis and dysplasia scores between diet groups at 4 weeks post-
infection. (B) Average combined colitis and dysplasia scores between diet groups at 4, 5
and 6 weeks post-infection to assess potential effect of time.

74

10.

BIBLIOGRAPHY

National Health and Nutrition Examination Survey In: National Center for Health
Statistics, CDC, http://www.cdc.gov/nchs/; 2003-2004.

WCRF/AICR: Food, Nutrition, Physical Activity, and the Prevention of Cancer: a
Global Perspective. hr Washington DC; 2007.

Moayyedi P: The epidemiology of obesity and gastrointestinal and other diseases:
an overview. Dig Dis Sci 2008, 53(9):2293-2299.

Burke CA: Colonic complications of obesity. Gastroenterol Clin North Am 2010,
39(1):47-55.

Nam SY, Kim BC, Han KS, Ryu KH, Park BJ, Kim HB, Nam BH: Abdominal
visceral adipose tissue predicts risk of colorectal adenoma in both sexes. Clin
Gastroenterol Hepatol 2010, 8(5):443-450 e441 -442.

Ronti T, Lupattelli G, Mannarino E: The endocrine function of adipose tissue: an
update. Clin Endocrinol (Oxf) 2006, 64(4):355-365.

Suganami T, Ogawa Y: Adipose tissue macrophages: their role in adipose tissue
remodeling. J Leukoc Biol 2010.

Trayhum P, Wood 1: Adipokines: inﬂammation and the pleiotropic role of white
adipose tissue. Br J Nutr 2004, 92(3):347-355.

Nishimura S, Manabe I, Nagasaki M, Eto K, Yarnashita H, Ohsugi M, Otsu M,
Hara K, Ueki K, Sugiura S et al: CD8+ effector T cells contribute to macrophage
recruitment and adipose tissue inﬂarrrrnation in obesity. Nat Med 2009, 15(8):914-
920.

Liu J, Divoux A, Sun J, Zhang J, Clement K, Glickrnan JN, Sukhova GK, Wolters
PJ, Du J, Gorgun CZ et al: Genetic deﬁciency and pharmacological stabilization
of mast cells reduce diet-induced obesity and diabetes in mice. Nat Med 2009,
15(8):940-945.

75

11.

12.

l3.

14.

15.

16.

17.

18.

19.

20.

Winer S, Chan Y, Paltser G, Truong D, Tsui H, Bahrami J, Dorfrnan R, Wang Y,
Zielenski J, Mastronardi F et a1 : Normalization of obesity-associated insulin
resistance through immunotherapy. Nat Med 2009, 15(8):921-929.

Barbarroja N, Lopez-Pedrera R, Mayas MD, Garcia-Fuentes E, Garrido-Sanchez
L, Macias-Gonzalez M, E1 Bekay R, Vidal-Puig A, T inahones FJ: The Obese
healthy paradox: is inﬂammation the answer? Biochem J 201 0.

Faber DR, van der Graaf Y, Westerink J, Visseren FL: Increased visceral adipose
tissue mass is associated with increased C-reactive protein in patients with
manifest vascular diseases. Atherosclerosis 2010.

Koster A, Stenholm S, Alley DE, Kim LJ, Sirnonsick EM, Kanaya AM, Visser M,
Houston DK, Nicklas BJ, Tylavsky FA et al: Body F at Distribution and
Inﬂammation Among Obese Older Adults With and Without Metabolic
Syndrome. Obesity (Silver Spring) 2010.

Bruce KD, Byme CD: The metabolic syndrome: common origins of a
multifactorial disorder. Postgrad Med J 2009, 85(1009):614-621.

Demerath EW, Reed D, Rogers N, Sun SS, Lee M, Choh AC, Couch W,
Czerwinski SA, Chunrlea WC, Siervogel RM et al: Visceral adiposity and its
anatomical distribution as predictors of the metabolic syndrome and
cardiometabolic risk factor levels. Am J Clin Nutr 2008, 88(5):1263-1271.

Elks CM, Francis J: Central adiposity, systemic inﬂammation, and the metabolic
syndrome. Curr Hypertens Rep, 12(2):99-104.

Pischon T, Nothlings U, Boeing H: Obesity and cancer. Proc Nutr Soc 2008,
67(2):]28-145.

Wang Y, Jacobs EJ, Patel AV, Rodriguez C, McCullough ML, Thun MJ, Calle
BE: A prospective study of waist circumference and body mass index in relation
to colorectal cancer incidence. Cancer Causes Control 2008, 19(7):783-792.

Clevers H: At the crossroads of inﬂammation and cancer. Cell 2004, 118(6):671-
674.

76

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

Baden JA, Abrams KR, Mayberry JP: The risk of colorectal cancer in ulcerative
colitis: a meta-analysis. Gut 2001, 48(4):526-535.

Florin T, Paterson E, Fowler E, Radford-Srrrith G: Clinically active Crohn's
disease in the presence of a low C-reactive protein. Scand J Gastroenterol 2006,
41(3):306-311.

Aljada A, Mohanty P, Ghanim H, Abdo T, Tripathy D, Chaudhuri A, Dandona P:
Increase in intranuclear nuclear factor kappaB and decrease in inhibitor kappaB in
mononuclear cells after a mixed meal: evidence for a proinﬂammatory effect. Am

J Clin Nutr 2004, 79(4):682-690.

Dandona P, Aljada A, Bandyopadhyay A: Inﬂammation: the link between insulin
resistance, obesity and diabetes. Trends Immunol 2004, 25(1):4—7.

Campos SP, Baumann H: Insulin is a prominent modulator of the cytokine-
stimulated expression of acute-phase plasma protein genes. Mal Cell Biol 1992,
12(4):]789-1797.

Dandona P, Aljada A: A rational approach to pathogenesis and treatment of type 2

diabetes mellitus, insulin resistance, inﬂammation, and atherosclerosis. Am J
Cardial 2002, 90(5A):27G-33G.

Chapman-Kiddell C, Davies P, Gillen L, Radford-Smith G: Role of diet in the
development of inﬂammatory bowel disease. Inflamm bowel dis 2010, 16(1): 137-
1 5 1 .

Maggio-Price L, Bielefeldt-Ohmann H, Treuting P, Iritani BM, Zeng W, Nicks A,
Tsang M, Shows D, Morrissey P, Viney J L: Dual infection with Helicobacter bilis

and Helicobacter hepaticus in p-glycoprotein-deﬁcient mdrla-/- mice results in
colitis that progresses to dysplasia. Am J Pathol 2005, 166(6): 1 793-1 806.

Ritz BW, Aktan I, Nogusa S, Gardner EM: Energy restriction impairs natural
killer cell function and increases the severity of inﬂuenza infection in young adult
male C57BL/6 rrrice. J Nutr 2008, 138(1 1):2269-2275.

Clinthome J F, Adams DJ, Fenton J I, Ritz BW, Gardner EM: Short-Term Re-
Feeding of Previously Energy-Restricted C57BL/6 Male Mice Restores Body
Weight and Body Fat and Attenuates the Decline in Natural Killer Cell Function
after Primary Inﬂuenza Infection. J Nutr 2010.

77

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

Ritz BW, Gardner EM: Malnutrition and energy restriction differentially affect
viral immunity. J Nutr 2006, 136(5):]141-1144.

Gardner EM: Caloric restriction decreases survival of aged mice in response to
primary inﬂuenza infection. J Gerantal A Biol Sci Med Sci 2005, 60(6):688-694.

Nogusa S, Ritz BW, Kassim SH, Jennings SR, Gardner EM: Characterization of
age-related changes in natural killer cells during primary inﬂuenza infection in
mice. Mech Ageing Dev 2008, 129(4):223-230.

Shi Y, Massague J: Mechanisms of TGF-beta signaling from cell membrane to
the nucleus. Cell 2003, 113(6):685-700.

Derynck R, Zhang YE: Smad-dependent and Smad-independent pathways in
TGF-beta family signalling. Nature 2003, 425(6958):577-584.

Zanninelli G, Vetuschi A, Sferra R, D'Angelo A, Fratticci A, Continenza MA,
Chiaramonte M, Gaudio E, Caprilli R, Latella G: Smad3 knock-out mice as a
useful model to study intestinal ﬁbrogenesis. World J Gastroenterol 2006,
12(8):]211-1218.

Samad F, Yamarnoto K, Pandey M, Loskutoff DJ: Elevated expression of
transforming growth factor-beta in adipose tissue from obese rrrice. Mal Med
1997, 3(1):37-48.

Choy L, Derynck R: Transforming growth factor-beta inhibits adipocyte
differentiation by Smad3 interacting with CCAAT/enhancer-binding protein
(C/EBP) and repressing C/EBP transactivation ﬁrnction. J Biol Chem 2003,
278(11):9609-9619.

Rosen ED, MacDougald OA: Adipocyte differentiation from the inside out. Nat
Rev Mal Cell Biol 2006, 7(12):885-896.

Choy L, Skillington J, Derynck R: Roles of autocrine TGF-beta receptor and
Smad signaling in adipocyte differentiation. J Cell Biol 2000, 149(3):667-682.

West DB, Boozer CN, Moody DL, Atkinson RL: Dietary obesity in nine inbred
mouse strains. Am J Physiol 1992, 262(6 Pt 2):R1025-1032.

78

42.

43.

45.

46.

47.

48.

49.

50.

51.

Alexander J, Chang GQ, Dourmashkin J T, Leibowitz SF: Distinct phenotypes of
obesity-prone AKR/J, DBA2J and C57BL/6J mice compared to control strains.
IntJ Obes (Land) 2006, 30(1):50-59.

Guo J, J on W, Gavrilova 0, Hall KD: Persistent diet-induced obesity in male
C57BL/6 mice resulting from temporary obesigenic diets. PLoS One 2009,
4(4):e5370.

Surwit RS, Feinglos MN, Rodin J, Sutherland A, Petro AE, Opara EC, Kuhn CM,
Rebuffe-Scrive M: Differential effects of fat and sucrose on the development of
obesity and diabetes in C57BL/6J and NJ rrrice. Metabolism 1995, 44(5):645-

65 1 .

Brownlow BS, Petro A, Feinglos MN, Surwit RS: The role of motor activity in
diet-induced obesity in C57BL/6J mice. Physiol Behav 1996, 60(1):37-41.

Parekh PI, Petro AE, Tiller JM, Feinglos MN, Surwit RS: Reversal of diet-
induced obesity and diabetes in C57BL/6J mice. Metabolism 1998, 47(9):]089-
1096.

Surwit RS, Petro AE, Parekh P, Collins S: Low plasma leptin in response to
dietary fat in diabetes- and obesity-prone mice. Diabetes 1997, 46(9):]516-1520.

Black BL, Croom J, Eisen EJ, Petro AE, Edwards CL, Surwit RS: Differential
effects of fat and sucrose on body composition in NJ and C57BL/6 mice.
Metabolism 1998, 47(1 1):1354-1359.

Petro AE, Cotter J, Cooper DA, Peters J C, Surwit SJ, Surwit RS: Fat,
carbohydrate, and calories in the development of diabetes and obesity in the
C57BL/6J mouse. Metabolism 2004, 53(4):454—457.

Fenton J I, Nunez NP, Yakar S, Perkins SN, Hord NG, Hursting SD: Diet-induced
adiposity alters the serum proﬁle of inﬂammation in C57BL/6N mice as measured
by antibody array. Diabetes Obes Metab 2009, 11(4):343 -3 54.

Alrnind K, Kahn CR: Genetic determinants of energy expenditure and insulin
resistance in diet-induced Obesity in mice. Diabetes 2004, 53(12):3274-3285.

79

52.

53.

54.

Ishimori N, Li R, Kelmenson PM, Korstanje R, Walsh KA, Churchill GA,
Forsman-Semb K, Paigen B: Quantitative trait loci that determine plasma lipids
and obesity in C57BL/6J and 129S1/SvaJ inbred mice. J Lipid Res 2004,
45(9):]624-1632.

Bachmanov AA, Reed DR, Tordoff MG, Price RA, Beauchamp GK: Nutrient
preference and diet-induced adiposity in C57BL/6ByJ and 129P3/J mice. Physiol
Behav 2001, 72(4):603-613.

Zhu Y, Richardson JA, Parada LF, Graff J M: Smad3 mutant mice develop
metastatic colorectal cancer. Cell 1998, 94(6):703-714.

80