THE COMPLEX INTERACTIONS BETWEEN GENETICS AND
ENVIRONMENT: DIET, INFLAMMATION AND INTESTINAL
TUMORIGENESIS
by
STEPHANIE KAY DOERNER
Submitted in partial fulfillment of the requirements
for the degree of Doctor of Philosophy
Dissertation advisors:
Nathan A. Berger, M.D.
Joseph H. Nadeau, Ph.D.
Department of Genetics
CASE WESTERN RESERVE UNIVERSITY
January 2013
This thesis is dedicated to my brother, Nate.
Thank you for everything.
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TABLE OF CONTENTS
Dedication 1
Table of Contents 2
List of Figures 7
List of Tables 10
List of Abbreviations 11
Acknowledgements 15
Abstract 18
CHAPTER 1 – Background and Significance 20
1.1 Summary of Research 21
1.2 Introduction to Colon Cancer 24
1.2.1 Biology of the Small Intestine 25
1.2.2 Biology of the Large Intestine 28
1.2.3 Regeneration of the Intestine 32
1.3 Immunity and Cancer 34
1.3.1 Intestinal Immunity 35
1.3.2 Lymphoid Cells of the Intestinal Mucosa 38
1.3.3 Immune System and Cancer 43
1.3.4 The Complement Component Cascade 44
1.3.5 Complement and Cancer 48
1.3.6 Prostaglandins and Cancer 49
1.4 Cancer of the Intestine 52
1.4.1 Types of Intestinal Polyps 52
1.4.2 Stages of Colon Cancer Development 56
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1.5 Causes of Colon Cancer 61
1.5.1 Hereditary Forms of Colon Cancer 61
1.5.2 Rare Types of Colon Cancer 66
1.5.3 Inflammation Associated Colon Cancer 70
1.5.4 Sporadic Causes of Colon Cancer 72
1.5.5 The APC Mutation and Wnt Signaling 79
1.5.6 Environmental Causes of Colon Cancer 82
1.6 Understanding Digestion and Metabolism 83
1.6.1 Understanding the Process of Digestion 84
1.6.2 Regulation of Appetite and Metabolism 87
1.7 The Obesity Epidemic 90
1.7.1 Obesity-Related Diseases 91
1.7.2 Environmental Effects on Obesity 93
1.7.3 Inflammation and Obesity 94
1.8 Dietary Fat: The Good, the Bad and the Ugly 98
1.8.1 Saturated Fatty Acids 100
1.8.1.1 Butyric Acid 101
1.8.1.2 Lauric and Myristic Acids 103
1.8.1.3 Palmitic and Stearic Acids 104
1.8.2 Monounsaturated Fatty Acids 105
1.8.2.1 The Mediterranean Diet and Olive Oil 105
1.8.2.2 Oleic Acid 107
1.8.2.3 Oleic:Stearic Acid Ratio 107
1.8.3 Polyunsaturated Fatty Acids 108
1.8.3.1 Alpha-Linolenic Acid 109
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1.8.3.2 Eicosapentaenoic and Docoshexaenoic Acids 109
1.8.3.3 Arachidonic Acid 112
1.8.3.4 Linoleic Acid 113
1.8.3.5 Conjugated Linoleic Acid 114
1.8.3.6 The Omega-3: Omega-6 Ratio 116
1.9 Using Mouse Models to Study Human Obesity and Colon Cancer 117
1.9.1 ApcMin/+ - A Mouse Model of Intestinal Neoplasia 119
1.9.2 Mouse Models of Polygenic Traits: Obesity 123
CHAPTER 2 – High Fat Diet Modulates Intestinal Polyp Formation,
Separate from Diet-Induced Obesity 127
2.1 Introduction 128
2.2 Methods 131
2.2.1 Mice 131
2.2.2 Diets 132
2.2.3 Study Design 132
2.2.4 Metabolic Parameters and Cytokine Analysis 135
2.2.5 Quantitative RT-PCR and Protein Analysis 136
2.2.6 Statistical Analysis 136
2.3 Results 136
2.3.1 Constructing mouse models to study diet, separate from obesity 136
2.3.2 High fat diet decreases lifespan in ApcMin/+ 140
2.3.3 Contrasting CSS responses to HF diets 141
2.3.4 High dietary fat increases intestinal neoplasia 149
2.3.5 Neutrophils increased in strains fed high dietary fat 152
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2.4 Discussion 154
CHAPTER 3 – Differential Effects of Dietary Fat on Inflammation
and Cancer of the Intestine 158
3.1 Introduction 159
3.2 Methods 161
3.2.1 Mice 161
3.2.2 Diets 161
3.2.3 Study Design 162
3.2.4 Metabolic Parameters and Cytokine Analysis 164
3.2.5 Quantitative RT-PCR and Protein Analysis 164
3.2.6 Statistical Analysis 165
3.3 Results 165
3.3.1 Differential effect of different dietary fat sources on obesity and
metabolic syndrome 165
3.3.2 Differential effects of fat on polyp burden of the small intestine 170
3.3.3 Contrasting responses to different fats on polyps of the colon 172
3.3.4 Early effects of different dietary fats on DIO and MetS 172
3.4.5 Early effects of different dietary fat sources on intestinal neoplasia 174
3.4.6 Effects of dietary fat sources on inflammation 180
3.4 Discussion 184
CHAPTER 4 – High Fat Diet-Induced Complement Signaling
Contributes to Intestinal Adenoma Risk 188
4.1 Introduction 189
4.2 Methods 190
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4.2.1 Mice 190
4.2.2 Diets 190
4.2.3 Study Design 191
4.2.4 Metabolic Parameters and Cytokines Analysis 192
4.2.5 Quantitative RT-PCR and Protein Analysis 192
4.2.6 Pharmacological Inhibition of C5aR 193
4.2.7 Fluorescence-Activated Cell Sorting (FACS) of Intestinal Immune Cells 193
4.2.8 Statistical Analysis 194
4.3 Results 194
4.3.1 A high fat diet induces inflammation in the circulation and intestine 194
4.3.2 Dietary mediation of complement induced inflammation 196
4.3.3 Inhibition of complement signaling attenuates intestinal neoplasia 200
4.4 Discussion 205
CHAPTER 5 – Summary of Conclusions and Future Directions 208
5.1 Summary of conclusions and evidence 209
5.2 Modulation of microbial profiles by dietary fat 215
5.2.1 Introduction 215
5.2.2 Questions and proposed experiments 217
5.2.2.1 Do microbial profiles differ in diets composed of specific fats? 217
5.2.2.2 Do microbial profiles associate with cancer severity in ApcMin/+ mice? 218
5.2.2.3 Can different dietary fats be used to change intestinal microbial profiles? 219
REFERENCES 220
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LIST OF FIGURES
CHAPTER 1 FIGURES
Figure 1.1 – The structure of the small intestine 26
Figure 1.2 – The structure of the large intestine 29
Figure 1.3 – Immunity in the small and large intestine 37
Figure 1.4 – Differentiation of CD4+ T-cell subsets 40
Figure 1.5 – A model of innate and adaptive immunity during
inflammation-induced cancer development 45
Figure 1.6 – Complement evasion by pathogens 47
Figure 1.7 – Synthesis of anti- and pro-inflammatory prostaglandins 51
Figure 1.8 – Stage 0 to Stage 2 of colon cancer progression 58
Figure 1.9 – Stage 3 of colon cancer progression 60
Figure 1.10 – Stage 4 of colon cancer progression 62
Figure 1.11 – The genetics of sporadic colon cancer 73
Figure 1.12 – Hallmarks of cancer 75
Figure 1.13 – Wnt signaling in health and disease 80
Figure 1.14 – Components of the digestive system 85
Figure 1.15 – Medical complications associated with obesity 92
Figure 1.16 – Adipose tissue, adipokines and inflammation 95
Figure 1.17 – Creation of the Chromosome Subsitution Strains (CSSs) 125
Figure 1.18 – CSSs after 100 days on LF and HF diets 126
CHAPTER 2 FIGURES
Figure 2.1 – Construction of the CSS.ApcMin/+ strains 139
Figure 2.2 – Body weights during the duration of the diet study 142
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Figure 2.3 – Survival curves for mice fed the coconut oil diets 143
Figure 2.4 – Blood cell counts in B6 and ApcMin/+ 144
Figure 2.5 – Growth weights from CSS.ApcMin/+ strains 145
Figure 2.6 – B6 and CSS body weight parameters 147
Figure 2.7 – B6 and CSS metabolic parameters 150
Figure 2.8 – High dietary fat increases polyp number and mass 151
Figure 2.9 – White blood cells in B6 and CSSs 153
CHAPTER 3 FIGURES
Figure 3.1 – Growth curves for mice fed the coconut, corn and olive diets 166
Figure 3.2 – Body weight parameters in mice fed cocnut, corn or olive oil diets 168
Figure 3.3 – Specific dietary fat sources have differential effects on polyp
number and mass 171
Figure 3.4 – Specific dietary fat sources have differential effects on
colon polyp incidence 173
Figure 3.5 – Growth curves for mice fed coconut, corn or olive oil diets for
30 days 175
Figure 3.6 – Body weight parameters for mice fed coconut, corn or olive diets 176
Figure 3.7 – Metabolic parameters from mice fed coconut, corn or olive oils 177
Figure 3.8 – Specific dietary fat sources have differential effects on polyp
number and mass after 30 days 178
Figure 3.9 – Expression analysis from B6 and ApcMin/+ fed the coconut diet 181
CHAPTER 4 FIGURES
Figure 4.1 – Cytokines analysis in B6 and ApcMin/+ fed the coconut oil diets 195
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Figure 4.2 – Total polyp numbers are decreased in A2.ApcMin/+ fed HF 197
Figure 4.3 – Complement C5a is elevated in mice fed a HF diet for
30 and 60 days 198
Figure 4.4 – Strains that carry A/J chromosome 2 are deficient in C5a 199
Figure 4.5 – Polyp numbers are reduced in mice deficient in C5a 201
Figure 4.6 – Complement C5a medicates diet-induced inflammation and
intestinal neoplasia 204
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LIST OF TABLES
CHAPTER 1 TABLES
Table 1.1 – Genetics of colon cancer 64
Table 1.2 – Mutations found in sporadic colon cancer 76
Table 1.3 – Effects of specific fatty acids on colon cancer 118
Table 1.4 – Known modifiers of ApcMin/+ 122
CHAPTER 2 TABLES
Table 2.1 – Makers used in the creation of the CSS.ApcMin/+ strains 133
Table 2.2 – Composition of hydrogenated coconut oil diet 135
Table 2.3 – Primer sequences for quantitative RT-PCR reactions 137
Table 2.4 – Body weight and metabolic parameters after 60 days on the
diet study 148
Table 2.5 – Summar of CSS.ApcMin/+ response to high saturated fat 156
CHAPTER 3 TABLES
Table 3.1 – Composition of coconut, corn and olive oil diets 163
Table 3.2 – Body weight and metabolic parameters for mice fed coconut,
corn or olive oil diets 169
Table 3.3 – Summary of dietary influences on B6 and ApcMin/+ 185
CHAPTER 4 TABLES
4.1 – Body weight and metabolic studies for complement studies 203
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LIST OF ABBREVIATIONS
AA Arachidonic Acid
AAM Alternatively Activated Macrophage
ACF Aberrant Crypt Foci
AFAP Attenuated Familial Adenomatous Polyposis
AgRP Agouti-Related Peptide
AICR American Institute for Cancer Research
ALA Alpha Linolenic Acid
α-MSH Alpha Melanocyte-Stimulating Hormone
AOM Azoxymethane
APC Adenomatis Polyposis Coli
B6 C57BL/6J
BMI Body Mass Index
CAM Classically Activated Macrophage
CCK Cholecystokinin
CCS Cronkhite-Canada Syndrome
CD Crohn’s Disease
CIMP CpG Island Methylator Phenotype
CIN Chromosomal Instability
CK1 Casein Kinase 1
CLA Conjugated Linoleic Acid
Coco Hydrogenated Coconut Oil
COX-2 Cyclooxygenase-2
CSS Chromosome Substitution Strain
DHA Docosahexaenoic Acid
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DIO Diet-Induced Obesity
DMH 1,2-Dimethylhydrazine
DVL Dishevelled
EFA Essential Fatty Acids
EFPM Epididymal Fat Pad Mass
ENU Ethylnitrosourea
EPA Eicosapentaenoic Acid
EPIC European Prospective Investigation into Cancer and Nutrition
FAP Familial Adenomatous Polyposis
FBW Final Body Weight
FRZ Frizzled
GI Gastrointestinal
GSK3β Glycogen Synthase 3 Beta
HDAC Histone Deacetylase
HF High Fat
HMPS Hereditary Mixed Polyposis Syndrome
HNPCC Hereditary Non-Polyposis Colon Cancer
HOMA-IR Homeostatic Model Assessment of Insulin Resistance
IARC International Agency for Research on Cancer
IBD Inflammatory Bowel Disease
Ig Immunoglobulin
IKKβ Inhibitor of NFκB Kinase Beta
IL Interleukin
12
IRS-1 Insulin Receptor Substrate-1
JNK1 Jun N-Terminal Kinase 1
JPS Juvenile Polyposis Syndrome
LA Linoleic Acid
LF Low Fat
LOH Loss of Heterozygosity
LCFA Long-Chain Fatty Acid
LPS Lipopolysaccharide
LRP LDL Receptor-Related Protein
MAP MYH-Associated Polyposis
MCFA Medium-Chain Fatty Acid
MC4R Melanocortin-4 Receptor
MetS Metabolic Syndrome
Min Multiple Intestinal Neoplasia
Mom Modifier of Min
MUFA Monounsaturated Fatty Acid
μg Microgram
μL Microliter
NFκB Nuclear Factor Kappa B
NPY Neuropeptide Y
NSAID Non-Steroidal Anti-Inflammatory Drugs
ω-3/6/9 Omega-3/6/9
PAMP Pathogen-Associated Molecular Pattern
PAT Perinodal Adipose Tissue
PG Prostaglandin
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PGE2 Prostaglandin E2
PJ Peutz-Jeghers Syndrome
POMC Pro-Opiomelanocortin
PTEN Phosphatase and Tensin Homolog
PUFA Polyunsaturated Fatty Acid
PYY Peptide YY
SEER Surveillance, Epidemiology and End Results
SEM Standard Error of the Mean
SCFA Short-Chain Fatty Acid
TLR Toll-Like Receptor
Tregs Regulatory T Cells
TNFα Tumor Necrosis Factor Alpha
QTL Quantitative Trait Loci
WAT White Adipose Tissue
WCRF World Cancer Research Fund
WHO World Health Organization
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ACKNOWLEDGEMENTS (in alphabetical order)
There are a number of people without whom this thesis might not have been written, and to whom I am greatly indebted. Stephanie Balow – I am eternally grateful for your friendship, thoughtfulness and honesty. I see many more years of running from zombies, ladies nights, and evenings with Dante and Cleo. Thanks for being such a wonderful friend, #2! Nathan Berger – You are an amazing mentor! You forced me to move forward and focus on the science despite all of the personal and scientific struggles I faced. You have been a continuous source of encouragement and motivation. Your passion for science and generousity towards everyone you encounter are truly amazing and I cannot put into words how thankful and lucky I am that you became an active part of my graduate school career. Thank you! Berger Family – The support and kindness showed to me by the Berger Family has been amazing. I especially want to thank Suzy for making me feel like another one of her children, her amazing meals and trips to the symphony. Malana Bey – You are the foundation that holds so many of us together and I am lucky to know you and have you as my friend. Coty Boger – Thanks for the love and support over my long college years. I have watched you grow up so fast and develop into the wonderful person you are. I am proud to be your aunt. Nate Boger – Realize that it is no exaggeration when I say I would not be where I am today had it not been for you and your guidance. You are such a vital part of my life and I owe so much to you, Big Brother!! Jill Cavano – Your enduring friendship, support, and loyalty has made you such an important part of my life. You have always been an immense source of comfort and encouragement and have been there when I have needed it the most with open arms and a big heart. You are a beautiful person, inside and out! The world needs more people like you! Sharon Church – Thank you for your constant support and love throughout my long college career. You have always pushed me to strive to be the best that I can be and taught me the meaning of hard-work and dedication. I love you, Mama! Colleen Croniger – You are a great friend and mentor to me and have helped me through the many hardships of life and graduate school. You have always been a source of comfort and I am so thankful for everything. Dave DeSantis – You helped me see the lighter side of every situation and always have a way of filling the lab with laughter. Here’s to good friendship, good advice and good beer. Hailey Frankboner – I am so proud of you. I know that you will go far in your life and I look forward to being there to support you as much as you have supported me over the years! I will always be here for you. Nikki Frankboner – To my loving seeeester, thank you for being patient during the times I couldn’t always be around and for always believing in me. You and your children are such a bright part of my life and I am so lucky to have you all. Billy Gale – Thank you for a lifetime of friendship that has filled the years with laughter and countless stories to share with our next generation. Mike Green – I’m glad I didn’t die before I met you. You are a wonderful friend and I am thankful for our immeasurable discussions about life and politics. Jason Heaney – Being part of a lab is like being part of a family. Like many siblings, we have shared the good times as well as the bad and our friendship is stronger because of it. I am thankful for the friendship that we have and the memories that go along with it. Annie Hill-Baskin – Thank you for your friendship and for countless late night
15 discussions about everything from life to bacon. Justine Ko – (My ninja #2) My coffee/chai buddy! You are an incredible student! I am truly lucky to have been given the opportunity to be a mentor to you and help in the early development of your scientific career. I am confident that you will be happy and successful. Tomak Kordula – It is because of my experience in your lab that convinced me to pursue research and graduate school. I cannot thank you enough for your support, encouragement, and great mentorship. Elaine Leung – (My ninja #1) Thank you for being a wonderful friend, a great student, understanding my humor and encouraging my love for zombies. I miss you and Rex greatly. Joe Nadeau – I would like to thank you for giving me the privilege to pursue my own interests as a graduate student in your lab and educating me in all the aspects of research from political to scientific. You have helped me develop into a strong and independent graduate student and I will be forever grateful for that. Lorrie Rice – Thank you for always being there to listen and being a constant source of sunshine, positivity and enouragement. Austin and Kayla Rockwell – Although many years away, I look forward to the day that I get to see you graduate from college. Thank you for the love and support. Jake Rockwell – Thank you for always being there to help and lookout for the family and for being so supportive over the years. Helen Salz – Your encouragement, understanding, patience, and dedication to me and my career has made you such an important part of my success. I owe you so much that I do not know where to begin. Thank you. Thank you. Thank you. Matt Schieferstein – You have a big heart and I cannot tell you how much I appreciate all of your support, dedication and patience. It is because of you that I believe in soul mates and am so lucky to have a person like you in my life. John Wang – You gave me a second lab to call home and never hesitated to lend a helping hand whenever I needed you. I cannot thank you enough for your support, your faith in me, and for always giving great words of wisdom to keep my spirits high. Rodge Wilson – Thank you for opening the world of science to me as a child and showing me that the mind never stops learning. I’m thinking bonus!! Harry VanKeulen – Thank you for helping me to build a strong scientific foundation, encouraging my passion for science and being a great mentor. Soha Yazbek –I have always looked up to you, and admire your hard-work and dedication. You have been a constant source of encouragement and support and have always been a friend that I can turn to for personal or scientific advice. I miss you so much! Jenn Zechel – If there is anyone that can understand my struggles in life and graduate school over the last years, it is you, my dear lab sister! We will one day look back on these years and find humor in it all. Thank you for your friendship, advice and strength. Gabe Zentner – Ich verzeihe dir für alles.
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I am grateful to the following individuals for taking time to read and critically evaluate this thesis:
Nathan Berger
Colleen Croniger
David DeSantis
Helen Salz
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The Complex Interactions Between Genetics and Environment: Diet, Inflammation
And Intestinal Tumorigenesis
Abstract by Stephanie Kay Doerner
Diet-induced obesity (DIO) and metabolic syndrome (MetS) are important factors that contribute to the development and progression of cancer, especially colon cancer.
DIO and MetS have reached epidemic proportions in the United States and are heavily influenced by diets high in saturated and omega-6 polyunsaturated fatty acids. Using the
ApcMin/+ model of intestinal neoplasia and diets constructed from 58% coconut, corn or olive oils, we demonstrate that high amounts of dietary fats can have differential effects on DIO and MetS, as well as on intestinal tumorigenesis when compared to ApcMin/+ fed corresponding calorically equivalent control diets that contained 10% fat from these same sources. Diets constructed from coconut or corn oil lead to more rapid tumor progression, elevated polyp number and mass, as well as increased mortality, thus eliciting a detrimental impact on disease outcome, while one created from olive oil fails to induce an increase in polyp burden and reduce cancer severity in mice with genetic predisposition to intestinal neoplasia. We demonstrate that the tumor promoting effects of different fats are associated with systemic and local intestinal inflammation and that excess nutritional richness from coconut or corn oil can increase pro-inflammatory factors such as IL-6, IL-1β, TNFα, COX-2 as well as pro-oncogenic factors such as Myc.
Adipokines, such as adiponectin and leptin, are differentially modulated in response to different fat sources. Short dietary exposure is sufficient to induce inflammation and
18 tumorigenesis before the onset of DIO or MetS, suggesting a potent effect of diet on intestinal immunity. Additionally, we demonstrate a novel mechanism for innate immunity in diet-induced intestinal cancer by demonstrating that complement signaling is activated in mice fed diets high in coconut oil. We show that pharmacological and genetic inhibition of complement factors can significantly reduce polyp number and mass in ApcMin/+. These results suggest that nutritional modification may be a useful approach to alter intestinal and systemic inflammation with potential preventative value for use in colon tumorigenesis and that diet, immunity and cancer are intrinsically related.
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CHAPTER 1
BACKGROUND AND SIGNIFICANCE
TO BE PUBLISHED IN:
Doerner SK and Berger NA. Dietary Fats as Mediators of Obesity, Inflammation and
Colon Cancer. Energy Balance and Cancer. Vol 7. Obesity , Inflammation and Cancer.
Dannenberg AJ and Berger NA, Eds. Springer (2013).
AND
Doerner SK and Heaney JD. Inflammation, Obesity and Colon Cancer. Energy Balance and Cancer, Vol. 7. Obesity, Inflammation, and Cancer. Dannenberg AJ and Berger NA,
Eds. Springer (2013).
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1.1 Summary of Research
Colon cancer is a major health threat in the United States and many other developed countries, contributing to a majority of the cancer related deaths worldwide.
Main influences associated with an increased risk of tumorigenesis in humans are the consumption of high fat, calorically dense diets, subsequent excess body fat and a collection of metabolic disorders such as insulin resistance, dyslipidemia, high cholesterol that comprise metabolic syndrome (MetS). This becomes increasingly concerning as the prevalence of diet-induced obesity (DIO) and MetS continues to rise, even in children, despite the negative and often fatal health consequences associated with these diseases. Dietary habits and sedentary lifestyles continue to favor tumor development in many societies, yet the specific biological contributions that each makes to intestinal tumorigenesis remains unclear.
Colon cancer is associated with deregulation of the inflammatory response, as increased cytokines and immune signals are elevated in patients suffering from colon tumorigenesis. This altered inflammatory process is also prevalent during high dietary fat consumption and in patients suffering from obesity or MetS. Because consumption of a high fat diet and diet-induced obesity (DIO) and related MetS are strongly correlated in humans, it is difficult to test the individual consequences that each contributes to colon cancer or understand how diet alone can influence cancer-promoting inflammation.
Consumption of a high fat diet and DIO are two factors strongly associated with increased risk of developing colon cancer in humans and this close relationship makes it difficult to appreciate how diet, obesity or a combination of both effect initiation, growth
21 or progression of cancer. The combination of increased access to a large variety of foods in the human diet and the difficulty of collecting accurate food information, makes defining the effects of specific dietary components complicated. Understanding the role of dietary factors on inflammation and colon cancer-related immune responses is important, as the intimate relationship between these factors remains elusive.
The overall goal of this research was to assess the separate impact of diet and DIO on colon cancer. In Chapter 2, we examine the separate effect of diet on intestinal adenoma formation. Using a unique mouse model system, the chromosome substitution strains (CSSs), we demonstrate that it is possible to separate diet from obesity and impaired insulin signaling. When we combined CSSs with a mouse strain predisposed to developing intestinal neoplasia, ApcMin/+, we were then able to separate the effects of diet on tumorigenesis, independent from obesity. This combination provided mice predisposed to intestinal neoplasia that when exposed to a high fat diet did not gain weight or develop symptoms characteristic of MetS. Using this unique mouse model, we were able to dissect the effect of high dietary saturated fat on intestinal tumorigenesis and demonstrate that high dietary saturated fat plays an important role in the development of intestinal polyps, regardless of obesity status and related co-morbidities.
In Chapter 3, we investigated the effect of specific dietary fats on intestinal tumorigenesis. Using a model predisposed to the development of intestinal polyps,
ApcMin/+, we tested the effects of diets high in saturated, polyunsaturated, or monounsaturated fatty acids from coconut, corn or olive oils, respectively, to determine if the specific sources of fat can differentially modulate polyp formation or if all high fat diets increased tumor burden equally. We demonstrate that specific dietary fats can have
22 rapid and powerful effects on polyp development, whereby some elicit potent pro- tumorigenic potential and increase inflammation while other fats fail to cause an unfavorable impact.
In Chapter 4, we show a novel role for the complement component cascade on intestinal neoplasia. We demonstrate that specific components of the complement cascade are activated in response to a high fat diet. We show that a diet high in hydrogenated coconut or corn oil increases circulating and local inflammatory factors and the complement component C5a. Partial or full genetic deficiency in complement C3 or
C5aR significantly reduced polyp number and mass in a dose dependent manner, while pharmacological inhibition of C5a significantly reduces the dietary-induced increase in polyp number and burden in the ApcMin/+ model, demonstrating an intimate relationship between diet and the complement cascade in the intestine.
Together, these studies provide strong evidence for the impact of diet on colon tumorigenesis. We observed that specific combinations of fats can have distinct effects on intestinal neoplasia, demonstrating that the source of dietary fat is crucial in disease progression instead of high caloric consumption. Importantly, we show that the source of dietary fat can have differential effects on dietary-induced inflammation. This valuable evidence is important because much of the colon cancer research is now being focused on how to eliminate the pro-tumorigenic inflammation that results from diet and DIO. These studies suggest that diet could be a potential preventative method for individuals predisposed to colon cancer. Additionally, we demonstrate a novel role for complement signaling in diet-induced intestinal inflammation. By targeting members of the
23 complement cascade, we show that drug therapies are effective in mice, an important advancement in colon cancer research.
1.2 Introduction to Colon Cancer
Colorectal cancer or colon cancer is the third most commonly diagnosed malignancy in both men and women in the United States and is the second leading cause of cancer-related deaths. In the United States alone, 141,380 colon cancer (71,850 in men, 69,360 in women) cases were diagnosed in 2011. The National Cancer Institute
(NCI) estimates that there will be 51,690 colorectal cancer related deaths in 2012, which is 5% higher than the estimated deaths in 2011 (Howlader et al. 2011; Jemal et al. 2011).
The life-time risk for individuals to develop colon cancer is approximately 6%, but the risk increases to 18% among individuals who have a first degree relative (parent, sibling or child) with colon cancer (Schoen 2000; Johns et al. 2001; Howlader et al. 2011).
Homeostasis in the intestine is carefully controlled by a vast number of cell types from epithelial cells that aid in digestion to immune cells that protect our bodies against host invasion. Numerous environmental and genetic changes can affect this delicately regulated system and in some cases can lead to cancer. Although the majority of polyps form in the large intestine in humans, there are numerous polyposis syndromes characterized by the development of small intestinal polyps. Intestinal cancer can arise from many cells types, mainly the epithelial cells and to comprehend the formation of polyps, it is essential to understand the structures and functions of the small and large intestines.
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1.2.1 Biology of the Small Intestine
The small intestine is part of the gastrointestinal tract that functions to digest food and absorb the essential nutrients needed for the body. The small intestine is comprised of three sections: duodenum, ileum and jejunum, where the process of digesting and absorbing proteins, lipids (fats), and carbohydrates takes place. These larger macromolecules must be broken down into smaller components: proteins into amino acids and small peptides, fats into fatty acids and glycerol, and carbohydrates into monosaccharide, oligosaccharides and polysaccharides in order to be taken into the circulating system and used for energy (Louvard et al. 1992; Qu et al. 1996).
There are four concentric layers in the small intestine: the mucosa, submucosa, muscularis externa and adventitia/serosa (Figure 1.1). Each layer plays a specific role in the protection and proper function of the intestine (Louvard et al. 1992). The first and inner most layer is the mucosa, which is further divided into three other layers: the epithelium, lamina propria and muscularis mucosae. The epithelium is the inner surface exposed to the lumen of the gastrointestinal (GI) tract that contains small projections called villi. Functions of the epithelial cells of the epithelium in the small intestine include secretion, selective absorption, protection, transcellular transport and detection of sensation. The intestinal wall consists of columnar epithelial cells, which secrete mucus that protects the body from the harsh substances involved in digestion and also helps food pass through the intestine. The lamina propria contains capillaries and a central lacteal
(lymph vessel), as well as lymphoid tissue. Lamina propria also contains glands with the ducts opening on to the mucosal epithelium, which secrete mucus and serous secretions.
The lamina propria contains lymph nodes and is rich in immune cells known as
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Figure 1.1 – Structure of the small intestine. The small intestine consists of three regions: the duodenum, jejunum and ileum that extend from the stomach to the cecum. There are four concentric layers: the mucosa, submucosa, muscularis externa and adventitia/serosa. Villi line the lumen of the small intestine and contain lacteals and blood capillaries as well as a range of cell types (i.e. endocrine, goblet, epithelial and absorptive). Encyclopedia Britannica, Inc.
26 lymphocytes (a majority of which are IgA-secreting B cells) that help protect the intestinal wall from pathogens that have access to the digestive tract (Brandtzaeg et al.
1996; Bamba 2002). The muscularis mucosae (or lamina muscularis mucosae) is a thin layer of smooth muscle found in most parts of the gastrointestinal tract, located outside the lamina propria. The muscularis mucosa molds the mucosa into a series of small folds that help food move within the intestine. It produces local movements of the mucosa, such as twitching to dislodge food particles that have adhered to the mucosa (Louvard et al. 1992; Brandtzaeg et al. 1996; Bamba 2002).
The second layer, the submucosa, consists of copious amounts of blood vessels, connective tissue, lymphatics, and nerves that branch into the surrounding areas of the mucosa and muscularis externa. This layer provides mechanical strength to the intestinal structure during digestion as well as during the rapid cell turnover that occurs in the mucosa. Muscularis externa is the third layer and consists of both inner circular and outer longitudinal muscular sections. The circular layer helps to prevent food from passing in the wrong direction, while the longitudinal layer helps to package and shorten the intestine. During a process called peristalsis, the circular and longitudinal layers contract moving food through the intestinal tract (Thompson et al. 1971; de Santa
Barbara et al. 2003). The fourth and outer most layer is the adventitia/serosa that is constructed mainly of connective tissue and the location in the intestine determines the presence of adventitia or serosa. In anatomy, serous membrane (or serosa) is a smooth membrane consisting of a thin layer of cells, which secrete serous fluid, and a thin connective tissue layer. Serous membranes line and enclose several body cavities, known as serous cavities, where they secrete a lubricating fluid which reduces friction from
27 muscle movement. Serosa is not to be confused with adventitia, a connective tissue layer which binds together structures rather than reducing friction between them. (Thompson et al. 1971; de Santa Barbara et al. 2003).
The superior mesenteric artery (a branch of the abdominal aorta) and the superior pancreaticduodenal artery (a branch of the hepatic artery) supply the small intestine with blood. These vessels run between layers of the mesentery, the membrane that connects the intestines with the wall of the abdominal cavity, and give off large branches that form a row of connecting arches from which branches arise to enter the wall of the small bowel. The blood from the intestine is returned by means of the superior mesenteric vein, which, with the splenic vein, forms the portal vein, which drains into the liver.
1.2.2 Biology of the Large Intestine
The large intestine consists of the cecum and ascending (right) colon, the transverse colon, the descending (left) colon, and the sigmoid colon, which is connected to the rectum (Figure 1.2). The cecum, which is at the beginning of the ascending colon, is the point at which the small intestine joins the large intestine. The cecum is home to large varieties of bacteria that aide in the breakdown of plant material. Projecting from the cecum is the appendix, which is a small finger-shaped tube that serves no known function (Thompson et al. 1971; de Santa Barbara et al. 2003).
The function of the large intestine is to absorb water, salt and vitamins K and B12 as well as to store, process, and eliminate the residue following digestion and absorption.
The intestinal matter remaining after water has been reclaimed is known as feces. Feces consist of undigested food (i.e. cellulose), billions of mostly harmless bacteria, bile
28
Figure 1.2 – The structure of the large intestine. The large intestine extends from the cecum to the anus and consists of four regions: the ascending, trasverse, decending and sigmoid colon. There are four concentric layers: the mucosa, submucosa, muscularis externa and adventitia/serosa. Encyclopedia Britannica, Inc.
29 pigments, and other materials. The feces are stored in the rectum and passed out through the anus to complete the digestion process (Perumal et al. 1968).
The structure of the large intestine is similar to that of the small intestine and is comprised of similar layers of mucosa, submucosa, muscularis externa and serosa/adventitia. Compared to the small intestine, the large intestine is much larger in diameter by as much as 3-fold. The layers that make up the wall of the colon are similar in some respects to those of the small intestine; there are distinct differences, however.
The external aspect of the colon differs markedly from that of the small intestine because of features known as the taeniae, haustra, and appendices epiploicae. The arrangement of the longitudinal muscle fiber is modified in the large intestine compared to that observed in the small intestine. The longitudinal muscle of the wall of the small intestine forms a continuous layer around it. On the other hand, the longitudinal muscle in the large intestine is reduced to three bands, called teniae coli that are situated at regular intervals round the colon. These bands are shorter than the other layers of the large intestine, which produce invaginations instead of villi. The taeniae are three long bands of longitudinal muscle fibers, about 1 cm in width, that are approximately equally spaced around the circumference of the colon. Between the thick bands of the taeniae, there is a thin coating of longitudinal muscle fibers. Because the taeniae are slightly shorter than the large intestine, the intestinal wall constricts and forms circular furrows of varying depths called haustra, or sacculations. The appendices epiploicae are collections of fatty tissue beneath the covering membrane. On the ascending and descending colon, they are usually found in two rows, whereas on the transverse colon they form one row (Qu et al.
1996).
30
The inner surface of the colon has many crypts that are lined with mucous glands and numerous goblet cells, and it lacks the villi and plicae circulares characteristic of the small intestine. It contains many solitary lymphatic nodules but no Peyer patches.
Characteristic of the colonic mucosa are deep tubular pits, increasing in depth toward the rectum. Goblet cells are more prevalent in the crypts than along the surface, and their number increases distally toward the rectum. The mucus facilitates the passage of the increasingly solid colonic contents, and covers bacteria and particulate matter. The absorptive cells have short, irregular microvilli, and although they secrete a glycocalyx, it has not been shown to contain digestive enzymes. The absorptive cells actively transport electrolytes. Water is also absorbed as it passively follows the electrolytes. As in the small intestine, undifferentiated cells are found at the base of the crypts. It is particularly rich in lymphoid cells and and lymph nodules may interrupt the regular spacing of the crypts and extend into the submucosa (this is particularly evident in the appendix, which contains large amounts of lymphoid tissue). As in the small intestine, lymphatic vessels form a network around the muscularis mucosae. However, no lymph vessels extend into the lamina propria between colonic crypts. The muscularis mucosa has a circular and longitudinal layer (Louvard et al. 1992; Brandtzaeg et al. 1996; Bamba 2002; de Santa
Barbara et al. 2003).
The inner layer of muscle of the large intestine is wound in a tight spiral around the colon, so that contraction results in compartmentalization of the lumen and its contents. The spiral of the outer layer, on the other hand, follows a loose undulating course, and contraction of this muscle causes the contents of the colon to shift forward and backward. The bulk of the contents, in particular the amount of undigested fiber,
31 influence these muscular activities (Louvard et al. 1992; Brandtzaeg et al. 1996; Bamba
2002; de Santa Barbara et al. 2003).
The arterial blood supply to the large intestine is supplied by branches of the superior and inferior mesenteric arteries (both of which are branches of the abdominal aorta) and the hypogastric branch of the internal iliac artery (which supplies blood to the pelvic walls and viscera, the genital organs, the buttocks, and the inside of the thighs).
The vessels form a continuous row of arches from which vessels arise to enter the large intestine. Venous blood is drained from the colon from branches that form venous arches similar to those of the arteries. These eventually drain into the superior and inferior mesenteric veins, which ultimately join with the splenic vein to form the portal vein. The innervation of the large intestine is similar to that of the small intestine (Louvard et al.
1992; Brandtzaeg et al. 1996; Qu et al. 1996; Bamba 2002; de Santa Barbara et al.
2003).
1.2.3 Regeneration of the Intestine
Given the harsh environment in the intestine, the epithelial cells that line the lumen of the small and large intestines must constantly be replenished. In mammalian systems, the epithelial layer of the intestine is considered the most vigorous self-renewing tissue in mice and humans and is completely replenished around every 2-3 days (de Santa
Barbara et al. 2003; van der Flier et al. 2009). Tissue homeostasis is maintained by multipotent intestinal stem cells that reside within the crypts between villi, which are finger-like projections that line the intestine. Such a rapid turnover of the entire tissue is supported by cell of the intestinal crypt, which includes intestinal stem cells, serving as
32 origin of all the intestinal epithelial cells. Within the crypt, position of cells is strictly determined upon degree of differentiation; stem cells reside at the lowest part, whereas progenitor cells reside at the upper part of the crypt, respectively. Also known as crypt cells, intestinal stem cells have the ability to self-renew and regenerate intestinal tissue by differentiating into endocrine cells, enterocytes, goblet cells, and Paneth cells. Under normal physiological conditions, the number of functional epithelial cells is maintained by the balance between the shedding of old cells from the tip of the villi, and the generation of newborn cells from the crypt by proliferation of progenitor cells. Newborn cells migrate from the crypt along the crypt-villus axis, and acquire specific functions as they differentiate into one of the intestinal epithelial cell lineages (Hall et al. 1994; Heath
1996; Crosnier et al. 2006).
Once the intestinal homeostatsis is disrupted, for example by sudden injury of the epithelial layer, the repair program will be carried out sequentially over time. The most acute and rapid response is called restitution, which is mediated by epithelial cells lining the margin of the damaged epithelial area (ulcer). Upon ulcer formation, epithelial cells migrate and cover the damaged area, so as to restore the integrity of the epithelial layer quickly. By such re-distribution and re-shaping of epithelial cells, the epithelial tissue makes it possible to reconstitute the barrier between the intestinal lumen and the submucosa without waiting for the increase of epithelial cell number (Okamoto et al.
2004).
However, in a later phase, the depth of the remaining crypt becomes elongated, which is due to the increase in rapidly proliferating, progenitor cell populations. This increase in growth promotion from the intestinal crypt, results in the reconstruction of the
33 intestinal epithelial tissue structure through the resteration of epithelials cells. Following such response, crypt itself may go through division, which completes regeneration of the tissue structure. Such a regenerative response needs to be carried out sequentially, and failure in one of the sequential steps may lead to persistence of refractory ulcers
(Okamoto et al. 2005).
In the small intestine, the surface area is dramatically enlarged through epithelial protrusions called villi. Three types of differentiated epithelial cells cover these villi: the absorptive enterocytes, mucous-secreting goblet cells, and hormone-secreting enteroendocrine cells. Three days after their terminal differentiation, the cells reach the tip of the villus, undergo spontaneous apoptosis, and are shed into the gut lumen (Potten
1992; Daniele et al. 1994; Simons et al. 2003). Paneth cells are unusual in that they settle at the crypt bottoms and represent the only differentiated cells that escape the upward migration. Paneth cells have a function in innate immunity and antibacterial defense as they secrete bactericidal defensing peptides and lysozymes. The modular organization of the epithelium of the small intestine and colon into crypts is structurally comparable
(Potten 1992). Histologically, there are, however, two important differences between the two types of epithelia. The colon carries no villi but has a flat surface epithelium.
Moreover, Paneth cells are absent in the colon (Eastwood 1977; Ayabe et al. 2004).
1.3 Immunity and Cancer
The complex biological process known as inflammation serves to eliminate pathogens and other elements that disrupt tissue integrity as a result of traumatic, infectious, toxic or autoimmune injury. Therefore, inflammation is considered an initial
34 defense response by the host to the threats associated with both infectious and noninfectious factors. A well-coordinated inflammatory response rapidly eliminates invading pathogens or limits their spread, invokes the adaptive immune system, and facilitates the clearance and healing of damaged host tissues (Balkwill et al. 2001; Nathan
2002). This process is essential to the survival and well-being of all humans and animals.
The process normally leads to recovery from infection and to healing, however, if targeted destruction and assisted repair are not properly regulated, inflammation can lead to persistent tissue damage by leukocytes or lymphocyte and this initially helpful defensive response can contribute to the pathogenesis of numerous diseases, including cancer (Balkwill et al. 2001; Nathan 2002).
1.3.1 Intestinal Immunity
The epithelium of the small intestine is an important part of the digestive system, but can also modulate the intestinal immune system. Epithelial cells express many receptors that can induce an inflammatory response, such as toll-like receptors, acting both as a barrier and as a first-line pathogen recognition system. The immunological challenge of how to discriminate self from non-self is particularly complex at epithelial barrier sites, such as the intestine, where large amounts of antigens, including harmless food antigens, antigens derived from resident microorganisms and pathogens, and toxins produced by foreign invadors, are encountered over a lifetime. Immune cells in the intestine are positioned to contribute both to protecting the fragile epithelial monolayer that lines the gut and to regulate the access of luminal antigens to the intestinal tissues,
35 thereby balancing levels of tolerance and inflammation. Failure to correctly discriminate harmless invaders from potentially detrimental ones can result in chronic inflammation.
Because the lumen of the gastrointestinal tract is exposed to the external environment, much of it is populated with potentially pathogenic microorganisms
(Figure 1.3). To protect the body against foreign invaders, the epithelium is equipped with Peyer's patches, which are organized lymphoid nodules. Peyer's patches are important structures essential for immune surveillance in the intestinal lumen and facilitate the generation of the immune response within the mucosa (Levinsky 1985). In the immune system, antigens are any substance recognized as foreign that can stimulate the production of an antibody. Peyer's patches are covered by a special epithelium that contains specialized cells called microfold cells (M cells) that sample antigens directly from the lumen and deliver them to antigen-presenting cells. B-cells and memory cells are stimulated upon encountering antigens in Peyer's patches. Pathogenic microorganisms and other antigens entering the intestinal tract encounter macrophages, dendritic cells, B- lymphocytes, and T-lymphocytes found in Peyer's patches (Figure 1.3). These cells then pass to the mesenteric lymph nodes where the immune response is amplified. Activated lymphocytes pass into the blood stream via the thoracic duct and travel to the gut where they carry out their final effector functions (Doe 1972; Bockman et al. 1983; Garside et al. 2004)
At the bottom of the intestinal crypt resides another group of cells important for the maintaining the complex interactions between intestinal immune defense and the normal flora, Paneth cells. Paneth cells, along with goblet cells, enterocytes, and enteroendocrine cells, represent the principal cell types of the epithelium of the small
36
Figure 1.3 – Immunity in the small and large intestines. A single layer of intestinal epithelial cells (IECs) provides a physical barrier that separates commensal bacteria in the intestinal lumen from the underlying lamina propria. The IECs lining the lumen are bathed in nutrients, commensal bacteria, IgA and goblet cell-produced mucus. Epithelial stem cells proliferate and give rise to daughter cells with the potential to proliferate. These IECs then differentiate into villous or colonic enterocytes, which absorb nutrients (small intestine) and water (colon). In addition to differentiated enterocytes and goblet cells, progenitor IECs differentiate into both enteroendocrine cells, which secrete enteric hormones, and Paneth cells at the base of the small intestinal crypts. Beneath the IECs, the lamina propria is made up of stromal cells (myofibroblasts), B cells, T cells, macrophages and dendritic cells. Certain subsets of T cells and dendritic cells localize between the IECs. The small intestine has regions of specialized epithelium termed follicle-associated epitheliumand microfold (M) cells that overlie the Peyer's patches and sample the intestinal lumen. Abreu. 2010.
37 intestine that help regulate normal intestinal homeostasis and defense against invading organisms. Paneth cells are the main epithelial cell type that secretes antimicrobial peptides, and is responsible for mucosal production of immunoglobulin A (IgA) (Bevins et al. 2011; Santaolalla et al. 2012). They are identified microscopically by their location just below the intestinal stem cells in the intestinal glands (crypts of Lieberkühn) and the large eosinophilic granules that occupy most of their cytoplasm. These granules consist of several anti-microbial compounds and other compounds that are known to be important for immunity and host-defense (Salzman 2010; Bevins et al. 2011). When exposed to bacteria or bacterial antigens, Paneth cells secrete some of these compounds into the lumen of the intestinal gland, thereby contributing to maintenance of the gastrointestinal barrier (Salzman 2010).
1.3.2 Lymphoid Cells of the Intestinal Mucosa
T helper (TH) cells are a sub-group of lymphocytes that play an important role in the immune system, particularly in the adaptive immune system. These cells have no cytotoxic or phagocytic activity; they cannot kill infected host cells or pathogens. Instead,
TH cells aid or influence other immune cells, for example through activation or direction
(Littman et al. 2010). TH cells have a prominent role in orchestrating protective responses, while promoting tolerance against harmless antigens. To fulfil specific requirements, TH cells differentiate into functional lineages, with each having a specialized role in immune responses. The differentiation of TH cell lineages is thought to predominantly, but not exclusively, defined by cytokines present in the
38 microenvironment (Zygmunt et al. 2011). However, the rigid distinction between the TH cell lineages has been blurred in recent years.
There are four subpopulations of TH cells: TH0, TH1, TH2 and TH17 cells (Figure
1.4). When naïve TH0 cells encounter antigen in secondary lymphoid tissues, they are capable of differentiating into inflammatory TH1 cells, helper TH2 cells or pathogenic
TH17 cells, which are distinguished by the cytokines they produce (Kanno et al. 2012).
Whether a TH0 cells becomes a TH1, TH2 or TH17 cell depends upon the cytokines in the environment, which are influenced by antigens. For example some antigens stimulate IL-
4 production which favors the generation of TH2 cells while other antigens stimulate IL-
12 production, which favors the generation of TH1 cells. TH1, TH2 and TH17 cells affect different cells and influence the type of an immune response. Cytokines produced by
TH1 cells activate macrophages and participate in the generation of cytoxic lymphocytes
(CTL), resulting in a cell-mediated immune response. In contrast cytokines produced by
TH2 cells help to activate B cells, resulting in antibody production (Qazi et al. 2009;
Kanno et al. 2012).
TH17 cells are a subset of TH cells that are enriched at mucosal sites and produce interleukin (IL)-17. The generation and maintenance of TH17 and induced regulatory T
(TREG) cells in the intestine has an important role in the equilibrium between immunity and tolerance. The differentiation of both subsets critically depends on the activity of transforming growth factor‑β (TGFβ)(Chen et al. 2003; Bettelli et al. 2006). Stimulation of naive T cells increases the expression of the TREG cell transcriptional regulator forkhead box P3 (FOXP3), which suppresses important regulators of TH17 cells (Ivanov et al. 2006). The presence of additional inflammatory signals, such as IL-6, IL-1β or
39
Figure 1.4 – Differentiation of CD4+ T-cell subsets. After the encounter of antigen and co-stimulatory molecules presented by antigen-presenting cells, naive CD4+ T cells can differentiate into multiple subpopulations. The lineage commitment of CD4+ T cells depends on the cytokine environment accompanying the T-cell activation process in secondary lymphoid organs. The diverse T-helper cell subtypes show differential activation of transcriptional programs and are characterized by secretion of certain cytokines that enable them to provide protection against different classes of pathogens and to mediate autoimmunity. IFN-γ, interferon-γ; IL, interleukin; TGF-β, transforming growth factor-β; Th1, T-helper 1 cell; TNF-α, tumor necrosis factor-α. Turner et al. 2010.
40
TNFα, suppresses FOXP3 expression, resulting in the development of TH17 cells
(Veldhoen et al. 2006). TREG cells can inhibit pro-inflammatory events in many cell types, whereas TH17 cells recruit additional immune cell types, including highly pro- inflammatory granulocytes, thereby enhancing the inflammatory response (Esplugues et al. 2011).
Regulatory T (TREG) cells are a component of the immune system that suppresses the immune responses of other cells. This is an important "self-check" built into the immune system to prevent excessive reactions. TREG cell populations mainly originate in the thymus, and these cells are termed naturally occurring TREG cells. However, TREG cell populations can also arise from precursor cells in the periphery, and in this case they are termed induced TREG cells. These induced TREG cells accumulate throughout life and are found at mucosal surfaces of the intestine (Josefowicz et al. 2012).
The intestines are equipped with mucus and epithelial barriers, protective bacterial flora, and a harsh array of chemicals that protect against unwanted trespassers
(Figure 1.3, Figure 1.4). For intruders that penetrate these defense systems, both the innate and adaptive responses create an inner defense. The innate immune response consists of a host of cell types, including neutrophils, eosinophils, mast cells, and macrophages, that is the first to respond to any type of unwelcome invader (Salzman
2010; Santaolalla et al. 2012). These cells are present throughout the body, especially in areas that are exposed to the outside environment such as the intestinal mucosa. Immune cells of the innate response contain a variety of pathogen-associated molecular pattern
(PAMP) receptors, such as Toll-like receptors (TLRs). Cells that contain PAMPs
41 regularly survey the surrounding environment, recognize and categorize threats into general classes, and elicit the appropriate responses (Garside et al. 2004).
Any continued immunological stimulus triggers the activation and deployment of the adaptive immune response. In contrast to the immediate responses of the innate immune system, the adaptive immune systems can take anywhere from four to seven days of gene rearrangement and somatic hypermutation to fully activate. The resulting immune cells have highly specific antibodies and effector lymphocyte responses against specific cell surface antigens on invading organisms that can persist for years after the extermination of the invader (Beck et al. 1996).
The immune system is a complex network of cells that respond to a large variety of stimuli. Recent work has demonstrated that metabolic programs are required for proper regulation and execution of the diverse functions of the immune system and that there is an intimate link between the two. For example, lymph nodes, which house many of the lymphocytes, macrophages and other immune cells of the intestine, are surrounded by depots of white adipose tissue (perinodal adipose tissue or PAT), which provides a stable source of energy during immune activation (Mattacks et al. 2002; Knight 2008).
Studies of lymph nodes have demonstrated that the composition of lipids provided by the
PAT differs significantly from that provided by neighboring adipose tissue. Specifically, the PAT of resting lymph nodes is dominated by polyunsaturated fatty acids (PUFAs), while concentrations of PUFAs are much lower in neighboring adipose tissue. Under conditions of prolonged inflammatory activation of the lymph node, the lipid concentration shifts to provide large amounts of saturated fatty acids and glycerol
(Mattacks et al. 2002). In vitro studies have shown the capacity of these lipid mixtures to
42 induce the quiescent or inflammatory profiles with which they are associated in vivo, independent of any immune signal (Beck et al. 1996; Kalinski 2012).
Macrophages are responsible for sensing, integrating, and responding to a wide array of stimuli from the local microenvironment. These versatile responses are coordinated through two distinct and mutually exclusive activations programs terms classical (M1) and alternative (M2) (Yehuda-Shnaidman et al. 2012). Classical activation occurs in response to products associated with bacterial infections such as lipopolysaccharide (LPS) or interferon-γ (IFN-γ). In contrast, alternative activation occurs in response to products derived from parasitic infections, such as IL-4 or IL-13
(Garrett et al. 2010). Although these two programs are essential for our vitality, both have known roles in health and diseases. For example, the alternative program is implicated in wound healing, tissue remodeling, atopic disease states, and apoptotic cell disposal. The classical program is thought to have functions in inflammatory diseases such as rheumatoid arthritis, inflammatory bowel disease and atheroschlerosis (Garrett et al. 2010; Yehuda-Shnaidman et al. 2012).
1.3.2 The Immune System and Cancer
The role of the immune system during cancer development is complex, and involves extensive reciprocal interactions between genetically altered cells, adaptive and innate immune cells, their soluble mediators and structural components present in the neoplastic microenvironment (Rizzo et al. 2011). Each state of cancer development can be modulated uniquely by the immune system, where full activation of adaptive immune cells at the tumor state may result in eradication of malignant cells or chronic activation
43 of innate immune cells at sites of premalignant growth can enhance tumor development.
In addition, the balance between desirable anti-tumor immune responses and undesirable cancer-promoting, chronic inflammatory responses largely depends on the context in which a malignancy is developing, the type of immune cells present (i.e. lymphocytes versus macrophages) and the surrounding tumor microenvironment (Secher et al. 2010;
Rizzo et al. 2011).
The diverse functions of the immune system in cancer initiation and development are centered on two ideas. The first, called the “cancer immunoediting theory”, postulates that the immune system protects the host against cancer development, similar to the way observed in a classical immune response against infection (Figure 1.5).
Examples include inhibition of tumor growth by cytokine-mediated lysis of tumor cells or anti-tumor cytotoxic-T-cell activity (Dunn et al. 2002). The second proposes that long- lasting inflammatory reactions facilitate malignant transformation and cancer progression
(Figure 1.5). Examples include paracrine regulation of intracellular pathways usually through NFκB, promotion of tumor development by humoral immune responses that increase chronic inflammation in the tumor microenvironment, or through suppression of anti-tumor T-cell responses by regulatory T cells (Balkwill et al. 2001; Coussens et al.
2002).
1.3.3 The Complement Component Cascade
The complement cascade is a crucial component of the innate immune response that fulfills numerous immunological functions such as recognition of foreign cells,
44
Figure 1.5 – A model of innate and adaptive immunity during inflammation-induced cancer development. Antigens that are present in early neoplastic tissues are transported to lymphoid organs by dendritic cells (DCs) that activate adaptive immune responses resulting in both tumour-promoting and antitumour effects. Activation of B cells and humoral immune responses results in chronic activation of innate immune cells in neoplastic tissues. Activated innate immune cells, such as mast cells, granulocytes and macrophages, promote tumour development by the release of potent pro-survival soluble molecules that modulate gene-expression programmes in initiated neoplastic cells, culminating in altered cell-cycle progression and increased survival. Inflammatory cells positively influence tissue remodelling and development of the angiogenic vasculature by production of pro-angiogenic mediators and extracellular proteases. Tissues in which these pathways are chronically engaged exhibit an increased risk of tumour development. By contrast, activation of adaptive immunity also elicits antitumour responses through T-cell-mediated toxicity (by induction of FAS, perforin and/or cytokine pathways) in addition to antibody-dependent cell-mediated cytotoxicity and antibody-induced complement-mediated lysis. de Visser et al. 2006.
45 communication with and activation of the adaptive immune system and removal of cellular debris (Walport 2001a; Walport 2001b). The generation of fragments that promote chemotaxis of inflammatory cells, enhancing phagocytosis by neutrophils and macrophages, participating in B cell and T cell activation, and clearance of immune complexes are all functions of this complex system. The complement cascade includes over 30 different proteins that synergize to form the membrane attack complex, which is capable of initiating lysis of microbes and recruiting immune cells such as neutrophils and macrophages to sites of exposure or infection (Walport 2001a; Walport 2001b;
Molina 2004) (Figure 1.6).
Complement proteins found in plasma are in a native quiescent state but are activated rapidly under the influence of specific stimuli. The complement cascade is activated through four different pathways: The classical, the alternative, the mannan- binding lectin (MBL) or the extrinsic protease pathway. Although all four pathways are activated by different stimuli (i.e. antibodies with specific recognition motifs or the plasma proteins known as mannan-binding lectins), the proteolytic activation of the third component of complement, C3, is shared among them (Molina 2004; Haas et al. 2007)
(Figure 1.6).
Activation of C3 plays a critical role in activating the potent effector mechanisms that are associated with complement. Cleavage of C3, to C3a and C3b, generates several biologically active fragments that are responsible for most of the complement functions.
The small C3a peptide is a potent anaphylatoxin and can induce chemotaxis and degranulation of eosinophils and mast cells, which results in the secretion of potent vasoactive and pro-inflammatory mediators. C3a also has immunosuppressive functions,
46
Figure 1.6 – Complement evasion by pathogens. A. After activation of the complement system by antibody complexes (classical pathway (CP)), terminal mannose (lectin pathway (LP)) or by spontaneous and induced C3 hydrolysis (alternative pathway (AP)), the C3 convertases cleave C3 to its active fragments C3a and C3b. Covalent binding of C3b (opsonization) amplifies the cascade and mediates phagocytosis and adaptive immune responses by binding to complement receptors (CRs). Accumulation of deposited C3b also leads to the assembly of C5 convertases that activate C5 to C5a and C5b. Whereas C5b initiates the formation of the lytic membrane-attack complex (MAC), the anaphylatoxins C3a and C5a induce pro-inflammatory and chemotactic responses by binding to their receptors (C3aR and C5aR). On pathogenic surfaces, properdin (P) induces and stabilizes the AP C3 convertase, which leads to enhanced complement activity. B. Microorganisms have developed many ways to evade complement actions. Suppression of CP activation can be achieved by trapping endogenous C1 inhibitor (C1-INH) to the surface or by inactivating antibodies through the capture of their Fc regions. Whereas the recruitment of soluble regulators by capturing host proteins is a common strategy to impair downstream complement actions, certain viruses also produce structural mimics of these regulators. In addition, some microbial proteins have similar activities to CD59 in preventing MAC formation. Direct inhibition of C3, the C3 and C5 convertases, C5 or the C5a receptor (C5aR) is a prominent strategy of Staphylococcus aureus. Finally, a set of different microbial proteases can degrade many of the crucial components of the complement system. These proteases act directly or by capturing and activating a human protease. An extended list of complement evasion proteins can be found in Supplementary information S1 (table). Increased and decreased activity is represented by thick and thin arrows, respectively. F, ficolin; fB, factor B; fD, factor D; fI, factor I, MASP, MBL-associated serine protease; MBL, mannose-binding lectin; RCA, regulators of complement activation. Lambris et al. 2008.
47 including inhibition of antibody production by B cells and secretion of anti-inflammatory cytokines by monocytes (Elsner et al. 1994; Fischer et al. 1997). Cleavage of C3 is also responsible for the production of the proteins that activate C5, another powerful anaphylatoxin and pro-inflammatory complement factor. C5a also interacts with granulocytes and monocytes/macrophages to cause increased chemotaxis, degranulation, adhesion to endothelial cells, the production of reactive oxygen species, and activates potent pro-inflammatory mediators (Elsner et al. 1994; Fischer et al. 1997).
1.3.4 Complement and Cancer
Despite significant research on the role of inflammation and immunosurveillance in the immunologic microenvironment of tumors, little attention has been given to the oncogenic capabilities of the complement cascade. The recent finding that complement may contribute to tumor growth suggests an insidious relationship between complement and cancer, especially in light of evidence that complement facilitates cellular proliferation and regeneration (Markiewski et al. 2008). Evidence shows that this diverse family of innate immune proteins facilitates dysregulation of mitogenic signaling pathways, sustained cellular proliferation, angiogenesis, insensitivity to apoptosis, invasion and migration, and escape from immunosurveillance.
Researchers have postulated that the chronicity of inflammation determines its cancer effect: Acute inflammation is believed to fight the development of neoplastic cells, whereas chronic inflammation encourages their genesis and spread (Guo et al.
2005). As a fundamental component of innate immunity, the complement cascade
(Figure 1.6) contains some of the most powerful proinflammatory molecules in the body,
48 including most notably the anaphylatoxins C3a and C5a. The contribution of the complement cascade to acute inflammation is well established, as is the continuous activation and consumption of complement proteins in chronic inflammatory states (Guo et al. 2005; Markiewski et al. 2009). Nevertheless, emerging literature examining the mechanistic relationship between inflammation and cancer has almost completely omitted the role of the complement cascade (Coussens et al. 2002). Thus, the recent finding that complement proteins C3, C4, and C5a may aid tumor growth through immunosuppression (Markiewski et al. 2008) is unexpected and suggests an insidious and previously unrecognized relationship between the complement system and cancer.
The proliferative abilities of the anaphylatoxins C3a and C5a have been documented and reveal the participation of several signal transduction pathways with known links to neoplastic progression (Mastellos et al. 2002). C3a receptor (C3aR) and
C5a receptor (C5aR) are both coupled to G-proteins. C3a/C3aR and C5a/C5aR binding activates members of the mitogen-activated protein kinase (MAPK) family including extracellular signal-regulated kinases (ERK) and p38 (Gerard et al. 1991; Ames et al.
1996; Schraufstatter et al. 2002). Furthermore, C3a and C5a increase the activation of phosphatidylinositol 3-kinase, Akt, and mammalian target of rapamycin, three other proteins strongly associated with neoplasia when overexpressed (Vivanco et al. 2002;
Corradetti et al. 2006).
1.3.4 Prostaglandins and Cancer
Prostaglandin synthesis involves the production of lipid compounds within the cells that act as chemical messengers to mediate biological processes, such as
49 inflammation, and are important in the normal function of many different tissues. Certain enzymes initiate prostaglandin synthesis by catalyzing a series of metabolic reactions that convert a fatty acid into the final biologically active product. Prostaglandins are autocrine and paracrine lipid mediators that act upon platelets, endothelium, uterine and mast cells. Prostaglandins are synthesized in the cell from the phospholipids or essential fatty acids (EFAs) (Figure 1.7). Drugs such as aspirin prevent the synthesis of prostaglandins and thus reduce pain and inflammation (Lanas et al. 2003; Greene et al.
2011).
When enzymes known as cyclooxygenases (COXs) are released, prostaglandin synthesis begins through the oxidation of fatty acids, particularly arachidonic acid.
Oxidation changes the basic structure of prostaglandins depends on the conditions required for the cell at the time. COX-1 is the enzyme responsible for maintaining normal levels of prostaglandins, while COX-2 mediates synthesis when tissues are injured or infected. Synthesis occurs in almost every cell type, with the exception of white blood cells and those lacking nuclei. When tissue injury occurs, various immune cells migrate to the site. This process of cellular response triggers COX-2 release, resulting in prostaglandin synthesis at the damaged part of the body. The prostaglandins lead to an inflammatory response, triggering fever and limiting infection and tissue loss (Park et al.
2006; Greene et al. 2011).
Various chemicals can inhibit prostaglandin (PG) synthesis such as aspirin. Both
COX-1 and COX-2 are inhibited by aspirin, which prevents the oxygenation of arachidonic acid that is necessary for synthesis for prostaglandin H2 (PGH2), which gives rise to the other factors such as PGF2, PGD2, PGE2, PGI2 and TXA2 (Figure 1.7). By
50
Figure 1.7 – Synthesis of anti- and pro-inflammatory prostaglandins. Prostaglandins are synthesized from fatty acids (blue) obtained from the dietary phospholipids (purple) and can either be anti-inflammatory (green) or pro-inflammatory (red). Phospholipids that give rise to anti-inflammatory prostaglandins such as ALA, OCT, and EPA are synthesized by the same enzymes (orange) that produce pro-inflammatory phospholipids such as LA, GLA and AA and thus compete for production. ALA; alpha-linolenic acid, OCT; octadecanoic acid, EPA; eicosapentaenoic acid, PGH3; prostaglandin H3, LA; linoleic acid, GLA; gamma-linolenic acid, AA; arachidonic acid, PGH2; prostaglandin H2, COX; cyclooxygenase.
51 preventing the enzyme activity, aspirin stops the inflammatory pathway and thus inhibits
PGE2 (Kniss et al. 1992). PGE2 is synthesized in substantial amounts at sites of inflammation where it acts as a powerful vasodilator and along with other mediators such as histamine, causes an increase in vascular permeability and inflammation. PGE2 is a principal mediator of inflammation in diseases such as rheumatoid arthritis and osteoarthritis. Nonsteroidal anti-inflammatory medications (NSAIDs) and selective COX-
2 inhibitors reduce PGE2 production to diminish the inflammation seen in these diseases
(Lanas et al. 2003; Park et al. 2006).
1.4 Cancer of the Intestine
“Polyp” is a general term used to describe a benign (non-cancerous) growth that arises on the inner surface of the intestinal wall. Intestinal polyps can be various shapes and sizes, and most are considered pre-cancerous, which means that cancer may develop if left untreated. Fortunately, colon polyps are typically found during routine colon cancer screening tests, such as a colonoscopy or flexible sigmoidoscopy. When found, these growths can be removed, which reduces the likelihood of developing colon cancer later in life.
1.4.1 Types of Intestinal Polyps
Polyps are defined by the structure and type of cells found in them. In general, cells in polyps are considered neoplastic or non-neoplastic (Fenoglio-Preiser et al. 1985).
In neoplastic tissue, rapid and uncontrolled growth occurs usually without the aid of growth signals or stimuli, shows partial or complete lack of structural organization and
52 functional coordination with normal tissue, and usually forms a distinct mass of tissue which may be either benign or malignant. Non-neoplastic polyps are small nodules that usually contain normal cellular components and are unlikely to develop into colon cancer. Polyps comprised of neoplastic cells, such as adenomas, have a higher likelihood of developing into colon cancer. In terms of shape, intestinal polyps come in two basic varieties: pedunculated and sessile. Pedunculated polyps are mushroom-like tissue growths that are attached to the surface of the mucous membrane by a long, thin stalk, or peduncle. Sessile polyps sit right on the surface of the mucous membrane. Sessile polyps do not have a stalk and are flat (Morson et al. 1976).
The six most common types of intesetinal polyps are inflammatory, hyperplastic, adenomatous (adenoma), hamartomatous, villous (tubulovillous) adenoma and adenocarcinomas (colon cancer). In addition to these, two less common polyp types include lymphoid, which are considered rare and benign (non-cancerous), and juvenile.
Juvenile refers to the type of polyp, not the age at which polyps first develop (Morson et al. 1976).
Inflammatory colon polyps are found most often in people with an inflammatory bowel disease (IBD), such as Crohn’s disease or ulcerative colitis. Inflammatory polyps may be referred to as "pseudopolyps," which means false polyps and consist of irregularly shaped islands of residual intact colonic mucosa that result from the mucosal ulceration and regeneration that occurs in the epithelium of individuals with inflammatory bowel diseases (Morson et al. 1976). Giant pseudopolyposis of the colon
(pseudopolyp larger than 1.5 cm in size) is a very rare complication of inflammatory bowel disease and it may lead to colonic intussusception or luminal obstruction, but the
53 more important clinical significance is that it can be endoscopically confused with a malignancy. Research has shown that treatment of the inflammatory bowel disease can cause these polyps to regress, thus they are generally regarded as having no malignant potential (Lukas 2010; Choi et al. 2012)
Hyperplastic polyps are the most common, non-neoplastic growth in the colon
(Hyman et al. 2004). Slowly occurring proliferation usually arises in the basal portion of the intestinal crypt creating abnormal growths of intestinal structures, such as the villi.
Microscopically, the epithelial cells usually appear normal, but are in greater numbers or larger in size (Morson et al. 1976). Despite the fact that the cells in hyperplastic polyps are growing and reproducing, these are considered lower risk for developing into cancer
(Boland et al. 1983).
Hamartomatous polyps are benign, focal malformations that resemble a neoplasm in the tissue of its origin. Instead of being composed of increased numbers of epithelial cells, hamartomatous polyps are composed of a mixture of tissue elements and cells normally found in the mucosal layer of the intestine, but which are growing in a disorganized mass. This is not a malignant tumor, and it grows at the same rate as the surrounding tissues (Morson et al. 1976; Chan et al. 2006).
Adenomatous polyps, or adenomas, are benign neoplastic growths with variable metastatic potential that are derived from glandular epithelium of the intestine. The crypts of the intestinal tissue can be coiled, branched and crowded. Immune and endocrine cells may be present, but are scattered throughout the crypt instead of only residing at the crypt base (Morson et al. 1976). There are three characteristics that are used to determine the potential of adenoma transformation: size, villous pathology, and
54 the degree of dysplasia within the adenoma. The adenomatous proliferation is characterized by different degrees of cell dysplasia (atypia or loss of normal differentiation of epithelium) irregular cells with hyperchromatic nuclei,
(pseudo)stratified nuclei, nucleolus, decreased mucosecretion, and mitosis. The architecture may be tubular, villous, or tubulo-villous. In most cases, the basement membrane and muscularis mucosae are intact (Morson et al. 1976). Adenomas are the most common type of polyp and make up about 70% of the polyps found in the colon
(Aickin et al. 1996). With the addition of DNA mutations that occur over time, adenomas can develop into colon cancer (Cho et al. 1992). With regular colon cancer screening, these polyps can be found and removed. More recent research has found that the sessile, or flat, type of polyps may be more common than originally believed and may be harder to detect on screening.
Approximately 15% of polyps that are found and removed with colon cancer screening are villous or tubulovillous adenomas. Villous adenomas are sessile tumors characterized as leaf or finger-like projections of the lamina propria covered by mucinous epithelium (Morson et al. 1976). These polyps usually cover a large surface area and are more dangerous because they have a high potential of becoming malignant. Malignant polyps are adenomas that have invaded beyong the muscularis mucosae. The cancer cells have thus gained access to the submucosa, which contains lymphatics and blood vessels and can spread to adjacent lymph nodes and less commonly to distant organs. Villous adenomas may be sessile, or flat, making them more difficult to remove (Jain et al.
2012).
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An adenocarcinoma is a malignant growth of the intestinal epithelium that arises from glandular tissue and is the most common form of colon cancer (Stearns 1978).
Normal colonic glands are numerous in the colon tissue and tend to be simple and tubular in appearance with a mixture of mucus secreting goblet cells and water absorbing cells.
Adenocarcinomas can be divided according to the grade of differentiation into well, moderately or poorly differentiated or into low grade (encompassing well- to moderately differentiated tumors) and high grade (including poorly differentiated adenocarcinoma and undifferentiated carcinoma) (Morson et al. 1976). Histologically, tumors resembling original structures are classified as well differentiated. Tumor cells that lost any resemblance to original tissue, both in appearance and structure form, are denoted as poorly differentiated tumor cells. Function of the surrounding cells depends highly on the degree of differentiation of the intestinal tissue (i.e. loss of mucus secretion due to poorly differentiated goblet cells) (van den Broek et al. 2009).
1.4.2 Stages of Colon Cancer Development
Intestinal tumors typically begin as benign adenomas or polyps in the lining of the colon or rectum that if left untreated can become cancerous. In colon cancer, there are specific morphological changes that occur in the intestine that are used to classify distinct stages of colon cancer progression. There are 5 stages of colon cancer (Stage 0 to Stage
4) that are characterized based on the invasiveness of the cancerous cells. The mode of treatment and often times cancer prognosis, are highly dependent on the stage of colon cancer. For example, later stage adenocarcinomas are associated with poor prognosis and usually require radiation therapy for treatment.
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In Stage 0 (carcinoma in situ), abnormal cells are found in the mucosa (innermost layer) of the intestinal wall (Figure 1.8). Stage 0 colon cancer is the most superficial of all the lesions and is limited to the mucosa without invasion of the lamina propria. In
Stage 1, cancerous cells have formed in the mucosa and have spread through the epithelium, lamina propria and muscularis mucosae to the submucosa which is directly beneath the layers of the mucosa (Figure 1.8). Early adenomas form with the loss of heterozygosity (LOH) in APC, β-catenin or other components of the Wnt signaling pathway. Early adenomas are observed as clusters of abnormal cells that grow in the mucosa of the intestine (Tanaka et al. 1991). When adenomas grow into the lumen of the intestine, the polyp is then classified as an adenomatous polyp (Willson 1989; Paraskeva et al. 1990; Shelton 2002).
When cancerous cells spread to the submucosal layer located underneath the mucosa they are known as intermediate adenomas. Intermediate adenomas usually result from mutations in KRAS, BRAF, or sometimes COX-2 (Oshima et al. 1996; Yuen et al.
2002). Stage 2 is divided into three substages: Stage 2A, 2B and 2C that are characterized by the invasiveness of the cancer growth as it infiltrates the intestinal wall, but does not come into contract with lymphatic tissues (Figure 1.8). In Stage 2A, cancerous cells have spread through the muscle layer of the intestinal wall to the serosa. In Stage 2B, cancerous cells have spread through the serosa of the intestinal wall, but have not spread to nearby organs. In Stage 2C, cancerous cells have spread through the serosa of the intestine to nearby organs. (Willson 1989; Paraskeva et al. 1990; Shelton 2002).
Adenomas of Stage 3 are termed late adenomas and can be attributed to mutations in SMAD2/4, PI3KCA, or IGF-IIR (Fink et al. 2003; Oikonomou et al. 2006; Barbi et al.
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Figure 1.8 – Stage 0 to Stage 2 of colon cancer progression. Stage 0 colon cancer is the most superficial of all the lesions and is limited to the mucosa without invasion of the lamina propria. In Stage 1, cancerous cells have formed in the mucosa and have spread through the epithelium, lamina propria and muscularis mucosae to the submucosa. Stage 2 is divided into three substages (A, B, C) based on the invasiveness of the cancer growth as it infiltrates the intestinal wall, but does not come into contract with lymphatic tissues. Terese Winslow, LLC. 2011.
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2010). Stage 3 is also divided into 3 substages: 3A, 3B, and 3C, which are similar to that of substages 2A, 2B and 2C with the exception that in Stage 3 the cancerous growth comes into contact with lymph nodes surrounding the intestine (Figure 1.9). In Stage 3A, cancerous cells have spread through the mucosa to the submucosa and may have spread to the muscle layer of the intestinal wall. What is distinct from Stage 2 progression is that the cancer has spread to at least one but not more than 3 nearby lymph nodes or cancer cells have formed in tissues near the lymph nodes; or cancer has spread through the mucosa to the submucosa and has spread to at least 4 but not more than 6 nearby lymph nodes. Stage 3B, the cancerous growth has spread through the muscle layer of the intestinal wall to the serosa or has spread through the serosa but not to nearby organs and has spread to at least one but not more than 3 nearby lymph nodes or cancer cells have formed in tissues near the lymph nodes; or cancer has spread to the muscle layer or to the serosa and has spread to at least 4 but not more than 6 nearby lymph nodes; or cancer has spread through the mucosa to the submucosa and may have spread to the muscle layer of the intestinal wall reaching 7 or more nearby lymph nodes. Stage 3C, cancerous cells have spread through the serosa of the intestinal wall but has not spread to nearby organs reaching at least 4 but not more than 6 nearby lymph nodes; or cancer spread through the muscle layer to the serosa or has spread through the serosa but has not spread to nearby organs and has spread to 7 or more nearby lymph nodes; or has spread through the serosa and has spread to nearby organs, to one or more nearby lymph nodes or cancer has spread to one or more nearby lymph nodes or cancer cells have formed in tissues near the lymph nodes (Willson 1989; Paraskeva et al. 1990; Shelton 2002).
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Figure 1.9 – Stage 3 of colon cancer progression. Stage 3 is also divided into 3 substages: 3A, 3B, and 3C, which are similar to that of substages 2A, 2B and 2C with the exception that in Stage 3, the cancerous growth comes into contact with lymph nodes surrounding the intestine. Terese Winslow, LLC. 2011.
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Stage 4 is divided into substages 4A and 4B that are classified based on the target organs (Figure 1.10). In Stage 4, cancer may have spread through the intestinal wall and possibly to nearby organs or lymph nodes. This stage is usually caused by mutations in the potent oncogene, p53 (Baker et al. 1990). In Stage 4A, cancer has spread to one organ other than the colon, such as the liver, lung, or ovary, or to a distant lymph node. In
Stage 4B, cancer has spread to more than one organ outside the colon or into the lining of the abdominal wall (Willson 1989; Paraskeva et al. 1990; Shelton 2002).
1.5 Causes of Colon Cancer
There are both genetic and environmental causes of colon cancer in humans.
Mutations in many genes such as APC, MUTHY, MLH1, MSH2, MSH6, and PMS2 contribute to heritable forms of colon cancer, while mutations in many of these same genes and others such as p53 or KRAS can result in sporadic cases. Other diseases such as obesity and inflammatory bowel diseases like Crohn’s disease (CD) and ulcerative colitis (UC) are known to increase risk of colon cancer development in humans.
Environmental factors such as diet, obesity-associated disorders such as metabolic syndrome (MetS), physical inactivity, smoking, alcohol consumption and sleep have been shown to modulate risk of colon cancer development in many studies.
1.5.1 Hereditary Forms of Colon Cancer
One of the risk factors associated with colon cancer is a family history, where having a first degree relative with the disease can increase risk by 3-fold (Johns et al.
2001). It is estimated that about 15% of colon cancer cases can be attributed to specific inherited gene mutations (Vogelstein et al. 1993). Genetic mutations have been identified
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Figure 1.10 – Stage 4 of colon cancer progression. Stage 4 is divided into substages 4A and 4B that are classified based on the target organs. In Stage 4, cancer may have spread through the intestinal wall and possibly to nearby organs or lymph nodes. In Stage 4A, cancer has spread to one organ other than the colon, such as the liver, lung, or ovary, or to a distant lymph node. In Stage 4B, cancer has spread to more than one organ outside the colon or into the lining of the abdominal wall. Terese Winslow, LLC. 2011.
62 as the cause of inherited cancer risk in some colon cancer–prone families and these mutations are estimated to account for only 5% to 6% of colon cases overall. It is likely that other undiscovered genes and background genetic factors contribute to the development of familial colon cancer in conjunction with non-genetic and environmental risk factors such as diet (Lerman et al. 2004). Several gene abnormalities have been discovered for various colon cancer disorders that allow colon cancer to be transmitted to family members and passed through generations (i.e. familial adenomatous polyposis, attenuated familial adenomatous polyposis, MYH-associated polyposis, and hereditary non-polyposis colon cancer) (Table 1.1).
A well described hereditary form of colon cancer is familial adenomatous polyposis (FAP) that is characterized by the presence of hundreds, sometimes thousands of precancerous polyps in the colon, rectum or lower regions of the small intestine
(Bulow 1987). The polyps usually begin to form at puberty, and colon cancer almost always develops later in life. FAP is inherited as an autosomal dominant trait caused by a mutation in the tumor suppressor, Adenomatous Polyposis Coli (APC), which is located on human chromosome 5 (Kinzler et al. 1991; Nishisho et al. 1991). Over 800 different
APC mutations are observed in FAP patients ranging from codon 200 to 1581
(Nieuwenhuis et al. 2007). There are various clinical phenotypes of FAP which include attenuated (10-100 polyps), sparse (100-500 polyps), and profuse (>2,000 polyps) that are caused by differences in APC mutations (Nieuwenhuis et al. 2007). Individuals with FAP have a 90-100% lifetime risk of developing colon cancer (Table 1.1). Surgery is routinely used to remove the colon in order to prevent the development of cancer.
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Colon Cancer Disease Gene Mutated Polyp Site Other Cancer Risk Risk (%) Bone, skin, retinal, thyroid, brain, Familial Adenomatous Polyposis APC Small, Large 90-100 liver Bone, skin, retinal, thyroid, brain, Attenuated Familial Adenomotous Polyposis APC Small, Large 70-80 livers endometrial, liver, ovarian, MYH-Associated Polyposis MUTYH Small, Large 50-100 bladder, thyroid, skin Pancreatic, liver, brain, Hereditary Non-polyposis Colon Cancer MLH1, MSH2, Small, Large 60-80 gallbladder, ovarian, uterine, (Lynch Syndrome) MSH6, PMS2 kidney, bladder, stomach Gastric, ovarian, pancreatic, Peutz-Jeghers Syndrome STK11/LKB1 Small, large 30 gallbladder, breast, uterine, testicular SMAD4, Juvenile Polyposis Syndrome Small, Large 39 Gatric, pancreatic BMPR1A Breast, ovarian, uterine, cervix, Cowden Disease PTEN Small, Large 30 bladder, endometrial, thyroid, kidney Hereditary Mixed Polyposis Syndrome GREM1? Large ND Pancreatic, Renal, Thyroid Cronkihite-Canada Syndrome Small, large 41 Gastric
Table 1.1 – Genetics of colon cancer. Listed are the various hereditary forms of colon cancer including rare forms of the disease. Mutations in known genes are included. Lifetime risk is estimated from patients with known genetic mutations.
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Individuals that develop FAP are also at an increased risk of developing other cancer, for example in the thyroid, stomach and breast (Galiatsatos et al 2006).
Attenuated familial adenomatous polyposis (AFAP) is an inherited predisposition to colorectal cancer characterized by fewer than 100 adenomatous polyps in the colon and rectum. It is said to be attenuated because there are fewer polyps than in FAP (Table
1.1) and people with AFAP tend to be older at the diagnosis of their polyps (average age of 44 years) and cancer (average age of 56 years), which is 10 to 15 years later than in classic FAP (Lynch et al. 1995). Patients with AFAP often belong to families that also have members with classic FAP and have a 70-80% lifetime risk of developing colon cancer (Table 1.1). As in FAP, there may also be polyps higher up in the intestinal tract in the duodenum and stomach and an elevated risk of stomach, liver, and breast cancer
(Lynch et al. 1995). Similar to FAP, AFAP is often associated with abnormalities in APC, although the mutations tend to cluster in the 5′ and 3′ regions of exon 15 instead of throughout the entire gene (Friedl et al. 1996).
A milder type of hereditary colon cancer has been identified that is inherited in an autosomal recessive manner and is referred to as autosomal recessive familial adenomatous polyposis or MYH-associated polyposis (MAP). MAP is caused by mutations a gene known as MUTYH (mutY homolog) from the mutY in Escherichia coli
(Table 1.1)(Al-Tassan et al. 2002). MUTYH is a gene found on human chromosome 1 that is essential for proper DNA repair during replication (McGoldrick et al. 1995). MAP is a recently discovered hereditary colon cancer syndrome that can increase lifetime risk of colon cancer by 30-50% (Table 1.1). Affected patients typically do not have a multigenerational family history of polyps or cancer of the colon but may have brothers
65 or sisters with it (Al-Tassan et al. 2002). In addition to colon cancer, MAP patients are also at an increased risk of developing endometrial, liver, ovarian, bladder, and thyroid and skin cancers including melanoma, squamous epithelial, and basal cell carcinomas
(Vogt et al. 2009; Win et al. 2011).
Hereditary non-polyposis colon cancer (HNPCC) or Lynch syndrome is a hereditary cancer syndrome which carries a 50-60% lifetime risk of developing colon cancer (Table 1.1) and an above-normal risk of other cancers (uterus, ovary, stomach, small intestine, biliary system, urinary tract, brain, and skin)( Dunlop et al. 1997; Lynch et al. 2003). Mutations in the DNA mismatch repairs genes, MLH1 or MSH2, account for
90% of HNPCC cases with the remaining due to mutations in MSH6 or PMS2 genes all of which are inherited in an autosomal dominant pattern (Table 1.1) (Fearon 2011).
Given the larger number of genes associated with HNPCC, it is often harder to diagnose and clinicians look for a high incidence of colon or endometrial cancer in families.
1.5.2 Rare Types of Colon Cancer
In addition to the inherited intestinal cancer diseases discussed above, there are also many rare genetic syndromes that exist and encompass a small percentage of colon cancer cases (Table 1.1). Although rare in occurrence, these types of disorders can give valuable information regarding the functionality of many disease genes involved in cancer. Peutz-Jeghers Syndrome, Juvenile Polyposis Syndrome, Cowden disease,
Hereditary Mixed Polyposis Syndrome, and Cronkhite-Canada Syndrome comprise a small collection of diseases whose patients are diagnosed based on the presence of intestinal polyps.
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Peutz-Jeghers (PJ) syndrome is a rare, early onset disorder that is characterized by hamartomatous (benign) GI polyps and mucocutaneous lesions that cause patches of hyperpigmentation in the mouth and on the lips, hands and feet (Williams et al. 1978;
Burdick et al. 1982). Polyp can range in size from microadenomas to polyps several centimeters in size and are usually found in the jejunum and ileum of the small intestine, but are also observed in the rectum, colon, stomach and duodenum. Associated abnormalities include bladder, bronchial and nasal polyps. Scoliosis, clubbed foot, bony tumors, as well as ovarian cysts have also been reported in PJ patients (Dormandy 1957).
Family history is an important factor used in diagnosing PJ syndrome as the disease occurs in an autosomal dominant inheritance pattern. Present on human chromosome 19, mutations in STK11 (serine/threonine kinase 11 or liver kinase B1) occur in about 90-
100% of patients diagnosed with this disorder (Table 1.1). Patients with PJ syndrome have as high as a 93% increased risk of developing any cancer (i.e. gastric, ovarian, pancreatic, or gallbladder cancers), a 66% increased risk in many gastrointestinal cancers, and a 30% lifetime risk of developing colon cancer (Table 1.1) (Hemminki et al. 1998;
Jenne et al. 1998).
Juvenile Polyposis Syndrome (JPS) is a rare disease characterized by the onset of benign hamartomatous juvenile polyps (benign intestinal polyps) as a child or within the first two decades of life. Clinically, JPS is defined by the presence of 5 or more juvenile polyps in the colon, juvenile polyps throughout the GI tract including the stomach as well as the small and large intestines, or any number of juvenile polyps and a positive family history of JPS (Jass et al. 1988; Chow et al. 2005). Although the polyps begin as benign growths, anywhere from 9-50% of cases can progress to malignancy. The lifetime risk of
67 developing colon cancer is about 39% (Table 1.1)(Chow et al. 2005). About 15-20% of patients with JPS develop other congenital abnormalities such as twisting of the intestine
(intestinal malrotation), cleft palate, brain or heart defects, hydrocephalus, polydactyly or genital and urinary tract defects. In addition to a 39% increase in colon cancer risk, JPS patients are also prone to developing gastric and pancreatic cancers (Howe et al. 1998).
Autosomal dominant mutations in SMAD4 or BMPR1A, genes involved in cell growth and proliferation, cause this rare disorder (Table 1.1) (Sayed et al. 2002).
Cowden disease or multiple hamartoma syndrome or PTEN hamartoma tumor syndrome is an autosomal dominant disorder characterized by intestinal hamartomas, facial trichilemmomas (benign neoplasms), oral mucosal papillomatosis, goiter (thyroid disease), acral keratoses, and palmoplantar keratosis (thickening of palms and soles) (Eng
1998; Marsh et al. 1998). Other clinical features of Cowden syndrome are diverse and include macrocephaly, oral papillomas and fibromas, skin tags, ovarian cysts, hearing loss, cataracts, and lipomas. Patients with Cowden syndrome also have an increased risk for developing many cancers including breast, endometrial, ovarian, uterine, thyroid, and kidney (Starink et al. 1986; Marsh et al. 1998). Lifetime risk of developing colon cancer in Cowden disease patients is about 30% (Table 1.1)(de la Chapelle 2004). Mutations in phosphatase and tensin homolog (PTEN), a modulator of G1 cell cycle progression, have been identified in 85% of subjects diagnosed with Cowden disease (Fearon 2011).
Hereditary Mixed Polyposis Syndrome (HMPS) is a hereditary condition that results in the development of a variety of types of polyps in the large bowel that can include tubular adenomas, villous adenomas, flat adenomas, atypical junenile polyps, or serrated adenomas. The most common polyp type is the hamartomatous juvenile polyp,
68 although adenomatous polyps (growths in the lining of the colon that can become cancerous), hyperplastic polyps (noncancerous growths in the lining of the colon), and adenocarcinomas may occur as well (Cao et al. 2006). HMPS differs from other colon syndromes, like FAP, in that the colon polyps are fewer in number, of mixed histology, and appear to be confined to the large bowel (Cao et al. 2006). Recent literature has shown that GREM1, involved in the reduction of the bone morphogenetic protein (BMP) pathway, is the genetic link to HMPS. (Table 1.1) (Jaeger et al. 2012). Individuals with
HMPS are at an increased risk for developing colon cancer, but because of its rare occurrence, the estimated lifetime risk has yet to be determined (Table 1.1). Patients with
HMPS are also at risk for developing pancreatic and renal cancers, and papillary thyroid carcinomas have also been reported (Tomlinson et al. 1999).
A very rare disorder, Cronkhite-Canada syndrome (CCS) is characterized by the presence of diffuse gastrointestinal polyposis in both the small and large intestines, dystrophic changes in the fingernails, alopecia (hair loss), cutaneous hyperpigmentation, diarrhea, weight loss, abdominal pain and several electrolyte disturbances
(hypocalcemia, hypomagnesimia, and hypokalemia) (Cronkhite et al. 1955).
Complications include gastrointestinal bleeding, intussusception, rectal prolapse, portal vein thrombosis, membranous glomerulonephritis, and protein-losing enteropathy
(Cronkhite et al. 1955). In addition to a 41% increase in developing colon cancer, CCS patients also have increased risk for developing gastric cancer (Table 1.1)(Egawa et al.
2000). With less than 400 cases reported worldwide, little is known about CCS and the genetic abnormalities that may lead to its development (Egawa et al. 2000).
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1.5.3 Inflammation Associated Colon Cancer
Inflammatory bowel disease (IBD) is a group of inflammatory conditions in the colon or small intestine, such as Crohn’s disease or ulcerative colitis (Xavier et al. 2007).
Epidemiologic and clinical studies indicate that patients affected by ulcerative colitis
(UC) and Crohn's disease (CD) have an increased risk of developing colon cancer by as much as 18% and 3%, respectively, and the risk of colon cancer is increased among patients with longstanding UC or CD (Pohl et al. 2000; Eaden et al. 2001). In recent years, the role of immune cells and their products have been shown to be pivotal in initiation and progression of colitis-associated colon cancer.
Chronic inflammation is thought to induce dysplasia by inducing DNA modifications in intestinal epithelial cells. Indeed, chronic accumulation of activated immune cells such as neutrophils, macrophages and dendritic cells is accompanied by the release of oxygen and nitrogen reactive species, which are known to induce genomic mutations (Meira et al. 2008; Westbrook et al. 2009). Additionally, chronic inflammation is associated with DNA methylation and histone modification that can result in silencing of tumor suppressors or activation of oncogenes (Grady et al. 2008; Colotta et al. 2009).
All these processes have been associated with the altered expression of genes involved in carcinogenesis such as p53, APC, KRAS and BCL-2 (Xie et al. 2008). Once initiated, dysplastic cells are subjected to the effect of cell-derived growth factors and cytokines which contribute to tumor growth.
Further evidence to support a role of inflammation in intestinal tumorigenesis is the use of non-steroidal anti-inflammatory drugs (NSAIDs) such as aspirin. An epidemiological study of 662,424 both men and women that reported aspirin use,
70 demonstrated that aspirin use was correlated with decreased colon cancer mortality (Thun et al. 1991). In the Sandler study, 635 patients with colorectal cancer were randomized to receive 325mg aspirin or placebo daily. After a follow-up of around 31 months, the mean number of adenomas was lower in the aspirin group while the incidence of one or more adenomas was 17% in aspirin treated patients versus 27% in the placebo group (Sandler et al. 2003). Another study examined 1121 patients with colorectal adenomas that were assigned to receive 81 or 325mg aspirin or placebo daily. Follow-up colonoscopy after 32 months showed an incidence of one or more adenomas of 38% in the 81mg aspirin group,
45% in the 325mg aspirin group, and 47% in the placebo group (Baron et al. 2003).
Studies conducted in the mouse model of intestinal tumorigenesis, ApcMin/+, have shown that aspirin induces apoptosis in intestinal epithelium through modulation of NFκB (Stark et al. 2007).
It has also been demonstrated that aspirin is a powerful inhibitor of cyclooxygenase-2 (COX-2), an important enzyme in prostaglandin synthesis that is overexpressed in colon cancer (Mitchell et al. 1993; Sano et al. 1995). Cyclooxygenase enzymes are involved in the conversion of arachidonic acid to prostaglandins that can have potent pro-inflammatory potential. Azoxymethane (AOM) treated rats supplemented with celecoxib, a COX-2 inhibitor, showed reductions in both incidence and multiplicity of colon tumors by about 93 and 97%, respectively. It also suppressed the overall colon tumor burden in these rats by more than 87% (Kawamori et al. 1998).
Treatment of ApcMin/+ mice with celecoxib resulted in a 29-50% reduction in intestinal polyps and 17% reduction in tumor size (Jacoby et al. 2000). FAP patients treated with celecoxib showed 28% and 30.7% reduction in polyp number and size, respectively,
71 demonstrating that COX-2 inhibitors were effective against genetic predispositions to human intestinal cancer (Steinbach et al. 2000).
1.5.4 Sporadic Causes of Colon Cancer
In addition to genetic predisposition to developing colon cancer, anywhere from
75-90% of colon cancer cases are considered sporadic, with no known family history or hereditary genetic mutation (Heyer et al. 1999). It is now well established that all cancers result from an accumulation of mutations that enhance a tumor cell’s ability to thrive
(Hanahan et al. 2011). For example, somatic mutations can result in the inactivation of tumor suppressors (i.e. APC, p53 or SMAD4) or activation of oncogenes (i.e. KRAS,
BRAF, PI3KCA or PTEN) that drive fierce proliferation and progressive transformation of normal cells to malignant derivatives (Fearon 2011) (Figure 1.11, Markowitz et al.
2009).
Cancer is a “multiple hit” disease, where tumorigenic cells grow by clonal evolution that is driven by multiple mutations (Hanahan et al. 2011). Colon cancer follows this “multiple hit” progression and develops through distinct morphological and histopathological changes that are characterized by the invasiveness of the tumor as well as the change in cancer genotype. Cancer cells develop many essential alterations in cell physiology that collectively help to maintain a pro-tumorigenic state while allowing them to infiltrate normal healthy tissues. Douglas Hanahan and Robert A. Weinberg have termed these cancer cell capabilities as “Hallmarks of Cancer” (Hanahan et al. 2011).
According to Hanahan and Weinberg, there are ten hallmarks of cancer that are distinctive and complementary and contribute to the progression of normal cells to a
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Figure 1.11 – The genetics of sporadic colon cancer. In the progression of colon cancer, genetic alterations target the genes that are identified at the top of the diagram. The microsatellite instability (MSI) pathway is initiated by mismatch-repair (MMR) gene mutation or by aberrant MLH1 methylation and is further associated with downstream mutations in TGFBR2 and BAX. The question mark indicates that genetic or epigenetic changes specific to metastatic progression have not been identified. Key growth factor pathways that are altered during colon neoplasia are shown at the bottom of the diagram. CIN (chromosomal instability), EGFR (epidermal growth factor receptor), 15-PGDH (15-prostaglandin dehydrogenase), and TGF-β (transforming growth factor β). Markowitz et al. 2009.
73 heterogeneous population of cancerous cell types. As normal cells progress through cancerous stages, they collect mutations that cause them to acquire many of these hallmark capabilities in a multistep fashion. These hallmarks of cancer include sustaining proliferative signaling, evading growth suppressors, avoiding immune destruction, enabling replicative immortality, tumor-promoting inflammation, activating invasion and metastasis, inducing angiogenesis, genome instability and mutation, resisting cell death, deregulating cellular energetics (Figure 1.12, Hanahan et al. 2011).
The acquisition of genomic instability is a crucial feature in tumor development and there are at least 3 distinct pathways in colorectal cancer pathogenesis: chromosomal instability (CIN), microsatellite instability, and CpG island methylator phenotype pathways. Most cases of colorectal cancer arise through the CIN pathway, which is characterized by widespread imbalances in chromosome number (aneuploidy) and loss of heterozygosity. The loss of genomic stability, DNA repair defects, and aberrant DNA methylation all drive the development of colorectal cancer by facilitating the multiplicity of tumor-associated mutations (Figure 1.11, Markowitz et al. 2009). Over the past three decades, molecular genetic studies have revealed some critical mutations underlying the pathogenesis of the sporadic forms of colon cancer. While some prominent tumor- suppressor genes such as APC, KRAS, and p53 are well explored, a larger collection of genes that are mutated in subsets of human colon cancer have yet to be appreciated
(Table 1.2)(Fearon 2011). Together with DNA-methylation and chromatin structure changes, the mutations act to disrupt conserved signaling pathways that are critical for the regulation of cellular metabolism, proliferation, differentiation, and survival (Fearon
2011).
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Figure 1.12 – Hallmarks of cancer. There are ten hallmarks of cancer that are distinctive and complementary and contribute to the progression of normal cells to a heterogeneous population of cancerous cell types. As normal cells progress through cancerous stages, they collect mutations that cause them to acquire many of these hallmark capabilities in a multistep fashion. Hanahan et al. 2011.
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Gene Type of Mutation Estimated Frequency of Alteration Oncogenes KRAS Point mutations (codons 12, 13, 61) 40% (>75% of mutations are at codon 12) NRAS Point mutations (codons 12, 13, 61) <5% PIK3CA Point mutations activating kinase activity 15–25% BRAF Point mutations activating kinase activity (e.g., V600E) 5–10% (mutations linked to CIMP-positive CRCs) EGFR Gene amplification 5–15% CDK8 Gene amplification 10–15% CMYC Gene amplification 5–10% CCNE1 Gene amplification 5% CTNNB1 Stabilizing point mutations, in-frame deletions near N terminus <5% NEU (HER2) Gene amplification <5% MYB Gene amplification <5% Tumor-Suppressor Genes P53 Point mutation, allele loss 60–70% (>95% of point mutations are missense) APC Frameshift, point mutation, deletion, allele loss 70–80% (nearly all mutations lead to truncated proteins) FBXW7 Nonsense, missense, deletion 20% PTEN Nonsense, deletion 10% SMAD4 Nonsense, missense, allele loss 10–15% SMAD2 Nonsense, deletion, allele loss 5–10% SMAD3 Nonsense, deletion 5% TGFβIIR Frameshift, nonsense 10–15% (>90% of MSI-H CRCs have mutations) TCF7L2 Frameshift, nonsense 5% (mutations in both MSI-H and MSS CRCs) ACVR2 Frameshift 10% (>80% of MSI-H CRCs have mutations) BAX Frameshift 5% (often one allele in ∼50% of MSI-H CRCs)
Table 1.2 – Mutations found in sporadic colon cancer. In green are oncogenes commonly mutated, while in in orange are tumor suppressors that are common inactivated.
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Chromosome instability (CIN) describes an increased rate of chromosome missegregation in mitosis resulting in a failure to maintain the correct chromosomal complement (euploidy). The aberrant chromosomal state of a cell can be classified based on the changes in ploidy, gain or loss of whole chromosomes (aneuploidy) or gross chromosomal rearrangements (GCR), all of which are hallmarks of solid cancers. The most common type of genomic instability in colon cancer is chromosomal instability
(CIN), which causes numerous changes in chromosomal copy number and structure.
Chromosomal instability is an efficient mechanism for causing the physical loss of a wild-type copy of tumor suppressor genes, such as APC, p53, and SMAD4 (Fearon
2011). This phenomenon is characteristic of about 80-85% of sporadic colon cancers.
There are numerous rare mutations that result in the inactivation of chromosomal stability during replication such as MRE11A and CDC4, which when present in colon tumors, account for the chromosome instability (Markowitz et al. 2009).
Mutations in APC are the initiating event in many colon cancers that cause the transformation of normal epithelium to adenomatas tissue (Rapaich Moser et al. 1990)
(Figure 1.11, Markowitz et al. 2009). One of the most common mutations in sporadic cases of colon cancer involves the inactivation of the APC gene. Mutations in APC can account for more than 80% of sporadic colon cancer cases (Fearon 2011). Patients that carry inactivating mutation in APC are at almost a 100% risk of developing colon cancer by the age of 40 (Markowitz et al. 2009). The tumor suppressor, APC, functions as part of a “degradation complex” in the Wnt signaling pathway that is involved in the degradation of β-catenin. When APC is inactivated, β-catenin levels increase, enter the
77 nucleus and drive transcription of many oncogenes (Nusse 2005). The Wnt signaling pathway and mutations in APC will be discussed in more detail below.
Defects in DNA-repair pathways lead to an accumulation of mutations in genomic DNA that result from non-repair or mis-repair of modifications introduced into the DNA by endogenous or exogenous agents or by the malfunction of DNA metabolic pathways. In some colon cancer patients, there is inactivation of genes required for repair of base-base mismatches in DNA, collectively referred to as mismatch repair genes
(Fishel et al. 1993). These inactivations can be inherited as discuss above with HNPCC, or sporadic in nature. Somatic inactivation of mismatch repair genes occurs in approximately 15% of patients with sporadic colon cancer and includes genes such as
MLH1 or MSH2 (Thibodeau et al. 1996).
Epigenetic silencing of genes, mediated by aberrant DNA methylation, is another mechanism of gene inactivation in colon cancer. In the normal genome, cytosine methylation occurs in areas of repetitive DNA sequences outside of exons and is largely excluded from the CpG-rich “CpG islands” in the promoter regions of approximately half of all genes (Issa 2004). Among the loci that can undergo aberrant methylation in colon cancer, a subgroup seems to become abnormally methylated as a group, a phenomenon called the CpG island methylator phenotype (CIMP). CIMP is observed in about 15% of colorectal cancers and is present in nearly all such tumors with aberrant methylation of
MLH1 (Toyota et al. 1999).
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1.5.5 The APC Mutation and Wnt Signaling
The Wnt signaling pathway is present in many species and is crucial for an immense number of biological processes during various stages of development. Wnt comes from the combination of the gene names Wingless (Drosophila melanogaster) and
Int-1 (Mus musculus) and can be found in slime molds to humans, with remarkable conservation in higher organisms (Nusse 2005; Clevers et al. 2012). Most mammalian genomes, including the human genome, harbor 19 Wnt genes, falling into 12 conserved
Wnt subfamilies, emphasizing evolutionary and functional importance of Wnt proteins
(Clevers et al. 2012).
In normal cells, the canonical pathway begins with the binding of one of the Wnt lipid-modified proteins (i.e. WNT1, WNT2, WNT2B, WNT3, WNT3A, etc.) to one of the ten Frizzled (FRZ) receptors (FRZ1-FRZ10)(Figure 1.13a). This binding leads to the activation of members of the Disheveled (Dvl) family and usually leads to an accumulation of β-catenin in the cytoplasm. This increase in β-catenin allows for nuclear localization, where it can interact with LEF/TCF to initiate transcription of Wnt target genes important for cellular development such as c-Myc, Cyclooxygenase-2 (COX-2),
Cyclin-D1, Tcf-1 or Sox9 (Nusse 2005). FRZ receptors interact with a transmembrane protein called LDL Receptor-Related Protein (LRP) that also associates with Wnt and a scaffolding protein, Axin. It is thought that LRP binding with the Wnt/FRZ/Axin complex is important for stabilization (Clevers et al. 2012).
In the absence of Wnt proteins, β-catenin must be degraded so genes involved in cell growth and proliferation are not constitutively active (Figure 1.13b). A complex of proteins forms a “degradation machine” that functions to bind and tag β-catenin for
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a. b. c.
Wnt
Dvl
L R R P L
L R R P L
L R R P L
Frizzled Frizzled Dvl Frizzled Axin Dvl CK1α
Axin GSK-3β Axin GSK-3β GSK-3β P β P P APC APC P CK1α P β APC CK1α β β β β β β β β β β β β β β β β β β β β β β
Groucho β β TCF TCF TCF
Doerner, SK (2012) Figure 1.13 – Wnt signaling in health and disease. A. In normal cells, the canonical pathway begins with the binding of one of the Wnt lipid-modified proteins to one of the ten Frizzled (FRZ) receptors. This binding leads to the activation of members of the Disheveled (Dvl) family and usually leads to an accumulation of β-catenin in the cytoplasm. B. In the absence of Wnt proteins, β-catenin must be degraded so genes involved in cell growth and proliferation are not constitutively active. A complex of proteins forms a “degradation machine” that functions to bind and tag β-catenin for degradation. This degradation machine consists multiple proteins (APC, GSK3β, AXIN, and CK1α) that reside in the cytoplasm. C. Alterations in the Wnt signaling pathway are associated with many types of carcinogenesis, especially colon cancer Mutations in the regulator genes, β-catenin, APC and AXIN, as well as in other components of this pathway have been reported. The effect of the various mutations is an increase in the levels of β- catenin that are localized to the nucleus and subsequent transcription of Wnt targets.
80 degradation. This degradation machine consists multiple proteins (APC, GSK3β, AXIN, and CK1α) that reside in the cytoplasm. Axin, no longer bound to Wnt or FRZ, acts as the scaffolding protein that holds the degradation machine together. To this scaffold, the
Adenomatous Polyposis Coli (APC) protein stabilizes the binding of β-catenin to the complex whereis is phosphorylated by two kinases, GSK-3β and CK1α. Phosphorylated
β-catenin is then ubiquitinated and destroyed by the proteosome. When Wnt ligand binds to a Frizzled family receptor and a co-receptor of the LRP family, the
APC/Axin/CK1/GSK3β destruction machine is inhibited, leading to the stabilization of β- catenin and its translocation to the nucleus where it interacts with TCF/LEF family transcription factors. In the absence of signal, TCF/LEF factors bind DNA at Wnt- responsive genes and interact with other factors (e.g. Groucho, histone deacetylase) to repress transcription (Nusse 2005; Clevers et al. 2012).
Alterations in the Wnt signaling pathway are associated with many types of carcinogenesis, especially colon cancer (Figure 1.13c) (Fodde et al. 2001; Suzuki et al.
2004). Chronic activation of the Wnt signaling pathway has been implicated in the development of a variety of human malignancies, including colorectal carcinomas, hepatocellular carcinomas (HCCs), melanomas and uterine and ovarian carcinomas.
Mutations in the regulator genes, β-catenin, APC and AXIN, as well as in other components of this pathway have been reported (Takahashi et al. 1998; Fodde et al.
2001). The effect of the various mutations is an increase in the levels of β-catenin that are localized to the nucleus and subsequent transcription of Wnt targets. Alterations in direct target genes like c-Myc, cyclin D1, VEGF, c-jun, matrix metalloproteinase (MMP-7), and
81 claudin-1 have all been shown to induce colon cancer in humans (Tetsu et al. 1999;
Brabletz et al. 1999; Miwa et al. 2001; Nusse 2005).
In 1991, investigators from multiple labs concurrently published the first work demonstrating a role for Wnt signaling in disease, revealing a role of APC in FAP
(Rapaich Moser et al. 1990; Nishisho et al. 1991). The following year, APC mutations were identified and are now observed in ~85% of sporadic colorectal tumors, demonstrating that adherent Wnt signaling through the activation of gene transcription by
β-catenin, is crucial factor in colon cancer (Cho et al. 1992; Clevers et al. 2012).
1.5.6 Environmental Causes of Colon Cancer
In addition to genetic contributions to colon cancer, many environmental causes exist that are known to increase colon cancer risk and mortality such as physical inactivity, reduced sleep, smoking, and high alcohol consumption. Out of 52 studies on physical activity and colon cancer, 37 found a statistically significant association between increased levels of physical activity and decreased colon cancer risk in at least one comparison. Accumulated evidence suggests that physical activity is associated with a
25% reduction in colon cancer risk (Wolin et al. 2011). In studies examining the effect of sleep and night shift work schedules, the Nurses' Health Study found that women and men chronically exposed to night and rotating night shift work had a 50% increase in risk of developing colon cancer compared with controls working only during the day
(Schernhammer et al. 2003). A meta-analysis was used to examine the association between smoking and colon cancer and found that compared to never smokers, current smokers had a 17% higher risk of developing colon cancer and a 40% higher risk of
82 colon cancer related mortality (Liang et al. 2009). Both lifetime and baseline alcohol consumption increase colon and rectum cancer risk, with more apparent risk increases for alcohol intakes greater than 30 g/day and subjects who drank seven or more alcoholic drinks per week had a statistically significant, 72% increase in risk of colon cancer as compared with nondrinkers (Khan et al. 2010).
Other environmental influences such as diet and diet-induced obesity (DIO) are closely associated with increased risk of developing colon cancer in humans (Wynder
1976; Yehuda-Shnaidman et al. 2012). Disruptions in energy balance are also responsible for modulating inflammation and metabolic disorders (i.e. Metabolic syndrome, MetS), factors also associated with increased colon cancer risk (Yehuda-Shnaidman et al. 2012).
Diet and DIO are important factors in the development of colon cancer and will be the focus of this thesis work, and therefore, will be discussed in greater detail below.
1.6 Understanding Digestion and Metabolism
Because the primary focus of this research is on diet and diet-induced obesity in relation to intestinal cancers, it is essential to understand the mechanisms behind digestion and metabolism. Consuming and digesting food are complex processes that involve intricate relationships between hormones and enzymes and includes cooperation from many systems of the body such as the endocrine, gastrointestinal, and nervous.
Many of the hormonal and enzymatic signals involved in digestion and metabolism can strongly influence dietary consumption and obesity and some are thought to play an active role in cancer development.
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1.6.1 Understanding the Process of Digestion
Digestion is the complex process in which nutrients are extracted and absorbed from food by a collection of organs and enzymes that comprises the gastrointestinal system. The gastrointestinal system includes the gastrointestinal tract (mouth, pharynx, esophagus, stomach, small intestine and large intestine) and accessory organs (salivary gland, liver, gallbladder, and pancreas) that secrete substances into the tract by connecting ducts (Figure 1.14).
Digestion begins in the mouth through mechanical grinding and an enzyme called salivary amylase in a process called mastication (Goldberg et al. 1975). After chewing, food is swallowed and passed through the pharynx, which helps keep food from entering the lungs. From the pharynx, the food/saliva mix (now called bolus) travels through the esophagus to the stomach. Gastric juices in combination with the muscular walls of the stomach vigorously mix the food to form a mixture called chyme. It is at this point that the chyme enters the small intestine and more aggressive digestion begins (Burks et al.
1985).
The pancreas acts as an exocrine gland and secretes enzymes into the small intestine via a duct (Figure 1.14). Pancreatic juices include pancreatic amylase, trypsin and chymotrypsin, and lipase which break down carbohydrates, proteins and fats, respectively (Wormsley et al. 1972). The pancreas is also responsible for the production of insulin, and therefore functions as an endocrine gland. Insulin is a hormone, produced by the pancreas, which is central to regulating carbohydrate and fat metabolism in the body. Insulin causes cells in the liver, muscle, and fat tissue to take up glucose from the blood, storing it as glycogen. Insulin stops the use of fat as an energy source by
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Figure 1.14 – Components of the digestive system. Digestion is the complex process in which nutrients are extracted and absorbed from food by a collection of organs and enzymes that comprises the gastrointestinal system. The gastrointestinal system includes the gastrointestinal tract (mouth, pharynx, esophagus, stomach, small intestine and large intestine) and accessory organs (salivary gland, liver, gallbladder, and pancreas) that secrete substances into the tract by connecting ducts. http://www.mille- soeren.dk/20_du_kan_redde_liv/20a_anatomy_pictures/26_Digestive_System_Anterior _View.jpg 85 inhibiting the release of glucagon (Steele 1966). With the exception of the metabolic disorders diabetes mellitus and metabolic syndrome (which will be discussed in later sections), insulin is provided within the body in a constant proportion to remove excess glucose from the blood, which otherwise would be toxic. When blood glucose levels fall below a certain level, the body begins to use stored sugar as an energy source through glycogenolysis, which breaks down the glycogen stored in the liver and muscles into glucose, which can then be utilized as an energy source (Eisenstein 1967).
The liver produces bile which is stored in the gallbladder and then sent to the small intestine. Bile emulsifies fats into smaller droplets to allow for further processing
(Holt 1972). The small intestine consists of small projections called villi each containing microvilli that function to increase the surface area for absorption. Each villi also contains blood vessels and a lacteal (lymph vessel). Peptases and maltases are embedded within the plasma membrane of the microvilli and function to completely breakdown peptides and disaccharides, respectively. Absorption is the most important function of the small intestine. Active transport moves glucose and amino acids into the intestinal cells and then out where they are picked up by capillaries. Fatty acids produced by the digestion of fat enter the villi via diffusion and are reassembled into fat (triglycerides).
They combine with proteins and are expelled by exocytosis. They move into the lacteals for transport via the lymphatic system in the mesenteric blood stream and travel to the liver for filtration and detoxification. Any remaining material travels to the large intestine where vitamin K, salt and water are absorbed before it is expelled as feces (Crane 1968;
Semenza 1968; Kay 1969)
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1.6.2 Regulation of Appetite and Metabolism
Hunger and satiety are carefully regulated by hormonal signals produced by components of the nervous and endocrine systems. Most of the integration of signals affecting food intakes place in an area of the brain called the hypothalamus, specifically the arcuate nucleus (Biebermann et al. 2012). Two pathways exist: one inhibiting food intake and increasing metabolism and the other stimulating nutrient intake and decreasing metabolism. The first pathway, the melanocortin pathway, is made up of appetite- inhibiting neurons containing pro-opiomelanocortin (POMC), which releases α- melanocyte-stimulating hormone (α-MSH). When α-MSH is released, is binds to melanocortin receptors, melanocortin- 3/4 receptor (MC3R/MC4R), present on second- order neurons, to inhibit food intake and increase the rate of metabolism. The stimulation of feeding is provided by the neuropeptide Y (NPY) pathway. Hunger signals stimulate the release of NPY, which binds to Y1 receptors to increase food intake and the storage of calories. The NPY system also releases agouti-related peptide (AgRP), which is an antagonist of MC4R. In addition, peptides that stimulate the melanocortin system inhibit the NPY system (Biebermann et al. 2012).
Leptin is an appetite-suppressing hormone secreted mostly by fat cells
(adipocytes) and that influences food intake by crossing the blood brain barrier to reach the hypothalamus (Maffei et al. 1995). When leptin levels in the brain rise, levels of
POMC increase in the hypothalamus, which stimulates the production of α-MSH and subsequent activation of MC3R and MC4R. Stimulation of MC3R and MC4R result in decreased food intake and adipose tissue deposition. In addition to activating POMC neurons, leptin inhibits the production of NPY, a stimulator of food intake, reduced
87 energy expenditure via decreased brown fat thermogenesis, increased white adipose deposition, and weight gain (De Vos et al. 1995; Maffei et al. 1995). Leptin also inhibits the production of AgRP, the MC3R and MC4R antagonist. Consequently, when leptin levels rise, food intake decreases but energy expenditure increases. In contrast, decreases in leptin levels produce the opposite results.
Adiponectin is a protein hormone that modulates a wide array of functions on a diverse number of target tissues that is exclusively secreted from adipose tissue (and also from the placenta in pregnancy) into the bloodstream and levels are inversely correlated with body fat percentage. For example, adiponectin has insulin-sensitizing, anti- inflammatory, as well as distinct effects of lipid metabolism. Key metabolic actions include regulation of glucose and lipid metabolism through stimulation of fatty acid oxidation, suppression of hepatic (liver) glucose output, and increased insulin sensitivity in the liver and skeletal muscle (Kelesidis et al. 2006; Ziemke et al. 2010). Adiponectin enhances insulin-induced phosphorylation of the insulin receptor and the ability of insulin to activate the phosphorylation of the adaptor protein insulin receptor substrate 1 (IRS-1)
(Stefan et al. 2002; Wang et al. 2007). Adiponectin regulates pancreatic β-cell proliferation in conjunction with leptin, suggesting that adiponectin may regulate insulin secretion directly (Kharroubi et al. 2003). Protection against insulin resistance and chronic inflammation are due to the effect of adiponectin on systemic carbohydrate and lipid profile improvements (Berg et al. 2001; Park et al. 2011).
Endocrine cells lining the gastrointestinal tract are the source of several peptides known to regulate feeding behavior. Cholecystokinin (CCK) was the first peptide shown to elicit satiety (Gibbs et al. 1973). CCK is released by cells in the duodenal mucosa in
88 response to fat and protein digestion products and in addition to inhibiting food intake, also inhibits gastric emptying which contributes to the satiety response (Gibbs et al.
1973). Another satiety factor, peptide YY (PYY), is secreted from enteroendocrine cells of the ileum and colon that are stimulated by fat digestion products. Circulating PYY reaches the hypothalamus, inhibiting NPY neurons and POMC neurons (Pappas et al.
1985). Ghrelin is secreted primarily by endocrine cells of the stomach, stimulates the release of growth hormone and increases appetite by stimulating neurons that express
NPY (Wren et al. 2000; Kamegai et al. 2001). Plasma levels of ghrelin increase during fasting, peaking just before food intake begins or when the subject is expecting a meal, and fall within an hour of the start of feeding (Tschöp et al. 2001).
Insulin is produced in response to food intake by the β-cells of the pancreas and is central to regulating carbohydrate and fat metabolism in the body. Insulin causes cells in the liver, muscle, and fat tissue to take up glucose from the blood, storing it as glycogen inside these tissues (Matschinsky 1990; Samuel et al. 2012). Like leptin, insulin can be transported across the blood brain barrier and is associated with decreased food intake
(Andik et al. 1949). Insulin stops the use of fat as an energy source by inhibiting the release of glucagon. With the exception of the metabolic disorder diabetes mellitus and
MetS, insulin is provided within the body in a constant proportion to remove excess glucose from the blood, which otherwise would be toxic. When blood glucose levels fall below a certain level, the body begins to use stored sugar as an energy source through glycogenolysis, which breaks down the glycogen stored in the liver and muscles into glucose, which can then be utilized as an energy source (Lönnroth 1991; Samuel et al.
2012).
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1.7 The Obesity Epidemic
In the past 50 years, the worldwide occurrence of obesity in humans has risen at an alarming rate. The World Health Organization (WHO) generally defines obesity as having a body mass index (BMI) equal to or higher than 30, as calculated by weight divided by height squared (kg/m2). Based on BMI, there are several overweight and obesity categories defined as overweight (BMI ≥ 25.0 to 30.0 kg/m2), Class I obesity
(BMI ≥ 30.0 to < 35.0 kg/m2), Class II obesity (BMI ≥ 35.0 to < 40.0 kg/m2), and Class
III obesity (BMI ≥ 40.0 kg/m2) (WHO 2000). Developed countries such as the United
States are the most heavily impacted by excess engery intake and it is estimated by the
WHO that 500 million people worldwide, or 1 out of 10 individuals, are considered obese. High income countries are not the only ones to suffer from excess of body fat, as the condition is on an startling rise in the developing world as well (Gill et al. 2005;
WHO 2006). The United States has one of the highest percentages of obese individuals
(BMI ≥30), with 33.9% of the adult population (18 years or over) classified as obese. In addition to The United States, many other countries have fallen victim to the obesity epidemic, such as Naura (78.5%), American Samoa (74.6%), Tokelau (63.4%), French
Polynesia (40.9%), Saudi Arabia (35.6%) and Panama (34.7%). The United States is followed by United Arab Emirates (33.7%), Egypt (30.3%), Bahrain (28.9%), Kuwait
(28.8%), New Zealand (26.5%), Mexico (23.6%), Canada (23.1%), and Greece (22.5%)
(WHO 2003; WHO 2006).
Careful regulation of appetite and metabolism are essential to maintain a normal body weight and prevent the development of disease. Mutations in many of the factors involved in appetite have been shown to cause obesity in humans and mouse models. For
90 example, mutations in MC4R were discovered in a group of obese children, all under the age of 10 (average BMI > 34kg/m2)(Yeo et al. 1998). Mouse models have been used extensively to study the genetics and biology of obesity. Numerous genetic models of obesity exist in the mouse and include mice with mutations in the lethal Agouti Yellow
(AY) (Morgan 1950), leptin (Barinaga 1995), melanocortin 4 recptor (MC4R) (Huszar et al. 1997) and melanocortin 3 receptor (Butler et al. 2000). For example, mice deficient in leptin (ob/ob mouse strain) are obese, but showed a 30% reduction in body weight when treated with human or mouse leptin for two weeks (Halaas et al. 1995).
1.7.1 Obesity-related diseases
Obese individuals have an increased risk for developing many other diseases such as heart disease, hypertension, infertility, obstructive sleep apnea, dyslipidemia, non- alcoholic fatty liver disease, type 2 diabetes, and metabolic syndrome (MetS) (Wynder
1976; Stein et al. 2004) (Figure 1.15). There is also a strong link between obesity and many malignancies including cancers of cancers of the esophagus, pancreas, prostate, renal, colon and rectum, postmenopausal breast, endometrium and kidney (Wynder 1976;
Yehuda-Shnaidman et al. 2012) (Figure 1.15). Because obesity plays such a large role in the development of MetS and both of these diseases are closely associated with colon cancer, MetS will be discussed in more detail below.
Metabolic syndrome (MetS), also referred to as insulin resistance syndrome or syndrome X, is a well-described clinical condition associated with obesity and is associated with colon cancer risk. MetS is defined by elevated body weight, dyslipidemia, hypertension, and insulin resistance (Prasad et al. 2012). This constellation
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Figure 1.15 – Medical complications associated with obesity. Obesity is associated with increased risk of many co-morbities ranging from strokes to the development of many cancers. Elsevier, Inc.
92 of clinical features is associated with an increased risk for cardiovascular disease and type 2 diabetes mellitus. Insulin resistance and type 2 diabetes mellitus are important features of obesity, whereby 90% of type 2 diabetes patients are overweight or obese
(WHO 2003). Insulin is a hormone produced by the beta cells of the pancreas in response to high blood glucose levels. In insulin-resistant patients, the cellular response to insulin is impaired, so more insulin must be produced to maintain normal blood glucose levels
(Prasad et al. 2012).
Genetic studies of obesity divide the condition into two forms. First, the monogenic forms of obesity are due to single gene defects such as leptin or melanocortin
4 receptor (MC4R) deficiencies and are very rare, comprising less than 5% of severe obesity cases. (Farooqi et al. 2005). The second form of obesity is more complex because both genetic and environmental factors contribute to obesity susceptibility.
Hundreds of genes are known to have minor contributions in determining excess body fat, making this second form of obesity a combination of interactions between genetics and developmental, behavioral and environmental influences (Friedman et al. 1991).
Unlike monogenic obesity, many genetic factors contribute to the multifactorial forms, and thus, these forms are described as polygenic.
1.7.2 Environmental Effects on Obesity
Obesity is a leading preventable cause of death worldwide and it is estimated that over 365,000 deaths a year are due to this escalating disease (Flegal et al. 2005;
Olshansky et al. 2005). Environment, especially diet, plays a monumental role in obesity development. Increased energy intake and decreased energy expenditure are the major
93 causes of obesity (Nkondjock et al. 2003). The increase in accessibility and affordability of high fat, calorie dense foods in addition to a sedentary lifestyle, probably contribute largely to the rapid increase in obesity cases.
A prime example of the strong influence of gene-diet interactions in the development of obesity is the assimilation of the Pima Indians to a Westernized culture in their migration from Mexico to Arizona (Lillioja et al. 1988; Ravussin 1993) The Pima
Indians living in Arizona are exposed to energy-dense foods and a decreased need for physical labor and therefore, have an extremely high prevalence of obesity and MetS.
Pima Indians that still live in Mexico, who follow a traditional diet and customs, have a much lower prevalence of these conditions (Baier et al. 2004). Although the Pima
Indians may have a strong genetic susceptibility to obesity and metabolic syndrome, these studies demonstrate the powerful impact of environment, especially diet, on these conditions.
1.7.3 Inflammation and Obesity
High fat diet-induced obesity and insulin resistance are associated with a chronic state of low-grade inflammation (Figure 1.16). Macrophages represent a heterogeneous population of immune cells that are instrumental in the immune response, specifically innate immunity. Recent studies have shown that macrophages are key mediators of obesity-induce insulin resistance, with a progressive infiltration of macrophages into adipose tissue (Shoelson et al. 2007; Olefsky et al. 2010). This chronic state of inflammation is characterized by elevated serum levels of proinflammatory cytokines
(IL-1β, IL-6, IL-8, IL-12 and TNFα), chemokines (monocyte chemotactic protein 1,
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Obese Adipose Tissue
Lean Adipose Tissue
Weight Gain
↓ TNFα ↑ TNFα ↓ Leptin ↑ Leptin ↓ Free Fatty Acids ↑ Free Fatty Acids ↓ IL-6 ↑ IL-6 ↓ IL-1 ↑ IL-1 ↓ IL-8 ↑ IL-8 ↓ Resistin ↑ Resistin ↓ MCP-1 ↑ MCP-1 ↑ IL-10 ↓ IL-10 ↑ Adiponectin ↓ Adiponectin
Alternatively activated (M2) Classically activated (M1)
Figure 1.16 – Adipose tissue, adipokines and inflammation. Adipose tissue can be described by at least three structural and functional classifications: lean with normal metabolic function, obese with mild metabolic dysfunction and obese with full metabolic dysfunction. As obesity develops, adipocytes undergo hypertrophy owing to increased triglyceride storage. With limited obesity, it is likely that the tissue retains relatively normal metabolic function and has low levels of immune cell activation and sufficient vascular function. However, qualitative changes in the expanding adipose tissue can promote the transition to a metabolically dysfunctional phenotype. Macrophages in lean adipose tissue express markers of an M2 or alternatively activated state, whereas obesity leads to the recruitment and accumulation of M1 or classically activated macrophages, as well as T cells, in adipose tissue. Anti-inflammatory adipokines, such as adiponectin or interleukin-10 (IL-10), are produced by lean adipose tissue. In states of obesity, adipose tissue generates large amounts of pro-inflammatory factors, including leptin, resistin, tumour necrosis factor (TNF), IL-1, IL-6, IL-8, and monocyte chemotactic protein-1 (MCP-1).
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MCP-1 and macrophage inflammatory protein 1, MIP-1), acute phage reactants (C- reactive protein or serum amyloid A), insulin reistance-associated adipokines (retinol binding protein 4, RBP4 or resistin) as well as decreased serum levels of the negative acute phase reactants (transcortin and transferrin) and insulin sensitivity-associated adipokines (adiponectin, visfatin or omentin) (Shoelson et al. 2007; Olefsky et al. 2010)
(Figure 1.16)
Studies in cultured murine adipocytes demonstrated that supplementation of
TNFα was sufficient both to recreate the insulin resistant phenotype observed in animal models fed a high fat diet and to promote obesity (Serrano-Marco et al. 2012). Central regulators of inflammation including nuclear factor κB (NFκB) and Jun N-terminal kinase 1 (JNK1) are chronically activated in adipose tissue from obese and insulin- resistant subjects. In response to TNFα stimulation, both JNK1 and inhibitor of NFκB kinase β (IKKβ, an NFκB activating kinase) directly phosphorylate serine residues on
IRS-1, the major downstream effector of the insulin receptor (McGee et al. 2011; Liu et al. 2012). These studies provide evidence to support the hypothesis by which inflammation disrupts insulin signaling in a self-sustaining manner.
Obesity is characterized by the accumulation of lipid in white adipose tissue
(WAT). What was once thought to be a simple storage depot for lipid molecules is now understood to be a complex endocrine organ comprised of preadipocytes, mesenchymal stem cells, macrophages, endothelial cells and fibroblasts. Adipose tissue plays a vital role not only in regulating energy homeostasis, but also the secretion of many proteins, called adipokines, that have been shown to influence immunity, insulin sensitivity, inflammation, blood pressure, lipid metabolism, energy homeostasis and appetite (Braun
96 et al. 2011). Dietary fatty acids are one important group of compounds that can regulate adipose tissue metabolism and secretory function. Dietary fat can act as both a major risk in the development of colon cancer or a protective factor that reduces its incidence
(Doubeni et al. 2012). Defining specific components or parts of a diet that can influence cancer risk is difficult, as isolating and controlling for individual nutrients in humans diets is near impossible.
Epidemiological studies show a strong and consistent link between features of
MetS (i.e. insulin resistance) and colon cancer in humans. In the EPIC (European
Prospective Investigation into Cancer and Nutrition) study examined 984 cases of colon cancer and discovered altered glucose metabolism was associated with an increased risk of colon and rectal cancers (Aleksandrova et al. 2012). Patients that were in the highest quartile of insulin and undergoing colonoscopy at the University of Carolina hospitals had a 2.2-fold significantly higher risk of colon adenoma formation (Vinikoor et al.
2009). In a study of Japanese men, MetS was defined by abdominal obesity in combination with any 2 of the following conditions (elevated triacylglycerols, lowered
HDL cholesterol, elevated blood pressure, and raised fasting glucose) was associated with a significant 40–50% increase in risk of colon adenomas (Kono et al. 1998). In a study conducted by the Metabolic Syndrome and Cancer Project (Me-Can), factors associated with MetS were significantly associated with colon cancer risk in 578,700 men and women patients (Stocks et al. 2010).
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1.8 Dietary Fat: The Good, the Bad, and the Ugly
Dietary fat is an essential part of our diet and is necessary for for proper growth and development. An important role of fat is to provide energy to the body, whereby fatty acid oxidation can supply almost 2 times the amount of energy that can be obtained from carbohydrates (Huffman et al. 2011; Campoy et al. 2012). Vitamins A, D, E and K are fat-soluble, and can only be digested, absorbed and transported in conjunction with fats.
Fat plays an essential role in the development of the brain and retina, maintaining healthy hair and skin, insulating internal organs against injury, maintaining body temperature, and promoting healthy cellular functions and proper cell membrane formation and fluidity. Dietary consumption of specific fatty acids can drastically change lipid membrane composition and diet therefore, plays a large role in cellular composition and function (Brookheart et al. 2009; Cinti 2011; Huffman et al. 2011).
The rise in colon cancer rates have been attributed to environmental factors, such as high dietary fat. One example is the rise in colon cancer incidence in Japanese immigrants (Potter et al. 1993; Flood et al. 2000). Data collected by the National Cancer
Institute’s Surveillance, Epidemiology and End Results (SEER) project showed that
Japanese men born in Japan had a slightly reduced risk of colorectal cancer compared with US-born white men. In contrast, Japanese men born in the US experienced rates twice as high as foreign-born Japanese men and had rates about 60% higher than those of
US-born white men. The incidence of colorectal cancer among Japanese women born in the US was about 40% higher than that of either women born in Japan or US-born white women (Flood et al. 2000). Colon cancer mortality was also increased in US-born
Japanese patients (Shimizu et al. 1987; Flood et al. 2000). Evidence suggests that this
98 drastic increase in colon cancer development and mortality is due to an increase in consumption of Westernized dietary components, mainly high dietary fat (Potter et al.
1993).
There are many different kinds of fats, but each is a variation on the same chemical structure. All fats are derivatives of fatty acids and glycerol. The molecules are called triglycerides, which are triesters of glycerol (an ester being the molecule formed from the reaction of the carboxylic acid and an organic alcohol). The properties of any specific fat molecule depend on the particular fatty acids that constitute it. Different fatty acids are composed of different numbers of carbon and hydrogen atoms and can also differ in the carbon:hydrogen ratio (Wolfe 1998).
Epidemiological studies have long tried to investigate the role of specific fatty acids on colon cancer in humans. Methods for collecting nutritional data in humans rely on self-reporting, food intake questionnaires, and food diaries, which can be very general in nature and inaccurate. For example, a self-report study is a type of survey where respondents record the type and quantity of food consumed without researcher interference. Human error and personal bias can strongly influence the results from this type of data collection. For example, errors might include incorrect food quantities due to misinterpretation of food portion sizes or difficulties in remembering food consumed over a period of time. Individuals may exaggerate the consumption of certain nutritional types such as healthy, “more acceptable” foods or misrepresent data based on social pressures. For this reason, many studies found it difficult to separate specific components of the diet to examine nutritional effects on colon cancer, therefore no differences were observed between the specific fatty acid tested and disease outcome
99
(Tuyns et al. 1987; Neoptolemos et al. 1988; Neoptolemos et al. 1991; Hendrickse et al.
1994; Hietanen et al. 1994; Slattery et al. 1997; Schloss et al. 1997; Baró et al. 1998).
Discussed below are studies conducted in humans and mice that provide evidence for the consumption of specific fatty acids and colon cancer outcome. Dietary studies are divided into saturated, monounsaturated or polyunsaturated fatty acid sections. Each type of dietary fatty acid, saturated, monounsaturated, and polyunsaturated, are required for maintainance of many biological functions and it has been demonstrated that specific types of fat can have beneficial effects on different diseases while others exert detrimental responses.
1.8.1 Saturated Fatty Acids
Saturated fat is fat that consists of triglycerides containing only saturated fatty acids. Saturated fatty acids have no double bonds between the individual carbon atoms of the fatty acid chain. That is, the chain of carbon atoms is fully "saturated" with hydrogen atoms (Khosla et al. 2012). There are many kinds of naturally occurring saturated fatty acids, which differ mainly in number of carbon atoms, from 3 carbons (propionic acid) to
36 (hexatriacontanoic acid). Various fats contain different proportions of saturated and unsaturated fat. Animal fats (i.e. butter, cheese, cream and lard) as well as plant products
(coconut, cottonseed and palm kernel oils) contain large amounts of saturated fatty acids such as butyric, lauric, myristic, palmitic and stearic acids. Although many studies suggest an undesirable health impact of consuming saturated fat, its consumption is essential for proper cell membrane formation, necessary for absorption of calcium into bone, and production of hormones cortisol, testosterone, estrogen and progesterone, boost
100 immune function. Studies have demonstrated that consumption of high amounts of saturated fats can be detrimental or beneficial to human health, but the health effects are dependent on the type of fatty acid (Nkondjock et al. 2003; Khosla et al. 2012).
1.8.1.1 Butyric Acid
Butyric acid is a short-chain fatty acid (SCFA) that is the main end product of fermentation of fiber (Cummings et al. 1987). In one case – control study that included
98 patients, a significant increase in butyric acid intake was found in the control but not the colon cancer patients (Neoptolemos et al. 1988). Another study demonstrated a significant reduction in butyric acid in colon cancer 31 patients in Denmark (Clausen et al. 1991). An ecological study was conducted using data on 20 healthy populations in 12 countries and showed that high butyrate consumption seemed to protect again chronic bowel diseases, including colon cancer (Bradburn et al. 1993). Butyric acid intake was examined in 1993 cases of colon cancer and 2410 population-based controls and was shown to be increased, again suggesting a positive associated between butyric acid and colon health in humans (Slattery et al. 1997).
Butyric acid or butyrate is derived from the microbial metabolism of dietary fiber in the colon where it plays an important role in linking colonocyte turnover and differentiation to luminal content (Macfarlane et al. 2012). In addition, butyrate appears to have both anti-inflammatory and cancer chemopreventive activities. For example, human HT-29 colon adenocarcinoma cells treated with 5mM butyrate showed a 40% decrease in proliferation compared to controls (Barnard et al. 1993). Another study showed that administration of butyrate to human Caco-2 colon carcinoma cells
101 significantly decreased c-myc levels, and subsequently decreased growth and proliferation (Souleimani et al. 1993). Butyrate pretreatment of an APC mutant human colon cell line (HT-29 cells) inhibited the tumor necrosis factor-alpha (TNF-α)-induced nuclear translocation of the proinflammatory transcription factor NFκB (Yin et al. 2001).
Another study in SW620 cells, human colonic carcinoma cells that harbor a mutation in
APC, demonstrated that butyrate treatment could induce G0-G1 cell cycle arrest and apoptosis (Bordonaro et al. 1999). Significant increases in apoptosis were observed in the colon of rats treated with azoxymethane (AOM), a colon specific carcinogen when give butyrate (Caderni et al. 1998).
Butyrate has been shown to act as an inhibitor of histone deacetylases (HDAC), which function to remove acetyl groups from lysine amino acids on histones, allowing the histones to bind the DNA more firmly. This is important because DNA expression is regulated by acetylation and deacetylation and can be modified based on how tight the
DNA wraps around histones (Choudhary et al. 2009). The HDAC inhibitors butyrate has been shown to block the TNFα induced activation of COX-2 protein and mRNA synthesis, and dramatically suppressed COX-2 activity in HT-29 cells (Tong et al. 2004).
It was also demonstrated that butyrate can rapidly promote cell-cycle arrest, apoptosis and influence cellular differentiation through modulation of NFκB (Place et al. 2005).
More recently, it was demonstrated that butyrate could modulate the expression of a potent Wnt signaling ligand, Wnt5, through its HDAC activity in human colon cancer lines (Li et al. 2012).
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1.8.1.2 Lauric and Myristic Acids
Lauric and myristic acids are two types of saturated fats that are considered medium-chain fatty acids (MCFAs). In contrast to the beneficial effects observed in butyric acid consumption, lauric and myristic acids appear to promote colon tumorigenesis. One study demonstrated a significant rise in lauric and myristic acid amounts in subjects at high risk of colon cancer (Neoptolemos et al. 1988). A case – control study noted a significant increase in lauric acid intake with colon cancer risk
(Slattery et al. 1997).
In murine RAW 264.7 cells, a monocyte/macrophage cell line, treatment with lauric or myristic acid could independently induce NFκB activation and expression of
COX-2 (Lee et al. 2001). Cyclooxygenase catalyzes the conversion of arachidonic acid to prostaglandin endoperoxide, and numerous studies have demonstrated that the levels of prostaglandins in various tumors, or the tumor's biosynthetic capacity of prostaglandins, are greater when compared with normal tissues (Bennett et al. 1977; Bennett et al. 1997).
Treatment of human colon cancer cells, HCT-116 cells, with lauric or myristic acid caused activation of NFκB and increased expression of the pro-inflammatory cytokine, interleukin (IL)-8, which has been shown to increase migration of colon cancer cells. It was also demonstrated that treatment of cultures of human non-malignant colon epithelial
(HCEC) and malignant SW48, SW480, HT29 and HCA-7 colon cells increased COX-2 which resulted in a 20-fold increase in prostaglandin production when treated with lauric or myristic acid (Wilson et al. 1999; Sharma et al. 2001; Zhao et al. 2007).
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1.8.1.3 Palmitic and Stearic Acids
Two types of long-chain fatty acids (LCFAs) include palmitic and stearic acids.
Fatty acid effects on colon cancer risk were examined in a national prospective case- control study in Scotland that included 1,455 incident cases and 1,455 matched controls.
This study found that palmitic acid was dose-dependently associated with increased colon cancer risk (Theodoratou et al. 2007). In human Caco-2 cells treated with palmitic acid demonstrated increased proliferation (van Greevenbroek et al. 1995). In ApcMin/+, levels of erythrocyte membrane compositions of palmitic acid were significantly associated with the development of intestinal tumors (Kuriki et al. 2008).
Similarly, several studies have demonstrated an increase in stearic acid intake and colon cancer risk. A clinical trial reported a significant elevation of stearic acid in colon cancer specimens while no difference was observed in normal tissue (Neoptolemos et al.
1988). Another small clinical investigation of 29 patients recorded a significant increase of stearic acid in the plasma of colon cancer patients compared to their controls (Baró et al. 1998). A case – control study also showed an increase in stearic acid consumption in colon cancer patients and reported elevations of stearic acid in the plasma and phospholipids compared to controls (Neoptolemos et al. 1991).
Stearic acid has been shown to increase proliferation in human colon cancer cells lines, as HT-29 cells treated with 30μM stearic acid showed an 11-23% increase in cellular growth compared to controls (Awad et al. 1995). Male Sprague-Dawley rats were injected weekly with dimethylhydrazine (DMH), elevations in stearic acid were correlated with increased colon tumors when compared to mice injected with saline.
When membrane phospholipids were examined, significantly high amounts of stearic
104 acid were observed in the tumor burdened mice compared to saline injected controls
(Habib et al. 1987). Membrane composition has been shown to be important in anti- cancer immunity and one study demonstrated that high levels of membrane stearic acid in tumor cells can inhibit the immune response and subsequent apoptosis (Schlager et al.
1978).
1.8.2 Monounsaturated Fatty Acids
Monounsaturated Fatty Acids (MUFAs) are fatty acids that have one double bond in the fatty acid chain and all of the remainder of the carbon atoms in the chain are single- bonded. MUFAs include myristoleic (C14:1), palmitoleic (C16:1), oleic (C18:1), gadoleic (20:1) and erucic (C22:1) acids. These fatty acids are found in red meat, dairy and plant products, and nuts. Oleic acid is the major component of olive oil and consequently, a considerable amount of attention has been focused on this MUFA and the consumption of the Mediterranean diet. The components of the traditional Mediterranean diet are: a high monounsaturated to saturated fat ratio; moderate alcohol consumption; a high consumption of legumes, cereals, fruits, and vegetables; low consumption of meat and meat products; and moderate consumption of milk and dairy products (Trichopoulou et al. 2000).
1.8.2.1 The Mediterranean Diet and Olive Oil
In general, Mediterranean countries have lower rates of colon cancer compared with other Western countries. For example, colon cancer mortality in Greece is about
40% lower than that in the United Kingdom (Ferlay et al. 2004; Parkin et al. 2005). An
105 ecological study comprising 28 countries reported that 76% of the inter-country variation in colon cancer incidence rates could be explained by three dietary factors, meat, fish and olive oil. Meat and fish were positively associated with the development of colon cancer, while olive oil was negatively associated (Stoneham et al. 2000). Three out of six case- control studies undertaken in Mediterranean populations showed an inverse association between monounsaturated to saturated lipid ratio intake and colorectal cancer
(Trichopoulou et al. 2000).
A case-control study conducted in the Marseilles region of southern France examined 399 patients with colon cancer and observed a reduction in olive oil intake compared to the age- and sex-matched controls (Macquart-Moulin et al. 1986). The relationship between various added (seasoning) fats and colon carcinoma risk was investigated using data from a second case-control study conducted in six Italian areas.
Cases were 1953 patients with histologically confirmed colon carcinomas, while the controls were 4154 subjects with no history of cancer. This study found that olive oil intake was negatively associated with risk of colon carcinomas (Braga et al. 1998).
Rats chemically treated with 1,2-dimethylhydrazine (DMH) fed a higher olive oil- based diet developed a significantly lower number of aberrant crypt foci (ACF) than rats fed a low concentration of olive oil. Olive oil dose-dependently downregulated the expression of both Bcl-2 and COX-2 in colonic mucosa and also abrogated the upregulation of Bcl-2 by DMH (Schwartz et al. 2004). Rats treated with AOM and supplemented with 5% dietary olive oil showed significant decreases in aberrant crypt foci (ACF) and prostaglandin E2 (PGE2), a product of arachidonic acid and potent pro- inflammatory factor (Bartolí et al. 2000).
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1.8.2.2 Oleic Acid
Oleic acid is an omega-9 (ω-9) monounsaturated fatty acid that is the major component of olive oil and can also be found in meats, nuts and dairy products.
Although numerous studies have been conducted on the beneficial effects of olive oil, few have investigated specific supplementation with oleic acid. A study conducted with human colon cancer cell lines show that treatment of HT-29 and Caco-2 cells with oleic acids resulted in decreased proliferation and increased apoptosis. It was also demonstrated in these cells that oleic acid could decrease factors associated with inflammation and tumorigenesis such as COX-2 and Bcl-2 (Llor et al. 2003).
Additionally in HT-29 cells, oleic acid has been shown to inhibit store-operated calcium entry, a calcium influx pathway important for proliferation and inflammation as well as calcium induced apoptosis in cancer cells (Carrillo et al. 2012).
1.8.2.3 Oleic:Stearic Acid Ratio
A few studies have suggested that the ratio of oleic acid to stearic acids is important in determining disease outcome. In two human studies, a decreased erythrocyte oleic:stearic acid ratio has been reported in patients with colorectal cancer and it has been proposed that similar changes exist in the cancer tissue (Mosconi et al. 1989;
Neoptolemos et al. 1991). Mice treated with DHM and fed diets high in stearic fatty acids that were supplemented with oleic acid showed reduction in polyp multiplicity and size (Takeshita et al. 1997). As described above, stearic acid increases risk of colon cancer in human and animal models. It was demonstrated in human cell culture that oleic acid can inhibit the proliferative effects of stearic acid as well has inhibit stearic acid-
107 induced NFκB activation and intercellular adhesion molecule-1 (ICAM-1) expression
(Harvey et al. 2010).
1.8.3 Polyunsaturated Fatty Acids
Polyunsaturated fatty acids (PUFAs) contain more than one double bond, and are therefore not inundated with hydrogen bonds like saturated fatty acids. The term
“unsaturated” refers to the fact that the molecules contain less than the maximum number of hydrogen atoms. In fatty acids the carbon atom of the methyl group at the end of the hydrocarbon chain is called the omega carbon (Li et al. 1994). PUFAs are essential for the proper functioning of the cell, particularly in intracellular signaling. The composition of PUFAs in the cell membrane can drastically change the functional efficiency and can be modulated by diet (Szachowicz-Petelska et al. 2007). Circulating fatty acids are affected by dietary consumption and provide substrates for energy production, for incorporation into lipid-containing structures and for storage lipid (Raatz et al. 2001).
There are two general groups of PUFAs that will be discussed, which are classified based on the location of the double bond from the methyl carbon: omega-3 (the double bond is three carbons from the methyl terminus) and omega-6 polyunsaturated fatty acids.
PUFAs are not interconvertible, and dietary substitution of one results in a competitive reduction in concentration of the other in all tissues (Li et al. 1994; Petrik et al. 2000b).
Omega-3 (ω-3) polyunsaturated fatty acids are essential fatty acids commonly found in plant and marine oils that include α-linolenic, eicosapentaenoic and docosahexaenoic acids (Li et al. 1994). Omega-6 (ω-6) polyunsaturated fatty acids are essential fatty acids
108 commonly found in corn, soybean, sunflower, and palm oils and include arachidonic, linoleic and γ-linolenic acids (Cunnane et al. 2003).
1.8.3.1 Alpha-Linolenic Acid
Consumption of α-linolenic acid (ALA) is an omega-3 polyunsaturated fatty acid that is associated with beneficial effects on disease outcome in many studies. In one clinical study, a significant decrease in plasma ALA concentration was observed in colon cancer patients compared to hospital-based controls (Baró et al. 1998). In another clinical study, serum phospholipids were measured in patients with FAP and compared to healthy controls. It was demonstrated that patients with FAP had significantly reduced levels of
ALA compared to control patients (Almendingen et al. 2007). Another clinical investigation demonstrated that patients with a normal colon exhibited high mucosal
ALA content when compared to those with colon adenomas or colon cancer (Fernández-
Bañares et al. 1996). Another study measured free fatty acids in patients at different stages of colon cancer progression and show that levels of ALA decreased as the stages of cancer advanced (Szachowicz-Petelska et al. 2007).
1.8.3.2 Eicosapentaenoic and Docoshexaenoic Acids
Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are essential ω-3 fatty acid found exclusively in fish and in some seaweeds. Numerous studies have determined that EPA and DHA have an inverse relationship with colon cancer. Although
EPA and DHA are metabolized differently, nearly all studies which address the association between ω-3 fatty acids and colon cancer in humans use a mixture of EPA
109 and DHA. Because most studies supplement them together, they will be discussed concurrently.
Significantly decreased EPA levels were observed in the mucosa and plasma phospholipid profiles of patients with adenomas or colon cancer compared to healthy controls (Fernández-Bañares et al. 1996). Numerous investigations have demonstrated decreased EPA intake and thus decreased plasma levels of EPA in patients with colon cancer compared to controls (Schloss et al. 1997; Baró et al. 1998). A 12-week, double- blind, randomized, placebo-controlled trial was conducted in Italy on the effect of ω-3 fatty acids, specifically EPA, on mucosal cell proliferation in 20 subjects at risk for colon cancer. A significant reduction was found in the abnormal mucosal cell proliferation in the experimental group receiving EPA. A longer investigation of 6 months revealed that
EPA supplementation (4.1g per day) increased mucosal composition of this fatty acid and significantly decreased intestinal proliferation in cancer patients (Anti et al. 1992; Anti et al. 1994). Similar to that seen with EPA, treatment of colon cancer patients with DHA
(1.1g per day) led to a reduction in rectal proliferation (Anti et al. 1992; Anti et al. 1994).
Several trials have observed significantly low intake and plasma concentrations of DHA and EPA among colon cancer patients as well as individuals at high risk for developing colon cancer (Karmali 1989; Schloss et al. 1997; Baró et al. 1998). Studies conducted in
ApcMin/+ demonstrated that DHA and EPA could decrease polyp multiplicity and size by
50% and significantly reduced pro-inflammatory prostaglandin levels compared to control-fed mice (Petrik et al. 2000).
The distinct beneficial effects of docosahexaenoic acid (DHA) have been investigated in more detail in animal models and human colon cancer cell lines. DHA
110 decreased ACF and polyp number by 40% in rats treated with DMH and significantly reduced ACF and tumor multiplicity in rats treated with AOM (Takahashi et al. 1993;
Takahashi et al. 1997). In human colon cancer cells, DHA was shown to activate many genes involved in apoptosis, such as cytochrome c, caspases 5, 8, 10 and 15 while decreasing expression of anti-apoptotic Bcl-2 family members as well as members involved in the prostaglandin synthesis pathway such as COX-2 and PGE2. In human
HT-29 and HCT116 cells, DHA has also been shown to reduce the levels of PPARγ, which regulates fatty acid storage and glucose metabolism (Narayanan et al. 2001; Lee et al. 2002; Calviello et al. 2004). Additionally, DHA in combination with the saturated fat, butyrate, has been shown to enhance mitochondrial lipid oxidation and calcium- dependent apoptosis in human HCT116 cells (Kolar et al. 2007).
Eicosapentaenoic acid (EPA) has also been independently investigated in more mechanistic detail and has beneficial effects on colon cancer. ApcMin/+ mice and AOM treated rats fed diets supplemented with EPA showed significantly decreased polyp number as well as decreased levels of COX-2 and PGE2 (Minoura et al. 1988; Whelan et al. 2002). Prostaglandin synthesis as well as PPARγ expression was significantly reduced in human HT-29 cells after treatment with EPA. These same studies demonstrated a significant decrease in proliferation and induction of apoptosis in the HT-
29 human colon cancer cell line (Dommels et al. 2003; Allred et al. 2008). One study observed that treatment of human HCT116 cells with EPA resulted in reductions in DNA polymerase activity and cell cycle arrest at the G1 checkpoint (Kumamoto-Yonezawa et al. 2009).
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1.8.3.3 Arachidonic Acid
Arachidonic acid (AA) is an omega-6 fatty acid that is associated with detrimental effects on disease outcome. Two independent studies demonstrated AA levels were significantly increased in plasma and intestinal tissue of colon cancer patients compared to controls (Neoptolemos et al. 1991; Hendrickse et al. 1994). Levels of AA serum phospholipids were significantly elevated in patients suffering from FAP when compared to healthy controls (Almendingen et al. 2007).
AA is the precursor to the production of prostaglandins, specifically the potent pro-inflammatory member, PGE2, in a process that requires COX-2 (Greene et al. 2011).
Expression of COX-2 in human gastric adenocarcinoma tissues has significantly higher levels of COX-2 mRNA when compared with paired gastric mucosal specimens devoid of cancer cells (Ristimäki et al. 1997). In one study, prostaglandin-producing suppressor monocytes were examined in 55 colon cancer patients and compared to 57 healthy controls. It was demonstrated that the prostaglandin-producing suppressor monocytes of colon cancer patients produced higher levels of PGE2, and thus, PGE2 levels were higher than observed in the healthy controls (Balch et al. 1984). Another study demonstrated that PGE2 levels are increased in colon cancer tumors (Hendrickse et al. 1994). The levels of prostaglandin E2 (PGE2), PGF2 alpha, PGI2, thromboxane A2 (TXA2), and leukotriene B4 (LTB4), which represent the cyclooxygenase and 5-lipoxygenase pathways, were determined in 21 pairs of surgically excised human colon cancer and histologically normal mucosa samples 5 to 10 cm away from the tumor. The levels of
PGE2 were elevated in colon cancer samples as compared with histologically normal mucosa samples distant from the cancer, whereas levels of prostacyclin (PGI2) were
112 decreased and no differences were observed between the other factors (Rigas et al. 1993).
Direct AA treatment significantly increased growth in two murine colon adenocarcinoma cell lines (MAC26 and MAC13) (Hussey et al. 1994). In rats treated with AOM or DMH and supplemented with AA showed a significant increase in colon cell proliferation, levels of AA in membrane lipids and tumor number (Petry et al. 1984; Nicholson et al.
1991).
1.8.3.4 Linoleic Acid
Linoleic acid (LA) is an essential fatty acid found in corn oil and is a major constituent of the American diet (Dupont et al. 1990; Kant 2000). Diets high in corn oil have been shown to significantly increase polyp multiplicity in various rodent studies
(Reddy et al. 1984; Reddy et al. 1988; Singh et al. 1997). Data surrounding the effect of
LA on intestinal tumorigenesis is complicated by the fact that early studies did not differentiate between LA and an alternative isomer, conjugated linoleic acid (CLA).
Without differentiating between specific LA isomer specific, numerous groups demonstrated that LA had a beneficial effect on colon cancer outcome (Tuyns et al. 1987;
Hietanen et al. 1994; Fernández-Bañares et al. 1996; Baró et al. 1998). Not until more recent studies was it appreciated that different LA isomers could have contrasting effects on disease (Kelley et al. 2007).
The Netherlands Cohort Study, which comprised 120,852 individuals (531 of which were diagnosed with colon cancer), detected that LA intake was associated with increased colon tumors. Specifically, this group observed a significant association with
LA and tumors that contained KRAS mutations (Weijenberg et al. 2007). LA is the
113 precursor in the biosynthesis of AA and subsequent pro-inflammatory prostaglandins, such as PGD2 and PGE2. Human Caco-2 cells supplemented with LA showed increases in cell growth and proliferation (Kim et al. 2002). In another study, human SW480 cells were treated with LF and CLA for 24 hours. Cells treated with LA showed significant elevations in cell proliferation and increases in levels of factors involved in the prostaglandin synthesis pathway, such as PGD2 and PGE2, none of which were observed in the CLA treated cells (Miller et al. 2001). AOM-treated rats supplemented with 5% linoleic acid demonstrated a significantly higher incidence of colon tumors, more tumors per rat, and greater malignant differentiation histologically than did those fed a control diet (Sakaguchi et al. 1984). Additionally, direct LA treatment significantly increased growth and proliferation in two murine colon adenocarcinoma cell lines (MAC26 and
MAC13) (Hussey et al. 1994).
1.8.3.5 Conjugated Linoleic Acid
Evidence for beneficial effects of CLA in humans has been hard to establish given the complications surrounding the LA isomers. The Swedish Mammography Cohort examined 60,708 women, and observed that women who consumed high amounts of
CLA-containing foods, such as dairy products, showed a significant reduction in colon cancer risk. Each increment of 2 servings of high-fat dairy foods/d corresponded to a
13% reduction in the risk of colorectal cancer (Larsson et al. 2005).
Although there is little epidemiological evidence to support the role of CLA in colon cancer, numerous studies have been conducted in human cell lines and animals models to confirm that CLA has favorable outcomes in colon cancer development. The
114 effects of physiologic concentrations of CLA were tested by administering CLA to human HT-29 cells. It was demonstrated that treatment with CLA decreased proliferation by 30% compared to control treated cells (Shultz et al. 1992). CLA administrated also significantly inhibited growth in human Caco-2 cells (Kim et al. 2002).
In DHM-treated rats, a 1% supplementation with conjugated linoleic acid (CLA) in the diet reduced tumor incidence in the colon by 57% and significantly increased the apoptotic index by 251%. In addition to an increase in apoptosis, CLA supplementation also decreased mucosal levels of prostaglandin E2, thromboxane B2 and arachidonic acid in a dose-dependent manner (Park et al. 2001). Dietary CLA was also shown to decrease polyp number, size and ACF formation as well as increase apoptosis in AOM-treated rats
(Kohno et al. 2002).
Mice treated with AOM and supplemented with CLA showed a significant reduction tumor multiplicity. In addition, CLA treatment decreased the amount of infiltrating macrophages mesenteric lymph nodes and increased regulatory T cell numbers. Mice genetically deficient of PPARγ showed similar polyp numbers and infiltrating immune cells when treated with CLA, demonstrating that the anti-tumor effect can be modulated through PPARγ signaling (Evans et al. 2010). In AOM-treated rats,
CLA treatment inhibited the formation of ACF as well as tumors by as much as 47% and increased PPARγ in tumorigenic tumors as well as surround normal mucosa (Kohno et al.
2004).
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1.8.3.6 The Omega 3: Omega 6 Ratio
Many studies have shown that changes in the omega-3:omega-6 (ω-3:ω-6) ratio may contribute to the early development of human colon cancer. Competition occurs between these precursor fatty acids in the COX signaling pathway which gives rise to certain prostaglandins, some pro- and others anti-inflammatory. Clinical guidelines suggest that based on the competitive nature of these fatty acids, a 1:1 ratio between ω-3 and ω-6 fatty acids is recommended for optimal health (Simopoulos et al. 1999). It is estimated that Westernized diets are composed of a ω-3:ω-6 ratio of 1:15-30 (Simopoulos
2006).
A randomized clinical trial examined the efficacy of the plasma phospholipid ω-
3:ω-6 ratio as a nutritional marker in the prevention of colonic tumor development and metastasis in 27 patients. A significant increase in the plasma phospholipid ω-3:ω-6 ratio was found in the experimental group which correlated with inhibition of the mucosal neoplastic proliferation, thus associating an increase in a ω-3:ω-6 ratio with decreased cancer risk (Huang et al. 1996). In an ecological study in Belgium, ω-3:ω-6 ratios were examined in 11,302 individuals for correlations with mortality associated with colon cancer. A significant inverse relationship was established between colon cancer and high
ω-3:ω-6 ratios (Staessen et al. 1998). Similarly, in an another study that examined 363 cases of patients with colon adenomas and 498 adenoma-free controls also observed an inverse relationship between an increased ω-3:ω-6 ratio and colon cancer risk (Pot et al.
2008).
On the basis of results reported from a number of studies conducted in different countries and with different populations of people, there is sufficient evidence to support
116 that specific fatty acids play a role in colon cancer etiology. This can be related to variations in their intake and their concentrations in different tissues of patients with colon cancer, compared to individuals free of malignant disease. Table 1.3 summarizes the results discussed in this section, where butryric, oleic, conjugated linoleic, α- linolenic, eicosapentaenoic and docosahexaenoic fatty acids have been shown to exert beneficial effects in colon cancer development or outcome. Conversely, lauric, myristic, palmitic, stearic, arachidonic, and linoleic are associated with more disadvantageous outcomes (Table 1.3).
1.9 Using Mouse Models to Study Human Obesity and Colon Cancer
Mouse models were used in the following studies included in this thesis to test the effects of diet, inflammation and obesity on intestinal tumorigenesis. Mouse research has led to major advances in our ability to treat a number of serious diseases and conditions.
For example, work on mice has resulted in successful treatments for colon cancer in humans such as the use of non-steroidal anti-inflammatory drugs (NSAIDs) (Boolbol et al. 1996; Jacoby et al. 2000).
It is advantageous to use mouse models because they have many similarities to their human homologues, the mouse and human genomes are about 85% the same.
Indeed, 99% of mouse genes have an equivalent in humans, making mice ideal for studying the function of human genes in health as well as diseases such as cancer, cardiovascular diseases and diabetes. (Mouse Genome Sequencing Consortium et al.
2002). Inbred mouse strains are commercially available that have been constructed to have fixed genetic backgrounds. For this reason, smaller sample sizes can be utilized in
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Affect on Colon Fatty Acid C:DB Type of Fat Type of FA Cancer Butyric 4:0 Saturated SCFA
Lauric 12:0 Saturated MCFA
Myristic 14:0 Saturated MCFA
Palmitic 16:0 Saturated LCFA
Stearic 18:0 Saturated LCFA
Oleic 18:1 Monounsaturated ω-9
Arachidonic 20:4 Polyunsaturated ω-6
Linoleic 18:2 Polyunsaturated ω-6
Conjugated-Linoleic 18:2 Polyunsaturated ω-6
α-Linolenic 18:3 Polyunsaturated ω-3
Docosahexaenoic 22:6 Polyunsaturated ω-3
Eicosapentaenoic 20:5 Polyunsaturated ω-3
Table 1.3 – Effects of specific fatty acids on colon cancer. Human and mouse studies have demonstrated that some fatty acids are beneficial for disease outcome, while others can have detrimental effects. Red denotes fatty acids that have a favorable outcome on colon cancer (i.e. reducing risk, decreasing polyp numbers, tumors, or burden), while those in green denote fatty acids that have been shown to increase colon cancer.
118 studies using mice given the controlled, reproducible, and heritable genetic background.
In humans, the considerable amount of genetic variability often confounds experimental results and requires the use of large samples sizes to establish statistical power.
Many environmental factors can be manipulated to meet specific research needs.
Unlike humans, mice offer the advantage of a controlled living environment where temperature, humidity, food, water, and exposure to other mice can be carefully monitored. Mice have a generally short gestation period of 21 days, therefore, breeding and maintaining colonies is a reasonable task.
In the following studies, we have constructed diets composed from different fat sources and study the specific effects of coconut, corn and olive on colon tumorigenesis.
In order to understand the role of diet on intestinal neoplasia, two mouse models were utilized. The first was a common mouse model used in the study of intestinal neoplasia,
ApcMin/+. The second was a panel of strains, Chromosome Substitution Strains (CSSs), a model of polygenic obesity. CSSs have been useful models in understanding the genetic and environmental influences of diet-induced obesity (Buchner et al. 2008; Yazbek et al.
2011).
1.9.1 ApcMin/+ - A Mouse Model of Intestinal Neoplasia
In 1986, an ethylnitrosourea (ENU) mutagenesis screen conducted by William F.
Dove resulted in the discovery of a mouse mutant that is one of the most widely used for the study of colon cancer today, the ApcMin/+ (Multiple intestinal neoplasia)(Moser et al.
1990; Kinzler et al. 1991). The ApcMin/+ carry an autosomal dominant, single base pair, nonsense mutation (Min) at codon 850 of the tumor suppressor, APC. These mice
119 develop hundreds of adenomas in the small intestine similar to the human disease familial adenomatous polyposis (FAP). The ApcMin/+ mouse is utilized as carcinogenesis model for both sporadic and inherited forms of colon cancer, and also provide an opportunity to study the pathogenesis of neoplasms in which the initial molecular defect is the same in humans and mice (Moser et al. 1990; Kinzler et al. 1991). The penetrance of the intestinal tumor phenotype, the speed in which the adenomas develop and the large numbers that are formed make the ApcMin/+ model ideal for studying in vivo effects that can later be applied to human diseases and therapies.
The ApcMin/+ models has been successfully used in evaluating potential chemopreventivie agents, such as dietary constituents or pharmaceuticals that prevent cancer development. So far, non-steroidal anti-inflammatory drugs (NSAIDs) like sulindac (Chiu et al 1997), piroxicam (Jacoby et al. 1996), aspirin (Mahmoud et al. 1998) and celecoxib (Jacoby et al. 2000) have been tested. Dietary components such as specific fats (Petrik et al. 2000a; Yu et al. 2001; Fini et al. 2010), vegetable-fruit mixtures (van
Kranen et al. 1998), flaxseed (Bommareddy et al. 2009), wheat bran oil (Sang et al.
2006), the rice bran constituent tricin (Cai et al. 2006), berries (Mutanen et al. 2008), vitamin D (Harris et al. 2004; Zheng et al. 2011), soy isoflavones (Sørensen et al. 1998), beef (Mutanen et al. 2000) as well as calorie restriction (Mai et al. 2003) have all been tested using this important model system.
In addition to increased susceptibility to the development of intestinal polyps,
ApcMin/+ mice also suffer from various co-morbities associated with cancer such as anemia and cachexia. ApcMin/+ mice develop severe anemia with decreasing levels of hematocrit and red blood cells as polyp formation progresses. Studies have shown that
120 this progressive anemia characterized by decreasing red blood cell counts and an increasing proportion of reticulocytes, suggest that these symptoms are consistent with anemia due to blood loss, most likely from the hundreds of polyps that are observed in this model (Moser et al. 1990). Another secondary condition associated with ApcMin/+ is cancer-related cachexia. Cachexia is characterized as an overall state of ill health, accompanied by a loss of lean body mass and fat mass (Ardies 2002). Cancer patients can lose up to 30% of their original body weight because of cancer-related cachexia.
Criterion used for the diagnosis of cachexia in adults is defined as “a complex metabolic syndrome associated with underlying illness and characterized by loss of muscle with or without loss of fat mass” (Evans et al. 2008). To be diagnosed with cachexia, a patient must have lost at least 5% body mass with three of the five following symptoms: decreased muscle strength, fatigue, anorexia, low fat-free mass, or abnormal circulating markers (i.e. elevated IL-6 or low hemoglobin levels) (Evans et al. 2008). The ApcMin/+ model recapitulates many of the characteristics seen in human cachexia such as loss of lean body mass, lack of anorexia, chronic inflammation, fatigue, and elevated levels of
IL-6 (Baltgalvis et al. 2010).
Different inbred backgrounds can greatly affect the polyp number observed in
ApcMin/+ and these genetics differences among strains have led to the discovery of numerous modifiers influencing polyp development. Differences in cancer phenotypes can be due to environmental factors such as diet or genetic modifiers, which are genes that can alter the severity of a disease by directly or indirectly interacting with the causal genetic mutation. To date, there are eleven known modifiers of Min (Mom) that can increase or decrease polyp number in ApcMin/+ mutants (Table 1.4). Briefly, Mom1 (now
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Modifier of Min Gene (if known) Chromosome Effect of modifier on polyp number Reference
Mom1 Pla2g2a 4 ~50% reduction Dietrich et al. 1993 Mom2 Apt5a1 18 88-95% decrease colon polyps Silverman et al. 2002 Mom3 QTL 18 3- to 5-fold increase Haines et al. 2005 Mom5 QTL 5 50% reduction Oikarinen et al. 2009 Mom6 QTL 4 24-34% reduction Cormier et al. 2000 Mom7 QTL 18 ~3-fold increase Kwong et al. 2007 Mom12 QTL 6 87% increase colon polyps Crist et al. 2011 Mom14 QTL 1 39% decrease Nnadi et al. 2012 Mom15 QTL 2 51% decrease Nnadi et al. 2012 Mom16 QTL 2 46% decrease Nnadi et al. 2012 Mom17 QTL 10 39% decrease Nnadi et al. 2012 Mom18 QTL 18 52% decrease Nnadi et al. 2012
Tabe 1.4 – Known modifiers of ApcMin/+. Different inbred backgrounds can greatly affect the polyp number observed in ApcMin/+ and these genetics differences among strains have led to the discovery of numerous modifiers influencing polyp development. Differences in cancer phenotypes can be due to environmental factors such as diet or genetic modifiers, which are genes that can alter the severity of a disease by directly or indirectly interacting with the causal genetic mutation.
122 identified as phospholipase A2, Pla2g2a) results in about a 50% reduction in polyp number (Dietrich et al. 1993), whereas Mom2 (now identified as ATP synthase, H+ transporting, mitochondrial F1 complex, alpha subunit 1, Atp5a1) can decrease polyp number by as much as 88-95% (Silverman et al. 2002). The quantitative trait loci, QTLs,
Mom5, Mom6, Mom14, Mom15, Mom16, Mom17, and Mom18 are known to reduce polyp number (Cormier et al. 2000; Oikarinen et al. 2009; Nnadi et al. 2012), while Mom3,
Mom7, and Mom12 function to increase polyp number (Haines et al. 2005; Kwong et al.
2007; Crist et al. 2011).
1.9.2 Polygenic Mouse Models of Obesity: Chromosome Substitution Strains
The complex nature of obesity makes it difficult to study in humans. Single mutations are very rare, so development of the disease is attributed to intricate interactions between multiple genes and various facets of the environment. Humans are diverse not only genetically, but environmentally as well and food amount and type, activity levels, smoking or drinking habits, and medication requirements greatly impact the outcome of human studies. Clinicians must rely on self-reporting or food intake questionnaires when obtaining information, which can be inaccurate. Mouse models are commonly used to study excess fat storage and can mimic the complex nature of human obesity.
Mouse models that closely resemble the complexity and polygenic nature of human obesity are the Chromosome Substitution Strains. Chromosome Substitution
Strains (CSSs) were constructed in the lab of Joseph Nadeau (Case Western Reserve
University) by replacing a chromosome of a donor strain (A/J) with the corresponding
123 chromosome of a host strain (B6) (Figure 1.17)(Singer et al. 2004). The F1 progeny that resulted from this initial cross were then backcrossed to the parental B6 strain. For 10 or more generations, progeny were chosen that have the A/J chromosome of interest. This ensured that remaining A/J DNA segments were lost through subsequent crossings and resulted in a fixed B6 background. After 10 or more generations, mice were obtained that carried one complete copy of the A/J chromosome of interest, while all other chromosomes were homosomic for B6. These mice were then intercrossed to generate mice that were homosomic for the A/J chromosome of interest or carried two complete copies of the A/J chromosome.
B6 and A/J have opposite responses to a diet high in fat. B6 is susceptible to diet- induced obesity and many other characteristics associated with metabolic syndrome such as glucose intolerance, dyslipidemia and hypertension that increase the possibility of developing type II diabetes and cardiovascular disease (Singer et al. 2004). The A/J inbred strain, in addition to being resistant to factors associated with metabolic syndrome, are also resistant to diet-induced obesity. Unpublished data from the Nadeau lab has demonstrated that these CSSs and their parental strains (A/J and B6) are consistently lean or obese when fed a diet high in saturated fat for 100 days (Figure 1.18).
124
C57BL/6J (Host) A/J (Donor)
1. … …
2. … F1 offspring
Heterozygous for the 3. … desired chromosome
Homozygous for the desired chromosome, 4. … C57BL/6J-Chr2A/J/NaJ
Figure 1.17 – Creation of the Chromosome Substitution Strains. (1) The inbred strain, C57BL/6J or B6 (red) is crossed with A/J (purple). (2) F1 offspring are produced. (3) Mice are crossed for 10 or more generations, selecting for the chromosome of interest in each generation (i.e. A/J Chromosome 2). (4) Mice heterozygous for the desired chromosome are intercrossed to generate a completed CSS, a mouse homozygous for the desired A/J chromosome.
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Figure 1.18 – CSSs are consistently lean or obese when fed a diet high in saturated fat. CSSs were placed on a diet high in saturated fat for 100 days and final body weights were taken. A/J, B6.A7 and B6.A17 (purple) were consistently lean when exposed to a HF diet for this duration, while B6, B6.A2 and B6.A9 (green) were consistently obese. These studies were conducted in two separate mouse facilities at Case Western Reserve University. Unpublished results from David Sinasac, Ph.D. and Annie Hill-Baskin.
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CHAPTER 2
HIGH FAT DIET MODULATES INTESTINAL POLYP
FORMATION, SEPARATE FROM DIET-INDUCED OBESITY
The results from this chapter were submitted for publication. Doerner SK, Reis ES, Leung ES, Ko JS, Heaney JD, Berger NA, Lambris JD, Nadeau JH. High-fat diet-induced complement activation mediates intestinal inflammation and neoplasia independent of obesity. Nature. Xx; xx-xx (2012).
Acknowledgements – I would like to thank Elaine S. Leung and Justine S. Ko for their tireless dedication and help with mouse work in these studies.
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2.1 Introduction
Consumption of high dietary fat is an important environmental factor that contributes to the development of obesity and associated co-morbidities such as chronic inflammation, insulin resistance, fatty liver disease, and cancer (Renehan et al. 2008;
Khandekar et al. 2011). An increase in consumption of high fat (HF) diets and sedentary lifestyles has resulted in a rapid increase in obesity, where in the United States as many as 70% of adults and 18% of children (age 6-19) are overweight or obese (Merlo et al.
2011). The World Cancer Research Fund (WCRF), American Institute for Cancer
Research (AICR) and the International Agency for Research on Cancer (IARC) found that increased body weight was associated with the development of many cancers, including colorectal, pancreatic and postmenopausal breast (Vainio et al. 2002; WCRF
2007). For example, WCRF/AICR/IARC showed that obesity could increase risk of colon cancer by 50-100% in both men and women (Vainio et al. 2002; WCRF 2007;
Wolin et al. 2008). However, such studies are frequently obscured by the close relationship between high fat (HF) diet, obesity and accompanying metabolic abnormalities in humans. The association of these factors with HF diet not only confounds the direct relationship between diet and colon cancer, but also complicates studies to determine the mechanisms by which HF diets promote carcinogenesis.
Numerous epidemiological and molecular studies link obesity, the consumption of a high fat diet and increased risk of developing colon cancer. It is known that obesity results in a state of chronic inflammation that leads to insulin resistance (Romeo et al.
2012). Physiological features associated with obesity, such as elevated metabolic factors
(i.e. insulin and leptin) and chronic inflammation, are often found in colon cancer patients
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(Khandekar et al. 2011). Further evidence to support a linkage between insulin perturbations is the use of Metformin, a drug used to treat diabetes mellitus, which has been shown to decrease the formation of aberrant crypt foci and reduce the number of large intestinal polyps in mouse models as well as reduced cancer risk in diabetic patients treated with the drug (Buzzai et al. 2008; Hosono et al. 2010; Li 2011).
Insulin, leptin and adiponectin are closely interacting factors involved in the development of metabolic syndrome (MetS) and their delicate balance is shifted in patients suffering from obesity or colon cancer. MetS is a collection of metabolic disorders (i.e. increased body weight, dyslipidemia, hypertension, and insulin resistance) is linked to increased risk of cardiovascular disease as well as elevated incidence of colon cancer in humans (Yehuda-Shnaidman et al. 2012). Insulin is central to the regulation of carbohydrate and fat metabolism, and acts as a positive regulator of leptin (Cohen et al.
1996). Leptin, a hormone that is secreted from adipocytes and is involved in appetite suppression, is found in excess in obese individuals and is associated with increased inflammation, proliferation and survival of human and mouse colon cancer cell lines
(Hoda et al. 2007). Adiponectin, an insulin sensitizing hormone secreted by mature adipocytes that decreases as body weight increases, and can inhibit leptin signaling as well as many pro-inflammatory factors, such as tumor necrosis factor alpha (TNFα), interleukin-6 (IL-6), IL-8 while inducing the anti-inflammatory IL-10 and IL-1 receptor antagonist. Colon carcinoma cell lines treated with adiponectin showed decreased IL-6- induced proliferation and suppressed colonic epithelial proliferation in high fat conditions
(Barb et al. 2007; Fujisawa et al. 2008). Additionally, epidemiological studies have
129 shown that individuals with low plasma adiponectin levels have a higher risk of developing colon cancer (Barb et al. 2007; Fujisawa et al. 2008; Fenton et al 2010).
There are multiple hypotheses that could explain the contribution of diet and DIO to colon cancer and the close associations makes understanding this relationship difficult.
It could be possible that factors associated with obesity, such as elevated insulin and leptin or a state of chronic inflammation, increase tumorigenesis directly. Diet could indirectly contribute to the elevation of these same metabolic factors, because of the close association between diet and the development of DIO. Certain diets could have components that act as carcinogens and have direct effects on tumorigenesis by increasing proliferation or decreasing apoptosis of intestinal cells. It could also be possible that particular diets lack anti-tumorigenic components that usually contribute to apoptosis or inhibit proliferation of tumors.
To untangle these similar speculations and test the independent contributions of nutrition and excess body fat on intestinal neoplasia, it was first necessary to generate a mouse model that could be used to separate diet from DIO. By combining mice resistant to diet-induced obesity with the mouse model of intestinal neoplasia, ApcMin/+ (Multiple intestinal neoplasia), a model to study the role of the diet in intestinal tumorigenesis was created. ApcMin/+ carries a germline mutation in the APC gene that results in the production of a truncated protein similar to that found in human colon cancers and numerous intestinal polyps that are used as a measure of colon cancer (Moser et al.
1990). Mutations in the human APC gene cause a hereditary form of colon cancer, familial adenomatous polyposis (FAP), and are observed in over 80% of sporadic colon cancer cases (Nishisho et al. 1991). ApcMin/+ was combined with Chromosome
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Substitution Strains (CSSs) to create novel mouse models that were resistant or susceptible to diet-induced obesity and predisposed to intestinal neoplasia
(CSS.ApcMin/+).
Using these innovative cancer models, the CSS.ApcMin/+ strains, we demonstrate that polyp number and burden are significantly increased in response to a diet high in saturated fat, signifying a powerful and distinct effect of HF on colon cancer separate from excess fat storage. Current understanding of insulin and leptin signaling postulate that elevations in adipose tissue result in increases in these metabolic factors. These findings, in addition to elucidating an obesity-independent role for diet in colon cancer, demonstrate that factors associated with MetS and obesity, such as leptin and insulin, are elevated prior to the onset of obesity. Given that diet plays such a crucial role in colon cancer development suggests that inexpensive, noninvasive dietary interventions may be a useful preventative option for those predisposed to colon cancer. Dietary modifications may also be useful in the reduction of sporadic colon cancer cases.
2.2 Methods
2.2.1 Mice. C57BL/6J (B6), C57BL/6J-ApcMin/+/J (ApcMin/+) and the Chromosome
Substitution Strains (CSSs, also known as Consomic strains) C57BL/6J-Chr2A/J/NaJ
(A2), C57BL/6J-Chr7A/J/NaJ (A7), C57BL/6J-Chr9A/J/NaJ (A9), and C57BL/6J-
Chr17A/J/NaJ (A17) were purchased from The Jackson Laboratory (Bar Harbor, ME).
CSSs are inbred strains in which a single chromosome (2, 7, 9 or 17) from a donor strain
(A/J) replaces the corresponding chromosome in the host strain (B6). CSSs were chosen according to their resistance (A7 and A17) or susceptibility (A2 and A9) to diet-induced
131 obesity. CSSs were backcrossed onto a B6.ApcMin/+ background and the resulting
CSS.ApcMin/+ strains (A2.ApcMin/+, A7.ApcMin/+, A9.ApcMin/+ and A17.ApcMin/+) or the corresponding wild-type controls (A2, A7, A9, and A17) were maintained on a 12 hour light/dark cycle at the Wolstein Research Facility (CWRU). Primers used for genotyping wild-type CSS and CSS.ApcMin/+ strains are summarized in Table 2.1. All procedures were approved and conducted in compliance with Institutional Animal Care and Use
Committee (IACUC) standards at Case Western Reserve University.
2.2.2 Diets. Diets were obtained from Research Diets, Inc. (New Brunswick, NJ) that differ in the amount of fat, but are identical in vitamins, protein sources, and minerals.
The high fat (HF) diet contained 58% kcal/g from hydrogenated oil (HF), while the low fat (LF) diet contained only 10.5% kcal/g from the same oil (LF). The coconut oil diets are rich in saturated fatty acids (99.1%) such as lauric and myristic acids (Table 2.2). The amounts of carbohydrates were increased in the LF diet to compensate for the loss of calories that would result from the fat. For this reason, the HF and LF diets will have comparable caloric values with 5558.5kcal/g and 5557.0kcal/g, respectively.
2.2.3 Study design. From birth to 30 days of age, all mice were fed an autoclaved standard laboratory diet that contained 13.5% fat (Table 2.2), Purina 5010 LabDiet
(Richmond, IN), and autoclaved water ad libitum. At 30 days of age, male mice were randomized to HF or LF dietary groups and fed ad libitum until sacrifice after 30 or 60 days on the diet. Prior to blood collection, mice were fasted for 12-14 hours and anesthetized using isoflurane. Whole blood, plasma and serum samples were collected from the retro-orbital sinus in tubes with or without EDTA. Body weight was measured every other day and body length was measured at the final time point to calculate body
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Location MIT Marker Chromosome Primer Sequences (cM)
D1Mit64 1 AGTGCATTATGAAGCCCCAC, TCAAATTTTAAAACAACCCATTTG 5.0 D1Mit294 1 CCCAAGGACACCTACGTGAT, CTGGCAAGTTCTGCTTTAACC 8.3 D1Mit231 1 GGGACTGCAAACACCACTTT, ACTCAGAAAGATGGGCATACTAGG 12.0 D1Mit76 1 ACAAAGGAAACTAAACAGACTCGG , CTCCCTCAAATACATCTTTGGC 32.8 D1Mit187 1 ACTGCAAAAGAATATGAAGAATCTTT , TATATGTACATTCGTGTGAACACACA 62.0 D1Mit446 1 TGAGTATATCATGAAGACAGCAACC , ACGTATTTACCTTGTTCTGAATTTTG 70.0 D1Mit36 1 GAGGAATGTAGAGTCCAACCTGG , TGAATAGATTAAGAGCCTGGAAGC 92.3
D1Mit362 1 CCAGACCTCTGTCCTGGTGT, ATGCGAGCACAAGCACAC 106.3 D1Mit155 1 ATGCATGCATGCACACGT, ACCGTGAAATGTTCACCCAT 112.0 D2Mit175 2 ATGACAAACAAGAAATAGGAAGGC, CATGTGCTTGAGCATGCAC 2.0 D2Mit359 2 GGATCTAGAGATACGTTACATTCCTT, TGAAATCTAACTCTGGTTGAAAAGC 5.0
D2Mit156 2 ACTGGGGAGACTAAATGGGG, ACTCTTCCATGCAACCGATT 32.0
D2Mit37 2 TGTGCAAGCCAGAAAAGTTG, GAAGGGGATTGTAAATTGGTACC 45.0
D2Mit484 2 AGGAGTGGTAAGCATGGTGG , TGCTGCAGGGAGGTAACAG 65.5
D2Mit310 2 TTTAAATGAAGAATAAGGTCAGAAACA, GCATTAATTCTCATTCTCAATAATGG 77.6
D2Mit266 2 GGATCTATGCTCCATTTTAATTGC, TCATCTTCTGGTTTCAACATGG 109.0
D7Mit178 7 ACCTCTGATTTCAGAACCCTTG, TAGAGAGCCACTAGCATATCATAACC 0.5
D7Mit309 7 TGATAAGGACCCTACAAGCACC, CACAGAGATGGACAGATACAGACA 16.0
D7Mit159 7 ATAGCAAAACAAAACAAAACTCTGG , GTAACTGGCACGCAGAGACA 27.8
D7Mit301 7 CTGTGAAGTATGCTTTCTCTTACACA , TGCTTTGCAGATGGCTCTAC 46.5
D7Mit66 7 TTCACTCCCAGCCAGTCTCT, TAACCAGGAAACACACGAACC 57.5
D7Mit259 7 CCCCTCCTCCTGACCTCTT, GTCTCCATGGGAACCACACT 72.0
D9Mit88 9 CATTATGCACCCCAGTTCCT, ACATGTGTAAGTGAAGATGTGTCG 12.0
D9Mit247 9 TTTTAATGGAGAGGGTGAGGG, AAGGAGACCCTGGGTCAGAG 17.0
D9Mit105 9 ACAGAGAAAGGACACAGATCCTG, TATCAAATTGGGAGTCATTTATGG 35.0
D9Mit11 9 GCCTTCATGTGTACCTGAATGCAC, GGCTCTGTAATCACTGAAGCTGGT 48.0
D9Mit214 9 AGCACAGGAAAAGGACGCTA, AACCTGTCTCTGTAAAACTATCTCCA 62.0
D9Mit18 9 TCACTGTAGCCCAGAGCAGT, CCTGTTGTCAACACCTGATG 71.0
D17Mit57 17 GCTGATAAACGTGGTGGCTT , GTTTAGTGGCTTCAAGTCACCC 7.6
D17Mit16 17 CCAGAAGACAGCATTCCACA, GTATGTCAGGGCTAGTTGACAG 17.4
D17Mit20 17 AGAACAGGACACCGGACATC, TCATAAGTAGGCACACCAATGC 34.3
D17Mit241 17 TTTCAAATTCATAGCCTCTTTTTC, TACAGAATGAGCAGGTTGTATTAAGG 45.3
D17Mit221 17 AACCAGATCATTAACAGTAATAAAGCA, TTGTGGCAAAAACAACCAAA 56.7
Table 2.1 – Markers used in the creation of the CSS.ApcMin/+ strains. Markers were designed by the Massachu setts Institute of Technology (MIT) and used to ensure that the A/J chromosome of interest was obtained at each generation and that recombination did not occur.
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Diet Fat Source Majority Fatty Acids, Type (%) Fat (%) Carbohydrate (%) Protein (%)
5050 Crude 13.5 59.0 27.6
LF Coconut 10.5 73.1 16.4 Lauric, Saturated (47.6), Myristic, Saturated (18.0), Stearic, Saturated (10.6), HF Coconut Other (23.8) 58.0 25.5 16.4
Table 2.2 – Composition of hydrogenated coconut oil diet. The 5010 diet was used as a stock diet and all mouse strains were maintained on this diet until the start of the diet studies. The high and low fat coconut oil diets were constructed to be identical in protein, vitamin and mineral content, but differ in the amount of saturated fat.
134 mass index (BMI). At the final time point mice were euthanized by cervical dislocation and epididymal fat pad mass (EFPM) was collected and weighed as a measure of adiposity. The small and large intestines were immediately removed, flushed using cold
PBS and, cut longitudinally. Since polyp frequency varies in different regions of the small intestine, the small intestine was sectioned into four equal parts when analyzed.
The regions were labeled SI-1 to SI-4, starting from the duodenum located below stomach (SI-1) to the jejunum (SI-2 and SI-3) to the ileum (SI-4) which is located just proximal to the cecum. The large intestine was excised and analyzed as one region (LI-1).
Polyps were counted and cross sectional diameter was measured in the small intestine and colon using a Leica MZ10F Modular Stereomicroscope. Individual polyp size and number were used to calculate a polyp area (area = πr2) for each polyp present in the intestine of a mouse. The sum of all the polyp areas per mouse was used to calculate a total polyp mass that was used as a surrogate measure of polyp burden. Colon polyp incidence was recorded, and the presence of colon polyps (affected) was compared to the total number of mice on the study to calculate the percent colon polyp incidence for each strain and dietary group. Intestinal samples were immediately collected for RNA and protein analysis, frozen in liquid nitrogen and stored at -80°C until use. Tissues were fixed in 10% buffered formalin and embedded in paraffin for histological analysis.
2.2.4 Metabolic parameters and cytokine analysis. Fasting insulin levels were determined using Mercodia Ultrasensitive Mouse Insulin ELISA (Uppsala, Sweden).
Fasting glucose was measured using a OneTouch Ultra glucometer (Life Scan, Inc.,
Milpitas, CA). Homeostatic model assessment of insulin resistance (HOMA-IR) was calculated using fasting insulin and glucose levels (HOMA-IR = fasting insulin (pmol/L)
135 x fasting blood glucose (mmol/L) /22.5). Leptin and adiponectin were measured in the plasma using ELISA kits from Millipore (Billerica, MA) and used according to the manufacturer’s instructions.
2.2.5 Quantitative RT-PCR and protein analysis. After 30 and 60 days on the diet study, size-matched polyps and normal tissue were collected from the small intestine of
B6.ApcMin/+ mice and B6, respectively. Tissues were immediately frozen in Qiagen RLT buffer (Valencia, CA) and RNA was extracted using the Qiagen RNeasy Mini Kit.
Quantitative RT-PCR was done using SYBR Green (Quanta BioSciences, Gaithersburg,
MD) and Primer3 software (Rozen et al. 2000; Howard Hughes Medical Center, National
Institute of Health). Primer sequences are indicated in Table 2.3. Tissues for western blot analysis were immediately submerged in RIPA buffer supplemented with phosphatase and protease inhibitors, frozen in liquid nitrogen and stored at -80°C until use. All antibodies (AKT, pAKT, IKK, pIKK, NFκB, p65 NFκB, STAT3, pSTAT3) were purchased from Cell Signaling Technology, Inc. (Beverly, MA) and used according to the manufacturer’s instructions.
2.2.6 Statistical Analysis. Student’s t-tests and one-way analysis of variance (ANOVA) were used to determine statistical significance, which was accepted at the p<0.05 level after Bonferroni correction for testing multiple hypotheses.
2.3 Results
2.3.1 Constructing mouse models to study diet, separate from obesity. To investigate the role of diet on intestinal tumorigenesis, it was necessary to construct mouse strains that could consume high dietary fat but were resistant to the characteristics associated
136
Primer Name Primer Sequences ATGGGTGTGAAGGGAAATAAGG COX-2 ACCCAGGTCCTCGCTTATG GCCTGCATCTCTTCTTGAGG C5aR CCATCCGCAGGTATGTTAGG AAGGGAAGGCTTTCTTCATTG F4/80 GTGGTCATCCCCCATCTGTA GCTGAAAGCTCTCCACCTCA IL-1β AGGCCACAGGTATTTTGTCG CTCTGCAAGAGACTTCCATCCAGT IL-6 GAAGTAGGGAAGGCCGTGG CTTGAATCCCTGCATAGAGGTAG TLR4 TCCAGCCACTGAAGTTCTGA CAGACCCTCACACTCAGATCAT TNF GGTTGTCTTTGAGATCCATGC GATCCATTGGAGGGCAAGTCT 18S CCAAGATCCAACTACGAGCTTTTT
Table 2.3 – Primer sequences for quantitative RT-PCR reactions. Primers were designed using Primer3 Software (Rozen et al. 2000).
137 with this high caloric intake such as obesity and metabolic syndrome (MetS). While still being susceptible to the development of intestinal tumors, these obesity-resistant strains could be used to examine if high dietary fat alone could modulate tumor development.
Chromosome Substitution Strains (CSSs) were constructed in the lab of Joseph
Nadeau (Case Western Reserve University) by replacing a chromosome of a donor strain
(A/J) with the corresponding chromosome of a host strain (B6) (Figure 1.17)(Singer et al. 2004). The F1 progeny that resulted from this initial cross were then backcrossed to the parental B6 strain. For 10 or more generations, progeny were chosen that have the A/J chromosome of interest. This ensured that remaining A/J DNA segments were lost through subsequent crossings and resulted in a fixed B6 background. After 10 or more generations, mice were obtained that carried one complete copy of the A/J chromosome of interest, while all other chromosomes were homosomic for B6. These mice were then intercrossed to generate mice that were homosomic for the A/J chromosome of interest or carried two complete copies of the A/J chromosome.
CSSs that differ in susceptibility to diet-induced obesity were used to create
CSS.ApcMin/+ strains by breeding the APC mutation onto a CSS background (Figure 2.1).
This was achieved by breeding ApcMin/+ to a CSS that was either obesity-susceptible (A2 or A9) or obesity-resistant (A7 or A17). The F1 progeny were backcrossed to the original
CSS strain and genotyped for the A/J chromosome to ensure that recombination did not occur to obtain two full copies of the A/J chromosome. Two strains that were consistently resistant to diet-induced obesity, (A7 and A17) were chosen to create
CSS.ApcMin/+ strains for the proposed studies. A7 and A17 were homosomic for A/J chromosomes 7 and 17, respectively, while the remainder of the genetic background was
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C57BL/6J-Chr2A/J/NaJ C57BL/6J-ApcMin/+
1. … …
2. … F1 offspring
Homozygous for the desired chromosome, 3. … (i.e. A2.ApcMin/+)
Figure 2.1 – Construction of the CSS.ApcMin/+ strains. (1) The CSS of interest (i.e. C57BL/6J-Chr2A/J/NaJ or B6.A2) was crossed with C57BL/6J-ApcMin/+ or B6.ApcMin/+. (2) F1 offspring were generated from the B6.A2 and B6.ApcMin/+ cross. (3) Mice that carried the ApcMin/+ mutation (light blue) were backcrossed to the parental CSS (i.e. B6.A2) to obtain a completed CSS.ApcMin/+ strain with two copies of the A/J chromosome of interest.
139 derived from B6. When these strains were crossed to ApcMin/+, the CSS.ApcMin/+ stains that resulted (A7.ApcMin/+ and A17.ApcMin/+) were resistant to diet-induced obesity, but susceptible to the development of intestinal adenomas. Two CSSs were chosen (A2 and
A9) to create CSS.ApcMin/+ strains that were susceptible to diet-induced obesity
(A2.ApcMin/+ and A9.ApcMin/+).
Several chromosomes exhibit known modifiers that alter the polyp frequency in the ApcMin/+ mouse model. Importantly, the selected CSSs do not carry known genetic modifiers that enhance or suppress the development of intestinal polyps in ApcMin/+ mice.
Known modifiers of ApcMin/+ are summarized in Table 1.4 (Chapter 1). Briefly, chromosomes 4(Mom1), 8(Foxl1), and 18(Mom2, Mom3, Mom7) that were shown to have these modifiers were avoided when choosing the CSSs. Modifiers have not been identified on chromosomes 2, 7, 9, or 17, which were chosen for the proposed studies.
Though we took precautions to avoid introducing complications of the study by using chromosome without known modifiers of tumor development or promotion, it is still possible that unknown modifiers exist.
2.3.2 High fat diet decreases lifespan in ApcMin/+. Due to the extreme polyp burden,
ApcMin/+ mice only live to about 120-180 days of age on average and consumption of a
HF diet is correlated with increased colon cancer mortality in humans. For this reason, we wanted to investigate the effect that a high fat diet would have on lifespan and determine an ideal time point for future studies with the ApcMin/+ mouse model. To test the effect of a HF diet on mortality and polyp burden, B6 and ApcMin/+ mice were fed a diet high or low in hydrogenated coconut oil (HFCoco and LFCoco, respectively). After 40 days on the
Min/+ diet study (70 days of age), Apc begin to lose body weight on the HFCoco and were
140
~10% leaner than the wildtype, B6, littermates after 60 days (90 days of age) (Figure
2.2). These results helped to establish 60 days as part of my study design. When put on
Min/+ survival studies, 50% survival was 140 days for Apc fed the HFCoco compared to 320 days observed in mice fed the LFCoco diet, a 2.3-fold decrease in survival (Figure 2.3).
After 500 days, B6 fed the HFCoco and LFCoco diets were still viable and healthy. These results demonstrate that HF diet does increase mortality as seen in human colon cancer patients.
ApcMin/+ mice are prone to progressive cachexia and anemia in response to polyp development in the intestine (Moser et al. 1990; Ardies 2002). After 60 days (90 days of age) on the HFCoco diet, reduced body weight (lean body mass) and lethargy were
Min/+ observed in the Apc fed the HFCoco diet, demonstrating that these conditions associated with cachexia had developed prior to the 120-180 time point usually seen in this model. Signs of cachexia were not observed in the wild-type B6 mice or in ApcMin/+ fed the LFCoco. Red blood cell counts, hemoglobin and hematocrit were used to establish anemia and all confirm that ApcMin/+ fed both diets had severe anemia, most likely due to the bleeding from polyps commonly seen in this model (Figure 2.4). Anemia was not observed in B6 wild-type mice, nor were there differences between red blood cells counts, hemoglobin or hematocrit between mice fed the HFCoco and LFCoco diets, revealing that diet does not affect anemia status (Figure 2.4).
2.3.3 Contrasting CSS responses to HF diets. B6, obesity-susceptible and obesity- resistant strains were fed the HFCoco or LFCoco diet for 60 days. Body weight was used as a surrogate measure of proper development and growth curves were used as one method to monitor the growth of the CSS strains on the LFCoco and HFCoco diets (Figure 2.5). All
141
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142
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Min/+ Figure 2.3 – Survival curves for mice fed the coconut oil diets. Apc fed the HFCoco (blue triangles) diet had an average lifespan of about 120 days (90 days on the diet study), while the lifespan ApcMin/+ fed the LFCoco diet (light blue triangles) was increased to about 310 days (220 days on the diet study). Wild- type B6 mice fed either coconut oil diets were still healthy with 100% survuval at 500 dats if age when the study was completed.
143
Figure 2.4 – Red blood cell counts, hemoglobin and hematocrit in B6 and ApcMin/+. (a) After 60 days on the HFCoco and LFCoco diets, mice positive for the Apc mutation showed a significant decrease in red blood cell counts. (b) hemoglobin and (c) hematocrit, demonstrating severe anemia. There are no differences in anemia measurements between mice fed the different diets, suggesting that diet does not affect anemia outcome in this model. ****p<0.0001
144
Figure 2.5 – Growth weights from CSS.ApcMin/+ strains on the coconut oil diet study. (a) Normal growth Min/+ pattern is observed in A2 and A2.Apc fed the LFCoco and HFCoco diets after 60 days. The characteristic weight loss classically seen in Apc mutants is not observed in the A2 strains, regardless of diet, suggesting healthy growth and development in these strains. (b) Conversely, the obesity-susceptible A9.ApcMin/+ fed the HFCoco diet started the study by gaining normal weight but begin to lose weight around 40 days on the diet study and continue to lose weight until the 60 day time point. The obesity-resistant (c) A7 and (d) A17 strains showed no signs of cachexia and body weight measurements demonstrate normal growth and development in all strains, regardless of genotype or diet.
145
A2 strains were continuing to gain weight in accordance with normal development with no signs of cachexia as seen in ApcMin/+ fed the same diet for the same duration. When
Min/+ compared to the same strain fed the LFCoco diet, A2 mice with or without the Apc mutation fed the HFCoco diet were significantly heavier (p<0.0001) (Figure 2.5a).
Interestingly, wild-type A9 continued to gain weights as expected on the LFCoco and
Min/+ HFCoco diets, but A9.Apc fed the HFCoco began to show signs of cachexia around the same time point as ApcMin/+ fed the same diet (Figure 2.5b). The obesity-resistance strains (A7 and A17) showed normal patterns of weight development on both diets
(Figure 2.5c and Figure 2.5d). No weight loss or signs of cachexia were observed after
60 days on the diet in these lean strains. As expected B6 and the obesity-susceptible
CSSs, wild-type A2 and A9, had significantly higher final body weight (FBW), epididymal fat pad mass (EFPM) and body mass index (BMI) (Figure 2.6, Table 2.4) when fed the HFCoco compared to the LFCoco diet, demonstrating that 60 days on the
HFCoco was sufficient to promote DIO and adiposity I n these strains. As explained
Min/+ Min/+ above, Apc and A9.Apc had reduced final body weights when fed the HFCoco diet compared to the same strain fed the LFCoco diet, suggesting the development of cancer- related cachexia (Figure 2.6, Table 2.4). Conversely, A2.ApcMin/+ continued to gain weight even at the completion of the study and were significantly heavier than the same strain fed the LFCoco diet (Figure 2.6, Table 2.4). Importantly, obesity-resistant CSSs,
A7 and A17, although still gaining weight at the end of the study still remained lean on both diets, proving these strains could be used to separate diet from obesity in these studies (Figure 2.6, Table 2.4). Regardless of Apc genotype or diet, the obesity-resistant
CSS.ApcMin/+ strains showed no signs of cachexia.
146
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Figure 2.6 – B6 and CSS body weights parameters. Final body weights, epididymal fat pad mass and body mass index after 60 days on the coconut oil diets. (a) Final body weight were significantly higher in obesity-susceptible strains (B6, A2, and A9) fed the HFCoco diet (purple) compared to the same strain fed the LFCoco diet (blue). Conversely, no final body weight increase was observed in the obesity-resistant strains (A7 and A17), regardless of diet. Similar results were discovered in the obesity-susceptible strains when examining (b) epididymal fat pad mass and (c) body mass index. **p<0.01, ***p<0.001.
147
Fasting Insulin Fasting Glucose Total Polyp Strain N FBW (g) ± SEM EFPM (g) ± SEM BMI ± SEM HOMA-IR (µg/L) ± SEM (mg/dL) ± SEM Number
B6.Apc+/+ 54 27.91 ± 0.24 0.61 ± 0.12 0.24 ± 0.008 0.34 ± 0.14 167.3 ± 14.2 29.1 ± 12.7 0.0 ± 0.0
B6.ApcMin/+ 54 25.78 ± 0.24 0.32 ± 0.04 0.25 ± 0.002 0.37 ± 0.05 202.0 ± 28.4 38.8 ± 7.6 14.0 ± 1.5
A2.Apc+/+ 29 27.66 ± 0.45 0.55 ± 0.07 0.25 ± 0.003 0.22 ± 0.07 154.0 ± 15.8 9.8 ± 3.3 0.0 ± 0.0
A2.ApcMin/+ 29 26.14 ± 0.47 0.46 ± 0.04 0.25 ± 0.003 0.31 ± 0.09 180.3 ± 14.3 13.2 ± 3.0 6.8 ± 0.5
A7.Apc+/+ 14 27.01 ± 0.33 0.42 ± 0.02 0.25 ± 0.003 0.23 ± 0.13 180.0 ± 57.0 22.4 ± 12.8 0.0 ± 0.0
A7.ApcMin/+ 14 26.27 ± 0.36 0.42 ± 0.03 0.25 ± 0.004 0.22 ± 0.08 116.5 ± 13.2 28.2 ± 6.6 14.8 ± 1.1
A9.Apc+/+ 4 25.85 ± 0.36 0.40 ± 0.04 0.24 ± 0.007 0.11 ± 0.09 119.3 ± 16.0 6.0 ± 1.7 0.0 ± 0.0
A9.ApcMin/+ 4 24.95 ± 0.36 0.24 ± 0.03 0.25 ± 0.003 0.25 ± 0.003 173.0 ± 12.7 18.1 ± 1.1 27.8 ± 1.3
A17.Apc+/+ 20 25.65 ± 0.34 0.34 ± 0.03 0.23 ± 0.003 0.50 ± 0.16 179.9 ± 8.9 21.7 ± 9.1 0.0 ± 0.0
A17.ApcMin/+ 28 25.57 ± 0.31 0.27 ± 0.02 0.24 ± 0.002 0.46 ± 0.22 225.1 ± 9.2 22.8 ± 2.4 12.7 ± 1.0
B6.Apc+/+ 46 31.32 ± 0.70** 1.29 ± 0.11** 0.28 ± 0.004** 1.23 ± 0.21** 261.4 ± 21.1** 107.4 ± 25.4** 0.0 ± 0.0
B6.ApcMin/+ 51 23.22 ± 0.70 0.36 ± 0.05 0.24 ± 0.006 0.43 ± 0.06 234.4 ± 11.7 43.3 ± 7.2 91.8 ± 4.8***
A2.Apc+/+ 30 32.40 ± 0.81** 1.63 ± 0.17** 0.29 ± 0.006** 2.02 ± 0.47** 293.8 ± 7.8** 242.4 ± 54.4** 0.0 ± 0.0
A2.ApcMin/+ 34 29.63 ± 0.87** 1.07 ± 0.12** 0.28 ± 0.006** 1.38 ± 0.26** 245.5 ± 20.4 120.1 ± 29.0** 25.8 ± 1.6***
A9.Apc+/+ 3 35.24 ± 0.31*** 1.86 ± 0.10*** 0.31 ± 0.003** 0.67 ± 0.02** 203.5 ± 27.5*** 58.2 ± 9.2*** 0.0 ± 0.0
A9.ApcMin/+ 3 27.34 ± 0.34** 0.59 ± 0.14** 0.27 ± 0.005** 0.40 ± 0.09** 185.0 ± 6.5 29.9 ± 5.9** 109.0 ± 7.2***
A7.Apc+/+ 16 27.50 ± 0.40 0.61 ± 0.07 0.26 ± 0.005 0.47 ± 0.28 150.0 ± 60.2 20.7 ± 14.4 0.0 ± 0.0
A7.ApcMin/+ 18 26.11 ± 0.50 0.35 ± 0.07 0.26 ± 0.005 0.20 ± 0.04 224.8 ± 25.6 17.5 ± 4.1 60.0 ± 10.5***
A17.Apc+/+ 24 27.92 ± 0.54 0.67 ± 0.09 0.26 ± 0.004 0.65 ± 0.20 192.5 ± 16.5 26.0 ± 7.5 0.0 ± 0.0
A17.ApcMin/+ 24 25.63 ± 0.36 0.45 ± 0.04 0.25 ± 0.003 0.60 ± 0.09 222.9 ± 16.7 45.1 ± 7.6 51.0 ± 2.7*** Table 2.4 – Body weight and metabolic parameters after 60 days on the diet study. Final body weight (FBW), epididymal fat pad mass (EFPM), body mass index (BMI), fasting insulin, fasting glucose, HOMA- IR and total polyp number were measured in B6 and CSSs with or without the Apc mutation fed the LFCoco and HFCoco diets. The grey shaded area denoted mice fed the LFCoco diet. For statistical analysis, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet. **p<0.01, ***p<0.001.
148
To investigate if 60 days on the HFCoco was sufficient to induce MetS in the wild- type CSS and CSS.ApcMin/+ strains, fasting insulin, fasting glucose as well as homeostatic model assessment of insulin resistance (HOMA-IR) were determined and used as a surrogate measurement for insulin resistance, a key component of MetS (Henderson et al.
2011). Fasting insulin, fasting glucose levels as well as HOMA-IR values were significantly elevated in the B6, A2 and A9 strains fed the HFCoco compared to the same strain fed the LFCoco diet (Figure 2.7, Table 2.4). No increase was observed in the obesity-resistant, A7 and A17, strains compared to the LF-fed controls (Figure 2.7,
Table 2.4). These results show that 60 days on a the HFCoco diet is sufficient time to develop DIO in the obesity susceptible strains and that there is clear distinction between the two groups of strains in response to a HF diet in terms of glucose metabolism after a
60 day exposure, making them an ideal model to separate the effects of diet from not only
DIO but components of MetS on intestinal tumorigenesis.
2.3.4 High dietary fat increases intestinal neoplasia. After 60 days on the HFCoco diet,
3.6- and 16.2-fold increase in polyp number and burden, respectively, were found in the
Min/+ small intestine of Apc compared to those fed the LFCoco diet (Figure 2.8, Table 2.4).
Similar to that observed in the ApcMin+, total polyp numbers and burden were significantly increased in all strains fed the HFCoco compared to the same strain fed the
LFCoco, regardless of obesity status (Figure 2.8, Table 2.4). Specifically, 3.6-, 3.0-fold increases in polyp number were observed in the small intestine of the obesity-susceptible
(A2.ApcMin/+ and A9.ApcMin/+, respectively) and 3.3- and 3.4-fold increases in the obesity- resistant (A7.ApcMin/+ and A17.ApcMin/+, respectively) compared to the same strain fed the
LFCoco diet. Polyp burden was also increased in all strains fed the HF diet, regardless of
149
Figure 2.7 – B6 and CSS metabolic parameters. Fasting insulin and HOMA-IR are elevated in obesity- susceptible mice after 60 days on the HFCoco diet. (a) Fasting insulin and (b) HOMA-IR were measured in B6 and CSSs with or without the Apc mutation fed the LFCoco (blue) or HFCoco (purple) diets. Fasting insulin and HOMA-IR were both elevated in all obesity-susceptible (B6, A2, A9) strains fed the HFCoco compared to those fed the LFCoco, but not the obesity-resistant (A7 and A17) strains. **p<0.01, ***p<0.001.
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Figure 2.8 – High dietary fat increases polyp number and mass. Total polyp number and total polyp Min/+ Min/+ mass were measured in Apc and CSS.Apc strains after 60 days on the LFCoco or HFCoco diets. (a) Total polyp number was increased in all strains fed the HFCoco diet (purple) compared to the LFCoco diet (blue), regardless of lean (A7 and A17) or obese (B6, A2, and A9) status. (b) Total polyp mass was significantly increased in all strains fed the HFCoco compared to the same LF-fed control strain. **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain Min/+ fed the LFCoco diet), ###p<0.001 (For statistical comparisons, each strain was compared to B6 or Apc fed the same diet).
151 obese, A2.ApcMin/+ and A9.ApcMin/+, (9.2- and 25.4-fold) or lean, A7.ApcMin/+ and
A17.ApcMin/+ (10.4- and 11.7-fold) status (Figure 2.8, Table 2.4). If obesity and associated metabolic changes were essential for enhanced polyp development, an increase in polyp number should have been observed in the lean but not the obese
Min/+ CSS.Apc strains. Instead, all strains fed the HFCoco diet showed substantial increases in total polyp number and burden, demonstrating that dietary fat can separately increase cancer development without the complications of obesity or MetS.
2.3.5 Neutrophils increased in strains fed high dietary fat. DIO is a condition that results in a state of chronic inflammation that results in the recruitment of macrophages and many other immune cells. Neutrophils are potent mediators of inflammation and can induce the activation of many pro-inflammatory factors, such as cytokines. (Khandekar et al. 2011). The above research demonstrates that high dietary fat can increase polyp number and burden, so to understand if diet could induce an inflammatory response, independent of diet, immune cells were measured after 60 days on the diet study (Figure
2.9). Total and differential white blood cell counts were measured and absolute lymphocytes, neutrophils, monocytes and eosinophils were determined. After 60 days on the diet study, absolute numbers of neutrophils were significantly elevated in all strains fed the HFCoco diet compared to the LF-fed controls, regardless of obesity or metabolic status (Figure 2.9). These results demonstrate that high dietary fat can increase these pro-inflammatory immune cells, independent of DIO and MetS.
Notably, although an increased polyp number and burden were observed in the
Min/+ obesity-susceptible A2.Apc males fed the HFCoco when compared to their LF-fed counterparts, this increase in tumor growth was significantly less when compared to
152
Figure 2.9 – Neutrophils increased in strains fed high dietary fat. After 60 days on the HFCoco and LFCoco diets, white blood cell counts were measured in B6 and CSSs with or without the Apc mutation. Lymphocytes (purple), eosinophils (green), monocytes (blue) and neutrophils (orange) were measured from whole blood collected from the retro-orbital sinus. After a 60 day exposure to the HFCoco diet, circulating neutrophils were significantly elevated in all strains, regardless of obesity status, with the exception of the A2 strains, which showed a significant decrease in when compared to B6 fed the same diet. *p<0.05 (For statistical comparisons, each strains fed the HFCoco diet was compared to the same strain fed the LFCoco diet), ##p<0.01 (For statistical comparisons, each strain was compared to B6 or ApcMin/+ fed the same diet).
153 males of other strains that were fed the equivalent HF diet (Figure 2.8, Table 2.4). These data indicate the presence of a factor on chromosome 2 that restricts intestinal tumorigenesis. Furthermore, an enhanced inflammatory state was observed in the
Min/+ Apc mice fed the HFCoco when compared to their LF counterparts, as evidenced by increased blood counts of neutrophils (Figure 2.9). The corresponding numbers were comparably lower in the A2.ApcMin/+ mice (Figure 2.9), again pointing to chromosome 2 as critical to promoting inflammation and intestinal adenoma progression. This will be investigated in more detail in Chapter 4 of this thesis.
2.4 Discussion
DIO and MetS are highly correlated with increased risk of colon cancer in humans, contributing to the progression and mortality of the disease. As the obesity epidemic shows few signs of abating, obesity-related cancer risk is an important medical concern. The World Health Organization (WHO) currently estimates that 800 million adults will be obese by 2015, which is 300 million more than current approximations and predicts a rise in obese individuals by about 100 million a year (Mokdad et al. 2004;
Mokdad et al. 2005). A fundamental cause of obesity is the energy imbalance between calories consumed and calories expended, making obesity a highly preventable disease that can be regulated through diet. This makes the understanding of dietary effects on
DIO and MetS in relation to cancer an important area of research.
Because CSS and CSS.ApcMin/+ strains mimic the complexity of human obesity and the Apc mutation is present in the majority of human colon cancers, this mouse model system was an ideal system to recapitulate the conditions observed in human disease. DIO and MetS are complex multisystem disorders that are closely associated
154 with the consumption of high fat, making it difficult to understand the independent role of diet on tumorigenesis. Using a novel mouse model system to study the effects of diet, we were able to demonstrate that high dietary fat can induced polyp formation in mice prone to intestinal neoplasia, separate from DIO or MetS. A 3.0 – 4.0-fold increase in polyp number was observed in all strains fed the HFCoco diet, regardless of obesity status, demonstrating that diet is crucial mediator in polyp development in the ApcMin/+ model
(Table 2.5).
There are multiple hypotheses surrounding the effect of diet and DIO on colon tumorigenesis that include direct or indirect mechanisms. Evidence from this study suggests that this source of dietary fat, coconut oil modulates metabolic factors prior to the onset of obesity and is a crucial factor in cancer development. Coconut oil is high in saturated fat and composed mostly of lauric, myristic, and stearic fatty acids that could be working in combination or independently to increase polyp number and mass.
Neutrophils, potent pro-inflammatory immune cells were also elevated in mice fed the HFCoco diet, demonstrating that diet is sufficient to induce an immune response and activate potent pro-inflammatory immune cells. Although these results suggest that high saturated fat can be considered a dietary carcinogen, it is unclear if diets high in saturated fat lack some pro-apoptotic or anti-inflammatory factor, which also contributes to the effect observed in intestinal neoplasia.
These findings, in addition to elucidating an obesity-independent role for diet in colon cancer, suggest that inexpensive, noninvasive dietary intervention may be a useful medical option to delay the onset of tumor development in individuals predisposed to
155
Fasting Fasting Small HF Diet FBW EFPM BMI HOMA Colon Insulin Glucose Intestine
B6
A2
A9
A7
A17
Table 2.5 – Summary of CSS.ApcMin/+ response to high saturated fat. Obesity-susceptible strains (B6, A2, A9) showed elevated final body weight (FBW), epididymal fat pad mass (EFPM), body mass index (BMI), fasting insulin, fasting glucose, and HOMA-IR (HOMA) after 60 days on the HFCoco diet compared to LF- fed controls. In contrast, the obesity-resistant strains (A7, A17) fed the HFCoco diet did not show elevations in these same measurements when compared to the same strain fed the LF diet. All strains showed an increase in small intestinal and colon polyps when fed the HFCoco diet after 60 days. Green denotes significant increase in HF-fed mice compared to the same strain fed the LF diet. Yellow denotes no significant elevation between mice fed LF or HF diets.
156 colon cancer and may also be a beneficial preventative treatment in sporadic cases.
Medical professionals may use these results to help establish dietary guidelines for patients at risk of developing colon cancer. Because we demonstrate that high saturated fat can increase tumorigenesis in mice prone to intestinal neoplasia, humans, especially high risk individuals such as FAP patients, should avoid foods high in this type and composition of dietary fat. Calorically dense diets are usually used to treat humans suffering from cancer related-cachexia. These studies show that high dietary fat can induce early onset cachexia in mice with intestinal neoplasia, suggesting that fat should not be utilized to increase caloric content in human cachexic patients.
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CHAPTER 3
DIFFERENTIAL EFFECTS OF DIETARY FAT ON
INFLAMMATION AND CANCER OF THE INTESTINE
The results from this chapter were submitted for publication. Doerner SK, Reis ES, Leung ES, Ko JS, Heaney JD, Berger NA, Lambris JD, Nadeau JH. High-fat diet-induced complement activation mediates intestinal inflammation and neoplasia independent of obesity. Nature. Xx; xx-xx (2012).
Acknowledgements – I would like to thank Elaine S. Leung and Justine S. Ko for their tireless dedication and help with mouse work in these studies.
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3.1 Introduction
Dietary fat is a vital part of our diet that is essential for energy, the absorption of essential vitamins, proper brain and cell membrane development and hormone production
(Huffman et al. 2011). Although different types of dietary fat are crucial for healthy body function, some can elicit negative effects during disease progression, especially colon cancer. Evidence shows that consumption of high amounts of dietary fats are associated with increased risk of developing colon cancer. The effect of fats depends not only on the quantity, but also on the composition of specific fatty acids and the sources from which they are derived (Jacobs 1988; Willett 1989). The impact of specific dietary components on colon tissue likely depends on a range of complex processes that influence inflammation, growth, development and differentiation in the colon epithelium.
Dietary fat and inflammation are two factors that profoundly influence the development and progression of colon cancer. The first observations that linked inflammation to cancer were made in the nineteenth century, on the basis of observations that tumors often developed at sites of chronic inflammation and that inflammatory cells were present in the biopsied tumors (Balkwill et al. 2001; Mantovani et al. 2008).
Chronic inflammation that is usually associated with an obese state or inflammatory bowel diseases can lead to increased susceptibility to colon cancer (Pendyala et al. 2011;
Ullman et al. 2011). For example, individuals with inflammatory bowel disease have as much as a 35% increased risk for developing colon cancer, while anti-inflammatory drugs, such as non-steroidal anti-inflammatory drugs (NSAIDs) like cyclooxygenase-2
(COX-2) inhibitors or aspirin, have been effective in the reduction of intestinal tumor formation (Koehne et al. 2004; Flossmann et al. 2007). The COX-2 inhibitor, celecoxib, has been shown to decrease polyps by as much as 93% in mouse models and significantly
159 decreases polyp multiplicity in Familial Adenomatous Polyposis (FAP) patients
(Kawamori et al. 1998; Steinbach et al. 2000).
Cytokines secreted from adipose tissue, adipokines, have been shown to be a large part of the inflammatory process observed in high fat diet consumption and diet-induced obesity (DIO). Leptin, a pro-inflammatory adipokine, has been shown to increase proliferation in human HT-29 cells and increases colon cell proliferation and aberrant crypt foci (ACF) in obese rats treated with 1,2-dimethylhydrazine (Liu et al. 2001).
Conversely, adiponectin, an anti-inflammatory adipokine, is adversely associated with colon cancer risk and high plasma levels are associated with as much as a 60% decrease in colon cancer risk (Okada et al. 2006).
Chronic low-grade inflammation results in the persistent production of macrophages and other pro-inflammatory immune cells, such as T lymphocytes in adipose and intestinal tissues. The secretion of pro-inflammatory cytokines such as tumor necrosis factor α (TNFα), interleukin-1β (IL-1β) and IL-6 can induce the differentiation and activation of lymphocytes and activate oncogenes such as NFκB and STAT3 (Fenton et al. 2006; Neurath et al. 2011). Epidemiological studies have demonstrated that diet- induced weight loss reduced systemic and local colonic expression of pro-inflammatory cytokines (Pendyala et al. 2011). What remains unclear is the effect that different dietary fats, specifically specific combinations of fatty acids, have on intestinal tumorigenesis.
To investigate the role of saturated, polyunsaturated (omega-6) and monounsaturated fats on intestinal polyp formation, ApcMin/+, a mouse model of intestinal neoplasia, were placed on diets constructed from coconut (hydrogenated), corn or olive oils, respectively. Diets were carefully constructed to control for other factors such as
160 protein amount and content, carbohydrate and mineral sources. We show that coconut and corn oils negatively affect polyp development and increase inflammation and polyp number and mass (overall polyp burden), while diets created with olive oil fail to initiation inflammation or increase polyp burden. We demonstrate that a short dietary exposure of 3 days is sufficient to induce significant polyp development in the small intestine of mice fed the HFCoco and HFCorn diets. Together, these results demonstrate that not all fats are created equal and that the source of fat, instead of the amount, contributes to intestinal tumorigenesis.
3.2 Methods
3.2.1 Mice. C57BL/6J (B6), C57BL/6J-ApcMin/+/J (ApcMin/+) were purchased from The
Jackson Laboratory (Bar Harbor, ME). Female ApcMin/+ mice are prone to developing mammary tumors, so only male mice were used for these studies to avoid complications with this second type cancer (Moser et al. 1990). Mice were maintained on a 12 hour light/dark cycle at the Wolstein Research Facility (CWRU). All procedures were approved and conducted in compliance with Institutional Animal Care and Use
Committee (IACUC) standards at Case Western Reserve University.
3.2.2 Diets. All modified diets were obtained from Research Diets, Inc. (New
Brunswick, NJ). All high fat (HF) diets contained 58% kcal/g from hydrogenated coconut, corn, or olive oil (HFCoco, HFCorn or HFOlive, respectively), while low fat (LF) diets contained 10.5% kcal/g from the same oils (LFCoco, LFCorn or LFOlive, respectively).
They differed in the amount of specific fats and carbohydrates, but were otherwise identical (Table 3.1). According to the manufacture specifications, HFCoco is high in
161 saturated fatty acids (99.1%) with the majority of fatty acids consisting of lauric, myristic and stearic acids, HFCorn is high in omega-6 polyunsaturated fatty acids (61.5%) with the majority of fatty acids consisting of linoleic, oleic and palmitic acids, and HFOlive is high in mono-unsaturated fatty acids (71.9%) with the majority of fatty acids consisting of oleic, linoleic, and palmitic acids (Table 3.1).
3.2.3 Study design. From birth to 30 days of age, all mice were fed an autoclaved standard laboratory diet that contained 13.5% fat, Purina 5010 LabDiet (Richmond, IN), and autoclaved water ad libitum. At 30 days of age, male mice were randomized to HF or
LF dietary groups and fed ad libitum until sacrifice after 3, 30 or 60 days on the diet.
Mice were fasted for 12-14 hours and anesthetized using isoflurane prior to blood collection. Whole blood, plasma and serum samples were collected from the retro-orbital sinus in tubes with or without EDTA. Body weight was measured every other day and body length was measured at the final time point to calculate body mass index (BMI). At the final time point mice were euthanized by cervical dislocation and epididymal fat pad mass (EFPM) was collected, weighed and used as a measure of adiposity. The small and large intestines were immediately removed, flushed using cold PBS and, cut longitudinally. Polyps were counted and cross sectional diameter was measured in the small intestine and colon using a Leica MZ10F Modular Stereomicroscope. Polyp size and number were used to calculate total polyp area (area = πr2), used as a surrogate measure of polyp burden in each mouse. Colon polyp incidence was recorded, and the presence of colon polyps (affected) was compared to the total number of mice on the study to calculate the percent colon polyp incidence for each strain and dietary group.
Intestinal samples were immediately collected for RNA and protein analysis, frozen in
162
Fat Majority Fatty Diet Fat (%) Carbohydrate (%) Protein (%) Source Acids (%) 5050 Crude 13.5 59.0 27.6 Lauric (47.6), LF Coconut 10.5 73.1 16.4 Myristic (18.0), Stearic (10.6), HF Coconut 58.0 25.5 16.4 Other (23.8) Linoleic (60.1), LF Corn 10.5 73.1 16.4 Oleic (24.9), Palmitic (10.9), HF Corn 58.0 25.5 16.4 Other (4.1) Oleic (70.5), LF Olive 10.5 73.1 16.4 Linoleic (13), Palmitic (11.5), HF Olive 58.0 25.5 16.4 Other (5)
Table 3.1 – Composition of hydrogenated coconut, corn and olive oil diets. The 5010 diet was used as a stock diet and all mouse strains were maintained on this diet until the start of the diet studies. The high and low fat coconut oil diets were constructed to be identical in protein, vitamin and mineral content, but differ in the amount of saturated fat, omega-6 polyunsaturated fat, and monounsaturated fat from hydrogenated coconut, corn and olive oils, respectively.
163 liquid nitrogen and stored at -80°C until use. Tissues were fixed in 10% buffered formalin and embedded in paraffin for histological analysis.
3.2.4 Metabolic parameters and cytokine analysis. Metabolic parameters are defined here as fasting insulin, glucose, adiponectin and leptin. Fasting insulin levels were determined using Mercodia Ultrasensitive Mouse Insulin ELISA (Uppsala, Sweden).
Fasting glucose was measured using an OneTouch Ultra glucometer (Life Scan, Inc.,
Milpitas, CA). Homeostatic model assessment of insulin resistance (HOMA-IR) was calculated using fasting insulin and glucose levels (HOMA-IR = fasting insulin (pmol/L) x fasting blood glucose (mmol/L) /22.5). Leptin and adiponectin were measured in the plasma using ELISA kits from Millipore (Billerica, MA). IL-6, IL-1β, TNF, IL-10, IL-23 were measured in the plasma, serum and intestinal samples using ELISA kits from R&D
Systems, Inc. (Minneapolis, MN) and used according to the manufacturer’s instructions.
3.2.5 Quantitative RT-PCR and protein analysis. Size-matched polyps and normal tissue were collected from the small intestine of ApcMin/+ mice and B6, respectively.
Tissues were immediately frozen in Qiagen RLT buffer (Valencia, CA) and RNA was extracted using the Qiagen RNeasy Mini Kit. Quantitative RT-PCR was done using
SYBR Green (Quanta BioSciences, Gaithersburg, MD) and Primer3 Software. Primers were described previously (Chapter 2, Table 2.1). Tissues for Western blot analysis were immediately submerged in RIPA buffer supplemented with phosphatase and protease inhibitors, frozen in liquid nitrogen and stored at -80°C until use. All antibodies
(AKT, pAKT, IKK, pIKK, NFκB, p65 NFκB, STAT3, pSTAT3) were purchased from
Cell Signaling Technology, Inc. (Beverly, MA) and used according to the manufacturer’s instructions.
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3.2.6 Statistical Analysis. Student’s t-tests and one-way analysis of variance (ANOVA) were used to determine statistical significance, which was accepted at the p<0.05 level after Bonferroni correction for testing multiple hypotheses.
3.3 Results
3.3.1 Differential effect of different dietary fat sources on obesity and metabolic syndrome. To understand the role of different dietary sources on diet-induced obesity
(DIO) and subsequent metabolic syndrome (MetS), B6 and ApcMin/+ mice were fed diets high or low in coconut, corn or olive oil for 60 days. It was demonstrated in Chapter 2 that 60 days on a high fat diet can induce DIO and MetS. If all dietary fats have similar effects on excess body fatness, obesity should be observed in all wild-type B6 mice fed a diet high in fat, regardless of source. If specific combinations of dietary fatty acids influence the progression of surplus fat storage, the source of fat will determine the
Min/+ obesity status. Similar to results described above (Chapter 2), Apc fed the HFCoco and HFCorn diets became cachexic after about 40 days on the diet study as evident by loss in body weight, decreased adiposity and lethargy (Figure 3.1). No cachexia was observed in mice fed the LFCoco or LFCorn, suggesting this state of ill health was a result of the high dietary fat and not the APC mutation alone. Conversely, no weight loss was
Min/+ observed in Apc fed the HFOlive or LFOlive diets, showing that diets constructed from olive oil did not induce or protected against cancer-related weight loss (Figure 3.1).
These results demonstrate that not all dietary fat sources can induce cancer-related cachexia and diets constructed from olive oil may be beneficial for individuals at risk of developing cancer-related cachexia.
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Figure 3.1 – Growth curves for mice fed the coconut, corn, or olive oil diets. Body weights were taken throughout the study for B6 and ApcMin/+fed diets high or low in coconut, corn or olive oil. Around 40 days on the diet study, ApcMin/+ fed the diets high in (a) coconut or (b) corn oil began to lose weight and show signs of cancer-related cachexia. This weight loss was not observed in the mice fed the (c) olive oil diet.
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After 60 days on the diet study, wild-type B6 fed the HFCoco were significantly heavier than corresponding LF-fed controls as measured by final body weight (FBW), epididymal fat pas mass (EFPM) and body mass index (BMI) (Figure 3.2, Table 3.2).
Conversely, mice fed the HFCorn failed to show an increase in FBW, EFPM and BMI when compared to mice fed the LFCorn (Figure 3.2, Table 3.2). Similar to the mice fed the coconut oil based diet, B6 fed the HFOlive diet were significantly heavier than mice fed the LFOlive diet. These results demonstrate that not all dietary fat sources equally encourage an increase in excess body mass and that an increase in caloric consumption alone is not sufficient to induce obesity. This could suggest that specific dietary fats are utilized or stored in distinctive ways, thus effecting overall body weight.
Because DIO and MetS are highly associated disorders, we next asked if specific dietary sources could differentially influence factors associated with MetS such as fasting insulin, fasting glucose or HOMA-IR after 60 days on the high fat diets. In humans,
MetS is characterized as a collection of metabolic disorders with obesity as a major characteristic of the syndrome (Groop 2000). Interestingly, the specific dietary fat sources had distinct effects on MetS, especially when analyzed in combination with the obesity status described above. Wild-type B6 mice fed the HFCoco developed DIO and had elevated fasting insulin, fasting glucose and HOMA-IR when compared to LF-fed controls (Table 3.2). This response is similar to what is observed in many humans patients suffering from MetS, where an increase in body weight associates with distruptions in insulin signaling. In contrast, B6 fed the HFOlive diet also developed obesity, but when compared to mice fed the LFOlive diet, did not show signs of developing
MetS when fasting insulin, fasting glucose or HOMA-IR were measured (Table 3.2). B6
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Figure 3.2 – Body weight parameters in mice fed coconut, corn or olive oil diets. Final body weight (FBW) and epididymal fat pad mass (EFPM) from B6 and ApcMin/+ fed diets constructed from coconut, corn or olive oils. After 60 days on the HFCoco diet (blue), B6 mice were significantly heavier than LF-fed control as measured by FBW and EFPM. No significant elevation in FBW or EFPM was observed in mice Min/+ fed the HFCorn diet (red) compared to corresponding controls. Both B6 and Apc fed the HFOlive diet (purple) were significantly heavier than mice fed the LFOlive diet after 60 days on the diet study. **p<0.001
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EFPM (g) Fasting Insulin Fasting Glucose Total Polyp Strain N Fat Source Diet Duration FBW (g) SEM BMI SEM SEM (µg/L) SEM (mg/dL) SEM Number B6.Apc+/+ 8 Coconut 30 23.89 0.80 0.35 0.03 0.24 0.007 0.36 0.01 209.6 5.1 0.0 0.0 B6.ApcMin/+ 9 Coconut 30 22.78 0.68 0.30 0.03 0.24 0.006 0.53 0.09 225.0 10.2 11.7 1.4 B6.Apc+/+ 7 Coconut 30 25.27 0.75 0.54 0.06 0.24 0.005 0.71 0.23 185.8 4.0 0.0 0.0 B6.ApcMin/+ 10 Coconut 30 22.63 0.35 0.39 0.05 0.24 0.005 0.91 0.13 229 13.7 81.6 8.3*** B6.Apc+/+ 10 Corn 30 23.25 0.46 0.37 0.03 0.22 0.003 0.48 0.05 183.6 11.7 0.0 0.0 B6.ApcMin/+ 15 Corn 30 22.26 0.28 0.42 0.02 0.21 0.003 0.24 0.03 164.8 6.9 27.2 1.8 B6.Apc+/+ 8 Corn 30 22.50 0.82 0.39 0.06 0.22 0.005 0.32 0.08 194.5 6.7 0.0 0.0 B6.ApcMin/+ 10 Corn 30 22.64 0.47 0.34 0.03 0.23 0.005 0.42 0.08 185.8 28.3 88.1 5.7*** B6.Apc+/+ 7 Olive 30 24.87 1.09 0.39 0.09 0.25 0.009 0.27 0.05 108.4 8.4 0.0 0.0 B6.ApcMin/+ 7 Olive 30 23.58 0.51 0.34 0.04 0.25 0.007 0.26 0.12 150.0 18.7 15.9 2.6 B6.Apc+/+ 6 Olive 30 25.49 1.05 0.44 0.11 0.26 0.008 0.30 0.06 150.3 10.1 0.0 0.0 B6.ApcMin/+ 8 Olive 30 24.14 0.78 0.43 0.06 0.25 0.007 0.29 0.02 153.0 12.2 24.8 1.5### B6.Apc+/+ 54 Coconut 60 27.91 0.24 0.61 0.12 0.24 0.008 0.34 0.14 167.3 14.2 0.0 0.0 B6.ApcMin/+ 54 Coconut 60 25.78 0.24 0.32 0.04 0.25 0.002 0.37 0.05 202.0 28.4 14.0 1.5 B6.Apc+/+ 46 Coconut 60 31.32 0.70** 1.29 0.11** 0.28 0.004** 1.23 0.21** 261.4 21.1** 0.0 0.0 B6.ApcMin/+ 51 Coconut 60 23.22 0.70 0.36 0.05 0.24 0.006 0.43 0.06 234.4 11.7 91.8 4.8*** B6.Apc+/+ 13 Corn 60 26.91 0.28 0.38 0.02 0.26 0.003 0.22 0.08 92.3 5.0 0.0 0.0 B6.ApcMin/+ 7 Corn 60 26.42 0.85 0.36 0.04 0.27 0.003 0.21 0.41 161.3 8.2 27.5 1.5 B6.Apc+/+ 13 Corn 60 26.28 0.78 0.60 0.08 0.24 0.008 0.43 0.09** 196.2 8.3*** 0.0 0.0 B6.ApcMin/+ 14 Corn 60 21.72 0.57 0.22 0.03 0.22 0.005 0.55 0.17** 200.1 10.5** 102.6 8.0*** B6.Apc+/+ 7 Olive 60 26.70 0.46 0.41 0.03 0.26 0.005 0.27 0.02 89.2 5.1 0.0 0.0 B6.ApcMin/+ 7 Olive 60 25.03 0.46 0.40 0.07 0.27 0.006 0.36 0.07 153.0 3.6 24.2 2.8 B6.Apc+/+ 17 Olive 60 30.94 1.06** 1.14 0.12*** 0.30 0.008*** 0.23 0.17 143.7 8.0 0.0 0.0 B6.ApcMin/+ 14 Olive 60 26.54 0.58 0.57 0.07 0.27 0.006 0.38 0.10 146.6 10.3 25.7 1.2 Table 3.2 – Body weight and metabolic parameters for mice fed coconut, corn or olive oil diets. Final body weight (FBW), epididymal fat pad mass (EFPM), body mass index (BMI), fasting insulin, fasting glucose, HOMA-IR and total polyp number were measured in B6 and CSSs with or without the Apc mutation fed the coconut, corn or olive oil diets. The grey shaded area denoted mice fed the LFCoco diet. For statistical analysis, each strain fed a HF diet was compared to the same strain fed the corresponding LF diet. **p<0.01, ***p<0.001.
169 fed the HFCorn diet did not develop obesity after 60 days on the diet study, but interestingly, had elevated levels of factors associated with MetS (Table 3.2). This demonstrates that there are intricate relationships between specific sources of dietary fatty acids and energy balance in mouse models and different dietary fat sources can have contrasting effects on disease outcome.
3.3.2 Differential effects of fat on polyp burden of the small intestine.
To test if any high fat in general or specific dietary sources could modulate polyp number or total polyp mass (polyp burden), B6 and ApcMin/+ were placed on diets high or low in coconut, corn or olive oil. After a 60 day exposure, polyp number was significantly increased (6.6- and 4.1-fold) in the males fed the HFCoco or HFCorn compared to LFCoco or LFCorn, respectively (Figure 3.3, Table 3.2). Total polyp mass was also significantly elevated in mice fed the diets high in coconut (19.4-fold) or corn (24.0-fold) oils compared to LF fed controls (Figure 3.3, Table 3.2). In contrast, no increase in polyp number or total polyp mass was observed between mice fed the HFOlive or LFOlive diets (Figure 3.3, Table 3.2). Mice fed the HFOlive failed to show the same increase in polyp number as observed in mice fed the HFCoco or HFCorn oil diets and when compared to mice fed these diets, had a 3.0- and 3.3-fold difference in polyp number, respectively.
These results demonstrate that the type of dietary fat can strongly influence intestinal polyp progression, independent of consumption of high calories alone.
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Figure 3.3 – Specific dietary fat sources have differential effects on polyp number and mass. Total polyp number and total polyp mass were measured in ApcMin/+ and strains after 60 days on the coconut, corn or olive oil diets. Total polyp number was increased in all strains fed the HFCoco Min/+ diet (blue)or HFCorn diet (red) compared to corresponding LF-fed controls. Apc fed the HFOlive (purple) failed to show an increase in polyp number when compared to LF-fed controls and was significantly less that observed in mice fed the coconut or corn oil diets. Total polyp Min/+ mass was significantly increased in Apc fed the HFCoco or HFCorn diets when compared to mice fed the corresponding LF diet. This increase in total polyp mass was not observed between mice fed the HFOlive or LFOlive diets. **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet), ###p<0.001 (For statistical comparisons, each strain was compared to B6 or ApcMin/+ fed the same diet).
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3.3.3 Contrasting responses to different fats on polyps of the colon.
The ApcMin/+ model is known for developing large numbers of polyps in the small intestine, similar to that seen in the colon of humans suffering from Familial
Adenomatous Polyposis (FAP) (Moser et al. 1990). To investigate if different dietary fats could change the number of ApcMin/+ mice affected with colon polyps (incidence) or modulate the number of polyps per mouse, male mice were fed diets high or low in
Min/+ coconut, corn or olive oil. After 60 days on the HFCoco diet, 82% of Apc mice had developed colon tumors compared to 46% observed in the LF-fed controls (χ2 = 14.273, p<0.0005). A 2-fold increase in total colon polyp numbers were observed in ApcMin/+ fed the HFCoco compared to mice fed the LFCoco (Figure 3.4). Similarly, polyp incidence was
Min/+ 2 increased to 94% in Apc fed the HFCorn diet compared to those fed the LFCorn diet (χ
= 12.0, p<0.0005), with a 5.6-fold increase in total colon polyp number in the mice fed the HFCorn diet compared to LF-fed controls (Figure 3.4). Interestingly, few colon polyps were detected in mice fed the HFOlive diet and although a 13% incidence was recorded, this was not significantly elevated from the 0% incidence observed in the ApcMin/+ fed the
2 LFOlive diet (χ = 0.777, p<.661). Mice fed the HFOlive diet had an average of 0.35±0.33 total colon polyps after 60 days on the diet study, which was significantly reduced compared to the 1.3±0.13 (p<0.001) or 2.4±0.27 (p<0.0001) observed in ApcMin/+ fed the
HFCoco or HFCorn diets, respectively (Figure 3.4).
3.3.4 Early effects of different dietary fats on DIO and MetS.
To test the early effects of coconut, corn and olive oils, before the onset of cancer- related cachexia, on obesity and associated MetS, B6 and ApcMin/+ males were placed on
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Figure 3.4 – Specific dietary fat sources have differential effects of colon polyp incidence. When present, colon polyp numbers were counted in each individual mouse. ApcMin/+ fed diets high in coconut (blue) or corn (red) oil showed a significant increase in colon polyp incidence compared to corresponding LF-fed controls. No difference was observed between mice fed diets high or low in olive oil (purple). Mice fed the Min/+ HFOlive failed to show the same increase in colon polyp incidence as Apc fed the HFCoco or HFCorn diets. **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet), ###p<0.001 (For statistical comparisons, each strain was compared to B6 or ApcMin/+ fed the same diet).
173 diets constructed from these various oils for 30 days. Growth curves were recorded for
B6 and ApcMin/+ fed diets high or low in coconut, corn or olive oil and demonstrate that all strains were still gaining weight at a normal rate of development, were not showing signs of cachexia and had not yet reached overt obesity (Figure 3.5). After 30 days on
Min/+ the HFCoco diet, B6 and Apc , no significant difference is observed between mice the
LF control diet as measured by FBW, EFPM, and BMI (Figure 3.6, Table 3.2). Similar results were observed in mice fed the corn and olive oil diets, 30 days was not sufficient to cause DIO or adiposity in mice fed high fat (Figure 3.6, Table 3.2). To measure if 30 days on a high fat diet was sufficient to induce increases in metabolic factors associated with MetS were measured. No significant elevations in fasting insulin, fasting glucose or
Min/+ HOMA-IR were observed in B6 or Apc males fed the HFCoco, HFCorn or HFOlive compared to corresponding LF-fed controls (Figure 3.7, Table 3.2).
3.4.5 Early effects of different dietary fat sources on intestinal neoplasia.
To examine if specific dietary fat combinations could increase intestinal tumorigenesis before the onset of DIO and MetS and to examine the early stages of polyp development, polyp number and total polyp mass were measured in ApcMin/+ after 30 days on the coconut, corn or olive oil diets (Figure 3.8). It was demonstrated above that 30 days on a high fat diet was not sufficient to cause DIO or MetS, so any change in overall polyp burden could be attributed to the effect of specific components of the diet. The specific dietary fat combinations had similar effects on polyp burden at 30 and 60 days.
Min/+ Polyp number was significantly increased by 6.6-fold in Apc fed the HFCoco diet compared to those fed the LFCoco diet (Figure 3.8, Table 3.2). Comparatively, total
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Figure 3.5 – Growth curves for B6 and ApcMin/+ fed the coconut, corn, or olive oil diets for 30 days. Body weights were taken throughout the 30 day diet study. All mice, regardless of dietary group, demonstrated increases in body weight that were appropriate for normal murine development. No signs of cancer-related cachexia were observed during this time period.
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Figure 3.6 – Body weight parameters for mice fed coconut, corn or olive diets. Final body weight (FBW) and epididymal fat pad mass (EFPM) from B6 and ApcMin/+ fed diets constructed from coconut, corn or Min/+ olive oils. No significant difference in FBW or EFPM was observed between B6 or Apc fed the HFCoco (blue), HFCorn (red) or HFOlive (purple) and the corresponding LF-fed controls after 30 days on the diet study.
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Figure 3.7 – Metabolic parameters from mice fed coconut, corn or olive oils. Fasting insulin and HOMA- IR from B6 and ApcMin/+ fed diets constructed from coconut, corn or olive oils. After 30 days on the diet study, no elevations in fasting insulin or HOMA-IR were observed in mice fed the HFCoco (blue), HFCorn (red) or HFOlive (purple) compared to mice fed the corresponding LF controls.
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Figure 3.8 – Specific dietary fat sources have differential effects on polyp number and mass after 30 days. Total polyp number and total polyp mass were measured in ApcMin/+ and strains after 300 days on the coconut, corn or olive oil diets. Total polyp number was increased in all strains fed the HFCoco diet (blue) or HFCorn diet (red) compared to Min/+ corresponding LF-fed controls. Apc fed the HFOlive (purple) failed to show an increase in polyp number when compared to LF-fed controls and was significantly less that observed in mice fed the coconut or corn oil diets. Total polyp mass was significantly Min/+ increased in Apc fed the HFCoco or HFCorn diets when compared to mice fed the corresponding LF diet. This increase in total polyp mass was not observed between mice fed the HFOlive or LFOlive diets. **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet), ###p<0.001 (For statistical comparisons, each strain was compared to B6 or ApcMin/+ fed the same diet).
178
179 polyp mass was also elevated by 22.9-fold in mice fed the HFCoco compared to LF-fed controls (Figure 3.8, Table 3.2). A similar pattern was observed in ApcMin/+ fed the
HFCorn diet, with a 3.2- and 24.0-fold increase in polyp number and total polyp mass, respectively, compared to mice fed the LFCorn diet (Figure 3.8, Table 3.2). Similar to the results observed after 60 days on the diet study, male mice fed the HFOlive diet failed to show this amplification of total polyp number or mass (Figure 3.8, Table 3.2). While tumor number remained similar between the 30 and 60 days, total polyp mass increased
Min/+ between these two time points in Apc fed the HFCoco or HFCorn, suggesting that some
HF diets can promote tumor growth as well as initiation. Additionally, these results suggest that the increase in overall polyp burden was due to components of the coconut and corn oil diets and not access body fatness or deregulated insulin signaling.
3.4.6 Effects of dietary fat sources on inflammation.
Chronic inflammation is observed in cases of obesity and inflammatory bowel disease is associated with increased risk of developing colon cancer (Pendyala et al.
2011; Ullman et al. 2011). To examine if the variances in polyp number and total polyp mass observed in response to the dietary fat sources that were detrimental to disease was due to distinctive dietary consequences on inflammation, systemic and local intestinal inflammation was measured in B6 and ApcMin/+ fed the coconut or corn oil diets for 30 days (Figure 3.9).
Adiponectin is an adipokine involved in glucose regulation and fatty acid catabolism that is secreted from fat cells in amounts that are inversely proportional to the amount of adipose tissue. The more weight an individual gains, systemic levels of
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Figure 3.9 – Expression analysis from B6 and ApcMin/+ fed the coconut oil diets for 30 days. (a) Expression analysis was conducted for circulating levels of leptin, adiponectin, IL-1β and IL-6 (red). (b) F4/80 and IL-6 expression were measured in adipose tissue (green). (c) Members of the prostaglandin pathway, COX-2 and PGE2, were measured from intestinal tissue (blue). (d) Inflammatory factors, IL-6, TNFα, and IL-1β as well as the oncogene, c-Myc, were measured from intestinal tissue (blue). *p<0.05, **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet).
181 adiponectin decrease and is thus, significantly decreased in obese individuals (Berg et al.
2002). Adiponectin has roles as an anti-inflammatory adipokine and has been shown to reduce pro-inflammatory factors such as IL-6 and TNFα (Yokota et al. 2000). Leptin is a satiety factor that is secreted mostly by adipose tissue and in contrast to adiponectin, is elevated in obese individuals (De Vos et al. 1995; Maffei et al. 1995). To test if different dietary fats could influence the levels of circulating adiponectin, plasma samples were collected from B6 and ApcMin/+ fed the coconut or corn diets for 30 days, prior to the onset of DIO or characteristics of MetS (Figure 3.9a). Male mice fed the HFCoco had a significant decrease in circulating adiponectin levels compared to LF-fed controls. B6 fed the LFCoco had the highest levels of adiponectin and was significantly higher than the other strains fed the coconut oil based diet. A significant decrease in adiponectin was
Min/+ observed in Apc compared to B6 controls, regardless of LFCoco or HFCoco diet.
Similar to the results observed in mice fed the coconut oil based diet, mice fed the HFCorn also demonstrated a significant decrease in circulating adiponectin. Elevations in
Min/+ systemic leptin levels were observed in B6 and Apc fed the HFCoco diet compared to mice fed the LFCoco diet after 30 days (Figure 3.9a). Similarly, leptin levels were
Min/+ significantly elevated in B6 and Apc fed the HFCorn diet compared to LF-fed controls.
Current understanding suggests that circulating adiponectin and leptin are regulated by weight gain and changes in adipose tissue size. Here we demonstrate that both of these factors can be modulated prior to the onset of DIO or changes in insulin signaling and therefore, suggests that adiponectin and leptin are modulated by dietary fat consumption.
Additional systemic inflammatory factors were measured in B6 and ApcMin/+ fed the LF or HF coconut or corn oil diets (Figure 3.9a). IL-6 and IL-1β are potent
182 proinflammatory factors that are increased in association with DIO and MetS and are also elevated in colon cancer patients. B6 fed the HFCoco diet had a significant increase in circulating IL-6 and IL-1β levels compared to LF-fed controls. Similar results were observed in B6 fed the HFCorn compared to mice fed the corresponding LF diet (data not shown). B6 mice do not develop intestinal polyps and were not significantly obese at this time point, so this suggested that these increases in IL-6 and IL-1β were due to the
HF diets. Conversely, levels of the anti-inflammatory cytokine, IL-10, were unchanged in mice fed coconut or corn oil diets (data not shown). This demonstrates that diets high in saturated or ω-6 polyunsaturated fats were able to induce an inflammatory response after only 30 days on the diet study prior to signs of DIO or MetS.
Macrophage infiltration in adipose tissue was assayed by measuring the expression levels of F4/80 in mice fed the coconut or corn oil diets (Figure 3.9b, data not shown). Wild type B6 fed the HFCoco or HFCorn diets has significantly increased
F4/80 levels compared to mice fed the corresponding LF control diets (Figure 3.9, data not shown), demonstrating that immune cell infiltration could be induced by saturated or
ω-6 polyunsaturated fatty acids, independent of positive energy balance or impaired
Min/+ insulin signaling. Apc fed the HFCoco or HFCorn diets had a significant elevation in macrophage infiltration compared to the same strain fed the corresponding LF diet or compared to wild type mice fed the HF diet as measured by F4/80 expression levels.
Levels of IL-6 were also elevated in wild type B6 fed the HF coconut or corn oil diets compared to corresponding LF-fed controls and this increase was further exacerbated in
ApcMin/+ fed these same HF diets (Figure 3.9b, data not shown). These results demonstrate that 30 days on a high fat diet is sufficient to induce macrophage infiltration
183 and an inflammatory response in adipose tissue as measured by F4/80 and IL-6, respectively.
Local expression of inflammatory factors was measured in intestinal tissue of B6 and ApcMin/+ fed diets constructed from coconut and corn oils (Figure 3.9d, data not shown). After 30 days on the diet study, pro-inflammatory cytokines such as IL-6, IL-1β and TNFα were significantly increased in B6 fed HFCoco or HFCorn oil diets and this response was further elevated in ApcMin/+ fed the same amount of dietary fat (Figure
3.9c). Expression of pro-inflammatory members of the prostaglandin pathway, COX-2
Min/+ and PGE2, were significantly elevated in the intestinal tissue of Apc fed the HFCoco or
HFCorn diets (Figure 3.9c, data not shown). This shows that diets constructed from coconut or corn oil increase intestinal inflammation prior to the onset of obesity.
Consumption of these same dietary fats exacerbate inflammatory signal in ApcMin/+ mice and promote increased prostaglandin signaling.
3.4 Discussion
Specific combinations of dietary fats had differential effects on total polyp number and total polyp mass (polyp burden) in the ApcMin/+ mouse model. We demonstrated that two dietary oils, coconut and corn, could induce increases in the overall polyp burden, independent of changes in energy balance or insulin signaling
(Table 3.3). We also demonstrated that olive oil, even in high amounts, was not sufficient to induce an increase in polyp burden or MetS in B6 or ApcMin/+. These results show that dietary fats that are high in saturated or omega-6 polyunsaturated fats can promote
184
Fasting Fasting Small HF Diet FBW EFPM BMI HOMA Colon Insulin Glucose Intestine
Coconut
Corn
Olive
Table 3.3 – Summary of dietary influences on B6 and ApcMin/+. Characteristics of obesity, MetS as well as polyp number in mice fed HF coconut, corn or olive oil diets for 60 days are summarized in the table above. Final body weight (FBW), epididymal fat pad mass (EFPM), body mass index (BMI), fasting insulin, and glucose were compared between mice fed HF diets and the corresponding LF diets. Small intestinal and colon polyp measurements were compared between mice fed HF and LF-fed controls. A green arrow denotes that a particular measurement in the HF-fed mice was significantly elevated compared to mice fed the corresponding LF control diet. A yellow dash indicates that there was no significant difference observed between mice fed the LF or HF diet.
185 disease progression, while those high in monounsaturated fats can be beneficial in restricting polyp growth.
Diet-induced inflammation is dependent on the source of dietary fat and not high caloric intake. We show that two different sources of fat, from coconut or corn, can induce inflammation in the intestine of ApcMin/+ mice and that this inflammation corresponds to the high polyp burden also observed in mice fed these same oils. We show that diets high in coconut and corn oil elicit inflammatory responses that are further exacerbated in mice which development intestinal neoplasia. We demonstrate that changes in adipokines and cytokine profiles occurs prior to the development of DIO or
MetS, and thus supporting that polyp development is affected by nutritional modification.
Together these results demonstrate a beneficial effect of dietary olive oil, while diets high in coconut and corn oil have detrimental effects on intestinal carcinogenesis. Differences in the influence of consumption of olive oil on insulin signaling, also suggest that this dietary fat may exert favorable effects MetS outcome.
The American diet depends heavily on the consumption of saturated fats (from beef, coconut oil, butter and dairy products) and omega-6 fats (from eggs, corn and other vegetable oils), so understanding the role that each plays on disease development is essential for the prevention, treatment and understanding diet-induced tumorigenesis
(Kant et al. 1994; Song et al. 2000). We have shown above that these dietary fats have adverse impacts on diseases that are associated with the development of cancer (DIO and
MetS) and increased the risk of intestinal tumorigenesis. Clinically, this information could be useful as individuals susceptible to cancers of the intestine should avoid these dietary fats. Low fat diets could be substituted for high fat ones and beneficial dietary
186 sources (olive) suggested instead of detrimental ones (coconut or corn). Diet as a method of preventative care against intestinal tumorigenesis is non-invasive and inexpensive when compared to radiation therapy or surgery. Future studies should focus on the beneficial effects of olive oil in colon cancer prevention in humans.
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CHAPTER 4
HIGH FAT DIET-INDUCED COMPLEMENT SIGNALING CONTRIBUTES TO INTESTINAL ADENOMA RISK
The results from this chapter were submitted for publication. Doerner SK, Reis ES, Leung ES, Ko JS, Heaney JD, Berger NA, Lambris JD, Nadeau JH. High-fat diet-induced complement activation mediates intestinal inflammation and neoplasia independent of obesity. Nature. Xx; xx-xx (2012).
Acknowledgements – I would like to thank Elaine S. Leung and Justine S. Ko for their tireless dedication and help with mouse work in these studies, David A. DeSantis for assistance with the PMX53 injection studies and Edimara S. Reis for aiding with the cell sorting and FACS analysis.
188
4.1 Introduction
The complement component cascade is an integral part of the innate and adaptive immune system involved in phagocytosis, cell lysis and chemotaxis. It has been demonstrated that the complement cascade functions in both metabolic syndrome and some cancers (Markiewski et al. 2008; Hernández-Mijares et al. 2011), however a role for complement factors in diet-induced tumor promotion has not been identified. The complement cascade is an important part of both the innate and adaptive immune response, functioning in the degranulation of mast cells, anaphylatoxin activity, chemotaxis and activation of leukocytes. Complement component 3 (C3) has been shown to be activated early in metabolic syndrome, is elevated in both obese children and adults, and genetic inhibition of the C3 receptor (C3aR) protects against diet-induced insulin resistance (Zhang et al. 2003; Mamane et al. 2009; Hernández-Mijares et al. 2011). C3 is elevated in patients suffering from inflammatory bowel diseases, syndromes that cause damage to the intestinal lining and predispose patients to colon cancer (Chen et al. 2011).
C5a is a downstream production of C3 activation and is a potent chemokine that is involved in the stimulation of neutrophils and depending on cell type, up-regulation of pro-inflammatory factors such as IL-1β, IL-6, TNFα, and NFκB (Guo et al. 2005).
Additionally, it has been demonstrated that genetic and pharmacological inhibition of the complement cascade reduces growth of transplanted cervical cancer growth in mice
(Markiewski et al. 2008). Thus suggesting that the complement system may be a central mediator of the chronic intestinal inflammation associated with diet-induced obesity and may significantly contribute to increased colon cancer risk.
189
We show that a diet high in hydrogenated coconut oil increases circulating and local inflammatory factors and the complement component C5a. Pharmacological or genetic inhibition of complement significantly prevents the dietary-induced increase in polyp number and burden in the ApcMin/+ model, demonstrating an intimate relationship between diet and the complement cascade in the intestine. We show a central and novel role for the complement cascade in diet-induced polyp development and show that both genetic and pharmacological inhibition of C5aR can prevent intestinal neoplasia by inhibiting NFκB signaling.
4.2 Methods
4.2.1 Mice. C57BL/6J (B6), C57BL/6J-ApcMin/+/J (ApcMin/+) were purchased from The
Jackson Laboratory (Bar Harbor, ME). Mice were maintained on a 12 hour light/dark cycle at the Wolstein Research Facility (CWRU). The complement knockout, C57BL/6J-
C3-/- (C3-/-) and C57BL/6J-C5aR-/- (C5aR-/-) were provided by John Lambris (University of Pennsylvania)( Höpken et al. 1996; Circolo et al. 1999). These strains were backcrossed for 10 generations onto a C57BL/6J background at the University of
Pennsylvania, Philadelphia, PA. All procedures were approved and conducted in compliance with Institutional Animal Care and Use Committee (IACUC) standards at
Case Western Reserve University.
4.2.2 Diets. Diets were obtained from Research Diets, Inc. (New Brunswick, NJ) that differ in the amount of fat, but are identical in vitamins, protein sources, and minerals.
The high fat (HF) diet contained 58% kcal/g from hydrogenated oil (HF), while the low fat (LF) diet contained only 10.5% kcal/g from the same oil (LF). The coconut oil diets are rich in saturated fatty acids (99.1%) such as lauric and myristic acids (Table 2.2). The
190 amounts of carbohydrates were increased in the LF diet to compensate for the loss of calories that would result from the fat. For this reason, the HF and LF diets will have comparable caloric values with 5558.5kcal/g and 5557.0kcal/g, respectively.
4.2.3 Study design. From birth to 30 days of age, all mice were fed an autoclaved standard laboratory diet that contained 13.5% fat (Table 2.2), Purina 5010 LabDiet
(Richmond, IN), and autoclaved water ad libitum. At 30 days of age, male mice were randomized to HF or LF dietary groups and fed ad libitum until sacrifice after 30 or 60 days on the diet. Prior to blood collection, mice were fasted for 12-14 hours and anesthetized using isoflurane. Whole blood, plasma and serum samples were collected from the retro-orbital sinus in tubes with or without EDTA. Body weight was measured every other day and body length was measured at the final time point to calculate body mass index (BMI). At the final time point mice were euthanized by cervical dislocation and epididymal fat pad mass (EFPM) was collected and weighed as a measure of adiposity. The small and large intestines were immediately removed, flushed using cold
PBS and, cut longitudinally. Since polyp frequency varies in different regions of the small intestine, the small intestine was sectioned into four equal parts when analyzed.
The regions were labeled SI-1 to SI-4, starting from the duodenum located below stomach (SI-1) to the jejunum (SI-2 and SI-3) to the ileum (SI-4) which is located above the cecum. The large intestine was excised and analyzed as one region (LI-1). Polyps were counted and cross sectional diameter was measured in the small intestine and colon using a Leica MZ10F Modular Stereomicroscope. Individual polyp size and number were used to calculate a polyp area (area = πr2) for each polyp present in the intestine of a mouse. The sum of all the polyp areas per mouse was used to calculate a total polyp mass
191 that was used as a surrogate measure of polyp burden. Colon polyp incidence was recorded, and the presence of colon polyps (affected) was compared to the total number of mice on the study to calculate the percent colon polyp incidence for each strain and dietary group. Intestinal samples were immediately collected for RNA and protein analysis, frozen in liquid nitrogen and stored at -80°C until use. Tissues were fixed in
10% buffered formalin and embedded in paraffin for histological analysis.
4.2.4 Metabolic parameters and cytokine analysis. Fasting insulin levels were determined using Mercodia Ultrasensitive Mouse Insulin ELISA (Uppsala, Sweden).
Fasting glucose was measured using a OneTouch Ultra glucometer (Life Scan, Inc.,
Milpitas, CA). Homeostatic model assessment of insulin resistance (HOMA-IR) was calculated using fasting insulin and glucose levels (HOMA-IR = fasting insulin (pmol/L) x fasting blood glucose (mmol/L) /22.5). Leptin and adiponectin were measured in the plasma using ELISA kits from Millipore (Billerica, MA). C5a, IL-6, IL-1β, TNF, IL-10,
IL-23 were measured in the plasma, serum and intestinal samples using ELISA kits from
R&D Systems, Inc. (Minneapolis, MN) and used according to the manufacturer’s instructions.
4.2.5 Quantitative RT-PCR and protein analysis. After 30 and 60 days on the diet study, size-matched polyps and normal tissue were collected from the small intestine of
ApcMin/+ mice and B6, respectively. Tissues were immediately frozen in Qiagen RLT buffer (Valencia, CA) and RNA was extracted using the Qiagen RNeasy Mini Kit.
Quantitative RT-PCR was done using SYBR Green (Quanta BioSciences, Gaithersburg,
MD) and Primer3 software (Rozen et al. 2000). Primer sequences are indicated in
Chapter 2 in Table 2.1. Tissues for western blot analysis were immediately submerged in
192
RIPA buffer supplemented with phosphatase and protease inhibitors, frozen in liquid nitrogen and stored at -80°C until use. All antibodies (AKT, pAKT, IKK, pIKK, NFκB, p65 NFκB, STAT3, pSTAT3) were purchased from Cell Signaling Technology, Inc.
(Beverly, MA) and used according to the manufacturer’s instructions.
4.2.6 Pharmacological inhibition of C5aR. C5aR inhibition was achieved using the
Ac-Phe-[Orn-Pro-(D-Cha)-Trp-Arg] peptide (PMX-53) (Paczkowski et al. 1999). An inactive peptide containing the same amino acids in a scrambled order was used as control. Drugs were diluted in PBS and subcutaneous injections were administered every other day at 1.0 or 2.0 mg/kg. For prevention studies, mice were injected with 1.0 mg/kg
PMX53 and fed a HFCoco for 30 days simultaneously. For treatment studies, mice were fed HFCoco for 30 days to ensure the maximum induction of polyp formation, then
2.0mg/kg PMX53 was administered for an additional 30 days while mice were simultaneously maintained on the HF diet.
4.2.7 Fluorescence-activated cell sorting (FACS) of intestinal immune cells.
Epithelial cells and lymphocytes from the lamina propria were isolated using a Percoll gradient as previously described (Denning et al 2007). Antibodies for CD11b, CD326,
CD88, CD274, F4/80, CD8, NK1.1, CD11c, CD3, CD45, CD103, CD4, I-Ab and GR1 were purchased from Biolegend (San Diego, CA) and used according to the manufacturer’s instructions. Alternatively, cells were stained with the respective isotypes.
All cell preparations showed at least 95% viability as determined by staining with DAPI
(Life Technologies). Samples were analyzed using the BD FACSCanto II flow cytometer software (BD Biosciences) and FCS Express (v4.0; De Novo Software).
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4.2.8 Statistical Analysis. Student’s t-tests and one-way analysis of variance (ANOVA) were used to determine statistical significance, which was accepted at the p<0.05 level after Bonferroni correction for testing multiple hypotheses.
4.3 Results
4.3.1 A high fat diet induces inflammation in the circulation and intestine.
Inflammation is a key component of cancer and it known to be increased in patients affected with diet-induced obesity. To examine if high dietary fat increased potent inflammatory factors early in intestinal polyp development, cytokines were measured from the blood and intestinal tissue of ApcMin/+ fed the coconut oil diets for 30 days (Figure 4.1). Local expression levels from intestinal tissue of proinflammatory IL-6,
Min/+ IL-1β, and COX-2 were significantly elevated in Apc fed the HFCoco diet (Figure
4.1). Significant increases in IL-6 and IL-1β were also observed in B6 mice fed the
HFCoco diet compared to LF-fed controls, demonstrating that diet can increase local expression of intestinal cytokines. Circulating levels of pro- and anti-inflammatory cytokines were measured in B6 and ApcMin/+ after 30 days on the diet study (Figure 4.1).
Circulating levels of IL-6, IL-1β, MCP-1 and C5a were significantly elevated in both strains fed a diet high in coconut oil compared to those fed LF, demonstrating that diet can induce an increase in systemic inflammation (Figure 4.1). Levels of TNFα were
Min/+ increased in Apc fed the HFCoco diet, showing that high saturated fat could exacerbate the pro-inflammatory effect in APC mutants. IL-10 was unchanged suggesting that
194
Figure 4.1 – Expression analysis from B6 and ApcMin/+ fed the coconut oil diets for 30 days. Expression analysis was conducted in intestinal samples from B6 and ApcMin/+ for IL-6, IL-1β and COX-2 (blue) after 30 days on the diet study. Circulating levels of IL-1β, IL-6, IL-10, TNFα, MCP-1 and C5a (purple) were measured in B6 and ApcMin/+ after 30 days. *p<0.05, **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet).
195 circulating inflammation was not due to repression of the anti-inflammatory IL-10 cytokine. Additionally, IL-1β and IL-6 levels were further exacerbated in ApcMin/+ suggesting a role for dietary induced inflammation in the promotion of polyp development (Figure 4.1).
4.3.2 Dietary mediation of complement induced inflammation in intestinal neoplasia.
Interestingly, polyp numbers in A2.Apc fed the HF and LF were reduced by 2.6-fold
(p<0.0001) and 2.0-fold (p<0.0001), respectively when compared to ApcMin/+ fed the same diets (Figure 4.2). Polyp burden was also significantly decreased in A2.Apc fed the
HF and LF diets (Figure 4.2) when compared to ApcMin/+ fed the same diet (5.7-fold; p<0.001 and 3.3-fold; p<0.001, respectively). A2 strains failed to show an immune response, as neutrophils were not increased after exposure to a HF diet, suggesting that
A/J chromosome 2 contains a modifier that mediates dietary-induced inflammation and intestinal neoplasia. Intriguingly, an essential complement component factor, C5, is located on this chromosome, is dysfunctional in the A/J inbred strain and is critical for neutrophil recruitment during the immune response (Linton 2001). To test if complement
Min/+ component C5a (C5a) was activated in B6 or Apc fed the HFCoco diet, circulating levels of C5a were measured by ELISA. After 30 and 60 days exposure to the HFCoco diet, C5a levels were significantly increased in both B6 and ApcMin/+ males compared to mice fed the corresponding LFCoco diet (Figure 4.3). No detectable levels of C5a were observed in A2.ApcMin/+ or wild-type A2, confirming the absence of complement component C5a in these strains (Figure 4.4). The activation of C5a suggests that high dietary fat can lead to activation of the complement cascade, suggesting a role for
196
Min/+ Figure 4.2 – Total polyp numbers are decreased in A2.Apc fed a HFCoco diet. Total polyp numbers were compared between ApcMin/+ and A2.ApcMin/+ fed diets high or low in coconut oil for 60 days. No significant difference was observed between Min/+ these two strains fed the LFCoco diet. In contrast, A2.Apc had significantly Min/+ reduced polyp numbers when compared to Apc fed the HFCoco diet. . ****p<0.0001 (For statistical comparisons, ApcMin/+ fed the HF diet was compared to A2.ApcMin/+ fed the HF diet, while the two strains fed the LF diet were also used as comparison).
197
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3 0 0 0 B 6 A P C B 6 A P C B 6 A P C B 6 A P C ______L F H F L F H F ______3 0 D a y s 6 0 D a y s
Figure 4.3 – Complement C5a is elevated in mice fed a high fat diet for 30 and 60 days. Circulating levels of complement component C5a (C5a) were measured after 30 and 60 days on the coconut oil diets. B6 and ApcMin/+ had significantly elevated levels of C5a after 30 and 60 days when compared to LF-fed controls. *p<0.05, **p<0.01, ****p<0.0001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet).
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Figure 4.4 – Strains that carry the A/J chromosome 2 have no detectable levels of C5a. Levels of C5a were measured after 60 days Min/+ Min/+ on the HFCoco diet in B6, Apc , A2, and A2.Apc . No detectable levels of C5a were detected in the strains that carried A/J chromosome 2. ****p<0.0001 (For statistical comparisons, ApcMin/+ fed the HF diet was compared to A2.ApcMin/+ fed the HF diet and B6 was compared to A2).
199 complement mediated inflammation in high fat diet-induced polyp development in
ApcMin/+ mice.
4.3.3 Genetic and pharmacological inhibition of complement signaling attenuates intestinal neoplasia. To verify the effect of complement deficiency on polyp development, C3-/- mice were combined with ApcMin/+ to generate mice lacking complement component C3, which is a key factor in all three complement signaling pathways and prone to intestinal neoplasia (C3-/-;ApcMin/+). After 30 days exposure to the
HF diet, mice that were partially or fully deficient for C3 had dose-dependent reductions in polyp number (2.0- and 3.7-fold, respectively) and burden (5.7- and 53.4-fold, respectively) in the small intestine (Figure 4.5). These results demonstrate that genetic inhibition of all complement pathways significantly reduces intestinal neoplasia. Similar results were observed when ApcMin/+ were crossed with mice deficient in the receptor of the pro-inflammatory complement component C5a (C5aR) to produce C5aR-/-;ApcMin/+ mice. After 30 days exposure to the HFCoco diet, a substantial decrease in polyp number and burden was observed in mice partially (2.5- and 14.8-fold, respectively) or fully (4.0- and 100.0-fold, respectively) deficient for C5aR. (Figure 4.5). Interestingly, no significant reduction in polyp number was observed in C5aR deficient mice fed the LF diet. These results demonstrate a complex interaction between a high fat diet and complement-mediated inflammation and that this pro-inflammatory response promotes tumor development.
To test the effect of inhibiting the pro-inflammatory C5a signaling, ApcMin/+ fed the HF diet were treated with a pharmacological agent, PMX53, that binds to C5aR and inhibits downstream signaling (Figure 4.5). After 30 days exposure to the HF diet as well
200
Figure 4.5 – Polyp numbers are reduced in mice deficient in C5a. After 30 days on the HFCoco diet, mice both partially and fully deficient in C5a showed a dose-dependent decrease in total polyp number and mass. This same pattern was observed in mice fed the HFCoco diet and treated with PMX53, a C5aR inhibitor. Significant reductions were observed in PMX53 treated mice compared to untreated or those treated with the control inhibitor. **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to B6). ###p<0.001 (For statistical comparisons, mice treated with the control inhibitor were compared to mice treated with PMX53).
201 as PMX53 treatment, ApcMin/+ males had a significant reduction in polyp number and burden compared to untreated mice (2.8- and 33.4-fold, respectively) or mice treated with a control inhibitor (2.7- and 28.1-fold, respectively) (Figure 4.5). No significant differences were observed in final body weight, BMI, EFPM, or fasting glucose between
B6 and ApcMin/+ treated with PMX53 or the control inhibitor (Table 4.5, Table 4.1).
Activation of the complement C3 and C5a can lead to the activation of the protein kinase AKT, a protein involved in many cellular growth and development pathways including cell survival and cell cycle progression (Grehan et al. 2005). AKT can also regulate cell survival by the inactivation of pro-apoptotic factors or activation of the IκB kinase (IKK), a key component of the nuclear factor κB (NFκB) pathway. Inactivation of
NFκB has been shown to reduce proliferation of some cancer cells and is a key regulator in the inflammatory response. Activated NFκB, measured by phosphorylation of Serine
536, was decreased in both the wild-type and polyp tissue of mice treated with PMX53 compared to those treated with the control inhibitor (Figure 4.6). Activated NFκB was substantially reduced in polyp tissue from mice treated with the C5aR inhibitor. Further, two upstream regulators of NFκB, AKT and IKK, show significant activation reduction in mice treated with the C5aR inhibitor with an even larger decrease observed in the polyp tissue (Figure 4.6). Together, these results demonstrate a role for complement- mediation regulation of NFκB signaling in intestinal polyp development that can be reduced with the pharmacological inhibition of C5aR. A reduction in IL-1β and TNFα expression was observed in polyps of mice treated with PMX53, indicating a reduction in the intestinal inflammatory response (Figure 4.6). Further, pharmacological targeting of
C5aR resulted in decreased mRNA expression levels of the pro-inflammatory cytokine
202
Drug Fasting Insulin Fasting Glucose Total Polyp Strain N FBW (g) ± SEM EFPM (g) ± SEM BMI ± SEM Treatment (µg/L) ± SEM (mg/dL) ± SEM Number
B6.Apc+/+ 5 N/A 22.48 ± 0.25 0.30 ± 0.02 0.23 ± 0.003 0.36 ± 0.01 209.6 ± 5.1 0.0 ± 0.0 B6.ApcMin/+ 7 N/A 21.68 ± 0.40 0.27 ± 0.03 0.23 ± 0.006 0.53 ± 0.09 225.0 ± 10.2 11.7 ± 1.4 B6.Apc+/+ 7 N/A 25.27 ± 0.75 0.54 ± 0.06 0.24 ± 0.005 0.71 ± 0.23 185.8 ± 4.0 0.0 ± 0.0 B6.ApcMin/+ 10 N/A 22.63 ± 0.35 0.39 ± 0.05 0.24 ± 0.005 0.91 ± 0.13 229 ± 13.7 81.6 ± 8.3*** B6.C5aR+/-;Apc+/+ 6 N/A 26.95 ± 1.49 0.23 ± 0.01 0.25 ± 0.005 120.0 ± 4.3 0.0 ± 0.0 B6.C5aR-/-;Apc+/+ 4 N/A 29.93 ± 2.03 0.28 ± 0.03 0.27 ± 0.01 128.5 ± 7.4 0.0 ± 0.0 B6.C5aR+/-;ApcMin/+ 5 N/A 25.54 ± 0.35 0.27 ± 0.009 0.25 ± 0.006 155.8 ± 11.4 15.3 ± 2.4 B6.C5aR-/-;ApcMin/+ 7 N/A 25.43 ± 0.47 0.26 ± 0.02 0.25 ± 0.006 173.8 ± 13.1 22.6 ± 1.2 B6.C5aR+/-;Apc+/+ 8 N/A 29.23 ± 1.38** 0.91 ± 0.28** 0.27 ± 0.01** 136.0 ± 9.9 0.0 ± 0.0 B6.C5aR-/-;Apc+/+ 9 N/A 27.00 ± 0.89** 0.54 ±0.07** 0.26 ± 0.005 117.3 ± 7.6 0.0 ± 0.0 B6.C5aR+/-;ApcMin/+ 4 N/A 27.32 ± 1.23** 0.73 ± 0.20** 0.26 ± 0.003 163.0 ± 7.4 33.3 ± 3.0### B6.C5aR-/-;ApcMin/+ 8 N/A 27.44 ± 0.76** 0.53 ± 0.02** 0.26 ± 0.004 158.7 ± 15.4 22.4 ± 1.5### B6.Apc+/+ 13 Control 24.42 ± 0.57 0.55 ± 0.04 0.25 ± 0.004 133.3 ± 7.5 0.0 ± 0.0 B6.ApcMin/+ 13 Control 23.14 ± 0.56 0.50 ± 0.02 0.25 ± 0.006 179.8 ± 8.6 77.5 ± 5.3 B6.Apc+/+ 12 PMX53 24.00 ± 0.70 0.54 ± 0.05 0.26 ± 0.004 131.4 ± 8.01 0.0 ± 0.0 B6.ApcMin/+ 18 PMX53 23.59 ± 0.60 0.41 ± 0.02 0.25 ± 0.005 152.2 ± 9.3 29.8 ± 1.9#### Table 4.2 – Body weight and metabolic parameters for complement studies. Final body weight (FBW) and epididymal fat pad mass (EFPM), body mass index (BMI), fasting insulin, fasting glucose, and polyp numbers from B6 and ApcMin/+, and mice deficient in C5a fed diets constructed from coconut oil. **p<0.01, ***p<0.001 (For statistical comparisons, each strain fed the HFCoco diet was compared to the same strain fed the LFCoco diet).
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Figure 4.6 – Complement C5a mediates diet-induced inflammation and intestinal neoplasia. Levels of phosphorylated AKT (pS473), IKK (pS176) and NFκB (pS536) were determined by Western blotting in the polyp tissue of ApcMin/+ mice or normal intestinal tissue of B6 mice treated with PMX53 or the control peptide. Total levels of AKT and NFκB were determined as a control for the protein amount loaded. Results are representative of 3 independent experiments. mRNA expression levels of the pro- inflammatory cytokine IL-1β and the proto-oncogene c-myc were determined by quantitative RT-PCR in the polyp tissue of ApcMin/+ or normal intestinal tissue of B6 mice treated with PMX53 or the control peptide. The percentage of viable CD11b+/GR-1+ neutrophils was determined by flow cytometry in the intestinal lamina propria of B6 and ApcMin/+ after drug treatment. C5a in turn induces the migration of inflammatory neutrophils to the intestinal lamina propria and activate the AKT/IKK/NFκB signaling pathway in intestinal cells. 204
IL-1β and the proto-oncogene c-Myc (Figure 4.6) in polyp tissue and prevented migration of inflammatory neutrophils to the intestinal lamina propria (Figure 4.6), which has previously been implicated as a key inflammatory trigger in response to DIO.
To test if PMX53 could be used as a cancer treatment after the development of intestinal polyps, ApcMin/+ were treated with the complement inhibitor after 30-days exposure to the HF. Mice were treated with 2mg/kg PMX53 while maintained on the
HFCoco diet for 30 days (60 days total on the diet study). It has been discussed above that polyp formation maximizes after 30 days exposure to a HF diet and is similar to the polyp numbers observed after 60 days. If polyp number or size was significantly reduced after
PMX53 treatment would suggest that inhibition of complement decreases proliferation or increases apoptosis of tumorigenic cells in the intestine. Although final body weight,
BMI and EFPM were significantly increased in ApcMin/+ treated with PMX53 (data not shown), no changes in polyp number or burden were observed between untreated
ApcMin/+ or those treated with PMX53 (data not shown). This suggests that complement inhibition has no effect on proliferation or apoptosis at a later stage of polyp development, but could play a role in early polyp development. It should be noted that treatment with PMX53 reduced weight loss usually associated with ApcMin/+ after exposure to the HFCoco, suggesting that complement inhibition could be used as a method to reduce cancer-related co-morbities.
4.4 Discussion
It was shown that complement component C5a is elevated in ApcMin/+ after exposure to a HF diet, suggesting an interaction between the inflammation mediated by
205 complement signaling and dietary fat, specifically saturated fatty acids. Deletion of both copies of C3 or C5aR decreased polyp number and size compared to mice with partial or
WT alleles for these complement factors. Pharmacological inhibition of C5aR also reduced polyp number and size after 30 days of treatment. These results indicate that the complement cascade, specifically C5a, is modulating polyp initiation and progression in
ApcMin/+. These studies also demonstrate a potential use for treating early stages of colon cancer in humans. Inflammatory bowel diseases often precede some types of colon cancer in humans, so targeting intestinal inflammation would be an ideal way to prevent the formation of these types of intestinal cancers. The use of PMX53 could be used to treat patients that have already had colon polyps removed to prevent the formation of new polyps.
Min (Multiple intestinal neoplasia) mice carry a dominant mutation in the adenomatous polyposis coli (APC) gene and develop multiple adenomas throughout their intestinal tract. A modifier of Min (Mom) is classified as a gene that increases or decreases phenotypes associated with the ApcMin/+ mutation (Bilger et al. 1996).
Numerous Moms have been identified that increase or decrease intestinal or colon polyps or modulate mammary tumorigenesis associated with ApcMin/+ females (Wang et al. 2007;
McCart et al. 2008). For example, Mom1, now identified as phospholipase A2 group IIA
(Pla2g2a), is a semi-dominant modifier of polyp size and multiplicity, resulting in a 50% reduction in polyp number (Dietrich et al. 1993; MacPhee et al. 1995).
Here, we have identified a novel type of Mom that is influenced by high dietary saturated fat. C5a reduces the development polyp number and mass in the ApcMin/+ mouse model. Identifying and understanding the function of modifiers is important in
206 clinical terms, because each could be used for pharmacological or therapeutic treatments as shown here with the PMX53 experiments or these studies provide evidence for the basic functions of factors involved in pathways associated with tumorigenesis. For example, these studies have also demonstrated the importance of inflammation in diet- induced polyp development.
207
CHAPTER 5
SUMMARY OF CONCLUSIONS AND FUTURE DIRECTIONS
208
5.1 Summary of conclusions and evidence
Because of the close association between diet and the development of DIO and
MetS in humans, it is difficult to separate the independent contributions that each has on intestinal cancer. In order to determine how dietary fat influences the development of tumorigenesis a mouse model system was generated that is resistant to DIO and MetS, but susceptible to intestinal neoplasia. Combining CSSs with ApcMin/+, we were able to investigate how high dietary fat mediates polyp development.
It was defined that CSSs can be used to separate the effect of diet from diet- induced obesity and metabolic syndrome on intestinal neoplasia and potentially other diseases. Specific CSS strains, A7.ApcMin/+ and A17.ApcMin/+, when combined with the
Min/+ Apc model, develop significantly more polyps when fed the HFCoco diet compared to the same strain fed the LFCoco diet. These same strains as well as the other obesity- resistance CSSs could be combined with other disease-causing mutations and used to test the effect of diet on other diseases.
Diet, separate from obesity, is crucial for polyp development. It is demonstrated using obesity-resistant CSS.ApcMin/+ strains, A7.ApcMin/+ and A17.ApcMin/+, that a diet high in saturated fat increases polyp number and total polyp mass even though these strains do not develop obesity. Final body weight, epididymal fat pad mass and body mass index were all similar between A7.ApcMin/+ and A17.ApcMin/+ regardless of the
LFCoco or HFCoco diet consumed, showing that these strains do not become obese after 60 days on a HF diet, an increase in polyp number was still observed. Because these strains
209 remain lean and do not develop characteristics associated with Mets after consumption of a high fat diet, this increase in polyp number can be attributed to high dietary fat.
Diet, separate from diet-induced insulin resistance, is crucial for intestinal polyp development. It is demonstrated using wild-type A7 and A17 strains, which are resistant to developing characteristics of metabolic syndrome, are still susceptible to diet-induced polyp progression. No significant difference in fasting insulin, fasting glucose or HOMA-
IR was observed between mice fed the HFCoco or the LFCoco of wild-type A7 or A17 strains, showing they were not insulin resistant. Polyp numbers were still significantly elevated in these two strains when fed the HFCoco diet, thus demonstrating that polyp development occurred independent of deregulation of insulin signaling.
There is strong evidence that A/J chromosome 2 contains a modifier that significantly decreases polyp number and mass. Evidence is demonstrated that there is a high fat diet dependent modifier of polyp number and mass on A/J chromosome 2 and that this modifier also effects neutrophil recruitment. Although A2.ApcMin/+ mice fed the
HFCoco had a significant increase in polyp burden compared to those fed the LF control diet, this number was significantly less than that observed in ApcMin/+ fed the same diet.
Circulating neutrophils were also significantly lower in the A2 strains compared to those seen in the ApcMin/+ fed the same diet. Together these results show that a modifier exists on A/J chromosome 2 that modulates polyp burden and neutrophil activation or recruitment.
Specific dietary fats can have different effects on diet-induced obesity and associated insulin-resistance and glucose signaling. It is demonstrated that the diets
210 constructed from coconut (hydrogenated), corn or olive oil have different effects on diet- induced obesity as well as insulin-resistance and glucose signaling. After 60 days on the diet study, wild-type B6 mice fed the HFCoco are obese as measured by FBW, EFPM and
BMI as well as insulin resistant. Mice fed the HFCorn diet do not develop diet-induced obesity but metabolic parameters are elevated. Mice fed the HFOlive diet develop diet- induced obesity but metabolic parameters do not change between those fed the HFOlive or
LFOlive diets. These results show that different dietary fats, though similar in calorie content, can have differential effects on diet-induced obesity and metabolic characteristics, demonstrating that the type of fat can strongly influence disease.
Specific dietary fat sources, such as coconut, corn or olive oil, can have different effects on intestinal neoplasia. In addition to changes in obesity status and metabolic parameters, specific kinds of fat also show differences in carcinogenic properties. Diets high in coconut (hydrogenated) or corn oil significantly increase total polyp number and mass in the small intestine and colon of ApcMin/+ mice. Conversely diets high in olive oil fail to increase polyp numbers or mass in the small intestine or colon as seen with the
HFCoco or HFCorn diets. These results demonstrate that not all fats are equal and the type of fat can have potent effects, detrimental or beneficial, on disease.
Inflammatory pathways are induced during intestinal polyp progression before the onset of obesity. It was shown that diets constructed from coconut or corn oils significantly increased inflammatory factors such as IL-6, IL-1β and TNFα in intestinal tissue before the onset of obesity. Factors associated with prostaglandin synthesis were also elevated in mice fed the HFCoco or HFCorn diets compared to those fed the corresponding LF diet. Systemic inflammation is also increased, as IL-6, IL-1β, and
211 leptin are elevated in mice fed the HFCoco or HFCorn diet. This demonstrates that inflammation occurs before obesity and insulin resistance and is influenced by dietary fatty acids.
Consumption of high dietary fat can activate the complement component cascade.
Activated levels of complement component C5a is significantly increased in strains fed a high fat diet. After 30 and 60 days on the HFCoco diet, systemic levels of complement component C5a were significantly elevated in both B6 and ApcMin/+ as measured by
ELISA. Similar results were observed in mice fed the HFCorn at 30 and 60 days. These results demonstrate that diets high in coconut and corn oil can elicit an immune response and can activate the complement component cascade.
In search of a link between diet and inflammation, we reassessed our findings in which A2.ApcMin/+ mice showed decreased tumorigenesis regardless of their dietary exposure and obesity or metabolic status. Notably, chromosome 2, present in the A/J strain as well as in CSS A2.ApcMin/+, contains a dysfunctional C5 gene. C5, a protein belonging to the complement system, is cleaved in response to complement activation, with the subsequent generation of the fragment C5a, a well-known pro-inflammatory mediator with a detrimental role in cancer. To determine whether diet modulates the levels of complement activation, we measured circulating levels of C5a in plasma of B6
Min/+ and Apc mice fed HFCoco or LFCoco. After 30 days of treatment, plasma levels of C5a
Min/+ were significantly elevated in both B6 and Apc strains fed HFCoco LF-fed animals.
The link between complement activation and intestinal tumorigenesis was confirmed in complement knockout strains backcrossed onto an ApcMin/+ background.
Absence of C3, an essential protein for complement activation, or of C5aR resulted in
212 decreased polyp number and burden in the small intestine of HF-fed mice in a dose- dependent fashion, supporting a role for the C5a-C5aR axis in diet-induced intestinal neoplasia. In addition, pharmacological targeting of C5aR with the antagonist peptide
PMX53, but not an inactive control peptide, resulted in a significant decrease in the polyp number and burden promoted by the exposure to high dietary saturated fat.
Mechanistically, abrogating C5aR signaling with PMX53 inhibited the AKT-
NFκB signaling pathway, which has previously been implicated in the promotion of inflammation and cancer. Whereas increased levels of phosphorylated AKT, IKK, and
Min/+ NFκB were observed in the polyp tissue from Apc mice fed HFCoco when compared to normal B6 tissue, this activation was attenuated in males treated with PMX53 but not the control peptide. Further, pharmacological targeting of C5aR resulted in decreased mRNA expression levels of the pro-inflammatory cytokine IL-1β and the proto-oncogene c-Myc in polyp tissue and prevented migration of inflammatory neutrophils to the intestinal lamina propria, which has previously been implicated as a key inflammatory trigger in response to DIO.
Collectively, our findings demonstrate that high dietary fat can activate complement, with further generation of C5a. C5a, in turn, promotes a pro-inflammatory environment by triggering signaling pathways that control the expression of proto- oncogenes and the release of inflammatory mediators, and consequently favor the formation of intestinal polyps in genetically susceptible mice.
Importantly, we provide three different examples that indicate dissociation between DIO and tumor development. They are: increased intestinal tumorigenesis in both DIO-susceptible and -resistant CSS animals, increased polyp numbers in lean
213 animals after only 3 days of HFD treatment, and lack of tumor progression in obese
HFOlive-fed males. As such, our data add to the current understanding by showing that
HF-induced complement activation and C5a generation promote inflammation and intestinal tumorigenesis prior to the onset of obesity or MetS. Given that HF-induced complement activation is an upstream event and is crucial for the further establishment of inflammation, and given the beneficial effects of anti-inflammatory therapies in cancer, our data point to complement-targeted therapeutics as a powerful means of preventing diet-induced neoplasia.
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5.2 Modulation of microbial profiles by dietary fat
5.2.1 Introduction
The human GI tract contains more than 1010 microorganisms that belong to more
500 species (Turnbaugh et al. 2006; Bäckhed et al. 2007). The symbiotic relationship between humans and enteric microorganisms is essential for important processes such as digestion and a proper immune system (Zoetendal et al. 2008). Although much is known about host biology and genetics in metabolism and cancer, less is known about the involvement of gut microbes in health and disease. The colonic ecosystem differs from that in the proximal gut in several important respects. The colonic microbiota represents the largest population of microbes colonizing humans from birth. Constraints on bacterial numbers, composition, and interaction with the host involve not only the innate and acquired immune system, but also the colonic mucin structure. While the microbiota provides beneficial protective, trophic, nutritional, and metabolic signals for the host, it may become a risk factor for disease depending on context and host susceptibility
(Ivanov et al. 2008; Mazmanian et al. 2008; Zoetendal et al. 2008).
The collection of intestinal bacteria, gut microbial profile, is essential for processing dietary polysaccharides (Bäckhed et al. 2004). The microbiota can be viewed as a metabolic “organ” exquisitely tuned to our physiology that performs functions that we have not had to evolve on our own.
The dominant phyla, Bacteroidetes and Firmicutes, are found in both humans and mice. It has been demonstrated that microbial profiles can strongly influence the development of obesity. For example, studies of lean and obese mice suggest that the gut microbiota affects energy balance by influencing the efficiency of calorie harvest from
215 the diet, and how this harvested energy is used and stored (Turnbaugh et al. 2006).
Human studies of lean or obese monozygotic or dizygotic twins showed that microbial profiles are shared among families on a general level (i.e. phyla), but each individual has a unique profile when examined in more detail (i.e. species) (Turnbaugh et al. 2009).
Certain metabolic byproducts that are generated from gut bacteria can have beneficial or detrimental effects on host diseases. For example, butyrate is a fermentation product of anaerobic bacteria (Clostridium strains) and has been shown to increase apoptosis, decrease proliferation, and have anti-inflammatory properties in mammalian intestinal epithelial cells (Hamer et al. 2008). Patients suffering from inflammatory bowel disease (IBD) such as ulcerative colitis or Crohn’s disease have deficiencies in many strains of butyrate-producing Clostridium, such as Faecalibacterium prausnitzii and have impaired butyrate metabolism in the colonic mucosa (Sokol et al. 2008;
Thibault et al. 2010). Oral and intraperitoneal administration of F. prausnitzii in a mouse
IBD model reduced colitis and mortality, respectively and increasing anti-inflammatory cytokines such as IL-10 (Sokol et al. 2008). This is one example of how specific bacterial strains can be used as potential therapeutics in intestinal diseases.
The intestinal flora can be manipulated by a variety of metabolic factors, changes in energy balance, or through the consumption of specific nutritional regimes. It has been demonstrated that Bacteroidetes, a specific phyla of bacteria, is found in lower numbers in obese individuals, and the percentage of another phyla, Firmicutes, is significantly elevated with increased body fatness (Ley et al. 2006). It is unclear if these specific strains modulate obesity (i.e. increase food digestion or absorption) or if obese conditions select these distinct families of microbes.
216
Intestinal bacteria contribute to obesity and cancer susceptibilities in both species, and obesity, diet and colon cancer can have an effect on the microbial profiles (Bäckhed et al. 2007). For example, Helicobacter hepaticus infection in mice can lead to the development of colitis and colon cancer (Mangerich et al. 2012). However, the relationships between host genetics, diet, obesity, susceptibility to colon cancer, and the relative numbers and kinds of intestinal bacteria have not been carefully studied.
Here, we demonstrated that different dietary sources can be either beneficial or detrimental in the development of intestinal tumorigenesis. Given that dietary factors and obesity status can modulate the intestinal flora suggests that diets high in coconut, corn or olive oil can change the bacterial profile.
5.2.2 Questions and Proposed Experiments
5.2.2.1 Do microbial profiles differ in mice fed diets composed of specific fats?
To understand the role of specific dietary fats on microbial profiles, mice will be fed diets high or low in hydrogenated coconut, corn or olive oil. To control for genetic background and sex specific effects, C57BL/6J (B6) males will be used for the proposed study. Cecum samples will be collected and sequencing of 16S rRNA will be conducted to determine microbial profiles for each dietary group. The 16S rRNA gene is a ribosomal component that is conserved in all bacteria, and it contains variable sequences that confer species specificity and is a common method used to distinguish bacteria genus and species (Wilson et al. 1990). Body weight, body mass index, total fat pad mass, fasting insulin, fasting glucose as well as a panel of both pro- and anti-inflammatory
217 cytokines will be collected from each dietary group. As described above, specific dietary fats have different effects on obesity and metabolic syndrome in B6 male mice.
It could be possible that each dietary fat source generates a specific bacteria profile in the intestine. If distinct microbial profiles are observed between the different dietary groups, drugs such as antibiotics, foster parenting, diet, and microbial inoculation may be used to modulate obesity and associated metabolic factors. For example, HFOlive does not induce increases in fasting insulin or glucose, therefore it may be possible to inoculate mice fed the HFCoco or HFCorn diets with intestinal bacteria from mice fed the
HFOlive diet to decrease factors involved in insulin signaling. If HFCoco or HFCorn fed mice inoculated with the flora of the mice fed the HFOlive show reductions in fasting insulin or fasting glucose, it would suggest that insulin signaling could be modulated through the diet by changing intestinal bacteria profiles.
5.2.2.2 Do microbial profiles associate with cancer severity in ApcMin/+ mice?
To examine if dietary fat can modulate microbial profiles and associate with intestinal cancer severity (polyp number, polyp size, and total polyp mass), B6 and
ApcMin/+ males will be fed diets low or high in hydrogenated coconut, corn, or olive oil.
As described above, it is known that specific dietary fats can have differential effects on cancer severity. To determine the general microbial profile found in each group, cecum samples will be collected from both ApcMin/+ and B6 from the studies described above fed the coconut, corn and olive oil diets. Targeting 16S rRNA, microbe arrays and quantitative RT-PCR will be used to evaluate the differences in dominant phyla and species between all the groups on different diets.
218
If significant differences are found, drugs such as antibiotics targeted at specific bacterial strains, foster parenting, diet and microbial inoculation may be used to manipulate the microbial profiles in colon cancer susceptible strains, thereby testing whether cancer severity is affected by these perturbations. In the future, it could be possible to develop antibodies against specific bacterial strains that are associated with disease progression or severity. Since human and mouse phyla are closely related, the identification of certain prevalent bacteria and their involvement in the development of colon cancer may give rise to a novel treatment that is non-invasive and inexpensive.
5.2.2.3 Can different dietary sources be used to change intestinal microbial profiles?
Microbial profiles change in response to a high fat diet, therefore, demonstrating that dietary intervention can be used to change the normal intestinal flora in humans (Ley et al. 2006). If specific groups of bacterial species are identified from the previous studies, it may be possible to control or modulate detrimental strains through changes in diet. Mice and humans have genetically similar strains of intestinal strains of bacteria, making mouse models a useful system to closely study and control the effect of different nutritional supplements on disease outcome.
219
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