Download Identification of genes involved in intestinal

Identification of genes involved in intestinal tumorigenesis
induced by low dietary folate in BALB/c and C57B1/6 mouse
strains.
By
YuanHang Cao
A thesis submitted to McGill University in fulfillment of the requirements of the degree
of Master of Science
February 2012
Department of Human Genetics
McGill University
Montreal, Quebec, Canada
ii
This thesis is dedicated to my family and my friend, for your unconditional love and
support. Thank you for helping me and believing in me through the last two and half
years.
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ACKNOWLEDGMENTS
Many people have contributed to my research project in the last two year at Montreal
Children Hospital Research Institute. I like to express my most sincere gratitude to those
people for your supports and encouragements that made this thesis possible.
I would like to thank my supervisor, Dr. Rima Rozen, for given me the opportunity to
work on this project. It is difficult to overstate my gratitude for her guidance,
encouragement and endless patience that made this project successful. It has truly been an
honor to work under your supervision.
To my supervisory committee members, Dr. Nada Jabado and Dr. Kenneth Hastings,
for your encouragement and insightful suggestions that made my project become better.
I am deeply indebted to Dr. Daniel Leclerc, whose insightful suggestions, expertise and
encouragement helped me through my entire research project.
To the former and current members of my lab, I want to thank them for their support and
patience throughout my training: Katherine Brown, Dr. Basak Celtikci, Dr. Karen
Christensen, Dr. David Garcia-Crespo, Dr. Liyuan Deng, Nafisa Jadavji, Dr. Erin
Knock, Dr. Andrea Lawrance, Aileen Lebosky, Dr. Leonie Mikael, Laura Pickell, Jill
Pancer, Carolyn Perugino, Danielle Meadows, Dr. Xiao-Ling Wang, and Dr. Qing
Wu.
To my colleague at Montreal Children Hospital Research Institute, Noha Gerges, for
your expertise on IPA analysis.
To Dr. Leonie Mikael, Nafisa Jadavji and Danielle Meadows, for proofreading.
To the students, staff and professor at MCHRI, I like to thank all of you for your help and
friendship.
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ABSTRACT
Folates are essential vitamins involved in nucleotide synthesis and DNA methylation.
Methylenetetrahydrofolate reductase (MTHFR) synthesizes the folate derivative utilized
in methylation reactions. Inadequate dietary folate intake and MTHFR deficiency may
increase the risk of developing colorectal cancer. Previous studies in our laboratory
showed that a low folate diet induces intestinal tumors in BALB/c but not in C57Bl/6
mice. In addition, mild MTHFR deficiency (Mthfr+/-) may increase tumor formation in
BALB/c mice fed low folate. To identify genetic differences responsible for tumor
susceptibility, we performed microarray analysis to compare gene expression in
preneoplastic intestine between BALB/c and C57Bl/6 mice fed low folate. We also
compared preneoplastic intestine expression of Mthfr+/- BALB/c mice fed low folate to
Mthfr+/+ BALB/c mice fed control diet. With quantitative real-time-PCR, we confirmed
significant changes in the retinoid/ PPARα pathway (Bcmo1, Aldh1a1, Ppara, Acot1,
Cd36, Cyp4a10, Aqp3, Hmgcs2 and Me1) and variation in expression of genes involved
in apoptosis, cell proliferation or immune response (Tgfbi, Arntl, Bmp5, Sprr2a, Atf3,
Plscr2, Ppme1 and Trem4). Gene-specific methylation changes consistent with mRNA
changes were observed for Bcmo1, Ppara and Bmp5. These results suggest that fatty acid
metabolism, PPARa/RXR activation and decreased expression of tumor suppressor genes
may be implicated in the transition from preneoplastic tissue to adenoma. DNA
methylation status may play an important role in the expression of some of these genes.
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RÉSUMÉ
L’acide folique est une vitamine essentielle pour la synthèse des nucléotides et les
réactions de méthylation. La methylènetétrahydrofolate réductase (MTHFR) permet de
synthétiser les molécules requises pour la méthylation de l’ADN. Un déficit en folates ou
en MTHFR peut augmenter le risque de développer un cancer colorectal. Des études
précédentes dans notre laboratoire ont montré qu'un régime alimentaire pauvre en folates
induit des tumeurs dans les souris BALB/c, mais pas dans la lignée C57BL/6. En plus,
une légère déficience en MTHFR (Mthfr+/-) peut augmenter le risque de développer des
tumeurs dans les souris BALB/c soumises à un régime alimentaire pauvre en folates.
Pour identifier les différences génétiques responsables de la sensibilité tumorale, on a fait
une comparaison de l’expression des gènes dans l’intestin des souris BALB/c et C57Bl/6
soumises à un régime alimentaire pauvre en folates, en utilisant des puces à ADN. On a
aussi comparé l’expression des gènes dans les intestins prénéoplasiques entre des souris
BALB/c Mthfr+/- déficient en folate et des souris BALB/c Mthfr+/+ qui ont un apport
suffisant en folates. En utilisant la PCR quantitative en temps réel, nous avons confirmé
des changements significatifs dans la voie des rétinoïdes/PPARA (Bcmo1, Aldh1a1,
Ppara, Acot1, Cd36, Cyp4a10, Aqp3, Hmgcs2 et Me1) et des variations de l’expression
des gènes participant à l’apoptose, la prolifération cellulaire et la réponse immunitaire
(Tgfbi, Arntl, Bmp5, Sprr2a, Atf3, Plscr2, Ppme1 et Trem4). Nous avons observé des
changements de méthylation cohérents avec les changements de l’ARNm pour Bcmo1,
Ppara et Bmp5. Ces observations suggèrent que métabolisme des acides gras, l’activation
de PPARA/RXR et la diminution de l’expression de gènes suppresseurs de tumeurs
peuvent être impliqués dans la transition entre le tissu prénéoplasiques et les adénomes.
vi
TABLE OF CONTENTS
Dedication……………………………………………………………………….....ii
Acknowledgments……………………………………………………………….....iii
Abstract………………………………………………………………………….....iv
Resume…………………………………………………………………….…….....v
Table of Contents…………………………………………………………..…….....vi
List of Figures……………………………………………………………..……......viii
List of Tables……………………………………………………………………......viii
Thesis Format……………………………………………………………………….ix
Contribution of Authors…………………………………………………………….ix
Abbreviations……………………………………………………………………….x
Conventions…………………………………………...……………………………xii
CHAPTERI: Literature Review ……………………………………………….....1
1.1
FOLATE METABOLISM AND MTHFR.......................................................2
1.1.1 Folate Metabolism...........................................................................................2
1.1.2 Impact of folate deficiency and cancer risk ....................................................3
1.1.3 Impact of MTHFR deficiency and cancer risk................................................7
1.1.4 Mouse model of MTHFR deficiency ..............................................................12
1.2
COLORECTAL CANCER .............................................................................13
1.2.1 Genetic defect .................................................................................................13
1.2.2 Environmental factors .....................................................................................16
1.3
THESIS RATIONAL.......................................................................................18
CHAPTER II: Strain differences in the retinoid/PPARα pathway and tumor
suppressor gene may influence intestinal tumor incidence....................................19
2.1
2.2
2.3
2.4
2.5
2.6
ABSTRACT...........................................................................................................20
INTRODUCTION.................................................................................................21
MATERIALS AND METHODS...........................................................................23
RESULTS..............................................................................................................30
DISCUSSION.......................................................................................................50
ACKNOWLEDGMENTS.....................................................................................55
CONNECTING TEXT-Chapter II-III.......................................................................56
CHAPTER III: Folate and MTHFR deficiency influences on aberrant gene
expression and methylation patterns during intestinal tumorigenesis in BALB/c
mice.............................................................................................................................57
3.1
3.2
3.3
3.4
ABSTRACT..........................................................................................................58
INTRODUCTION.................................................................................................59
MATERIALS AND METHODS...........................................................................61
RESULTS..............................................................................................................65
vii
3.5 DISCUSSION......................................................................................................78
3.6 ACKNOWLEDGMENTS....................................................................................81
CHAPTER IV: General Discussion & Conclusions...............................................82
4.1 The effects of mouse strain, low dietary folate, MTHFR deficiency on intestinal
adenomas incidence and tumor progression.......................................................83
4.2 Retinoid pathway................................................................................................83
4.3 PPARα related inflammatory response and oxidative stress..............................84
4.4 Cell growth and apoptosis..................................................................................86
4.5 Future Direction.................................................................................................88
4.6 Conclusions........................................................................................................89
REFERENCES.........................................................................................................90
APPENDIX: Compliance Forms, Certificates, Permission Letter......................101
viii
LIST OF FIGURES
Figure 1.1 Folate metabolic pathways...........................................................................10
Figure 2.1 Confirmation of the quality of RNA used in microarray experiment...........24
Figure 2.2 Identification of individual genes and functional gene categories with
significant changes in expression between C57BL/6 and BALB/c mouse strains.........32
Figure 2.3 Confirmation of BCDO1 protein level ........................................................45
Figure 2.4 Confirmation of Aldh1a1 expression level...................................................46
Figure 2.5 Confirmation of methylation changes between BALB/c and
C57Bl/6 mice under low folate diet................................................................................48
Figure 3.1 Confirmation of the quality of RNA used in microarray experiment...........62
Figure 3.2 Identificantion of individual genes and functional gene categories
with significant expression changes between BALB/c, Mthfr+/-, FD and
BALB/c, Mthfr+/+, CD mice.........................................................................................66
Figure 3.3 Confirmation of genes expression with qRT-PCR.......................................75
Figure 3.4 Bcmo1 methylation levels in normal intestine for Mthfr+/+ or
Mthfr+/- BALB/c mice, fed FD or CD............................................................................77
LIST OF TABLES
Table 2.1 Primer sequences and amplicon parameters..................................................27
Table 2.2 Determination of relative mRNA levels for 14 selected genes
by quantitative RT-PCR in BALB/c and C57BL/6 mice...............................................36
Table 2.3 List of probe sets meeting significance and fold changes
between BALB/c and C57Bl/6 mouse strain.................................................................37
Table 3.1 Primer sequences and amplicon parameters..................................................64
Table 3.2 List of probe sets meeting significance and fold changes in
BALB/c strain between MTHFR +/- FD and MTHFR +/+ CD mice............................68
ix
THESIS FORMAT
This thesis contains 4 chapters. Chapter I is a review of previous literatures related to
this research project. Chapter II and Chapter III present research data in the form of
scientific publication with connecting text in between. Chapter IV provides a general
summary and discussion of this thesis.
CONTRIBUTIONS OF THE AUTHORS
For chapter II and III, the candidate conducted the experiments, interpreted the result
and completed the manuscript in collaboration with Dr. Daniel Leclerc and his supervisor.
In chapter II, the candidate carried out DNA and RNA extraction for microarray and
methylation study, microarray analysis, IPA functional analysis, real-time RT-PCR
confirmation and western blot assay. Dr. Qing Wu performed genotyping and tissue
collection. Dr. Daniel Leclerc conducted pyrosequencing experiment, designed primers
for real-time RT-PCR and pyrosequencing experiment, and assisted in microarray
analysis. Dr. Leonie Mikael assisted in statistical analysis and Western blot analysis. Dr.
LiYuan Deng assisted in real-time RT-PCT confirmation and methylation analysis. Noha
Gerges assisted in IPA functional analysis.
In chapter III, Dr. Daniel Leclerc assisted in the analyses of microarray data and
designed primers for real-time RT-PCR experiment. Noha Gerges assisted in IPA
functional analysis.
x
ABBREVIATIONS
Acot1
Acyl-CoA thioesterase 1
ALDH
Aldehyde dehydrogenase
Aldh1a1
Aldehyde dehydrogenase 1 family member A1
ANOVA
Analysis of variance
APC
Adenomatous Polyposis Coli
APT
Affymetrix Powerful Tools
Aqp3
Aquaporin 3
Arntl
Aryl hydrocarbon receptor nuclear translocator-like
ATF3
Activating transcription factor3
Bcmo1
Beta-carotene 15,15'-monooxygenase 1
Bmp5
Bone morphogenetic protein 5
CD
Control diet
CD36
Cluster of differentiation 36
CRC
Colorectal cancer
Cyp4a10
Cytochrome P450 family 4 subfamily a, polypeptide 10
DHFR
Dihydrofolate reductase;
DSB
Double-strand DNA breakage
dTMP
Deoxythymidine monophosphate;
dUMP
Deoxyuridine monophosphate;
FAD
Flavine adenine dinucleotide
FAP
Familial adenomatous polyposis
FD
Low folate diet
Gapdh
Glyceraldehyde 3-phosphate dehydrogenase
Hcy
Homocysteine
Hmgcs2
3-hydroxy-3-methylglutaryl-Coenzyme A synthase 2
HNPCC
Hereditary nonpolyposis CRC
IPA
Ingenuity Pathways Analysis
LOH
Loss of heterozygosity (LOH)
Me1
Malic enzyme 1
MethyleneTHF 5, 10-methylenetetrahydrofolate
MSI
Microsatellite instability
MTHFR
Methylenetetrahydrofolate reductase
MTR
Methionine synthase
Pla2g2a
Phospholipase A2, group IIA
Pparα
Peroxisome proliferator-activated receptor alpha
PPME1
Protein phosphatase methylesterase 1
PPRE
Peroxisome proliferator response element
RAR
Retinoic acid receptor
ROS
Reactive oxygen species
qRT-PCR
Quantitative real-time RT-PCR
RXR
Retinoid X receptor
xi
SAH
SAM
SHMT
Sprr2a
Tgfbi
THF
TS
5-methylTHF
S-adenosylhomocysteine
S-adenosylmethionine
Serine hydroxymethyltransferase
Small proline-rich protein 2A
Transforming growth factor beta-induced
Tetrahydrofolate
Thymidylate synthase.
5-methyltetrahydrofolate
xii
CONVENTIONS
In this thesis, the name of human genes are uppercase and italicised (i.e., BCMO1)
and the name of mouse genes are titlecase and italicised (i.e., Bcmo1). The name of
protein are not italicised and both human and mouse protein name are uppercase (i.e.,
BCMO1).
CHAPTER I
Literature Review
1
1.1 FOLATE METABOLISM AND MTHFR
1.1.1 Folate Metabolism
Folate derivatives are necessary for several essential metabolic processes, including
nucleotide synthesis and methylation reactions. Insufficient dietary folate intake results in
folate deficiency and can lead to several health problems, including abnormal fetal
developmental and neurological abnormalities, as well as increased risk for cancer
development (1). Dietary folate is not biologically active until it is processed by
dihydrofolate reductase (DHFR) into tetrahydrofolate (THF) and used for the production of
nucleotides and methionine (Figure 1.1). THF can be converted into 10-formylTHF, an
important substrate required for purine synthesis. Both THF and 10-formylTHF can be
converted into 5, 10-methylenetetrahydrofolate (methyleneTHF), a substrate involved in
thymidine biosynthesis. Methylenetetrahydrofolate reductase (MTHFR), one of the most
studied enzymes in folate metabolism, converts 5,10-methylenetetrahydrofolate, a carbon
donor for nucleotide synthesis, to 5-methyltetrahydrofolate (5-methylTHF), the main
circulating form of folate (2). 5-methylTHF works as a methyl donor in the conversion of
homocysteine to methionine and S-adenosylmethionine (SAM), a universal methyl donor in
mutilple reactions (3). 5-methylTHF is converted back into THF by methionine synthase
during methionine synthesis.
2
1.1.2 Impact of folate deficiency and cancer risk
Clinical
Low level of folic acid can be the result of poor nutrition, malabsorption or some other
deficiency that disrupts folate metabolism. Depletion of folate can result in morphological
abnormalities and megaloblastic changes in the marrow and blood cells as well as
abnormalities in the intestinal epithelium. As folate deficiency persists, individuals may
develop anemia as well as diarrhea (4). Individuals with milder folate deficiency may present
with hyperhomocysteinemia due to impaired conversion of homocysteine to methionine (5).
High levels of homocysteine in blood can increase the risk of atherosclerotic disease (6) and
neural tube defects (7).
Recently, there was growing evidences from epidemiological studies to suggest that folate
deficiency may play a role in the development of cancer (8). The growth of tumors requires a
large amount of energy and genetic materials for cell division. As folic acid plays a crucial
role in the biosynthesis of nucleotides and the generation of methyl groups that protect
genomic integrity, depletion of such an important vitamin lead to impaired gene silencing,
novel genetic mutations and DNA damage, all of which may contribute to cancer
development. A strong association has been found between folate deficiency and cancer in
human colorectal cancer (9). Dietary studies in humans showed that individuals with low
folate consumption were 30-40% more likely to develop colorectal cancer as compared to
individuals with high folate consumption (8, 10).
3
Genetic
5, 10-methylene THF is required for the synthesis of deoxythymidylate (dTMP) from
deoxyuridylate (dUMP) by thymidylate synthase (TS). Folate deficiency results in the
depletion of dTMP and creates an imbalance in nucleotide pools. This event has been
observed in several cell culture studies where the dUMP:dTMP ratio was significantly higher
in folate deficient cells compared to control (11,12). Depletion of dTMP and accumulation of
dUMP increases the frequency of uracil misincorporation into DNA. Such observations were
made both in vitro (13) and in vivo (14). In addition, studies of colorectal cancer in human
also showed an increased amount of uracil incorporation in the DNA sequences of epithelial
cancer cell line (14).
The relationship between uracil misincorporation and DNA damage due to folate
deficiency has been confirmed in several cell culture studies. A study in Escherichia coli
demonstrated that excision repair of uracil residues in DNA can lead to double-strand DNA
breakage (DSB) if the incorporated uracils are closely spaced and located on opposite strands
(15). Furthermore, it has been shown that the severity of chromosome breakage in cultured
folate deficient blood cell cultures was dependent upon the concentration of dUMP and
dTMP (16). Similar results were also found in BALB/c mice when they were fed with low
folate diet based on the measurement of phosphorylated form of histone H2AX, a marker for
DSB (17, 18). The ratio of dUTP:dTTP and DNA damage was higher in BALB/c mice fed
with low folate diet compared to control diet.
Chromosome breakage and DNA damage induced by folate deficiency increase the risk of
developing any type of cancer due to accumulated mutations, increased chromosome
4
instability and increased aberration frequency (19). Chromosome breakage can contribute to
the development of cancer in many ways. First, a double-strand DNA break in tumor
suppressor genes could completely repress its expression and block important mechanisms,
such as apoptosis, from occurring. This scenario is often observed in solid human tumors
(20). In addition, chromosome breakage increases the frequency of chromosome
translocation, and may lead to the activation of oncogenes responsible for cell proliferation
and tumor growth or the creation of an oncogenic hybrid protein with failures in DNA repair
(21). Cancers that are often caused by chromosome translocations include leukemia,
lymphoma and other solid malignancies (22).
Epigenetic
Since 5-methylTHF is crucial in the synthesis of methionine and S-adenosylmethionine,
as such, depletion of folic acid may potentially lead to severe disruptions in DNA
methylation patterns by slowing down the conversion of homocysteine to methionine. A
study done in humans showed that five weeks of folate depletion in postmenopausal women
significantly decreased global DNA methylation (23). Global demethylation was also
observed in human colon cell line under folate deficiency conditions. Theses observations
suggest that a relationship exists between folate supply and DNA methylation status.
Furthermore, folate deficiency in mice (18) and rats (24) also results in global
hypomethylation.
DNA methylation plays an important role in maintaining genome integrity. Global DNA
hypomethylation is frequently observed in different types of cancer at the early stage of
5
tumor development (25). Severe DNA hypomethylation can lead to chromosome loss due to
failure in chromatin condensation during mitosis (26). In addition, DNA hypomethylation
may disrupt gene imprinting. Although it is difficult to assess the impact of overall decreases
in DNA methylation, demethylation at specific loci that have oncogenic properties may affect
the risk for cancer development (25).
Depletion of folic acid may also lead to increased DNA methylation at specific loci. It has
been shown in rat livers that exons 6-7 of the p53 gene were hypomethylated after 36 weeks
of folate depletion, but were hypermethylated in tumor tissue that developed after 54 weeks
of folate depletion (13). This change in the DNA methylation pattern was explained by the
elevation of the methylation capacity of tumor tissues as compared to control and 36 week
depleted tissues. Like DNA hypomethylation, DNA hypermethylation of a specific gene may
also be considered as key event in cancer development. Hypermethylation at the promoter
region of important tumor-suprressor genes such as p53 and hMLH1 were frequently
observed in hepatic and colon cancer respectively (27, 28).
6
1.1.3 Impact of MTHFR deficiency and cancer risk
MTHFR polymorphisms and functional impact
Since the discovery of MTHFR gene, many mutations have been found to impair the
enzyme activity of MTHFR enzyme. The most common mutation observed in human is a
missense mutation located at nucleotide position 677, resulting in an alanine to valine amino
acid substitution at amino acid 222 (29). There frequency of the MTHFR 677CÆT
polymorphism varies widely among various ethic groups. It has been reported that up to 1215% Asian and Caucasian are homozygous for the MTHFR 677T variant, for AfricanAmerican populations, the frequency of TT homozygosity is relatively low (30,31). It has
been shown that MTHFR 677CÆT polymorphism reduces MTHFR enzymatic activity and
increases its sensitivity to heat degradation (2). The functional changes in the MTHFR
677CÆT variant are most likely due to an increased dissociation of flavine adenine
dinucleotide (FAD), a cofactor produced from riboflavin that stabilizes the MTHFR enzyme
(32, 33). The effect of the MTHFR C677T polymorphism can be compensated through
sufficient folate (33) suggesting that the impact of this mutation is significant only under
conditions of folate deficiency. Several studies in humans suggest that only under folate
depletion, increases in blood homocysteine levels and genome wide hypomethylation were
observed in individuals with MTHFR 677T allele (34, 35).
Another common MTHFR polymorphism is an adenine to cytosine substitution at
nucleotide position 1298, and results in a glutamine to alanine change at amino acid sequence
(36). The frequency of homozygote (CC) MTHFR 1298AÆC variant varies from 7 to 12 %
in North American population. This polymorphism also decreases MTHFR enzyme activity
7
but does not affect the protein’s heat tolerance (37). Studies suggested that the effect of
MTHFR 1298AÆC polymorphism is similar to MTHFR C667T polymorphism, however, the
effect of MTHFR 1298AÆC polymorphism is still unclear (38, 39).
MTHFR polymorphisms and health issues
MTHFR plays an important role in the distribution of intracellular folate for nucleotide
production and methylation reactions. Therefore, homozygosity for the MTHFR C677T
polymorphism can induced health problems that are similar to those caused by folate
deficiency. It has been reported that individuals homozygous for MTHFR C677T have
increased risk of heart disease, neural defects and cancer development (40). The significance
of MTHFR A1298C polymorphisms to human health still needs investigation, though some
studies suggested that this polymorphism may confer protection against leukemia and
colorectal cancer under folate deficiency (41, 42).
MTHFR 677T variant and cancer risk
MTHFR C677T polymorphism plays different roles in cancer development. It has been
shown that individuals with two MTHFR 677T alleles were more resistant against colorectal
cancer, cervical cancer and various types of leukemia but were more susceptible to breast
cancer, stomach cancer and pancreatic cancer (40, 43). This tissue-specific role of the
MTHFR 677T variant on cancer development may be explained by the different folate
requirements and different criteria for folate deficiency in different tissues (44). In addition,
several studies have shown that the effect of the MTHFR 677T variant on cancer risk can be
modified by environmental factors and other genetic factors including: alcohol, smoking, diet
supply and genetic changes to other genes that affect folate metabolism (31, 40, 41, and 42).
8
The relationship between colorectal cancer risk and the MTHFR 677T variant has been
extensively studied. It appears that individuals with TT genotype have a lower colorectal
cancer risk when the folate level is high, a higher colorectal cancer risk when the folate level
is low (42). It is still unclear how MTHFR 677T variant differentially modifies the risk of
colorectal cancer under different diet condition, but mechanisms have been proposed based
on functional changes mediated by MTHFR C677T polymorphism. Individuals with TT
genotype have reduced MTHFR activity and slower 5,10-methyleneTHF to 5-methylTHF
conversion. When folate level is high, there will be sufficient amounts of 5,10-methyleneTHF
for nucleotide biosynthesis, to maintain the balance of nucleotide pool, and to prevent uracil
incorporation during DNA replication (45). In addition, with a high supply of intracellular
folate, MTHFR can continually produce 5-methylTHF to reach the levels required for SAM
synthesis and DNA methylation. When folate level is low, decreased MTHFR activity caused
by the MTHFR C677T polymorphism leads to lower 5-methylTHF level. The effect mediated
by the MTHFR 677T allele can ensure an adequate level of 5,10-methyleneTHF for DNA
synthesis, however, DNA methylation will be disrupted due to decreased SAM synthesis
(45).
9
Figure1.1.Folate metabolic pathway
Folate needs to be processed into tetrahydrofolate (THF) by dihydrofolate reductase (DHFR)
for nucleotide and methionine synthesis. THF can be further processed into 5, 10methylenetetrahydrofolate for 5-methylTHF synthesis. MTHFR (★) is responsible to convert
5, 10-methylenetetrahydrofolate into 5-methylTHF. Methionine synthase (MTR) uses the
methyl group provide by 5-methylTHF during the conversion of homocysteine to methionine.
5-methylTHF is converted back into THF during this process. Methionine is used for Sadenosylmethionine (SAM) synthesis, a universal methyl donor invovled in methylation
event. SAM can be processed into S-adenosylhomocysteine (SAH) and homocysteine.
Adapted from Roy et. al., (46)
10
11
1.1.4 Mouse model of MTHFR deficiency
The MTHFR gene was first isolated and cloned in the Rozen Laboratory. The mouse
genomic clone of MTHFR is 19 kb long, and the amino acid sequence of mouse MTHFR is
90% similar to human MTHFR (47). The MTHFR mouse model was developed to study the
effect of MTHFR deficiency; this model was created by a knockout of the mouse Mthfr gene.
MTHFR heterozygote (Mthfr+/-) and homozygote knockout animals (Mthfr-/-) have elevated
homocysteine levels, as well as disrupted SAM levels (48). MTHFR heterozygote (Mthfr+/-)
animals are models for mild MTHFR deficiency. These animals have reduced enzyme
activity since they only have one wild type Mthfr copy. Previous studies showed that
MTHFR heterozygous mice (Mthfr+/-) have increased pregnancy loss, development delay and
some birth defects (49). MTHFR homozygous knockout animals (Mthfr-/-) are models for
severe MTHFR deficiency; these animals have no functional MTHFR.
12
1.2 COLORECTAL CANCER
Colorectal cancer (CRC) is one of the most frequently observed cancers in the western
world and the mortality of patients affected by CRC is close to 30% (50). Factors that modify
the risk of CRC can range from diet, alcohol, and smoking to genetic mutations and
hereditary disease (51, 52, 53). A strong association between folate deficiency, alcohol
consumption and colon cancer risk has been found (54) in humans. In addition, several
studies have demonstrated that consumption of unsaturated fats and reduced physical activity
increases the risk of colon cancer. The progress in defining genetic risk factor for CRC has
been equally significant. Mutations in several genes involved in cell proliferation, DNA
repair and cell survival have all been identified to be critical for human colorectal cancer
development.
1.2.1 Genetic defect
In general, genetic defects that increase CRC risk can be divide into: loss of or reduction
of a tumor suppressor gene and gain of or increased function of an oncogene. These genetic
defects may be caused by chromosomal instability, chromosomal translocation, deregulated
expression and gain or loss of function gene mutations.
Defect in APC gene
Adenomatous polyp, an abnormal growth within the epithelium, is considered to be a
major precursor to CRC (55). Patients that have their adenomas removed have reduced CRC
risk (56). In addition, individuals with inherited diseases or mutations that predispose them to
13
adenomas frequently develop CRC as they get older (57). Familial adenomatous polyposis
(FAP) is an inherited disease caused by mutations in Adenomatous Polyposis Coli (APC)
gene and represents a big CRC risk factor (58). APC plays an important role in the canonical
Wnt signaling pathway and regulates several process involved in cell proliferation and
survival (59, 60). In the absence of Wnt signaling, the APC protein can bind to β-catenin and
phosphorylate β-catenin for degradation with the help of Axin and glycogen synthase kinase
3 β (61). Almost all mutations in the APC gene lead to protein truncation and disrupt the
degradation of β-catenin. β-catenin is allowed to build up in cytoplasm where it forms
complexes with DNA-binding protein and activates genes involved in cancer development in
nucleus (62). Mutations in the APC gene are observed in about 70%-80% of colorectal
adenomas (61) and APC inactivation is thought to be responsible for the initiation of tumor
development. An APCMin/+ mutant mouse was generated to be used as a model system to
study the effect of APC inactivation (63), and many intestinal adenomas are found in the
intestine of APCMin/+ mice. The loss of wild type APC allele was found in tumor tissue
from APCMin/+ mice in the early phase of cancer development (64). This finding suggested
APC inactivation occurs early during tumor growth and may be responsible for the initiation
of tumor growth.
Defect in DNA repair gene
Microsatellite instability (MSI) is another frequently observed phenotype that may
increase the risk of CRC. MSI is frequently observed in patients with hereditary nonpolyposis
CRC (HNPCC) and sporadic CRC (65, 66). A cell line study showed that patients with MSI
have a 100-fold increases in mutation rate at repetitive DNA sequences compare to controls
14
(67). This suggests that variations of microsatellites observed in colorectal cancer patients are
caused by mutations in DNA repair genes. Indeed, mutations of DNA repair genes MSH2 and
MLH1 were found in the majority of HNPCC patients (68, 69). A single wild-type allele is
required for DNA repair; however, the remaining allele can be silenced by a newly acquired
mutation or changes in the DNA methylation pattern. Cells that lose both copies of the wildtype allele will quickly accumulate mutations elsewhere in the genome, which will eventually
lead to cancer development. Silencing of MLH1 through increased methylation in the
promoter region was observed in MSI-induced CRC patient without HNPCC implication
(68).
Defect in K-RAS and P53
K-RAS is a member of the Ras family and involved in cell proliferation and survival
through activation of its downstream signaling pathway. Mutations of Ras family genes are
frequently observed in different types of human cancer (70). It has been reported that the
frequency of K-RAS mutation in human CRC is close to 40% (71). In addition, mutations of
B-RAF and PIK3CA, genes downstream of K-RAS, were found in several cases of CRC (72,
73). These mutations can lead to overactivation of MAPK and P13K pathways and enhance
cell growth.
p53, also known as the guardian of the genome, is involved in cell cycle control and
apoptosis. Up to 70% of loss of heterozygosity (LOH) in CRC was found at 17p, where the
p53 gene is located (71). p53 often carries mutations in one of its alleles in CRC with LOH.
However, LOH and p53 mutation are absent in most adenomas. This observation suggests
that p53 gene mutation may be responsible for the transition from adenoma to carcinoma
15
(74). Inactivation of the p53 gene allows cell growth to continue under different stresses and
prevents apoptosis to increase cell survival.
1.2.2 Environmental factors
The progression from adenoma to carcinoma is a slow process; several mutations in
different tumor suppressors and oncogenes are required. However, this process can be
drastically shorted by environmental factors.
Alcohol and smoking
It is well known that alcohol and smoking lead to increased risk of developing different
types of cancer. Although the role of smoking in CRC development is still unclear, two
studies in humans showed that smoking causes a 1.2 fold increase in CRC incidence (75, 76).
Alcohol consumption on the other hand, is considered as a cause for the initiation of CRC
(77). The increased cancer risk conferred by alcohol can be explained by the generation of
acetaldehyde, a carcinogenic compound, and generation of reactive oxygen species (ROS)
during the metabolism of ethanol (78). It is interesting to note that acetaldehyde can reduce
the level of folate, an important vitamin involved in the maintenance of genome stability in
intestine (79). A study in rat showed that heavy consumption of alcohol leads to reduced
SAM generation and hypermethylation (80).
Folate depletion
The correlation between folate depletion and CRC risk has been confirmed in human
studies (8, 10). Folate deficiency could lead to an imbalance in the nucleotide pool and
disruption of DNA repair. DNA damage caused by folate deficiency can be enhanced by
alcohol intake. Furthermore, dietary studies using the APCMin/+ mouse model have shown
16
that low folate supplementation can lead to increased tumor numbers during the early stage of
cancer development (81). Our lab generated a mouse model carrying a defective copy of the
Mthfr to investigate the effect of folate and Mthfr deficiency on the risk of CRC (17). A
case/control study using this mouse model showed that low folate diets (control diet with
2mg folate/kg, low folate diet with 0.3mg folate/kg) can induce intestinal tumors in BALB/c
mice; approximately 25% of these mice develop intestinal tumors after a year on the low
folate diet (17, 18, 82). Furthermore, our laboratory showed that mice with a genetic
deficiency in Mthfr (Mthfr+/-), formed more tumors on the low folate diet than mice without
Mthfr deficiency (Mthfr+/+). In addition, we reported that C57Bl/6J mice did not form tumors
under the same conditions as the BALB/c mice (18). A microarray experiment was done to
compare expression profiles of normal intestinal tissues and tumor tissues in BALB/c mice
using Affimetrix Mouse Genome 430-2 chips. Some critical mechanisms in folate-related
tumorigenesis, including disrupted cell cycle control, apoptosis and DNA repair were
identified (17,18, 82).
17
1.3 THESIS RATIONAL
Although several mechanisms involved in intestinal tumor progression have been
identified based on the information obtained from the comparisons between tumor and
normal tissue, little is known about the expression changes responsible for the initiation of
tumor growth. More importantly, the impact of methylation change on tumor susceptibility
under folate and Mthfr deficiency need to be elucidated.
In Chapter II, the genetic difference between BALB/c and C57Bl/6 mice will be
investigated using normal preneoplastic intestinal tissues. In addition, modifier genes
responsible for the initiation of intestinal tumorigenesis will be identified.
In Chapter III, the effect of folate and MTHFR deficiency on gene expression and
methylation will be studied in BALB/c mice to access their relationship with risk of
developing intestinal tumor.
18
Chapter II
Strain differences in the retinoid/PPARα pathway and tumour suppressor gene
may influence intestinal tumor incidence
19
2.1 ABSTRACT
Folates are important vitamins involved in nucleotide synthesis and DNA methylation.
Inadequate folate intake may increase risk for developing colorectal cancer. Previous studies
have shown that a low-folate diet induces intestinal tumors in BALB/c mice; more recently, it
has been reported that C57BL/6 mice do not form tumors under the same conditions. To
identify genes that could contribute to tumor susceptibility, we compared gene expression
profiles in preneoplastic intestine of BALB/c and C57BL/6 mice fed low-folate diets. We
identified 74 genes that were up-regulated and 90 genes that were down regulated in BALB/c
mice compared to C57BL/6 mice. Using quantitative real-time-PCR, we confirmed decreased
expression of Bcmo1 and increased expression of Aldh1a in BALB/c mice, which would be
expected to up-regulate the PPARα pathway, and confirmed the increased expression of
Pparα and several downstream genes (Aqp3, Cd36, Cyp4a10, Hmgcs2, Acot1 and Me1).
Furthermore, we verified, in BALB/c mice, the decreased expression of 4 genes (Tgfbi, Arntl,
Sprr2a, and Bmp5) with tumor-suppressor properties. For Bcmo1, Pparα, and Bmp5, we
observed significant DNA methylation changes between strains that were consistent with the
changes in mRNA levels. We suggest that disturbed regulation of the retinoid/PPARα
pathway and altered expression of tumor suppressors may contribute to the formation of
intestinal tumors induced by low folate intake.
20
2.2 INTRODUCTION
The initiation and progression of the neoplastic process depend on heritable properties and
their interaction with different environmental factors. Thus nutrition, in addition to genetic
factors, has a critical role in cancer development. Epidemiological studies have demonstrated
a strong correlation between low folate intake and increased risk of colon cancer (54). Folate
derivatives are necessary for several essential metabolic pathways, including nucleotide
synthesis and methylation reactions. Methylenetetrahydrofolate reductase (MTHFR), one of
the most studied genes in folate metabolism, regulates the distribution of one-carbon units
between nucleotide production and methylation reactions. MTHFR is responsible for the
conversion of 5, 10-methylenetetrahydrofolate (methyleneTHF), a carbon donor for
nucleotide synthesis, to 5-methyltetrahydrofolate (5-methylTHF), the main circulating form
of folate. 5-MethylTHF is required for homocysteine (Hcy) conversion to methionine, which
is subsequently used to generate S-adenosylmethionine (SAM), a universal methyl donor (3).
Folate metabolism affects DNA and SAM synthesis; it has been suggested that folate
deficiency can induce tumor formation through DNA damage and alteration of DNA
methylation (83). To better characterize the mechanisms of folate deficiency-induced
intestinal cancer, we established a mouse model with spontaneous intestine neoplasia induced
by folate deficiency. Tumors are observed after feeding BALB/c mice with a FD diet for 1
year (17). Microarray analysis was performed to compare the expression profiles of normal
preneoplastic intestine and tumors in the BALB/c mice (82). Results from this analysis
suggest that some critical mechanisms for folate-related tumorigenesis include increased
21
DNA damage, altered DNA methylation, and reduced apoptosis (17, 18, and 82).
Interestingly, another mouse strain, C57BL/6, did not form any tumors under the same FD
diet (18). A comparison between BALB/c and C57Bl/6 mice normal intestine revealed
significant strain differences in one-carbon metabolism and DNA repair pathway (84). In
addition, methylation studies suggested that only BALB/c mice showed a significant global
decrease in DNA methylation level under folate deficiency.
Recently, there has been growing evidence suggesting that the intestinal microbiome plays
an important role in the initiation and progression of colorectal cancer. Intestinal bacteria can
actively contribute to CRC development through production of carcinogens, induction of cell
proliferation and DNA damage (85, 86, 87). To prevent infection and to eliminate the
influence of intestinal microbiome in our study, BALB/c and C57BL/6 mice were given
succinylsulfathiozole, an anti-bacterial drug, in all our experiments.
No studies have examined the expression profile of normal intestine in BALB/c and
C57Bl/6 mice fed FD diet in order to determine genes responsible for the initiation of
tumorigenesis. Furthermore, the influence of methylation changes induced by folate
deficiency at specific genes on intestinal tumor development is unclear and needs to be
examined. In the present study, we used preneoplastic intestinal tissues for comparison of
gene expression profiles of BALB/c and C57BL/6 mouse strains, to identify candidate genes
that could contribute to tumorigenesis under FD diets. Our work has revealed genetic and
epigenetic differences in the regulation of the retinoid/PPARα pathway and in the expression
of some tumor suppressor genes.
22
2.3 MATERIALS AND METHODS
Mice and diets
After weaning, BALB/c Mthfr+/- mice and C57BL/6 Mthfr+/- mice were fed with low folate
diet (FD, 0.3mg folate/kg diet) for 1 year. These diets contain succinylsulfathiozole (1%) to
prevent folate synthesis by intestinal flora. Mice were sacrificed and small intestines were
removed and examined under a dissecting microscope to determine tumor incidence as
previously reported (17, 18, 82 and 84). To avoid gender effects, all mice used in our
experiments were female.
RNA extraction from normal preneoplastic intestine
RNA was extracted from 30 mg frozen normal duodenal tissue using RNeasy Micro Kit
(Qiagen). Some earlier studies showed that duodenal region was more susceptible to
tumorigenesis (17). Eight samples for microarrays, to focus on strain differences, were
prepared from four BALB/c Mthfr+/- mice and four C57BL/6 Mthfr+/- mice fed with low folate
diet. Liquid nitrogen treatment was used during RNA extraction to minimize RNA
degradation. Deoxyribonuclease I (Invitrogen) treatment was performed on column to
remove genomic DNA, as recommended by Qiagen. High quality of extracted RNA was
verified using denaturing gel electrophoresis in 1% agarose gel (Figure 2.1). Agilent
BioAnalyzer electrophoretogram quality controls were also performed by McGill University
- Genome Quebec Innovation Centre to confirm the RNA integrity.
23
Figure 2.1 Confirmation of the quality of RNA used in microarray experiment
B1, B2, B3, B4 are RNA extracted from BALB/c (Mthfr+/-) mice under low folate diets
(0.3mg folate/kg) and C1, C2, C3, C4 are RNA extracted from C57B1/6J (Mthfr+/-) mice
under low folate diets (0.3mg folate/kg). 28S:18S ratio range from 1.5 to 2.
Microarray analysis
24
Affymetrix Mouse Gene 1.0 ST Array Chips were used for the comparison of expression
profile between BALB/c Mthfr+/- and C57BL/6 Mthfr+/- mice fed with FD diet (0.3mg
folate/kg diet) to identify potential oncogenes and tumor suppressors that are differentially
expressed between the two strains of mice. We considered C57BL/6 mice as the control
group and BALB/c mice as the tumor susceptible group. Affymetrix Powerful Tools (APT)
was used to normalize raw microarray data. Flexarray, statistical data analysis software for
gene expression microarrays, developed by McGill University - Genome Quebec Innovation
Centre, was used to treat microarrays data (88). Wright and Simon’s implementation of the
Empirical Bases method was used to calculate expression fold change and p-value. Genes
with expression fold change greater than 2 and a p-value less than 0.05 after false discovery
rate correction were considered significant. Ingenuity Pathways Analysis (IPA) was used for
assessment of biological processes that are most significantly perturbed in our dataset.
Quantitative real-time RT-PCR (qRT-PCR)
RNA (1.5ug) from BALB/c and C57BL/6 mice normal duodenal tissues was reversetranscribed into cDNA using SuperScript II reverse transcriptase (Invitrogen). These RNA
were extracted from a different cohort of BALB/c and C57BL/6 mice to confirm microarray
data. RNasin (Promega) was used to prevent RNA degradation. Primers for phospholipase
A2, group IIA (Pla2g2a), beta-carotene 15,15'-monooxygenase 1 (Bcmo1), aldehyde
dehydrogenase 1 family member A1 (Aldh1a1), peroxisome proliferator-activated receptor
alpha (Pparα), acyl-CoA thioesterase 1 (Acot1), cluster of differentiation 36 (Cd36), 3hydroxy-3-methylglutaryl-Coenzyme A synthase 2 (Hmgcs2), aquaporin 3 (Aqp3), malic
25
enzyme 1 (Me1), cytochrome P450 family 4 subfamily a, polypeptide 10 (Cyp4a10), small
proline-rich protein 2A (Sprr2a), aryl hydrocarbon receptor nuclear translocator-like (Arntl),
bone morphogenetic protein 5 (Bmp5) and transforming growth factor beta-induced (Tgfbi)
genes were designed (Table 2.1) and shown to amplify a unique amplicon of the expected
size (data not shown). A no-template control sample and a no-reverse-transcriptase control
sample were included for every qRT-PCR experiment as negative controls. A standard curve
using a mixture of all cDNA samples from RT was used to quantify the expression levels of
candidate genes. Candidate gene expression was normalized to glyceraldehyde 3-phosphate
dehydrogenase (Gapdh).
Table 2.1 Primer sequences and amplicon parameters
26
Gene
symbol
Forward & reverse primers
5' -> 3'
Amplicon
size (bp)
Tm2
(°C)
Pla2g2a
F: GGCTGTGTCAGTGCGATAAA
R: TGCAAAACATGTTGGGGTAG
96
81.1
Bcmo1
F: TGTTTCTGGAGCAGCCTTTT
R: ATGTCTTGTCCTCCCTGTCG
108
82.8
Aldh1a1
F: TACTTGTCGGATTTAGGAGG
R:CACTTGGTATTGTTTGACCATGA
88
79.8
Pparα
F: CCTGAACATCGAGTGTCGAA
R: CGAATAGTTCGCCGAAAGAA
102
83.3
Acot1
F: TACTTCCCGCTGTGCAGCGC
R: TGAGGCTTGGGCTCCCCTCC
77
86.5
Cd36
F: GGACCCCGAGGACCACACTGT
R: ATGTGGTGCAGCTGCTACAGCC
127
83.8
Hmgcs2
F: CTGCCGTGGGATGCTGTGGG
R: GAAGAGGGAGGCTGTGCCGC
168
87
Aqp3
F: CCTTGTGATGTTTGGCTGTG
R: CCAAAAGCCAAGTTGATGGT
90
86.6
Me1
F: CAGCGTCTGTTGCGGTTGCG
R: CCCAAGGCAGCCTCTCCAGC
106
84.8
Cyp4a10
F: ACTCTCCCCGACACAGCCACT
R: AGTCGGGCTAAGGGCATGGGG
166
85.8
Sprr2a
F: TTGAGCCTTGTCTTCCTTCAG
R: GAGGTGGGCATTGCTCATAG
72
84.3
Arntl
F: CCACAGCACAGGCTATTTGA
R: TCGTTGTCTGGCTCATTGTC
75
83.3
Bmp5
F: ACATGGGCCTCAGTCAAAAC
R: GCTCTCACGGATCGAAGAAG
78
82.3
Tgfbi
F: CTGCCATTGACATCCTCAAA
R: GCCAGGAAGGTCAACTGTTC
73
80.6
Immunoblotting
Protein extracts were prepared from duodenum tissues, using four Mthfr+/- BALB/c mice
27
and four Mthfr+/- C57BL/6 mice. For all samples, 50ug of protein were separated on SDSpolyacrylamide gels. Primary antibodies were diluted in 2% skim milk in TBS-Tween and
incubated with the membrane overnight. Primary antibodies and their dilutions were: 1:600
PPARα (H-98) antibody (Santa Cruz Biotechnology), 1:8000 actin antibody (Sigma) and
1:200 beta-carotene 15,15'-monooxygenase1 (BCDO1) (S-13) antibody (Santa Cruz
Biotechnology). Anti-rabbit IgG (GE Healthcare, Mississauga, Canada) was used as the
secondary antibody for PPARα and actin; donkey anti-goat IgG-HRP (Santa Cruz
Biotechnology) was used as secondary antibody for BCDO1. Densitometric analysis of the
fluorograms was performed by two observers, one of whom was blinded to the identity of the
assessed samples.
Quantitative CpG methylation analysis by pyrosequencing
DNA was isolated from duodenums using the DNeasy Blood & Tissue Kit (Qiagen,
Toronto, Canada) and subjected to bisulfite treatment using the Qiagen Epitect Bisulfite Kit
(Qiagen, Toronto, Canada), as recommended by the manufacturer. Amplification was
performed with the Pyromark PCR kit (Qiagen, Toronto, Canada), prior to pyrosequencing.
The resulting biotinylated PCR product was bound to Streptavidin Sepharose High
Performance Beads (GE Healthcare, Mississauga, Canada) for solid phase template
preparation. Then, the immobilized PCR product was purified using the Pyromark
Pyrosequencing Vacuum Prep tool. Denaturation and washes were done as recommended by
the manufacturer. Pyrosequencing reactions were performed on the PyroMark Q24 Platform
(Qiagen, Toronto, Canada). PyroMark Q24 software was used for data analysis.
MALDI-TOF Analysis of DNA Methylation Patterns
28
Quantitative measurement of methylation using the Sequenom EpiTYPER technology
(Sequenom Inc, San Diego, CA, USA) was performed at the McGill University and Genome
Quebec Innovation Centre to verify the methylation data generated by pyrosequencing. All
procedures were performed as recommended by the manufacturer.
Statistical analysis
The quantitative data are presented as the average value of replicates ± SEM. Levene's test
was performed to access the equality of variance in different samples. For parametric data,
independent t-test was used. For non parametric data, Mann-Whitney U test was used in
place of independent t-test. These analyses were performed using SPSS for WINDOWS
software, version 11.0. P-value <0.05 were considered significant. For IPA functional
analysis, Fisher’s exact test was used to select functions and pathways with a p-value superior
to 0.05.
2.4 RESULTS
Tumor incidence in BALB/c and C57BL/6 strains
29
None of the 64 FD, C57BL/6 mice developed tumors. In contrast, 25% tumor incidence
was observed in 55 FD BALB/c mice (data not shown). This difference in tumor incidence
between the strains is consistent with our earlier observations (18).
Differences between FD BALB/c and C57BL/6 gene expression profiles
There were 282 genes with significant changes in expression (Fig. 2.2 A); 91 genes with
increased expression in BALB/c compared to C57Bl/6 and 191 genes with decreased
expression (Table 2.1).
Using IPA, these 282 genes were categorized into different groups based on their
functions (Fig. 2.2 B). The top 3 categories were lipid metabolism, molecular transport and
small molecule biochemistry. In addition, IPA canonical pathways analysis was used to
identify the pathways that were the most significant from our data set. Glutathione
metabolism, PXR/RXR activation, NRF2-mediated oxidative stress response and LPS/IL-1
mediated inhibition of RXR function were the top pathways. Since some of the earlier studies
had reported regulability of Pparα by homocysteine (89), we performed manual inspection of
the gene list and observed that several genes downstream of Pparα or genes that could
modulate its activity (Bcmo1 and Aldh1a1) also appeared to be changed in expression. We
also identified some tumor suppressors that differed in expression between strains. Based on
the above criteria, we selected 13 candidate genes for RT-PCR confirmation (Table 2.1). In
addition, we examined Pla2g2a, which has previously been shown to affect tumorigenesis
and to have different expression levels between BALB/c and C57BL/6 mice. Our total of 14
candidate genes therefore included 9 members of the Pparα pathway, 4 tumor suppressors
30
and Pla2g2a. These genes share links to lipid metabolism, oxidative stress, apoptosis, cancer
or cell cycle regulation.
31
Figure 2.2 Identification of individual genes and functional gene categories with
significant changes in expression between C57BL/6 and BALB/c mouse strains.
A. Two-dimensional scatter plot depicting the comparison of genes expressed by 4 C57BL/6
mice versus 4 BALB/c mice on low-folate diet. Averaged expression of genes is represented
by dots. Genes on the identity line (diagonal) denote no changes in expression level. The cutoffs for 2-fold induction and repression is indicated by the two parallel lines above and below
the diagonal, respectively. Genes with a fold change greater than 2 or smaller than 0.5 falls
outside of these boundaries. B. Categories of genes that are differentially expressed during
the C57BL/6 and BALB/c comparison. The 12 IPA-sorted categories with highest P-values
are shown. This analysis is based on the gene list provided in Table 2.2. Values after the bars
indicate the number of genes in each category.
32
A.
B.
33
Differential expression between BALB/c and C57Bl/6 mice
To validate the expression differences between strains that were observed by
microarray analysis, we measured expression of 14 candidate genes (see Table 2.1) using
quantitative real-time RT-PCR. To confirm micro-array data, we compared expression of
FD BALB/c mice (n=4) versus FD C57BL/6 mice (n=4). These animals had not been
used in the microarray analyses and therefore represented biological replicates.
Pla2g2a is highly expressed in BALB/c compared to C57BL/6 mice, based on our
gene profiling experiment (GEO Accession Number: GSE34012) and qRT-PCR
determinations (Table 2.1). This result was predictable, since BALB/c mice were
previously shown to possess a normal Pla2g2a genotype, whereas in C57BL/6 mice, its
coding sequence is disrupted by a frameshift mutation in exon 3, resulting in virtually
undetectable expression (90). Therefore, it constitutes an excellent internal control in our
experiments. It was crucial for us to confirm the Pla2g2a status, since Pla2g2a wild-type
allele behaves as a modifier in C57BL/6J-Min strain, acting as a tumor suppressor (91).
According to Pla2g2a confirmation performed by Dr. Leclerc (data not shown), BALB/c
mice used in our experiment are homozygous for this wild-type Pla2g2a allele. Therefore
other difference(s) must explain the different tumor sensitivity of these 2 mouse strains.
Using qRT-PCR, we found the expression level of Bcmo1, is 35 times lower in
BALB/c mice compared to C57BL/6 mice. In addition, a 1.7 fold expression increase of
Aldh1a1 was observed in BALB/c mice. Pparα is up-regulated 3.3 fold in BALB/c mice.
The expression of genes down stream of Pparα including Acot1, Cd36, Hmgcs2, Aqp3,
Me1 and Cyp4a10 were also increased (Table 2.2).
34
Expressions of four candidate genes with tumor suppressor properties were examined.
Sprr2a expression is 69 times lower in BALB/c mice, Arntl expression is 2.3 times lower
in BALB/c mice; Bmp5 expression is 2 times lower in BALB/c mice; Tgfbi expression is
2 times lower in BALB/c mice. These results showed that there is a tumor-promoting
environment in the normal intestine of BALB/c mice. In summary, out of the 14 candidate
genes selected, there were 5 genes with decreased expression and 9 genes with increased
expression in BALB/c FD mice compared to C57BL/6 FD mice (Table 2.2); these results
were consistent with microarray data (Table 2.3).
The protein analysis has been done to confirm our RT-PCR results at protein level.
PPARα and BCDO1 protein levels were measured using western blot. There was no
significant change in PPARα protein between BALB/c and C57BL/6 groups (data not
shown). However, it has been shown that BCDO1 can inhibit PPARα-RXR
heterodimerization through retinaldehyde synthesis (92). We therefore investigated
changes in BCDO1 protein levels between BALB/c and C57BL/6 strain. According to
western blot results, the level of BCDO1 protein is significantly increased in C57BL/6
compared to BALB/c mice (Fig. 2.3B); this is consistent with change in Bcmo1 mRNA.
35
TABLE 2.2
Determination of relative mRNA levels for 14 selected genes by quantitative RT-PCR in BALB/c
and C57BL/6 micel.
For qRT-PCR analysis, fold change expression levels were adjusted using Gapdh as the normalizer and
C57BL/6 as the calibrator. The altered expression for the same set of genes, deduced from the
microarrays data that gave impetus to our analysis, is also shown for comparisonl. Procedures for
samples preparation, microarrays analysis and real-time PCR are described under Materials and
Methods.
1
All fold changes are means from 4 mice per group.
2
Detection p-values from FlexArray software (see Materials and Methods).
3
P-values were derived from one-factor ANOVA comparisons between mouse strains.
4
Fold change from microarrays data is slightly inferior to the threshold of 2-fold change.
36
Table 2.3 List of probe sets meeting significance and fold changes between BALB/c and C57Bl/6 mouse strain
Gene
Accession no.
Probeset
Gene product
Fold change
(BALB/c vs.
C57Bl/6)
LOC433762
AY140896
10573865
EG665955
FJ556972
10586076
St3gal4
NM_009178
10592084
Trim12
Sprr2a
Sprr2a
H2-Q2
Gvin1
AI451617
Gvin1
C530030P08Rik
Gpr151
Dio1
LOC280487
Gm4638
Slc34a2
NM_023835
NM_011468
AY158986
NM_010392
NM_029000
NM_199146
NM_029000
ENSMUST00000101381
NM_181543
NM_007860
X16670
XM_001480931
NM_011402
10566326
10493850
10493856
10444802
10566571
10566366
10566578
10375121
10458641
10514912
10469127
10574432
10521892
Apol7c
Arntl
NM_175391
NM_007489
10430186
10556463
Mus musculus endogenous defective Murine
leukemia virus LI-12 truncated pol/envelope
fusion protein
SFFVp cell-line DS19-sc9 envelope
glycoprotein 52 mRNA
ST3 beta-galactoside alpha-2,3sialyltransferase 4
tripartite motif-containing 12
small proline-rich protein 2A
small proline-rich protein 2A
histocompatibility 2, Q region locus 2
GTPase, very large interferon inducible 1
expressed sequence AI451617
GTPase, very large interferon inducible 1
RIKEN cDNA C530030P08 gene
G protein-coupled receptor 151
deiodinase, iodothyronine, type I
pol polyprotein
predicted gene 4638
solute carrier family 34 (sodium phosphate),
member 2
apolipoprotein L 7c
aryl hydrocarbon receptor nuclear
37
(FDR)Adjusted
p-value
0.005534745
1.72E-09
0.007799419
1.56E-07
0.02425566
1.45E-05
0.03989737
0.06503025
0.07335339
0.08190073
0.09159499
0.09754758
0.101537
0.1322828
0.1681726
0.1789403
0.1816043
0.1816043
0.1873931
7.10E-06
3.22E-05
0.00013865
1.55E-06
2.83E-07
8.88E-06
6.35E-07
1.89E-05
0.0044231
1.13E-05
0.00357178
0.00357178
0.00983462
0.2066785
0.2107964
0.00357178
0.00011187
Bcmo1
Acp1
Apol10a
Rec8
Fam20a
Ly6e
V165-D-J-C mu
Itpripl2
NM_021486
NM_001110239
NM_177744
NM_020002
NM_153782
NM_008529
ENSMUST00000103526
NM_001033380
10575750
10399820
10425037
10415332
10392464
10424676
10403031
10567297
Nlrp1b
Cyp2c55
NM_001162414
NM_028089
10388065
10463005
Igh-6
BC053409
10403069
Fam132a
NM_026125
10511258
BC005685
5830417I10Rik
BC005685
BC059914
10504757
10493335
translocator-like
beta-carotene 15,15'-monooxygenase
acid phosphatase 1, soluble
apolipoprotein L 10a
REC8 homolog (yeast)
family with sequence similarity 20, member A
lymphocyte antigen 6 complex, locus E
IgM variable region
inositol 1,4,5-triphosphate receptor interacting
protein-like 2
NLR family, pyrin domain containing 1B
cytochrome P450, family 2, subfamily c,
polypeptide 55
immunoglobulin heavy chain 6 (heavy chain
of IgM)
family with sequence similarity 132, member
A
cDNA sequence BC005685
RIKEN cDNA 5830417I10 gene
H2-Ab1
Nlrp9b
Arl2bp
Hspa8
Mcoln3
BC005685
AA467197
Prom1
Pycard
NM_207105
NM_194058
NM_024191
NM_031165
NM_134160
BC005685
ENSMUST00000047498
NM_008935
NM_023258
10444291
10550749
10574204
10584572
10496756
10538901
10475517
10529824
10568355
histocompatibility 2, class II antigen A, beta 1
NLR family, pyrin domain containing 9B
ADP-ribosylation factor-like 2 binding protein
heat shock protein 8
mucolipin 3
cDNA sequence BC005685
expressed sequence AA467197
prominin 1
PYD and CARD domain containing
38
0.2177995
0.2335721
0.2468172
0.249729
0.2589584
0.2593662
0.274666
0.2777584
0.03728898
9.27E-05
0.00630259
9.18E-05
5.54E-06
0.00015824
0.00293715
0.00026672
0.2793053
0.2861106
1.93E-05
0.00053426
0.2901247
0.02885004
0.2936725
0.00024765
0.3028646
0.3095174
0.00031987
0.00216325
0.3131114
0.313837
0.3188672
0.3230328
0.3312822
0.3335593
0.3488806
0.3513249
0.3589843
0.0001242
0.00073611
1.89E-05
6.66E-05
0.00284951
0.00086797
0.01128966
8.34E-05
0.00011144
Tc2n
Naaladl1
NM_028924
NM_001009546
10402195
10460746
Slc26a2
9230105E10Rik
Ly96
Myo7a
5330432E05Rik
Dpep1
Nek5
NM_007885
NM_001146007
NM_016923
NM_008663
AK030563
NM_007876
NM_177898
10459183
10566333
10344966
10565634
10497197
10576235
10577471
Defa24
Paqr9
NM_001024225
NM_198414
10570735
10587871
Mfsd4
NM_001114662
10357660
Slc9a3
Nfil3
Scoc
Nlrp1c
Adh6a
Bmp5
Tgfbi
Mtmr7
1810022C23Rik
Ocm
Npas2
Acta1
NM_001081060
NM_017373
NM_001039137
NR_027858
NM_026945
NM_007555
NM_009369
NM_001040699
BC014724
NM_033039
NM_008719
NM_009606
10406176
10409278
10450904
10388086
10496447
10587231
10405587
10578300
10408647
10535524
10345675
10582592
tandem C2 domains, nuclear
N-acetylated alpha-linked acidic dipeptidaselike 1
solute carrier family 26 (sulfate transporter)
RIKEN cDNA 9230105E10 gene
lymphocyte antigen 96
myosin VIIA
RIKEN cDNA 5330432E05 gene
dipeptidase 1 (renal)
NIMA (never in mitosis gene a)-related
expressed kinase 5
defensin, alpha, 24
progestin and adipoQ receptor family member
IX
0.3633609
0.3648974
0.00116752
0.01365709
0.3673603
0.3699571
0.3766541
0.3772852
0.3839805
0.3879877
0.3894574
0.00019201
0.00049141
0.00045076
1.61E-05
0.00207457
0.00695986
0.00163614
0.4007168
0.4010177
0.00094703
0.00157912
major facilitator superfamily domain
containing 4
solute carrier family 9 member 3
nuclear factor, interleukin 3, regulated
short coiled-coil protein
NLR family, pyrin domain containing 1C
alcohol dehydrogenase 6A
bone morphogenetic protein 5
transforming growth factor, beta induced
myotubularin related protein 7
RIKEN cDNA 1810022C23 gene
oncomodulin
neuronal PAS domain protein 2
actin, alpha 1, skeletal muscle
0.4032384
0.00445133
0.4079791
0.408093
0.4094134
0.4171563
0.4188848
0.4209038
0.4326343
0.432683
0.433619
0.4359328
0.4388987
0.4395937
0.00222174
0.03129361
0.00213601
0.00089635
0.00049364
0.00023607
3.97E-05
0.00251012
0.00299905
0.00226654
0.00149916
0.00908969
39
St3gal1
NM_009177
10429160
Ublcp1
NM_024475
10385361
Gbe1
1700011H14Rik
H2-K1
Nfu1
NM_028803
BC026534
NM_001001892
NM_020045
10436500
10419392
10450075
10539769
Sprr1a
Ifit3
NM_009264
NM_010501
10499899
10462618
Trim30
Rhoq
AI747699
Slc14a1
NM_009099
NM_145491
BC052506
NM_028122
10566358
10447341
10467110
10459866
Klra2
NM_008462
10548552
Art2b
Apobec3
NM_019915
NM_001160415
10565994
10425321
Clic6
Gstm3
Pop4
NM_172469
NM_010359
NM_025390
10436958
10501218
10562578
Ceacam20
NM_027839
10550740
Tmem22
Arhgap19
NM_001101483
NM_027667
10596051
10467637
ST3 beta-galactoside alpha-2,3sialyltransferase 1
ubiquitin-like domain containing CTD
phosphatase 1
glucan (1,4-alpha-), branching enzyme 1
RIKEN cDNA 1700011H14 gene
histocompatibility 2, K1, K region
NFU1 iron-sulfur cluster scaffold homolog (S.
cerevisiae)
small proline-rich protein 1A
interferon-induced protein with
tetratricopeptide repeats 3
tripartite motif-containing 30
ras homolog gene family, member Q
expressed sequence AI747699
solute carrier family 14 (urea transporter),
member 1
killer cell lectin-like receptor, subfamily A,
member 2
ADP-ribosyltransferase 2b
apolipoprotein B mRNA editing enzyme,
catalytic polypeptide 3
chloride intracellular channel 6
glutathione S-transferase, mu 3
processing of precursor 4, ribonuclease
P/MRP family
carcinoembryonic antigen-related cell
adhesion molecule 20
transmembrane protein 22
Rho GTPase activating protein 19
40
0.4415221
4.90E-05
0.4448551
0.00367047
0.4460431
0.4465597
0.4483485
0.4488468
0.00436201
0.04419854
0.00207457
0.00012178
0.4492685
0.4496206
0.02273524
0.00856655
0.450669
0.4518576
0.4586554
0.4592487
0.01031727
0.00226654
0.00978599
0.01684946
0.4606051
0.00707377
0.4676423
0.4683317
0.03729867
0.00131287
0.4684722
0.4709963
0.471944
0.00089635
0.00431595
0.00123009
0.473114
0.00197894
0.4740012
0.4803207
0.00219761
0.01027976
Ang4
LOC641050
Ccnyl1
Tmem8
BC049349
Pcp4l1
Acot2
Slc28a2
NM_177544
M11024
NM_001097644
NM_021793
BC049349
NM_025557
NM_134188
NM_172980
10419575
10504761
10346960
10442932
10572733
10360053
10397145
10475487
Mgst1
Rdh16
Abhd6
A930018M24Rik
Pxmp4
Tm4sf4
Hddc3
Crp
Bnip3
Gm10881
Cml3
Mt1
Pparα
NM_019946
NM_009040
NM_025341
BC137729
NM_021534
NM_145539
NM_026812
NM_007768
NM_009760
ENSMUST00000103364
NM_001037842
NM_013602
NM_011144
10542470
10367045
10412607
10419525
10488797
10492174
10554463
10351852
10414269
10545212
10545865
10574027
10425987
Akr1b8
Gm8840
Cml3
Scpep1
Actc1
Cml3
NM_008012
XR_032645
NM_001037842
NM_029023
NM_009608
NM_053097
10537146
10355310
10545862
10389719
10485982
10545869
angiogenin, ribonuclease A family, member 4
hypothetical protein LOC641050
cyclin Y-like 1
transmembrane protein 8
cDNA sequence BC049349
Purkinje cell protein 4-like 1
acyl-CoA thioesterase 2
solute carrier family 28 (sodium-coupled
nucleoside transporter), member 2
microsomal glutathione S-transferase 1
retinol dehydrogenase 16
abhydrolase domain containing 6
RIKEN cDNA A930018M24 gene
peroxisomal membrane protein 4
transmembrane 4 superfamily member 4
HD domain containing 3
C-reactive protein, pentraxin-related
BCL2/adenovirus E1B interacting protein 3
immunoglobulin kappa chain variable 12-47
camello-like 3
metallothionein 1
peroxisome proliferator activated receptor
alpha
aldo-keto reductase family 1, member B8
predicted gene 8840
camello-like 3
serine carboxypeptidase 1
actin, alpha, cardiac muscle 1
camello-like 3
41
0.4807262
0.4848457
0.4857009
0.4914232
0.4918985
0.4957613
2.009056
2.031704
0.03180832
0.00050455
0.00313647
0.00040937
0.00037865
0.01064235
0.00357178
0.0429692
2.045885
2.053973
2.061204
2.070792
2.076833
2.092779
2.10807
2.131945
2.171234
2.184635
2.189851
2.217721
2.237919
0.00107934
0.00737271
0.0045218
0.00054685
0.00207457
0.02938281
0.00248301
0.00312981
0.00881421
0.02938281
0.03180832
0.04861039
0.0113346
2.249236
2.252575
2.268361
2.289274
2.292474
2.295729
0.03358876
0.00225361
0.02725537
0.00049364
1.93E-05
0.01512144
Nek10
NM_001034865
10412805
Nr1d2
NM_011584
10417734
Lxn
Ly6c1
Cryz
Alad
Gm129
Pm20d1
Ms4a12
NM_016753
NM_010741
NM_009968
NM_008525
BC132471
NM_178079
XM_355147
10498576
10429568
10497001
10513608
10373452
10349694
10466165
Glo1
Cyp2c70
NM_025374
NM_145499
10471675
10467410
Hdhd3
NM_024257
10513604
Gm7120
Adh4
NM_001039244
NM_011996
10407387
10496466
Acot1
Pyroxd2
NM_012006
NM_029011
10397148
10467784
Gstm2
Tbc1d23
Fah
Tpmt
Gclc
EG547347
NM_008183
NM_026254
NM_010176
NM_016785
NM_010295
NM_001034909
10501222
10440050
10565315
10409021
10587266
10450733
NIMA (never in mitosis gene a)- related
kinase 10
nuclear receptor subfamily 1, group D,
member 2
latexin
lymphocyte antigen 6 complex
crystallin, zeta
aminolevulinate, delta-, dehydratase
predicted gene 129
peptidase M20 domain containing 1
membrane-spanning 4-domains, subfamily A,
member 12
glyoxalase 1
cytochrome P450, family 2, subfamily c,
polypeptide 70
haloacid dehalogenase-like hydrolase domain
containing 3
predicted gene 7120
alcohol dehydrogenase 4 (class II), pi
polypeptide
acyl-CoA thioesterase 1
pyridine nucleotide-disulphide oxidoreductase
domain 2
glutathione S-transferase, mu 2
TBC1 domain family, member 23
fumarylacetoacetate hydrolase
thiopurine methyltransferase
glutamate-cysteine ligase, catalytic subunit
predicted gene, EG547347
42
2.314339
0.04036927
2.330614
0.02309345
2.368765
2.382234
2.387635
2.399274
2.421796
2.475633
2.47641
0.00147881
0.00357178
0.00035595
0.00025651
0.00157617
1.93E-05
0.00051191
2.494884
2.594659
0.00220213
0.00164206
2.596922
0.00010689
2.602003
2.619111
0.00545835
0.00220213
2.630419
2.662267
0.00329914
4.79E-05
2.691066
2.730921
2.788574
2.867379
2.869606
2.924297
1.92E-05
2.37E-05
0.00010841
0.00058684
0.00299071
0.00177597
Rdh18
Cyp4a31
AY053573
NM_201640
10367050
10507171
retinol dehydrogenase 18
cytochrome P450, family 4, subfamily a,
polypeptide 31
2.951325
3.022653
0.00220297
0.01111845
Ugt2b36
NM_001029867
10531051
3.065458
0.00094703
Cd36
Art2a
Hmgcs2
NM_001159557
NM_007490
NM_008256
10528207
10565990
10494643
3.074054
3.123384
3.13638
0.00237714
0.00050455
0.02281441
Gm1077
Atp6v0e2
ENSMUST00000103355
NM_133764
10545202
10538082
3.202131
3.231116
0.00662247
1.89E-05
BC035947
Aqp3
Ugt2b5
BC034187
NM_016689
NM_009467
10355954
10512156
10531057
3.242243
3.471731
3.499424
0.0010541
2.35E-05
0.00035101
Aim2
S100g
Tmem116
Gm9078
Hal
Mogat1
Me1
NM_001013779
NM_009789
NM_001161627
XR_031413
NM_010401
NM_026713
NM_008615
10351867
10607705
10525256
10601088
10365769
10347741
10595480
3.499606
3.568506
3.59073
3.661862
3.667482
3.716977
3.729022
1.89E-05
0.00357178
8.34E-05
0.00040415
1.89E-05
0.00385548
0.00057828
Ugt2b38
NM_133894
10531073
4.02317
0.01265626
1810030J14Rik
LOC629446
Dbp
NM_025470
BC057932
NM_016974
10351959
10367744
10553092
UDP glucuronosyltransferase 2 family,
polypeptide B36
CD36 antigen
ADP-ribosyltransferase 2a
3-hydroxy-3-methylglutaryl-Coenzyme A
synthase 2
predicted gene 1077
ATPase, H+ transporting, lysosomal V0
subunit E2
cDNA sequence BC035947
aquaporin 3
UDP glucuronosyltransferase 2 family,
polypeptide B5
absent in melanoma 2
S100 calcium binding protein G
transmembrane protein 116
predicted gene 9078
histidine ammonia lyase
monoacylglycerol O-acyltransferase 1
malic enzyme 1, NADP(+)-dependent,
cytosolic
UDP glucuronosyltransferase 2 family,
polypeptide B38
RIKEN cDNA 1810030J14 gene
gag protein
D site albumin promoter binding protein
4.33555
4.486484
4.813771
0.00357178
6.19E-06
0.00159626
43
LOC641089
ENSMUST00000103538
10403057
Cyp4a10
NM_010011
10507163
Cyp4a32
NM_001100181
10507177
Mt2
H28
Paqr7
NM_008630
NM_031367
NM_027995
10574023
10502801
10508992
Abhd1
Pla2g2a
H2-Ea
NR_003522
NR_002926
NM_010381
10520622
10509584
10450161
similar to Ig heavy chain V region BCL1
precursor
cytochrome P450, family 4, subfamily a,
polypeptide 10
cytochrome P450, family 4, subfamily a,
polypeptide 32
metallothionein 2
histocompatibility 28
progestin and adipoQ receptor family member
VII
abhydrolase domain containing 1
phospholipase A2
histocompatibility 2, class II antigen E alpha
44
4.837636
0.00092037
5.023185
0.00220297
5.145282
0.00436201
5.650173
5.85751
7.235348
0.02426092
6.82E-05
1.22E-06
8.025494
48.97038
50.37321
4.22E-07
1.03E-07
7.62E-08
Figure 2.3 Confirmation of BCDO1 protein level
A. Western immunoblot of BCDO1. Beta-actin used as control. B. Western immunoblotting
analysis of BCDO1 in normal intestine of BALB/c and C57BL/6 mice. BCDO1 protein
levels were quantified and normalized to beta-actin levels for each sample. #P<0.05
(independent t-test).
A.
C57BL/6
BALB/c
BCDO1
Beta-actin
B.
45
Figure 2.4 Confirmation of Aldh1a1 expression level
Aldh1a1 mRNA levels in normal intestine of BALB/c and C57BL/6 mice fed FD. Values are
means ± SEM, n = 4. #P< 0.05, strain effect for FD (independent t-test).
46
Differential DNA methylation level between BALB/c and C57Bl/6 mice
DNA methylation was measured in Pparα, Bmp5 and Bcmo1 gene using Sequenom®
EpiTYPER® and pyrosequencing.
For Pparα, we measured 48 CpG site from Pparα CpG island (UCSC mm9,
chr15:565678-85566062) and 10 CpG sites from Pparα CpG shore (UCSC mm9,
chr15:85567020-85567354). We detected significant methylation levels at only one of the
tested CpG sites in the CpG island and in all 10 CpG sites in the CpG shore (data not shown).
Out of 11 CpG site, all 10 CpG in CpG shore showed significant change in DNA methylation
level between BALB/c and C57BL/6 strains (Fig. 2.5A). Methylation levels of 6 CpG sites
located at 5’ region of Bcmo1 gene (chr8:119619563-119619649) were measured and
significant increases in DNA methylation increases in BALB/c mice were found at CpG 1, 2
and 5. In addition, borderline significant (p=0.052) methylation increase in BALB/c mice
was observed in CpG 4 (Fig. 2.5B). Four out of six CpG sites located 100kb downstream of
Bmp5 gene (UCSC mm9, chr9:75862936-75862986) showed significant increases in BALB/c
mice were found in CpG 2, 3 and 4. A borderline significance (p=0.053) were observed in
CpG 1 and CpG 5 (Fig. 2.5C).
47
Figure 2.5 Confirmation of methylation changes between BALB/c and C57Bl/6 mice
under low folate diet.
A. Pparα DNA methylation levels in normal intestine of Mthfr+/- BALB/c and C57BL/6 mice fed
CD or FD. CpG47 is part of a DNA segment encompassing 48 CpG dinucleotides in Pparα CpG
island (UCSC mm9, chr15:565678-85566062. CpG1 to 10 are part of a DNA fragment in Pparα
CpG island shore (UCSC mm9, chr15:85567020-85567354). Epityper generated data for 9 CpG
units, corresponding to CpG1 and CpG3 to cpG10. Pyrosequencing evaluated methylation of
CpG2 and CpG3. Percentage methylation for CpG3 obtained by pyrosequencing showed less than
2% variation compared to data from Epityper. Values are means ± SEM, for C57BL/6 group n= 3
and BALB/c group n = 6 animals. “*” suggested a significant methylation change between
strains; P<0.001 for CpG4, 6, 7, 9 and 10; P<0.005 for CpG1, 2, 3 and 8; P<0.05 for CpG5
(independent t-tests). B. Bcmo1 methylation levels in normal intestine of Mthfr+/- BALB/c and
C57BL/6 mice fed FD. Pyrosequencing was used to test 6 CpG dinucleotides in Bcmo1 CpG
Island. They are part of the UCSC mm9 chr8:119619563-119619649 DNA segment.Values are
means ± SEM; for C57BL/6 group n= 3 and for BALB/c group n = 6. “*” designates a significant
methylation change between strains, with P< 0.05; the difference was almost significant for
CpG4, with P=0.053 (independent t-test). C. Bmp5 methylation levels in normal intestine of
BALB/c and C57BL/6 mice fed FD. The 6 CpG are part of a CpG island located in a previously
identified regulatory element of Bmp5, 100Kb downstream of this gene. They are included in a
DNA segment encompassing chr9:75862936-75862986 of UCSC mm9 database.Values are
means ± SEM; for C57BL/6 group n= 3 and BALB/c group n = 6. “*” indicates a significant
methylation change between strain; P< 0.05 (independent t-test). The strain effect showed
borderline significance for CpG1 and CpG5 (P=0.053 for both dinucleotides, independent t-tests).
48
A. Pparα
B. Bcmo1
*
*
*
C. Bmp5
49
2.5 DISCUSSION
Cancer is a multistep process and the impact of poor nutrition in tumorigenesis is an
accepted fact. Past studies in colorectal cancer showed that low folate intake alone is able to
induce intestinal tumors in BALB/c mice, whereas C57BL/6 did not form tumors under the
same conditions (17). In the present study, we identified modifier genes between BALB/c and
C57BL/6 mice using microarrays to find modifier genes involved in the initiation of folateinduced tumorigenesis. Based on functional characterization, fourteen genes may promote
tumorigenesis in BALB/c mice through inflammation response and down-regulation of
tumor-suppressor genes.
The low expression level of Pla2g2a mRNA in C57BL/6 was previously reported (90) as
a result of a disruption in the coding sequence. We confirmed that BALB/c mice bear wildtype Pla2g2a sequence, that is known to confer some resistance to intestinal adenoma
formation, and that mutant Pla2g2a genotype is present in C57BL/6 strain (Fig. 2.2). The
mutated allele has the property to favor adenoma formation (90). Down-regulation of
Pla2g2a in C57Bl/6 mice demonstrates that tumor formation in BALB/c mice cannot be
explained by differences in Pla2g2a tumor suppressor expression between the 2 strains.
Pparα codes for a ligand-activated transcription factor involved in the activation of genes
responsible for increased oxidative stress and DNA damage (93). Study on dietary folate
induced intestinal tumors expression profile done previously in the laboratory also showed
that DNA damage plays an important role in tumor formation and progression (18). Our RTPCR results suggested an increased Pparα expression in BALB/c mice, the strain that
develop tumor under folate deficiency. This observation is consistent with microarray results.
It is well accepted that folate deficiency leads to disrupted methylation process. In this study,
we compared the methylation level of Pparα CpG sites located at 5’ region between BALB/c
50
and C57BL/6 mice to determine whether Pparα expression is affected by DNA methylation.
According to Pyrosequencing and Epityper results, Pparα methylation is higher in BALB/c
mice compare to C57BL/6. Methylation of DNA is generally assumed to result in decreased
transcription; this change may be inconsistent with the higher mRNA levels that we observed
in BALB/c mice. However, a plausible explanation to this observation would be that these
CpG sites could be part of binding site for a repressor within the 5’ region of Pparα and
heavy methylation at these CpG dinucleotides may contribute to higher expression. We also
measured PPARα protein level, no significant changes of PPARα protein were observed when
comparing the two strains (data not shown).
PPARα needs to form a heterodimer with retinoid X receptor (RXR) and binds to
peroxisome proliferator response element (PPRE) to activate expression of Pparα target
genes. Therefore, changes in RXR can equally affect expression of genes regulated by
PPARα/RXR complexes. Beta-carotene mono-oxygenase 1 (BCDO1 protein) is an enzyme
that processes beta-carotene into retinaldehyde, a precursor of retinoic acid. Retinaldehydes
can inhibit Pparα/RXR association by binding to RXR ligand binding domains and prevent
its activation (94). BCDO1 deficiency in BALB/c mice could result in accumulation of betacarotene and reduced retinaldehyde synthesis. Lower concentration of retinaldehyde in
BALB/c mice can not effectively prevent the activation of RXR through competitive binding;
therefore up-regulation of Bcmo1 reduces PPARα/RXR heterodimer formation. No
significant RXR expression changes were observed according to microarray data.
The low Bcmo1 expression we observed in BALB/c mice could contribute to increased
PPARα/RXR mediated response and activation of genes downstream of Pparα. To test
whether Bcmo1 expression is affected by DNA methylation, we investigated methylation
level of 6 CpG sites of Bcmo1 gene and confirmed significant methylation difference
between strains (Fig. 2.5B). There are three CpG sites (CpG1, 2 and 5) with higher
51
methylation in BALB/c mice compare to C57BL/6 mice. Consistent changes in mRNA levels
were shown by our RT-PCR results. Using western blot, we also showed BCDO1 protein
level is higher in C57BL/6 mice compared to BALB/c mice (Fig. 2.3 A).
Since the availability of retinaldehyde is crucial for the regulation of RXR activation, we
verified expression changes of all known members of ALDH gene family that play important
role in processing retinaldehyde. According to our micro-array data, only Aldh1a1 showed a
significant change in expression. Aldh1a1 is responsible for processing retinaldehyde into
retinoic acid and mice with Aldh1a1 deficiency have increased retinaldehyde levels (95). We
confirmed an up-regulation of Aldh1a1 in BALB/c mice at mRNA level using qRT-PCR (Fig
2.4). This finding is consistent with micro-array data and shows that retinaldehyde is
processed faster in BALB/c mice compared to C57BL/6 mice, which provide further support
to the hypothesis that low levels of BCDO1 in BALB/c mice facilitates Pparα/RXR
association and promote expression of gene down steam of Pparα.
Indeed, we found 6 genes downstream of Pparα to be up-regulated in BALB/c mice. AcylCoA thioesterase I (ACOT1) is an enzyme involved in the regulation of ligand supply for
nuclear receptors and can be regulated by Pparα (96). Up-regulation of Acot1 could
potentially form a positive feedback loop with Pparα to boost expression of both genes since
Pparα/RXR complexes can activate Acot1 expression. Aquaporin3 (AQP3) is a water channel
protein that plays an important role in epidermal proliferation. It has a PPRE at the 5’
promoter region and it has been shown that increased Aqp3 expression promotes skin and
lung cancer (97). Aqp3-deficient mice are much more resistant to skin cancer and disruption
of Aqp3 expression has a big impact on epithelial cell migration and proliferation (98). Here,
we showed that expression of Aqp3 is higher in BALB/c mice. Cd36, also known as fatty
acid translocase, is a Pparα target gene involved in ROS generation and lipoprotein transport.
Up-regulation of Cd36 is associated with increased inflammation and oxidative stress (99). In
52
addition, Cd36 played an important role in the accumulation of linoleic acid, a substrate that
up-regulates Cyp4a expression and induces oxidative stress. 3-hydroxy-3- methylglutarylCoA synthase 2 (Hmgcs2) is an enzyme involved in ketone production. Ketogenesis is
undesirable for cell proliferation and has a negative impact on tumor growth (100). The upregulation we observed in BALB/c mice may be a result of self-defense mechanism in the
early stage of tumor development. NADP-dependent malic enzyme (Me1) is responsible for
processing malate into pyruvate and CO2 and energy production (101). It is possible that upregulation of Me1 is an early event preceding tumor growth since a large amount of energy is
required for cell proliferation.
Previous studies suggested changes in cell cycle regulation (17) and decreased apoptosis
(82) are key events that promoting spontaneous tumor formation in folate deficiency-induced
tumor mouse model. In this study, we found that four genes with tumor suppressor properties
were down-regulated in BALB/c mice. Arntl, also known as Bmal1, is involved in regulation
of tumor cell apoptosis, cell-cycle progression and DNA damage response. It has been shown
in murine colon cancer cells that loss of Arntl expression lead to decreased p53 expression
and increased cdc2, cyclin B1, cyclin D1, cyclinE at protein level (102). Arntl expression
level is 2.3 times lower in BALB/c compare to C57BL/6 mice according to our RT-PCR
results. The decrease in Arntl expression in BALB/c mice is consistent with the higher tumor
susceptibility associated with this mouse strain. In vivo cancer studies using Tgfbi (-/-) mice
showed that Tgfbi works as a tumor suppressor through inhibition of cyclin D1 (103). Our
data also shows that expression of Tgfbi decreased in mice that are more susceptible to
cancer. Tgfbi expression is 2 times lower in BALB/c mice, the strain susceptible to tumor
development. Small proline-rich protein 2A (Sprr2a) is a protein involved in the formation of
keratinocytes. A recently study of Sprr2a overexpression in mouse biliary epithelial cell and
in human liver suggested that Sprr2a works as a SH3 ligand and increases resistance against
53
oxidative stress (104). Sprr2a expression level is 69 times lower in BALB/c compare to
C57BL/6 mice according to our qRT-PCR results. A lower Sprr2a expression in BALB/c
mice resulted in lower resistance to oxidative stress-induced by Pparα/RXR complex
mediated response. Bone morphogenetic protein 5 (Bmp5) is a member of TGF-β super
family. This gene has an important role in development and down-regulation of Bmp5 often
correlated with deregulated cell proliferation. It has been shown that epigenetic inactivation
of the Bmp gene is implicated in the development of lung cancer through Ras/MAP-kinase
signalling pathway (105). In addition, a study in human myeloma cells suggested that BMP5
acts as a tumor suppressor by inhibiting cell proliferation and promoting apoptosis (106).
Bmp5 expression levels is 2 times lower in BALB/c compared to C57BL/6 mice according to
our RT-PCR results. Higher expression of Bmp5 in C57BL/6 mice could contribute to the
tumor resistance associated with this mouse strain. We compared methylation patterns of 6
CpG sites of Bmp5 gene and confirmed significant methylation differences between strains at
4 CpG sites (Fig. 2.5C). CpG sites of BALB/c mice were more methylated compared to
C57BL/6 mice. This observation is consistent with the lower Bmp5 expression that we found
in BALB/c mice. Researchers are traditionally viewing cancer as a genetic disease, but it is
now becoming apparent that the onset of cancer is preceded by epigenetic abnormalities. The
methylation changes in Bmp5 gene may be part of such initiating events.
Although we used succinylsulfathiozole to minimize the presence of intestinal bacteria in
BALB/c and C57BL/6 intestines, the effect of an anti-bacterial drug may be different
between strains. Depending on the remaining intestinal bacteria that have not been removed
by succinylsulfathiozole, gene expression patterns and tumor incidence may be different in
BALB/c and C57BL/6 mice. As several genes involved in oxidative stress response were upregulated in BALB/c mice, we cannot rule out the possibility that there are more remaining
intestinal bacteria in BALB/c mice compared to C57BL/6 mice. In addition, down-regulation
54
of tumor suppressor genes in BALB/c mice makes them more susceptible to tumor initiation
induced by bacteria-produced stimuli.
In conclusion, this study presents novel data supporting oxidative stress-induced DNA
damages and altered expression of tumor suppressors as major factors in the initiation of
tumor formation in BALB/c mice. This study also demonstrates the importance of retinol
metabolism and its implication in the regulation of a lipid metabolism pathway. These
findings emphasize that adenomas observed in BALB/c mice resulted from the disruption of
multiple process, and suggesting gene specific methylation differences between different
strains as potential factors that influence the susceptibility to tumorigenesis.
2.6 ACKNOWLEDGMENTS
We would like to thank LM and LD for their technical assistances and NJ for
proofreading. YC, DL and RR contributed to the study design, data analysis and manuscript
preparation. YC, DL contributed to data collection.
55
CONNECTING TEXT –Chapter II-III
The observations from Chapter II suggest that up-regulation of modifier genes involved in
retinoid/PPARα pathway and down-regulation of tumor suppressors may be responsible for
the initiation of tumor development in BALB/c mice. In addition, the link between changes in
methylation and gene expression was confirmed with gene expression patterns suggesting
that altered methylation may be responsible for the onset of cancer. However, these genes
were identified through strain comparison only. The impact of folate and MTHFR deficiency
still remains to be understood. In the next chapter, the effect of dietary folate and MTHFR in
intestinal tumorigenesis will be investigated in BALB/c mice.
56
Chapter III
Folate and MTHFR deficiency influences on aberrant gene expression and
methylation patterns during intestinal tumorigenesis in BALB/c mice
57
3.1 ABSTRACT
Disruption of folate metabolism can result in several disease conditions due to disruption
in nucleotide and amino acid synthesis. Defects in MTHFR, a key enzyme responsible for the
distribution of one-carbon units in folate metabolism, modifies cancer risk, depending on
intracellular folate status. A previous study showed that tumor incidence in Mthfr+/- BALB/c
mice fed low folate diet (FD) is higher compared to Mthfr+/+ BALB/c mice fed control diet
(CD). Comparison of gene expression in preneoplastic intestine between these two groups
identified 13 genes that were up-regulated and 51 genes that were down-regulated in Mthfr+/-,
BALB/c mice on FD compared to Mthfr+/+, BALB/c mice on CD. Using quantitative realtime-PCR, we confirmed significant changes in the retinoid pathway (Bcmo1 and Aldh1a1)
and variations in several genes involved in immune response and apoptosis (Atf3, Trem4,
Plscr2 and Ppme1). In addition, consistent gene-specific methylation changes between
different diets and Mthfr genotypes were observed for Bcmo1. These observations suggest
that disruption in genes involved in retinoid acid synthesis, apoptosis and pro-inflammatory
response may contribute to a higher risk of developing intestinal tumors in Mthfr+/-, BALB/c
mice fed FD.
58
3.2 INTRODUCTION
The development of colorectal cancer (CRC) can be attributed to a combination of genetic
and environmental factors. It has been reported that individuals with low folate intake are 3040% more susceptible to CRC than individuals with adequate folate intake (10). Defects in
MTHFR, a key enzyme which synthesizes a folate derivative utilized in methylation
reactions, is believed to increase colorectal cancer risk. The association between
Mthfr677CÆT polymorphism and risk for colorectal cancer has been found in several
epidemiological studies (107,108). Unlike other mutations, the Mthfr 677CÆT
polymorphism is considered as a protective factor under high folate supplementation and a
risk factor for colorectal cancer under folate deficiency. This nutrient-dependant effect of
Mthfr 677CÆT polymorphism can be explained by changes in the distribution of 5,10methyleneTHF and 5-methylTHF molecules depending on folate supply.
To study the effect of folate and MTHFR deficiency on colorectal cancer, a mouse model
for spontaneous intestine neoplasia has been generated using BALB/c mice with a single
functional copy of Mthfr gene. BALB/c and C57Bl/6 mice were fed with FD and CD over 1
year; tumors were only observed in BALB/c mice (17). Several candidate genes involved in
cell cycle control, cell survival and DNA repair, were identified by comparing expression
profiles of tumor tissue with normal tissue (17, 18). In addition, increased expression of
folate-metabolizing enzymes that reduce 5,10-methyleneTHF level for nucleotide synthesis
has been found in BALB/c mice (84). These observations, in combination with decreased
expression of tumor suppressors and increased retinoid/Pparα expression in BALB/c, could
explain the susceptibility of BALB/c mice to intestinal tumorigenesis.
Few studies have been conducted to assess changes of tumor modifier genes induced by
folate depletion in preneoplastic duodenum tissues of BALB/c mice. In addition, the
influence of different Mthfr genotypes under FD and CD on gene expression and DNA
59
methylation levels need to be investigated. In this study, we used the microarray approach to
assess gene expression changes between BALB/c Mthfr +/- mice on FD and BALB/c Mthfr +/+
mice on CD. Quantitative real-time PCR (qRT-PCR) was used to determine dietary and
genotype effects separately. We showed significant genetic and epigenetic differences of
retinoid/PPARα pathway genes between BALB/c mice fed FD and CD, consistent with
previous strain analysis. In addition, we identified several new modifier genes involved in
immune response and apoptosis.
60
3.3 MATERIALS AND METHODS
Mice and diets
After weaning, BALB/c Mthfr+/- and BALB/c Mthfr+/+ mice were fed with a control diet
(CD, 2mg folate/kg diet) or a low folate diet (FD, 0.3mg folate/kg diet) for 1 year. The
incidence of neoplasia is higher in Mthfr+/- mice and in mice on low folate diet.
RNA extraction from normal preneoplastic intestine
RNA was extracted from duodenum tissues using RNeasy Micro Kit (Qiagen) as
described in chapter II. Eight samples for microarrays were prepared from four BALB/c
Mthfr+/- mice fed FD and four BALB/c Mthfr+/+ mice fed CD. High quality of extracted RNA
was verified using denaturing gel electrophoresis in 1% agarose gel. (Figure 3.1) In addition,
sixteen RNA sample were extracted from BALB/c Mthfr+/- and BALB/c Mthfr+/+ mice fed CD
and FD (4 mice per group). These RNA samples were used as biological replicates to confirm
genotype and dietary effects on expression of candidate genes identified in microarray
experiment.
61
Figure 3.1 Confirmation of the quality of RNA used in microarray experiment
B1, B2, B3, B4 are RNA extracted from BALB/c (Mthfr+/-) mice on FD (0.3mg folate/kg) and
C1, C2, C3, C4 are RNA extracted from BALB/c (Mthfr+/+) mice on CD. 28S:18S ratio range
from 1.5 to 2.
62
Microarray analysis and quantitative real-time RT-PCR (qRT-PCR) confirmation
Microarray experiments were performed using Affymetrix Mouse Gene 1.0 ST Array
Chips. As the risk of developing intestinal tumor is lower in Mthfr wild type mice fed CD, we
considered BALB/c Mthfr+/-, CD group as the group with higher tumor resistant and BALB/c
Mthfr+/-, FD group as the tumor susceptible group. Genes with expression fold changes
greater than 1.4 and a p-value smaller than 0.01 after false discovery rate correction were
considered significant. Ingenuity Pathways Analysis (IPA) was used to assess biological
process with the most significant changes in our dataset. Quantitative RT-PCR were
performed as described in chapter II using sixteen RNA samples (1.5ug) from BALB/c
Mthfr+/- FD mice and BALB/c Mthfr+/+ CD mice. Primers for Atf3, Trem4, Plscr2 and Ppme1
were designed (Table 3.1) and amplified a unique amplicon of the expected size (data not
shown).
Quantitative CpG methylation analysis by pyrosequencing
We used pyrosequencing to measure the DNA methylation of Bcmo1 in BALB/c mice, as
previously described in chapter II.
Statistical analysis
Quantitative data are presented as the average value of replicates ± SEM. Levene's test
was performed to access the equality of variance in different samples. Two-factor analysis of
variance (ANOVA) was used to evaluate, individually, the effects of diet and genotype on
gene expression. As indicated in results, t-tests were also performed for specific comparisons.
Box-cox transformation was used to transform non-parametric data sets. Mann-Whitney U
test was used for some non-parametric comparisons. Statistical analyses were performed
using SPSS for WINDOWS software, version 11.0 and XLSTAT software. P-values <0.05
were considered significant.
63
Table 3.1 Primer sequences and amplicon parameters
Atf3
F: TCGGATGTCCTCTGCGCTGGA
R: GGGCCGCCTCAGACTTGGTG
80
84.3
Trem4
F: CGAACACAGGAGGGTGAGAC
R: CTTACACCAGATCTTCTCGCT
82
80.8
Plscr2
F: TGGGTATGCCCCTCAGTATC
R: CCAGACTGGGGAACTTGGTA
96
83.8
Ppme1
F: CCCCAGTGTGGCCATGCAGT
R: GCTCTGCAAACCTGTGCCGGA
91
84.8
64
3.4 RESULTS
Differences between BALB/c Mthfr+/-, FD and Mthfr+/+, CD gene expression profiles
There were 64 genes with significant changes in expression (Fig. 3.2 A); 51 genes with
increased expression and 13 genes with decreased expression in Mthfr
+/-
BALB/c mice on
FD compared to Mthfr +/+ BALB/c mice on CD (Table 3.2).
These 64 genes were categorized into different groups based on their functions using IPA
software (Fig. 3.2 B). The top 3 categories were lipid metabolism, small molecule
biochemistry and nucleic acid metabolism. Fatty acid metabolism, LPS/IL-1 mediated
inhibition of RXR function and PXR/RXR activation were identified as pathways with the
most significant changes according to IPA canonical pathways analysis. In chapter two, we
showed several genes in retinoid/Pparα with differential expression between BALB/c and
C57Bl/6 mice on FD. In this study, we performed visual inspection of the gene list and
observed several genes which had been previously identified (Bcmo1, Sprr2a and Aldh1a1)
also appeared to have differential expression between Mthfr
+/-
, FD and Mthfr
+/+
, CD
BALB/c mice. In addition, we found several genes involved in immune response,
methylation and apoptosis that differed in expression between the two groups. Based on the
above criteria, we selected 7 candidate genes for RT-PCR confirmation. These genes share
links to inflammation, apoptosis, oxidative stress and tumorigenesis.
65
Figure 3.2 Identificantion of individual genes and functional gene categories with
significant expression changes between BALB/c, Mthfr+/-, FD and BALB/c, Mthfr+/+, CD
mice.
A. Two-dimensional scatter plot depicting the comparison of genes expressed by 4 BALB/c,
Mthfr+/-, FD mice versus 4 BALB/c, Mthfr+/+, CD mice. The average gene expression is
represented by dots. Genes on the identity line (diagonal) denote no changes in expression
level. The cut-offs for 1.4-fold induction and repressions are indicated by the two parallel
lines above and below the diagonal, respectively. Genes with a fold change smaller than 1.4
or greater than 0.67 fall outside of these boundaries. B. Categories of genes that are
differentially expressed between BALB/c, Mthfr+/-, FD mice and BALB/c, Mthfr+/+, CD
mice. The 12 IPA-sorted categories with highest P-values are shown. This analysis is based
on the gene list provided in Table 3.1. Values after the bars indicate the number of genes in
each category.
66
A.
B.
67
Table 3.2 List of probe sets meeting significance and fold changes in BALB/c strain between MTHFR
mice
Gene
+/-
FD and MTHFR
+/+
CD
(FDR)Adjusted
p-value
Accession
no.
Probe
set
Gene product
Mela
Mela
Slc1a3
D10049
BC113756
NM_148938
10582545
10582549
10427590
0.06624362
0.199669
0.4970533
0.006701025
0.007864486
1.40E-08
Sprr2a
Gpr157
Bcmo1
0610012H03Ri
k
Atf3
Sema7a
NM_011468
NM_177366
NM_021486
NM_028747
10493850
10510509
10575750
10474307
melanoma antigen
melanoma antigen
solute carrier family 1 (glial high affinity
glutamate transporter), member 3
small proline-rich protein 2A
G protein-coupled receptor 157
beta-carotene 15,15'-monooxygenase
RIKEN cDNA 0610012H03 gene
0.5287812
0.5306703
0.5331266
0.5802062
0.004746888
4.52E-05
4.86E-05
0.000524586
NM_007498
NM_011352
10361091
10585778
activating transcription factor 3
sema domain, immunoglobulin domain
(Ig), and GPI membrane anchor,
(semaphorin) 7A
0.5870641
0.6114579
0.005046058
0.00284734
Sfi1
NM_030207
10383632
0.620659
0.00036043
Cyp2u1
NM_027816
10502214
Sfi1 homolog, spindle assembly
associated (yeast)
cytochrome P450, family 2, subfamily u,
polypeptide 1
0.6217946
0.001532599
Tnfrsf23
NM_024290
10569504
0.6393265
0.001193973
Fold change
(BALB/c +/- FD vs.
BALB/c +/+ CD)
tumor necrosis factor receptor
superfamily, member 23
68
Tspan12
Fbxl3
Aldh1a1
NM_173007
NM_015822
NM_013467
10543306
10422067
10461979
0.6983744
1.40026
1.400588
0.004757039
0.006045806
0.00899108
1.409548
0.004111299
1.414317
0.008409645
10389231
10379127
10530259
10399632
tetraspanin 12
F-box and leucine-rich repeat protein 3
aldehyde dehydrogenase family 1,
subfamily A1
ATP-binding cassette, sub-family B
(MDR/TAP), member 1B
LON peptidase N-terminal domain and
ring finger 1
chemokine (C-C motif) ligand 3
sperm associated antigen 5
RIKEN cDNA 9130230L23 gene
RIKEN cDNA F630048H11 gene
Abcb1b
NM_011075
10519555
Lonrf1
NM_001081150
10578207
Ccl3
Spag5
9130230L23Rik
F630048H11Ri
k
Plscr1
C3ar1
Lipa
Grb7
Rundc3b
Gm766
NM_011337
NM_017407
NR_027961
AK170335
1.419001
1.424217
1.431609
1.431832
0.001146621
0.004674163
0.000524586
0.00395117
NM_011636
NM_009779
NM_021460
NM_010346
NM_198620
BC151094
10587792
10547657
10467139
10380927
10528090
10549154
phospholipid scramblase 1
complement component 3a receptor 1
lysosomal acid lipase A
growth factor receptor bound protein 7
RUN domain containing 3B
predicted gene 766
1.433563
1.437229
1.455523
1.463685
1.465055
1.474683
0.00039314
0.000126889
0.001728771
0.000151019
0.006775206
0.006962669
Klra17
NM_133203
10548437
1.475718
0.000348968
A530064D06Ri
k
NM_178796
10451646
killer cell lectin-like receptor, subfamily
A, member 17
RIKEN cDNA A530064D06 gene
1.491121
0.000958206
Gpr155
Snord37
NM_001080707
AF357364
10483679
10365003
G protein-coupled receptor 155
small nucleolar RNA
1.495484
1.514176
0.000524586
1.90E-05
Slc16a13
NM_172371
10387791
1.515341
0.000960748
Rbbp8
Clec4a1
NM_001081223
NM_199311
10453867
10541555
solute carrier family 16 (monocarboxylic
acid transporters), member 13
retinoblastoma binding protein 8
C-type lectin domain family 4, member a1
1.520381
1.52777
0.002699431
0.003230564
69
Cyp4f15
NM_134127
10443898
Akr1c13
NM_013778
10403303
Emr4
NM_139138
10445953
A930001N09Ri
k
Arl14
Slc23a2
BC113191
10443027
BC104368
NM_018824
10492586
10487906
Nek3
NM_011848
10577492
Serpinb5
NM_009257
10349108
Slc6a20b
NM_011731
10597949
Mfsd7b
NM_001081259
10361075
Ugt2b36
NM_001029867
10531051
Nr1h4
NM_009108
10371784
Ppme1
Opn3
Tmem140
Lhfpl2
Capg
NM_028292
NM_010098
NM_197986
NM_172589
NM_007599
10565873
10360454
10537227
10406676
10539135
OTTMUSG000
00010657
NM_001083918
10510215
cytochrome P450, family 4, subfamily f,
polypeptide 15
aldo-keto reductase family 1, member
C13
EGF-like module containing, mucin-like,
hormone receptor-like sequence 4
RIKEN cDNA A930001N09 gene
1.539679
0.006899908
1.551467
0.008584441
1.55195
0.000286295
1.552717
0.00299297
ADP-ribosylation factor-like 14
solute carrier family 23 (nucleobase
transporters), member 2
NIMA (never in mitosis gene a)-related
expressed kinase 3
serine (or cysteine) peptidase inhibitor,
clade B, member 5
solute carrier family 6 (neurotransmitter
transporter), member 20B
major facilitator superfamily domain
containing 7B
1.554469
1.554879
0.007853788
0.00066403
1.56097
0.006136094
1.575453
0.000194279
1.575754
0.008224406
1.576
0.002719474
1.584242
0.006045806
1.584618
0.00284734
1.585815
1.610279
1.612627
1.622328
1.680293
0.002719474
0.003372821
0.001248455
0.005264711
0.001066554
1.753379
2.60E-05
UDP glucuronosyltransferase 2 family,
polypeptide B36
nuclear receptor subfamily 1, group H,
member 4
protein phosphatase methylesterase 1
opsin 3
transmembrane protein 140
lipoma HMGIC fusion partner-like 2
capping protein (actin filament), gelsolinlike
predicted gene, OTTMUSG00000010657
70
Zfp442
Tsku
Rdh18
Paqr7
BC023805
NM_001024619
AY053573
NM_027995
10488459
10565727
10367050
10508992
Angptl4
Cyp4b1
NM_020581
NM_007823
10450038
10515201
Hsd3b3
NM_001161742
10500555
Plscr2
Pdk4
NM_008880
NM_013743
10587799
10543017
Ces3
Hsd3b2
NM_053200
NM_153193
10580635
10500547
Tdpoz3
NM_207271
10494003
zinc finger protein 442
tsukushin
retinol dehydrogenase 18
progestin and adipoQ receptor family
member VII
angiopoietin-like 4
cytochrome P450, family 4, subfamily b,
polypeptide 1
hydroxy-delta-5-steroid dehydrogenase, 3
beta- and steroid delta-isomerase 3
1.754461
1.800799
1.873362
1.893568
0.002914242
0.007461095
0.000298723
0.004408808
1.903085
1.90774
0.003396102
0.000298723
2.002854
0.000766519
phospholipid scramblase 2
pyruvate dehydrogenase kinase,
isoenzyme 4
carboxylesterase 3
hydroxy-delta-5-steroid dehydrogenase, 3
beta- and steroid delta-isomerase 2
TD and POZ domain containing 3
2.084744
2.109608
8.88E-06
0.000387017
2.14211
2.201288
0.002719474
0.000362313
3.363323
2.60E-05
71
We used quantitative real-time RT-PCR (qRT-PCR) to confirm microarray data. In order to
determine if folate deficiency and MTHFR deficiency could contribute to gene regulation, we
used a total of 16 mice in 4 groups (4 mice per group); the groups were Mthfr+/+CD, Mthfr+/+
FD, Mthfr+/- CD and Mthfr+/- FD. These animals had not been used in the microarray
analyses, therefore, represented biological replicates.
Effect of folate deficiency on differential gene expression
To investigate the influence of folate depletion, we performed a dietary comparison (low
folate vs. control diet) using Mthfr+/- BALB/c mice and Mthfr
+/+
BALB/c mice. Two-factor
Anova showed significant lower expression of Bcmo1 (Figure 3.3 A) in FD mice (p=0.04) for
both Mthfr genotypes. This dietary difference was larger in Mthfr
compared to Mthfr
+/-
+/+
mice (1.9 fold)
mice (1.39 fold). We also detected increased expression in Aldh1a1
gene (Figure 3.3 B) in FD mice (p= 0.021) for both Mthfr genotypes. The up-regulation of
Aldh1a1 expression is more significant in Mthfr+/- mice (1.81 fold) compared to Mthfr
+/+
mice (1.32 fold). Expression of Sprr2a was also measured, no significant expression changes
was observed (data not shown). No significant Atf3 expression changes were found using
two-factor Anova. However, using independent t-test, we found that Atf3 is down-regulated
(1.42 fold) in Mthfr+/- BALB/c mice on low folate diet (p=0.05) (Figure 3.3 C). Significant
up-regulation of Plscr2 in BALB/c mice on low folate diet was also confirmed in Mthfr+/mice (Figure 3.3 D). For Ppme1 and Trem4, we did not find a significant change in
expression between mice on different diets.
72
Effect of Mthfr deficiency on differential gene expression
To study the influence of MTHFR deficiency, we compared Mthfr+/- mice to Mthfr
+/+
mice fed CD or FD. For Bcmo1, we found significant expression changes between Mthfr
+/+
and Mthfr +/- mice (p=0.001) on CD and FD. Lower expression of Bcmo1 was associated with
Mthfr +/- genotype in BALB/c mice on CD (3.57 fold increases) and FD (2.61 fold increases).
For Aldh1a1 (Figure 3.3 B) and Sprr2a, no significant expression changes were observed
between Mthfr +/+ and Mthfr +/- mice. Up-regulation of Ppme1 in Mthfr +/- mice (p= 0.04) was
confirmed (Figure 3.3 E) in BALB/c mice on FD (1.62 fold). For Atf3, Plscr2 and Trem4, we
did not find significant changes in expression comparing Mthfr
+/+
and Mthfr
+/-
mice.
However, it is necessary to point out that we did find a borderline significant change for
Trem4 (p=0.055), by comparing Mthfr +/+ CD and Mthfr +/- FD mice (figure 3.3 F).
73
Figure 3.3 Confirmation of genes expression with qRT-PCR
A. Bcmo1 mRNA levels in normal intestine of BALB/c Mthfr +/+ and +/- mice on control diet
(CD) or low folate diet (FD). Values are the mean ± SEM of 4 mice per group. *P< 0.05,
significant dietary effect in Balb/c mice (two-factor ANOVA). Means with a “&” indicate a
significant difference between Mthfr genotype; P< 0.05 (two-factor ANOVA). B. Effect of
diet and Mthfr genotype on Aldh1a1 expression in BALB/c mice. *P< 0.05, diet effect (twofactor ANOVA). C. Effect of diet and Mthfr genotype on Atf3 expression in BALB/c mice.
No significant dietary or genotype effect (two-factor anova). *P< 0.05, dietary effect in
Mthfr+/- mice (independent t-test). D. Effect of diet and genotype on expression of Plscr2 in
BALB/c mice. Significant dietary and genotype interaction (p=0.03, two-factor anova). *P<
0.05, dietary effect in Mthfr+/- mice according to Post-hoc analysis (Tukey HSD). E. Effect of
diet and genotype on expression of Ppme1 in BALB/c mice. Significant dietary and genotype
interaction (P=0.09, two-factor Anova) was found. #P< 0.05, genotype effect in mice on FD
according to Post-hoc analysis (Tukey HSD). F. Effect of diet and genotype on expression of
Trem4. No significant dietary or genotype effect (two-factor anova). Borderline significance
(P=0.055, independent t-test) between Mthfr+/- BALB/c mice fed FD and Mthfr+/+ BALB/c
mice fed CD.
74
A. Bcmo1
D. Plscr2
B. Aldh1a1
C. Atf3
E. Ppme1
F. trem4
75
Differential DNA methylation in normal intestine
Insufficient folate supply and MTHFR defects can lower the availability of 5-methylTHF,
a crucial molecule required for the synthesis of S-adenosylmethionine and methylation
reactions. To investigate whether the change of Bcmo1 expression could be related to
genomic DNA methylation, we measured Bcmo1 DNA methylation level in a total of 24
BALB/c mice. The groups were Mthfr+/+ CD, Mthfr+/+ FD, Mthfr+/- CD and Mthfr+/- FD (6
mice per group). Methylation levels of 6 CpG sites in Bcmo1 were measured using
pyrosequencing (Figure 3.4). We observed significant methylation changes between FD and
CD mice at CpG 1 (p=0.001) and CpG 4 (p=0.021). For both CpG sites, the methylation level
of mice fed FD was higher compared to mice fed CD. All 6 CpG sites showed significant
methylation changes between Mthfr+/+ and Mthfr+/- mice. CpG 1 and 4 had higher DNA
methylation levels for Mthfr+/- mice compared to Mthfr+/+ mice fed FD and CD. For CpG 2,
3, 5 and 6, significant methylation changes between Mthfr genotype were present only in
mice fed CD.
76
Figure 3.4 Bcmo1 methylation levels in normal intestine for Mthfr+/+ or Mthfr+/- BALB/c
mice, fed FD or CD. Pyrosequencing was used to test 6 CpG dinucleotides in Bcmo1 CpG
island. They are part of the UCSC mm9 chr8:119619563-119619649 DNA segment. Values
are means ± SEM for 6 animals per group. Effect of diet on Bcmo1 methylation for Mthfr+/+
mice. “*” indicates a significant methylation change between diets; “#” indicates a significant
methylation change between Mthfr genotypes. Significant diet and Mthfr genotype effect P<
0.05 for CpG1 and 4 (two-factor Anova). Significant Mthfr genotype effect P< 0.05 for CpG
2, 3, 5 and 6 in mice fed CD (Mann-Whitney test).
77
Discussion
Poor nutrition contributes to increased risk of multiple types of cancer. The association of
folate deficiency and increased colorectal cancer risk has been observed in human (8). In
addition, it has been shown that Mthfr polymorphism can modify the risk for colorectal
cancer depending on the level of intracellular folate molecules (108). However, the
interaction between folate and Mthfr deficiency and their implication on tumor development
merit further investigations. In this study, we used microarray experiments to identify gene
differences between Mthfr+/- FD and Mthfr
+/+
BALB/c mice fed with FD and CD
respectively. Using qRT-PCR, we confirmed significant changes in 6 genes that may promote
increased tumor incidence in Mthfr+/- mice on low folate diet.
Previously, we found down-regulation of Bcmo1 expression and lower level of BCDO1,
protein encoded by Bcmo1, in BALB/c mice compared to C57 strain. BCDO1 is an essential
enzyme responsible for processing beta-carotene into retinaldehyde. It has been shown that
retinaldehyde can bind to RXR ligand binding domains and prevent its activation (92). In this
study, we detected significant difference in Bcmo1 expression between diet and Mthfr
genotype. The high Bcmo1 expression observed in Mthfr
+/+
mice and in mice fed CD could
result in increases in retinaldehyde levels and RXR inhibition (Figure 3.3 A). This may affect
PPARα/RXR complex formation and reduce inflammation response. We also found
significant DNA methylation changes at 6 CpG sites for Bcmo1 gene (Figure 3.4). We found
two CpG sites with significant higher methylation levels in mice fed FD compared to mice
fed CD. This observation is consistent with a lower Bcmo1 expression level observed in
BALB/c mice fed FD. For all 6 CpG sites, we detected significantly higher DNA methylation
in Mthfr
+/-
mice compared to Mthfr
+/+
mice. This observation is consistent with a lower
Bcmo1 expression level observed in Mthfr +/- mice.
78
Retinaldehyde is a precursor for retinoic acid. The conversion of retinaldehyde to retinoic
acid is carried out by products of aldehyde dehydrogenase (ALDH) gene family. According
to microarray data, only Aldh1a1 showed a significant expression change (1.4 fold). In mice,
Aldh1a1 deficiency is associated with increased retinaldehyde levels and reduced retinoic
acid levels (95). The high Aldh1a1 expression in mice fed FD implies that conversion of
retinaldehyde to retinoic acid is faster in folate deficient mice (Figure 3.3 B). This
observation, coupled with the down-regulation of Bcmo1 in Mthfr
+/-
mice and mice fed with
FD suggests a lower retinaldehyde level in these mice. No significant effects of folate or
Mthfr were observed in BALB/c mice for Aldh1a1 methylation (data not shown).
Activating transcription factor3 (Atf3) is a transcription factor involved in the regulation of
several genes involved in cell growth including maspin, PAI-1, MTA-1 and B-catenin (109).
ATF3 can be activated by drugs with anti-inflammatory activity (110, 111). In addition, it has
been shown that ATF3 expression is lower in human colorectal cancer cells compared to
normal tissue that is close to tumor tissue (112). These findings suggest ATF3 may act as a
tumor suppressor through regulation of cell proliferation. We observed a lower expression of
Atf3 in mice fed FD (Figure 3.3 C). This observation is consistent with higher tumor
incidence observed in BALB/c mice fed FD. The down-regulation of Atf3 is more obvious in
Mthfr
+/-
mice. It is possible that the expression pattern of Atf3 is more disrupted with a
defective Mthfr allele.
Phospholipid scramblase overexpression is frequently observed in human colorectal
cancer (113); this molecule contributes to tumor development through regulation of genes
involved in cell proliferation and apoptosis (114). In this study, we observed a higher
expression of Plscr2 in Mthfr
+/-
mice on low folate diet (Figure 3.3 D). This observation is
consistent with higher tumor incidence observed in BALB/c mice fed FD. There are no
significant expression changes in Mthfr
+/+
mice on low folate diet. This implies that the
79
alteration of Plscr2 expression is mainly caused by Mthfr deficiency.
Protein phosphatase 2A is an important tumor suppressor gene involved in the inactivation
of ERK, PI3K-Akt pathway involved in cell survival and proliferation (115). Inhibition or
reducing PP2A could lead to increased cell proliferation and tumor transformation (116).
Protein phosphatase methylesterase 1 (PPME1) can inhibit PP2A mediated through
demethylation of PP2A protein (117). We showed that higher expression of Ppme1 is
associated with Mthfr +/- genotype in mice on low folate diet. This is consistent with a higher
cancer risk observed in Mthfr
+/-
mice. It may be that the effects of Mthfr genotype become
apparent when folate level is low.
PDC-TREM, also known as TREM4, is believed to be involved autoimmune response
through recognition of aberrant DNA (118). There is an increasing body of evidence
suggesting that TREM receptors are involved in inflammation-triggered diseases (119).
Although we did not detect significant expression changes between diet and Mthfr genotype,
an up-regulation of Trem4 expression (p=0.055) was observed in Mthfr
compared to Mthfr
+/-
mice fed FD
+/+
mice fed CD. We suggest that folate and MTHFR deficiency may
interact to up-regulate Trem4 expression.
In conclusion, this study presents novel data supporting the role of retinoid pathway and
identifies new modifier genes affecting tumor growth in BALB/c mice. This study also shows
the importance of folate and MTHFR enzyme in the initiation of cancer development.
80
3.6 ACKNOWLEDGMENTS
We would like to thank Dr. Daniel Leclerc for performing pyrosequencing experiments
and for designing qRT-PCR primers for Atf3, Plscr2, Ppme1 and Trem4. We would like to
acknowledge LiYuan Deng for her technical assistance.
81
Chapter IV
General Discussion & Conclusions
82
4.1 The effects of mouse strain, low dietary folate, and MTHFR deficiency
on intestinal adenoma incidence and tumor progression
In Chapters II and III, we identified several genes involved in intestinal tumor initiation.
One of the most notable findings was to confirm the disruption of retinoid pathway in
preneoplastic intestine tissues. Inflammation and oxidative stress mediated by PPARα/RXR
complex were identified as a potential mechanism for the initiation of cancer development in
BALB/c mice. In addition, alteration of oncogenes and tumor suppressor genes were
observed in mouse groups with lower cancer susceptibility, which is consistent with previous
findings. Furthermore, we showed that DNA methylation level is affected by folate intake
and changes in folate processing enzymes. Finally, it was shown that changes of mRNA
expression are generally consistent with DNA methylation changes induced by folate and
MTHFR deficiency, with the exception of Pparα.
4.2 Retinoid pathway
Retinoids are essential molecules involved in the regulation of cell growth, differentiation,
and apoptosis (92). Retinoic acid, the active form of retinoid, regulates gene expression
through retinoic acid receptor and retinoid X receptor (RAR/RXR) heterodimer. In addition,
RXR can interact with other nuclear receptors like PPARα and PPAR γ. Retinoid can not be
synthesized directly in humans; all retinoids are converted from dietary carotenoids
molecules (beta-carotene, alpha-carotene, gamma-carotene, and beta-cryptoxanthin) (120).
Beta-carotene is the major provitamin A carotenoid and can be cleaved by BCDO1 and
BCDO2 into retinoic acid precursors. We did not detect significant expression changes for
Bcdo2 gene in both microarrays experiment. For BCDO1, we confirmed significant changes
at mRNA and protein level between BALB/c and C57Bl/6 mice fed FD. In addition, we
83
showed methylation pattern of Bcmo1 gene is consistent with BCDO1 level. Low level of
Bcmo1 gene expression is associated with BALB/c mouse strain and low folate diet. It is
interesting to note that a higher tumor incidence is also observed in BALB/c mice fed FD. A
recent human GWAS study showed polymorphisms in BCDO1 affecting the beta-carotene
conversion efficiency can lead to vitamin A deficiency in women (121). Retinaldehyde is a
retinoic acid precursor generated by BCDO1. It can bind weakly to the ligand binding site of
RXR and PPARα and prevent their activation. Retinaldehyde dehydrogenases are responsible
for processing retinaldehyde into retinoic acid. Defects in retinaldehyde dehydrogenases may
lead to retinoic acid deficiency and accumulation of retinaldehyde. Indeed, studies done in
mice showed that low expression of Alde1a1 is associated with accumulation of
retinaldehyde (94, 95). We showed a high level of Bcmo1 and low level of Aldh1a1 in
C57Bl/6 mice on low folate diet. This suggested the level of retinaldehyde is high in C57Bl/6
mice. A high level of retinaldehyde can lead to inactivation of RAR or RXR and prevent
activation of genes that are regulated by heterodimers like PPARα/RXR.
4.3 PPARα related inflammatory response and oxidative stress
According to IPA analysis, lipid metabolism is classified as the top pathway with the
highest number of differentially expressed gene between BALB/c and C57Bl/6 mice fed FD.
Human colorectal cancer microarray analysis also suggests that lipid metabolism pathway
plays a crucial role in cancer development (122). We found several genes with significant
expression differences were downstream of PPARα. PPARα is a nuclear hormone receptor
involved in inflammation, lipid metabolism, and catabolic reaction (123). It can form a
heterodimer with RXR and binds to peroxisome proliferator response element (PPRE) to
activate transcription of specific genes. We found 6 genes downstream of PPARα with
84
increased expression in BALB/c mice. Increase of Acot1 enhances PPARα-mediated response
through the regulation of ligand supply. Activated PPARα can activate Cd36, an important
protein involved in the accumulation of linoleic acid and Cyp4a activation. Accumulation of
linoleic acid and Cyp4a10 up-regulation contributes to ROS generation and increased DNA
damage. Similar expression changes for Acot1, Cd36 and Cyp4a10 were found in microarray
experiments focusing on genes regulated by PPARα in mouse and human studies (124, 125).
AQP3 is a water channel protein. Over expression of Aqp3 can lead to increased permeability
of the epithelial cell layer, and cell damage. In addition, increase of Aqp3 contributes to faster
epithelial cell proliferation and increases skin cancer susceptibility. It has been shown that the
effect mediated by Aqp3 was greatly reduced in Pparα knock out mice (126). Activation of
Hmgcs2 and Me1 by Pparα up-regulation was also confirmed by other microarray
experiments (127). In this study, up-regulation of Pparα in BALB/c mice was observed at the
mRNA level only. The up-regulation of Pparα downstream genes in BALB/c mice can be
explained by impaired PPARα/ RXR heterodimerization caused by altered Bcmo1 and
Aldh1a1 expression. Pparα methylation level is higher in BALB/c mice; this is inconsistent
with mRNA changes. It is possible that Pparα CpG sites we measured are not involved in
gene expression.
85
4.4 Cell growth and apoptosis
Uncontrolled cell growth and disrupted apoptosis are important events in tumor
development. Previous colorectal cancer studies using the Mthfr deficient mouse model
showed significant changes of genes involved in cell cycle control and apoptosis between
tumor and normal tissues. In this study, we identified several genes involved in cell
proliferation and apoptosis expressed differently in preneoplastic tissues between mouse
strains (BALB/c and C57Bl/6), diet (FD and CD) and genotype (Mthfr+/- and Mthfr+/+).
We found four genes with tumor suppressor properties (Sprr2a, Arntl, Bmp5 and Tgfbi)
were regulated in BALB/c mice compared to C57Bl/6 mice. Bmp5 plays an important role in
cell differentiation and apoptosis and decreased Bmp5 expression is often associated with
uncontrolled cell proliferation. Epigenetic inactivation of Bmp5 gene is a common event
observed in lung cancer (105). Higher Bmp5 DNA methylation level was observed in
BALB/c mice compared to C57Bl/6 mice. This is consistent with lower Bmp5 expression in
BALB/c mice. Arntl and Tgfbi are both involved in apoptosis and cell-cycle control through
regulation of cyclin (102, 103). Down-regulation of these genes could lead to increased cell
proliferation. A recent study using mouse and human cell lines showed that Sprr2a may
increase resistance against oxidative stress (104). BALB/c mice may be more sensitive to
oxidative stress induced DNA damage due to low Sprr2a expression. These observations
suggest that down regulation of tumor suppressor genes in BALB/c mice may contribute to
tumor susceptibility in BALB/c mice.
Folate and MTHFR deficiency are both considered as risk factors for colorectal cancer.
Significant dietary effects were observed in Atf3 and Plscr2; significant genotype effects
were observed in Ppme1. Plscr2, a phospholipid scramblase involved in cell growth and
apoptosis, was up-regulated in the mouse group (Mthfr+/-, BALB/c mice fed FD) with highest
86
tumor susceptibility. A similar observation was found in a human colorectal cancer study,
where PLSCR1, another member of phospholipid scramblase family, was overexpressed in
patients at an early stage of colorectal cancer compared to healthy individuals (128). This is
consistent with observations in BALB/c mice. Atf3, a transcription factor activated by
different stress responses, plays a key role in the activation of genes involved in cell growth
(109). Atf3 can enhance p53 mediated effect by blocking p53 degradation (129) suggesting
that Atf3 may act as a tumor suppressor by contributing to the maintenance of the integrity of
the genome. No significant dietary effects were detected in Mthfr +/+ BALB/c mice for Plscr2
and Atf3. In this case, the effect of folate depletion may be compensated by a higher MTHFR
enzyme activity. Ppme1 played a crucial role in maintaining ERK pathway through inhibition
of PP2A. This allows activation of different signalling pathways involved in cell proliferation
and survival. Ppme1 activation is correlated with astrocytic glioma progression in humans
(130). Significant up-regulation of Ppme1 in Mthfr +/- mice was observed in BALB/c mice
fed FD. It is possible that effects of MTHFR deficiency become significant under folate
deficiency. There are increasing studies suggesting that Trem4 is involved in the innate
immune response and inflammatory responses. An increase of Trem4 expression was
observed in Mthfr +/- mice on FD with borderline significance (p=0.055) compared to Mthfr
+/+
mice on CD. Since we had only 4 mice in each group for qRT-PCR confirmation, genes
with subtle expression changes may be difficult to confirm. Further experiments with larger
sample numbers may provide more accurate data on gene expression changes.
87
4.5 Future Directions
Different approaches can be taken to validate the role of genes and methylation changes
identified in chapters II and III. Small interfering RNA and cell transfections can be used to
study the effect of Bcmo1 deficiency. Another approach would be to use mutagenesis and
introduce mutations in Bcmo1 gene to reduce its enzyme activity or a plasmid-based
approach can be used to over express Bcmo1. By inhibiting Bcmo1 in normal cell lines or
over-expressing Bcmo1 in preneoplastic and adenomas cell lines, it would allow for better
understanding of the role of Bcmo1 in tumor development. Similar approaches can be used to
study other candidate genes confirmed in chapters II and III. As BCDO1 is essential for
retinoic acid synthesis, it would be worthwhile to assess the effect of retinoic acid depletion
on intestinal tumor growth. Retinaldehyde plays an important role in the inhibition of
RXR/PPAR complex. Although several studies have shown that high intracellular
retinaldehyde level are associated with reduced RXR/PPARγ mediated responses, there are
few studies showing that retinaldehyde can inhibit RXR/PPARα formation. Repressing
retinaldehyde dehydrogenase genes in mouse intestinal epithelial cell lines can be done to
assess the effect of increased retinaldehyde levels on RXR/PPARα mediated responses.
Intestinal epithelial cell lines from BALB/c and C57Bl/6 mice can be used to test the effects
of folate depletion on DNA methylation changes. These approaches can also be done using
human intestinal cell lines with Mthfr polymorphism and folate deficiency to provide further
information on the initiation of colorectal cancer.
88
4.6 Conclusions
It is well known that folate depletion is associated with increased risk of colorectal cancer
in humans. Several studies have shown that disruptions in folate metabolism can lead to
increased DNA damage and altered DNA methylation patterns. A large number of genes have
been identified that are differentially expressed between intestinal tumor tissues and normal
tissues. However, few studies have been done to identify genes responsible for the initiation
of tumor development in preneoplastic intestine tissue. This thesis identified genes
potentially responsible for the susceptibility of BALB/c mice to intestinal cancer. In addition,
it showed that deficiency in folate intake and MTHFR can lead to increased colorectal cancer
risk. Methylation differences between different mouse strains and different folate intake have
been confirmed for several of these genes suggesting that gene-specific methylation changes
can affect susceptibility to tumorigenesis. This thesis also reported that disruption of retinoid
pathway may be implicated in intestinal tumorigenesis. More studies should be done to
confirm the role of Bcmo1 in the initiation of cancer development.
89
REFERENCES
1. Krishnaswamy K, Madhavan, Nair K. Importance of folate in human nutrition. Br J
Nutr. May;85 Suppl 2:S115-24. (2001)
2. Frosst P, Blom H.J, Milos R, Goyette P, Sheppard C.A., Matthews R.G., Boers,
G.J.H., den Heijer, M., Kluijtmans, L.A.J. & Rozen, R. A candidate genetic risk
factor for vascular disease: a common mutation in methylenetetrahydrofolate
reductase. Nature Genetics Letters, 10, 111-113. (1995)
3. Loenen WA. Biochem Soc Trans. S-adenosylmethionine: jack of all trades and master
of everything? Apr; 34(Pt 2):330-3. (2006)
4. Lindenbaum J, Allen RH. Clinical spectrum and diagnosis of folate deficiency. In:
Bailey L, ed. Folate in health and disease. Marcel Deker, NewYork: 43-74 (1995)
5. Kang SS, Wong PW, Norusis M. Homocysteinemia due to folate deficiency.
Metabolism 36:458-462. (1987)
6. Pasterkamp G, Algra A, Grobbee DE, de Jaegere PP, Banga JD, van der Graaf Y.
Homocysteine and the stage of atherosclerotic disease: a study in patients suffering
from clinically silent and clinically manifest atherosclerotic disease. Eur J Clin Invest.
May;32(5):309-15. (2002)
7. Eskes TKAB. From anaemia to spinal bifida-the story of folic acid. A tribute to
Professor Richard Smithells. Euro J Obstet Gynecol Reprod Biol 90:119-123. (2000)
8. Giovannuci E, Rimm EB, Ascherio A et al. Alcohol, low-methionine-low-folate diets,
and risk of colon cancer in men. J Natl Cancer Inst 87 (4): 265-73. (1995)
9. Mason J. Folate status: effect on carcinogenesis. In: Bailey L, ed. Folate in health and
disease. Marcel Dekker, New York: 361-378. (1995)
10. Baron JA, Sandler RS, Haile RW et al. Folate intake, alcohol consumption, cigarette
smoking, and risk of colorectal adenomas. J Natl Cancer Inst. Jan 7;90(1):57-62.
(1998)
11. James SJ, Basnakian AG, Miller BJ. In vitro folate deficiency induces
deoxynucleotide pool imbalance, apoptosis, and mutagenesis in Chinese hamster
ovary cells. Cancer Res 1994: 54:5075-5080. (1994)
12. Melnyk S, Pogribna M, Miller BJ et al. Uracil misincorporation, DNA strand breaks
and gene amplification are associated with tumorigenic cell transformation in folate
deficient/repleted Chinese hamster ovary cells. Cancer Lett 146:35-44. (1999)
90
13. Pogribny IP, Miller BJ, James SJ et al. Alterations in hepatic p53 gene methylation
patterns during tumor progression with folate/methyl deficiency in the rat. Cancer
Lett 115:31-38. (1997)
14. Duthie SJ, Narayanan S, Blum S et al. Folate deficiency in vitro induces uracil
misincoporation and DNA hypomethylation and inhibits DNA excision repair in
immortalized normal human colon epithelial cells. Nutr Cancer 37(2): 245-251.
(2000)
15. Dianov GL, Timchenko TV, Sinitsina OI et al. Repair of uracil residues closely
spaced on the opposite strands of plasmid DNA results in double-strand break and
deletion formation. Mol Gen Genet 225(3):448-452. (1991)
16. Reidy JA. Folate-and deoxyuridine-sensitive chromatid breakage may result from
DNA repair during G2. Mutat Res 192:217-219. (1987)
17. Knock E, Deng L, Wu Q, Leclerc D, Wang XL, Rozen R. Low dietary folate initiates
Intestinal Tumors in Mice, with altered expression of G2-M Checkpoint Regulators
Polo-Like Kinase 1and cell division cycle 25c. Cancer Res 66: (21). (2006)
18. Knock E, Deng L, Wu Q, Lawrance AK, Wang XL, Rozen R. Strain differences in
mice highlight the role of DNA damage in Neoplasia induced by low dietary folate. J
Nutr 138: 653-658. (2008)
19. Hagmar L, Bonassi S. Stromberg U et al. Chromosomal aberrations in lymphocytes
predict human cancer : A report from the European Study Group on Cytogenetic
Biomarkers and Health (ESCH). Cancer Res 58:4117-4121. (1998)
20. Moynahan ME, Jasin M. Loss of heterozygosity induced by a double-strand break.
Proc Natl Acad Sci 94:8988-8993. (1997)
21. Mitelman F. Recurrent chromosome aberrations in cancer. Mutat Res 462:247-253.
(2000)
22. Elliot B, Jasin M. Human Genome and Diseases: Review. Double-strand breaks and
translocations in cancer. Cell Mol Life Sco 59:373-385. (2002)
23. Jacob RA, Gretz DM, Taylor PC et al. Moderate folate depletion increases plasma
homocysteine and decreases lymphocyte DNA methylation in postmenopausal
women. J Nutr 128:1204-1212. (1998)
24. Pogribny IP, Basnakian AG, Miller BJ et al. Breaks in genomic DNA and within the
p53 gene are associated with hypomethylation in livers of folate/ methyl-deficient
rats. Cancer Res 55:1894-1901. (1995)
25. Laird PW, Jaenisch R. DNA methylation and cancer. Hum Mol Genet 3:1487-1495.
91
(1994)
26. Guttenbach M, Schmid M. Exclusion of specific human chromosomes into
micronuclei my 5-azacytidine treatment of lymphocyte cultures. Exp Cell Res
211:127-132. (1994)
27. Pogribny I, James SJ. Reduction of p53 gene expression in human primary
hepatocellular carcinoma is associated with promoter region methylation without
coding region mutation. Cancer Letters 176:169-174. (2002)
28. Deng G, Peng E, Terdiman J et al. Methylation of hMLH1 promoter correlates with
the gene silencing with a region –specific manner in colorectal cancer. Br J cancer 86:
574-579. (2002)
29. Goyette P, Sumner JS, Milos R et al. Human methylenetetrahydrofolate reductase:
isolation of cDNA, mapping and mutation identification. Nat. Genet. 7, 195-200
(1994).
30. Ueland PM, Hustad S, Schneede J, Refsum H, Vollset SE: Biological and clinical
implications of the MTHFR C677T polymorphism. Trends Pharmacol. Sci. 22, 195201 (2001).
31. Bailey LB: Folate, methyl-related nutrients, alcohol, and the MTHFR 677C>T
polymorphism affect cancer risk: intake recommendations. J. Nutr. 133, 3748S-3753S
(2003).
32. Guenther BD, Sheppard CA, Tran P, Rozen R, Matthews RG, Ludwig ML: The
structure and properties of methylenetetrahydrofolate reductase from Escherichia coli
suggest how folate ameliorates human hyperhomocysteinemia. Nat. Struct. Biol. 6,
359-365 (1999).
33. Yamada K, Chen Z, Rozen R, Matthews RG: Effects of common polymorphisms on
the properties of recombinant human methylenetetrahydrofolate reductase. Proc. Natl
Acad. Sci. USA 98, 14853-14858 (2001).
34. Jacques PF, Bostom AG, Williams RR et al. Relation between folate status, a common
mutation in methylenetetrahydrofolate reductase, and plasma homocysteine
concentrations. Circulation 93, 7-9 (1996).
35. McNulty H, McKinley MC, Wilson B et al. Impaired functioning of thermolabile
methylenetetrahydrofolate reductase is dependent on riboflavin status: implications
for riboflavin requirements. Am. J. Clin. Nutr. 76, 436-441 (2002).
36. van der Put NM, Gabreels F, Stevens EM et al. A second common mutation in the
methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube
defects? Am. J. Hum. Genet. 62, 1044-1051 (1998).
92
37. Weisberg I, Tran P, Christensen B, Sibani S, Rozen R. A second genetic
polymorphism in methylenetetrahydrofolate reductase (MTHFR ) associated with
decreased enzyme activity. Mol. Genet. Metab. 64, 169-172 (1998).
38. Friedman G, Goldschmidt N, Friedlander Y et al. A common mutation A1298C in
human methylenetetrahydrofolate reductase gene: association with plasma total
homocysteine and folate concentrations. J. Nutr. 129, 1656-1661 (1999).
39. Lievers KJ, Boers GH, Verhoef P et al. A second common variant in the
methylenetetrahydrofolate reductase ( MTHFR ) gene and its relationship to MTHFR
enzyme activity, homocysteine, and cardiovascular disease risk. J. Mol. Med. 79, 522528 (2001).
40. Ueland PM, Hustad S, Schneede J, Refsum H, Vollset SE: Biological and clinical
implications of the MTHFR C677T polymorphism. Trends Pharmacol. Sci. 22, 195201 (2001).
41. Robien K, Ulrich CM: 5,10-methylenetetra-hydrofolate reductase polymorphisms and
leukemia risk: a HuGE minireview. Am. J. Epidemiol. 157, 571-582 (2003).
42. Sharp L, Little J: Polymorphisms in genes involved in folate metabolism and
colorectal neoplasia: a HuGE review. Am. J. Epidemiol. 159, 423-443 (2004).
43. Kim YI: 5,10-methylenetetrahydrofolate reductase polymorphisms and
pharmacogenetics: a new role of single nucleotide polymorphisms in the folate
metabolic pathway in human health and disease. Nutr. Rev. 63, 398-407 (2005).
44. Kim YI: Methylenetetrahydrofolate reductase polymorphisms, folate, and cancer risk:
a paradigm of gene-nutrient interactions in carcinogenesis. Nutr. Rev. 58, 205-209
(2000).
45. Ma J, Stampfer MJ, Giovannucci E, Artigas C, Hunter DJ, Fuchs C, Willett WC,
Selhub J, Hennekens CH, Rozen R. Methylenetetrahydrofolate reductase
polymorphism, dietary interactions, and risk of colorectal cancer.Cancer Res. Mar
15;57(6):1098-102. (1997)
46. Roy M, Leclerc D, Wu Q, Gupta S, Kruger WD, Rozen R.(2008)Valproic acid
increases expression of methylenetetrahydrofolate reductase (MTHFR) and induces
lower teratogenicity in MTHFR deficiency.J Cell Biochem. Oct 1;105(2):467-76.
(2008)
47. Goyette P, Sumner JS, Milos R, Duncan AM, Rosenblatt DS, Matthews RG, Rozen R.
Human methylenetetrahydrofolate reductase: isolation of cDNA, mapping and
mutation identification. Nat Genet. Jun;7(2):195-200. (1994)
93
48. Chen, Z., Karaplis, A.C., Ackerman, S.L., Pogribny, I.P., Melnyk, S., Lussier-Cacan,
S., Chen, M.F., Pai, A., John, S.W., Smith, R.S., Bottiglieri, T., Bagley, P., Selhub, J.,
Rudnicki, M.A., James, S.J. & Rozen, R. Mice deficient in methylenetetrahydrofolate
reductase exhibit hyperhomocysteinemia and decreased methylation capacity, with
neuropathology and aortic lipid deposition. Hum Mol Genet, 10, 433-443. (2001)
49. Pickell L, Li D, Brown K, Mikael LG, Wang XL, Wu Q, Luo L, Jerome-Majewska L,
Rozen R. Methylenetetrahydrofolate reductase deficiency and low dietary folate
increase embryonic delay and placental abnormalities in mice. Birth Defects Res A
Clin Mol Teratol. Jun; 85(6):531-41. (2009)
50. Jemal A, Siegel R,Ward E, Hao Y, Xu J, Thun MJ. Cancer statistics. Cancer J. Clin.
58:225–49 (2009)
51. Huxley RR, Ansary-Moghaddam A, Clifton P, Czernichow S, Parr CL, Woodward M.
The impact of dietary and lifestyle risk factors on risk of colorectal cancer: a
quantitative overview of the epidemiological evidence. Int. J. Cancer 125:171–80
(2009)
52. Taylor DP, Burt RW, Williams MS, Haug PJ, Cannon-Albright LA. Population-based
family history–specific risks for colorectal cancer: a constellation approach.
Gastroenterology 138:877–85. (2010)
53. Segditsas S, Tomlinson I. Colorectal cancer and genetic alterations in theWnt
pathway. Oncogene25:7531–37. (2006)
54. Giovannucci E. Modifiable risk factors for colon cancer. Gastroenterol Clin North
Am, 31, 925–43. (2002)
55. Jass JR. Classification of colorectal cancer based on correlation of clinical,
morphological and molecular features. Hisopathology 50:113–30. (2007)
56. Winawer SJ, Zauber AG, Ho MN, O’Brien MJ, Gottlieb LS, et al. Prevention of
colorectal cancer by colonoscopic polypectomy. The National Polyp Study
Workgroup. N. Engl. J. Med. 329:1977–81. (1993)
57. Lynch HT, de la Chapelle A. Hereditary colorectal cancer. N. Engl. J. Med. 348:919–
32. (2003)
58. Rustgi AK. The genetics of hereditary colon cancer. Genes Dev. 21:2525–38. (2007)
59. Polakis P. The many ways of Wnt in cancer. Curr. Opin. Genet. Dev. 17:45–51.
(2007)
60. Brocardo M, Henderson S. APC shuttling to the membrane, nucleus, and beyond.
Trends Cell Biol.18:587–96. (2009)
94
61. Aoki K, Taketo MM. Adenomatous polyposis coli (APC): a multi-functional tumor
suppressor gene. J. Cell Sci. 120:3327–35. (2007)
62. Mosimann C, Hausmann G, Basler K. β-catenin hits chromatin: regulation of Wnt
target gene activation. Nat. Rev. Mol. Cell Biol. 10:276–86 (2009)
63. Moser AR, Pitot HC, Dove WF. A dominant mutation that predisposes to multiple
intestinal neoplasia in the mouse. Science 247: 322-324. (1990)
64. Levy DB, Smith KJ, Beazer-Barclay Y, Hamilton SR, Vogelstein B and Kinzler KW.
Inactivation of both APC alleles in human and mouse tumors. Cancer Res 54: 5953–
5958. (1994)
65. Thibodeau SN, BrenG, Schaid D. Microsatellite instability in cancer of the proximal
colon. Science260:816–19. (1993)
66. Ionov Y, Peinado MA, Malkhosyan S, Shibata D, Perucho M. Ubiquitous somatic
mutations in simple repeated sequences reveals a new mechanism for colonic
carcinogenesis. Nature 363:558–61. (1993)
67. Parsons R, LiGM, Longley MJ, FangWH, Papadopoulos N, et al. Hyper mutability
and mismatch repair deficiency in RER+ tumor cells. Cell 75:1227–36. (1993)
68. Vilar E, Gruber SB. Microsatellite instability in colorectal cancer—the stable
evidence. Nat. Rev.Clin. Oncol. 7:153–62. (2010)
69. Abdel-Rahman WM, Peltom¨aki P. Lynch syndrome and related familial colorectal
cancers. Crit.Rev. Oncog. 14:1–22. (2008)
70. Malumbres M, Barbacid M. RAS oncogenes: the first 30 years. Nat. Rev. Cancer
3:459–65. (2003)
71. Vogelstein B, Fearon ER, Hamilton SR, Kern SE, Preisinger AC, et al. Genetic
alterations during colorectal-tumor development. N. Engl. J. Med. 319:525–32.
(1988)
72. Rajagopalan H, Bardelli A, Lengauer C, Kinzler KW, Vogelstein B, Velculescu VE.
Tumorigenesis: RAF/RAS oncogenes and mismatch-repair status. Nature 418:934.
(2002)
73. Samuels Y, Wang Z, Bardelli A, Silliman N, Ptak J, et al. High frequency of mutations
of thePIK3CA gene in human cancers. Science 304:554. (2004)
74. Baker SJ, Preisinger AC, Jessup JM, Paraskeva C, Markowitz S, et al. p53 gene
mutations occur in combination with 17p allelic deletions as late events in colorectal
95
75. Botteri E, Iodice S, Bagnardi V, Raimondi S, Lowenfels AB, Maisonneuve P.
Smoking and colorectal cancer: a meta-analysis. JAMA2008;300:2765–78. (2008)
76. Liang PS, Chen TY, Giovannucci E. Cigarette smoking and colorectal cancer
incidence and mortality: systematic review and meta-analysis. Int J Cancer
2009;124:2406–15. (2009)
77. Zisman AL, Nickolov A, Brand RE, Gorchow A, Roy HK. Associations between the
age at diagnosis and location of colorectal cancer and the use of alcohol and tobacco:
implications for screening. Arch Intern Med. 2006 Mar 27;166(6):629-34. (2006)
78. Seitz HK, Matsuzaki S, Yokoyama A, Homann N, Väkeväinen S, Wang XD. 2001
Alcohol and cancer. Alcohol Clin Exp Res. May;25 (5 Suppl ISBRA):137S-143S.
(2001)
79. Homann N, Tillonen J, Salaspuro M, Microbially produced acetaldehyde from
ethanol may increase the risk of colon cancer via folate deficiency. Int J Cancer 2000;
86(2): 169-73. (2000)
80. Choi SW, Stickel F, Baik HW et al. Chronic alcohol consumption induces genomic
but not p53-specific DNA hypomethylation in rat colon. J Nutr 129 (11): 1945-50.
(1999)
81. Sibani S, Melnyk S, Pogribny IP, et al. Studies of methionine cycle intermediates
(SAM, SAH), DNA methylation, and the impact of folate deficiency on tumor
numbers in Apc min/+ mice. Carcinogenesis 23:61–5. (2002)
82. Garcia-Crespo D, Knock E, Jabado N, Rozen R. Intestinal neoplasia induced by low
dietary folate is associated with altered tumor expression profiles and decreased
apoptosis in mouse normal intestine. J Nutr 139: 488-494. (2009)
83. Kim YI Folate and DNA methylation: a mechanistic link between folate deficiency
and colorectal cancer? Cancer Epidemiol Biomarkers Prev. Apr;13(4):511-9. (2004)
84. Knock E, Deng L, Krupenko N, Mohan RD, Wu Q, Leclerc D, Gupta S, Elmore CL,
Kruger W, Tini M, Rozen R. Susceptibility to intestinal tumorigenesis in folatedeficient mice may be influenced by variation in one-carbon metabolism and DNA
repair. J Nutr Biochem Nov;22(11):1022-9. (2011)
85. Toprak NU, Yagci A, Gulluoglu BM, Akin ML, Demirkalem P, et al. A possible role
of Bacteroides fragilis enterotoxin in the aetiology of colorectal cancer. Clin
Microbiol Infect 12: 782–786. (2006)
86. Wang X, Allen TD, May RJ, Lightfoot S, Houchen CW, et al. Enterococcus faecalis
96
induces aneuploidy and tetraploidy in colonic epithelial cells through a bystander
effect. Cancer Res 68: 9909–9917. (2008)
87. Cuevas-Ramos G, Petit CR, Marcq I, Boury M, Oswald E, et al. Escherichia coli
induces DNA damage in vivo and triggers genomic instability in mammalian cells.
Proc Natl Acad Sci U S A 107: 11537–11542. (2010)
88. Blazejczyk B. FlexArray: Statistical Data Analysis Software for Gene Expression
Microarrays, Made with Life Scientists in Mind. Canadian Bioinformatics Help Desk
(CBHD) Newsletter Issue 69 - December 13. (2007)
89. Mikael LG, Wang XL, Wu Q, Jiang H, Maclean KN, Rozen R.
Hyperhomocysteinemia is associated with hyper triglyceridemia in mice with
methylenetetrahydrofolate reductase deficiency. Mol Genet Metab. Sep-Oct;98 (12):187-94. (2009)
90. Kennedy, B.P., Payette, P., Mudgett, J., Vadas, P., Pruzanski, W.Kwan, M., Tang, C.,
Rancourt, D.E., and Cromlish, W.A. A natural disruption of the secretory group II
phospholipase A2 gene in inbred mouse strains. J. Biol. Chem. 270, 22378–22385.
(1995)
91. Dietrichw, F.E. S., Lander, J.S., Smitha, R., Moserk, A., Gould et al., Genetic
identification of Mom-I, a major modifier locus affecting Min-induced intestinal
neoplasia in the mouse. Cell 75: 631-639. (1993)
92. Hessel S,Eichinger A,Isken A,Amengual J,Hunzelmann S,Hoeller U,Elste V,Hunziker
W,Goralczyk R,Oberhauser V,von Lintig J,Wyss. A CMO1 deficiency abolishes
vitamin A production from β-carotene and alters lipid metabolism in mice. J Biol
Chem 282:33553–33561. (2007)
93. Pyper SR, Viswakarma N, Yu S, Reddy JK. PPARalpha: energy combustion,
hypolipidemia, inflammation and cancer. Nucl Recept Signal. Apr 16;8:e002. (2010)
94. Ziouzenkova, Q., G. Orasanu, M. Sharlach, T. E. Akiyama, J. P.Berger, J. Viereck, J.
A. Hamilton, G. Tang, G. G. Dolnikowski,S. Vogel, G. Duester and J. Plutzky.
Retinaldehyderepresses adipogenesis and diet-induced obesity. Nat. Med.13:695-702.
(2007)
95. Molotkov A, Duester G (2003). Genetic evidence that retinaldehyde dehydrogenase
Raldh1 (Aldh1a1) functions downstream of alcohol dehydrogenase Adh1 in
metabolism of retinol to retinoic acid. J Biol Chem. Sep 19;278(38):36085-90. (2003)
96. Dongol B, Shah Y, Kim I, Gonzalez FJ, Hunt MC.The acyl-CoA thioesterase I is
regulated by PPARalpha and HNF4alpha via a distal response element in the
promoter.J Lipid Res. Aug;48(8):1781-91. (2007)
97
97. Verkman AS, Hara-Chikuma M, Papadopoulos MC. Aquaporins--new players in
cancer biology. J Mol Med. 2008 May;86(5):523-9. (2008)
98. Levin MH, Verkman AS. Aquaporin-3-dependent cell migration and proliferation
during corneal re-epithelialization. Invest Ophthalmol Vis Sci. Oct;47(10):4365-72.
(2006)
99. Okamura DM, Pennathur S, Pasichnyk K, López-Guisa JM, Collins S, Febbraio M,
Heinecke J, Eddy AA. CD36 regulates oxidative stress and inflammation in hyper
cholesterolemic CKD. J Am Soc Nephrol. Mar;20(3):495-505. (2009)
100. Camarero N, Mascaró C, Mayordomo C, Vilardell F, Haro D, Marrero PF.K
HMGCS2 Is a c-Myc target gene expressed in differentiated cells of human colonic
epithelium and down-regulated in colon cancer.Mol Cancer Res. Sep;4(9):645-53.
(2006)
101. Coleman DL, Kuzava JE.Genetic regulation of malic enzyme activity in the
mouse. J Biol Chem. Nov 15;266(32):21997-2002. (1991)
102. Zeng ZL, Wu MW, Sun J, Sun YL, Cai YC, Huang YJ, Xian LJ. Effects of the
biological clock gene Bmal1 on tumour growth and anti-cancer drug activity. J
Biochem. Sep;148(3):319-26. (2010)
103. Zhang Y, Wen G, Shao G, Wang C, Lin C, Fang H, Balajee AS, Bhagat G, Hei TK,
Zhao Y. TGFBI deficiency predisposes mice to spontaneous tumor development.
Cancer Res. Jan 1;69(1):37-44. (2009)
104. Demetris AJ, Specht S, Nozaki I, Lunz JG 3rd, Stolz DB, Murase N, Wu T. Small
proline-rich proteins (SPRR) function as SH3 domain ligands, increase resistance to
injury and are associated with epithelial-mesenchymal transition (EMT) in
cholangiocytes. J Hepatol. Feb;48(2):276-88. Epub 2007 Dec 17. (2008)
105. Kraunz KS, Nelson HH, Liu M, Wiencke JK, Kelsey KT. Interaction between the
bone morphogenetic proteins and Ras/MAP-kinase signalling pathways in lung
cancer.Br J Cancer. Oct 17;93(8):949-52. (2005)
106. Ro TB, Holt RU, Brenne AT, Hjorth-Hansen H, Waage A, Hjertner O, Sundan A,
Borset M. Bone morphogenetic protein-5, -6 and -7 inhibit growth and induce
apoptosis in human myeloma cells. Oncogene. Apr 15;23(17):3024-32. (2004)
107. Chen J, Giovannucci E, Kelsey K et al. Methylenetetrahydrofolate reductase
polymorphism and the risk of colorectal cancer. Cancer Res 56:4862-4864. (1996)
108. Ma J, Stampfer MJ, Giovannuci E et al. Methylenetetrahydrofolate reductase
polymorphism, dietary interactions and risk of colorectal cancer. Cancer Res 57:
1098-1102. (1997)
98
109. Bottone FG Jr, Moon Y, Kim JS, Alston-Mills B, Ishibashi M, Eling TE.The antiinvasive activity of cyclooxygenase inhibitors is regulated by the transcription factor
ATF3 (activating transcription factor 3).Mol Cancer Ther. May;4(5):693-703. (2005)
110. Carter TH, Liu K, Ralph W Jr, et al. Dindolylmethane alters gene expression in
human keratinocytes in vitro. J Nutr 132:3314–24. (2002)
111. Shtil AA, Mandlekar S, Yu R, et al. Differential regulation of mitogen-activated
protein kinases by microtubule-binding agents in human breast cancer cells.
Oncogene 18:377–84. (1999)
112. Bottone FG Jr, Martinez JM, Collins JB, Afshari CA, Eling TE. Gene modulation
by the cyclooxygenase inhibitor, sulindac sulfide, in human colorectal carcinoma
cells: POSSIBLE LINK TO APOPTOSIS. J Biol Chem 278:25790–801. (2003)
113. Kuo YB, Chan CC, Chang CA, Fan CW, Hung RP, Hung YS, Chen KT, Yu JS,
Chang YS, Chan EC. Identification of phospholipid scramblase 1 as a biomarker and
determination of its prognostic value for colorectal cancer. Mol Med. Jan-Feb;17(12):41-7. (2011)
114. Huang Y, Zhao Q, Chen GQ. Phospholipid scramblase 1.Sheng Li Xue Bao. Dec
25;58(6):501-510. (2006)
115. Westermarck J, Hahn WC. Multiple pathways regulated by the tumor suppressor
PP2A in transformation. Trends Mol Med 14: 152–60. (2008)
116. Chen W, Possemato R, Campbell KT, Plattner CA, Pallas DC, Hahn WC.
Identification of specific PP2A complexes involved in human cell transformation.
Cancer Cell. Feb;5(2):127-36. (2004)
117. Puustinen P, Junttila MR, Vanhatupa S, Sablina AA, Hector ME, Teittinen K,
Raheem O, Ketola K, Lin S, Kast J, Haapasalo H, Hahn WC, Westermarck J.PME-1
protects extracellular signal-regulated kinase pathway activity from protein
phosphatase 2A-mediated inactivation in human malignant glioma. Cancer Res. Apr
1;69(7):2870-7. (2009)
118. Takeshita F, Ishii KJ.Intracellular DNA sensors in immunity. Curr Opin Immunol.
Aug;20(4):383-8. (2008)
119. Ford JW, McVicar DW.TREM and TREM-like receptors in inflammation and
disease.Curr Opin Immunol. Feb;21(1):38-46. (2009)
120. Olson JA, Hayaishi O. The enzymatic cleavage of beta-carotene into vitamin A by
soluble enzymes of rat liver and intestine. Proc Natl Acad Sci U S A.
Nov;54(5):1364-70. (1965)
99
121. Lietz G, Oxley A, Leung W, Hesketh J.Single nucleotide polymorphisms upstream
from the β-carotene 15,15'-monoxygenase gene influence provitamin A conversion
efficiency in female volunteers.J Nutr. Jan;142(1):161S-5S. (2012)
122. Yeh CS, Wang JY, Cheng TL, Juan CH, Wu CH, Lin SR. Fatty acid metabolism
pathway play an important role in carcinogenesis of human colorectal cancers by
Microarray-Bioinformatics analysis. Cancer Lett. Feb 28;233(2):297-308. (2006)
123. Rakhshandehroo M, Knoch B, Müller M, Kersten S. Peroxisome proliferatoractivated receptor alpha target genes. PPAR Res. pii: 612089. (2010)
124. Rakhshandehroo M, Hooiveld G, Müller M, Kersten S. Comparative analysis of
gene regulation by the transcription factor PPARalpha between mouse and human.
PLoS One. Aug 27;4(8):e6796. (2009)
125. Yamazaki K, Kuromitsu J, Tanaka I.Microarray analysis of gene expression
changes in mouse liver induced by peroxisome proliferator- activated receptor alpha
agonists. Biochem Biophys Res Commun. Jan 25;290(3):1114-22. (2002)
126. Patsouris D, Mandard S, Voshol PJ, Escher P, Tan NS, Havekes LM, Koenig W,
März W, Tafuri S, Wahli W, Müller M, Kersten S. PPARalpha governs glycerol
metabolism. J Clin Invest. Jul;114(1):94-103. (2004)
127. Moffit JS, Koza-Taylor PH, Holland RD, Thibodeau MS, Beger RD, Lawton MP,
Manautou JE. Differential gene expression in mouse liver associated with the hepato
protective effect of clofibrate. Toxicol Appl Pharmacol. Jul 15;222(2):169-79. (2007)
128. Kuo YB, Chan CC, Chang CA, Fan CW, Hung RP, Hung YS, Chen KT, Yu JS,
Chang YS, Chan EC. Identification of phospholipid scramblase 1 as a biomarker and
determination of its prognostic value for colorectal cancer.Mol Med. Jan-Feb;17(12):41-7. (2011)
129. Yan C, Boyd DD.ATF3 regulates the stability of p53: a link to cancer. Cell Cycle.
May;5(9):926-9. (2006)
130. Puustinen P, Junttila MR, Vanhatupa S, Sablina AA, Hector ME, Teittinen K,
Raheem O, Ketola K, Lin S, Kast J, Haapasalo H, Hahn WC, Westermarck J. PME-1
protects extracellular signal-regulated kinase pathway activity from protein
phosphatase 2A-mediated inactivation in human malignant glioma. Cancer Res. Apr
1;69(7):2870-7. (2009)
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APPENDIX
Compliance Forms, Certificates, Permission Letter
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