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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. iii 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. iv 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. v 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. 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