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ToxSci Advance Access originally published online on March 20, 2008
Toxicological Sciences 2008 104(1):86-99; doi:10.1093/toxsci/kfn063
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© The Author 2008. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

Identification of Genes that May Play Critical Roles in Phenobarbital (PB)-Induced Liver Tumorigenesis due to Altered DNA Methylation

Jennifer M. Phillips* and Jay I. Goodman{dagger},1

* Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824 {dagger} Department of Pharmacology and Toxicology, Michigan State University, B-440 Life Sciences Building, East Lansing, MI 48824

1 To whom correspondence should be addressed. Fax: (517) 353-8915. E-mail: goodman3{at}msu.edu.

Received February 13, 2008; accepted March 14, 2008


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
Aberrant DNA methylation plays important roles in tumorigenesis, and the nongenotoxic rodent tumor promoter phenobarbital (PB) alters methylation patterns to a greater extent in liver tumor susceptible as compared to resistant mice (Watson and Goodman, 2002Go). Unique hepatic regions of altered DNA methylation (RAMs) were identified in sensitive B6C3F1, as compared to resistant C57BL/6, mice at 2 or 4 weeks of PB treatment using a novel approach involving methylation-sensitive restriction digestion, arbitrarily primed PCR, and capillary electrophoresis (Bachman et al., 2006b). PCR products representing 90 of 170 (53%) total unique B6C3F1 RAMs at 2 or 4 weeks were cloned and subjected to BLAST-like alignment tool searches that resulted in 51 gene matches; some of these have documented oncogenic or tumor suppressor roles. Importantly, uniquely hypomethylated genes play roles in angiogenesis (e.g., chymase 1, tyrosine kinase nonreceptor 2, and possibly ephrin B2 and triple functional domain, PTPRF interacting) and invasion and metastasis, including those involved in the epithelial-mesenchymal transition (transcription factor 4, transforming growth factor beta receptor II, and ral guanine nucleotide dissociation stimulator). Common cellular targets and regulators of the genes representing unique B6C3F1 RAMs were uncovered, indicating that they might act in concert to more efficiently promote tumorigenesis. Genes not previously associated with mouse liver tumorigenesis exhibited altered methylation at these very early times following PB treatment. We hypothesize that at least some of the unique PB-induced B6C3F1 RAMs represent key events facilitating transformation, which is consistent with a causative role of altered DNA methylation during early stages of tumorigenesis.

Key Words: DNA methylation; epigenetic; mouse liver; phenobarbital, tumors.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
DNA methylation, i.e., 5-methylcytosine, occurs at approximately 70% of CpG dinucleotides (Naveh-Many and Cedar, 1981Go) and evidence suggests that methylation at non-CpG sites such as CpA and CpT is mediated by DNA methyltransferase 3a (Ramsahoye et al., 2000Go). DNA methylation silences retrotransposable elements, controls genomic imprinting, and regulates tissue-specific gene expression during development (Reik, 2007Go). Altered DNA methylation is an epigenetic mechanism that plays multiple roles during tumor formation (Counts and Goodman, 1995Go). Carcinogenesis is a multistep/multistage process involving the progressive clonal expansion of cells that have accumulated critical, heritable alterations within tumor suppressors and oncogenes, providing them with growth advantages over neighboring cells (Feinberg et al., 2006Go; Hanahan and Weinberg, 2000Go; Nowell, 1976Go). The key modifications in genes that contribute to crucial processes can be mutations and/or epigenetic alterations since these might be functionally identical. Mutation as well as DNA hypermethylation can silence tumor suppressor genes, while mutation as well as hypomethylation can activate oncogenes (Goodman and Watson, 2002Go).

Phenobarbital (PB) is the prototypical nongenotoxic rodent liver tumor promoter that causes hypertrophy, hyperplasia, and upregulation of drug metabolizing enzymes, e.g., cytochrome P450s (Whysner et al., 1996Go). Some details regarding PB-induced tumor promotion have emerged. In N-nitrosodiethylamine (DEN)–initiated B6C3F1 mice, a tumor-promoting dose of PB (0.05%, wt/wt) caused an increase in focal DNA synthesis and a simultaneous decrease in apoptosis, likely facilitating preneoplastic lesion growth in the liver (Kolaja et al., 1996bGo). DEN-initiated Connexin32-null mice develop liver tumors at a high rate that is not enhanced by PB treatment (Moennikes et al., 2000Go), indicating that inhibition of gap junctional intracellular communication (GJIC) is key in the mechanism of action of PB; it has been suggested that inhibition and downregulation of GJIC are involved in tumor promotion and progression, respectively (Trosko and Chang, 2001Go). Additionally, the nuclear constitutive active/androstane receptor (CAR) mediates PB-induced hepatomegaly in mouse liver (Wei et al., 2000Go) and it is essential for tumor promotion by PB in DEN-initiated C3H/He mice (Yamamoto et al., 2004Go). Furthermore, DEN-initiated CAR wild-type mice, promoted with PB for 23 (precancerous liver lesions present) or 32 (liver tumors present) weeks, exhibited unique hepatic regions of altered DNA methylation (RAMs) as compared to DEN-initiated CAR knock-out mice promoted for 23 weeks (Phillips et al., 2007Go).

Importantly, methylation patterns are disrupted to a greater extent in liver tumor–susceptible, as compared to resistant, mice upon treatment with 0.05% (wt/wt) PB, including higher levels of hypermethylation in the two sensitive groups (C3H/He >> B6C3F1 > C57BL/6) (Watson and Goodman, 2002). After 12 months of treatment with 0.05% (wt/wt) PB in drinking water, 100% of B6C3F1 and no C57BL/6 mice develop liver tumors (Becker, 1982Go). It is hypothesized that their differential abilities to maintain normal methylation patterns contribute to the disparity in their liver tumor susceptibilities (Watson and Goodman, 2002). An important question to address is, in which genes do changes in methylation play a key role? One approach might have been to look for PB-induced changes in expression (e.g., a microarray study) followed by methylation analysis of those genes whose expressions were altered. The problem here lies with the tedious task of evaluating methylation status in, possibly, thousands of genes plus the likelihood that at early times following treatment with PB, some key genes could exhibit modified methylation but not yet to the extent that expression was affected. Therefore, we decided to first look for altered methylation with the understanding that this could be followed up with expression analysis.

RAMs were detected by a novel approach involving methylation-sensitive restriction digestion, arbitrarily primed PCR (AP-PCR), and capillary electrophoresis (Bachman et al., 2006bGo). Unique RAMs in the sensitive B6C3F1, as compared to the resistant C57BL/6, mice in response to 2 or 4 weeks of 0.05% (wt/wt) PB treatment were discerned (Bachman et al., 2006bGo). It is hypothesized that among the PB-induced unique RAMs in the sensitive mice are those that play critical mechanistic roles early during promotion of tumorigenesis.

Only a few genes, including CAR (Yamamoto et al., 2004Go), have previously been linked to mouse liver tumorigenesis. Promotion by PB (Aydinlik et al., 2001Go) and 2,2',4,4',5,5'-hexachlorobiphenyl (PCB 153) (Strathmann et al., 2006Go) leads to tumors with mutations in the β-catenin gene, possibly the result of selective clonal expansion of cells bearing the mutation. Myc amplification occurs in liver tumors with no detectable methylation changes (Vorce and Goodman, 1991Go). Mouse liver tumors display activating Ha-ras mutations (Wiseman et al., 1986Go), in addition to hypomethylation of the 5' region (Vorce and Goodman, 1991Go) and increased Ha-ras expression (Counts et al., 1997Go). Similarly, Ki-ras is hypomethylated in liver tumors, and this change might be essential, though not necessarily sufficient, for overexpression (Vorce and Goodman, 1991Go). PB induces hypomethylation of raf in B6C3F1 mouse liver, which could lead to increased expression (Ray et al., 1994Go).

In this study, unique RAMs that formed in hepatic DNA of sensitive B6C3F1, as compared with resistant C57BL/6, mice at an early stage of PB promotion (Bachman et al., 2006bGo) were annotated. PCR products representing unique RAMs were cloned and the BLAST-like alignment tool (BLAT) was employed to ascertain with which genes, nonprotein-coding regions and "unannotated" regions of the genome these RAMs are associated. Altered DNA methylation was discerned in a number of genes that have not previously been implicated in mouse liver tumorigenesis, though many have been associated with tumorigenesis in other species, including humans. An informatics approach was then utilized to elucidate biological pathways that might be disrupted by PB-induced altered DNA methylation and, therefore, contribute to carcinogenesis.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
Animals, Treatments, and Tissue Samples
B6C3F1 (C57BL/6 x C3H/He) and C57BL/6 mice were acquired (Charles River Laboratories, Wilmington, MA) and randomly assigned to control or treatment groups with six or seven animals per group (Bachman et al., 2006bGo). PB was administered in drinking water at a concentration of 0.05% (wt/wt) for 2 or 4 weeks, and liver tissue was harvested as described (Bachman et al., 2006bGo). Treatment, housing, and care were in accordance with the Animal Use and Care Guidelines of Michigan State University.

DNA isolation.
Liver tissue was homogenized in 1 ml of TRIzol Reagent (Invitrogen, Carlsbad, CA), and DNA was isolated via the manufacturer's protocol (Bachman et al., 2006bGo).

Evaluation of DNA Methylation Status by AP-PCR and Capillary Electrophoresis
DNA methylation status was evaluated by an AP-PCR, capillary electrophoresis procedure (Bachman et al., 2006aGo). This technique permits the simultaneous evaluation of treatment-related hypomethylations (less methylation in a region that was methylated in control), hypermethylations (more methylation in a region that was methylated in control), and new methylations (methylation in a region that was not methylated in control) in numerous regions of the genome.

Restriction digests.
Each DNA sample was subjected to three separate double restriction digests that were performed in duplicate with (1) a methylation-insensitive enzyme and (2) a methylation-sensitive enzyme. Digestion with a methylation-sensitive enzyme, RsaI or BfaI, ensures complete digestion by the methylation-sensitive enzyme, MspI, HpaII, or BssHII. Restriction digestion with RsaI/MspI, RsaI/HpaII, and BfaI/BssHII was carried out as described previously (Bachman et al., 2006bGo). MspI and HpaII recognize 5' CCGG 3' sites and cut between the internal cytosine and guanine. MspI will not restrict DNA if the external cytosine is methylated, while HpaII will not restrict DNA if the internal cytosine is methylated. BssHII recognizes 5' GCGCGC 3' sites and cuts between the first guanine and cytosine residues and will not restrict DNA if several combinations of cytosines in the sequence are methylated. BfaI sites appear less frequently in CpG islands than RsaI sites and, thus, CpG islands are more intact following digestion of DNA with the former enzyme as compared to the latter (Shiraishi et al., 1995Go). Therefore, the use of BfaI in combination with BssHII, a six-base rare cutter with a GC-rich recognition sequence, provides an additional, important "window" into our DNA methylation status analysis that complements the data obtained with the RsaI/MspI and RsaI/HpaII digests.

AP-PCR and capillary electrophoretic separation of products.
AP-PCR and capillary electrophoresis were performed as described previously (Bachman et al., 2006bGo); however, two corrections were made: the five-cycle stage of the AP-PCR reaction was followed by 30 cycles (not 40 cycles as stated originally), starting with a denaturation step of 94°C for 30 s (not 15 s as stated originally). The digested DNA was subjected to AP-PCR using a single arbitrary primer, 5' AAC CCT CAC CCT AAC CCC GG 3' (Gonzalgo et al., 1997Go), which was fluorescently labeled at the 5' end with HEX (Integrated DNA Technologies, Coralville, IA). This primer binds well to GC-rich regions, and the 5' CCGG 3' sequence at its 3' end increases the probability of binding to the MspI and HpaII restriction sites, permitting the detection of methylation at the site of primer annealing and between sites of primer annealing.

Data analysis.
The resulting PCR products were evaluated with regard to their size, in base pairs, and corresponding peak areas, using the Excel program. A consensus, average peak area was calculated for each experimental group. This permits the consensus peak area of a control group to be compared with the consensus peak area of a treatment group, in order to determine if there are differences in methylation at a particular PCR product size, and if so, these PCR products are considered to be RAMs. Treatment-related RAMs include: (1) hypomethylations, both 100% decreases, and decreases which are statistically significant (Student's t-test, p < 0.05) when compared to control, (2) hypermethylations, which are increases that are statistically significant (Student's t-test, p < 0.05) when compared to control, and (3) new methylations, in which PCR product formed following treatment but did not form under control conditions. A detailed description of the data analysis procedure was provided previously (Bachman et al., 2006aGo,bGo) and included the following comparisons: (1) B6C3F1, 2-week 0.05% PB versus B6C3F1, 2-week control data, (2) C57BL/6, 2-week 0.05% PB versus C57BL/6, 2-week control data, (3) B6C3F1, 4-week 0.05% PB versus B6C3F1, 4-week control data, and (4) C57BL/6, 4-week 0.05% PB versus C57BL/6, 4-week control data (Bachman et al., 2006bGo). The capillary electrophoresis data obtained from the individual animals in each treatment group plus the controls can be found in Supplemental Information, Individual Animal Data (Supplemental Figs. S1S25).

Common and unique RAMs.
In order to determine if the RAMs that occurred at the same PCR product size in two treatment groups are equivalent (common RAMs) or different (unique RAMs), ANOVA tests, p < 0.05, were performed (Bachman et al., 2006bGo). In this way, for example, unique RAMs in the B6C3F1, 4-week 0.05% PB–treated group as compared to the C57BL/6, 4-week 0.05% PB–treated group were identified. In addition, one-way ANOVA, p < 0.05, was used to discern unique B6C3F1 0.05% PB–induced RAMs that "carried forward" from the 2- to 4-week timepoint.

Identification of PB-Induced Unique B6C3F1 RAMs
Cloning and sequencing of AP-PCR products.
In order to identify in what regions of the genome the PB-induced unique B6C3F1 RAMs occurred, the AP-PCR products were first cloned using an in-gel approach. The AP-PCR products and a 100-bp DNA ladder (Invitrogen) were electrophoresed through a 3% NuSieve GTG low melting temperature agarose gel (Lonza Biosciences, Basel, Switzerland). Portions of the gel that contained PCR products within 100 bp size ranges were excised, melted, and used for in-gel cloning reactions prepared with the pGEM-T Easy Vector Kit (Promega, Madison, WI). Clones that contained PCR product inserts were purified and sequenced at the Research Technology and Support Facility at Michigan State University. Sequencing reactions were prepared using either SP6- or T7-sequencing primers (as described in the pGEM-T Easy Vector Technical Manual; Promega) and subsequently run on an ABI 3730xl Genetic Analyzer.

Comparison of the sizes of cloned AP-PCR products to the sizes of unique RAMs.
After the sequences were obtained, the sizes of the cloned products were compared to the sizes of the unique RAMs in order to determine which cloned products represented unique B6C3F1 RAMs at the 2- or 4-week timepoints. In many instances, it can be confidently stated that a particular cloned product represents a single RAM and as such the methylation status of that RAM is unambiguous. However, the raw data analysis performed to establish if a RAM occurred in a treatment as compared to a control group (Bachman et al., 2006aGo) is based on the understanding that the ABI 3130 Genetic Analyzer capillary electrophoresis instrument does not detect PCR product sizes with 100% accuracy. Therefore, in certain instances during the analysis of the raw data, PCR product sizes are combined. Six or seven animals per experimental group were used, and restriction digestions were performed in duplicate, followed by AP-PCR, for a total of 12 or 14 reactions. If multiple PCR product sizes within 2 bp of one another displayed product in less than half of the 12 or 14 AP-PCR reactions, these products were considered to be "identical" and were subsequently combined. This procedure has implications for analysis of the cloning data. For example, two RAMs occur uniquely in the B6C3F1 mice at 4 weeks as a result of RsaI/HpaII digestion: a new methylation at 306 bp and a hypomethylation at 310 bp (Fig. 1). A PCR product of 308 bp was cloned and a BLAT search showed that the product spans the transcriptional start site of NK2 transcription factor-related, locus 6 (Nkx6-2) (Table 1). Due to our basic data analysis assumption, we were not able to confidently state whether Nkx6-2 represents the newly methylated RAM at 306 bp or the hypomethylated RAM at 310 bp. The "methylation status" data column in Table 1 reflects this limitation, where 16% (14/85) of the genes, and regions of the genome which are greater than 10 kb away from a known gene, are tentatively classified as having multiple methylation statuses at either 2 or 4 weeks (e.g., Hypo/New for a single region at 4 weeks).


Figure 1
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FIG. 1. Unique RAMs that formed in the livers of B6C3F1 mice in response to 2 or 4 weeks of treatment with 0.05% (wt/wt) PB. Liver tumor–susceptible B6C3F1 and resistant C57BL/6 mice were treated for 2 or 4 weeks with a tumor-promoting dose (0.05%, wt/wt) of PB. RAMs were detected in both groups by a procedure involving methylation-sensitive restriction digestion, AP-PCR, and capillary electrophoresis. Unique RAMs in the B6C3F1, as compared to the C57BL/6, mice were identified at 2 Figure 1 and 4 Figure 1 weeks. Those that were observed at both the 2- and 4-week timepoints are referred to as carry forward RAMs Figure 1.

 

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TABLE 1 PCR Products Representing Unique PB-Induced RAMs in Liver Tumor–Sensitive B6C3F1, as Compared to Resistant C57BL/6, Mice Were Cloned and Subjected to BLAT Searches

 
Analysis of AP-PCR product sequences.
The sequences were subjected to BLAT database searches of the mouse genome (UCSC Genome Browser, July 2007 mouse assembly, http://genome.ucsc.edu/cgi-bin/hgBlat?command = start) in order to ascertain in which regions of the genome the unique PB-induced B6C3F1 RAMs occurred. The BLAT program allows a nucleotide or amino acid sequence to be aligned to an index of the entire genome of an animal. In the case of DNA sequence queries, BLAT can detect sequence alignments of 95% or greater similarity of regions with lengths of 25 or more base pairs. Additional information about the genomic region/gene is listed, including, but not limited to gene information, sequence conservation between species, GC percentage, and the location of single nucleotide polymorphisms and repeat elements. The unique RAMs were classified according to a scheme that indicates where, in relation to a gene (e.g., within an intron, within an exon, upstream of the transcriptional start site), they are located (Fig. 2). Genes that were identified using BLAT searches were subjected to biological pathway analysis via Pathway Studio 5.0 (Ariadne Genomics, Rockville, MD). In this fashion, pathways for the individual genes were elucidated. In addition, common cellular targets (Fig. 3) and regulators (Supplemental Fig. S34) of the unique B6C3F1 genes of interest at 4 weeks were discerned.


Figure 2
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FIG. 2. A scheme to classify cloned PCR products that represent unique PB-induced B6C3F1 RAMs based on their locations within the mouse genome as determined by BLAT searches (UCSC Genome Browser). PCR products representing unique B6C3F1 RAMs were cloned and subjected to BLAT searches. Depending on where, in relation to a gene, the PCR product aligned, it was assigned a particular genomic classification. For example, any PCR products designated as 1.B.ii. are located between 2 and 10 kb upstream from an annotated gene.

 

Figure 3
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FIG. 3. Common cellular targets of genes that represent RAMs in liver tumor–susceptible B6C3F1 mice at 4 weeks of PB treatment. An informatics approach was utilized to uncover cellular targets that can be affected by two or more genes representing unique PB-induced B6C3F1 RAMs at 4 weeks. Red symbols are common cellular targets of the unique RAMs. The arrows point toward the common target; positive arrows Figure 3 indicate that the common RAM positively affects the target, while negative arrows Figure 3 denote a negative effect. Unique RAMs are hypomethylated (green), hypermethylated (orange), or newly methylated (blue). A combination of colors (i.e., green and orange) depicts a RAM with an ambiguous methylation status at the 4-week timepoint. The shapes of the entities represent the specific class of molecules to which a RAM or common target belongs: extracellular proteins or nuclear receptors Figure 3, ligands Figure 3, kinases Figure 3 and transcription factors Figure 3.

 

    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
Figure 1 depicts the 170 total unique RAMs that were detected following a tumor-promoting dose of PB for 2 or 4 weeks in the sensitive B6C3F1, as compared to resistant C57BL/6 mice, including eight carry forward RAMs that were observed at both the 2- and 4-week timepoints (Bachman et al., 2006bGo). We hypothesized that among the unique RAMs in the B6C3F1 mice, some are playing critical mechanistic roles during liver tumor formation. In this study, PCR products were cloned that represent 90 (53%) of the unique RAMs, and these products were annotated via the BLAT sequence alignment tool (Table 1). Selected literature references for Table 1 are located in Supplemental Table 1. RAMs were also classified based on their location relative to a known gene (Table 1 and Fig. S26) and chromosomal distribution (Fig. S27). All of the annotated genes were subsequently investigated via an informatics approach in order to determine the function of the gene, in addition to any gene products that are common cellular targets and/or regulators of the unique RAMs of interest at 4 weeks. Five representative pathways of individual unique B6C3F1 RAMs in addition to a functional summary of these RAMs can be found in Supplemental Information (Figs. S28–S33).

As explained in the "Materials and Methods," some identified RAMs could unambiguously be assigned a specific methylation status (Table 1). Hypomethylated RAMs at 2 weeks were coiled-coil domain containing 137 (Ccdc137), dead box polypeptide 54 (Ddx54), myoferlin (Fer1l3), protein phosphatase 4c, catalytic subunit (Ppp4c), solute carrier family 9 (sodium/hydrogen exchanger), member 5 (Slc9a5), and WSC domain containing 1 (Wscd1). At 4 weeks, hypomethylated RAMs were ADAM metallopeptidase with thrombospondin type 1 motif, 17 (Adamts17), anaphase-promoting complex subunit 7 (Anapc7), ADP-ribosylation factor–interacting protein 1 (Arfip1), B-cell scaffold protein with ankyrin repeats 1 (Bank1), CMT1A-duplicated region transcript 4 (Cdrt4), chymase 1 (Cma1), cut-like 2 (Cutl2), dead box polypeptide 54 (Ddx54), myoferlin (Fer1l3), F-box and WD-40 domain protein 7, archipelago homolog (Drosophila) (Fbxw7), meteorin, glial cell differentiation regulator like (Metrnl), odd Oz/ten-m homolog 2 (Odz2), pleckstrin homology domain containing, family F (with FYVE domain) member 1 (Plekhf1), prickle-like protein 2 (Prickle2), ral guanine nucleotide dissociation stimulator (Ralgds), sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3G (Sema3g), stromal interaction molecule 1 (Stim1), transcription factor 4 (Tcf4), transcriptional enhancer factor-1 (Tead1), transforming growth factor, beta receptor II (Tgfbr2), threonine aldolase (Tha1), tyrosine kinase nonreceptor 2 (Tnk2), and transient receptor potential cation channel, subfamily M, member 3 (Trpm3). Carry forward hypomethylations were those that were seen at both the 2- and 4-week timepoints: growth arrest–specific 2 like 3 (Gas2l3), potassium channel, subfamily K, member 10 (Kcnk10), tyrosine hydroxylase (Th), Williams-Beuren syndrome chromosome region 17 homolog (Wbscr17), a probable repeat element that was linked to multiple chromosomes (295 bp), and a PCR product that aligned to an uncharacterized region (479 bp).

RAMs that were unambiguously assigned a hypermethylated status at 4 weeks of PB treatment were coiled-coiled domain containing 137 (Ccdc137), RNA-binding motif protein 10 (Rbm10), and THAP domain containing and apoptosis-associated protein 3 (Thap3). Furthermore, unambiguous new methylations at 4 weeks were branched chain aminotransferase 2, mitochondrial (Bcat2), bcl2-like 13 (Bcl2l13), Discs, large homolog-associated protein 4 (Dlgap4), nuclear receptor corepressor 2 (Ncor2), retinoid X receptor beta (Rxrb), ST6 (alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase 3 (Siat7c), transmembrane protein 104 (Tmem104), ubiquitin-conjugating enzyme E2D 1 (Ube2d1), and WSC domain containing 1 (Wscd1). Carry forward newly methylated RAMs were brain-specific angiogenesis inhibitor 3 (Bai3), RIKEN cDNA C630007B19 gene (Tafa-1), and an uncharacterized region (524 bp). With regards to increases in methylation at 2 weeks, pleckstrin homology domain containing, family F (with FYVE domain) member 1 (Plekhf1) was newly methylated, and there were no unambiguous examples of hypermethylations.

Since the data analysis procedure sometimes involved the combination of PCR product sizes that are within 2 bp of one another, in addition to the fact that three different methylation-sensitive enzyme pairs were utilized, situations occurred in which it was not possible to unambiguously assign a specific methylation status to a RAM. For example, in the case of Nfe2l2, restriction digestion by RsaI/HpaII followed by AP-PCR and CE resulted in the detection of 2 RAMs within 2 bp of one another that possessed different methylation statuses (Table 1). Because of the ±2 bp combination rule of the data analysis procedure, one cannot be certain whether Nfe2l2 is hypomethylated or newly methylated at 2 weeks based on digestion with RsaI/HpaII. In the case of Prickle2, RsaI/MspI digestion revealed a hypomethylated RAM, while the BfaI/BssHII digest revealed a newly RAM at 2 weeks (Table 1). Thus, Prickle2 could represent one or both of these RAMs since different restriction digestions were utilized, each of which reveals information regarding the methylation patterns of different cytosines at and within the sites of primer annealing. Therefore, multiple genes were discerned which could not be assigned a specific methylation status. Table 1 indicates the methylation statuses and particular treatment periods at which these genes displayed altered methylation. These genes were ephrin B2 (Efnb2), zinc finger and SCAN domain containing 22 (Zscan22), inositol polyphosphate-5-phosphatase A (Inpp5a), nuclear factor, erythroid-derived 2, like 2 (Nfe2l2), NK2 transcription factor-related, locus 6 (Nkx2-6), prickle-like protein 2 (Prickle2), protein tyrosine phosphatase, receptor type O (Ptpro), src-related kinase lacking C-terminal regulatory tyrosine and N-terminal myristylation sites (Srms), transcription factor 4 (Tcf4), triple functional domain (PTPRF interacting) (Trio), ubiquitin-conjugating enzyme E2D 1 (Ube2d1), and WSC domain containing 1 (Wscd1).

There were five PCR products which each associated with multiple hits that displayed the highest BLAT scores, indicating that many top hits for each PCR product showed the fewest mismatches as compared to the sequence of interest. As such, any of these top hits might correspond to the PCR product sequence. Furthermore, all the top hits for a particular PCR product represented regions on various chromosomes, yet the product aligned to the identical repetitive element. Therefore, these five RAMs (237, 259, 260, 295, and 442–445 bp) appear to be linked to a different, specific repetitive element, and thus we are unable to determine with certainty which genomic region the unique RAM represents. BLAT searches also revealed that 27 PCR products are uncharacterized (i.e., located more than 10 kb away from a known gene). Of these 27 RAMs, the methylation statuses of 22 were unambiguous and therefore could be classified as hypo- (17 RAMs), hyper- (2 RAMs), or new- (3 RAMs) methylations at a particular timepoint. Three of 27 uncharacterized RAMs could be assigned a specific methylation status at both the 2- and 4-week timepoints, although the changes were opposite in direction (e.g., the RAM was hypomethylated at 2 weeks and newly methylated at 4 weeks). Finally, for two of 27 uncharacterized RAMs, the methylation statuses at 4 weeks were unambiguous, while the statuses at 2 weeks were not (e.g., at 2 weeks, the RAM is either hypo- or newly methylated).

In order to uncover interconnections between the genes whose methylation statuses changed uniquely in the B6C3F1 mice, an informatics program was utilized to identify their common protein targets and regulators at 4 weeks of PB treatment. Figure 3 illustrates the common cellular targets of several of the unique RAMs of interest at 4 weeks; those genes listed in Table 1 that do not appear in Figure 3 do not possess targets that are in common with any of the other 4-week genes. As examples, interleukin 8 (IL-8) is a common target of Cma1, Ncor2, and Tcf4 and similarly, vascular endothelial growth factor (Vegf) is a common target of Cma1, Tcf4, and Tgfbr2. In this way, potential common targets of multiple RAMs of interest were ascertained in order to determine whether common cellular processes might be affected which might more efficiently facilitate tumorigenesis. Additionally, common cellular regulators of the genes of interest at 4 weeks were identified and this figure is located in Supplemental Information (Fig. S34).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
Following administration of a liver tumor–promoting dose of PB (0.05%, wt/wt) for 2 or 4 weeks, 170 unique RAMs were identified in livers of B6C3F1 mice, which are sensitive to PB-induced tumorigenesis, as compared to the resistant C57BL/6 (Fig. 1) (Bachman et al., 2006bGo). The current study focused on annotating those unique RAMs via BLAT searches in order to determine in which genomic regions these methylation changes occurred and discerning the processes that these RAMs might affect which could facilitate tumorigenesis. PCR products were cloned that represent 90 of 170 RAMs, and 51 genes whose methylation statuses changed uniquely in the sensitive mice were ascertained. These genes and their functions are summarized in Table 1. Twenty-seven RAMs aligned to regions of the mouse genome which are located further than 10 kb away from any known genes.

Prior to this study, only a few specific genes, in addition to CAR (Yamamoto et al., 2004Go), were associated with mouse liver tumorigenesis, e.g., Ha-ras, Raf, Myc, and Ctnnbl (β-Catenin) (Aydinlik et al., 2001Go; Counts et al., 1997Go; Ray et al., 1994Go; Vorce and Goodman, 1991Go; Wiseman et al., 1986Go); these generally were identified late during tumorigenesis. It is possible that some of the altered methylation observed after carcinoma development might have arisen secondarily, rather than having been causal; therefore, we are interested in understanding the roles of methylation changes occurring early during the multistage transformation process. The time dependence of the unique PB-induced B6C3F1 RAMs, as well as the identification of several changes that were observed at both 2 and 4 weeks ("carry forward" RAMs), support the notion that this anomalous methylation plays a causative role in tumor formation (Bachman et al., 2006bGo). The current data support our hypothesis that this approach can discern "new" genes that might be involved in PB-induced tumorigenesis due to aberrant methylation (Table 1). Individually, the genes with altered methylation statuses might be critical; however, importantly, evidence presented here suggests that these genes can influence common cellular processes. In other words, unique RAMs might cooperate to increase/decrease cellular functions, i.e., upregulation of oncogenes and downregulation of suppressor genes, which drive tumorigenesis.

For example, PB altered methylation patterns of multiple genes involved in invasion and metastasis. At 4 weeks, Tgfbr2, Tcf4, and Ralgds were hypomethylated uniquely and Bachman et al. (2006b)Go demonstrated Ha-ras hypomethylation and its increased expression in B6C3F1 mice. These four genes are associated with the epithelial-mesenchymal cell transition (EMT), a mechanism of tumor progression ultimately leading to invasion and migration. Several events are linked to EMT, including but not limited to the downregulation of E-cadherin, which can sequester β-catenin, rendering this protein unavailable for heterodimerizing with Tcf4 and facilitating transcription genes that promote proliferation, plus the initiation of Tgfb and Ras signal transduction pathways (Thiery, 2002Go). Additionally, Tnk2 and Ralgds (hypomethylated, 4 weeks), along with Efnb2 and Trio (both possibly hypomethylated, 4 weeks), play crucial roles during invasion and metastasis (Gale et al., 1996Go; Nakada et al., 2004Go; van der Horst et al., 2005Go; Ward et al., 2001Go; Yoshizuka et al., 2004Go).

The existence of common cellular targets and regulators of a subset of the unique genes indicate that key signaling processes are potentially affected (Fig. 3 and Fig. S34). Involved in angiogenesis are Efnb2 (possibly hypomethylated, 4 weeks) (Maekawa et al., 2003Go), and Tcf4 and Cma1 (both hypomethylated, 4 weeks), both of which can upregulate Vegf (Katada et al., 2002Go; Zhang et al., 2001Go). An increase in Nf-kB activity might result from Ppp4c (hypomethylated, 4 weeks), which activates it (Hu et al., 1998Go) and Ncor2 (newly methylated, 4 weeks), which inhibits it (Lee et al., 2000Go). Nf-kB–induced secretion of IL-6 from liver macrophages increases tumor cell survival and growth, promoting carcinogenesis (Lawrence et al., 2007Go), and a Nf-kB–dependent increase in IL-8 expression contributes to both angiogenesis and metastasis in tumor cells (Karashima et al., 2003Go). Furthermore, common targets and regulators of IL-6 and IL-8 were demonstrated (Fig. 3 and Fig. S34). IL-6 might be upregulated via relieving inhibition by Ncor2 (Song et al., 2005Go); we show that Ncor2 is newly methylated at 4 weeks and thus possibly silenced. IL-6 can upregulate Ralgds in leukemic cells (Senga et al., 2001Go) and Efnb2 in Kaposi sarcoma cells (Masood et al., 2005Go). Ralgds mediates the survival of transformed cells via the JNK/SAPK pathway, and Ralgds is essential for skin tumor formation in mice (González-García et al., 2005Go). Thus, IL-6 might indirectly contribute to survival, angiogenesis, invasion and metastasis. Similarly, IL-8 can be regulated by several unique RAMs: Tcf4 and Cma1 (hypomethylated, 4 weeks) up-regulate IL-8 in liver cells and EoL-1 cells, respectively (Lévy et al., 2002Go; Terakawa et al., 2006Go), while Ncor2 (newly methylated, 4 weeks) can block IL-8 transcription (Hoberg et al., 2004Go). Therefore, IL-6 and IL-8, common targets and/or regulators of several key genes, might facilitate the clonal expansion of preneoplastic cells by further contributing to cell growth/survival, angiogenesis, invasion, and metastasis. Figure 4 summarizes the possible functional significance, regarding tumorigenesis, of selected genes that exhibited altered methylation uniquely in the B6C3F1 mouse following PB treatment, along with a subset of key common targets/regulators of these genes. Selected literature references for the relationships depicted in this figure are noted in Supplemental Information (Fig. S35 and Supplemental Table 2).


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FIG. 4. The possible functional significance, regarding tumorigenesis, of selected genes that exhibited altered methylation uniquely in the B6C3F1 mouse following treatment with PB. The current study identified RAMs at 2 or 4 weeks of 0.05% PB treatment and annotated 51 genes that represent these regions. Several of these genes are well documented as playing critical roles in tumorigenesis (dark gray ovals). Unique PB-induced hypomethylation and decreased expression of Ha-ras (light gray oval) in B6C3F1 mice has been demonstrated (Bachman et al., 2006bGo). The appropriate timepoint of PB treatment is denoted (2 or 4 weeks), and the methylation statuses of the RAMs are indicated by H (hypomethylation), Y (hypermethylation), or N (new methylation). RAMs with an ambiguous methylation status are indicated by the presence of two letters (i.e., H or Y). IL-6 is a common 4-week regulator, and IL-8 and Vegf are common 4-week targets, of multiple unique RAMs in the liver tumor–susceptible B6C3F1 mice (white ovals). Ralgds is a key downstream effector of Ha-ras. Selected literature references for the relationships depicted in this diagram are noted in Supplemental Information (Fig. S35 and Supplemental Table 2).

 
Since our approach for the identification of unique RAMs in the sensitive B6C3F1 mice involved isolation of DNA from homogenized whole liver, it is impossible to determine whether each methylation change occurred in the same cell or in numerous, different cells. Regardless, one unique RAM might provide a growth advantage to a single cell; accumulation of multiple RAMs in the same cell could additively or synergistically enhance aberrant proliferation. Moreover, these RAMs might occur in various liver cell types: hepatocytes, Kupffer macrophages, and/or sinusoidal endothelial cells. Hepatocytes are not the only cells that play crucial roles in hepatocarcinogenesis; liver macrophages secrete IL-6 that can increase tumor cell growth and survival (Lawrence et al., 2007Go). Interactions between different cell types are important during tumor formation, so it is essential to utilize whole animal studies that permit critical interactions between different cell types in the target tissue to be observed, e.g., the innate immune system plays a crucial role in diethylnitrosamine-induced hepatocellular carcinoma in mice (Naugler et al., 2007Go). Mature mammalian cells can be stimulated to dedifferentiate into an embryonic stem cell-like state (Okita et al., 2007Go; Wernig et al., 2007Go). This fact, coupled with the capability of mature hepatocytes to proliferate either in a compensatory fashion, e.g., following partial hepatectomy (Steer, 1995Go), or in response to treatment with mitogens such as PB (Counts et al., 1996Go; Kolaja et al., 1996aGo), indicates that it is possible that mature hepatocytes are liver tumor cell progenitors. This notion is not incompatible with the suggestion that tumors originate from stem cell transformation (Reya et al., 2001Go), as both scenarios might be operative. Thus, it is important to evaluate methylation changes in whole tissue.

Treatment with a tumor-promoting dose of PB for 2 or 4 weeks stimulates hepatocyte proliferation in B6C3F1 male mice (Counts et al., 1996Go; Kolaja et al., 1996aGo). Upon further treatment, PB inhibits proliferation in the normal hepatocyte population, while preneoplastic cells may continue to divide (reviewed in Counts et al., 1996Go). The observed methylation changes might give certain cells the ability to "escape" the inhibition of proliferation by PB, facilitating clonal expansion of preneoplastic cells. Therefore, replication-dependent passive demethylation could produce hypomethylated RAMs. Conversely, active demethylation (Bhattacharya et al., 1999Go) or cytidine deaminases (Morgan et al., 2004Go) could also generate hypomethylated RAMs. PB-induced differences in activity and/or localization of demethylases, DNA methyltransferases (DNMT1, DNMT3a, and DNMT3b), methyl-binding proteins, and/or enzymes involved in one-carbon metabolism (Ulrey et al., 2005Go) could be responsible for the detected methylation changes. While the detailed mechanisms involved in PB-induced alteration of methylation remain to be discerned, it is important to recognize that the sensitive B6C3F1, as compared to the C57BL/6, mice appear to be "defective" with regard to the ability to preserve normal methylation patterns (Watson and Goodman, 2002).

Methylation changes in 55% (29 of 51) of the genes representing unique B6C3F1 RAMs occur within introns (Table 1). Alterations in methylation within immediate 5' promoter regions might result in gene expression changes (Esteller, 2007Go). However, current studies indicate that most mammalian genes possess multiple promoters and a large number of novel intergenic promoters have been discovered, and these might result in the transcription of noncoding RNA products (Sandelin et al., 2007Go). Additionally, a PB-responsive gene (Ugt1a1) contains an important cis regulatory element located 3 kb upstream from the transcriptional start site (Sugatani et al., 2001Go), and regulatory elements can also be found within introns (Fedorova and Fedorov, 2003Go) or near the 3' region (Cawley et al., 2004Go). Hence, it is possible that the RAMs associated with genomic regions other than immediate 5' promoter sequences can facilitate changes in gene expression.

The unique B6C3F1 RAMs occurred very early, at 2 and 4 weeks of PB treatment, and a subset of the discerned genes that represent the RAMs of interest can potentially influence processes that are associated with late stages of tumorigenesis, including angiogenesis, invasion, and metastasis. These data support the idea that cancer evolves in a stepwise series of clonal expansions, accumulating heritable alterations in their genomes (mutations and/or epigenetic changes), which, in a progressive fashion, provide a growth advantage over neighboring cells (Nowell, 1976Go). It is our contention that altered methylation plays critical roles during PB-induced liver tumor formation in rodents. We believe that the genes involved in rodent liver tumorigenesis are fundamentally the same as those underlying tumorigenesis in human tissues and hypothesize that there are key differences in the capacity to maintain overall stability of the genome (e.g., DNA methylation status is more stable in human cells as compared to rodent cells) (reviewed in Goodman and Watson, 2002Go). This could account, in part, for the increased susceptibility to tumorigenesis exhibited by rodents as compared to humans (Rangarajan and Weinberg, 2003Go). This study has discerned genes that display unique methylation changes in PB-treated liver tumor–susceptible mice and which can now be linked to liver tumorigenesis based on the processes in which they are involved. We are now turning our attention toward real-time PCR and microarray analysis of the key genes in order to determine the extent to which expression changes are associated with the observed PB-induced altered DNA methylation during early phases of tumorigenesis.


    SUPPLEMENTARY DATA
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
Supplementary data are available online at http://toxsci.oxfordjournals.org/.


    FUNDING
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
National Institutes of Health and National Institute of Environmental Health Sciences (T32-ES-7255) to J.M.P.


    ACKNOWLEDGMENTS
 
Research support, in the form of a gift, from the R.J. Reynolds Tobacco Company is acknowledged gratefully.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
 FUNDING
 REFERENCES
 
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