PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Gut. Author manuscript; available in PMC Mar 1, 2012.
Published in final edited form as:
Published online Oct 29, 2010. doi:  10.1136/gut.2010.217182
PMCID: PMC3040598
NIHMSID: NIHMS270371
Molecular Pathologic Epidemiology of Colorectal Neoplasia: An Emerging Transdisciplinary and Interdisciplinary Field
Shuji Ogino, Andrew T. Chan, Charles S. Fuchs, and Edward Giovannucci
Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA USA (SO); Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA USA (SO, CSF); Cancer Epidemiology Program and Gastrointestinal Malignancies Program, Dana-Farber/Harvard Cancer Center, Boston, MA USA (SO, ATC, CSF, EG); Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA USA (ATC); Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA USA (ATC, CSF, EG); Departments of Epidemiology and Nutrition, Harvard School of Public Health, Boston, MA USA (EG)
Correspondence to: Shuji Ogino, MD, PhD, MS(Epidemiology), Center for Molecular Oncologic Pathology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, 44 Binney St., Room JF-215C, Boston, MA 02115 USA, Telephone: +1-617-632-3978; Fax: +1-617-582-8558, shuji_ogino/at/dfci.harvard.edu
Colorectal cancer is a complex disease resulting from somatic genetic and epigenetic alterations, including locus-specific CpG island methylation and global DNA or LINE-1 hypomethylation. Global molecular characteristics such as microsatellite instability (MSI), CpG island methylator phenotype (CIMP), global DNA hypomethylation, and chromosomal instability cause alterations of gene function in a genome-wide scale. Activation of oncogenes including KRAS, BRAF and PIK3CA affects intracellular signaling pathways and has been associated with CIMP and MSI. Traditional epidemiology research has investigated various factors in relation to an overall risk of colon and/or rectal cancer. However, colorectal cancers comprise a heterogeneous group of diseases with different sets of genetic and epigenetic alterations. To better understand how a particular exposure influences the carcinogenic process, somatic molecular changes and tumor biomarkers have been studied in relation to the exposure of interest. Moreover, an investigation of interactive effects of tumor molecular changes and the exposures of interest on tumor behavior (prognosis or clinical outcome) can lead to a better understanding of tumor molecular changes, which may be prognostic or predictive tissue biomarkers. These new research efforts represent “Molecular Pathologic Epidemiology”, which is a multidisciplinary field of investigations of the interrelationship between exogenous and endogenous (e.g., genetic) factors, tumoral molecular signatures and tumor progression. Furthermore, integrating genome-wide association studies (GWAS) with molecular pathologic investigation is a promising area. Examining the relationship between susceptibility alleles identified by GWAS and specific molecular alterations can help elucidate the function of these alleles and provide insights into whether susceptibility alleles are truly causal. Although there are challenges, molecular pathologic epidemiology has unique strengths, and can provide insights into the pathogenic process and help optimize personalized prevention and therapy. In this review, we overview this relatively new field of research and discuss measures to overcome challenges and move this field forward.
Keywords: colorectal carcinoma, multistep carcinogenesis, etiologic, risk factor, survival, molecular change, prevention
Molecular pathologic epidemiology, the concept of which has been consolidated by Ogino and Stampfer, [1] is a relatively new field of epidemiology based on molecular classification of cancer. In molecular pathologic epidemiology, a known or suspected etiologic factor is examined in relation to a specific somatic molecular change, in order to gain insights into the carcinogenic mechanism.[1] In recent years, there is a new direction of this field where we examine an interactive effect of tumoral molecular features and a lifestyle or other exposure factor on tumor behavior (prognosis or clinical outcome).[2] In this review, we focus on colorectal neoplasia, overview current status of molecular pathologic epidemiology, describe various challenges in this field, and propose future directions.
Colorectal cancer is a disease which is characterized by uncontrolled growth of colorectal epithelial cells. According to the multistep carcinogenesis theory, [3, 4] colorectal epithelial cells accumulate a number of molecular changes and eventually become fully malignant cells. Genetic and epigenetic events during the carcinogenesis process differ considerably from tumor to tumor. Thus, colorectal cancer is not a single disease. Rather, colorectal cancer encompasses a heterogeneous complex of diseases with different sets of genetic and epigenetic alterations. Essentially, each tumor arises and behaves in a unique fashion that is unlikely to be exactly recapitulated by any other tumor.[5]
We typically classify colorectal cancers into categories according to a well-defined molecular feature (e.g., microsatellite instability, MSI-high vs. microsatellite stability, MSS), because substantial evidence suggests that tumors with similar characteristics (e.g., MSI-high) have arisen by similar mechanisms and will behave in a similar fashion.[5] Thus, the major purposes of molecular classification are: 1) to predict natural history (i.e., prognosis); 2) to predict response or resistance to a certain treatment or intervention; and 3) to examine the relationship between a certain etiologic factor (i.e., lifestyle, environmental or genetic) and a molecular subtype, so that we can provide evidence for causality and optimize preventive strategies.
For any marker for molecular classification, we need to consider two key points. The first question is whether a given molecular feature reflects genome-wide changes. For example, MSI, chromosomal instability (CIN), the CpG island methylator phenotype (CIMP), and global DNA hypomethylation reflect genome-wide or epigenome-wide aberrations. Because these molecular features often confound the relationship between a locus-specific change and an exposure or outcome of interest, it is important to consider potential confounding by these genome-wide features whenever one examines locus-specific changes. The second question is whether a given molecular change has by itself driven cancer initiation or progression, or is simply linked to other important molecular events. For example, loss of heterozygosity (LOH) events may not by itself cause tumor progression; rather, underlying genomic instability (i.e., CIN) or functional loss of important genes within the lost chromosomal segment may cause tumor progression. Nevertheless, even if a given molecular change is consequential rather than causal, the change not only can be a good surrogate marker of a certain cancer pathway, but also may ultimately become a driver in later steps of tumor progression.
Traditional epidemiology research has investigated lifestyle, environmental or genetic factors that might increase or decrease risk of developing colorectal cancer.[6, 7] The weight of the evidence, in conjunction with results from in vitro and animal models or human experimental trials, can lead to particular factors being widely considered to be etiologically linked to cancer. Etiologic factors which have been implicated in colorectal carcinogenesis include red and processed meat, excess alcohol intake, deficiency of B and D vitamins, obesity, physical inactivity, diabetes mellitus, smoking, family history of colorectal cancer, inflammatory bowel diseases, among others.[8] More recently, the field of molecular epidemiology has evolved since 1990s, encompassing genome-wide association studies (GWAS) since 2000s.[9, 10] Molecular epidemiology refers to a specialized field of epidemiology where investigators examine genetic and molecular variation in a population and its interaction with dietary, lifestyle or environmental factors, to find clues to plausible causative links between etiologic factors and diseases. However, the mechanisms with which plausible etiologic factors influence the carcinogenic process remain largely speculative.
In traditional molecular pathology, investigators examine molecular characteristics in tumor cells to better understand carcinogenic processes and tumor cell behavior. In the last two decades, our knowledge on somatic molecular alterations in the carcinogenic process has substantially improved.[5, 1116] As illustrated in Figure 1, these two approaches, epidemiology and molecular pathology, have converged to improve our understanding of how certain exposures influence carcinogenesis by examining molecular pathologic marks of tumor initiation or progression, in relation to the exposures of interest.[1] This represents a relatively new field of scientific investigation, which has been coined “Molecular Pathologic Epidemiology”.[1] If a specific lifestyle or dietary factor can prevent the occurrence of a specific somatic molecular change, it would add considerable scientific basis to such a preventive strategy. Specificity of the association for a certain molecular change provides further evidence for a causal relationship. For an individual who has a susceptibility to a specific somatic molecular change, we may be able to develop a personalized preventive strategy, which targets specific molecules or pathways.
Figure 1
Figure 1
Illustration of traditional epidemiology (A), traditional molecular pathology (B), and molecular pathologic epidemiology (C). Note that molecular pathology plays a central role in molecular pathologic epidemiology. Molecular pathologic epidemiology addresses (more ...)
Table 1 is a comprehensive list of molecular pathologic epidemiology studies on colorectal neoplasia.[1745][4688][89101][102151] One challenge is that, despite a number of studies on some topics (e.g., one-carbon metabolism gene polymorphisms and epigenetic changes), generalisable confirmed findings are uncommon. We discuss possible reasons and various challenges in a later section. Nonetheless, there have been observations confirmed by notable independent studies: a case-control study by the Slattery et al.’s group[114] and a prospective cohort study by Iowa Women’s Health Study (IWHS)[78] have independently shown that cigarette smoking is associated with CIMP-positive tumor, and with BRAF-mutated tumor. As another example, the association between obesity and microsatellite stable (MSS) tumor has been demonstrated by three independent case-control studies, including the Slattery et al.’s group, [123] North Carolina Colon Cancer Study (NCCCS), [116] and Colon Cancer Family Registry (CCFR).[35] With regard to germline genetic variants and molecular changes, MLH1 rs1800734 promoter SNP has been associated with MSI-high tumors in three independent case-case and case-control studies, [38, 108, 115] and MGMT rs16906252 promoter SNP has been associated with MGMT promoter methylation and loss of expression in colorectal cancer[94] and normal colorectal mucosa and peripheral blood cells in individuals without cancer.[152, 153] These consistent data across different studies increase validity of each other’s findings and support etiologic roles of cigarette smoking, obesity and germline variants in specific pathways of colorectal carcinogenesis. Ultimately, our understanding of these specific neoplasia pathways will clarify areas for disease intervention.
Table 1
Table 1
Molecular pathologic epidemiology studies on possible etiologic factors and molecular changes in colorectal neoplasia
Recently, GWAS have identified a number of candidate susceptibility loci for colorectal cancer.[9, 10] Currently, a significant limitation in interpreting GWAS results is our limited understanding of the functional relevance of risk alleles identified by GWAS. As a promising future direction, a molecular pathologic epidemiology approach can be used to validate findings of GWAS in certain ways. First, if a candidate cancer susceptibility variant is hypothesized to regulate expression of a nearby gene, the relationship between the variant and gene expression in tumor tissue can be examined.[59] Second, if a candidate variant is hypothesized to cause a genetic or epigenetic alteration in a critical pathway, the relationship between the variant and tumoral molecular alterations in the particular pathway can be examined.[134] Specificity of the relationship between the variant and the tumor molecular alterations will provide additional evidence to support a causal effect of the putative cancer susceptibility allele.
Additional examples of studies and findings on three specific areas (energy balance, inflammation, and one-carbon metabolism) will be discussed in later sections because these have been particularly active areas of investigations.
Figure 2 illustrates three basic approaches to investigate the relationship between an exposure (e.g., smoking) and a tumor molecular change (e.g., KRAS mutation). A fourth approach, an interventional cohort study (not illustrated in Figure 2) is a gold standard; however, to date no interventional molecular pathologic epidemiology data have been published.
Figure 2
Figure 2
Comparison of a case-case study design (A), a case-control study design (B) and a prospective cohort study design (C). Smoking status is used as an example of an exposure variable, and KRAS mutation status in colorectal cancer as an outcome variable. (more ...)
The first approach is a “case-case” approach (Figure 2A), where tumors are classified into subtypes according to a molecular feature, and then distributions of an exposure variable of interest among different subtypes are compared. For example, if it is hypothesized that smoking causes KRAS mutation, one may expect to observe that KRAS-mutated cancer patients contain a higher fraction of smokers than KRAS-wild-type cancer patients. A limitation of this approach is that it is not possible to obtain information on distribution of an exposure variable among the background population that has given rise to the cancer cases. Thus, the direction of any association cannot be determined; if there is a positive association between smoking and KRAS-mutated tumors (i.e., a negative association between smoking and KRAS-wild-type tumors), it is uncertain whether smoking protects against KRAS-wild-type tumors, or smoking causes KRAS-mutated tumors.
The second approach is a case-control study (Figure 2B), where non-cancer control subjects should ideally be randomly sampled from the background population that has given rise to the cancer cases. In traditional cancer epidemiology, distributions of an exposure of interest between cases and controls are compared. In molecular pathologic epidemiology, one can compare distributions of a given exposure between cancer cases with a specific molecular alteration (e.g., KRAS mutation), cancer cases without the alteration, and controls. If the exposure has caused the particular alteration, it is expected to see a higher fraction of exposed individuals among cancer cases with the alteration but not among cancer cases without the alteration, compared to controls. Nevertheless, case-control approaches in molecular pathologic epidemiology face the same inherent limitations of traditional case-control studies. Such caveats include recall bias, differential selection bias between cases and controls, among others. One advantage of a case-control design over a prospective cohort design is its relative ease to recruit a large number of colorectal cancer cases. Important examples of case-control studies include Colon Cancer Family Registry (CCFR), [26, 34, 35, 39, 56, 66, 76, 77, 79, 80, 106, 107, 154] a population-based case-control study of colorectal cancer by Slattery et al., [4145, 113115, 123139, 155, 156] and the Molecular Epidemiology of Colorectal Cancer Study (MECCS) in northern Israel.[59, 110, 111, 157159]
The third approach is a prospective cohort study (Figure 2C), which is less prone to potential bias related to case-case and case-control designs. A nested case-control design, a case-case design within a prospective cohort study, and a case-cohort design[160] are derivatives of prospective cohort studies. In molecular pathologic epidemiology, investigators examine the incidence rates of cancer with a specific alteration (e.g., KRAS mutation) in exposed vs. unexposed individuals, as well as the incidence rates of cancer without the specific alteration in exposed vs. unexposed individuals. If the exposure causes the particular alteration, one would expect to see a higher incidence rate of cancer with the alteration in exposed individuals than in unexposed individuals, and similar incidence rates of cancer without the alteration between the exposed and unexposed groups. In molecular pathologic epidemiology of colorectal cancer, to date, seven prospective cohort studies have published substantial data: European Prospective Investigation into Cancer and Nutrition (EPIC), [89, 103, 161164] the Health Professionals Follow-up Study (HPFS), [2, 1825, 36, 61, 65, 72, 91101, 118, 119, 121] the Iowa Women’s Health Study (IWHS), [78, 165, 166] the Melbourne Collaborative Cohort Study (MCCS), [53, 167169] the Netherlands Cohort Study (NLCS), [2833, 4648, 64, 8284, 141, 144, 146, 147] the Northern Sweden Health and Disease Study (NSHDS), [142, 170, 171] and the Nurses’ Health Study (NHS).[2, 1825, 36, 61, 65, 72, 91101, 117119, 121, 172] Prospective cohort studies require substantial amounts of participants, follow-up time and funding support, and substantial efforts of researchers and other personnel. Therefore, judicious utilization of the existing resource of prospective cohort studies is a cost effective approach.
As a new direction of molecular pathologic epidemiology, our group has started examining how lifestyle or genetic factors interact with tumor molecular features to influence tumor cell behavior (prognosis or clinical outcome). Table 2 lists studies on interactive prognostic effects of lifestyle or genetic factors and tumoral features in colorectal cancer.[2, 1821, 57, 72, 92, 93, 95101, 173178] In traditional molecular pathology, investigators examine tumoral molecular characteristics to better predict prognosis and response to specific treatments.[11] In addition to tumoral molecular features, lifestyle, environmental or genetic factors likely influence tumor cell behavior through the tumor microenvironment. Lifestyle factors (e.g., physical activity or smoking) or genetic factors (e.g., SNPs or family history) have been shown to influence clinical outcome of colorectal cancer patients.[168, 179185] To better understand how a certain lifestyle, environmental or genetic factor influences tumor cell behavior, it is of interest to examine interactive prognostic effects of the lifestyle, environmental or genetic factor and tumoral molecular features. If a particular exposure is associated with worse outcome only among patients with a specific tumoral molecular change, but not among those without the molecular change, this provides evidence that the exposure factor might influence tumor aggressiveness through that molecular change or pathway. We will discuss specific examples in the following sections.
Table 2
Table 2
Molecular pathologic epidemiology studies to examine interactive prognostic effects of lifestyle or other etiologic factors and tumoral somatic changes in colorectal cancer.
Studies have shown that obesity is associated with worse survival of colon cancer patients.[168, 186189] However, how obesity affects clinical outcome of cancer patients remains largely unknown. In 2008, our group started a new direction of molecular pathologic epidemiology, to examine an interactive prognostic effect of obesity (prediagnosis body mass index, BMI) and FASN (fatty acid synthase) expression in colon cancer.[2] We found that the adverse prognostic effect of obesity was present in patients with FASN-positive colon cancers, but not in patients with FASN-negative colon cancers.[2] These data suggest that excessive energy present in obese patients may contribute to growth and proliferation of tumor cells with FASN activation.[2] This study has opened new opportunities for investigating how lifestyle factors affect tumor cell behavior through cellular molecules. In traditional epidemiology, investigators examine the relationship between an exposure factor (e.g., obesity) and survival of cancer patients regardless of tumor molecular subtype; thus, mechanistic hypotheses remain speculative. For example, it is hypothesized that obesity increases tumor aggressiveness potentially through a certain cellular molecule such as FASN. Without analysis of FASN in tumor, the hypothesis still remains speculative. In molecular pathologic epidemiology, we can specifically test the hypothesis by examining the relations between obesity and patient survival in tumor FASN-positive cases and between obesity and patient survival in tumor FASN-negative cases.[2] If the hypothesis is true, we expect to observe the significant obesity/survival relationship in FASN-positive cases, but not in FASN-negative cases.[2]
Our subsequent investigations have found that a number of other tumor molecular changes interact with prediagnosis BMI to modify tumor aggressiveness.[96, 98, 99] Those tumor changes include STMN1 expression, [96] CDKN1A (p21) expression, [99] and CDKN1B (p27) cellular localization, [98] all of which have been linked to energy balance and related signal transduction pathways.[190193] In addition, our analysis on interactive prognostic effects of physical activity and tumor markers have revealed that postdiagnosis physical activity is beneficial only in patients with CDKN1B-nuclear-positive colon cancers, but not in patients with CDKN1B-altered or lost colon cancers.[174] These results collectively provide evidence for tumor-host interactions (energy balance status and tumor molecular alterations) that influence tumor cell behavior.
Epidemiological studies have shown that regular use of aspirin or non-steroidal anti-inflammatory drug (NSAID) is associated with decreased risks of colorectal cancer and adenomas.[194203] Randomized trials have confirmed that regular use of aspirin[204206] or other inhibitors of PTGS2 (prostaglandin endoperoxide synthase 2, cyclooxygenase-2, COX-2)[207209] decreases risk of developing colorectal adenomas. Experimental evidence suggests an important role of PTGS2 in colorectal carcinogenesis.[210212] Thus, it is hypothesized that PTGS2 (COX-2) inhibitors may prevent colorectal tumor through inhibition of PTGS2. Molecular pathologic epidemiology research has provided further insights on mechanisms of cancer preventive effect of PTGS2 inhibition. Utilizing the Nurses’ Health Study (NHS) and the Health Professionals Follow-up Study (HPFS), we found that regular aspirin use decreases risk of cancers with PTGS2 (COX-2) overexpression, but not that of cancers without PTGS2 overexpression.[36] This specific inverse association between aspirin use and incidence of PTGS2-positive cancer provides further evidence for the carcinogenic role of PTGS2 (COX-2), and for the role of PTGS2 (COX-2) inhibitors in cancer prevention.
We have also shown that PTGS2 (COX-2) overexpression is associated with aggressive tumor behavior, [176] and that regular aspirin use after colorectal cancer diagnosis significantly decreases mortality in patients with PTGS2-positive cancers, but not in patients with PTGS2-negative cancers.[173] This specificity of the relation between aspirin use and low mortality in PTGS2-expressing cases provides additional evidence for the role of PTGS2 inhibition in prevention of cancer progression.
Colorectal cancer is a complex disease resulting from both genetic and epigenetic alterations, including abnormal DNA methylation patterns.[213, 214] DNA hypomethylation at LINE-1 repetitive elements has been associated with poor prognosis in colon cancer.[177] LINE-1 hypomethylation may provide alternative promoter activation, [215] and contribute to non-coding RNA expression that regulates expression of many genes.[216, 217] Retrotransposons activated by DNA hypomethylation may transpose themselves throughout the genome, leading to gene disruptions[218] and chromosomal instability (CIN).[219, 220] In addition, there exists a specific tumor phenotype – the CpG island methylator phenotype (CIMP), characterized by propensity for widespread CpG island hypermethylation.[221] High degree of CIMP (CIMP-high) is a distinct phenotype, [5, 15, 222225] and the most common cause of microsatellite instability (MSI) in colorectal cancer through epigenetic inactivation of a mismatch repair gene MLH1.[226230] Independent of MSI, CIMP-high is associated with older age, female gender, proximal tumor location, [228, 231, 232] high tumor grade, signet ring cells, [233] BRAF mutation, [228, 231, 232] wild-type TP53, [228, 234] inactive PTGS2 (COX-2), [234] inactive CTNNB1 (β-catenin), [235] loss of CDKN1B (p27), [236] high-level LINE-1 methylation, [231, 237] stable chromosomes, [238, 239] and expression of DNMT3B, [175] CDKN1A (p21), [240] and SIRT1.[92] Thus, CIMP status is a potential confounder for many locus-specific tumor variables.[5] Moreover, the relationship between KRAS mutation and another type of CIMP {“CIMP-low”, [5, 231, 241245] “CIMP2”, [246] and “intermediate-methylation epigenotype”[247]} has been demonstrated. Importantly, different CIMP subtypes appear to show different locus-specific methylation patterns.[231, 244, 246248] Accumulating evidence suggests that CIMP-high colorectal cancers arise through the “serrated pathway”, [249259] which has substantial implications in studies on colorectal polyps and adenomas, because of potential differences in detection rates, removal rates and natural histories between conventional and serrated precursor lesions. The elucidation of mechanisms of epigenetic aberrations will improve our understanding of the carcinogenic process.
One-carbon metabolism is considered to play major roles in DNA synthesis and methylation reactions.[260] In most epidemiological studies, low folate intake has been associated with higher risks of colorectal cancer[261266] and adenoma.[266269] However, results from randomized clinical trials of folic acid supplementation among individuals with a prior history of colorectal adenomas have been disappointing. A meta-analysis of these randomized trials[270] has demonstrated that folic acid supplementation does not decrease adenoma recurrence risk after short-term follow-up. In fact, one randomized trial[271, 272] suggested a potential tumor-promoting effect of folic acid supplementation. Thus, there has been much controversy on dietary folate, folic acid fortification/supplementation and risks of colorectal neoplasia.[270, 272274] Examining molecular changes in tumor cells in relation to folate intake may provide additional insights on the possible link between one-carbon metabolism and carcinogenesis.
Folate deficiency is associated with an increase in de novo DNA methyltransferase activity.[275, 276] Altered levels of folate metabolites and intermediates are associated with aberrant DNA methylation patterns.[70, 277] The MTHFR rs1801131 polymorphism (codon 429) has been associated with colon cancer with the CpG island methylator phenotype (CIMP) in case-control and case-case studies, [41, 61] although another case-cohort study has not confirmed this finding.[48] Notably, the latter case-cohort study has shown that the MTR rs1805087 polymorphism is inversely associated with CIMP in men.[48] Collectively, genetic variations in one-carbon metabolism pathways may play roles in epigenetic events during carcinogenesis.
With regard to global DNA methylation level, experimental data support a link between folate level and cellular DNA methylation level.[278280] In our prospective cohort studies, subjects reporting low folate intake experienced an increased risk of colon cancer with global DNA (LINE-1) hypomethylation, but folate intake had no influence on a risk of LINE-1 hypermethylated cancer.[119] In a randomized, double-blinded, placebo-controlled trial, folic acid supplementation was inversely associated with global DNA hypomethylation in normal colon mucosa.[281] However, in the Aspirin/Folate Polyp Prevention Trial, there was no significant influence on LINE-1 methylation in normal colon mucosa by folic acid supplementation.[282]
Besides influence of one-carbon nutrients, local DNA sequence context may influence assembly of a methylation reaction machinery and locus-specific DNA methylation. Studies have shown that cis-acting elements cause allele-specific methylation in the mammalian genome.[283286] Thus, germline variations in putative cis-acting elements may influence epigenetic status; such examples include MLH1 rs1800734 promoter SNP, [38, 108, 115] and MGMT rs16906252 promoter SNP.[94, 152, 153]
Although molecular pathologic epidemiology is a very promising field, a number of challenges exist. Molecular pathologic epidemiology research has the same set of inherent limitations as traditional epidemiology research and pathology research, including those related to bias (e.g., selection bias, recall bias, measurement errors, and misclassification), confounding, generalisability and causal inference. In addition, there are other issues specific to molecular pathologic epidemiology. Many of the issues have previously been discussed.[287289] In this section, we systematically discuss various issues specific to molecular pathologic epidemiology and propose measures to overcome those issues.
1. Selection bias
Since we can analyze only a finite number of cases, controls, or cohort participants, selection bias is a universal issue. The use of cancer cases in one or a few hospitals may be a source of selection bias since patients have selected the one or few hospitals based on referral or their own preference. To decrease bias due to differential hospital selection by patients, a large population-based investigation or multicenter investigation is desirable. To minimize selection bias, it is necessary to make the best effort to retrieve enough tissue materials from as many hospitals and pathology laboratories as possible.
In molecular pathologic epidemiology, a tumor tissue retrieval rate is almost inevitably less than 100%.[156, 290] Patient and disease characteristics may influence the tissue retrieval rate. Specimen availability may be related to tumor size and patient outcome;[291] this may be especially true in colorectal adenomas. A large epidemiological study has shown that tumor tissue retrieval rates in early-stage intramucosal cancer and advanced stage IV cancer are lower compared to stage I-III cancers.[156] Nonetheless, both case-control and prospective cohort studies have shown that demographic features and dietary and other exposure factors are similar between cases with tumor tissue analyzed and those without available tumor tissue.[36, 156]
Another source of selection bias is treatment before surgical resection of tumor. While this has not been a major issue in colon cancer, treatment prior to surgical resection of rectal cancer is now common. First, selection of patients for treatment is likely nonrandom and influenced by many factors. Second, treatment before surgery can eliminate most or all tumor cells in resection specimens in some patients, while treatment is ineffective in other patients. Thus, availability of ample tumor cells is determined by treatment effect which is likely influenced by tumor molecular characteristics. Third, treatment itself can introduce molecular changes which may not naturally occur. Thus, if treatment is administered before surgical resection, it is recommended to collect tumor specimens that were taken prior to such treatment.
2. Sample size
In studies on tumor prognostic markers, a frequent problem is using inappropriate sample sizes that are too small to conduct robust statistical analysis and draw meaningful conclusions.[292] Small sample sizes lead to a number of problems including a large variation of an effect estimate with wide confidence limits, random and nonrandom selection bias, and publication bias. Publication bias refers to a phenomenon that studies with null findings have a higher likelihood of being unwritten and unpublished compared to studies with “significant” findings. In the published literature, small underpowered studies with “significant” findings have been over-represented, relative to small underpowered studies with null findings. In a meta-analysis of TP53 alterations and head and neck cancer outcome, [293] not only publication bias, but also selective presentations of data in many small studies appear to be a serious problem that can lead to biased and misleading conclusions.
In molecular pathologic epidemiology, sample size is a substantial issue. Even when a parent study is large-scale, any given molecular pathologic epidemiology study requires multiple exclusions based on availability of tumor tissue materials and valid assay results. In molecular pathologic epidemiology, by definition, a subset analysis for different outcomes (a molecular change present vs. absent) is performed. A sample size for a smaller subset may not be large enough to provide adequate statistical power. Population-based studies have shown that molecular subtyping is often skewed: BRAF mutation (10–15% mutated vs. 85–90% wild-type), [53, 228, 294, 295] PIK3CA mutation (15–20% mutated vs. 80–85% wild-type), [296, 297] NRAS mutation (2% mutated vs. 98% wild-type), [65] MSI (15% high vs. 85% low/MSS), [35, 64, 126, 231] KRAS mutation (35–40% mutated vs. 60–65% wild-type), [30, 242, 298] or CIMP (10–20% high vs. 80–90% low/negative;[170, 243, 294, 299] or 15–30% positive vs. 70–85% negative[53, 64, 228]). Therefore, for any future cancer epidemiology research, one should design a study as large as possible, because tumor molecular subtyping is increasingly common in cancer epidemiology.
3. Measurement error and misclassification
In addition to measurement error and misclassification in exposure variables and covariates, nontrivial measurement error and misclassification may be present in an outcome variable, i.e., tumor molecular subtyping. This particular combination (i.e., measurement errors and misclassification in both exposure and outcome assessments) is a unique challenge in molecular pathologic epidemiology.
Tumor molecular and immunohistochemical assays should be validated and monitored for its precision and accuracy. In immunohistochemical analysis, it is possible to observe a correlative error between two completely unrelated proteins because of the presence of poor quality tissue specimens, which fail to react with any specific antibody leading to false negative results.[5] Thus, in such poor quality cases, negativity of one protein tends to coincide with negativity of another protein even with the absence of any true association. Since those cases with poor quality materials are inevitably present in large-scale epidemiology studies, one should be cautious when interpreting an apparent positive correlation between two proteins by immunohistochemistry assays.[5] The presence of internal control in tumor tissue may solve this problem to some extent.
To decrease run-to-run variability in immunohistochemical assays, the use of tissue microarray (TMA) is recommended.[289] All cases in the same TMA slide can be processed and treated in a similar manner during immunostaining. We recommend inclusion in TMA of normal tissue adjacent to tumor tissue from the same individual whenever normal tissue is available. Normal colon mucosa may serve as an internal control. Tissue cores can be separately taken from tumor edge and center and labeled as such. Because TMA is cost efficient for a large-scale study, any epidemiology study or clinical trial should consider TMA for immunohistochemical evaluations of expression of multiple proteins.
4. Multiple hypothesis testing
Multiple hypothesis testing is a common issue in epidemiology, and is even more problematic in molecular pathologic epidemiology. By definition, molecular pathologic epidemiology involves subset analyses on tumor subtypes, which exacerbate the potential for false positive findings due to multiple hypothesis testing.[1] If one crosses a wide range of lifestyle and other exposure variables with a variety of molecular changes, the likelihood for a nominally significant chance finding is high.[1] In this post-genomic era, we can potentially generate a countless number of hypotheses as we have already experienced in GWAS.[300302] False positive findings can potentially confuse the literature, scientific field, and clinical practice.[303] If a higher significance level is required, then we require to have a large sample size.
An important question is whether the molecular pathologic epidemiology approach should be hypothesis-driven or exploratory as GWAS. If the former is the case, how can we prioritize various hypotheses to allocate our limited resource? If the latter is the case, how can we make formal rules of statistical significance and validation of findings? The border between hypothesis-driven research and exploratory research may not be distinct in molecular pathologic epidemiology. For example, a proposed link between smoking and MSI-high, CIMP-high or BRAF-mutated colon cancers may be regarded as either exploratory or hypothesis-based. Where do we draw a line between hypothesis testing vs. exploration? At the very least, initial few studies examining the relationship between a certain exposure and a specific molecular change should be regarded as exploratory and hypothesis-generating. Any generated hypothesis needs to be validated by independent datasets.
We acknowledge that any novel hypothesis could at first result from a fortuitous discovery by multiple hypothesis testing. If we successfully implement proper measures, the pace of our new discovery can be much faster than before. To generate and test new hypotheses, validate new findings, solidify new knowledge, and implement new public health recommendations and measures, we should develop an optimal and standardized way of streamlining the sequence of discoveries and validation in molecular pathologic epidemiology.
5. Generalisability
All issues mentioned above affect generalisability of study findings. Many findings by molecular pathologic epidemiology studies (as shown in Tables 1 and and2)2) are yet to be validated in other independent datasets. It is challenging since there is a wide variety in study designs and populations, and differences in tumor molecular assays add further diversity between different studies. On the other hand, because of the presence of such enormous heterogeneity between different studies, consistent findings across different studies can be regarded as generalisable findings.
6. Direct causation of molecular changes vs. selective advantage
Although molecular pathologic epidemiology illuminates carcinogenic mechanisms, it still needs experimental data to confirm a causal relationship. There still remains a question whether an exposure of interest can either directly or indirectly cause a specific molecular change, or create a specific environment which can provide selective advantage for clonal expansion of a cell with a specific molecular change. Tumor molecular alterations may not only represent the interactions of carcinogens with DNA repair mechanisms or epigenetic machinery, but also reflect the tissue-specific selection of those alterations that provide pre-malignant and malignant cells with a clonal growth advantage.
7. How we can examine the process of tumor progression in observational molecular pathologic epidemiology
Since some molecular changes have been known to occur early (e.g., APC loss, KRAS mutation), etiologic factors which appear to cause those early events can be considered to contribute to tumor initiation/progression early in the carcinogenic process. Another way is to analyze colorectal polyp/adenoma and colorectal cancer within the same population, and investigate how an exposure of interest is related to somatic molecular events in cancer and precursor lesions.
8. Multidisciplinary research environment and cross-training and education
Molecular pathologic epidemiology is transdisciplinary and interdisciplinary by nature (see Stokols et al.[304] for the definitions of transdisciplinarity and interdisciplinarity). It requires expertise of diverse fields including, at least, epidemiology, biostatistics, pathology, and oncology. Therefore, collaborative environment is essential, and cross training and education are extremely useful to advance this interdisciplinary area of science. Especially, training in epidemiology and biostatistics during pathology training is very beneficial.[305] Increasing needs and trend for team science rather than solo science have been well documented.[304, 306, 307]
“Molecular Pathologic Epidemiology” is a relatively new, evolving field of epidemiology which is designed to elucidate how various exposures affect initiation, transformation and progression of neoplasia.[1] A new direction of molecular pathologic epidemiology is to investigate interactive effects of dietary or lifestyle exposures and tumoral molecular features on tumor behavior (prognosis or clinical outcome), so that one can attribute the effects of dietary or lifestyle variables to a specific molecular subtype of cancer.[2] A number of hurdles must be overcome because of unique and new challenges which we have not faced in traditional epidemiology research. To overcome those issues, it is necessary to coordinate research effort around the world and to possibly formulate a system where one can discover and validate new findings. As a result, molecular pathologic epidemiology research will continue to provide profound insights on carcinogenic process and help us optimize prevention and treatment strategies.
Acknowledgments
We thank all investigators who have contributed to this emerging multidisciplinary field of science.
Funding: This work was supported by U.S. National Institute of Health [P01 CA87969 (to S.E. Hankinson), P01 CA55075 (to W.C. Willett), P50 CA127003 (to C.S.F.), R01 CA137178 (to A.T.C.), K07 CA122826 (to S.O.), R01 CA151993 (to S.O.)]. The content is solely the responsibility of the authors and does not necessarily represent the official views of NCI or NIH. Funding agencies did not have any role in the decision to submit the manuscript for publication or the writing of the manuscript.
Abbreviations
BMIbody mass index
CCFRColon Cancer Family Registry
CIconfidence interval
CIMPCpG island methylator phenotype
CINchromosomal instability
EPICEuropean Prospective Investigation into Cancer and Nutrition
GWASgenome-wide association study
HPFSHealth Professionals Follow-up Study
HRhazard ratio
KPMCP-UT-MNKaiser Permanente Medical Care Program of Northern California, the state of Utah and the Twin City Metropolitan area of Minnesota (the M Slattery group’s case-control study)
LOHloss of heterozygosity
MCCSMelbourne Collaborative Cohort Study
MSImicrosatellite instability
MECCSMolecular Epidemiology of Colorectal Cancer Study (northern Israel)
MSI-Hmicrosatellite instability-high
MSI-Lmicrosatellite instability-low
MSSmicrosatellite stability
NCCCSNorth Carolina Colon Cancer Study
NHSNurses’ Health Study
NLCSThe Netherlands Cohort Study
NSAIDnon-steroidal anti-inflammatory drug
NSHDSNorthern Sweden Health and Disease Study
ORodds ratio
PTGS2prostaglandin endoperoxide synthase 2 (cyclooxygenase-2, COX-2)
RCTrandomized, placebo-controlled trial
SEERSurveillance Epidemiology, and End Results
SNPsingle nucleotide polymorphism
WBFTWheat Bran Fiber Trial

Footnotes
Competing interest: None to declare.
Copyright licence statement: The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Gut editions and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://group.bmj.com/products/journals/instructions-for-authors/licence-forms).
1. Ogino S, Stampfer M. Lifestyle factors and microsatellite instability in colorectal cancer: The evolving field of molecular pathological epidemiology. J Natl Cancer Inst. 2010;102:365–7. [PMC free article] [PubMed]
2. Ogino S, Nosho K, Meyerhardt JA, et al. Cohort study of fatty acid synthase expression and patient survival in colon cancer. J Clin Oncol. 2008;26:5713–20. [PMC free article] [PubMed]
3. Vogelstein B, Fearon ER, Hamilton SR, et al. Genetic alterations during colorectal-tumor development. N Engl J Med. 1988;319:525–32. [PubMed]
4. Kinzler KW, Vogelstein B. Lessons from hereditary colorectal cancer. Cell. 1996;87:159–70. [PubMed]
5. Ogino S, Goel A. Molecular classification and correlates in colorectal cancer. J Mol Diagn. 2008;10:13–27. [PubMed]
6. Colditz GA, Sellers TA, Trapido E. Epidemiology - identifying the causes and preventability of cancer? Nat Rev Cancer. 2006;6:75–83. [PubMed]
7. Greenwald P, Dunn BK. Landmarks in the history of cancer epidemiology. Cancer Res. 2009;69:2151–62. [PubMed]
8. Chan AT, Giovannucci EL. Primary prevention of colorectal cancer. Gastroenterology. 2010;138:2029–43 e10. [PMC free article] [PubMed]
9. Tenesa A, Dunlop MG. New insights into the aetiology of colorectal cancer from genome-wide association studies. Nat Rev Genet. 2009;10:353–8. [PubMed]
10. Fletcher O, Houlston RS. Architecture of inherited susceptibility to common cancer. Nat Rev Cancer. 2010;10:353–61. [PubMed]
11. Hamilton SR. Targeted therapy of cancer: new roles for pathologists in colorectal cancer. Mod Pathol. 2008;21 (Suppl 2):S23–30. [PubMed]
12. Grady WM, Carethers JM. Genomic and epigenetic instability in colorectal cancer pathogenesis. Gastroenterology. 2008;135:1079–99. [PMC free article] [PubMed]
13. Walther A, Johnstone E, Swanton C, et al. Genetic prognostic and predictive markers in colorectal cancer. Nat Rev Cancer. 2009;9:489–99. [PubMed]
14. Markowitz SD, Bertagnolli MM. Molecular origins of cancer: Molecular basis of colorectal cancer. N Engl J Med. 2009;361:2449–60. [PMC free article] [PubMed]
15. Jass JR. Classification of colorectal cancer based on correlation of clinical, morphological and molecular features. Histopathology. 2007;50:113–30. [PubMed]
16. Soreide K, Nedrebo BS, Knapp JC, et al. Evolving molecular classification by genomic and proteomic biomarkers in colorectal cancer: potential implications for the surgical oncologist. Surg Oncol. 2009;18:31–50. [PubMed]
17. Arain MA, Sawhney M, Sheikh S, et al. CIMP Status of Interval Colon Cancers: Another Piece to the Puzzle. Am J Gastroenterol. 2010;105:1189–95. [PubMed]
18. Baba Y, Nosho K, Shima K, et al. Relationship of CDX2 loss with molecular features and prognosis in colorectal cancer. Clin Cancer Res. 2009;15:4665–73. [PMC free article] [PubMed]
19. Baba Y, Nosho K, Shima K, et al. Aurora-A expression is independently associated with chromosomal instability in colorectal cancer. Neoplasia. 2009;11:418–25. [PMC free article] [PubMed]
20. Baba Y, Nosho K, Shima K, et al. HIF1A overexpression is associated with poor prognosis in a cohort of 731 colorectal cancers. Am J Pathol. 2010;176:2292–301. [PubMed]
21. Baba Y, Nosho K, Shima K, et al. PTGER2 overexpression in colorectal cancer is associated with microsatellite instability, independent of CpG island methylator phenotype. Cancer Epidemiol Biomarkers Prev. 2010;19:822–31. [PMC free article] [PubMed]
22. Baba Y, Huttenhower C, Nosho K, et al. Epigenomic diversity of colorectal cancer indicated by LINE-1 methylation in a database of 869 tumors. Mol Cancer. 2010;9:125. [PMC free article] [PubMed]
23. Baba Y, Nosho K, Shima K, et al. Hypomethylation of the IGF2 DMR in colorectal tumors, detected by bisulfite pyrosequencing, is associated with poor prognosis. Gastroenterology. 2010 in press. [PMC free article] [PubMed]
24. Baba Y, Nosho K, Shima K, et al. Prognostic significance of AMP-activated protein kinase expression and modifying effect of MAPK3/1 in colorectal cancer. Br J Cancer. 2010 in press. [PMC free article] [PubMed]
25. Baba Y, Nosho K, Shima K, et al. Phosphorylated AKT expression is associated with PIK3CA mutation, low stage and favorable outcome in 717 colorectal cancers. Cancer. in press. [PMC free article] [PubMed]
26. Bapat B, Lindor NM, Baron J, et al. The association of tumor microsatellite instability phenotype with family history of colorectal cancer. Cancer Epidemiol Biomarkers Prev. 2009;18:967–75. [PMC free article] [PubMed]
27. Bautista D, Obrador A, Moreno V, et al. Ki-ras mutation modifies the protective effect of dietary monounsaturated fat and calcium on sporadic colorectal cancer. Cancer Epidemiol Biomarkers Prev. 1997;6:57–61. [PubMed]
28. Bongaerts BW, de Goeij AF, van den Brandt PA, et al. Alcohol and the risk of colon and rectal cancer with mutations in the K-ras gene. Alcohol. 2006;38:147–54. [PubMed]
29. Bongaerts BW, de Goeij AF, de Vogel S, et al. Alcohol consumption and distinct molecular pathways to colorectal cancer. Br J Nutr. 2007;97:430–4. [PubMed]
30. Brink M, de Goeij AF, Weijenberg MP, et al. K-ras oncogene mutations in sporadic colorectal cancer in The Netherlands Cohort Study. Carcinogenesis. 2003;24:703–10. [PubMed]
31. Brink M, Weijenberg MP, De Goeij AF, et al. Fat and K-ras mutations in sporadic colorectal cancer in The Netherlands Cohort Study. Carcinogenesis. 2004;25:1619–28. [PubMed]
32. Brink M, Weijenberg MP, de Goeij AF, et al. Meat consumption and K-ras mutations in sporadic colon and rectal cancer in The Netherlands Cohort Study. Br J Cancer. 2005;92:1310–20. [PMC free article] [PubMed]
33. Brink M, Weijenberg MP, de Goeij AF, et al. Dietary folate intake and k-ras mutations in sporadic colon and rectal cancer in The Netherlands Cohort Study. Int J Cancer. 2005;114:824–30. [PubMed]
34. Campbell PT, Curtin K, Ulrich CM, et al. Mismatch repair polymorphisms and risk of colon cancer, tumour microsatellite instability and interactions with lifestyle factors. Gut. 2009;58:661–7. [PMC free article] [PubMed]
35. Campbell PT, Jacobs ET, Ulrich CM, et al. Case-control study of overweight, obesity, and colorectal cancer risk, overall and by tumor microsatellite instability status. J Natl Cancer Inst. 2010;102:391–400. [PMC free article] [PubMed]
36. Chan AT, Ogino S, Fuchs CS. Aspirin and the Risk of Colorectal Cancer in Relation to the Expression of COX-2. New Engl J Med. 2007;356:2131–42. [PubMed]
37. Chang SC, Lin PC, Lin JK, et al. Role of MTHFR polymorphisms and folate levels in different phenotypes of sporadic colorectal cancers. Int J Colorectal Dis. 2007;22:483–9. [PubMed]
38. Chen H, Taylor NP, Sotamaa KM, et al. Evidence for heritable predisposition to epigenetic silencing of MLH1. Int J Cancer. 2007;120:1684–8. [PubMed]
39. Chia VM, Newcomb PA, Bigler J, et al. Risk of microsatellite-unstable colorectal cancer is associated jointly with smoking and nonsteroidal anti-inflammatory drug use. Cancer Res. 2006;66:6877–83. [PubMed]
40. Clarizia AD, Bastos-Rodrigues L, Pena HB, et al. Relationship of the methylenetetrahydrofolate reductase C677T polymorphism with microsatellite instability and promoter hypermethylation in sporadic colorectal cancer. Genet Mol Res. 2006;5:315–22. [PubMed]
41. Curtin K, Slattery ML, Ulrich CM, et al. Genetic polymorphisms in one-carbon metabolism: associations with CpG island methylator phenotype (CIMP) in colon cancer and the modifying effects of diet. Carcinogenesis. 2007;28:1672–9. [PMC free article] [PubMed]
42. Curtin K, Ulrich CM, Samowitz WS, et al. Thymidylate synthase polymorphisms and colon cancer: associations with tumor stage, tumor characteristics and survival. Int J Cancer. 2007;120:2226–32. [PubMed]
43. Curtin K, Samowitz WS, Wolff RK, et al. Assessing tumor mutations to gain insight into base excision repair sequence polymorphisms and smoking in colon cancer. Cancer Epidemiol Biomarkers Prev. 2009;18:3384–8. [PMC free article] [PubMed]
44. Curtin K, Samowitz WS, Wolff RK, et al. MSH6 G39E polymorphism and CpG island methylator phenotype in colon cancer. Mol Carcinog. 2009;48:989–94. [PMC free article] [PubMed]
45. Curtin K, Samowitz WS, Wolff RK, et al. Somatic alterations, metabolizing genes and smoking in rectal cancer. Int J Cancer. 2009;125:158–64. [PMC free article] [PubMed]
46. de Vogel S, van Engeland M, Luchtenborg M, et al. Dietary folate and APC mutations in sporadic colorectal cancer. J Nutr. 2006;136:3015–21. [PubMed]
47. de Vogel S, Bongaerts BW, Wouters KA, et al. Associations of dietary methyl donor intake with MLH1 promoter hypermethylation and related molecular phenotypes in sporadic colorectal cancer. Carcinogenesis. 2008;29:1765–73. [PubMed]
48. de Vogel S, Wouters KA, Gottschalk RW, et al. Genetic variants of methyl metabolizing enzymes and epigenetic regulators: associations with promoter CpG island hypermethylation in colorectal cancer. Cancer Epidemiol Biomarkers Prev. 2009;18:3086–96. [PubMed]
49. Diergaarde B, Vrieling A, van Kraats AA, et al. Cigarette smoking and genetic alterations in sporadic colon carcinomas. Carcinogenesis. 2003;24:565–71. [PubMed]
50. Diergaarde B, Braam H, van Muijen GN, et al. Dietary factors and microsatellite instability in sporadic colon carcinomas. Cancer Epidemiol Biomarkers Prev. 2003;12:1130–6. [PubMed]
51. Diergaarde B, van Geloof WL, van Muijen GN, et al. Dietary factors and the occurrence of truncating APC mutations in sporadic colon carcinomas: a Dutch population-based study. Carcinogenesis. 2003;24:283–90. [PubMed]
52. Eaton AM, Sandler R, Carethers JM, et al. 5,10-methylenetetrahydrofolate reductase 677 and 1298 polymorphisms, folate intake, and microsatellite instability in colon cancer. Cancer Epidemiol Biomarkers Prev. 2005;14:2023–9. [PubMed]
53. English DR, Young JP, Simpson JA, et al. Ethnicity and risk for colorectal cancers showing somatic BRAF V600E mutation or CpG island methylator phenotype. Cancer Epidemiol Biomarkers Prev. 2008;17:1774–80. [PubMed]
54. Fernandez-Peralta AM, Daimiel L, Nejda N, et al. Association of polymorphisms MTHFR C677T and A1298C with risk of colorectal cancer, genetic and epigenetic characteristic of tumors, and response to chemotherapy. Int J Colorectal Dis. 2010;25:141–51. [PubMed]
55. Ferraz JM, Zinzindohoue F, Lecomte T, et al. Impact of GSTT1, GSTM1, GSTP1 and NAT2 genotypes on KRAS2 and TP53 gene mutations in colorectal cancer. Int J Cancer. 2004;110:183–7. [PubMed]
56. Figueiredo JC, Levine AJ, Lee WH, et al. Genes involved with folate uptake and distribution and their association with colorectal cancer risk. Cancer Causes Control. 2010;21:597–608. [PMC free article] [PubMed]
57. Firestein R, Shima K, Nosho K, et al. CDK8 expression in 470 colorectal cancers in relation to beta-catenin activation, other molecular alterations and patient survival. Int J Cancer. 2010;126:2863–73. [PMC free article] [PubMed]
58. Gonzalo V, Lozano JJ, Munoz J, et al. Aberrant gene promoter methylation associated with sporadic multiple colorectal cancer. PLoS One. 2010;5:e8777. [PMC free article] [PubMed]
59. Gruber SB, Moreno V, Rozek LS, et al. Genetic variation in 8q24 associated with risk of colorectal cancer. Cancer Biol Ther. 2007;6:1143–7. [PubMed]
60. Hansen TF, Sorensen FB, Spindler KL, et al. Microvessel density and the association with single nucleotide polymorphisms of the vascular endothelial growth factor receptor 2 in patients with colorectal cancer. Virchows Arch. 2010 in press. [PubMed]
61. Hazra A, Fuchs CS, Kawasaki T, et al. Germline polymorphisms in the one-carbon metabolism pathway and DNA methylation in colorectal cancer. Cancer Causes Control. 2010:331–45. [PMC free article] [PubMed]
62. Huang CC, Chien WP, Wong RH, et al. NAT2 fast acetylator genotype and MGMT promoter methylation may contribute to gender difference in K-RAS mutation occurrence in Taiwanese colorectal cancer. Environ Mol Mutagen. 2009;50:127–33. [PubMed]
63. Hubner RA, Lubbe S, Chandler I, et al. MTHFR C677T has differential influence on risk of MSI and MSS colorectal cancer. Hum Mol Genet. 2007;16:1072–7. [PubMed]
64. Hughes LA, van den Brandt PA, de Bruine AP, et al. Early life exposure to famine and colorectal cancer risk: a role for epigenetic mechanisms. PLoS One. 2009;4:e7951. [PMC free article] [PubMed]
65. Irahara N, Baba Y, Nosho K, et al. NRAS mutations are rare in colorectal cancer. Diagn Mol Pathol. 2010 in press. [PMC free article] [PubMed]
66. Jacobs ET, Martinez ME, Campbell PT, et al. Genetic variation in the retinoid X receptor and calcium-sensing receptor, and risk of colorectal cancer in the Colon Cancer Family Registry. Carcinogenesis. 2010 in press. [PMC free article] [PubMed]
67. Jensen LH, Lindebjerg J, Cruger DG, et al. Microsatellite instability and the association with plasma homocysteine and thymidylate synthase in colorectal cancer. Cancer Invest. 2008;26:583–9. [PubMed]
68. Kang MY, Lee BB, Ji YI, et al. Association of interindividual differences in p14ARF promoter methylation with single nucleotide polymorphism in primary colorectal cancer. Cancer. 2008;112:1699–707. [PubMed]
69. Karpinski P, Myszka A, Ramsey D, et al. Polymorphisms in methyl-group metabolism genes and risk of sporadic colorectal cancer with relation to the CpG island methylator phenotype. Cancer Epidemiol. 2010;34:338–44. [PubMed]
70. Kawakami K, Ruszkiewicz A, Bennett G, et al. The folate pool in colorectal cancers is associated with DNA hypermethylation and with a polymorphism in methylenetetrahydrofolate reductase. Clin Cancer Res. 2003;9:5860–5. [PubMed]
71. Konishi K, Shen L, Jelinek J, et al. Concordant DNA methylation in synchronous colorectal carcinomas. Cancer Prev Res (Phila Pa) 2009;2:814–22. [PMC free article] [PubMed]
72. Kure S, Nosho K, Baba Y, et al. Vitamin D receptor expression is associated with PIK3CA and KRAS mutations in colorectal cancer. Cancer Epidemiol Biomarkers Prev. 2009;18:2765–72. [PMC free article] [PubMed]
73. Lafuente MJ, Casterad X, Trias M, et al. NAD(P)H:quinone oxidoreductase-dependent risk for colorectal cancer and its association with the presence of K-ras mutations in tumors. Carcinogenesis. 2000;21:1813–9. [PubMed]
74. Langerod A, Bukholm IR, Bregard A, et al. The TP53 codon 72 polymorphism may affect the function of TP53 mutations in breast carcinomas but not in colorectal carcinomas. Cancer Epidemiol Biomarkers Prev. 2002;11:1684–8. [PubMed]
75. Laso N, Mas S, Jose Lafuente M, et al. Decrease in specific micronutrient intake in colorectal cancer patients with tumors presenting Ki-ras mutation. Anticancer Res. 2004;24:2011–20. [PubMed]
76. Levine AJ, Figueiredo JC, Lee W, et al. Genetic variability in the MTHFR gene and colorectal cancer risk using the colorectal cancer family registry. Cancer Epidemiol Biomarkers Prev. 2010;19:89–100. [PMC free article] [PubMed]
77. Levine AJ, Figueiredo JC, Lee W, et al. A candidate gene study of folate-associated one carbon metabolism genes and colorectal cancer risk. Cancer Epidemiol Biomarkers Prev. 2010;19:1812–21. [PMC free article] [PubMed]
78. Limsui D, Vierkant RA, Tillmans LS, et al. Cigarette Smoking and Colorectal Cancer Risk by Molecularly Defined Subtypes. J Natl Cancer Inst. 2010;102:1012–22. [PMC free article] [PubMed]
79. Lindor NM, Rabe KG, Petersen GM, et al. Parent of origin effects on age at colorectal cancer diagnosis. Int J Cancer. 2010;127:361–6. [PMC free article] [PubMed]
80. Lindor NM, Yang P, Evans I, et al. Alpha-1-antitrypsin deficiency and smoking as risk factors for mismatch repair deficient colorectal cancer: A study from the colon cancer family registry. Mol Genet Metab. 2010;99:157–9. [PMC free article] [PubMed]
81. Lubbe SJ, Webb EL, Chandler IP, et al. Implications of familial colorectal cancer risk profiles and microsatellite instability status. J Clin Oncol. 2009;27:2238–44. [PubMed]
82. Luchtenborg M, Weijenberg MP, de Goeij AF, et al. Meat and fish consumption, APC gene mutations and hMLH1 expression in colon and rectal cancer: a prospective cohort study (The Netherlands) Cancer Causes Control. 2005;16:1041–54. [PubMed]
83. Luchtenborg M, Weijenberg MP, Kampman E, et al. Cigarette smoking and colorectal cancer: APC mutations, hMLH1 expression, and GSTM1 and GSTT1 polymorphisms. Am J Epidemiol. 2005;161:806–15. [PubMed]
84. Luchtenborg M, Weijenberg MP, Wark PA, et al. Mutations in APC, CTNNB1 and K-ras genes and expression of hMLH1 in sporadic colorectal carcinomas from the Netherlands Cohort Study. BMC Cancer. 2005;5:160. [PMC free article] [PubMed]
85. Martinez ME, Maltzman T, Marshall JR, et al. Risk factors for Ki-ras protooncogene mutation in sporadic colorectal adenomas. Cancer Res. 1999;59:5181–5. [PubMed]
86. Mas S, Lafuente MJ, Crescenti A, et al. Lower specific micronutrient intake in colorectal cancer patients with tumors presenting promoter hypermethylation in p16(INK4a), p4(ARF) and hMLH1. Anticancer Res. 2007;27:1151–6. [PubMed]
87. Mokarram P, Naghibalhossaini F, Saberi Firoozi M, et al. Methylenetetrahydrofolate reductase C677T genotype affects promoter methylation of tumor-specific genes in sporadic colorectal cancer through an interaction with folate/vitamin B12 status. World J Gastroenterol. 2008;14:3662–71. [PMC free article] [PubMed]
88. Naghibalhossaini F, Mokarram P, Khalili I, et al. MTHFR C677T and A1298C variant genotypes and the risk of microsatellite instability among Iranian colorectal cancer patients. Cancer Genet Cytogenet. 2010;197:142–51. [PubMed]
89. Naguib A, Mitrou PN, Gay LJ, et al. Dietary, lifestyle and clinicopathological factors associated with BRAF and K-ras mutations arising in distinct subsets of colorectal cancers in the EPIC Norfolk study. BMC Cancer. 2010;10:99. [PMC free article] [PubMed]
90. Newcomb PA, Zheng Y, Chia VM, et al. Estrogen plus progestin use, microsatellite instability, and the risk of colorectal cancer in women. Cancer Res. 2007;67:7534–9. [PubMed]
91. Nosho K, Kure S, Irahara N, et al. A prospective cohort study shows unique epigenetic, genetic, and prognostic features of synchronous colorectal cancers. Gastroenterology. 2009;137:1609–20.e3. [PMC free article] [PubMed]
92. Nosho K, Shima K, Irahara N, et al. SIRT1 histone deacetylase expression is associated with microsatellite instability and CpG island methylator phenotype in colorectal cancer. Mod Pathol. 2009;22:922–32. [PMC free article] [PubMed]
93. Nosho K, Shima K, Kure S, et al. JC virus T-antigen in colorectal cancer is associated with p53 expression and chromosomal instability, independent of CpG island methylator phenotype. Neoplasia. 2009;11:87–95. [PMC free article] [PubMed]
94. Ogino S, Hazra A, Tranah GJ, et al. MGMT germline polymorphism is associated with somatic MGMT promoter methylation and gene silencing in colorectal cancer. Carcinogenesis. 2007;28:1985–90. [PubMed]
95. Ogino S, Shima K, Baba Y, et al. Colorectal cancer expression of peroxisome proliferator-activated receptor-gamma (PPARG, PPARgamma) is associated with good prognosis. Gastroenterology. 2009;136:1242–50. [PMC free article] [PubMed]
96. Ogino S, Nosho K, Baba Y, et al. A cohort study of STMN1 expression in colorectal cancer: body mass index and prognosis. Am J Gastroenterol. 2009;104:2047–56. [PMC free article] [PubMed]
97. Ogino S, Nosho K, Kirkner GJ, et al. PIK3CA mutation is associated with poor prognosis among patients with curatively resected colon cancer. J Clin Oncol. 2009;27:1477–84. [PMC free article] [PubMed]
98. Ogino S, Shima K, Nosho K, et al. A cohort study of p27 localization in colon cancer, body mass index, and patient survival. Cancer Epidemiol Biomarkers Prev. 2009;18:1849–58. [PMC free article] [PubMed]
99. Ogino S, Nosho K, Shima K, et al. p21 expression in colon cancer and modifying effects of patient age and body mass index on prognosis. Cancer Epidemiol Biomarkers Prev. 2009;18:2513–21. [PMC free article] [PubMed]
100. Ogino S, Nosho K, Irahara N, et al. A cohort study of cyclin d1 expression and prognosis in 602 colon cancer cases. Clin Cancer Res. 2009;15:4431–8. [PMC free article] [PubMed]
101. Ogino S, Nosho K, Irahara N, et al. Prognostic significance and molecular associations of 18q loss of heterozygosity: a cohort study of microsatellite stable colorectal cancers. J Clin Oncol. 2009;26:5713–20. [PMC free article] [PubMed]
102. Oyama K, Kawakami K, Maeda K, et al. The association between methylenetetrahydrofolate reductase polymorphism and promoter methylation in proximal colon cancer. Anticancer Res. 2004;24:649–54. [PubMed]
103. Park JY, Mitrou PN, Keen J, et al. Lifestyle factors and p53 mutation patterns in colorectal cancer patients in the EPIC-Norfolk study. Mutagenesis. 2010;25:351–8. [PubMed]
104. Paz MF, Avila S, Fraga MF, et al. Germ-line variants in methyl-group metabolism genes and susceptibility to DNA methylation in normal tissues and human primary tumors. Cancer Res. 2002;62:4519–24. [PubMed]
105. Plaschke J, Schwanebeck U, Pistorius S, et al. Methylenetetrahydrofolate reductase polymorphisms and risk of sporadic and hereditary colorectal cancer with or without microsatellite instability. Cancer Lett. 2003;191:179–85. [PubMed]
106. Poynter JN, Haile RW, Siegmund KD, et al. Associations between smoking, alcohol consumption, and colorectal cancer, overall and by tumor microsatellite instability status. Cancer Epidemiol Biomarkers Prev. 2009;18:2745–50. [PMC free article] [PubMed]
107. Poynter JN, Jacobs ET, Figueiredo JC, et al. Genetic Variation in the Vitamin D Receptor (VDR) and the Vitamin D-Binding Protein (GC) and Risk for Colorectal Cancer: Results from the Colon Cancer Family Registry. Cancer Epidemiol Biomarkers Prev. 2010;19:525–36. [PMC free article] [PubMed]
108. Raptis S, Mrkonjic M, Green RC, et al. MLH1 -93G>A promoter polymorphism and the risk of microsatellite-unstable colorectal cancer. J Natl Cancer Inst. 2007;99:463–74. [PubMed]
109. Ricciardiello L, Goel A, Mantovani V, et al. Frequent loss of hMLH1 by promoter hypermethylation leads to microsatellite instability in adenomatous polyps of patients with a single first-degree member affected by colon cancer. Cancer Res. 2003;63:787–92. [PubMed]
110. Rozek LS, Lipkin SM, Fearon ER, et al. CDX2 polymorphisms, RNA expression, and risk of colorectal cancer. Cancer Res. 2005;65:5488–92. [PubMed]
111. Rozek LS, Herron CM, Greenson JK, et al. Smoking, gender, and ethnicity predict somatic BRAF mutations in colorectal cancer. Cancer Epidemiol Biomarkers Prev. 2010;19:838–43. [PMC free article] [PubMed]
112. Samowitz WS, Slattery ML, Kerber RA. Microsatellite instability in human colonic cancer is not a useful clinical indicator of familial colorectal cancer. Gastroenterology. 1995;109:1765–71. [PubMed]
113. Samowitz WS, Wolff RK, Ma KN, et al. Polymorphisms in insulin-related genes predispose to specific KRAS2 and TP53 mutations in colon cancer. Mutat Res. 2006;595:117–24. [PubMed]
114. Samowitz WS, Albertsen H, Sweeney C, et al. Association of smoking, CpG island methylator phenotype, and V600E BRAF mutations in colon cancer. J Natl Cancer Inst. 2006;98:1731–8. [PubMed]
115. Samowitz WS, Curtin K, Wolff RK, et al. The MLH1 -93 G>A promoter polymorphism and genetic and epigenetic alterations in colon cancer. Genes Chromosomes Cancer. 2008;47:835–44. [PMC free article] [PubMed]
116. Satia JA, Keku T, Galanko JA, et al. Diet, lifestyle, and genomic instability in the north Carolina colon cancer study. Cancer Epidemiol Biomarkers Prev. 2005;14:429–36. [PubMed]
117. Schernhammer ES, Ogino S, Fuchs CS. Folate intake and risk of colon cancer in relation to p53 status. Gastroenterology. 2008;135:770–80. [PMC free article] [PubMed]
118. Schernhammer ES, Giovannuccci E, Fuchs CS, et al. A prospective study of dietary folate and vitamin B and colon cancer according to microsatellite instability and KRAS mutational status. Cancer Epidemiol Biomarkers Prev. 2008;17:2895–8. [PMC free article] [PubMed]
119. Schernhammer ES, Giovannucci E, Kawasaki T, et al. Dietary folate, alcohol, and B vitamins in relation to LINE-1 hypomethylation in colon cancer. Gut. 2010;59:794–9. [PMC free article] [PubMed]
120. Shannon B, Gnanasampanthan S, Beilby J, et al. A polymorphism in the methylenetetrahydrofolate reductase gene predisposes to colorectal cancers with microsatellite instability. Gut. 2002;50:520–4. [PMC free article] [PubMed]
121. Shima K, Nosho K, Baba Y, et al. Prognostic significance of CDKN2A (p16) promoter methylation and loss of expression in 902 colorectal cancers: cohort study and literature review. Int J Cancer. 2010 in press. [PMC free article] [PubMed]
122. Sinicrope FA, Foster NR, Sargent DJ, et al. Obesity Is an Independent Prognostic Variable in Colon Cancer Survivors. Clin Cancer Res. 2010;16:1884–93. [PMC free article] [PubMed]
123. Slattery ML, Curtin K, Anderson K, et al. Associations between cigarette smoking, lifestyle factors, and microsatellite instability in colon tumors. J Natl Cancer Inst. 2000;92:1831–6. [PubMed]
124. Slattery ML, Curtin K, Anderson K, et al. Associations between dietary intake and Ki-ras mutations in colon tumors: a population-based study. Cancer Res. 2000;60:6935–41. [PubMed]
125. Slattery ML, Anderson K, Curtin K, et al. Lifestyle factors and Ki-ras mutations in colon cancer tumors. Mutat Res. 2001;483:73–81. [PubMed]
126. Slattery ML, Anderson K, Curtin K, et al. Dietary intake and microsatellite instability in colon tumors. Int J Cancer. 2001;93:601–7. [PubMed]
127. Slattery ML, Potter JD, Curtin K, et al. Estrogens Reduce and Withdrawal of Estrogens Increase Risk of Microsatellite Instability-positive Colon Cancer. Cancer Res. 2001;61:126–30. [PubMed]
128. Slattery ML, Curtin K, Schaffer D, et al. Associations between family history of colorectal cancer and genetic alterations in tumors. Int J Cancer. 2002;97:823–7. [PubMed]
129. Slattery ML, Curtin K, Ma K, et al. Diet activity, and lifestyle associations with p53 mutations in colon tumors. Cancer Epidemiol Biomarkers Prev. 2002;11:541–8. [PubMed]
130. Slattery ML, Curtin K, Ma K, et al. GSTM-1 and NAT2 and genetic alterations in colon tumors. Cancer Causes Control. 2002;13:527–34. [PubMed]
131. Slattery ML, Curtin K, Wolff R, et al. PPARgamma and colon and rectal cancer: associations with specific tumor mutations, aspirin, ibuprofen and insulin-related genes (United States) Cancer Causes Control. 2006;17:239–49. [PubMed]
132. Slattery ML, Curtin K, Sweeney C, et al. Diet and lifestyle factor associations with CpG island methylator phenotype and BRAF mutations in colon cancer. Int J Cancer. 2007;120:656–63. [PubMed]
133. Slattery ML, Wolff RK, Curtin K, et al. Colon tumor mutations and epigenetic changes associated with genetic polymorphism: insight into disease pathways. Mutat Res. 2009;660:12–21. [PMC free article] [PubMed]
134. Slattery ML, Herrick J, Curtin K, et al. Increased Risk of Colon Cancer Associated with a Genetic Polymorphism of SMAD7. Cancer Res. 2010;70:1479–85. [PMC free article] [PubMed]
135. Slattery ML, Curtin K, Wolff RK, et al. Diet, physical activity, and body size associations with rectal tumor mutations and epigenetic changes. Cancer Causes Control. 2010 in press. [PMC free article] [PubMed]
136. Slattery ML, Wolff RK, Herrick JS, et al. Calcium, vitamin D, VDR genotypes, and epigenetic and genetic changes in rectal tumors. Nutr Cancer. 2010;62:436–42. [PMC free article] [PubMed]
137. Slattery ML, Wolff RK, Herrick JS, et al. Alcohol consumption and rectal tumor mutations and epigenetic changes. Dis Colon Rectum. 2010;53:1182–9. [PMC free article] [PubMed]
138. Slattery ML, Herrick J, Lundgreen A, et al. Genetic variation in a metabolic signaling pathway and colon and rectal cancer risk: mTOR, PTEN, STK1, RPKAA1, PRKAG2, TSC1, TSC2, PI3K, and Akt1. Carcinogenesis [PMC free article] [PubMed]
139. Ulrich CM, Curtin K, Samowitz W, et al. MTHFR variants reduce the risk of G:C->A:T transition mutations within the p53 tumor suppressor gene in colon tumors. J Nutr. 2005;135:2462–7. [PubMed]
140. van den Donk M, van Engeland M, Pellis L, et al. Dietary folate intake in combination with MTHFR C677T genotype and promoter methylation of tumor suppressor and DNA repair genes in sporadic colorectal adenomas. Cancer Epidemiol Biomarkers Prev. 2007;16:327–33. [PubMed]
141. van Engeland M, Weijenberg MP, Roemen GM, et al. Effects of dietary folate and alcohol intake on promoter methylation in sporadic colorectal cancer: the Netherlands cohort study on diet and cancer. Cancer Res. 2003;63:3133–7. [PubMed]
142. Van Guelpen B, Dahlin AM, Hultdin J, et al. One-carbon metabolism and CpG island methylator phenotype status in incident colorectal cancer: a nested case-referent study. Cancer Causes Control. 2010;21:557–66. [PubMed]
143. Ward RL, Williams R, Law M, et al. The CpG island methylator phenotype is not associated with a personal or family history of cancer. Cancer Res. 2004;64:7618–21. [PubMed]
144. Wark PA, Weijenberg MP, van’t Veer P, et al. Fruits, vegetables, and hMLH1 protein-deficient and -proficient colon cancer: The Netherlands cohort study. Cancer Epidemiol Biomarkers Prev. 2005;14:1619–25. [PubMed]
145. Wark PA, Van der Kuil W, Ploemacher J, et al. Diet, lifestyle and risk of K-ras mutation-positive and -negative colorectal adenomas. Int J Cancer. 2006;119:398–405. [PubMed]
146. Weijenberg MP, Luchtenborg M, de Goeij AF, et al. Dietary fat and risk of colon and rectal cancer with aberrant MLH1 expression, APC or KRAS genes. Cancer Causes Control. 2007;18:865–79. [PMC free article] [PubMed]
147. Weijenberg MP, Aardening PW, de Kok TM, et al. Cigarette smoking and KRAS oncogene mutations in sporadic colorectal cancer: results from the Netherlands Cohort Study. Mutat Res. 2008;652:54–64. [PubMed]
148. Wish TA, Hyde AJ, Parfrey PS, et al. Increased Cancer Predisposition in Family Members of Colorectal Cancer Patients Harboring the p. V600E BRAF Mutation: a Population-Based Study. Cancer Epidemiol Biomarkers Prev. 2010;19:1831–9. [PubMed]
149. Wu AH, Shibata D, Yu MC, et al. Dietary heterocyclic amines and microsatellite instability in colon adenocarcinomas. Carcinogenesis. 2001;22:1681–4. [PubMed]
150. Wu AH, Siegmund KD, Long TI, et al. Hormone therapy, DNA methlyation and colon cancer. Carcinogenesis. 2010 in press (published online) [PMC free article] [PubMed]
151. Yang P, Cunningham JM, Halling KC, et al. Higher risk of mismatch repair-deficient colorectal cancer in alpha(1)-antitrypsin deficiency carriers and cigarette smokers. Mol Genet Metab. 2000;71:639–45. [PubMed]
152. Candiloro IL, Dobrovic A. Detection of MGMT promoter methylation in normal individuals is strongly associated with the T allele of the rs16906252 MGMT promoter single nucleotide polymorphism. Cancer Prev Res (Phila Pa) 2009;2:862–7. [PubMed]
153. Hawkins NJ, Lee JH, Wong JJ, et al. MGMT methylation is associated primarily with the germline C>T SNP (rs16906252) in colorectal cancer and normal colonic mucosa. Mod Pathol. 2009;22:1588–99. [PubMed]
154. Newcomb PA, Baron J, Cotterchio M, et al. Colon Cancer Family Registry: an international resource for studies of the genetic epidemiology of colon cancer. Cancer Epidemiol Biomarkers Prev. 2007;16:2331–43. [PubMed]
155. Slattery ML, Potter J, Caan B, et al. Energy balance and colon cancer--beyond physical activity. Cancer Res. 1997;57:75–80. [PubMed]
156. Slattery ML, Edwards SL, Palmer L, et al. Use of archival tissue in epidemiologic studies: collection procedures and assessment of potential sources of bias. Mutat Res. 2000;432:7–14. [PubMed]
157. Gornick MC, Castellsague X, Sanchez G, et al. Human papillomavirus is not associated with colorectal cancer in a large international study. Cancer Causes Control. 2010;21:737–43. [PubMed]
158. Khoury-Shakour S, Gruber SB, Lejbkowicz F, et al. Recreational physical activity modifies the association between a common GH1 polymorphism and colorectal cancer risk. Cancer Epidemiol Biomarkers Prev. 2008;17:3314–8. [PMC free article] [PubMed]
159. Chaiter Y, Gruber SB, Ben-Amotz A, et al. Smoking attenuates the negative association between carotenoids consumption and colorectal cancer risk. Cancer Causes Control. 2009;20:1327–38. [PubMed]
160. Kulathinal S, Karvanen J, Saarela O, et al. Case-cohort design in practice - experiences from the MORGAM Project. Epidemiol Perspect Innov. 2007;4:15. [PMC free article] [PubMed]
161. Riboli E, Kaaks R. The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int J Epidemiol. 1997;26 (Suppl 1):S6–14. [PubMed]
162. Park JY, Mitrou PN, Dahm CC, et al. Baseline alcohol consumption, type of alcoholic beverage and risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition-Norfolk study. Cancer Epidemiol. 2009;33:347–54. [PubMed]
163. Park JY, Mitrou PN, Luben R, et al. Is bowel habit linked to colorectal cancer? - Results from the EPIC-Norfolk study. Eur J Cancer. 2009;45:139–45. [PubMed]
164. Loh YH, Mitrou PN, Bowman R, et al. MGMT Ile143Val polymorphism, dietary factors and the risk of breast, colorectal and prostate cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk study. DNA Repair (Amst) 2010 [PubMed]
165. Folsom AR, Kaye SA, Prineas RJ, et al. Increased incidence of carcinoma of the breast associated with abdominal adiposity in postmenopausal women. Am J Epidemiol. 1990;131:794–803. [PubMed]
166. Bisgard KM, Folsom AR, Hong CP, et al. Mortality and cancer rates in nonrespondents to a prospective study of older women: 5-year follow-up. Am J Epidemiol. 1994;139:990–1000. [PubMed]
167. Haydon AM, Macinnis RJ, English DR, et al. Physical activity, insulin-like growth factor 1, insulin-like growth factor binding protein 3, and survival from colorectal cancer. Gut. 2006;55:689–94. [PMC free article] [PubMed]
168. Haydon AM, Macinnis RJ, English DR, et al. Effect of physical activity and body size on survival after diagnosis with colorectal cancer. Gut. 2006;55:62–7. [PMC free article] [PubMed]
169. Osborne NJ, Gurrin LC, Allen KJ, et al. HFE C282Y homozygotes are at increased risk of breast and colorectal cancer. Hepatology. 2010;51:1311–8. [PubMed]
170. Dahlin AM, Palmqvist R, Henriksson ML, et al. The Role of the CpG Island Methylator Phenotype in Colorectal Cancer Prognosis Depends on Microsatellite Instability Screening Status. Clin Cancer Res. 2010;16:1845–55. [PubMed]
171. Kaaks R, Stattin P, Villar S, et al. Insulin-like growth factor-II methylation status in lymphocyte DNA and colon cancer risk in the Northern Sweden Health and Disease cohort. Cancer Res. 2009;69:5400–5. [PubMed]
172. Colditz GA, Hankinson SE. The Nurses’ Health Study: lifestyle and health among women. Nat Rev Cancer. 2005;5:388–96. [PubMed]
173. Chan AT, Ogino S, Fuchs CS. Aspirin use and survival after diagnosis of colorectal cancer. JAMA. 2009;302:649–58. [PMC free article] [PubMed]
174. Meyerhardt JA, Ogino S, Kirkner GJ, et al. Interaction of molecular markers and physical activity on mortality in patients with colon cancer. Clin Cancer Res. 2009;15:5931–6. [PMC free article] [PubMed]
175. Nosho K, Shima K, Irahara N, et al. DNMT3B expression might contribute to CpG island methylator phenotype in colorectal cancer. Clin Cancer Res. 2009;15:3663–71. [PMC free article] [PubMed]
176. Ogino S, Kirkner GJ, Nosho K, et al. Cyclooxygenase-2 expression is an independent predictor of poor prognosis in colon cancer. Clin Cancer Res. 2008;14:8221–7. [PMC free article] [PubMed]
177. Ogino S, Nosho K, Kirkner GJ, et al. A cohort study of tumoral LINE-1 hypomethylation and prognosis in colon cancer. J Natl Cancer Inst. 2008;100:1734–8. [PMC free article] [PubMed]
178. Ogino S, Meyerhardt JA, Irahara N, et al. KRAS mutation in stage III colon cancer and clinical outcome following intergroup trial CALGB 89803. Clin Cancer Res. 2009;15:7322–9. [PMC free article] [PubMed]
179. Meyerhardt JA, Giovannucci EL, Holmes MD, et al. Physical activity and survival after colorectal cancer diagnosis. J Clin Oncol. 2006;24:3527–34. [PubMed]
180. Meyerhardt JA, Heseltine D, Niedzwiecki D, et al. Impact of physical activity on cancer recurrence and survival in patients with stage III colon cancer: findings from CALGB 89803. J Clin Oncol. 2006;24:3535–41. [PubMed]
181. Kune GA, Kune S, Watson LF. The effect of family history of cancer, religion, parity and migrant status on survival in colorectal cancer. The Melbourne Colorectal Cancer Study. Eur J Cancer. 1992;28A:1484–7. [PubMed]
182. Slattery ML, Kerber RA. The impact of family history of colon cancer on survival after diagnosis with colon cancer. Int J Epidemiol. 1995;24:888–96. [PubMed]
183. Chan JA, Meyerhardt JA, Niedzwiecki D, et al. Association of family history with cancer recurrence and survival among patients with stage III colon cancer. Jama. 2008;299:2515–23. [PubMed]
184. Zell JA, Honda J, Ziogas A, et al. Survival after colorectal cancer diagnosis is associated with colorectal cancer family history. Cancer Epidemiol Biomarkers Prev. 2008;17:3134–40. [PMC free article] [PubMed]
185. McCleary NJ, Niedzwiecki D, Hollis D, et al. Impact of smoking on patients with stage III colon cancer: results from Cancer and Leukemia Group B 89803. Cancer. 2010;116:957–66. [PMC free article] [PubMed]
186. Meyerhardt JA, Catalano PJ, Haller DG, et al. Influence of body mass index on outcomes and treatment-related toxicity in patients with colon carcinoma. Cancer. 2003;98:484–95. [PubMed]
187. Meyerhardt JA, Tepper JE, Niedzwiecki D, et al. Impact of body mass index on outcomes and treatment-related toxicity in patients with stage II and III rectal cancer: findings from Intergroup Trial 0114. J Clin Oncol. 2004;22:648–57. [PubMed]
188. Dignam JJ, Polite BN, Yothers G, et al. Body mass index and outcomes in patients who receive adjuvant chemotherapy for colon cancer. J Natl Cancer Inst. 2006;98:1647–54. [PubMed]
189. Tamakoshi K, Wakai K, Kojima M, et al. A prospective study of body size and colon cancer mortality in Japan: The JACC Study. Int J Obes Relat Metab Disord. 2004;28:551–8. [PubMed]
190. Saal LH, Johansson P, Holm K, et al. Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity. Proc Natl Acad Sci U S A. 2007;104:7564–9. [PubMed]
191. Imamura K, Ogura T, Kishimoto A, et al. Cell cycle regulation via p53 phosphorylation by a 5′-AMP activated protein kinase activator, 5-aminoimidazole- 4-carboxamide-1-beta-D-ribofuranoside, in a human hepatocellular carcinoma cell line. Biochem Biophys Res Commun. 2001;287:562–7. [PubMed]
192. Jones RG, Plas DR, Kubek S, et al. AMP-activated protein kinase induces a p53-dependent metabolic checkpoint. Mol Cell. 2005;18:283–93. [PubMed]
193. Medema R, Kops G, Bos J, et al. AFX-like forkhead transcription mediate cell-cycle regulation by Ras and PKB through p27/kip1. Nature. 2000;404:782–7. [PubMed]
194. Ulrich CM, Bigler J, Potter JD. Non-steroidal anti-inflammatory drugs for cancer prevention: promise, perils and pharmacogenetics. Nat Rev Cancer. 2006;6:130–40. [PubMed]
195. Thun MJ, Namboodiri MM, Heath CW., Jr Aspirin use and reduced risk of fatal colon cancer. N Engl J Med. 1991;325:1593–6. [PubMed]
196. Rosenberg L, Palmer JR, Zauber AG, et al. A hypothesis: nonsteroidal anti-inflammatory drugs reduce the incidence of large-bowel cancer. J Natl Cancer Inst. 1991;83:355–8. [PubMed]
197. Thun MJ, Calle EE, Namboodiri MM, et al. Risk factors for fatal colon cancer in a large prospective study. J Natl Cancer Inst. 1992;84:1491–500. [PubMed]
198. Muller AD, Sonnenberg A, Wasserman IH. Diseases preceding colon cancer. A case-control study among veterans. Dig Dis Sci. 1994;39:2480–4. [PubMed]
199. Giovannucci E, Rimm EB, Stampfer MJ, et al. Aspirin use and the risk for colorectal cancer and adenoma in male health professionals [see comments] Ann Intern Med. 1994;121:241–6. [PubMed]
200. Giovannucci E, Egan KM, Hunter DJ, et al. Aspirin and the risk of colorectal cancer in women [see comments] N Engl J Med. 1995;333:609–14. [PubMed]
201. Chan AT, Giovannucci EL, Schernhammer ES, et al. A prospective study of aspirin use and the risk for colorectal adenoma. Ann Intern Med. 2004;140:157–66. [PubMed]
202. Chan AT, Giovannucci EL, Meyerhardt JA, et al. Long-term use of aspirin and nonsteroidal anti-inflammatory drugs and risk of colorectal cancer. JAMA. 2005;294:914–23. [PMC free article] [PubMed]
203. Chan AT, Giovannucci EL, Meyerhardt JA, et al. Aspirin dose and duration of use and risk of colorectal cancer in men. Gastroenterology. 2008;134:21–8. [PMC free article] [PubMed]
204. Baron JA, Cole BF, Sandler RS, et al. A randomized trial of aspirin to prevent colorectal adenomas. N Engl J Med. 2003;348:891–9. [PubMed]
205. Sandler RS, Halabi S, Baron JA, et al. A randomized trial of aspirin to prevent colorectal adenomas in patients with previous colorectal cancer. N Engl J Med. 2003;348:883–90. [PubMed]
206. Benamouzig R, Deyra J, Martin A, et al. Daily soluble aspirin and prevention of colorectal adenoma recurrence: one-year results of the APACC trial. Gastroenterology. 2003;125:328–36. [PubMed]
207. Bertagnolli MM, Eagle CJ, Zauber AG, et al. Celecoxib for the prevention of sporadic colorectal adenomas. N Engl J Med. 2006;355:873–84. [PubMed]
208. Arber N, Eagle CJ, Spicak J, et al. Celecoxib for the prevention of colorectal adenomatous polyps. N Engl J Med. 2006;355:885–95. [PubMed]
209. Baron JA, Sandler RS, Bresalier RS, et al. A randomized trial of rofecoxib for the chemoprevention of colorectal adenomas. Gastroenterology. 2006;131:1674–82. [PubMed]
210. Tsujii M, Kawano S, Tsuji S, et al. Cyclooxygenase regulates angiogenesis induced by colon cancer cells. Cell. 1998;93:705–16. [PubMed]
211. Williams CS, Tsujii M, Reese J, et al. Host cyclooxygenase-2 modulates carcinoma growth. J Clin Invest. 2000;105:1589–94. [PMC free article] [PubMed]
212. Sonoshita M, Takaku K, Sasaki N, et al. Acceleration of intestinal polyposis through prostaglandin receptor EP2 in Apc(Delta 716) knockout mice. Nat Med. 2001;7:1048–51. [PubMed]
213. Esteller M. Epigenetics in cancer. N Engl J Med. 2008;358:1148–59. [PubMed]
214. Jones PA, Baylin SB. The epigenomics of cancer. Cell. 2007;128:683–92. [PubMed]
215. Speek M. Antisense promoter of human L1 retrotransposon drives transcription of adjacent cellular genes. Mol Cell Biol. 2001;21:1973–85. [PMC free article] [PubMed]
216. Peaston AE, Evsikov AV, Graber JH, et al. Retrotransposons regulate host genes in mouse oocytes and preimplantation embryos. Dev Cell. 2004;7:597–606. [PubMed]
217. Faulkner GJ, Kimura Y, Daub CO, et al. The regulated retrotransposon transcriptome of mammalian cells. Nat Genet. 2009;41:563–71. [PubMed]
218. Han JS, Szak ST, Boeke JD. Transcriptional disruption by the L1 retrotransposon and implications for mammalian transcriptomes. Nature. 2004;429:268–74. [PubMed]
219. Yamada Y, Jackson-Grusby L, Linhart H, et al. Opposing effects of DNA hypomethylation on intestinal and liver carcinogenesis. Proc Natl Acad Sci U S A. 2005;102:13580–5. [PubMed]
220. Howard G, Eiges R, Gaudet F, et al. Activation and transposition of endogenous retroviral elements in hypomethylation induced tumors in mice. Oncogene. 2008;27:404–8. [PubMed]
221. Toyota M, Ahuja N, Ohe-Toyota M, et al. CpG island methylator phenotype in colorectal cancer. Proc Natl Acad Sci U S A. 1999;96:8681–6. [PubMed]
222. Issa JP, Shen L, Toyota M. CIMP, at Last. Gastroenterology. 2005;129:1121–4. [PubMed]
223. Grady WM. CIMP and colon cancer gets more complicated. Gut. 2007;56:1498–500. [PMC free article] [PubMed]
224. Samowitz W. The CpG island methylator phenotype in colorectal cancer. J Mol Diagn. 2007;9:281–3. [PubMed]
225. Teodoridis JM, Hardie C, Brown R. CpG island methylator phenotype (CIMP) in cancer: Causes and implications. Cancer Lett. 2008;268:177–86. [PubMed]
226. Kane MF, Loda M, Gaida GM, et al. Methylation of the hMLH1 promoter correlates with lack of expression of hMLH1 in sporadic colon tumors and mismatch repair-defective human tumor cell lines. Cancer Res. 1997;57:808–11. [PubMed]
227. Hawkins N, Norrie M, Cheong K, et al. CpG island methylation in sporadic colorectal cancers and its relationship to microsatellite instability. Gastroenterology. 2002;122:1376–87. [PubMed]
228. Samowitz W, Albertsen H, Herrick J, et al. Evaluation of a large, population-based sample supports a CpG island methylator phenotype in colon cancer. Gastroenterology. 2005;129:837–45. [PubMed]
229. Ogino S, Cantor M, Kawasaki T, et al. CpG island methylator phenotype (CIMP) of colorectal cancer is best characterised by quantitative DNA methylation analysis and prospective cohort studies. Gut. 2006;55:1000–6. [PMC free article] [PubMed]
230. Weisenberger DJ, Siegmund KD, Campan M, et al. CpG island methylator phenotype underlies sporadic microsatellite instability and is tightly associated with BRAF mutation in colorectal cancer. Nat Genet. 2006;38:787–93. [PubMed]
231. Nosho K, Irahara N, Shima K, et al. Comprehensive biostatistical analysis of CpG island methylator phenotype in colorectal cancer using a large population-based sample. PLoS ONE. 2008;3:e3698. [PMC free article] [PubMed]
232. Sanchez JA, Krumroy L, Plummer S, et al. Genetic and epigenetic classifications define clinical phenotypes and determine patient outcomes in colorectal cancer. Br J Surg. 2009;96:1196–204. [PubMed]
233. Ogino S, Odze RD, Kawasaki T, et al. Correlation of pathologic features with CpG island methylator phenotype (CIMP) by quantitative DNA methylation analysis in colorectal carcinoma. Am J Surg Pathol. 2006;30:1175–83. [PubMed]
234. Ogino S, Brahmandam M, Kawasaki T, et al. Combined analysis of COX-2 and p53 expressions reveals synergistic inverse correlations with microsatellite instability and CpG island methylator phenotype in colorectal cancer. Neoplasia. 2006;8:458–64. [PMC free article] [PubMed]
235. Kawasaki T, Nosho K, Ohnishi M, et al. Correlation of beta-catenin localization with cyclooxygenase-2 expression and CpG island methylator phenotype (CIMP) in colorectal cancer. Neoplasia. 2007;9:569–77. [PMC free article] [PubMed]
236. Ogino S, Kawasaki T, Kirkner GJ, et al. Loss of nuclear p27 (CDKN1B/KIP1) in colorectal cancer is correlated with microsatellite instability and CIMP. Mod Pathol. 2007;20:15–22. [PubMed]
237. Ogino S, Kawasaki T, Nosho K, et al. LINE-1 hypomethylation is inversely associated with microsatellite instability and CpG methylator phenotype in colorectal cancer. Int J Cancer. 2008;122:2767–73. [PMC free article] [PubMed]
238. Ogino S, Kawasaki T, Kirkner GJ, et al. 18q loss of heterozygosity in microsatellite stable colorectal cancer is correlated with CpG island methylator phenotype-negative (CIMP-0) and inversely with CIMP-low and CIMP-high. BMC Cancer. 2007;7:72. [PMC free article] [PubMed]
239. Goel A, Nagasaka T, Arnold CN, et al. The CpG Island Methylator Phenotype and Chromosomal Instability Are Inversely Correlated in Sporadic Colorectal Cancer. Gastroenterology. 2007;132:127–38. [PubMed]
240. Ogino S, Kawasaki T, Kirkner GJ, et al. Down-regulation of p21 (CDKN1A/CIP1) is inversely associated with microsatellite instability and CpG island methylator phenotype (CIMP) in colorectal cancer. J Pathol. 2006;210:147–54. [PubMed]
241. Ogino S, Kawasaki T, Kirkner GJ, et al. CpG island methylator phenotype-low (CIMP-low) in colorectal cancer: possible associations with male sex and KRAS mutations. J Mol Diagn. 2006;8:582–8. [PubMed]
242. Ogino S, Kawasaki T, Kirkner GJ, et al. Molecular correlates with MGMT promoter methylation and silencing support CpG island methylator phenotype-low (CIMP-low) in colorectal cancer. Gut. 2007;56:1409–16. [PMC free article] [PubMed]
243. Barault L, Charon-Barra C, Jooste V, et al. Hypermethylator phenotype in sporadic colon cancer: study on a population-based series of 582 cases. Cancer Res. 2008;68:8541–6. [PubMed]
244. Kawasaki T, Ohnishi M, Nosho K, et al. CpG island methylator phenotype-low (CIMP-low) colorectal cancer shows not only few methylated CIMP-high-specific CpG islands, but also low-level methylation at individual loci. Mod Pathol. 2008;21:245–55. [PubMed]
245. Kim JH, Shin SH, Kwon HJ, et al. Prognostic implications of CpG island hypermethylator phenotype in colorectal cancers. Virchow Arch. 2009;455:485–94. [PubMed]
246. Shen L, Toyota M, Kondo Y, et al. Integrated genetic and epigenetic analysis identifies three different subclasses of colon cancer. Proc Natl Acad Sci U S A. 2007;104:18654–9. [PubMed]
247. Yagi K, Akagi K, Hayashi H, et al. Three DNA methylation epigenotypes in human colorectal cancer. Clin Cancer Res. 2010;16:21–33. [PubMed]
248. Iacopetta B, Grieu F, Li W, et al. APC gene methylation is inversely correlated with features of the CpG island methylator phenotype in colorectal cancer. Int J Cancer. 2006;119:2272–8. [PubMed]
249. Jass JR. Serrated adenoma of the colorectum and the DNA-methylator phenotype. Nat Clin Pract Oncol. 2005;2:398–405. [PubMed]
250. O’Brien MJ. Hyperplastic and serrated polyps of the colorectum. Gastroenterol Clin North Am. 2007;36:947–68. viii. [PubMed]
251. O’Brien MJ, Yang S, Clebanoff JL, et al. Hyperplastic (serrated) polyps of the colorectum: relationship of CpG island methylator phenotype and K-ras mutation to location and histologic subtype. Am J Surg Pathol. 2004;28:423–34. [PubMed]
252. O’Brien MJ, Yang S, Mack C, et al. Comparison of microsatellite instability, CpG island methylation phenotype, BRAF and KRAS status in serrated polyps and traditional adenomas indicates separate pathways to distinct colorectal carcinoma end points. Am J Surg Pathol. 2006;30:1491–501. [PubMed]
253. Oh K, Redston M, Odze RD. Support for hMLH1 and MGMT silencing as a mechanism of tumorigenesis in the hyperplastic-adenoma-carcinoma (serrated) carcinogenic pathway in the colon. Hum Pathol. 2005;36:101–11. [PubMed]
254. East JE, Saunders BP, Jass JR. Sporadic and syndromic hyperplastic polyps and serrated adenomas of the colon: classification, molecular genetics, natural history, and clinical management. Gastroenterol Clin North Am. 2008;37:25–46. v. [PubMed]
255. Kambara T, Simms LA, Whitehall VL, et al. BRAF mutation is associated with DNA methylation in serrated polyps and cancers of the colorectum. Gut. 2004;53:1137–44. [PMC free article] [PubMed]
256. Snover DC, Jass JR, Fenoglio-Preiser C, et al. Serrated polyps of the large intestine: a morphologic and molecular review of an evolving concept. Am J Clin Pathol. 2005;124:380–91. [PubMed]
257. Goldstein NS. Serrated pathway and APC (conventional)-type colorectal polyps: molecular-morphologic correlations, genetic pathways, and implications for classification. Am J Clin Pathol. 2006;125:146–53. [PubMed]
258. Vaughn CP, Wilson AR, Samowitz WS. Quantitative evaluation of CpG island methylation in hyperplastic polyps. Mod Pathol. 2010;23:151–6. [PubMed]
259. Messick CA, Church J, Casey G, et al. Identification of the methylator (serrated) colorectal cancer phenotype through precursor serrated polyps. Dis Colon Rectum. 2009;52:1535–41. [PubMed]
260. Stover PJ. One-carbon metabolism-genome interactions in folate-associated pathologies. J Nutr. 2009;139:2402–5. [PubMed]
261. Su LJ, Arab L. Nutritional status of folate and colon cancer risk: evidence from NHANES I epidemiologic follow-up study. Ann Epidemiol. 2001;11:65–72. [PubMed]
262. Giovannucci E, Rimm EB, Ascherio A, et al. Alcohol, low-methionine--low-folate diets, and risk of colon cancer in men [see comments] J Natl Cancer Inst. 1995;87:265–73. [PubMed]
263. Giovannucci E, Stampfer MJ, Colditz GA, et al. Multivitamin use, folate, and colon cancer in women in the Nurses’ Health Study. Ann Intern Med. 1998;129:517–24. [PubMed]
264. Glynn SA, Albanes D, Pietinen P, et al. Colorectal cancer and folate status; a nested case-control study among smokers. Cancer Epidemiology, biomarkers and prevention. 1996;5:487–94. [PubMed]
265. Slattery ML, Schaffer D, Edwards SL, et al. Are dietary factors involved in DNA methylation associated with colon cancer? Nutr Cancer. 1997;28:52–62. [PubMed]
266. Boutron-Ruault MC, Senesse P, Faivre J, et al. Folate and alcohol intakes: related or independent roles in the adenoma-carcinoma sequence? Nutr Cancer. 1996;26:337–46. [PubMed]
267. Giovannucci E, Stampfer MJ, Colditz GA, et al. Folate, methionine, and alcohol intake and risk of colorectal adenoma. J Natl Cancer Inst. 1993;85:875–84. [PubMed]
268. Tseng M, Murray SC, Kupper LL, et al. Micronutrients and the risk of colorectal adenomas. Am J Epidemiol. 1996;144:1005–14. [PubMed]
269. Bird CL, Swendseid ME, Witte JS, et al. Red cell and plasma folate, folate consumption, and the risk of colorectal adenomatous polyps. Cancer Epidemiol Biomarkers Prev. 1995;4:709–14. [PubMed]
270. Carroll C, Cooper K, Papaioannou D, et al. Meta-analysis: folic acid in the prevention of colorectal adenomas and the chemoprevention of colorectal cancer. Aliment Pharmacol Ther. 2010;31:708–18. [PubMed]
271. Cole BF, Baron JA, Sandler RS, et al. Folic acid for the prevention of colorectal adenomas: a randomized clinical trial. JAMA. 2007;297:2351–9. [PubMed]
272. Ulrich CM, Potter JD. Folate and cancer--timing is everything. JAMA. 2007;297:2408–9. [PubMed]
273. Mason JB, Dickstein A, Jacques PF, et al. A temporal association between folic acid fortification and an increase in colorectal cancer rates may be illuminating important biological principles: a hypothesis. Cancer Epidemiol Biomarkers Prev. 2007;16:1325–9. 2. [PubMed]
74. Luebeck EG, Moolgavkar SH, Liu AY, et al. Does folic acid supplementation prevent or promote colorectal cancer? Results from model-based predictions. Cancer Epidemiol Biomarkers Prev. 2008;17:1360–7. [PMC free article] [PubMed]
275. Pogribny IP, Basnakian AG, Miller BJ, et al. Breaks in genomic DNA and within the p53 gene are associated with hypomethylation in livers of folate/methyl-deficient rats [published erratum appears in Cancer Res 1995 Jun 15;55(12):2711] Cancer Res. 1995;55:1894–901. [PubMed]
276. Pogribny I, Miller B, James S. Alterations in hepatic p53 gene methylation patterns during tumor progression with folate/methyl deficiency in the rat. Cancer Lett. 1997;115:31–8. [PubMed]
277. Kim YI, Pogribny IP, Salomon RN, et al. Exon-specific DNA hypomethylation of the p53 gene of rat colon induced by dimethylhydrazine. Modulation by dietary folate. Am J Pathol. 1996;149:1129–37. [PubMed]
278. Linhart HG, Troen A, Bell GW, et al. Folate deficiency induces genomic uracil misincorporation and hypomethylation but does not increase DNA point mutations. Gastroenterology. 2009;136:227–35 e3. [PMC free article] [PubMed]
279. Hervouet E, Debien E, Campion L, et al. Folate supplementation limits the aggressiveness of glioma via the remethylation of DNA repeats element and genes governing apoptosis and proliferation. Clin Cancer Res. 2009;15:3519–29. [PubMed]
280. Wasson GR, McGlynn AP, McNulty H, et al. Global DNA and p53 region-specific hypomethylation in human colonic cells is induced by folate depletion and reversed by folate supplementation. J Nutr. 2006;136:2748–53. [PubMed]
281. Pufulete M, Al-Ghnaniem R, Khushal A, et al. Effect of folic acid supplementation on genomic DNA methylation in patients with colorectal adenoma. Gut. 2005;54:648–53. [PMC free article] [PubMed]
282. Figueiredo JC, Grau MV, Wallace K, et al. Global DNA hypomethylation (LINE-1) in the normal colon and lifestyle characteristics and dietary and genetic factors. Cancer Epidemiol Biomarkers Prev. 2009;18:1041–9. [PMC free article] [PubMed]
283. Kerkel K, Spadola A, Yuan E, et al. Genomic surveys by methylation-sensitive SNP analysis identify sequence-dependent allele-specific DNA methylation. Nat Genet. 2008;40:904–8. [PubMed]
284. Schilling E, El Chartouni C, Rehli M. Allele-specific DNA methylation in mouse strains is mainly determined by cis-acting sequences. Genome Res. 2009;19:2028–35. [PubMed]
285. Zhang Y, Rohde C, Reinhardt R, et al. Non-imprinted allele-specific DNA methylation on human autosomes. Genome Biol. 2009;10:R138. [PMC free article] [PubMed]
286. Tycko B. Mapping allele-specific DNA methylation: a new tool for maximizing information from GWAS. Am J Hum Genet. 2010;86:109–12. [PubMed]
287. Porta M, Malats N, Vioque J, et al. Incomplete overlapping of biological, clinical, and environmental information in molecular epidemiological studies: a variety of causes and a cascade of consequences. J Epidemiol Community Health. 2002;56:734–8. [PMC free article] [PubMed]
288. Slattery ML. The science and art of molecular epidemiology. J Epidemiol Community Health. 2002;56:728–9. [PMC free article] [PubMed]
289. Sherman ME, Howatt W, Blows FM, et al. Molecular pathology in epidemiologic studies: a primer on key considerations. Cancer Epidemiol Biomarkers Prev. 2010;19:966–72. [PMC free article] [PubMed]
290. Bosman FT, Yan P, Tejpar S, et al. Tissue biomarker development in a multicentre trial context: a feasibility study on the PETACC3 stage II and III colon cancer adjuvant treatment trial. Clin Cancer Res. 2009;15:5528–33. [PubMed]
291. Hoppin JA, Tolbert PE, Taylor JA, et al. Potential for selection bias with tumor tissue retrieval in molecular epidemiology studies. Ann Epidemiol. 2002;12:1–6. [PubMed]
292. McShane LM, Altman DG, Sauerbrei W, et al. Reporting recommendations for tumor marker prognostic studies (REMARK) J Natl Cancer Inst. 2005;97:1180–4. [PubMed]
293. Kyzas PA, Loizou KT, Ioannidis JP. Selective reporting biases in cancer prognostic factor studies. J Natl Cancer Inst. 2005;97:1043–55. [PubMed]
294. Ogino S, Nosho K, Kirkner GJ, et al. CpG island methylator phenotype, microsatellite instability, BRAF mutation and clinical outcome in colon cancer. Gut. 2009;58:90–6. [PMC free article] [PubMed]
295. de Vogel S, Weijenberg MP, Herman JG, et al. MGMT and MLH1 promoter methylation versus APC, KRAS and BRAF gene mutations in colorectal cancer: indications for distinct pathways and sequence of events. Ann Oncol. 2009;20:1216–22. [PubMed]
296. Nosho K, Kawasaki T, Ohnishi M, et al. PIK3CA mutation in colorectal cancer: relationship with genetic and epigenetic alterations. Neoplasia. 2008;10:534–41. [PMC free article] [PubMed]
297. Barault L, Veyries N, Jooste V, et al. Mutations in the RAS-MAPK, PI(3)K (phosphatidylinositol-3-OH kinase) signaling network correlate with poor survival in a population-based series of colon cancers. Int J Cancer. 2008;122:2255–9. [PubMed]
298. Samowitz WS, Curtin K, Schaffer D, et al. Relationship of Ki-ras mutations in colon cancers to tumor location, stage, and survival: a population-based study. Cancer Epidemiol Biomarkers Prev. 2000;9:1193–7. [PubMed]
299. Ogino S, Kawasaki T, Kirkner GJ, et al. Evaluation of markers for CpG island methylator phenotype (CIMP) in colorectal cancer by a large population-based sample. J Mol Diagn. 2007;9:305–14. [PubMed]
300. Hunter DJ, Khoury MJ, Drazen JM. Letting the genome out of the bottle--will we get our wish? N Engl J Med. 2008;358:105–7. [PubMed]
301. Cantor RM, Lange K, Sinsheimer JS. Prioritizing GWAS results: A review of statistical methods and recommendations for their application. Am J Hum Genet. 2010;86:6–22. [PubMed]
302. Moore JH, Asselbergs FW, Williams SM. Bioinformatics Challenges for Genome-Wide Association Studies. Bioinformatics. 2010;26:445–55. [PMC free article] [PubMed]
303. Kohane IS, Masys DR, Altman RB. The incidentalome: a threat to genomic medicine. JAMA. 2006;296:212–5. [PubMed]
304. Stokols D, Hall KL, Taylor BK, et al. The science of team science: overview of the field and introduction to the supplement. Am J Prev Med. 2008;35:S77–89. [PubMed]
305. Wade A. Fear or favour? Statistics in pathology. J Clin Pathol. 2000;53:16–8. [PMC free article] [PubMed]
306. Wuchty S, Jones BF, Uzzi B. The increasing dominance of teams in production of knowledge. Science. 2007;316:1036–9. [PubMed]
307. Sellers TA, Caporaso N, Lapidus S, et al. Opportunities and barriers in the age of team science: strategies for success. Cancer Causes Control. 2006;17:229–37. [PubMed]