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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Cancer Causes Control. Author manuscript; available in PMC Feb 14, 2012.
Published in final edited form as:
PMCID: PMC3278857
NIHMSID: NIHMS265179

MGMT promoter methylation, loss of expression and prognosis in 855 colorectal cancers

Abstract

Objective

O6-methylguanine-DNA methyltransferase (MG MT) is a DNA repair enzyme. MGMT promoter hypermethylation and epigenetic silencing often occur as early events in carcinogenesis. However, prognostic significance of MGMT alterations in colorectal cancer remains uncertain.

Methods

Utilizing a database of 855 colon and rectal cancers in two prospective cohort studies (the Nurses’ Health Study and the Health Professionals Follow-up Study), we detected MGMT promoter hypermethylation in 325 tumors (38%) by MethyLight and loss of MGMT expression in 37% (247/672) of tumors by immunohistochemistry. We assessed the CpG island methylator phenotype (CIMP) using eight methylation markers [CACNA1G, CDKN2A (p16), CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1], and LINE-1 (L1) hypomethylation, TP53 (p53), and microsatellite instability (MSI).

Results

MGMT hypermethylation was not associated with colorectal cancer–specific mortality in univariate or multivariate Cox regression analysis [adjusted hazard ratio (HR) = 1.03; 95% confidence interval (CI), 0.79–1.36] that adjusted for clinical and tumor features, including CIMP, MSI, and BRAF mutation. Similarly, MGMT loss was not associated with patient survival. MGMT loss was associated with G>A mutations in KRAS (p = 0.019) and PIK3CA (p = 0.0031).

Conclusions

Despite a well-established role of MGMT aberrations in carcinogenesis, neither MGMT promoter methylation nor MGMT loss serves as a prognostic biomarker in colorectal cancer.

Keywords: Colon cancer, MGMT, Hypermethylation, Epigenetics, Clinical outcome

Introduction

The O6-methylguanine-DNA methyltransferase (MGMT) gene encodes DNA repair protein and is frequently inactivated in colorectal cancer [1, 2]. Polymorphisms in MGMT have been associated with colorectal cancer risk [3, 4], and MGMT promoter methylation in normal colonic mucosa might be a predisposing factor for cancer as a field effect and an early event in colorectal carcinogenesis [5, 6]. MGMT promoter methylation and loss of expression have been associated with G>A mutations in a variety of genes such as KRAS, PIK3CA, TP53, and APC [711]. Jass [12] proposed the molecular classification based on CIMP, MSI, BRAF, KRAS, and MGMT promoter methylation, indicating that MGMT methylation is one of the key molecular alterations in colorectal cancer. In addition, MGMT has potential as a therapeutic target in human cancer [13, 14]. Collectively, it is of interest to examine a prognostic role of MGMT alteration as a tumor biomarker. In brain tumors and B-cell lymphoma, MGMT methylation or loss of MGMT has been associated with poor prognosis [1517]. However, prognostic significance of MGMT alteration in colorectal cancer remains inconclusive due to limited statistical power of all previous studies (Table 1; all n < 200) [1822].

Table 1
Studies on prognostic significance of MGMT methylation (top) or loss of MGMT (bottom) in colorectal cancer

In this study using the database of a large number (n = 855) of stage I–IV colorectal cancers, we examined the prognostic effect of MGMT promoter methylation and loss of expression. Since we concurrently assessed other molecular variables including LINE-1 hypomethylation, MSI, CIMP, and mutation in KRAS, BRAF, and PIK3CA, we could evaluate the prognostic effect of MGMT alteration after controlling for those potential confounders.

Materials and methods

Study population

We utilized the database of two prospective cohort studies, the Nurses’ Health Study (n = 121,701 women followed since 1976) [23] and the Health Professionals Follow-up Study (n = 51,529 men followed since 1986) [23]. Participants have been sent biennial questionnaires to update information on potential risk factors and to identify newly diagnosed cancers in themselves and their first-degree relatives. We collected paraffin-embedded tumor tissue blocks of incident colorectal cancers from hospitals where participants with colorectal cancer underwent tumor resection. Hematoxylin and eosin (H&E)–stained tissue sections from all colorectal cancer cases were confirmed by a pathologist (S.O.) unaware of other data. The tumor grade was categorized as low versus high (>50 vs. ≤50% gland formation). Positive family history of colorectal cancer was defined as the presence of colorectal cancer in any first-degree relative. We excluded cases that were preoperatively treated. Based on the availability of adequate follow-up and tumor tissue data, 855 stage I–IV colorectal cancer cases diagnosed up to 2002 were included. Patients were observed until death or June 2009, whichever came first. This study was approved by the Human Subjects Committees at Harvard School of Public Health and Brigham and Women’s Hospital.

Pyrosequencing of KRAS, BRAF, and PIK3CA, and microsatellite instability (MSI) analysis

Genomic DNA was extracted from paraffin-embedded tissue. PCR and pyrosequencing targeted for KRAS (codons 12 and 13) [24], BRAF (codon 600) [25], and PIK3CA (exons 9 and 20) [11] were performed. Microsatellite instability (MSI) analysis was performed using 10 micro-satellite markers (D2S123, D5S346, D17S250, BAT25, BAT26, BAT40, D18S55, D18S56, D18S67, and D18S487) [26]. MSI-high was defined as the presence of instability in ≥30% of the markers and MSI-low/microsatellite stable (MSS) as instability in 0–29% of markers [26].

Methylation analyses for CpG islands and LINE-1

Sodium bisulfite treatment and subsequent real-time PCR were performed to quantify promoter methylation in MGMT and eight other CpG islands (CACNA1G, CDKN2A, CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1) [27, 28]; the latter eight markers have been shown to be specific for CIMP [29]. CIMP-high was defined as the presence of ≥6/8 methylated markers, CIMP-low as the presence of 1/8–5/8 methylated markers, and CIMP-0 as the absence (0/8) of methylated markers [30]. We defined and validated the cut point for MGMT promoter methylation positivity (percentage of methylated reference, or PMR> 4) as previously described [31]. LINE-1 methylation levels were quantified by PCR-pyrosequencing [32, 33].

Immunohistochemical analysis

Immunohistochemical methods for MGMT and TP53 (p53) were previously described [26], and expression patterns were interpreted by a pathologist (S.O.) unaware of other data. In agreement studies, a random selection of more than 100 cases for each marker was interpreted by a second pathologist unaware of other data (MGMT by K.S.; TP53 by K.N.). The concordance between the two observers (both p < 0.0001) was 0.86 for MGMT (κ = 0.70) and 0.87 for TP53 (κ = 0.75), indicating substantial agreement. The concordance between MGMT methylation and loss of MGMT was 81% (κ = 0.59).

Statistical analysis

We used SAS program (Version 9.1, SAS Institute, Cary, NC) for all statistical analysis. All p values were two-sided, and significance level was set at p = 0.05. The chi-square test (or Fisher’s exact test) was performed for categorical variables. For survival analysis, the Kaplan–Meier method and log-rank test were used. For analyses of colorectal cancer–specific mortality, deaths as a result of causes other than colorectal cancer were censored. To control for confounding, we used multivariate stage-matched (stratified) Cox proportional hazard models to compute hazard ratio (HR) of death according to MGMT status. To avoid residual confounding and overfitting, disease stage (I, IIA, IIB, IIIA, IIIB, IIIC, IV, unknown) was used as a stratifying variable, utilizing the “strata” option in the SAS “proc phreg” command. The multivariate model initially included age at diagnosis (continuous), sex, year of diagnosis (continuous), BMI (<30 vs. ≥30 kg/m2), family history of colorectal cancer (present vs. absent), tumor location (proximal colon vs. distal colon vs. rectum), tumor grade (low vs. high), MSI (high vs. low/MSS), CIMP (high vs. low vs. CIMP-0), LINE-1 methylation (continuous), and BRAF. A backward elimination with a threshold of p = 0.20 was used to select variables in the final model. For cases with missing information in any of the categorical variables [tumor location (0.9%), tumor grade (0.5%), MSI (3.0%), BRAF (4.8%)], we included those cases in a majority category of a given covariate to avoid overfitting. We confirmed that excluding cases with missing information in any of the covariates did not substantially alter results (data not shown). An interaction was assessed by including the cross product of the MGMT methylation (or MGMT loss) variable and another variable of interest (without data-missing cases) in a multivariate model, and the Wald test was performed. A p value for statistical significance was adjusted for multiple hypothesis testing to p = 0.0029 (=0.05/17) by Bonferroni correction.

In addition, we constructed multivariate logistic regression analysis model to assess the independent effect of MGMT loss on G>A mutations in KRAS or PIK3CA (as a binary outcome variable). The model initially included age at diagnosis (continuous), sex, year of diagnosis (continuous), BMI (<30 vs. ≥30 kg/m2), family history of colorectal cancer (present vs. absent), tumor location (proximal vs. distal), MSI (high vs. low/MSS), CIMP (high vs. low/0), LINE-1 methylation (continuous), and MGMT loss, and a backward elimination with a threshold of p = 0.20 was done to select variables in the final model.

Results

MGMT methylation and loss of MGMT in colorectal cancer

MGMT promoter methylation was detected in 325 (38%) of 885 tumors, and loss of MGMT was detected in 247 (37%) of 672 tumors. There was a significant association between MGMT promoter methylation and CIMP status (p < 0.0001). Loss of MGMT was significantly associated with PIK3CA mutation (p = 0.0031) and inversely associated with TP53 expression (p = 0.0004; Table 2).

Table 2
Clinical and molecular characteristics in colorectal cancer with MGMT promoter methylation/loss of MGMT

MGMT methylation/loss and G>A mutations in KRAS and PIK3CA

Because functional loss of MGMT may contribute to G>A mutations [711], we examined the relations between MGMT methylation (or loss) and G>A mutations in KRAS and PIK3CA (Table 2). MGMT loss was significantly associated with G>A mutations in KRAS (p = 0.019) and PIK3CA (p = 0.0031) (by a priori hypothesis testing), while MGMT methylation was not. In multivariate logistic regression analysis to assess independent effect of MGMT loss on G>A mutations, MGMT loss remained significantly associated with G>A mutations in KRAS (adjusted OR, 1.58; 95% CI, 1.07–2.34; p = 0.021) and PIK3CA (adjusted OR, 2.55; 95% CI, 1.40–4.68; p = 0.0024).

MGMT methylation, loss of MGMT, and survival of patients with colorectal cancer

Among the 855 patients, there were 415 deaths including 234 colorectal cancer–specific deaths. The median follow-up time for censored patients was 13.0 years. For either colorectal cancer–specific or overall mortality, MGMT methylation was not significantly associated with patient outcome in log-rank test, or univariate or multivariate stage–matched Cox regression analysis (Table 3, Fig. 1). Likewise, loss of MGMT was not significantly associated with colorectal cancer–specific or overall mortality in univariate or multivariate stage–matched analysis (Table 3, Fig. 1).

Fig. 1
Kaplan–Meier curves for colorectal cancer–specific survival (upper panel) and overall survival (lower panel), according to MGMT promoter methylation (a, b) or loss of MGMT (c, d) in colorectal cancer
Table 3
MGMT promoter methylation/loss of MGMT in colorectal cancer and patient mortality

We analyzed the prognostic effect of MGMT methylation or loss of MGMT in colon cancer and rectal cancer separately, since clinical management for patients with colon cancer differ from that for patients with rectal cancer. MGMT methylation (or MGMT loss) was not significantly associated with colorectal cancer–specific or overall mortality in either patients with colon cancer or rectal cancer (Table 3).

There was no significant modifying effect on the prognostic influence of MGMT methylation (or MGMT loss) by Table 2 Clinical and molecular characteristics in colorectal cancer with MGMT promoter methylation/loss of MGMT any of the other variables including sex, age, year of diagnosis, BMI, family history of colorectal cancer, tumor location, stage, tumor grade, CIMP, MSI, BRAF, KRAS, PIK3CA, LINE-1 methylation, and TP53 (all Pinteraction > 0.02).

Discussion

We conducted this study to examine whether MGMT promoter methylation or loss of expression in colorectal cancer has any prognostic role. This question has remained inconclusive due to limited statistical power of all previous studies on this topic [1822]. Given the crucial roles of MGMT aberrations in colorectal carcinogenesis or a potential use of MGMT as a therapeutic target in human cancer, the assessment of MGMT alteration (i.e., MGMT promoter methylation or loss of MGMT) and clinical outcome using a large number of cancers is needed. Utilizing the database of 855 clinically and molecularly annotated colorectal cancers in the two large prospective cohort studies, we found that MGMT alteration was not associated with patient prognosis in colorectal cancer. In addition, we assessed the prognostic effect of MGMT promoter methylation (or MGMT loss), controlling for other molecular features, including CIMP, MSI, and BRAF mutation, all of which have been documented to be critical in colorectal carcinogenesis.

Studying molecular variants and somatic changes is important in cancer research [3442]. Recent studies have shown that MGMT promoter polymorphism (rs16906252) is associated with MGMT methylation in colorectal cancer [43], in normal colorectal mucosa [44], and in peripheral blood cells from normal individuals [45]. Epigenetic silencing of MGMT by promoter methylation in normal colonic mucosa may be a predisposing factor for cancer as a field effect and an early event in colorectal carcinogenesis [5, 6]. In addition, MGMT methylation might be a valuable biomarker in plasma for early detection of colorectal cancer [46].

Studies on colorectal cancer have shown that MGMT methylation is associated with MGMT loss [5, 6, 47]. In agreement with these studies [5, 6, 47], our current study showed a good concordance (81%, κ = 0.59, p < 0.0001) between MGMT methylation and MGMT loss. MGMT methylation and loss of MGMT were not perfectly correlated perhaps due to a few reasons. First, loss of MGMT expression may be caused not only by promoter methylation but also by other mechanisms such as a gene deletion or mutation. Second, in rare cases, promoter methylation may be present in only one MGMT allele, and the MGMT protein may be expressed from the second allele. Third, there may be other molecules (such as miRNA) that may downregulate MGMT.

MGMT promoter methylation or loss of expression in colorectal cancer has been associated with G>A mutations in KRAS [7, 9, 10, 44, 48], TP53 [8, 9], and PIK3CA [11]. Our current study is the first one to perform multivariate analysis and show that MGMT loss is associated with G>A mutations in KRAS and PIK3CA, independent of potential confounders. Thus, our current study supports the concept that loss of MGMT contributes to G>A mutations of KRAS and PIK3CA.

Previous studies [1822] have shown no prognostic significance of MGMT methylation (or loss of MGMT) in colorectal cancers (Table 1). These previous studies [1822] on prognostic significance of MGMT methylation (or MGMT loss) are limited by low statistical power (n < 200). In contrast to the prior studies [1822], our study examined both MGMT promoter methylation and loss of MGMT expression in a much larger cohort of colorectal cancers. In the current study, MGMT methylation was found in 38% of colorectal cancer. Previous studies [1822] have shown a large variation in the frequency of MGMT promoter methylation (21–61%; Table 1). This variation might be caused by differences in study samples and/or methylation detection methods (MSP vs. quantitative MethyLight vs. Pyrosequencing) and might also be in part due to a chance variation in the small studies.

With regard to the predictive role of MGMT aberrations, Braun et al. [34] examined a predictive role of loss of MGMT expression (among other markers) in 1,125 patients with metastatic colorectal cancer who underwent different chemotherapy treatment arms (fluorouracil vs. fluorouracil/irinotecan vs. fluorouracil/oxaliplatin) and found no predictive role of MGMT aberrations.

There are limitations in this study. For example, data on cancer treatment were limited. Nonetheless, it is unlikely that chemotherapy use substantially differed according to MGMT status in tumor, since such data were unavailable for treatment decision making. In addition, our multivariate survival analysis adjusted for disease stage as finely as I, IIA, IIB, IIIA, IIIB, IIIC, IV on which treatment decision making was mostly based. As another limitation, beyond cause of mortality, data on cancer recurrences were unavailable in these cohort studies. Nonetheless, colorectal cancer–specific survival might be a reasonable surrogate of colorectal cancer–specific outcome.

There are advantages in utilizing the database of the two prospective cohort studies, the Nurses’ Health Study and the Health Professionals Follow-up Study, to examine prognostic significance of tumor biomarkers. Anthropometric measurements, family history, cancer staging, and other clinical, pathologic, and tumoral molecular data were prospectively collected, blinded to patient outcome. Cohort participants who developed cancer were treated at hospitals throughout the United States and thus more representative colorectal cancers in the US population than patients in one to a few academic hospitals. There were no demographic difference between cases with tumor tissue analyzed and those without tumor tissue analyzed [23]. Finally, our rich tumor database enabled us to simultaneously assess pathologic and tumoral molecular correlates and control for confounding by a number of tumoral molecular alterations.

In conclusion, our findings suggest that MGMT promoter methylation or loss of expression is not a prognostic biomarker in colorectal cancer, despite its well-established role in carcinogenesis.

Acknowledgments

We deeply thank the Nurses’ Health Study and Health Professionals Follow-up Study cohort participants who have generously agreed to provide us with biological specimens and information through responses to questionnaires, and hospitals and pathology departments throughout the United States for providing us with medical records and tumor tissue specimens. This work was supported by U.S. National Institute of Health (NIH) grants P01 CA87969 (to SE Hankinson), P01 CA55075 (to WC Willett), P50 CA127003 (to CSF), K07 CA122826 (to SO), and R01 CA151993 (to SO), and in part by grants from the Bennett Family Fund and from the Entertainment Industry Foundation National Colorectal Cancer Research Alliance. Y.B. was supported by a fellowship grant from the Uehara Memorial Foundation. K.N. and M.S. were supported by fellowship grants from the Japan Society for Promotion of Science. The content is solely the responsibility of the authors and does not necessarily represent the official views of NCI or NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Abbreviations

BMI
Body mass index
CI
Confidence interval
CIMP
CpG island methylator phenotype
HR
Hazard ratio
MGMT
O6-methylguanine-DNA methyltransferase
MSI
Microsatellite instability
MSS
Microsatellite stable
OR
Odds ratio

Footnotes

Conflicts of interest No conflicts of interest exist.

Contributor Information

Kaori Shima, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.

Teppei Morikawa, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.

Yoshifumi Baba, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.

Katsuhiko Nosho, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.

Maiko Suzuki, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.

Mai Yamauchi, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.

Marika Hayashi, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.

Edward Giovannucci, Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA. Departments of Epidemiology and Nutrition, Harvard School of Public Health, Boston, MA, USA.

Charles S. Fuchs, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA. Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA.

Shuji Ogino, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA. Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, MA, USA. 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.

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