PTGER2 Overexpression in Colorectal Cancer is Associated with Microsatellite Instability, Independent of CpG Island Methylator Phenotype

doi:10.1158/1055-9965.EPI-09-1154

Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 March 3.

Published in final edited form as:

Cancer Epidemiol Biomarkers Prev. 2010 March; 19(3): 822–831.

Published online 2010 March 3. doi: 10.1158/1055-9965.EPI-09-1154

PMCID: PMC2837535

NIHMSID: NIHMS171772

PTGER2 Overexpression in Colorectal Cancer is Associated with Microsatellite Instability, Independent of CpG Island Methylator Phenotype

Yoshifumi Baba,¹ Katsuhiko Nosho,¹ Kaori Shima,¹ Wolfram Goessling,^1,^2,³ Andrew T. Chan,⁴ Kimmie Ng,¹ Jennifer A. Chan,¹ Edward L. Giovannucci,^5,⁶ Charles S. Fuchs,^1,⁵ and Shuji Ogino^1,⁷

¹Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA

²Genetics and Gastroenterology Divisions, Brigham and Women's Hospital, Boston, MA

³Harvard Stem Cell Institute, Cambridge, MA

⁴Gastrointestinal Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA

⁵Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA

⁶Departments of Epidemiology and Nutrition, Harvard School of Public Health, Boston, MA

⁷Department of Pathology, Brigham and Women’s Hospital, Boston and Harvard Medical School, Boston, MA

Correspondence to: Shuji Ogino, M.D., Ph.D., 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, Tel: 617-632-3978; Fax: 617-277-9015, Email: shuji_ogino/at/dfci.harvard.edu

Y Baba, K Nosho and K Shima contributed equally.

The publisher's final edited version of this article is available free at Cancer Epidemiol Biomarkers Prev

See other articles in PMC that cite the published article.

Abstract

Background

Prostaglandin-endoperoxide synthase 2 (PTGS2, the HUGO Gene Nomenclature Committee-approved official symbol for cycloxygenase-2, COX-2) and its enzymatic product prostaglandin E2 have critical roles in inflammation and carcinogenesis through the G-protein-coupled prostaglandin E receptor 2 (PTGER2, EP2). The PTGS2 (COX-2) pathway is a promising target for cancer therapy and chemoprevention. PTGS2 (COX-2) expression in colon cancer has been inversely associated with survival as well as tumoral microsatellite instability (MSI) and the CpG island methylator phenotype (CIMP). However, the prognostic significance of PTGER2 expression or its relationship with MSI, CIMP, LINE-1 hypomethylation or PTGS2 (COX-2) remains uncertain.

Methods

Utilizing the database of 516 colorectal cancers in two prospective cohort studies with clinical outcome data, we detected PTGER2 overexpression in 169 (33%) tumors by immunohistochemistry. We analyzed MSI using 10 microsatellite markers; CIMP by MethyLight (real-time methylation-specific PCR) on 8-marker panel [CACNA1G, CDKN2A (p16), CRABP1, IGF2, MLH1, NEUROG1, RUNX3 and SOCS1]; BRAF, KRAS, PIK3CA, and methylation in LINE-1 by Pyrosequencing; and CTNNB1 (β-catenin) and TP53 (p53) by immunohistochemistry.

Results

PTGER2 overexpression was positively associated with mucinous component (p=0.0016), signet ring cells (p=0.0024), CIMP-high (p=0.0023), and MSI-high (p<0.0001). In multivariate analysis, the significant relationship between PTGER2 and MSI-high persisted (adjusted odds ratio 2.82; 95% confidence interval, 1.69–4.72; p<0.0001). PTGER2 was not significantly associated with PTGS2 (COX-2), TP53 or CTNNB1 expression, patient survival or prognosis.

Conclusion

PTGER2 overexpression is associated with MSI-high in colorectal cancer.

Impact

Our data imply potential roles of inflammatory reaction by PTGER2 upregulation in carcinogenic process to MSI-high colorectal cancer.

Keywords: colon cancer, PGE, MSI, CIMP, PTGS2

INTRODUCTION

Prostaglandin-endoperoxide synthase 2 (PTGS2, the HUGO Gene Nomenclature Committee-approved official symbol for cycloxygenase-2, or COX-2) and its enzymatic product prostaglandin E2 (PGE2) play important roles in cancer cell proliferation, invasion, stem cells regeneration and tumor angiogenesis (1–7). Epidemiologic evidence suggests that regular aspirin use decreases colorectal cancer incidence and mortality through inhibition of PTGS2 (COX-2) (8, 9). In fact, the PTGS2 (COX-2) pathway has been an attractive target for chemoprevention and multiple trials targeting this pathway have been ongoing (10–19). PGE2 produces cellular signaling through binding to prostaglandin E receptors (PTGER), designated as PTGER1 (EP1), PTGER2 (EP2), PTGER3 (EP3), and PTGER4 (EP4) (20–23). Among them, PTGER2 has been shown to play critical roles in PTGS2 (COX-2)-induced colon cancer development in an experimental system (24). Thus, a better understanding of the role of PTGER2 in colorectal cancer is crucial for the purpose of cancer therapy and chemoprevention targeting the PTGS2 (COX-2) pathway. However, there has been no comprehensive large-scale study on PTGER2 expression in human cancers.

Microsatellite instability (MSI) refers to altered lengths (“instability”) of short nucleotide repeat sequences (“microsatellite”) in tumor DNA compared to normal DNA. A high degree of MSI (MSI-high) is present as a distinct phenotype in ~15% of colorectal cancers, and MSI-high tumors are believed to arise through a distinct precursor pathway (25). Most MSI-high cancers are caused by epigenetic silencing of a DNA mismatch repair gene MLH1, in a setting of widespread promoter CpG island methylation referred to as the CpG island methylator phenotype (CIMP) (26–28). A minority of MSI-high cancers are due to other causes of sporadic mismatch repair deficiency or a germline mutation in a mismatch repair gene (29–31). MSI and CIMP status reflect global genomic and epigenomic aberrations in tumor cells and determine clinical, pathologic and molecular characteristics of colorectal cancer (31). Thus, a molecular classification based on MSI and CIMP status is increasingly important (30, 31). Although PTGS2 (COX-2) expression in colorectal cancer has been inversely associated with MSI (32–34) and CIMP (34), the relationship between PTGER2, MSI and CIMP remains unknown.

We therefore conducted this study with three main aims. First, we examined the importance of PTGER2 in human colorectal cancer by determining the overall prevalence of PTGER2 expression in a large number of tumors (N=516). Second, since we concurrently assessed other important markers of colorectal cancer, including MSI, CIMP, PTGS2 (COX-2) and β-catenin, as well as mutations in KRAS, BRAF, and PIK3CA, we evaluated the relations of PTGER2 expression with those molecular features. Thirdly, given the potentially important role of PTGER2 in tumor progression, we specifically assessed the relationship between PTGER2 expression and patient prognosis. It is important to publish well-designed studies on patient outcome with adequate statistical power and even with null findings, to avoid potential publication bias.

MATERIALS AND METHODS

Study group

We utilized the databases of two independent, prospective cohort studies; the Nurses’ Health Study (N = 121,701 women followed since 1976) (8), and the Health Professionals Follow-up Study (N = 51,529 men followed since 1986) (8). Every 2 years, participants have been sent follow-up questionnaires to update information on potential risk factors and to identify newly diagnosed cancers in themselves and their first degree relatives. During prospective follow-up of the cohort participants up to 2002, there were 1691 incident colorectal cancer patients with available medical records, who would have adequate follow-up up to 2008. Study physicians reviewed all records related to colorectal cancer, and recorded TNM stage and tumor location. We collected paraffin-embedded tissue blocks from hospitals where patients underwent tumor resections (8). We excluded cases preoperatively treated with radiation and/or chemotherapy. Based on availability of adequate tissue specimens for tissue microarray construction (TMA) and results, a total of 516 colorectal cancers were included (Table 1). Among our cohort studies, there was no significant difference in demographic features between cases with tissue available and those without available tissue (8). The distribution of tumor stage was similar among cases with tumor tissue available and those without available tissue, although cases without available tissue showed a higher frequency of cases with missing stage data; the distribution of tumor stage was as follows (in the order of I, II, III, IV, and unknown): 113 (22%), 162 (31%), 137 (27%), 71 (14%), and 33 (6.4%) among cases with tissue available, and 287 (24%), 264 (22%), 259 (22%), 189 (16%), and 176 (15%) among cases without available tissue. Tissue sections from all colorectal cancer cases were reviewed by a pathologist (S.O.) unaware of other data. As “less than 50% gland formation” is generally accepted as the definition of high grade colorectal cancer (i.e. poorly differentiated tumor), the tumor grade was categorized as high (<50% gland formation) vs. low (≥50% gland formation). The extent of extracellular mucinous component and signet ring cell component was recorded. Patients were observed until death or June 2008, whichever came first. This current analysis represents a new analysis of PTGER2 on the existing colorectal cancer database that has been previously characterized for CIMP, MSI, LINE-1 methylation and clinical outcome (35–39), which is analogous to novel studies using the well-described cell lines or animal models. We have not examined PTGER2 expression in any of our previous studies. Written informed consent was obtained from all study subjects. Tissue collection and analyses were approved by the Harvard School of Public Health and Brigham and Women’s Hospital Institutional Review Boards.

Table 1

Frequency of PTGER2 overexpression in colorectal cancer

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

Genomic DNA was extracted from tumor and PCR and Pyrosequencing targeted for KRAS (codons 12 and 13) (40), BRAF (codon 600) (41) and PIK3CA (exons 9 and 20) (42) were performed as previously described. The status of MSI was determined by analyzing variability in the length of the microsatellite markers from tumor DNA compared to normal DNA. In addition to the recommended MSI panel consisting of D2S123, D5S346, D17S250, BAT25, and BAT26 (43), we used BAT40, D18S55, D18S56, D18S67, and D18S487 (i.e., 10-marker panel) (44). MSI-high was defined as the presence of instability in ≥30% of the markers, MSI-low as instability in 1–29% of the markers, and “microsatellite stable” (MSS) tumors as tumors without an unstable marker.

Real-time PCR for CpG island methylation and Pyrosequencing to measure LINE-methylation

Sodium bisulfite treatment on genomic DNA and subsequent real-time PCR (MethyLight) were validated and performed as previously described (45). We quantified DNA methylation in 8 CIMP-specific promoters [CACNA1G, CDKN2A (p16), CRABP1, IGF2, MLH1, NEUROG1, RUNX3 and SOCS1] (28, 35, 46, 47). CIMP-high was defined as the presence of ≥6 of 8 methylated promoters, CIMP-low as the presence of 1/8–5/8 methylated promoters, and CIMP-0 as the absence (0/8) of methylated promoters, according to the previously established criteria (35). In order to accurately quantify relatively high methylation levels in LINE-1 repetitive elements, we utilized Pyrosequencing as previously described (48, 49).

Immunohistochemistry for PTGER2, p53, PTGS2 (COX-2) and β-catenin

Tissue microarrays (TMAs) were constructed as previously described (34). Two 0.6-mm tissue cores each from tumor and normal colonic mucosa were placed in each TMA block. Appropriate positive and negative controls were included in each run of immunohistochemistry. Methods of immunohistochemical procedure and interpretation were previously described for p53 (50), PTGS2 (COX-2) (44, 51) and β-catenin (52). For PTGER2 staining (Figure 1), antigen retrieval was performed, and deparaffinized tissue sections in Antigen Retrieval Citra Solution (Biogenex Laboratories, San Ramon, CA) were treated with microwave (15 min). Tissue sections were incubated with 10% normal goat serum (Vector Laboratories, Burlingame, CA) in phosphate-buffered saline (30 min). Primary antibody against PTGER2 [Rabbit polyclonal anti-EP₂ receptor, 1:500 dilution; Cayman Chemical, Ann Arbor, MI] was applied, and the slides were maintained at 4°C for overnight, followed by rabbit secondary antibody (Vector Laboratories) (30 min), an avidin–biotin complex conjugate (Vector Laboratories) (30 min), diaminobenzidine (5 min) and methyl-green counterstain. Most normal epithelial cells showed weak cytoplasmic PTGER2 expression. In each case, we recorded the fraction of tumor cells with cytoplasmic PTGER2 overexpression as compared to normal colonic epithelial cells. Considering the inverse relation between PTGS2 (COX-2) expression and MSI (32–34), we used MSI to determine a cutoff for PTGER2 positivity. There was no alternative biologically-based method to determine the cutoff of PTGER2 expression in a large number of paraffin-embedded tumors. In our initial exploratory analysis, we randomly select 258 tumors from 516 tumors as a training set. Using the training set with available MSI data, the frequency of MSI-high in each category was as follows: 12% (12/104) in 0–24% of tumor cells expressing PTGER2; 7.4% (4/54) in 25–49% of tumor cells expressing PTGER2; 22% (19/85) in ≥50% of tumor cells expressing PTGER2. Thus, PTGER2 positivity was defined as cytoplasmic overexpression in ≥50% tumor cells. In the remaining validation set with available MSI data, PTGER2 overexpression was significantly associated with MSI-high [odds ratio (OR) 3.42; 95% confidence interval (CI), 1.84–6.33; in the training set, OR 2.55; 95% CI, 1.24–5.28], confirming the validity of our cutoff for PTGER2 positivity, although it might not be the best cutoff.

Figure 1

PTGER2 expression in colorectal cancer.

PTGER2 expression in colon cancer cells (white arrowheads).
No PTGER2 overexpression in colon cancer cells (black arrowheads).
Frequencies of MSI/CIMP subtypes of colorectal cancer according to PTGER2 expression status.

(more ...)

Each immunohistochemical marker was interpreted by one of the investigators (PTGER2 by Y.B.; p53 and PTGS2 by S.O.; β-catenin by K.N.) unaware of other data. For agreement studies, a random selection of more than 100 cases was examined for each marker by a second pathologist (PTGER2 by K.S.; p53 by K.N.; PTGS2 by R. Dehari, Kanagawa Cancer Center; and β-catenin by S.O.) unaware of other data. The concordance between the two observers (all p<0.0001) was 0.84 (κ=0.69; N=128) for PTGER2, 0.87 (κ=0.75; N=118) for p53, 0.92 (κ=0.62; N=108) for PTGS2 (COX-2) and 0.83 (κ=0.65; N=402) for β-catenin, indicating substantial agreement.

Statistical analysis

All statistical analyses used SAS program (Version 9.1, SAS Institute, Cary, NC). All p values were two-sided, and statistical significance was set at p=0.05. Nonetheless, when we performed multiple hypothesis testing, a p value for significance was adjusted by Bonferroni correction to p=0.0029 (=0.05/17). For categorical data, the chi-square test was performed and odds ratio (OR) with 95% confidence interval (CI) was computed. To assess independent relations of PTGER2 overexpression with other variables, we constructed a multivariate logistic regression model, initially including sex, age at diagnosis (continuous), body mass index (BMI, <30 vs. ≥30 kg/m²), year of diagnosis (continuous), family history of colorectal cancer in any first degree relative (present vs. absent), tumor location (rectum vs. colon), tumor stage (I–II vs. III–IV), tumor grade (low vs. high), mucinous component (0% vs. >0%), signet ring cells (0% vs. >0%), CIMP status (high vs. low/0), MSI status (high vs. low/MSS), LINE-1 methylation (continuous), BRAF, KRAS, PIK3CA, p53, PTGS2 (COX-2) and β-catenin. A backward stepwise elimination with a threshold of p=0.20 was used to select variables in the final model. For cases with missing information in variables [tumor location (1.7%), tumor grade (5.2%), CIMP (2.3%), MSI (1.2%), BRAF (1.6%), KRAS (0.8%), p53 (1.9%), and PTGS2 (0.9%)], we included those cases in a majority category of the missing variable, in order to avoid overfitting. After the selection was done, we assigned separate missing indicator variables to those cases with missing information in any of the categorical covariates in the final model. We confirmed that excluding cases with missing information in any of the covariates did not substantially alter results (data not shown).

For survival analysis, Kaplan-Meier method and log-rank test were used to assess survival time distribution according to PTGER2 status. For analyses of colorectal cancer-specific mortality, death as a result of colorectal cancer was the primary end point and deaths as a result of other causes were censored. To assess independent effect of PTGER2 on mortality, we constructed a multivariate, stage-matched (stratified) Cox proportional hazard model to compute a hazard ratio (HR) according to PTGER2 status, initially adjusted for sex, age, BMI, family history of colorectal cancer, year of diagnosis, tumor location, tumor grade, mucinous component, signet ring cell component, CIMP, MSI, BRAF, KRAS, PIK3CA, LINE-1 methylation, p53, PTGS2 (COX-2) and β-catenin. A backward stepwise elimination with a threshold of p=0.20 was used to select variables in the final model. Tumor stage (I, IIA, IIB, IIIA, IIIB, IIIC, IV, unknown) was used as a stratifying (matching) variable in Cox models using the “strata” option in the SAS “proc phreg” command to avoid residual confounding and overfitting. The proportionality of hazard assumption was satisfied by evaluating time-dependent variables, which were the cross-product of the PTGER2 variable and survival time (p=0.91 for colon cancer-specific mortality; p=0.42 for overall mortality). An interaction was assessed by including the cross product of PTGER2 variable and another variable of interest (without data-missing cases) in a multivariate Cox model, and the Wald test was performed.

RESULTS

PTGER2 overexpression in colorectal cancer

Among 516 colorectal cancers, we observed PTGER2 overexpression in 169 tumors (33%) by immunohistochemistry. Table 1 shows the relationships of PTGER2 status with various clinical, pathologic or molecular features. PTGER2 overexpression appeared to be associated with male gender [odds ratio (OR) 1.60; 95% confidence interval (CI), 1.09–2.34; p=0.015], mucinous component (OR 1.90; 95% CI, 1.27–2.83; p=0.0016), signet ring cells (OR 2.89; 95% CI, 1.42-5.88; p=0.0024), MSI-high (compared to MSI-low/MSS; OR 2.94; 95% CI, 1.84–4.69; p<0.0001), CIMP-high (compared to CIMP-low/0; OR 2.35; 95% CI, 1.44–3.84; p=0.0005) and BRAF mutation (OR 1.70; 95% CI, 1.01–2.84; p=0.044); nonetheless, multiple testing should be considered and p=0.0029 was required for statistical significance after Bonferroni correction. PTGER2 overexpression was not significantly associated with other tumoral variables including PTGS2 (COX-2), p53 or β-catenin expression, KRAS or PIK3CA mutation, or LINE-1 methylation. Notably, PTGER2 overexpression was not significantly related with tumor location (p=0.66).

Thus, PTGER2 expression was significantly associated with both MSI-high and CIMP-high (p<0.0029). Considering the pathogenic link between CIMP and MSI, we stratified tumors according to MSI and CIMP status, and examined a distribution of MSI/CIMP subtypes among PTGER2-positive tumors and PTGER2-negative tumors (Figure 1C). The proportion of tumors with MSI-high was significantly larger among PTGER2-positive tumors than among PTGER2-negative tumors regardless of CIMP status (p<0.0001), suggesting the role of PTGER2 in the MSI-high pathway to colorectal cancer (Figure 1D).

PTGER2 overexpression is independently associated with MSI-high

We performed multivariate logistic regression analysis to examine whether PTGER2 overexpression was independently associated with MSI or any of clinical, pathologic and other molecular variables (Table 2). PTGER2 overexpression was significantly associated with MSI-high (multivariate OR 2.82; 95% CI, 1.69–4.72; p<0.0001). In addition, PTGER2 overexpression appears to be related with signet ring cells (multivariate OR 2.82; 95% CI, 1.27-6.27; p=0.011) and age at diagnosis (for a 10-year increase; multivariate OR 1.36; 95% CI, 1.07-1.72; p=0.012); however, considering multiple hypothesis testing, these associations with p>0.0029 might simply be chance findings. The independent association between PTGER2 overexpression and MSI-high was observed separately in female cases (the Nurses’ Health Study; multivariate OR 2.56; 95% CI, 1.38–4.73; p=0.0028) and male cases (the Health Professionals Follow-up Study; multivariate OR 4.09; 95% CI, 1.64–10.2; p=0.0025).

Table 2

Multivariate analysis of the relationship with PTGER2 in colorectal cancer

PTGER2 overexpression and patient survival

We assessed the influence of PTGER2 overexpression on patient mortality. During follow-up of 491 patients who were eligible for survival analysis, there were 235 deaths, including 139 deaths attributed to colorectal cancer. Mean and median follow-up for censored cases was 12.7 years and 11.9 years, respectively. Utilizing our cohort database with adequate patient follow-up, we previously demonstrated that molecular features in colon cancer such as PTGS2 (COX-2) expression, BRAF mutation, FASN expression, PIK3CA mutation and LINE-1 hypomethylation were significantly associated with patient prognosis (36–39, 51). In Kaplan-Meier analysis, PTGER2 overexpression was not significantly associated with colorectal cancer-specific (log rank p=0.55) or overall survival (log rank p=0.26) (Figure 2). We performed univariate and multivariate Cox regression analysis to assess patient mortality according to PTGER2 status (Table 3). For colorectal cancer-specific or overall mortality, PTGER2 overexpression was not significantly related with patient outcome in univariate, stage-matched, or multivariate analysis.

Figure 2

Kaplan-Meier curves for colorectal cancer-specific survival (upper panel) and overall survival (lower panel) according to PTGER2 status in colorectal cancer. The bottom table shows the number of patients who were alive and at risk of death at each time (more ...)

Table 3

PTGER2 expression in colorectal cancer and patient mortality

Finally, we examined whether the influence of PTGER2 overexpression on overall survival was modified by any of the other variables including sex, age, BMI, family history of colorectal cancer, tumor location, mucinous component, signet ring cells, stage, tumor grade, CIMP, MSI, BRAF, KRAS, PIK3CA, LINE-1 methylation, p53, PTGS2 (COX-2) and β-catenin. We did not observe a significant effect modification by any of the covariates in survival analysis (all P_interaction >0.08). Notably, either in women (the Nurses’ Health Study) or men (the Health Professionals Follow-up Study), PTGER2 expression was not significantly associated with patient survival (p=0.67 and P=0.26, respectively).

DISCUSSION

In this study, we examined PTGER2 (prostaglandin E receptor 2, EP2) expression in colorectal cancer, in relation to expression of prostaglandin-endoperoxide synthase 2 (PTGS2, the HUGO Gene Nomenclature Committee-approved official symbol for cycloxygenase-2, or COX-2), microsatellite instability (MSI), the CpG island methylator phenotype (CIMP) and clinical outcome. PTGER2 is a G-protein-coupled receptor that mediates the action of prostaglandin E2 (PGE2), a major product of PTGS2 (COX-2), which contributes to colon cancer development. As the inverse association of PTGS2 (COX-2) with MSI and CIMP has been reported in colorectal cancer (32–34), a better understanding of interrelationship between PTGER2, PTGS2 (COX-2), MSI and CIMP may shed lights on biological mechanisms of PTGS2 (COX-2)-induced tumorigenesis. We found that PTGER2 overexpression was significantly associated with MSI-high, independent of CIMP status and other variables. Our data further support PTGER2 expression as one of unique characteristics of MSI-high colorectal cancer.

Our resource of a large number of colorectal cancers derived from the two prospective cohort studies has enabled us to precisely estimate the frequency of colorectal cancers with a specific molecular feature (such as PTGER2 overexpression, MSI-high, CIMP-high, etc.) at the population level. The large number of cases has also provided a sufficient power in our multivariate logistic regression analysis and survival analysis.

Studying molecular changes is important in colorectal cancer research (53–61). A molecular classification based on MSI and CIMP status is increasingly important, because MSI and CIMP reflect global genomic and epigenomic aberrations, respectively, in tumor cells (30, 31). Some studies including our previous study indicated the “inverse” association of PTGS2 (COX-2) expression with MSI-high and CIMP-high in colorectal cancer (32–34). Interestingly, our current study has shown that PTGER2 overexpression is positively associated with MSI-high, independent of CIMP status. MSI status reflects genomic aberrations in tumor cells and determines molecular characteristics and phenotypes of colorectal cancer. Our findings suggest that PTGER2 overexpression may play a role in the pathway to MSI-high cancer, whereas PTGS2 (COX-2) overexpression may be important in the pathway to MSI-low/MSS cancer (Figure 1D). Additional studies are necessary to confirm our findings as well as to elucidate the exact relationship between the PTGS2 (COX-2)/PTGER2 pathway and MSI status in colorectal tumorigenesis.

The prognostic role of PTGER2 overexpression in human cancer is inconclusive. A study on esophageal squamous cell carcinoma (N=226) has reported that PTGER2 overexpression is related with poor prognosis in univariate analysis, but not in multivariate analysis (62). Another study on lung cancer has indicated the prognostic value of PTGER2 overexpression among individuals with squamous cell carcinoma (N=39), but not among those with adenocarcinoma (N=43) (63). In a previous study on colorectal cancer (N=72) (64), PTGER2 overexpression was independently associated with poor prognosis. However, most of these studies were limited by low statistical power. Small studies (N<100) with null results have much higher likelihood of being unpublished than small studies with “significant” results, leading to publication bias. In our current study (N=516), PTGER2 overexpression was not significantly associated with clinical outcome, while it was highly significantly associated with MSI-high (P<0.0001). An experimental study using colon cancer cells has shown that PTGER2 expression leads to increased tumor growth, supporting PTGER2 as an oncogene (24). Nonetheless, colorectal cancers with activation of a given oncogene or inactivation of a given tumor suppressor are not always associated with poor clinical outcome. For example, MSI-high cancers are associated with inactivation of many tumor suppressors and with good prognosis (65). Our findings suggest that PTGER2 overexpression may not mark an aggressive type of colorectal cancer.

The PTGS2 (COX-2)/PGE2 pathway is increasingly important as a target for colorectal cancer treatment and chemoprevention (10–19). Within our two prospective cohort studies, regular aspirin use reduced the risk of developing colorectal cancer, in particular, tumor with PTGS2 (COX-2) overexpression (8). In addition, regular aspirin use after the diagnosis of colorectal cancer was associated with lower risk of colorectal cancer-specific and overall mortality, especially among patients with tumors with PTGS2 (COX-2) overexpression (9). Thus, in the near future, PTGS2 (COX-2) expression may well serve as a selective marker for aspirin treatment in the management of colorectal cancer (16). Aspirin has been reported to suppress MSI in mismatch repair-deficient and hereditary nonpolyposis colorectal cancer cells (66, 67). Considering the intriguing relation between PTGS2 (COX-2), PTGER2, and MSI status demonstrated in our current study, the effect of aspirin on colorectal cancer may be influenced not only by PTGS2 (COX-2) expression status but also PTGER2 expression status. In this respect, our findings may be of clinical interest. We currently plan further analysis on PTGER2 expression, aspirin use and patient survival to test this latter hypothesis.

In conclusion, PTGER2 overexpression in colorectal cancer is associated with MSI, independent of CIMP status, PTGS2 (COX-2), and other variables. An exact mechanism of the possible pathogenic link between the PTGS2 (COX-2)/PTGER2 pathway and MSI needs to be investigated. A better understanding of the role of PTGER2 in colorectal cancer is important for the purpose of cancer therapy and chemoprevention targeting the PTGS2 (COX-2) pathway.

Acknowledgments

This work was supported by The U.S. National Institute of Health (NIH) grants P01 CA87969 (to S. Hankinson), P01 CA55075 (to W. Willett), P50 CA127003 (to C.S.F.), K07 CA107412 (to A.T.C.) and K07 CA122826 (to S.O.), and in part by grants from the Bennett Family Fund and the Entertainment Industry Foundation National Colorectal Cancer Research Alliance (NCCRA). K.No. was supported by a fellowship grant from the Japan Society for Promotion of Science. In addition, A.T.C. was supported by a grant from the Damon Runyon Cancer Research Foundation. These funding sponsors had no role or involvement in the study design, the collection, analysis and interpretation of data, or writing and submission of the manuscript. 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. We thank Frank Speizer, Walter Willett, Susan Hankinson, Meir Stampfer, and many other staff members who implemented and have maintained the cohort studies.

Abbreviations and HUGO Gene Nomenclature Committee-approved official gene symbols


BMI	body mass index

CI	confidence interval

CIMP	CpG island methylator phenotype

COX-2	cyclooxygenase-2

HR	hazard ratio

MSI	microsatellite instability

MSS	microsatellite stable

OR	odds ratio

PGE2	prostaglandin E2

PTGER2	prostaglandin E receptor 2 (subtype EP2)

PTGS2	prostaglandin-endoperoxide synthase 2 (cyclooxygenase-2)

Footnotes

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. No conflicts of interest exist.

References

1. Brown JR, DuBois RN. COX-2: a molecular target for colorectal cancer prevention. J Clin Oncol. 2005;23:2840–2855. [PubMed]

2. Wang D, Buchanan FG, Wang H, Dey SK, DuBois RN. Prostaglandin E2 enhances intestinal adenoma growth via activation of the Ras-mitogen-activated protein kinase cascade. Cancer Res. 2005;65:1822–1829. [PubMed]

3. Jain S, Chakraborty G, Raja R, Kale S, Kundu GC. Prostaglandin E2 regulates tumor angiogenesis in prostate cancer. Cancer Res. 2008;68:7750–7759. [PubMed]

4. Markowitz SD. Colorectal neoplasia goes with the flow: prostaglandin transport and termination. Cancer Prev Res (Phila Pa) 2008;1:77–79. [PMC free article] [PubMed]

5. Greenhough A, Smartt HJ, Moore AE, et al. The COX-2/PGE2 pathway: key roles in the hallmarks of cancer and adaptation to the tumour microenvironment. Carcinogenesis. 2009;30:377–386. [PubMed]

6. Goessling W, North TE, Loewer S, et al. Genetic interaction of PGE2 and Wnt signaling regulates developmental specification of stem cells and regeneration. Cell. 2009;136:1136–1147. [PMC free article] [PubMed]

7. Yan M, Myung SJ, Fink SP, et al. 15-Hydroxyprostaglandin dehydrogenase inactivation as a mechanism of resistance to celecoxib chemoprevention of colon tumors. Proc Natl Acad Sci U S A. 2009;106:9409–9413. [PubMed]

8. Chan AT, Ogino S, Fuchs CS. Aspirin and the risk of colorectal cancer in relation to the expression of COX-2. N Engl J Med. 2007;356:2131–2142. [PubMed]

9. Chan AT, Ogino S, Fuchs CS. Aspirin use and survival after diagnosis of colorectal cancer. JAMA. 2009;302:649–658. [PMC free article] [PubMed]

10. Castellone MD, Teramoto H, Gutkind JS. Cyclooxygenase-2 and colorectal cancer chemoprevention: the beta-catenin connection. Cancer Res. 2006;66:11085–11088. [PubMed]

11. Clevers H. Colon cancer--understanding how NSAIDs work. N Engl J Med. 2006;354:761–763. [PubMed]

12. Arber N, Eagle CJ, Spicak J, et al. Celecoxib for the prevention of colorectal adenomatous polyps. N Engl J Med. 2006;355:885–895. [PubMed]

13. Bertagnolli MM, Eagle CJ, Zauber AG, et al. Celecoxib for the prevention of sporadic colorectal adenomas. N Engl J Med. 2006;355:873–884. [PubMed]

14. Arber N. Cyclooxygenase-2 inhibitors in colorectal cancer prevention: point. Cancer Epidemiol Biomarkers Prev. 2008;17:1852–1857. [PubMed]

15. Bertagnolli MM, Eagle CJ, Zauber AG, et al. Five-year efficacy and safety analysis of the Adenoma Prevention with Celecoxib Trial. Cancer Prev Res (Phila Pa) 2009;2:310–321. [PMC free article] [PubMed]

16. Neugut AI. Aspirin as adjuvant therapy for colorectal cancer: a promising new twist for an old drug. JAMA. 2009;302:688–689. [PubMed]

17. Cuzick J, Otto F, Baron JA, et al. Aspirin and non-steroidal anti-inflammatory drugs for cancer prevention: an international consensus statement. Lancet Oncol. 2009;10:501–507. [PubMed]

18. Jankowski J, Hunt R. Cyclooxygenase-2 inhibitors in colorectal cancer prevention: counterpoint. Cancer Epidemiol Biomarkers Prev. 2008;17:1858–1861. [PubMed]

19. Leshno M, Moshkowitz M, Arber N. Point/Counterpoint: Aspirin is clinically effective in chemoprevention of colorectal neoplasia: point. Cancer Epidemiol Biomarkers Prev. 2008;17:1558–1561. [PubMed]

20. 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;7:1048–1051. [PubMed]

21. Hull MA, Ko SC, Hawcroft G. Prostaglandin EP receptors: targets for treatment and prevention of colorectal cancer? Mol Cancer Ther. 2004;3:1031–1039. [PubMed]

22. Sung YM, He G, Fischer SM. Lack of expression of the EP2 but not EP3 receptor for prostaglandin E2 results in suppression of skin tumor development. Cancer Res. 2005;65:9304–9311. [PubMed]

23. Hawcroft G, Ko CW, Hull MA. Prostaglandin E2-EP4 receptor signalling promotes tumorigenic behaviour of HT-29 human colorectal cancer cells. Oncogene. 2007;26:3006–3019. [PubMed]

24. Castellone MD, Teramoto H, Williams BO, Druey KM, Gutkind JS. Prostaglandin E2 promotes colon cancer cell growth through a Gs-axin-beta-catenin signaling axis. Science. 2005;310:1504–1510. [PubMed]

25. Grady WM, Carethers JM. Genomic and epigenetic instability in colorectal cancer pathogenesis. Gastroenterology. 2008;135:1079–1099. [PMC free article] [PubMed]

26. Issa JP. CpG island methylator phenotype in cancer. Nat Rev Cancer. 2004;4:988–993. [PubMed]

27. Samowitz WS, Albertsen H, Herrick J, et al. Evaluation of a large, population-based sample supports a CpG island methylator phenotype in colon cancer. Gastroenterology. 2005;129:837–845. [PubMed]

28. 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;38:787–793. [PubMed]

29. Samowitz WS. The CpG island methylator phenotype in colorectal cancer. J Mol Diagn. 2007;9:281–283. [PubMed]

30. Jass JR. Classification of colorectal cancer based on correlation of clinical, morphological and molecular features. Histopathology. 2007;50:113–130. [PubMed]

31. Ogino S, Goel A. Molecular classification and correlates in colorectal cancer. J Mol Diagn. 2008;10:13–27. [PubMed]

32. Sinicrope FA, Lemoine M, Xi L, et al. Reduced expression of cyclooxygenase 2 proteins in hereditary nonpolyposis colorectal cancers relative to sporadic cancers. Gastroenterology. 1999;117:350–358. [PubMed]

33. Karnes WE, Jr, Shattuck-Brandt R, Burgart LJ, et al. Reduced COX-2 protein in colorectal cancer with defective mismatch repair. Cancer Res. 1998;58:5473–5477. [PubMed]

34. Ogino S, Brahmandam M, Kawasaki T, Kirkner GJ, Loda M, Fuchs CS. 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;8:458–464. [PMC free article] [PubMed]

35. Ogino S, Kawasaki T, Kirkner GJ, Kraft P, Loda M, Fuchs CS. Evaluation of markers for CpG island methylator phenotype (CIMP) in colorectal cancer by a large population-based sample. J Mol Diagn. 2007;9:305–314. [PubMed]

36. Ogino S, Nosho K, Kirkner GJ, et al. CpG island methylator phenotype, microsatellite instability, BRAF mutation and clinical outcome in colon cancer. Gut. 2009;58:90–96. [PMC free article] [PubMed]

37. 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;100:1734–1738. [PMC free article] [PubMed]

38. 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;27:1477–1484. [PMC free article] [PubMed]

39. 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;26:5713–5720. [PMC free article] [PubMed]

40. Ogino S, Kawasaki T, Brahmandam M, et al. Sensitive sequencing method for KRAS mutation detection by Pyrosequencing. J Mol Diagn. 2005;7:413–421. [PubMed]

41. Ogino S, Kawasaki T, Kirkner GJ, Loda M, Fuchs CS. CpG island methylator phenotype-low (CIMP-low) in colorectal cancer: possible associations with male sex and KRAS mutations. J Mol Diagn. 2006;8:582–588. [PubMed]

42. Nosho K, Kawasaki T, Ohnishi M, et al. PIK3CA mutation in colorectal cancer: relationship with genetic and epigenetic alterations. Neoplasia. 2008;10:534–541. [PMC free article] [PubMed]

43. Boland CR, Thibodeau SN, Hamilton SR, et al. A National Cancer Institute Workshop on Microsatellite Instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer. Cancer Res. 1998;58:5248–5257. [PubMed]

44. Ogino S, Brahmandam M, Cantor M, et al. Distinct molecular features of colorectal carcinoma with signet ring cell component and colorectal carcinoma with mucinous component. Mod Pathol. 2006;19:59–68. [PubMed]

45. Ogino S, Kawasaki T, Brahmandam M, et al. Precision and performance characteristics of bisulfite conversion and real-time PCR (MethyLight) for quantitative DNA methylation analysis. J Mol Diagn. 2006;8:209–217. [PubMed]

46. 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;55:1000–1006. [PMC free article] [PubMed]

47. 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]

48. Ogino S, Kawasaki T, Nosho K, et al. LINE-1 hypomethylation is inversely associated with microsatellite instability and CpG island methylator phenotype in colorectal cancer. Int J Cancer. 2008;122:2767–2773. [PMC free article] [PubMed]

49. Irahara N, Nosho K, Baba Y, et al. Precision of pyrosequencing assay to measure LINE-1 methylation in colon cancer, normal colonic mucosa and peripheral blood cells. J Mol Diagn. 2010 in press. [PubMed]

50. Ogino S, Kawasaki T, Kirkner GJ, Yamaji T, Loda M, Fuchs CS. Loss of nuclear p27 (CDKN1B/KIP1) in colorectal cancer is correlated with microsatellite instability and CIMP. Mod Pathol. 2007;20:15–22. [PubMed]

51. 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;14:8221–8227. [PMC free article] [PubMed]

52. 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;9:569–577. [PMC free article] [PubMed]

53. Fatima N, Yi M, Ajaz S, et al. Altered gene expression profiles define pathways in colorectal cancer cell lines affected by celecoxib. Cancer Epidemiol Biomarkers Prev. 2008;17:3051–3061. [PubMed]

54. Takai T, Kanaoka S, Yoshida K, et al. Fecal cyclooxygenase 2 plus matrix metalloproteinase 7 mRNA assays as a marker for colorectal cancer screening. Cancer Epidemiol Biomarkers Prev. 2009;18:1888–1893. [PubMed]

55. Barry EL, Sansbury LB, Grau MV, et al. Cyclooxygenase-2 polymorphisms, aspirin treatment, and risk for colorectal adenoma recurrence--data from a randomized clinical trial. Cancer Epidemiol Biomarkers Prev. 2009;18:2726–2733. [PMC free article] [PubMed]

56. Poynter JN, Siegmund KD, Weisenberger DJ, et al. Molecular characterization of MSI-H colorectal cancer by MLHI promoter methylation, immunohistochemistry, and mismatch repair germline mutation screening. Cancer Epidemiol Biomarkers Prev. 2008;17:3208–3215. [PMC free article] [PubMed]

57. 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;18:967–975. [PMC free article] [PubMed]

58. 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;18:3086–3096. [PubMed]

59. 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;17:1774–1780. [PubMed]

60. 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;18:1041–1049. [PMC free article] [PubMed]

61. 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;18:3384–3388. [PMC free article] [PubMed]

62. Kuo KT, Wang HW, Chou TY, et al. Prognostic role of PGE2 receptor EP2 in esophageal squamous cell carcinoma. Ann Surg Oncol. 2009;16:352–360. [PubMed]

63. Alaa M, Suzuki M, Yoshino M, et al. Prostaglandin E2 receptor 2 overexpression in squamous cell carcinoma of the lung correlates with p16INK4A methylation and an unfavorable prognosis. Int J Oncol. 2009;34:805–812. [PubMed]

64. Gustafsson A, Hansson E, Kressner U, et al. EP1-4 subtype, COX and PPAR gamma receptor expression in colorectal cancer in prediction of disease-specific mortality. Int J Cancer. 2007;121:232–240. [PubMed]

65. Popat S, Hubner R, Houlston RS. Systematic review of microsatellite instability and colorectal cancer prognosis. J Clin Oncol. 2005;23:609–618. [PubMed]

66. Ruschoff J, Wallinger S, Dietmaier W, et al. Aspirin suppresses the mutator phenotype associated with hereditary nonpolyposis colorectal cancer by genetic selection. Proc Natl Acad Sci U S A. 1998;95:11301–11306. [PubMed]

67. McIlhatton MA, Tyler J, Burkholder S, et al. Nitric oxide-donating aspirin derivatives suppress microsatellite instability in mismatch repair-deficient and hereditary nonpolyposis colorectal cancer cells. Cancer Res. 2007;67:10966–10975. [PubMed]