Dig Dis Sci (2014) 59:436–445 DOI 10.1007/s10620-013-2917-1
ORIGINAL ARTICLE
Cyclooxygenase-2 Expression Is Associated with Poor Overall Survival of Patients with Gastric Cancer: A Meta-Analysis Jian Song • Hong Su • Yang-yang Zhou Liang-liang Guo
•
Received: 27 May 2013 / Accepted: 7 October 2013 / Published online: 1 November 2013 Ó Springer Science+Business Media New York 2013
Abstract Background Cyclooxygenase-2 (COX-2) is believed to be involved in gastric carcinogenesis. However, it is still controversial whether COX-2 expression can be regarded as a prognostic factor for gastric cancer patients. Aim To obtain a more accurate relationship between COX-2 overexpression and prognosis in gastric cancer by meta-analysis. Method Relevant articles published up to May 2013 were searched by use of several keywords in electronic databases. Separate hazard ratio (HR) estimates and 95 % confidence intervals (95 % CI) for COX-2 overexpression and overall survival (OS) and disease-free survival (DFS) with gastric cancer were extracted. Combined HR with 95 % CI was calculated by use of Stata11.0 software to estimate the size of the effect. Publication bias testing and sensitivity analysis were also performed. Results A total of 27 studies which included 3,891 gastric cancer patients were combined in the final analysis. Combined results suggested that COX-2 overexpression was associated with an unfavorable OS (HR 1.58, 95 % CI 1.36–1.84) but not DFS (HR 1.15, 95 % CI 0.93–1.43) among patients with gastric cancer. Publication bias was absent. Sensitivity analysis suggested that the results of this meta-analysis were robust. Conclusions The results of this meta-analysis suggest that high COX-2 expression may be an independent risk factor for poor OS of patients with gastric cancer. More large prospective studies are now needed to further clarify the
J. Song H. Su (&) Y. Zhou L. Guo Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 69 Meishan Road, Hefei 230032, Anhui Province, China e-mail: [email protected]
123
prognostic value of COX-2 expression for DFS in gastric cancer. Keywords Gastric cancer Cyclooxygenase-2 (COX-2) Overall survival (OS) Disease-free survival (DFS) Meta-analysis
Introduction Gastric cancer is one of the main malignant tumors, and incidence and mortality have both increased in recent years [1]. Despite continuous improvements in its treatment, survival of gastric cancer patients has not been substantially improved [2]. It is, therefore, very important to identify prognostic factors for gastric cancer which can help us find a better treatment and preventive measures for extending the life of gastric cancer patients. Traditional clinicopathological characteristics, for example tumor size and stage, do not fully predict individual clinical outcome, and much better prognostic factors are needed. The molecular biomarkers involved in tumor development may provide information about the clinical manifestation of the disease and should be considered as potential prognostic factors. Several molecular markers, for example E-cadherin, matrix metalloproteinase-9, and vascular endothelial growth factor (VEGF), have been proved to be associated with prognosis for gastric cancer patients [3–5]. Among biomarkers, COX-2 expression has recently attracted increasing research attention. COX-2, an important rate-limiting enzyme in prostaglandin synthesis, is closely related to tumor development [6]. It has been confirmed that COX-2 affects tumor progression mainly by inhibiting tumor apoptosis, and promoting tumor angiogenesis, tumor invasiveness, and
Dig Dis Sci (2014) 59:436–445
proliferation of tumor cells [7, 8]. The COX-2 pathway has been proved to contribute to gastric tumorigenesis in a transgenic mouse model [9]. Inhibition of COX-2 has also been associated with regression of gastric adenomas in mice [10]. Overexpression of COX-2 has been demonstrated in a variety of malignancies, for example lung, ovarian, and cervical, and is usually associated with an unfavorable survival results [11–13]. Previous studies have found that COX-2 overexpression was associated with several clinicopathological data, for example advance stage, tumor size, and lymph node metastasis, in gastric cancer [14–16]. Several studies have described the relationship between COX-2 expression and prognosis in gastric cancer [17–43]. However, the results were inconsistent. Some researchers found that COX-2 overexpression predicted poor survival [17–22, 24–26, 28, 33, 35, 37, 38, 42] whereas others did not agree [23, 27, 29–32, 34, 36, 39–41, 43]. Meta-analysis is a popular and powerful tool which overcomes the limitation of small sample sizes by combining results from several individual studies to generate a best assessment [44]. We therefore conducted a meta-analysis of published articles to obtain a quantitative estimate of the prognostic significance of COX-2 expression in gastric cancer.
437
Two authors (Song and Zhou) performed the search and identification independently. Data Extraction Two authors (Song and Guo) independently extracted year of publication, name of the first author, country, number of patients, years of follow up, TNM stage, patients characteristics, experimental method, cut off value, percentage of COX-2 positive expression, analytical method, HR, and 95 % CI from the included articles. If any of the above information were not reported in the study, items were treated as ‘‘NR (not reported).’’ Quality Assessment We conducted a quality assessment for each eligible study by using reporting recommendations for tumor marker prognostic studies (REMARK) [45]. Eighteen items were extracted from REMARK (Table 1), which have been used in previous meta-analysis [46]. Each item scored 1 if the study met the demands, otherwise 0 score was given to the study. The final score ranged from 0 to 18 for each study, with higher scores indicating better methodology. Statistical Analysis
Methods Search Strategy and Study Selection Relevant articles studying the relationship between COX-2 expression and survival of gastric cancer patients published up to May, 2013, were retrieved by online search in PubMed and China National Knowledge Infrastructure. We used the keywords: (‘‘cyclooxygenase-2’’ or ‘‘COX-2’’) and (‘‘gastric cancer’’ or ‘‘gastric neoplasms’’ or ‘‘gastric carcinoma’’ or ‘‘stomach cancer’’ or ‘‘stomach neoplasms’’ or ‘‘stomach carcinoma’’) and (‘‘prognostic’’ or ‘‘prognosis’’ or ‘‘survival’’ or ‘‘survive’’). All included studies were required to be written in English or Chinese. References of the original studies were also checked, to ensure all eligible studies could be included. Literature inclusion criteria were: 1 it investigated the association between COX-2 overexpression and overall survival (OS) and/or diseasefree survival (DFS) in gastric cancer patients who underwent surgical resection; 2 it measured COX-2 protein expression in primary gastric cancer tissue by immunohistochemistry (IHC); 3 the value of HR and 95 % CI could be obtained or calculated on the basis of the information given in articles; and 4 for duplicate articles, the newest or most informative was selected.
In this meta-analysis, HR and 95 % CI were used to calculate the overall effect estimate. Some of the studies included provided HR and 95 % CI explicitly. For some studies which did not provide HR and 95 % CI, we calculated the values from the available data or the Kaplan– Meier survive curve in the original studies by using the methods illustrated by Tierney et al. [47] and Parmar et al. [48]. Available data refers to the total number of events, the log-rank statistic and its p value, or the O-E statistic (difference between numbers of observed and expected events). We read the Kaplan–Meier curves by using Engauge Digitizer version 2.11 (free software downloaded from http://sourceforge.net). Heterogeneity was assessed by use of the v2 test and the Q test. When heterogeneity was significant, we used a random-effect model. Otherwise, we used a fixed-effect model. Publication bias was evaluated by use of Begg’s funnel plot and Egger’s linear regression test [49]. The stability of the results was checked by sensitivity analysis. Subgroup analysis was performed by use of different analytical methods (univariate or multivariate) and on the basis of areas (Asian or non-Asian). A pooled HR [1 suggested that positive COX-2 expression predicted an unfavorable prognosis for gastric cancer patients. It was regarded as statistically significant if the 95 % CI of HR did not overlap 1. All the p values were two-sided, p \ 0.05 was regarded as statistically
123
438 Table 1 Definitions of 18 items used to assess study quality 1. Objectives or prespecified hypothesis: state the study objectives, prespecified hypothesis, or study protocol 2. Sample size: state a statistical sample size or power calculation 3. Follow-up description: state the follow-up period or the median follow-up time 4. Population source: state health-care setting from which patients were recruited 5. Population selection criteria: state inclusion or exclusion 6. Population characteristics: state the population characteristics (e.g., age, gender, and disease stage) 7. Number of patients included in each stage of the analysis and reason for drop out: description of number of patients at different stages, including the number of patients who participated in the study, who met the inclusion criteria, and who were followed up, and reason for dropout Assay method 1. Sample handling: state the method of storage 2. Assay method: state the type of assay method used to measure COX-2 3. Manufacturer: state the name of the company which makes the assay for COX-2 4. Cutoff point determination: state methods used for cutoff point determination Confounders 1. Conventional risk factors: state the conventional risk factors (e.g., age, gender, depth of tumor, lymph node metastasis) 2. Other biomarkers (e.g., p53 and microvessel density): state other biologicmarker relating with the disease Outcome 1. Clinical endpoint: define the clinical endpoint 2. Validation: state the outcome events checked by independent source (e.g.,medical records, outpatient visits, by letter, and by telephone) Analysis 1. Univariate estimate: report the effect of COX-2 on outcome 2. Multivariate estimate: adjusted for risk factors or other biomarkers 3. Missing value: state the number of patients with missing value for survival or confounders and how to deal with it
significant. All statistical calculations were performed by use of Stata 11.0.
Results Literature Selection and Study Characteristics Initially, three independent authors (Song, Zhou, and Guo) reviewed the titles and abstracts of the identified studies and excluded irrelevant papers. Full texts of the remaining 37 studies were reviewed to check whether they met the inclusion criteria. Among these, six papers [15, 16, 50–53] contained insufficient data to extract HR and 95 % CI. One
123
Dig Dis Sci (2014) 59:436–445
study estimated the effect of COX-2 overexpression on relapse-free survival in gastric cancer [54]. Moreover, three studies [55–57] were excluded because identical cohorts of patients were used in other selected studies. Twenty-seven papers [17–43] were included in the final analysis. All the main characteristics of the included studies are summarized in Table 2. Among the studies included, 26 papers reported OS results, and only four provided DFS results. The total number of patients was 3,891, ranging from 49 to 830 per study. Most of the studies were conducted on Asian populations [17, 18, 20–23, 25, 26, 28, 30– 34, 36–43]; only five studies were conducted on non-Asian populations [19, 24, 27, 29, 35]. Some of the studies defined the cut off value by use of complex score (CS) combining intensity and percentage of COX-2 expression [17, 19, 20, 23–25, 27, 29–31, 34, 35, 39, 43] whereas the others only used the percentage of COX-2 expression [18, 21, 22, 26, 28, 33, 36–38, 40–42]. One study [32] did not report the definition of COX-2 overexpression. The percent of COX-2 overexpression ranged from 13.9 to 71.6 %. The HR and 95 % CI were directly extracted from 13 original studies [17–20, 23, 24, 26, 30–32, 35, 37, 38]. We obtained the value from the available data for two studies [28, 42], and read the useful data from the Kaplan–Meier curves in the remaining 12 studies [21, 22, 25, 27, 29, 33, 34, 36, 39– 41, 43]. Overall, 11 studies calculated HR and 95 % CI by multivariate analysis [17, 19, 20, 24, 26, 30–32, 35, 37, 38]; the other 16 studies used univariate analysis [18, 21– 23, 25, 27–29, 33, 34, 36, 39–43]. Quality Assessment The final score for all the included studies ranged from 11 to 16; the mean score was 13.4. There was no statistical significance (p = 0.553) between the studies that reported univariate analysis (mean score = 13.6) and studies which reported multivariate analysis (mean score = 13.1). We also failed to find a significant difference between Asian and non-Asian studies (p = 0.999). Main Results The main results of this meta-analysis are shown in Table 3. The combined HR of all studies reporting the effect of COX-2 expression on OS was 1.58 (95 % CI 1.36–1.84), suggesting that COX-2 overexpression was associated with a poor OS in gastric cancer (Fig. 1). There was significant heterogeneity among the studies (I2 = 58.6 %, p \ 0.05). When HRs calculated by univariate analysis were combined, a statistically significant association between COX-2 overexpression and OS of gastric cancer patients was observed (HR 1.51, 95 % CI 1.22–1.86; Fig. 2). The
Dig Dis Sci (2014) 59:436–445
439
Table 2 Main characteristics of included studies First author
Year
Country
No.
TNM
Cut-off
Positive expression (%)
HR estimate
Analytic method
Result
HR (95 % CI)
Zhang [17]
2013
China
830
I–IV
CS
54.0
HR
Multivariate
OS
1.65 (1.34–2.03)
Jiang [18]
2012
China
49
I–IV
10
65.3
KM
Univariate
OS
2.28 (1.72–3.51)
Fanelli [19] Gou [20]
2012 2011
Brazil China
137 56
I–IV I–IV
CS CS
13.9 69.6
HR HR
Multivariate Multivariate
OS OS
3.34 (1.43–9.75) 3.24 (1.20–3.83)
Zhang [21]
2011
China
82
I–IV
5
62.2
KM
Univariate
OS
2.97 (1.51–5.84)
Sun [22]
2011
China
109
I–IV
10
71.6
KM
Univariate
OS
2.16 (1.48–2.86)
Tatsuwaki [23]
2010
Japan
71
I–IV
CS
67.6
HR
Univariate
OS
1.69 (0.81–3.52)
Mrena [24]
2010
Finland
321
I–IV
CS
54.0
HR
Multivariate
OS
1.54 (1.13–2.11)
Li [25]
2010
China
65
NR
CS
66.2
KM
Univariate
OS
2.76 (1.21–6.28)
Zhai [26]
2009
China
104
NR
10
63.5
HR
Multivariate
OS
1.92 (1.18–3.13)
Yamac [27]
2008
Turkey
65
I–IV
CS
49.0
KM
Univariate
OS
0.84 (0.48–1.45)
KM
Univariate
DFS
0.81 (0.52–1.36)
Ye [28]
2008
China
60
I–IV
10
63.3
Available data
Univariate
OS
3.95 (1.51–10.29)
Lazar [29]
2008
Romania
61
0–IV
CS
57.4
KM
Univariate
OS
1.22 (0.84–1.78)
Kolev [30]
2008
Japan
152
I–IV
CS
38.2
HR
Multivariate
OS
0.99 (0.54–1.82)
DFS
0.86 (0.44–1.71)
Da [31]
2008
China
68
I–IV
CS
67.7
HR
Multivariate
OS
1.04 (0.40–2.68)
Gudis [32] Li [33]
2007 2006
Japan China
129 89
I–IV NR
NR 30
56.6 61.8
HR KM
Multivariate Univariate
OS OS
0.70 (0.32–1.53) 1.64 (1.23–2.61)
Joo [34]
2006
Korea
119
I–IV
CS
60.5
KM
Univariate
OS
0.95 (0.61–1.49)
Linder [35]
2005
Finland
258
I–IV
CS
59.7
HR
Multivariate
DFS
1.54 (1.14–2.09)
Yu [36]
2005
China
195
I–IV
10
58.0
KM
Univariate
OS
1.14 (0.72–1.80)
Okano [37]
2004
Japan
166
NR
30
54.8
HR
Multivariate
OS
2.05 (1.15–3.66)
Shi [38]
2003
China
232
NR
0
18.1
HR
Multivariate
OS
2.17 (1.49–3.18)
Joo [39]
2002
Korea
140
I–IV
CS
61.4
KM
Univariate
OS
0.96 (0.60–1.50)
Leung [40]
2001
China
49
NR
10
48.7
KM
Univariate
OS
1.29 (0.70–2.36)
Lee [41]
2001
China
109
I–IV
50
64.2
KM
Univariate
OS
1.20 (0.80–1.79)
Chen [42]
2001
China
71
I–IV
0
68.0
Available data
Univariate
OS
2.71 (1.20–6.28)
Lim [43]
2000
Korea
104
I–IV
CS
70.2
KM
Univariate
OS
0.92 (0.47–1.79)
KM
Univariate
DFS
0.91 (0.68–1.82)
NR not reported, CS complex score combining intensity and percentage of COX-2 expression, KM Kaplan–Meier curves, OS overall survival; disease-free survival
combined HR of studies reporting HRs based on multivariate analysis was 1.72 (95 % CI 1.38–2.14; Fig. 3), indicating that COX-2 overexpression was an independent prognostic factor for patients with gastric cancer. When grouped by country, the combined HRs of Asian and nonAsian studies were 1.62 (95 % CI 1.37–1.92) and 1.35 (95 % CI 1.09–1.68), respectively. However, there was no significant relationship between COX-2 overexpression and DFS (HR 1.15, 95 % CI 0.93–1.43; Fig. 4) of patients with gastric cancer. No significant heterogeneity was observed (I2 = 58.2 %, p = 0.066).
Publication Bias Test and Sensitivity Analysis Publication bias was assessed by use of Egger’s regression test and Begg’s funnel plot. Begg’s funnel plot for both OS and DFS revealed no obvious bias (Figs. 5, 6). Further confirmation by use of Egger’s regression test also failed to find evidence of publication bias in OS (t = 0.04, p = 0.965) and DFS (t = -2.70, p = 0.114). To evaluate the stability of this meta-analysis, a sensitivity analysis, which removed one study at a time, was performed. The results suggested that our results were robust.
123
440
Dig Dis Sci (2014) 59:436–445
Table 3 Main results of this meta-analysis Number of studies
HR (95 % CI)
Heterogeneity x2
I2
p
Overall survival (OS) All
26
1.58 (1.36–1.84)
60.44
58.6
0.000
Univariate analysis Multivariate analysis
16
1.51 (1.22–1.86)
39.94
62.4
0.000
10
1.72 (1.38–2.14)
18.35
51.0
0.031
Country Asian
22
1.62 (1.37–1.92)
50.65
58.5
0.000
Non-Asian
4
1.35 (1.09–1.68)
7.21
58.4
0.065
Disease-free survival (DFS)
4
1.15 (0.93–1.43)
7.18
58.2
0.066
Discussion Gastric cancer is a major public health problem that seriously affects human health. Despite much progress in recent years, five year survival is still low for gastric cancer patients [2]. Meta-analysis has proved that positive COX-2 expression is significantly related to an unfavorable prognosis for lung, colorectal, cervical, ovarian, pancreatic, and esophageal squamous cell carcinoma [11–13, 58–60].
Fig. 1 Forest plot showing the combined HR for OS for all included studies
However, there was no consensus on COX-2 expression and prognosis for patients with gastric cancer. As far as we are aware, this is the first meta-analysis to clarify this controversial issue. In this meta-analysis, we combined 27 published studies to yield summary statistics which indicated COX-2 expression is significantly associated with unfavorable OS for patients with gastric cancer. COX, also known as prostaglandin H synthase, is the crucial enzyme in the biosynthesis of prostaglandin. It has at least two isozymes: COX-1 and COX-2 [7]. Under normal physiological conditions, COX-2 is undetectable in most organisms. COX-2 can be synthesized only when cells receive appropriate stimulation, for example cytokines, endotoxin, tumor-promoting agents, and oncogene [6]. Tumor angiogenesis is the basis of tumor growth. VEGF, a poor prognostic factor in gastric cancer, is of crucial importance in tumor angiogenesis [61]. Many studies have indicated that COX-2 and VEGF expression are positively correlated [5, 15, 29, 46, 57]. It has also been reported that microvessel density is significantly greater in patients with COX-2 overexpression [50, 62]. COX-2 overexpression may affect prognosis in gastric cancer by promoting tumor angiogenesis. COX-2 expression can also increase the level of expression of inhibitor of apoptosis gene bcl-2, and reduce the level of transforming growth factor-B2 receptor, which is involved in regulation of programmed cell death,
Study ID
HR (95% CI)
% Weight
Zhang[17] (2013) Jiang[18] (2012) Fanelli[19] (2012) Gou[20] (2011) Zhang[21] (2011) Sun[22] (2011) Mrena[23] (2010) Li[24] (2010) Tatsuwaki[25] (2010) Zhai[26] (2009) Yamac[27] (2008) Lazar[28] (2008) Da[29] (2008) Ye[30] (2008) Kolev[31] (2008) Gudis[32] (2007) Li[33] (2006) Joo[34] (2006) Yu[36] (2005) Okano[37] (2004) Shi[38] (2003) Joo[39] (2002) Chen[40] (2001) Leung[41] (2001) Lee[42] (2001) Lim[43] (2000) Overall (I-squared = 58.6%, p = 0.000)
1.65 (1.34, 2.03) 2.28 (1.72, 3.51) 3.34 (1.43, 9.75) 3.24 (1.20, 3.83) 2.97 (1.51, 5.84) 2.16 (1.48, 2.86) 1.54 (1.13, 2.11) 2.76 (1.21, 6.28) 1.69 (0.81, 3.52) 1.92 (1.18, 3.13) 0.84 (0.48, 1.45) 1.22 (0.84, 1.78) 1.04 (0.40, 2.68) 3.90 (1.51, 10.29) 0.99 (0.54, 1.82) 0.70 (0.32, 1.53) 1.64 (1.03, 2.61) 0.95 (0.61, 1.49) 1.14 (0.72, 1.80) 2.05 (1.15, 3.66) 2.17 (1.49, 3.18) 0.96 (0.60, 1.50) 2.71 (1.20, 6.28) 1.29 (0.70, 2.36) 1.20 (0.80, 1.79) 0.92 (0.47, 1.79) 1.58 (1.35, 1.84)
6.57 5.31 1.89 3.59 3.03 5.55 5.70 2.35 2.74 4.24 3.77 5.15 1.91 1.89 3.42 2.52 4.41 4.56 4.47 3.60 5.12 4.47 2.34 3.42 4.92 3.07 100.00
NOTE: Weights are from random effects analysis .0972
123
1
10.3
Dig Dis Sci (2014) 59:436–445
441 %
Study ID
HR (95% CI)
Weight
Jiang[18] (2012)
2.28 (1.72, 3.51)
8.28
Zhang[21] (2011)
2.97 (1.51, 5.84)
5.14
Sun[22] (2011)
2.16 (1.48, 2.86)
8.57
Li[24] (2010)
2.76 (1.21, 6.28)
4.10
Tatsuwaki[25] (2010)
1.69 (0.81, 3.52)
4.70
Yamac[27] (2008)
0.84 (0.48, 1.45)
6.23
Lazar[28] (2008)
1.22 (0.84, 1.78)
8.07
Ye[30] (2008)
3.90 (1.51, 10.29)
3.36
Li[33] (2006)
1.64 (1.03, 2.61)
7.11
Joo[34] (2006)
0.95 (0.61, 1.49)
7.30
Yu[36] (2005)
1.14 (0.72, 1.80)
7.18
Joo[39] (2002)
0.96 (0.60, 1.50)
7.18
Chen[40] (2001)
2.71 (1.20, 6.28)
4.08
Leung[41] (2001)
1.29 (0.70, 2.36)
5.72
Lee[42] (2001)
1.20 (0.80, 1.79)
7.78
Lim[43] (2000)
0.92 (0.47, 1.79)
5.20
Overall (I-squared = 62.4%, p = 0.000)
1.51 (1.22, 1.86)
100.00
NOTE: Weights are from random effects analysis
.0972
1
10.3
Fig. 2 Forest plot showing the combined HR for OS by univariate analysis %
Study ID
HR (95% CI)
Weight
Zhang[17] (2013)
1.65 (1.34, 2.03)
19.08
Fanelli[19] (2012)
3.34 (1.43, 9.75)
4.29
Gou[20] (2011)
3.24 (1.20, 3.83)
8.87
Mrena[23] (2010)
1.54 (1.13, 2.11)
15.73
Zhai[26] (2009)
1.92 (1.18, 3.13)
10.82
Da[29] (2008)
1.04 (0.40, 2.68)
4.36
Kolev[31] (2008)
0.99 (0.54, 1.82)
8.37
Gudis[32] (2007)
0.70 (0.32, 1.53)
5.90
Okano[37] (2004)
2.05 (1.15, 3.66)
8.89
Shi[38] (2003)
2.17 (1.49, 3.18)
13.68
Overall (I-squared = 51.0%, p = 0.031)
1.72 (1.38, 2.14)
100.00
NOTE: Weights are from random effects analysis
.103
1
9.75
Fig. 3 Forest plot showing the combined HR for OS by multivariate analysis
thus leading to inhibition of tumor apoptosis [6]. Several studies have shown that COX-2 expression is also positively correlated with matrix metalloproteinase (MMP) expression [56, 63]. MMP can degrade the extracellular matrix of tumor cells, enabling tumor cells to infiltrate and diffuse more
easily [64]. In general, COX-2 may be involved in tumor development mainly via tumor angiogenesis, inhibition of tumor apoptosis, and proliferation of tumor cells. Epidemiological studies have suggested that regular and long-term use of aspirin and other NSAIDs can reduce
123
442
Dig Dis Sci (2014) 59:436–445 Study
%
ID
HR (95% CI)
Weight
Yamac[27] (2008)
0.81 (0.52, 1.36)
20.12
Kolev[30] (2008)
0.86 (0.44, 1.71)
10.09
Linder[35] (2005)
1.54 (1.14, 2.09)
50.61
Lim[43] (2000)
0.91 (0.68, 1.82)
19.18
Overall (I-squared = 58.2%, p = 0.066)
1.15 (0.93, 1.43)
100.00
.44
1
2.27
Fig. 4 Forest plot showing the combined HR for DFS of gastric cancer patients
1.5
log[hr]
1
.5
0
-.5 0
.2
.4
.6
s.e. of: log[hr]
Fig. 5 Begg’s Funnel plot for studies reporting OS
1
log[hr]
.5
0
-.5 0
.2
s.e. of: log[hr]
Fig. 6 Begg’s Funnel plot for studies reporting DFS
123
.4
mortality from several malignancies, including gastric cancer [65, 66]. Further confirmation by meta-analysis also indicated that regular use of aspirin may be associated with reduced risk of noncardia gastric cancer [67]. The main site of action of aspirin and NSAIDs is COX, so it effectively inhibits COX activity. Hence we inferred that COX and prostaglandin may be involved in a series of pathophysiological processes related to the occurrence and development of cancer. Compared with non-selective COX inhibitors, selective COX-2 inhibitors, for example celecoxib, have a distinct advantage in reducing gastrointestinal side effects. Experimental treatment of gastric cancer in mice showed that the combination of celecoxib and indomethacin inhibited cell proliferation by more than 65 % [68]. Epidemiological and animal experiments confirmed that COX-2 inhibitors increase sensitivity to chemotherapeutic drugs in several cancers [69, 70]. Attention should be drawn to some of the articles included in this meta-analysis. In the study by Mrena et al. [24], COX-2 expression was found to be a prognostic factor for diploid, but not aneuploid, tumors. It has been reported that the possibility of metastasis tends to be high for aneuploid tumors, resulting in poor prognosis for gastric cancer patients [71]. COX-2 expression may reveal aggressive potential before the occurrence of major chromosomal changes. Li et al. [25] evaluated COX-2 expression in primary gastric tumors (PT) and lymph node metastases (LNMs). COX-2 expression was proved to be associated with poor prognosis for LNMs but not PT. This difference may be indicative of heterogeneity in the significance of molecule expression in PT and LNMs. It would be extremely valuable to investigate the prognostic significance of COX-2 expression in LNMs with well-designed studies.
Dig Dis Sci (2014) 59:436–445
This meta-analysis has several limitations. All the included studies measured COX-2 expression by IHC. Many factors, for example primary antibody and antibody concentration, may affect the results. However, it was impossible to perform a subgroup analysis to investigate the potential effect of technique on the combined results. There are also large differences between definitions of positive COX-2 expression. Some of the studies used CS whereas others used percentage COX-2 expression only. This also may be a limitation. Formulation of a unified COX-2 positive standard is urgently required. Treatment of the patients among the studies was not identical, which may affect survival time among the studies. However, most of the studies did not give information about treatment of the gastric cancer patients. Other characteristics of the patients, for example gender, age, tumor size, and TNM, may lead to heterogeneous results. But, because of lack of sufficient information, an attempt to perform subgroup analysis failed. All these sources of variability may cause bias. Publication bias may overvalue the combined HR. In general, a study with a positive result is easy to accept whereas a study with a negative result is often rejected. The studies in this meta-analysis are restricted to articles written in English and Chinese, which may also lead to bias. Among the studies reporting a correlation between COX-2 expression and survival of patients with gastric cancer, six were excluded because of insufficient data. This may be another potential factor which causes bias. Furthermore, the method used to estimate HR and 95 % CI for articles which did not report HR directly, which is based the published articles [44, 45], may be another potential source of bias. The strategy, which did not completely eliminate inaccuracy in extracted survival data and the estimated HR, seems to be less reliable than values obtained directly from published articles. We did, however, study the survival curves published by two of the authors and compared the HR and 95 % CI with the published results, to confirm the accuracy of estimated HR. In conclusion, published data suggest that high COX-2 expression may be an independent prognostic factor for patients with gastric cancer. The findings may also suggest that COX-2 inhibition could improve survival in gastric cancer. However, large prospective studies are needed to establish the clinical value of COX-2 inhibitors in prevention and/or treatment of gastric cancer. Conflict of interest
None.
References 1. Ferlay J, Shin HR, Bray F, et al. Estimates of worldwide burden of cancer in 2008: Globocan 2008. Int J Cancer. 2010;127: 2893–2917.
443 2. Herszenyi L, Tulassay Z. Epidemiology of gastrointestinal and liver tumors. Eur Rev Med Pharmacol Sci. 2010;14:249–258. 3. Xing X, Tang YB, Yuan G, et al. The prognostic value of E-cadherin in gastric cancer: a meta-analysis. Int J Cancer. 2013;132:2589–2596. 4. Zhang QW, Liu L, Chen R, et al. Matrix metalloproteinase-9 as a prognostic factor in gastric cancer: a meta-analysis. Asian Pac J Cancer Prev. 2012;13:2903–2908. 5. Peng L, Zhan P, Zhou Y, et al. Prognostic significance of vascular endothelial growth factor immunohistochemical expression in gastric cancer: a meta-analysis. Mol Biol Rep. 2012;39: 9473–9484. 6. Thiel A, Mrena J, Ristima¨ki A. Cyclooxygenase-2 and gastric cancer. Cancer Metastasis Rev. 2011;30:387–395. 7. Wu WK, Sung JJ, Lee CW, et al. Cyclooxygenase-2 in tumorigenesis of gastrointestinal cancers: an update on the molecular mechanisms. Cancer Lett. 2010;295:7–16. 8. Fujimura T, Ohta T, Oyama K, et al. Role of cyclooxygenase-2 in the carcinogenesis of gastrointestinal tract cancers: a review and report of personal experience. World J Gastroenterol. 2006;12: 1336–1345. 9. Oshima H, Oshima M, Inaba K, et al. Hyperplastic gastric tumors induced by activated macrophages in COX-2/mPGES-1 transgenic mice. EMBO J. 2004;23:1669–1678. 10. Thiel A, Narko K, Heinonen M, et al. Inhibition of cyclooxygenase-2 causes regression of gastric adenomas in trefoil factor 1 deficient mice. Int J Cancer. 2012;131:1032–1041. 11. Jiang H, Wang J, Zhao W. Cox-2 in non-small cell lung cancer: a meta-analysis. Clin Chim Acta. 2013;419:26–32. 12. Lee JY, Myung SK, Song YS. Prognostic role of cyclooxygenase2 in epithelial ovarian cancer: a meta-analysis of observational studies. Gynecol Oncol. 2013;129:613–619. 13. Huang M, Chen Q, Xiao J, et al. Prognostic significance of cyclooxygenase-2 in cervical cancer: a meta-analysis. Int J Cancer. 2013;132:363–373. 14. Almeida PR, Ferreira FV, Santos CC, et al. Immunoexpression of cyclooxygenase-2 in primary gastric carcinomas and lymph node metastases. World J Gastroenterol. 2012;18:778–784. 15. Joo YE, Rew JS, Seo YH, et al. Cyclooxygenase-2 overexpression correlates with vascular endothelial growth factor expression and tumor angiogenesis in gastric cancer. J Clin Gastroenterol. 2003;37:28–33. 16. Tang H, Wang J, Bai F, et al. Positive correlation of osteopontin, cyclooxygenase-2 and vascular endothelial growth factor in gastric cancer. Cancer Invest. 2008;26:60–67. 17. Zhang X, Wu Q, Gan L, et al. Reduced group IVA phospholipase A2 expression is associated with unfavorable outcome for patients with gastric cancer. Med Oncol. 2013;30:454. 18. Jiang H, Qiao XL, Huang FY. Expressions and clinical significance of Smad4 and Cox-2 in gastric cancer. J Clin Med Pract. 2012;16:30–33. 19. Fanelli MF, Chinen LT, Begnami MD, et al. The influence of transforming growth factor-a, cyclooxygenase-2, matrix metalloproteinase (MMP)-7, MMP-9 and CXCR4 proteins involved in epithelial–mesenchymal transition on overall survival of patients with gastric cancer. Histopathology. 2012;61: 153–161. 20. Gou HF, Chen XC, Zhu J, et al. Expressions of COX-2 and VEGF-C in gastric cancer: correlations with lymphangiogenesis and prognostic implications. J Exp Clin Cancer Res. 2011;30:14. 21. Zhang C, Wang XQ, Xu C, et al. Expression of cyr-61 and cox-2 in gastric carcinoma and its clinical significance. J China Med Univ. 2011;40:744–748. 22. Sun GY, Luo DH, Wu JS, et al. The expression of NICD and COX-2 in gastric carcinoma tissues and its clinical biological significance. J Med Res. 2011;40:61–66.
123
444 23. Tatsuwaki H, Tanigawa T, Watanabe T, et al. Reduction of 15-hydroxyprostaglandin dehydrogenase expression is an independent predictor of poor survival associated with enhanced cell proliferation in gastric adenocarcinoma. Cancer Sci. 2010;101: 550–558. 24. Mrena J, Wiksten JP, Kokkola A, et al. COX-2 is associated with proliferation and apoptosis markers and serves as an independent prognostic factor in gastric cancer. Tumour Biol. 2010;31:1–7. 25. Li Y, Tan BB, Fan LQ, et al. Expression of COX-2, survivin in regional lymph node metastases of gastric carcinoma and the correlation with prognosis. Hepatogastroenterology. 2010;57:1435–1441. 26. Zhai JH, Li N, Zhang L, et al. Expression of P16, C-MYC and COX-2 in gastric carcinoma and relationship with the prognosis of patients. J Zhejiang Coll Tradit Chin Med. 2009;33:321–322. 27. Yamac D, Ayyildiz T, Coskun U, et al. Cyclooxygenase-2 expression and its association with angiogenesis, Helicobacter pylori, and clinicopathologic characteristics of gastric carcinoma. Pathol Res Pract. 2008;204:527–536. 28. Ye SC, Wang JY, Yuan GZ, et al. Expression of COX-2 and P-gp and its prognosis in gastric carcinoma. Chin Gen Pract. 2008;11:291–294. 29. Lazar D, Taban S, Ardeleanu C, et al. Immunohistochemical expression of the cyclooxygenase-2 (COX-2) in gastric cancer. The correlations with the tumor angiogenesis and patients’ survival. Rom J Morphol Embryol. 2008;49:371–379. 30. Kolev Y, Uetake H, Takagi Y, et al. Lactate dehydrogenase-5 (LDH-5) expression in human gastric cancer: association with hypoxia-inducible factor (HIF-1alpha) pathway, angiogenic factors production and poor prognosis. Ann Surg Oncol. 2008;15:2336–2344. 31. Da MX, Wu XT, Wang J, et al. Expression of cyclooxygenase-2 and vascular endothelial growth factor-C correlates with lymphangiogenesis and lymphatic invasion in human gastric cancer. Arch Med Res. 2008;39:92–99. 32. Gudis K, Tatsuguchi A, Wada K, et al. Clinical significance of prostaglandin E synthase expression in gastric cancer tissue. Hum Pathol. 2007;38:1826–1835. 33. Li M, Liu W, Zhu YF, et al. Correlation of COX-2 and K-ras expression to clinical outcome in gastric cancer. Acta Oncol. 2006;45:1115–1119. 34. Joo YE, Chung IJ, Park YK, et al. Expression of cyclooxygenase2, p53 and Ki-67 in gastric cancer. J Korean Med Sci. 2006;21:871–876. 35. Linder N, Haglund C, Lundin M, et al. Decreased xanthine oxidoreductase is a predictor of poor prognosis in early-stage gastric cancer. J Clin Pathol. 2006;59:965–971. 36. Yu JR, Wu YJ, Qin Q, et al. Expression of cyclooxygenase-2 in gastric cancer and its relation to liver metastasis and long-term prognosis. World J Gastroenterol. 2005;11:4908–4911. 37. Okano H, Shinohara H, Miyamoto A, et al. Concomitant overexpression of cyclooxygenase-2 in HER-2-positive on Smad4reduced human gastric carcinomas is associated with a poor patient outcome. Clin Cancer Res. 2004;10:6938–6945. 38. Shi H, Xu JM, Hu NZ, et al. Prognostic significance of expression of cyclooxygenase-2 and vascular endothelial growth factor in human gastric carcinoma. World J Gastroenterol. 2003;9: 1421–1426. 39. Joo YE, Oh WT, Rew JS, et al. Cyclooxygenase-2 expression is associated with well-differentiated and intestinal-type pathways in gastric carcinogenesis. Digestion. 2002;66:222–229. 40. Leung WK, To KF, Ng YP, et al. Association between cyclooxygenase-2 overexpression and missense p53 mutations in gastric cancer. Br J Cancer. 2001;84:335–339. 41. Lee TL, Leung WK, Lau JY, et al. Inverse association between cyclooxygenase-2 overexpression and microsatellite instability in gastric cancer. Cancer Lett. 2001;168:133–140.
123
Dig Dis Sci (2014) 59:436–445 42. Chen CN, Sung CT, Lin MT, et al. Clinicopathologic association of cyclooxygenase 1 and cyclooxygenase 2 expression in gastric adenocarcinoma. Ann Surg. 2001;233:183–188. 43. Lim HY, Joo HJ, Choi JH, et al. Increased expression of cyclooxygenase-2 protein in human gastric carcinoma. Clin Cancer Res. 2000;6:519–525. 44. Nordmann AJ, Kasenda B, Briel M. Meta-analyses: what they can and cannot do. Swiss Med Wkly. 2012;142:w13518. 45. McShane LM, Altman DG, Sauerbrei W. Reporting recommendations for tumor marker prognostic studies (remark). Exp Oncol. 2006;28:99–105. 46. Chen M, Cai E, Huang J, et al. Prognostic value of vascular endothelial growth factor expression in patients with esophageal cancer: a systematic review and meta-analysis. Cancer Epidemiol Biomarkers Prev. 2012;21:1126–1134. 47. Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007;7:8–16. 48. Parmar MK, Torri V, Stewart L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med. 1998;17:2815–2834. 49. Egger M, Smith GD, Schneider M, Minder C. Bias in metaanalysis detected by a simple, graphical test. BMJ. 1997;315: 629–634. 50. Zhao HC, Qin R, Chen XX, et al. Microvessel density is a prognostic marker of human gastric cancer. World J Gastroenterol. 2006;12:7598–7603. 51. Han SL, Tang HJ, Hua YW, et al. Expression of COX-2 in stomach cancers and its relation to their biological features. Dig Surg. 2003;20:107–114. 52. Al-Moundhri MS, Al-Hadabi I, Al-Mawaly K, et al. Prognostic significance of cyclooxygenase-2, epidermal growth factor receptor 1, and microvascular density in gastric cancer. Med Oncol. 2012;29:1739–1747. 53. Dicken BJ, Graham K, Hamilton SM, et al. Lymphovascular invasion is associated with poor survival in gastric cancer: an application of gene-expression and tissue array techniques. Ann Surg. 2006;243:64–73. 54. Vidal O, Soriano-Izquierdo A, Pera M, et al. Positive VEGF immunostaining independently predicts poor prognosis in curatively resected gastric cancer patients: results of a study assessing a panel of angiogenic markers. J Gastrointest Surg. 2008;12: 1005–1014. 55. Mrena J, Wiksten JP, Thiel A, et al. Cyclooxygenase-2 is an independent prognostic factor in gastric cancer and its expression is regulated by the messenger RNA stability factor HuR. Clin Cancer Res. 2005;11:7362–7368. 56. Mrena J, Wiksten JP, Nordling S, et al. MMP-2 but not MMP-9 associated with COX-2 and survival in gastric cancer. J Clin Pathol. 2006;59:618–623. 57. Kolev Y, Uetake H, Iida S, et al. Prognostic significance of VEGF expression in correlation with COX-2, microvessel density, and clinicopathological characteristics in human gastric carcinoma. Ann Surg Oncol. 2007;14:2738–2747. 58. Jamieson NB, Carter CR, McKay CJ, et al. Tissue biomarkers for prognosis in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis. Clin Cancer Res. 2011;17:3316–3331. 59. Li L, Zhao J, Wu Z, et al. Meta-analysis: clinicopathological and prognostic significance of cyclooxygenase-2 expression on oesophageal squamous cell carcinoma. Aliment Pharmacol Ther. 2009;30:589–596. 60. Peng L, Zhou Y, Wang Y, et al. Prognostic significance of COX2 immunohistochemical expression in colorectal cancer: a metaanalysis of the literature. PLoS ONE. 2013;8:e58891. 61. Claesson-Welsh L, Welsh M. VEGFA and tumour angiogenesis. J Intern Med. 2013;273:114–127.
Dig Dis Sci (2014) 59:436–445 62. Tatsuguchi A, Matsui K, Shinji Y, et al. Cyclooxygenase-2 expression correlates with angiogenesis and apoptosis in gastric cancer tissue. Hum Pathol. 2004;35:488–495. 63. Sun WH, Sun YL, Fang RN, et al. Expression of cyclooxygenase2 and matrix metalloproteinase-9 in gastric carcinoma and its correlation with angiogenesis. Jpn J Clin Oncol. 2005;35: 707–713. 64. Lukaszewicz-Zaja˛c M, Mroczko B, Szmitkowski M. Gastric cancer—the role of matrix metalloproteinases in tumor progression. Clin Chim Acta. 2011;412:1725–1730. 65. Gamba CA, Swetter SM, Stefanick ML, et al. Aspirin is associated with lower melanoma risk among postmenopausal Caucasian women: the women’s health initiative. Cancer. 2013;119:1562–1569. 66. Gammon MD, Terry MB, Arber N, et al. Nonsteroidal antiinflammatory drug use associated with reduced incidence of adenocarcinomas of the esophagus and gastric cardia that overexpress cyclin D1: a population-based study. Cancer Epidemiol Biomarkers Prev. 2004;13:34–39.
445 67. Yang P, Zhou Y, Chen B, et al. Aspirin use and the risk of gastric cancer: a meta-analysis. Dig Dis Sci. 2010;55:1533–1539. 68. Yu J, Tang BD, Leung WK, et al. Different cell kinetic changes in rat stomach cancer after treatment with celecoxib or indomethacin: implications on chemoprevention. World J Gastroenterol. 2005;11:41–45. 69. Liu H, Huang P, Xu X, et al. Anticancer effect of celecoxibvia COX-2 dependent and independent mechanisms in human gastric cancers cells. Dig Dis Sci. 2009;54:1418–1424. 70. Keller JJ, Giardiello FM. Chemoprevention strategies using NSAIDs and COX-2 inhibitors. Cancer Biol Ther. 2003;2:140–149. 71. Russo A, Bazan V, Migliavacca M, et al. Prognostic significance of DNA ploidy, S-phase fraction, and tissue levels of aspartic, cysteine, and serine proteases in operable gastric carcinoma. Clin Cancer Res. 2000;6:178–184.
123
ORIGINAL ARTICLE
Cyclooxygenase-2 Expression Is Associated with Poor Overall Survival of Patients with Gastric Cancer: A Meta-Analysis Jian Song • Hong Su • Yang-yang Zhou Liang-liang Guo
•
Received: 27 May 2013 / Accepted: 7 October 2013 / Published online: 1 November 2013 Ó Springer Science+Business Media New York 2013
Abstract Background Cyclooxygenase-2 (COX-2) is believed to be involved in gastric carcinogenesis. However, it is still controversial whether COX-2 expression can be regarded as a prognostic factor for gastric cancer patients. Aim To obtain a more accurate relationship between COX-2 overexpression and prognosis in gastric cancer by meta-analysis. Method Relevant articles published up to May 2013 were searched by use of several keywords in electronic databases. Separate hazard ratio (HR) estimates and 95 % confidence intervals (95 % CI) for COX-2 overexpression and overall survival (OS) and disease-free survival (DFS) with gastric cancer were extracted. Combined HR with 95 % CI was calculated by use of Stata11.0 software to estimate the size of the effect. Publication bias testing and sensitivity analysis were also performed. Results A total of 27 studies which included 3,891 gastric cancer patients were combined in the final analysis. Combined results suggested that COX-2 overexpression was associated with an unfavorable OS (HR 1.58, 95 % CI 1.36–1.84) but not DFS (HR 1.15, 95 % CI 0.93–1.43) among patients with gastric cancer. Publication bias was absent. Sensitivity analysis suggested that the results of this meta-analysis were robust. Conclusions The results of this meta-analysis suggest that high COX-2 expression may be an independent risk factor for poor OS of patients with gastric cancer. More large prospective studies are now needed to further clarify the
J. Song H. Su (&) Y. Zhou L. Guo Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 69 Meishan Road, Hefei 230032, Anhui Province, China e-mail: [email protected]
123
prognostic value of COX-2 expression for DFS in gastric cancer. Keywords Gastric cancer Cyclooxygenase-2 (COX-2) Overall survival (OS) Disease-free survival (DFS) Meta-analysis
Introduction Gastric cancer is one of the main malignant tumors, and incidence and mortality have both increased in recent years [1]. Despite continuous improvements in its treatment, survival of gastric cancer patients has not been substantially improved [2]. It is, therefore, very important to identify prognostic factors for gastric cancer which can help us find a better treatment and preventive measures for extending the life of gastric cancer patients. Traditional clinicopathological characteristics, for example tumor size and stage, do not fully predict individual clinical outcome, and much better prognostic factors are needed. The molecular biomarkers involved in tumor development may provide information about the clinical manifestation of the disease and should be considered as potential prognostic factors. Several molecular markers, for example E-cadherin, matrix metalloproteinase-9, and vascular endothelial growth factor (VEGF), have been proved to be associated with prognosis for gastric cancer patients [3–5]. Among biomarkers, COX-2 expression has recently attracted increasing research attention. COX-2, an important rate-limiting enzyme in prostaglandin synthesis, is closely related to tumor development [6]. It has been confirmed that COX-2 affects tumor progression mainly by inhibiting tumor apoptosis, and promoting tumor angiogenesis, tumor invasiveness, and
Dig Dis Sci (2014) 59:436–445
proliferation of tumor cells [7, 8]. The COX-2 pathway has been proved to contribute to gastric tumorigenesis in a transgenic mouse model [9]. Inhibition of COX-2 has also been associated with regression of gastric adenomas in mice [10]. Overexpression of COX-2 has been demonstrated in a variety of malignancies, for example lung, ovarian, and cervical, and is usually associated with an unfavorable survival results [11–13]. Previous studies have found that COX-2 overexpression was associated with several clinicopathological data, for example advance stage, tumor size, and lymph node metastasis, in gastric cancer [14–16]. Several studies have described the relationship between COX-2 expression and prognosis in gastric cancer [17–43]. However, the results were inconsistent. Some researchers found that COX-2 overexpression predicted poor survival [17–22, 24–26, 28, 33, 35, 37, 38, 42] whereas others did not agree [23, 27, 29–32, 34, 36, 39–41, 43]. Meta-analysis is a popular and powerful tool which overcomes the limitation of small sample sizes by combining results from several individual studies to generate a best assessment [44]. We therefore conducted a meta-analysis of published articles to obtain a quantitative estimate of the prognostic significance of COX-2 expression in gastric cancer.
437
Two authors (Song and Zhou) performed the search and identification independently. Data Extraction Two authors (Song and Guo) independently extracted year of publication, name of the first author, country, number of patients, years of follow up, TNM stage, patients characteristics, experimental method, cut off value, percentage of COX-2 positive expression, analytical method, HR, and 95 % CI from the included articles. If any of the above information were not reported in the study, items were treated as ‘‘NR (not reported).’’ Quality Assessment We conducted a quality assessment for each eligible study by using reporting recommendations for tumor marker prognostic studies (REMARK) [45]. Eighteen items were extracted from REMARK (Table 1), which have been used in previous meta-analysis [46]. Each item scored 1 if the study met the demands, otherwise 0 score was given to the study. The final score ranged from 0 to 18 for each study, with higher scores indicating better methodology. Statistical Analysis
Methods Search Strategy and Study Selection Relevant articles studying the relationship between COX-2 expression and survival of gastric cancer patients published up to May, 2013, were retrieved by online search in PubMed and China National Knowledge Infrastructure. We used the keywords: (‘‘cyclooxygenase-2’’ or ‘‘COX-2’’) and (‘‘gastric cancer’’ or ‘‘gastric neoplasms’’ or ‘‘gastric carcinoma’’ or ‘‘stomach cancer’’ or ‘‘stomach neoplasms’’ or ‘‘stomach carcinoma’’) and (‘‘prognostic’’ or ‘‘prognosis’’ or ‘‘survival’’ or ‘‘survive’’). All included studies were required to be written in English or Chinese. References of the original studies were also checked, to ensure all eligible studies could be included. Literature inclusion criteria were: 1 it investigated the association between COX-2 overexpression and overall survival (OS) and/or diseasefree survival (DFS) in gastric cancer patients who underwent surgical resection; 2 it measured COX-2 protein expression in primary gastric cancer tissue by immunohistochemistry (IHC); 3 the value of HR and 95 % CI could be obtained or calculated on the basis of the information given in articles; and 4 for duplicate articles, the newest or most informative was selected.
In this meta-analysis, HR and 95 % CI were used to calculate the overall effect estimate. Some of the studies included provided HR and 95 % CI explicitly. For some studies which did not provide HR and 95 % CI, we calculated the values from the available data or the Kaplan– Meier survive curve in the original studies by using the methods illustrated by Tierney et al. [47] and Parmar et al. [48]. Available data refers to the total number of events, the log-rank statistic and its p value, or the O-E statistic (difference between numbers of observed and expected events). We read the Kaplan–Meier curves by using Engauge Digitizer version 2.11 (free software downloaded from http://sourceforge.net). Heterogeneity was assessed by use of the v2 test and the Q test. When heterogeneity was significant, we used a random-effect model. Otherwise, we used a fixed-effect model. Publication bias was evaluated by use of Begg’s funnel plot and Egger’s linear regression test [49]. The stability of the results was checked by sensitivity analysis. Subgroup analysis was performed by use of different analytical methods (univariate or multivariate) and on the basis of areas (Asian or non-Asian). A pooled HR [1 suggested that positive COX-2 expression predicted an unfavorable prognosis for gastric cancer patients. It was regarded as statistically significant if the 95 % CI of HR did not overlap 1. All the p values were two-sided, p \ 0.05 was regarded as statistically
123
438 Table 1 Definitions of 18 items used to assess study quality 1. Objectives or prespecified hypothesis: state the study objectives, prespecified hypothesis, or study protocol 2. Sample size: state a statistical sample size or power calculation 3. Follow-up description: state the follow-up period or the median follow-up time 4. Population source: state health-care setting from which patients were recruited 5. Population selection criteria: state inclusion or exclusion 6. Population characteristics: state the population characteristics (e.g., age, gender, and disease stage) 7. Number of patients included in each stage of the analysis and reason for drop out: description of number of patients at different stages, including the number of patients who participated in the study, who met the inclusion criteria, and who were followed up, and reason for dropout Assay method 1. Sample handling: state the method of storage 2. Assay method: state the type of assay method used to measure COX-2 3. Manufacturer: state the name of the company which makes the assay for COX-2 4. Cutoff point determination: state methods used for cutoff point determination Confounders 1. Conventional risk factors: state the conventional risk factors (e.g., age, gender, depth of tumor, lymph node metastasis) 2. Other biomarkers (e.g., p53 and microvessel density): state other biologicmarker relating with the disease Outcome 1. Clinical endpoint: define the clinical endpoint 2. Validation: state the outcome events checked by independent source (e.g.,medical records, outpatient visits, by letter, and by telephone) Analysis 1. Univariate estimate: report the effect of COX-2 on outcome 2. Multivariate estimate: adjusted for risk factors or other biomarkers 3. Missing value: state the number of patients with missing value for survival or confounders and how to deal with it
significant. All statistical calculations were performed by use of Stata 11.0.
Results Literature Selection and Study Characteristics Initially, three independent authors (Song, Zhou, and Guo) reviewed the titles and abstracts of the identified studies and excluded irrelevant papers. Full texts of the remaining 37 studies were reviewed to check whether they met the inclusion criteria. Among these, six papers [15, 16, 50–53] contained insufficient data to extract HR and 95 % CI. One
123
Dig Dis Sci (2014) 59:436–445
study estimated the effect of COX-2 overexpression on relapse-free survival in gastric cancer [54]. Moreover, three studies [55–57] were excluded because identical cohorts of patients were used in other selected studies. Twenty-seven papers [17–43] were included in the final analysis. All the main characteristics of the included studies are summarized in Table 2. Among the studies included, 26 papers reported OS results, and only four provided DFS results. The total number of patients was 3,891, ranging from 49 to 830 per study. Most of the studies were conducted on Asian populations [17, 18, 20–23, 25, 26, 28, 30– 34, 36–43]; only five studies were conducted on non-Asian populations [19, 24, 27, 29, 35]. Some of the studies defined the cut off value by use of complex score (CS) combining intensity and percentage of COX-2 expression [17, 19, 20, 23–25, 27, 29–31, 34, 35, 39, 43] whereas the others only used the percentage of COX-2 expression [18, 21, 22, 26, 28, 33, 36–38, 40–42]. One study [32] did not report the definition of COX-2 overexpression. The percent of COX-2 overexpression ranged from 13.9 to 71.6 %. The HR and 95 % CI were directly extracted from 13 original studies [17–20, 23, 24, 26, 30–32, 35, 37, 38]. We obtained the value from the available data for two studies [28, 42], and read the useful data from the Kaplan–Meier curves in the remaining 12 studies [21, 22, 25, 27, 29, 33, 34, 36, 39– 41, 43]. Overall, 11 studies calculated HR and 95 % CI by multivariate analysis [17, 19, 20, 24, 26, 30–32, 35, 37, 38]; the other 16 studies used univariate analysis [18, 21– 23, 25, 27–29, 33, 34, 36, 39–43]. Quality Assessment The final score for all the included studies ranged from 11 to 16; the mean score was 13.4. There was no statistical significance (p = 0.553) between the studies that reported univariate analysis (mean score = 13.6) and studies which reported multivariate analysis (mean score = 13.1). We also failed to find a significant difference between Asian and non-Asian studies (p = 0.999). Main Results The main results of this meta-analysis are shown in Table 3. The combined HR of all studies reporting the effect of COX-2 expression on OS was 1.58 (95 % CI 1.36–1.84), suggesting that COX-2 overexpression was associated with a poor OS in gastric cancer (Fig. 1). There was significant heterogeneity among the studies (I2 = 58.6 %, p \ 0.05). When HRs calculated by univariate analysis were combined, a statistically significant association between COX-2 overexpression and OS of gastric cancer patients was observed (HR 1.51, 95 % CI 1.22–1.86; Fig. 2). The
Dig Dis Sci (2014) 59:436–445
439
Table 2 Main characteristics of included studies First author
Year
Country
No.
TNM
Cut-off
Positive expression (%)
HR estimate
Analytic method
Result
HR (95 % CI)
Zhang [17]
2013
China
830
I–IV
CS
54.0
HR
Multivariate
OS
1.65 (1.34–2.03)
Jiang [18]
2012
China
49
I–IV
10
65.3
KM
Univariate
OS
2.28 (1.72–3.51)
Fanelli [19] Gou [20]
2012 2011
Brazil China
137 56
I–IV I–IV
CS CS
13.9 69.6
HR HR
Multivariate Multivariate
OS OS
3.34 (1.43–9.75) 3.24 (1.20–3.83)
Zhang [21]
2011
China
82
I–IV
5
62.2
KM
Univariate
OS
2.97 (1.51–5.84)
Sun [22]
2011
China
109
I–IV
10
71.6
KM
Univariate
OS
2.16 (1.48–2.86)
Tatsuwaki [23]
2010
Japan
71
I–IV
CS
67.6
HR
Univariate
OS
1.69 (0.81–3.52)
Mrena [24]
2010
Finland
321
I–IV
CS
54.0
HR
Multivariate
OS
1.54 (1.13–2.11)
Li [25]
2010
China
65
NR
CS
66.2
KM
Univariate
OS
2.76 (1.21–6.28)
Zhai [26]
2009
China
104
NR
10
63.5
HR
Multivariate
OS
1.92 (1.18–3.13)
Yamac [27]
2008
Turkey
65
I–IV
CS
49.0
KM
Univariate
OS
0.84 (0.48–1.45)
KM
Univariate
DFS
0.81 (0.52–1.36)
Ye [28]
2008
China
60
I–IV
10
63.3
Available data
Univariate
OS
3.95 (1.51–10.29)
Lazar [29]
2008
Romania
61
0–IV
CS
57.4
KM
Univariate
OS
1.22 (0.84–1.78)
Kolev [30]
2008
Japan
152
I–IV
CS
38.2
HR
Multivariate
OS
0.99 (0.54–1.82)
DFS
0.86 (0.44–1.71)
Da [31]
2008
China
68
I–IV
CS
67.7
HR
Multivariate
OS
1.04 (0.40–2.68)
Gudis [32] Li [33]
2007 2006
Japan China
129 89
I–IV NR
NR 30
56.6 61.8
HR KM
Multivariate Univariate
OS OS
0.70 (0.32–1.53) 1.64 (1.23–2.61)
Joo [34]
2006
Korea
119
I–IV
CS
60.5
KM
Univariate
OS
0.95 (0.61–1.49)
Linder [35]
2005
Finland
258
I–IV
CS
59.7
HR
Multivariate
DFS
1.54 (1.14–2.09)
Yu [36]
2005
China
195
I–IV
10
58.0
KM
Univariate
OS
1.14 (0.72–1.80)
Okano [37]
2004
Japan
166
NR
30
54.8
HR
Multivariate
OS
2.05 (1.15–3.66)
Shi [38]
2003
China
232
NR
0
18.1
HR
Multivariate
OS
2.17 (1.49–3.18)
Joo [39]
2002
Korea
140
I–IV
CS
61.4
KM
Univariate
OS
0.96 (0.60–1.50)
Leung [40]
2001
China
49
NR
10
48.7
KM
Univariate
OS
1.29 (0.70–2.36)
Lee [41]
2001
China
109
I–IV
50
64.2
KM
Univariate
OS
1.20 (0.80–1.79)
Chen [42]
2001
China
71
I–IV
0
68.0
Available data
Univariate
OS
2.71 (1.20–6.28)
Lim [43]
2000
Korea
104
I–IV
CS
70.2
KM
Univariate
OS
0.92 (0.47–1.79)
KM
Univariate
DFS
0.91 (0.68–1.82)
NR not reported, CS complex score combining intensity and percentage of COX-2 expression, KM Kaplan–Meier curves, OS overall survival; disease-free survival
combined HR of studies reporting HRs based on multivariate analysis was 1.72 (95 % CI 1.38–2.14; Fig. 3), indicating that COX-2 overexpression was an independent prognostic factor for patients with gastric cancer. When grouped by country, the combined HRs of Asian and nonAsian studies were 1.62 (95 % CI 1.37–1.92) and 1.35 (95 % CI 1.09–1.68), respectively. However, there was no significant relationship between COX-2 overexpression and DFS (HR 1.15, 95 % CI 0.93–1.43; Fig. 4) of patients with gastric cancer. No significant heterogeneity was observed (I2 = 58.2 %, p = 0.066).
Publication Bias Test and Sensitivity Analysis Publication bias was assessed by use of Egger’s regression test and Begg’s funnel plot. Begg’s funnel plot for both OS and DFS revealed no obvious bias (Figs. 5, 6). Further confirmation by use of Egger’s regression test also failed to find evidence of publication bias in OS (t = 0.04, p = 0.965) and DFS (t = -2.70, p = 0.114). To evaluate the stability of this meta-analysis, a sensitivity analysis, which removed one study at a time, was performed. The results suggested that our results were robust.
123
440
Dig Dis Sci (2014) 59:436–445
Table 3 Main results of this meta-analysis Number of studies
HR (95 % CI)
Heterogeneity x2
I2
p
Overall survival (OS) All
26
1.58 (1.36–1.84)
60.44
58.6
0.000
Univariate analysis Multivariate analysis
16
1.51 (1.22–1.86)
39.94
62.4
0.000
10
1.72 (1.38–2.14)
18.35
51.0
0.031
Country Asian
22
1.62 (1.37–1.92)
50.65
58.5
0.000
Non-Asian
4
1.35 (1.09–1.68)
7.21
58.4
0.065
Disease-free survival (DFS)
4
1.15 (0.93–1.43)
7.18
58.2
0.066
Discussion Gastric cancer is a major public health problem that seriously affects human health. Despite much progress in recent years, five year survival is still low for gastric cancer patients [2]. Meta-analysis has proved that positive COX-2 expression is significantly related to an unfavorable prognosis for lung, colorectal, cervical, ovarian, pancreatic, and esophageal squamous cell carcinoma [11–13, 58–60].
Fig. 1 Forest plot showing the combined HR for OS for all included studies
However, there was no consensus on COX-2 expression and prognosis for patients with gastric cancer. As far as we are aware, this is the first meta-analysis to clarify this controversial issue. In this meta-analysis, we combined 27 published studies to yield summary statistics which indicated COX-2 expression is significantly associated with unfavorable OS for patients with gastric cancer. COX, also known as prostaglandin H synthase, is the crucial enzyme in the biosynthesis of prostaglandin. It has at least two isozymes: COX-1 and COX-2 [7]. Under normal physiological conditions, COX-2 is undetectable in most organisms. COX-2 can be synthesized only when cells receive appropriate stimulation, for example cytokines, endotoxin, tumor-promoting agents, and oncogene [6]. Tumor angiogenesis is the basis of tumor growth. VEGF, a poor prognostic factor in gastric cancer, is of crucial importance in tumor angiogenesis [61]. Many studies have indicated that COX-2 and VEGF expression are positively correlated [5, 15, 29, 46, 57]. It has also been reported that microvessel density is significantly greater in patients with COX-2 overexpression [50, 62]. COX-2 overexpression may affect prognosis in gastric cancer by promoting tumor angiogenesis. COX-2 expression can also increase the level of expression of inhibitor of apoptosis gene bcl-2, and reduce the level of transforming growth factor-B2 receptor, which is involved in regulation of programmed cell death,
Study ID
HR (95% CI)
% Weight
Zhang[17] (2013) Jiang[18] (2012) Fanelli[19] (2012) Gou[20] (2011) Zhang[21] (2011) Sun[22] (2011) Mrena[23] (2010) Li[24] (2010) Tatsuwaki[25] (2010) Zhai[26] (2009) Yamac[27] (2008) Lazar[28] (2008) Da[29] (2008) Ye[30] (2008) Kolev[31] (2008) Gudis[32] (2007) Li[33] (2006) Joo[34] (2006) Yu[36] (2005) Okano[37] (2004) Shi[38] (2003) Joo[39] (2002) Chen[40] (2001) Leung[41] (2001) Lee[42] (2001) Lim[43] (2000) Overall (I-squared = 58.6%, p = 0.000)
1.65 (1.34, 2.03) 2.28 (1.72, 3.51) 3.34 (1.43, 9.75) 3.24 (1.20, 3.83) 2.97 (1.51, 5.84) 2.16 (1.48, 2.86) 1.54 (1.13, 2.11) 2.76 (1.21, 6.28) 1.69 (0.81, 3.52) 1.92 (1.18, 3.13) 0.84 (0.48, 1.45) 1.22 (0.84, 1.78) 1.04 (0.40, 2.68) 3.90 (1.51, 10.29) 0.99 (0.54, 1.82) 0.70 (0.32, 1.53) 1.64 (1.03, 2.61) 0.95 (0.61, 1.49) 1.14 (0.72, 1.80) 2.05 (1.15, 3.66) 2.17 (1.49, 3.18) 0.96 (0.60, 1.50) 2.71 (1.20, 6.28) 1.29 (0.70, 2.36) 1.20 (0.80, 1.79) 0.92 (0.47, 1.79) 1.58 (1.35, 1.84)
6.57 5.31 1.89 3.59 3.03 5.55 5.70 2.35 2.74 4.24 3.77 5.15 1.91 1.89 3.42 2.52 4.41 4.56 4.47 3.60 5.12 4.47 2.34 3.42 4.92 3.07 100.00
NOTE: Weights are from random effects analysis .0972
123
1
10.3
Dig Dis Sci (2014) 59:436–445
441 %
Study ID
HR (95% CI)
Weight
Jiang[18] (2012)
2.28 (1.72, 3.51)
8.28
Zhang[21] (2011)
2.97 (1.51, 5.84)
5.14
Sun[22] (2011)
2.16 (1.48, 2.86)
8.57
Li[24] (2010)
2.76 (1.21, 6.28)
4.10
Tatsuwaki[25] (2010)
1.69 (0.81, 3.52)
4.70
Yamac[27] (2008)
0.84 (0.48, 1.45)
6.23
Lazar[28] (2008)
1.22 (0.84, 1.78)
8.07
Ye[30] (2008)
3.90 (1.51, 10.29)
3.36
Li[33] (2006)
1.64 (1.03, 2.61)
7.11
Joo[34] (2006)
0.95 (0.61, 1.49)
7.30
Yu[36] (2005)
1.14 (0.72, 1.80)
7.18
Joo[39] (2002)
0.96 (0.60, 1.50)
7.18
Chen[40] (2001)
2.71 (1.20, 6.28)
4.08
Leung[41] (2001)
1.29 (0.70, 2.36)
5.72
Lee[42] (2001)
1.20 (0.80, 1.79)
7.78
Lim[43] (2000)
0.92 (0.47, 1.79)
5.20
Overall (I-squared = 62.4%, p = 0.000)
1.51 (1.22, 1.86)
100.00
NOTE: Weights are from random effects analysis
.0972
1
10.3
Fig. 2 Forest plot showing the combined HR for OS by univariate analysis %
Study ID
HR (95% CI)
Weight
Zhang[17] (2013)
1.65 (1.34, 2.03)
19.08
Fanelli[19] (2012)
3.34 (1.43, 9.75)
4.29
Gou[20] (2011)
3.24 (1.20, 3.83)
8.87
Mrena[23] (2010)
1.54 (1.13, 2.11)
15.73
Zhai[26] (2009)
1.92 (1.18, 3.13)
10.82
Da[29] (2008)
1.04 (0.40, 2.68)
4.36
Kolev[31] (2008)
0.99 (0.54, 1.82)
8.37
Gudis[32] (2007)
0.70 (0.32, 1.53)
5.90
Okano[37] (2004)
2.05 (1.15, 3.66)
8.89
Shi[38] (2003)
2.17 (1.49, 3.18)
13.68
Overall (I-squared = 51.0%, p = 0.031)
1.72 (1.38, 2.14)
100.00
NOTE: Weights are from random effects analysis
.103
1
9.75
Fig. 3 Forest plot showing the combined HR for OS by multivariate analysis
thus leading to inhibition of tumor apoptosis [6]. Several studies have shown that COX-2 expression is also positively correlated with matrix metalloproteinase (MMP) expression [56, 63]. MMP can degrade the extracellular matrix of tumor cells, enabling tumor cells to infiltrate and diffuse more
easily [64]. In general, COX-2 may be involved in tumor development mainly via tumor angiogenesis, inhibition of tumor apoptosis, and proliferation of tumor cells. Epidemiological studies have suggested that regular and long-term use of aspirin and other NSAIDs can reduce
123
442
Dig Dis Sci (2014) 59:436–445 Study
%
ID
HR (95% CI)
Weight
Yamac[27] (2008)
0.81 (0.52, 1.36)
20.12
Kolev[30] (2008)
0.86 (0.44, 1.71)
10.09
Linder[35] (2005)
1.54 (1.14, 2.09)
50.61
Lim[43] (2000)
0.91 (0.68, 1.82)
19.18
Overall (I-squared = 58.2%, p = 0.066)
1.15 (0.93, 1.43)
100.00
.44
1
2.27
Fig. 4 Forest plot showing the combined HR for DFS of gastric cancer patients
1.5
log[hr]
1
.5
0
-.5 0
.2
.4
.6
s.e. of: log[hr]
Fig. 5 Begg’s Funnel plot for studies reporting OS
1
log[hr]
.5
0
-.5 0
.2
s.e. of: log[hr]
Fig. 6 Begg’s Funnel plot for studies reporting DFS
123
.4
mortality from several malignancies, including gastric cancer [65, 66]. Further confirmation by meta-analysis also indicated that regular use of aspirin may be associated with reduced risk of noncardia gastric cancer [67]. The main site of action of aspirin and NSAIDs is COX, so it effectively inhibits COX activity. Hence we inferred that COX and prostaglandin may be involved in a series of pathophysiological processes related to the occurrence and development of cancer. Compared with non-selective COX inhibitors, selective COX-2 inhibitors, for example celecoxib, have a distinct advantage in reducing gastrointestinal side effects. Experimental treatment of gastric cancer in mice showed that the combination of celecoxib and indomethacin inhibited cell proliferation by more than 65 % [68]. Epidemiological and animal experiments confirmed that COX-2 inhibitors increase sensitivity to chemotherapeutic drugs in several cancers [69, 70]. Attention should be drawn to some of the articles included in this meta-analysis. In the study by Mrena et al. [24], COX-2 expression was found to be a prognostic factor for diploid, but not aneuploid, tumors. It has been reported that the possibility of metastasis tends to be high for aneuploid tumors, resulting in poor prognosis for gastric cancer patients [71]. COX-2 expression may reveal aggressive potential before the occurrence of major chromosomal changes. Li et al. [25] evaluated COX-2 expression in primary gastric tumors (PT) and lymph node metastases (LNMs). COX-2 expression was proved to be associated with poor prognosis for LNMs but not PT. This difference may be indicative of heterogeneity in the significance of molecule expression in PT and LNMs. It would be extremely valuable to investigate the prognostic significance of COX-2 expression in LNMs with well-designed studies.
Dig Dis Sci (2014) 59:436–445
This meta-analysis has several limitations. All the included studies measured COX-2 expression by IHC. Many factors, for example primary antibody and antibody concentration, may affect the results. However, it was impossible to perform a subgroup analysis to investigate the potential effect of technique on the combined results. There are also large differences between definitions of positive COX-2 expression. Some of the studies used CS whereas others used percentage COX-2 expression only. This also may be a limitation. Formulation of a unified COX-2 positive standard is urgently required. Treatment of the patients among the studies was not identical, which may affect survival time among the studies. However, most of the studies did not give information about treatment of the gastric cancer patients. Other characteristics of the patients, for example gender, age, tumor size, and TNM, may lead to heterogeneous results. But, because of lack of sufficient information, an attempt to perform subgroup analysis failed. All these sources of variability may cause bias. Publication bias may overvalue the combined HR. In general, a study with a positive result is easy to accept whereas a study with a negative result is often rejected. The studies in this meta-analysis are restricted to articles written in English and Chinese, which may also lead to bias. Among the studies reporting a correlation between COX-2 expression and survival of patients with gastric cancer, six were excluded because of insufficient data. This may be another potential factor which causes bias. Furthermore, the method used to estimate HR and 95 % CI for articles which did not report HR directly, which is based the published articles [44, 45], may be another potential source of bias. The strategy, which did not completely eliminate inaccuracy in extracted survival data and the estimated HR, seems to be less reliable than values obtained directly from published articles. We did, however, study the survival curves published by two of the authors and compared the HR and 95 % CI with the published results, to confirm the accuracy of estimated HR. In conclusion, published data suggest that high COX-2 expression may be an independent prognostic factor for patients with gastric cancer. The findings may also suggest that COX-2 inhibition could improve survival in gastric cancer. However, large prospective studies are needed to establish the clinical value of COX-2 inhibitors in prevention and/or treatment of gastric cancer. Conflict of interest
None.
References 1. Ferlay J, Shin HR, Bray F, et al. Estimates of worldwide burden of cancer in 2008: Globocan 2008. Int J Cancer. 2010;127: 2893–2917.
443 2. Herszenyi L, Tulassay Z. Epidemiology of gastrointestinal and liver tumors. Eur Rev Med Pharmacol Sci. 2010;14:249–258. 3. Xing X, Tang YB, Yuan G, et al. The prognostic value of E-cadherin in gastric cancer: a meta-analysis. Int J Cancer. 2013;132:2589–2596. 4. Zhang QW, Liu L, Chen R, et al. Matrix metalloproteinase-9 as a prognostic factor in gastric cancer: a meta-analysis. Asian Pac J Cancer Prev. 2012;13:2903–2908. 5. Peng L, Zhan P, Zhou Y, et al. Prognostic significance of vascular endothelial growth factor immunohistochemical expression in gastric cancer: a meta-analysis. Mol Biol Rep. 2012;39: 9473–9484. 6. Thiel A, Mrena J, Ristima¨ki A. Cyclooxygenase-2 and gastric cancer. Cancer Metastasis Rev. 2011;30:387–395. 7. Wu WK, Sung JJ, Lee CW, et al. Cyclooxygenase-2 in tumorigenesis of gastrointestinal cancers: an update on the molecular mechanisms. Cancer Lett. 2010;295:7–16. 8. Fujimura T, Ohta T, Oyama K, et al. Role of cyclooxygenase-2 in the carcinogenesis of gastrointestinal tract cancers: a review and report of personal experience. World J Gastroenterol. 2006;12: 1336–1345. 9. Oshima H, Oshima M, Inaba K, et al. Hyperplastic gastric tumors induced by activated macrophages in COX-2/mPGES-1 transgenic mice. EMBO J. 2004;23:1669–1678. 10. Thiel A, Narko K, Heinonen M, et al. Inhibition of cyclooxygenase-2 causes regression of gastric adenomas in trefoil factor 1 deficient mice. Int J Cancer. 2012;131:1032–1041. 11. Jiang H, Wang J, Zhao W. Cox-2 in non-small cell lung cancer: a meta-analysis. Clin Chim Acta. 2013;419:26–32. 12. Lee JY, Myung SK, Song YS. Prognostic role of cyclooxygenase2 in epithelial ovarian cancer: a meta-analysis of observational studies. Gynecol Oncol. 2013;129:613–619. 13. Huang M, Chen Q, Xiao J, et al. Prognostic significance of cyclooxygenase-2 in cervical cancer: a meta-analysis. Int J Cancer. 2013;132:363–373. 14. Almeida PR, Ferreira FV, Santos CC, et al. Immunoexpression of cyclooxygenase-2 in primary gastric carcinomas and lymph node metastases. World J Gastroenterol. 2012;18:778–784. 15. Joo YE, Rew JS, Seo YH, et al. Cyclooxygenase-2 overexpression correlates with vascular endothelial growth factor expression and tumor angiogenesis in gastric cancer. J Clin Gastroenterol. 2003;37:28–33. 16. Tang H, Wang J, Bai F, et al. Positive correlation of osteopontin, cyclooxygenase-2 and vascular endothelial growth factor in gastric cancer. Cancer Invest. 2008;26:60–67. 17. Zhang X, Wu Q, Gan L, et al. Reduced group IVA phospholipase A2 expression is associated with unfavorable outcome for patients with gastric cancer. Med Oncol. 2013;30:454. 18. Jiang H, Qiao XL, Huang FY. Expressions and clinical significance of Smad4 and Cox-2 in gastric cancer. J Clin Med Pract. 2012;16:30–33. 19. Fanelli MF, Chinen LT, Begnami MD, et al. The influence of transforming growth factor-a, cyclooxygenase-2, matrix metalloproteinase (MMP)-7, MMP-9 and CXCR4 proteins involved in epithelial–mesenchymal transition on overall survival of patients with gastric cancer. Histopathology. 2012;61: 153–161. 20. Gou HF, Chen XC, Zhu J, et al. Expressions of COX-2 and VEGF-C in gastric cancer: correlations with lymphangiogenesis and prognostic implications. J Exp Clin Cancer Res. 2011;30:14. 21. Zhang C, Wang XQ, Xu C, et al. Expression of cyr-61 and cox-2 in gastric carcinoma and its clinical significance. J China Med Univ. 2011;40:744–748. 22. Sun GY, Luo DH, Wu JS, et al. The expression of NICD and COX-2 in gastric carcinoma tissues and its clinical biological significance. J Med Res. 2011;40:61–66.
123
444 23. Tatsuwaki H, Tanigawa T, Watanabe T, et al. Reduction of 15-hydroxyprostaglandin dehydrogenase expression is an independent predictor of poor survival associated with enhanced cell proliferation in gastric adenocarcinoma. Cancer Sci. 2010;101: 550–558. 24. Mrena J, Wiksten JP, Kokkola A, et al. COX-2 is associated with proliferation and apoptosis markers and serves as an independent prognostic factor in gastric cancer. Tumour Biol. 2010;31:1–7. 25. Li Y, Tan BB, Fan LQ, et al. Expression of COX-2, survivin in regional lymph node metastases of gastric carcinoma and the correlation with prognosis. Hepatogastroenterology. 2010;57:1435–1441. 26. Zhai JH, Li N, Zhang L, et al. Expression of P16, C-MYC and COX-2 in gastric carcinoma and relationship with the prognosis of patients. J Zhejiang Coll Tradit Chin Med. 2009;33:321–322. 27. Yamac D, Ayyildiz T, Coskun U, et al. Cyclooxygenase-2 expression and its association with angiogenesis, Helicobacter pylori, and clinicopathologic characteristics of gastric carcinoma. Pathol Res Pract. 2008;204:527–536. 28. Ye SC, Wang JY, Yuan GZ, et al. Expression of COX-2 and P-gp and its prognosis in gastric carcinoma. Chin Gen Pract. 2008;11:291–294. 29. Lazar D, Taban S, Ardeleanu C, et al. Immunohistochemical expression of the cyclooxygenase-2 (COX-2) in gastric cancer. The correlations with the tumor angiogenesis and patients’ survival. Rom J Morphol Embryol. 2008;49:371–379. 30. Kolev Y, Uetake H, Takagi Y, et al. Lactate dehydrogenase-5 (LDH-5) expression in human gastric cancer: association with hypoxia-inducible factor (HIF-1alpha) pathway, angiogenic factors production and poor prognosis. Ann Surg Oncol. 2008;15:2336–2344. 31. Da MX, Wu XT, Wang J, et al. Expression of cyclooxygenase-2 and vascular endothelial growth factor-C correlates with lymphangiogenesis and lymphatic invasion in human gastric cancer. Arch Med Res. 2008;39:92–99. 32. Gudis K, Tatsuguchi A, Wada K, et al. Clinical significance of prostaglandin E synthase expression in gastric cancer tissue. Hum Pathol. 2007;38:1826–1835. 33. Li M, Liu W, Zhu YF, et al. Correlation of COX-2 and K-ras expression to clinical outcome in gastric cancer. Acta Oncol. 2006;45:1115–1119. 34. Joo YE, Chung IJ, Park YK, et al. Expression of cyclooxygenase2, p53 and Ki-67 in gastric cancer. J Korean Med Sci. 2006;21:871–876. 35. Linder N, Haglund C, Lundin M, et al. Decreased xanthine oxidoreductase is a predictor of poor prognosis in early-stage gastric cancer. J Clin Pathol. 2006;59:965–971. 36. Yu JR, Wu YJ, Qin Q, et al. Expression of cyclooxygenase-2 in gastric cancer and its relation to liver metastasis and long-term prognosis. World J Gastroenterol. 2005;11:4908–4911. 37. Okano H, Shinohara H, Miyamoto A, et al. Concomitant overexpression of cyclooxygenase-2 in HER-2-positive on Smad4reduced human gastric carcinomas is associated with a poor patient outcome. Clin Cancer Res. 2004;10:6938–6945. 38. Shi H, Xu JM, Hu NZ, et al. Prognostic significance of expression of cyclooxygenase-2 and vascular endothelial growth factor in human gastric carcinoma. World J Gastroenterol. 2003;9: 1421–1426. 39. Joo YE, Oh WT, Rew JS, et al. Cyclooxygenase-2 expression is associated with well-differentiated and intestinal-type pathways in gastric carcinogenesis. Digestion. 2002;66:222–229. 40. Leung WK, To KF, Ng YP, et al. Association between cyclooxygenase-2 overexpression and missense p53 mutations in gastric cancer. Br J Cancer. 2001;84:335–339. 41. Lee TL, Leung WK, Lau JY, et al. Inverse association between cyclooxygenase-2 overexpression and microsatellite instability in gastric cancer. Cancer Lett. 2001;168:133–140.
123
Dig Dis Sci (2014) 59:436–445 42. Chen CN, Sung CT, Lin MT, et al. Clinicopathologic association of cyclooxygenase 1 and cyclooxygenase 2 expression in gastric adenocarcinoma. Ann Surg. 2001;233:183–188. 43. Lim HY, Joo HJ, Choi JH, et al. Increased expression of cyclooxygenase-2 protein in human gastric carcinoma. Clin Cancer Res. 2000;6:519–525. 44. Nordmann AJ, Kasenda B, Briel M. Meta-analyses: what they can and cannot do. Swiss Med Wkly. 2012;142:w13518. 45. McShane LM, Altman DG, Sauerbrei W. Reporting recommendations for tumor marker prognostic studies (remark). Exp Oncol. 2006;28:99–105. 46. Chen M, Cai E, Huang J, et al. Prognostic value of vascular endothelial growth factor expression in patients with esophageal cancer: a systematic review and meta-analysis. Cancer Epidemiol Biomarkers Prev. 2012;21:1126–1134. 47. Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007;7:8–16. 48. Parmar MK, Torri V, Stewart L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med. 1998;17:2815–2834. 49. Egger M, Smith GD, Schneider M, Minder C. Bias in metaanalysis detected by a simple, graphical test. BMJ. 1997;315: 629–634. 50. Zhao HC, Qin R, Chen XX, et al. Microvessel density is a prognostic marker of human gastric cancer. World J Gastroenterol. 2006;12:7598–7603. 51. Han SL, Tang HJ, Hua YW, et al. Expression of COX-2 in stomach cancers and its relation to their biological features. Dig Surg. 2003;20:107–114. 52. Al-Moundhri MS, Al-Hadabi I, Al-Mawaly K, et al. Prognostic significance of cyclooxygenase-2, epidermal growth factor receptor 1, and microvascular density in gastric cancer. Med Oncol. 2012;29:1739–1747. 53. Dicken BJ, Graham K, Hamilton SM, et al. Lymphovascular invasion is associated with poor survival in gastric cancer: an application of gene-expression and tissue array techniques. Ann Surg. 2006;243:64–73. 54. Vidal O, Soriano-Izquierdo A, Pera M, et al. Positive VEGF immunostaining independently predicts poor prognosis in curatively resected gastric cancer patients: results of a study assessing a panel of angiogenic markers. J Gastrointest Surg. 2008;12: 1005–1014. 55. Mrena J, Wiksten JP, Thiel A, et al. Cyclooxygenase-2 is an independent prognostic factor in gastric cancer and its expression is regulated by the messenger RNA stability factor HuR. Clin Cancer Res. 2005;11:7362–7368. 56. Mrena J, Wiksten JP, Nordling S, et al. MMP-2 but not MMP-9 associated with COX-2 and survival in gastric cancer. J Clin Pathol. 2006;59:618–623. 57. Kolev Y, Uetake H, Iida S, et al. Prognostic significance of VEGF expression in correlation with COX-2, microvessel density, and clinicopathological characteristics in human gastric carcinoma. Ann Surg Oncol. 2007;14:2738–2747. 58. Jamieson NB, Carter CR, McKay CJ, et al. Tissue biomarkers for prognosis in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis. Clin Cancer Res. 2011;17:3316–3331. 59. Li L, Zhao J, Wu Z, et al. Meta-analysis: clinicopathological and prognostic significance of cyclooxygenase-2 expression on oesophageal squamous cell carcinoma. Aliment Pharmacol Ther. 2009;30:589–596. 60. Peng L, Zhou Y, Wang Y, et al. Prognostic significance of COX2 immunohistochemical expression in colorectal cancer: a metaanalysis of the literature. PLoS ONE. 2013;8:e58891. 61. Claesson-Welsh L, Welsh M. VEGFA and tumour angiogenesis. J Intern Med. 2013;273:114–127.
Dig Dis Sci (2014) 59:436–445 62. Tatsuguchi A, Matsui K, Shinji Y, et al. Cyclooxygenase-2 expression correlates with angiogenesis and apoptosis in gastric cancer tissue. Hum Pathol. 2004;35:488–495. 63. Sun WH, Sun YL, Fang RN, et al. Expression of cyclooxygenase2 and matrix metalloproteinase-9 in gastric carcinoma and its correlation with angiogenesis. Jpn J Clin Oncol. 2005;35: 707–713. 64. Lukaszewicz-Zaja˛c M, Mroczko B, Szmitkowski M. Gastric cancer—the role of matrix metalloproteinases in tumor progression. Clin Chim Acta. 2011;412:1725–1730. 65. Gamba CA, Swetter SM, Stefanick ML, et al. Aspirin is associated with lower melanoma risk among postmenopausal Caucasian women: the women’s health initiative. Cancer. 2013;119:1562–1569. 66. Gammon MD, Terry MB, Arber N, et al. Nonsteroidal antiinflammatory drug use associated with reduced incidence of adenocarcinomas of the esophagus and gastric cardia that overexpress cyclin D1: a population-based study. Cancer Epidemiol Biomarkers Prev. 2004;13:34–39.
445 67. Yang P, Zhou Y, Chen B, et al. Aspirin use and the risk of gastric cancer: a meta-analysis. Dig Dis Sci. 2010;55:1533–1539. 68. Yu J, Tang BD, Leung WK, et al. Different cell kinetic changes in rat stomach cancer after treatment with celecoxib or indomethacin: implications on chemoprevention. World J Gastroenterol. 2005;11:41–45. 69. Liu H, Huang P, Xu X, et al. Anticancer effect of celecoxibvia COX-2 dependent and independent mechanisms in human gastric cancers cells. Dig Dis Sci. 2009;54:1418–1424. 70. Keller JJ, Giardiello FM. Chemoprevention strategies using NSAIDs and COX-2 inhibitors. Cancer Biol Ther. 2003;2:140–149. 71. Russo A, Bazan V, Migliavacca M, et al. Prognostic significance of DNA ploidy, S-phase fraction, and tissue levels of aspartic, cysteine, and serine proteases in operable gastric carcinoma. Clin Cancer Res. 2000;6:178–184.
123
