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International Journal of Clinical and Experimental Medicine logoLink to International Journal of Clinical and Experimental Medicine
. 2015 Aug 15;8(8):12448–12462.

Cyclooxygenase-2 -1195G>A (rs689466) polymorphism and cancer susceptibility: an updated meta-analysis involving 50,672 subjects

Yafeng Wang 1,*, Heping Jiang 2,*, Tianyun Liu 3,*, Weifeng Tang 4, Zhiqiang Ma 5
PMCID: PMC4612841  PMID: 26550156

Abstract

The association between cyclooxygenase-2 (COX-2) -1195G>A (rs689466) polymorphism and cancer risk has been extensively explored. However, the results of previous studies remain controversial. To address this gap, we performed an updated meta-analysis of fifty-eight studies involving a total of 50,672 subjects. Searching of PubMed and Embase databases was performed for publications on the association between COX-2 -1195G>A polymorphism and the risk of cancer. Statistical correlation was identified between COX-2 -1195G>A variants and overall cancer risk in five genetic models. In a sub-group analysis based on cancer type, significant association between COX-2 -1195G>A polymorphism and increased risk of gastric cancer, pancreatic cancer, hepatocellular carcinoma and other cancers was found. In a sub-group analysis by ethnicity, increased cancer risk was observed among Asians instead of Caucasians, Africans and mixed populations. Furthermore, in a sub-group analysis based on cancer system, increased cancer risk was found in digestive system cancer and other system cancer. Non-parametric “trim-and-fill” method was harnessed as a sensitivity analysis method and the results suggested our findings reliable. In summary, the results of our meta-analysis highlight that COX-2 -1195G>A polymorphism may be a risk factor for cancer.

Keywords: Cancer, gene polymorphism, cyclooxygenase-2, meta-analysis

Introduction

Accumulating evidence demonstrates that carcinogenesis is a multi-step and multi-factorial process that results from complex interactions of both environmental and genetic factors. The pathogenesis of malignance is very complicated and has not been clarified completely, although recent studies have kept a watchful eye on the role of the chronic infection and immune system [1,2]. Recently, evidence highlights that inflammatory factors of chronic infection may have a hand in the development of multiple cancers by mediating immune suppression, suppressing apoptosis and promoting cell proliferation [3-5]. For this reason, chronic infection is increasing as a hot spot in clinical and experimental cancer research [6,7].

Inflammatory factors of chronic infection have long been considered as a risk candidate for multiple human malignances [8-11]. Of late, Wang reported that the modifiable risk factors elucidate nearly 60% of cancer related deaths in China, with a prominent role of tobacco consumption and chronic infection [12].

Cyclooxygenase-2 (COX-2), an inducible enzyme, converts arachidonic acid to prostaglandins which are the effective mediators of inflammation reaction. It is reported that COX-2 is over-expressed in tumor tissue specimens, whereas in normal tissue, its expression is often undetectable [13,14]. Previous clinical and experimental investigation suggested that COX-1/-2 inhibitor attenuates the risk of carcinoma [15].

Of late, the association between COX-2 -1195G>A (rs689466) and cancer risk was extensively explored. Previous studies supported that COX-2 -1195G>A was associated with increased risk of overall cancer, especially in non-nonsteroidal anti-inflammatory drug users [16-18]. Recently, more investigations were performed to validate this potential correlation. Up to now, fifty-eight studies focus on the association of COX-2 -1195G>A polymorphism with malignance, and the results remain conflicting. The aim of our study was to extensively investigate the association between COX-2 -1195G>A polymorphism and cancer risk by an updated meta-analysis.

Materials and methods

Search strategy

All publications investigating the association between COX-2 -1195G>A and cancer risk were identified by exhausted electronic literature searches of PubMed and Embase databases (published up to July 31, 2014) with search terms of ‘COX2’, ‘COX-2’, ‘Cyclooxygenase-2’, ‘Cyclooxygenase 2’, ‘rs689466’, ‘polymorphism’, ‘mutation’, ‘locus’, ‘SNP’, ‘neoplasm’, ‘carcinoma’, ‘cancer’, ‘tumor’, and ‘malignance’. Additionally, in searching, no language was restricted. The citations in retrieved publications, published reviews, comments and letters were also scanned for relevant publications.

Inclusion and exclusion criteria

Included studies had to meet the following criteria: 1) they should be case-control or cohort study design; 2) they should focus on the association between COX-2 -1195G>A polymorphism and cancer; 3) they should supply the available frequencies of genotypes or alleles; 4) genotype distributions among controls were consistent with Hardy-Weinberg equilibrium (HWE). The major exclusion criteria were: 1) no usable data reported; 2) overlapping data; 3) only relevant to oncotherapy; not case-control study or cohort study design; 5) comment, review, editorial, meta-analysis or letter.

Data extraction

In a standardized form, three researchers (Y. Wang, H. Jiang and T. Liu) extracted the data independently and the following items were extracted: the first author’s last name, year of publication, cancer type, country, populations, genotype frequencies and sample size (total cases and controls), genotype method. When we meet conflicting evaluations, differences were adjudicated and reached a consensus on all of the items after discussion among all reviewers.

Statistical analysis

Crude odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated to evaluate the strength of association between COX-2 -1195G>A polymorphism and cancer risk. The pooled ORs were conducted for five genetic models including allele comparing model (A vs. G), dominant model (AA+GA vs. GG), recessive model (AA vs. GA+GG), heterozygote comparison (GA vs. GG) and homozygote comparison (AA vs. GG). P < 0.05 (two tailed) was defined as statistically significant. We also performed stratification analyses by cancer type (any cancer type < 3 individual case-control studies was defined as ‘other cancers’), ethnicity and system. Heterogeneity was calculated by a chi square-based Q statistical and I2 test. Statistical significance was considered at P < 0.1 or I2 > 50% and a random effect model (the DerSimonian-Laird method) was used [19], otherwise a fixed-effect model (the Mantel-Haenszel method) was applied [20]. A web-based HWE program (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl) was harnessed to assess the evidence of HWE in controls. The potential publication bias was measured by the Begg’s funnel plot and Egger’s test. The statistical significance level was set at 0.05. Nonparametric “trim-and-fill” method was used to determine the stability of our results. All the statistical manipulations were performed using STATA (Version 12.0) statistical software (Stata Corp LP, College Station, Texas).

Results

Studies characteristics

A total of 959 relevant publications were retrieved from electronic literature searches. The detailed selecting process was presented in Figure 1. In some publications, there were more than two independent groups, which were treated separately as individual studies [21-26]. Lastly, fifty-eight studies on the association of COX-2 -1195G>A polymorphism with cancer risk were pooled [22,27-57]. Among them, eleven investigated colorectal cancer [21,26,34,55,58-60], eight investigated esophageal cancer [22,43,44,46,61,62], six investigated hepatocellular carcinoma [33,38,42,50,63,64], five investigated prostate cancer [29,36,57,65], four investigated gastric cancer [31,32,52,53], four investigated lymphoma [24,56], four investigated breast cancer [27,51,54,66], three investigated pancreatic cancer [47,48,67], and the others investigated gallbladder cancer [45], bladder cancer [30,37], head and neck cancer [28,68], leukemia [35,39], lung cancer [41,69], skin cancer [70,71] and oral cancer [40,49]. With respect to subjects, twenty-seven were Asians [27-53], twenty-five were Caucasians [21,24,26,57-71], four were mixed populations [22,54-56] and two were Africans [22,57]. Table 1 gives characteristics and Table 2 gives COX-2 -1195G>A genotype and allele frequencies.

Figure 1.

Figure 1

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Flow diagram showing the study selection procedure in meta-analysis.

Table 1.

Characteristics of studies in the meta-analysis

Study Publication year Ethnicity Country Cancer type Sample size (case/control) Genotype method
Moatter et al. 2014 Asians Pakistan breast cancer 150/101 PCR-RFLP
Gharib et al. 2014 Caucasians Egypt hepatocellular carcinoma 120/130 PCR-RFLP
Niu et al. 2014 Asians China head and neck cancer 260/1047 TaqMan
Sugie et al. 2014 Asians Japan prostate cancer 134/86 PCR-RFLP
Pereira et al. 2014 Caucasians Portugal colorectal cancer 246/480 MassARRAY iPLEX Gold technology
Chang et al. 2013 Asians China bladder cancer 375/375 PCR-RFLP
Andersen et al. 2013 Caucasians Denmark colorectal cancer 970/1789 KASP™ genotyping assay
Makar et al. 2013 Caucasians USA colorectal cancer 1470/1837 IlluminaTM GoldenGate
Makar et al. 2013 Caucasians USA colorectal cancer 583/775 IlluminaTM GoldenGate
Makar et al. 2013 Caucasians USA colorectal cancer 959/1535 IlluminaTM GoldenGate
Makar et al. 2013 Caucasians USA colorectal cancer 505/839 IlluminaTM GoldenGate
Kopp et al. 2013 Caucasians Denmark prostate cancer 334/334 RT-PCR
Shin et al. 2012 Asians Korea gastric cancer 100/100 PCR-RFLP
Li et al. 2012 Asians China gastric cancer 296/319 PCR-RFLP
Chang et al. 2012 Asians China hepatocellular carcinoma 298/298 PCR-RFLP
Zhang et al. 2012 Asians China colorectal cancer 343/340 PCR-RFLP
Talar-Wojnarowska et al. 2011 Caucasians Poland pancreatic cancer 85/116 PCR-RFLP
Bye et al. 2011 Africans South Africa esophageal cancer 358/477 TaqMan
Bye et al. 2011 mixed South Africa esophageal cancer 201/427 TaqMan
Zheng et al. 2011 Asians China leukemia 446/725 PCR-RFLP
Wu et al. 2011 Asians China prostate cancer 218/436 PCR-RFLP
Akkiz et al. 2011 Caucasians Turkey hepatocellular carcinoma 129/129 PCR-RFLP
Brasky et al. 2011 Caucasians USA breast cancer 1077/1910 RT-PCR
Gangwar et al. 2011 Asians India bladder cancer 212/250 PCR-RFLP
Fan et al. 2011 Asians China hepatocellular carcinoma 780/780 TaqMan
Piranda et al. 2010 mixed Brazil breast cancer 318/273 PCR-RFLP
Wang et al. 2010 Asians China leukemia 266/266 PCR-RFLP
Mittal et al. 2010 Asians India oral cancer 193/137 PCR-RFLP
Liu et al. 2010 Asians China lung cancer 358/716 PCR-RFLP
Liu et al. 2010 Asians China hepatocellular carcinoma 210/210 PCR–RFLP
Chen et al. 2009 Asians China esophageal cancer 188/324 PCR-RFLP
Hoff et al. 2009 Caucasians The Netherlands colorectal cancer 326/369 PCR-RFLP
Kristinsson et al. 2009 Caucasians The Netherlands esophageal cancer 174/240 PCR-RFLP
Kristinsson et al. 2009 Caucasians The Netherlands esophageal cancer 70/240 PCR-RFLP
Hu et al. 2009 Asians China esophageal cancer 180/194 PCR-RFLP
Srivastava et al. 2009 Asians India gallbladder cancer 167/184 PCR-RFLP
Thompson et al. 2009 mixed USA colorectal cancer 422/481 Taqman
Upadhyay et al. 2009 Asians India esophageal cancer 174/216 PCR-RFLP
Zhao et al. 2009 Asians China pancreatic cancer 393/786 PCR-RFLP
Peters et al. 2009 Caucasians The Netherlands head and neck cancer 431/438 PCR-RFLP
Chang et al. 2009 mixed USA lymphoma 473/373 TaqMan
Xu et al. 2008 Asians China pancreatic cancer 283/566 PCR-RFLP
Chiang et al. 2008 Asians China oral cancer 377/442 PCR-RFLP
Vogel et al. 2008 Caucasians Denmark lung cancer 403/744 TaqMan
Hoeft et al. 2008 Caucasians Germany lymphoma 554/710 TaqMan
Hoeft et al. 2008 Caucasians Germany lymphoma 35/710 TaqMan
Hoeft et al. 2008 Caucasians Germany lymphoma 116/710 TaqMan
Xu et al. 2008 Asians China hepatocellular carcinoma 270/540 PCR-RFLP
Cheng et al. 2007 Africans USA prostate cancer 89/506 Taqman
Cheng et al. 2007 Caucasians USA prostate cancer 417/506 Taqman
Moons et al. 2007 Caucasians The Netherlands esophageal cancer 140/240 PCR-RFLP
Lira et al. 2007 Caucasians Italy skin cancer 107/133 PCR-RFLP
Gao et al. 2007 Asians China breast cancer 615/643 PCR-RFLP
Vogel et al. 2007 Caucasians Denmark skin cancer 322/322 Taqman
Jiang et al. 2007 Asians China gastric cancer 254/304 PCR-RFLP
Siezen et al. 2006 Caucasians Netherlands colorectal cancer 204/399 PCR-RFLP
Siezen et al. 2006 Caucasians Netherlands colorectal cancer 304/373 PCR-RFLP
Liu et al. 2006 Asians China gastric cancer 248/1523 DHPLC
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PCR-RFLP: polymerase chain reaction-restriction fragment length polymorphism; DHPLC: denaturing high-performance liquid chromatography analysis.

Table 2.

COX-2 -1195G>A polymorphism genotype distribution and allele frequency

Study Publication year Case Control Case Control HWE
GG GA AA GG GA AA A G A G
Moatter et al. 2014 4 19 112 3 21 77 243 27 175 27 0.304270
Gharib et al. 2014 17 60 43 31 66 33 146 94 132 128 0.858603
Niu et al. 2014 61 126 72 222 542 271 270 248 1084 986 0.109869
Sugie et al. 2014 21 61 52 20 47 19 165 103 85 87 0.387570
Pereira et al. 2014 15 85 143 16 133 323 371 115 779 165 0.614121
Chang et al. 2013 89 181 105 97 171 107 391 359 385 365 0.090733
Andersen et al. 2013 47 313 587 61 560 1126 1487 407 2812 682 0.397081
Makar et al. 2013 57 455 910 67 509 1198 2275 569 2905 643 0.162224
Makar et al. 2013 20 185 376 29 237 509 937 225 1255 295 0.828845
Makar et al. 2013 33 287 619 63 496 958 1525 353 2412 622 0.904941
Makar et al. 2013 21 138 338 20 249 558 814 180 1365 289 0.205656
Kopp et al. 2013 13 111 210 12 112 210 531 137 532 136 0.533685
Shin et al. 2012 14 54 32 22 41 37 118 82 115 85 0.107125
Li et al. 2012 53 145 98 80 166 73 341 251 312 326 0.461235
Chang et al. 2012 70 144 84 74 145 81 312 284 307 293 0.569879
Zhang et al. 2012 50 216 77 94 184 62 370 316 308 372 0.089719
Talar-Wojnarowska et al. 2011 13 26 46 44 48 24 118 52 96 136 0.113223
Bye et al. 2011 0 44 301 1 47 417 646 44 881 49 0.786975
Bye et al. 2011 0 40 154 9 112 298 348 40 708 130 0.686305
Zheng et al. 2011 100 222 124 176 365 184 470 422 733 717 0.850095
Wu et al. 2011 57 100 61 104 210 122 222 214 454 418 0.464218
Akkiz et al. 2011 2 36 91 2 32 95 218 40 222 36 0.707524
Brasky et al. 2011 34 271 660 54 471 1199 1591 339 2869 579 0.353199
Gangwar et al. 2011 162 48 2 182 64 4 52 372 72 428 0.543520
Fan et al. 2011 204 390 186 205 381 194 762 798 769 791 0.522773
Piranda et al. 2010 3 62 224 3 51 190 510 68 431 57 0.838274
Wang et al. 2010 63 128 75 65 127 74 278 254 275 257 0.472808
Mittal et al. 2010 3 57 133 5 32 100 323 63 232 42 0.241040
Liu et al. 2010 84 172 102 178 345 193 376 340 731 701 0.336883
Liu et al. 2010 31 110 69 52 108 50 248 172 208 212 0.677855
Chen et al. 2009 42 88 58 57 165 102 204 172 369 279 0.487719
Hoff et al. 2009 12 101 213 13 124 232 527 125 588 150 0.470706
Kristinsson et al. 2009 15 59 100 6 80 154 259 89 388 92 0.240585
Kristinsson et al. 2009 5 26 39 6 80 154 104 36 388 92 0.240585
Hu et al. 2009 39 80 61 50 103 41 202 158 185 203 0.371617
Srivastava et al. 2009 104 52 11 142 37 5 74 260 47 321 0.185970
Thompson et al. 2009 9 138 275 15 168 297 688 156 762 198 0.130845
Upadhyay et al. 2009 126 46 2 168 45 3 50 298 51 381 0.994569
Zhao et al. 2009 85 194 114 212 401 173 422 364 747 825 0.521326
Peters et al. 2009 22 134 275 15 163 260 684 178 683 193 0.081594
Chang et al. 2009 19 124 314 13 99 249 752 162 597 125 0.422989
Xu et al. 2008 58 143 82 154 284 128 307 259 540 592 0.892966
Chiang et al. 2008 80 187 101 114 235 93 389 347 421 463 0.166848
Vogel et al. 2008 17 124 262 24 253 467 648 158 1187 301 0.143186
Hoeft et al. 2008 14 147 361 19 197 447 869 175 1091 235 0.627123
Hoeft et al. 2008 1 13 19 19 197 447 51 15 1091 235 0.627123
Hoeft et al. 2008 1 33 76 19 197 447 185 35 1091 235 0.627123
Xu et al. 2008 52 125 93 119 287 134 311 229 555 525 0.138287
Cheng et al. 2007 2 20 67 0 12 77 154 24 166 12 0.495255
Cheng et al. 2007 13 134 270 15 122 280 674 160 682 152 0.705855
Moons et al. 2007 3 54 83 10 76 154 220 60 384 96 0.871799
Lira et al. 2007 3 25 76 2 33 96 177 31 225 37 0.658979
Gao et al. 2007 121 305 175 150 327 166 655 547 659 627 0.652871
Vogel et al. 2007 10 95 199 15 121 179 493 115 479 151 0.338448
Jiang et al. 2007 48 132 74 62 163 79 280 228 321 287 0.186688
Siezen et al. 2006 10 59 127 20 128 243 313 79 614 168 0.557997
Siezen et al. 2006 19 132 283 41 226 422 698 170 1070 308 0.148689
Liu et al. 2006 44 116 88 377 771 375 292 204 1521 1525 0.626310
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HWE: Hardy-Weinberg equilibrium.

Meta-analysis results

In total, 50,672 subjects (19,947 cases and 30,725 controls) were relevant to the association between COX-2 -1195G>A and cancer risk. Overall, significantly increased cancer risk was associated with the COX-2 -1195A allele: dominant model comparison AA+GA vs. GG (OR, 1.14; 95% CI, 1.04-1.25; P = 0.007), recessive model comparison AA vs. GA+GG (OR, 1.11; 95% CI, 1.04-1.18; P = 0.003), homozygote comparison AA vs. GG (OR, 1.21; 95% CI, 1.07-1.36; P = 0.002), heterozygote comparison GA vs. GG (OR, 1.09; 95% CI, 1.00-1.18; P = 0.045) and allele comparison A vs. G (OR, 1.09; 95% CI, 1.03-1.15; P = 0.002) (Table 3). In a sub-group analysis based on cancer type, the association between COX-2 -1195G>A polymorphism and an increased risk of gastric cancer was identified in five genetic models: AA+GA vs. GG (OR, 1.43; 95% CI, 1.15-1.76; P = 0.001), AA vs. GA+GG (OR, 1.36; 95% CI, 1.02-1.81; P = 0.036), AA vs. GG (OR, 1.72; 95% CI, 1.35-2.20; P < 0.001), GA vs. GG (OR, 1.28; 95% CI, 1.02-1.60; P = 0.031) and A vs. G (OR, 1.30; 95% CI, 1.16-1.47; P < 0.001), of pancreatic cancer in five genetic models: AA+GA vs. GG (OR, 1.66; 95% CI, 1.12-2.48; P = 0.012), AA vs. GA+GG (OR, 1.93; 95% CI, 1.14-3.30; P = 0.015), AA vs. GG (OR, 2.36; 95% CI, 1.27-4.40; P = 0.007), GA vs. GG (OR, 1.30; 95% CI, 1.04-1.62; P = 0.022) and A vs. G (OR, 1.66; 95% CI, 1.11-2.47; P = 0.013), of hepatocellular carcinoma in one genetic model: AA vs. GG (OR, 1.43; 95% CI, 1.02-2.00; P = 0.039) and of other cancers in two genetic models: AA vs. GA+GG (OR, 1.14; 95% CI, 1.03-1.25; P = 0.009) and A vs. G (OR, 1.09; 95% CI, 1.02-1.16; P = 0.011) (Table 4). In a sub-group analysis by ethnicity, our results confirmed that COX-2 -1195A allele was associated with an increased cancer risk in Asians: AA+GA vs. GG (OR, 1.22; 95% CI, 1.10-1.34; P < 0.001), AA vs. GA+GG (OR, 1.23; 95% CI, 1.12-1.35; P < 0.001), AA vs. GG (OR, 1.36; 95% CI, 1.20-1.55; P < 0.001), GA vs. GG (OR, 1.15; 95% CI, 1.05-1.26; P = 0.003) and A vs. G (OR, 1.17; 95% CI, 1.10-1.25; P < 0.001), a borderline decreased cancer risk was identified in two genetic models: AA vs. GA+GG (OR, 0.69; 95% CI, 0.48-1.01; P = 0.058) and A vs. G (OR, 0.70; 95% CI, 0.49-1.01; P = 0.056) in Africans, but not in Caucasians or mixed populations (Table 3; Figure 2). Additionally, in a sub-group analysis based on cancer system, a significant increased risk of digestive system cancer was confirmed in five genetic models: AA+GA vs. GG (OR, 1.22; 95% CI, 1.06-1.39; P = 0.004), AA vs. GA+GG (OR, 1.14; 95% CI, 1.04-1.26; P = 0.008), AA vs. GG (OR, 1.31; 95% CI, 1.10-1.57; P = 0.003), GA vs. GG (OR, 1.15; 95% CI, 1.02-1.30; P = 0.018) and A vs. G (OR, 1.13; 95% CI, 1.04-1.22; P = 0.003) and of other system cancer in one genetic model: AA vs. GA+GG (OR, 1.21; 95% CI, 1.02-1.42; P = 0.026) (Table 5; Figure 3).

Table 3.

Meta-analysis of COX-2 -1195G>A polymorphisms and cancer risk in a sub-group analysis by race

Genetic comparison Population OR (95% CI); P Test of heterogeneity
(p-Value, I2) Model
AA+GA vs. GG All 1.14 (1.04-1.25); 0.007 < 0.001, 43.4% R
Asians 1.22 (1.10-1.34); < 0.001 0.014, 41.4% R
Caucasians 0.97 (0.80-1.17); 0.716 0.009, 44.6% R
Africans 0.58 (0.09-3.61);0.556 0.280, 14.4% F
Mixed 1.28 (0.79-2.08); 0.321 0.378, 2.9% F
AA vs. GA+GG All 1.11 (1.04-1.18); 0.003 < 0.001, 56.5% R
Asians 1.23 (1.12-1.35); < 0.001 0.024, 38.3% R
Caucasians 1.02 (0.93-1.12); 0.660 < 0.001, 58.6% R
Africans 0.69 (0.48-1.01); 0.058 0.265, 19.7% F
Mixed 1.13 (0.96-1.33); 0.148 0.294, 19.2% F
AA vs. GG All 1.21 (1.07-1.36); 0.002 < 0.001, 54.4% R
Asians 1.36 (1.20-1.55); < 0.001 0.006, 45.6% R
Caucasians 0.99 (0.79-1.24); 0.940 < 0.001, 57.9% R
Africans 0.54 (0.09-3.31); 0.501 0.263, 20.0% F
Mixed 1.31 (0.81-2.14); 0.273 0.338, 10.9% F
GA vs. GG All 1.09 (1.00-1.18); 0.045 0.073, 22.2% R
Asians 1.15 (1.05-1.26); 0.003 0.085, 28.5% R
Caucasians 0.94 (0.82-1.08); 0.375 0.281, 12.8% F
Africans 0.89 (0.13-6.02); 0.903 0.348, 0.0% F
Mixed 1.22 (0.73-2.02); 0.451 0.513, 0.0% F
A vs. G All 1.09 (1.03-1.15); 0.002 < 0.001, 63.9% R
Asians 1.17 (1.10-1.25); < 0.001 0.001, 51.0% R
Caucasians 1.02 (0.93-1.11); 0.720 < 0.001, 66.1% R
Africans 0.70 (0.49-1.01); 0.056 0.186, 42.7% F
Mixed 1.12 (0.97-1.30); 0.115 0.170, 40.3% F
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F indicates fixed model; R indicates random model.

Table 4.

Meta-analysis of COX-2 -1195G>A polymorphisms and cancer risk in a sub-group analysis by cancer type

Genetic comparison Cancer type OR (95% CI); P Test of heterogeneity
(p-Value, I2) Model
AA+GA vs. GG All 1.14 (1.04-1.25); 0.007 < 0.001, 43.4% R
Breast cancer 1.11 (0.88-1.39); 0.374 0.700, 0.0% F
Hepatocellular carcinoma 1.16 (0.99-1.36); 0.060 0.169, 35.7% F
Prostate cancer 1.00 (0.76-1.33); 0.984 0.453, 0.0% F
Colorectal cancer 1.03 (0.78-1.36); 0.848 0.001, 65.6% R
Gastric cancer 1.43 (1.15-1.76); 0.001 0.568, 0.0% F
Pancreatic cancer 1.66 (1.12-2.48); 0.012 0.054, 65.8% R
Esophageal cancer 0.91 (0.56-1.47); 0.697 0.013, 60.5% R
Lymphoma 1.07 (0.67-1.70); 0.776 0.682, 0.0% F
Other cancers 1.08 (0.96-1.21); 0.179 0.158, 28.5% F
AA vs. GA+GG All 1.11 (1.04-1.18); 0.003 < 0.001, 56.5% R
Breast cancer 1.03 (0.90-1.17); 0.665 0.316, 15.1% F
Hepatocellular carcinoma 1.22 (0.96-1.54); 0.100 0.040, 57.1% R
Prostate cancer 1.01 (0.74-1.36); 0.962 0.031, 62.3% R
Colorectal cancer 1.00 (0.91-1.11); 0.926 0.030, 49.9% R
Gastric cancer 1.36 (1.02-1.81); 0.036 0.076, 56.3% R
Pancreatic cancer 1.93 (1.14-3.30); 0.015 0.002, 83.3% R
Esophageal cancer 1.00 (0.76-1.31); 0.989 0.013, 60.8% R
Lymphoma 1.02 (0.86-1.21); 0.795 0.608, 0.0% F
Other cancers 1.14 (1.03-1.25); 0.009 0.601, 0.0% F
AA vs. GG All 1.21 (1.07-1.36);0.002 < 0.001, 54.4% R
Breast cancer 1.14 (0.88-1.47); 0.316 0.551, 0.0% F
Hepatocellular carcinoma 1.43 (1.02-2.00); 0.039 0.032, 59.2% R
Prostate cancer 1.08 (0.79-1.48); 0.619 0.156, 39.9% F
Colorectal cancer 1.02 (0.78-1.35); 0.880 0.003, 62.7% R
Gastric cancer 1.72 (1.35-2.20); < 0.001 0.336, 11.3% F
Pancreatic cancer 2.36 (1.27-4.40); 0.007 0.006, 80.4% R
Esophageal cancer 0.90 (0.46-1.77); 0.770 0.005, 65.1% R
Lymphoma 1.07 (0.67-1.71); 0.761 0.668, 0.0% F
Other cancers 1.13 (0.98-1.30); 0.090 0.427, 1.9% F
GA vs. GG All 1.09 (1.00-1.18); 0.045 0.073, 22.2% R
Breast cancer 1.07 (0.85-1.36); 0.556 0.784, 0.0% F
Hepatocellular carcinoma 1.11 (0.94-1.31); 0.201 0.450, 0.0% F
Prostate cancer 0.97 (0.72-1.30); 0.837 0.799, 0.0% F
Colorectal cancer 1.03 (0.80-1.34); 0.798 0.009, 57.3% R
Gastric cancer 1.28 (1.02-1.60); 0.031 0.518, 0.0% F
Pancreatic cancer 1.30 (1.04-1.62); 0.022 0.608, 0.0% F
Esophageal cancer 0.90 (0.58-1.42); 0.661 0.040, 52.4% R
Lymphoma 1.06 (0.66-1.71); 0.812 0.692, 0.0% F
Other cancers 1.04 (0.92-1.17); 0.531 0.193, 24.8% F
A vs. G All 1.09 (1.03-1.15); 0.002 < 0.001, 63.9% R
Breast cancer 1.04 (0.94-1.15); 0.458 0.274, 22.9% F
Hepatocellular carcinoma 1.17 (0.99-1.38); 0.057 0.026, 60.7% R
Prostate cancer 1.00 (0.79-1.26); 0.976 0.027, 63.5% R
Colorectal cancer 1.02 (0.92-1.13); 0.737 0.001, 67.9% R
Gastric cancer 1.30 (1.16-1.47); < 0.001 0.209, 33.9% F
Pancreatic cancer 1.66 (1.11-2.47); 0.013 < 0.001, 88.1% R
Esophageal cancer 0.99 (0.80-1.23); 0.936 0.003, 67.9% R
Lymphoma 1.02 (0.88-1.19); 0.752 0.608, 0.0% F
Other cancers 1.09 (1.02-1.16); 0.011 0.170, 27.2% F
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F indicates fixed model; R indicates random model.

Figure 2.

Figure 2

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Meta-analysis of COX-2 -1195G>A polymorphism and cancer risk in Asians: allele comparing model.

Table 5.

Meta-analysis of COX-2 -1195G>A polymorphisms and cancer risk in a sub-group analysis by cancer system

Genetic comparison Cancer system OR (95% CI); P Test of heterogeneity
(p-Value, I2) Model
AA+GA vs. GG All 1.14 (1.04-1.25); 0.007 < 0.001, 43.4% R
Reproductive and breast cancer 1.11 (0.88-1.39); 0.374 0.700, 0.0% F
Digestive system cancer 1.22 (1.06-1.39); 0.004 < 0.001, 57.8% R
Urogenital cancer 1.00 (0.83-1.21); 0.999 0.555, 0.0% F
hematological malignancy 1.08 (0.88-1.33); 0.445 0.903, 0.0% F
Respiratory system cancer 1.01 (0.77-1.33); 0.919 0.320, 0.0% F
Other system cancer 0.88 (0.67-1.16); 0.364 0.466, 0.0% F
AA vs. GA+GG All 1.11 (1.04-1.18); 0.003 < 0.001, 56.5% R
Reproductive and breast cancer 1.03 (0.90-1.17); 0.665 0.316, 15.1% F
Digestive system cancer 1.14 (1.04-1.26); 0.008 < 0.001, 68.6% R
Urogenital cancer 0.99 (0.79-1.24); 0.923 0.090, 45.3% R
hematological malignancy 1.05 (0.92-1.20); 0.487 0.811, 0.0% F
Respiratory system cancer 1.09 (0.90-1.32); 0.359 0.915, 0.0% F
Other system cancer 1.21 (1.02-1.42); 0.026 0.563, 0.0% F
AA vs. GG All 1.21 (1.07-1.36); 0.002 < 0.001, 54.4% R
Reproductive and breast cancer 1.14 (0.88-1.47); 0.316 0.551, 0.0% F
Digestive system cancer 1.31 (1.10-1.57); 0.003 < 0.001, 67.0% R
Urogenital cancer 1.06 (0.83-1.35); 0.624 0.302, 16.8% F
hematological malignancy 1.12 (0.89-1.42); 0.343 0.870, 0.0% F
Respiratory system cancer 1.03 (0.76-1.41); 0.832 0.353, 0.0% F
Other system cancer 0.97 (0.71-1.31); 0.821 0.420, 0.0% F
GA vs. GG All 1.09 (1.00-1.18); 0.045 0.073, 22.2% R
Reproductive and breast cancer 1.07 (0.85-1.36); 0.556 0.784, 0.0% F
Digestive system cancer 1.15 (1.02-1.30); 0.018 0.008, 40.4% R
Urogenital cancer 0.99 (0.81-1.22); 0.951 0.819, 0.0% F
hematological malignancy 1.06 (0.85-1.32); 0.597 0.917, 0.0% F
Respiratory system cancer 0.98 (0.73-1.30); 0.876 0.256, 22.5% F
Other system cancer 0.81 (0.61-1.07); 0.143 0.543, 0.0% F
A vs. G All 1.09 (1.03-1.15); 0.002 < 0.001, 63.9% R
Reproductive and breast cancer 1.04 (0.94-1.15); 0.458 0.274, 22.9% F
Digestive system cancer 1.13 (1.04-1.22); 0.003 < 0.001, 74.3% R
Urogenital cancer 0.99 (0.84-1.16); 0.871 0.063, 49.8% R
hematological malignancy 1.05 (0.95-1.16); 0.370 0.822, 0.0% F
Respiratory system cancer 1.05 (0.92-1.21); 0.471 0.891, 0.0% F
Other system cancer 1.08 (0.96-1.23); 0.206 0.302, 17.7% F
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F indicates fixed model; R indicates random model.

Figure 3.

Figure 3

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Meta-analysis of COX-2 -1195G>A polymorphism and cancer risk in digestive cancer system: allele comparing model.

Publication bias

Results of Funnel plots and the Egger’s test indicated that there was no publication bias in this meta-analysis (A vs. G: Begg’s test P = 0.872, Egger’s test P = 0.372; AA vs. GG: Begg’s test P = 0.862, Egger’s test P = 0.981; GA vs. GG: Begg’s test P = 0.872, Egger’s test P = 0.908; AA+GA vs. GG: Begg’s test P = 0.995, Egger’s test P = 0.875; AA vs. GA+GG: Begg’s test P = 0.717, Egger’s test P = 0.088; Figure 4).

Figure 4.

Figure 4

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Begg’s funnel plot analysis for publication bias in overall cancer: allele comparing model.

Sensitivity analyses

Nonparametric “trim-and-fill” method was performed to determine the reliability of our results. The adjusted ORs and CIs were not qualitatively altered, which demonstrated COX-2 -1195G>A polymorphism might be a risk factor for overall cancer risk (A vs. G: adjusted pooled OR = 1.09, 95% CI: 1.03-1.15, P = 0.002; AA vs. GG: adjusted pooled OR = 1.21, 95% CI: 1.07-1.36, P = 0.002; AA+GA vs. GG: adjusted pooled OR = 1.14, 95% CI: 1.04-1.25, P = 0.007; AA vs. GA+GG: adjusted pooled OR = 1.09, 95% CI: 1.02-1.18, P = 0.014; GA vs. GG: adjusted pooled OR = 1.09, 95% CI: 1.00-1.18, P = 0.045; Figure 5).

Figure 5.

Figure 5

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Filled funnel plot of meta-analysis in overall cancer: allele comparing model.

Heterogeneity

Significant heterogeneity was obvious in each model among the recruited studies. Sub-group analyses were conducted to explore the source of heterogeneity. The results supported that publications conducted in Asians, Caucasians, colorectal cancer, hepatocellular carcinoma, prostate cancer, gastric cancer, pancreatic cancer, esophageal cancer and digestive system cancer might contribute to the major origin of heterogeneity.

Discussion

In the current meta-analysis, the results indicated that the COX-2 -1195G>A variants increased cancer risk, especially for gastric cancer, pancreatic cancer, hepatocellular carcinoma and other cancers, such effect was still found in subgroup of digestive system cancer, other system cancer and Asians. Further investigations of the functional interpretation are warranted to comprehend the mechanisms for our results.

The COX-2 gene is located on chromosome 1q25.2-3 and is composed of ten exons that encode different functional domains. In 5’ region, there are several response elements, such as activation protein-2, nuclear factor kB, transforming growth factor, stimulatory protein-1 and cyclic adenosine monophosphate binding sites [72]. Mutation in these regulatory elements might alter gene transcription. As an example, a locus in one of the COX-2 promoter regions might change binding capacity for certain nuclear proteins, which suggested to be associated with the level of COX-2 expression [72]. A previous report showed that COX-2 -1195G>A variant modified the transcription of the COX-2 promoter, leading to several fold greater expression of COX-2 [73]. Combined with our results, these findings demonstrated that the -1195G>A mutation in COX-2 increased the risk of cancer, perhaps by modifying binding capacity for certain nuclear proteins and promoting the expression of COX-2 gene.

Since cancer types might affect the findings of meta-analysis, subgroup analysis was carried out. The results highlighted that COX-2 -1195G>A polymorphism was associated with the risk of gastric cancer, pancreatic cancer, hepatocellular carcinoma and other cancers, but not of esophageal cancer, colorectal cancer, prostate cancer, breast cancer or lymphoma, which was consistent with previous meta-analysis [74-76]. However, these results should be explained with very caution. In some subgroups, only three or four studies were recruited for analysis, which might have insufficient power to obtain a reliable result. Therefore, these correlations need to be further confirmed or refuted in larger size, well-designed studies. Because race could also affect the findings, we conducted subgroup analysis. Our results demonstrated the COX-2 -1195G>A polymorphism was associated with an increased cancer risk in Asians but not in Caucasians or mixed populations. While in Africans subgroup, a borderline evidence of association between the COX-2 -1195G>A polymorphism and cancer risk was identified. Considering only two moderate sample size studies were included and the findings might be due to fluke. Further studies should be performed to confirm the possible effects of COX-2 -1195G>A polymorphism. In the current meta-analysis, the correlations observed in different system were analyzed as well. The results suggested that COX-2 -1195G>A polymorphism was associated with the risk of digestive system cancer, which was consistent with previous study [16].

Compared with the previous meta-analyses, some advantages of current study should be adequately addressed. First of all, it updated all eligible data for COX-2 -1195G>A polymorphism and the risk of cancer. Then, our results corroborated COX-2 -1195G>A polymorphism effected on pancreatic cancer for the first time. Finally, the methodological issues in pooled analysis (e.g., publication bias, sensitivity and heterogeneity), were all well explored. Although the primary results were stable and suggestive, there were some limitations of this analysis, which should be considered when interpreting the results. First of all, in some subgroup, only two or three eligible case-control studies were recruited; therefore, in these subgroups, the results might be a fluke. For example, in Africans, a borderline evidence of association between the COX-2 -1195G>A polymorphism and cancer risk was identified. In our study, however, only two studies were included, which might have limited the power to get an accurate result. Second, the eligible studies included only published studies, which might lead to bias, although the statistical data did not show it. Thirdly, large inter-study heterogeneity was observed in overall and some subgroups, which meant explanation of our results, should be very cautious. This could be due to other diversities between investigations, such as gender, age, specified type of cancer, ethnicity variations, smoking, drinking, non-steroidal anti-inflammatory drug use, different lifestyle factors, other environmental risk factors, selection criteria of subjects, and socio-economic factors as well. For lack of access to original data from the reviewed publications, these factors were not considered. Finally, the data of GWAS were not available; the power of the results might be limited.

In conclusion, the investigation of the relationship between COX-2 -1195G>A polymorphisms and cancer risk is very popular but controversial at present. Our results support that COX-2 -1195G>A polymorphism is associated with an increased risk of cancer, especially, in gastric cancer, pancreatic cancer, hepatocellular carcinoma, digestive system cancer and Asians subgroups. In the future, more large-scale and well-designed epidemiological studies are warranted to validate or refute these findings.

Acknowledgements

This study was supported in part by Jiangsu Province Natural Science Foundation (BK2010333, BK2011481).

Disclosure of conflict of interest

None.

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