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International Journal of Clinical and Experimental Pathology logoLink to International Journal of Clinical and Experimental Pathology
. 2017 Sep 1;10(9):9527–9540.

Association between glutathione peroxidase-1 (GPX1) Rs1050450 polymorphisms and cancer risk

Chengdi Wang 1,*, Rui Zhang 1,*, Nan Chen 2, Lan Yang 1, Yinsu Wang 2, Yan Sun 2, Lin Huang 2, Min Zhu 1, Yulin Ji 1, Weimin Li 1
PMCID: PMC6965984  PMID: 31966829

Abstract

Glutathione peroxidase (GPX), one of the antioxidant enzymes, exerts a vital role in reducing oxidative damage. GPX1 Pro198Leu (rs1050450) polymorphism has been reported in the development of several cancers, while the results were inconsistent. We thus conducted this meta-analysis to identify the association between GPX1 (rs1050450) polymorphism and cancer risk. 52 eligible publications with 60 case-control studies were included, with 21,296 cancer patients and 30,346 controls. The results in total population suggested there was a significant association between GPX1 (rs1050450) polymorphism and cancer susceptibility in part genetic models (TT vs CT+CC: OR = 1.15, 95% CI = 1.01-1.32, P = 0.042; TT vs CC: OR = 1.15, 95% CI = 1.00-1.31, P = 0.044; T vs C: OR = 1.09, 95% CI = 1.01-1.17, P = 0.02). The stratified analysis by cancer types suggested a positive correlation between GPX1 (rs1050450) polymorphism and the development of bladder cancer (TT+CT vs CC: OR = 1.72, 95% CI = 1.09-2.70, P = 0.019; TT vs CT+CC: OR = 3.56, 95% CI = 1.42-8.94, P = 0.007; TT vs CC: OR = 3.75, 95% CI = 1.41-9.94, P = 0.008; T vs C: OR = 1.941, 95% CI = 1.17-3.22, P = 0.01) as well as head and neck cancer (TT vs CT+CC: OR = 2.19, 95% CI = 1.39-3.46, P = 0.001) and brain cancer (TT+CT vs CC: OR = 1.19, 95% CI = 1.03-1.37, P = 0.018). These results support that GPX1 (rs1050450) polymorphism might be a candidate marker for cancer risk with type-specific effects.

Keywords: Glutathione peroxidase-1, rs1050450, polymorphism, cancer, susceptibility

Introduction

Cancer is an increasingly leading cause of death and is considered as a severe health burden in both developing and developed countries [1]. A variety of underlying mechanisms have been confirmed to demonstrate the carcinogenesis process and imbalance of oxidative stress [2]. Oxidation has been proved to participate in quite a few pathogenic processes, including anti-infection process, aging, carcinogenesis, metastasis and angiogenesis [3].

During these processes, previous evidence has demonstrated that reactive oxygen species (ROS)-mediated oxidative damage played a critical role, which initiated a storm of free radical cascade and subsequently caused indirect damage to cellular component, leading to denaturing and dysfunction of proteins [4], saturation and structural modification of certain lipids and DNA strains breaking [5]. Because most of these damages were irreversible and fatal, oxidative stress might decrease the genome stability and thus increase the possibility of tumorgenesis.

Anti-oxidative system plays a key role in preventing catastrophic oxidative storm in our body and it works as a balanced cycle. With the consumption of reductive species, certain enzyme families recycle to restore these reductive active molecules. Glutathione peroxidase (GPX) family is one of those anti-oxidative enzyme families, among which GPX1, encoded by GPX1 gene in humans and locating on chromosome 3, is the most abundant one functioning in the detoxification of hydrogen peroxide [6].

Multiple single nucleotide polymorphisms (SNPs) have been identified in the DNA sequences of GPX1 gene, however, only the Pro198Leu (also known as rs1050450, noted in NCBI database as position 200 and it has also been recorded to at position 197) polymorphism has been extensively investigated. Previous studies have demonstrated the association between low level of circulating GPX1 and increased risk of cancer, which was found in several types of cancers including breast cancer [7,8], lung cancer [9], prostate cancer [10], and colorectal cancer [11]. As with the presumption, GPX1 Pro198Leu (C>T) polymorphism affected GPX1 activity, which might further play an important role in cancer development. However, possible relationships between GPX1 polymorphism and cancer have been studied only in separate types of cancer with conflicting results. Thus, we conducted a comprehensive meta-analysis to explore the association of GPX1 Pro198Leu (rs1050450) polymorphism with risk for cancer and investigated each individual tumor in subgroup analysis.

Methods

Study selection

PubMed, Embase, Science Direct, and Cochrane Library were searched on October 17, 2016 using the mesh terms: “glutathione peroxidase1 or GPX1”, “polymorphism or variant or mutation” and “cancer or carcinoma or malignancy”. There was no language restriction. All searched results underwent abstract review and potentially eligible studies were reviewed through whole text. Additional potential eligible studies regarding this topic were identified through the references in retrieved articles.

Inclusion and exclusion criteria

In our meta-analysis, we used the following inclusion criteria: (1) case-control studies or cohort studies, (2) studies investigating the relationship between GPX1 (rs1050450) polymorphism and cancer risk, and (3) Odds ratio (OR) with 95% confidence interval (CI) being applied to assess the strength of association. Studies were excluded if they met the following criteria: (1) in vitro studies or review articles, (2) duplicated publications, and (3) reports with incomplete data. If studies used overlapped cases, only the study with the largest sample size was enrolled.

Data extraction

Two investigators extracted all data independently, and a consensus was reached prior to further process. For one publication with several cancer types, each type was treated separately. From each study, the following basic characteristics were extracted: first author’s name, year of publication, country of origin, ethnicity of the study population, source of control groups (population-based or hospital-based controls), genotyping methods, total number of cancer cases and controls, and genotype distributions of cases and controls.

Statistical analysis

The following genotype contrasts were evaluated: dominate genetic model (CT+TT vs CC), recessive genetic model (TT vs CT+CC), homozygote comparison (TT vs CC), heterozygote comparison (CT vs CC), and allele comparison (T vs C). The association between GPX1 Pro198Leu polymorphism and cancer risk was measured using the odds ratio (OR) with 95% confidence interval (95% CI). The significance of the pooled OR was determined by the Z test and P value less than 0.05 indicated that the result was of statistical significance. In addition, subgroup analysis according to cancer types and ethnicity were performed. In terms of heterogeneity, P<0.10 or I2>50% represented that heterogeneity existed in pooled ORs. When homogeneity was acceptable (P≥0.10, I2≤50%), a fixed-effects model was applied to secondary analysis; otherwise, a random-effects model was used [12,13]. Publication bias was assessed by Begg’s funnel plot and Egger’s linear regression test. We also further performed sensitivity analysis to evaluate the stability of our results. All P values were two-sided. All analyses were performed using STATA 12.0 (STATA Corporation, College Station, TX).

Results

Characteristics of eligible studies

According to our searching strategy, a total of 52 publications with 60 case-control studies were included in this meta-analysis, with 21,296 cancer patients and 30,346 controls. The study selection process was shown in (Figure 1). The baseline characteristics of included studies and genotype distributions were summarized in Tables 1 and 2. These 60 case-control studies were published from 2000 to 2016, among which there were 11 studies regarding prostate cancer, 10 studies on breast cancer, 6 studies about brain tumors (including acoustic neuroma, glioma, glioblastoma, multiforme, and meningioma), 6 studies on lung cancer, 5 studies regarding bladder cancer, 5 studies on colorectal cancer, 4 studies regarding skin cancer (including basal cell carcinoma, squamous cell carcinoma, and melanoma), 4 studies on non-Hodgkin lymphoma (NHL), 2 studies about hepatocellular carcinoma, 1 study on gastric cancer, 2 studies on myeloid leukemia, 3 studies regarding head and neck cancer (including laryngeal cancer and oral cavity cancer), and 1 study on pancreatic cancer. In all 52 included publications, 40 reports were analyzing Caucasian, 6 reports from Asian, 2 reports of African-Americans, and 12 reports of mixed ethnicity. Diverse genotyping methods were used in the included studies, various from polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), TaqMan, general PCR, and Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI/TOF).

Figure 1.

Figure 1

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Flow chart of study selection in this meta-analysis.

Table 1.

Baseline characteristics of eligible studies

First Author No.# Year Country Ethnicity Source of Controls Sample Quality Control Control Health Cancer Type Case/Control Genotyping method HWE
Abe [14] 2011 USA Caucasian PB Blood NA NA Prostate cancer 356/745 PCR Yes
Ahn [15] 2005 USA Caucasian PB Blood Yes NA Breast cancer 1038/1088 MALDI-TOF Yes
Arsova-Sarafinovska [10] 2009 Macedonia Caucasian HB Blood NA NA Prostate cancer 82/123 PCR Yes
Aynali [16] 2013 Turkey Caucasian HB Blood NA Health Laryngeal cancer 25/23 PCR No
Banescu [17] 2014 Romania Caucasian HB Blood NA Health CML 168/321 PCR-RFLP Yes
Banescu [18] 2016 Romania Caucasian HB Blood NA Health AML 102/303 PCR-RFLP No
Bhatti [19] 1 2009 USA Caucasian HB Blood Yes Unhealth Glioma 327/457 TaqMan NA
Bhatti [19] 2 2009 USA Caucasian HB Blood Yes Unhealth Glioblastoma multiforme 157/457 TaqMan NA
Bhatti [19] 3 2009 USA Caucasian HB Blood Yes Unhealth Meningioma 121/457 TaqMan NA
Cebrian [20] 2006 UK Caucasian PB Blood Yes NA Breast cancer 2293/2278 TaqMan Yes
Cheng [21] 2011 USA Mixed PB Blood NA NA Prostate cancer 150/761 PCR NA
Choi [22] 1 2007 USA Caucasian PB Blood Yes Health Prostate cancer 452/1221 MALDI-TOF Yes
Choi [22] 2 2007 USA African American PB Blood Yes Health Prostate cancer 29/119 MALDI-TOF Yes
Cox [23] 2004 USA Caucasian PB Blood NA NA Breast cancer 1323/1910 TaqMan Yes
Erdem [24] 2012 Turkey Caucasian HB Blood NA NA Prostate cancer 33/91 PCR Yes
Ermolenko [25] 2010 Russia Caucasian HB Blood NA NA Breast cancer 927/474 PCR TaqMan Yes
Ezzikouri [26] 2010 France Caucasian HB Blood Yes Health (163) HCV(59) Hepatocellular carcinoma 96/222 PCR-RFLP Yes
Goerlitz [27] 2011 Egypt Caucasian PB NA Yes NA Bladder Cancer 625/626 TaqMan Yes
Hansen [28] 2005 Norway Caucasian PB Blood NA NA Colorectal cancer 166/397 PCR Yes
Hansen [11] 2009 Denmark Caucasian PB Blood Yes NA Colorectal cancer 375/779 PCR Yes
He [29] 1 2010 USA Caucasian PB NA NA NA Melanoma 207/809 TaqMan Yes
He [29] 2 2010 USA Caucasian PB NA NA NA SCC 257/809 TaqMan Yes
He [29] 3 2010 USA Caucasian PB NA NA NA BCC 281/809 TaqMan Yes
Hu [8] 2003 Canada African American PB Blood Yes NA Breast cancer 79/517 PCR Yes
Hu [30] 2004 USA Mixed HB Blood NA NA Head and neck cancer 133/517 PCR Yes
Hu [31] 2005 USA Mixed HB Blood Yes NA Colon cancer 53/53 PCR Yes
Ichimura [32] 2004 Japan Asian HB Blood Yes Health Bladder cancer 213/209 PCR-RFLP Yes
Jablonska [33] 2015 Poland Caucasian HB Blood Yes Health Breast cancer 136/183 PCR Yes
Karunasinghe [34] 2013 New Zealand Mixed HB Blood NA Health Prostate cancer 410/441 PCR Yes
Knight [35] 2004 Canada Caucasian PB Blood NA NA Breast cancer 399/372 TaqMan Yes
Kucukgergin [36] 1 2011 Turkey Caucasian HB Blood NA Health Prostate cancer 134/159 PCR-RFLP Yes
Kucukgergin [37] 2 2012 Turkey Caucasian HB Blood NA Health Bladder cancer 157/224 PCR-RFLP Yes
Lan [38] 2007 USA Caucasian PB Blood Yes NA NHL 449/520 PCR No
Lee [39] 2006 Korea Asian HB Blood NA NA Lung cancer 200/200 PCR Yes
Lightfoot [40] 1 2006 UK Caucasian PB Blood NA NA NHL-UK 620/762 TaqMan Yes
Lightfoot [40] 2 2006 USA Caucasian PB Blood NA NA NHL-USA 308/684 TaqMan Yes
Meplan [41] 2013 Denmark Caucasian PB Blood NA NA Breast cancer 933/959 PCR Yes
Meplan [42] 2010 Czech Caucasian HB Blood Yes Health Colorectal cancer 681/637 PCR No
Oskina NA [43] 2014 Russia Caucasian HB Blood NA NA Prostate cancer 361/326 TaqMan Yes
Parlaktas [44] 2015 Turkey Caucasian HB Blood NA Health Prostate cancer 49/49 PCR Yes
Paz-y-Miño [45] 2010 Ecuador Mixed PB Blood NA NA Bladder cancer 97/120 PCR-RFLP Yes
Peters [46] 2008 USA Mixed PB Blood Yes NA Colorectal cancer 772/777 TaqMan Yes
Raaschou-Nielsen [9] 2007 Denmark Caucasian PB Blood NA NA Lung cancer 432/798 PCR Yes
Rajaraman [47] 1 2008 USA Mixed HB Blood Yes Unhealth Acoustic neuroma 69/494 TaqMan Yes
Rajaraman [47] 2 2008 USA Mixed HB Blood Yes Unhealth Meningioma 134/494 TaqMan Yes
Rajaraman [47] 3 2008 USA Mixed HB Blood Yes Unhealth Glioma 362/494 TaqMan Yes
Ratnasinghe [48] 2000 Finland Caucasian PB Blood Yes NA Lung cancer 315/313 TaqMan Yes
Ravn-Haren [7] 2006 Denmark Caucasian PB Blood Yes NA Breast cancer 377/377 PCR Yes
Reszka [49] 2009 Poland Caucasian HB Blood NA Health Bladder cancer 33/47 PCR Yes
Rosenberger [50] 2008 Germany Caucasian PB Blood Yes NA Lung cancer 186/207 MALDI-TOF Yes
Skuladottir [51] 2005 Denmark Caucasian PB Blood NA NA Lung cancer 320/618 PCR NA
Steinbrecher [52] 2010 Germany Caucasian PB Blood NA Health Prostate cancer 248/492 MALDI-TOF Yes
Su [53] 2015 China Asian HB Blood Yes NA Hepatocellular carcinoma 434/480 PCR-RFLP Yes
Tang [54] 2010 USA Mixed HB Blood NA Health Pancreatic cancer 575/648 PCR Yes
Tsai [55] 2012 China Asian HB Blood Yes Health Breast cancer 260/224 PCR No
Vogel [56] 2004 Denmark Caucasian PB Blood NA NA Basal Cell Carcinoma 317/317 PCR Yes
Wang [57] 2008 China Asian HB Blood NA NA Gastric cancer 361/363 PCR-RFLP Yes
Wang [58] 2006 USA Mixed PB Blood Yes NA NHL 740/636 TaqMan Yes
Wu [59] 2010 China Asian HB Blood NA Health Oral cavity cancer 122/122 PCR Yes
Yang [4] 2004 USA Mixed HB Blood Yes NA Lung cancer 237/234 PCR No
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#

number of data separately reported by articles.

HWE, Hardy-Weinberg equilibrium; MALDI-TOF, Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry; PCR, polymerase chain reaction; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; PB, population-based; HB, hospital-based; NA, not available; CML, Chronic myeloid leukemia; NHL, non-Hodgkin lymphoma; BCC, Basal cell carcinoma; SCC, Squamous cell carcinoma.

Table 2.

Genotype frequency distribution of GPX1 gene polymorphism

First Author No.# Ethnicity Cancer Type System Case Control HWE
TT CC CT TT CC CT
Abe [14] Caucasian Prostate cancer Prostate cancer 169 137 50 340 314 91 Yes
Ahn [15] Caucasian Breast cancer Breast cancer 472 456 110 523 453 112 Yes
Arsova-Sarafinovska [10] Caucasian Prostate cancer Prostate cancer 54 17 11 57 47 19 Yes
Aynali [16] Caucasian Laryngeal cancer Head and neck cancer 0 23 2 0 20 3 No
Banescu [17] Caucasian CML Hematological malignancies 16 118 34 34 203 84 Yes
Banescu [18] Caucasian AML Hematological malignancies 3 28 71 34 190 79 No
Bhatti [19] 1 Caucasian Glioma Brain cancer 158 169 236 221 NA
Bhatti [19] 2 Caucasian Glioblastoma multiforme Brain cancer 74 83 236 221 NA
Bhatti [19] 3 Caucasian Meningioma Brain cancer 55 66 236 221 NA
Cebrian [20] Caucasian Breast cancer Breast cancer 1109 964 220 1066 993 219 Yes
Cheng [21] Mixed Prostate cancer Prostate cancer 49 53 371 342 NA
Choi [22] 1 Caucasian Prostate cancer Prostate cancer 227 190 35 616 515 90 Yes
Choi [22] 2 African American Prostate cancer Prostate cancer 12 15 2 51 53 15 Yes
Cox [23] Caucasian Breast cancer Breast cancer 581 515 133 774 694 161 Yes
Erdem [24] Caucasian Prostate cancer Prostate cancer 11 17 5 40 41 10 Yes
Ermolenko [25] Caucasian Breast cancer Breast cancer 452 375 100 192 230 52 Yes
Ezzikouri [26] Caucasian Hepatocellular carcinoma Digestive system cancer 50 32 14 108 88 26 Yes
Goerlitz [27] Caucasian Bladder Cancer Bladder Cancer 330 236 46 326 254 38 Yes
Hansen [28] 1 Caucasian Colorectal cancer Digestive system cancer 82 68 16 196 163 38 Yes
Hansen [11] 2 Caucasian Colorectal cancer Digestive system cancer 173 164 38 342 348 89 Yes
He [29] 1 Caucasian Melanoma Skin cancer 94 86 27 419 327 63 Yes
He [29] 2 Caucasian SCC Skin cancer 128 107 22 419 327 63 Yes
He [29] 3 Caucasian BCC Skin cancer 141 124 16 419 327 63 Yes
Hu [30] African American Breast cancer Breast cancer 36 25 18 244 209 64 Yes
Hu [30] Mixed Head and neck cancer Head and neck cancer 69 30 34 244 209 64 Yes
Hu [31] Mixes Colon cancer Digestive system cancer 33 15 5 24 26 3 Yes
Ichimura [32] Asian Bladder cancer Bladder cancer 166 47 0 187 22 0 Yes
Jablonska [33] Caucasian Breast cancer Breast cancer 73 51 12 75 85 23 Yes
Karunasinghe [34] Mixed Prostate cancer Prostate cancer 122 110 30 216 186 33 Yes
Knight [35] Caucasian Breast cancer Breast cancer 192 171 34 169 164 39 Yes
Kucukgergin [36] 1 Caucasian Prostate cancer Prostate cancer 32 62 40 78 61 20 Yes
Kucukgergin [37] 2 Caucasian Bladder cancer Bladder cancer 63 64 30 117 87 20 Yes
Lan [38] Caucasian NHL Hematological malignancies 215 191 43 261 200 59 No
Lee [39] Asian Lung cancer Lung cancer 116 84 0 154 46 0 Yes
Lightfoot [40] 1 Caucasian NHL-UK Hematological malignancies 311 259 43 438 268 55 Yes
Lightfoot [40] 2 Caucasian NHL-USA Hematological malignancies 142 128 38 335 283 65 Yes
Meplan [41] Caucasian Breast cancer Breast cancer 465 396 72 503 370 86 Yes
Meplan [42] Caucasian Colorectal cancer Digestive system cancer 354 306 21 355 259 23 No
Oskina NA [43] Caucasian Prostate cancer Prostate cancer 183 146 32 153 132 41 Yes
Parlaktas [44] Caucasian Prostate cancer Prostate cancer 27 16 6 24 17 8 Yes
Paz-y-Miño [45] Mixed Bladder cancer Bladder cancer 28 19 50 73 42 5 Yes
Peters [46] Mixed Colorectal cancer Digestive system cancer 351 288 77 355 331 57 Yes
Raaschou-Nielsen [9] Caucasian Lung cancer Lung cancer 209 184 39 348 358 92 Yes
Rajaraman [47] 1 Mixed Acoustic neuroma Brain cancer 28 30 7 236 178 46 Yes
Rajaraman [47] 2 Mixed Meningioma Brain cancer 57 56 10 236 178 46 Yes
Rajaraman [47] 3 Mixed Glioma Brain cancer 165 140 35 236 178 46 Yes
Ratnasinghe [48] Caucasian Lung cancer Lung cancer 91 157 67 132 135 46 Yes
Ravn-Haren [7] Caucasian Breast cancer Breast cancer 176 168 33 205 136 36 Yes
Reszka [49] Caucasian Bladder cancer Bladder cancer 13 15 5 27 18 1 Yes
Rosenberger [50] Caucasian Lung cancer Lung cancer 114 63 9 97 89 21 Yes
Skuladottir [51] Caucasian Lung cancer Lung cancer 50 69 172 185 NA
Steinbrecher [52] Caucasian Prostate cancer Prostate cancer 123 108 16 264 181 42 Yes
Su [53] Asian Hepatocellular carcinoma Digestive system cancer 371 19 0 454 27 0 Yes
Tang [54] Mixed Pancreatic cancer Digestive system cancer 263 240 49 316 242 58 Yes
Tsai [55] Asian Breast cancer Breast cancer 247 13 0 166 58 0 No
Vogel [56] Caucasian Basal Cell Carcinoma Skin cancer 150 136 31 151 139 27 Yes
Wang [57] Asian Gastric cancer Digestive system cancer 315 44 2 326 35 2 Yes
Wang [58] Mixed NHL Hematological malignancies 360 310 70 291 284 61 Yes
Wu [59] Asian Oral cavity cancer Head and neck cancer 108 12 0 112 10 0 Yes
Yang [4] Mixed Lung cancer Lung cancer 111 98 20 114 85 29 No
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#

number of data separately reported by articles.

HWE, Hardy-Weinberg equilibrium; CML, Chronic myeloid leukemia; AML, Acute myeloid leukemia; NHL, non-Hodgkin lymphoma; BCC, Basal cell carcinoma; SCC, Squamous cell carcinoma.

Pooled analysis

When all collected data were pooled into the meta-analysis, results showed that significant associations were found regarding to the following three genetic models (TT vs CT+CC: OR = 1.15, 95% CI = 1.01-1.32, P = 0.042; TT vs CC: OR = 1.15, 95% CI = 1.00-1.31, P = 0.044; T vs C: OR = 1.09, 95% CI = 1.01-1.17, P = 0.02), respectively (Figure 2). As for stratified analyses by cancer types, HWE and ethnicity, the pooled ORs for additive model and recessive model comparison suggested GPX1 (rs1050450) polymorphism was significantly associated with an increased risk of bladder cancer (TT+CT vs CC: OR = 1.72, 95% CI = 1.09-2.70, P = 0.019; TT vs CT+CC: OR = 3.56, 95% CI = 1.42-8.94, P = 0.007; TT vs CC: OR = 3.75, 95% CI = 1.41-9.94, P = 0.008; T vs C: OR = 1.94, 95% CI = 1.17-3.22, P = 0.01), and a relative association was found in head and neck cancer (TT vs CT+CC: OR = 2.19, 95% CI = 1.39-3.46, P = 0.001) and brain cancer (TT+CT vs CC: OR = 1.19, 95% CI = 1.03-1.37, P = 0.018). However, in prostate cancer, breast cancer, NHL, lung cancer and digestive system cancer, significant association was not found in any genetic model (all P>0.05). The association between GPX1 rs1050450 polymorphism and susceptibility to cancer was further proved in subgroup with controls consistent with Hardy-Weinberg equilibrium (TT+CT vs CC: OR = 1.07, 95% CI = 1.00-1.15, P = 0.041; T vs C: OR = 1.08, 95% CI = 1.01-1.15, P = 0.025). In subgroup analysis stratified by ethnicity, no associations were appreciated in Caucasian population (OR = 1.06, 95% CI = 0.98-1.15, P = 0.132), Asians (OR = 1.04, 95% CI = 0.47-2.30, P = 0.915), African-Americans (OR = 1.066, 95% CI = 0.71-1.61, P = 0.76), or mixed ethnicity population (OR = 1.11, 95% CI = 0.94-1.30, P = 0.216). The main results of the meta-analysis were summarized in Table 3.

Figure 2.

Figure 2

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Forest plot for the association between the GPX1 rs1050450 polymorphism and cancer risk (T vs C). We detected significant association between the GPX1 rs1050450 polymorphism and cancer susceptibility.

Table 3.

The results of evidence synthesis in this meta-analysis

Variables Dominant model (TT+CT vs CC) Recessive model (TT vs CT+CC) Homozygote model (TT vs CC) Heterozygote model (CT vs CC) Allel contrast model (T vs C)
OR (95% CI) P I2 (%) OR (95% CI) P I2 (%) OR (95% CI) P I2 (%) OR (95% CI) P I2 (%) OR (95% CI) P I2 (%)
All 1.08 (1.00-1.17) 0.051 70.50 1.15 (1.01-1.32) 0.042 72.00 1.15 (1.00-1.31) 0.044 66.60 1.03 (0.95-1.12) 0.42 67.80 1.09 (1.01-1.17) 0.02 79.90
By cancer type
    Prostate cancer 1.07 (0.87-1.32) 0.512 67.80 1.10 (0.81-1.48) 0.546 55.50 1.12 (0.77-1.64) 0.556 69.30 1.04 (0.84-1.29) 0.694 61.20 1.06 (0.87-1.28) 0.573 75.70
    Breast cancer 0.87 (0.72-1.05) 0.132 85.60 0.98 (0.88-1.09) 0.711 0.00 0.97 (0.86-1.09) 0.57 0.00 0.87 (0.71-1.06) 0.163 86.10 0.91 (0.80-1.04) 0.148 82.40
    Head and neck cancer 0.88 (0.62-1.25) 0.491 0.00 2.19 (1.39-3.46) 0.001 52.30 NA NA NA 0.73 (0.31-1.74) 0.482 67.90 1.17 (0.91-1.51) 0.215 0.00
    Hematological malignancies 1.13 (0.94-1.37) 0.203 55.70 1.29 (0.73-2.30) 0.383 91.00 1.20 (0.82-1.76) 0.341 69.10 1.11 (0.99-1.25) 0.082 37.00 1.22 (0.95-1.57) 0.125 88.30
    Brain cancer 1.19 (1.03-1.37) 0.018 0.00 0.98 (0.69-1.39) 0.886 0.00 1.07 (0.74-1.54) 0.735 0.00 1.22 (0.98-1.52) 0.082 0.00 1.1 (0.94-1.29) 0.244 0.00
    Digestive system cancer 1.02 (0.93-1.13) 0.65 7.90 1.07 (0.89-1.29) 0.464 0.00 1.06 (0.87-1.29) 0.559 0.00 1.01 (0.91-1.12) 0.803 35.10 1.03 (0.95-1.11) 0.507 0.00
    Bladder cancer 1.72 (1.09-2.70) 0.019 82.70 3.56 (1.42-8.94) 0.007 87.40 3.75 (1.41-9.94) 0.008 87.80 1.24 (0.89-1.74) 0.203 62.10 1.94 (1.17-3.22) 0.01 91.90
    Skin cancer 1.11 (0.96-1.28) 0.175 0.00 1.15 (0.89-1.49) 0.293 49.10 1.19 (0.91-1.56) 0.202 48.20 1.09 (0.94-1.27) 0.275 0.00 1.09 (0.97-1.22) 0.132 14.70
    Lung cancer 1.17 (0.79-1.75) 0.431 87.00 0.82 (0.49-1.37) 0.445 73.90 0.82 (0.41-1.66) 0.588 84.70 1.19 (0.77-1.86) 0.433 86.80 1.07 (0.74-1.55) 0.709 89.60
By ethnicity
    Caucasian 1.06 (0.98-1.15) 0.132 63.80 1.08 (0.94-1.25) 0.276 68.20 1.08 (0.94-1.24) 0.304 62.30 1.04 (0.96-1.12) 0.362 57.60 1.06 (0.98-1.14) 0.139 75.60
    Mixed 1.11 (0.94-1.30) 0.216 64.30 1.44 (0.98-2.11) 0.067 82.00 1.41 (0.98-2.04) 0.065 78.20 0.99 (0.85-1.16) 0.943 53.80 1.19 (0.98-1.45) 0.077 85.20
    AfricanAmerican 1.07 (0.71-1.61) 0.76 0.00 1.24 (0.32-4.76) 0.751 65.10 1.56 (0.88-2.77) 0.133 48.00 0.91 (0.58-1.43) 0.679 0.00 1.19 (0.88-1.61) 0.258 0.00
    Asian 1.04 (0.47-2.30) 0.915 91.60 NA NA NA NA NA NA 1.05 (0.47-2.32) 0.912 91.60 1.02 (0.50-2.07) 0.954 90.50
By HWE
    Yes 1.07 (1.00-1.15) 0.041 62.20 1.11 (0.99-1.25) 0.081 61.60 1.13 (0.99-1.29) 0.059 64.30 1.04 (0.97-1.11) 0.336 56.60 1.08 (1.01-1.15) 0.025 73.10
    No 0.82 (0.17-4.09) 0.809 94.40 2.08 (0.22-19.66) 0.523 97.00 2.55 (0.17-37.87) 0.496 93.50 0.64 (0.14-3.01) 0.575 93.70 0.86 (0.21-3.54) 0.836 97.20
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P, P-value of Z-test to evaluate the significance of the ORs; NA, not available.

Publication bias and sensitivity analysis

Begg’s (Pr>|z| = 0.245) and Egger’s (P>|t| = 0.132) test was performed to assess the publication bias of pooled literatures, which was shown in the (Figure 3). The shapes of the funnel plots were symmetrical in the dominant genetic models, which indicated that the publication bias did not emerge in the cohort. When dropping each study in sensitivity analysis, the results of the meta-analysis didn’t change, which suggested the reliability of the results.

Figure 3.

Figure 3

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Begg’s funnel plot and Egger’s on publication bias for included studies on the association of the GPX1 rs1050450 polymorphism and cancer susceptibility (TT vs CT+CC). The funnel plot seemed symmetrical, suggesting absence of publication bias.

Discussion

The current meta-analysis, including 21,296 cancer patients and 30,346 controls from 60 case-control studies, investigated the relationship between the GPX1 (rs1050450) polymorphism and cancer risk. To the best of our knowledge, this was the first meta-analysis in such a large sample size with comprehensive evaluation of the association between the polymorphism of GPX1 and the tumor risk. We found that individuals with TT/CT genotypes harbored increased risk of cancer, especially in patients with bladder cancer as shown in the subgroup analysis.

Oxidative stress is an inevitable result of aerobic life. Previous studies have suggested that reactive oxygen species (ROS)-related oxidative damage plays a vital role in carcinogenesis [1]. ROS are modulated by regular metabolic process in vivo and can initiate a series of free radical formation. ROS can result in the breakage of DNA, oxidization of proteins and lipid [2]. DNA damages may inactivate cancer suppressor genes and further reduce the integrity of genome [37]. GPX1 plays a crucial role in the detoxification of mitochondrial ROS. High level expression of GPX1 could increase the antioxidant capacity in one cell, thus reducing intracellular oxidative stress. The appropriate adjustment of GPX1 levels has been considered as a significant factor in different stages of carcinogenesis both in vitro and vivo experiments [60]. Accumulating evidences have demonstrated that the GPX1 (rs1050450 C>T) polymorphism may increase carcinogenesis risk. According to our study, the result indicated that individuals with the CT/TT (ProLeu/LeuLeu) genotypes were associated with a higher risk of cancer than subjects carrying the wild ProPro genotype.

Since cancer origins could influence the outcomes as shown in previous studies, we conducted subgroup analysis according to cancer types. Except for bladder cancer and brain tumor, we did not find any positive association regarding to prostate cancer, breast cancer, lung cancer, colorectal cancer, NHL, skin cancer, digestive system cancer and head and neck cancer. Prostate cancer and bladder cancer are two of the most common urological malignancies. Previous studies suggested that the association of GPX1 (rs1050450) polymorphism with prostate cancer and bladder cancer was inconclusive [22,27,34,37]. Therefore, current meta-analysis was designed to determine a more accurate role of GPX (rs1050450 C>T) polymorphism since this meta-analysis investigated a large number of individuals and could also estimate the effect of genetic factors [8]. In addition, we previously put forward that only two studies reported African-Americans and only five studies reported Asian population. Hence, larger-sample studies and combined analysis are warranted to further verify the role of ethnic discrepancy in the relationship of the GPX1 polymorphism and cancer risks, especially for African-Americans and Asians.

In interpreting current results, several limitations of the meta-analysis should be addressed. First, as only publications indexed by selected databases were included in the current study, some relevant published studies with null results were missing and ongoing studies with unpublished data were unavailable, which may have influenced our results. Second, part of the studies investigated comparing several different sets of cases with the same set of control, which might reduce the statistical power for identifying those possible associations. Third, the lack of the original data of the reviewed studies limited our further evaluation of the potential interactions. In the meantime, current study also had some merits. For one thing, over 60 studies were pooled from 52 publications, which significantly increased statistical power of the analysis. For another, on the basis of our studies, we found a novel way to predict the association between GPX (rs1050450 C>T) polymorphism and cancer risk, especially in bladder cancer.

To summarize, the results from the meta-analysis provided some evidence that the GPX1 Pro198Leu (rs1050450 C>T) polymorphism might contribute to genetic susceptibility to cancer especially in bladder cancer, supporting the hypothesis that the polymorphism could serve as a potential tumor predicting biomarker. However, the conclusion should be interpreted with caution. The detailed analysis of genetic models and inclusion of large-scale studies regarding African-Americans and Asians, and comprehensive study design with respect to gene-gene and gene-environment interaction are warranted.

Acknowledgements

This work was funded by the National Natural Science Foundation of China (Grant No. 81171320).

Disclosure of conflict of interest

None.

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