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Keywords:

  • cytotoxic T-lymphocyte antigen 4;
  • cancer;
  • meta-analysis;
  • polymorphism;
  • risk

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

BACKGROUND:

Polymorphisms in the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene have been implicated in susceptibility to cancer, but the many published studies have reported inconclusive results. The objective of the current study was to conduct a meta-analysis investigating the association between polymorphisms in the CTLA-4 gene and the risk of cancer.

METHODS:

The PubMed and EMBASE databases were searched for all articles published up to September 19, 2010 that addressed cancer and polymorphisms, variants, or mutations of CTLA-4. A statistical analysis was performed using proprietary statistical software.

RESULTS:

Three polymorphisms (+49 adenine/guanine [+49A/G], −318 cytosine/thymine [−318C/T], and the +6230G/A polymorphism [CT60]) in 48 case-control studies from 27 articles were analyzed. The results indicated that individuals who carried the +49 G allele (AG + GG) had a 16% decreased risk of cancer compared with homozygotes (+49AA; odds ratio [OR], 0.84; 95% confidence interval [CI], 0.74-0.95). However, there was no significant association between the risk of cancer and the −318C/T polymorphism or the CT60 polymorphism (−318C/T: OR, 1.23; 95% CI, 0.99-1.54 for TT + TC vs CC; CT60: OR, 1.02; 95% CI, 0.80-1.29 for AA + AG vs GG). In further stratified analyses for the +49A/G and −318C/T polymorphisms, the decreased risk of cancer remained in subgroups of Europeans, patients with breast cancer, and patients with lung cancer for the +49A/G polymorphism; whereas an increased risk of cancer was observed among Europeans for the −318C/T polymorphism.

CONCLUSIONS:

Results from the current meta-analysis suggested that the +49A/G and −318C/T polymorphisms in CTLA-4 are risk factors for cancer. To further evaluate gene-gene and gene-environment interactions between CTLA-4 polymorphisms and the risk of cancer, more studies with larger groups of patients will be required. Cancer 2011;. © 2011 American Cancer Society.

Cancer is a multifactorial disease that results from complex interactions between genetic and environmental factors.1-3 The etiology of cancer is complicated and has not been elucidated completely, although recent studies have focused on the role of the immune system.4 Important steps in tumorigenesis include the evasion of immune surveillance by tumor cells and the production of immunosuppressive cytokines.5-7 For this reason, tumor immunity is increasing as a hot spot in cancer research.6

Burnet first described the concept of immunologic surveillance in the recognition and destruction of transformed tumor cells.6, 8 The most significant antitumor response is cell-mediated and involves T lymphocytes and natural killer (NK) cells. Thus, genetic variants of the genes that regulate the activation and proliferation of T lymphocytes and NK cells may affect the risk of cancer.9

Cytotoxic T-lymphocyte antigen 4 (CTLA-4) (cluster of differentiation 152 [CD152]), a member of the immunoglobulin superfamily that is expressed mainly on activated T cells, plays a critical role in the negative regulation of T-cell proliferation and activation.10 Mice deficient the CTLA-4 gene were born healthy but developed severe lymphoproliferative disorders and autoimmune diseases and died early.11, 12 In addition to inhibiting T-cell proliferation and activation, CTLA-4 also induces Fas-independent apoptosis of activated T cells.13 It has been suggested that, during the early stage of tumorigenesis, CTLA-4 may elevate the T-cell activation threshold, thereby attenuating the antitumor response and increasing susceptibility to cancer.10

The CTLA-4 gene is located on chromosome 2q33 and is composed of 4 exons that encode separate functional domains: a leader sequence, an extracellular domain, a transmembrane domain, and a cytoplasmic domain.9, 14, 15 This gene is polymorphic, and >100 single nucleotide polymorphisms have been identified,16 such as the +49 adenine/guanine (+49A/G), +6230G/A (CT60), −318 cytosine/thymine (−318C/T), −1611G/A, and −1722T/C polymorphisms, etc.9, 17 Among all of these polymorphisms, the +49A/G polymorphism (reference single nucleotide polymorphism no. 231775 [rs231775]), the −318C/T polymorphism (rs5742909), and the CT60 polymorphism (G/A; rs3087243) were the most widely studied for their implication in cancer risk.6, 9-11, 14, 17-38 Many studies indicated that these 3 polymorphisms were involved in the etiology of various cancers, including cervical cancer,11, 24, 25, 28 lung cancer,10, 21 breast cancer,19, 14, 38 hepatocellular cancer,27, 28 and so on. However, the results from those studies remain conflicting rather than conclusive. Considering the important role of CTLA-4 in tumorigenesis, we performed a meta-analysis on all eligible case-control studies to estimate the overall cancer risk associated with these polymorphisms. To our knowledge, this is the most comprehensive meta-analysis conducted to date with respect to the associations between CTLA-4 polymorphisms and cancer risk.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

Identification of Eligible Studies

A literature search of the PubMed and EMBASE databases (updated to September 19, 2010) was conducted using combinations of the following terms: “polymorphism or variant or mutation” and “cancer or carcinoma” and “CTLA-4 or cytotoxic T-lymphocyte antigen-4.” There was no language restriction. All studies that evaluated the associations between polymorphisms of the CTLA-4 gene and cancer risk were retrieved. Studies that were included in the meta-analysis had to meet all of the following criteria: 1) evaluation of the polymorphisms (+49A/G, −318C/T, and CT60) in CTLA-4 gene and cancer risk, 2) use of a case-control design, 3) sufficient genotype numbers for estimating an odds ratio (OR) with a 95% confidence interval (CI), and 4) genotype distributions of control consistent with Hardy-Weinberg equilibrium (HWE). Accordingly, the following exclusion criteria were also used: 1) abstracts and reviews and 2) studies that did not report genotype frequency. For studies with overlapping or repeating data, the most recent or complete studies with the largest numbers of cases and controls were included.

Data Extraction

Two of the authors (Y.Z. and J.Z.) extracted all data independently, complied with the selection criteria, and reached a consensus on all items. In case of disagreement, a third author (H.F.) assessed the articles. The following items were collected: first author's name, year of publication, country of origin, ethnicity, definition of study patients (cases), source of the control group (controls), genotyping method, cancer type, total number of cases and controls, and genotype distributions in cases and controls.

Statistical Analysis

The strength of associations between CTLA-4 polymorphisms and cancer risks were assessed as ORs with corresponding 95% CIs. The genetic models that were evaluated for pooled ORs of these polymorphisms were dominant models (GG + GA vs AA for +49A/G, TT + TC vs CC for −318C/T, and AA + AG vs GG for CT60). The OR was calculated by using a fixed-effects model (the Mantel-Haenszel method) or a random-effects model (the DerSimonian and Laird method) according to heterogeneity. Heterogeneity among studies was checked by using the chi-square–based Q statistic and was considered statistically significant at P < .10. When P > .10, the pooled OR of each study was calculated by using the fixed-effects model; otherwise, the random-effects model was used. The significance of the pooled OR was determined by using a Z-test, and P < .05 was considered statistically significant. To evaluate ethnicity-specific and cancer type-specific effects, subgroup analyses were performed by ethnic group and cancer type for the +49A/G polymorphism and the −318C/T polymorphism, which were investigated in a sufficient number of studies (if 1 cancer type was investigated by <3 individual case-control studies, then it was combined into the group of “other cancers”). For each polymorphism, other genetic models (for +49A/G, GG vs GA + AA, GG vs AA, GA vs AA, and G vs A; for −318C/T, TT vs TC + CC, TT vs CC, TC vs CC, and T vs C; for CT60, AA vs AG + GG, AA vs GG, AG vs GG, and A vs G) also were used to assess the association with cancer risk.

Publication bias was analyzed by several methods. Visual inspection of asymmetry in funnel plots was carried out. The Begg test and the Egger test also were used to statistically assess publication bias.39

Hardy-Weinberg equilibrium was tested by Pearson's χ2 test. All statistical tests were performed using Review Manager (RevMan) software (version 4.2; Ther Cochrane Collaboration, Oxford, United Kingdom) and the STATA statistical software package (version 10.0; StataCorp, College Station, Tex).

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

Study Selection and Characteristics in the Meta-Analysis

In total, 533 results were identified that were relevant to the search terms (Fig. 1). After an initial screening the of titles and abstracts, 36 potential articles were included for full-text view. Two articles were excluded after additional screening, because they were not relevant to cancer risk in relation to the investigated polymorphisms (+49A/G, −318C/T, and CT60). Thus, 34 articles were remained for data extraction. Two additional articles were excluded because they did not report usable data., and 2 other articles analyzed 2 cancer types using the same control group,26, 35 and the cancers were combined as 1 cancer type for each polymorphism. Thus, in total, 62 case-control studies were identified. In addition, 4 case-control studies were excluded for overlapping data, 10 case-control studies were excluded because the number of genotypes was not consistent with HWE in the control group. Finally, in total, 48 case-control studies from 27 articles were identified.6, 9-11, 14, 17-38 Overall, there were 22 articles (including 28 case-control studies) on the +49A/G polymorphism,6, 9-11, 18-20, 21-23, 25-31, 33-37 13 articles (including 13 case-control studies) on the −318C/T polymorphism,11, 17-19, 21, 22, 24, 25, 29-32, 34 and 7 articles (including 7 case-control studies) on the CT60 polymorphism.11, 17, 18, 26, 29, 34, 38 Of these articles, 6 investigated cervical cancer,11, 24, 25, 28, 29, 31 5 investigated colorectal cancer,9, 23, 26, 32, 35 and 4 investigated breast cancer.10, 14, 19, 38 The other articles investigated lung cancer, gastric cancer, oral cancer, leukemia, esophageal cancer, hepatocellular cancer, skin cancer, thymoma, lymphoma, melanoma, renal cancer, and nasopharyngeal cancer. Among 27 articles, 14 were from Asia,6, 9-11, 14, 19,21, 25, 27, 28, 33-35, 38 11 were from Europe,18, 20, 22-24, 26, 29-32, 36, 37 and 1 was from the United States.17 Different genotyping methods were used, including restriction fragment length polymorphism, TaqMan, amplification-refractory mutation system, Sequenom (Sequenom, Inc., San Diego, Calif), polymerase chain reaction (PCR)-ligation detection reaction, SNaPshot (Applied Biosystems, Foster City, Calif), and multiplex-PCR with hybridization. The characteristics of each article are listed in Table 1. The genotype numbers for each polymorphism are listed in Table 2.

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Figure 1. This is a flow diagram of included and excluded studies. HWE indicates Hardy-Weinberg equilibrium.

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Table 1. Characteristics of Populations and Cancer Types of the Studies Included in the Meta-Analysis
StudyCountryEthnicityCancer TypeNo. of Cases/ ControlsGenotype MethodPolymorphisms
  • PCR indicates polymerase chain reaction; A, adenine; G, guanine; C, cytosine; T, thymine; RFLP, restriction fragment length polymorphism; SSCP, single-strand conformation polymorphism; LDR, ligation detection reaction; ARMS, amplification-refractory mutation system.

  • a

    Sequenom, Inc. (San Diego, Calif).

  • b

    Applied Biosystems (Foster City, Calif).

Bouwhuis 201022GermanyEuropeanMelanoma763/734TaqMan+49A/G, −318C/T
Castro 200931SwedenEuropeanCervical973/1763Multiplex PCR with hybridization+49A/G, −318C/T
Cheng 200634ChinaAsianLymphoma62/250RFLP, Sequenom+49A/G, CT60, −318C/T
Chuang 200518GermanEuropeanThymoma125/173RFLPCT60, −318C/T
Cozar 200726SpainEuropeanColon, renal223/176TaqMan+49A/G, CT60
Dilmec 200832TurkeyEuropeanColorectal56/162RFLP−318C/T
Ghaderi 200414IranAsianBreast197/151PCR-SSCP+49A/G
Gu 201027ChinaAsianHepatocellular375/419PCR-LDR+49A/G
Hadinia 200735IranAsianColorectal, gastric155/190RFLP, PCR-ARMS+49A/G
Hu 201028ChinaAsianHepatocellular, cervical1549/1563TaqMan+49A/G
Ivansson 201024SwedenEuropeanCervical1281/808Taqman, multiplex PCR with hybridization−318C/T
Kammerer 201037GermanEuropeanOral83/40RT-PCR+49A/G
Khaghanzadeh 201021IranAsianLung124/127RFLP, PCR-ARMS+49A/G, −318C/T
Li 200838ChinaAsianBreast328/327RFLPCT60
Mahajan 200836PolandEuropeanGastric464/480TaqMan+49A/G
Pawlak 201029PolandEuropeanCervical147/225RFLP+49A/G, CT60, −318C/T
Piras 200520ItalyEuropeanNHL100/128RFLP+49A/G
Qi 20109ChinaAsianColorectal124/407PCR-LDR+49A/G
Rahimifar 201025IranAsianCervical55/110RFLP, PCR-ARMS+49A/G, −318C/T
Solerio 200523ItalyEuropeanColorectal132/238RFLP+49A/G
Su 200711ChinaAsianCervical144/378RFLP+49A/G, CT60, −318C/T
Sun 200810ChinaAsianlung, breast, esophagus, gastric cardia5832/5832RFLP, Sequenoma+49A/G
Suwalska 200830PolandEuropeanLeukemia178/336SNaPshotb+49A/G, −318C/T
Wang 200719ChinaAsianBreast117/148RFLP+49A/G, CT60, −318C/T
Welsh 200917United StatesAmericanSkin1643/849TaqMan, SequenomaCT60, −318C/T
Wong 20066ChinaAsianOral118/147RFLP+49A/G
Xiao 201033ChinaAsianNasopharyngeal457/485RFLP+49A/G
Table 2. Distribution of Cytotoxic T-Lymphocyte Antigen 4 Genotype and Allele Among Cancer Patients (Cases) and Controls
 CasesControlsCasesControls 
CT60 G/A PolymorphismGGAGAAGGAGAAGAGAHWE
Cheng 2006343920315479179826387113Yes
Chuang 200518406124439535141109181165Yes
Cozar 2007264211169478840195249182168Yes
Li 2008383212417220114193188468154500Yes
Pawlak 201029415815771044314088258190Yes
Su 200711874572381231721959599157Yes
Welsh 20091745079135028038515617911591945697Yes
 CasesControlsCasesControls 
+49A/G PolymorphismAAAGGGAAAGGGGAGAHWE
Bouwhuis 201022289369104283345106947577911557Yes
Castro 20093125244925245682543495395317371693Yes
Cheng 20063422634291021193094160340Yes
Cozar 2007261198715787721325117233119Yes
Ghaderi 200414841049607219272122192110Yes
Gu 2010275116615045179183268466269545Yes
Hadinia 20073576601211759142128429387Yes
Hu 201028 (C)a80290326563003534509424121006Yes
Hu 201028 (H)a1063803677937639959211145341174Yes
Kammerer 20103735321611236102644535Yes
Khaghanzadeh 201021664413684771767018361Yes
Mahajan 200836891535915218970331271493329Yes
Pawlak 2010294372267110343158124245189Yes
Piras 200520742337443111712919165Yes
Qi 20109460604517918368180269545Yes
Rahimifar 2010252827058457832716159Yes
Solerio 200523764313128911919569347129Yes
Su 2007111762604215517896182239511Yes
Sun 200810 (B, B)b1014854746544655968714335761564Yes
Sun 200810 (B, J)b1004554827345154665514195971543Yes
Sun 200810 (E, B)b1284344487340652969013305521464Yes
Sun 200810 (GC, B)b6023523539209282355705287773Yes
Sun 200810 (L, B)b1355195098148856378915376501614Yes
Sun 200810 (L, J)b1254394689043849368913756181424Yes
Suwalska 2008305684307110647196144248200Yes
Wang 20071948591055702315579180116Yes
Wong 2006612584825645882154114180Yes
Xiao 2010335719520538201246309605277693Yes
 CasesControlsCasesControls 
−318C/T PolymorphismCCCTTTCCCTTTCTCTHWE
  • HWE indicates Hardy-Weinberg equilibrium; G, guanine; A, adenine; C, cytosine; T, thymine.

  • a

    (C) indicates cervical cancer; (H), hepatocellular carcinoma.

  • b

    (B, B) indicates breast cancer in Beijing; (B, J), breast cancer in Jiangsu; (E, B), esophageal cancer in Beijing; (GC, B), gastric cardia cancer in Beijing; (L, B), lung cancer in Beijing; (L, J), lung cancer in Jiangsu.

Bouwhuis 2010226191368596130813741521322146Yes
Castro 20093151248196223147113417622353165Yes
Cheng 2006345930209401121345842Yes
Chuang 200518942831393042163430838Yes
Dilmec 2008324880149121104831014Yes
Ivansson 20102410442289666138423162461470146Yes
Khaghanzadeh 2010211071721051612312122618Yes
Pawlak 201029993831803512364439537Yes
Rahimifar 201025513089201105319822Yes
Su 2007111053813066752484067977Yes
Suwalska 2008301214272676242845659670Yes
Wang 200719843301291902013327719Yes
Welsh 200917130627213682132728842981496146Yes

Quantitative Synthesis

The +49A/G polymorphism

In total, 12,151 cancer cases and 14,069 controls from 28 case-control studies were included in the current meta-analysis of the relation between the +49A/G polymorphism and the risk of cancer. Nineteen case-control studies were from Asia, and 9 were from Europe. Overall, there was statistical evidence of an association between the +49A/G polymorphism and overall cancer risk (OR, 0.84; 95% CI, 0.74-0.95; P = .007 for GG + GA vs AA) (Fig. 2). In the subgroup analysis by cancer type, the results indicated that individuals with variant genotypes had a significantly lower risk of breast cancer (OR, 0.71; 95% CI, 0.59-0.86; P = .0004 for GG + GA vs AA) and lung cancer (OR, 0.72; 95% CI, 0.54-0.97; P = .03 for GG + GA vs AA) (Fig. 3). In the subgroup analysis by ethnicity, significant decreased cancer risks were observed among Asians (OR, 0.80; 95% CI, 0.69-0.94; P = .006 for GG + GA vs AA) but not among Europeans (OR, 0.93; 95% CI, 0.78-1.10; P = .39 for GG + GA vs AA) (Fig. 4). No publication bias was detected with either the funnel plot or the Egger test (t = 0.64; P = .527). Other comparison results are listed in Table 3.

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Figure 2. Meta-analysis with a random-effects model for the association between cancer risk and the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene +49 adenine/guanine (+49A/G) polymorphism (GG + GA vs AA) is illustrated. OR indicates odds ratio; CI, confidence interval; Chi2, chi-square test; df, degrees of freedom; I2, measure to quantify the degree of heterogeneity in meta-analyses.

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Figure 3. Meta-analysis with a random-effects model for the association between cancer risk and the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene +49 adenine/guanine (+49A/G) polymorphism (GG + GA vs AA) is illustrated in a subgroup analysis by cancer type. OR indicates odds ratio; CI, confidence interval; Chi2, chi-square test; df, degrees of freedom; I2, measure to quantify the degree of heterogeneity in meta-analyses.

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Figure 4. Meta-analysis with a random-effects model for the association between cancer risk and the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene +49 adenine/guanine (+49A/G) polymorphism (GG + GA vs AA) is illustrated in a subgroup analysis by ethnicity. OR indicates odds ratio; CI, confidence interval; Chi2, chi-square test; df, degrees of freedom; I2, measure to quantify the degree of heterogeneity in meta-analyses.

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Table 3. Summary of Results From Different Comparative Genetic Models
PolymorphismGenetic ModelNo. of ParticipantsOR (95% CI)ZPI2, %PHetEffect Model
  1. OR indicates odds ratio; CI, confidence interval; Z, test for overall effect; I2, index of heterogeneity; PHet, P value for heterogeneity; G, guanine; A, adenine; C, cytosine; T, thymine.

+49A/GGG+GA vs AA26,2200.84(0.74-0.95)2.70.00765.6<.00001Random
 GG vs GA+AA26,2200.85(0.79-0.92)4.12<.000135.4.03Random
 GG vs AA14,7210.76(0.65-0.90)3.29.00164.7<.00001Random
 GA vs AA16,2740.88(0.78-0.99)2.18.0354.8.0003Random
 G vs A52,4400.89(0.83-0.95)3.37.000762<.00001Random
−318C/TTT+TC vs CC11,5321.23(0.99-1.54)1.88.0662.7.001Random
 TT vs TC+CC11,5321.05(0.85-1.29)0.46.650.82Fixed
 TT vs CC96381.23(0.81-1.86)0.99.320.78Fixed
 TC vs CC91591.23(0.99-1.52)1.84.0760.3.003Random
 T vs C23,0641.20(1.00-1.44)1.97.0563.4.001Random
CT60 G/AAA+AG vs GG49291.02(0.80-1.29)0.13.9055.9.03Random
 AA vs AG+GG49291.00(0.78-1.28)0.01.9946.0.09Random
 AA vs GG27310.98(0.67-1.43)0.10.9262.7.01Random
 AG vs GG37881.12(0.98-1.30)1.62.1031.5.19Random
 A vs G98581.00(0.83-1.19)0.04.9666.2.007Random
The −318C/T polymorphism

In total, 5577 cases and 5955 controls from 13 case-control studies were included in our meta-analysis of the relation between the −318C/T polymorphism and the risk of cancer. Five case-control studies were from Asia, 7 were from Europe, and 1 was from the United States. Our results did not suggest any statistical evidence of an association between the −318C/T polymorphism and overall cancer risk (OR, 1.23; 95% CI, 0.99-1.54; P = .06 for TT + TC vs CC) (Fig. 5). In the subgroup analysis by cancer type, no significant association between this polymorphism and the risk of cervical cancer was identified (OR, 1.14; 95% CI, 0.72-1.81; P = .57 for TT + TC vs CC) (Fig. 6). In the subgroup analysis by ethnicity, a significantly increased risk of cancer was identified among Europeans (OR, 1.28; 95% CI, 1.01-1.61; P = .04 for TT + TC vs CC) but not among Asians (OR, 0.93; 95% CI, 0.44-1.97; P = .85 for TT + TC vs CC) or Americans (OR, 1.07; 95% CI, 0.86-1.34; P = .55 for TT + TC vs CC) (Fig. 7). No publication bias was detected by either the funnel plot or the Egger test (t = 0.09; P = .932). Other comparison results are listed in Table 3.

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Figure 5. Meta-analysis with a random-effects model for the association between cancer risk and the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene −318 cytosine/thymine (−318C/T) polymorphism (TT + TC vs CC) is illustrated. OR indicates odds ratio; CI, confidence interval; Chi2, chi-square test; df, degrees of freedom; I2, measure to quantify the degree of heterogeneity in meta-analyses.

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Figure 6. Meta-analysis with a random-effects model for the association between cancer risk and the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene −318 cytosine/thymine (−318C/T) polymorphism (TT + TC vs CC) is illustrated in a subgroup analysis by cancer type. OR indicates odds ratio; CI, confidence interval; Chi2, chi-square test; df, degrees of freedom; I2, measure to quantify the degree of heterogeneity in meta-analyses.

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Figure 7. Meta-analysis with a random-effects model for the association between cancer risk and the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene −318 cytosine/thymine (−318C/T) polymorphism (TT + TC vs CC) is illustrated in a subgroup analysis by ethnicity. OR indicates odds ratio; CI, confidence interval; Chi2, chi-square test; df, degrees of freedom; I2, measure to quantify the degree of heterogeneity in meta-analyses.

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The CT60 polymorphism

In total, 2581 cases and 2348 controls from 7 case-control studies were included in our meta-analysis on the relation between the CT60 polymorphism and the risk of cancer. Three case-control studies were from Asia, 3 were from Europe, and 1 was from the United States. Our results did not suggest any statistical evidence of an association between the CT60 polymorphism and the overall risk of cancer (OR, 1.02; 95% CI, 0.80-1.29; P = .90 for AA + GA vs GG) (Fig. 8). Further subgroup analyses were not performed because of limited data for this polymorphism. Publication bias was detected by both the funnel plot and the Egger test (t = −2.24; P = .075). Other comparison results are listed in Table 3.

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Figure 8. Meta-analysis with a random-effects model for the association between cancer risk and the cytotoxic T-lymphocyte antigen 4 (CTLA-4) gene +6230 guanine/adenine (G/A) polymorphism (CT60) (AA + AG vs GG) is illustrated. OR indicates odds ratio; CI, confidence interval; Chi2, chi-square test; df, degrees of freedom; I2, measure to quantify the degree of heterogeneity in meta-analyses.

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DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

There is individual susceptibility to cancer even with the same environmental exposure.40-44 Host genetic factors, including variants of genes involved in the tumorigenesis, may affect these differences. Thus, in recent years, interest in genetic susceptibility to cancer has led to an increase in the study of polymorphisms of the genes involved in tumorigenesis. The CTLA-4 gene has been widely studied, and many studies have been carried out to test the hypothesis that polymorphisms in CTLA-4 gene may be associated with the risk of cancer; however, the data have yielded conflicting results. To produce more precise results, we performed a meta-analysis to evaluate these associations.

This meta-analysis, which included a total of 48 case-control studies from 27 articles, examined the associations of 3 widely studied polymorphisms in the CTLA-4 gene and cancer risk. The results indicated that variant genotype (AA + AG) of the +49A/G polymorphism is associated with a significant decrease in the overall risk of cancer, whereas the −318C/T and CT60 polymorphisms did not appear to have a significant association on the overall risk of cancer. The results from our stratification analyses indicated that there is an effect modification of the cancer risk by cancer type and ethnicity for the +49A/G polymorphism, whereas an effect modification of cancer risk was observed by ethnicity but not by cancer site for the −318C/T polymorphism.

CTLA-4, as a negative regulation factor of T-cell proliferation and activation, plays an important role in cancer immunosurveillance. It may be involved in cancer development and progression. The current meta-analysis results indicate a significant impact of CTLA-4 polymorphisms on the overall cancer risk and particularly indicate a decreased risk of cancer for carriers of the +49A/G polymorphism. The +49A/G polymorphism results in a threonine (Thr) to alanine (Ala) substitution in the leading peptide of the CTLA-4 receptor.12 It has reported that the 49G allele has lower messenger RNA efficiency and decreased CTLA-4 production than the 49A allele, and individuals with the 49GG genotype may have greater T-cell proliferation than those with the 49AA genotype under the condition of suboptimal stimulation.12 In addition, this polymorphism enhances the CTLA-4 protein to bind its ligand B7.1, and the interaction between CTLA-4 Thr and B7.1 is significantly stronger than that between CTLA-4 Ala and B7.1.10 The mechanism by which this polymorphism modifies CTLA-4 function mat be mediated by an amino acid substitution in the peptide leader sequence, which enhances the capability of variant CTLA-4 to communicate with the B7.1 molecule.10 In combination with our current results, these findings indicate that the Thr-to-Ala change in CTLA-4 results in CTLA-4-triggered inhibition of T-cell proliferation and activation, which may be associated with the risk of cancer.

Because tumor origin can influence the results from meta-analyses, we performed subgroup analyses by cancer type for the +49A/G and −318C/T polymorphisms. The results indicated that the +49A/G polymorphism is associated with a decreased risk of lung cancer and breast cancer but not of cervical cancer, colorectal cancer, or gastric cancer. In addition, our results indicated the lack of an association between the −318C/T polymorphism and cervical cancer. However, all of these results should be interpreted with caution. Because, for some cancer types, only 3 case-control studies were included, which may have limited power to reveal a reliable association, in the future, large numbers of studies will be required to validate these associations. In the current meta-analysis, the associations observed in different ethnic population also were analyzed for these 2 polymorphisms. The +49A/G polymorphism was associated with a decreased risk of cancer among Asians but not among Europeans, whereas the −318C/T polymorphism was associated with an increased risk among Europeans but not among Asians. These results strongly indicate that interactions between genetic diversity among different ethnicities and genetic variants may contribute to different cancer risks. Both ethnic factors and environmental factors affect the risk of cancer in different population. In the future, more studies should be carried out to analyze these associations, especially for gene-environment and gene-gene interactions.

We have to mention the importance of heterogeneity and publication bias, which may influence the results of meta-analyses. Significant heterogeneity existed in overall comparisons in the dominant model for all 3 polymorphisms. After subgroup analyses by cancer types and ethnicity, the heterogeneity effectively was decreased or removed in some subgroups, suggesting different roles for cancer types and genetic backgrounds even for the same polymorphism. Publication bias is another important issue in meta-analyses. In the current study, publication bias was analyzed by using Begg funnel plots and the Egger test. We didn't detect a significant publication bias for all three polymorphisms, suggesting the reliability of our results.

In interpreting the current results, some limitations should be considered. First, all case-control studies were from Asia, Europe, and the United States; thus, our results may be applicable only to these ethnic groups. Second, because only studies that were indexed by the selected databases were included for data analysis, some relevant published studies or unpublished studies with null results were missed, which may have biased our results. Third, data were not stratified by other factors, such as environmental and lifestyle variables, because insufficient information was extracted from the primary publication.

In conclusion, the results from this meta-analysis suggest that the +49A/G and −318C/T polymorphisms in CTLA-4, but not the CT60 polymorphism, represent risk factors for cancer. Future large-scale studies will be needed to clarify the gene-gene and gene-environment interactions between CTLA-4 polymorphisms and cancer risk.

CONFLICT OF INTEREST DISCLOSURES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

This study was supported by grants 30470761 and 30871117 from National Natural Science Foundation of China.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES