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. 2015 Oct 21;21:3186–3196. doi: 10.12659/MSM.895257

Common Polymorphisms in the NFKBIA Gene and Cancer Susceptibility: A Meta-Analysis

Meng Zhang 1,A,B,*, Junjie Huang 2,E,F,*, Xiuxiu Tan 1,B,*, Jian Bai 1,D, Hao Wang 1,B,C, Yukun Ge 1,D,E, Hu Xiong 1,C,D, Jizhou Shi 3,B,E, Wei Lu 1,C,D, Zhaojie Lv 1,B,E,G,✉, Chaozhao Liang 4,5,B,C,D,E,✉
PMCID: PMC4621165  PMID: 26488500

Abstract

Background

NFKBIA encodes the inhibitors of nuclear factor-κB (NF-κB), which regulate the translation of the genes involved in the inflammatory and immune reactions. Polymorphisms (rs2233406, rs3138053, and rs696) of NFKBIA have been implicated in susceptibility to many cancer types.

Material/Methods

To evaluate the association between polymorphisms of NFKBIA and cancer susceptibility, a meta-analysis including a total of 7182 cancer cases and 10 057 controls from 28 case-control studies was performed. Data were extracted and pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated.

Results

Combined data demonstrated that rs3138053 polymorphism of NFKBIA was associated with cancer susceptibility in an allelic model (C vs. T: OR=10.754, 95%CI=4.175–27.697, Pheterogeneity=0.000), while the polymorphism of rs696 appeared to play a protective role in tumorigenesis (CC+CT vs. TT: OR=0.879, 95%CI=0.787–0.982, Pheterogeneity=0.107). When stratification analysis was performed by cancer type, an increased association of rs3138053 was recognized in hepatocarcinoma (C vs. T: OR=42.180, 95%CI=27.970–63.612, Pheterogeneity=0.007), while a decreased association of rs696 was identified in Hodgkin lymphoma (C vs. T: OR=0.792, 95%CI=0.656–0.956, Pheterogeneity=0.116; CC vs. TT: OR=0.658, 95%CI=0.448–0.965, Pheterogeneity=0.076; CC vs. CT+TT: OR=0.734, 95%CI=0.562–0.958, Pheterogeneity=0.347). By ethnicity, rs696 appears to be a protective candidate among Caucasians (CT vs. TT: OR=0.809, 95%CI=0.676–0.969, Pheterogeneity=0.459).

Conclusions

Our data demonstrated that the rs3138053 polymorphism of NFKBIA gene is a candidate for susceptibility to overall cancers, while rs696 plays a protective role.

MeSH Keywords: Genetic Linkage, Medical Oncology, Meta-Analysis

Background

Nuclear factor-κB (NF-κB) belongs to a family of transcription factors that play a crucial role in inflammatory and immune reactions [2]. The malfunctioning of NF-κB contributes to the inhibition of apoptosis, cell replication, and angiogenesis, all of which are occur in cancer cells [3]. Several pieces of evidence have demonstrated the connection between the defective function of IκB and cancer progression. Overexpression of NF-κB has been identified in several categories of cancer, including Hodgkin’s lymphoma, multiple myeloma, colorectal cancer, and melanoma [1]. Additionally, it was discovered that the expression of IκB was decreased among prostate cancer patients [4]. These results indicate the significant role of IκBs in regulating the oncogenic potential of NF-κB and in cancer development. From these points of view, malfunctioning in the expression of IκB may remain a risk factor for cancer.

IκBα is encoded by NFKBIA genes located on chromosome 14q13. NFKBIA rs2233406, rs3138053, and rs696 polymorphisms are situated in the binding regions for CCAAT/enhancer binding protein and GATA binding protein 2, respectively. They may regulate IκBα expression, and influence NF-κB activation; these polymorphisms (rs2233406, rs3138053, and rs696) are directly related to apoptosis, inappropriate immune cell development, and delayed cell growth [5]. The effect of polymorphisms within the NFKBIA gene on cancer susceptibility has been investigated in a number of cancers [6–12]. It was reported that polymorphic variants in the 39-untranslated region of NFKBIA was associated with a susceptibility to multiple myeloma, Hodgkin’s lymphoma, prostate cancer, breast cancer, colorectal cancer, gastric cancer, and melanoma [13–19].

However, the susceptibility modulation impacts of the polymorphisms were inconsistent in various studies because the sample sizes enrolled were limited and the ethnic backgrounds of subjects in various studies were different. Evidence of the relationship between genetic polymorphisms and cancer susceptibility can be provided by a quantitative synthesis to accumulate data from different studies. In this paper we present the results of a comprehensive meta-analysis performed on publicly available databases.

Material and Methods

Literature sources and search strategy

We conducted a systematic literature search in Google Scholar, PubMed, and Web of Science databases (up to 20 June 2015) to accumulate all available studies on the association between polymorphisms of NFKBIA (rs2233406, rs3138053, and rs696) and cancer susceptibility by using the following the search strategy: (“NFKBIA” OR “Nuclear factor kappa B inhibitor”) AND (“polymorphism” OR “mutation” OR “variation”) AND (“susceptibility” OR “risk” OR “effects”) AND (“cancer” OR “tumour” OR “carcinoma”). Studies were also searched manually on the reference lists of reviews and retrieved studies for additional eligible studies.

Inclusion and exclusion criteria

The articles enrolled in the present meta-analysis were consistent with these criteria: (a) the relationship between the polymorphisms in NFKBIA and cancer susceptibility was identified in the studies; (b) the study method was case-control; and (c) we could extract the ORs with 95%CIs of all the cases and controls. Studies were excluded when they were: (a) studies without sufficient raw data to evaluate odds ratios with 95% confidence intervals; (b) case-only studies; (c) duplicated publications; and (d) studies based on animals or families.

Data extraction

The data were extracted independently by 3 investigators (M. Zhang, J. J. Huang, and X. X. Tan). Data with discrepancies were discussed by all authors. The following data were collected: name of first author, publication year, country of origin, ethnicity, cancer type, total numbers of cases and controls, source of controls, and genotype or allele distribution in cases and controls. Ethnic backgrounds were categorized as Asian and Caucasian.

Statistical analysis

We assessed the relationship between the NFKBIA polymorphisms and cancer susceptibility by employing the ORs and 95% CIs in the studies and calculated the pooled ORs on the allele contrast (t vs. T), dominant (Tt+tt vs. TT), and recessive (tt vs. Tt+TT) models. Comparisons were also performed in heterozygote (Tt vs. TT) and homozygote (tt vs. TT) (TT, homozygotes for the common allele; Tt, heterozygotes; tt, homozygotes for the rare allele). The P values of HWE were calculated by χ2 test for the genotype distribution in controls. The meta-analyses were conducted by using STATA 12.0 software (Stata Corporation, College Station, Texas). A chi-square based Q-statistic test was performed to evaluate the heterogeneity of studies in the case-control studies [20]. If the Q test (P>0.1) indicated homogeneity within studies, the fixed-effects model was used [21]; otherwise, the random-effects model was used [22]. We also evaluated heterogeneity across studies by calculation of the inconsistency index (I2<25%: no heterogeneity; I2=25–50%: moderate heterogeneity; I2>50%: significant heterogeneity). Stratification analyses were performed by source of control, cancer type, and ethnicity. We removed a single study each time to evaluate the stability of the results. Begg’s funnel plot and Egger’s test were used to assess publication bias.

Results

The identification and characteristics of eligible studies

As demonstrated in Figure 1, after a systematic literature search in the databases on the relevance between NFKBIA polymorphisms and cancer susceptibility, a total of 107 potential records were initially identified. After checking the abstracts, 70 irrelevant studies were excluded, some studies were with insufficient data and others were duplicated studies. When the full texts were examined, we excluded 19 articles with no polymorphism studies, non-case-control studies, studies not on cancer, and reviews. Another 4 publications were excluded because they were on other polymorphisms in NFKBIA, were duplicates, or lacked eligible samples. Finally, 14 articles containing 28 independent case-control studies with a total of 7182 cases and 10 057 controls were enrolled in this meta-analysis [23–36]. Table 1 presents the characteristics of all eligible studies; 9 were population-based and the others were hospital-based. All studies were case-controlled, including 9 liver cancer studies, 5 colorectal cancer studies, 3 breast cancer studies, 3 prostate cancer studies, 2 oral cancer studies, 2 oesophageal cancer studies, 1 ovarian cancer study, and 1 multiple myeloma study. The ethnicities in these case-control studies were categorized as Asian (23 studies) and Caucasian (5 studies).

Figure 1.

Figure 1

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Flow chart presenting the study selection procedure.

Table 1.

Characteristics of the enrolled studies.

SNP First author Year Ethnicity Genotyping method Source of control Cancer type Control Case
AA AB BB P (HWE) Y or N AA AB BB
rs2233406 Lu et al. 2015 Asian PCR-RFLP HB OC 478 190 19 0.982 Y 486 181 20
Zhang et al. 2014 Asian PCR HB HCC 1292 321 28 0.123 Y 204 41 6
Cheng et al. 2013 Asian PCR HB HCC 438 78 4 0.797 Y 106 27 2
Lin et al. 2012 Asian TaqMan HB ORC 438 78 4 0.797 Y 351 101 10
Tan et al. 2013 Asian PCR HB CRC 163 69 5 0.459 Y 169 60 8
Wang et al. 2014 Asian PCR-RFLP HB BC 297 162 42 0.004 N 212 102 32
Wang et al. 2014 Asian PCR-RFLP HB BC 297 162 42 0.004 N 46 25 0
Wang et al. 2014 Asian PCR-RFLP HB BC 297 162 42 0.004 N 30 20 7
He et al. 2009 Asian PCR HB HCC 685 181 20 0.056 Y 149 52 1
Han et al. 2015 Asian PCR-RFLP HB PC 586 321 29 0.058 Y 508 356 72
Umar et al. 2013 Asian PCR PB ESCC 149 141 21 0.106 Y 145 122 23
rs3138053 Lin et al. 2012 Asian TaqMan HB ORC 438 78 4 0.797 Y 351 101 10
Tan et al. 2013 Asian PCR HB CRC 163 69 5 0.459 Y 169 60 8
Gao et al. 2014 Asian PCR PB HCC 336 48 40 0.000 N 173 21 19
Spink et al. 2006 Caucasian PCR PB MM 94 91 11 0.066 Y 64 77 16
He et al. 2009 Asian PCR HB HCC 780 106 0 0.058 Y 164 38 0
Han et al. 2015 Asian PCR-RFLP HB PC 586 321 29 0.058 Y 508 356 72
Zhang et al. 2014 Asian PCR PB HCC 1289 308 27 0.087 Y 214 38 1
Cheng et al. 2013 Asian PCR HB HCC 438 78 4 0.797 Y 106 27 2
rs696 Umar et al. 2013 Asian PCR PB ESCC 59 165 87 0.219 Y 71 140 79
Gao et al. 2006 Asian PCR-RFLP HB CRC 81 259 237 0.450 Y 26 109 64
Gao et al. 2006 Caucasian PCR-RFLP HB CRC 74 221 143 0.466 Y 29 72 54
Zhang et al. 2014 Asian PCR HB HCC 248 794 561 0.231 Y 55 109 84
Gao et al. 2014 Asian HapMap PB HCC 149 196 76 0.412 Y 65 115 33
Osborne et al. 2005 Caucasian PCR PB HL 8 22 20 0.64 Y 4 26 21
Chang et al. 2009 Caucasian Taqman PB HL 53 158 153 0.245 Y 92 215 156
Han et al. 2015 Asian PCR-RFLP HB PC 165 458 313 0.909 Y 173 442 321
Song et al. 2011 Caucasian PCR-RFLP PB CRC 212 531 262 0.06 Y 233 460 308
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PCR – polymerase chain reaction; PCR-RFLP – polymerase chain reaction-restriction fragment length polymorphism; Y – P(HWE) >0.05; N – P(HWE) ≤0.05; HCC – hepatocellular carcinoma; OC – ovarian cancer; BC – breast cancer; CRC – colorectal cancer; HL – Hodgkin lymphoma; PC – prostate cancer; ESCC – esophageal squamous cell carcinoma; MM – multiple myeloma; ORC – oral cancer; HB – hospital-based; PB – population-based;

Pooled analysis

The primary results of the present meta-analysis and the heterogeneity test are summarized in Table 2. In addition, we also rated the methodological quality of the included studies according to the Newcastle-Ottawa Scale (Table 3). By pooling ORs and 95% CIs, we discovered that rs2233406 polymorphism of NFKBIA was not associated with susceptibility to cancers (Table 2A). However, we identified a significant increased susceptibility in the rs3138053 polymorphism of NFKBIA (C vs. T: OR=10.754, 95%CI=4.175–27.697, Pheterogeneity=0.000; Figure 2A, Table 2B). Another impressive finding was that the polymorphism of rs696 appeared to play a protective role in tumorigenesis, as suggested by the pooled ORs (CC+CT vs. TT: OR=0.879, 95%CI=0.787–0.982, Pheterogeneity=0.107; Figure 2B, Table 2C).

Table 2A.

Results of meta-analysis for rs2233406 polymorphism in NFKBA and cancer susceptibility.

Variables (rs2233406) Case/control C vs. T CC vs. TT CT vs. TT CC+CT vs. TT CC vs. CT+TT
OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%)
Total 3674/7241 1.098 (0.944–1.277) 0.000 47.1 1.387 (0.942–2.042) 0.017 28.9 1.077 (0.931–1.246) 0.030 24.8 1.097 (0.937–1.283) 0.005 36.2 1.390 (0.977–1.978) 0.043 21.8
Source of control
 HB 3384/6930 1.112 (0.942–1.312) 0.000 49.4 1.417 (0.914–2.198) 0.014 32.1 1.099 (0.941–1.284) 0.031 25.9 1.117 (0.944–1.323) 0.005 37.9 1.409 (0.940–2.111) 0.032 25.7
Cancer type
 HCC 588/3047 1.082 (0.851–1.375) 0.236 9.5 1.038 (0.348–3.103) 0.187 16.3 1.131 (0.789–1.622) 0.082 35.8 1.115 (0.821–1.515) 0.146 23.0 1.014 (0.324–3.175) 0.165 19.9
 BC 474/1503 0.841 (0.581–1.215) 0.132 31.2 0.390 (0.026–5.968) 0.048 55.2 1.222 (0.673–2.221) 0.693 0.0 0.889 (0.695–1.138) 0.616 0.0 0.396 (0.024–6.446) 0.043 57.0
HWE
 Y 3200/5738 1.148 (0.967–1.362) 0.002 48.9 1.535 (0.982–2.400) 0.046 26.1 1.103 (0.924–1.318) 0.014 36.2 1.137 (0.944–1.369) 0.004 43.7 1.535 (1.027–2.296)* 0.099 17.6
 N 474/1503 0.952 (0.691–1.310) 0.096 32.9 0.994 (0.398–2.484) 0.084 35.5 0.954 (0.750–1.214) 0.624 0.0 0.949 (0.758–1.188) 0.398 0.0 1.009 (0.425–2.396) 0.094 33.3
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Table 2B.

Results of meta-analysis for rs3138053 polymorphism in NFKBA and cancer susceptibility.

Variables (rs3138053) Case/control C vs. T CC vs. TT TC vs. TT CC+TC vs. TT CC vs. TC+TT
OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%)
Total 2595/5343 10.754 (4.175–27.697)* 0.000 97.8 1.683 (0.979–2.891) 0.023 34.8 1.178 (0.954–1.455) 0.012 39.9 1.209 (0.964–1.517) 0.002 48.9 1.632 (1.001–2.660) 0.055 26.3
Source of control
 HB 1972/3099 10.381 (3.513–30.677)* 0.000 97.4 2.652 (1.810–3.886) 0.767 0.0 1.335 (1.075–1.657) 0.093 24.7 1.405 (1.146–1.721)* 0.114 21.4 2.460 (1.686–3.590)* 0.867 39.0
 PB 623/2244 11.377 (1.472–87.963)* 0.000 98.6 1.029 (0.415–2.551) 0.068 39.3 0.913 (0.662–1.259) 0.205 13.5 0.928 (0.639–1.347) 0.074 37.9 1.632 (1.001–2.660) 0.105 26.3
Ethnicity
 Asian 2438/5147 13.628 (4.922–37.731) 0.000 97.8 1.577 (0.817–3.043) 0.013 42.9 1.168 (0.920–1.483) 0.006 44.5 1.192 (0.923_1.539) 0.001 54.9 1.553 (0.851–2.834) 0.031 35.2
Cancer type
 HCC 590/3030 42.180 (27.970–63.612)* 0.007 63.8 0.718 (0.070–7.340) 0.077 46.2 1.206 (0.706–2.062) 0.007 63.7 1.192 (0.668–2.127) 0.003 69.1 0.716 (0.080–6.438) 0.094 41.3
HWE
 Y 2382/4919 10.585 (3.663–30.581) 0.000 98.0 2.133 (1.317–3.455)* 0.217 8.5 1.216 (0.975–1.518) 0.012 40.1 1.260 (0.992–1.601) 0.003 49.3 2.063 (1.350–3.154)* 0.296 3.3
 N 213/424 12.036 (8.430–17.184) – – 0.923 (0.519–1.641) – – 0.850 (0.493–1.465) – – 0.883 (0.582–1.339) – – 0.940 (0.530–1.667) – –
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Table 2C.

Results of meta-analysis for rs696 polymorphism in NFKBA and cancer susceptibility.

Variables (rs696) Case/ control C vs. T CC vs. TT CT vs. TT CC+CT vs. TT CC vs. CT+TT
OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%) OR (95% CI) Pa I2 (%)
Total 3556/5705 0.952 (0.894–1.014) 0.121 13.8 0.891 (0.783–1.013) 0.194 79.5 0.884 (0.738–1.058) 0.044 24.6 0.879 (0.787–0.982)* 0.107 15.3 0.946 (0.811–1.103) 0.025 29.5
Ethnicity
 Caucasian 1670/1857 0.971 (0.882–1.069) 0.034 0.0 0.930 (0.766–1.128) 0.055 36.5 0.809 (0.676–0.969)* 0.459 0.0 0.851 (0.719–1.007) 0.304 3.1 1.002 (0.718–1.399) 0.010 53.7
 Asian 1886/3848 0.939 (0.863–1.021) 0.431 42.6 0.861 (0.725–1.023) 0.527 0.0 0.921 (0.691–1.227) 0.015 45.8 0.901 (0.778–1.044) 0.054 32.5 0.923 (0.798–1.068) 0.306 2.9
Source of control
 PB 2018/2151 0.963 (0.882–1.051) 0.047 34.2 0.906 (0.759–1.081) 0.080 27.1 0.908 (0.687–1.200) 0.050 33.4 0.887 (0.765–1.028) 0.075 28.1 0.945 (0.718–1.243) 0.016 45.0
 HB 1538/3554 0.941 (0.858–1.031) 0.397 0.0 0.875 (0.726–1.054) 0.439 0.0 0.868 (0.656–1.148) 0.093 28.3 0.870 (0.736–1.028) 0.205 11.9 0.942 (0.781–1.136) 0.165 16.9
Cancer type
 HL 514/414 0.792 (0.656–0.956)* 0.116 34.8 0.658 (0.448–0.965)* 0.076 46.6 1.126 (0.408–3.111) 0.118 34.8 0.758 (0.534–1.077) 0.080 45.3 0.734 (0.562–0.958)* 0.347 0.0
 CRC 1355/2020 1.003 (0.907–1.110) 0.269 5.7 1.014 (0.825–1.2480 0.702 0.0 0.901 (0.673–1.206) 0.184 16.7 0.908 (0.760–1.086) 0.726 0.0 0.995 (0.680–1.456) 0.009 62.4
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I2 – 0–25, means no heterogeneity; 25–50, means modest heterogeneity; >50, means high heterogeneity; HWE – Hardy-Weinberg equilibrium; Y – polymorphisms conformed to HWE in the control group; N – polymorphisms did not conform to HWE in the control group; Pa – P value of Q test for heterogeneity test; *means statistically significant (P<0.05); The source of control, HB – hospital-based; PB – population-based; HCC – hepatocellular carcinoma; HL – Hodgkin lymphoma; CRC – colorectal cancer; BC – breast cancer.

Table 3.

Methodological quality of the included studies according to the Newcastle-Ottawa Scale.

Author Ethnicity Adequacy of Case Definition Representativeness of the Cases Selection of Controls Definition of Controls Comparability Cases/ Controls Ascertainment of exposure Same method of ascertainment Non-response rate
rs2233406 Lu et al. Asian * * NA * ** * * *
Zhang et al. Asian * * NA * ** * * *
Cheng et al. Asian * * NA * ** * * *
Lin et al. Asian * * NA * ** * * *
Tan et al. Asian * * NA * ** * * *
Wang et al. Asian * * NA * ** * * *
Wang et al. Asian * * NA * ** * * *
Wang et al. Asian * * NA * ** * * *
He et al. Asian * * NA * ** * * *
Han et al. Asian * * NA * ** * * *
Umar et al. Asian * * * * ** * * *
rs3138053 Lin et al. Asian * * NA * ** * * *
Tan et al. Asian * * NA * ** * * *
Gao et al. Asian * * * * ** * * *
Spink et al. Caucasian * * * NA ** * * *
He et al. Asian * * NA * ** * * *
Han et al. Asian * * NA * ** * * *
Zhang et al. Asian * * * * ** * * *
Cheng et al. Asian * * NA * ** * * *
rs696 Umar et al. Asian * * * * ** * * *
Gao et al. Asian * * NA * ** * * *
Gao et al. Caucasian * * NA * ** * * *
Zhang et al. Asian * * NA * ** * * *
Gao et al. Asian * * * * ** * * *
Osborne et al. Caucasian * * * NA ** * * *
Chang et al. Caucasian * * * NA ** * * *
Han et al. Asian * * NA * ** * * *
Song et al. Caucasian * * * * ** * * *
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This table identifies ‘high’ quality choices with a ‘star’. A study can be awarded a maximum of one star for each numbered item within the Selection and Exposure categories. A maximum of two stars can be given for Comparability. *, Yes; NA – not applicable. (http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm).

Figure 2A.

Figure 2A

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Meta-analysis of the association between NFKBIA rs3138053 polymorphism and overall cancer susceptibility (C vs. T).

Figure 2B.

Figure 2B

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Meta-analysis of the association between NFKBIA rs696 polymorphism and overall cancer susceptibility (CC+CT vs. TT).

Subgroup analysis

In the subgroup meta-analysis by cancer type, the rs3138053 polymorphism of NFKBIA was revealed to be an important factor in HCC cancer susceptibility, and the pooled results were statistically significant (C vs. T: OR=42.180, 95%CI=27.970–63.612, Pheterogeneity=0.007; Table 2B). Some significantly decreased susceptibility of the rs696 polymorphism of NFKBIA was observed in Hodgkin lymphoma (C vs. T: OR=0.792, 95%CI=0.656–0.956, Pheterogeneity=0.116; CC vs. TT: OR=0.658, 95%CI=0.448–0.965, Pheterogeneity=0.076; CC vs. CT+TT: OR=0.734, 95%CI=0.562–0.958, Pheterogeneity=0.347; Table 2C). The source analysis indicated positive association of the rs3138053 polymorphism in the hospital-based group (C vs. T: OR=10.381, 95%CI=3.513–30.677, Pheterogeneity=0.000; CC+TC vs. TT: OR=1.405, 95%CI=1.146–1.721, Pheterogeneity=0.114; CC vs. TC+TT: OR=2.460, 95%CI=1.686–3.590, Pheterogeneity=0.867; Table 2B) and the population-based group (C vs. T: OR=11.377, 95%CI=1.472–87.963, Pheterogeneity=0.000; Table 2B). Caucasians seems to benefit more from the polymorphism of rs696 (CT vs. TT: OR=0.809, 95%CI=0.676–0.969, Pheterogeneity=0.459; Table 2C) than Asians (CT vs. TT: OR=0.921, 95%CI=0.691–1.227, Pheterogeneity=0.015; Table 2C). In addition, polymorphisms that conformed to HWE in the control group showed positive association in rs2233406 (CC vs. CT+TT: OR=1.535, 95%CI=1.027–2.296, Pheterogeneity=0.099; Figure 2C and Table 2A) and rs3138053 (CC vs. TT: OR=2.133, 95%CI=1.317–3.455, Pheterogeneity=0.217; CC vs. TC+TT: OR=2.063, 95%CI=1.350–3.154, Pheterogeneity=0.296; Table 2B).

Figure 2C.

Figure 2C

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Subgroup analysis of the association between NFKBIA polymorphisms and overall cancer risk by HWE (Hardy-Weinberg equilibrium).

Sensitivity analysis and publication bias risk

The sensitivity analyses were conducted by excluding each single case-control study in turn, and no separate study shows an influence on the pooled OR. Begg’s funnel plot and Egger’s test were performed to assess the risk of publication bias and no visual publication bias was shown (rs3138053: C vs. T: P=0.181 for egger’s test; rs696: CC+CT vs. TT: P=0.552 for Egger’s test, Figure 3A; rs2233406: CC vs. CT+TT: P=0.175 for Egger’s test, Figure 3B).

Figure 3A.

Figure 3A

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Publication bias examinations by Begg’s funnel plots and Egger’s test (rs696: CC+CT vs. TT). Asymmetrical plots or P<0.10 suggest potential bias. Each point represents a separate study for the indicated association, and the horizontal line depicts mean effect size. Logor natural logarithm of OR; s.e. standard error.

Figure 3B.

Figure 3B

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Publication bias examinations by Begg’s funnel plots and Egger’s test (rs2233406: CC vs. CT+TT). Asymmetrical plots or P<0.10 suggest potential bias. Each point represents a separate study for the indicated association, and the horizontal line depicts mean effect size. Logor natural logarithm of OR; s.e. standard error.

Discussion

The activation and translocation of NF-κB to the nucleus modulate the translation of the genes involved in inflammatory and immune activities, cell adhering, differentiating, growing, angiogenesis, and apoptosis through kinases, which leads to the phosphorylation, ubiquitination, and degradation of IκBs [37]. The p50 subunit, encoded by the NF-κB, has several common polymorphisms in the promoter region. The promoter sequence polymorphisms contribute to an increased expression of NF-κB messenger (m) RNA. NF-κB is important to cancer pathogenesis, preventing apoptosis and enhancing growth and survival by the upregulation of several genes [38]. Individual single-nucleotide polymorphisms (rs2233406, rs3138053, and rs696) in the NFKBIA gene may affect expression and function of the protein. Specifically, allelic differences in the NFKBIA promoter and 30UTR region may change IκBa expression and affect complex formation with NF-κB. In this way, cell growth and anti-apoptosis are regulated [39].

Li et al. [40] and Zou et al. [41] reported that genetic polymorphisms of the NFKBIA gene were associated with cancer susceptibility and severity in sporadic colorectal cancer and oral cancer. Klein et al. [42] proved that the polymorphism of NFKBIA was linked to Crohn’s disease. Other studies also drew similar conclusions in breast [9], prostate [13], and stomach [14] cancers. However, results from studies in various geographic areas were not consistent. To the best of our knowledge, this is the first meta-analysis to assess the relationship between these 3 polymorphisms (rs2233406, rs3138053, and rs696) of NFKBIA gene and overall cancer susceptibility. Our analysis validated that individuals with the variant allele (rs3138053) appear to have increased susceptibility to cancer. Interestingly, we found a contrary effect of variant allele (rs696), which seems to be associated with decreased susceptibility to cancer. In the subgroup analysis by cancer type, significantly decreased susceptibility of Hodgkin lymphoma with rs696 polymorphism was observed, whereas no significant association was found among studies of colorectal cancer.

The heterogeneity test in the present study showed that there was no evident heterogeneity in terms of the 3 polymorphisms for all cancer types between the studies. Additionally, various cancer categories did not contribute to the overall heterogeneity in association with the polymorphisms, suggesting that our present combined analyses were unbiased, regardless of cancer types. Despite the obvious advantages of our meta-analysis containing large sample sizes, some limitations of this study should be mentioned. The complex factors such as age, sex, and region may bring some bias. Studies reported in other languages may bias the present results because the negative findings are usually difficult to be included. Therefore, further study is needed to evaluate the independent and combined effect of these polymorphisms.

Conclusions

In conclusion, this meta-analysis indicated that the rs3138053 polymorphism of NFKBIA gene is a candidate for susceptibility to overall cancers, especially in HCC cancer, while the rs696 plays a protective role against cancers, especially in Hodgkin lymphoma patients and in Caucasians. Moreover, because of the limitations described above, well-designed studies considering gene-gene and gene-environment effects should be conducted to confirm these relationships.

Footnotes

Source of support: The work by C.L. and Z.L. was supported by Shenzhen Health and Family Planning Key Discipline Promotion Project (No. 201506026)

Conflict of interest statement

None.

References

  • 1.Domingo-Domenech J, Oliva C, Rovira A, et al. Interleukin 6, a nuclear factor-kappaB target, predicts resistance to docetaxel in hormone-independent prostate cancer and nuclear factor-kappaB inhibition by PS-1145 enhances docetaxel antitumor activity. Clin Cancer Res. 2006;12(18):5578–86. doi: 10.1158/1078-0432.CCR-05-2767. [DOI] [PubMed] [Google Scholar]
  • 2.Ahn KS, Sethi G, Aggarwal BB. Nuclear factor-kappa B: from clone to clinic. Curr Mol Med. 2007;7(7):619–37. doi: 10.2174/156652407782564363. [DOI] [PubMed] [Google Scholar]
  • 3.Naugler WE, Karin M. NF-kappaB and cancer-identifying targets and mechanisms. Curr Opin Genet Dev. 2008;18(1):19–26. doi: 10.1016/j.gde.2008.01.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Lind DS, HS, Malaty J, Rekkas S, et al. Nuclear factor-kappa B is upregulated in colorectal cancer. Surgery. 2001;130:363–69. doi: 10.1067/msy.2001.116672. [DOI] [PubMed] [Google Scholar]
  • 5.Oltulu YM, Coskunpinar E, Ozkan G, et al. Investigation of NF-kappaB1 and NF-kappaBIA gene polymorphism in non-small cell lung cancer. Biomed Res Int. 2014;2014:530381. doi: 10.1155/2014/530381. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Yang JJ, Cho LY, Ko KP, et al. Interaction effects between genes involved in the AKT signaling pathway and phytoestrogens in gastric carcinogenesis: a nested case-control study from the Korean Multi-Center Cancer Cohort. Mol Nutr Food Res. 2012;56(11):1617–26. doi: 10.1002/mnfr.201200169. [DOI] [PubMed] [Google Scholar]
  • 7.Shiels MS, Engels EA, Shi J, et al. Genetic variation in innate immunity and inflammation pathways associated with lung cancer risk. Cancer. 2012;118(22):5630–36. doi: 10.1002/cncr.27605. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Huang D, Yang L, Liu Y, et al. Functional polymorphisms in NFkappaB1/IkappaBalpha predict risks of chronic obstructive pulmonary disease and lung cancer in Chinese. Hum Genet. 2013;132(4):451–60. doi: 10.1007/s00439-013-1264-9. [DOI] [PubMed] [Google Scholar]
  • 9.Curran JE, Weinstein SR, Griffiths LR. Polymorphic variants of NFKB1 and its inhibitory protein NFKBIA, and their involvement in sporadic breast cancer. Cancer Lett. 2002;188(1–2):103–7. doi: 10.1016/s0304-3835(02)00460-3. [DOI] [PubMed] [Google Scholar]
  • 10.Lewander A, Arbman G, Sun XF. Polymorphism in the promoter region of the NFKBIA gene is rare in Swedish and Chinese colorectal cancer patients and controls. Mol Med Rep. 2010;3(1):69–74. doi: 10.3892/mmr_00000220. [DOI] [PubMed] [Google Scholar]
  • 11.White KL, Vierkant RA, Phelan CM, et al. Polymorphisms in NF-kappaB inhibitors and risk of epithelial ovarian cancer. BMC Cancer. 2009;9:170. doi: 10.1186/1471-2407-9-170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Shafi’i MSM, SS, Mustapha MA. The genetic variation A>G at 3′ UTR of nuclear factor kappa B 1 A (NFkB1A) influences susceptibility of sporadic colorectal cancer in Malaysian population. Int Med J. 2012;19(2):98–101. [Google Scholar]
  • 13.Zhang P, Wei Q, Li X, et al. A functional insertion/deletion polymorphism in the promoter region of the NFKB1 gene increases susceptibility for prostate cancer. Cancer Genet Cytogenet. 2009;191(2):73–77. doi: 10.1016/j.cancergencyto.2009.01.017. [DOI] [PubMed] [Google Scholar]
  • 14.Lo SS, Chen JH, Wu CW, Lui WY. Functional polymorphism of NFKB1 promoter may correlate to the susceptibility of gastric cancer in aged patients. Surgery. 2009;145(3):280–85. doi: 10.1016/j.surg.2008.11.001. [DOI] [PubMed] [Google Scholar]
  • 15.Gao J, Pfeifer D, He L-J, et al. Association ofNFKBIApolymorphism with colorectal cancer risk and prognosis in Swedish and Chinese populations. Scand J Gastroenterol. 2007;42(3):345–50. doi: 10.1080/00365520600880856. [DOI] [PubMed] [Google Scholar]
  • 16.Bodelon C, Madeleine MM, Johnson LG, et al. Genetic variation in the TLR and NF-kappaB pathways and cervical and vulvar cancer risk: a population-based case-control study. Int J Cancer. 2014;134(2):437–44. doi: 10.1002/ijc.28364. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Bu H, Rosdahl I, Sun XF, Zhang H. Importance of polymorphisms in NF-kappaB1 and NF-kappaBIalpha genes for melanoma risk, clinicopathological features and tumor progression in Swedish melanoma patients. J Cancer Res Clin Oncol. 2007;133(11):859–66. doi: 10.1007/s00432-007-0228-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Marcos M, Pastor I, Gonzalez-Sarmiento R, Laso FJ. A functional polymorphism of the NFKB1 gene increases the risk for alcoholic liver cirrhosis in patients with alcohol dependence. Alcohol Clin Exp Res. 2009;33(11):1857–62. doi: 10.1111/j.1530-0277.2009.01023.x. [DOI] [PubMed] [Google Scholar]
  • 19.Kim LH, Shin HD, Park BL, et al. Identification of variants in NFKBIA and association analysis with hepatocellular carcinoma risk among chronic HBV patients. Hum Mutat. 2003;21(6):652–53. doi: 10.1002/humu.9146. [DOI] [PubMed] [Google Scholar]
  • 20.Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60. doi: 10.1136/bmj.327.7414.557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst. 1959;22(4):719–48. [PubMed] [Google Scholar]
  • 22.DerSimonian R, Laird N. Meta-analysis in clinical trials. Controll Clin Trials. 1986;7(3):177–88. doi: 10.1016/0197-2456(86)90046-2. [DOI] [PubMed] [Google Scholar]
  • 23.Chang ET, Birmann BM, Kasperzyk JL, et al. Polymorphic variation in NFKB1 and other aspirin-related genes and risk of Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev. 2009;18(3):976–86. doi: 10.1158/1055-9965.EPI-08-1130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Cheng CW, Su JL, Lin CW, et al. Effects of NFKB1 and NFKBIA gene polymorphisms on hepatocellular carcinoma susceptibility and clinicopathological features. PloS One. 2013;8(2):e56130. doi: 10.1371/journal.pone.0056130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Gao J, Xu HL, Gao S, et al. Genetic polymorphism of NFKB1 and NFKBIA genes and liver cancer risk: a nested case-control study in Shanghai, China. BMJ Open. 2014;4(2):e004427. doi: 10.1136/bmjopen-2013-004427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Han X, Zhang JJ, Yao N, et al. Polymorphisms in NFKB1 and NFKBIA Genes Modulate the Risk of Developing Prostate Cancer among Han Chinese. Med Sci Monit. 2015;21:1707–15. doi: 10.12659/MSM.893471. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.He Y, Zhang H, Yin J, et al. IkappaBalpha gene promoter polymorphisms are associated with hepatocarcinogenesis in patients infected with hepatitis B virus genotype C. Carcinogenesis. 2009;30(11):1916–22. doi: 10.1093/carcin/bgp226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Lin CW, Hsieh YS, Hsin CH, et al. Effects of NFKB1 and NFKBIA gene polymorphisms on susceptibility to environmental factors and the clinicopathologic development of oral cancer. PloS One. 2012;7(4):e35078. doi: 10.1371/journal.pone.0035078. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Lu ZH, Gu XJ, Shi KZ, et al. Association between genetic polymorphisms of inflammatory response genes and the risk of ovarian cancer. J Formos Med Assoc. 2015 doi: 10.1016/j.jfma.2015.01.002. [Epub ahead of print] [DOI] [PubMed] [Google Scholar]
  • 30.Osborne J, Lake A, Alexander FE, et al. Germline mutations and polymorphisms in the NFKBIA gene in Hodgkin lymphoma. Int J Cancer. 2005;116(4):646–51. doi: 10.1002/ijc.21036. [DOI] [PubMed] [Google Scholar]
  • 31.Song S, Chen D, Lu J, et al. NFkappaB1 and NFkappaBIA polymorphisms are associated with increased risk for sporadic colorectal cancer in a southern Chinese population. PloS One. 2011;6(6):e21726. doi: 10.1371/journal.pone.0021726. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Spink CF, Gray LC, Davies FE, et al. Haplotypic structure across the I kappa B alpha gene (NFKBIA) and association with multiple myeloma. Cancer Lett. 2007;246(1–2):92–99. doi: 10.1016/j.canlet.2006.02.001. [DOI] [PubMed] [Google Scholar]
  • 33.Tan SC, Suzairi MS, Aizat AA, Aminudin MM, et al. Gender-specific association of NFKBIA promoter polymorphisms with the risk of sporadic colorectal cancer. Med Oncol. 2013;30(4):693. doi: 10.1007/s12032-013-0693-6. [DOI] [PubMed] [Google Scholar]
  • 34.Umar M, Upadhyay R, Kumar S, et al. Association of common polymorphisms in TNFA, NFkB1 and NFKBIA with risk and prognosis of esophageal squamous cell carcinoma. PloS One. 2013;8(12):e81999. doi: 10.1371/journal.pone.0081999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Wang Z, Liu Q-L, Sun W, et al. Genetic polymorphisms in inflammatory response genes and their associations with breast cancer risk. Croat Med J. 2014;55(6):638–46. doi: 10.3325/cmj.2014.55.638. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Zhang Q. Effect of functional nuclear factor kappaB genetic polymorphisms on hepatitis B virus persistence and their interactions with viral mutations on the risk of hepatocellular carcinoma. Annals of Oncology Advance Access. 2014 doi: 10.1093/annonc/mdu451. [DOI] [PubMed] [Google Scholar]
  • 37.Sun Z, Andersson R. NF-kappaB activation and inhibition: a review. Shock. 2002;18(2):99–106. doi: 10.1097/00024382-200208000-00001. [DOI] [PubMed] [Google Scholar]
  • 38.Charbonneau B, Block MS, Bamlet WR, et al. Risk of ovarian cancer and the NF-kappaB pathway: genetic association with IL1A and TNFSF10. Cancer Res. 2014;74(3):852–61. doi: 10.1158/0008-5472.CAN-13-1051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Wang S, Zhang M, Zeng Z, et al. IkappaBalpha polymorphisms were associated with increased risk of gastric cancer in a southern Chinese population: a case-control study. Life Sci. 2011;88(17–18):792–97. doi: 10.1016/j.lfs.2011.02.016. [DOI] [PubMed] [Google Scholar]
  • 40.Li RN, Hung YH, Lin CH, et al. Inhibitor IkappaBalpha promoter functional polymorphisms in patients with rheumatoid arthritis. J Clin Immunol. 2010;30(5):676–80. doi: 10.1007/s10875-010-9439-9. [DOI] [PubMed] [Google Scholar]
  • 41.Zou YF, YF, Feng XL, Tao JH, Ding N. Association between NFKB1-94ins/delATTG promoter polymorphism and cancer risk: a metaanalysis. Cancer Invest. 2011;29:78–85. doi: 10.3109/07357907.2010.535054. [DOI] [PubMed] [Google Scholar]
  • 42.Klein W, Tromm A, Folwaczny C, et al. A polymorphism of the NFKBIA gene is associated with Crohn’s disease patients lacking a predisposing allele of the CARD15 gene. Int J Colorectal Dis. 2004;19(2):153–56. doi: 10.1007/s00384-003-0531-y. [DOI] [PubMed] [Google Scholar]

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