# MTHFR C677T Gene Polymorphism and Head and Neck Cancer Risk: A Meta-Analysis Based on 23 Publications

Authors: Yu-Ming Niu; Mo-Hong Deng; Wen Chen; Xian-Tao Zeng; Jie Luo
Journal: Disease Markers
 (2015)

---

## Abstract

Objective. Conflicting results on the association between MTHFR polymorphism and head and neck cancer (HNC) risk were reported. We therefore performed a meta-analysis to derive a more precise relationship between MTHFR C677T polymorphism and HNC risk. Methods. Three online databases of PubMed, Embase, and CNKI were researched on the associations between MTHFR C677T polymorphism and HNC risk. Twenty-three published case-control studies involving 4,955 cases and 8,805 controls were collected. Odds ratios (ORs) with 95% confidence interval (CI) were used to evaluate the relationship between MTHFR C677T polymorphism and HNC risk. Sensitivity analysis, cumulative analyses, and publication bias were conducted to validate the strength of the results. Results. Overall, no significant association between MTHFR C677T polymorphism and HNC risk was found in this meta-analysis (T versus C: OR = 1.04, 95% CI = 0.92–1.18; TT versus CC: OR = 1.15, 95% CI = 0.90–1.46; CT versus CC: OR = 1.00, 95% CI = 0.85–1.17; CT + TT versus CC: OR = 1.01, 95% CI = 0.87–1.18; TT versus CC + CT: OR = 1.11, 95% CI = 0.98–1.26). In the subgroup analysis by HWE, ethnicity, study design, cancer location, and negative significant associations were detected in almost all genetic models, except for few significant risks that were found in thyroid cancer. Conclusion. This meta-analysis demonstrates that MTHFR C677T polymorphism may not be a risk factor for the developing of HNC.


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## Body

## 1. Introduction

Head and neck cancer (HNC) is the sixth most common cancer worldwide. It affects the upper aerodigestive epithelium of the paranasal sinuses, nasal cavity, oral cavity, pharynx, and larynx [1]. In 2008, approximately 633,000 new cases and 355,000 deaths occurred because of HNC particularly in South-Central Asia and Central and Eastern Europe [2, 3]. Treatment options for HNC are complicated and include surgery, radiotherapy, chemotherapy, and biological treatments that decrease the quality of life of patients with functional disabilities and facial abnormalities. HNC is a multifactorial disease that may be caused by various complex factors, including human papilloma virus (HPV) infection, lifestyle, and genetic factors [4].Smoking and alcohol consumption are the major risk factors of HNC. Genetic mutations may potentially alter the susceptibility of an individual to HNC [5]. However, only a small proportion of vulnerable individuals may develop HNC. To date, genetic mutations such as single nucleotide polymorphisms are important for tumorigenesis and increase the risk of developing HNC and other cancers.Folate is important in deoxynucleoside synthesis to provide methyl groups and in intracellular methylation reactions [6]. Low folate levels can result in uracil misincorporation during DNA synthesis, leading to chromosomal damage, breaks in DNA strands, impaired DNA repair, and DNA hypomethylation [7]. Methylenetetrahydrofolate reductase (MTHFR) is an important enzyme in folate metabolism. Epidemiological evidence suggests that the genetic variants encoding the enzymes involved in folate metabolism may increase the risk of HNC by altering DNA methylation synthesis and genomic stability. Genetic mutations in MTHFR gene alter folate level and DNA methylation that may lead to hereditary diseases and cancer development [8–10].MTHFR C677T (Ala222Val) polymorphism may result in cancer development by altering the activity of MTHFR enzyme [11]. In 2002, Weinstein et al. conducted the first study and reported a negative association between MTHFR C677T polymorphism and HNC risk [12]. Since then, numerous studies have been performed to determine the association between MTHFR C677T polymorphism and HNC risk, but the results are conflicting. In 2009, Boccia et al. conducted a meta-analysis of nine published studies [13]. Additional studies on the association between MTHFR C677T polymorphism and HNC risk have been published. Therefore, a comprehensive meta-analysis of all the relevant studies should be performed to predict this association accurately.


## 2. Materials and Methods

### 2.1. Search Strategy and Inclusion Criteria

Three online bibliographic databases (PubMed, Embase, and CNKI) were searched with the following search terms “head and neck cancer,” “oropharyngeal cancer,” “MTHFR,” “methylenetetrahydrofolate reductase,” “polymorphism,” “variant,” and “meta-analysis” in English and Chinese. Relevant studies were manually searched to identify from the references of original studies and review articles on the association between MTHFR C677T polymorphism and HNC risk that were published from 2002 (when the first study on this topic was published) to August 10, 2014. All the selected studies complied with the following three inclusion criteria: (a) case-control study on the MTHFR C677T polymorphism and HNC risk, (b) sufficient published data for estimating the odds ratios (ORs) and 95% confidence intervals (CIs), and (c) only the largest or most recent publication that was selected when multiple studies reported the same or overlapping data [14].


### 2.2. Data Extraction

Two investigators (Niu and Deng) independently extracted the following data from each included study: the first author’s name, publication date, country, ethnicity (categorized as Asian, Caucasian, and mixed race), study design, number of cases and controls subjects, Hardy-Weinberg equilibrium (HWE), minor allele frequency (MAF), and cancer location. The information from all included studies was compared in terms of accuracy, and discrepancies were discussed with a third reviewer until consensus was achieved.


### 2.3. Statistical Analysis

Crude ORs with 95% CIs were calculated to assess the strength of the correlation between MTHFR C677T polymorphism and HNC risk. Pooled ORs were calculated for allele contrast model (T versus C), codominant model (TT versus CC, CT versus CC), dominant model (TT + CT versus CC), and recessive model (TT versus CC + CT), respectively. Subgroup analysis was performed to statistically analyze HWE, ethnicity, study design, and cancer location. Heterogeneity assumption was calculated based on theI
2 statistics with low, moderate, and high I
2 values of 25%, 50%, and 75%, respectively [15, 16]. OR estimation of each models was calculated by using the fixed-effects model (Mantel-Haenszel method) if the I
2
≤
50
% (which indicated a lack of heterogeneity) [17]. Otherwise, a random-effects model (the DerSimonian and Laird method) was used [18]. Potential publication bias was estimated by the Egger’s linear regression test [19]. Statistical analyses were performed using STATA version 11.0 (Stata Corporation, College Station, TX, USA). Two-sided P values were used, and P
<
0.05 was considered statistically significant.


## 2.1. Search Strategy and Inclusion Criteria

Three online bibliographic databases (PubMed, Embase, and CNKI) were searched with the following search terms “head and neck cancer,” “oropharyngeal cancer,” “MTHFR,” “methylenetetrahydrofolate reductase,” “polymorphism,” “variant,” and “meta-analysis” in English and Chinese. Relevant studies were manually searched to identify from the references of original studies and review articles on the association between MTHFR C677T polymorphism and HNC risk that were published from 2002 (when the first study on this topic was published) to August 10, 2014. All the selected studies complied with the following three inclusion criteria: (a) case-control study on the MTHFR C677T polymorphism and HNC risk, (b) sufficient published data for estimating the odds ratios (ORs) and 95% confidence intervals (CIs), and (c) only the largest or most recent publication that was selected when multiple studies reported the same or overlapping data [14].


## 2.2. Data Extraction

Two investigators (Niu and Deng) independently extracted the following data from each included study: the first author’s name, publication date, country, ethnicity (categorized as Asian, Caucasian, and mixed race), study design, number of cases and controls subjects, Hardy-Weinberg equilibrium (HWE), minor allele frequency (MAF), and cancer location. The information from all included studies was compared in terms of accuracy, and discrepancies were discussed with a third reviewer until consensus was achieved.


## 2.3. Statistical Analysis

Crude ORs with 95% CIs were calculated to assess the strength of the correlation between MTHFR C677T polymorphism and HNC risk. Pooled ORs were calculated for allele contrast model (T versus C), codominant model (TT versus CC, CT versus CC), dominant model (TT + CT versus CC), and recessive model (TT versus CC + CT), respectively. Subgroup analysis was performed to statistically analyze HWE, ethnicity, study design, and cancer location. Heterogeneity assumption was calculated based on theI
2 statistics with low, moderate, and high I
2 values of 25%, 50%, and 75%, respectively [15, 16]. OR estimation of each models was calculated by using the fixed-effects model (Mantel-Haenszel method) if the I
2
≤
50
% (which indicated a lack of heterogeneity) [17]. Otherwise, a random-effects model (the DerSimonian and Laird method) was used [18]. Potential publication bias was estimated by the Egger’s linear regression test [19]. Statistical analyses were performed using STATA version 11.0 (Stata Corporation, College Station, TX, USA). Two-sided P values were used, and P
<
0.05 was considered statistically significant.


## 3. Results

### 3.1. Study Characteristics

One hundred thirteen articles were retrieved by literature search. After a careful evaluation, twenty-three related case-control studies on the relationship between MTHFR C677T polymorphism and HNC risk were included in this meta-analysis (Figure1) [12, 20–41]. Table 1 presents the main characteristics of these studies. Of the 23 studies, 9 studies focused on Asian populations [20, 24, 28, 29, 31, 33, 37–39], 10 studies described Caucasian populations [21–23, 25, 27, 30, 32, 35, 40, 41], and 4 studies assessed mixed populations [12, 26, 34, 36]. The diverse genotyping methods included PCR-RFLP and TaqMan, and the genotypic distribution of the controls was consistent with the HWE in all except four studies [23, 25, 26, 39].Table 1
Characteristics of case-control studies included in the meta-analysis.
Genotype distribution
First author
Year
Country/region
Racial descent
Source of controls
Case
Control
Case
Control
Genotyping type
P for HWE
MAF
Location
CC
CT
TT
CC
CT
TT
Weinstein [12]
2002
Puerto Rico
Mixed
Population control
135
146
67
53
15
69
62
15
PCR-RFLP
0.85
0.32
Oral
Kureshi [20]
2004
Pakistan
Asian
NA
50
54
32
18
0
32
18
4
PCR-RFLP
0.52
0.24
HN
Neumann [21]
2005
USA
Caucasian
Hospital control
537
545
258
244
35
278
216
51
PCR-RFLP
0.34
0.29
HN
Capaccio [22]
2005
Italy
Caucasian
Population control
65
100
18
33
14
36
46
18
PCR-RFLP
0.62
0.41
HN
Vairaktaris [23]
2006
Greece
Caucasian
Population control
110
120
28
76
6
45
65
10
PCR-RFLP
0.04
0.35
Oral
Suzuki [24]
2007
Japan
Asian
Hospital control
237
711
88
113
36
252
331
128
TaqMan
0.29
0.41
HN
Reljic [25]
2007
Croatia
Caucasian
Population control
81
102
45
27
9
35
59
8
PCR-RFLP
0.01
0.37
HN
Hsiung [26]
2007
USA
Mixed
Population control
277
524
128
149
218
306
NA
NA
NA
HN
Hung [27]
2007
Europe
Caucasian
Hospital control
779
2530
373
327
79
1272
1025
233
TaqMan
0.20
0.30
HN
Solomon [28]
2008
India
Asian
NA
126
100
48
55
23
48
42
10
PCR-RFLP
0.86
0.31
Oral
Siraj [35]
2008
Saudi Arabia
Caucasian
Population control
49
511
30
18
1
372
126
13
PCR-RFLP
0.55
0.15
Thyroid
Ni [29]
2008
China
Asian
Hospital control
207
400
48
95
64
152
187
61
PCR-RFLP
0.78
0.39
Laryngeal
Rodrigues [36]
2010
Brazil
Mixed
Population control
100
100
44
43
13
46
40
14
PCR-RFLP
0.28
0.34
HN
Kruszyna [30]
2010
Poland
Caucasian
Population control
131
250
69
52
10
126
104
20
PCR-RFLP
0.82
0.29
Laryngeal
Cao [37]
2010
China
Asian
Population control
511
552
310
169
32
334
188
30
PCR-RFLP
0.60
0.23
NP
Tsai [31]
2011
Taiwan
Asian
Hospital control
620
620
391
186
43
322
236
62
PCR-RFLP
0.06
0.29
Oral
Supic [32]
2011
Serbia
Caucasian
Hospital control
96
162
50
32
14
80
66
16
PCR-RFLP
0.66
0.30
Oral
Sailasree [33]
2011
India
Asian
Hospital control
101
138
92
8
1
108
29
1
PCR-RFLP
0.53
0.11
Oral
Prasad [38]
2011
India
Asian
NA
97
241
86
10
1
228
12
1
PCR-RFLP
0.07
0.03
Thyroid
Fard-Esfahani [39]
2011
Iran
Asian
Hospital control
154
198
69
71
14
82
108
8
multiplex PCR
<0.01
0.31
Thyroid
Ozdemir [40]
2012
Turkey
Caucasian
NA
60
50
28
25
7
33
14
3
Real-time PCR
0.38
0.20
Thyroid
Galbiatti [34]
2012
Brazil
Mixed
Population control
322
531
130
147
45
226
250
55
PCR-RFLP
0.24
0.34
HN
Vylliotis [41]
2013
Greek/Germany
Caucasian
Population control
110
120
76
28
6
65
45
10
PCR-RFLP
0.58
0.27
Oral
HWE in controls.
MAF: minor allele frequency in controls.
NA: not applicable.
HN: head and neck.
NP: nasopharyngeal.Figure 1
Flowchart of the study selection process.


### 3.2. Meta-Analysis

The main results of this meta-analysis and heterogeneity test are presented in Table2. Overall, no significant association between MTHFR C677T polymorphism and HNC risk was found in this meta-analysis (T versus C: OR = 1.04, 95% CI = 0.92–1.18, P
=
0
.
55, I
2
=
72.5
%; TT versus CC: OR = 1.15, 95% CI = 0.90–1.46, P
=
0
.
26, I
2
=
56.8
%; CT versus CC: OR = 1.00, 95% CI = 0.85–1.17, P
=
0
.
9
9, I
2
=
65.8
%; CT + TT versus CC: OR = 1.01, 95% CI = 0.87–1.18, P
=
0
.
8
6, I
2
=
69.7
% (Figure 2); TT versus CC + CT: OR = 1.11, 95% CI = 0.98–1.26, P
=
0
.
10, I
2
=
49.8
%). Subsequent analysis of the HWE studies showed similar lack of associations between MTHFR C677T polymorphism and HNC risk (T versus C: OR = 1.05, 95% CI = 0.92–1.21, P
=
0
.
47, I
2
=
75.0
%; TT versus CC: OR = 1.14, 95% CI = 0.88–1.48, P
=
0
.
3
4, I
2
=
61.4
%; CT versus CC: OR = 1.02, 95% CI = 0.88–1.19, P
=
0
.
76, I
2
=
60.3
%; CT + TT versus CC: OR = 1.03, 95% CI = 0.88–1.20, P
=
0
.
69, I
2
=
68.4
%; TT versus CC + CT: OR = 1.11, 95% CI = 0.89–1.39, P
=
0
.
3
5, I
2
=
52.2
%). Further, stratified analysis of ethnicity, study design, cancer location, and smoking habits showed no significant association between MTHFR C677T polymorphism and HNC risk. Notable, slight increased risks were found in the risk of developing thyroid cancer (T versus C: OR = 1.30, 95% CI = 1.03–1.65, P
=
0
.
04, I
2
=
43.9
%; TT versus CC: OR = 2.06, 95% CI = 1.04–4.10, P
=
0
.
04, I
2
=
0.0
%).Table 2
Summary ORs and 95% CI of MTHFR C677T polymorphism and head and neck cancer risk.
T versus C
TT versus CC
CT versus CC
CT + TT versus CC
TT versus CC + CT
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)
Total
1.04
0.92–1.18
0.55
72.5
1.15
0.90–1.46
0.26
56.8
1.00
0.85–1.17
0.99
65.8
1.01
0.87–1.18
0.86
69.7
1.11
0.98–1.26
0.10
49.8
HWE
1.05
0.92–1.21
0.47
75.0
1.14
0.88–1.48
0.34
61.4
1.02
0.88–1.19
0.76
60.3
1.03
0.88–1.20
0.69
68.4
1.11
0.89–1.39
0.35
52.2
Ethnicity
Asian
1.03
0.78–1.36
0.83
86.0
1.29
0.73–2.28
0.38
79.6
0.96
0.73–1.25
0.75
70.8
1.00
0.74–1.36
0.99
80.4
1.28
0.80–2.06
0.30
74.0
Caucasian
1.39
0.89–1.20
0.65
49.1
1.04
0.85–1.27
0.66
0.0
1.04
0.81–1.35
0.75
69.5
1.05
0.83–1.33
0.67
66.3
1.01
0.84–1.22
0.90
0.0
Other
1.08
0.92–1.27
0.36
0.0
1.25
0.87–1.78
0.23
0.0
1.00
0.79–1.27
0.98
0.0
0.96
0.81–1.15
0.68
0.0
1.24
0.89–1.74
0.21
0.0
Design
PB
1.01
0.90–1.14
0.84
29.5
1.16
0.92–1.46
0.21
0.0
0.95
0.76–1.20
0.68
60.1
0.96
0.80–1.15
0.64
53.5
1.18
0.95–1.74
0.14
0.0
HB
0.98
0.77–1.25
0.86
87.9
1.09
0.69–1.74
0.71
82.9
0.94
0.72–1.22
0.72
79.1
0.96
0.72–1.27
0.76
84.3
1.07
0.72–1.58
0.74
79.2
Location
Oral
0.88
0.67–1.17
0.38
75.3
0.85
0.64–1.12
0.25
48.0
0.81
0.57–1.15
0.24
70.7
0.84
0.59–1.20
0.33
74.4
0.91
0.70–1.20
0.52
34.0
Laryngeal
1.33
0.68–2.60
0.40
90.6
1.82
0.51–6.44
0.353
86.1
1.22
0.70–2.13
0.48
70.5
1.37
0.63–3.00
0.43
86.8
1.64
0.64–4.17
0.30
77.9
Thyroid
1.30
1.03–1.65
0.04
43.9
2.06
1.04–4.10
0.04
0.0
1.48
0.84–2.62
0.17
65.9
1.53
0.92–2.53
0.10
60.5
2.02
1.04–3.92
0.04
0.0
aTest for heterogeneity.
PB: population based; HB: hospital based.Figure 2
OR of head and neck cancer associated with MTHFR C677T polymorphism for the CT + TT versus CC model in total.


### 3.3. Sensitivity Analysis and Cumulative Analysis

Each study included in this meta-analysis was deleted one by one to determine the effect of an individual dataset to the pooled ORs; the results were consistent in all of the research genetic models (Figure3 for the dominant model), indicating that our results are statistically robust (Table 3 for the dominant model). In the cumulative meta-analysis, the results always showed negative association with the increasing number of studies (Figure 4 for the dominant model).Table 3
Sensitivity analysis through deleting each study to reflect the influence of the individual dataset to the pooled ORs in CT + TT versus CC model.
Study omitted
Estimate
95% conf. interval
Weinstein et al. (2002) [12]
1.0189941
0.87112659
1.1919612
Kureshi et al. (2004) [20]
1.0193014
0.87365657
1.1892264
Capaccio et al. (2005) [22]
1.0022544
0.85940462
1.1688484
Neumann et al. (2005) [21]
1.007629
0.85724384
1.184396
Vairaktaris et al. (2006) [23]
0.99266464
0.85276967
1.155509
Hung et al. (2007) [27]
1.0095826
0.85412776
1.193331
Hsiung et al. (2007) [26]
1.0266064
0.87583935
1.2033266
Reljic et al. (2007) [25]
1.0438555
0.90103817
1.2093099
Suzuki et al. (2007) [24]
1.0195761
0.86892009
1.1963534
Ni et al. (2008) [29]
0.97470093
0.84459507
1.1248491
Siraj et al. (2008) [35]
0.9954946
0.85466665
1.1595275
Solomon et al. (2008) [28]
0.99778956
0.85548556
1.1637648
Cao et al. (2010) [37]
1.0159856
0.86369467
1.1951293
Kruszyna et al. (2010) [30]
1.0192744
0.87083119
1.1930214
Rodrigues et al. (2010) [36]
1.0113139
0.86534274
1.1819084
Fard-Esfahani et al. (2011) [39]
1.0215796
0.87302911
1.1954068
Prasad and Wilkhoo (2011) [38]
0.99519187
0.85606372
1.1569312
Sailasree et al. (2011) [33]
1.0387301
0.89613956
1.2040093
Supic et al. (2011) [32]
1.0191994
0.87169868
1.1916586
Tsai et al. (2011) [31]
1.0461444
0.90586507
1.2081468
Galbiatti et al. (2012) [34]
1.0096141
0.85997182
1.1852955
Ozdemir et al. (2012) [40]
0.99327004
0.85463184
1.1543981
Vylliotis et al. (2013) [41]
1.0391399
0.89383554
1.2080653
Combined
1.0136127
0.87153344
1.178854Figure 3
Sensitivity analysis through deletion of one study at a time to reflect the influence of the individual dataset to the pooled ORs in CT + TT versus CC model.Figure 4
Cumulative meta-analyses according to publication year in CT + TT versus CC model.


### 3.4. Publication Bias

Funnel plot and Egger’s test were performed to estimate the publication bias among the included studies. Shapes of the funnel plots for all genetic models did not reveal any asymmetrical evidence (Figure5 showed the funnel plots for the dominant model in all populations). The result was further supported by the data with Egger’s test. No significant publication bias was found in this meta-analysis (P
=
0
.
85 for T versus C; P
=
0
.
86 for TT versus CC; P
=
0
.
91 for CT versus CC; P
=
0
.
72 for CT + TT versus CC; P
=
0
.
97 for TT versus CC + CT).Figure 5
Funnel plot analysis to detect publication bias for CT + TT versus CC model. Each point represents a separate study for the indicated association.


## 3.1. Study Characteristics

One hundred thirteen articles were retrieved by literature search. After a careful evaluation, twenty-three related case-control studies on the relationship between MTHFR C677T polymorphism and HNC risk were included in this meta-analysis (Figure1) [12, 20–41]. Table 1 presents the main characteristics of these studies. Of the 23 studies, 9 studies focused on Asian populations [20, 24, 28, 29, 31, 33, 37–39], 10 studies described Caucasian populations [21–23, 25, 27, 30, 32, 35, 40, 41], and 4 studies assessed mixed populations [12, 26, 34, 36]. The diverse genotyping methods included PCR-RFLP and TaqMan, and the genotypic distribution of the controls was consistent with the HWE in all except four studies [23, 25, 26, 39].Table 1
Characteristics of case-control studies included in the meta-analysis.
Genotype distribution
First author
Year
Country/region
Racial descent
Source of controls
Case
Control
Case
Control
Genotyping type
P for HWE
MAF
Location
CC
CT
TT
CC
CT
TT
Weinstein [12]
2002
Puerto Rico
Mixed
Population control
135
146
67
53
15
69
62
15
PCR-RFLP
0.85
0.32
Oral
Kureshi [20]
2004
Pakistan
Asian
NA
50
54
32
18
0
32
18
4
PCR-RFLP
0.52
0.24
HN
Neumann [21]
2005
USA
Caucasian
Hospital control
537
545
258
244
35
278
216
51
PCR-RFLP
0.34
0.29
HN
Capaccio [22]
2005
Italy
Caucasian
Population control
65
100
18
33
14
36
46
18
PCR-RFLP
0.62
0.41
HN
Vairaktaris [23]
2006
Greece
Caucasian
Population control
110
120
28
76
6
45
65
10
PCR-RFLP
0.04
0.35
Oral
Suzuki [24]
2007
Japan
Asian
Hospital control
237
711
88
113
36
252
331
128
TaqMan
0.29
0.41
HN
Reljic [25]
2007
Croatia
Caucasian
Population control
81
102
45
27
9
35
59
8
PCR-RFLP
0.01
0.37
HN
Hsiung [26]
2007
USA
Mixed
Population control
277
524
128
149
218
306
NA
NA
NA
HN
Hung [27]
2007
Europe
Caucasian
Hospital control
779
2530
373
327
79
1272
1025
233
TaqMan
0.20
0.30
HN
Solomon [28]
2008
India
Asian
NA
126
100
48
55
23
48
42
10
PCR-RFLP
0.86
0.31
Oral
Siraj [35]
2008
Saudi Arabia
Caucasian
Population control
49
511
30
18
1
372
126
13
PCR-RFLP
0.55
0.15
Thyroid
Ni [29]
2008
China
Asian
Hospital control
207
400
48
95
64
152
187
61
PCR-RFLP
0.78
0.39
Laryngeal
Rodrigues [36]
2010
Brazil
Mixed
Population control
100
100
44
43
13
46
40
14
PCR-RFLP
0.28
0.34
HN
Kruszyna [30]
2010
Poland
Caucasian
Population control
131
250
69
52
10
126
104
20
PCR-RFLP
0.82
0.29
Laryngeal
Cao [37]
2010
China
Asian
Population control
511
552
310
169
32
334
188
30
PCR-RFLP
0.60
0.23
NP
Tsai [31]
2011
Taiwan
Asian
Hospital control
620
620
391
186
43
322
236
62
PCR-RFLP
0.06
0.29
Oral
Supic [32]
2011
Serbia
Caucasian
Hospital control
96
162
50
32
14
80
66
16
PCR-RFLP
0.66
0.30
Oral
Sailasree [33]
2011
India
Asian
Hospital control
101
138
92
8
1
108
29
1
PCR-RFLP
0.53
0.11
Oral
Prasad [38]
2011
India
Asian
NA
97
241
86
10
1
228
12
1
PCR-RFLP
0.07
0.03
Thyroid
Fard-Esfahani [39]
2011
Iran
Asian
Hospital control
154
198
69
71
14
82
108
8
multiplex PCR
<0.01
0.31
Thyroid
Ozdemir [40]
2012
Turkey
Caucasian
NA
60
50
28
25
7
33
14
3
Real-time PCR
0.38
0.20
Thyroid
Galbiatti [34]
2012
Brazil
Mixed
Population control
322
531
130
147
45
226
250
55
PCR-RFLP
0.24
0.34
HN
Vylliotis [41]
2013
Greek/Germany
Caucasian
Population control
110
120
76
28
6
65
45
10
PCR-RFLP
0.58
0.27
Oral
HWE in controls.
MAF: minor allele frequency in controls.
NA: not applicable.
HN: head and neck.
NP: nasopharyngeal.Figure 1
Flowchart of the study selection process.


## 3.2. Meta-Analysis

The main results of this meta-analysis and heterogeneity test are presented in Table2. Overall, no significant association between MTHFR C677T polymorphism and HNC risk was found in this meta-analysis (T versus C: OR = 1.04, 95% CI = 0.92–1.18, P
=
0
.
55, I
2
=
72.5
%; TT versus CC: OR = 1.15, 95% CI = 0.90–1.46, P
=
0
.
26, I
2
=
56.8
%; CT versus CC: OR = 1.00, 95% CI = 0.85–1.17, P
=
0
.
9
9, I
2
=
65.8
%; CT + TT versus CC: OR = 1.01, 95% CI = 0.87–1.18, P
=
0
.
8
6, I
2
=
69.7
% (Figure 2); TT versus CC + CT: OR = 1.11, 95% CI = 0.98–1.26, P
=
0
.
10, I
2
=
49.8
%). Subsequent analysis of the HWE studies showed similar lack of associations between MTHFR C677T polymorphism and HNC risk (T versus C: OR = 1.05, 95% CI = 0.92–1.21, P
=
0
.
47, I
2
=
75.0
%; TT versus CC: OR = 1.14, 95% CI = 0.88–1.48, P
=
0
.
3
4, I
2
=
61.4
%; CT versus CC: OR = 1.02, 95% CI = 0.88–1.19, P
=
0
.
76, I
2
=
60.3
%; CT + TT versus CC: OR = 1.03, 95% CI = 0.88–1.20, P
=
0
.
69, I
2
=
68.4
%; TT versus CC + CT: OR = 1.11, 95% CI = 0.89–1.39, P
=
0
.
3
5, I
2
=
52.2
%). Further, stratified analysis of ethnicity, study design, cancer location, and smoking habits showed no significant association between MTHFR C677T polymorphism and HNC risk. Notable, slight increased risks were found in the risk of developing thyroid cancer (T versus C: OR = 1.30, 95% CI = 1.03–1.65, P
=
0
.
04, I
2
=
43.9
%; TT versus CC: OR = 2.06, 95% CI = 1.04–4.10, P
=
0
.
04, I
2
=
0.0
%).Table 2
Summary ORs and 95% CI of MTHFR C677T polymorphism and head and neck cancer risk.
T versus C
TT versus CC
CT versus CC
CT + TT versus CC
TT versus CC + CT
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)a
OR
95% CI
P
I
2 (%)
Total
1.04
0.92–1.18
0.55
72.5
1.15
0.90–1.46
0.26
56.8
1.00
0.85–1.17
0.99
65.8
1.01
0.87–1.18
0.86
69.7
1.11
0.98–1.26
0.10
49.8
HWE
1.05
0.92–1.21
0.47
75.0
1.14
0.88–1.48
0.34
61.4
1.02
0.88–1.19
0.76
60.3
1.03
0.88–1.20
0.69
68.4
1.11
0.89–1.39
0.35
52.2
Ethnicity
Asian
1.03
0.78–1.36
0.83
86.0
1.29
0.73–2.28
0.38
79.6
0.96
0.73–1.25
0.75
70.8
1.00
0.74–1.36
0.99
80.4
1.28
0.80–2.06
0.30
74.0
Caucasian
1.39
0.89–1.20
0.65
49.1
1.04
0.85–1.27
0.66
0.0
1.04
0.81–1.35
0.75
69.5
1.05
0.83–1.33
0.67
66.3
1.01
0.84–1.22
0.90
0.0
Other
1.08
0.92–1.27
0.36
0.0
1.25
0.87–1.78
0.23
0.0
1.00
0.79–1.27
0.98
0.0
0.96
0.81–1.15
0.68
0.0
1.24
0.89–1.74
0.21
0.0
Design
PB
1.01
0.90–1.14
0.84
29.5
1.16
0.92–1.46
0.21
0.0
0.95
0.76–1.20
0.68
60.1
0.96
0.80–1.15
0.64
53.5
1.18
0.95–1.74
0.14
0.0
HB
0.98
0.77–1.25
0.86
87.9
1.09
0.69–1.74
0.71
82.9
0.94
0.72–1.22
0.72
79.1
0.96
0.72–1.27
0.76
84.3
1.07
0.72–1.58
0.74
79.2
Location
Oral
0.88
0.67–1.17
0.38
75.3
0.85
0.64–1.12
0.25
48.0
0.81
0.57–1.15
0.24
70.7
0.84
0.59–1.20
0.33
74.4
0.91
0.70–1.20
0.52
34.0
Laryngeal
1.33
0.68–2.60
0.40
90.6
1.82
0.51–6.44
0.353
86.1
1.22
0.70–2.13
0.48
70.5
1.37
0.63–3.00
0.43
86.8
1.64
0.64–4.17
0.30
77.9
Thyroid
1.30
1.03–1.65
0.04
43.9
2.06
1.04–4.10
0.04
0.0
1.48
0.84–2.62
0.17
65.9
1.53
0.92–2.53
0.10
60.5
2.02
1.04–3.92
0.04
0.0
aTest for heterogeneity.
PB: population based; HB: hospital based.Figure 2
OR of head and neck cancer associated with MTHFR C677T polymorphism for the CT + TT versus CC model in total.


## 3.3. Sensitivity Analysis and Cumulative Analysis

Each study included in this meta-analysis was deleted one by one to determine the effect of an individual dataset to the pooled ORs; the results were consistent in all of the research genetic models (Figure3 for the dominant model), indicating that our results are statistically robust (Table 3 for the dominant model). In the cumulative meta-analysis, the results always showed negative association with the increasing number of studies (Figure 4 for the dominant model).Table 3
Sensitivity analysis through deleting each study to reflect the influence of the individual dataset to the pooled ORs in CT + TT versus CC model.
Study omitted
Estimate
95% conf. interval
Weinstein et al. (2002) [12]
1.0189941
0.87112659
1.1919612
Kureshi et al. (2004) [20]
1.0193014
0.87365657
1.1892264
Capaccio et al. (2005) [22]
1.0022544
0.85940462
1.1688484
Neumann et al. (2005) [21]
1.007629
0.85724384
1.184396
Vairaktaris et al. (2006) [23]
0.99266464
0.85276967
1.155509
Hung et al. (2007) [27]
1.0095826
0.85412776
1.193331
Hsiung et al. (2007) [26]
1.0266064
0.87583935
1.2033266
Reljic et al. (2007) [25]
1.0438555
0.90103817
1.2093099
Suzuki et al. (2007) [24]
1.0195761
0.86892009
1.1963534
Ni et al. (2008) [29]
0.97470093
0.84459507
1.1248491
Siraj et al. (2008) [35]
0.9954946
0.85466665
1.1595275
Solomon et al. (2008) [28]
0.99778956
0.85548556
1.1637648
Cao et al. (2010) [37]
1.0159856
0.86369467
1.1951293
Kruszyna et al. (2010) [30]
1.0192744
0.87083119
1.1930214
Rodrigues et al. (2010) [36]
1.0113139
0.86534274
1.1819084
Fard-Esfahani et al. (2011) [39]
1.0215796
0.87302911
1.1954068
Prasad and Wilkhoo (2011) [38]
0.99519187
0.85606372
1.1569312
Sailasree et al. (2011) [33]
1.0387301
0.89613956
1.2040093
Supic et al. (2011) [32]
1.0191994
0.87169868
1.1916586
Tsai et al. (2011) [31]
1.0461444
0.90586507
1.2081468
Galbiatti et al. (2012) [34]
1.0096141
0.85997182
1.1852955
Ozdemir et al. (2012) [40]
0.99327004
0.85463184
1.1543981
Vylliotis et al. (2013) [41]
1.0391399
0.89383554
1.2080653
Combined
1.0136127
0.87153344
1.178854Figure 3
Sensitivity analysis through deletion of one study at a time to reflect the influence of the individual dataset to the pooled ORs in CT + TT versus CC model.Figure 4
Cumulative meta-analyses according to publication year in CT + TT versus CC model.


## 3.4. Publication Bias

Funnel plot and Egger’s test were performed to estimate the publication bias among the included studies. Shapes of the funnel plots for all genetic models did not reveal any asymmetrical evidence (Figure5 showed the funnel plots for the dominant model in all populations). The result was further supported by the data with Egger’s test. No significant publication bias was found in this meta-analysis (P
=
0
.
85 for T versus C; P
=
0
.
86 for TT versus CC; P
=
0
.
91 for CT versus CC; P
=
0
.
72 for CT + TT versus CC; P
=
0
.
97 for TT versus CC + CT).Figure 5
Funnel plot analysis to detect publication bias for CT + TT versus CC model. Each point represents a separate study for the indicated association.


## 4. Discussion

MTHFR irreversibly catalyzes the conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, which is a cosubstrate in the transmethylation of homocysteine to methionine. Methionine is the precursor of S-adenosyl-L-methionine, which is the primary methyl donor during DNA methylation process [42, 43]. In another metabolic reaction, 5,10-methylenetetrahydrofolate is involved in the conversion of deoxyuridylate monophosphate to deoxythymidylate monophosphate. Low levels of 5,10-methylenetetrahydrofolate would result in increasing the amounts of uracil incorporated in DNA to replace thymine, thereby increasing the ratio of point mutations and resulting in DNA breakage [6]. All of these factors are important in cancer development.Molecular studies have shown that genetic susceptibility is one of the most important risk factors for cancer development. MTHFR gene is mapped in chromosome 1p36.3, is composed of 11 exons and 10 introns, and encodes a 77 KD protein [44, 45]. MTHFR gene C677T polymorphism, which is characterized by the transition of cytosine to thymine, leads to an amino acid change from alanine (Ala) to valine (Val) at codon 222 in exon 4. Previous studies have shown individuals with mutant homozygous 677TT genotype and heterozygous 677CT genotype showed approximately 30% and 65% activities of the MTHFR enzyme, respectively, compared with individuals with wild-type 677CC genotype [11]. Both heterozygous (CT) and homozygous (TT) variants possibly increase enzyme thermolability, reduce MTHFR enzyme activity, and decrease folate concentrations in plasma and red blood cells [46].To date, large numbers of studies have investigated the association between the MTHFR C677T polymorphism and cancer risks, but the results are inconsistent. The MTHFR C677T variant is a possible risk factor of pancreatic [46], esophageal [47], and breast cancers [48] but exerts a possible protective effect against colorectal cancer [49]. However, the MTHFR C677T variant is not associated with lung [50] and prostate cancers [51].In 2002, Weinstein et al. observe no association between MTHFR C677T polymorphism and HNC (oral cancer) risk in a Puerto Rican population. Since then, many studies have assessed this association but have obtained inconsistent results. Solomon et al. [28] found that the mutation in homozygous 677TT genotype is associated with a high risk of oral squamous cell carcinoma among Indian heavy drinkers (OR = 3.0; 95% CI = 2.02–4.0). Ni et al. [29] also found that the individuals with 677CT and 677TT genotype had a 1.66-fold (95% CI: 1.08–2.52) and 3.35-fold (95% CI: 2.07–5.54) increased risk of developing laryngeal squamous cell carcinoma, respectively, compared with those who had 677CC genotype in a Chinese population. Vairaktaris et al. [23] supposed that mutations inMTHFR slightly increased the risk of oral cancers. Capaccio et al. [22] and Neumann et al. [21] observed the same results for oropharyngeal cancer and HNC among individuals with the CT genotype. In contrast, some studies indicated that the T allele exerts a protective effect against HNC. Sailasree et al. [33] demonstrated that the 677 (CT + TT) genotype was associated with a significant 3-fold reduction in the risk of oral cancer (95% CI = 0.16–0.78) in Indian patients. Tsai et al. [31] showed that the MTHFR 677CT and 677TT genotypes exerted protective effects against oral cancer in Taiwan patients (95% CI = 0.54–0.81 and 95% CI = 0.41–0.86, resp.). Moreover, Reljic et al. [25] also reported a decreased risk tendency for 677CT genotype in a Croatian population. However, other studies have shown no significant association between MTHFR C677T polymorphism and HNC risk [12, 20, 24, 26, 27, 30, 32, 34]. In the stratified analysis with drinking and smoking status, the T allele is also considered as an increased risk factor [24, 32].This meta-analysis included 23 related studies involving 4,955 cases and 8,805 controls. No significant association was found in all of the genetic models and stratified analysis based on the HWE, ethnicity and study design, and cancer location, expect for few significant risks that were found in thyroid cancer. These results are consistent with two previous meta-analysis on MTHFR gene polymorphism and HNC and oral cancer risk by Boccia et al. [13] in 2009 and Zhuo et al. [52] in 2012, respectively. These meta-analyses included only 9 and 6 studies, respectively. Because of the small sample size and inadequate stratified analysis, further review and meta-analysis with larger sample sizes are necessary to accurately predict the associations between MTHFR C677T polymorphism and HNC risk.There were some limitations in this meta-analysis. First, these results are based on unadjusted estimates that lack original data from the included studies. Therefore, the evaluation of the gene-environment interactions during HNC development was limited. Second, MTHFR C677T polymorphism was not analyzed in combination with other related genes involved in folate metabolism, such as methionine synthase (MTR), methionine synthase reductase (MTRR), and adjacent polymorphic locus (A1298C), and the effect of gene-gene interactions of MTHFR C677T polymorphism on HNC development was not illustrated clearly. Third, information of folate intake was not obtained, and the influence of folate on the association between MTHFR C677T polymorphism and HNC risk was not explained. Fourth, very few studies included in this meta-analysis involve the smoking and drinking status of patients, and the interaction between gene mutation and effect of environmental factors was not be evaluated accurately. Fifth, heterogeneity existed in all of the genetic models in the total population in our meta-analysis. And the subgroup analyses were conducted to decrease or prevent the occurrence of heterogeneity. The random-effects model was used to estimate the combined effect size when significant heterogeneity was observed.Despite these limitations, no publication bias was observed. Sensitivity analysis also indicated that the included studies provided consistent and robust results.


## 5. Conclusion

In summary, no significant association was found between the MTHFR C677T polymorphism and HNC risk. Therefore, large-scale case-control and population-based studies involving potential gene-gene and gene-environment interactions are necessary to investigate the association further.



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*Source: 681313-2015-01-31.xml*