HNC involves a series of tumors originating in the oropharynx, hypopharynx, oral cavity, lip, larynx, or nasopharynx. Smoking, alcohol consumption, and high-risk human papillomaviruses have been related to HNC. In connection with the role of genetics in HNC, several recent meta-analyses have reported the association of polymorphisms with the risk of HNCs.
Cellular inflammation and immunity can play a significant role in various stages of carcinogenesis [1] such as head and neck cancers (HNCs). HNC mortality rates are elevating and disproportionately affect people in low- and middle-income countries and areas with restricted resources [2]. Global Burden of Disease Study (GBD) in 2016 estimated 512,492 deaths due to HNC (a minimum of 15,018 deaths in North Africa and the Middle East to a maximum of 199,280 in South Asia) and predicted the death count to reach 705,901 in 2030 [3][4][3,4]. HNC involves a series of tumors originating in the oropharynx, hypopharynx, oral cavity, lip, larynx, or nasopharynx [5]. Smoking, alcohol consumption, and high-risk human papillomaviruses have been related to HNC [5][6][7][5,6,7]. In connection with the role of genetics in HNC, several recent meta-analyses have reported the association of polymorphisms with the risk of HNCs [8][9][10][11][8,9,10,11].
A number of heterocyclic and aromatic amines are the main carcinogenic compounds of tobacco smoke [12][13][12,13] that their metabolism in humans is complex and includes acetylation as a main pathway for DNA mutation and the onset of carcinogenesis [14]. In particular, two N-acetyltransferases, NAT1 and NAT2 perform a role in catalyzing the deactivation and activation of several carcinogenic amines through N- and O-acetylation, respectively [14][15][14,15]. Both NAT genes ( NAT1 and NAT2 ) have polymorphisms in humans and in accordance with slow and rapid acetylator phenotypes [16]. The NAT2 metabolized gene is located in region 10 of chromosome 8p21, which contains two exons with a long intron of about 8.6 kb [17]. Exon 1 is very short (100 bp) and the entire protein-coding region in Exon 2 is 870 bp [18]. Also, the NAT1 gene is located on the short arm of chromosome 8 (8p21) [19][20][19,20]. NAT1 accelerates acetylation specifically for arylamine receptor structures such as p-aminosalicylic and p-aminobenzoic acids [21] and NAT2 acetylates other arylamine-acceptor structures, such as isoniazid, sulfasalazine, procainamide, and caffeine [19].
Evidence from the published articles on the relationship between NAT1 and NAT2 polymorphisms and HNC susceptibility is conflicting [22][23][22,23]. The association between the polymorphisms ( NAT1 and NAT2 ) and the HNC risk has been evaluated by one [24] and four [25][26][27][28][25,26,27,28] meta-analyses, respectively. However, these studies were published several years ago with the most recent one being published in 2015. Therefore, through this meta-analysis, we intend to update the evidence on the association between the polymorphisms and the HNC risk by including more studies. In addition, we aim to conduct trial sequential analysis (TSA) and meta-regression.
Twenty-eight studies included in the analysis were published between 1998 and 2014 ( Table 1 ). Fourteen articles [22][23][29][30][31][32][33][34][35][36][37][38][39][40][22,23,36,37,38,39,40,41,42,43,44,45,46,47] reported the results in Caucasians, nine [41][42][43][44][45][46][47][48][49][35,48,49,50,51,52,53,54,55] in Asians, and five [50][51][52][53][54][56,57,58,59,60] among participants of mixed ethnicity. The control source in eighteen articles [22][23][41][30][32][33][36][37][38][39][42][43][45][46][47][51][52][54][22,23,35,37,39,40,43,44,45,46,48,49,51,52,53,57,58,60] was hospitals and ten [29][31][34][35][40][44][48][49][50][53][36,38,41,42,47,50,54,55,56,59] recruited the controls from a general population. In total, the articles included 5154 HNC cases and 6194 controls. Age, gender distribution, sample size, tumor type, genotyping method, and the quality score are shown in Table 1 .
The First Author, Publication Year | Country | Ethnicity | Control Source | Number | Mean Year | Male Percentage | Type of Tumor | Genotyping Method | Quality Score | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Case | Control | Case | Control | Case | Control | |||||||
Gonzalez, 1998 [34] | Spain | Caucasian | PB | 75 | 200 | 58.7 | 45 | 100 | 75 | Oral, pharyngeal, laryngeal | PCR-RFLP | 7 |
Katoh, 1998 [41] | Japan | Asian | HB | 62 | 122 | 61.7 | 62.4 | 64.5 | 61.5 | Oral | PCR-RFLP | 7 |
Henning, 1999 [23] | Germany | Caucasian | HB | 255 | 510 | 61.4 | NA | 90.6 | NA | Laryngeal | PCR | 7 |
Jourenkova-Mironova, 1999 [37] | France | Caucasian | HB | 250 | 172 | 54.4 | 54.9 | 96 | 94.8 | Oral, pharyngeal, laryngeal | PCR-RFLP | 7 |
Morita, 1999 [48] | Japan | Asian | PB | 145 | 164 | 59.0 | 49.8 | 86.9 | 62.2 | Oral, pharyngeal, laryngeal | PCR | 7 |
Olshan, 2000 [54] | USA | Mixed | HB | 171 | 193 | 59.5 | 56.8 | 81.3 | 59.1 | Oral, pharyngeal, laryngeal | PCR | 7 |
Chen, 2001 [29] | USA | Caucasian | PB | 341 | 552 | NA | NA | 70.4 | 71.6 | Oral | PCR-RFLP | 9 |
Fronhoffs, 2001 [32] | Germany | Caucasian | HB | 291 | 300 | 59.8 | 47.1 | 80.1 | 58 | Oral, pharyngeal, laryngeal | RT-PCR | 6 |
Hahn, 2002 [35] | Germany | Caucasian | PB | 94 | 92 | 61.5 | 45.1 | 65.9 | 51.1 | Oral | PCR-RFLP | 7 |
Lei, 2002 [45] | China | Asian | HB | 62 | 56 | 60.2 | 58.2 | NA | NA | Laryngeal | PCR-RFLP | 7 |
Varzim, 2002 [40] | Portugal | Caucasian | PB | 88 | 172 | 62.8 | 43.0 | 94.3 | 72.7 | Laryngeal | PCR-RFLP | 7 |
Cheng, 2003 [43] | Taiwan | Asian | HB | 279 | 325 | NA | NA | NA | NA | Pharyngeal | PCR-RFLP | 6 |
Gajecka, 2005 [33] | Poland | Caucasian | HB | 289 | 311 | 57.9 | 45.9 | 100 | 100 | Laryngeal | PCR-RFLP | 8 |
Rydzanicz, 2005 [38] | Poland | Caucasian | HB | 266 | 143 | 61.6 | 53.1 | 95.1 | 100 | Oral, pharyngeal, laryngeal | PCR-RFLP | 8 |
Unal, 2005 [39] | Turkey | Caucasian | HB | 45 | 104 | 53.5 | 50.0 | 93.3 | 65.4 | Laryngeal | PCR-RFLP | 7 |
Marques, 2006 [52] | Brazil | Mixed | HB | 231 | 212 | 56.6 | 55.3 | 83.5 | 79.2 | Oral | PCR-RFLP | 8 |
Gara, 2007 [51] | Tunisia | Mixed | HB | 64 | 160 | 50.7 | 53.6 | 65.6 | 45 | Oral, pharyngeal, laryngeal | PCR-RFLP | 7 |
Majumder, 2007 [47] | India | Asian | HB | 297 | 342 | NA | NA | NA | NA | Oral | PCR-RFLP | 6 |
Boccia, 2008 [22] | Italy | Caucasian | HB | 210 | 245 | 63.6 | 63.3 | 71.4 | 72.2 | Oral, pharyngeal, laryngeal | PCR-RFLP | 8 |
Buch, 2008 [50] | USA | Mixed | PB | 182 | 399 | 58.7 | 58.7 | 87.4 | 75.7 | Oral | PCR-RFLP | 9 |
Harth, 2008 [36] | Germany | Caucasian | HB | 312 | 300 | 59.7 | 47.2 | 80.4 | 58.7 | Oral, pharyngeal, laryngeal | PCR-RFLP | 6 |
Chatzimichalis, 2010 [30] | Greece | Caucasian | HB | 88 | 102 | 66.5 | 62.5 | 87.5 | 74.5 | Laryngeal | PCR-RFLP | 8 |
Demokan, 2010 [31] | Turkey | Caucasian | PB | 95 | 93 | 59.6 | 53.3 | 86.3 | 52.7 | Oral, pharyngeal, laryngeal | PCR | 8 |
Hou, 2011 [44] | China | Asian | PB | 172 | 170 | 49.6 | 49.6 | 100 | 100 | Oral, pharyngeal | PCR-RFLP and Taqman | 9 |
Balaji, 2012 [42] | India | Asian | HB | 157 | 132 | 53.1 | 55.1 | 54.8 | 34.8 | Oral | Taqman | 7 |
Majumder, 2012 [46] | India | Asian | HB | 299 | 381 | NA | NA | NA | NA | Oral | PCR | 6 |
Tian, 2013 [49] | China | Asian | PB | 233 | 102 | 60.0 | 60.0 | NA | NA | Laryngeal | PCR | 8 |
Marques, 2014 [53] | Brazil | Mixed | PB | 101 | 141 | NA | NA | NA | NA | Oral, pharyngeal, laryngeal | PCR-RFLP | 7 |
Table 2 shows the prevalence of slow and rapid acetylators of NAT1 and NAT2 polymorphisms. Eight studies [23][41][31][32][37][40][46][54][23,35,38,39,44,47,52,60] included NAT1 polymorphism with 1509 HNC cases and 1829 controls and twenty-five studies [22][23][41][29][30][31][33][34][35][36][37][38][39][40][42][43][44][45][47][48][49][50][51][52][53][22,23,35,36,37,38,40,41,42,43,44,45,46,47,48,49,50,51,53,54,55,56,57,58,59] included NAT2 polymorphism with 4393 HNC cases and 5321 controls.
Author, Year | NAT1 | |||
---|---|---|---|---|
Case | Control | |||
Slow | Rapid | Slow | Rapid | |
Katoh, 1998 [41] | 9 | 53 | 46 | 76 |
Henning, 1999 [23] | 144 | 109 | 232 | 164 |
Jourenkova-Mironova, 1999 [37] | 141 | 109 | 98 | 74 |
Olshan, 2000 [54] | 83 | 88 | 108 | 85 |
Fronhoffs, 2001 [32] | 195 | 96 | 206 | 94 |
Varzim, 2002 [40] | 48 | 40 | 107 | 65 |
Demokan, 2010 [31] | 53 | 42 | 42 | 51 |
Majumder, 2012 [46] | 128 | 171 | 168 | 213 |
Author, Year | NAT2 | |||
Case | Control | |||
Slow | Rapid | Slow | Rapid | |
Gonzalez, 1998 [34] | 28 | 47 | 37 | 163 |
Katoh, 1998 [41] | 7 | 55 | 7 | 115 |
Henning, 1999 [23] | 138 | 117 | 286 | 224 |
Jourenkova-Mironova, 1999 [37] | 142 | 108 | 91 | 81 |
Morita, 1999 [48] | 18 | 127 | 17 | 147 |
Chen, 2001 [29] | 198 | 143 | 302 | 250 |
Hahn, 2002 [35] | 59 | 35 | 57 | 35 |
Lei, 2002 [45] | 50 | 12 | 34 | 22 |
Varzim, 2002 [40] | 47 | 41 | 76 | 96 |
Cheng, 2003 [43] | 39 | 240 | 54 | 271 |
Gajecka, 2005 [33] | 127 | 162 | 165 | 146 |
Rydzanicz, 2005 [38] | 131 | 135 | 72 | 71 |
Unal, 2005 [39] | 15 | 30 | 7 | 97 |
Marques, 2006 [52] | 29 | 202 | 38 | 174 |
Gara, 2007 [51] | 33 | 31 | 59 | 101 |
Majumder, 2007 [47] | 190 | 107 | 205 | 137 |
Boccia, 2008 [22] | 109 | 101 | 128 | 117 |
Buch, 2008 [50] | 84 | 98 | 224 | 175 |
Harth, 2008 [36] | 189 | 123 | 181 | 119 |
Chatzimichalis, 2010 [30] | 39 | 49 | 65 | 37 |
Demokan, 2010 [31] | 50 | 45 | 45 | 48 |
Hou, 2011 [44] | 46 | 126 | 33 | 137 |
Balaji, 2012 [42] | 100 | 57 | 67 | 65 |
Tian, 2013 [49] | 189 | 44 | 56 | 46 |
Marques, 2014 [53] | 48 | 53 | 51 | 90 |
When there was one study for a subgroup, we could delete it [55][61]. Subgroup analyses were performed based on ethnicity, sample size, control source, genotyping method, and tumor type ( Table 3 ). With regards to NAT1 polymorphism, no subgroup differences were observed. For NAT2 polymorphism, significant subgroup effects were observed for ethnicity and the control source. Slow acetylators among Asians and also the population-based studies could be effective factors on the pooled result of the association between NAT2 polymorphism and the HNC risk.
Polymorphism | Variable (N) | OR | 95% CI | p-Value | I2 | Pheterogeneity |
---|---|---|---|---|---|---|
NAT1 | Overall (8) | 0.89 | 0.77, 1.02 | 0.09 | 48% | 0.06 |
Ethnicity | ||||||
Caucasian (5) | 0.96 | 0.80, 1.15 | 0.64 | 0% | 0.45 | |
Asian (2) | 0.55 | 0.17, 1.80 | 0.32 | 87% | 0.005 | |
Control source | ||||||
Hospital-based (6) | 0.87 | 0.74, 1.01 | 0.06 | 46% | 0.10 | |
Population-based (2) | 1.05 | 0.51, 2.17 | 0.90 | 72% | 0.06 | |
Sample size | ||||||
≥200 (6) | 0.90 | 0.77, 1.04 | 0.15 | 0% | 0.87 | |
<200 (2) | 0.67 | 0.13, 3.56 | 0.64 | 91% | 0.0007 | |
Genotyping method | ||||||
PCR (4) | 0.94 | 0.79, 1.14 | 0.54 | 26% | 0.26 | |
PCR-RFLP (3) | 0.64 | 0.34, 1.18 | 0.15 | 74% | 0.02 | |
Tumor type | ||||||
Oral (2) | 0.55 | 0.17, 1.80 | 0.32 | 87% | 0.005 | |
Laryngeal (2) | 0.87 | 0.67, 1.15 | 0.33 | 0% | 0.43 | |
NAT2 | Overall (25) | 1.22 | 1.02, 1.46 | 0.03 | 74% | <0.00001 |
Ethnicity | ||||||
Caucasian (13) | 1.10 | 0.89, 1.37 | 0.38 | 71% | <0.0001 | |
Asian (8) | 1.60 | 1.13, 2.26 | 0.008 | 69% | 0.002 | |
Mixed (4) | 1.04 | 0.61, 1.77 | 0.89 | 79% | 0.003 | |
Control source | ||||||
Hospital-based (15) | 1.10 | 0.88, 1.37 | 0.39 | 71% | <0.0001 | |
Population-based (10) | 1.41 | 1.04, 1.92 | 0.03 | 75% | <0.0001 | |
Sample size | ||||||
≥200 (20) | 1.19 | 1.00, 1.42 | 0.05 | 70% | <0.00001 | |
<200 (5) | 1.49 | 0.68, 3.29 | 0.32 | 85% | <0.0001 | |
Genotyping method | ||||||
PCR (4) | 1.47 | 0.77, 2.78 | 0.24 | 85% | 0.0002 | |
PCR-RFLP (19) | 1.14 | 0.93, 1.39 | 0.21 | 72% | <0.00001 | |
Tumor type | ||||||
Oral (7) | 1.05 | 0.80,1.38 | 0.72 | 62% | 0.01 | |
Pharyngeal (2) | 0.82 | 0.54, 1.24 | 0.35 | 0% | 0.96 | |
Laryngeal (8) | 1.48 | 0.88, 2.51 | 0.14 | 88% | <0.00001 |
The meta-regression analyses assessing the effect of publication year, the sample size, and the mean age and gender distribution of cases and controls on the risk of HNC in NAT1 and NAT2 polymorphisms are shown in Table 4 . Sample size, the mean age of cases, and the percentage of males in the controls were confounding factors for the pooled result of the association between NAT2 polymorphism and the HNC susceptibility. With an increase in sample size, age of the cases, and percentage of males in the controls, the OR decreased.
Polymorphism | Variable | Point Estimate | Standard Error | Lower Limit | Upper Limit | Z-Value | p-Value | |
---|---|---|---|---|---|---|---|---|
NAT1 | Publication year | Slope | 0.01830 | 0.01361 | −0.00837 | 0.04497 | 1.34462 | 0.17875 |
Intercept | −36.77098 | 27.26207 | −90.20365 | 16.66169 | −1.34880 | 0.17740 | ||
Sample size | Slope | 0.00027 | 0.00045 | −0.00060 | 0.00115 | 0.61240 | 0.54027 | |
Intercept | −0.25993 | 0.24912 | −0.74819 | 0.22833 | −1.04340 | 0.29676 | ||
Mean age of cases | Slope | −0.01179 | 0.03248 | −0.07546 | 0.05186 | −0.36300 | 0.71660 | |
Intercept | 0.57037 | 1.93376 | −3.21972 | 4.36047 | 0.29496 | 0.76803 | ||
Mean age of controls | Slope | −0.02263 | 0.03624 | −0.09365 | 0.04839 | −0.62459 | 0.53224 | |
Intercept | 1.17938 | 2.13386 | −3.00290 | 5.36167 | 0.55270 | 0.58047 | ||
Male percentage of cases | Slope | −0.01131 | 0.01256 | −0.03593 | 0.01331 | −0.90074 | 0.36773 | |
Intercept | 0.86738 | 1.11137 | −1.31087 | 3.04562 | 0.78046 | 0.43512 | ||
Male percentage of controls | Slope | −0.00268 | 0.00617 | −0.01478 | 0.00942 | −0.43474 | 0.066375 | |
Intercept | 0.03230 | 0.43459 | −0.81948 | 0.88409 | 0.07433 | 0.94074 | ||
NAT2 | Publication year | Slope | 0.00944 | 0.01016 | −0.01047 | 0.02934 | 0.092942 | 0.35267 |
Intercept | −18.82284 | 20.36308 | −58.73373 | 21.08806 | −0.92436 | 0.35530 | ||
Sample size | Slope | −0.00080 | 0.00020 | −0.00120 | −0.00040 | −3.91239 | 0.00009 | |
Intercept | 0.50882 | 0.11300 | 0.28733 | 0.73030 | 4.50265 | 0.00001 | ||
Mean age of cases | Slope | −0.04050 | 0.01356 | −0.06706 | −0.01393 | −2.098776 | 0.00281 | |
Intercept | 2.47888 | 0.80007 | 0.91077 | 4.04699 | 3.09832 | 0.00195 | ||
Mean age of controls | Slope | −0.00438 | 0.00889 | −0.02180 | 0.01305 | −0.49203 | 0.62270 | |
Intercept | 0.34691 | 0.47403 | −0.58217 | 1.27600 | 0.73184 | 0.46427 | ||
Male percentage of cases | Slope | −0.0629 | 0.00393 | −0.01399 | 0.00141 | −1.60201 | 0.10915 | |
Intercept | 0.57366 | 0.33428 | −0.08152 | 1.22884 | 1.71610 | 0.08614 | ||
Male percentage of controls | Slope | −0.00785 | 0.00289 | −0.01351 | −0.00219 | −2.71989 | 0.00653 | |
Intercept | 0.64373 | 0.22152 | 0.20956 | 1.07790 | 2.90598 | 0.00366 |
There was no association between NAT1 polymorphism and susceptibility to HNC, whereas an association between and NAT2 polymorphism and the HNC risk was found. Slow acetylators of NAT2 polymorphism were at greater risk for HNC than the rapid acetylators. Despite the stability of the results, the presence of high heterogeneity, publication bias, and confounding factors warrant the need for more studies to confirm the results of the present meta-analysis as well as TSA.