Susceptibility to Head and Neck Cancers: Comparison
Please note this is a comparison between Version 1 by Masoud Sadeghi and Version 2 by Beatrix Zheng.

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.

  • head and neck carcinoma
  • oral carcinoma
  • polymorphism
  • N-acetyltransferases
  • meta-analysis

1. Introduction

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.

2. Analysis on Results

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 .

Table 1. Characteristics of the articles included in the meta-analysis.
The First Author, Publication YearCountryEthnicityControl SourceNumberMean YearMale PercentageType of TumorGenotyping MethodQuality Score
CaseControlCaseControlCaseControl
Gonzalez, 1998 [34]SpainCaucasianPB7520058.74510075Oral, pharyngeal, laryngealPCR-RFLP7
Katoh, 1998 [41]JapanAsianHB6212261.762.464.561.5OralPCR-RFLP7
Henning, 1999 [23]GermanyCaucasianHB25551061.4NA90.6NALaryngealPCR7
Jourenkova-Mironova, 1999 [37]FranceCaucasianHB25017254.454.99694.8Oral, pharyngeal, laryngealPCR-RFLP7
Morita, 1999 [48]JapanAsianPB14516459.049.886.962.2Oral, pharyngeal, laryngealPCR7
Olshan, 2000 [54]USAMixedHB17119359.556.881.359.1Oral, pharyngeal, laryngealPCR7
Chen, 2001 [29]USACaucasianPB341552NANA70.471.6OralPCR-RFLP9
Fronhoffs, 2001 [32]GermanyCaucasianHB29130059.847.180.158Oral, pharyngeal, laryngealRT-PCR6
Hahn, 2002 [35]GermanyCaucasianPB949261.545.165.951.1OralPCR-RFLP7
Lei, 2002 [45]ChinaAsianHB625660.258.2NANALaryngealPCR-RFLP7
Varzim, 2002 [40]PortugalCaucasianPB8817262.843.094.372.7LaryngealPCR-RFLP7
Cheng, 2003 [43]TaiwanAsianHB279325NANANANAPharyngealPCR-RFLP6
Gajecka, 2005 [33]PolandCaucasianHB28931157.945.9100100LaryngealPCR-RFLP8
Rydzanicz, 2005 [38]PolandCaucasianHB26614361.653.195.1100Oral, pharyngeal, laryngealPCR-RFLP8
Unal, 2005 [39]TurkeyCaucasianHB4510453.550.093.365.4LaryngealPCR-RFLP7
Marques, 2006 [52]BrazilMixedHB23121256.655.383.579.2OralPCR-RFLP8
Gara, 2007 [51]TunisiaMixedHB6416050.753.665.645Oral, pharyngeal, laryngealPCR-RFLP7
Majumder, 2007 [47]IndiaAsianHB297342NANANANAOralPCR-RFLP6
Boccia, 2008 [22]ItalyCaucasianHB21024563.663.371.472.2Oral, pharyngeal, laryngealPCR-RFLP8
Buch, 2008 [50]USAMixedPB18239958.758.787.475.7OralPCR-RFLP9
Harth, 2008 [36]GermanyCaucasianHB31230059.747.280.458.7Oral, pharyngeal, laryngealPCR-RFLP6
Chatzimichalis, 2010 [30]GreeceCaucasianHB8810266.562.587.574.5LaryngealPCR-RFLP8
Demokan, 2010 [31]TurkeyCaucasianPB959359.653.386.352.7Oral, pharyngeal, laryngealPCR8
Hou, 2011 [44]ChinaAsianPB17217049.649.6100100Oral, pharyngealPCR-RFLP and Taqman9
Balaji, 2012 [42]IndiaAsianHB15713253.155.154.834.8OralTaqman7
Majumder, 2012 [46]IndiaAsianHB299381NANANANAOralPCR6
Tian, 2013 [49]ChinaAsianPB23310260.060.0NANALaryngealPCR8
Marques, 2014 [53]BrazilMixedPB101141NANANANAOral, pharyngeal, laryngealPCR-RFLP7
Abbreviations: HB, hospital-based; PB, Population-based; PCR, Polymerase Chain Reaction; RT, Real Time; RFLP, Restriction Fragment Length Polymorphism; NA, Not Available. Taqman: The 5′ Nuclease Assay.

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.

Table 2. Prevalence of the polymorphisms of N-acetyltransferases 1 and 2 (NAT1 and NAT2), (slow vs. rapid acetylators).
Author, Year NAT1
CaseControl
SlowRapidSlowRapid
Katoh, 1998 [41]9534676
Henning, 1999 [23]144109232164
Jourenkova-Mironova, 1999 [37]1411099874
Olshan, 2000 [54]838810885
Fronhoffs, 2001 [32]1959620694
Varzim, 2002 [40]484010765
Demokan, 2010 [31]53424251
Majumder, 2012 [46]128171168213
Author, YearNAT2
CaseControl
SlowRapidSlowRapid
Gonzalez, 1998 [34]284737163
Katoh, 1998 [41]7557115
Henning, 1999 [23]138117286224
Jourenkova-Mironova, 1999 [37]1421089181
Morita, 1999 [48]1812717147
Chen, 2001 [29]198143302250
Hahn, 2002 [35]59355735
Lei, 2002 [45]50123422
Varzim, 2002 [40]47417696
Cheng, 2003 [43]3924054271
Gajecka, 2005 [33]127162165146
Rydzanicz, 2005 [38]1311357271
Unal, 2005 [39]1530797
Marques, 2006 [52]2920238174
Gara, 2007 [51]333159101
Majumder, 2007 [47]190107205137
Boccia, 2008 [22]109101128117
Buch, 2008 [50]8498224175
Harth, 2008 [36]189123181119
Chatzimichalis, 2010 [30]39496537
Demokan, 2010 [31]50454548
Hou, 2011 [44]4612633137
Balaji, 2012 [42]100576765
Tian, 2013 [49]189445646
Marques, 2014 [53]48535190

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.

Table 3. Subgroup analyses of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators).
PolymorphismVariable (N)OR95% CIp-ValueI2Pheterogeneity
NAT1Overall (8)0.890.77, 1.020.0948%0.06
Ethnicity     
Caucasian (5)0.960.80, 1.150.640%0.45
Asian (2)0.550.17, 1.800.3287%0.005
Control source     
Hospital-based (6)0.870.74, 1.010.0646%0.10
Population-based (2)1.050.51, 2.170.9072%0.06
Sample size     
≥200 (6)0.900.77, 1.040.150%0.87
<200 (2)0.670.13, 3.560.6491%0.0007
Genotyping method     
PCR (4)0.940.79, 1.140.5426%0.26
PCR-RFLP (3)0.640.34, 1.180.1574%0.02
Tumor type     
Oral (2)0.550.17, 1.800.3287%0.005
Laryngeal (2)0.870.67, 1.150.330%0.43
NAT2Overall (25)1.221.02, 1.460.0374%<0.00001
Ethnicity     
Caucasian (13)1.100.89, 1.370.3871%<0.0001
Asian (8)1.601.13, 2.260.00869%0.002
Mixed (4)1.040.61, 1.770.8979%0.003
Control source     
Hospital-based (15)1.100.88, 1.370.3971%<0.0001
Population-based (10)1.411.04, 1.920.0375%<0.0001
Sample size     
≥200 (20)1.191.00, 1.420.0570%<0.00001
<200 (5)1.490.68, 3.290.3285%<0.0001
Genotyping method     
PCR (4)1.470.77, 2.780.2485%0.0002
PCR-RFLP (19)1.140.93, 1.390.2172%<0.00001
Tumor type     
Oral (7)1.050.80,1.380.7262%0.01
Pharyngeal (2)0.820.54, 1.240.350%0.96
Laryngeal (8)1.480.88, 2.510.1488%<0.00001
Abbreviations: PCR, Polymerase Chain Reaction; RFLP, Restriction Fragment Length Polymorphism.

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.

Table 4. Meta-regression analysis of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators).
PolymorphismVariable Point EstimateStandard ErrorLower LimitUpper LimitZ-Valuep-Value
NAT1Publication yearSlope0.018300.01361−0.008370.044971.344620.17875
Intercept−36.7709827.26207−90.2036516.66169−1.348800.17740
Sample sizeSlope0.000270.00045−0.000600.001150.612400.54027
Intercept−0.259930.24912−0.748190.22833−1.043400.29676
Mean age of casesSlope−0.011790.03248−0.075460.05186−0.363000.71660
Intercept0.570371.93376−3.219724.360470.294960.76803
Mean age of controlsSlope−0.022630.03624−0.093650.04839−0.624590.53224
Intercept1.179382.13386−3.002905.361670.552700.58047
Male percentage of casesSlope−0.011310.01256−0.035930.01331−0.900740.36773
Intercept0.867381.11137−1.310873.045620.780460.43512
Male percentage of controlsSlope−0.002680.00617−0.014780.00942−0.434740.066375
Intercept0.032300.43459−0.819480.884090.074330.94074
NAT2Publication yearSlope0.009440.01016−0.010470.029340.0929420.35267
Intercept−18.8228420.36308−58.7337321.08806−0.924360.35530
Sample sizeSlope−0.000800.00020−0.00120−0.00040−3.912390.00009
Intercept0.508820.113000.287330.730304.502650.00001
Mean age of casesSlope−0.040500.01356−0.06706−0.01393−2.0987760.00281
Intercept2.478880.800070.910774.046993.098320.00195
Mean age of controlsSlope−0.004380.00889−0.021800.01305−0.492030.62270
Intercept0.346910.47403−0.582171.276000.731840.46427
Male percentage of casesSlope−0.06290.00393−0.013990.00141−1.602010.10915
Intercept0.573660.33428−0.081521.228841.716100.08614
Male percentage of controlsSlope−0.007850.00289−0.01351−0.00219−2.719890.00653
Intercept0.643730.221520.209561.077902.905980.00366

3. Current Insights

This meta-analysis showed a significant relationship between NAT2 polymorphisms and the HNC susceptibility with slow acetylators being at higher risk for HNC than rapid acetylators. For NAT2 polymorphism, the ethnicity, the control source, and genotyping methods could modify the association of this polymorphism and the HNC risk. In addition, TSA showed the amount of information for the association between the polymorphisms (NAT1 and NAT2) and the HNC risk was not large enough.
The findings from studies exploring the association of NAT1 polymorphism with other cancers and HNC are different. One meta-analysis [24] found NAT1 polymorphism to be related to the risk of lung, colorectal, head and neck, bladder, and gastric carcinomas, but not with prostate, breast, and pancreatic carcinomas and non-Hodgkin’s lymphoma. Varzim et al. [40][47] checked the association between NAT1 polymorphism and the laryngeal cancer risk and found that the association depends on tumor location. Among the eight studies included in our meta-analyses [23][41][31][32][37][40][46][54][23,35,38,39,44,47,52,60] which evaluated the association between NAT1 polymorphism and the HNC risk, just one study [41][35] reported a protective role of NAT1 slow acetylators in the HNC patients while the rest of the studies did not find any association.
Comparing the individual studies included in the meta-analysis, differences were observed between the studies. For example, five studies [34][39][42][49][41,46,48,55] found an elevated risk of HNC for NAT2 slow acetylators, one found a protective role of these acetylators in HNC patients, and three did not find any association between NAT2 polymorphism and the HNC risk [23][38][43][23,45,49].
Effective factors on the association between NAT polymorphisms and the risk of HNC were not included in our analysis due to low numbers of studies, including smoking, gene combination, and the linkage disequilibrium. One study [34][41] found an elevated frequency of the NAT2 slow acetylator genotypes among HNC patients who smoked less than those who smoked more frequently. Another study reported an association in cases with a smoking history ≤30 years in duration [41][35]. These contradictory results [41][34][39][35,41,46] suggest the need to evaluate the effect of NAT polymorphisms independent of the history of smoking. In addition, assessing the frequencies of gene-gene combination (NAT2 with GSTM1, XPD, and CYP1A1) between cases with laryngeal cancer and the controls, the frequency of combinations was superior to cases than in controls where the numbers of combinations had an increased risk of laryngeal cancer and the numbers of other combinations had a protective role [33][40]. The linkage disequilibrium between the genes of NAT1 and NAT2 has been observed in HNC [23][31][56][23,38,62] and other cancers [57][58][59][63,64,65]. Research [60][66] showed the highest level of carcinogen-DNA adducts formation in cases with acetylation activity of NAT1 rapid and NAT2 slow. Therefore, future studies should consider the linkage between these polymorphisms.

4. Conclusions

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.