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Interaction between tumour necrosis factor-α gene polymorphisms and substance use on risk of betel quid-related oral and pharyngeal squamous cell carcinoma in Taiwan
archives of oral biology 56 (2011) 1162–1169
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Interaction between tumour necrosis factor-a gene polymorphisms and substance use on risk of betel quid-related oral and pharyngeal squamous cell carcinoma in Taiwan Cheng-Mei Yang a,b,1, Yu-Yi Hou c,d,1, Yi-Ten Chiu e,f, Hung-Chih Chen a, Sau-Tung Chu c, Chao-Chuan Chi c, Michael Hsiao e,g, Chien-Yiing Lee h, Christina Jen-Chia Hsieh e, Yu-Chen Lin i, Yao-Dung Hsieh a,j, Luo-Ping Ger e,f,* a
Department of Dentistry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan Department of Dental Laboratory Technology, Shu Zen College of Medicine & Management, Kaohsiung, Taiwan c Department of Otorhinolaryncology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan d Department of Nursing, Yuh-Ing Junior College of Health Care & Management, Kaohsiung, Taiwan e Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan f Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung, Taiwan g Genomics Research Center, Academia Sinica, Taipei, Taiwan h Department of Dentistry, Zuoying Armed Forces General Hospital, Kaohsiung, Taiwan i Department of Life Science, Fu Jen University, Taipei, Taiwan j Graduate School of Dental Science, National Defense Medical Center, Taipei, Taiwan b
article info
abstract
Article history:
Objective: Betel quid (BQ) components induce the secretion of tumour necrosis factor-alpha
Accepted 18 March 2011
(TNF-a) in oral keratinocytes, which promotes oral mucosal inflammation and oral cancer.
Keywords:
and 238G>A) with the risk and prognosis of BQ-related oral and pharyngeal squamous cell
This study was carried out to evaluate the association of TNFA genetic variants (308G>A Oral and pharyngeal cancer
carcinoma (OPSCC).
Single nucleotide polymorphisms
Design: A total of 403 subjects (205 cancer cases and 198 healthy controls) who habitually
Betel-quid
chewed BQ were recruited. The genotypes were determined by TaqMan real-time assays.
Tumour necrosis factor
Results: G allele and G/G genotype at TNFA 308 were associated with a 1.95-fold (95%CI:
Interaction
1.16–3.28, pcorrected = 0.024) and 2.28-fold (95%CI: 1.30–4.00, pcorrected = 0.008) increased risk of cancer as compared to those with A allele or A/A + A/G genotypes, respectively. In addition, G allele ( p = 0.080) and G/G genotype ( p = 0.076) at TNFA 238 were associated with a borderline but statistically significant increased risk of OPSCC. The combined G/G + G/G genotype at both loci had a 2.37-fold increased risk of OPSCC as compared to those with other combined genotypes (95%CI: 1.41–4.00, p = 0.001). Interactions between combined genotypes and smoking status were also found to contribute to risk of BQ-related OPSCC. There was no association of TNFA genotypes with clinicopathologic findings or the survival of OPSCC patients.
* Corresponding author at: Department of Medical Education and Research, Kaohsiung Veterans General Hospital, 386 Ta-Chung 1st Rd., Kaohsiung, Taiwan. Tel.: +886 7 346 8356; fax: +886 7 346 8056. E-mail addresses: [email protected], [email protected] (L.-P. Ger). 1 The first two authors contributed equally to this work. 0003–9969/$ – see front matter . Crown Copyright # 2011 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.archoralbio.2011.03.009
archives of oral biology 56 (2011) 1162–1169
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Conclusions: BQ-chewers who carry the G allele or G/G genotype in TNFA 308 may have an increased risk of OPSCC. The intensity of cigarette smoking modulates the effect of the combined TNFA genotypes on risk of BQ-related OPSCC. Crown Copyright # 2011 Published by Elsevier Ltd. All rights reserved.
1.
Introduction
Oral and pharyngeal cancer is one of the most prevalent cancers, currently listed as the 6th leading cancer worldwide, and is particularly common in southeastern Asia.1 In Taiwan, oral and pharyngeal cancer is the fourth leading cancer in men, the top cancer in young male adults (25–44 yrs old). It is also the 6th leading cause of cancer deaths in males. Squamous cell carcinoma (SCC) accounts for more than 90% of all oral and pharyngeal cancers.3 Betel quid (BQ) chewing has been ranked as a Group I carcinogen by the International Agency of Research on Cancer (IARC) and may play an etiological role in the development of oral and pharygeal SCC (OPSCC).4–6 In Taiwan, approximately 90% of OPSCC patients chew betel quids regularly; the risk of developing OPSCC from chewing betel quids is higher than that from smoking or excessive alcohol drinking.2,7 BQ components have been shown to induce the secretion of tumour necrosis factor-alpha (TNF-a) in oral keratinocytes,6,8 which may provoke oral mucosal inflammation9 and oral cancer.6 TNF-a is a pleiotropic cytokine that plays an important role in inflammation, cancer, and apoptosis.10 Preclinical and clinical studies have shown the therapeutic anti-tumour effects of TNF-a in tumours,11 but there is increasing evidence that it may also promote the development and spread of cancer.12,13 TNFA is located on chromosome 6p21.231 in the polymorphic region of MHC III, and its promoter polymorphisms have been intensively studied as a potential determinant of disease susceptibility. Commonly described variants of TNFA polymorphisms consist of G to A transitions in the promoter region at positions 238 and 308.14 Recent studies have shown that TNFA promoter at 308 has direct effects on TNFA gene regulation.15,16 A significant association between the TNFA 308 G/A polymorphism and higher levels of expression of TNF-a has been found.17 TNFA 238 is a putative repressor site located in a 25 bp stretch of TNFA promoter.18 The association of single nucleotide polymorphisms (SNPs) of the TNFA gene with OPSCC has been inconclusive and controversial.3,19–22 TNFA gene polymorphisms have been reported in patients with tobacco-related OPSCC,22 but not in BQ-related OPSCC. In Taiwanese BQ chewers, 70% were also alcohol drinkers and more than 90% were smokers.23 Studies have indicated that BQ chewing and smoking may synergistically contribute to the development of OPSCC.7,23,24 The interactive effects between TNFA genetic polymorphisms and substance use; such as BQ chewing, smoking, and alcohol drinking; on risk of oral cancer remains uncertain. Therefore, the present study was undertaken to investigate the relationship between TNFA genetic variants and susceptibility to BQ-related OPSCC. The effect of interactions between TNFA genetic variants and substance use on the risk of BQ-related OPSCC was also evaluated. In
addition, the association of TNFA genotypes with clinicopathologic features and survival of OPSCC patients was also determined.
2.
Materials and methods
2.1.
Study subjects
In this study, 403 male subjects who habitually chewed BQ were recruited: 205 OPSCC case patients and 198 healthy controls. Case patients with newly diagnosed, previously untreated, and pathologically confirmed primary OPSCC (of the oral cavity, oropharynx, and hypopharynx) were recruited between January 2004 and November 2007 from the Department of ENT and Dentistry at Kaohsiung Veterans General Hospital (KSVGH). Case patients with complete follow up (195, 95.12%) and annual reviews of medical records entered the survival analysis. The 198 healthy controls were recruited from the oral health screen clinic at the Department of Otolaryngology, KSVGH and from the oral health screen campaigns for vehicle drivers, cleaners, and hardware workers held by the Kaohsiung city government or Department of Otolaryngology, KSVGH between 2004 and 2007. The selection criteria for controls included the absence of history of cancer and oral precancerous lesions, and negative screening for oral precancerous lesions. Controls were frequency-matched to case patients on age (5 years), ethnicity, and years of BQ chewing. After signing an informed consent, each subject was interviewed using a structured questionnaire that elicited detailed information on the history of betel quid chewing, cigarette smoking, alcohol drinking habits, and the general demographic data. At the end of the interview, each subject donated 7–15 ml of blood in an EDTA tube according to the protocol that had been approved by the Institutional Review Board of KSVGH. A BQ chewer was defined as a person who had chewed at least one betel quid per day for one year or more. Pack-years of BQ consumption were calculated using the following: packyears = (mean number of betel quids chewed per day/20 betel quids) number of years chewed. Light and heavy BQ chewers were categorized by using the median values of BQ consumption (pack-years) in controls as the cutoff. A smoker was defined as a person who had smoked at least one cigarette per day for one year or more. Pack-years of cigarette consumption were calculated using the following: pack-years = (mean number of cigarettes smoked per day/20 cigarettes) number number of years smoked. Light and heavy smokers were categorized by using the median value of cigarette consumption (pack-years) in controls as the cutoff. A drinker was defined as a person who had drunk at least once a week for more than one year. Gram-years of alcohol consumption were
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calculated using the following: gram-years = mean gram of alcohol drank per day number of years drank. Light and heavy drinkers were also categorized by using the median value of alcohol consumption (gram-years) in controls as the cutoff. The survival time was estimated from the time of operation or biopsy to November 2010. Overall survival (OS) was calculated from the date of initial resection of the primary tumour to the date of death from any cause or last follow-up. Disease-specific survival was measured from the time of initial resection of the primary tumour to the date of cancerspecific death or last follow-up. Disease-free survival was calculated from the date of initial resection of the primary tumour to date of recurrence or last follow-up. Pathological TNM classification was determined at the time of the initial resection of the tumour in accordance with the guidelines of the 2002 American Joint Committee on Cancer (AJCC) system.
2.2.
SNP genotyping
Genomic DNA for genotyping was extracted and purified from whole-blood samples with QIAamp1 DNA midi kit according to the manufacturer’s instructions (Qiagen Sciences1, Germantown, MD, USA). The detection of genotypes of TNFA 238 G>A and TNFA 308 G>A was performed by the TaqMan realtime PCR method, and then analysed by ABI PRISM 7500
Sequence Detection System (Applied Biosystems, Foster City, CA) in 96-well format. The SNPs of TNFA 238 G>A and TNFA 308 G>A were assayed by use of TaqMan real-time polymerase chain reaction (PCR) (Applied Biosystems, Foster City, CA, USA). PCR reactions were carried out in a reaction mixes containing 10 ng DNA, 5 ml 2 TaqMan Universal PCR Master Mix (Applied Biosystems), 0.5 ml 20 Primer/Probe mixture, and ddH2O to a final volume of 10 ml. The PCR program was as follows: 95 8C for 10 min, followed by 40 cycles of 15 s at 92 8C, and 1 min at 60 8C. A single no-DNA-template control in each 96-well format was used for quality control. The allelic-specific fluorescence data from each plate were analysed using the SDS v1.3.1 software (Applied Biosystems, 2005) to determine the genotype of each sample. The quality control procedures were implemented to ensure high genotyping accuracy in our laboratory. A senior researcher independently reviewed all of the absolute quantification curves for fluorescence data in TaqMan assays. Finally, 100% of the samples of the less prevalent genotypes and 10% of the samples of the more prevalent genotypes were randomly selected and run in duplicate to ensure accuracy of genotyping.
2.3.
Statistical analysis
For each tested polymorphism, departure from Hardy– Weinberg equilibrium in controls was evaluated by x2 test
Table 1 – Distribution and odds ratios of demographic and substance use for OPSCC. Factor/category Age (mean SD) <40 40–49 50–59 60
OPSCC cases (n = 205)
BQ controls (n = 198)
Number (%)
Number (%)
49.27 7.97 24 (11.7) 78 (38.0) 88 (42.9) 15 (7.3)
48.92 8.23 26 (13.1) 75 (37.9) 81 (40.9) 16 (8.1)
CORa (95%CI)
p-Valueb 0.670c
1.00 1.13 (0.60–2.13) 1.18 (0.63–2.21) 1.02 (0.41–2.49)
0.714 0.613 0.973
(78.3) (7.1) (12.1) (2.5)
1.00 0.92 (0.42–1.99) 0.69 (0.36–1.32) 0.73 (0.19–2.78)
0.826 0.258 0.649
Ethnicity Fukienese Hakka Mainlander Aborigines
169 14 18 4
Years of education 6 7–12 >12
70 (34.1) 116 (56.6) 19 (9.3)
63 (31.8) 120 (60.6) 15 (7.6)
1.00 0.87 (0.57–1.33) 1.14 (0.53–2.43)
0.521 0.735
BQ chewing (packd-years) Light (>18.5) Heavy (>18.5)
92 (44.9) 113 (55.1)
99 (50.0) 99 (50.0)
1.00 1.23 (0.83–1.82)
0.303
Smoking (packe-years) Never-smoker Light (1–29.9) Heavy (>29.9)
21 (10.2) 102 (49.8) 82 (40.0)
12 (6.1) 94 (47.5) 92 (46.5)
1.00 0.62 (0.29–1.33) 0.51 (0.24–1.10)
0.219 0.086
Drinking (gram-years) Never-drinker Light (1–1276.8) Heavy (>1276.8)
44 (21.5) 84 (41.0) 77 (37.6)
77 (38.9) 60 (30.3) 61 (30.8)
1.00 2.45 (1.49–4.03) 2.21 (1.34–3.64)
<0.001 0.002
a b c d e
(82.4) (6.8) (8.8) (2.0)
COR, crude odds ratios. p-Value is estimated by logistic regression. p-Value is estimated by t-test. Twenty betel quids per pack. Twenty cigarettes per pack.
155 14 24 5
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with 1 df. Measures of pairwise LD between polymorphisms within the same gene were carried out with HaploView software (http://www.broad.mit.edu/personal/jcbarret/haploview/). Univariate analysis was first performed to calculate the crude odds ratios and their 95% confidence intervals (CI) of selected demographic and risk factors, as well as genetic polymorphisms amongst cases and controls by logistic regression. Multiple logistic regression was used to evaluate the association of allelic types and genotypes of polymorphisms in TNFA with OPSCC risk by adjusting various confounders, such as age, ethnicity, education, the pack-years of BQ chewing and cigarette smoking, as well as the gram-years of alcohol drinking. In addition, false discovery rate (FDR) was applied for p-value correction for multiple comparisons of all allelic or genotypic types.25 Chisquare test was used to evaluate the correlation between each genotype and clinicopathologic parameter. The cumulative survival curves were estimated using the Kaplan– Meier method and comparison of the survival curves between different genotypes was performed by the logrank test. A Cox proportional hazards model was also used to assess the prognostic value of TNFA genotypes together with other clinicopathologic covariates. All statistical analysis was performed using the SPSS software package (version 12.0, SPSS Inc., Chicago, IL). The results of p < 0.05 were considered statistically significant.
3.
Results
3.1. Demographic and substance use features of the subjects The demographic data of the 403 recruited subjects are shown in Table 1. There was no difference in the mean age between the 205 OPSCC patients (49.27 7.97, range: 32–72 years) and the 198 controls (48.92 8.23, range: 28–75 years, p = 0.670). The cut-off was set at 18.5 pack-years (twenty nuts per pack) for BQ chewers, 29.9 pack-years (twenty cigarettes per pack) for smokers, and 1276.8 gram-years for drinkers. Most BQ chewers (89.8% in cases and 94% in controls) also had a habit of cigarette smoking. The distribution of ethnicity, years of education, BQ chewing, as well as smoking was similar between the two groups. Alcohol drinking was associated with a significantly increased risk for OPSCC in both light and heavy drinkers (COR = 2.45, 95%CI: 1.49–4.03, p < 0.001; COR = 2.21, 95%CI: 1.34–3.64, p = 0.002, respectively).
3.2.
Polymorphisms associated with BQ-related OPSCC
The genotype distributions of 308G>A and 238G>A were in Hardy–Weinberg equilibrium for controls (p values being 0.086 and 0.688, respectively). Amongst these two SNPs (308 and
Table 2 – Association of the genotypes and allelic types with OPSCC risk.
Genotypes
OPSCC cases (n = 205) Number (%)
BQ controls (n = 198) Number (%)
OPSCC cases VS. BQ controls
OR (95% CI)
Crude p-value
Pcorrected
Adjusted ORa (95% CI) p-valuea
Pcorrected
TNFA-308G>A
A G A/A G/A G/G
27 (6.6)
43 (10.9)
1.00
383 (93.4)
353 (89.1)
1.72 (1.05-2.86)
2 (1.0)
0 (0.0)
23 (11.2)
43 (21.7)
180 (87.8)
155 (78.3)
1.00 0.033
0.066
1.00 2.00 (1.17-3.42)
1.95 (1.16-3.28)
0.012
0.024
0.004
0.008
0.080
0.080
0.076
0.076
1.00 0.012
0.024
2.28 (1.30-4.00)
0.123
0.123
2.63 (0.89-7.78)
TNFA-238G>A
A G A/A G/A G/G
5 (1.2)
11 (2.8)
1.00
405 (98.8)
385 (97.2)
2.31 (0.80-6.72)
0 (0)
0 (0)
5 (2.4)
11 (5.6)
200 (97.6)
187 (94.4)
1.00
1.00 2.35 (0.80-6.90)
1.00 0.119
0.119
2.71 (0.90-8.12)
Combined genotypes of TNFA –308G>A and -238G>A
G/A+G/A A/A+G/A G/G+G/G a
30 (14.6)
52 (26.3)
1.00
175 (85.4)
146 (73.7)
2.08(1.26-3.53)
p-value are adjusted for age (40-49, 50-59,
of betel quid chewing ( > 18.5 vs.
1.00 0.004
2.37 (1.41-4.00)
60 vs. < 40), ethnicity (Hakka, Mainlander vs. Fukienese), education (7-12, > 12 vs.
0.001
6), the pack-years
18.5), smoking (1-29.9, > 29.9 VS. never-smoking) and the gram-years of drinking (1-1276.8, > 1276.8 VS. never-
drinker) by multiple logistic regression
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0.494
11/31 14/18
4/19 26/33
Cigarette smoking Light Heavy
Alcohol drinking Never drinking Drinking
f
CS: case (OPSCC); CN: control (BQ control). b Others include diplotype of 308G/A and 238GA and diplotype of 308A/A and 238G/A. c G/G + G/G: TNFA 308GG genotype and 238GG genotype. d p-Value are adjusted for age (40–49, 50–59, 60 vs. <40), ethnicity (Hakka, Mainlander vs. Fukienese), education (7–12, >12 vs. 6), the pack-years of betel quid chewing (>18.5 vs. 218.5) and smoking (>29.9 vs. 29.9) and the gram-years of drinking (1–1276.8, >1276.8 vs. never-drinker) by multiple logistic regression. e BQ chewing light is 18.5 pack-years and heavy is <18.5 pack-years. f Cigarette smoke light is 29.9 pack-years and heavy is >29.9 pack-years.
40/58 135/88
91/63 68/74
82/75 93/71
G/G + G/G
Others
10/24 20/28 BQ chewinge Light Heavy
a
0.054 0.024 3.50 (0.98–12.53) 2.17 (1.19–3.96) 1.00 1.00 3.28 (1.04–10.36) 1.95 (1.09–3.48) 1.00 1.00
0.043 0.024
0.043 0.048
0.054 0.012
0.017 <0.001 0.499 4.65 (2.07–10.44) 1.33 (0.58–3.07) 1.00 1.00 4.07 (1.91–8.70) 1.18 (0.55–2.56) 1.00 1.00
<0.001 0.672
<0.001 0.672
<0.001 0.499
0.016 0.084 0.008 0.084 3.32 (1.38–8.01) 1.83 (0.92–3.62) 1.00 1.00 2.62 (1.18–5.85) 1.83 (0.96–3.52) 1.00 1.00
0.018 0.068
0.036 0.068
p-valued G/G + G/G Others pcorrected p-value G/G + G/G Others
Adjusted OR (95%CI) CS/CN
TNFA 308G>A combined with 238G>A
Crude OR (95%CI)
c b
a
Table 3 – Odds ratios for OPSCC according to the combined genotypes of TNFA G S308A and TNFA GS238A and substance use.
pcorrected
0.327
P for interaction
archives of oral biology 56 (2011) 1162–1169
238), only the 308 locus showed significant association with OPSCC (Table 2). The G allele at TNFA 308 was significantly associated with increased risk of OPSCC (AOR = 1.95, 95%CI: 1.16–3.28, p = 0.012), even after FDR correction ( p = 0.024). Using A/A and G/A as the reference group, homozygous G/G at TNFA 308 conferred a significant 2.28-fold increased risk for OPSCC (95%CI: 1.30–4.00, p = 0.004), even after FDR correction ( p = 0.008). Although no significant difference was found in allelic and genotypic frequencies between patients and controls at locus 238, a borderline significant increased risk was found for those with the G allele and GG genotype after adjustment of confounders in the logistic regression model (AOR = 2.63, 95%CI: 0.89–7.78, p = 0.080 and AOR = 2.71, 95%CI: 0.90–8.12, p = 0.076, respectively) and after FDR correction ( p = 0.080 and 0.076, respectively). Linkage disequilibrium was not found between SNPs at locus 308 and locus 238 (r2 = 0.001, D0 = 0.636), therefore, haplotype analysis was not performed. In this study, we analysed possible combinations of genotypes formed by 308 G>A and 238 G>A. Carriers with the combined genotype of G/G + G/G at locus 308 and 238 had a 2.37-fold increased risk of OPSCC compared to those with other combined genotypes (AOR = 2.37; 95%CI: 1.41–4.00, p = 0.001).
3.3. Interactions between substance use and the combined genotype of S308 and S238 SNPs Risks associated with the combined genotype significantly differed depending on the intensity of cigarette smoking. Such interactions were not found for the intensity of BQ chewing or alcohol drinking (shown in Table 3). The G/G + G/G genotype was correlated with a greater risk of BQ-related OPSCC in the stratum of light smokers (29.9 pack-year; 95%CI: 2.07–10.44, p < 0.001). However, in the stratum of heavy smokers, no significant association was found between the various combined genotypes and risk of BQ-related OPSCC (95%CI: 0.58–3.07, p = 0.499). Therefore, the influence of G/G + G/G genotype on risk of OPSCC appeared to be greater in light smokers (AOR = 4.65) than that in heavy smokers (AOR = 1.33; pinteraction = 0.017). These results might suggest that the intensity of cigarette smoking modulates the effect of the combined TNFA genotypes on BQ-related OPSCC risk.
3.4. Association of TNFA genotypes with clinicopathologic features and survival of OPSCC patients The clinicopathologic characteristics of the BQ-related OPSCC patients are summarized in Table 4. There was no correlation between genetic variants in TNFA (308 and 238) and clinicopathologic findings, such as age of disease onset, cell differentiation, AJCC pathological stage, T classification, N classification, recurrence status, and metastasis status at diagnosis (shown in Table 4). With a median follow-up of 44.97 (range 1.37–82.97) months, the overall survival rate was 50.38 3.80% at 5 years. The disease-specific survival rate was 51.46 3.83% at 5 years. The disease-free survival rate remained constant at 57.57 3.88% 4 years from the time of initial resection. In addition, the median overall survival time was 5.96 years and the median disease-specific survival time was 6.04 years. There was no any associations between genetic
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Table 4 – The TNF A genotypes in relation to clinicopathologic features in BQ-related OPSCC patients. Variables
TNFA 308G>A
TNFA 238G>A
G/G (n = 172)
G/A + A/A (n = 23)
Number (%)
Number (%)
91 (52.9) 81 (47.1)
9 (39.1) 14 (60.9)
x2 = 1.541
Cell differentiation Well Moderate + Poor
34 (19.8) 138 (80.2)
3 (13.0) 20 (87.0)
Pathological stage I + II III + IV
90 (52.3) 82 (47.7)
T classification T1 + T2 T3 + T4
G/G (n = 190)
G/A + A/A (n = 5)
Number (%)
Number (%)
0.214
99 (52.1) 91 (47.9)
x2 = 0.597
0.578a
12 (52.2) 11 (47.8)
x2 < 0.001
125 (72.7) 47 (27.3)
16 (69.6) 7 (30.4)
N classification N0 N1 + N2
115 (66.9) 57 (33.1)
Recurrence status No Yes Metastasis status No Yes
Age (years) <50 50
a
Statistic
Statistic
p-Value
1 (20.0) 4 (80.0)
x2 = 2.010
0.202a
35 (18.4) 155 (81.6)
2 (40.0) 3 (60.0)
x2 = 1.476
0.241a
0.989
100 (52.6) 90 (47.4)
2 (40.0) 3 (60.0)
x2 = 0.312
0.671a
x2 = 0.098
0.754
138 (72.6) 52 (27.4)
3 (60.0) 2 (40.0)
x2 = 0.388
0.618a
15 (65.2) 8 (34.8)
x2 = 0.025
0.875
127 (66.8) 63 (33.2)
3 (60.0) 2 (40.0)
x2 = 0.103
1.000a
107 (62.2) 65 (37.8)
13 (56.5) 10 (43.5)
x2 = 0.277
0.598
115 (60.5) 75 (39.5)
5 (100.0) 0 (0.0)
x2 = 3.207
0.159a
151 (87.8) 21 (12.2)
20 (87.0) 3 (13.0)
x2 = 0.013
1.000a
167 (87.9) 23 (12.1)
4 (80.0) 1 (20.0)
x2 = 0.281
0.485a
Two-tailed Fisher’s exact test.
variants in TNFA (308 and 238) and disease-specific survival and disease-free survival (data not shown).
4.
p-Value
Discussion
Our study showed that G allele and G/G genotype at TNFA 308 and 238 were significantly associated with an increased risk of BQ-related OPSCC, although the significance found for 238 was only marginal. The combined genotype of G/G + G/G at locus 308 and 238 was associated with an increased risk of OPSCC. Risks associated with this combined genotype differed significantly depending on the intensity of cigarette smoking; however, such associations were not detected for the intensity of BQ chewing or alcohol drinking. These findings suggest that TNFA gene may play a role in the development of BQ-related OPSCC. However, genetic variants of TNFA were not correlated with clinicopathologic features and survival of BQ-related OPSCC patients. To the best of our knowledge, this is the first study to investigate the role of TNFA genetic variants and the interactions between TNFA gene and substance use in the development of OPSCC amongst the Taiwanese BQ-chewing population. The TNFA 238A allele is known to cause a significant decrease in the transcription of the TNFA gene in human blood cells.14,26 No significant association was observed at the 238 SNP with tobacco-related oral carcinoma in Asian Indians.22 For Taiwanese people, Liu et al. reported that the 238 G/G genotype was significantly associated with the increased risk of Oral SCC as compared with the G/A genotype (OR = 3.85, p = 0.02).21 We also observed that the TNFA 238G allele and G/
G genotype had a similarly increased risk of BQ-related OPSCC as compared with A allele and G/A genotype (for G allele: AOR = 2.63, p = 0.080; for GG genotype: AOR = 2.71, p = 0.076, respectively), although only a marginal significance was found. Both findings suggest that excessive expression of TNF-a may be associated with OPSCC. However, the frequency of the 238A allele was rare in our study (1.2% for cases and 2.8% for controls), but was similar to the frequencies previously reported in Asian populations, as low as 1.0% for cases and 3.4% for controls in a Taiwanese study and 0% for both cases and controls in an Indian study.21,22 However, inconsistencies amongst these three studies due to small sample sizes (or rare allele), ethnic differences, or different substance-related (tobacco-related or BQ-related) oral cancers cannot be excluded. Therefore, validation studies with independent large cohorts are required. Our results showed that the G allele and G/G genotype at TNFA 308 were associated with increased risk of OPSCC, consistent with previous studies.19,21 Both Chiu et al. and Liu et al. suggest that the 308A allele confers a protective effect against cancer, possibly by increasing TNF-a production. Two in vitro studies demonstrated that the 308A allele is associated with transcription of TNF-a that is about 7 times more efficient than that associated with G allele.15,16 These findings are consistent with the anti-cancer properties of TNFa.11 TNF-a may induce apoptosis of tumour cells through binding to cell surface receptors, which leads to secondary signalling events and the activation of endonucleases and DNA fragmentation.27 TNF-a, especially high doses of TNF-a in soluble form, may promote tumour lysis by activating the antitumour T-cell response.11,28,29 In addition, an epidemiological
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study has shown that the 308G/G genotype is significantly associated with increased risk of oral submucosa fibrosis (OSF), a pre-cancerous lesion with a high malignant trasformation rate, possibly resulting from the decreased collagenase activity of TNF-a.19 Therefore, the 308 G/G genotype was associated with the risk of OSF and in turn BQ-related OPSCC. However, other studies did not reported such associations between the risk of OPSCC and the 308A allele.3,20,22,30 These contradictory results may indicate either differences in pathogenesis as a result of variation in substance use or ethnic stratification in each study. We found a synergistic relationship between the TNFA combined genotypes and smoking status that modified the risk of BQ-related OPSCC. The cellular origin of Oral SCC is the oral keratinocyte, and keratinocyte inflammation is crucial for the pathogenesis of cancer and tissue fibrosis.6 Cigarette smoking, alcohol drinking, and BQ chewing play important roles in the aetiology of OSF and OPSCC, and may act in synergy.7,24,31,32 It is possible that using these substances contributed to the pathogenesis of OPSCC through the suppression of the immune action by affecting the production of inflammatory cytokines such as TNF-a.6,33–37 Some studies reported that cigarette smoking suppresses the production of TNF-a, adversely affects the function of human NK cells and contributes to a higher incidence of cancer.36–38 In our study, the GG + GG genotype was associated with a significantly greater risk for BQ-related OPSCC for light smokers but not for heavy smokers. It is possible that the detrimental suppression of TNF-a as a result of light exposure to cigarette smoke can be overcome with the protective combined genotype (the combined genotype of 308G/A and 238GA as well as the genotype of 308A/A and 238G/A). However, the adverse effects of the suppression of TNF-a as a result of heavy exposure to cigarette smoke might be too great for the protective combined genotype to confer protection. Further experimental studies are necessary to evaluate the validity of this hypothesis. In this study, we reported that TNFA polymorphisms are associated with the development of OPSCC. TNF-a is primarily produced by activated macrophages, T lymphocytes, and natural killer (NK) cells. Its bioactivity is mainly regulated by soluble TNF-a-binding receptors.27 Previous studies have shown a correlation of high TNF-a concentrations with Oral SCC,12,39 but do not answer the question of whether high concentrations of TNF-a are simply a byproduct of oral cancer milieu, or whether TNF-a plays a more active role in the disease process. If we postulate that high concentrations of TNF-a might decrease the risk of OPSCC, then alleles producing lower concentrations, such as the 308G allele and 238A allele, might be considered risk factors for OPSCC. Further investigation is needed to clarify this issue. There are several limitations in this study. Firstly, this study was single-centred. Secondly, TNF-a serum concentration was not measured in healthy and cancer patients at different stages due to the retrospective nature of the study. TNF-a can be regulated by its receptors. Genetic alterations and the expression of TNF receptors have been shown to be related to the development of Oral SCC.22,39 Our findings on TNF-a polymorphisms might be insufficient to clarify the complex interplay amongst a number of different genes
controlling expression of cytokines in OPSCC. Therefore, replication studies on more cytokines and TNF receptors with independent large cohorts are suggested. In conclusion, our study suggests that BQ chewers in Taiwan who carry the G allele or G/G homozygotes in TNFA 308 may have an increased risk of developing BQ-related OPSCC. The contribution of interactions between the combined genotype (308 and 238) with substance use to the risk of BQ-related OPSCC was found only for smoking.
Acknowledgments We thank Yi-Cheng Lee and Ya-Hui Chiao for interview data collection and statistical analysis. We also express our appreciation to Dr. Susan Shin-Jung Lee for assistance in English editing. Funding: Segments of this research were supported by funding from the National Science Council NSC93-2320-B075B-005 (to Luo-Ping Ger), Kaohsiung Veterans General Hospital VGHKS96-091 (to Sau-Tung Chu), VGHKS-97-109 (to Yu-Yi Hou), VGHKS-99-078 (Yu-Yi Hou), and VGHKS-99-099 (to Luo-Ping Ger), and Zuoying Armed Forces Hospital ZAFH9810 (to Chien-Yiing Lee). Competing interests: None declared. Ethical approval: Judgement’s reference number is VGHKS97-CT3-17.
references
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9. Chang MC, Chiang CP, Lin CL, Lee JJ, Hahn LJ, Jeng JH. Cellmediated immunity and head and neck cancer: with special emphasis on betel quid chewing habit. Oral Oncol 2005;41(8):757–75. 10. Oppenheim JJ, Feldmann M. Cytokine reference: a compendium of cytokine and other mediators of host defense. In: Feldmann M, Brennan FM, editors. Cytokines and disease. London: Academic Press; 2001. p. 1619–1632. 11. Waterston A, Bower M. TNF and cancer: good or bad? Cancer Ther 2004:131–48. 12. Hohberger L, Wuertz BR, Xie H, Griffin T, Ondrey F. TNFalpha drives matrix metalloproteinase-9 in squamous oral carcinogenesis. Laryngoscope 2008;118(8):1395–9. 13. Kaomongkolgit R, Manokawinchoke J, Sanchavanakit N, Pavasant P, Sumrejkanchanakij P. Fibronectin supports TNF-a-induced osteopontin expression through b1 integrin and ERK in HN-22 cells. Arch Oral Biol 2010;55(2):101–7. 14. Kaluza W, Reuss E, Grossmann S, Hug R, Schopf RE, Galle PR, et al. Different transcriptional activity and in vitro TNFalpha production in psoriasis patients carrying the TNFalpha 238A promoter polymorphism. J Invest Dermatol 2000;114(6):1180–3. 15. Wilson AG, Symons JA, McDowell TL, McDevitt HO, Duff GW. Effects of a polymorphism in the human tumor necrosis factor alpha promoter on transcriptional activation. Proc Natl Acad Sci USA 1997;94(7):3195–9. 16. Glossop JR, Dawes PT, Nixon NB, Mattey DL. Polymorphism in the tumour necrosis factor receptor II gene is associated with circulating levels of soluble tumour necrosis factor receptors in rheumatoid arthritis. Arthritis Res Ther 2005;7(6):R1227–34. 17. Kroeger KM, Carville KS, Abraham LJ. The 308 tumor necrosis factor-alpha promoter polymorphism effects transcription. Mol Immunol 1997;34(5):391–9. 18. Fong CL, Siddiqui AH, Mark DF. Identification and characterization of a novel repressor site in the human tumor necrosis factor alpha gene. Nucleic Acids Res 1994;22(6):1108–14. 19. Chiu CJ, Chiang CP, Chang ML, Chen HM, Hahn LJ, Hsieh LL, et al. Association between genetic polymorphism of tumor necrosis factor-alpha and risk of oral submucous fibrosis, a pre-cancerous condition of oral cancer. J Dent Res 2001;80(12):2055–9. 20. Chen WC, Tsai MH, Wan L, Tsai CH, Tsai FJ. CYP17 and tumor necrosis factor-alpha gene polymorphisms are associated with risk of oral cancer in Chinese patients in Taiwan. Acta Otolaryngol 2005;125(1):96–9. 21. Liu CJ, Wong YK, Chang KW, Chang HC, Liu HF, Lee YJ. Tumor necrosis factor-alpha promoter polymorphism is associated with susceptibility to oral squamous cell carcinoma. J Oral Pathol Med 2005;34(10):608–12. 22. Gupta R, Sharma SC, Das SN. Association of TNF-alpha and TNFR1 promoters and 3’ UTR region of TNFR2 gene polymorphisms with genetic susceptibility to tobaccorelated oral carcinoma in Asian Indians. Oral Oncol 2008;44(5):455–63. 23. Tsai KY, Su CC, Lin YY, Chung JA, Lian IB. Quantification of betel quid chewing and cigarette smoking in oral cancer patients. Community Dent Oral Epidemiol 2009;37(6):555–61. 24. Lee SS, Yang SF, Ho YC, Tsai CH, Chang YC. The upregulation of metallothionein-1 expression in areca quid chewing-associated oral squamous cell carcinomas. Oral Oncol 2008;44(2):180–6.
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journal homepage: http://www.elsevier.com/locate/aob
Interaction between tumour necrosis factor-a gene polymorphisms and substance use on risk of betel quid-related oral and pharyngeal squamous cell carcinoma in Taiwan Cheng-Mei Yang a,b,1, Yu-Yi Hou c,d,1, Yi-Ten Chiu e,f, Hung-Chih Chen a, Sau-Tung Chu c, Chao-Chuan Chi c, Michael Hsiao e,g, Chien-Yiing Lee h, Christina Jen-Chia Hsieh e, Yu-Chen Lin i, Yao-Dung Hsieh a,j, Luo-Ping Ger e,f,* a
Department of Dentistry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan Department of Dental Laboratory Technology, Shu Zen College of Medicine & Management, Kaohsiung, Taiwan c Department of Otorhinolaryncology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan d Department of Nursing, Yuh-Ing Junior College of Health Care & Management, Kaohsiung, Taiwan e Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan f Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung, Taiwan g Genomics Research Center, Academia Sinica, Taipei, Taiwan h Department of Dentistry, Zuoying Armed Forces General Hospital, Kaohsiung, Taiwan i Department of Life Science, Fu Jen University, Taipei, Taiwan j Graduate School of Dental Science, National Defense Medical Center, Taipei, Taiwan b
article info
abstract
Article history:
Objective: Betel quid (BQ) components induce the secretion of tumour necrosis factor-alpha
Accepted 18 March 2011
(TNF-a) in oral keratinocytes, which promotes oral mucosal inflammation and oral cancer.
Keywords:
and 238G>A) with the risk and prognosis of BQ-related oral and pharyngeal squamous cell
This study was carried out to evaluate the association of TNFA genetic variants (308G>A Oral and pharyngeal cancer
carcinoma (OPSCC).
Single nucleotide polymorphisms
Design: A total of 403 subjects (205 cancer cases and 198 healthy controls) who habitually
Betel-quid
chewed BQ were recruited. The genotypes were determined by TaqMan real-time assays.
Tumour necrosis factor
Results: G allele and G/G genotype at TNFA 308 were associated with a 1.95-fold (95%CI:
Interaction
1.16–3.28, pcorrected = 0.024) and 2.28-fold (95%CI: 1.30–4.00, pcorrected = 0.008) increased risk of cancer as compared to those with A allele or A/A + A/G genotypes, respectively. In addition, G allele ( p = 0.080) and G/G genotype ( p = 0.076) at TNFA 238 were associated with a borderline but statistically significant increased risk of OPSCC. The combined G/G + G/G genotype at both loci had a 2.37-fold increased risk of OPSCC as compared to those with other combined genotypes (95%CI: 1.41–4.00, p = 0.001). Interactions between combined genotypes and smoking status were also found to contribute to risk of BQ-related OPSCC. There was no association of TNFA genotypes with clinicopathologic findings or the survival of OPSCC patients.
* Corresponding author at: Department of Medical Education and Research, Kaohsiung Veterans General Hospital, 386 Ta-Chung 1st Rd., Kaohsiung, Taiwan. Tel.: +886 7 346 8356; fax: +886 7 346 8056. E-mail addresses: [email protected], [email protected] (L.-P. Ger). 1 The first two authors contributed equally to this work. 0003–9969/$ – see front matter . Crown Copyright # 2011 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.archoralbio.2011.03.009
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Conclusions: BQ-chewers who carry the G allele or G/G genotype in TNFA 308 may have an increased risk of OPSCC. The intensity of cigarette smoking modulates the effect of the combined TNFA genotypes on risk of BQ-related OPSCC. Crown Copyright # 2011 Published by Elsevier Ltd. All rights reserved.
1.
Introduction
Oral and pharyngeal cancer is one of the most prevalent cancers, currently listed as the 6th leading cancer worldwide, and is particularly common in southeastern Asia.1 In Taiwan, oral and pharyngeal cancer is the fourth leading cancer in men, the top cancer in young male adults (25–44 yrs old). It is also the 6th leading cause of cancer deaths in males. Squamous cell carcinoma (SCC) accounts for more than 90% of all oral and pharyngeal cancers.3 Betel quid (BQ) chewing has been ranked as a Group I carcinogen by the International Agency of Research on Cancer (IARC) and may play an etiological role in the development of oral and pharygeal SCC (OPSCC).4–6 In Taiwan, approximately 90% of OPSCC patients chew betel quids regularly; the risk of developing OPSCC from chewing betel quids is higher than that from smoking or excessive alcohol drinking.2,7 BQ components have been shown to induce the secretion of tumour necrosis factor-alpha (TNF-a) in oral keratinocytes,6,8 which may provoke oral mucosal inflammation9 and oral cancer.6 TNF-a is a pleiotropic cytokine that plays an important role in inflammation, cancer, and apoptosis.10 Preclinical and clinical studies have shown the therapeutic anti-tumour effects of TNF-a in tumours,11 but there is increasing evidence that it may also promote the development and spread of cancer.12,13 TNFA is located on chromosome 6p21.231 in the polymorphic region of MHC III, and its promoter polymorphisms have been intensively studied as a potential determinant of disease susceptibility. Commonly described variants of TNFA polymorphisms consist of G to A transitions in the promoter region at positions 238 and 308.14 Recent studies have shown that TNFA promoter at 308 has direct effects on TNFA gene regulation.15,16 A significant association between the TNFA 308 G/A polymorphism and higher levels of expression of TNF-a has been found.17 TNFA 238 is a putative repressor site located in a 25 bp stretch of TNFA promoter.18 The association of single nucleotide polymorphisms (SNPs) of the TNFA gene with OPSCC has been inconclusive and controversial.3,19–22 TNFA gene polymorphisms have been reported in patients with tobacco-related OPSCC,22 but not in BQ-related OPSCC. In Taiwanese BQ chewers, 70% were also alcohol drinkers and more than 90% were smokers.23 Studies have indicated that BQ chewing and smoking may synergistically contribute to the development of OPSCC.7,23,24 The interactive effects between TNFA genetic polymorphisms and substance use; such as BQ chewing, smoking, and alcohol drinking; on risk of oral cancer remains uncertain. Therefore, the present study was undertaken to investigate the relationship between TNFA genetic variants and susceptibility to BQ-related OPSCC. The effect of interactions between TNFA genetic variants and substance use on the risk of BQ-related OPSCC was also evaluated. In
addition, the association of TNFA genotypes with clinicopathologic features and survival of OPSCC patients was also determined.
2.
Materials and methods
2.1.
Study subjects
In this study, 403 male subjects who habitually chewed BQ were recruited: 205 OPSCC case patients and 198 healthy controls. Case patients with newly diagnosed, previously untreated, and pathologically confirmed primary OPSCC (of the oral cavity, oropharynx, and hypopharynx) were recruited between January 2004 and November 2007 from the Department of ENT and Dentistry at Kaohsiung Veterans General Hospital (KSVGH). Case patients with complete follow up (195, 95.12%) and annual reviews of medical records entered the survival analysis. The 198 healthy controls were recruited from the oral health screen clinic at the Department of Otolaryngology, KSVGH and from the oral health screen campaigns for vehicle drivers, cleaners, and hardware workers held by the Kaohsiung city government or Department of Otolaryngology, KSVGH between 2004 and 2007. The selection criteria for controls included the absence of history of cancer and oral precancerous lesions, and negative screening for oral precancerous lesions. Controls were frequency-matched to case patients on age (5 years), ethnicity, and years of BQ chewing. After signing an informed consent, each subject was interviewed using a structured questionnaire that elicited detailed information on the history of betel quid chewing, cigarette smoking, alcohol drinking habits, and the general demographic data. At the end of the interview, each subject donated 7–15 ml of blood in an EDTA tube according to the protocol that had been approved by the Institutional Review Board of KSVGH. A BQ chewer was defined as a person who had chewed at least one betel quid per day for one year or more. Pack-years of BQ consumption were calculated using the following: packyears = (mean number of betel quids chewed per day/20 betel quids) number of years chewed. Light and heavy BQ chewers were categorized by using the median values of BQ consumption (pack-years) in controls as the cutoff. A smoker was defined as a person who had smoked at least one cigarette per day for one year or more. Pack-years of cigarette consumption were calculated using the following: pack-years = (mean number of cigarettes smoked per day/20 cigarettes) number number of years smoked. Light and heavy smokers were categorized by using the median value of cigarette consumption (pack-years) in controls as the cutoff. A drinker was defined as a person who had drunk at least once a week for more than one year. Gram-years of alcohol consumption were
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calculated using the following: gram-years = mean gram of alcohol drank per day number of years drank. Light and heavy drinkers were also categorized by using the median value of alcohol consumption (gram-years) in controls as the cutoff. The survival time was estimated from the time of operation or biopsy to November 2010. Overall survival (OS) was calculated from the date of initial resection of the primary tumour to the date of death from any cause or last follow-up. Disease-specific survival was measured from the time of initial resection of the primary tumour to the date of cancerspecific death or last follow-up. Disease-free survival was calculated from the date of initial resection of the primary tumour to date of recurrence or last follow-up. Pathological TNM classification was determined at the time of the initial resection of the tumour in accordance with the guidelines of the 2002 American Joint Committee on Cancer (AJCC) system.
2.2.
SNP genotyping
Genomic DNA for genotyping was extracted and purified from whole-blood samples with QIAamp1 DNA midi kit according to the manufacturer’s instructions (Qiagen Sciences1, Germantown, MD, USA). The detection of genotypes of TNFA 238 G>A and TNFA 308 G>A was performed by the TaqMan realtime PCR method, and then analysed by ABI PRISM 7500
Sequence Detection System (Applied Biosystems, Foster City, CA) in 96-well format. The SNPs of TNFA 238 G>A and TNFA 308 G>A were assayed by use of TaqMan real-time polymerase chain reaction (PCR) (Applied Biosystems, Foster City, CA, USA). PCR reactions were carried out in a reaction mixes containing 10 ng DNA, 5 ml 2 TaqMan Universal PCR Master Mix (Applied Biosystems), 0.5 ml 20 Primer/Probe mixture, and ddH2O to a final volume of 10 ml. The PCR program was as follows: 95 8C for 10 min, followed by 40 cycles of 15 s at 92 8C, and 1 min at 60 8C. A single no-DNA-template control in each 96-well format was used for quality control. The allelic-specific fluorescence data from each plate were analysed using the SDS v1.3.1 software (Applied Biosystems, 2005) to determine the genotype of each sample. The quality control procedures were implemented to ensure high genotyping accuracy in our laboratory. A senior researcher independently reviewed all of the absolute quantification curves for fluorescence data in TaqMan assays. Finally, 100% of the samples of the less prevalent genotypes and 10% of the samples of the more prevalent genotypes were randomly selected and run in duplicate to ensure accuracy of genotyping.
2.3.
Statistical analysis
For each tested polymorphism, departure from Hardy– Weinberg equilibrium in controls was evaluated by x2 test
Table 1 – Distribution and odds ratios of demographic and substance use for OPSCC. Factor/category Age (mean SD) <40 40–49 50–59 60
OPSCC cases (n = 205)
BQ controls (n = 198)
Number (%)
Number (%)
49.27 7.97 24 (11.7) 78 (38.0) 88 (42.9) 15 (7.3)
48.92 8.23 26 (13.1) 75 (37.9) 81 (40.9) 16 (8.1)
CORa (95%CI)
p-Valueb 0.670c
1.00 1.13 (0.60–2.13) 1.18 (0.63–2.21) 1.02 (0.41–2.49)
0.714 0.613 0.973
(78.3) (7.1) (12.1) (2.5)
1.00 0.92 (0.42–1.99) 0.69 (0.36–1.32) 0.73 (0.19–2.78)
0.826 0.258 0.649
Ethnicity Fukienese Hakka Mainlander Aborigines
169 14 18 4
Years of education 6 7–12 >12
70 (34.1) 116 (56.6) 19 (9.3)
63 (31.8) 120 (60.6) 15 (7.6)
1.00 0.87 (0.57–1.33) 1.14 (0.53–2.43)
0.521 0.735
BQ chewing (packd-years) Light (>18.5) Heavy (>18.5)
92 (44.9) 113 (55.1)
99 (50.0) 99 (50.0)
1.00 1.23 (0.83–1.82)
0.303
Smoking (packe-years) Never-smoker Light (1–29.9) Heavy (>29.9)
21 (10.2) 102 (49.8) 82 (40.0)
12 (6.1) 94 (47.5) 92 (46.5)
1.00 0.62 (0.29–1.33) 0.51 (0.24–1.10)
0.219 0.086
Drinking (gram-years) Never-drinker Light (1–1276.8) Heavy (>1276.8)
44 (21.5) 84 (41.0) 77 (37.6)
77 (38.9) 60 (30.3) 61 (30.8)
1.00 2.45 (1.49–4.03) 2.21 (1.34–3.64)
<0.001 0.002
a b c d e
(82.4) (6.8) (8.8) (2.0)
COR, crude odds ratios. p-Value is estimated by logistic regression. p-Value is estimated by t-test. Twenty betel quids per pack. Twenty cigarettes per pack.
155 14 24 5
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with 1 df. Measures of pairwise LD between polymorphisms within the same gene were carried out with HaploView software (http://www.broad.mit.edu/personal/jcbarret/haploview/). Univariate analysis was first performed to calculate the crude odds ratios and their 95% confidence intervals (CI) of selected demographic and risk factors, as well as genetic polymorphisms amongst cases and controls by logistic regression. Multiple logistic regression was used to evaluate the association of allelic types and genotypes of polymorphisms in TNFA with OPSCC risk by adjusting various confounders, such as age, ethnicity, education, the pack-years of BQ chewing and cigarette smoking, as well as the gram-years of alcohol drinking. In addition, false discovery rate (FDR) was applied for p-value correction for multiple comparisons of all allelic or genotypic types.25 Chisquare test was used to evaluate the correlation between each genotype and clinicopathologic parameter. The cumulative survival curves were estimated using the Kaplan– Meier method and comparison of the survival curves between different genotypes was performed by the logrank test. A Cox proportional hazards model was also used to assess the prognostic value of TNFA genotypes together with other clinicopathologic covariates. All statistical analysis was performed using the SPSS software package (version 12.0, SPSS Inc., Chicago, IL). The results of p < 0.05 were considered statistically significant.
3.
Results
3.1. Demographic and substance use features of the subjects The demographic data of the 403 recruited subjects are shown in Table 1. There was no difference in the mean age between the 205 OPSCC patients (49.27 7.97, range: 32–72 years) and the 198 controls (48.92 8.23, range: 28–75 years, p = 0.670). The cut-off was set at 18.5 pack-years (twenty nuts per pack) for BQ chewers, 29.9 pack-years (twenty cigarettes per pack) for smokers, and 1276.8 gram-years for drinkers. Most BQ chewers (89.8% in cases and 94% in controls) also had a habit of cigarette smoking. The distribution of ethnicity, years of education, BQ chewing, as well as smoking was similar between the two groups. Alcohol drinking was associated with a significantly increased risk for OPSCC in both light and heavy drinkers (COR = 2.45, 95%CI: 1.49–4.03, p < 0.001; COR = 2.21, 95%CI: 1.34–3.64, p = 0.002, respectively).
3.2.
Polymorphisms associated with BQ-related OPSCC
The genotype distributions of 308G>A and 238G>A were in Hardy–Weinberg equilibrium for controls (p values being 0.086 and 0.688, respectively). Amongst these two SNPs (308 and
Table 2 – Association of the genotypes and allelic types with OPSCC risk.
Genotypes
OPSCC cases (n = 205) Number (%)
BQ controls (n = 198) Number (%)
OPSCC cases VS. BQ controls
OR (95% CI)
Crude p-value
Pcorrected
Adjusted ORa (95% CI) p-valuea
Pcorrected
TNFA-308G>A
A G A/A G/A G/G
27 (6.6)
43 (10.9)
1.00
383 (93.4)
353 (89.1)
1.72 (1.05-2.86)
2 (1.0)
0 (0.0)
23 (11.2)
43 (21.7)
180 (87.8)
155 (78.3)
1.00 0.033
0.066
1.00 2.00 (1.17-3.42)
1.95 (1.16-3.28)
0.012
0.024
0.004
0.008
0.080
0.080
0.076
0.076
1.00 0.012
0.024
2.28 (1.30-4.00)
0.123
0.123
2.63 (0.89-7.78)
TNFA-238G>A
A G A/A G/A G/G
5 (1.2)
11 (2.8)
1.00
405 (98.8)
385 (97.2)
2.31 (0.80-6.72)
0 (0)
0 (0)
5 (2.4)
11 (5.6)
200 (97.6)
187 (94.4)
1.00
1.00 2.35 (0.80-6.90)
1.00 0.119
0.119
2.71 (0.90-8.12)
Combined genotypes of TNFA –308G>A and -238G>A
G/A+G/A A/A+G/A G/G+G/G a
30 (14.6)
52 (26.3)
1.00
175 (85.4)
146 (73.7)
2.08(1.26-3.53)
p-value are adjusted for age (40-49, 50-59,
of betel quid chewing ( > 18.5 vs.
1.00 0.004
2.37 (1.41-4.00)
60 vs. < 40), ethnicity (Hakka, Mainlander vs. Fukienese), education (7-12, > 12 vs.
0.001
6), the pack-years
18.5), smoking (1-29.9, > 29.9 VS. never-smoking) and the gram-years of drinking (1-1276.8, > 1276.8 VS. never-
drinker) by multiple logistic regression
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0.494
11/31 14/18
4/19 26/33
Cigarette smoking Light Heavy
Alcohol drinking Never drinking Drinking
f
CS: case (OPSCC); CN: control (BQ control). b Others include diplotype of 308G/A and 238GA and diplotype of 308A/A and 238G/A. c G/G + G/G: TNFA 308GG genotype and 238GG genotype. d p-Value are adjusted for age (40–49, 50–59, 60 vs. <40), ethnicity (Hakka, Mainlander vs. Fukienese), education (7–12, >12 vs. 6), the pack-years of betel quid chewing (>18.5 vs. 218.5) and smoking (>29.9 vs. 29.9) and the gram-years of drinking (1–1276.8, >1276.8 vs. never-drinker) by multiple logistic regression. e BQ chewing light is 18.5 pack-years and heavy is <18.5 pack-years. f Cigarette smoke light is 29.9 pack-years and heavy is >29.9 pack-years.
40/58 135/88
91/63 68/74
82/75 93/71
G/G + G/G
Others
10/24 20/28 BQ chewinge Light Heavy
a
0.054 0.024 3.50 (0.98–12.53) 2.17 (1.19–3.96) 1.00 1.00 3.28 (1.04–10.36) 1.95 (1.09–3.48) 1.00 1.00
0.043 0.024
0.043 0.048
0.054 0.012
0.017 <0.001 0.499 4.65 (2.07–10.44) 1.33 (0.58–3.07) 1.00 1.00 4.07 (1.91–8.70) 1.18 (0.55–2.56) 1.00 1.00
<0.001 0.672
<0.001 0.672
<0.001 0.499
0.016 0.084 0.008 0.084 3.32 (1.38–8.01) 1.83 (0.92–3.62) 1.00 1.00 2.62 (1.18–5.85) 1.83 (0.96–3.52) 1.00 1.00
0.018 0.068
0.036 0.068
p-valued G/G + G/G Others pcorrected p-value G/G + G/G Others
Adjusted OR (95%CI) CS/CN
TNFA 308G>A combined with 238G>A
Crude OR (95%CI)
c b
a
Table 3 – Odds ratios for OPSCC according to the combined genotypes of TNFA G S308A and TNFA GS238A and substance use.
pcorrected
0.327
P for interaction
archives of oral biology 56 (2011) 1162–1169
238), only the 308 locus showed significant association with OPSCC (Table 2). The G allele at TNFA 308 was significantly associated with increased risk of OPSCC (AOR = 1.95, 95%CI: 1.16–3.28, p = 0.012), even after FDR correction ( p = 0.024). Using A/A and G/A as the reference group, homozygous G/G at TNFA 308 conferred a significant 2.28-fold increased risk for OPSCC (95%CI: 1.30–4.00, p = 0.004), even after FDR correction ( p = 0.008). Although no significant difference was found in allelic and genotypic frequencies between patients and controls at locus 238, a borderline significant increased risk was found for those with the G allele and GG genotype after adjustment of confounders in the logistic regression model (AOR = 2.63, 95%CI: 0.89–7.78, p = 0.080 and AOR = 2.71, 95%CI: 0.90–8.12, p = 0.076, respectively) and after FDR correction ( p = 0.080 and 0.076, respectively). Linkage disequilibrium was not found between SNPs at locus 308 and locus 238 (r2 = 0.001, D0 = 0.636), therefore, haplotype analysis was not performed. In this study, we analysed possible combinations of genotypes formed by 308 G>A and 238 G>A. Carriers with the combined genotype of G/G + G/G at locus 308 and 238 had a 2.37-fold increased risk of OPSCC compared to those with other combined genotypes (AOR = 2.37; 95%CI: 1.41–4.00, p = 0.001).
3.3. Interactions between substance use and the combined genotype of S308 and S238 SNPs Risks associated with the combined genotype significantly differed depending on the intensity of cigarette smoking. Such interactions were not found for the intensity of BQ chewing or alcohol drinking (shown in Table 3). The G/G + G/G genotype was correlated with a greater risk of BQ-related OPSCC in the stratum of light smokers (29.9 pack-year; 95%CI: 2.07–10.44, p < 0.001). However, in the stratum of heavy smokers, no significant association was found between the various combined genotypes and risk of BQ-related OPSCC (95%CI: 0.58–3.07, p = 0.499). Therefore, the influence of G/G + G/G genotype on risk of OPSCC appeared to be greater in light smokers (AOR = 4.65) than that in heavy smokers (AOR = 1.33; pinteraction = 0.017). These results might suggest that the intensity of cigarette smoking modulates the effect of the combined TNFA genotypes on BQ-related OPSCC risk.
3.4. Association of TNFA genotypes with clinicopathologic features and survival of OPSCC patients The clinicopathologic characteristics of the BQ-related OPSCC patients are summarized in Table 4. There was no correlation between genetic variants in TNFA (308 and 238) and clinicopathologic findings, such as age of disease onset, cell differentiation, AJCC pathological stage, T classification, N classification, recurrence status, and metastasis status at diagnosis (shown in Table 4). With a median follow-up of 44.97 (range 1.37–82.97) months, the overall survival rate was 50.38 3.80% at 5 years. The disease-specific survival rate was 51.46 3.83% at 5 years. The disease-free survival rate remained constant at 57.57 3.88% 4 years from the time of initial resection. In addition, the median overall survival time was 5.96 years and the median disease-specific survival time was 6.04 years. There was no any associations between genetic
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Table 4 – The TNF A genotypes in relation to clinicopathologic features in BQ-related OPSCC patients. Variables
TNFA 308G>A
TNFA 238G>A
G/G (n = 172)
G/A + A/A (n = 23)
Number (%)
Number (%)
91 (52.9) 81 (47.1)
9 (39.1) 14 (60.9)
x2 = 1.541
Cell differentiation Well Moderate + Poor
34 (19.8) 138 (80.2)
3 (13.0) 20 (87.0)
Pathological stage I + II III + IV
90 (52.3) 82 (47.7)
T classification T1 + T2 T3 + T4
G/G (n = 190)
G/A + A/A (n = 5)
Number (%)
Number (%)
0.214
99 (52.1) 91 (47.9)
x2 = 0.597
0.578a
12 (52.2) 11 (47.8)
x2 < 0.001
125 (72.7) 47 (27.3)
16 (69.6) 7 (30.4)
N classification N0 N1 + N2
115 (66.9) 57 (33.1)
Recurrence status No Yes Metastasis status No Yes
Age (years) <50 50
a
Statistic
Statistic
p-Value
1 (20.0) 4 (80.0)
x2 = 2.010
0.202a
35 (18.4) 155 (81.6)
2 (40.0) 3 (60.0)
x2 = 1.476
0.241a
0.989
100 (52.6) 90 (47.4)
2 (40.0) 3 (60.0)
x2 = 0.312
0.671a
x2 = 0.098
0.754
138 (72.6) 52 (27.4)
3 (60.0) 2 (40.0)
x2 = 0.388
0.618a
15 (65.2) 8 (34.8)
x2 = 0.025
0.875
127 (66.8) 63 (33.2)
3 (60.0) 2 (40.0)
x2 = 0.103
1.000a
107 (62.2) 65 (37.8)
13 (56.5) 10 (43.5)
x2 = 0.277
0.598
115 (60.5) 75 (39.5)
5 (100.0) 0 (0.0)
x2 = 3.207
0.159a
151 (87.8) 21 (12.2)
20 (87.0) 3 (13.0)
x2 = 0.013
1.000a
167 (87.9) 23 (12.1)
4 (80.0) 1 (20.0)
x2 = 0.281
0.485a
Two-tailed Fisher’s exact test.
variants in TNFA (308 and 238) and disease-specific survival and disease-free survival (data not shown).
4.
p-Value
Discussion
Our study showed that G allele and G/G genotype at TNFA 308 and 238 were significantly associated with an increased risk of BQ-related OPSCC, although the significance found for 238 was only marginal. The combined genotype of G/G + G/G at locus 308 and 238 was associated with an increased risk of OPSCC. Risks associated with this combined genotype differed significantly depending on the intensity of cigarette smoking; however, such associations were not detected for the intensity of BQ chewing or alcohol drinking. These findings suggest that TNFA gene may play a role in the development of BQ-related OPSCC. However, genetic variants of TNFA were not correlated with clinicopathologic features and survival of BQ-related OPSCC patients. To the best of our knowledge, this is the first study to investigate the role of TNFA genetic variants and the interactions between TNFA gene and substance use in the development of OPSCC amongst the Taiwanese BQ-chewing population. The TNFA 238A allele is known to cause a significant decrease in the transcription of the TNFA gene in human blood cells.14,26 No significant association was observed at the 238 SNP with tobacco-related oral carcinoma in Asian Indians.22 For Taiwanese people, Liu et al. reported that the 238 G/G genotype was significantly associated with the increased risk of Oral SCC as compared with the G/A genotype (OR = 3.85, p = 0.02).21 We also observed that the TNFA 238G allele and G/
G genotype had a similarly increased risk of BQ-related OPSCC as compared with A allele and G/A genotype (for G allele: AOR = 2.63, p = 0.080; for GG genotype: AOR = 2.71, p = 0.076, respectively), although only a marginal significance was found. Both findings suggest that excessive expression of TNF-a may be associated with OPSCC. However, the frequency of the 238A allele was rare in our study (1.2% for cases and 2.8% for controls), but was similar to the frequencies previously reported in Asian populations, as low as 1.0% for cases and 3.4% for controls in a Taiwanese study and 0% for both cases and controls in an Indian study.21,22 However, inconsistencies amongst these three studies due to small sample sizes (or rare allele), ethnic differences, or different substance-related (tobacco-related or BQ-related) oral cancers cannot be excluded. Therefore, validation studies with independent large cohorts are required. Our results showed that the G allele and G/G genotype at TNFA 308 were associated with increased risk of OPSCC, consistent with previous studies.19,21 Both Chiu et al. and Liu et al. suggest that the 308A allele confers a protective effect against cancer, possibly by increasing TNF-a production. Two in vitro studies demonstrated that the 308A allele is associated with transcription of TNF-a that is about 7 times more efficient than that associated with G allele.15,16 These findings are consistent with the anti-cancer properties of TNFa.11 TNF-a may induce apoptosis of tumour cells through binding to cell surface receptors, which leads to secondary signalling events and the activation of endonucleases and DNA fragmentation.27 TNF-a, especially high doses of TNF-a in soluble form, may promote tumour lysis by activating the antitumour T-cell response.11,28,29 In addition, an epidemiological
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study has shown that the 308G/G genotype is significantly associated with increased risk of oral submucosa fibrosis (OSF), a pre-cancerous lesion with a high malignant trasformation rate, possibly resulting from the decreased collagenase activity of TNF-a.19 Therefore, the 308 G/G genotype was associated with the risk of OSF and in turn BQ-related OPSCC. However, other studies did not reported such associations between the risk of OPSCC and the 308A allele.3,20,22,30 These contradictory results may indicate either differences in pathogenesis as a result of variation in substance use or ethnic stratification in each study. We found a synergistic relationship between the TNFA combined genotypes and smoking status that modified the risk of BQ-related OPSCC. The cellular origin of Oral SCC is the oral keratinocyte, and keratinocyte inflammation is crucial for the pathogenesis of cancer and tissue fibrosis.6 Cigarette smoking, alcohol drinking, and BQ chewing play important roles in the aetiology of OSF and OPSCC, and may act in synergy.7,24,31,32 It is possible that using these substances contributed to the pathogenesis of OPSCC through the suppression of the immune action by affecting the production of inflammatory cytokines such as TNF-a.6,33–37 Some studies reported that cigarette smoking suppresses the production of TNF-a, adversely affects the function of human NK cells and contributes to a higher incidence of cancer.36–38 In our study, the GG + GG genotype was associated with a significantly greater risk for BQ-related OPSCC for light smokers but not for heavy smokers. It is possible that the detrimental suppression of TNF-a as a result of light exposure to cigarette smoke can be overcome with the protective combined genotype (the combined genotype of 308G/A and 238GA as well as the genotype of 308A/A and 238G/A). However, the adverse effects of the suppression of TNF-a as a result of heavy exposure to cigarette smoke might be too great for the protective combined genotype to confer protection. Further experimental studies are necessary to evaluate the validity of this hypothesis. In this study, we reported that TNFA polymorphisms are associated with the development of OPSCC. TNF-a is primarily produced by activated macrophages, T lymphocytes, and natural killer (NK) cells. Its bioactivity is mainly regulated by soluble TNF-a-binding receptors.27 Previous studies have shown a correlation of high TNF-a concentrations with Oral SCC,12,39 but do not answer the question of whether high concentrations of TNF-a are simply a byproduct of oral cancer milieu, or whether TNF-a plays a more active role in the disease process. If we postulate that high concentrations of TNF-a might decrease the risk of OPSCC, then alleles producing lower concentrations, such as the 308G allele and 238A allele, might be considered risk factors for OPSCC. Further investigation is needed to clarify this issue. There are several limitations in this study. Firstly, this study was single-centred. Secondly, TNF-a serum concentration was not measured in healthy and cancer patients at different stages due to the retrospective nature of the study. TNF-a can be regulated by its receptors. Genetic alterations and the expression of TNF receptors have been shown to be related to the development of Oral SCC.22,39 Our findings on TNF-a polymorphisms might be insufficient to clarify the complex interplay amongst a number of different genes
controlling expression of cytokines in OPSCC. Therefore, replication studies on more cytokines and TNF receptors with independent large cohorts are suggested. In conclusion, our study suggests that BQ chewers in Taiwan who carry the G allele or G/G homozygotes in TNFA 308 may have an increased risk of developing BQ-related OPSCC. The contribution of interactions between the combined genotype (308 and 238) with substance use to the risk of BQ-related OPSCC was found only for smoking.
Acknowledgments We thank Yi-Cheng Lee and Ya-Hui Chiao for interview data collection and statistical analysis. We also express our appreciation to Dr. Susan Shin-Jung Lee for assistance in English editing. Funding: Segments of this research were supported by funding from the National Science Council NSC93-2320-B075B-005 (to Luo-Ping Ger), Kaohsiung Veterans General Hospital VGHKS96-091 (to Sau-Tung Chu), VGHKS-97-109 (to Yu-Yi Hou), VGHKS-99-078 (Yu-Yi Hou), and VGHKS-99-099 (to Luo-Ping Ger), and Zuoying Armed Forces Hospital ZAFH9810 (to Chien-Yiing Lee). Competing interests: None declared. Ethical approval: Judgement’s reference number is VGHKS97-CT3-17.
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