Head and neck squamous cell carcinoma (HNSCC) is a common malignancy that ranks sixth in incidence of all cancers. The HNSCC tumors display dysregulation of cell differentiation, cell cycle control, epithelial and stromal interactions, apoptosis, angiogenesis and their associated pathways [1,2]. Although its exact cause remains unclear, like most malignancies, HNSCC pathogenesis is affected by both genetic and environmental factors [1].
Of the approximately 500,000 new cases of HNSCC each year, many occur in the oral cavity, pharynx, and larynx. Oral squamous cell carcinoma (OSCC) is the most common type of HNSCC, and China has one of the highest incidences of this cancer [2]. Importantly, OSCC is nearly asymptomatic, which makes early diagnosis very difficult; to date, there are no accurate predictors of OSCC onset and/or progression. Therefore, identification of risk factors and high-risk populations for OSCC would enable advancements in the primary and secondary prevention of OSCC.
Cigarette smoking and alcohol consumption are known environmental risk factors for OSCC [3,4]. Cigarette smoke contains polycyclic aromatic hydrocarbons, heterocyclic amines, and nitrosamines that are all carcinogenic. Long-term alcohol consumption can lead to combined overdose of reactive oxygen species (ROS) and acetaldehyde, inducing carcinogenesis. Certain enzymes have been shown to be responsible for the biotransformation of chemical carcinogens, either for activation or excretion. For example, cytochrome P4501A1, encoded by CYP1A1, is a catabolite-activating enzyme involved in the biotransformation of both tobacco and alcohol. P4501A1-mediated metabolism of tobacco combustion products, mainly polycyclic aromatic hydrocarbons, can lead to the formation of DNA adducts that contribute to tumor formation, specifically HNSCC [5]. Other metabolizing enzymes, with variations in their respective genes, have also been previously implicated in cancer susceptibility. These include, but are not limited to, glutathione S-transferase (GST), superoxide dismutate (SOD), proteins of the SOD family, and acetaldehyde dehydrogenase (ALDH). Glutathione S-transferase plays a role in metabolizing benzo[a]pyrene (a tobacco-specific carcinogen), as well as other carcinogenic compounds. Superoxide dismutase, an endogenous antioxidant enzyme, has certain polymorphisms implicated in cancer susceptibility. Acetaldehyde dehydrogenase, along with alcohol dehydrogenase (ADH), metabolizes ethanol by breaking apart the molecule in order to eliminate it from the body. Genetic polymorphism in ALDH2 has been previously investigated and shown to be associated with specific cancer types [5]. However, genes encoding these enzymes have multiple functional variants, blurring their role in OSCC susceptibility. At least one recent study found that expression of CYP1A1 and ALDH2 proteins did not affect OSCC prognosis [6]. Thus, the specific contribution of polymorphisms in genes encoding enzymes involved in biotransformation of alcohol and tobacco components remains unclear; specifically, the role in promoting OSCC requires further study. This study reports the investigation of the association between genetic polymorphism of
This prospective study included 750 patients who were admitted to our hospital from June 2011 to May 2015. Another 750 participants who received physical examinations during the same time period were selected as healthy controls; the physical examination showed no cancer or hereditary diseases. There was no statistically significant difference in age, gender, place of origin or nationality, and the subjects were unrelated. Participant demographic data, smoking history, alcohol drinking history, occupational history and family tumor history were collected. The smoking status was evaluated using the smoking index (SI) that was the product of the daily number of cigarettes multiplied by number of years of smoking. Based on SI values, the participants were divided into the following categories: non smokers, individuals with SI ≤400, and individuals with SI 400. Alcohol consumption was evaluated with the drinking index (DI) that was the product of the daily amount of drinking (in grams) multiplied by the number of years of drinking. Based on DI values, the participants were classified as non drinkers, those with DI ≤3000, and those with DI 3000. The study was approved by the General Hospital of Daqing Oil Field, Daqing, Heilongjiang Province, People’s Republic of China (PRC). Informed written consent was obtained from all participants.
From each participant, 3 mL blood was collected in vacutainers with EDTA as anticoagulant. The QIAmpDNA extraction kit (Qiagen GmbH, Hilden, Germany) was used to extract DNA from white blood cells. Extracted DNA was stored at –30 °C. Polymerase chain reaction (PCR) was used to amplify the DNA to the levels required for restriction fragment length polymorphism (RFLP) analysis. For all reactions, a total volume of 25 μL comprised 2.5 μL 10 × buffer, 2.5 μL dNTP, 20 pmol upstream primers, 20 pmol downstream primers (see below), 0.75 μL Taq DNA polymerase (all PCR reagents from Promega, Madison, WI, USA), and 100 ng template DNA. Reactions were performed on PE480 thermocycler (Perkin Elmer?, Norwalk, CT, USA), as follows: initial denaturation at 94 °C for 4 min., and 35 cycles of denaturation at 94 °C for 40 seconds, annealing at 55 °C for 40 seconds, and extension at 72 °C for 50 seconds, and final extension at 72 °C for 5 min. The PCR products were digested with restriction endonucleases as appropriate (described below). A total reaction volume of 20 μL comprised 1 ng PCR product, 2 μL 10 × NEB (New England Biolabs, Ipswich, MA, USA) reaction buffer, and 10 U endonuclease; reactions were performed at 37 °C for 3 hours. Digestion products were separated by 100V electrophoresis on a 3.0% agarose gel, for 1 hour. After 30 min. in ethidium bromide, bands were detected by ultraviolet light.
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The difference in genotype distributions between the patient and control groups was determined using the χ2 test. A non conditional logistic regression model was used to analyze the adjusted odds ratio (OR) for risk of oral squamous cell carcinoma with different genotypes, as well as the combined effects between smoking, drinking, and genotype. The 95% confidence interval (CI) is also reported. The Statistical Package for the Social Sciences (SPSS Inc., Chicago, IL, USA) version 11.0 was used for statistical analysis. Statistical significance was accepted at a
General demographic and clinical information for participants in both groups are provided in Table 1. There was no statistically significant difference in gender or age between case and control groups (
General characteristics of healthy controls and patients with oral squamous cell carcinoma. OR: odds ratio; 95% CI: 95% confidence interval; SD: standard deviation; SI: smoking index; DI: drinking index.Characteristics Control Group Patient Group OR Value 95% CI Sex males 498 (66.40%) 504 (67.20%) 0.97 0.78-1.20 >0.05 Age years; mean±SD 55.51±4.42 55.49±4.33 – – >0.05 Smoking status non-smoker 451 (60.13%) 265 (35.33%) 2.76 2.24-3.40 <0.01 Drinking status did not drink 468 (62.40%) 256 (34.13%) 3.20 2.59-3.96 <0.01
For each of the enzyme encoding genes we investigated, the distribution of genotypes, significantly differed between cases and controls (all
Distribution of OR: odds ratio; 95% CI: 95% confidence interval.Genotype Control Group Patient Group OR Value 95% CI % % 593 79.00 463 61.73 1.00 1.86-2.95 <0.01 605 80.67 380 50.67 1.00 3.23-5.12 <0.01 598 79.73 395 52.67 1.00 2.81-43.44 <0.01 419 55.87 231 30.80 1.00 1.95-4.47 <0.01 444 55.60 212 30.53 1.00 2.97-4.57 <0.01
Because there was a significant shift of the genotype frequencies observed in individuals with OSCC compared to controls, we also examined whether OSCC patients were more likely to carry multiple variant genotypes than healthy subjects. The combined distribution of
The combined distribution of OR: odds ratio; 95% CI: 95% confidence interval.Number of Control Group Patient Group OR Value 95% CI % % 0 97 12.93 8 1.07 1.00 – <0.01 1 290 38.67 64 8.53 2.68 1.23-5.78 – 2 210 28.00 230 30.67 13.28 6.31-27.97 – 3 90 12.00 278 37.07 37.45 17.53-80.02 – 4 56 7.47 156 20.80 33.78 15.44-73.90 – 5 7 0.93 14 1.86 24.25 7.61-77.27 –
Table 4 depicts the results of the analysis of
Combined analysis of smoking status, and variant genotype distribution in relation to oral squamous cell carcinoma susceptibility. OR: odds ratio; 95% CI: 95% confidence interval.Number of Smoking Control Group Patient Group OR Value 95% CI % % 0 [–] 92 12.27 31 4.13 1.00 – – 1 [–] 118 15.73 43 5.73 1.04 0.64-1.70 0.86 2 [–] 116 15.47 90 12.00 2.22 1.44-3.44 <0.01 3 [–] 71 9.47 53 7.07 2.14 1.31-3.50 <0.01 4 [–] 40 5.33 46 6.13 3.30 1.92-5.67 <0.01 5 [–] 14 1.87 2 0.27 0.41 0.09-1.87 0.25 0 [+] 37 4.93 14 1.87 0.89 0.43-1.86 0.76 1 [+] 100 13.33 92 12.27 2.52 1.61-3.96 <0.01 2 [+] 78 10.40 147 19.60 2.43 1.65-3.58 <0.01 3 [+] 35 4.67 128 17.07 4.90 2.92-8.21 <0.01 4 [+] 44 5.87 81 10.80 1.60 0.91-2.80 0.10 5 [+] 5 0.67 23 3.07 32.20 5.49-118-91 <0.01
Furthermore, within the sub-population of smokers, SI was synergistic with multiple variant genotypes (Table 5). In the patient group, the presence of multiple variant genotypes and an SI>400 was significantly more common compared to the control group (
Combined analysis of smoking index, and variant genotype distribution in relation to oral squamous cell carcinoma susceptibility. OR: odds ratio; 95% CI: 95% confidence interval.Number of Smoking Control Group Patient Group OR Value 95% CI % % 0 ≤400 45 6.00 2 0.27 1.00 – – 1 ≤400 54 7.20 16 2.13 0.22 0.05-1.00 0.07 2 ≤400 45 6.00 23 3.07 0.38 0.08-1.86 0.23 3 ≤400 33 4.40 44 5.87 1.00 1.00-0.21 1.00 4 ≤400 23 3.07 32 4.27 1.04 0.21-5.12 0.96 5 ≤400 2 0.27 3 0.40 1.12 0.11-11.60 0.92 0 400 3 0.40 4 0.53 1.82 0.51-2.85 0.49 1 400 45 6.00 24 3.20 1.80 0.85-3.80 0.12 2 400 28 3.73 123 16.40 8.60 4.50-16.44 <0.01 3 400 11 1.47 153 20.40 10.43 4.88-22.31 <0.01 4 400 9 1.20 57 7.60 4.55 1.88-11.02 <0.01 5 400 1 0.13 4 0.53 2.67 0.16-45.14 0.50
A similar analysis was applied to
Combined analysis of drinking status, and variant genotype distribution in relation to oral squamous cell carcinoma susceptibility. OR: odds ratio; 95% CI: 95% confidence interval.Number of Drinking Control Group Patient Group OR Value 95% CI % % 0 [–] 100 13.33 27 3.60 1.00 – – 1 [–] 166 22.13 42 5.60 0.41 0.21-0.80 0.01 2 [–] 105 14.00 77 10.27 1.18 0.61-2.28 0.62 3 [–] 51 6.80 65 8.67 2.05 1.03-4.11 0.04 4 [–] 43 5.73 43 5.73 1.61 0.78-3.32 0.20 5 [–] 3 0.40 2 0.27 1.07 0.16-7.06 0.94 0 [+] 29 3.87 18 2.40 0.44 0.21-0.90 0.03 1 [+] 52 6.93 93 12.40 7.07 4.38-11.42 <0.01 2 [+] 89 11.87 160 21.33 2.45 1.66-3.63 <0.01 3 [+] 55 7.33 116 15.47 1.66 1.02-2.69 0.04 4 [+] 41 5.47 84 11.20 2.05 1.67-3.60 0.01 5 [+] 16 2.13 23 3.07 2.16 0.32-14.41 0.43
The synergistic effect of the DI and combined expression of variant genotypes is depicted in Table 7. In the patient group, the presence of multiple variants and a DI >3000 was significantly more common compared to the control group (
Combined analysis of drinking index, and variant genotype distribution in relation to oral squamous cell carcinoma susceptibility. OR: odds ratio; 95% CI: 95% confidence interval.Number of Drinking Control Group Patient Group OR Value 95% CI % % 0 ≤3000 21 2.80 3 0.40 1.00 – – 1 ≤3000 47 6.27 15 2.00 0.80 0.01-077 0.03 2 ≤3000 49 6.53 26 3.47 0.13 0.01-1.25 0.08 3 ≤3000 36 4.80 38 5.07 0.26 0.03-2.47 3.79 4 ≤3000 16 2.13 28 3.73 0.44 0.05-4.26 0.48 5 ≤3000 3 0.40 4 0.53 0.33 0.02-4.74 0.42 0 3000 1 0.13 4 0.53 2.96 0.55-6.28 0.08 1 3000 24 3.20 44 5.87 5.74 2.67-12.35 <0.01 2 3000 39 5.20 122 16.27 5.90 3.27-10.71 <0.01 3 3000 30 4.00 138 18.40 4.36 2.38-7.97 <0.01 4 3000 14 1.87 54 7.20 2.20 0.94-5.16 0.07 5 3000 2 0.27 18 2.40 6.75 0.83-54.66 0.07
Table 8 displays the results of the analysis of the presence of variant genotypes combined with smoking and drinking status. In the patient group, there were significantly more patients who had multiple variants and were positive for both smoking and drinking history as compared to the control group.
Combined analysis of smoking and drinking status, and variant genotype distribution in relation to oral squamous cell carcinoma susceptibility. OR: odds ratio; 95% CI: 95% confidence interval.Number of Smoking Drinking Controls Patients OR 95% CI % % 0 [–] [–] 68 9.07 15 2.00 1.00 – – 1 [–] [–] 82 10.93 12 1.60 1.04 0.64-1.70 0.86 2 [–] [–] 48 6.40 42 5.60 2.22 1.44-3.44 <0.01 3 [–] [–] 27 3.60 21 2.80 2.14 1.31-3.50 <0.01 4 [–] [–] 18 2.40 18 2.40 3.30 1.91-5.67 <0.01 5 [–] [–] 1 0.13 1 0.13 0.41 0.09-1.87 0.25 0 [–] [+] 24 3.20 16 2.13 1.91 0.31-11.81 0.48 1 [–] [+] 36 4.80 31 4.13 7.07 4.38-11.42 <0.01 2 [–] [+] 68 9.07 48 6.40 2.45 1.66-3.63 <0.01 3 [–] [+] 44 5.87 32 4.27 1.66 1.02-2.69 0.04 4 [–] [+] 22 2.93 28 3.73 2.05 1.17-3.60 0.01 5 [–] [+] 13 1.73 1 0.13 2.16 0.32-14.40 0.43 0 [+] [–] 32 4.27 12 1.60 0.86 0.16-4.63 0.87 1 [+] [–] 84 11.20 30 4.00 2.53 1.51-3.96 <0.01 2 [+] [–] 57 7.60 35 4.67 2.43 1.65-3.58 <0.01 3 [+] [–] 24 3.20 44 5.87 4.90 2.92-8.21 <0.01 4 [+] [–] 25 3.33 25 3.33 1.60 0.91-2.80 0.10 5 [+] [–] 2 0.27 1 0.13 32.20 5.49-188.91 <0.01 0 [+] [+] 5 0.67 2 0.27 3.45 1.62-5.41 <0.01 1 [+] [+] 16 2.13 62 8.27 10.36 6.53-16.44 <0.01 2 [+] [+] 21 2.80 112 14.93 6.20 4.12-9.33 <0.01 3 [+] [+] 11 1.47 84 11.20 5.23 3.33-820 <0.01 4 [+] [+] 19 2.53 56 7.47 4.19 2.67-6.58 <0.01 5 [+] [+] 3 0.40 22 2.93 13.26 4.09-42.97 <0.01
The pathogenesis of OSCC is complex, involving combined action of a variety of environmental and genetic factors [11-13]. Smoking and drinking are the main risk factors for OSCC [14,15]. Our findings confirm that smoking and drinking were significantly more frequent in individuals with OSCC than in the control individuals. Heavy cigarette and alcohol consumption were also significantly higher in the OSCC group compared to the control group.
The CYP1A1 is a member of the cytochrome P450 family involved in the metabolism of exogenous materials, encoding aryl hydrocarbon hydrolase (AHH), and activating polycyclic aromatic hydrocarbon and aromatic amine [16]. Our results showed that the distribution of genotypes for
Superoxide dismutase is generally considered as the first line antioxidative defense in the body [17]. This enzyme can be highly effective against ROS to protect the cells and tissues from oxidative stress [18]. The SOD dysregulation is correlated with growth of human malignant tumors [19,20]. Further, EC-SOD appears to be important for tumor formation [21-23], and is correlated with OSCC [24]. Our study mirrored the earlier studies that indicated EC-SOD association with OSCC and showed a significant difference in distribution of EC-SOD genotypes between the patient and control groups [24].
The GST polymorphisms are also correlated with cancer susceptibility. Glutathione S-transferase can catalyze the binding of electrophilic carcinogens and glutathione, to metabolize compounds that are easily soluble in water and excrete them.
Animal studies have found that the
Interestingly, our study also found significant differences in the prevalence of combined
Further investigations and studies of the effects of these gene and environmental interactions is paramount to an earlier diagnosis of OSCC. More studies of non Asian populations is another avenue of research worth undertaking.