Abstract
Toll‐like receptors (TLR) play a pivotal role in sensing a wide range of pathogens, including bacteria, fungi and viruses. A dysregulation of TLR signaling may increase the risk of developing chronic inflammatory diseases and cancers. The aim of this study was to investigate the association of TLR2 R753Q,TLR4 D299G, and T399I polymorphisms with nasopharyngeal carcinoma (NPC) and to explore the effects of these polymorphisms on cytokine and chemokine expression in NPC biopsies. The genotypes of the three loci among 236 patients with NPC and 287 healthy controls were determined by PCR‐RFLP. Cytokines and chemokines mRNA and protein in NPC biopsies were measured by real‐time quantitative PCR and ELISA, respectively. Results showed that the combined CT/TT genotype of T399I was associated with increased NPC risk, with an odds ratio of 1.853 (95% confidence interval: 1.184–2.961). Also, individuals with the T allele of T399I showed a 1.842‐fold increase in NPC risk compared to those with the T399I C allele (95% confidence interval: 1.213–3.015). Messenger RNA levels of interleukin (IL)‐1α, tumor necrosis factor‐α and IL‐10 were significantly elevated in patients with T399I combined CT/TT genotype; IL‐1α and IL‐10 protein concentration significantly increased in NPC patients with T399I combined CT/TT genotype compared to those with the T399I CC genotype. Our data suggest that TLR4 T399I modify cytokines and chemokines patterns and play a role in the development of NPC. (Cancer Sci 2012; 103: 653–658)
A highly invasive and metastatic malignant tumor, NPC arises from the epithelial cells lining of the nasopharynx. It shows a distinct geographical distribution with the highest incidence in South‐East Asia; NPC is rare in Europe and North America.1 Microscopically, NPC are characterized by a heavy infiltration of nonmalignant lymphocytes. The etiology of NPC is poorly understood, although various lines of evidence suggest that infections with EBV, alcohol consumption, consumption of salted fish, and genetic susceptibility, such as chromosomal aberrations and SNP, may play a role in the development of NPC.2, 3, 4
Inflammatory processes are involved in cancer incidence and progression,5 and accumulating evidence implicates inflammation in NPC. Inflammatory cytokines and chemokines are associated with the risk of cancer; in particular, IL‐1, IL‐2, IL‐8, IL‐10, IL‐12 and TNF‐α have shown to be associated with a higher risk for NPC,6, 7, 8, 9 and increased blood levels of IL‐1 and IL‐12 have been demonstrated in NPC patients.7, 8
The TLR family of receptors plays a pivotal role in sensing a wide range of pathogens, including bacteria, fungi and viruses. These receptors have been evolutionarily conserved to recognize pathogen‐associated molecular patterns.10 Once TLR are initiated, the downstream transcription factors of TLR signaling, such as nuclear factor kappa‐light‐chain‐enhancer of activated B cells, are activated and promote pro‐inflammatory cytokines and chemokines production as well as innate, adaptive immune responses targeting invading pathogens. A dysregulation of TLR signaling may contribute to a higher risk of developing chronic inflammatory diseases and cancers.11, 12, 13 A total of 10 functional human TLR have been identified,14 with TLR4 and TLR2 being the principal receptors involved in recognizing bacterial cell wall components and capsid ligands from several viruses.14, 15
The ability to respond properly to TLR ligands may be impaired by SNP within the TLR family of genes, which results in an altered susceptibility to inflammatory diseases and cancers. Polymorphisms in TLR4 and TLR2 have already been studied. Recently, most studies have focused on two SNP of the human TLR4 gene: an A/G substitution at 896 bp and a C/T substitution at 1196 pb. The A/G substitution at 896 bp results in an aspartic acid to glycine replacement in amino acid sequence 299 (D299G, SNP ID: rs 4986790); the C/T substitution at 1196 pb results in a theronine to isoleucine exchange in amino acid sequence 399 (T399I, SNP ID: rs 4986791). In the TLR2 gene, the G/A substitution at 2258 pb results in an arginine to glutamine substitution in amino acid sequence 753 (R753Q, SNP ID: rs5743708). Toll‐like receptor 4 SNP may influence the expression of inflammatory cytokines and chemokines, such as IL‐6, IL‐8, TNF‐α, IL‐10, monocyte chemotactic protein 1 (MCP‐1) and human macrophage inflammatory protein‐1α (MIP‐1α), and are associated with susceptibility to gastric cancer and lymphoma,16, 17, 18 while TLR2 variants may influence susceptibility to marginal zone lymphoma.18
Gene polymorphisms in the TLR pathway could alter response to infection and downstream inflammatory effects, influencing disease susceptibility and progression. EBV plays a pivotal role in the development of NPC, but only a few people develop the disease in areas where NPC is endemic even though most individuals have been exposed to EBV infections, which suggests that genetic differences may contribute to NPC.
To further explore whether SNP in TLR2 and TLR4 influence NPC pathogenesis and whether these polymorphisms are associated with modified inflammatory cytokine and chemokine responses in NPC biopsies, we conducted an investigation of TLR4 and TLR2 gene polymorphisms in a case‐control study.
Materials and Methods
Study population
This case‐control study included 236 Chinese NPC patients and 287 healthy controls, who were previously described in detail.8 All subjects were unrelated ethnic Han Chinese recruited from Department of Otolaryngology, West China Hospital, Sichuan University (Chengdu, China) and the First Affiliated Hospital of Luzhou Medical College (Luzhou, China) between 2007 and 2009. All NPC cases were histologically confirmed by the local diagnosing pathologists. The histological types were classified as non‐keratinaizing carcinoma, squamous cell carcinoma, and undifferentiated carcinoma, according to World Health Organization criteria.19 As a control group, 287 healthy subjects were randomly selected from 8302 individuals who received an annual check‐up during the same period when the NPC subjects were recruited. The control subjects had no history of any diseases. There were no significant differences between the patients and control subjects in terms of gender, age, smoking status, alcohol consumption and area of residence (urban or rural). After providing written informed consent, each participant was scheduled for an interview, and a structured questionnaire was administered by interviewers to collect information. Those who had smoked less than one cigarette per day and smoked for <1 year total were defined as nonsmokers; all others were considered smokers. Individuals that consumed three or more alcoholic drinks a week for over 6 months were considered drinkers. Approximately 5‐mL peripheral blood anticoagulated with EDTA was collected from each participant. DNA was extracted from the blood samples using the salting‐out method and frozen at −20°C until tested.20 Approval for the study was given by the ethics committee of the Chinese Human Genome Project.
Genotypes
The SNP of the TLR4 gene, D299G and T399I, and the TLR2 gene, R753Q, were determined by PCR‐RFLP. The following PCR primers, designed based on descriptions from Rigoli et al. and Speletas et al.,21, 22 were used: 5′‐TTA GAA ATG AAG GAA ACT TGG AAA AG‐3′ and 5′‐TTT GTC AAA CAA TTA AAT AAG TGA TTA ATA‐3′for D299G; 5′‐GGT TGC TGT TCT CAA AGT GAT TTT GGG AGA A‐3′and 5′‐CCT GAA GAC TGG AGA GTG AGT TAA ATG CT‐3′ for T399I; and 5′‐TAT GGT CCA GGA GCT GGA GA‐3′ and 5′‐TGA CAT AAA GAT CCC AAC TAG ACA A‐3′ for R753Q. The PCR reaction was performed in a total volume of 25 μL, which was composed of 0.2 mmol/L dNTP, 0.2 mmol/L each primer and 0.5 unit of Taq DNA Polymerase (Invitrogen, Shanghai, China). Reaction conditions used with the ABI 9600 thermal cycler (Applied Biosystems, Shanghai, China) were as follows: 95°C for 4 min; 35 cycles of 95°C for 45 s, and 45 s of annealing (56°C for D299G and 58°C for T399I) at 72°C for 10 min. The 10 μL amplified samples of D299G, T399I and R753Q SNP were digested with 5 units each of BsaBI, HinfI and SfcI restriction enzymes (New England BioLabs, Shanghai, China) at 37°C, overnight. The digested products were analyzed on 6% non‐denaturing PAGE followed by silver staining. In repeated random genotyping, of 20% of the samples, the genotypes were identical, and the genotyping method was confirmed by the DNA sequencing analysis.
mRNA of cytokines and chemokines measurement by real‐time quantitative PCR and protein measurement by ELISA
To investigate TLR4 T399I's effectt on mRNA and protein expression of cytokines and chemokines, we selected NPC biopsies from all 25 patients with TLR4 399 CT/TT genotype and 30 patients with the CC genotype. The patients were matched by sex, age and pathologic diagnosis. All the samples were stored in a −80°C freezer until tested for cytokines and chemokines.
Total RNA was isolated from NPC biopsies with an RNA extraction kit (Invitrogen). Reverse transcription was performed using 1 μg total RNA in a total volume of 20 μL RT mixture (Invitrogen). For quantitative PCR, the mRNA expression levels were normalized by using the complementary DNA of the housekeeping gene β‐actin. Real‐time quantitative PCR was performed on an ABI 7700 Sequence Detector (Applied Biosystems). Fast real‐time PCR was performed with a SYBR Green PCR Master Mix (Applied Biosystems). Specific primers provided by QIAGEN (Shanghai, China) were used for IL‐1α, IL‐1β, IL‐8, IL‐10, and TNF‐α. The PCR was carried out according to the manufacturers' instructions, at 50°C for 2 min and 95°C for 10 min, followed by 40 cycles of 95°C for 15 s and 60°C for 60 s. The specificity of PCR products was tested according to the dissociation curves. The relative expression levels of cytokines were analyzed using the equation: . Each assay was performed in duplicate, and each cytokine assay tested all RNA samples in the same experiment.
The levels of IL‐1α, IL‐1β, IL‐8, IL‐10 and TNF‐α protein expression in NPC biopsies homogenate were measured with conventional double‐sandwich ELISA kits (Invitrogen). Assays were performed in accordance with the manufacturer's instructions. Samples were assayed in duplicate, and the mean values were calculated.
Statistical analysis
Any deviation from the Hardy–Weinberg equilibrium was calculated by the chi‐square goodness‐of‐fit test. Frequency of polymorphism among the different groups was analyzed using Fisher's exact test or chi‐square test. A t‐test was used to determine the difference in cytokine expression and concentration, which was represented as the mean of the two genotype groups. The OR with 95% CI was used to estimate the association of certain polymorphisms and NPC risk. The OR and 95% CI were calculated with an unconditional logistic regression model and adjusted according to age, sex, alcohol use, smoking status and area of residence. P < 0.05 was considered significant. All data were analyzed with the spss v. 11.5 (SPSS China, Beijing, China) statistical package.
Results
Clinical characteristics of the study participants
Select characteristics of the 236 NPC cases and 287 cancer‐free controls are summarized in Table 1. The median age of the patients was 51.3 years (range, 34–82 years), and the median age of the controls was 53.5 years (range, 30–80 years). There were no significant differences in the age, sex, smoking and alcohol consumption status of the cases and controls, which suggests that the matching based on these variables was adequate. For the 236 NPC patients, the diagnoses were non‐keratinaizing carcinoma (n = 185), squamous cell carcinoma (n = 37) and undifferentiated carcinoma (n = 14).
Table 1.
Characteristics of the study population
| Variables | NPC patients n = 236 (%) | Controls n = 287 (%) | P‐value |
|---|---|---|---|
| Age (mean ± SD) | 51.3 ± 8.7 | 53.5 ± 8.5 | 0.459 |
| Sex | |||
| Male | 184 (78.0) | 218 (76.0) | 0.604 |
| Female | 52 (22.0) | 69 (24.0) | |
| Smoking status | |||
| Smoker | 131 (55.5) | 161 (56.1) | 0.481 |
| Nonsmokers | 105 (44.5) | 126 (43.9) | |
| Alcohol use | |||
| Drinkers | 164 (69.5) | 196 (68.3) | 0.421 |
| Non‐drinkers | 72 (30.5) | 91 (31.7) | |
| Area of residence | |||
| Urban | 89 (37.7) | 106 (36.9) | 0.856 |
| Rural | 147 (62.3) | 181 (63.1) | |
| Clinical stage | |||
| Stage I and II | 40 (16.9) | – | – |
| Stage III and IV | 196 (83.1) | ||
| Histological type | |||
| Non‐keratinaizing carcinoma | 185 (78.4) | – | – |
| Squamous cell carcinoma | 37 (15.7) | ||
| Undifferentiated carcinoma | 14 (5.9) | ||
NPC, nasopharyngeal carcinoma.
Genetic association study of TLR SNP and NPC
To evaluate the association between the TLR4 and TLR2 polymorphisms and NPC susceptibility in Chinese patients, the blood samples of 236 NPC patients and 287 healthy individuals were analyzed. Genotype and allele frequencies of D299G, T399I and R753Q in both the cases and controls are shown in Table 2. The genotype distributions of the three polymorphisms among the controls and the cases were in Hardy–Weinberg equilibrium (P > 0.05). The frequencies of CC, CT, and TT genotypes for the T399I polymorphism were 79.7%, 19.1%, and 1.2%, respectively, in the patients and 88.5%, 11.1% and 0.4%, respectively, in the controls. The allele frequencies of C and T for T399I were 89.2% and 10.8% in the patients and 94.1% and 5.9% in the controls. The genotype and allele distribution for T399I showed statistically significant differences between the cases and controls (P = 0.007 and P = 0.004, respectively). The combined CT/TT genotype of T399I was associated with increased NPC risk at OR = 1.853 (95% CI: 1.184–2.961); individuals with T allele of T399I showed a 1.842‐fold increase risk for NPC risk compared to those with the T399I C allele (95% CI: 1.213–3.015). Table 2 also shows the genotype and allele distributions of D299G and R753Q among the cases and controls. There were no significant differences (P > 0.05).
Table 2.
Frequency distributions of TLR SNP among cases and controls and their associations with NPC
| Polymorphisms | NPC patients n = 236 (%) | Controls n = 287 (%) | ORa (95% CI) | P‐value |
|---|---|---|---|---|
| D299G | ||||
| AA | 205 (86.9) | 250 (87.1) | 1.000 | |
| AG+GG | 31 (13.1) | 37 (12.9) | 1.038 (0.359–1.658) | 1.000 |
| A | 439 (93.0) | 533 (93.0) | 1.00 | |
| G | 33 (7.0) | 41 (7.0) | 0.987 (0.632–1.595) | 1.000 |
| T399I | ||||
| CC | 188 (79.7) | 254 (88.5) | 1.000 | |
| CT+TT | 48 (20.3) | 33 (11.5) | 1.853 (1.184–2.961) | 0.007 |
| C | 421 (89.2) | 540 (94.1) | 1.000 | |
| T | 51 (10.8) | 34 (5.9) | 1.842 (1.213–3.015) | 0.004 |
| R753Q | ||||
| GG | 203 (86.1) | 245 (85.4) | 1.000 | |
| AG+AA | 33 (13.9) | 42 (14.6) | 0.956 (0.624–1.488) | 0.900 |
| G | 426 (92.6) | 530 (92.3) | 1.000 | |
| A | 46 (7.4) | 44 (7.7) | 1.361 (0.859–2.113) | 0.268 |
NPC, nasopharyngeal carcinoma; SNP, single nucleotide polymorphism; TLR, Toll‐like receptor.
Odds ration (OR) and 95% confidence interval (CI) were adjusted by age, sex, smoking status, alcohol consumption and area of residence.
The associations of clinicopathological parameters of NPC and TLR polymorphisms and stratification analysis of T399I polymorphism and NPC risk
No associations were found between TLR polymorphisms and clinical stage or various histological types (differentiation levels) (Table 3). The interactions between T399I genotypes and sex, smoking status and alcohol consumption were analyzed; the stratified OR was calculated, and there were no significant differences (data not shown).
Table 3.
Associations between clinicopathological parameters of NPC and TLR polymorphisms
| Genotypes | Clinical stages | P | Histological type | χ2 | P‐value | |||
|---|---|---|---|---|---|---|---|---|
| Stage I and II n = 40 (%) | Stage III and IV n = 196 (%) | Non‐keratinizing carcinoma n = 185 (%) | Squamous cell carcinoma n = 37 (%) | Undifferentiated carcinoma n = 14 (%) | ||||
| D299G | ||||||||
| AA | 34 (85.0) | 171 (87.2) | 0.702 | 161 (87.0) | 32 (86.5) | 12 (85.7) | 0.025 | 0.988 |
| AG+GG | 6 (15.0) | 25 (12.8) | 24 (13.0) | 5 (13.5) | 2 (14.3) | |||
| T399I | ||||||||
| CC | 31 (77.5) | 157 (80.1) | 0.709 | 149 (80.5) | 29 (78.4) | 10 (71.4) | 0.712 | 0.701 |
| CT+TT | 9 (22.5) | 39 (19.9) | 36 (19.5) | 8 (21.6) | 4 (28.6) | |||
| R753Q | ||||||||
| GG | 35 (87.5) | 168 (85.7) | 0.767 | 161 (87.0) | 33 (89.2) | 9 (64.3) | 5.963 | 0.051 |
| AG+AA | 5 (12.5) | 28 (14.3) | 24 (13.0) | 4 (10.8) | 5 (35.7) | |||
T399I polymorphism with respect to mRNA and protein of cytokines and chemokines
To study the relationship between genotype and phenotype, the expression of inflammation‐related cytokines and chemokines in the NPC biopsies were investigated.
As shown in Figure 1, by analyzing mRNA in NPC biopsies from all 25 patients with TLR4 T399I combined CT/TT genotype and 30 patients with the CC genotype, we found mRNA levels of IL‐1α, TNF‐α and IL‐10 significantly elevated in patients with T399I combined CT/TT genotype compared to those with CC genotype (Δcycle threshold [C t] = 1.51 ± 0.80 vs 2.17 ± 0.71, ΔC t = 1.52 ± 0.70 vs 2.53 ± 0.61, ΔC t = 1.09 ± 0.53 vs 2.76 ± 0.57, respectively). The mRNA of IL‐1α, TNF‐α and IL‐10 increased 1.58‐fold, 2.01‐fold and 3.18‐fold, respectively, in individuals with T399I combined CT/TT genotype. The mRNA of levels IL‐1β and IL‐8 did not significantly differ between the groups (data not shown).
Figure 1.
Messenger RNA (mRNA) expression of IL‐1α, TNF‐α and IL‐10 in biopsies of NPC patients with TLR4 T399I polymorphism. Results are shown as boxplots. (a) Results show that the ΔC t value of IL‐1α was 1.51 ± 0.80 vs 2.17 ± 0.71. (b) Results show that the ΔC t value of TNF‐α was 1.52 ± 0.70 vs 2.53 ± 0.61. Samples 51 and 52 were outliers. (c) Results show that the ΔC t value of IL‐10 was 1.09 ± 0.53 vs 2.76 ± 0.57. The mRNA levels of IL‐1α, TNF‐α and IL‐10 in patients with T399I combined CT/TT genotype were significantly elevated compared with individuals with the CC genotype. IL, interleukin; NPC, nasopharyngeal carcinoma; TLR, Toll‐like receptor; TNF, tumor necrosis factor.
Protein concentration in NPC biopsies from all 25 patients with TLR4 T399I combined CT/TT genotype and 30 patients with CC genotype were also analyzed. As shown in Figure 2, IL‐1α and IL‐10 protein concentrations in biopsies of NPC patients differed significantly. In NPC patients with T399I combined CT/TT genotype, IL‐1α was significantly elevated (38.28.24 ± 9.97 pg/mg) compared to patients with CC genotype (23.93 ± 6.18 pg/mg). Similarly, IL‐10 was significantly elevated in NPC patients with combined CT/TT genotype (22.24 ± 6.49 pg/mg) compared to those with CC genotype (14.37 ± 6.27 pg/mg). There were no significant differences in IL‐1β, IL‐8 and TNF‐α concentration between the groups (data not shown).
Figure 2.
TLR4 T399I polymorphism affected the protein concentration of IL‐1α and IL‐10 in biopsies of NPC patients. Results are shown as boxplots. (a) Results show that IL‐1α was significantly elevated in NPC patients with combined CT/TT genotype (38.24 ± 9.97 pg/mg) compared to those with CC genotype (23.93 ± 6.18 pg/mg). Samples 27, 28 and 29 were outliers. (b) Results show that IL‐10 was significantly elevated in NPC patients with combined CT/TT genotype (22.24 ± 6.49 pg/mg) compared to those with the CC genotype (14.37 ± 6.27 pg/mg). IL, interleukin; NPC, nasopharyngeal carcinoma; TLR, Toll‐like receptor.
Discussion
To our knowledge, this is the first study to investigate whether TLR4 and TLR2 gene polymorphisms are related to the occurrence of NPC in a Chinese population and whether these gene polymorphisms correlate to mRNA and protein expression of inflammation‐related cytokines and chemokines in NPC biopsies. In this study, we have shown that the C/T polymorphism at 1196 pb of TLR4, an asparagine (T) to lysine (I) substitution in amino acid sequence 399 (T399I), was significantly associated with the risk of NPC. The combined CT/TT genotype of T399I was associated with increased NPC risk compared to the CC genotype (OR = 1.853, 95% CI: 1.184–2.961, P = 0.007). Moreover, individuals with the T allele of T399I showed a 1.842‐fold increase in NPC risk compared with the T399I C allele (95% CI: 1.213–3.015, P = 0.004). We also found that mRNA expression of IL‐1α, IFN‐α and IL‐10 and protein concentrations of IL‐1α and IL‐10 were significantly increased in patients with the combined CT/TT genotype of T399I polymorphism. These findings suggest that the TLR4 T399I polymorphism could be a contributing factor in NPC risk, but it could be used as a genetic susceptibility marker for NPC.
In most parts of the world, NPC is rare, but it occurs at a high frequency in South‐East Asia and China and at a somewhat lower but still elevated rate in North and East Africa. Microscopically, one striking feature of NPC is a heavy infiltration of nonmalignant lymphocytes, and most of these lymphocytes have been shown to be T cells. Another important feature of NPC is its association with the EBV infection. Studies have shown that the expression of EBV gene products is involved in the latent and lytic cycles in NPC specimens, and some of these viral gene products might have the capacity to induce or influence inflammatory cytokine production, such as IL‐10, IL‐6 and TGF‐β.23, 24 The contribution of inflammation and inflammatory cells to the process of tumor development and progression has been increasingly recognized.25, 26 Elevated expression of cytokines is a common phenomenon of tumor cell lines derived from many cancers, such as melanomas, leukemias, and gastric and ovarian carcinoma.27, 28, 29, 30 Evidence has shown that a substantial proportion of malignant tumors worldwide arise from infection and chronic inflammation.31 Both inflammatory and tumor cells produce an assorted array of cytokines and chemokines, which mediate all aspects of inflammation and profoundly affect the development and progression of cancer.32, 33 Previous studies have shown that NPC is associated with overexpression of numerous cytokines in NPC biopsies. EBV infection is ubiquitous in the world, but NPC incidence differs according to geographic region, and the reasons for this selective susceptibility are not fully understood. However, it is clear that environmental, viral and host factors play a role.
As a family of receptors, TLR play a pivotal role in sensing a wide range of pathogens, including bacteria, fungi and viruses.10 Recent works have documented that TLR may be an important pattern recognition receptor in the immune response directed against EBV infection, which may evade the immune system by modulation of the TLR signaling pathway.34, 35 TLR signaling initiated by various pathogens triggers a cascade of signaling events that stimulate the production of pro‐inflammatory cytokines and chemokines, initiating the inflammatory response. As a consequence, a dysregulation of TLR signaling may contribute to an imbalance between pro‐ and anti‐inflammatory cytokines and lead to a higher risk of developing chronic inflammatory diseases and cancer.11 Several SNP within individual TLR have been identified. The ability to respond properly to TLR ligands may be impaired by SNP within TLR genes, causing an altered susceptibility to the outcome of infectious or inflammatory diseases and cancers.11, 16 A number of molecular epidemiologic studies on the TLR4 and TLR2 genotypes and cancer susceptibility have been reported. Zheng et al.36 showed that the 11381G/C variant was positively associated with prostate cancer in a Swedish population, but Chen et al.37 demonstrated that the 11381G/C variant was not associated with prostate cancer. Cheng et al.38 suggested that rs10759932 was associated with a four‐fold increased risk of prostate cancer. Garza‐Gonzalez et al. and Trejo‐de la O et al. found no significant difference in frequency of TLR4D299G and TLR4T399I genotypes among gastric cancer patients and controls.13, 16 However, Trejo‐de la O et al.16 showed that TLR4 polymorphisms could influence the expression of cytokine and chemokine in the gastric mucosa. Santini et al.10 demonstrated that TLR4Thr399Ile polymorphism is linked with an increased susceptibility to gastric cancer. Nischalke et al.39 suggested that the TLR2 −196 to −174del allele affects hepatitis C virus loads and increases the risk for hepatocellular carcinoma in hepatitis C virus genotype 1‐infected patients.
The mechanisms by which TLR polymorphisms affect cancer risk remain unknown, but evidence shows that chronic inflammation pathogenesis is the underlying pathological event in these malignancies. NPC is an epithelial cancer that is causally associated with EBV infection; studies have shown that cytokines synthesis might contribute to lymphocyte infiltration and/or tumor growth during NPC development.40 Therefore, it is plausible that the various phenotypes of TLR may result in individuals with various inflammatory response and NPC risk.
Our study shows that TLR4 polymorphisms probably play a major role in susceptibility to NPC. Genotypes of TLR4 T399I TT and CT are associated with increased NPC susceptibility and IL‐10 expression in NPC biopsies and are a risk factor for NPC development. A possible mechanism for TLR4 polymorphism in modulating NPC susceptibility and tumor development is through the regulation of the expression of cytokines. TLR signaling initiated by various pathogens, such as EBV, triggers a cascade of signaling events that stimulate the production of pro‐inflammatory cytokines and chemokines. Of them, TNF‐α stimulates tumor cell growth, affects stromal cells and enhances both metastasis and angiogenesis;32 IL‐10 plays a major role in the development of cancer.41 We speculated that the ability to respond properly to TLR ligands may be impaired by SNP within TLR genes, and a dysregulation of TLR signaling may contribute to an imbalance between pro‐ and anti‐inflammatory cytokines, causing an altered susceptibility to the outcome of cancers. Although the precise mechanisms by which TLR4 gene polymorphisms are associated with NPC remains undetermined, additional functional studies could provide valuable characterization of the molecular mechanisms by which TLR are involved in susceptibility to NPC. Continued study of the role of TLR polymorphisms to NPC susceptibility from other ethnic populations would also be of great value.
Disclosure Statement
The authors have no conflicts of interest.
Abbreviations
- CI
confidence interval
- EBV
Epstein–Barr virus
- IL
interleukin
- NPC
nasopharyngeal carcinoma
- OR
odds ratio
- SNP
single nucleotide polymorphism
- TLR
toll‐like receptor
- TNF
tumor necrosis factor
Acknowledgments
This work was financially supported by Applied Basic Research Programs of Science and Technology Bureau of Sichuan Province (No. 07JY029‐134) and Foundation of Sichuan Educational Committee (No.07ZB110).
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