Association of p53 codon72 Arg>Pro polymorphism with susceptibility to nasopharyngeal carcinoma: evidence from a case–control study and meta-analysis

Tumor suppressor p53 is a critical player in the fight against cancer as it controls the cell cycle check point, apoptotic pathways and genomic stability. It is known to be the most frequently mutated gene in a wide variety of human cancers. Single-nucleotide polymorphism of p53 at codon72 leading to substitution of proline (Pro) in place of arginine (Arg) has been identified as a risk factor for development of many cancers, including nasopharyngeal carcinoma (NPC). However, the association of this polymorphism with NPC across the published literature has shown conflicting results. We aimed to conduct a case–control study for a possible relation of p53 codon72 Arg>Pro polymorphism with NPC risk in underdeveloped states of India, combine the result with previously available records from different databases and perform a meta-analysis to draw a more definitive conclusion. A total of 70 NPC patients and 70 healthy controls were enrolled from different hospitals of north-eastern India. The p53 codon72 Arg>Pro polymorphism was typed by polymerase chain reaction, which showed an association with NPC risk. In the meta-analysis consisting of 1842 cases and 2330 controls, it was found that individuals carrying the Pro allele and the ProPro genotype were at a significantly higher risk for NPC as compared with those with the Arg allele and the ArgArg genotype, respectively. Individuals with a ProPro genotype and a combined Pro genotype (ProPro+ArgPro) also showed a significantly higher risk for NPC over a wild homozygote ArgArg genotype. Additionally, the strength of each study was tested by power analysis and genotype distribution by Hardy–Weinberg equilibrium. The outcome of the study indicated that both allele frequency and genotype distribution of p53 codon72 Arg>Pro polymorphism were significantly associated with NPC risk. Stratified analyses based on ethnicity and source of samples supported the above result.


INTRODUCTION
Nasopharyngeal carcinoma (NPC) arises from the epithelial cells that cover the upper part of the throat behind the nose and near the base of the skull. The disease is treatable at an early stage but the majority of NPC patients are diagnosed at a late stage because of the exhibition of nonspecific symptoms related to other head and neck illnesses. 1,2 General symptoms of NPC include trismus, otitis media, hearing loss, nasal regurgitation, cranial nerve palsies, nasal twang, bleeding and pain. 3 The World Health Organization histopathological grading system classifies NPC into three types: keratinizing squamous cell carcinoma; non-keratinizing differentiated carcinoma; and undifferentiated carcinoma. 4 The American joint committee on cancer established tumor, node and metastasis classification to determine the different stages of NPC.
Epidemiological studies suggest the association of food habits (alcohol, intake of salted fish containing nitrosamine, herbal tea and herbal medicine), lifestyle (occupational exposure to formaldehyde, chlorophenol, wood dust, tobacco users) and viral infection (Epstein-Barr virus and human papilloma virus) in the etiology of NPC. [5][6][7][8][9] However, many individuals exposed to these parameters do not develop NPC, which indicates the involvement of genetic factors. To establish a link between genetic factors and NPC development, study of single-nucleotide polymorphism (SNP) in tumor suppressor genes has been the focus of many researchers.
p53 is a well-established tumor suppressor gene located on chromosome 17p13.1. It plays a critical role in response to genotoxic stress and tries to maintain genomic stability and control proper execution of the cell cycle and apoptotic pathways. [10][11][12] Deregulated function of p53 may result in loss of this regulation, resulting in uncontrolled cell proliferation and cancer development. [13][14][15] Polymorphisms in p53 or target genes impair the function of the p53 signaling pathway. 16 The most studied polymorphism in p53 is located in exon 4 at codon72. It carries either the CGC sequence that encodes arginine or the CCC sequence that encodes proline due to G/C transversion. 17,18 As a result, two allelic forms (Arg and Pro) and three genotypes (ArgArg, ArgPro and ProPro) have evolved. These allelic variants and genotypes oscillate in their binding capacity to the transcriptional factors, induction of apoptosis and repression of transformation of human cells. 7,[18][19][20] Arg variants induce apoptosis more efficiently than do the Pro variants, which may be due to their ability to localize into mitochondria and regulate the release of cytochrome C into cytosol. 18 The released cytochrome C in turn activates caspase-3, one of the key executioners of apoptosis. 21,22 This difference between Arg and Pro variants may provide the plausible cause for Pro allele's involvement in increased susceptibility to NPC. Earlier, several studies including our present study among the populations of north-eastern India have investigated the relation between p53 codon72 Arg4Pro polymorphism and NPC risk. [23][24][25][26][27][28][29][30][31][32] The purpose of a case-control study of northeastern Indian populations was also to find out the incidence of different stages of NPC among them and to examine the clinical symptoms manifested by them. However, these findings were inconsistent and inconclusive. In view of the fact that a single study may have been underpowered in clarifying the association, we performed a meta-analysis to combine the findings of all earlier studies from public records and data from the present study according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 33 guidelines to explore the overall association and derive a near-specific conclusion.

RESULTS AND DISCUSSION
NPC is a public health problem in many countries; it has a complex etiology and ranks 24th among the most frequently diagnosed cancers. 34 The incidence rate of this cancer is highest in south-east Asia and about 92% of new cases are being found in economically developing countries. 34 In India, this rate is comparable to that of the United Kingdom with the younger age peak in the second decade. 35,36 Several susceptible genes have been implicated for NPC risk, such as tumor suppressor p53, TGFβ1, IL-12 p40 and DNA repair genes. 28,[37][38][39] In contrast, FokI and Bsm I polymorphisms of vitamin D receptor gene, SNP of deleted in liver cancer-1 (−29A/T) showed no association with NPC. 40,41 However, polymorphisms in PIN-1, TNF-α and glutathione S-transferase genes are indirectly associated with NPC as they influence the p53 codon72 polymorphism. [42][43][44] These studies suggest that genetic predisposition may play a role in NPC development. Hence, we conducted a study in the north-eastern Indian population among healthy controls and NPC patients to find out the prevalence of p53 codon72 Arg4Pro polymorphism (  29 in 2010, found that the p53 codon72 polymorphism carried an increased NPC risk independently or in combination with the murine double minute-2 (MDM2) polymorphism in a Chinese population sample, suggesting a gene-gene interaction in NPC pathogenesis. Furthermore, Li et al., 28 in 2013, reported that p53 codon72 and miR-34b/c rs4938723 polymorphisms may singly or collaboratively contribute to the risk for NPC. Two more studies reported this polymorphism as an independent prognostic marker for NPC, and hence one could speculate that this polymorphism means more risk for incidence and more risk for an aggressive disease. 45,46 Moreover, Zhang et al., in 2014, observed a weak effect of p53 polymorphisms on NPC risk. However, they found a significant risk with combination genotypes (i.e., p53 codon72 ArgPro+ProPro, MDM2 rs2279244 GT+GG, PTEN rs11202592 CC, AKT1 rs1130233 AA). 30 Overall, variability in study results may be attributed to variation in study design, environmental factors, genetic backgrounds, racial heterogeneity, sample size, source of controls and enrollment criteria for NPC cases. A previous meta-analysis showed that the ProPro homozygote of p53 codon72 possesses an increased NPC risk. 47 In another meta-analysis, Jiqiao Yang et al. 48 analyzed publicly available data under five comparison models (allele contrast, homozygous, heterozygous, dominant and recessive) and showed the association of p53 codon72 Arg4Pro, MMP-1 (1G42G), MMP-2 (−1306C4T), CYP2E1 (RsaI) and XRCC1 codon399 Arg4Gln polymorphism with increased risks for NPC.
In our meta-analysis, all eligible reports that fulfilled the inclusion criteria were identified from publication search and the data from the The search items included the combination of the following key words: p53, p53 codon72, p53 codon72 ArgPro, p53 codon72 Arg4Pro, p53 Arg72Pro or rs1042522; and nasopharyngeal cancer, nasopharyngeal carcinoma or NPC; and mutation, polymorphism, single nucleotide polymorphisms or SNPs. The inclusion criteria were case-control studies in peer-reviewed journals and articles containing useful allele and genotype frequency. The exclusion criteria were case reports without control, overlapping data with previous publications, and review articles. p53 codon72 polymorphism is associated with NPC SK Sahu et al north-eastern Indian population were also included for evaluation. [23][24][25][26][27][28][29][30][31][32] Thus, a total of 10 case-control studies counting 1842 NPC patients and 2330 controls comprising populations from India, China, Tunisia, Portugal and Thailand were included in the final meta-analysis ( Figure 1). The characteristics of all studies considered for the p53 codon72 Arg4Pro polymorphism were given. Minor allele frequency, Hardy-Weinberg equilibrium and a post hoc power of each study were calculated to detect the probability of association between p53 codon72 Arg4Pro polymorphisms and NPC at the 0.05 level of significance, assuming small effect size (w = 0.15). In the north-eastern Indian population, the minor allele frequency of the p53 codon72 Arg4Pro was 0.37 for controls and 0.56 for NPC. The power of this case-control study was too weak (23%) to detect any mild effect of the polymorphisms on disease susceptibility.
The distribution of genotype frequency among controls in all these studies did not deviate from Hardy-Weinberg equilibrium since P40.05, except the study in the north-eastern Indian population (Table 3).
It is worth noting that the small size of samples from the northeastern population may be due to the low incidence of NPC.
Significant associations between p53 codon72 Arg4Pro polymorphism and NPC risk were observed in the combined analysis of overall studies (Pro vs Arg: OR = 1.  (Table 4) and forest plots (figures not shown) indicated that the p53 codon72 polymorphism among Asians and population-based studies was associated with the development of NPC in all five comparison models (Pro vs Arg, ProPro vs ArgArg, ArgPro vs ArgArg, ProPro+ArgPro vs ArgArg and ProPro vs ArgArg+ProPro). In Caucasian and hospital-based studies a similar risk was noted in three comparison models (Pro vs Arg, ProPro vs ArgArg and ProPro vs ArgArg+ProPro). In the overall Chinese studies NPC risk was found for all comparison models except for the recessive model. Sensitivity analyses were carried out to assess the stability of the results in the overall and stratified analysis by sequential omission of individual study each time. It was observed that the influence of individual data sets on the significance of pooled ORs was not markedly influenced by any single study (data not shown). Funnel plot and Egger's test were conducted in five comparison models to assess the publication bias in the overall combined meta-analyses. The shape of funnel plots did not reveal any evidence of asymmetry ( Figure 3). Stratified analysis in Asian, population-based and Chinese studies also showed similar trends in the shape of the funnel plots (figures not shown). Furthermore, Egger's test in overall, Asian, population-based and Chinese studies did not show evidence of publication bias in any of the comparison models as P-values were larger than 0.05 (Table 4). However, publication bias (Funnel plot and Egger's test) was not possible in Caucasian and hospital-based studies because the numbers of studies were less than three. Heterogeneity within and among different studies were tested with Q-value, P-value of heterogeneity (P H ) and I 2 statistics ( Table 4). The random-effects model was used for meta-analysis if the Q-statistic was significant (P H o 0.05), which indicates heterogeneity across studies. The fixed-effect model was employed when P H ⩾ 0.05. In the overall population, the fixedeffect model was employed for meta-analysis of the p53 codon72 Arg4Pro polymorphism in four comparison models (Pro vs Arg, ProPro vs ArgArg, ArgPro vs ArgArg and ProPro+ArgPro vs ArgArg). However, the ProPro vs ArgArg+ArgPro comparison model showed heterogeneity among studies in the overall population and the random-effect model was used.  based on samples collected from hospitals or random populations, different countries and ethnicities, power of the study, genotyping method and the distribution of the genotype among NPC and controls were listed. HWE was tested using the web-based tools (http://www.oege.org/software/ we-mr-calc.shtml). Power analysis was performed by G power software (version 3.1). 52 p53 codon72 polymorphism is associated with NPC SK Sahu et al Figure 2. Forest plots for association between p53 codon72 Arg4Pro polymorphism and NPC risk. The squares and horizontal lines correspond to the study-specific OR and 95% CI, respectively. The area of the squares reflects the study-specific weight and the diamond represents the pooled OR and 95% CI. In the stratified analysis, the fixed-effect model was employed in all comparison models of Asian studies except the Pro vs Arg comparison, in which the random-effect model was used. In Caucasian studies the fixed-effect model was employed in all comparison models. In population-based and Chinese studies the fixed-effect model was employed in all comparison models except in the ProPro vs ArgArg+ArgPro comparison model, which reflects the combined results of the overall study. In hospital-based studies the fixed-effect model was employed in three comparison models (Pro vs Arg, ProPro vs ArgArg and ProPro vs ArgArg +ProPro) and the random-effect model in two comparison models (ArgPro vs ArgArg and ProPro+ArgPro vs ArgArg). The overall pooled results indicate that the p53 codon72 polymorphism is a significant risk factor in the pathogenesis of NPC. Stratified analyses in Asian, Caucasian, hospital-based, population-based and Chinese case-control studies corroborate this association. This meta-analysis supports the findings in north-eastern Indian populations. To our knowledge, the current study is the first to analyze the p53 codon72 polymorphism and association with NPC in the Indian population.
In conclusion, our case-control study in North Indian populations and meta-analysis results as evidenced from five genetic models suggest that the p53 codon72 Arg4Pro polymorphism could be employed as a risk factor for NPC. However, some limitations exist in the current meta-analysis. Association of p53 codon72 polymorphism with susceptibility to the histological and clinical grade of NPC patients has not been investigated because of lack of available data on the subject. Abbreviations: 95% CI, 95% confidence intervals; Fixed, fixed-effect model; OR, odds ratio; P H , P-vaue of heterogeneity analysis. Meta-analysis was performed with comprehensive meta-analysis V2 software in overall studies, Asian, Caucasian, population-based, hospital-based and Chinese studies. Association of p53 codon72 Arg4Pro polymorphisms with NPC was assessed by the estimation of the combined odds ratio (OR), P-value and 95% confidence interval (CI) in five different models: (i) allele contrast (Pro vs Arg), (ii) homozygous comparison (ProPro vs ArgArg), (iii) heterozygous comparison (ArgPro vs ArgArg), (iv) dominant (ProPro+ArgPro vs ArgArg) and (v) recessive (ProPro vs ArgArg+ProPro) model. Heterogeneity between studies was calculated using Cochran's Q-statistic and I 2 values as described earlier. 53,54 Based on heterogeneity or homogeneity among the included studies, the random (Der Simonian and Laird method) or fixed (Mantel-Haenszel's method) model was used to calculate combined OR and 95% CI. Publication bias was assessed from Egger's regression analysis.
p53 codon72 polymorphism is associated with NPC SK Sahu et al The p53 Arg form is more susceptible to degradation than the Pro form by human papilloma virus E6 protein. 49 Notably, Epstein-Barr virus infection modulates the effect of the p53 family 22 and is a well-nown risk factor for NPC. Nevertheless, whether the p53 Arg or the Pro form is also susceptible to degradation by viruses or by other infectious agents needs to be investigated. Further, as there are a large number of SNPs for p53, the SNP studied in the present analysis was limited only to the functionally important one. In future, screening of all p53 and related polymorphisms in larger samples based on ethnicity in view of confounding factors such as age, sex, cigarette smoke, tobacco use, alcohol intake, dietary habit, stages of NPC and socioeconomic status is required to validate the findings.