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Evaluation of the p53 Arg72Pro polymorphism and its association with cancer risk: a HuGE review and meta-analysis

Published online by Cambridge University Press:  17 April 2015

MOHAMMAD HAROON KHAN ,
AFTAB KHALIL  and
HAMID RASHID
MOHAMMAD HAROON KHAN*
Affiliation:
Department of Bioinformatics, Mohammad Ali Jinnah University, Islamabad, Pakistan
AFTAB KHALIL
Affiliation:
Department of Bioinformatics, Mohammad Ali Jinnah University, Islamabad, Pakistan
HAMID RASHID
Affiliation:
Department of Bioinformatics, Mohammad Ali Jinnah University, Islamabad, Pakistan
*
* Corresponding author: Dr Mohammad Haroon Khan, Lecturer, Department of Bioinformatics, Mohammad Ali Jinnah University, Islamabad, Pakistan. Tel: +91 111 87 87 87 ext. 161. Cell: +91 331 5495540. E-mail: [email protected]
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Summary

Codon 72 is a hotspot of polymorphisms in the TP53 gene, which encodes a hub protein in the protein–protein interaction network of p53. It is thus a central player in the apoptotic pathway, preventing cancer. A large number of articles have been published exploring its association with an increased susceptibility to most common cancers. However, these studies have produced inconclusive results, which may be due to their small sample sizes or study designs. To comprehensively evaluate the potential correlation between the TP53 Pro72Arg polymorphism and cancer risk and to better characterize the Pro72Arg polymorphism, we performed a systematic HuGE review and meta-analysis of candidate studies through online resources, according to the proposal of MOOSE and the PRISMA statement. The identified articles were carefully examined according to the inclusion criteria. Pooled odds ratios were calculated on the basis of different genetic models, while heterogeneity was assessed through a chi-based Q-test and I2. After applying the inclusion filters, we obtained a pool of 54 eligible studies, representing 18 718 cases and 21 261 controls. Overall, non-significant cancer risk was observed in all the genetic models but their observed heterogeneity was extremely significant. In subgroup analysis, an increased susceptibility was observed in the case of colorectal cancer, while in cancers of the female reproductive system, significantly increased risk was detected in all the genetic models except the dominant model. In another subgroup analysis, significantly increased cancer risk was observed among Asians in homozygous and recessive models, while in Americans increased cancer risk was observed only in dominant and recessive models. No association was observed in the rest of the populations. In conclusion, pooled subgroup analysis on the basis of ethnicity proved that the TP53 Arg72Pro polymorphism is associated with an increased risk of cancer in Asians and Americans only and is not associated in other populations. It can therefore be concluded that this meta-analysis of available data suggests partial confirmation of the association between the TP53 Arg72Pro polymorphism and cancer risk susceptibility.

Type
Research Papers
Information
Genetics Research , Volume 97 , 2015 , e7
Copyright
Copyright © Cambridge University Press 2015 

1. Introduction

Cancer, a major threat to humanity, is a multi-factorial disorder caused by genetic or environmental factors, or the interactions of these (Bredberg, Reference Bredberg2011). Genetic factors include point mutations or chromosomal aberrations, which can result in the breakdown of the relevant pathways and can enhance cancer susceptibility (Zhang et al., Reference Zhang, Li and Xu2013).

TP53 is a tumor suppressor gene, encoding a transcription factor (hub protein) in the protein–protein interaction network of p53. It is a central player in the apoptotic pathway that detects internal and external signals and effectors, and induces death in response to a number of cellular stresses, thereby preventing cancer stresses (Vogelstein et al., Reference Vogelstein, Lane and Levine2000; Horn & Vousden, Reference Horn and Vousden2007). Unfortunately, >50% of human cancers show alterations in this genome guardian (Milner & Medcalf, Reference Milner and Medcalf1991). More than 20 000 different types of alterations in human TP53 have been observed (Olivier et al., Reference Olivier, Eeles, Hollstein, Khan, Harris and Hainaut2002), with the addition of a number of SNPs that have also been proven to differentially enhance cancer susceptibility in different ethnic groups (Packer et al., Reference Packer, Yeager, Burdett, Welch, Beerman, Qi, Sicotte, Staats, Acharya, Crenshaw, Eckert, Puri, Gerhard and Chanock2006). They may affect the function of the TP53 gene product through increased enigmatic splicing, altering the stability of the downstream transcript, enhanced mutability or differential expression (Lozano & Levine, Reference Lozano and Levine1991; Lozano, Reference Lozano1994).

Codon 72 is a hotspot of polymorphisms in the TP53 gene. rs1042522 is the most studied SNP at this codon, encoding an Arg–Pro substitution (Sprague et al., Reference Sprague, Trentham-Dietz, Garcia-Closas, Newcomb, Titus-Ernstoff, Hampton, Chanock, Haines and Egan2007). Located in the proline-rich region, it can affect the structure of the SH3-binding domain. The gene product with the Arg residue has been found to be more efficient for apoptotic activity as compared to the counterpart with the Pro residue at codon 72. The allelic/variant frequencies of codon 72 differ among different world populations and also are responsible for differential cancer susceptibility in these populations (Dumont et al., Reference Dumont, Leu, Della Pietra, George and Murphy2003).

In recent years, a large number of studies have been published exploring the association of the TP53 Pro72Arg polymorphism and increased susceptibility to most common cancers, including prostate cancer (PCa). The results of a single study may be underpowered due to certain reasons and it is clear from the literature that these studies have reported conflicting results, which may be due to their small sample sizes or study design (Yang et al., Reference Yang, Xu, Lu., Han, Tao, Lu, Wang, Di and Gu2012).To comprehensively evaluate the potential correlation between the TP53 Pro72Arg polymorphism and cancer risk, and to further our understanding and to allow for a more precise characterization of the Pro72Arg polymorphism, we designed a systematic HuGE review and meta-analysis of candidate studies.

2. Materials and methods

This study was undertaken according to the proposal of MOOSE and the PRISMA statement. We performed a systematic search of the relevant literature for articles discussing the TP53 codon 72 (rs1042522) polymorphism and its association with cancer risk. The online resources, including Google scholar, MEDLINE, PubMed and Embase, were used with the combination of terms ‘Arg72 or rs1042522, polymorphism or variant or TP53 or SNP’ and ‘cancer or carcinoma or adenocarcinoma’ (From 2000 to 2014). The identified full-length articles were carefully and systematically examined and retrieved by the co-authors. We only included those studies that were in agreement with our inclusion criteria in the meta-analysis, namely: (1) the publication to be included must be a case-control study; (2) the publication must refer to the association of the TP53 codon 72 polymorphism and cancer risk; (3) the publication must refer to both the sample sizes of cases and controls along with distribution of alleles/genotypes or other necessary information that can help to infer results; (4) if multiple publications are available on the same/overlapping data, the publication with the most recent and largest population will be included in the study; and (5) the language of publication was confined to English only.

The data were extracted independently by all the authors from the eligible articles, and then the results were compared. Disagreements, if any, were resolved by discussion and reasoning, and the following information was collected from each study: name of first author, year of publication, study title, total number of samples (cases and controls), type of cancer, ethnicity and distribution of genotypes in case and control groups, as shown in Fig. 1 and Table 1.

Fig. 1. A general flow diagram of study identification according to MOOSE and PRISMA statement.

Table 1. Characteristics of case-control studies included in the meta-analysis.

ABCS, Amsterdam Breast Cancer Study, Netherlands; BBC, British Breast Cancer, London, UK; CIN, cervical intraepithelial neoplasia; EABT, extra-axial brain tumour; Familial BCa, familial breast cancer; HaBCS, Hannover Breast Cancer Study, Germany; HCC, hepatocellular carcinoma; HeBCS, Helsinki Breast Cancer Study, Finland; SCCHN, squamous cell cancer of the head and neck; SEARCH, Study of Epidemiology & Risk Factors in Cancer Heredity, Cambridge, UK; Sporadic BCa, sporadic breast cancer.

We performed the meta-analysis according to the criteria described earlier. Hardy-Weinberg equilibrium (HWE) was calculated using Fisher's exact/chi-square for each study, and P < 0·05 was considered statistically significant. We only included those studies that were in agreement with HWE. The strength of association between the TP53 Pro72Arg polymorphism and cancer risk was assessed through odds ratios (ORs) along with their 95%CI. Pooled ORs were calculated on the basis of four different genetic models, including CC vs. GG, CC vs. CG, dominant and recessive models. We further subdivided the association by analyzing by ethnicity and cancer type. Ethnicity was classified into Asian, European, American (North and South), Australian and African populations. We assessed heterogeneity through chi-based Q-tests, and P > 0·10 was considered statistically significant. In cases lacking heterogeneity among the studies, the Mantel-Haenszel (fixed effects) model was used to calculate the pooled ORs; otherwise, the random effects model was used. I2 was also calculated to quantitatively assess the percentage of variation among the studies as a result of heterogeneity. The values were classified into four classes to generalize the observed heterogeneity, as follows: zero value = no observed heterogeneity, values > 0⩽25% = low observed heterogeneity, values > 25%⩽50% = moderate observed heterogeneity, values > 50%⩽75% = high observed heterogeneity and values > 75% = very high observed heterogeneity. We confirmed the stability of the results through the sensitivity analysis, and we examined publication bias through funnel plots and qualitatively by Egger's test. All the statistical analysis was conducted by using comprehensive Meta Analysis Software version 2.2·064.

3. Results

After a comprehensive search, we identified a total of 257 publications and reviewed them using the defined inclusion criteria (Fig. 1). After applying the inclusion filters we obtained a pool of 54 eligible studies, representing a total of 18 718 cases and 21 261controls for the p53 Arg72Pro polymorphism. Some of the included articles consist of more than one study; for these, each study was considered as an independent data set. The main characteristics of all the included data sets are listed in Table 1, and Table 2 consists of the quantitative results of this meta-analysis and their heterogeneity. As shown in Table 2, the data sets included different studies from different world populations, including 24 from Asian, 17 from European, ten from American (North and South), one from Australia and two from African populations.

Table 2. Pooled analysis of association of P72R (rs1042522) polymorphism and cancer risk.

CI, confidence intervals, I2, percentage of variation across studies as a result of heterogeneity; OR, odds ratio.

Overall, non-significantly elevated cancer risk was found in all the genetic models (CC vs. GG, OR: 1·14, 95%CI: 0·96–1·12, I2 = 77·54, P = 0·000; CC vs. CG, OR: 1·10, 95%CI: 0·96–1·27, I2 = 70·64, P = 0·000; dominant, OR: 1·07, 95%CI: 0·97–1·17, I2 = 69·97, P = 0·000; recessive, OR: 1·13, 95%CI: 0·98–1·30, I2 = 74·85, P = 0·000) but the observed heterogeneity was extremely significant in the models. To further focus our analysis, we stratified the data into subgroups on the basis of cancer types and population/ethnicity. An increased susceptibility was observed in the results of all genetic models in the case of colorectal cancer (CC vs. GG, OR: 2·73, 95%CI: 1·54–4·84, I2 = 75·19, P = 0·007; CC vs. CG, OR: 1·65, 95%CI: 1·34–2·04, I2 = 0·00, P = 0·731; dominant, OR: 1·95, 95%CI: 1·20–3·15, I2 = 73·36, P = 0·010; recessive, OR: 1·93, 95%CI: 1·44–2·59, I2 = 48·02, P = 0·123), while in cancers of the female reproductive system, significantly increased risk was detected in all the genetic models except the dominant model (CC vs. GG, OR: 1·61, 95%CI: 1·33–1·95, I2 = 75·09, P = 0·000; CC vs. CG, OR: 1·65, 95%CI: 1·36–2·01, I2 = 77·99, P = 0·000; recessive: OR: 1·71, 95%CI: 1·42–2·04, I2 = 79·19, P = 0·000). In the case of pancreatic cancer, only the dominant model (OR: 1·30, 95%CI: 1·01–1·67, I2 = 90·21, P = 0·001) was found to be associated with increased risk, while no association/significant association was observed for the rest of the cancer types included in the study.

In the subgroup analysis on the basis of ethnicity, significantly increased cancer risk was observed among Asians in CC vs. GG (OR: 1·14, 95%CI: 1·03–1·26, I2 = 78·73, P = 0·000) and recessive models (CC vs. GG+CG, OR: 1·17, 95%CI: 1·06–1·29, I2 = 83·07, P = 0·000), while in Americans significantly increased cancer risk was observed in dominant (OR: 1·33, 95%CI: 1·06–1·68, I2 = 74·82, P = 0·000) and recessive models (OR: 1·22, 95%CI: 1·01–1·46, I2 = 72·78, P = 0·000). No association was observed in rest of the populations (Table 2).

(i) Publication bias and sensitivity analysis

Publication bias was assessed both through the visual inspection of the funnel plots symmetry and the statistical evidence of the Begg's and Mazumdar's rank correlation test and Egger's linear regression method (CC vs. GG, Kendall's tau = 0·015, two tailed P = 0·86; Egger: bias = 0·93 [95% CI: -0·28–2·14], two tailed P = 0·05; CC vs. CG, Kendall's tau = 0·1, two tailed P = 0·3; Egger: bias = 1·11 [95%CI: -0·02–2·24], two tailed P = 0·053; dominant, Kendall's tau = −0·07, two tailed P = 0·42; Egger: bias = 0·36 [95%CI: -0·52–1·26], two tailed P = 0·41; recessive, Kendall's tau = 0·1, two tailed P = 0·30; Egger: bias = 1·08 [95%CI: -0·14–2·31], two tailed P = 0·08).

4. Discussion

We explored the association of the TP53 P72R polymorphism and increased cancer susceptibility in this study, including 54 eligible case-control studies representing 18 718 cases and 21 261 controls. We observed that the presence of the TP53 P72R polymorphism showed no association with increased cancer susceptibility in the overall pooled analysis, while in the subgroup analysis, the cancer risk was significantly pronounced in colorectal cancer and cancers of the female reproductive system. However, no significant association of the polymorphism was observed in the rest of the cases.

TP53 is one of the most widely explored genes because of its role as a tumor suppressor, playing a major role both in cancer development and progression. There were many epidemiological studies available on its genetic association, expounding the correlation of the TP53 P72R polymorphism and increased cancer risk, but their results were controversial (Anzola et al., Reference Anzola, Cuevas, Lopez-Martinez, Saiz, Burgos and de Pancorbo2003; Yoon et al., Reference Yoon, Chang, Ahn, Kim, Park, Kang, Park, Myoung, Kim do, Chon and Han2008; Di Vuolo et al., Reference Di Vuolo, Buonaguro, Izzo, Losito, Botti, Buonaguro and Tornesello2011; Sumbul et al., Reference Sumbul, Akkız, Bayram, Bekar, Akgollu and Sandıkci2012). The conflicting results may partially be due to the small sample sizes of the studies and sampling effects, because each of these studies typically involved relatively few cases and controls.

(i) Hepatocellular carcinoma

Chen et al. (Reference Chen, Liu, Li, Wei, Yan and Wen2011) studied the correlation of the TP53 R72P polymorphism and hepatocellular carcinoma (HCC) risk, including six studies. They were unable to provide any evidence of an association in Caucasians and Asians. Similar results were published in another study by Xu et al. (Reference Xu, Zheng, Dai, Du, Liu, Zhao and Li2012) based on ten case-control studies with a total of 2026 cases and 2733 controls. In subgroup analyses stratified on the basis of ethnicity, they showed that the polymorphism was associated with increased risk of HCC in Caucasians under the allelic contrast model (C vs. G, OR: 1·20, 95%CI: 1·03–1·41), homozygous model (CC vs. GG, OR: 1·74, 95%CI: 1·23–2·47) and recessive model (CC vs. CG+GG, OR: 1·85, 95%CI: 1·33–2·57). They further reported that the TP53 Arg72Pro polymorphism may have a race-specific effect on HCC risk. Lv et al. (Reference Lv, Wang, Zhou and Sun2013) performed another meta-analysis on the same topic, including 11 case-control studies with a total of 2718 cases and 3752 controls. Overall, significantly increased risk of HCC was identified among carriers of the homozygous genotype CC vs. GG (OR: 1·38, 95%CI: 1·03–1·85) and recessive model (CC vs. CG+GG, OR: 1·28, 95%CI: 1·03–1·59). In the subgroup analysis, on the basis of ethnicity, increased risk of HCC was observed in their results in Asians and Caucasians. In Asians, association was observed in the recessive model (CC vs. GG+CG, OR: 1·17, 95%CI: 1·02–1·34), while in Caucasians association was observed in the homozygous model (CC vs. GG, OR: 1·65, 95%CI: 1·07–2·56) and recessive model (CC vs. CG+GG, OR: 1·74, 95%CI: 1·14–2·66). This meta-analysis suggests that the TP53 Arg72Pro polymorphism may play a critical role in HCC development, and gender and family history may not modulate the effect of this polymorphism on HCC risk. Hu et al. (Reference Hu, Zhao, Yang and Hu2014) also examined the validity of the TP53 Arg72Pro polymorphism and its association with increased susceptibility of HCC. They identified 15 eligible studies with 3704 cases and 4559 controls, but their results did not support any association in between the Pro (C) allele and HCC risk. However, subgroup analysis showed significant associations between the G to C polymorphism and susceptibility to HCC when stratifying by race etc. In Asians, G vs. C, OR: 0·39, 95%CI: 0·36–0·41; GG vs. CC, OR: 0·85, 95%CI: 0·74–0·98; CG vs. CC, OR: 0·88, 95%CI: 0·78–1·00; GG+CG vs. CC, OR: 0·87, 95%CI: 0·78–0·98; in the Caucasian population, C vs. G, OR: 0·27, 95%CI: 0·24–0·32; GG vs. CC, OR: 0·61, 95%CI: 0·39–0·94; CG vs. CC, OR: 0·55, 95%CI; 0·35–0·87; GG+CG vs. CC, OR: 0·57, 95%CI; 0·38–0·88. This meta-analysis suggests that the TP53 Arg72Pro polymorphism may be associated with increased risk of HCC, especially in subgroup analysis of Asian and Caucasian populations.

(ii) Sarcoma

Chang and Yu (Reference Chang and Yu2014) designed a study to examine the association between the p53 codon 72 polymorphism and sarcoma risk among Caucasians. Their results did not provide any statistical evidence for significant sarcoma risk associated with the TP53 codon 72 polymorphism (G vs. C, OR: 1·03, 95%CI: 0·90–1·18; GG vs. CC, OR: 1·00, 95%CI: 0·80–1·26; GG+CG vs. CC, OR: 0·99, 95%CI; 0·83–1·19; GG vs. CG+CC, OR: 1·09, 95%CI: 0·89–1·35; CG vs. CC, OR: 0·95, 95%CI: 0·71–1·27). They also did not find any significant links in the subgroup analysis on the basis of ethnicity and sarcoma type. Their results therefore suggest that the TP53 codon 72 polymorphism may not play a role in sarcoma development in the Caucasian population.

(iii) Glioma

He et al. (Reference He, Xia, Liu, Li and Wang2013) performed a meta-analysis on the association between the TP53 codon 72 polymorphism and glioma risk, but no pronounced association was observed in their overall pooled analysis (C vs. G, OR: 1·04, 95%CI: 0·90–1·20; CC vs. GG, OR: 0·95, 95%CI: 0·80–1·14; CG vs. GG, OR: 1·01, 95%CI: 0·79–1·29; CG+CC vs. GG, OR: 1·03, 95%CI: 0·82–1·29; CC vs. GG+CG, OR: 1·02, 95%CI: 0·86–1·22). In subgroup analysis, the polymorphism was again proven to have no affect on glioma risk in population-based, hospital-based, astrocytoma and oligodendroglioma studies among Caucasians. Similar results were also produced by other researchers (Zhu et al., Reference Zhu, Lu, Li, Yao and Xu2014) in their study, performed on similar disorders (the allele contrast, OR: 1·04, 95%CI: 0·94–1·16; CC vs. GG, OR: 1·01, 95%CI: 0·83–1·22; the dominant model, OR: 1·02, 95%CI; 0·93–1·12; recessive model, OR: 1·06, 95%CI: 0·88–1·28; and the heterozygote genotypes: CG vs. GG, OR: 1·03, 95%CI: 0·90–1·17, P = 0·082). In the subgroup analysis stratified by ethnicity, neither the subjects of Asian descent nor the subjects of Caucasian descent showed any effect on glioma risk. Another meta-analysis of the same disorder and same polymorphism also showed that there is no association between the TP53 Arg72Pro polymorphism and increased risk of glioma (C vs. G, OR: 1·02, 95%CI: 0·85–1·22; CC vs. GG, OR: 1·06, 95%CI: 0·85–1·34; CC+CG vs. GG, OR: 1·07, 95%CI: 0·91–1·27), and the same results were again observed in the subgroup analysis by ethnicity especially in Caucasians. However, a slight association was recorded in the case of Asians (OR: 1·42, 95%CI: 1·00–2·02) (Zhang et al., Reference Zhang, Li, Li, Li, Sun, Li and Li2014). It can therefore be inferred that there is limited available evidence for an association between the TP53 codon 72 polymorphism and glioma risk and thus more comprehensive and systematic studies are needed to provide a more comprehensive evaluation of this polymorphism in Asians.

(iv) Urologic cancers

Li et al. (Reference Li, Wei, Jiang, Wang and Xu2010) investigated bladder cancer in their meta-analysis performed with six studies, and found that the patients had a comparatively lower frequency of CG genotypes (OR: 0·80, 95%CI: 0·64–0·99). In the subgroup analysis, Caucasian patients were found to have a higher frequency of GG (OR: 1·64, 95%CI: 1·18–2·28) than CG (OR: 0·62, 95%CI: 0·44–0·86). In another subgroup analysis on the basis of cancer stage, they further observed that the invasive bladder cancers had comparatively lower frequency of GG (OR: 0·58, 95%CI: 0·36–0·93) and higher frequency of CG (OR: 0·62, 95%CI: 0·44–0·86) than the non-invasive bladder cancers. On the basis of these results they suggested that the TP53 Arg72Pro polymorphism is significantly associated with bladder cancer and its genotypic distribution varies with the cancer stage. Another group of researchers determined more precisely the relationship between the p53 Arg72Pro polymorphism and PCa risk. Their analysis was based on 17 case-control studies involving 2371 PCa cases and 2854 controls. In the overall pooled analysis, their results showed a non-significant association between the TP53 Arg72Pro polymorphism and PCa risk in all genetic models. However, significant association was observed in Caucasians in the co-dominant (OR: 1·57, 95%CI: 1·08–2·28, P = 0·017) and recessive model (CC vs. CG+GG, OR: 1·60, 95%CI: 1·12–2·27, P = 0·009) when the included studies were limited only to those conforming the Hardy-Weinberg equilibrium (Lu et al., Reference Lu, Liu, Zeng, He, Peng, Deng, Wang, Xie, Li, Qin and Li2014). It was therefore concluded that the CC genotype of the TP53 Arg72Pro polymorphism is significantly associated with increased risk of PCa in Caucasians.

(v) Cancers of the female reproductive system

Tang et al. (Reference Tang, He, Chan and Luo2012) performed a meta-analysis to estimate any possible correlation between the TP53 Arg72Pro polymorphism and endometrial cancer. Nine published studies, with a total of 829 cases and 1387 controls, were included in the study. Their overall pooled results suggested a non-significant association between the TP53 Arg72Pro polymorphism and cancer risk, especially in Caucasians and Asians in any of the genetic models (additive model, OR: 1·027, 95%CI: 0·893–1·18, P = 0·71; recessive model, OR: 1·099, 95%CI: 0·802–1·507, P = 0·556; dominant model, OR: 1·013, 95%CI: 0·842–1·219, P = 0·89). A recent study performed by Alqumber et al. (Reference Alqumber, Akhter, Haque, Panda and Mandal2014) investigated the association between the TP53 Arg72Pro polymorphism and susceptibility to ovarian cancer. The meta-analysis, which was based on 12 studies including 993 cases and 1264 controls, showed non-significant association (C vs. G, OR: 0·980, 95%CI: 0·677–1·419; CC vs. GG, OR: 0·731, 95%CI: 0·341–1·564; CG vs. GG, OR: 1·237, 95%CI: 0·862–1·773; dominant model, OR: 1·089, 95%CI: 0·706–1·681; recessive model, OR: 0·754, 95%CI: 0·428–1·329). Similar results were recorded in the subgroup analysis stratified by ethnicity in the Caucasian population.

There are many studies available investigating the association of the TP53 Arg72Pro polymorphism and the risk of other cancers. Dai et al. (Reference Dai, Gast, Horska, Schrappe, Bartram, Hemminki, Kumar and Bermejo2009) suggested in their meta-analysis performed on 32 case-control studies that the Pro allele of the TP53 Arg72Pro polymorphism was emerging as a low-penetrance susceptibility allele for the development of lung cancer. Zhou et al. (Reference Zhou, Li, Zhuang, Liu, Wu, Yao, Du, Wei and Wu2007) observed that the TP53 Arg72Pro polymorphism was significantly associated with gastric cancer among Asians. They also suggested that variations in genotype distribution may be due to location, stage and histological differentiation. Similar results were produced in another study conducted on cervical cancer. The researchers found that the TP53 GG genotype at codon 72 did not seem to represent a risk marker for the development of cervical lesions in the majority of the European countries studied (Sousa et al., Reference Sousa, Santos, Pinto and Medeiros2007).

We tried our best to include the most recent publications in our study. Our results are consistent with those of Zhang et al. (Reference Zhang, Shao, Yu, Hua, Mi and Feng2011), who also observed non-significant association between the TP53 Pro72Arg polymorphism and overall PCa risk (allelic contrast, RR: 1·02, 95%CI: 0·96–1·09; homozygous model, RR: 1·12, 95%CI: 0·74–1·70; heterozygous model, RR: 1·22, 95%CI: 0·94–1·60; dominant model, RR: 1·05, 95%CI: 1·00–1·11; recessive model, RR: 0·96, 95%CI: 0·67–1·37). They also found the same results in a stratified analysis in all genotype models by ethnicity. Moreover, no associations of the TP53 Arg72Pro polymorphism with colorectal cancer (Dahabreh et al., Reference Dahabreh, Linardou, Bouzika, Varvarigou and Murray2010) and breast cancer (Ma et al., Reference Ma, Yang, Liu, Zhang, Yang, Wang and Qin2010) risk were observed.

The limitations of our meta-analysis include the following: (1) Some of the included studies have rather small sample sizes, which were technically not satisfactory to determine any possible association in between the TP53 Arg72Pro polymorphism and cancer risk; (2) cancer being a multi-factorial, complex disease, different interactions such as gene–gene, gene–environment and protein–protein interactions may be further evaluated to better understand the complexities in depth; and (3) the majority of the literature is focused on the association between the TP53 Arg72pro polymorphism and cancer risk, which are usually not concerned with the haplotype effects on cancer development.

In the present meta-analysis, there were 24 studies from Asians, 17 from Europe, ten from America (North and South), two from Africa and one from Australia. Pooled subgroup analysis on the basis of ethnicity showed that the TP53Arg72Pro polymorphism is associated with increased risk of cancer only in Asians and Americans but not in other populations. On the basis of our results, it can be inferred that this association is still vague in different populations, and so more studies with larger sample sizes are needed for more systematic and comprehensive assessment, especially in Asians. It can therefore be concluded that, this meta-analysis of available data suggests partial confirmation of the association between the TP53 Arg72Pro polymorphism and cancer risk susceptibility.

The authors would like to extend thanks to Ms Raisa Bano and Mr Shahid Hussain for their technical assistance.

Author contributions

All the authors were directly involved in the whole process, therefore it is disclosed that all the authors contributed equally towards the research.

Declaration of interest

None.

References

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Figure 0

Fig. 1. A general flow diagram of study identification according to MOOSE and PRISMA statement.

Figure 1

Table 1. Characteristics of case-control studies included in the meta-analysis.

Figure 2

Table 2. Pooled analysis of association of P72R (rs1042522) polymorphism and cancer risk.