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. 2013 Mar 20;5(5):1397–1402. doi: 10.3892/etm.2013.1019

p53 codon 72 polymorphism and breast cancer risk: A meta-analysis

JING HOU 1, YUAN JIANG 1, WENRU TANG 2,✉, SHUTING JIA 2,✉
PMCID: PMC3671901  PMID: 23737888

Abstract

p53 is a tumor suppressor gene and plays important roles in the etiology of breast cancer. Studies have produced conflicting results concerning the role of p53 codon 72 polymorphism (G>C) on the risk of breast cancer; therefore, a meta-analysis was performed to estimate the association between the p53 codon 72 polymorphism and breast cancer. Screening of the PubMed database was conducted to identify relevant studies. Studies containing available genotype frequencies of the p53 codon 72 polymorphism were selected and a pooled odds ratio (OR) with 95% confidence interval (CI) was used to assess the association. Sixty-one published studies, including 28,539 breast cancer patients and 32,788 controls were identified. The results suggest that variant genotypes are not associated with breast cancer risk (Pro/Pro + Arg/Pro vs. Arg/Arg: OR=1.016, 95% CI=0.931–1.11, P=0.722). The symmetric funnel plot, Egger’s test (P=0.506) and Begg’s test (P=0.921) were all suggestive of the lack of publication bias. This meta-analysis suggests that the p53 codon 72 Pro/Pro + Arg/Pro genotypes are not associated with an increased risk of breast cancer. To validate the association between the p53 codon 72 polymorphism and breast cancer, further studies with larger numbers of participants worldwide are required.

Keywords: p53, meta-analysis, breast cancer

Introduction

Breast cancer is one of the most common cancers affecting the morbidity and mortality of females worldwide (1). While numerous risk factors for breast cancer have been identified, including genetic predisposition and estrogen level, the molecular mechanisms related to breast carcinogenesis remain under analysis (2,3). Previous studies have shown alterations in cell cycle regulatory proteins in breast carcinoma, including the overexpression and increase of the cyclin genes, inactivation and deletions of the Rb gene and alterations of the p53 gene (4–6). Therefore, this disease is a result of collective alterations of oncogenes and tumor suppressor genes. It is well-known that p53, the guardian of the genome, is a stress response protein. p53 functions mainly as a tetramer transcription factor that regulates a large number of genes in response to various stresses, including ontogeny activation and DNA damage (7). p53 is involved in the pro-survival response of cell cycle arrest and DNA damage repair, as well as the pro-death response of apoptosis (8). In the case of a mutation occurring in the p53 gene, p53 may not only lose its normal functions, but also gain new abilities that promote tumorigenesis (9). p53 is the most frequently mutated gene in human tumors; >50% of tumors harbor mutations in the p53 gene (10). Besides its role as a tumor suppressor gene, aberrant p53 expression may play a significant role in regulating angiogenesis (11,12). Chromosomal aberrations and p53 protein abnormalities may be involved in malignant transformation of endometriosis in the ovary (13).

The p53 tumor suppressor gene contains 11 exons, located on chromosome 17p13. The codon 72 polymorphism (rs1042522) is located in exon 4 with a CGC to CCC transition, leading to an arginine to proline amino acid substitution in amino acid position 72 (Arg72Pro). Studies have reported that the codon 72 polymorphism is associated with a risk for the development of cancer (14). The two polymorphic variants have been shown to have not only structural differences, as reflected by distinct electrophoresis patterns of migration, but also different biological properties (15,16). A number of case-control studies have been conducted to explore the correlation between the p53 codon 72 polymorphism and breast cancer risk in humans. However, the results are inconsistent. Another problem is that these published studies have only modest sample sizes, which limits their significance. By performing a meta-analysis, a prevailing method for the quantitative summary of different results, the data may be assessed and the sample size increased to a reasonable level. In the present study, a meta-analysis was conducted to quantitatively assess the effect of the p53 codon 72 polymorphism on the risk of breast cancer.

Materials and methods

Publication search

PubMed was searched using the terms ‘p53’, ‘polymorphism’ and ‘breast cancer’ (the last search update was on May 1, 2012). The search was limited to English-language papers. Additional studies were identified by a manual search of the references of original studies. Of the studies with the same or overlapping data published by the same investigators, the most recent ones with the largest number of subjects were selected. Case-control studies containing available genotype frequencies of Arg72Pro were selected.

Statistical analysis

For the control group of each study, the allelic occurrence was considered and the observed genotype frequencies of the p53 codon 72 polymorphism were assessed for Hardy-Weinberg equilibrium using the χ2 test. The power of the correlation between the p53 codon 72 polymorphism and breast cancer risk was assessed by odds ratios (ORs) with 95% confidence intervals (CIs). The risks of breast cancer for the GC and CC genotypes, relative to the wild-type GG homozygote were assessed; then, the risks of breast cancer for GC/CC vs. GG and CC vs. GC/GG, and finally the supercilious dominant and recessive effects of the variant C allele were determined. Stratified analyses according to background, the source of controls and clinicopathological individuality were also performed. In considering the possibility of heterogeneity across the studies, an arithmetical test for heterogeneity was performed based on the Q-test. P<0.05 for the Q-test was considered to indicate a lack of heterogeneity among the studies. The summary OR estimate of each study was calculated by the random effects model (17,18). The potential for publication bias was examined by Begg’s test and Egger’s linear regression test. P<0.05 was considered to indicate a statistically significant difference (19). All statistical analyses were performed with Stata software (version 9.0; Stata Corporation, College Station, TX, USA).

Results

Sixty-one case-control studies concerning the association between p53 codon 72 polymorphism and breast cancer were identified, which included 28,539 breast cancer cases and 32,788 controls. These data were used in a meta-analysis (Table I). The sharing of genotypes in the controls of all the studies was in agreement with Hardy-Weinberg equilibrium.

Table I.

Distribution of the p53 codon 72 polymorphism for cases and controls.

Breast cancer
Control
Population First author (ref) Year Arg/Arg Arg/Pro Pro/Pro Arg/Arg Arg/Pro Pro/Pro P-valuea
Asian Kawajiri (40) 1993 5 51 37 38 165 144 0.36
Khaliq (41) 2000 13 18 10 177 321 191 0.08
Li (30) 2002 6 11 11 14 26 10 0.74
Huang (28) 2003 36 100 64 30 138 114 0.21
Katiyar (29) 2003 6 51 20 8 24 9 0.27
Mahasneh (42) 2004 8 19 16 29 51 56 0.01
Noma (43) 2004 29 69 93 31 76 111 0.00
Siddique (44) 2005 20 38 36 38 120 107 0.64
Ma (45) 2006 77 178 149 100 222 150 0.29
Gochhait (26) 2007 48 109 86 97 160 76 0.52
Khadang (37) 2007 29 109 83 40 90 75 0.17
Rajkumar (46) 2008 59 125 66 141 224 135 0.02
Zhang (34) 2007 17 45 21 33 87 47 0.52
Lum (47) 2008 88 200 105 13 38 29 0.93
Singh (48) 2008 13 45 46 12 64 29 0.01
Kazemi (49) 2009 6 30 6 0 45 12 0.00
Song (50) 2009 221 544 339 220 508 349 0.16
Koh (51) 2011 102 197 73 179 319 145 0.90
Kara (52) 2010 105 84 14 72 80 17 0.44
Leu (53) 2011 71 90 78 104 129 88 0.00
Caucasian Själander (22) 1996 24 93 95 61 253 375 0.06
Weston (33) 1997 6 27 32 3 42 72 0.28
Wang-Gohrke (54) 1998 5 46 56 21 117 167 0.93
Papadakis (55) 2000 12 10 34 6 41 12 0.00
Wang-Gohrke (32) 2002 49 221 282 40 203 300 0.49
Buyru (25) 2003 12 39 64 12 43 21 0.20
Suspitsin (56) 2003 42 203 284 27 159 207 0.63
Menzel (57) 2004 30 170 275 30 114 158 0.17
Kalemi (23) 2005 3 13 26 9 32 10 0.07
Ohayon (58) 2005 3 40 89 19 94 54 0.02
Tommiska (39) 2005 109 617 825 52 278 403 0.67
Baynes (35) 2007 148 768 1107 166 854 1177 0.52
Garcia-Closas (59) 2007 196 1021 1368 228 1249 1774 0.69
Franeková (60) 2007 8 34 49 9 55 92 0.84
Johnson (61) 2007 30 185 257 183 925 1354 0.15
Schmidt (38) 2007 618 3228 4499 511 2677 3661 0.48
Sprague (31) 2007 100 644 909 129 704 1021 0.61
Akkiprik (24) 2009 20 50 25 12 49 46 0.85
Cavallone (62) 2008 10 67 80 9 46 57 0.95
Costa (63) 2008 25 86 137 54 212 380 0.00
De Vecchi (64) 2008 15 150 185 14 131 207 0.23
Nordgard (65) 2008 5 58 46 14 34 73 0.00
Lång (66) 2009 6 45 65 5 58 79 0.15
Denisov (77) 2009 25 124 148 29 99 147 0.05
Henríquez (27) 2009 8 54 73 28 100 167 0.03
Hrstka (68) 2009 40 15 62 45 8 55 0.00
Bisof (69) 2010 11 23 61 5 42 61 0.51
Ebner (70) 2010 17 108 138 14 103 137 0.34
Kara (52) 2010 14 84 105 17 80 72 0.44
Alshatwi (71) 2012 22 52 26 32 51 17 0.66
Alawadi (72) 2011 81 200 7 50 112 26 0.00
Others Weston (33) 1997 1 9 6 4 14 12 0.98
Weston (73) 1994 7 8 3 12 16 10 0.34
Helland (74) 1998 6 40 63 13 90 122 0.50
Mabrouk (36) 2003 3 9 18 4 26 19 0.23
Damin (21) 2006 64 48 6 70 111 21 0.02
Cox (75) 2007 104 569 804 131 838 1255 0.57
Gaudet (76) 2008 46 244 288 34 138 218 0.08
Aoki (67) 2009 3 29 40 7 53 30 0.01
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a

P-value for Hardy-Weinberg equilibrium in the control group.

The results of the association between the p53 codon 72 polymorphism and breast cancer and the heterogeneity test are shown in Table II. The dominant model (Pro/Pro + Pro/Arg vs.Arg/Arg) demonstrated no significant association in Asian (OR=1.028, 95% CI=0.879–1.201, P=0.732), Caucasian (OR=1.036, 95% CI=0.927–1.159, P=0.531) or other subjects (OR=1.016, 95% CI=0.931–1.11, P=0.722).

Table II.

ORs and 95% CI for breast cancer and the p53 codon 72 polymorphism under different genetic models.

Genetic model Population Pooled OR (95% CI) P-value P-value
Heterogeneity Begg’s test Egger’s test
Additive (Pro vs. Arg) Asian 1.016 (0.958–1.077) 0.539 <0.001 0.948 0.889
Caucasian 1.002 (0.972–1.033) 0.903 <0.001 0.368 0.417
Others 0.956 (0.88–1.039) 0.288 <0.001 0.463 0.388
Overall 1 (0.975–1.026) 0.993 <0.001 0.356 0.357
Recessive (Pro/Pro vs. Arg-carriers) Asian 1.012 (0.882–1.162) 0.861 0.01 0.846 0.862
Caucasian 1.019 (0.916–1.134) 0.726 <0.001 0.486 0.602
Others 1.168 (0.852–1.602) 0.335 <0.001 1 0.356
Overall 1.029 (0.95–1.115) 0.479 <0.001 0.602 0.37
Dominant (Pro-carriers vs. Arg/Arg) Asian 1.028 (0.879–1.201) 0.732 0.012 0.506 0.921
Caucasian 1.036 (0.927–1.159) 0.531 0.035 0.773 0.599
Others 0.912 (0.651–1.277) 0.591 0.064 0.835 0.299
Overall 1.016 (0.931–1.11) 0.722 0.001 0.565 0.36
Pro/Arg vs. Arg/Arg Asian 1.027 (0.887–1.188) 0.725 0.082 0.916 0.931
Caucasian 1.045 (0.926–1.179) 0.473 0.028 0.959 0.868
Others 0.884 (0.652–1.199) 0.428 0.16 0.835 0.567
Overall 1.018 (0.933–1.111) 0.689 0.007 0.904 0.739
Pro/Pro vs. Arg/Arg Asian 1.035 (0.843–1.272) 0.74 0.001 0.248 0.829
Caucasian 1.029 (0.881–1.203) 0.717 <0.001 0.444 0.667
Others 1.021 (0.673–1.55) 0.922 0.042 0.345 0.377
Overall 1.028 (0.916–1.153) 0.639 <0.001 0.188 0.385
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OR, odds ratio; CI, confidence interval.

Discussion

Given the important roles of p53 in multiple cellular functions, including gene transcription, DNA repair and apoptosis, it is biologically plausible that p53 polymorphisms may be associated with a risk of breast cancer (20). Human breast cancer is a disease with significant clinical consequences. The mechanism of breast cancer remains relatively unknown. Single nucleotide polymorphisms (SNPs) are used as a tool to investigate genetic variations and disease susceptibility.

Although a number of previous studies have reported a significant association between the p53 codon 72 polymorphism and breast cancer risk (21–34), others have identified no such association (35–39). In order to resolve this conflict, in the current study, a meta-analysis was conducted to examine the association between a commonly studied p53 polymorphism (codon 72 G<C, Arg72Pro) and breast cancer risk. A total of 28,539 breast cancer cases and 32,788 controls from 61 studies were included in the final analysis, to derive a more precise estimation of the presence or absence of this association. The polymorphism in codon 72 of the p53 gene was identified to have no association with breast cancer risk, either when the incorporated study populations were pooled or when they were subjected to a stratified analysis consistent with background or the source of controls. The latter result suggests that differences in genetic education, living environment and sources of controls do not impact any potential association between the p53 codon 72 polymorphism and breast cancer risk. Two assets of the current study were the large number of samples included and its failure to identify a significant association in any of the genetic models tested. Nevertheless, several limitations must be acknowledged. The controls in the studies were not homogenously defined, such that the control subjects in the different studies have varying risks of evolving breast cancer. Additionally, the results obtained in the present study are based on unadjusted estimations. A more accurate analysis could be conducted if more detailed individual data were available to allow it to be adjusted according to other covariates, including premenopause, postmenopause, smoking and drinking status, basal metabolic index, family history and environmental factors.

In conclusion, this meta-analysis, with a large model size, provides a strong indication that the p53 codon 72 polymorphism is not associated with breast cancer risk. Future studies should extend this investigation by incorporating other potential risk factors for breast cancer.

Acknowledgments

This work was supported by the National Science Foundation of China (No. 31170735,81260501), the Planned Science and Technology Project of Yunnan Province (2011DH011, 2012FB134).

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