Abstract

Wilms tumor is the most common renal malignancy that occurs in children. TP53 gene is considered as a tumor-suppressing gene through controlling cell growth. TP53 gene rs1042522 C>G (Arg72Pro) polymorphism is widely investigated in various types of cancers. However, it is not established if TP53 rs1042522 C>G polymorphism is a candidate variant for Wilms tumor risk. The aim of the study was to determine whether TP53 rs1042522 C>G polymorphism is responsible for the risk of Wilms tumor in Chinese children. All subjects (355 cases and 1070 controls) from four centers of China were genotyped for rs1042522 C>G polymorphism. The effect of rs1042522 C>G polymorphism on Wilms tumor prevalence was analyzed using logistic regression models. We failed to detect a significant relationship between rs1042522 C>G polymorphism and Wilms tumor risk. Further stratification analysis also could not detect a significant relationship. We conclude that TP53 rs1042522 C>G polymorphism might not have enough impact on the risk of Wilms tumor. More validation study with larger sample size will be required to better define the role of TP53 rs1042522 C>G polymorphism in Wilms tumor risk.

Introduction

Wilms tumor (nephroblastoma) is a most frequently occurring renal malignancy in children, with a prevalence of nearly 1 in 10,000 in Western countries [1–3]. In China, the incidence rate of Wilms tumor is approximately 3.3 in one million children between 2002 and 2010 [4]. Wilms tumor mirrors the different stages of kidney development and commonly presents epithelial, stromal, and blastemal (undifferentiated) components in varying proportions [5]. Wilms tumor typically develops within precursor lesions known as intralobar nephrogenic rests (ILNRs) and perilobar nephrogenic rests (PLNRs) [6]. The overall 5-year survival rate exceeds the benchmark of 90% in developed countries [7–9]. However, nearly 25% of Wilms tumor patients relapse [10,11]. Moreover, disappointing events such as 25% of survivors with severe chronic health conditions and high treatment cost await to be solved.

Nearly 98% of Wilms tumors are sporadic, whereas the rest 2% of cases have at least one relatives suffering from Wilms tumor [12]. Up to now, the major genetic knowledge of Wilms tumor was largely restricted to mutations of Wilms tumor gene 1 (WT1), Wilms tumor gene on the X chromosome (WTX), tumor protein 53 (TP53), catenin β 1 (CTNNB1), and the imprinted 11p15 region [13–15]. In addition, many novel mutations in different genes were also revealed by genomic analyses [16–20]. However, all the identified genetic variants still could not explicitly elucidate the carcinogenesis of Wilms tumor. Therefore, the present study aimed to identifying more genetic causes of Wilms tumor.

TP53 gene, a highly polymorphic gene in human cancers, is located on chromosome 17p13.1 [21]. Its encoded protein, p53 protein, is involved in various cellular activities such as cell cycle control, senescence, apoptosis, and maintenance of DNA integrity [22–26]. Evidence are emerging about the genetic impact of TP53 gene on the risk of various cancers [27]. TP53 rs1042522 C>G polymorphism ranks the most widely investigated polymorphism. However, there lacks multicenter study on the association between TP53 rs1042522 C>G polymorphism and Wilms tumor risk, except our recent investigation using relatively small sample size [28]. Considering the critical role of TP53 rs1042522 C>G polymorphism in cancer risk, we selected this polymorphism for further analyzation. The main objective of the present study was to analyze the relationship between TP53 rs1042522 C>G polymorphism and Wilms tumor risk in a much larger sample size.

Materials and methods

Study subjects

A total of 355 cases from four hospitals (Guangzhou Women and Children’s Medical Center, The First Affiliated Hospital of Zhengzhou University, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, and Second Affiliated Hospital of Xi’an Jiao Tong University) located in four different cities of China (Guangzhou, Zhengzhou, Wenzhou, and Xi’an) participated in this project. The cases were individuals diagnosed with Wilms tumor. A total of 1070 controls were enrolled randomly from those who resided in the same areas of cases at the same time [29–34]. Recruitment details of the subjects were described as previously [28,35–37]. Trained medical staff collected patients’ information on age, gender, and clinical stages. Personal written informed consent was collected prior study. The present study was approved by all the four Institutional Review Boards of the respective hospitals.

Genotyping

All subjects donated a blood sample at recruitment. DNA was then extracted from the blood sample using a TIANamp Blood DNA Kit (TianGen Biotech Co. Ltd., Beijing, China). Genotyping was conducted using TaqMan methodology as previously described [38–41]. Negative controls with water were also included to ensure genotyping accuracy. We reran 10% of samples in duplicate to test reproducibility.

Statistical analysis

The χ2 test for genotype distribution was applied to detect deviation from the Hardy–Weinberg equilibrium (HWE) in control group. Two-sided χ2 test was also performed in a case–control analysis to analyze the difference of clinical-pathologic characteristics. Wilms tumor risk was estimated as odds ratios (ORs) and 95% confidence intervals (CIs), based on unconditional logistic regression adjusted for age and gender. P<0.05 was considered as statistical significant. SAS statistical package, version 9.1 (SAS Institute, Cary, NC) was used to conduct the analyses.

Results

Population characters

The frequency distribution of selected variables of all the subjects was presented in Table 1. No significant differences of age and gender were detected between cases and controls (P=0.131 for age and P=0.182 for gender). In classified clinical stages of the cases, 33.52% were diagnosed as clinical stages I, 25.92% were as II, 22.25% were as III, 13.24% were as IV, and 5.07% were as not available (NA).

Table 1
Frequency distribution of selected variables in Wilms tumor patients and controls
Variables Cases (n=355) Controls (n=1070) P* 
 No. No.  
Age range, month 1–148.63 0.03–156 0.131 
Mean ± SD 30.67 ± 23.96 32.27 ± 26.89  
  ≤18 125 35.21 425 39.72  
  >18 230 64.79 645 60.28  
Gender     0.182 
  Female 163 45.92 448 41.87  
  Male 192 54.08 622 58.13  
Clinical stages      
  I 119 33.52    
  II 92 25.92    
  III 79 22.25    
  IV 47 13.24    
  NA 18 5.07    
Variables Cases (n=355) Controls (n=1070) P* 
 No. No.  
Age range, month 1–148.63 0.03–156 0.131 
Mean ± SD 30.67 ± 23.96 32.27 ± 26.89  
  ≤18 125 35.21 425 39.72  
  >18 230 64.79 645 60.28  
Gender     0.182 
  Female 163 45.92 448 41.87  
  Male 192 54.08 622 58.13  
Clinical stages      
  I 119 33.52    
  II 92 25.92    
  III 79 22.25    
  IV 47 13.24    
  NA 18 5.07    

Abbreviations: SD, standard deviation; NA, not available.

*

Two-sided χ2 test for distributions between Wilms tumor patients and cancer-free controls.

TP53 gene rs1042522 C>G polymorphism and Wilms tumor susceptibility

A total of 354 patients and 1069 healthy controls were successfully genotyped. The association between TP53 rs1042522 C>G polymorphism and Wilms risk was listed in Table 2. The controls were in HWE for rs1042522 C>G polymorphism (HWE = 0.331). Genotype frequencies of CC, CG, and GG genotypes among cases were 27.40%, 52.54%, and 20.06% while in controls 28.34%, 51.17%, and 20.49%, respectively. No statistically significant relationship was observed between TP53 rs1042522 C>G polymorphism and Wilms tumor risk, either adjustment for age and gender or not.

Table 2
Association between TP53 rs1042522 C>G polymorphism and Wilms tumor risk
Genotype Cases (N=354) Controls (N=1069) P* Crude OR (95% CI) P Adjusted OR (95% CI) P 
rs1042522 (HWE = 0.331) 
  CC 97 (27.40) 303 (28.34)  1.00  1.00  
  CG 186 (52.54) 547 (51.17)  1.06 (0.80–1.41) 0.676 1.06 (0.80–1.41) 0.680 
  GG 71 (20.06) 219 (20.49)  1.01 (0.71–1.44) 0.944 1.01 (0.71–1.44) 0.939 
  Additive   0.902 1.01 (0.85–1.20) 0.904 1.01 (0.85–1.20) 0.900 
  Dominant 257 (72.60) 766 (71.66) 0.732 1.05 (0.80–1.37) 0.734 1.05 (0.80–1.37) 0.733 
  Recessive 283 (79.94) 850 (79.51) 0.862 0.97 (0.72–1.31) 0.862 0.98 (0.72–1.32) 0.870 
Genotype Cases (N=354) Controls (N=1069) P* Crude OR (95% CI) P Adjusted OR (95% CI) P 
rs1042522 (HWE = 0.331) 
  CC 97 (27.40) 303 (28.34)  1.00  1.00  
  CG 186 (52.54) 547 (51.17)  1.06 (0.80–1.41) 0.676 1.06 (0.80–1.41) 0.680 
  GG 71 (20.06) 219 (20.49)  1.01 (0.71–1.44) 0.944 1.01 (0.71–1.44) 0.939 
  Additive   0.902 1.01 (0.85–1.20) 0.904 1.01 (0.85–1.20) 0.900 
  Dominant 257 (72.60) 766 (71.66) 0.732 1.05 (0.80–1.37) 0.734 1.05 (0.80–1.37) 0.733 
  Recessive 283 (79.94) 850 (79.51) 0.862 0.97 (0.72–1.31) 0.862 0.98 (0.72–1.32) 0.870 

Abbreviations: CI, confidence interval; HWE, Hardy–Weinberg equilibrium; OR, odds ratio.

*

χ2 test for genotype distributions between Wilms tumor patients and cancer-free controls.

Adjusted for age and gender.

Stratification analysis

To deeply determine whether rs1042522 C>G polymorphism influences Wilms tumor risk under certain strata, we carried out stratification analysis by age, gender, and clinical stages. Yet, we still failed to detect any positive relationship of interest among all the analyzed strata (Table 3).

Table 3
Stratification analysis of TP53 rs1042522 C>G polymorphism with Wilms tumor risk
Variables rs1042522 (Cases/Controls) Crude OR (95% CI) P Adjusted OR* (95% CI) P* 
 CC CG/GG     
Age, month 
  ≤18 35/119 90/306 1.00 (0.64–1.56) 1.000 1.00 (0.64–1.55) 0.981 
  >18 62/184 167/460 1.08 (0.77–1.51) 0.665 1.07 (0.76–1.50) 0.699 
Gender 
  Females 47/124 116/323 0.95 (0.64–1.41) 0.790 0.95 (0.64–-1.41) 0.793 
  Males 50/179 141/443 1.14 (0.79–1.64) 0.485 1.14 (0.79–1.64) 0.497 
Clinical stages 
  I 39/303 80/766 0.81 (0.54–1.22) 0.312 0.81 (0.54–1.22) 0.317 
  II 22/303 69/766 1.24 (0.75–2.04) 0.396 1.24 (0.76–2.05) 0.392 
  III 17/303 62/766 1.44 (0.83–2.51) 0.194 1.44 (0.83–2.51) 0.196 
  IV 17/303 30/766 0.70 (0.38–1.28) 0.248 0.70 (0.38–1.28) 0.243 
  I+II 61/303 149/766 0.97 (0.70–1.34) 0.836 0.97 (0.70–1.34) 0.847 
  III+IV 34/303 92/766 1.07 (0.71–1.62) 0.748 1.07 (0.70–1.62) 0.756 
Variables rs1042522 (Cases/Controls) Crude OR (95% CI) P Adjusted OR* (95% CI) P* 
 CC CG/GG     
Age, month 
  ≤18 35/119 90/306 1.00 (0.64–1.56) 1.000 1.00 (0.64–1.55) 0.981 
  >18 62/184 167/460 1.08 (0.77–1.51) 0.665 1.07 (0.76–1.50) 0.699 
Gender 
  Females 47/124 116/323 0.95 (0.64–1.41) 0.790 0.95 (0.64–-1.41) 0.793 
  Males 50/179 141/443 1.14 (0.79–1.64) 0.485 1.14 (0.79–1.64) 0.497 
Clinical stages 
  I 39/303 80/766 0.81 (0.54–1.22) 0.312 0.81 (0.54–1.22) 0.317 
  II 22/303 69/766 1.24 (0.75–2.04) 0.396 1.24 (0.76–2.05) 0.392 
  III 17/303 62/766 1.44 (0.83–2.51) 0.194 1.44 (0.83–2.51) 0.196 
  IV 17/303 30/766 0.70 (0.38–1.28) 0.248 0.70 (0.38–1.28) 0.243 
  I+II 61/303 149/766 0.97 (0.70–1.34) 0.836 0.97 (0.70–1.34) 0.847 
  III+IV 34/303 92/766 1.07 (0.71–1.62) 0.748 1.07 (0.70–1.62) 0.756 

OR, odds ratio; CI, confidence interval.

*

Adjusted for age and gender, omitting the corresponding variable.

Discussion

Here, in order to validate the role of TP53 rs1042522 C>G polymorphism on Wilms tumor risk, we conducted a four-center case–control study with 355 cases and 1070 controls in Chinese population. To our knowledge, this is by now the largest case–control study regarding the relationship between TP53 rs1042522 C>G polymorphism and Wilms tumor risk.

TP53, a tumor suppressor gene, is located on chromosome 17p13 and is 20 kb long in humans [42]. Hundreds of polymorphisms in TP53 gene have been identified to be associated with cancer risk [43]. Among them, TP53 rs1042522 C>G polymorphism ranks the most widely investigated polymorphism. The rs1042522 C>G polymorphism at codon 72 in exon 4 of the TP53 gene is the non-synonymous substitution of C>G, which results in an amino acid transversion from arginine (Arg) to proline (Pro) [44]. Such amino acid transversion alters the primary structures and consequentially biochemical functions. Experimental studies revealed that TP53 codon 72 Pro variant was related to a reduction in inducing apoptosis, while an increase in inducing cell cycle arrest [45,46].

Given the critical role of TP53 rs1042522 C>G polymorphism in carcinogenesis, many researchers attempted to elucidate their roles in certain cancer type risk. A previous study in an Indian population explored the association between TP53 gene rs1042522 C>G polymorphism and the risk of thyroid cancer. The authors found that rs1042522 C>G polymorphism conferred higher susceptibility to thyroid cancer [47]. Chen et al. [48] genotyped 168 retinoblastoma patients and 185 adult controls from China. They observed no significant difference in allele or genotypic frequencies of TP53 gene rs1042522 C>G polymorphism between cases and controls. By genotyping 288 healthy subjects and 286 neuroblastoma patients in European descent, Cattelani et al. [49] found that the TP53 gene rs1042522 C>G polymorphism had no significant impact on conferring to risk of neuroblastoma. For breast cancer, the role of TP53 gene rs1042522 C>G polymorphism vary from protective [50] to no association [51] or increase [52] in risk. The discrepancies of the above-mentioned conclusions may be attributed to the differences in cancer types, population sources, geographical environment, and sample sizes. Therefore, elucidating the exact role of TP53 rs1042522 C>G polymorphism on certain type of cancer under certain population is of great necessity.

TP53 rs1042522 C>G polymorphism in influencing Wilms tumor risk remains largely unknown. Andrade et al. [53] was the first to assess the impact of TP53 polymorphisms on risk of Wilms tumor. They found the rs1042522 C allele carriers may be associated with increased Wilms tumor risk, using 46 cases and 300 controls from Brazil. In our previous experiments, we failed to obtain evidence that TP53 rs1042522 C>G polymorphism predisposes to Wilms tumor risk [28]. Yet this previous study only included 145 Wilms tumor cases and 531 controls enrolled from one single hospital. To establish a more precise relationship between TP53 rs1042522 C>G polymorphism and Wilms tumor risk, we enlarge our sample size, with 355 cases and 1070 controls from four hospitals located in four different cities of China. Unexpectedly, we still failed to detect any significant contribution of the TP53 rs1042522 C>G polymorphism to Wilms tumor risk. Plausible interpretations of the null association include relatively small sample size and low-penetrance susceptibility of single polymorphism. We speculated that differences in the study population created a disparity between the study conducted by Andrade et al. [53] and our study.

Several limitations accompany the current article. The moderate sample size limited the statistical power to detect weak interactions. Some findings might be just due to chance, particularly for stratification analysis. All the samples were selected from Chinese Han population, and that the lack of crossing ethnicity data is just another one of the limitation of the present study. Furthermore, we only concentrated on genetic factors; analysis of environmental factors and genetic–environmental factors were not conducted. Last, the only one analyzed polymorphism here is far from enough to fully elucidate the risk of Wilms tumor.

Notwithstanding these limitations, our data provided a relative strong evidence that single TP53 gene rs1042522 C>G polymorphism may not have enough impact on the risk of Wilms tumor. Further studies into the molecular mechanisms of TP53 gene rs1042522 C>G polymorphism may provide deeper insights into the etiology of Wilms tumor.

Funding

This study was funded bygrants from the National Natural Science Foundation of China [81502187]; and Pearl River S&T Nova Program of Guangzhou [201710010086].

Competing Interests

The authors declare that there are no competing interests associated with the manuscript.

Author Contribution

All authors contributed significantly to this work. P.L., W.L., J.C., H.Z., and J.H. performed the research study and collected the data; J.H. analyzed the data; J.Z. and J.W. designed the research study; P.L. and Z.Z. wrote the paper; JH prepared all the Tables. All authors reviewed the manuscript. In addition, all authors have read and approved the manuscript.

Abbreviations

     
  • Arg

    arginine

  •  
  • CI

    confidence interval

  •  
  • CTNNB1

    catenin β 1

  •  
  • HWE

    Hardy–Weinberg equilibrium

  •  
  • ILNR

    intralobar nephrogenic rest

  •  
  • NA

    not available

  •  
  • OR

    odds ratio

  •  
  • PLNR

    perilobar nephrogenic rest

  •  
  • Pro

    proline

  •  
  • TP53

    tumor protein 53

  •  
  • WT1

    Wilms tumor gene 1

  •  
  • WTX

    Wilms tumor gene on the X chromosome

References

References
1.
Breslow
N.E.
,
Olson
J.
,
Moksness
J.
,
Beckwith
J.B.
and
Grundy
P.
(
1996
)
Familial Wilms’ tumor: a descriptive study
.
Med. Pediatr. Oncol.
27
,
398
403
[PubMed]
2.
Breslow
N.
,
Olshan
A.
,
Beckwith
J.B.
and
Green
D.M.
(
1993
)
Epidemiology of Wilms tumor
.
Med. Pediatr. Oncol.
21
,
172
181
[PubMed]
3.
Hohenstein
P.
,
Pritchard-Jones
K.
and
Charlton
J.
(
2015
)
The yin and yang of kidney development and Wilms’ tumors
.
Genes Dev.
29
,
467
482
[PubMed]
4.
Bao
P.P.
,
Li
K.
,
Wu
C.X.
,
Huang
Z.Z.
,
Wang
C.F.
et al.
(
2013
)
Recent incidences and trends of childhood malignant solid tumors in Shanghai, 2002-2010
.
Zhonghua Er Ke Za Zhi
51
,
288
294
[PubMed]
5.
Beckwith
J.B.
,
Kiviat
N.B.
and
Bonadio
J.F.
(
1990
)
Nephrogenic rests, nephroblastomatosis, and the pathogenesis of Wilms’ tumor
.
Pediatr. Pathol.
10
,
1
36
[PubMed]
6.
Charlton
J.
,
Williams
R.D.
,
Sebire
N.J.
,
Popov
S.
,
Vujanic
G.
et al.
(
2015
)
Comparative methylome analysis identifies new tumour subtypes and biomarkers for transformation of nephrogenic rests into Wilms tumour
.
Genome Med.
7
,
11
[PubMed]
7.
Sonn
G.
and
Shortliffe
L.M.
(
2008
)
Management of Wilms tumor: current standard of care
.
Nat. Clin. Pract. Urol.
5
,
551
560
[PubMed]
8.
Davidoff
A.M.
(
2009
)
Wilms’ tumor
.
Curr. Opin. Pediatr.
21
,
357
364
[PubMed]
9.
Dome
J.S.
,
Liu
T.
,
Krasin
M.
,
Lott
L.
,
Shearer
P.
et al.
(
2002
)
Improved survival for patients with recurrent Wilms tumor: the experience at St. Jude Children’s Research Hospital
.
J. Pediatr Hematol. Oncol.
4
,
192
198
10.
Malogolowkin
M.
,
Cotton
C.A.
,
Green
D.M.
,
Breslow
N.E.
,
Perlman
E.
et al.
(
2008
)
Treatment of Wilms tumor relapsing after initial treatment with vincristine, actinomycin D, and doxorubicin. A report from the National Wilms Tumor Study Group
.
Pediatr. Blood Cancer
50
,
236
241
[PubMed]
11.
Pritchard-Jones
K.
,
Moroz
V.
,
Vujanic
G.
,
Powis
M.
,
Walker
J.
et al.
(
2012
)
Treatment and outcome of Wilms’ tumour patients: an analysis of all cases registered in the UKW3 trial
.
Ann. Oncol.
23
,
2457
2463
[PubMed]
13.
Little
S.E.
,
Hanks
S.P.
,
King-Underwood
L.
,
Jones
C.
,
Rapley
E.A.
et al.
(
2004
)
Frequency and heritability of WT1 mutations in nonsyndromic Wilms’ tumor patients: a UK Children’s Cancer Study Group Study
.
J. Clin. Oncol.
22
,
4140
4146
[PubMed]
14.
Gadd
S.
,
Huff
V.
,
Huang
C.C.
,
Ruteshouser
E.C.
,
Dome
J.S.
et al.
(
2012
)
Clinically relevant subsets identified by gene expression patterns support a revised ontogenic model of Wilms tumor: a Children’s Oncology Group Study
.
Neoplasia
14
,
742
756
[PubMed]
15.
Scott
R.H.
,
Douglas
J.
,
Baskcomb
L.
,
Huxter
N.
,
Barker
K.
et al.
(
2008
)
Constitutional 11p15 abnormalities, including heritable imprinting center mutations, cause nonsyndromic Wilms tumor
.
Nat. Genet.
40
,
1329
1334
[PubMed]
16.
Gadd
S.
,
Huff
V.
,
Walz
A.L.
,
Ooms
A.
,
Armstrong
A.E.
et al.
(
2017
)
A Children’s Oncology Group and TARGET initiative exploring the genetic landscape of Wilms tumor
.
Nat. Genet.
49
,
1487
1494
[PubMed]
17.
Wegert
J.
,
Ishaque
N.
,
Vardapour
R.
,
Georg
C.
,
Gu
Z.
et al.
(
2015
)
Mutations in the SIX1/2 pathway and the DROSHA/DGCR8 miRNA microprocessor complex underlie high-risk blastemal type Wilms tumors
.
Cancer Cell
27
,
298
311
[PubMed]
18.
Torrezan
G.T.
,
Ferreira
E.N.
,
Nakahata
A.M.
,
Barros
B.D.
,
Castro
M.T.
et al.
(
2014
)
Recurrent somatic mutation in DROSHA induces microRNA profile changes in Wilms tumour
.
Nat. Commun.
5
,
4039
[PubMed]
19.
Rakheja
D.
,
Chen
K.S.
,
Liu
Y.
,
Shukla
A.A.
,
Schmid
V.
et al.
(
2014
)
Somatic mutations in DROSHA and DICER1 impair microRNA biogenesis through distinct mechanisms in Wilms tumours
.
Nat. Commun.
2
,
4802
[PubMed]
20.
Walz
A.L.
,
Ooms
A.
,
Gadd
S.
,
Gerhard
D.S.
,
Smith
M.A.
et al.
(
2015
)
Recurrent DGCR8, DROSHA, and SIX homeodomain mutations in favorable histology Wilms tumors
.
Cancer Cell
27
,
286
297
[PubMed]
21.
Pietsch
E.C.
,
Humbey
O.
and
Murphy
M.E.
(
2006
)
Polymorphisms in the p53 pathway
.
Oncogene
25
,
1602
1611
[PubMed]
22.
Vogelstein
B.
,
Lane
D.
and
Levine
A.J.
(
2000
)
Surfing the p53 network
.
Nature
408
,
307
310
[PubMed]
23.
Surget
S.
,
Khoury
M.P.
and
Bourdon
J.C.
(
2013
)
Uncovering the role of p53 splice variants in human malignancy: a clinical perspective
.
Onco Targets Ther.
7
,
57
68
[PubMed]
24.
Sharpless
N.E.
and
DePinho
R.A.
(
2002
)
p53: good cop/bad cop
.
Cell
110
,
9
12
[PubMed]
25.
Levine
A.J.
(
1997
)
p53, the cellular gatekeeper for growth and division
.
Cell
88
,
323
331
[PubMed]
26.
Bullock
A.N.
and
Fersht
A.R.
(
2001
)
Rescuing the function of mutant p53
.
Nat. Rev. Cancer
1
,
68
76
[PubMed]
27.
Whibley
C.
,
Pharoah
P.D.
and
Hollstein
M.
(
2009
)
p53 polymorphisms: cancer implications
.
Nat. Rev. Cancer
9
,
95
107
[PubMed]
28.
Fu
W.
,
Zhuo
Z.J.
,
Jia
W.
,
Zhu
J.
,
Zhu
S.B.
et al.
(
2017
)
Association between TP53 gene Arg72Pro polymorphism and Wilms’ tumor risk in a Chinese population
.
Onco. Targets Ther.
10
,
1149
1154
[PubMed]
29.
He
J.
,
Wang
F.
,
Zhu
J.
,
Zhang
R.
,
Yang
T.
et al.
(
2016
)
Association of potentially functional variants in the XPG gene with neuroblastoma risk in a Chinese population
.
J. Cell. Mol. Med.
20
,
1481
1490
[PubMed]
30.
He
J.
,
Zou
Y.
,
Wang
T.
,
Zhang
R.
,
Yang
T.
et al.
(
2017
)
Genetic variations of GWAS-Identified genes and neuroblastoma susceptibility: a replication study in Southern Chinese children
.
Transl. Oncol.
10
,
936
941
[PubMed]
31.
He
J.
,
Zou
Y.
,
Liu
X.
,
Zhu
J.
,
Zhang
J.
et al.
(
2018
)
Association of common genetic variants in Pre-microRNAs and neuroblastoma susceptibility: a two-center study in Chinese children
.
Mol. Ther. Nucleic Acids
11
,
1
8
[PubMed]
32.
Wang
J.
,
Zhuo
Z.
,
Chen
M.
,
Zhu
J.
,
Zhao
J.
et al.
(
2018
)
RAN/RANBP2 polymorphisms and neuroblastoma risk in Chinese children: a three-center case-control study
.
Aging (Albany NY)
10
,
808
818
[PubMed]
33.
Zhou
H.
,
Zhuo
Z.
,
Chen
S.
,
Zhao
J.
,
Mo
Y.
et al.
(
2018
)
Polymorphisms in MYCN gene and neuroblastoma risk in Chinese children: a 3-center case-control study
.
Cancer Manag. Res.
10
,
1807
1816
[PubMed]
34.
Cheng
J.
,
Zhuo
Z.
,
Xin
Y.
,
Zhao
P.
,
Yang
W.
et al.
(
2018
)
Relevance of XPD polymorphisms to neuroblastoma risk in Chinese children: a four-center case-control study
.
Aging (Albany NY)
10
,
1989
2000
[PubMed]
35.
Fu
W.
,
Zhu
J.
,
Xiong
S.W.
,
Jia
W.
,
Zhao
Z.
et al.
(
2017
)
BARD1 Gene Polymorphisms Confer Nephroblastoma Susceptibility
.
EBioMedicine
16
,
101
105
[PubMed]
36.
Zhu
J.
,
Fu
W.
,
Jia
W.
,
Xia
H.
,
Liu
G.C.
et al.
(
2018
)
Association between NER pathway gene polymorphisms and Wilms tumor risk
.
Mol. Ther. Nucleic Acids
12
,
854
860
[PubMed]
37.
Zhu
J.
,
Jia
W.
,
Wu
C.
,
Fu
W.
,
Xia
H.
et al.
(
2018
)
Base excision repair gene polymorphisms and Wilms tumor susceptibility
.
EBio Med.
33
,
88
93
[PubMed]
38.
He
J.
,
Qiu
L.X.
,
Wang
M.Y.
,
Hua
R.X.
,
Zhang
R.X.
et al.
(
2012
)
Polymorphisms in the XPG gene and risk of gastric cancer in Chinese populations
.
Hum. Genet.
131
,
1235
1244
[PubMed]
39.
Hua
R.X.
,
Zhuo
Z.J.
,
Shen
G.P.
,
Zhu
J.
,
Zhang
S.D.
et al.
(
2016
)
Polymorphisms in the XPC gene and gastric cancer susceptibility in a Southern Chinese population
.
Onco. Targets Ther.
9
,
5513
5519
[PubMed]
40.
Zhuo
Z.J.
,
Liu
W.
,
Zhang
J.
,
Zhu
J.
,
Zhang
R.
et al.
(
2018
)
Functional polymorphisms at ERCC1/XPF genes confer neuroblastoma risk in Chinese children
.
EBio Med.
30
,
113
119
[PubMed]
41.
Zhuo
Z.J.
,
Zhang
R.
,
Zhang
J.
,
Zhu
J.
,
Yang
T.
et al.
(
2018
)
Associations between lncRNA MEG3 polymorphisms and neuroblastoma risk in Chinese children
.
Aging (Albany NY)
10
,
481
491
[PubMed]
42.
Marcel
V.
,
Catez
F.
and
Diaz
J.J.
(
2015
)
p53, a translational regulator: contribution to its tumour-suppressor activity
.
Oncogene
34
,
5513
5523
[PubMed]
43.
Hrstka
R.
,
Coates
P.J.
and
Vojtesek
B.
(
2009
)
Polymorphisms in p53 and the p53 pathway: roles in cancer susceptibility and response to treatment
.
J. Cell. Mol. Med.
13
,
440
453
[PubMed]
44.
Matlashewski
G.J.
,
Tuck
S.
,
Pim
D.
,
Lamb
P.
,
Schneider
J.
et al.
(
1987
)
Primary structure polymorphism at amino acid residue 72 of human p53
.
Mol. Cell. Biol.
7
,
961
963
[PubMed]
45.
Pim
D.
and
Banks
L.
(
2004
)
p53 polymorphic variants at codon 72 exert different effects on cell cycle progression
.
Int. J. Cancer
108
,
196
199
[PubMed]
46.
Dumont
P.
,
Leu
J.I.
,
Della Pietra
A.C.
III
,
George
D.L.
and
Murphy
M.
(
2003
)
The codon 72 polymorphic variants of p53 have markedly different apoptotic potential
.
Nat. Genet.
33
,
357
365
[PubMed]
47.
Khan
M.S.
,
Pandith
A.A.
,
Masoodi
S.R.
,
Khan
S.H.
,
Rather
T.A.
et al.
(
2015
)
Significant association of TP53 Arg72Pro polymorphism in susceptibility to differentiated thyroid cancer
.
Cancer Biomark
15
,
459
465
[PubMed]
48.
Chen
R.
,
Liu
S.
,
Ye
H.
,
Li
J.
,
Du
Y.
et al.
(
2015
)
Association of p53 rs1042522, MDM2 rs2279744, and p21 rs1801270 polymorphisms with retinoblastoma risk and invasion in a Chinese population
.
Sci. Rep.
5
,
13300
[PubMed]
49.
Cattelani
S.
,
Ferrari-Amorotti
G.
,
Galavotti
S.
,
Defferrari
R.
,
Tanno
B.
et al.
(
2012
)
The p53 codon 72 Pro/Pro genotype identifies poor-prognosis neuroblastoma patients: correlation with reduced apoptosis and enhanced senescence by the p53-72P isoform
.
Neoplasia
14
,
634
643
[PubMed]
50.
Kalemi
T.G.
,
Lambropoulos
A.F.
,
Gueorguiev
M.
,
Chrisafi
S.
,
Papazisis
K.T.
et al.
(
2005
)
The association of p53 mutations and p53 codon 72, Her 2 codon 655 and MTHFR C677T polymorphisms with breast cancer in Northern Greece
.
Cancer Lett.
222
,
57
65
[PubMed]
51.
Baynes
C.
,
Healey
C.S.
,
Pooley
K.A.
,
Scollen
S.
,
Luben
R.N.
et al.
(
2007
)
Common variants in the ATM, BRCA1, BRCA2, CHEK2 and TP53 cancer susceptibility genes are unlikely to increase breast cancer risk
.
Breast Cancer Res.
9
,
R27
[PubMed]
52.
Huang
X.E.
,
Hamajima
N.
,
Katsuda
N.
,
Matsuo
K.
,
Hirose
K.
et al.
(
2003
)
Association of p53 codon Arg72Pro and p73 G4C14-to-A4T14 at exon 2 genetic polymorphisms with the risk of Japanese breast cancer
.
Breast Cancer
10
,
307
311
[PubMed]
53.
Andrade
R.C.
,
Cardoso
L.C.
,
Ferman
S.E.
,
Faria
P.S.
,
Seuanez
H.N.
et al.
(
2014
)
Association of TP53 polymorphisms on the risk of Wilms tumor
.
Pediatr. Blood Cancer
61
,
436
441
[PubMed]
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