# AURKA rs8173 G>C Polymorphism Decreases Wilms Tumor Risk in Chinese Children

Authors: Tongyi Lu; Li Li; Jinhong Zhu; Jiabin Liu; Ao Lin; Wen Fu; Guochang Liu; Huimin Xia; Tiesong Zhang; Jing He
Journal: Journal of Oncology
 (2019)

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## Abstract

Wilms tumor is the most common type of renal malignancy in children. Previous studies have demonstrated that single nucleotide polymorphisms (SNPs) in theAURKA gene could predispose to several human malignancies. We recruited 145 cases and 531 cancer-free controls to investigate whether AURKA gene variants modify Wilms tumor susceptibility. Three AURKA SNPs (rs1047972 C>T, rs2273535 T>A, and rs8173 G>C) were genotyped by the Taqman methodology. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the strength of association between AURKA SNPs and Wilms tumor risk. We found that only the rs8173 G>C polymorphism was significantly associated with Wilms tumor risk (GC vs. GG: adjusted OR (AOR) = 0.50, 95% CI = 0.35–0.73, P=0.0002; GC/CC vs. GG: AOR = 0.60, 95% CI = 0.42–0.88, P=0.008). Stratification analysis revealed that rs8173 GC/CC genotypes were associated with Wilms tumor risk among children aged >18 months (AOR = 0.56, 95% CI = 0.34–0.93, P=0.024), male children (AOR = 0.54, 95% CI = 0.33–0.90, P=0.017), and children with clinical stage III + IV diseases (AOR = 0.56, 95% CI = 0.35–0.90, P=0.017). Haplotype analysis indicated that the CAG haplotype was significantly associated with increased Wilms tumor risk. In conclusion, our findings indicated that the AURKA rs8173 G>C polymorphism was associated with decreased Wilms tumor risk in Chinese children.


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## Body

## 1. Introduction

Wilms tumor (WT), also known as nephroblastoma, is the most common renal malignancy in children [1, 2]. It accounts for 6% to 7% of malignant tumors in children under the age of 15 years, with an incidence rate of about 7–10 cases per million in Western countries [3]. The incidence rate of WT in Chinese is around 3.3 cases per million [4]. Over the past 20 years, because of the application of multimodality treatment, including surgery, radiotherapy, chemotherapy, and autologous stem cell transplantation, the overall survival rate of 5 years has increased from 30% to 90% [2, 5–7]. Despite the great achievements in the treatment of WT, the prognosis of nearly 25% of patients with high-risk diseases remains unsatisfying [8]. In addition, about 25% of survivors suffer from the high cost of treatment and the physical torment of some chronic conditions [9, 10].Previous studies have found that genetic factors contribute to the risk of Wilms tumor and identified a number of genes associated with WT, including Wilms’ tumor protein 1 (WT1), β-catenin, tumor protein 53 (TP53), catenin beta 1 (CTNNB1), and AMER1 [11–13]. Although recent genome-wide studies on WT have revealed some previously unknown gene mutations implicated with WT, current known genetic variants are not adequate to fully elucidate the pathogenesis of WT [14]. Therefore, it is particularly important to identify more causal genetic variants for WT.Aurora kinase A (AURKA) is located at chromosome 20q13.2, consisting of 12 exons [15]. It encodes a centrosome-related serine/threonine kinase found to be overexpressed in many human cancers, including primary colorectal carcinoma, esophageal squamous cell carcinoma, neuroblastoma, and breast and ovarian cancers [16–19]. Overexpression of AURKA leads to abnormal centrosome amplification, thereby affecting the stability of the genome and inducing tumorigenesis [16, 20]. Furthermore, inhibition of AURKA expression could result in abnormal cell mitosis, eventually leading to cell death [21–23]. Therefore, AURKA might be an attractive target for anticancer therapies [24].In addition, previous studies had found that theAURKA gene single nucleotide polymorphism (SNP) was closely related to the risk of several human malignancies [25–27]. Early research demonstrated that the AA genotype of AURKA rs2273535 T>A could increase the risk of oral cancer [28]. Studies in recent years have also found that AURKA rs2273535 T>A polymorphism could enhance the susceptibility of gastric cancer [15]. Furthermore, there were related studies reported that Caucasians carrying AURKA rs1047972 T>C had a relatively low risk of developing breast cancer [26]. However, studies regarding their association with WT risk are lacking. Therefore, we performed this case-control study with 145 cases of WT and 531 control subjects to assess the association between AURKA gene polymorphisms and WT susceptibility in Chinese children.


## 2. Materials and Methods

### 2.1. Study Subjects

In this study, a total of 145 cases of WT and 531 controls were collected from the Guangzhou Women and Children Medical Center from 2001 to 2016, as we described previously [29]. Controls were selected from those receiving routine physical examination during the same period. The cases included in this study were all sporadic and the control groups were confirmed free of history of malignancy. Both WT patients and controls were frequency-matched based on the age, gender, and ethnicity. The frequency distribution information of selected variables for WT cases and cancer-free controls was summarized in Supplementary Table 1. We obtained written informed consents from the parents or legal guardians of all subjects. The study protocol was approved by the Institutional Review Board of the Guangzhou Women and Children’s Center (Ethical Approval Number: 2018022102).


### 2.2. SNP Selection and Genotyping

The selection criteria for potentially functional polymorphisms have been described in detail previously [30]. Briefly, we choose potential functional polymorphisms in the 5′-flanking region, 5′UTR, 3′UTR, and exons of the AURKA gene. Three SNPs in the AURKA gene were finally selected (rs1047972 C>T (Assay ID: AN322ZF), rs2273535 T>A (Assay ID: C__25623289_10), and rs8173 G>C (Assay ID: C__8947675_10)). The rs1047972 C>T polymorphism may lead to amino acid alteration from Val to Ile at codon 57; the rs2273535 T>A polymorphism may lead to splicing alteration, whereas the rs8173 G>C polymorphism may lead to miRNA binding alteration. These three SNPs could capture additional fourteen SNPs (Supplementary Table 2). Moreover, there was no significant linkage disequilibrium between paired polymorphisms in Supplementary Figure 1 (rs8173/rs1047972, R2 = 0.119; rs8173/rs2273535, R2 = 0.527; rs1047972/rs2273535, R2 = 0.291) [31]. Human genomic DNA was mainly extracted from the peripheral blood samples using the TIANamp Blood DNA Kit (TianGen Biotech, Beijing, China). The mean yield of DNA was 12.21 μg (median = 6.25 μg; range = 1.08 to 60 μg), with a mean A260/A280 ratio of 1.89 (median = 1.90; range = 1.78 to 2.05). AURKA SNPs were genotyped using the ABI-7900 Sequence Detection System (Applied Biosystem, Foster City, CA) and Taqman real-time PCR, as described previously [30]. The information on all the genotyped samples for all three SNPs was summarized in Supplementary Figure 2.


### 2.3. Genotype and Gene Expression Correlation Analysis

The FAM210B mRNA expression data were retrieved for transformed fibroblasts cells with different genotypes ofAURKA SNPs from the GTEx Portal database (https://www.gtexportal.org/home/). These data were used to assess the correlation between rs8173 G>C genotypes and mRNA expression-level alteration [32].


### 2.4. Statistical Analysis

All statistical analysis of data was processed by SAS (version 9.4; SAS Institute, Cary, NC, USA). The distribution of subject characteristics between cases and controls was examined by a bilateralχ2 test. The goodness-of-chi-squared test was used to validate whether the genotype frequencies in the controls were consistent with the Hardy–Weinberg equilibrium (HWE). Multivariate logistic regression analysis was adopted to calculate the odds ratios (ORs) and 95% confidence intervals (CIs). The adjusted ORs and 95% CIs were calculated using an unconditional logistic regression model with adjustment for age and gender to assess the association between AURKA polymorphisms and WT risk. Inferred haplotypes of AURKA gene were based on observed genotypes, and adjusted ORs and 95% CIs were obtained by logistic regression models with adjustment for age and gender. P<0.05 was considered to be statistically significant.


## 2.1. Study Subjects

In this study, a total of 145 cases of WT and 531 controls were collected from the Guangzhou Women and Children Medical Center from 2001 to 2016, as we described previously [29]. Controls were selected from those receiving routine physical examination during the same period. The cases included in this study were all sporadic and the control groups were confirmed free of history of malignancy. Both WT patients and controls were frequency-matched based on the age, gender, and ethnicity. The frequency distribution information of selected variables for WT cases and cancer-free controls was summarized in Supplementary Table 1. We obtained written informed consents from the parents or legal guardians of all subjects. The study protocol was approved by the Institutional Review Board of the Guangzhou Women and Children’s Center (Ethical Approval Number: 2018022102).


## 2.2. SNP Selection and Genotyping

The selection criteria for potentially functional polymorphisms have been described in detail previously [30]. Briefly, we choose potential functional polymorphisms in the 5′-flanking region, 5′UTR, 3′UTR, and exons of the AURKA gene. Three SNPs in the AURKA gene were finally selected (rs1047972 C>T (Assay ID: AN322ZF), rs2273535 T>A (Assay ID: C__25623289_10), and rs8173 G>C (Assay ID: C__8947675_10)). The rs1047972 C>T polymorphism may lead to amino acid alteration from Val to Ile at codon 57; the rs2273535 T>A polymorphism may lead to splicing alteration, whereas the rs8173 G>C polymorphism may lead to miRNA binding alteration. These three SNPs could capture additional fourteen SNPs (Supplementary Table 2). Moreover, there was no significant linkage disequilibrium between paired polymorphisms in Supplementary Figure 1 (rs8173/rs1047972, R2 = 0.119; rs8173/rs2273535, R2 = 0.527; rs1047972/rs2273535, R2 = 0.291) [31]. Human genomic DNA was mainly extracted from the peripheral blood samples using the TIANamp Blood DNA Kit (TianGen Biotech, Beijing, China). The mean yield of DNA was 12.21 μg (median = 6.25 μg; range = 1.08 to 60 μg), with a mean A260/A280 ratio of 1.89 (median = 1.90; range = 1.78 to 2.05). AURKA SNPs were genotyped using the ABI-7900 Sequence Detection System (Applied Biosystem, Foster City, CA) and Taqman real-time PCR, as described previously [30]. The information on all the genotyped samples for all three SNPs was summarized in Supplementary Figure 2.


## 2.3. Genotype and Gene Expression Correlation Analysis

The FAM210B mRNA expression data were retrieved for transformed fibroblasts cells with different genotypes ofAURKA SNPs from the GTEx Portal database (https://www.gtexportal.org/home/). These data were used to assess the correlation between rs8173 G>C genotypes and mRNA expression-level alteration [32].


## 2.4. Statistical Analysis

All statistical analysis of data was processed by SAS (version 9.4; SAS Institute, Cary, NC, USA). The distribution of subject characteristics between cases and controls was examined by a bilateralχ2 test. The goodness-of-chi-squared test was used to validate whether the genotype frequencies in the controls were consistent with the Hardy–Weinberg equilibrium (HWE). Multivariate logistic regression analysis was adopted to calculate the odds ratios (ORs) and 95% confidence intervals (CIs). The adjusted ORs and 95% CIs were calculated using an unconditional logistic regression model with adjustment for age and gender to assess the association between AURKA polymorphisms and WT risk. Inferred haplotypes of AURKA gene were based on observed genotypes, and adjusted ORs and 95% CIs were obtained by logistic regression models with adjustment for age and gender. P<0.05 was considered to be statistically significant.


## 3. Results

### 3.1. Association betweenAURKA Gene Polymorphisms and Wilms Tumor Susceptibility

In this study, 143 cases and 531 controls were successfully genotyped. All selected SNP genotypes had a frequency distribution consistent with HWE (rs1047972 C>T,P=0.598; rs2273535 T>A, P=0.701; rs8173 G>C, P=0.272). The genotype frequencies of the case group and control group are shown in Table 1. We found rs8173 G>C polymorphism was significantly associated with decreased WT risk (GC vs. GG: adjusted OR (AOR) = 0.50, 95% CI = 0.35–0.73, P=0.0002; GC/CC vs. GG: AOR = 0.60, 95% CI = 0.42–0.88, P=0.008).Table 1
Association betweenAURKA gene polymorphisms and Wilms tumor susceptibility.
Genotype
Cases (N = 143)
Controls (N = 531)
P
a
Crude OR (95% CI)
P
Adjusted OR (95% CI)b
P
b
rs1047972 C>T (HWE = 0.598)
CC
110 (76.92)
412 (77.59)
1.00
1.00
CT
30 (20.98)
110 (20.72)
0.89 (0.57–1.39)
0.613
0.89 (0.57–1.39)
0.622
TT
3 (2.10)
9 (1.69)
1.09 (0.29–4.08)
0.898
1.10 (0.29–4.10)
0.891
Additive
0.945
1.05 (0.71–1.55)
0.809
1.04 (0.71–1.54)
0.834
Dominant
33 (23.08)
119 (22.41)
0.866
1.04 (0.67–1.61)
0.865
1.03 (0.66–1.60)
0.889
Recessive
140 (97.90)
522 (98.31)
0.746
1.24 (0.33–4.65)
0.747
1.22 (0.33–4.59)
0.764
rs2273535 T>A (HWE = 0.701)
TT
66 (46.15)
234 (44.07)
1.00
1.00
TA
65 (45.45)
234 (44.07)
0.82 (0.57–1.16)
0.263
0.82 (0.57–1.17)
0.265
AA
12 (8.39)
63 (11.86)
0.56 (0.29–1.08)
0.084
0.56 (0.29–1.08)
0.085
Additive
0.502
0.88 (0.67–1.17)
0.377
0.88 (0.67–1.17)
0.374
Dominant
77 (53.85)
297 (55.93)
0.656
0.92 (0.63–1.33)
0.656
0.92 (0.63–1.33)
0.659
Recessive
131 (91.61)
468 (88.14)
0.241
0.68 (0.36–1.30)
0.244
0.68 (0.35–1.29)
0.237
rs8173 G>C (HWE = 0.272)
GG
71 (49.65)
196 (36.91)
1.00
1.00
GC
54 (37.76)
263 (49.53)
0.51 (0.35–0.73)
0.0003
0.50 (0.35–0.73)
0.0002
CC
18 (12.59)
72 (13.56)
0.62 (0.35–1.08)
0.090
0.61 (0.35–1.08)
0.088
Additive
0.018
0.74 (0.56–0.98)
0.033
0.75 (0.56–0.99)
0.040
Dominant
72 (50.35)
335 (63.09)
0.006
0.59 (0.41–0.86)
0.006
0.60 (0.42–0.88)
0.008
Recessive
125 (87.41)
459 (86.44)
0.762
0.92 (0.53–1.60)
0.762
0.92 (0.53–1.61)
0.781
OR, odds ratio; CI, confidence interval; HWE, Hardy–Weinberg equilibrium.aχ2 test for genotype distributions between Wilms tumor patients and controls; badjusted for age and gender.


### 3.2. Stratification Analysis

Subsequently, we explored the association between rs8173 G>C polymorphism and WT risk by stratified analysis. The results of the stratified analysis were based on the age, gender, and clinical stage (Table2). We found that carriers of rs8173 GC/CC genotypes had a decreased WT risk when compared with GG genotype carriers, among children older than 18 months (AOR = 0.56, 95% CI = 0.34–0.93, P=0.024), male children (AOR = 0.54, 95% CI = 0.33–0.90, P=0.017), and those with the clinical stage III + IV diseases (AOR = 0.56, 95% CI = 0.35–0.90, P=0.017).Table 2
Stratification analysis ofAURKA rs8173 genotypes with Wilms tumor susceptibility.
Variables
rs8173 (cases/controls)
OR (95% CI)
P
AOR (95% CI)a
P
a
GG
GC/CC
Age (months)
≤18
34/97
31/136
0.65 (0.37–1.13)
0.127
0.65 (0.38–1.13)
0.128
>18
37/99
41/199
0.55 (0.33–0.91)
0.021
0.56 (0.34–0.93)
0.024
Gender
Female
31/92
33/141
0.70 (0.40–1.21)
0.199
0.70 (0.40–1.22)
0.203
Male
40/104
39/194
0.52 (0.32–0.86)
0.011
0.54 (0.33–0.90)
0.017
Clinical stages
I + II
25/196
28/335
0.66 (0.37–1.16)
0.144
0.71 (0.40–1.26)
0.245
III + IV
41/196
40/335
0.57 (0.36–0.91)
0.019
0.56 (0.35–0.90)
0.017
OR, odds ratio; CI, confidence interval; AOR, adjusted odds ratio.aAdjusted for age and gender, without the corresponding stratification factor.


### 3.3. Haplotype Analysis

Based on a combined analysis of the three SNP polymorphisms in theAURKA gene, eight haplotypes were inferred (Table 3). Compared with the reference CAC haplotype, only CAG haplotype was associated with significant increased WT risk (AOR = 1.99, 95% CI = 1.05–3.77, P=0.034).Table 3
Frequency of inferred haplotypes of theAURKA gene based on observed genotypes and their association with the risk of Wilms tumor.
Haplotypesa
Cases (n = 286)
Controls (n = 1062)
Crude OR (95% CI)
P
AOR (95% CI)b
P
b
CAC
62 (21.68)
279 (26.27)
1.00
1.00
CAG
17 (5.94)
36 (3.39)
2.00 (1.06–3.77)
0.033
1.99 (1.05–3.77)
0.034
CTC
18 (6.29)
86 (8.10)
0.89 (0.50–1.57)
0.676
0.91 (0.51–1.62)
0.748
CTG
153 (53.50)
533 (50.19)
1.21 (0.88–1.68)
0.240
1.21 (0.88–1.67)
0.249
TAC
8 (2.80)
34 (3.20)
1.00 (0.44–2.25)
0.990
0.99 (0.44–2.24)
0.983
TAG
2 (0.70)
11 (1.04)
0.77 (0.17–3.55)
0.736
0.74 (0.16–3.40)
0.694
TTC
2 (0.70)
8 (0.75)
1.06 (0.22–5.09)
0.945
1.09 (0.23–5.28)
0.913
TTG
24 (8.39)
75 (7.06)
1.35 (0.79–2.30)
0.266
1.34 (0.79–2.29)
0.279
OR, odds ratio; CI, confidence interval; AOR, adjusted odds ratio.aThe haplotype order was rs1047972, rs2273535, and rs8173; bobtained in logistic regression models with adjustment for age and gender.


### 3.4. Genotype-Based mRNA Expression Analysis

We found that the rs8173 G>C polymorphism was significantly associated with alteredAURKA gene expression in transformed fibroblast cells (P=4.3∗10−12) using data from GTEx portal (Figure 1).Figure 1
Genotype-based mRNA expression alteration in transformed fibroblasts cells forAURKA rs8173 G>C polymorphism based on data from the GTEx portal database (https://www.gtexportal.org/home/).


## 3.1. Association betweenAURKA Gene Polymorphisms and Wilms Tumor Susceptibility

In this study, 143 cases and 531 controls were successfully genotyped. All selected SNP genotypes had a frequency distribution consistent with HWE (rs1047972 C>T,P=0.598; rs2273535 T>A, P=0.701; rs8173 G>C, P=0.272). The genotype frequencies of the case group and control group are shown in Table 1. We found rs8173 G>C polymorphism was significantly associated with decreased WT risk (GC vs. GG: adjusted OR (AOR) = 0.50, 95% CI = 0.35–0.73, P=0.0002; GC/CC vs. GG: AOR = 0.60, 95% CI = 0.42–0.88, P=0.008).Table 1
Association betweenAURKA gene polymorphisms and Wilms tumor susceptibility.
Genotype
Cases (N = 143)
Controls (N = 531)
P
a
Crude OR (95% CI)
P
Adjusted OR (95% CI)b
P
b
rs1047972 C>T (HWE = 0.598)
CC
110 (76.92)
412 (77.59)
1.00
1.00
CT
30 (20.98)
110 (20.72)
0.89 (0.57–1.39)
0.613
0.89 (0.57–1.39)
0.622
TT
3 (2.10)
9 (1.69)
1.09 (0.29–4.08)
0.898
1.10 (0.29–4.10)
0.891
Additive
0.945
1.05 (0.71–1.55)
0.809
1.04 (0.71–1.54)
0.834
Dominant
33 (23.08)
119 (22.41)
0.866
1.04 (0.67–1.61)
0.865
1.03 (0.66–1.60)
0.889
Recessive
140 (97.90)
522 (98.31)
0.746
1.24 (0.33–4.65)
0.747
1.22 (0.33–4.59)
0.764
rs2273535 T>A (HWE = 0.701)
TT
66 (46.15)
234 (44.07)
1.00
1.00
TA
65 (45.45)
234 (44.07)
0.82 (0.57–1.16)
0.263
0.82 (0.57–1.17)
0.265
AA
12 (8.39)
63 (11.86)
0.56 (0.29–1.08)
0.084
0.56 (0.29–1.08)
0.085
Additive
0.502
0.88 (0.67–1.17)
0.377
0.88 (0.67–1.17)
0.374
Dominant
77 (53.85)
297 (55.93)
0.656
0.92 (0.63–1.33)
0.656
0.92 (0.63–1.33)
0.659
Recessive
131 (91.61)
468 (88.14)
0.241
0.68 (0.36–1.30)
0.244
0.68 (0.35–1.29)
0.237
rs8173 G>C (HWE = 0.272)
GG
71 (49.65)
196 (36.91)
1.00
1.00
GC
54 (37.76)
263 (49.53)
0.51 (0.35–0.73)
0.0003
0.50 (0.35–0.73)
0.0002
CC
18 (12.59)
72 (13.56)
0.62 (0.35–1.08)
0.090
0.61 (0.35–1.08)
0.088
Additive
0.018
0.74 (0.56–0.98)
0.033
0.75 (0.56–0.99)
0.040
Dominant
72 (50.35)
335 (63.09)
0.006
0.59 (0.41–0.86)
0.006
0.60 (0.42–0.88)
0.008
Recessive
125 (87.41)
459 (86.44)
0.762
0.92 (0.53–1.60)
0.762
0.92 (0.53–1.61)
0.781
OR, odds ratio; CI, confidence interval; HWE, Hardy–Weinberg equilibrium.aχ2 test for genotype distributions between Wilms tumor patients and controls; badjusted for age and gender.


## 3.2. Stratification Analysis

Subsequently, we explored the association between rs8173 G>C polymorphism and WT risk by stratified analysis. The results of the stratified analysis were based on the age, gender, and clinical stage (Table2). We found that carriers of rs8173 GC/CC genotypes had a decreased WT risk when compared with GG genotype carriers, among children older than 18 months (AOR = 0.56, 95% CI = 0.34–0.93, P=0.024), male children (AOR = 0.54, 95% CI = 0.33–0.90, P=0.017), and those with the clinical stage III + IV diseases (AOR = 0.56, 95% CI = 0.35–0.90, P=0.017).Table 2
Stratification analysis ofAURKA rs8173 genotypes with Wilms tumor susceptibility.
Variables
rs8173 (cases/controls)
OR (95% CI)
P
AOR (95% CI)a
P
a
GG
GC/CC
Age (months)
≤18
34/97
31/136
0.65 (0.37–1.13)
0.127
0.65 (0.38–1.13)
0.128
>18
37/99
41/199
0.55 (0.33–0.91)
0.021
0.56 (0.34–0.93)
0.024
Gender
Female
31/92
33/141
0.70 (0.40–1.21)
0.199
0.70 (0.40–1.22)
0.203
Male
40/104
39/194
0.52 (0.32–0.86)
0.011
0.54 (0.33–0.90)
0.017
Clinical stages
I + II
25/196
28/335
0.66 (0.37–1.16)
0.144
0.71 (0.40–1.26)
0.245
III + IV
41/196
40/335
0.57 (0.36–0.91)
0.019
0.56 (0.35–0.90)
0.017
OR, odds ratio; CI, confidence interval; AOR, adjusted odds ratio.aAdjusted for age and gender, without the corresponding stratification factor.


## 3.3. Haplotype Analysis

Based on a combined analysis of the three SNP polymorphisms in theAURKA gene, eight haplotypes were inferred (Table 3). Compared with the reference CAC haplotype, only CAG haplotype was associated with significant increased WT risk (AOR = 1.99, 95% CI = 1.05–3.77, P=0.034).Table 3
Frequency of inferred haplotypes of theAURKA gene based on observed genotypes and their association with the risk of Wilms tumor.
Haplotypesa
Cases (n = 286)
Controls (n = 1062)
Crude OR (95% CI)
P
AOR (95% CI)b
P
b
CAC
62 (21.68)
279 (26.27)
1.00
1.00
CAG
17 (5.94)
36 (3.39)
2.00 (1.06–3.77)
0.033
1.99 (1.05–3.77)
0.034
CTC
18 (6.29)
86 (8.10)
0.89 (0.50–1.57)
0.676
0.91 (0.51–1.62)
0.748
CTG
153 (53.50)
533 (50.19)
1.21 (0.88–1.68)
0.240
1.21 (0.88–1.67)
0.249
TAC
8 (2.80)
34 (3.20)
1.00 (0.44–2.25)
0.990
0.99 (0.44–2.24)
0.983
TAG
2 (0.70)
11 (1.04)
0.77 (0.17–3.55)
0.736
0.74 (0.16–3.40)
0.694
TTC
2 (0.70)
8 (0.75)
1.06 (0.22–5.09)
0.945
1.09 (0.23–5.28)
0.913
TTG
24 (8.39)
75 (7.06)
1.35 (0.79–2.30)
0.266
1.34 (0.79–2.29)
0.279
OR, odds ratio; CI, confidence interval; AOR, adjusted odds ratio.aThe haplotype order was rs1047972, rs2273535, and rs8173; bobtained in logistic regression models with adjustment for age and gender.


## 3.4. Genotype-Based mRNA Expression Analysis

We found that the rs8173 G>C polymorphism was significantly associated with alteredAURKA gene expression in transformed fibroblast cells (P=4.3∗10−12) using data from GTEx portal (Figure 1).Figure 1
Genotype-based mRNA expression alteration in transformed fibroblasts cells forAURKA rs8173 G>C polymorphism based on data from the GTEx portal database (https://www.gtexportal.org/home/).


## 4. Discussion

In this case-control study, we analyzed 143 WT patients and 531 controls to investigate the association between threeAURKA SNPs (rs1047972, rs2273535, and rs8173) and WT risk of in Chinese children. To the best of our knowledge, this is the first study to investigate the association between AURKA gene polymorphisms and WT susceptibility.Previous studies have found thatAURKA was overexpressed in several common human malignancies, which in turn promoted cell proliferation and tumor progression and metastasis [33–35]. The abnormal expression of AURKA could lead to abnormal chromosome segregation, decreased chromosome stability, and finally increase the susceptibility to malignant transformation [36]. Studies in recent years have shown that AURKA SNPs were closely related to cancer risk. An early study by Lee et al. indicated that the AURKA gene rs2273535 was associated with oral cancer risk [28]. A research by Guo et al. [37] illustrated that the rs2273535 polymorphism was closely related to the increased risk of breast cancer, especially in Asian populations. Interestingly, studies have also found that the Phe allelic variation in AURKA rs2273535 appears to prevent breast cancer in Malaysian Chinese [38]. In addition, Dai et al. [26] reported that the AURKA rs1047972 polymorphism was associated with reduced incidence of breast cancer in Caucasians. These findings suggest that the effects of AURKA SNPs might be tissue dependent and ethnicity dependent.We previously did not find a significant association betweenAURKA SNPs and neuroblastoma susceptibility [31]. Interestingly, in this study, our results showed that AURKA rs8173 G>C significantly reduced the WT risk, although no significant association was found for AURKA rs1047972 C>T and rs2273535 T>A. In addition, stratified analysis revealed that individuals carrying AURKA rs8173 GC/CC genotypes had significantly decreased susceptibility to WT in several subgroups, including older than 18 months, male, and clinical stages III + IV.A previous study showed that theAURKA rs2273535 polymorphism had a strong LD with the rs1047972 genotype. Patients with AURKA haplotype variants exhibited high kinase activity and tended to develop advanced gastric cancer more readily [39]. In this study, we found that the WT risk in individuals with rs1047972/rs2273535/rs8173 CAG haplotype almost doubled, when compared with individuals with CAC haplotype. However, there were no significant association between the other six haplotypes and the risk of WT.AURKA has been extensively investigated in neuroblastoma. ShRNA-mediated AURKA gene silencing assays have demonstrated that reducing AURKA expression would inhibit cell proliferation in neuroblastoma [40–42]. It is worth mentioning that studies also have found that overexpression or expansion of AURKA is associated with poor prognosis in a variety of cancer patients and inhibition of AURKA expression can trigger tumor cell death [21–23]. Previous studies have shown that the LIN28B-RAN-AURKA axis was involved in the development of neuroblastoma, and AURKA, as a confluence of LIN28B-RAN signaling, could further promote cell cycle progression by phosphorylating many cell cycle regulators and stabilizing N-myc protein (encoded by MYCN gene) [41, 42]. The LIN28B-RAN-AURKA-MYCN signaling cascade in the development of neuroblastoma provides a new insight into the molecular mechanism by which AURKA rs8173 reduced the risk of WT. The role of AURKA in the development of Wilms tumor is currently lacking. However, based on literature search, we found that AURKA is involved in a variety of tumors. Because of the universal contributions of AURKA in tumors, we hypothesized that AURKA might be also implicated in WT and therefore performed the current study. Based on previous reports, we speculated that the AURKA rs8173 might reduce the risk of WT by inhibiting the proliferation and migration of tumor cells through the LIN28B-RAN-AURKA-MYCN signaling pathway.Some shortcomings should be mentioned in our research. First, the study included 145 patients and 531 controls. Because of the limited sample size, some important results may be accidental. Studies with large samples are indispensible to verify our results. Second, only threeAURKA SNPs were investigated in the study. Other potentially functional AURKA gene polymorphisms should be studied in the future. Third, the genotype distribution in this hospital-based study might not represent genotype distribution across the general population, which may bias the case-control study to some extent. Finally, functional experiments should be conducted to strengthen the findings in the current study.


## 5. Conclusions

Overall, our study confirmed that theAURKA rs8173 G>C polymorphism is associated with reduced WT risk in Chinese children. In the future, multicenter collaboration is needed to further expand the sample size from different regions and different races to clarify the impact of AURKA SNPs on the risk of WT more accurately.



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*Source: 9074908-2019-09-15.xml*