Previous studies have demonstrated that polymorphisms in the AURKA gene are associated with various types of cancer. In neuroblastoma, AURKA protein product regulates N-myc protein levels and plays a critical role in tumorigenesis. To investigate the association between three AURKA polymorphisms (rs1047972 C>T, rs2273535 T>A, and rs8173 G>C) and neuroblastoma susceptibility in Chinese populations, we performed this two-center case–control study including 393 neuroblastoma cases and 812 controls. Two study populations were recruited from two different regions in China. No significant associations were identified amongst any of the three AURKA polymorphisms and the risk of neuroblastoma. Similar observations were found in the stratified analysis. In conclusion, our results indicate that none of the AURKA polymorphisms are associated with neuroblastoma susceptibility in two distinct Chinese populations. Further studies with larger sample sizes and different ethnicities are warranted to validate our results.

Introduction

Neuroblastoma is a neuroendocrine tumor that originates from the developing sympathetic nervous system. It is the most common solid malignancy in the first year of life, accounting for approximately 15% of pediatric cancer deaths [1]. Despite remarkable advances in multimodality treatment, the survival rate for patients with high-risk tumors remains approximately 50% [1,2]. At present, the etiology of neuroblastoma remains far from clear. Genetic variations have been shown to be important factors in the origination and development of neuroblastoma [3–5]. A previous genome-wide association study (GWAS) demonstrated that common genetic variations in the BARD1 gene may contribute to the etiology of the aggressive neuroblastoma [6]. Moreover, polymorphisms in the CDKN1B gene were found to associate with neuroblastoma susceptibility [7]. Over the past years, several GWASs have identified a number of genetic alterations that not only influence neuroblastoma formation but also contribute to malignant transformation [8–10]. Single nucleotide polymorphisms (SNPs) within DDX4, HSD17B12, and DUSP12 are recurrent in low-risk neuroblastoma [11,12]. SNPs in CASC15, LMO1, and LIN28B are enriched in high-risk neuroblastoma and are correlated with neuroblastoma tumor aggressiveness [10,13,14]. Previous study demonstrated that LIN28B promotes AURKA expression via inhibition of let-7, further driving neuroblastoma oncogenesis [15].

AURKA, located at chromosome region 20q13.2, encodes a serine/threonine kinase (Aurora-A) that has been shown to play a crucial role in regulating mitosis. Overexpression of Aurora-A contributes to centrosomal duplication abnormalities, genomic instability, and the promotion of tumorigenesis [16,17]. Over the past decade, Aurora-A overexpression has been demonstrated in multiple human cancers, including primary colorectal carcinoma, esophageal squamous cell carcinoma, and breast and ovarian cancers [17–19]. And overexpression of Aurora-A is associated with advanced clinical states, worse overall survival, and shorter event-free survival in patients with neuroblastoma [20]. In addition, several studies confirmed that AURKA polymorphisms were associated with the risk of several human cancers [21–24]. To date, no study has assessed the associations between AURKA SNPs and the risk of neuroblastoma.

To evaluate the associations between the SNPs in the AURKA gene and neuroblastoma susceptibility, we conducted this case–control study with 393 neuroblastoma cases and 812 control subjects from the Chinese population.

Materials and methods

Study subjects

In the present study, a total of 393 neuroblastoma cases and 812 controls were recruited from two different regions of China [25–28]. The first population was composed of 275 neuroblastoma cases and 531 controls from the Guangzhou Women and Children’s Medical Center [29–31]. The second population consisted of 118 neuroblastoma cases and 281 controls from The First Affiliated Hospital of Zhengzhou University [32,33]. Both the cases and controls were of Chinese Han ethnicity and were genetically unrelated. The cases and controls were matched according to age, gender, and ethnicity. Neuroblastoma patients were diagnosed by biopsy and staged according to the International Neuroblastoma Staging System (INSS) [34]. The present study was approved by the Institutional Review Board of each institution. Written informed consent was acquired from the parents or guardians of each participant.

Polymorphism selection and genotyping

Polymorphisms were chosen based on the following criteria: (i) minor allele frequency >5% for CHB subjects; (ii) potentially functional as predicted by SNPinfo (http://snpinfo.niehs.nih.gov/) software; (iii) not investigated for the association with neuroblastoma susceptibility. We searched the potentially functional polymorphisms located in the 5′-flanking region, 5′ UTR, 3′ UTR, and exon of AURKA gene. Three SNPs (rs1047972 C>T, rs2273535 T>A, and rs8173 G>C) in the AURKA gene were selected (Supplementary Table S1). These three SNPs can capture additional fourteen SNPs. As shown in Supplementary Figure S1, there was no significant linkage disequilibrium between paired polymorphisms (R2 = 0.119 between rs8173 and rs1047972; R2 = 0.527 between rs8173 and rs2273535; and the R2 = 0.291 between rs1047972 and rs2273535). These SNPs were genotyped using TaqMan real-time PCR following a published protocol [35–38]. To ensure credible genotyping results, 10% of the samples were randomly selected for repeated genotyping assays, and the results were 100% concordant.

Statistical analysis

Differences in genotype frequencies as well as in demographic variables between cases and controls were compared by two-sided χ2 tests. Hardy–Weinberg equilibrium (HWE) for the genotype frequencies in controls was calculated by a goodness-of-fit χ2 test. Associations between AURKA SNPs and neuroblastoma were estimated using adjusted odds ratios (ORs) and 95% confidence intervals (CIs). We also performed analyses stratified by age, gender, tumor sites, and clinical stages. P<0.05 was considered statistically significant. All statistical tests were performed using SAS software (version 9.4; SAS Institute, Cary, NC, U.S.A.).

Results

AURKA gene polymorphisms and neuroblastoma susceptibility

In the present study, 393 cases and 812 controls were successfully genotyped. The genotype frequencies of the three AURKA polymorphisms and their associations with neuroblastoma susceptibility are summarized in Table 1. The observed genotype frequencies amongst the control subjects were in HWE (P=0.337 for the rs1047972 C>T polymorphism, P=0.174 for the rs2273535 T>A polymorphism, and P=0.506 for the rs8173 G>C polymorphism). No significant associations were identified between any of the three AURKA SNPs and the risk of neuroblastoma.

Table 1
The correlation of AURKA gene polymorphisms with neuroblastoma risk
Genotype Cases (n=393) Controls (n=812) P1 Crude OR (95% CI) P Adjusted OR (95% CI)2 P2 
rs1047972 C>T (HWE = 0.337) 
  CC 305 (77.61) 629 (77.46)  1.00  1.00  
  CT 87 (22.14) 168 (20.69)  1.07 (0.80–1.43) 0.660 1.07 (0.80–1.43) 0.671 
  TT 1 (0.25) 15 (1.85)  0.14 (0.02–1.05) 0.055 0.14 (0.02–1.04) 0.055 
Additive   0.070 0.92 (0.70–1.20) 0.535 0.92 (0.70–1.20) 0.526 
  Dominant 88 (22.39) 183 (22.54) 0.955 0.99 (0.74–1.32) 0.955 0.99 (0.74–1.32) 0.943 
  Recessive 392 (99.75) 797 (98.15) 0.024 0.14 (0.02–1.03) 0.053 0.14 (0.02–1.03) 0.053 
rs2273535 T>A (HWE = 0.174) 
  TT 182 (46.31) 377 (46.43)  1.00  1.00  
  TA 171 (43.51) 340 (41.87)  1.04 (0.81–1.35) 0.753 1.04 (0.81–1.34) 0.765 
  AA 40 (10.18) 95 (11.70)  0.87 (0.58–1.31) 0.513 0.87 (0.58–1.31) 0.511 
Additive   0.699 0.97 (0.81–1.16) 0.735 0.97 (0.81–1.16) 0.728 
  Dominant 211 (53.69) 435 (53.57) 0.969 1.01 (0.79–1.28) 0.969 1.00 (0.79–1.28) 0.981 
  Recessive 353 (89.82) 717 (88.30) 0.433 0.86 (0.58–1.26) 0.433 0.86 (0.58–1.27) 0.435 
rs8173 G>C (HWE = 0.506) 
  GG 164 (41.73) 314 (38.67)  1.00  1.00  
  GC 176 (44.78) 389 (47.91)  0.87 (0.67–1.12) 0.278 0.86 (0.67–1.12) 0.265 
  CC 53 (13.49) 109 (13.42)  0.93 (0.64–1.36) 0.711 0.93 (0.64–1.36) 0.698 
Additive   0.555 0.94 (0.78–1.12) 0.473 0.94 (0.78–1.12) 0.458 
  Dominant 229 (58.27) 498 (61.33) 0.309 0.88 (0.69–1.13) 0.309 0.88 (0.69–1.12) 0.294 
  Recessive 340 (86.51) 703 (86.58) 0.976 1.01 (0.71–1.43) 0.976 1.00 (0.71–1.43) 0.981 
Combined effect of protective genotypes3 
  0 162 (41.22) 312 (38.42)  1.00  1.00  
  1–3 231 (58.78) 500 (61.58) 0.351 0.89 (0.70–1.14) 0.351 0.89 (0.69–1.13) 0.335 
Genotype Cases (n=393) Controls (n=812) P1 Crude OR (95% CI) P Adjusted OR (95% CI)2 P2 
rs1047972 C>T (HWE = 0.337) 
  CC 305 (77.61) 629 (77.46)  1.00  1.00  
  CT 87 (22.14) 168 (20.69)  1.07 (0.80–1.43) 0.660 1.07 (0.80–1.43) 0.671 
  TT 1 (0.25) 15 (1.85)  0.14 (0.02–1.05) 0.055 0.14 (0.02–1.04) 0.055 
Additive   0.070 0.92 (0.70–1.20) 0.535 0.92 (0.70–1.20) 0.526 
  Dominant 88 (22.39) 183 (22.54) 0.955 0.99 (0.74–1.32) 0.955 0.99 (0.74–1.32) 0.943 
  Recessive 392 (99.75) 797 (98.15) 0.024 0.14 (0.02–1.03) 0.053 0.14 (0.02–1.03) 0.053 
rs2273535 T>A (HWE = 0.174) 
  TT 182 (46.31) 377 (46.43)  1.00  1.00  
  TA 171 (43.51) 340 (41.87)  1.04 (0.81–1.35) 0.753 1.04 (0.81–1.34) 0.765 
  AA 40 (10.18) 95 (11.70)  0.87 (0.58–1.31) 0.513 0.87 (0.58–1.31) 0.511 
Additive   0.699 0.97 (0.81–1.16) 0.735 0.97 (0.81–1.16) 0.728 
  Dominant 211 (53.69) 435 (53.57) 0.969 1.01 (0.79–1.28) 0.969 1.00 (0.79–1.28) 0.981 
  Recessive 353 (89.82) 717 (88.30) 0.433 0.86 (0.58–1.26) 0.433 0.86 (0.58–1.27) 0.435 
rs8173 G>C (HWE = 0.506) 
  GG 164 (41.73) 314 (38.67)  1.00  1.00  
  GC 176 (44.78) 389 (47.91)  0.87 (0.67–1.12) 0.278 0.86 (0.67–1.12) 0.265 
  CC 53 (13.49) 109 (13.42)  0.93 (0.64–1.36) 0.711 0.93 (0.64–1.36) 0.698 
Additive   0.555 0.94 (0.78–1.12) 0.473 0.94 (0.78–1.12) 0.458 
  Dominant 229 (58.27) 498 (61.33) 0.309 0.88 (0.69–1.13) 0.309 0.88 (0.69–1.12) 0.294 
  Recessive 340 (86.51) 703 (86.58) 0.976 1.01 (0.71–1.43) 0.976 1.00 (0.71–1.43) 0.981 
Combined effect of protective genotypes3 
  0 162 (41.22) 312 (38.42)  1.00  1.00  
  1–3 231 (58.78) 500 (61.58) 0.351 0.89 (0.70–1.14) 0.351 0.89 (0.69–1.13) 0.335 
1

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

2

Adjusted for age and gender.

3

Protective genotypes were rs1047972 TT, rs2273535 AA, and rs8173 GC/CC.

Stratification analysis

We then divided participants into subgroups according to age, gender, clinical stage, and site of origin. The effects of the selected polymorphisms on the risk of neuroblastoma were assessed in this stratified analysis (Table 2). The effects of combined risk genotypes on neuroblastoma risk were also assessed. However, no significant association was discovered for any of the selected polymorphisms.

Table 2
Stratification analysis for association between AURKA gene genotypes and neuroblastoma susceptibility
Variables rs1047972 (case/control) AOR (95% CI) P1 rs2273535 (case/control) AOR (95% CI) P1 rs8173 (case/control) AOR (95% CI) P1 Protective genotypes (case/control) AOR (95% CI) P1 
 CC CT/TT   TT TA/AA   GG GC/CC   1–3   
Age, months 
≤18 103/241 23/64 0.84 (0.50–1.43) 0.522 64/147 62/158 0.90 (0.60–1.37) 0.624 59/132 67/173 0.87 (0.57–1.32) 0.501 59/130 67/175 0.84 (0.56–1.28) 0.425 
>18 202/388 65/119 1.05 (0.74–1.48) 0.789 118/230 149/277 1.05 (0.78–1.41) 0.759 105/182 162/325 0.86 (0.64–1.17) 0.344 103/182 164/325 0.89 (0.66–1.21) 0.458 
Gender 
Female 130/269 38/73 1.09 (0.70–1.70) 0.715 77/161 91/181 1.06 (0.73–1.53) 0.773 67/139 101/203 1.05 (0.72–1.53) 0.821 66/138 102/204 1.06 (0.72–1.55) 0.772 
Male 175/360 50/110 0.93 (0.64–1.36) 0.711 105/216 120/254 0.97 (0.70–1.33) 0.834 97/175 128/295 0.78 (0.56–1.07) 0.123 96/174 129/296 0.78 (0.57–1.08) 0.136 
Sites of origin 
Adrenal gland 118/629 35/183 1.00 (0.66–1.51) 0.999 67/377 86/435 1.09 (0.77–1.55) 0.623 56/314 97/498 1.06 (0.74–1.51) 0.768 55/312 98/500 1.08 (0.75–1.54) 0.696 
Retroperitoneal 68/629 19/183 0.96 (0.57–1.65) 0.894 40/377 47/435 1.02 (0.75–1.59) 0.941 38/314 49/498 0.82 (0.52–1.28) 0.381 37/312 50/500 0.85 (0.54–1.33) 0.476 
Mediastinum 87/629 22/183 0.88 (0.54–1.45) 0.621 55/377 54/435 0.86 (0.58–1.28) 0.460 52/314 57/498 0.71 (0.47–1.06) 0.090 52/312 57/500 0.70 (0.47–1.04) 0.080 
Others 27/629 9/183 1.14 (0.53–2.47) 0.737 17/377 19/435 0.97 (0.50–1.89) 0.922 15/314 21/498 0.90 (0.45–1.77) 0.750 15/312 21/500 0.88 (0.45–1.75) 0.723 
Clinical stage 
I + II + 4s 131/629 31/183 0.82 (0.54–1.26) 0.367 80/377 82/435 0.90 (0.64–1.26) 0.520 77/314 85/498 0.71 (0.50–0.996) 0.047 75/312 87/500 0.74 (0.52–1.04) 0.079 
III + IV 158/629 53/183 1.14 (0.80–1.62) 0.466 93/377 118/435 1.09 (0.80–1.48) 0.573 77/314 134/498 1.07 (0.78–1.47) 0.660 77/312 134/500 1.06 (0.78–1.46) 0.699 
Variables rs1047972 (case/control) AOR (95% CI) P1 rs2273535 (case/control) AOR (95% CI) P1 rs8173 (case/control) AOR (95% CI) P1 Protective genotypes (case/control) AOR (95% CI) P1 
 CC CT/TT   TT TA/AA   GG GC/CC   1–3   
Age, months 
≤18 103/241 23/64 0.84 (0.50–1.43) 0.522 64/147 62/158 0.90 (0.60–1.37) 0.624 59/132 67/173 0.87 (0.57–1.32) 0.501 59/130 67/175 0.84 (0.56–1.28) 0.425 
>18 202/388 65/119 1.05 (0.74–1.48) 0.789 118/230 149/277 1.05 (0.78–1.41) 0.759 105/182 162/325 0.86 (0.64–1.17) 0.344 103/182 164/325 0.89 (0.66–1.21) 0.458 
Gender 
Female 130/269 38/73 1.09 (0.70–1.70) 0.715 77/161 91/181 1.06 (0.73–1.53) 0.773 67/139 101/203 1.05 (0.72–1.53) 0.821 66/138 102/204 1.06 (0.72–1.55) 0.772 
Male 175/360 50/110 0.93 (0.64–1.36) 0.711 105/216 120/254 0.97 (0.70–1.33) 0.834 97/175 128/295 0.78 (0.56–1.07) 0.123 96/174 129/296 0.78 (0.57–1.08) 0.136 
Sites of origin 
Adrenal gland 118/629 35/183 1.00 (0.66–1.51) 0.999 67/377 86/435 1.09 (0.77–1.55) 0.623 56/314 97/498 1.06 (0.74–1.51) 0.768 55/312 98/500 1.08 (0.75–1.54) 0.696 
Retroperitoneal 68/629 19/183 0.96 (0.57–1.65) 0.894 40/377 47/435 1.02 (0.75–1.59) 0.941 38/314 49/498 0.82 (0.52–1.28) 0.381 37/312 50/500 0.85 (0.54–1.33) 0.476 
Mediastinum 87/629 22/183 0.88 (0.54–1.45) 0.621 55/377 54/435 0.86 (0.58–1.28) 0.460 52/314 57/498 0.71 (0.47–1.06) 0.090 52/312 57/500 0.70 (0.47–1.04) 0.080 
Others 27/629 9/183 1.14 (0.53–2.47) 0.737 17/377 19/435 0.97 (0.50–1.89) 0.922 15/314 21/498 0.90 (0.45–1.77) 0.750 15/312 21/500 0.88 (0.45–1.75) 0.723 
Clinical stage 
I + II + 4s 131/629 31/183 0.82 (0.54–1.26) 0.367 80/377 82/435 0.90 (0.64–1.26) 0.520 77/314 85/498 0.71 (0.50–0.996) 0.047 75/312 87/500 0.74 (0.52–1.04) 0.079 
III + IV 158/629 53/183 1.14 (0.80–1.62) 0.466 93/377 118/435 1.09 (0.80–1.48) 0.573 77/314 134/498 1.07 (0.78–1.47) 0.660 77/312 134/500 1.06 (0.78–1.46) 0.699 

Abbreviation: AOR, adjusted OR.

1

Adjusted for age and gender, omitting the corresponding stratify factor.

Discussion

We conducted the present case–control study with a total of 393 neuroblastoma patients and 812 control subjects to investigate the impact of three AURKA SNPs on the risk of neuroblastoma in Chinese populations. Our data indicated that none of the selected SNPs were associated with neuroblastoma susceptibility in two independent Chinese populations. To the best of our knowledge, this is the first study to investigate the association between neuroblastoma susceptibility and polymorphisms in the AURKA gene.

AURKA has been reported to be overexpressed in several human malignancies and encodes a serine/threonine kinase that is involved in the processes of proliferation, survival, invasion, and stemness in multiple types of cancer [17]. Several studies have demonstrated that AURKA SNPs were associated with the risk of cancer [21–23]. Lee at al. [39] identified an association between a genetic variant (rs2273535) in the AURKA gene and oral cancer. A recent study has demonstrated that AURKA SNPs (rs1047972 and rs2273535) increase the risk of oral squamous cell carcinoma [40]. In Malaysian Chinese, AURKA rs2273535 protected against breast cancer [41]. A meta-analysis suggested that AURKA rs1047972 is associated with a decreased breast cancer risk in Caucasians, while AURKA rs2273535 polymorphism is associated with an increased risk of breast cancer [23]. This finding indicates that the functions of AURKA SNPs may vary depending on the types of cancer and ethnic differences.

Aurora A is responsible for stabilizating N-myc in neuroblastoma. [17,42]. A previous study demonstrated that LIN28B-RAN-AURKA axis is implicated in neuroblastoma oncogenesis. Aurora A overexpression in neuroblastoma is associated with advanced clinical states, MYCN amplification, disease relapse, and progression [43]. As a transcriptional regulator, MYCN (encoding N-myc) plays a crucial role during embryonic development. In addition, MYCN amplification, which is involved in the inhibition of both cell-cycle exit and normal differentiation, contributes to neuroblastoma initiation and progression [44–46]. Knockdown of AURKA has been shown to decrease N-myc protein levels and neuroblastoma cell proliferation [47]. However, we failed to detect any significant association between these AURKA SNPs (rs1047972 C>T, rs2273535 T>A, and rs8173 G>C) and neuroblastoma susceptibility in the present study. The negative results might be attributed to the limited sample size. The relatively small sample size might not be large enough to detect an association.

Several limitations in our study should be mentioned. First, the sample size in the present study might not be large enough to draw accurate conclusions. Increasing the sample size would increase the power to detect risk variants and increase the credibility of any observed associations. Analyses with large sample sizes are essential to verify our results. Second, the etiology of neuroblastoma is complex and multifactorial. Several important factors such as dietary intake and living environment contribute to neuroblastoma pathogenesis. The results should be explained with caution, because these confounding factors were not included in the current study. Third, only three AURKA SNPs were investigated in our study. Other polymorphisms in the AURKA gene should be investigated in future study. Fourth, the genotype distribution in this hospital-based study may not reflect that in the general population, which would inevitably result in selection bias.

In summary, our study confirmed that none of the AURKA polymorphisms (rs1047972 C>T, rs2273535 T>A, and rs8173 G>C) were associated with neuroblastoma susceptibility in two distinct Chinese populations. Future studies with larger sample sizes and different ethnicities are required to further clarify the effect of AURKA SNPs on the risk of neuroblastoma.

Funding

This work was supported by the Pearl River S&T Nova Programme of Guangzhou [grant number 201710010086]; and the State Clinical Key Specialty Construction Project (Paediatric Surgery) 2013 [grant number GJLCZD1301].

Competing interests

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

Author contribution

All authors contributed significantly to this work: J.T., J. Zhang, F.-H.W., J.-H.Z., J.-H.L., H.W., and J.H. performed the research study and collected the data. J.H. and Y.Q. analyzed the data; H.X., J.H., and W.L. designed the research study. J.T. and J. Zhu wrote the paper. J.H. prepared all the tables. All authors reviewed the manuscript. In addition, all the authors read and approved the manuscript.

Abbreviations

     
  • GWAS

    genome-wide association study

  •  
  • HWE

    Hardy–Weinberg equilibrium

  •  
  • SNP

    single nucleotide polymorphism

References

References
1
Maris
J.M.
(
2010
)
Recent advances in neuroblastoma
.
N. Engl. J. Med.
362
,
2202
2211
[PubMed]
2
Matthay
K.K.
,
Reynolds
C.P.
,
Seeger
R.C.
,
Shimada
H.
,
Adkins
E.S.
et al
(
2009
)
Long-term results for children with high-risk neuroblastoma treated on a randomized trial of myeloablative therapy followed by 13-cis-retinoic acid: a children’s oncology group study
.
J. Clin. Oncol.
27
,
1007
1013
[PubMed]
3
Capasso
M.
,
Diskin
S.
,
Cimmino
F.
,
Acierno
G.
,
Totaro
F.
et al
(
2014
)
Common genetic variants in NEFL influence gene expression and neuroblastoma risk
.
Cancer Res.
74
,
6913
6924
[PubMed]
4
Capasso
M.
and
Diskin
S.J.
(
2010
)
Genetics and genomics of neuroblastoma
.
Cancer Treat. Res.
155
,
65
84
[PubMed]
5
Oldridge
D.A.
,
Wood
A.C.
,
Weichert-Leahey
N.
,
Crimmins
I.
,
Sussman
R.
et al
(
2015
)
Genetic predisposition to neuroblastoma mediated by a LMO1 super-enhancer polymorphism
.
Nature
528
,
418
421
[PubMed]
6
Capasso
M.
,
Devoto
M.
,
Hou
C.
,
Asgharzadeh
S.
,
Glessner
J.T.
et al
(
2009
)
Common variations in BARD1 influence susceptibility to high-risk neuroblastoma
.
Nat. Genet.
41
,
718
723
[PubMed]
7
Capasso
M.
,
McDaniel
L.D.
,
Cimmino
F.
,
Cirino
A.
,
Formicola
D.
et al
(
2017
)
The functional variant rs34330 of CDKN1B is associated with risk of neuroblastoma
.
J. Cell. Mol. Med.
21
,
3224
3230
[PubMed]
8
Bosse
K.R.
,
Diskin
S.J.
,
Cole
K.A.
,
Wood
A.C.
,
Schnepp
R.W.
et al
(
2012
)
Common variation at BARD1 results in the expression of an oncogenic isoform that influences neuroblastoma susceptibility and oncogenicity
.
Cancer Res.
72
,
2068
2078
[PubMed]
9
Russell
M.R.
,
Penikis
A.
,
Oldridge
D.A.
,
Alvarez-Dominguez
J.R.
,
McDaniel
L.
et al
(
2015
)
CASC15-S is a tumor suppressor lncRNA at the 6p22 neuroblastoma susceptibility locus
.
Cancer Res.
75
,
3155
3166
[PubMed]
10
Wang
K.
,
Diskin
S.J.
,
Zhang
H.
,
Attiyeh
E.F.
,
Winter
C.
et al
(
2011
)
Integrative genomics identifies LMO1 as a neuroblastoma oncogene
.
Nature
469
,
216
220
[PubMed]
11
Bagatell
R.
and
Cohn
S.L.
(
2016
)
Genetic discoveries and treatment advances in neuroblastoma
.
Curr. Opin. Pediatr.
28
,
19
25
[PubMed]
12
Nguyen
L.B.
,
Diskin
S.J.
,
Capasso
M.
,
Wang
K.
,
Diamond
M.A.
et al
(
2011
)
Phenotype restricted genome-wide association study using a gene-centric approach identifies three low-risk neuroblastoma susceptibility loci
.
PLoS Genet.
7
,
e1002026
[PubMed]
13
Diskin
S.J.
,
Capasso
M.
,
Schnepp
R.W.
,
Cole
K.A.
,
Attiyeh
E.F.
et al
(
2012
)
Common variation at 6q16 within HACE1 and LIN28B influences susceptibility to neuroblastoma
.
Nat. Genet.
44
,
1126
1130
[PubMed]
14
Newman
E.A.
and
Nuchtern
J.G.
(
2016
)
Recent biologic and genetic advances in neuroblastoma: Implications for diagnostic, risk stratification, and treatment strategies
.
Semin. Pediatr. Surg.
25
,
257
264
[PubMed]
15
Schnepp
R.W.
,
Khurana
P.
,
Attiyeh
E.F.
,
Raman
P.
,
Chodosh
S.E.
et al
(
2015
)
A LIN28B-RAN-AURKA signaling network promotes neuroblastoma tumorigenesis
.
Cancer Cell
28
,
599
609
[PubMed]
16
Ewart-Toland
A.
,
Briassouli
P.
,
de Koning
J.P.
,
Mao
J.H.
,
Yuan
J.W.
et al
(
2003
)
Identification of Stk6/STK15 as a candidate low-penetrance tumor-susceptibility gene in mouse and human
.
Nat. Genet.
34
,
403
412
[PubMed]
17
Yan
M.
,
Wang
C.
,
He
B.
,
Yang
M.
,
Tong
M.
et al
(
2016
)
Aurora-A kinase: a potent oncogene and target for cancer therapy
.
Med. Res. Rev.
36
,
1036
1079
[PubMed]
18
Bischoff
J.R.
,
Anderson
L.
,
Zhu
Y.
,
Mossie
K.
,
Ng
L.
et al
(
1998
)
A homologue of Drosophila aurora kinase is oncogenic and amplified in human colorectal cancers
.
EMBO J.
17
,
3052
3065
[PubMed]
19
Tong
T.
,
Zhong
Y.
,
Kong
J.
,
Dong
L.
,
Song
Y.
et al
(
2004
)
Overexpression of Aurora-A contributes to malignant development of human esophageal squamous cell carcinoma
.
Clin. Cancer Res.
10
,
7304
7310
[PubMed]
20
Ramani
P.
,
Nash
R.
and
Rogers
C.A.
(
2015
)
Aurora kinase A is superior to Ki67 as a prognostic indicator of survival in neuroblastoma
.
Histopathology
66
,
370
379
[PubMed]
21
Xu
L.
,
Zhou
X.
,
Jiang
F.
and
Yin
R.
(
2014
)
STK15 rs2273535 polymorphism and cancer risk: a meta-analysis of 74,896 subjects
.
Cancer Epidemiol.
38
,
111
117
[PubMed]
22
Qin
J.
,
He
X.F.
,
Wei
W.
,
Liu
Z.Z.
,
Xie
J.J.
et al
(
2015
)
Association between the STK15 polymorphisms and risk of cancer: a meta-analysis
.
Mol. Genet. Genomics
290
,
97
114
[PubMed]
23
Dai
Z.J.
,
Kang
H.F.
,
Wang
X.J.
,
Shao
Y.P.
,
Lin
S.
et al
(
2014
)
Association between genetic polymorphisms in AURKA (rs2273535 and rs1047972) and breast cancer risk: a meta-analysis involving 37,221 subjects
.
Cancer Cell Int.
14
,
91
[PubMed]
24
Wang
B.
,
Hsu
C.J.
,
Chou
C.H.
,
Lee
H.L.
,
Chiang
W.L.
et al
(
2018
)
Variations in the AURKA gene: biomarkers for the development and progression of hepatocellular carcinoma
.
Int. J. Med. Sci.
15
,
170
175
[PubMed]
25
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
26
Zhang
Z.
,
Chang
Y.
,
Jia
W.
,
Zhang
J.
,
Zhang
R.
et al
(
2018
)
LINC00673 rs11655237 C>T confers neuroblastoma susceptibility in Chinese population
.
Biosci. Rep.
38
,
27
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.
,
28
Yang
X.
,
He
J.
,
Chang
Y.
,
Luo
A.
,
Zhang
J.
et al
(
2018
)
HOTAIR gene polymorphisms contribute to increased neuroblastoma susceptibility in Chinese children
.
Cancer
,
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.
,
Wang
F.
,
Zhu
J.
,
Zhang
Z.
,
Zou
Y.
et al
(
2017
)
The TP53 gene rs1042522 C>G polymorphism and neuroblastoma risk in Chinese children
.
Aging (Albany N.Y.)
9
,
852
859
[PubMed]
31
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]
32
Zhang
J.
,
Zhuo
Z.J.
,
Wang
J.
,
He
J.
,
Yang
L.
et al
(
2017
)
CASC15 gene polymorphisms reduce neuroblastoma risk in Chinese children
.
Oncotarget
8
,
91343
91349
[PubMed]
33
Zhang
J.
,
Lin
H.
,
Wang
J.
,
He
J.
,
Zhang
D.
et al
(
2017
)
LMO1 polymorphisms reduce neuroblastoma risk in Chinese children: a two-center case-control study
.
Oncotarget
8
,
65620
65626
[PubMed]
34
Brodeur
G.M.
,
Pritchard
J.
,
Berthold
F.
,
Carlsen
N.L.
,
Castel
V.
et al
(
1993
)
Revisions of the international criteria for neuroblastoma diagnosis, staging, and response to treatment
.
J. Clin. Oncol.
11
,
1466
1477
[PubMed]
35
Gong
J.
,
Tian
J.
,
Lou
J.
,
Wang
X.
,
Ke
J.
et al
(
2017
)
A polymorphic MYC response element in KBTBD11 influences colorectal cancer risk, especially in interaction with a MYC regulated SNP rs6983267
.
Ann Oncol.
,
36
Li
J.
,
Zou
L.
,
Zhou
Y.
,
Li
L.
,
Zhu
Y.
et al
(
2017
)
A low-frequency variant in SMAD7 modulates TGF-beta signaling and confers risk for colorectal cancer in Chinese population
.
Mol. Carcinog.
56
,
1798
1807
[PubMed]
37
Lou
J.
,
Gong
J.
,
Ke
J.
,
Tian
J.
,
Zhang
Y.
et al
(
2017
)
A functional polymorphism located at transcription factor binding sites, rs6695837 near LAMC1 gene, confers risk of colorectal cancer in Chinese populations
.
Carcinogenesis
38
,
177
183
[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
Lee
C.P.
,
Chiang
S.L.
,
Lee
C.H.
,
Tsai
Y.S.
,
Wang
Z.H.
et al
(
2015
)
AURKA Phe31Ile polymorphism interacted with use of alcohol, betel quid, and cigarettes at multiplicative risk of oral cancer occurrence
.
Clin. Oral Investig.
19
,
1825
1832
[PubMed]
40
Chou
C.H.
,
Chou
Y.E.
,
Chuang
C.Y.
,
Yang
S.F.
and
Lin
C.W.
(
2017
)
Combined effect of genetic polymorphisms of AURKA and environmental factors on oral cancer development in Taiwan
.
PLoS ONE
12
,
e0171583
[PubMed]
41
Chong
E.T.
,
Goh
L.P.
,
See
E.U.
,
Chuah
J.A.
,
Chua
K.H.
et al
(
2016
)
Association of CYP2E1, STK15 and XRCC1 polymorphisms with risk of breast cancer in Malaysian women
.
Asian Pac. J. Cancer Prev.
17
,
647
653
[PubMed]
42
Otto
T.
,
Horn
S.
,
Brockmann
M.
,
Eilers
U.
,
Schuttrumpf
L.
et al
(
2009
)
Stabilization of N-Myc is a critical function of Aurora A in human neuroblastoma
.
Cancer Cell
15
,
67
78
[PubMed]
43
Shang
X.
,
Burlingame
S.M.
,
Okcu
M.F.
,
Ge
N.
,
Russell
H.V.
et al
(
2009
)
Aurora A is a negative prognostic factor and a new therapeutic target in human neuroblastoma
.
Mol. Cancer Ther.
8
,
2461
2469
[PubMed]
44
Grimmer
M.R.
and
Weiss
W.A.
(
2006
)
Childhood tumors of the nervous system as disorders of normal development
.
Curr. Opin. Pediatr.
18
,
634
638
[PubMed]
45
Ruiz-Perez
M.V.
,
Henley
A.B.
and
Arsenian-Henriksson
M.
(
2017
)
The MYCN protein in health and disease
.
Genes
8
,
E113
[PubMed]
46
Valter
K.
,
Zhivotovsky
B.
and
Gogvadze
V.
(
2018
)
Cell death-based treatment of neuroblastoma
.
Cell Death Dis.
9
,
113
[PubMed]
47
Romain
C.
,
Paul
P.
,
Kim
K.W.
,
Lee
S.
,
Qiao
J.
et al
(
2014
)
Targeting Aurora kinase-A downregulates cell proliferation and angiogenesis in neuroblastoma
.
J. Pediatr. Surg.
49
,
159
165
[PubMed]

Author notes

*

These authors contributed equally to this work.

This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).

Supplementary data