Skip to main content
Oncotarget logoLink to Oncotarget
. 2017 Aug 7;8(39):65620–65626. doi: 10.18632/oncotarget.20018

LMO1 polymorphisms reduce neuroblastoma risk in Chinese children: a two-center case-control study

Jiao Zhang 1,*, Huiran Lin 3,*, Jiaxiang Wang 1, Jing He 2, Da Zhang 1, Pan Qin 1, Lin Yang 1, Lizhao Yan 1
PMCID: PMC5630358  PMID: 29029458

Abstract

Previous genome-wide association and validation studies suggest that LIM domain only 1 (LMO1) gene polymorphisms affect neuroblastoma susceptibility. In this work, we used Taqman methodology to genotype four LMO1 polymorphisms (rs110419 A > G, rs4758051 G > A, rs10840002 A > G and rs204938 A > G) in 118 neuroblastoma cases and 281 controls from Northern China. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the association. We found that rs4758051 G > A was associated with a decreased neuroblastoma risk (AA vs. GG: adjusted OR = 0.28, 95% CI = 0.13–0.62; AG/AA vs. GG: adjusted OR = 0.62, 95% CI = 0.40–0.97; AA vs. GG/AG: adjusted OR = 0.33, 95% CI = 0.15–0.69). Likewise, carrying the rs10840002 G allele was also associated with a decreased neuroblastoma risk in this Northern Chinese population. In a combination analysis using Southern and Northern Chinese populations, we found that those carrying the rs110419 G, rs4758051 A or rs10840002 G allele were at decreased neuroblastoma risk, and this finding was supported by a false-positive report probability analysis. These results further verify that LMO1 polymorphisms are protective against neuroblastoma. Case-control studies with larger samples and using other ethnicities are still needed to confirm our conclusion.

Keywords: LMO1, neuroblastoma, GWAS, polymorphism, susceptibility

INTRODUCTION

Neuroblastoma is a common solid tumor derived from primordial sympathetic neural precursors and has complicated clinical manifestations [1]. Around the world, it ranks as the third leading cause of cancer-related death in children [2]. In China, neuroblastoma accounts for nearly 10% of childhood tumors, and its incidence is about 7.7 cases per million [3]. Despite great achievements in multimodality treatment, the 5-year survival rate for neuroblastoma remains at less than 40% [4]. Moreover, due to their chronic health conditions, survivors have difficulty finding marriage partners and employment [5]. Thus, neuroblastoma remains a great burden for the affected children and for their families and society [6].

The etiology of neuroblastoma is not yet fully understood, and the risk factors affecting the susceptibility to neuroblastoma have not been well documented [7]. Epidemiological studies suggest children may be more susceptible to neuroblastoma if their parents were exposed to environmental risk factors, including radiation sources, wood dust and hydrocarbons [8, 9]. However, most children whose parents are exposed to environmental risk factors do not develop neuroblastoma [10]. Mounting evidence suggests genetic polymorphisms may somehow influence the predisposition to neuroblastoma [1115].

The LIM domain only 1 (LMO1) gene is located on chromosome 11p15 and encodes an intertwining LIM-only transcriptional regulator [16]. LMO1 is a member of the LMO gene family [17, 18] and is highly expressed in bone marrow and the nervous system [19], though it was first identified at human T cell acute lymphoblastic leukemia chromosomal translocations [20]. LMO1 protein has been implicated in the initiation and development of several cancers [18]. In addition, LMO1 gene single nucleotide polymorphisms (SNPs) reportedly affect susceptibility to acute lymphoblastic leukemia [21] and neuroblastoma [16].

We previously investigated the association between LMO1 polymorphisms and neuroblastoma risk in a Southern Chinese population [22]. Given the likely genetic variation across different regions, the respective roles of genetic factors in neuroblastoma risk may differ. Therefore, to further confirm the relationship between LMO1 polymorphisms and neuroblastoma risk, we performed the current hospital-based case-control study using subjects from Northern China.

RESULTS

Population characteristics

The demographic characteristics of the included 118 cases and 281 controls are summarized in Supplementary Table 1. No significant differences were observed in the age (P = 0.189) or gender (P = 0.196) distribution between cases and controls. According to the INSS criteria [23], 15 (12.82%) patients were classified as stage I, 31 (26.50%) as stage II, 19 (16.24%) as stage III, 49 (41.88%) as stage IV, and 3 (2.56%) as stage 4s neuroblastoma. Among these, 89 (75.42%) tumors originated in the adrenal gland, 19 (16.10%) in the mediastinum, and 10 (8.47%) and other regions.

LMO1 polymorphisms and neuroblastoma risk in Northern Chinese children

The genotype frequencies of the four LMO1 polymorphisms and their associations with neuroblastoma risk are listed in Table 1. Among the controls, all four tested SNPs were in Hardy-Weinberg equilibrium (all PHWE > 0.05). Moreover, the analyses indicated that carrying the rs4758051 A allele had a protective effect against developing neuroblastoma (AA vs. GG: adjusted odds ratio (OR) = 0.28, 95% confidence interval (CI) = 0.13–0.62, P = 0.002; AG/AA vs. GG: adjusted OR = 0.62, 95% CI = 0.40–0.97, P = 0.035; AA vs. GG/AG: adjusted OR = 0.33, 95% CI = 0.15–0.69, P = 0.003). Similarly, we found that carrying the rs10840002 G allele was associated with a decreased risk of neuroblastoma (GG vs. AA: adjusted OR = 0.42, 95% CI = 0.21–0.85, P = 0.016; GG vs. AG/AA: adjusted OR = 0.48, 95% CI = 0.26–0.91, P = 0.025). However, we failed to detect an association between the rs110419 A > G or rs204938 A > G polymorphism and neuroblastoma risk, whether or not adjusted for age and sex.

Table 1. Association of LMO1 polymorphisms with neuroblastoma susceptibility in children from Henan province.

Genotype Cases (N = 118) Controls (N = 281) P a Crude OR (95% CI) P Adjusted OR (95% CI)b Pb
rs110419 (HWE = 0.677)
 AA 47 (39.83) 86 (30.60) 1.00 1.00
 AG 54 (45.76) 142 (50.53) 0.70 (0.43–1.12) 0.134 0.69 (0.43–1.11) 0.122
 GG 17 (14.41) 53 (18.86) 0.59 (0.31–1.13) 0.109 0.57 (0.30–1.09) 0.090
 Additive 0.179 0.75 (0.55–1.03) 0.074 0.74 (0.54–1.01) 0.060
 Dominant 71 (60.17) 195 (69.40) 0.074 0.67 (0.43–1.04) 0.075 0.65 (0.42–1.03) 0.064
 Recessive 101 (85.59) 228 (81.04) 0.286 0.72 (0.40–1.31) 0.287 0.71 (0.39–1.28) 0.253
rs4758051 (HWE = 0.946)
 GG 50 (42.37) 88 (31.32) 1.00 1.00
 AG 59 (50.00) 138 (49.11) 0.75 (0.47–1.19) 0.228 0.76 (0.48–1.21) 0.252
 AA 9 (7.63) 55 (19.57) 0.29 (0.13–0.63) 0.002 0.28 (0.13–0.62) 0.002
 Additive 0.006 0.60 (0.43–0.84) 0.003 0.60 (0.43–0.83) 0.002
 Dominant 68 (57.63) 193 (68.68) 0.034 0.62 (0.40–0.97) 0.035 0.62 (0.40–0.97) 0.035
 Recessive 109 (92.37) 226 (80.43) 0.003 0.34 (0.16–0.71) 0.004 0.33 (0.15–0.69) 0.003
rs10840002 (HWE = 0.620)
 AA 42 (35.59) 78 (27.76) 1.00 1.00
 AG 62 (52.54) 144 (51.25) 0.80 (0.50–1.29) 0.360 0.81 (0.50–1.31) 0.389
 GG 14 (11.86) 59 (21.00) 0.44 (0.22–0.88) 0.021 0.42 (0.21–0.85) 0.016
 Additive 0.064 0.69 (0.50–0.95) 0.025 0.68 (0.50–0.94) 0.021
 Dominant 76 (64.41) 203 (72.24) 0.119 0.70 (0.44–1.10) 0.120 0.69 (0.44–1.10) 0.119
 Recessive 104 (88.14) 222 (79.00) 0.031 0.51 (0.27–0.95) 0.034 0.48 (0.26–0.91) 0.025
rs204938 (HWE = 0.687)
 AA 77 (65.25) 168 (59.79) 1.00 1.00
 AG 36 (30.51) 97 (34.52) 0.81 (0.51–1.29) 0.377 0.82 (0.51–1.32) 0.415
 GG 5 (4.24) 16 (5.69) 0.68 (0.24–1.93) 0.470 0.70 (0.25–1.98) 0.499
 Additive 0.565 0.82 (0.56–1.19) 0.288 0.83 (0.57–1.20) 0.323
 Dominant 41 (34.75) 113 (40.21) 0.306 0.79 (0.51–1.24) 0.306 0.80 (0.51–1.26) 0.343
 Recessive 113 (95.76) 265 (94.31) 0.552 0.73 (0.26–2.05) 0.554 0.74 (0.26–2.09) 0.575

aχ2 test for genotype distributions between neuroblastoma patients and controls.

bAdjusted for age and gender.

LMO1 polymorphisms and neuroblastoma risk in combined subjects

To further elucidate the association between LMO1 polymorphisms and neuroblastoma risk, we combined our present results the data from our earlier study [22]. In the combination analysis (Table 2), we found that those carrying the rs110419 G allele were at decreased risk of neuroblastoma (AG vs. AA: adjusted OR = 0.67, 95% CI = 0.51–0.88, P = 0.004; GG vs. AA: adjusted OR = 0.58, 95% CI = 0.40–0.84, P = 0.004; AG/GG vs. AA: adjusted OR = 0.65, 95% CI = 0.50–0.83, P = 0.001), as were those carrying the rs4758051 A allele (AA vs. GG: adjusted OR = 0.57, 95% CI = 0.39–0.84, P = 0.005; AA vs. GG/AG: adjusted OR = 0.59, 95% CI = 0.41–0.84, P = 0.004) or the rs10840002 G allele (GG vs. AA: adjusted OR = 0.66, 95% CI = 0.46–0.95, P = 0.026; GG vs. AG/AA: adjusted OR = 0.68, 95% CI = 0.49–0.94, P = 0.020). No significant association was observed between rs204938 A > G and neuroblastoma risk.

Table 2. LMO1 polymorphisms and neuroblastoma susceptibility in combined subjects.

Genotype Cases (N = 374) Controls (N = 812) Pa Crude OR (95% CI) P Adjusted OR (95% CI)b Pb
rs110419 (HWE = 0.239)
AA 150 (40.11) 245 (30.17) 1.00 1.00
AG 171 (45.72) 417 (51.35) 0.67 (0.51–0.88) 0.004 0.67 (0.51–0.88) 0.004
GG 53 (14.17) 150 (18.47) 0.58 (0.40–0.84) 0.004 0.58 (0.40–0.84) 0.004
Additive 0.003 0.74 (0.62–0.89) 0.001 0.74 (0.62–0.89) 0.001
Dominant 224 (59.89) 567 (69.83) 0.001 0.65 (0.50–0.83) 0.001 0.65 (0.50–0.83) 0.001
Recessive 321 (85.83) 662 (81.53) 0.068 0.73 (0.52–1.02) 0.068 0.73 (0.52–1.03) 0.069
rs4758051 (HWE = 0.271)
GG 145 (38.77) 282 (34.73) 1.00 1.00
AG 185 (49.47) 380 (46.80) 0.95 (0.73–1.24) 0.688 0.95 (0.73–1.24) 0.698
AA 44 (11.76) 150 (18.47) 0.57 (0.39–0.84) 0.005 0.57 (0.39–0.84) 0.005
Additive 0.014 0.80 (0.67–0.96) 0.014 0.80 (0.67–0.96) 0.014
Dominant 229 (61.23) 530 (65.27) 0.178 0.84 (0.65–1.08) 0.178 0.84 (0.65–1.08) 0.182
Recessive 330 (88.24) 662 (81.53) 0.004 0.59 (0.41–0.85) 0.004 0.59 (0.41–0.84) 0.004
rs10840002 (HWE = 0.233)
AA 132 (35.29) 260 (32.02) 1.00 1.00
AG 186 (49.73) 384 (47.29) 0.95 (0.73–1.25) 0.736 0.96 (0.73–1.26) 0.744
GG 56 (14.97) 168 (20.69) 0.66 (0.46–0.95) 0.025 0.66 (0.46–0.95) 0.026
Additive 0.062 0.83 (0.70–0.99) 0.042 0.83 (0.70–0.99) 0.043
Dominant 242 (64.71) 552 (67.98) 0.265 0.86 (0.67–1.12) 0.266 0.87 (0.67–1.12) 0.270
Recessive 318 (85.03) 644 (79.31) 0.019 0.68 (0.49–0.94) 0.020 0.68 (0.49–0.94) 0.020
rs204938 (HWE = 0.485)
AA 241 (64.44) 522 (64.29) 1.00 1.00
AG 119 (31.82) 262 (32.27) 0.98 (0.76–1.28) 0.904 0.98 (0.76–1.28) 0.908
GG 14 (3.74) 28 (3.45) 1.08 (0.56–2.09) 0.813 1.07 (0.55–2.08) 0.834
Additive 0.961 1.01 (0.81–1.25) 0.967 1.00 (0.81–1.25) 0.976
Dominant 133 (35.56) 290 (35.71) 0.959 0.99 (0.77–1.28) 0.959 0.99 (0.77–1.28) 0.958
Recessive 360 (96.26) 784 (96.55) 0.798 1.09 (0.57–2.09) 0.798 1.08 (0.56–2.08) 0.820

aχ2 test for genotype distributions between neuroblastoma patients and controls.

bAdjusted for age and gender.

False-positive report probability (FPRP) analysis showed that all of the statistically significant associations remained noteworthy, when a prior probability of association of 0.25 was considered. At a prior probability level of 0.1, all except one association (rs10840002 A > G) remained noteworthy. At a prior probability level of 0.01, only the association between rs110419 A > G and neuroblastoma risk remained noteworthy (FPRP = 0.168). Detailed information from the FPRP analysis is listed in Table 3.

Table 3. False-positive report probability values for significant findings in combined subjects.

Genotype Crude OR (95% CI) Pa Statistical Powerb Prior probability
0.25 0.1 0.01 0.001 0.0001
rs110419 A > G
 AG vs. AA 0.67 (0.51–0.88) 0.004 0.606 0.017 0.051 0.370 0.856 0.983
 GG vs. AA 0.58 (0.40–0.84) 0.004 0.256 0.044 0.120 0.601 0.938 0.993
 AG/GG vs. AA 0.65 (0.50–0.83) 0.001 0.392 0.006 0.018 0.168 0.671 0.953
rs4758051 G > A
 AA vs. GG 0.57 (0.39–0.84) 0.005 0.284 0.050 0.137 0.635 0.946 0.994
 AA vs. GG/AG 0.59 (0.41–0.85) 0.004 0.259 0.044 0.122 0.605 0.939 0.994
rs10840002 A > G
 GG vs. AA 0.66 (0.46–0.95) 0.025 0.557 0.119 0.288 0.816 0.978 0.998
 GG vs. AG/AA 0.68 (0.49–0.94) 0.020 0.521 0.103 0.257 0.792 0.975 0.997

aChi-square test was used to calculate the genotype frequency distributions.

bStatistical power was calculated using the number of observations in the subgroup and the OR and P values in this table.

DISCUSSION

In the present case-control study, we further verified the effect of LMO1 polymorphisms on neuroblastoma risk in a Northern Chinese population. Consistent with our earlier findings [22], we observed that LMO1 polymorphisms were associated with a decreased risk of neuroblastoma. To our knowledge, this is the first study to validate the association between LMO1 polymorphisms and neuroblastoma risk using two resident groups in China. This combined analysis improves the statistical power for assessing the impact of LMO1 polymorphisms on neuroblastoma risk.

A previous genome-wide association study revealed that LMO1 polymorphisms were associated with predisposition to neuroblastoma [16]. In that study, Wang et al. detected four SNPs in LMO1 gene (rs110419 A > G, rs4758051 G > A, rs10840002 A > G and rs204938 A > G) that were associated with neuroblastoma risk in subjects of European ancestry. Thereafter, case-control studies conducted with Italian [24], African-American [25] and Northern Chinese [26] populations verified LMO1 polymorphisms to be factors affecting neuroblastoma risk. In 2016, we conducted the first epidemiological study on the effect of LMO1 polymorphisms on neuroblastoma susceptibility in a Southern Chinese population [22]. We genotyped the aforementioned LMO1 SNPs in 256 cases and 531 controls. We only found that the rs110419 A > G polymorphism was associated with a significantly lower neuroblastoma risk. However the strength of that conclusion was limited by the small sample. We have therefore now expanded the size of our sample.

Here, we assessed the relationship between LMO1 polymorphisms and neuroblastoma risk in an additional 118 cases and 281 controls. Our analysis indicates that carrying the rs4758051 A or rs10840002 G allele is associated with decreased risk of neuroblastoma in a Northern Chinese population. In our earlier study of a Southern Chinese population, we detected a significant protective association between only the rs110419 A > G polymorphism and neuroblastoma risk [22]. Two possible explanations for this discrepancy are as follows. First, the small sizes of the samples used in these two studies means the statistical power of analyzing the association between a single polymorphism and cancer risk is small. Second, because these two studies were conducted in different regions in China, the inconsistency may be attributable to differences in the genetic variations, environmental exposures, and gene-environment interactions across the different regions.

To increase the representation for our conclusions, we combined the results from our present study with those from our earlier one. The combined analysis indicated that carrying the rs110419 G, rs4758051 A or rs10840002 G allele was associated with a decreased risk for neuroblastoma. The larger sample in the combined analysis highlights the important protective effect of LMO1 polymorphisms on neuroblastoma risk. In addition, the FPRP analysis also enhances the robustness of our findings.

Although this is a relatively large sample for investigating the correlation between LMO1 polymorphisms and neuroblastoma risk in the Chinese, several limitations still exist. First, we only genotyped four SNPs in this study, other potentially functional polymorphisms not discovered in genome-wide association studies were omitted. These include the rs2168101 G > T polymorphism, which was recently found to be associated with neuroblastoma [14]. Second, all of the subjects were recruited from two hospitals and most lived in Southern or Northern China, which inevitably caused selection bias. Third, we failed to assess several important environmental factors, including dietary intake, paternal exposures, and the subjects’ living environment. The absence of such information limits our ability to conduct a gene-environmental interaction analysis. Fourth, the sample size is still not large enough to ensure a robust conclusion. Fifth, the potential mechanisms of action of the four polymorphisms were not studied. Experimental analysis of the mechanisms of potentially functional LMO1 polymorphisms is needed.

In summary, we have further confirmed the protective effect of LMO1 polymorphisms on neuroblastoma susceptibility in a Chinese population. More case-control studies based on other ethnicities and multicenter investigations are encouraged to support these observations.

MATERIALS AND METHODS

Study subjects

The recruitment criteria for neuroblastoma patients and controls were described previously [22, 27, 28]. A total of 118 neuroblastoma patients and 281 healthy controls from Henan province (Northern China) were ultimately included in the study [29]. Briefly, all children with neuroblastoma histologically confirmed at The First Affiliated Hospital of Zhengzhou University between August 2011 and April 2017 were enrolled in the study. During the same period, 281 age- and gender-matched controls were also recruited at the same hospital. Before their participation, we obtained informed written consent for all subjects. The present study was approved by the Institutional Review Board of the hospital.

SNP selection and genotyping

Four LMO1 SNPs (rs110419 A > G, rs4758051 G > A, rs10840002 A > G and rs204938 A > G) identified as being associated with neuroblastoma in an earlier genome-wide association study were selected (Supplementary Table 2) [16]. Genotyping these four SNPs was performed using Taqman real-time PCR. The detailed procedure can be found in our earlier study [30]. To ensure the accuracy of the genotyping results, about 10% of the samples were also genotyped by sequencing [31, 32], and 100% genotype concordance was obtained.

Statistical analysis

The goodness-of-fit χ2 test was applied to assess whether the selected SNPs were in Hardy-Weinberg equilibrium among the controls. Two-sided χ2 tests were employed to compare demographic variables and genotype frequencies between cases and controls. To evaluate the strength of the relationship between LMO1 polymorphisms and neuroblastoma susceptibility, ORs and 95% CIs were calculated using unconditional logistic regression analyses. To determine whether the significant findings were “noteworthy”, we adopted the FPRP analysis [33, 34]. We calculated FPRP for a range of prior probabilities from 0.0001 to 0.25 and used 0.2 as a cut-point for FPRP. Values of P < 0.05 were considered statistically significant. SAS software (version 9.4; SAS Institute, Cary, NC) was used to perform all statistical analyses.

SUPPLEMENTARY MATERIALS TABLES

ACKNOWLEDGMENTS AND FUNDING

This study was supported by grants from National Natural Science Foundation of China (No. 81502187), Pearl River S&T Nova Program of Guangzhou (No: 201710010086), and State Clinical Key Specialty Construction Project (Pediatric Surgery) 2013 (No: GJLCZD1301).

Footnotes

CONFLICTS OF INTEREST

No competing interests to declare.

REFERENCES

  • 1.Maris JM, Hogarty MD, Bagatell R, Cohn SL. Neuroblastoma. Lancet. 2007;369:2106–2120. doi: 10.1016/S0140-6736(07)60983-0. [DOI] [PubMed] [Google Scholar]
  • 2.Smith MA, Seibel NL, Altekruse SF, Ries LA, Melbert DL, O’Leary M, Smith FO, Reaman GH. Outcomes for children and adolescents with cancer: challenges for the twenty-first century. J Clin Oncol. 2010;28:2625–2634. doi: 10.1200/JCO.2009.27.0421. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Bao PP, Li K, Wu CX, Huang ZZ, Wang CF, Xiang YM, Peng P, Gong YM, Xiao XM, Zheng Y. [Recent incidences and trends of childhood malignant solid tumors in Shanghai, 2002–2010]. [Article in Chinese] Zhonghua Er Ke Za Zhi. 2013;51:288–294. [PubMed] [Google Scholar]
  • 4.Matthay KK, Villablanca JG, Seeger RC, Stram DO, Harris RE, Ramsay NK, Swift P, Shimada H, Black CT, Brodeur GM, Gerbing RB, Reynolds CP. Treatment of high-risk neuroblastoma with intensive chemotherapy, radiotherapy, autologous bone marrow transplantation, and 13-cis-retinoic acid. Children’s Cancer Group. N Engl J Med. 1999;341:1165–1173. doi: 10.1056/NEJM199910143411601. [DOI] [PubMed] [Google Scholar]
  • 5.Laverdiere C, Liu Q, Yasui Y, Nathan PC, Gurney JG, Stovall M, Diller LR, Cheung NK, Wolden S, Robison LL, Sklar CA. Long-term outcomes in survivors of neuroblastoma: a report from the Childhood Cancer Survivor Study. J Natl Cancer Inst. 2009;101:1131–1140. doi: 10.1093/jnci/djp230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kaatsch P. Epidemiology of childhood cancer. Cancer Treat Rev. 2010;36:277–285. doi: 10.1016/j.ctrv.2010.02.003. [DOI] [PubMed] [Google Scholar]
  • 7.Maris JM. Recent advances in neuroblastoma. N Engl J Med. 2010;362:2202–2211. doi: 10.1056/NEJMra0804577. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.De Roos AJ, Olshan AF, Teschke K, Poole C, Savitz DA, Blatt J, Bondy ML, Pollock BH. Parental occupational exposures to chemicals and incidence of neuroblastoma in offspring. Am J Epidemiol. 2001;154:106–114. doi: 10.1093/aje/154.2.106. [DOI] [PubMed] [Google Scholar]
  • 9.De Roos AJ, Teschke K, Savitz DA, Poole C, Grufferman S, Pollock BH, Olshan AF. Parental occupational exposures to electromagnetic fields and radiation and the incidence of neuroblastoma in offspring. Epidemiology. 2001;12:508–517. doi: 10.1097/00001648-200109000-00008. [DOI] [PubMed] [Google Scholar]
  • 10.Patton T, Olshan AF, Neglia JP, Castleberry RP, Smith J. Parental exposure to medical radiation and neuroblastoma in offspring. Paediatr Perinat Epidemiol. 2004;18:178–185. doi: 10.1111/j.1365-3016.2004.00554.x. [DOI] [PubMed] [Google Scholar]
  • 11.Capasso M, Diskin SJ. Genetics and genomics of neuroblastoma. Cancer Treat Res. 2010;155:65–84. doi: 10.1007/978-1-4419-6033-7_4. [DOI] [PubMed] [Google Scholar]
  • 12.Han W, Zhou Y, Zhong R, Wu C, Song R, Liu L, Zou L, Qiao Y, Zhai K, Chang J, Huang L, Lu X, Lou J, et al. Functional polymorphisms in FAS/FASL system increase the risk of neuroblastoma in Chinese population. PLoS One. 2013;8:e71656. doi: 10.1371/journal.pone.0071656. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Capasso M, Diskin S, Cimmino F, Acierno G, Totaro F, Petrosino G, Pezone L, Diamond M, McDaniel L, Hakonarson H, Iolascon A, Devoto M, Maris JM. Common genetic variants in NEFL influence gene expression and neuroblastoma risk. Cancer Res. 2014;74:6913–6924. doi: 10.1158/0008-5472.CAN-14-0431. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Oldridge DA, Wood AC, Weichert-Leahey N, Crimmins I, Sussman R, Winter C, McDaniel LD, Diamond M, Hart LS, Zhu S, Durbin AD, Abraham BJ, Anders L, et al. Genetic predisposition to neuroblastoma mediated by a LMO1 super-enhancer polymorphism. Nature. 2015;528:418–421. doi: 10.1038/nature15540. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.He J, Wang F, Zhu J, Zhang R, Yang T, Zou Y, Xia H. Association of potentially functional variants in the XPG gene with neuroblastoma risk in a Chinese population. J Cell Mol Med. 2016;20:1481–1490. doi: 10.1111/jcmm.12836. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Wang K, Diskin SJ, Zhang H, Attiyeh EF, Winter C, Hou C, Schnepp RW, Diamond M, Bosse K, Mayes PA, Glessner J, Kim C, Frackelton E, et al. Integrative genomics identifies LMO1 as a neuroblastoma oncogene. Nature. 2011;469:216–220. doi: 10.1038/nature09609. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Boehm T, Foroni L, Kennedy M, Rabbitts TH. The rhombotin gene belongs to a class of transcriptional regulators with a potential novel protein dimerisation motif. Oncogene. 1990;5:1103–1105. [PubMed] [Google Scholar]
  • 18.Matthews JM, Lester K, Joseph S, Curtis DJ. LIM-domain-only proteins in cancer. Nat Rev Cancer. 2013;13:111–122. doi: 10.1038/nrc3418. [DOI] [PubMed] [Google Scholar]
  • 19.Greenberg JM, Boehm T, Sofroniew MV, Keynes RJ, Barton SC, Norris ML, Surani MA, Spillantini MG, Rabbitts TH. Segmental and developmental regulation of a presumptive T-cell oncogene in the central nervous system. Nature. 1990;344:158–160. doi: 10.1038/344158a0. [DOI] [PubMed] [Google Scholar]
  • 20.Boehm T, Baer R, Lavenir I, Forster A, Waters JJ, Nacheva E, Rabbitts TH. The mechanism of chromosomal translocation t(11;14) involving the T-cell receptor C delta locus on human chromosome 14q11 and a transcribed region of chromosome 11p15. EMBO J. 1988;7:385–394. doi: 10.1002/j.1460-2075.1988.tb02825.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Beuten J, Gelfond JA, Piwkham D, Pollock BH, Winick NJ, Collier AB, 3rd, Tomlinson GE. Candidate gene association analysis of acute lymphoblastic leukemia identifies new susceptibility locus at 11p15 (LMO1) Carcinogenesis. 2011;32:1349–1353. doi: 10.1093/carcin/bgr091. [DOI] [PubMed] [Google Scholar]
  • 22.He J, Zhong W, Zeng J, Zhu J, Zhang R, Wang F, Yang T, Zou Y, Xia H. LMO1 gene polymorphisms contribute to decreased neuroblastoma susceptibility in a Southern Chinese population. Oncotarget. 2016;7:22770–22778. doi: 10.18632/oncotarget.8178. https://doi.org/10.18632/oncotarget.8178. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Brodeur GM, Pritchard J, Berthold F, Carlsen NL, Castel V, Castelberry RP, De Bernardi B, Evans AE, Favrot M, Hedborg F. Revisions of the international criteria for neuroblastoma diagnosis, staging and response to treatment. Prog Clin Biol Res. 1994;385:363–369. [PubMed] [Google Scholar]
  • 24.Capasso M, Diskin SJ, Totaro F, Longo L, De Mariano M, Russo R, Cimmino F, Hakonarson H, Tonini GP, Devoto M, Maris JM, Iolascon A. Replication of GWAS-identified neuroblastoma risk loci strengthens the role of BARD1 and affirms the cumulative effect of genetic variations on disease susceptibility. Carcinogenesis. 2013;34:605–611. doi: 10.1093/carcin/bgs380. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Latorre V, Diskin SJ, Diamond MA, Zhang H, Hakonarson H, Maris JM, Devoto M. Replication of neuroblastoma SNP association at the BARD1 locus in African-Americans. Cancer Epidemiol Biomarkers Prev. 2012;21:658–663. doi: 10.1158/1055-9965.EPI-11-0830. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Lu J, Chu P, Wang H, Jin Y, Han S, Han W, Tai J, Guo Y, Ni X. Candidate Gene Association Analysis of Neuroblastoma in Chinese Children Strengthens the Role of LMO1. PLoS One. 2015;10:e0127856. doi: 10.1371/journal.pone.0127856. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.He J, Zhang R, Zou Y, Zhu J, Yang T, Wang F, Xia H. Evaluation of GWAS-identified SNPs at 6p22 with neuroblastoma susceptibility in a Chinese population. Tumour Biol. 2016;37:1635–1639. doi: 10.1007/s13277-015-3936-7. [DOI] [PubMed] [Google Scholar]
  • 28.He J, Wang F, Zhu J, Zhang Z, Zou Y, Zhang R, Yang T, Xia H. The TP53 gene rs1042522 C > G polymorphism and neuroblastoma risk in Chinese children. Aging (Albany NY) 2017;9:852–859. doi: 10.18632/aging.101196. https://doi.org/10.18632/aging.101196. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Zhang J, Wang J, Liu Q, Gao J, Wang Q. Polymorphisms of glucose-regulated protein 78 and clinical relevance of neuroblastoma: Risk and prognosis. J Cancer Res Ther. 2016;12:1178–1183. doi: 10.4103/0973-1482.193119. [DOI] [PubMed] [Google Scholar]
  • 30.He J, Qiu LX, Wang MY, Hua RX, Zhang RX, Yu HP, Wang YN, Sun MH, Zhou XY, Yang YJ, Wang JC, Jin L, Wei QY, et al. Polymorphisms in the XPG gene and risk of gastric cancer in Chinese populations. Hum Genet. 2012;131:1235–1244. doi: 10.1007/s00439-012-1152-8. [DOI] [PubMed] [Google Scholar]
  • 31.Li J, Zou L, Zhou Y, Li L, Zhu Y, Yang Y, Gong Y, Lou J, Ke J, Zhang Y, Tian J, Zou D, Peng X, et al. A low-frequency variant in SMAD7 modulates TGF-beta signaling and confers risk for colorectal cancer in Chinese population. Mol Carcinog. 2017;56:1798–1807. doi: 10.1002/mc.22637. [DOI] [PubMed] [Google Scholar]
  • 32.Lou J, Gong J, Ke J, Tian J, Zhang Y, Li J, Yang Y, Zhu Y, Gong Y, Li L, Chang J, Zhong R, Miao X. A functional polymorphism located at transcription factor binding sites, rs6695837 near LAMC1 gene, confers risk of colorectal cancer in Chinese populations. Carcinogenesis. 2017;38:177–183. doi: 10.1093/carcin/bgw204. [DOI] [PubMed] [Google Scholar]
  • 33.Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N. Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J Natl Cancer Inst. 2004;96:434–442. doi: 10.1093/jnci/djh075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.He J, Wang MY, Qiu LX, Zhu ML, Shi TY, Zhou XY, Sun MH, Yang YJ, Wang JC, Jin L, Wang YN, Li J, Yu HP, et al. Genetic variations of mTORC1 genes and risk of gastric cancer in an Eastern Chinese population. Mol Carcinog. 2013;52:E70–79. doi: 10.1002/mc.22013. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials


Articles from Oncotarget are provided here courtesy of Impact Journals, LLC

RESOURCES