Online ISSN: 1945-4589
Research Paper Volume 10, Issue 3 pp 481—491

Associations between lncRNA MEG3 polymorphisms and neuroblastoma risk in Chinese children

Zhen-Jian Zhuo1,2, *,, Ruizhong Zhang1, *,, Jiao Zhang3, *,, Jinhong Zhu4, , Tianyou Yang1, , Yan Zou1, , Jing He1,5, , Huimin Xia1, ,

  • 1 Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzho, Guangdong 510623, China
  • 2 School of Chinese Medicine, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong 999077, China
  • 3 Department of Pediatric Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzho, Henan 450052, China
  • 4 Department of Clinical Laboratory, Molecular Epidemiology Laboratory, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150040, China
  • 5 Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Department of Experimental Research, Collaborative Innovation Center for Cancer Medicine, Guangzho, Guangdong 510060, China
* Equal contribution

Received: February 12, 2017       Accepted: March 22, 2018       Published: March 27, 2018      

https://doi.org/10.18632/aging.101406
How to Cite

Copyright: Zhuo et al. This is an open‐access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Neuroblastoma is the third most common childhood cancer after leukemias and cancer of the central nervous system. Long noncoding RNA MEG3 polymorphisms have been shown to confer cancer susceptibility; however, their roles in the genetic predisposition to neuroblastoma remain unclarified. To answer this question, we genotyped two MEG3 polymorphisms, rs7158663 G>A and rs4081134 G>A, in 392 neuroblastoma children and 783 controls by TaqMan method. The results showed that neither single locus nor the combination analysis supported an association between MEG3 polymorphism and neuroblastoma risk. Interestingly, we found that subjects carrying rs4081134 AG/AA genotypes significantly tended to develop neuroblastoma among subgroups with age >18 month (adjusted OR=1.36, 95% CI=1.01-1.84) and clinical stage III+IV disease (adjusted OR=1.47, 95% CI=1.08-1.99), when compared with reference group. In the combined analysis of MEG3 polymorphisms, we found that carriers of 2 risk genotypes were more likely to have higher risk of developing neuroblastoma than those with 0-1 risk genotype among children more than 18 months of age (adjusted OR=1.36, 95% CI=1.01-1.84, P=0.042), and with clinical stages III+IV disease (adjusted OR=1.47, 95% CI=1.08-2.00, P=0.014). Our data suggest MEG3 as a weak-effect neuroblastoma susceptibility gene. Well-designed studies with large sample studies are needed to further validate this finding.

Introduction

Neuroblastoma is a heterogeneous tumor rising from neural crest progenitor cells. It is the most common solid neoplasm in children, accounting for nearly 10% of all childhood cancers [1]. Neuroblastoma is characterized by broadly clinical presentation. Some bearing favorable tumors have spontaneous regression without chemotherapy; others have metastatic disease resistant to even intense treatment [2,3]. Survival rates of patients with the most aggressive form of neuroblastoma are less than 40%, even after receiving intensive therapy [1,4,5].

Neuroblastoma can be classified into familial and sporadic types, according to the presence or absence of germline mutations. Familial neuroblastoma is rare, and accounts for about 1-2% of all cases [6]. Most of the familial neuroblastoma are related to the recurrent mutations in PHOX2B [7,8] or ALK gene [9,10]. However, the genetic bases of sporadic neuroblastoma, remains largely unknown. Previous studies have suggested that several environmental factors such as dwelling condition, maternal medication use, and childhood infections are potential risk factors for sporadic neuroblastoma [11,12], but direct link is lacking. Growing evidence suggests that genetic variants can modify the risk of neuroblastoma [13–18]. For example, common genetic variants of NEFL and CNKN1B are associated with neuroblastoma susceptibility [19,20].

Long non-coding RNAs (lncRNAs) are a class of non-coding transcripts with more than 200 nucleotides in length [21]. A plethora of studies have revealed that lncRNAs are implicated in tumorigenesis [22,23]. They can regulate pathophysiological activities of cells in the epigenetic, transcriptional, or posttranscriptional levels [24,25]. So far, numerous polymorphisms in the lncRNAs have been identified to be associated with cancer risk. For example, a genome-wide association study (GWAS) by Guo et al. identified 45 candidate lncRNAs associated with prostate cancer susceptibility [26]. Yang et al. first reported that lncRNA H19 genetic variants may contribute to gastric cancer risk [27]. Notable, our previous study also revealed the association between LINC00673 rs11655237 C>T polymorphism and neuroblastoma susceptibility [28].

The lncRNA MEG3 is a tumor suppressor. It has been involved in several types of cancer, including bladder cancer [29], gastric cancer [30], hepatocellular carcinoma [31], and lung cancer [32]. Accumulating evidence has suggested that genetic variants in the MEG3 gene predispose to cancer. However, the impacts of MEG3 polymorphisms in neuroblastoma risk remain unclear. Therefore, we conducted a gene-based association analysis of MEG3 polymorphisms and neuroblastoma risk.

Results

MEG3 polymorphisms and neuroblastoma susceptibility

In total, 393 cases and 812 controls were included in the current study (Supplementary Table 1), of which, 392 cases and 783 controls were successfully genotyped. Both of polymorphisms (rs7158663 G>A and rs4081134 G>A) were in accordance with Hardy-Weinberg equilibrium (HWE) in the control subjects (rs7158663: HWE=0.725, and rs4081134: HWE=0.762). However, neither of the two MEG3 polymorphisms was associated with neuroblastoma susceptibility, no matter adjusted for age and gender or not. We next evaluated the effects of combined risk genotypes on neuroblastoma susceptibility. Similarly, no significant association was found (Table 1). Null associations between MEG3 polymorphisms and neuroblastoma susceptibility were also observed for Guangdong and Henan subjects, individually (Supplementary Table 2).

Table 1. Associations between MEG3 polymorphisms and neuroblastoma susceptibility.

GenotypeCases
(N=392)		Controls
(N=783)		PaCrude OR
(95% CI)		PAdjusted OR
(95% CI) b		Pb
rs7158663 (HWE=0.725)
GG233 (59.44)433 (55.30)1.001.00
AG141 (35.97)296 (37.80)0.89 (0.69-1.14)0.3510.89 (0.69-1.15)0.354
AA18 (4.59)54 (6.90)0.62 (0.36-1.08)0.0920.62 (0.35-1.07)0.088
Additive0.1930.84 (0.69-1.03)0.0880.84 (0.68-1.03)0.086
Dominant159 (40.56)350 (44.70)0.1770.84 (0.66-1.08)0.1770.84 (0.66-1.08)0.177
Recessive374 (95.41)729 (93.10)0.1200.65 (0.38-1.12)0.1230.65 (0.37-1.12)0.117
rs4081134 (HWE=0.762)
GG200 (51.02)443 (56.58)1.001.00
AG165 (42.09)294 (37.55)1.24 (0.97-1.60)0.0921.25 (0.97-1.60)0.090
AA27 (6.89)46 (5.87)1.30 (0.79-2.15)0.3071.31 (0.79-2.17)0.297
Additive0.1931.19 (0.98-1.45)0.0831.19 (0.98-1.45)0.079
Dominant192 (48.98)340 (43.42)0.0711.25 (0.98-1.60)0.0711.25 (0.98-1.60)0.069
Recessive365 (93.11)737 (94.13)0.4981.19 (0.73-1.94)0.4981.19 (0.73-1.95)0.486
Combine risk genotypes
018 (4.59)53 (6.77)1.001.00
1182 (46.43)391 (49.94)1.37 (0.78-2.41)0.2731.38 (0.79-2.43)0.262
2192 (48.98)339 (43.30)0.1021.67 (0.95-2.93)0.0751.68 (0.96-2.96)0.071
0-1200 (51.02)444 (56.70)1.001.00
2192 (48.98)339 (43.30)0.0651.26 (0.99-1.60)0.0651.26 (0.99-1.61)0.063
OR, odds ratio; CI, confidence interval.
aχ2 test for genotype distributions between neuroblastoma cases and cancer-free controls.
b Adjusted for age and gender.

Stratification analysis

Stratification analysis by age, gender, tumor sites of origin and clinical stages was further performed (Table 2). No significant association was identified for rs7158663 G>A and neuroblastoma susceptibility. Interestingly, we found that subjects carrying rs4081134 AG/AA genotypes were at significantly increased risk of developing neuroblastoma among children older than 18 months of age [adjusted odds ratio (OR)=1.36, 95% confidence interval (CI)=1.01-1.84] and those with clinical stage III+IV disease (adjusted OR=1.47, 95% CI=1.08-1.99), when compared with reference group. In addition, combined analysis indicated that the presence of 2 risk genotypes collectively increased neuroblastoma risk in the children >18 months of age (adjusted OR=1.36, 95% CI=1.01-1.84, P=0.042), and subgroup with III+IV clinical stages (adjusted OR=1.47, 95% CI=1.08-2.00, P=0.014). We further performed stratification analysis for subjects from Guangdong (Supplementary Table 3) and Henan province, separately (Supplementary Table 4). The results showed that 2 risk genotypes increased neuroblastoma risk in subjects with III+IV clinical stage disease from Guangdong province (adjusted OR=1.58, 95% CI=1.08-2.31, P=0.019).

Table 2. Stratification analysis of MEG3 polymorphisms with neuroblastoma susceptibility.

Variablesrs7158663
(cases/controls)		AOR (95% CI) aPars4081134
(cases/controls)		AOR (95% CI) aPaRisk genotypes
(cases/controls)		AOR (95% CI) aPa
GGAG/AAGGAG/AA0-12
Age, month
≤1874/16151/1320.84 (0.55-1.29)0.42764/15661/1371.09 (0.72-1.65)0.69664/15761/1361.10 (0.72-1.68)0.650
>18159/272108/2180.85 (0.63-1.15)0.280136/287131/2031.36 (1.01-1.84)0.042136/287131/2031.36 (1.01-1.84)0.042
Gender
Females101/18167/1470.82 (0.56-1.19)0.29787/19281/1361.31 (0.90-1.91)0.15587/19281/1361.31 (0.90-1.91)0.155
Males132/25292/2030.87 (0.63-1.20)0.380113/251111/2041.21 (0.88-1.67)0.243113/252111/2031.22 (0.89-1.68)0.223
Sites of origin
Adrenal gland92/43361/3500.83 (0.58-1.18)0.28680/44373/3401.20 (0.84-1.69)0.31880/44473/3391.20 (0.85-1.70)0.306
Retroperitoneal50/43336/3500.89 (0.57-1.40)0.61043/44343/3401.29 (0.82-2.01)0.26943/44443/3391.29 (0.83-2.02)0.258
Mediastinum63/43346/3500.91 (0.60-1.36)0.63458/44351/3401.15 (0.77-1.72)0.49358/44451/3391.16 (0.77-1.73)0.478
Others21/43315/3500.88 (0.45-1.73)0.71217/44319/3401.45 (0.74-2.83)0.28117/44419/3391.46 (0.75-2.84)0.273
Clinical stages
I+II+4s95/43367/3500.87 (0.62-1.23)0.43993/44369/3400.97 (0.69-1.37)0.86993/44469/3390.98 (0.69-1.38)0.892
III+IV128/43382/3500.79 (0.58-1.09)0.14899/443111/3401.47 (1.08-1.99)0.01599/444111/3391.47 (1.08-2.00)0.014
AOR, adjusted odds ratio; CI, confidence interval.
a Adjusted for age and gender, omitting the corresponding stratification factor.

Discussion

To determine the association of the MEG3 polymorphisms with neuroblastoma risk, we conducted this hospital-based case-control study in Chinese children. Our study provides evidence of the effects of MEG3 polymorphisms on neuroblastoma susceptibility. Neither of the rs7158663 G>A and rs4081134 G>A significantly modifies neuroblastoma risk. Notably, subjects with rs4081134 AG/AA genotypes were more likely to develop neuroblastoma among subgroup with age >18 month and clinical stage III+IV disease.

LncRNA MEG3 is located on chromosome 14q32.3. It is the first lncRNA identified as a tumor suppressor, preventing cancer initiation and development [33]. Sun et al. showed that knockdown of MEG3 expression by siRNA could promote gastric cancer proliferation in vitro and decreased expression level of MEG3 was related to poor prognosis in gastric cancer [34]. A study by Braconi et al. showed that ectopic expression of MEG3 induced apoptosis in hepatocellular cancer PRC/PRF/5 cells [31]. Another study indicated that a rs116907618 polymorphism in MEG3 did not significantly affect platinum-based chemotherapy response in lung cancer patients [35]. Recently, Zhou et al. found that lncRNA MEG3 downregulation contributes to nickel malignant transformation of human bronchial epithelial cells via modulating PHLPP1 transcription and HIF-1α translation [36]. These findings intrigued us to investigate whether MEG3 might be also involved in neuroblast malignant transformation. The associations between MEG3 polymorphisms and cancer risks have been also investigated. In a case-control study including 518 cases and 527 controls, Cao et al. genotyped five tagged single nucleotide polymorphisms (tagSNPs) in the MEG3 (rs3087918, rs11160608, rs4081134, rs10144253, and rs7158663) to investigate their role in colorectal cancer risk [37]. They observed that MEG3 rs7158663, but not other polymorphisms, was associated with colorectal cancer risk.

Herein, we are the first group to explore the association between MEG3 polymorphisms and neuroblastoma susceptibility in Chinese children. The results showed that either the MEG3 polymorphism alone or in combination did not confer neuroblastoma susceptibility. However, another case-control study by Cao et al. [37] demonstrated that MEG3 rs7158663 AA genotype significantly increased colorectal cancer risk, compared with GG genotype in Chinese population. Their also failed to identify a significant association between rs4081134 and colorectal cancer risk. Polymorphisms may exert diverse genetic effects on cancer susceptibility, depending on different cancer types, geographical regions, and ethnicities. In the stratified analysis, we found that subjects carrying rs4081134 AG/AA genotype significantly tended to develop neuroblastoma among subgroup older than 18 month of age and those with clinical stage III+IV disease, when compared with reference group. It should be noted that this positive association in subgroups might be a chance finding and a result of limited statistical power caused by relatively small sample size.

Though it is the first study performed on the association of interest, limitations accompany. The primary weakness of this study is the relative small sample size. This weakness may impair the strength of the statistical power, especially for the stratification analysis. Second, we only investigated two polymorphisms in the MEG3 gene. More potentially functional polymorphisms in the MEG3 are needed to be studied. Third, the results obtained from Chinese children cannot be directly extrapolated to other populations. Finally, only genetic factors were considered in this study, since environmental factors that may influence neuroblastoma risk were not available.

In summary, the present data indicate that MEG3 polymorphisms have low penetrant effects on neuroblastoma risk. Well-designed case-control studies with larger samples are needed to confirm these findings. Moreover, in vitro and in vivo functional analysis is warranted to reveal the mechanism how the genetic polymorphisms in MEG3 affect the neuroblastoma risk.

Materials and Methods

Study subjects

A total of 393 cases with neuroblastoma and 812 healthy controls of Chinese origin were enrolled for the current study (Supplementary Table 1). The detailed information of these subjects was described in our former studies [28,38,39]. Informed consent was obtained from each participant or their guardian before the research. The study protocols received approval from the Institutional Review Board of Guangzhou Women and Children’s Medical Center, and The First Affiliated Hospital of Zhengzhou University.

Polymorphism selection and genotyping

In brief, we searched the potentially functional candidate SNPs located in the 5’- flanking region, 5’ untranslated region, 3’ untranslated region, and exon of MEG3 gene. Two polymorphisms (rs7158663 G>A and rs4081134 G>A) were selected for analysis. Both the two SNPs are located in transcription factor binding sites (TFBS). There is no significant linkage disequilibrium (R2<0.8) between these two SNPs in the MEG3 gene (R2=0.08 between rs7158663 and rs4081134) (Supplemental Figure 1). The genomic DNA was firstly extracted from peripheral blood donated by subjects using TIANamp Blood DNA Kit (TianGen Biotech Co. Ltd., Beijing, China). Then the DNA samples were further genotyped on a standard commercial TaqMan real-time PCR [40–43]. More details on genotyping and quality control analyses were reported elsewhere [44–46]. To verify results, 10% of the samples was chosen to a second run. All duplicate sets had a concordance rate of 100%.

Statistical analysis

Tests for deviation from HWE of the selected polymorphisms in controls were performed by good-of-fit χ2 test. Then the two-sided χ2 test was adopted to measure the differences in the demographic variables and genotypic frequencies between all cases and controls. ORs and 95% CIs calculated from logistic regression analysis were used to assess the strength of association between MEG3 polymorphisms and neuroblastoma risk. We used version 9.4 SAS software (SAS Institute, Cary, NC) to conduct all statistical analyses. All the P values were two sided, and P values less than 0.05 were considered as significant.

Supplementary Materials

Supplementary File

Conflicts of Interest

No competing interests to declare.

Funding

This study was supported by grants from the Pearl River S&T Nova Programme of Guangzhou (No: 201710010086), the National Natural Science Foundation of China (Grant No. 81502046), and the State Clinical Key Specialty Construction Project (Paediatric Surgery) 2013 (No: GJLCZD1301).

References

  • 1. Matthay KK, Maris JM, Schleiermacher G, Nakagawara A, Mackall CL, Diller L, Weiss WA. Neuroblastoma. Nat Rev Dis Primers. 2016; 2:16078. https://doi.org/10.1038/nrdp.2016.78 [PubMed]
  • 2. Cheung NK, Dyer MA. Neuroblastoma: developmental biology, cancer genomics and immunotherapy. Nat Rev Cancer. 2013; 13:397–411. https://doi.org/10.1038/nrc3526 [PubMed]
  • 3. Maris JM. Recent advances in neuroblastoma. N Engl J Med. 2010; 362:2202–11. https://doi.org/10.1056/NEJMra0804577 [PubMed]
  • 4. Maris JM, Hogarty MD, Bagatell R, Cohn SL. Neuroblastoma. Lancet. 2007; 369:2106–20. https://doi.org/10.1016/S0140-6736(07)60983-0 [PubMed]
  • 5. Esposito MR, Aveic S, Seydel A, Tonini GP. Neuroblastoma treatment in the post-genomic era. J Biomed Sci. 2017; 24:14. https://doi.org/10.1186/s12929-017-0319-y [PubMed]
  • 6. Capasso M, Diskin SJ. Genetics and genomics of neuroblastoma. Cancer Treat Res. 2010; 155:65–84. https://doi.org/10.1007/978-1-4419-6033-7_4 [PubMed]
  • 7. Bourdeaut F, Trochet D, Janoueix-Lerosey I, Ribeiro A, Deville A, Coz C, Michiels JF, Lyonnet S, Amiel J, Delattre O. Germline mutations of the paired-like homeobox 2B (PHOX2B) gene in neuroblastoma. Cancer Lett. 2005; 228:51–58. https://doi.org/10.1016/j.canlet.2005.01.055 [PubMed]
  • 8. Mosse YP, Laudenslager M, Khazi D, Carlisle AJ, Winter CL, Rappaport E, Maris JM. Germline PHOX2B mutation in hereditary neuroblastoma. Am J Hum Genet. 2004; 75:727–30. https://doi.org/10.1086/424530 [PubMed]
  • 9. Mosse YP, Laudenslager M, Longo L, Cole KA, Wood A, Attiyeh EF, Laquaglia MJ, Sennett R, Lynch JE, Perri P, Laureys G, Speleman F, Kim C, et al. Identification of ALK as a major familial neuroblastoma predisposition gene. Nature. 2008; 455:930–35. https://doi.org/10.1038/nature07261 [PubMed]
  • 10. Chen Y, Takita J, Choi YL, Kato M, Ohira M, Sanada M, Wang L, Soda M, Kikuchi A, Igarashi T, Nakagawara A, Hayashi Y, Mano H, Ogawa S. Oncogenic mutations of ALK kinase in neuroblastoma. Nature. 2008; 455:971–74. https://doi.org/10.1038/nature07399 [PubMed]
  • 11. Cook MN, Olshan AF, Guess HA, Savitz DA, Poole C, Blatt J, Bondy ML, Pollock BH. Maternal medication use and neuroblastoma in offspring. Am J Epidemiol. 2004; 159:721–31. https://doi.org/10.1093/aje/kwh108 [PubMed]
  • 12. Menegaux F, Olshan AF, Neglia JP, Pollock BH, Bondy ML. Day care, childhood infections, and risk of neuroblastoma. Am J Epidemiol. 2004; 159:843–51. https://doi.org/10.1093/aje/kwh111 [PubMed]
  • 13. Maris JM, Mosse YP, Bradfield JP, Hou C, Monni S, Scott RH, Asgharzadeh S, Attiyeh EF, Diskin SJ, Laudenslager M, Winter C, Cole KA, Glessner JT, et al. Chromosome 6p22 locus associated with clinically aggressive neuroblastoma. N Engl J Med. 2008; 358:2585–93. https://doi.org/10.1056/NEJMoa0708698 [PubMed]
  • 14. Capasso M, Devoto M, Hou C, Asgharzadeh S, Glessner JT, Attiyeh EF, Mosse YP, Kim C, Diskin SJ, Cole KA, Bosse K, Diamond M, Laudenslager M, et al. Common variations in BARD1 influence susceptibility to high-risk neuroblastoma. Nat Genet. 2009; 41:718–23. https://doi.org/10.1038/ng.374 [PubMed]
  • 15. 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. https://doi.org/10.1371/journal.pone.0071656 [PubMed]
  • 16. 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; 7:22770–78. https://doi.org/10.18632/oncotarget.8178 [PubMed]
  • 17. 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; 9:852–59. https://doi.org/10.18632/aging.101196 [PubMed]
  • 18. He J, Zou Y, Wang T, Zhang R, Yang T, Zhu J, Wang F, Xia H. Genetic Variations of GWAS-Identified Genes and Neuroblastoma Susceptibility: a Replication Study in Southern Chinese Children. Transl Oncol. 2017; 10:936–41. https://doi.org/10.1016/j.tranon.2017.09.008 [PubMed]
  • 19. 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; 74:6913–24. https://doi.org/10.1158/0008-5472.CAN-14-0431 [PubMed]
  • 20. Capasso M, McDaniel LD, Cimmino F, Cirino A, Formicola D, Russell MR, Raman P, Cole KA, Diskin SJ. The functional variant rs34330 of CDKN1B is associated with risk of neuroblastoma. J Cell Mol Med. 2017; 21:3224–30. https://doi.org/10.1111/jcmm.13226 [PubMed]
  • 21. Wilusz JE, Sunwoo H, Spector DL. Long noncoding RNAs: functional surprises from the RNA world. Genes Dev. 2009; 23:1494–504. https://doi.org/10.1101/gad.1800909 [PubMed]
  • 22. Hu Y, Wang J, Qian J, Kong X, Tang J, Wang Y, Chen H, Hong J, Zou W, Chen Y, Xu J, Fang JY. Long noncoding RNA GAPLINC regulates CD44-dependent cell invasiveness and associates with poor prognosis of gastric cancer. Cancer Res. 2014; 74:6890–902. https://doi.org/10.1158/0008-5472.CAN-14-0686 [PubMed]
  • 23. Ylipaa A, Kivinummi K, Kohvakka A, Annala M, Latonen L, Scaravilli M, Kartasalo K, Leppanen SP, Karakurt S, Seppala J, Yli-Harja O, Tammela TL, Zhang W, et al. Transcriptome Sequencing Reveals PCAT5 as a Novel ERG-Regulated Long Noncoding RNA in Prostate Cancer. Cancer Res. 2015; 75:4026–31. https://doi.org/10.1158/0008-5472.CAN-15-0217 [PubMed]
  • 24. Bonasio R, Shiekhattar R. Regulation of transcription by long noncoding RNAs. Annu Rev Genet. 2014; 48:433–55. https://doi.org/10.1146/annurev-genet-120213-092323 [PubMed]
  • 25. Mercer TR, Mattick JS. Structure and function of long noncoding RNAs in epigenetic regulation. Nat Struct Mol Biol. 2013; 20:300–07. https://doi.org/10.1038/nsmb.2480 [PubMed]
  • 26. Guo H, Ahmed M, Zhang F, Yao CQ, Li S, Liang Y, Hua J, Soares F, Sun Y, Langstein J, Li Y, Poon C, Bailey SD, et al. Modulation of long noncoding RNAs by risk SNPs underlying genetic predispositions to prostate cancer. Nat Genet. 2016; 48:1142–50. https://doi.org/10.1038/ng.3637 [PubMed]
  • 27. Yang C, Tang R, Ma X, Wang Y, Luo D, Xu Z, Zhu Y, Yang L. Tag SNPs in long non-coding RNA H19 contribute to susceptibility to gastric cancer in the Chinese Han population. Oncotarget. 2015; 6:15311–20. https://doi.org/10.18632/oncotarget.3840 [PubMed]
  • 28. Zhang Z, Chang Y, Jia W, Zhang J, Zhang R, Zhu J, Yang T, Xia H, Zou Y, He J. LINC00673 rs11655237 C>T confers neuroblastoma susceptibility in Chinese population. Biosci Rep. 2018; 38. https://doi.org/10.1042/BSR20171667 [PubMed]
  • 29. Ying L, Huang Y, Chen H, Wang Y, Xia L, Chen Y, Liu Y, Qiu F. Downregulated MEG3 activates autophagy and increases cell proliferation in bladder cancer. Mol Biosyst. 2013; 9:407–11. https://doi.org/10.1039/c2mb25386k [PubMed]
  • 30. Yan J, Guo X, Xia J, Shan T, Gu C, Liang Z, Zhao W, Jin S. MiR-148a regulates MEG3 in gastric cancer by targeting DNA methyltransferase 1. Med Oncol. 2014; 31:879. https://doi.org/10.1007/s12032-014-0879-6 [PubMed]
  • 31. Braconi C, Kogure T, Valeri N, Huang N, Nuovo G, Costinean S, Negrini M, Miotto E, Croce CM, Patel T. microRNA-29 can regulate expression of the long non-coding RNA gene MEG3 in hepatocellular cancer. Oncogene. 2011; 30:4750–56. https://doi.org/10.1038/onc.2011.193 [PubMed]
  • 32. Terashima M, Tange S, Ishimura A, Suzuki T. MEG3 Long Noncoding RNA Contributes to the Epigenetic Regulation of Epithelial-Mesenchymal Transition in Lung Cancer Cell Lines. J Biol Chem. 2017; 292:82–99. https://doi.org/10.1074/jbc.M116.750950 [PubMed]
  • 33. Zhou Y, Zhang X, Klibanski A. MEG3 noncoding RNA: a tumor suppressor. J Mol Endocrinol. 2012; 48:R45–53. https://doi.org/10.1530/JME-12-0008 [PubMed]
  • 34. Sun M, Xia R, Jin F, Xu T, Liu Z, De W, Liu X. Downregulated long noncoding RNA MEG3 is associated with poor prognosis and promotes cell proliferation in gastric cancer. Tumour Biol. 2014; 35:1065–73. https://doi.org/10.1007/s13277-013-1142-z [PubMed]
  • 35. Gong WJ, Yin JY, Li XP, Fang C, Xiao D, Zhang W, Zhou HH, Li X, Liu ZQ. Association of well-characterized lung cancer lncRNA polymorphisms with lung cancer susceptibility and platinum-based chemotherapy response. Tumour Biol. 2016; 37:8349–58. https://doi.org/10.1007/s13277-015-4497-5 [PubMed]
  • 36. Zhou C, Huang C, Wang J, Huang H, Li J, Xie Q, Liu Y, Zhu J, Li Y, Zhang D, Zhu Q, Huang C. LncRNA MEG3 downregulation mediated by DNMT3b contributes to nickel malignant transformation of human bronchial epithelial cells via modulating PHLPP1 transcription and HIF-1alpha translation. Oncogene. 2017; 36:3878–89. https://doi.org/10.1038/onc.2017.14 [PubMed]
  • 37. Cao X, Zhuang S, Hu Y, Xi L, Deng L, Sheng H, Shen W. Associations between polymorphisms of long non-coding RNA MEG3 and risk of colorectal cancer in Chinese. Oncotarget. 2016; 7:19054–59. https://doi.org/10.18632/oncotarget.7764 [PubMed]
  • 38. He J, Zou Y, Liu X, Zhu J, Zhang J, Zhang R, Yang T, Xia H. Association of common genetic variants in pre-microRNAs and neuroblastoma susceptibility: a two-center study in Chinese children. Mol Ther Nucleic Acids. 2018; 11:1–8. https://doi.org/10.1016/j.omtn.2018.01.003
  • 39. Zhuo ZJ, Liu W, Zhang J, Zhu J, Zhang R, Tang J, Yang T, Zou Y, He J, Xia H. Functional Polymorphisms at ERCC1/XPF Genes Confer Neuroblastoma Risk in Chinese Children. EBioMedicine. 2018; Epub ahead of print. https://doi.org/10.1016/j.ebiom.2018.03.003 [PubMed]
  • 40. Gong J, Tian J, Lou J, Wang X, Ke J, Li J, Yang Y, Gong Y, Zhu Y, Zou D, Peng X, Yang N, Mei S, et al. A polymorphic MYC response element in KBTBD11 influences colorectal cancer risk, especially in interaction with a MYC regulated SNP rs6983267. Ann Oncol. 2017; Epub ahead of print. https://doi.org/10.1093/annonc/mdx789 [PubMed]
  • 41. 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; 56:1798–807. https://doi.org/10.1002/mc.22637 [PubMed]
  • 42. 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; 38:177–83. https://doi.org/10.1093/carcin/bgw204 [PubMed]
  • 43. Zou D, Lou J, Ke J, Mei S, Li J, Gong Y, Yang Y, Zhu Y, Tian J, Chang J, Zhong R, Gong J, Miao X. Integrative expression quantitative trait locus-based analysis of colorectal cancer identified a functional polymorphism regulating SLC22A5 expression. Eur J Cancer. 2018; 93:1–9. https://doi.org/10.1016/j.ejca.2018.01.065 [PubMed]
  • 44. 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; 20:1481–90. https://doi.org/10.1111/jcmm.12836 [PubMed]
  • 45. He J, Yang T, Zhang R, Zhu J, Wang F, Zou Y, Xia H. Potentially functional polymorphisms in the LIN28B gene contribute to neuroblastoma susceptibility in Chinese children. J Cell Mol Med. 2016; 20:1534–41. https://doi.org/10.1111/jcmm.12846 [PubMed]
  • 46. Hua RX, Zhuo ZJ, Zhu J, Zhang SD, Xue WQ, Zhang JB, Xu HM, Li XZ, Zhang PF, He J, Jia WH. XPG Gene Polymorphisms Contribute to Colorectal Cancer Susceptibility: A Two-Stage Case-Control Study. J Cancer. 2016; 7:1731–39. https://doi.org/10.7150/jca.15602 [PubMed]
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Corresponding Authors

Huimin Xia
xia-huimin@foxmail.com

Jing He
hejing@gwcmc.org

Keywords
MEG3 polymorphism neuroblastoma susceptibility
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