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. 2019 Dec 12;24(2):1160–1168. doi: 10.1111/jcmm.14836

LMO1 polymorphisms and the risk of neuroblastoma: Assessment of meta‐analysis of case‐control studies

Mohammad Hashemi 1,2,✉, Sahel Sarabandi 2, Shima Karami 2, Jarosław Śmieja 3, Abdolkarim Moazeni‐Roodi 4, Saeid Ghavami 5,6, Marek J Łos 7,✉
PMCID: PMC6991665  PMID: 31830377

Abstract

Neuroblastoma (NB), a neuroendocrine tumour, is one of the most prevalent cancers in children. The link between LMO1 polymorphisms and NB has been investigated by several groups, rendering inconclusive results. Here, with this comprehensive systematic review and up‐to‐date meta‐analysis, we aim to distinctively elucidate the possible correlation between LMO1 polymorphisms and NB susceptibility. Eligible studies were systematically researched and identified using PubMed, Web of Science and Scopus databases up to 10 February 2019. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of the associations. Our findings revealed that rs110419 and rs2168101 polymorphisms were significantly associated with a decreased risk of NB in all genetic models. In addition, the rs4758051 variant appeared protective against NB in homozygous, dominant and allele genetic models, whereas the rs10840002 variant markedly decreased the risk of NB in the allele model. In contrast, the rs204938 polymorphism showed a positive association with NB susceptibility in allele genetic models. In summary, our meta‐analysis is the first to provide clear evidence of an association between specific polymorphisms of LMO1 and susceptibility to NB. Of note, additional larger well‐designed studies would be helpful to further evaluate and confirm this association.

Keywords: LMO1, meta‐analysis, neuroblastoma, polymorphism

1. INTRODUCTION

Neuroblastoma (NB) is the most common solid tumour outside of the cranium in children, especially within the first 5 years after birth (median age of diagnosis at about 17 months).1, 2, 3 The tumours are most common in the abdomen (65%), followed by the neck, pelvis and chest (2). Neuroblastoma is a neuroendocrine tumour, which originates from the developing sympathetic nervous system, and its prevalence varies worldwide, affecting approximately 8‐14 individuals per million in the developed countries.4

Possible risk factors suspected of aiding the development of NB in children include parental exposure to radiation sources, solders, wood dust and hydrocarbons.5, 6 Hence, degradation of environment may contribute to the occurrence of the cancer. Furthermore, with the advances in regenerative medicine and the use of novel biomaterials in implants such risks may increase.7, 8

Our group performed in the past years several meta‐analyses,9, 10, 11 which underlined the role of polymorphisms in various cancer‐associated genes. Over the last decade, genome‐wide association studies (GWAS) have identified several loci linked to NB susceptibility,12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 of which the LIM domain only 1 (LMO1) gene at 11p15.4 represents a promising candidate.14 LMO1 was recognized as neuroblastoma oncogene.14 It also acts as an oncogene in colorectal cancer (CRC) and lung cancer. LMO1 overexpression is a new predictive marker for anti‐EGFR therapy.23, 24 However, no significant differences were observed for LMO1 gene expression level between tumour tissues and corresponding adjacent benign tissues in human breast cancer, hepatocellular carcinoma (HCC) and gastric cancer (GC), which suggests that LMO1 gene may display a more complex functional network in these cancers.24 Sun et al25 have found that the expression levels of LMO1 in gastric cancer tissues were higher than those in adjacent tissues and the overexpression of LMO1 could be as a markers of poor prognosis. Deregulated expression of LMO1 may be involved in the development and maintenance of T‐ALL (T‐acute lymphoblastic leukaemia).26

Thus far, several studies have investigated LMO1 polymorphisms and their impact on NB susceptibility, with varying and inconclusive results.14, 20, 27, 28, 29, 30, 31, 32, 33 In the current study, we performed an up‐to‐date meta‐analysis to more precisely evaluate the association between specific LMO1 polymorphisms and NB susceptibility.

2. METHODS

2.1. Literature search

To identify all potentially eligible literature, PubMed, Scopus and Web of Science databases were searched for relevant publications up to February 2019. The search keywords were ‘neuroblastoma’ and ‘LIM domain only 1 or LMO1’ and ‘polymorphism or mutation or variation’. Studies were included in our meta‐analysis if they met the following inclusion criteria: (a) original case‐control studies; and (b) studies comprising necessary genotyping data of LMO1 polymorphisms in both disease cases and controls. The exclusion criteria were as follows: (a) case reports, conference abstracts, meta‐analyses and duplication data; and (b) studies lacking genotype information.

2.2. Data extraction

Two investigators independently searched literature and extracted the appropriate data from eligible studies. Data collected from each study included: the first author, publication date, country, ethnicity of study participants, control‐population source, genotyping methods of LOM1 polymorphisms, genotype distributions in cases and controls, and the result of the HWE test (Table 1).

Table 1.

Characteristics of all studies included in the meta‐analysis

First author Year Country Ethnicity Source of control Genotyping method Case/Control Cases Controls HWE (P)
rs110419             AA AG GG A G AA AG GG A G  
Capasso M 2013 Italy Caucasian PB Illumina HumanHap550 323/774 87 152 84 326 320 133 370 271 636 912 0.727
Capasso M 2013 USA European American PB Illumina HumanHap550 1626/2575 509 787 330 1805 1447 599 1310 666 2508 2642 0.357
He J 2016 China Asian HB TaqMan 256/531 103 117 36 323 189 159 275 97 593 469 0.248
He L 2018 China Asian HB TaqMan 313/762 150 118 45 418 208 279 355 128 913 611 0.405
Latorre V 2012 USA African American HB Illumina HumanHap 550 365/2491 223 124 18 570 160 1491 863 137 3845 1137 0.409
Lu J 2015 China Asian HB MassARRAY iPLEX 244/305 – – – 359 129 – – – 369 241 –
Oldridge DA 2015 USA European American N.A Illumina HumanHap550 2101/4202 – – – 2349 1853 – – – 4110 4294 –
Wang K 2011 USA Discovery N.A Illumina HumanHap550 1627/3254 – – – 1790 1464 – – – 3189 3319 –
Wang K 2011 USA US replication N.A Illumina Human610 190/1507 – – – 232 148 – – – 1477 1537 –
Wang K 2011 USA UK replication N.A TaqMan 253/845 – – – 268 238 – – – 811 879 –
Wang K 2011 USA Italian replication N.A TaqMan 181/491 – – – 177 185 – – – 403 579 –
Zhang J 2017 China Asian HB TaqMan 374/812 150 171 53 471 277 245 417 150 907 717 0.239
rs4758051             GG AG AA G A GG AG AA G A  
Capasso M 2013 Italy Caucasian PB Illumina HumanHap550 340/792 70 156 114 296 384 141 405 246 687 897 0.248
Capasso M 2013 USA European American PB Illumina HumanHap550 1624/2571 436 787 401 1659 1589 525 1292 754 2342 2800 0.507
He J 2016 China Asian HB TaqMan 256/531 95 126 35 316 196 194 242 95 630 432 0.199
He L 2018 China Asian HB TaqMan 313/762 138 123 52 399 227 256 364 142 876 648 0.530
Latorre V 2012 USA African American HB Illumina HumanHap 550 365/2491 239 108 18 586 144 1692 713 86 4097 885 0.310
Lu J 2015 China Asian HB MassARRAY iPLEX 244/305 – – – 332 156 – – – 357 253 –
Oldridge DA 2015 USA European American N.A Illumina HumanHap550 2101/4202 – – – 2059 2143 – – – 4605 3799 –
Wang K 2011 USA Discovery N.A Illumina HumanHap550 1627/3254 – – – 1660 1594 – – – 2929 3579 –
Wang K 2011 USA US replication N.A Illumina Human610 190/1507 – – – 209 171 – – – 1356 1658 –
Wang K 2011 USA UK replication N.A TaqMan 253/845 – – – 258 248 – – – 761 930 –
Wang K 2011 USA Italian replication N.A TaqMan 181/491 – – – 163 199 – – – 412 570 –
Zhang J 2017 China Asian HB TaqMan 374/812 145 185 44 475 273 282 380 150 944 680 0.271
rs10840002             AA AG GG A G AA AG GG A G  
He J 2016 China Asian HB TaqMan 256/531 90 124 42 304 208 182 240 109 604 458 0.070
He L 2018 China Asian HB TaqMan 313/762 120 128 65 368 258 240 375 147 855 669 0.981
Latorre V 2012 USA African American HB Illumina HumanHap 550 365/2491 204 128 33 536 194 1430 897 164 3757 1225 0.148
Lu J 2015 China Asian HB MassARRAY iPLEX 244/305 – – – 317 171 – – – 342 268 –
Wang K 2011 USA Discovery N.A Illumina HumanHap550 1627/3254 – – – 1367 1887 – – – 2408 4100 –
Wang K 2011 USA US replication N.A Illumina Human610 190/1507 – – – 167 213 – – – 1145 1869 –
Wang K 2011 USA UK replication N.A TaqMan 253/845 – – – 187 319 – – – 608 1082 –
Zhang J 2017 China Asian HB TaqMan 374/812 132 186 56 450 298 260 384 168 904 720 0.233
rs204938             AA AG GG A G AA AG GG A G  
He J 2016 China Asian HB TaqMan 256/531 164 83 9 411 101 354 165 12 873 189 0.153
He L 2018 China Asian HB TaqMan 313/762 200 97 16 497 129 476 258 28 1210 314 0.336
Latorre V 2012 USA African American HB Illumina HumanHap 550 365/2490 42 162 161 246 484 241 1040 1209 1522 3458 0.426
Lu J 2015 China Asian HB MassARRAY iPLEX 244/305 – – – 359 129 – – – 489 121 –
Wang K 2011 USA Discovery N.A Illumina HumanHap550 1627/3254 – – – 1660 1594 – – – 3644 2864 –
Wang K 2011 USA US replication N.A Illumina Human610 190/1507 – – – 190 190 – – – 1658 1356 –
Wang K 2011 USA UK replication N.A TaqMan 253/845 – – – 253 253 – – – 946 744 –
Zhang J 2017 China Asian HB TaqMan 374/812 241 119 14 601 147 522 262 28 1306 318 0.485
rs2168101             GG GT TT G T GG GT TT G T  
He J 2018 China Asian HB TaqMan 373/812 245 117 11 607 139 407 342 63 1156 468 0.448
He L 2018 China Asian HB TaqMan 313/762 214 85 14 513 113 401 310 51 1112 412 0.389
Oldridge DA 2015 USA European American N.A Illumina HumanHap550 – – – – 3185 1017 – – – 5774 2630 –
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2.3. Statistical analysis

All analyses were performed using STATA 14.1 (Stata Corporation). Departure from Hardy‐Weinberg equilibrium (HWE) in controls was examined by the χ 2 test. The strength of the association between LMO1 polymorphisms and NB risk was assessed by pooled odds ratios (ORs) and their 95% confidence intervals (CIs). The Z‐test was implemented to establish the statistical significance of the pooled ORs. We estimated the between‐study heterogeneity by the Q‐test and I 2‐test, with P < .10 indicating the presence of heterogeneity. In case of heterogeneity, a random‐effect model was used; otherwise, a fixed‐effect model was employed.

We determined publication bias using funnel plots for visual inspection and by conducting quantitative estimations using the Egger's test. Sensitivity analyses were carried out by sequentially ignoring a single study at a time to assess the impact of individual data sets on the pooled ORs.

3. RESULTS

3.1. Study characteristics

Figure 1A shows a flow chart of the study selection procedure. Ultimately, 9 published articles14, 20, 27, 28, 29, 30, 31, 32, 33 that met our inclusion criteria were identified: 12 case‐control studies on rs110419 and rs4758051 polymorphisms, 8 studies on rs10840002 and rs204938 polymorphisms, and three studies on the rs2168101polymorphism were also included in our meta‐analysis. The Figure 1B‐D illustrates the position of the analysed polymorphisms within the LMO1 gene. The articles were published between 2011 and 2018, and they include representatives of major ethnic groups (Caucasians, European Americans, African Americans and Asians). The main characteristics of these studies are listed in Table 1.

Figure 1.

Figure 1

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Basic information about the presented study. (A) Flow chart of the study selection procedure, (B) map of the human LMO1 gene (USCS genome browser: chr11:8,224,449‐8,263,388). Exons 1‐4 are numbered and represented by black boxes. C) Positions of the single‐nucleotid variations within the first intron of the LMO1 gene (D) positions of the single‐nucleotid variations within the 3′ UTR region of the LMO1 gene (not up to scale)

3.1.1. Association of rs110419 polymorphism and neuroblastoma risk

Quantitative analysis revealed that the rs110419 variant markedly decreased the risk of NB in heterozygous (OR = 0.72, 95%CI = 0.65‐0.79, P < .00001, AG vs AA), homozygous (OR = 0.59, 95%CI = 0.52‐0.67, P < .00001, GG vs AA), dominant, (OR = 0.68, 95%CI = 0.59‐0.78, P < .00001, AG + GG vs AA), recessive (OR = 0.73, 95%CI = 0.66‐0.82, P < .00001, GG vs AG + AA) and allele (OR = 0.75, 95%CI = 0.71‐0.79, P < .00001, G vs A) genetic models (Table 2, Figure 2).

Table 2.

Association between LMO1 polymorphisms and susceptibility to neuroblastoma

Polymorphism No. Genetic model Test of association Heterogeneity (I 2 (%), P) Egger's test
OR (95%CI) Z P χ 2 I 2 (%) P P
rs110419 6 AG vs AA 0.72 (0.65‐0.79) 6.77 <.00001 8.15 39 .15 .643
6 GG vs AA 0.59 (0.52‐0.67) 8.09 <.00001 4.03 0 .55 .565
6 AG + GG vs AA 0.68 (0.59‐0.78) 5.29 <.00001 10.65 53 .06 .772
6 GG vs AG + AA 0.73 (0.66‐0.82) 5.51 <.00001 1.66 0 .89 .411
12 G vs A 0.75 (0.71‐0.79) 10.14 <.00001 17.78 38 .09 .293
rs4758051 6 AG vs GG 0.85 (0.71‐1.01) 1.85 .06 13.56 63 .02 .487
6 AA vs GG 0.76 (0.61‐0.96) 2.32 .02 12.36 60 .03 .207
6 AG + AA vs GG 0.83 (0.70‐0.99) 2.08 .04 15.62 68 .008 .363
6 AA vs AG + GG 0.86 (0.70‐1.06) 1.38 .17 13.51 63 .02 .612
12 A vs G 0.86 (0.75‐0.99) 2.13 .03 121.1 91 <.00001 .245
rs10840002 4 AG vs AA 0.92 (0.80‐1.05) 1.24 .22 9.98 40 .17 .764
4 GG vs AA 0.89 (0.65‐1.23) 0.71 .48 8.04 63 .05 .750
4 AG + GG vs AA 0.91 (0.80‐1.04) 1.35 .18 4.38 32 .22 .506
4 GG vs AG + AA 0.94 (0.68‐1.30) 0.37 .71 9.98 70 .02 .724
8 G vs A 0.87 (0.79‐0.95) 3.00 .003 15.31 54 .03 .587
rs204938 4 AG vs AA 0.96 (0.83‐1.12) 0.48 .63 0.97 0 .81 .922
4 GG vs AA 0.97 (0.74‐1.28) 0.21 .83 4.11 27 .25 .044
4 AG + GG vs AA 0.97 (0.84‐1.13) 0.36 .72 1.76 0 .62 .685
4 GG vs AG + AA 0.92 (0.76‐1.12) 0.79 .43 4.20 28 .24 .046
8 G vs A 1.13 (1.00‐1.26) 2.03 .04 20.15 65 .005 .635
rs2168101 2 GT vs GG 0.54 (0.45‐0.66) 6.13 <.00001 0.25 0 .61 –
2 TT vs GG 0.39 (0.25‐0.60) 4.17 <.00001 1.56 36 .21 –
2 GT + TT vs GG 0.52 (0.43‐0.63) 6.84 <.00001 0.01 0 .91 –
2 TT vs GT + GG 0.48 (0.31‐0.75) 3.21 .001 1.70 41 .19  
3 G vs T 0.64 (0.55‐0.74) 5.96 <.00001 4.54 56 .10 –
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Figure 2.

Figure 2

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Forest plot representing the association between the LMO1 rs110419 polymorphism and neuroblastoma susceptibility in allele genetic models (G vs A)

The rs4758051 variant markedly decreased the risk of NB in homozygous (OR = 0.76, 95%CI = 0.61‐0.96, P = .02, AA vs GG), dominant (OR = 0.68, 95%CI = 0.59‐0.78, P = .04, AG + GG vs AA) and allele (OR = 0.86, 95%CI = 0.75‐0.99, P = .03, A vs G) genetic models (Table 2, Figure 3). Similar findings were true for the rs10840002 variant, but only in the allele genetic model OR = 0.87, 95%CI = 0.79‐0.95, P = .003, G vs A; Table 2). In addition, the rs2168101 polymorphism was associated with decreased risk of NB susceptibility in heterozygous (OR = 0.54, 95%CI = 0.45‐0.66, P < .00001, GT vs GG), homozygous (OR = 0.39, 95%CI = 0.25‐0.60, P < .00001, TT vs GG), dominant (OR = 0.52, 95%CI = 0.43‐0.63, P < .00001, GT + TT vs GG), recessive (OR = 0.48, 95%CI = 0.31‐0.75, P = .001, TT vs GT + GG) and allele (OR = 0.64, 95%CI = 0.55‐0.74, P < .00001, G vs T) genetic models (Table 2). In contrast to the other polymorphisms evaluated, the results revealed that rs204938 marginally increased the risk of NB in the allele genetic model (OR = 1.13, 95%CI = 1.00‐1.26, P = .04, G vs A; Table 2).

Figure 3.

Figure 3

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Forest plot representing the association between the LMO1 rs4758051 polymorphism and neuroblastoma susceptibility in allele genetic models (A vs G)

3.1.2. Heterogeneity and publication bias

Between‐study heterogeneity across studies included into pooled analysis is displayed in Table 2. No evidence of heterogeneity was observed between studies for rs110419 and rs2168101 polymorphisms. For rs4758051; however, heterogeneity was identified in all codominant, dominant, recessive and allele genetic models (Table 2). Regarding rs10840002, no heterogeneity was observed in heterozygous, homozygous and dominant genetic models. No evidence of heterogeneity was found for rs204938 in heterozygous, homozygous, dominant and recessive genetic models (Table 2).

Begg's funnel plots and Egger's tests were performed to estimate the publication bias of the included literature. The Egger's tests revealed no existence of publication bias for all polymorphisms, except rs204938 in homozygous and recessive genetic models (Table 2, Figure 4).

Figure 4.

Figure 4

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Begg's funnel plot for the association between the LMO1 rs110419 polymorphism and neuroblastoma risk (G vs A)

3.1.3. Sensitivity analysis

Sensitivity analysis was conducted to assess the effects of individual studies on the stability of the pooled ORs. With sequential removal of individual study results from the analysis for rs110419, the pooled ORs remained significantly consistent in heterozygous, homozygous, recessive, dominant and allele genetic models (Figure 5). With regards to rs10840002, the ORs remained unchanged in heterozygous and allele genetic models. Lastly, the pooled ORs changed in all genetic models for rs204938 and rs4758051 polymorphisms.

Figure 5.

Figure 5

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Sensitivity analyses of studies on the association of the LMO1 rs110419 polymorphism and neuroblastoma (G vs A)

4. DISCUSSION

Genetic susceptibility to NB has led to growing attention of the studies focused on genetic variations. To date, several reports on the potential association between LMO1 polymorphisms and NB development have been published, but the findings were inconsistent. Somehow surprisingly, none of the polymorphisms are in the coding region of the LMO1 gene. Therefore, they do not result in any amino acid change. They seem not to be related to splicing variants either and; therefore, the nature of their association with susceptibility to NB remains elusive. Three polymorphisms: rs110419, rs2168101 and rs204938 are located in the intron 1, while rs4758051 and rs1084000 are in the intergenic region, beyond the last, fourth exon of the LMO1 gene. Hence, the analysed polymorphisms most likely affect regulatory mechanisms within the LMO1 gene.

Our meta‐analysis, based on systematically collected studies, aimed to obtain an accurate summary of the estimates of the strength of association between specific LMO1 gene polymorphisms and NB susceptibility, and, to our best knowledge, is the first to do so. We found that rs110419, rs4758051, rs10840002 and rs2168101 polymorphisms were associated with reduced susceptibility to NB, while the rs204938 polymorphism increased the risk of the disease.

He et al30 reported that rs110419, rs10840002, rs4758051 and rs2168101 polymorphisms of the LMO1 gene were associated with a decreased risk of NB in an eastern Chinese subpopulation. In addition, the rs2168101 and rs3750952 polymorphisms were markedly associated with decreased NB susceptibility in children from North and South China.28 Similarly, the LMO1 rs110419 A > G polymorphism was linked to a reduced NB risk in Southern Chinese children.29 A significant association between the rs204926 variant and NB susceptibility has been reported,32 and rs4758051 and rs10840002 polymorphisms were associated with decreased NB.33 Furthermore, a significant association between the rs110419 polymorphism and risk of NB was observed in an Italian population as well as European American children.27 Conversely, no significant associations between LMO1 polymorphisms and NB risk were observed in African Americans.31 While some studies indicate that frequently occurring polymorphisms at the LMO1 locus are strongly connected to susceptibility to developing NB.14 The observed differences in susceptibility, between populations, are likely due to the overall genetic background that modifies the LMO1 prone risk factors.

This meta‐analysis has a few limitations that should be considered. First, we have only included studies published in the English language. Second, there was significant heterogeneity among studies. There was also variation in study sample size, populations and ethnicity of participants, (please see Table 1 for details). Third, our findings were obtained with a relatively limited sample size and consequently, our conclusions are preliminary in nature. Fourth, the assessments of gene‐gene and gene/environment interactions were not performed despite some data suggest so.

In conclusion, our meta‐analysis is the first to provide evidence of an association between specific genetic polymorphisms of the LMO1 gene and susceptibility to NB. Further validation by well‐designed studies performed by international multicenter programme (addressing diverse ethnic populations) is needed to conclusively confirm the impact of specific LMOI polymorphisms on NB susceptibility and development. Unfortunately, at present we lack sufficient number of studies (studied populations) to reliably perform such analyses. Nevertheless, the presented analysis offers interesting insight into the analysed polymorphisms, as outlined above.

CONFLICT OF INTEREST

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript or in the decision to publish the results.

AUTHOR CONTRIBUTIONS

M. Hashemi, S. Sarabandi, S. Karami, A. Moazeni‐Roodi, J. Śmieja: involved in conceptualization, data collection, validation, statistical analysis and manuscript writing (first draft); S. Ghavami and MJ Łos: formally analysed and finalized the manuscript.

ACKNOWLEDGEMENTS

The authors would like to thank Science Impact (Winnipeg) for post‐editing the manuscript. JS and MJŁ thank you for the support from Polish National Science Centre, grants # 2016/21/B/ST7/02241.

Hashemi M, Sarabandi S, Karami S, et al. LMO1 polymorphisms and the risk of neuroblastoma: Assessment of meta‐analysis of case‐control studies. J Cell Mol Med. 2020;24:1160–1168. 10.1111/jcmm.14836

Contributor Information

Mohammad Hashemi, Email: mhd.hashemi@gmail.com, Email: hashemim@zaums.ac.ir.

Marek J. Łos, Email: bioappl@gmail.com.

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