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Genetic variants of m1A modification genes and the risk of neuroblastoma: novel insights from a Chinese case-control study

Human Genomics volume 19, Article number: 50 (2025) Cite this article

Abstract

Background

The N1-adenosine methylation (m1A) modification plays a significant role in various cancers. However, the functions of m1A modification genes and their variants in neuroblastoma remain to be elucidated.

Methods

We conducted a case-control study involving 402 neuroblastoma patients and 473 cancer-free controls from China via the TaqMan genotyping method to evaluate m1A modification gene polymorphisms. Multivariate logistic regression analysis was conducted to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Additionally, expression quantitative trait locus (eQTL) analysis utilizing the Genotype-Tissue Expression database was performed to investigate the impacts of significant polymorphisms on gene expression. The relationships between gene expression and the risk and prognosis of neuroblastoma patients were further examined via publicly available datasets by using the R2 platform.

Results

We found that TRMT10C rs4618204 C > T significantly decreased neuroblastoma risk (CT/TT vs. CC: adjusted OR = 0.74, 95% CI = 0.56–0.97, P = 0.030). Moreover, polymorphisms of the TRMT10C (rs3762735), TRMT6 (rs451571 and rs236110), and ALKBH3 (rs10768993 and rs2292889) genes were associated with neuroblastoma risk in specific subgroups. Complete linkage disequilibrium and eQTL analysis revealed a significant association between rs4618204 C > T and reduced expression of the TRMT10C gene. Additionally, higher expression levels of the TRMT10C gene were observed to be linked to increased risk, malignancy, and poorer prognosis in neuroblastoma patients.

Conclusions

TRMT10C rs4618204 C > T was demonstrated to be significantly associated with an increased risk of neuroblastoma and may serve as a potential molecular marker for early diagnosis. Further studies are warranted to fully elucidate the specific molecular mechanisms involved in this effect.

Clinical trial number

Not applicable.

Graphical Abstract

Introduction

Neuroblastoma is a solid tumor arising within the sympathetic nervous system, and accumulating evidence suggests that it originates from neural crest cells [1]. Neuroblastoma ranks as the second most common extracranial solid tumor in pediatric patients, accounting for approximately 15% of tumor-related mortality [2, 3]. The incidence rate of pediatric neuroblastoma ranges from 7.7 to 8.8 cases per million children in China [4]. In developed regions such as Europe and the United States, the incidence of neuroblastoma in children varies significantly, with the standardized incidence rate ranging from 6.1 to 21.5 cases per million children [5, 6]. Patients with low-risk and moderate-risk neuroblastoma generally have a favorable prognosis, with an overall 5-year survival rate exceeding 90% [7, 8]. However, patients with high-risk neuroblastoma continue to have a poor prognosis despite undergoing intensive multimodal therapies, including surgery, chemotherapy, radiotherapy, and immunotherapy [9]. Neuroblastoma is a highly heterogeneous tumor characterized by diverse clinical and molecular features. For example, MYCN amplification is observed in approximately 20–25% of neuroblastoma cases and has been demonstrated to be correlated with an unfavorable prognosis in patients with neuroblastoma [10]. Deletions of chromosomes 1p and 11q have been associated with an increased risk of neuroblastoma [8]. Additionally, mutations in the anaplastic lymphoma kinase (ALK) gene have been detected in approximately 8% of neuroblastoma cases, with the ALK gene F1174L mutation being associated with MYCN amplification [11]. Recent studies have identified TERT rearrangements and ATRX loss as factors associated with neuroblastoma malignancy [12, 13]. Additionally, mutations in PTPN14, DOCK8, and RAS have been linked to neuroblastoma recurrence [14, 15].

As inherent and stable genetic markers, single nucleotide polymorphisms (SNPs) serve as excellent tools for identifying disease risk factors. Previous large-scale genome-wide association studies (GWASs) have identified several SNPs associated with neuroblastoma susceptibility [16]. For example, Mario et al. identified and validated the significant associations of six SNPs of the BARD1 gene (rs6435862, rs3768716, rs17487792, rs6712055, rs7587476, and rs6715570) with high-risk neuroblastoma in the discovery cohort and independent validation cohort [17]. Moreover, we validated the associations of the BARD1 rs6435862 T > G and rs3768716 A > G polymorphisms with increased neuroblastoma susceptibility in southern Chinese children [18]. Another GWAS revealed that BARD1 rs17489363 and rs1048108 are associated with a high risk of neuroblastoma and that rs17489363 C > T may promote the proliferation of neuroblastoma by reducing BARD1 expression [19]. Maris et al. reported that a genetic variant (rs110419) of the LIM domain only 1 (LMO1) gene was significantly associated with an increased risk of neuroblastoma [16]. A three-center case-control study from eastern China also revealed a significant association between SNPs in the LMO1 gene (rs110419, rs4758051, rs10840002, and rs2168101) and neuroblastoma risk [20]. The rs2168101 G > T polymorphism reduces the binding of this locus to transcription factors, thereby reducing the expression of the oncogene LMO1, which reduces the susceptibility to neuroblastoma [21]. Based on the pleiotropic effects of genetic factors, Formicola et al. identified rs13337397 as being highly associated with neuroblastoma by a meta-analysis of GWAS data for neuroblastoma and coronary artery disease [22]. Additionally, the risk allele at rs13337397 significantly increases CFDP1 gene expression, and high CFDP1 gene expression is associated with neuroblastoma cell survival and proliferation. A cross-association analysis combining the GWAS results for melanoma and neuroblastoma revealed a significant association of rs2153977 with neuroblastoma, and the minor allele of rs2153977 was observed to reduce SLC16A1 gene expression [23]. The SLC16A1 gene has been observed to be associated with the worst clinical outcome, as well as associated with neuroblastoma cell proliferation and invasion. In a GWAS involving 2817 neuroblastoma patients and 7473 controls, HACE1 rs4336470 and LIN28B rs17065417 were observed to be associated with the risk of neuroblastoma [24]. Specifically, rs17065417 may influence neuroblastoma development by modulating LIN28B gene expression. We have identified several SNPs associated with neuroblastoma susceptibility via the use of candidate gene approaches, including polymorphisms in the ERCC1, XPF, ALKBH5, NSUN2, and TET2 genes [25,26,27,28]. However, the current findings remain insufficient to fully elucidate the genetic mechanisms underlying all cases of neuroblastoma.

In recent years, a growing body of evidence has demonstrated that RNA methylations play crucial roles in tumorigenesis [29]. N1-adenosine methylation (m1A) is a prevalent RNA modification that occurs in eukaryotes. Initially, the m1A modification was identified as a conserved modification in tRNA and rRNA, and recent evidence indicates that the m1A modification is also present in mRNAs [30, 31]. The identified m1A methyltransferase genes include TRMT6, TRMT61A, TRMT61B, and TRMT10C. Additionally, the methyltransferases that primarily recognize N1-methyladenosine in tRNAs regulate tRNA-mediated translation processes [32]. The demethylases of the ALKBH1 and ALKBH3 genes recognize tRNAs to facilitate the demethylation of m1A [33, 34]. Moreover, YTHDF1, YTHDF2, YTHDF3, and YTHDC1 proteins recognize m1A modifications and regulate RNA stability [35]. Wang et al. reported a significant increase in m1A modifications in hepatocellular carcinoma (HCC) [36]. In addition, the TRMT6/TRMT61A complex elevates m1A in tRNAs, thereby increasing PPARδ translation and potentially mediating the growth of cancer. A high expression level of the TRMT10C gene is associated with poor prognosis in HCC patients and may contribute to adverse cancer progression via the PI3K-Akt signaling pathway [37]. The ALKBH3 protein promotes the expression of CSF-1 through the demethylation of CSF-1 mRNA, thus contributing to the malignant progression of ovarian and breast cancers [38]. Furthermore, m1A genes play a significant role in various cancers. However, their role in neuroblastoma remains unclear. Therefore, we hypothesized that SNPs in m1A modification genes could influence gene expression and mediate neuroblastoma development. To test this hypothesis, we conducted a case-control study to investigate the associations between m1A gene polymorphisms and neuroblastoma susceptibility in Chinese children.

Materials and methods

Study subjects

We recruited 402 children who were diagnosed with neuroblastoma (case group) and 473 children without any tumors (control group) from the Children’s Hospital of Nanjing Medical University (Table S1) [27, 39, 40]. The participants in the case group had a confirmed histopathological diagnosis of primary neuroblastoma, had no history of malignancies in other organs, and had not received chemotherapy prior to sample collection. The control group consisted of healthy children aged 0–14 years who had no history of tumors, neurological disorders, congenital genetic diseases, infectious diseases, or other significant medical conditions. Written informed consent was obtained from all of the participants or their legal guardians. This study was approved by the Institutional Review Committee of Children’s Hospital of Nanjing Medical University (Approval No: 202112141-1).

Polymorphism selection and genotyping

We conducted a comprehensive screening of SNPs in the 5’ flanking region, 5’ untranslated region (UTR), 3’ UTR, and intron and exon regions of the m1A modification genes (TRMT10C, TRMT6, TRMT61A, TRMT61B, ALKBH3, YTHDF1, YTHDF2, and YTHDF3) via the dbSNP database (http://www.ncbi.nlm.nih.gov/SNP). The potential functions of the selected SNPs were predicted by the online tool SNPinfo (https://snpinfo.niehs.nih.gov/). Single nucleotide polymorphisms located in the coding regions of functional genes that could cause amino acid variations (nonsynonymous SNPs), SNPs located in microRNAs, transcription factor-binding sites, and SNPs affecting splicing were included in this study. The MAF of the selected SNPs was determined to be greater than 5% in the Chinese Han population. The LDlink tool (https://ldlink.nih.gov/) was employed to assess the linkage disequilibrium (LD) between SNPs, and there was no significant LD observed between the SNPs (R²<0.8). Finally, we successfully included 23 SNPs in the m1A genes, and their functional annotations are shown in Table S2. Genomic DNA was extracted from the blood or tissue samples of all of the subjects via a TIANamp DNA Kit (TianGen Biotech Co. Ltd., Beijing, China). The DNA concentration and purity were assessed via a UV spectrophotometer (NanoDrop Technologies, Inc., Wilmington, DE). Genotyping was conducted via TaqMan® SNP genotyping assays (Applied Biosystems, CA, USA) [41,42,43]. To ensure accuracy, 10% of the samples were retested, and the results demonstrated 100% concordance.

Statistical analysis

Differences in genotype frequency distribution and demographic characteristics between the case group and control group were evaluated via chi-square tests. To assess whether the genotype frequencies adhered to Hardy-Weinberg equilibrium (HWE) in the control group, a goodness-of-fit test was conducted for each SNP. Multivariate logistic regression analyses were employed to estimate the odds ratio (OR) and 95% confidence interval (CI) after adjusting for potential confounding factors (including age and sex). The statistical power was calculated via the PS (Power and Sample Size Calculations) program V.3.1.2. Among 402 neuroblastoma samples and 473 control samples, when the significance level α was 0.05 and the minor allele frequency (MAF) of the SNPs was 0.1–0.5, a power of 80% was determined to detect the minimum effect size ranging from 0.472 to 0.682 and from 1.466 to 1.766. Using the Genotype-Tissue Expression (GTEx) online portal V10 (https://www.gtexportal.org/home/), we conducted an expression quantitative trait loci (eQTL) analysis to preliminarily investigate how SNPs influence gene expression. Log2-transformed gene expression data for neuroblastoma tissues and normal adrenal gland tissues (which were consistent and comparable across the sequencing platforms) were downloaded from the R2 platform (http://r2.amc.nl) (Table S3). Nonparametric statistical tests were employed to analyze differences in gene expression between the different groups. GraphPad Prism (V9.5.1) was used to generate violin plots and bar graphs. Kaplan-Meier analyses were also performed via the R2 platform. All of the tests of statistical significance were two-sided, with a significance level set at 0.05. Raw data management was conducted via STATA V18.0, and statistical analyses were performed via SAS V9.4.

Results

Associations of m1A modification gene polymorphisms with neuroblastoma susceptibility

In this case-control study involving 402 neuroblastoma patients and 473 controls, we successfully conducted genotyping for 23 candidate polymorphisms of m1A modification genes. In the control group, the genotype frequencies of the candidate SNPs (except for rs6139878 and rs1048928) were in accordance with HWE. Table 1 presents the associations between neuroblastoma susceptibility and the SNPs of the TRMT10C, TRMT6, TRMT61A, TRMT61B, ALKBH3, YTHDF1, YTHDF2, and YTHDF3 genes. The multivariate logistic regression model, which was adjusted for confounding factors (including age and sex), demonstrated that TRMT10C rs4618204 was significantly associated with the risk of neuroblastoma. Specifically, the dominant model indicated that individuals with the CT and TT genotypes exhibited a reduced neuroblastoma susceptibility compared with those with the CC genotype (CT/TT vs. CC: adjusted OR = 0.74, 95% CI = 0.56–0.97, P = 0.030).

Table 1 Association between m1A modification gene polymorphisms and neuroblastoma risk in children from Jiangsu Province
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Stratification analysis of m1A modification gene polymorphisms

Stratification analysis revealed that the TRMT10C rs4618204 CT/TT genotype was significantly associated with a reduced risk of neuroblastoma in some subgroups (age > 18 months: adjusted OR = 0.70, 95% CI = 0.50–0.99, P = 0.040; males: adjusted OR = 0.60, 95% CI = 0.41–0.87, P = 0.008; retroperitoneal: adjusted OR = 0.68, 95% CI = 0.47–0.98, P = 0.037) (Table 2). Compared with the CC genotype, the CG/GG genotypes of TRMT10C rs3762735 were associated with an increased risk of neuroblastoma in the male (adjusted OR = 1.62, 95% CI = 1.05–2.49, P = 0.028), adrenal gland (adjusted OR = 1.89, 95% CI = 1.18–3.04, P = 0.008), and stage I + II + 4s (adjusted OR = 1.51, 95% CI = 1.02–2.22, P = 0.037) subgroups. Compared with the 0–2 risk genotype, the 3–5 risk genotype was significantly associated with an increased risk of neuroblastoma across multiple subgroups (age > 18 months: adjusted OR = 1.61, 95% CI = 1.14–2.28, P = 0.007; males: adjusted OR = 1.70, 95% CI = 1.14–2.53, P = 0.009; retroperitoneal: adjusted OR = 1.64, 95% CI = 1.13–2.39, P = 0.010; mediastinum: adjusted OR = 1.54, 95% CI = 1.01–2.35, P = 0.048; Stages I + II + 4s: adjusted OR = 1.60, 95% CI = 1.10–2.32, P = 0.013; Stages III + IV: adjusted OR = 1.53, 95% CI = 1.05–2.24, P = 0.029).

Table 2 Stratification analysis for the associations of TRMT10C gene polymorphisms with neuroblastoma risk in children from Jiangsu Province
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Compared with the TT genotype, the TC/CC genotypes of TRMT6 rs451571 were associated with a reduced risk of neuroblastoma in the subgroup of tumors originating from the mediastinum (adjusted OR = 0.63, 95% CI = 0.41–0.97, P = 0.035) (Table 3). In the retroperitoneal subgroup, the dominant model of TRMT6 rs236110 was significantly associated with reduced susceptibility to neuroblastoma (CA/AA vs. CC: adjusted OR = 0.64, 95% CI = 0.43–0.94, P = 0.022). Compared with possessing 0–2 protective genotypes, the possession of 3–5 protective genotypes was significantly associated with a reduced risk of neuroblastoma across multiple subgroups (age > 18 months: adjusted OR = 0.53, 95% CI = 0.38–0.75, P = 0.0003; males: adjusted OR = 0.58, 95% CI = 0.39–0.86, P = 0.006; adrenal gland: adjusted OR = 0.60, 95% CI = 0.37–0.96, P = 0.034; retroperitoneal: adjusted OR = 0.66, 95% CI = 0.45–0.96, P = 0.028; stages I + II + 4s: adjusted OR = 0.64, 95% CI = 0.45–0.93, P = 0.019; stages III + IV: adjusted OR = 0.66, 95% CI = 0.46–0.97, P = 0.032).

Table 3 Stratification analysis for the associations of TRMT6 gene polymorphisms with neuroblastoma risk in children from Jiangsu Province
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The dominant model of ALKBH3 rs10768993 was significantly associated with a reduced risk of neuroblastoma in the subgroup of tumors originating from the mediastinum (GA/AA vs. GG: adjusted OR = 0.62, 95% CI = 0.41–0.93, P = 0.021) (Table 4). Compared with the CC genotype, in children aged ≤ 18 months (adjusted OR = 0.37, 95% CI = 0.17–0.85, P = 0.018) and females (adjusted OR = 0.47, 95% CI = 0.26–0.84, P = 0.012), the presence of the ALKBH3 rs2292889 CG/GG genotype was significantly associated with a reduced risk of neuroblastoma. In terms of candidate SNPs of the ALKBH3 gene, five protective genotypes were significantly associated with a reduced risk of neuroblastoma compared with 0–4 genotypes in the age > 18 months (adjusted OR = 0.64, 95% CI = 0.46–0.89, P = 0.009) and mediastinum (adjusted OR = 0.60, 95% CI = 0.39–0.90, P = 0.014) subgroups.

Table 4 Stratification analysis for the associations of ALKBH3 gene polymorphisms with neuroblastoma risk in children from Jiangsu Province
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No significant associations were identified between the polymorphisms of the YTHDF1 (rs6011668) and YTHDF3 (rs7464) genes and neuroblastoma susceptibility within the analyzed subgroups (Table 5).

Table 5 Stratification analysis for the associations of YTHDF1 and YTHDF3 gene polymorphisms with neuroblastoma risk in children from Jiangsu Province
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eQTL analysis of significant polymorphisms

Our findings demonstrated that TRMT10C rs4618204 C > T significantly influences the risk of neuroblastoma. To investigate the relationship between rs4618204 C > T and gene expression, we conducted eQTL analysis using data from the GTEx database. Given that rs4618204 was not found in the GTEx database, we utilized the LDlink tool to identify SNPs in complete linkage disequilibrium with rs4618204 within the Chinese Han population (R2 = 1.00). We subsequently investigated the impacts of these SNPs on gene expression via GTEx data. We observed that the genotypes of the SNPs in complete linkage disequilibrium with the rs4618204 T allele were associated with reduced TRMT10C gene expression (Table S4). Specifically, we focused on rs6809742, which is located near the TRMT10C gene, as well as rs13072301, which resides within an intronic region of the TRMT10C gene (Fig. 1A). The eQTL analysis revealed that both the rs6809742 T > C and rs13072301 C > G variants were associated with downregulated TRMT10C gene expression in skeletal muscle (Fig. 1B, D) and tibial artery tissues (Fig. 1C, E).

Fig. 1
figure 1

Complete linkage analysis and eQTL analysis demonstrated the impact of the TRMT10C rs4618204 C > T polymorphism on gene expression. A, TRMT10C rs4618204 C > T is fully linked to rs13072301 T > C and rs6809742 C > G (R2 = 1). B-C, rs13072301 T > C is associated with reduced expression of the TRMT10C gene in both skeletal muscle (P = 4.73 × 10− 6) and tibial artery tissues (P = 2.47 × 10− 4). D-E, rs6809742 C > G significantly decreases TRMT10C gene expression in both skeletal muscle (P = 3.62 × 10− 6) and tibial artery tissues (P = 2.93 × 10− 4)

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Association of the TRMT10C gene with risk and prognosis in neuroblastomas

The eQTL results revealed that rs4618204 C > T was associated with decreased expression of the TRMT10C gene. Compared with that in the normal adrenal gland group, TRMT10C gene expression was significantly elevated in the neuroblastoma group (Fig. 2A). In high-risk (Fig. 2B) and advanced-stage (Fig. 2C) neuroblastoma patients, the expression level of the TRMT10C gene was significantly elevated. Kaplan-Meier analyses demonstrated that elevated TRMT10C gene expression was significantly correlated with adverse outcomes in neuroblastoma patients (Fig. 2D, E).

Fig. 2
figure 2

The impact of TRMT10C gene expression on the risk, invasion, and prognosis of neuroblastoma. A, TRMT10C gene expression is significantly elevated in neuroblastoma tissues compared with normal adrenal gland tissues. B, TRMT10C gene expression is significantly elevated in the high-risk neuroblastoma group compared with the non-high-risk group. C, TRMT10C gene expression is significantly elevated in stage 4 neuroblastoma patients compared with other clinical stage groups. D-E, Increased expression of the TRMT10C gene is significantly associated with reduced event-free survival (EFS) and overall survival (OS) in neuroblastoma patients

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Discussion

We conducted a case-control study involving 402 neuroblastoma patients and 473 cancer-free controls from China to investigate the associations between 23 polymorphisms of m1A modification genes and neuroblastoma susceptibility. Our findings revealed that TRMT10C rs4618204 C > T was significantly associated with a reduced risk of neuroblastoma. Additionally, some polymorphisms of the TRMT10C (rs3762735), TRMT6 (rs451571 and rs236110), and ALKBH3 (rs10768993 and rs2292889) genes were observed to be associated with the risk of neuroblastoma in certain subgroups.

To elucidate the potential mechanism by which TRMT10C rs4618204 C > T influences neuroblastoma susceptibility, we conducted a comprehensive linkage analysis and eQTL analysis. Our findings revealed that the rs4618204 T allele was associated with reduced expression of the TRMT10C gene in skeletal muscle and tibial artery tissues. Additionally, we observed significantly elevated TRMT10C gene expression in neuroblastoma tissues compared with normal adrenal gland tissues. Notably, TRMT10C gene expression was also significantly greater in both high-risk and advanced-stage neuroblastoma patients. These results indicate that increased TRMT10C gene expression is linked to neuroblastoma risk and invasiveness. Furthermore, Kaplan-Meier analyses demonstrated that high TRMT10C gene expression was associated with poorer prognosis in neuroblastoma patients. Collectively, these findings support the significant association between the rs4618204 C > T polymorphism and a reduced risk of neuroblastoma. The rs4618204 C > T variant or linked SNPs may mitigate neuroblastoma risk by downregulating TRMT10C gene expression. Taken together, our results suggest that rs4618204 C > T is a credible biomarker for neuroblastoma risk.

Our results also suggest that the expression of the TRMT10C gene may play an important role in the development and progression of neuroblastoma. The TRMT10C demethylase interacts with SDR5C1 to methylate position 9 of the mitochondrial tRNA [44]. It also catalyzes the formation of m1A modifications at position 9 of the mitochondrial ND5 mRNA, which play crucial roles in regulating mitochondrial protein translation and function [45]. Metodiev et al. demonstrated that mutations in the TRMT10C gene can affect MRPP1 protein stability and mt-tRNA processing, thereby leading to mitochondrial disease [46]. Elevated expression of the TRMT10C gene was observed to be associated with poor prognosis in both glioma and HCC patients [47, 48]. The expression level of the TRMT10C gene was demonstrated to be positively correlated with the proliferation, colony formation, and migration of both ovarian and cervical cancer cells [49]. Consistent with our findings, previous studies have demonstrated that the TRMT10C gene functions as an oncogene. Yu et al. reported via GSEA that the upregulation of the TRMT10C gene is associated with cell division and the MYC pathway [37]. Additionally, the downregulation of genes involved in cell division was demonstrated to be the mechanism of cell death induced by HDAC11 depletion in neuroblastoma cells [50]. As an important member of the MYC family, the MYCN gene is frequently amplified in neuroblastoma [51]. Amplification of the MYCN oncogene is associated with high-risk neuroblastoma and poor prognosis [52]. Zhu et al. reported that the MYCN gene synergizes with the LMO1 gene to promote the proliferation of adrenal precursor cells, thereby contributing to the development of neuroblastoma [53]. These results suggest that TRMT10C may affect the development of neuroblastoma by interacting with cell division and the MYC pathway. The precise molecular mechanisms by which the TRMT10C gene influences the onset and progression of neuroblastoma warrant further investigation.

Additionally, stratification analysis revealed that polymorphisms of the TRMT10C (rs3762735 C > G), TRMT6 (rs451571 T > C and rs236110 C > A), and ALKBH3 (rs10768993 G > A and rs2292889 C > G) genes were associated with the risk of neuroblastoma in certain subgroups. Liu et al. reported that the rs3762735 C > G polymorphism is associated with increased hepatoblastoma susceptibility [54]. Moreover, Chang et al. reported that the rs236110 C > A polymorphism is associated with an elevated risk of Wilms tumor [55]. In contrast, our findings indicate that this variant may reduce the risk of neuroblastoma in specific subgroups. These observations suggest that the rs236110 C > A polymorphism may exert distinct effects across different types of tumors.

For the first time, we identified a significant association between m1A modification gene polymorphisms and neuroblastoma susceptibility in Chinese children, along with the underlying involved mechanisms. Our findings provide important molecular markers for the early diagnosis of neuroblastoma and offer insights into its pathogenesis. However, this study has several limitations. First, our study population was derived from Nanjing, China, and further research incorporating samples from a broader geographic distribution is necessary to validate the generalizability of these findings. Second, we did not account for additional environmental factors, which may have resulted in an underestimation of the potential interactions between genetic and environmental factors in the development of neuroblastoma. Third, the use of multiple tests to explore susceptibility loci in neuroblastoma may lead to false-positive results. We adjusted P values with the use of the Bonferroni method, which is a more stringent method for adjusting for multiple testing approaches and may lead to nonsignificant associations due to the performance of too many tests. The preliminary positive results require further validation in independent cohorts of neuroblastoma patients and controls. Finally, two SNPs (rs6809742 T > C and rs13072301 C > G) completely linked to rs4618204 C > T were observed to reduce TRMT10C gene expression in skeletal muscle and tibial artery tissues via eQTL analysis of the GTEx database. No significant associations were observed between these two SNPs and gene expression in adrenal gland tissues. Further studies are needed to verify the association between rs4618204 C > T and the TRMT10C gene in adrenal tissues and explore the specific mechanism affecting neuroblastoma.

Conclusion

In summary, our findings demonstrate a significant association between the TRMT10C gene rs4618204 C > T polymorphism and a reduced risk of neuroblastoma. These results provide an important molecular marker for the early diagnosis of neuroblastoma.

Data availability

All of the data are available upon request.

Abbreviations

ALK:

Anaplastic lymphoma kinase

SNP:

Single nucleotide polymorphism

GWAS:

Genome-wide association study

LMO1:

LIM domain only 1

m1A:

N1-methyladenosine

HCC:

Hepatocellular carcinoma

UTR:

Untranslated region

MAF:

Minor allele frequency

LD:

Linkage disequilibrium

HWE:

Hardy-Weinberg equilibrium

OR:

Odds ratio

CI:

Confidence interval

GTEx:

Genotype-Tissue Expression

eQTL:

Expression quantitative trait loci

EFS:

Event-free survival

OS:

Overall survival

References

  1. Kameneva P, Artemov AV, Kastriti ME, Faure L, Olsen TK, Otte J, et al. Single-cell transcriptomics of human embryos identifies multiple sympathoblast lineages with potential implications for neuroblastoma origin. Nat Genet. 2021;53(5):694–706.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Zafar A, Wang W, Liu G, Wang X, Xian W, McKeon F, et al. Molecular targeting therapies for neuroblastoma: progress and challenges. Med Res Rev. 2021;41(2):961–1021.

    Article  PubMed  Google Scholar 

  3. He M, Cai JB, Wu X, Tang YB, Wang JY, Mao JQ, et al. Perioperative complication incidence and risk factors for retroperitoneal neuroblastoma in children: analysis of 571 patients. World J Pediatr. 2024;20(3):250–8.

    Article  PubMed  Google Scholar 

  4. Bao PP, Li K, Wu CX, Huang ZZ, Wang CF, Xiang YM, et al. [Recent incidences and trends of childhood malignant solid tumors in Shanghai, 2002–2010]. Zhonghua Er Ke Za Zhi. 2013;51(4):288–94.

    PubMed  Google Scholar 

  5. Tas ML, Reedijk AMJ, Karim-Kos HE, Kremer LCM, van de Ven CP, Dierselhuis MP, et al. Neuroblastoma between 1990 and 2014 in the Netherlands: increased incidence and improved survival of high-risk neuroblastoma. Eur J Cancer. 2020;124:47–55.

    Article  CAS  PubMed  Google Scholar 

  6. Steliarova-Foucher E, Colombet M, Ries LAG, Moreno F, Dolya A, Bray F, et al. International incidence of childhood cancer, 2001-10: a population-based registry study. Lancet Oncol. 2017;18(6):719–31.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Kholodenko IV, Kalinovsky DV, Doronin II, Deyev SM, Kholodenko RV. Neuroblastoma origin and therapeutic targets for immunotherapy. J Immunol Res. 2018;2018:7394268.

  8. Irwin MS, Naranjo A, Zhang FF, Cohn SL, London WB, Gastier-Foster JM, et al. Revised neuroblastoma risk classification system: A report from the children’s oncology group. J Clin Oncol. 2021;39(29):3229–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Zhang J, Zhao Y, Wang J, Sneh T, Yu Q, Zhou X, et al. NBPF1 independently determine the risk stratification and prognosis of patients with neuroblastoma. Genomics. 2020;112(6):3951–7.

    Article  CAS  PubMed  Google Scholar 

  10. Bagatell R, Beck-Popovic M, London WB, Zhang Y, Pearson AD, Matthay KK, et al. Significance of MYCN amplification in international neuroblastoma staging system stage 1 and 2 neuroblastoma: a report from the international neuroblastoma risk group database. J Clin Oncol. 2009;27(3):365–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Azarova AM, Gautam G, George RE. Emerging importance of ALK in neuroblastoma. Semin Cancer Biol. 2011;21(4):267–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Valentijn LJ, Koster J, Zwijnenburg DA, Hasselt NE, van Sluis P, Volckmann R, et al. TERT rearrangements are frequent in neuroblastoma and identify aggressive tumors. Nat Genet. 2015;47(12):1411–4.

    Article  CAS  PubMed  Google Scholar 

  13. Molenaar JJ, Koster J, Zwijnenburg DA, van Sluis P, Valentijn LJ, van der Ploeg I, et al. Sequencing of neuroblastoma identifies chromothripsis and defects in neuritogenesis genes. Nature. 2012;483(7391):589–93.

    Article  CAS  PubMed  Google Scholar 

  14. Schramm A, Köster J, Assenov Y, Althoff K, Peifer M, Mahlow E, et al. Mutational dynamics between primary and relapse neuroblastomas. Nat Genet. 2015;47(8):872–7.

    Article  CAS  PubMed  Google Scholar 

  15. Lin L, Miao L, Lin H, Cheng J, Li M, Zhuo Z, et al. Targeting RAS in neuroblastoma: is it possible? Pharmacol Ther. 2022;236:108054.

    Article  CAS  PubMed  Google Scholar 

  16. Wang K, Diskin SJ, Zhang H, Attiyeh EF, Winter C, Hou C, et al. Integrative genomics identifies LMO1 as a neuroblastoma oncogene. Nature. 2011;469(7329):216–20.

    Article  CAS  PubMed  Google Scholar 

  17. Capasso M, Devoto M, Hou C, Asgharzadeh S, Glessner JT, Attiyeh EF, et al. Common variations in BARD1 influence susceptibility to high-risk neuroblastoma. Nat Genet. 2009;41(6):718–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhang R, Zou Y, Zhu J, Zeng X, Yang T, Wang F, et al. The association between GWAS-identified BARD1 gene SNPs and neuroblastoma susceptibility in a Southern Chinese population. Int J Med Sci. 2016;13(2):133–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Cimmino F, Avitabile M, Diskin SJ, Vaksman Z, Pignataro P, Formicola D, et al. Fine mapping of 2q35 high-risk neuroblastoma locus reveals independent functional risk variants and suggests full-length BARD1 as tumor-suppressor. Int J Cancer. 2018;143(11):2828–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. He L, Zhu J, Han F, Tang Y, Zhou C, Dai J, et al. LMO1 gene polymorphisms reduce neuroblastoma risk in Eastern Chinese children: A Three-Center Case-Control study. Front Oncol. 2018;8:468.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Oldridge DA, Wood AC, Weichert-Leahey N, Crimmins I, Sussman R, Winter C, et al. Genetic predisposition to neuroblastoma mediated by a LMO1 super-enhancer polymorphism. Nature. 2015;528(7582):418–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Formicola D, Lasorsa VA, Cantalupo S, Testori A, Cardinale A, Avitabile M, et al. CFDP1 is a neuroblastoma susceptibility gene that regulates transcription factors of the noradrenergic cell identity. HGG Adv. 2023;4(1):100158.

    CAS  PubMed  Google Scholar 

  23. Avitabile M, Succoio M, Testori A, Cardinale A, Vaksman Z, Lasorsa VA, et al. Neural crest-derived tumor neuroblastoma and melanoma share 1p13.2 as susceptibility locus that shows a long-range interaction with the SLC16A1 gene. Carcinogenesis. 2020;41(3):284–95.

    Article  CAS  PubMed  Google Scholar 

  24. Diskin SJ, Capasso M, Schnepp RW, Cole KA, Attiyeh EF, Hou C, et al. Common variation at 6q16 within HACE1 and LIN28B influences susceptibility to neuroblastoma. Nat Genet. 2012;44(10):1126–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Zhuo ZJ, Liu W, Zhang J, Zhu J, Zhang R, Tang J, et al. Functional polymorphisms at ERCC1/XPF genes confer neuroblastoma risk in Chinese children. EBioMedicine. 2018;30:113–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Guan Q, Lin H, Hua W, Lin L, Liu J, Deng L, et al. Variant rs8400 enhances ALKBH5 expression through disrupting miR-186 binding and promotes neuroblastoma progression. Chin J Cancer Res. 2023;35(2):140–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lin L, Deng C, Zhou C, Zhang X, Zhu J, Liu J, et al. NSUN2 gene rs13181449 C > T polymorphism reduces neuroblastoma risk. Gene. 2023;854:147120.

    Article  CAS  PubMed  Google Scholar 

  28. Lin L, Wang B, Zhang X, Deng C, Zhou C, Zhu J, et al. Functional TET2 gene polymorphisms increase the risk of neuroblastoma in Chinese children. IUBMB Life. 2024;76(4):200–11.

    Article  CAS  PubMed  Google Scholar 

  29. Barbieri I, Kouzarides T. Role of RNA modifications in cancer. Nat Rev Cancer. 2020;20(6):303–22.

    Article  CAS  PubMed  Google Scholar 

  30. RajBhandary UL, Stuart A, Faulkner RD, Chang SH, Khorana HG. Nucleotide sequence studies on yeast phenylalanine sRNA. Cold Spring Harb Symp Quant Biol. 1966;31:425–34.

    Article  CAS  PubMed  Google Scholar 

  31. Dominissini D, Nachtergaele S, Moshitch-Moshkovitz S, Peer E, Kol N, Ben-Haim MS, et al. The dynamic N(1)-methyladenosine methylome in eukaryotic messenger RNA. Nature. 2016;530(7591):441–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Chujo T, Suzuki T. Trmt61B is a methyltransferase responsible for 1-methyladenosine at position 58 of human mitochondrial tRNAs. RNA. 2012;18(12):2269–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Liu F, Clark W, Luo G, Wang X, Fu Y, Wei J, et al. ALKBH1-Mediated tRNA demethylation regulates translation. Cell. 2016;167(3):816–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Chen Z, Qi M, Shen B, Luo G, Wu Y, Li J, et al. Transfer RNA demethylase ALKBH3 promotes cancer progression via induction of tRNA-derived small RNAs. Nucleic Acids Res. 2019;47(5):2533–45.

    Article  CAS  PubMed  Google Scholar 

  35. Liu Y, Zhang S, Gao X, Ru Y, Gu X, Hu X. Research progress of N1-methyladenosine RNA modification in cancer. Cell Commun Signal. 2024;22(1):79.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Wang Y, Wang J, Li X, Xiong X, Wang J, Zhou Z, et al. N(1)-methyladenosine methylation in tRNA drives liver tumourigenesis by regulating cholesterol metabolism. Nat Commun. 2021;12(1):6314.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Shi Q, Xue C, Yuan X, He Y, Yu Z. Gene signatures and prognostic values of m1A-related regulatory genes in hepatocellular carcinoma. Sci Rep. 2020;10(1):15083.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Woo HH, Chambers SK. Human ALKBH3-induced m(1)A demethylation increases the CSF-1 mRNA stability in breast and ovarian cancer cells. Biochim Biophys Acta Gene Regul Mech. 2019;1862(1):35–46.

    Article  CAS  PubMed  Google Scholar 

  39. Guan Q, Zhang X, Liu J, Zhou C, Zhu J, Wu H, et al. ALKBH5 gene polymorphisms and risk of neuroblastoma in Chinese children from Jiangsu Province. Cancer Innov. 2024;3(2):e103.

    Article  CAS  PubMed  Google Scholar 

  40. Zhang W, Zhu J, Zhang M, Chang J, Liu J, Chen L, et al. Improving neuroblastoma risk prediction through a polygenic risk score derived from genome-wide association study-identified loci. Chin J Cancer Res. 2025;37(1):1–11.

    Article  PubMed  PubMed Central  Google Scholar 

  41. He J, Yuan L, Lin H, Lin A, Chen H, Luo A, et al. Genetic variants in m(6)A modification core genes are associated with glioma risk in Chinese children. Mol Ther Oncolytics. 2021;20:199–208.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Yin H, Wang X, Zhang S, He S, Zhang W, Lu H, et al. Nucleotide excision repair gene polymorphisms and hepatoblastoma susceptibility in Eastern Chinese children: A five-center case-control study. Chin J Cancer Res. 2024;36(3):298–305.

    PubMed  PubMed Central  Google Scholar 

  43. Chen YP, Liao YX, Zhuo ZJ, Yuan L, Lin HR, Miao L, et al. Association between genetic polymorphisms of base excision repair pathway and glioma susceptibility in Chinese children. World J Pediatr. 2022;18(9):632–5.

    Article  CAS  PubMed  Google Scholar 

  44. Vilardo E, Nachbagauer C, Buzet A, Taschner A, Holzmann J, Rossmanith W. A subcomplex of human mitochondrial RNase P is a bifunctional methyltransferase–extensive moonlighting in mitochondrial tRNA biogenesis. Nucleic Acids Res. 2012;40(22):11583–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Safra M, Sas-Chen A, Nir R, Winkler R, Nachshon A, Bar-Yaacov D, et al. The m1A landscape on cytosolic and mitochondrial mRNA at single-base resolution. Nature. 2017;551(7679):251–5.

    Article  CAS  PubMed  Google Scholar 

  46. Metodiev MD, Thompson K, Alston CL, Morris AAM, He L, Assouline Z, et al. Recessive mutations in TRMT10C cause defects in mitochondrial RNA processing and multiple respiratory chain deficiencies. Am J Hum Genet. 2016;98(5):993–1000.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Mao M, Chu Q, Lou Y, Lv P, Wang LJ. RNA N1-methyladenosine regulator-mediated methylation modification patterns and heterogeneous signatures in glioma. Front Immunol. 2022;13:948630.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Li D, Li K, Zhang W, Yang KW, Mu DA, Jiang GJ, et al. The m6A/m5C/m1A regulated gene signature predicts the prognosis and correlates with the immune status of hepatocellular carcinoma. Front Immunol. 2022;13:918140.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wang Q, Zhang Q, Huang Y, Zhang J. m1A regulator TRMT10C predicts poorer survival and contributes to malignant behavior in gynecological cancers. DNA Cell Biol. 2020;39(10):1767–78.

    Article  CAS  PubMed  Google Scholar 

  50. Thole TM, Lodrini M, Fabian J, Wuenschel J, Pfeil S, Hielscher T, et al. Neuroblastoma cells depend on HDAC11 for mitotic cell cycle progression and survival. Cell Death Dis. 2017;8(3):e2635.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Combaret V, Bergeron C, Noguera R, Iacono I, Puisieux A. Circulating MYCN DNA predicts MYCN-amplification in neuroblastoma. J Clin Oncol. 2005;23(34):8919–20. author reply 8920.

    Article  PubMed  Google Scholar 

  52. Matthay KK, Maris JM, Schleiermacher G, Nakagawara A, Mackall CL, Diller L, et al. Neuroblastoma. Nat Rev Dis Primers. 2016;2:16078.

    Article  PubMed  Google Scholar 

  53. Zhu S, Zhang X, Weichert-Leahey N, Dong Z, Zhang C, Lopez G, et al. LMO1 synergizes with MYCN to promote neuroblastoma initiation and metastasis. Cancer Cell. 2017;32(3):310–e323315.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Liu Y, Zhu J, Wang X, Zhang W, Li Y, Yang Z, et al. TRMT10C gene polymorphisms confer hepatoblastoma susceptibility: evidence from a seven-center case-control study. J Cancer. 2024;15(16):5396–402.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Chang X, Zhu J, Hua RX, Deng C, Zhang J, Cheng J, et al. TRMT6 gene rs236110 C > A polymorphism increases the risk of Wilms tumor. Gene. 2023;882:147646.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

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Funding

This work was supported by the National Natural Science Foundation of China (No: 82173593, 32300473), Guangzhou Science and Technology Project (No: 2025A04J4696, 2025A04J4537), and Guangdong Basic and Applied Basic Research Foundation (No: 2023A1515220053).

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Author notes

  1. Jiaming Chang, Lei Lin and Wenli Zhang contributed equally to this work.

Authors and Affiliations

  1. Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangdong Provincial Key Laboratory of Research in Structural Birth Defect Disease, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, 9 Jinsui Road, Guangzhou, 510623, Guangdong, China

    Jiaming Chang, Lei Lin, Wenli Zhang, Jiliang Yang, Mengzhen Zhang, Huimin Yin, Xinxin Zhang, Yan Zou & Jing He

  2. Department of Pathology, Children’s Hospital of Nanjing Medical University, Nanjing, 210008, Jiangsu, China

    Chunlei Zhou

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  1. Jiaming Chang
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Contributions

All of the involved authors significantly contributed to this research. Jiaming Chang, Lei Lin, Wenli Zhang, Yan Zou, and Jing He: study design; data analysis; table and figure preparation; original article writing; and final approval of the article. Jiaming Chang, Wenli Zhang, Xinxin Zhang, and Jing He: funding acquisition. Chunlei Zhou: sample and data collection; and final approval of the article. Jiliang Yang, Mengzhen Zhang, Huimin Yin, and Xinxin Zhang: DNA extraction; TaqMan genotyping; and final approval of the article.

Corresponding authors

Correspondence to Yan Zou or Jing He.

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The research scheme was approved by the institutional review board of Children’s Hospital of Nanjing Medical University (Approval No: 202112141-1). In accordance with the guidelines of the Declaration of Helsinki, each participant provided written informed consent.

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Chang, J., Lin, L., Zhang, W. et al. Genetic variants of m1A modification genes and the risk of neuroblastoma: novel insights from a Chinese case-control study. Hum Genomics 19, 50 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40246-025-00767-0

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Keywords

Human Genomics

ISSN: 1479-7364