A five-gene signature derived from m6A regulators to improve prognosis prediction of neuroblastoma

Predictive role of SLC1A5 in neuroblastoma prognosis and immunotherapy

BACKGROUND

Neuroblastoma, a prevalent extracranial solid tumor in pediatric patients, demonstrates significant clinical heterogeneity, ranging from spontaneous regression to aggressive metastatic disease. Despite advances in treatment, high-risk neuroblastoma remains associated with poor survival. SLC1A5, a key glutamine transporter, plays a dual role in promoting tumor growth and immune modulation. However, its contributions to neuroblastoma biology remain largely unexplored.

METHODS

This study utilized clinical neuroblastoma samples from 20 patients and 1310 cases from four public datasets to investigate SLC1A5 expression, biological function, and prognostic significance. Differential expression, Kaplan-Meier survival analysis, gene set enrichment analysis, and weighted correlation network analysis were conducted. Functional validation included qPCR, immunohistochemistry, Western blotting, and cell proliferation assays using the SLC1A5 inhibitor V-9302. A prognostic signature, SRPS, was constructed and validated using machine-learning approaches. Immune infiltration analysis was performed to evaluate the tumor immune microenvironment.

RESULTS

SLC1A5 expression was significantly elevated in high-risk neuroblastoma and correlated with advanced stages and poor prognosis. GSEA revealed mTORC1 signaling enrichment in high SLC1A5 expression groups, validated by increased p-p70S6K levels in tumor samples and neuroblastoma cells. V-9302 treatment suppressed mTORC1 signaling and inhibited cell proliferation. Hub-genes were identified to form the SRPS model, which demonstrated superior prognostic performance compared to existing models. Immune infiltration analysis revealed a more immunosuppressive tumor microenvironment associated with high SLC1A5 expression. Additionally, SLC1A5 negatively regulated ST8SIA1, a gene crucial for GD2 biosynthesis, suggesting that SLC1A5 inhibition may enhance GD2-directed immunotherapies.

CONCLUSION

SLC1A5 plays a pivotal role in neuroblastoma by promoting tumor progression and shaping an immunosuppressive microenvironment. The SRPS model, incorporating SLC1A5-associated genes, offers robust prognostic utility. Targeting SLC1A5 through advanced drug delivery systems and combined metabolic-immunotherapeutic strategies may enhance treatment specificity and efficacy. These findings provide a foundation for novel therapeutic approaches to improve outcomes in high-risk neuroblastoma patients.

IGF2BPs as novel m6A readers: Diverse roles in regulating cancer cell biological functions, hypoxia adaptation, metabolism, and immunosuppressive tumor microenvironment

m6A methylation is the most frequent modification of mRNA in eukaryotes and plays a crucial role in cancer progression by regulating biological functions. Insulin-like growth factor 2 mRNA-binding proteins (IGF2BP) are newly identified m6A 'readers'. They belong to a family of RNA-binding proteins, which bind to the m6A sites on different RNA sequences and stabilize them to promote cancer progression. In this review, we summarize the mechanisms by which different upstream factors regulate IGF2BP in cancer. The current literature analyzed here reveals that the IGF2BP family proteins promote cancer cell proliferation, survival, and chemoresistance, inhibit apoptosis, and are also associated with cancer glycolysis, angiogenesis, and the immune response in the tumor microenvironment. Therefore, with the discovery of their role as 'readers' of m6A and the characteristic re-expression of IGF2BPs in cancers, it is important to elucidate their mechanism of action in the immunosuppressive tumor microenvironment. We also describe in detail the regulatory and interaction network of the IGF2BP family in downstream target RNAs and discuss their potential clinical applications as diagnostic and prognostic markers, as well as recent advances in IGF2BP biology and associated therapeutic value.

Identification of m6A-associated genes as prognostic and immune-associated biomarkers in Wilms tumor

OBJECTIVES

Wilms tumor (WT) is a common renal malignant tumor in children. We aimed to investigate the potential prognostic value of m6A-related genes and their relationship to the immune microenvironment in WT.

METHODS

RNA-seq data and clinical information from 121 WT and 6 normal samples were obtained from the University of California Santa Cruz Xena database. We used various bioinformatics analysis tools to analyze these data and verify the expression level of m6A-related genes by experiments.

RESULTS

Four m6A-related genes were successfully screened, including ADGRG2, CPD, CTHRC1, and LRTM2. Kaplan-Meier survival curves showed that the four genes were closely related to the prognosis of WT, which was also confirmed by receiver operator characteristic curves. Subsequently, in the immune microenvironment of WT, we discovered that Th1_cells were positively correlated with ADGRG2, CCR was negatively correlated with CPD, CCR was positively correlated with CTHRC1, APC_co_stimulation, CCR, Macrophages, inflammation-promoting cells, Treg, and Type_II_IFN_Reponse were negatively correlated with LRTM2. Finally, qRT-PCR showed that expression levels of the four genes were upregulated in the nephroblastoma cell lines (G-401, SK-NEP-1, and WT-CLS1) compared with the human embryonic kidney cell lines (293T).

CONCLUSIONS

Taken together, our study first time screened the m6A-related genes and revealed that ADGRG2, CPD, CTHRC1, and LRTM2 are the prognostic and immune-associated biomarkers in WT.

Development and validation of a 21-gene prognostic signature in neuroblastoma

Survival outcomes for patients with neuroblastoma vary markedly and reliable prognostic markers and risk stratification tools are lacking. We sought to identify and validate a transcriptomic signature capable of predicting risk of mortality in patients with neuroblastoma. The TARGET NBL dataset (n = 243) was used to develop the model and two independent cohorts, E-MTAB-179 (n = 478) and GSE85047 (n = 240) were used as validation sets. EFS was the primary outcome and OS was the secondary outcome of interest for all analysis. We identified a 21-gene signature capable of stratifying neuroblastoma patients into high and low risk groups in the E-MTAB-179 (HR 5.87 [3.83-9.01], p < 0.0001, 5 year AUC 0.827) and GSE85047 (HR 3.74 [2.36-5.92], p < 0.0001, 5 year AUC 0.815) validation cohorts. Moreover, the signature remained independent of known clinicopathological variables, and remained prognostic within clinically important subgroups. Further, the signature was effectively incorporated into a risk model with clinicopathological variables to improve prognostic performance across validation cohorts (Pooled Validation HR 6.93 [4.89-9.83], p < 0.0001, 5 year AUC 0.839). Similar prognostic utility was also demonstrated with OS. The identified signature is a robust independent predictor of EFS and OS outcomes in neuroblastoma patients and can be combined with clinically utilized clinicopathological variables to improve prognostic performance.

Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma

Neuroblastoma is a childhood neurological tumor which affects hundreds of thousands of children worldwide, and information about its prognosis can be pivotal for patients, their families, and clinicians. One of the main goals in the related bioinformatics analyses is to provide stable genetic signatures able to include genes whose expression levels can be effective to predict the prognosis of the patients. In this study, we collected the prognostic signatures for neuroblastoma published in the biomedical literature, and noticed that the most frequent genes present among them were three: AHCY, DPYLS3, and NME1. We therefore investigated the prognostic power of these three genes by performing a survival analysis and a binary classification on multiple gene expression datasets of different groups of patients diagnosed with neuroblastoma. Finally, we discussed the main studies in the literature associating these three genes with neuroblastoma. Our results, in each of these three steps of validation, confirm the prognostic capability of AHCY, DPYLS3, and NME1, and highlight their key role in neuroblastoma prognosis. Our results can have an impact on neuroblastoma genetics research: biologists and medical researchers can pay more attention to the regulation and expression of these three genes in patients having neuroblastoma, and therefore can develop better cures and treatments which can save patients' lives.

Combining multiple cell death pathway-related risk scores to develop neuroblastoma cell death signature

PURPOSE

Cell death plays an important role in tumourigenesis and progression; nevertheless, the clinical significance of cell death-related genes in neuroblastoma remains incompletely understood.

METHODS

We separately constructed the corresponding risk scores for each of the eight cell death pathways separately and assessed their predictive performance. Through Cox regression analysis, these eight risk scores were integrated to obtain final cell death risk scores (CDRS). We evaluated the predictive performance of CDRS in multiple datasets and compared its accuracy with the clinical characteristics of patients and some existing prognostic models for neuroblastoma. We then explored the differences in immune infiltration between the high and low CDRS groups, and the significance of CDRS on EFS and disease progression.

RESULTS

All eight risk scores have high predictive accuracy, with the Immunogenic-RS being the most accurate and the cuproptosis-RS the least accurate. Model genes are mainly enriched in a variety of cancer-related pathways and are closely related to the clinical characteristics. CDRS showed superior and robust predictive performance in multiple datasets and was more accurate than the clinical characteristics of patients and some existing prognostic models for neuroblastoma. High CDRS group featured distinct immune cold tumor profiles and may have poorer immune checkpoint inhibitor efficacy. CDRS had significance in predicting EFS and disease progression.

CONCLUSION

We integrated risk scores associated with multiple cell death pathways to develop a high-performing and robust neuroblastoma signature. CDRS was a promising tool that may help with risk assessment and prediction of overall prognosis, and thus improve clinical outcomes.

The risk of COVID-19 can be predicted by a nomogram based on m6A-related genes

BACKGROUND

The expression of m6A-related genes and their significance in COVID-19 patients are still unknown.

METHODS

The GSE177477 and GSE157103 datasets of the Gene Expression Omnibus were used to extract RNA-seq data. The expression of 26 m6A-related genes and immune cell infiltration in COVID-19 patients were analyzed. Finally, we built and validated a nomogram model to predict the risk of COVID-19 infection.

RESULTS

There were significant differences in 11 m6A regulatory factors between patients with COVID-19 and healthy individuals. The classification of disease subtypes based on m6A-related gene levels can be distinguished. COVID-19 patients in GSE177477 were classified into two categories based on m6A-related genes. The patients in cluster A were all symptomatic, while those in cluster B were asymptomatic. A significant correlation was also found between immune cells and m6A-related genes. Finally, seven m6A-related disease-characteristic genes, HNRNPA2B1, ELAVL1, RBM15, RBM15B, YTHDC1, HNRNPC, and WTAP, were screened to construct a nomogram model for predicting risk. The calibration curve, decision curve analysis, and clinical impact curve analysis were used to show that the nomogram model was effective and had a high net efficacy for risk prediction.

CONCLUSIONS

m6A-related genes were correlated with immune cells. The nomogram model effectively predicted COVID-19 risk. Moreover, m6A-related genes may be associated with the presence or absence of symptoms in COVID-19 patients.

Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma

Background

Neuroblastoma is the most common extracranial solid tumor of childhood, arising from the sympathetic nervous system. High-risk neuroblastoma (HRNB) remains a major therapeutic challenge with low survival rates despite the intensification of therapy. This study aimed to develop a malignant-cell marker gene signature (MMGS) that might serve as a prognostic indicator in HRNB patients.

Methods

Multi-omics datasets, including mRNA expression (single-cell and bulk), DNA methylation, and clinical information of HRNB patients, were used to identify prognostic malignant cell marker genes. MMGS was established by univariate Cox analysis, LASSO, and stepwise multivariable Cox regression analysis. Kaplan–Meier (KM) curve and time-dependent receiver operating characteristic curve (tROC) were used to evaluate the prognostic value and performance of MMGS, respectively. MMGS further verified its reliability and accuracy in the independent validation set. Finally, the characteristics of functional enrichment, tumor immune features, and inflammatory activity between different MMGS risk groups were also investigated.

Results

We constructed a prognostic model consisting of six malignant cell maker genes (MAPT, C1QTNF4, MEG3, NPW, RAMP1, and CDT1), which stratified patients into ultra-high-risk (UHR) and common-high-risk (CHR) group. Patients in the UHR group had significantly worse overall survival (OS) than those in the CHR group. MMGS was verified as an independent predictor for the OS of HRNB patients. The area under the curve (AUC) values of MMGS at 1-, 3-, and 5-year were 0.78, 0.693, and 0.618, respectively. Notably, functional enrichment, tumor immune features, and inflammatory activity analyses preliminarily indicated that the poor prognosis in the UHR group might result from the dysregulation of the metabolic process and immunosuppressive microenvironment.

Conclusion

This study established a novel six-malignant cell maker gene prognostic model that can be used to predict the prognosis of HRNB patients, which may provide new insight for the treatment and personalized monitoring of HRNB patients.

The role of m6A modification in pediatric cancer

With the development of RNA modification research, the importance of N6-methyladenosine (m6A) in tumors cannot be ignored. m6A promotes the self-renewal of tumor stem cells and the proliferation of tumor cells. It affects post-transcriptional gene expression through epigenetic mechanisms, combining various factors to determine proteins' fate and altering the biological function. This modification process runs through the entire tumors, and genes affected by m6A modification may be the critical targets for cancers breakthroughs. Though generally less dangerous than adult cancer, pediatric cancer accounts for a significant proportion of child deaths. What is more alarming is that the occurrences of adult tumors are highly associated with the poor prognoses of pediatric tumors. Therefore, it is necessary to pay attention to the importance of pediatric cancer and discover new therapeutic targets, which will help improve the therapeutic effect and prognoses of the diseases. We collected and investigated m6A modification in pediatric cancers based on mRNA and non-coding RNA, finding that m6A factors were involved in glioma, hepatoblastoma, nephroblastoma, neuroblastoma, osteosarcoma, medulloblastoma, retinoblastoma, and acute lymphoblastic leukemia. Consequently, we summarized the relationships between the m6A factors and these pediatric cancers.

Functions, mechanisms, and therapeutic implications of METTL14 in human cancer

RNA modification plays a crucial role in many biological functions, and its abnormal regulation is associated with the progression of cancer. Among them, N6-methyladenine (m6A) is the most abundant RNA modification. Methyltransferase-like 14 (METTL14) is the central component of the m6A methylated transferase complex, which is involved in the dynamic reversible process of m6A modification. METTL14 acts as both an oncogene and tumor suppressor gene to regulate the occurrence and development of various cancers. The abnormal m6A level induced by METTL14 is related to tumorigenesis, proliferation, metastasis, and invasion. To date, the molecular mechanism of METTL14 in various malignant tumors has not been fully studied. In this paper, we systematically summarize the latest research progress on METTL14 as a new biomarker for cancer diagnosis and its biological function in human tumors and discuss its potential clinical application. This study aims to provide new ideas for targeted therapy and improved prognoses in cancer.

Characterization of m6A-related lncRNA signature in neuroblastoma

N6-methyladenosine (m6A) constitutes one of the most common modifications in mRNA, rRNA, tRNA, microRNA, and long-chain noncoding RNA. The influence of modifications of m6A on the stability of RNA depends upon the expression of methyltransferase ("writer") and demethylase ("eraser") and m6A binding protein ("reader"). In this study, we identified a set of m6A-related lncRNA expression profiles in neuroblastoma (NBL) based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program. Thereupon, we identified two subgroups of neuroblastoma (high-risk group and low-risk group) by applying consensus clustering to m6A RNA methylation regulators ("Readers,", "Writer," and "Erase"). Relative to the low-risk group, the high-risk group correlates with a poorer prognosis. Moreover, the present study also revealed that the high-risk group proves to be significantly positively enriched in the tumor-related signaling pathways, including the P53 signaling pathway, cell cycle, and DNA repair. This finding indicates that these molecular prognostic markers may also be potentially valuable in early diagnosis, which provides a new research direction for the study of molecular mechanisms underlying the development of NBL. In conclusion, this study constructed a new model of NBL prognosis based on m6a-associated lncRNAs. Ultimately, this model is helpful for stratification of prognosis and development of treatment strategies.

Identification of a Five-Gene Signature Derived From MYCN Amplification and Establishment of a Nomogram for Predicting the Prognosis of Neuroblastoma

Background: Neuroblastoma (NB), the most common solid tumor in children, exhibits vastly different genomic abnormalities and clinical behaviors. While significant progress has been made on the research of relations between clinical manifestations and genetic abnormalities, it remains a major challenge to predict the prognosis of patients to facilitate personalized treatments. Materials and Methods: Six data sets of gene expression and related clinical data were downloaded from the Gene Expression Omnibus (GEO) database, ArrayExpress database, and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. According to the presence or absence of MYCN amplification, patients were divided into two groups. Differentially expressed genes (DEGs) were identified between the two groups. Enrichment analyses of these DEGs were performed to dig further into the molecular mechanism of NB. Stepwise Cox regression analyses were used to establish a five-gene prognostic signature whose predictive performance was further evaluated by external validation. Multivariate Cox regression analyses were used to explore independent prognostic factors for NB. The relevance of immunity was evaluated by using algorithms, and a nomogram was constructed. Results: A five-gene signature comprising CPLX3, GDPD5, SPAG6, NXPH1, and AHI1 was established. The five-gene signature had good performance in predicting survival and was demonstrated to be superior to International Neuroblastoma Staging System (INSS) staging and the MYCN amplification status. Finally, a nomogram based on the five-gene signature was established, and its clinical efficacy was demonstrated. Conclusion: Collectively, our study developed a novel five-gene signature and successfully built a prognostic nomogram that accurately predicted survival in NB. The findings presented here could help to stratify patients into subgroups and determine the optimal individualized therapy.

Development and Validation of a Five-RNA-Based Signature and Identification of Candidate Drugs for Neuroblastoma

Neuroblastoma (NBL) originating from the sympathetic nervous system is the most prevalent solid tumor in infancy. Although there is sufficient variability in prognosis among different age pyramids, age-related gene expression profiles and biomarkers remain poorly explored. The present study aimed to construct a signature based on differentially expressed genes (DEGs) between two age groups in NBL. Univariate Cox regression, multivariate Cox regression, and LASSO analyses were used to identify the optimal prognostic factors. The prediction ability of the model was assessed using the receiver operating characteristic (ROC) curve and C-index. Functional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes and gene ontology databases. A total of 1,160 DEGs were identified between the two groups, and 204 DEGs impacted the survival of NBL. Functional enrichment analysis revealed that the DEGs were involved in retinol metabolism, cholesterol metabolism, and glycolysis/gluconeogenesis pathways. Five RNAs, namely F8A3, PDF, ANKRD24, FAXDC2, and TMEM160 were recruited into the signature. They were correlated with COG risk classification, INSS stage, and histology. MYCN amplification was linked to FAXDC2, TMEM160, PDF, and F8A3. The expression levels of ANKRD24, PDF, and TMEM160 were lower in the hyperdiploid groups. Only FAXDC2 levels were different in the different MKI grades. The ROC curve showed that the five-RNA–based signatures effectively predicted the OS of NBL (3-years AUC = 0.791, 5-years AUC = 0.816) in the TARGET cohort. The predictive capability was also validated by the GSE49711 cohort (3-years AUC = 0.851, 5-years AUC = 0.848). The C-index in the TARGET and GSE49711 cohorts was 0.749 and 0.809, respectively. The potential mechanisms of the five RNAs were also explored via gene set enrichment analysis, and candidate drugs targeting the five genes, including dabrafenib, vemurafenib, and bafetinib, were screened. In conclusion, we constructed a five-RNA–based signature to predict the survival of NBL and screened candidate agents against NBL.

A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer

Ovarian cancer (OC) is the leading cause of cancer-related death among all gynecological tumors. N6-methyladenosine (m6A)-related regulators play essential roles in various tumors, including OC. However, the expression of m6A RNA methylation regulators and the related regulatory network in OC and their correlations with prognosis remain largely unknown. In the current study, we obtained the genome datasets of OC from GDC and GTEx database and analyzed the mRNA levels of 21 key m6A regulators in OC and normal human ovarian tissues. The expression levels of 7 m6A regulators were lower in both the OC tissues and the high-stage group. Notably, the 5-year survival rate of patients with OC presenting low VIRMA expression or high HNRNPA2B1 expression was higher than that of the controls. Next, a risk score model based on the three selected m6A regulators (VIRMA, IGF2BP1, and HNRNPA2B1) was built by performing a LASSO regression analysis, and the moderate accuracy of the risk score model to predict the prognosis of patients with OC was examined by performing ROC curve, nomogram, and univariate and multivariate Cox regression analyses. In addition, a regulatory network of miRNAs-m6A regulators-m6A target genes, including 2 miRNAs, 3 m6A regulators, and 47 mRNAs, was constructed, and one of the pathways, namely, miR-196b-5p-IGF2BP1-PTEN, was initially validated based on bioinformatic analysis and assay verification. These results demonstrated that the risk score model composed of three m6A RNA methylation regulators and the related network of miRNAs-m6A regulators-m6A target genes is valuable for predicting the prognosis of patients with OC, and these molecules may serve as potential biomarkers or therapeutic targets in the future.

IGF2BP2 promotes the progression of colorectal cancer through a YAP-dependent mechanism

To explore the effect of insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) on colorectal cancer (CRC) by recognizing the m6A modification of YAP mRNA thus activating ErbB2 expression. High expressions of IGF2BP2, YAP, and ErbB2 promoted the proliferation, migration and invasion of CRC cells and reduced their apoptosis. IGF2BP2 recognized the m6A on YAP mRNA and promoted the translation of mRNA. YAP regulated ErbB2 expression by promoting TEAD4 enrichment in ErbB2 promoter region. Therefore, IGF2BP2 promoted the expression of ErbB2 to enhance the proliferation, invasion and migration of CRC cells, to repress cell apoptosis, and to promote solid tumor formation in nude mice. IGF2BP2 activates the expression of ErbB2 by recognizing the m6A of YAP, thus affecting the cell cycle of CRC, inhibiting cell apoptosis, and promoting proliferation.

Regulatory Mechanisms of the RNA Modification m6A and Significance in Brain Function in Health and Disease

RNA modifications have emerged as an additional layer of regulatory complexity governing the function of almost all species of RNA. N⁶-methyladenosine (m⁶A), the addition of methyl groups to adenine residues, is the most abundant and well understood RNA modification. The current review discusses the regulatory mechanisms governing m⁶A, how this influences neuronal development and function and how aberrant m⁶A signaling may contribute to neurological disease. M⁶A is known to regulate the stability of mRNA, the processing of microRNAs and function/processing of tRNAs among other roles. The development of antibodies against m⁶A has facilitated the application of next generation sequencing to profile methylated RNAs in both health and disease contexts, revealing the extent of this transcriptomic modification. The mechanisms by which m⁶A is deposited, processed, and potentially removed are increasingly understood. Writer enzymes include METTL3 and METTL14 while YTHDC1 and YTHDF1 are key reader proteins, which recognize and bind the m⁶A mark. Finally, FTO and ALKBH5 have been identified as potential erasers of m⁶A, although there in vivo activity and the dynamic nature of this modification requires further study. M⁶A is enriched in the brain and has emerged as a key regulator of neuronal activity and function in processes including neurodevelopment, learning and memory, synaptic plasticity, and the stress response. Changes to m⁶A have recently been linked with Schizophrenia and Alzheimer disease. Elucidating the functional consequences of m⁶A changes in these and other brain diseases may lead to novel insight into disease pathomechanisms, molecular biomarkers and novel therapeutic targets.

The role of N6-methyladenosine mRNA in the tumor microenvironment

In recent years, the most widely distributed eukaryotic messenger RNA (mRNA) modification, N6-methyladenosine (m6A), has received a large amount of interest, in part due to the development and advances of high-throughput RNA sequencing. The effects of m6A mRNA on tumor progression have been the most widely studied, and large amounts of conflicting data have been reported due to differences in tumor contexts, cell types or cell states. The majority of these studies were related to the significance of m6A mRNA on tumor cells, including on proliferation, stemness, invasion capability, etc. However, it has been noted that tumorigenesis and tumor progression cannot occur without support from the tumor microenvironment (TME), which contains multiple types of stromal cells, such as infiltrating immune cells (IICs), vascular cells, mesenchymal stem cells (MSCs), cancer-associated fibroblasts (CAFs), and various environmental factors. Here, we summarized the contributions of abnormal m6A mRNA in stromal cells within the TME and described the effects of m6A mRNA on TME remodeling.

Associations between WTAP gene polymorphisms and neuroblastoma susceptibility in Chinese children

BACKGROUND

Previous studies have revealed that WTAP is related to multiple types of cancer. Recently, WTAP has been reported as an independent prognostic factor in patients with neuroblastoma.

METHODS

To explore the association between three WTAP polymorphisms (rs9457712 G>A, rs1853259 A>G and rs7766006 G>T) and neuroblastoma susceptibility in Chinese populations, we performed this case-control study including 898 neuroblastoma cases and 1,734 controls. We genotyped these potentially functional single nucleotide polymorphisms (SNPs) by TaqMan assays. The odds ratios (ORs) and 95% confidence intervals (CIs) by logistic regression models were used to assess the relationship between WTAP SNPs and the risk of neuroblastoma.

RESULTS

No significant associations were observed in the overall analysis between any of the three WTAP polymorphisms and the risk of neuroblastoma. However, in the age ≤18 months subgroup, we found that the rs1853259 AG/GG genotype exerted protective effects against neuroblastoma (adjusted OR =0.77, 95% CI: 0.59-0.998, P=0.048), whereas the presence of 1-2 combined risk genotypes significantly increased the risk of neuroblastoma (adjusted OR =1.32, 95% CI: 1.02-1.71, P=0.036).

CONCLUSIONS

WTAP gene polymorphisms only have a weak impact on the risk of neuroblastoma in the Chinese children. Further case-control studies, preferable on larger sample sizes, are needed to validate our results.

Epitranscriptomic regulation of transcriptome plasticity in development and diseases of the brain

Proper development of the nervous system is critical for its function, and deficits in neural development have been impli-cated in many brain disorders. A precise and predictable developmental schedule requires highly coordinated gene expression programs that orchestrate the dynamics of the developing brain. Especially, recent discoveries have been showing that various mRNA chemical modifications can affect RNA metabolism including decay, transport, splicing, and translation in cell type- and tissue-specific manner, leading to the emergence of the field of epitranscriptomics. Moreover, accumulating evidences showed that certain types of RNA modifications are predominantly found in the developing brain and their dysregulation disrupts not only the developmental processes, but also neuronal activities, suggesting that epitranscriptomic mechanisms play critical post-transcriptional regulatory roles in development of the brain and etiology of brain disorders. Here, we review recent advances in our understanding of molecular regulation on transcriptome plasticity by RNA modifications in neurodevelopment and how alterations in these RNA regulatory programs lead to human brain disorders.