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YTHDF3 rs7464 A > G polymorphism increases Chinese neuroblastoma risk: A multiple-center case-control study
Huiran Lin1, Yongping Chen2, Liping Chen1
1Department 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, Guangzhou, China.
Abstract:
Neuroblastoma (NB), a rare childhood cancer originating in nerve tissue. YTHDF3, a member of the YTH domain protein family, is involved in RNA m6A modification and cancer progression. Polymorphisms in YTHDF3 may influence its expression and biological function. Herein, this study estimated the association between YTHDF3 polymorphisms (rs2241753, rs2241754, and rs7464) and NB susceptibility in a multicenter study comprising 898 cases and 1734 controls. We genotyped YTHDF3 candidate polymorphisms by the TaqMan assay. Logistic regression analysis was applied to indicate the possible relationships between these polymorphisms and NB susceptibility, using odds ratios (ORs) and 95% confidence intervals (CIs). Logistic regression analysis revealed that the rs2241753 GA versus GG decreased NB risk (Adjusted OR = 0.84, 95% CI = 0.71-0.997, p = .047), while the rs7464 GG versus AA enhanced NB risk (Adjusted OR = 1.62, 95% CI = 1.20-2.18, p = .002). Additionally, rs7464 GG versus AA/AG showed a higher risk (Adjusted OR = 1.66, 95% CI = 1.24-2.22, p = .0006). Combination analysis showed that having 1-3 risk genotypes versus 0 was associated with increased NB risk (Adjusted OR = 1.28, 95%CI = 1.09-1.51, p = .003). The significance of rs7464 and the risk genotypes combination persisted across multiple subgroups, whereas rs2241754 was significant only in mediastinal NB. False-positive report probability (FPRP) confirmed the reliability of results. Notably, the interaction between rs7464 and rs2241754 may increase NB risk dramatically. Our study demonstrated that YTHDF3 rs7464 A > G significantly affected NB susceptibility, warranting validation in larger sample sizes.
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