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Hepatoblastoma as the most prevalent hepatic malignancy in children, its etiology remains unclear. N6-Methyladenosine (m6A) modification which can modify various physiological processes, plays a critical role in tumorigenesis. Methyltransferase-like 14 (METTL14), an important component of the m6A methyltransferase complex, remains elusive during hepatoblastoma occurrence and development. We explored the relationship between METTL14 gene polymorphisms (rs1064034 T > A, rs298982 G > A, rs62328061 A > G, rs9884978 G > A, and rs4834698 T > C) and hepatoblastoma susceptibility from 313 patients and 1446 controls. The role of METTL14 polymorphisms in hepatoblastoma was evaluated by odds ratios (ORs) and 95% confidence intervals (CIs). Of the included subjects, 308 patients and 1444 controls were successfully genotyped. We did not find any significant correlation between the risk of hepatoblastoma and the five potentially functional METTL14 polymorphisms individually. However, the presence of 4-5 risk genotypes exhibited a significant increased hepatoblastoma risk (adjusted OR = 1.32, 95% CI = 1.03-1.69, P = 0.031) compared to those carriers with 0-3 risk genotypes. Furthermore, the stratified analysis demonstrated that the rs1064034 AA genotype, rs62328061 AG/GG genotypes, rs4834698 TC/CC genotypes, and 4-5 risk genotypes were related to hepatoblastoma susceptibility in certain subgroups. The expression quantitative trait loci (eQTL) analysis revealed that rs1064034 T > A and rs4834698 T > C were correlated with the expression levels of METTL14 and its surrounding genes. Prospectively, these findings suggested that METTL14 polymorphisms may correlation with hepatoblastoma susceptibility and provide a fresh insight into the genetic underpinnings of m6A modification in hepatoblastoma.
Pubmed ID: 34743822
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Database as central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms. Distinguishes report of how to assay SNP from use of that SNP with individuals and populations. This separation simplifies some issues of data representation. However, these initial reports describing how to assay SNP will often be accompanied by SNP experiments measuring allele occurrence in individuals and populations. Community can contribute to this resource.
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