SynthesisFrontiers in oncology2023
The relationship between single nucleotide polymorphisms and skin cancer susceptibility: A systematic review and network meta-analysis.
Synthesis in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Nucleotide excision repair gene polymorphisms and hepatoblastoma susceptibility in Eastern Chinese children: A five-center case-control study.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2024Article
- Influence of H19 polymorphisms on breast cancer: risk assessment and prognostic implications via LincRNA H19/miR-675 and downstream pathways.Frontiers in oncology · 2024Article
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Authors and funding
9 authors.
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Abstract
Background: Single nucleotide polymorphisms (SNPs) interfere with the function of certain genes and thus may influence the probability of skin cancer. The correlation between SNPs and skin cancer (SC) lacks statistical power, however. Therefore, the purpose of this study was to identify the gene polymorphisms involved in skin cancer susceptibility using network meta-analysis and to determine the relationship between SNPs and SC risk. Methods: PubMed, Embase, and Web of Science were searched for articles including "SNP" and different types of SC as keywords between January 2005 and May 2022. The Newcastle-Ottawa Scale was used to assess bias judgments. The odds ratio (ORs) and their 95% confidence intervals ( Results: A total of 275 SNPs from 59 studies were included in the study. Two subgroup SNP networks using the allele model and dominant model were analyzed. The alternative alleles of rs2228570 (FokI) and rs13181 (ERCC2) were the first-ranking SNPs in both subgroups one and two of the allele model, respectively. The homozygous dominant genotype and heterozygous genotype of rs475007 in subgroup one and the homozygous recessive genotype of rs238406 in subgroup two were most likely to be associated with skin cancer based on the dominant model. Conclusions: According to the allele model, SNPs FokI rs2228570 and ERCC2 rs13181 and, according to the dominant model, SNPs MMP1 rs475007 and ERCC2 rs238406 are closely linked to SC risk.
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