Association between genetic polymorphisms and endometrial cancer risk: a systematic review. Issue 9 (17th February 2020)

• Record Type: Journal Article
• Authors: Bafligil, Cemsel; Thompson, Deborah J; Lophatananon, Artitaya; Smith, Miriam J; Ryan, Neil AJ; Naqvi, Anie; Evans, D Gareth; Crosbie, Emma J
• Is Part Of: Journal of medical genetics. Volume 57:Issue 9(2020)
• Page Start: 591
• Page End: 600
• Publication Date: 2020-02-17
• Subjects: endometrial cancer -- single nucleotide polymorphism (SNP) -- systematic review -- genetic epidemiology -- risk prediction; Medical genetics -- Periodicals; 616.042
• DOI: 10.1136/jmedgenet-2019-106529
• Languages: English
• ISSNs: 1468-6244

Abstract

Abstract : Introduction: Endometrial cancer is one of the most commonly diagnosed cancers in women. Although there is a hereditary component to endometrial cancer, most cases are thought to be sporadic and lifestyle related. The aim of this study was to systematically review prospective and retrospective case–control studies, meta-analyses and genome-wide association studies to identify genomic variants that may be associated with endometrial cancer risk. Methods: We searched MEDLINE, Embase and CINAHL from 2007 to 2019 without restrictions. We followed PRISMA 2009 guidelines. The search yielded 3015 hits in total. Following duplicate exclusion, 2674 abstracts were screened and 453 full-texts evaluated based on our pre-defined screening criteria. 149 articles were eligible for inclusion. Results: We found that single nucleotide polymorphisms (SNPs) in HNF1B, KLF, EIF2AK, CYP19A1, SOX4 and MYC were strongly associated with incident endometrial cancer. Nineteen variants were reported with genome-wide significance and a further five with suggestive significance. No convincing evidence was found for the widely studied MDM2 variant rs2279744. Publication bias and false discovery rates were noted throughout the literature. Conclusion: Endometrial cancer risk may be influenced by SNPs in genes involved in cell survival, oestrogen metabolism and transcriptional control. Larger cohorts are needed to identify more variants with genome-wide significance.