Genetics may play role in endometrial cancer risk

Six single nucleotide polymorphisms (SNPS) may be strongly associated with endometrial cancer risk, according to a new analysis of the latest evidence on genetics of the disease. The findings suggest that clinicians may one day be able to test for these and other variants to calculate a risk score for endometriosis in their patients, but first the associations identified must be validated in large-scale studies.

Methods
Published in The Journal of Medical Genetics, the research showed a role for HNF1B, KLF, EIF2AK, CYP19A1, SOX4, and MYC in development of incident endometrial cancer but no convincing evidence that MDM2, which has been widely studied, is associated with endometrial cancer risk. Researchers from the UK performed the new study, which was a systematic review of prospective and retrospective case-control studies, meta-analyses, and genome-wide association studies (GWAS). They searched MEDLINE, Embase and CINAHL from 2007 to 2019 for studies that reported associations between SNPs and endometrial cancer risk.

Candidate-gene studies with at least 100 women and GWAS with at least 1,000 women in the case arm were selected to ensure reliability of results. To construct a panel of up to 30 SNPs with the strongest evidence of association, those with the strongest P values were selected. Of 3,015 articles generated by initial literature search, 149 were considered eligible for inclusion in the analysis.

Findings
The intent of the analysis was to identify the most robust endometrial cancer-associated SNPS and assess their us as a panel in a theoretical polygenic risk score (PRS) calculation. The authors found that HNF1B, KLF, EIF2AK, CYP19A1, SOX4, and MYC were strongly associated with incident endometrial cancer. Nineteen variants were reported with genome-wide significance and another five with suggestive significance. No convincing evidence was found for MDM2 variant rs2279744. 

Conclusions
The researchers said that publication bias and false discovery rates were common in the literature they reviewed. They noted that the papers reported on included small candidate-gene studies, meta-analyses of studies with conflicting results, and findings on significant SNPs that have not been validated in any larger GWAS. Nevertheless, they said that “the multiplicative effects of [the top 24 SNPS studied] could be used in a PRS to allow personalized risk prediction models to be developed for targeted screening and prevention interventions for women at greatest risk of endometrial cancer.”