Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary's Hospital, Manchester, United Kingdom; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary's Hospital, Manchester, United Kingdom.
Strangeways Research Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Genet Med. 2022 Sep;24(9):1847-1856. doi: 10.1016/j.gim.2022.05.014. Epub 2022 Jun 15.
Single-nucleotide variations (SNVs) (formerly single-nucleotide polymorphism [SNV]) influence genetic predisposition to endometrial cancer. We hypothesized that a polygenic risk score (PRS) comprising multiple SNVs may improve endometrial cancer risk prediction for targeted screening and prevention.
We developed PRSs from SNVs identified from a systematic review of published studies and suggestive SNVs from the Endometrial Cancer Association Consortium. These were tested in an independent study of 555 surgically-confirmed endometrial cancer cases and 1202 geographically-matched controls from Manchester, United Kingdom and validated in 1676 cases and 116,960 controls from the UK Biobank (UKBB).
Age and body mass index predicted endometrial cancer in both data sets (Manchester: area under the receiver operator curve [AUC] = 0.77, 95% CI = 0.74-0.80; UKBB: AUC = 0.74, 95% CI = 0.73-0.75). The AUC for PRS19, PRS24, and PRS72 were 0.58, 0.55, and 0.57 in the Manchester study and 0.56, 0.54, and 0.54 in UKBB, respectively. For PRS19, women in the third tertile had a 2.1-fold increased risk of endometrial cancer compared with those in the first tertile of the Manchester study (odds ratio = 2.08, 95% CI = 1.61-2.68, P = 5.75E-9). Combining PRS19 with age and body mass index improved discriminatory power (Manchester study: AUC = 0.79, 95% CI = 0.76-0.82; UKBB: AUC =0.75, 95% CI = 0.73-0.76).
An endometrial cancer risk prediction model incorporating a PRS derived from multiple SNVs may help stratify women for screening and prevention strategies.
单核苷酸变异（SNV）（以前称为单核苷酸多态性 [SNV]）影响子宫内膜癌的遗传易感性。我们假设，由多个 SNV 组成的多基因风险评分（PRS）可能会提高针对靶向筛查和预防的子宫内膜癌风险预测。
我们从系统评价发表的研究和子宫内膜癌协会联盟的提示性 SNV 中开发了 PRS。这些在英国曼彻斯特的 555 例经手术证实的子宫内膜癌病例和 1202 例地理匹配对照的独立研究中进行了测试，并在 UKBB（英国生物库）的 1676 例病例和 116960 例对照中进行了验证。
年龄和体重指数在两个数据集（曼彻斯特：接收器操作特征曲线下的面积 [AUC] = 0.77，95%CI = 0.74-0.80；UKBB：AUC = 0.74，95%CI = 0.73-0.75）中预测了子宫内膜癌。在曼彻斯特研究中，PRS19、PRS24 和 PRS72 的 AUC 分别为 0.58、0.55 和 0.57，在 UKBB 中分别为 0.56、0.54 和 0.54。对于 PRS19，与曼彻斯特研究第一三分位数的女性相比，第三三分位数的女性子宫内膜癌风险增加了 2.1 倍（比值比= 2.08，95%CI = 1.61-2.68，P = 5.75E-9）。将 PRS19 与年龄和体重指数相结合可提高区分能力（曼彻斯特研究：AUC = 0.79，95%CI = 0.76-0.82；UKBB：AUC = 0.75，95%CI = 0.73-0.76）。
纳入来自多个 SNV 的 PRS 的子宫内膜癌风险预测模型可能有助于为筛查和预防策略分层女性。
