A case–control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density. Issue 8 (13th July 2019)

• Record Type: Journal Article
• Authors: Brentnall, Adam R.; van Veen, Elke M.; Harkness, Elaine F.; Rafiq, Sajjad; Byers, Helen; Astley, Susan M.; Sampson, Sarah; Howell, Anthony; Newman, William G.; Cuzick, Jack; Evans, Dafydd Gareth R.
• Is Part Of: International journal of cancer. Volume 146:Issue 8(2020)
• Page Start: 2122
• Page End: 2129
• Publication Date: 2019-07-13
• Subjects: risk prediction -- risk stratification -- breast cancer -- SNPs -- Tyrer–Cuzick -- breast density; Cancer -- Periodicals; Cancer -- Prevention -- Periodicals; 616.994
• DOI: 10.1002/ijc.32541
• Languages: English
• ISSNs: 0020-7136

Abstract

Abstract : Panels of single nucleotide polymorphisms (SNPs) stratify risk for breast cancer in women from the general population, but studies are needed assess their use in a fully comprehensive model including classical risk factors, mammographic density and more than 100 SNPs associated with breast cancer. A case–control study was designed (1, 668 controls, 405 cases) in women aged 47–73 years attending routine screening in Manchester UK, and enrolled in a wider study to assess methods for risk assessment. Risk from classical questionnaire risk factors was assessed using the Tyrer–Cuzick model; mean percentage visual mammographic density was scored by two independent readers. DNA extracted from saliva was genotyped at selected SNPs using the OncoArray. A predefined polygenic risk score based on 143 SNPs was calculated (SNP143). The odds ratio (OR, and 95% confidence interval, CI) per interquartile range (IQ‐OR) of SNP143 was estimated unadjusted and adjusted for Tyrer–Cuzick and breast density. Secondary analysis assessed risk by oestrogen receptor (ER) status. The primary polygenic risk score was well calibrated (O/E OR 1.10, 95% CI 0.86–1.34) and accuracy was retained after adjustment for Tyrer–Cuzick risk and mammographic density (IQ‐OR unadjusted 2.12, 95% CI% 1.75–2.42; adjusted 2.06, 95% CI 1.75–2.42). SNP143 was a risk factor for ER+ and ER− breast cancer (adjusted IQ‐OR, ER+ 2.11, 95% CI 1.78–2.51; ER− 1.81, 95% CI 1.16–2.84). In conclusion, polygenic risk scores based on a large number of SNPs improve risk stratification in combination with classical risk factors and mammographic density, and SNP143 was similarly predictive for ER‐positive and ER‐negative disease. Abstract : What's new? Panels of single nucleotide polymorphisms (SNPs) stratify risk for breast cancer in women from the general population, but studies are needed to assess their use in a fully‐comprehensive model including classical questionnaire risk factors, mammographic density, and more than 100 SNPs associated with breast cancer. In this study, the predictive ability of a predefined panel of 143 SNPs was assessed after adjustment for questionnaire risk factors and mammography density using women from a U.K. cohort. The panel showed substantial improvement in risk stratification in combination with classical risk factors and mammographic density, for both oestrogen receptor‐positive and negative breast cancer.