Incremental impact of breast cancer SNP panel on risk classification in a screening population of white and African American women

Abstract

Breast cancer risk prediction remains imperfect, particularly among non-white populations. This study examines the impact of including single nucleotide polymorphism (SNP) alleles in risk prediction for white and African American women undergoing screening mammogram. Using a prospective cohort study, standard risk information and buccal swabs were collected at the time of screening mammography. A 12 SNP panel was performed by deCODE Genetics. Five-year and lifetime risks incorporating SNPs were calculated by multiplying estimated Breast Cancer Risk Assessment Tool (BCRAT) risk by the total genetic risk ratio. Concordance between the BCRAT and the Combined Model (BCRAT + SNPs) in identifying high-risk women was measured using the kappa statistic. SNP data were available for 813 women (39% African American, 55% white). The mean BCRAT 5-year risk was 1.70% for whites and 1.19% for African Americans. Mean genetic risk ratios were 1.10 in whites and 1.29 in African Americans. Among whites, three SNPs had higher frequencies, and among African Americans, seven SNPs had higher and four had lower high-risk allele frequencies than previously reported. Agreement between the BCRAT and the Combined Model was relatively low for identifying high-risk women (5-year κ=0.53, lifetime κ=0.37). Addition of SNPs had the greatest effect among African Americans, with 13% identified as having high 5-year risk by BCRAT, but 33% by the Combined Model. A greater proportion of African Americans were reclassified as having high 5-year risk than whites using the Combined Model (21% vs. 10%). The addition of SNPs to the BCRAT reclassifies the high-risk status of some women undergoing screening mammography, particularly African Americans. Further research is needed to determine the clinical validity and utility of the SNP panel for use in breast cancer risk prediction, particularly among African Americans for whom these risk alleles have generally not been validated.

Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography

“…In this University of Pennsylvania Institutional Review Board (IRB) approved, HIPAA compliant study, we retrospectively identified a cohort of women aged 40 years or older from our routine breast screening population who had also been prospectively recruited by a separate, IRB-approved, HIPAA compliant clinical study at our institution investigating the added value of genomic markers in breast cancer risk prediction [ 37 ]. For the purposes of our study, informed consent was waived, as this was a retrospective analysis and these women were already consented for research purposes in the original study [ 37 ] at the time of their recruitment. Each of these women was imaged as part of their routine screening with a full-field digital mammography (FFDM) system (Selenia Dimensions, Hologic Inc.) under a standard protocol.…”

“…For each woman, information regarding the genotype of 12 SNPs were obtained from a commercially available assay based on Illumina Infinium II whole-genome genotyping (deCODE BreastCancer, deCODE genetics, Inc.) [ 37 ]. The deCODE SNP assay includes 12 genetic loci, specifically 2q35 ( rs13387042 ), MRPS30 ( rs4415084 ), FGFR2 ( rs1219648 ), TNRC9/TOX3 ( rs3803662 ), 8q24 ( rs13281615 ), LSP1 ( rs3817198 ), MAP3K1 ( rs889312 ), NEK10 ( rs4973768 ), 1p11 ( rs11249433 ), RAD51L1 ( rs999737 ), COX11/STXBP4 ( rs6504950 ), and CASP8 ( rs1045485 ), which have been consistently associated with either overall or subtype specific cancer risk, the risk for metastatic disease or age at diagnosis [ 39 - 49 ].…”

Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management

“…Therefore, other genetic models include several single nucleotide polymorphisms (SNPs) in low penetrant genes, as they are more frequent in the general population and thus are preferable in the primary screening programs. Some models analyze 7 [73], 12 [74], 51 [72], 77 [75], 88 [76] or 153 SNPs [77]. However, the predictive ability of these genetic models, explained by an area under the ROC curve (AUC) is individually low, ranging from 0.53 to 0.68 [75,77].…”

“…When combined multiplicatively with other risk models (i.e., BRCAT / Gail model), a substantial improvement in specificity and sensitivity was observed [72,73,76,78]. Addition of a genetic risk model (12 SNPs) to the BRCAT had a greater effect among African Americans than in whites as it reclassifies the high-risk status of several women undergoing screening mammography [74].…”

A way forward for cancer prevention therapy: personalized risk assessment

“…McCarthy et al evaluated the performance of the BCRAT and the combined BCRAT+SNPs model using a cohort of African American and white women [55]. Agreement between the BCRAT and the BCRAT+SNPs model was low for identifying high-risk women.…”