METHODS: In this study, we determined the prevalence of germline APOBEC3B deletion and its association with breast cancer risk in a cross-sectional hospital-based Asian multi-ethnic cohort of 1451 cases and 1442 controls from Malaysia. We compared gene expression profiles of breast cancers arising from APOBEC3B deletion carriers and non-carriers using microarray analyses. Finally, we characterised the overall abundance of tumour-infiltrating immune cells in breast cancers from TCGA and METABRIC using ESTIMATE and relative frequency of 22 immune cell subsets in breast cancers from METABRIC using CIBERSORT.
RESULTS: The minor allelic frequency of APOBEC3B deletion was estimated to be 0.35, 0.42 and 0.16 in female populations of Chinese, Malay and Indian descent, respectively, and that germline APOBEC3B deletion was associated with breast cancer risk with odds ratios of 1.23 (95 % CI: [1.05, 1.44]) for one-copy deletion and 1.38 (95 % CI: [1.10, 1.74]) for two-copy deletion compared to women with no deletion. Germline APOBEC3B deletion was not associated with any clinicopathologic features or the expression of any APOBEC family members but was associated with immune response-related gene sets (FDR q values
METHODS: Volumetric mammographic density was compared for 1501 Malaysian and 4501 Swedish healthy women, matched on age and body mass index. We used multivariable log-linear regression to determine the risk factors associated with mammographic density and mediation analysis to identify factors that account for differences in mammographic density between the two cohorts.
RESULTS: Compared to Caucasian women, percent density was 2.0% higher among Asian women (p
METHODS: In this study, we built a new model (Asian Risk Calculator) for estimating the likelihood of carrying a pathogenic variant in BRCA1 or BRCA2 gene, using germline BRCA genetic testing results in a cross-sectional population-based study of 8,162 Asian patients with breast cancer. We compared the model performance to existing mutation prediction models. The models were evaluated for discrimination and calibration.
RESULTS: Asian Risk Calculator included age of diagnosis, ethnicity, bilateral breast cancer, tumor biomarkers, and family history of breast cancer or ovarian cancer as predictors. The inclusion of tumor grade improved significantly the model performance. The full model was calibrated (Hosmer-Lemeshow P value = .614) and discriminated well between BRCA and non-BRCA pathogenic variant carriers (area under receiver operating curve, 0.80; 95% CI, 0.75 to 0.84). Addition of grade to the existing clinical genetic testing criteria targeting patients with breast cancer age younger than 45 years reduced the proportion of patients referred for genetic counseling and testing from 37% to 33% (P value = .003), thereby improving the overall efficacy.
CONCLUSION: Population-specific customization of mutation prediction models and clinical genetic testing criteria improved the accuracy of BRCA mutation prediction in Asian patients.