METHODS: Men enrolled in the IMPACT study provided serum samples during regular visits. Hormonal levels were calculated using immunoassays. Free testosterone (FT) was calculated from TT and sex hormone binding globulin (SHBG) using the Sodergard mass equation. Age, body mass index (BMI), prostate-specific antigen (PSA) and hormonal concentrations were compared between genetic cohorts. We also explored associations between age and TT, SHBG, FT and PCa, in the whole subset and stratified by BRCA1/2 PVs status.
RESULTS: A total of 777 participants in the IMPACT study had TT and SHBG measurements in serum samples at annual visits, giving 3940 prospective androgen levels, from 266 BRCA1 PVs carriers, 313 BRCA2 PVs carriers and 198 non-carriers. The median number of visits per patient was 5. There was no difference in TT, SHBG and FT between carriers and non-carriers. In a univariate analysis, androgen levels were not associated with PCa. In the analysis stratified by carrier status, no significant association was found between hormonal levels and PCa in non-carriers, BRCA1 or BRCA2 PVs carriers.
CONCLUSIONS: Male BRCA1/2 PVs carriers have a similar androgen profile to non-carriers. Hormonal levels were not associated with PCa in men with and without BRCA1/2 PVs. Mechanisms related to the particularly aggressive phenotype of PCa in BRCA2 PVs carriers may therefore not be linked with circulating hormonal levels.
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.
METHODS: Data were collected on 271 BRCA1 and 301 BRCA2 families from Malaysia and Singapore, ascertained through population/hospital-based case-series (88%) and genetic clinics (12%). Age-specific cancer risks were estimated using a modified segregation analysis method, adjusted for ascertainment.
FINDINGS: BC and OC relative risks (RRs) varied across age groups for both BRCA1 and BRCA2. The age-specific RR estimates were similar across ethnicities and country of residence. For BRCA1 carriers of Malay, Indian and Chinese ancestry born between 1950 and 1959 in Malaysia, the cumulative risk (95% CI) of BC by age 80 was 40% (36%-44%), 49% (44%-53%) and 55% (51%-60%), respectively. The corresponding estimates for BRCA2 were 29% (26-32%), 36% (33%-40%) and 42% (38%-45%). The corresponding cumulative BC risks for Singapore residents from the same birth cohort, where the underlying population cancer incidences are higher compared to Malaysia, were higher, varying by ancestry group between 57 and 61% for BRCA1, and between 43 and 47% for BRCA2 carriers. The cumulative risk of OC by age 80 was 31% (27-36%) for BRCA1 and 12% (10%-15%) for BRCA2 carriers in Malaysia born between 1950 and 1959; and 42% (34-50%) for BRCA1 and 20% (14-27%) for BRCA2 carriers of the same birth cohort in Singapore. There was evidence of increased BC and OC risks for women from >1960 birth cohorts (p-value = 3.6 × 10-5 for BRCA1 and 0.018 for BRCA2).
INTERPRETATION: The absolute age-specific cancer risks of Asian carriers vary depending on the underlying population-specific cancer incidences, and hence should be customised to allow for more accurate cancer risk management.
FUNDING: Wellcome Trust [grant no: v203477/Z/16/Z]; CRUK (PPRPGM-Nov20∖100002).
METHODS: We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases; 3,740 controls). Forty-three noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of four independent case-control studies across three regions in Asia (4,716 cases; 5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed.
RESULTS: In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR = 0.81; P value 6.3 × 10(-13)). Our results also provide support for associations reported from published NPC GWAS-rs6774494 (P = 1.5 × 10(-12); located in the MECOM gene region), rs9510787 (P = 5.0 × 10(-10); located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (P = 2.8 × 10(-8), P = 7.0 × 10(-7), and P = 8.4 × 10(-7), respectively; located in the CDKN2A/B gene region).
CONCLUSIONS: We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene has been shown to be important for telomere maintenance and has been reported to be overexpressed in NPC, and an EBV protein expressed in NPC (LMP1) has been reported to modulate TERT expression/telomerase activity.
IMPACT: Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis.
METHODS AND ANALYSIS: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk.
ETHICS AND DISSEMINATION: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3).
METHODS: We established a nurse- and community-navigator-led navigation program in breast clinics of four public hospitals located in Peninsular and East Malaysia and evaluated the impact of navigation on timeliness of diagnosis and treatment.
RESULTS: Patients with breast cancer treated at public hospitals reported facing barriers to accessing care, including having a poor recognition of breast cancer symptoms and low awareness of screening methods, and facing financial and logistics challenges. Compared with patients diagnosed in the previous year, patients receiving navigation experienced timely ultrasound (84.0% v 65.0%; P < .001), biopsy (84.0% v 78.0%; P = .012), communication of news (63.0% v 40.0%; P < .001), surgery (46% v 36%; P = .008), and neoadjuvant therapy (59% v 42%, P = .030). Treatment adherence improved significantly (98.0% v 87.0%, P < .001), and this was consistent across the network of four breast clinics.
CONCLUSION: Patient navigation improves access to timely diagnosis and treatment for women presenting at secondary and tertiary hospitals in Malaysia.
METHODS: A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.
RESULTS: The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.
CONCLUSIONS: We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.