Foulkes, William D.

Background The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. Methods We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. Results For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. Conclusions This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

ABSTRACTRare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single‐marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden‐type approaches attempt to identify aggregation of RVs across case‐control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large‐scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway‐level RV analysis results from a prostate cancer (PC) risk case‐control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Abstract Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev; 24(7); 1121–9. ©2015 AACR.

Abstract BRCA1 and BRCA2 are the most important breast and ovarian cancer susceptibility genes. Biallelic mutations in BRCA2 can lead to Fanconi anemia and predisposition to cancers, whereas biallelic BRCA1 mutations have not been confirmed, presumably because one wild-type BRCA1 allele is required during embryogenesis. This study describes an individual who was diagnosed with ovarian carcinoma at age 28 and found to have one allele with a deleterious mutation in BRCA1, c.2457delC (p.Asp821Ilefs*25), and a second allele with a variant of unknown significance in BRCA1, c.5207T>C (p.Val1736Ala). Medical records revealed short stature, microcephaly, developmental delay, and significant toxicity from chemotherapy. BRCA1 p.Val1736Ala cosegregated with cancer in multiple families, associated tumors showed loss of wild-type BRCA1, and BRCA1 p.Val1736Ala showed reduced DNA damage localization. These findings represent the first validated example of biallelic deleterious human BRCA1 mutations and have implications for the interpretation of genetic test results. Significance: Accurate assessment of genetic testing data for BRCA1 mutations is essential for clinical monitoring and treatment strategies. Here, we report the first validated example of an individual with biallelic BRCA1 mutations, early-onset ovarian cancer, and clinically significant hypersensitivity to chemotherapy. Cancer Discov; 3(4); 399–405. ©2012 AACR. See related commentary by D'Andrea, p. 376 This article is highlighted in the In This Issue feature, p. 363

Purpose The sensitivity of magnetic resonance imaging (MRI) for breast cancer screening exceeds that of mammography. If MRI screening reduces mortality in women with a BRCA1 or BRCA2 mutation, it is expected that the incidence of advanced-stage breast cancers should be reduced in women undergoing MRI screening compared with those undergoing conventional screening. Patients and Methods We followed 1,275 women with a BRCA1 or BRCA2 mutation for a mean of 3.2 years. In total, 445 women were enrolled in an MRI screening trial in Toronto, Ontario, Canada, and 830 were in the comparison group. The cumulative incidences of ductal carcinoma in situ (DCIS), early-stage, and late-stage breast cancers were estimated at 6 years in the cohorts. Results There were 41 cases of breast cancer in the MRI-screened cohort (9.2%) and 76 cases in the comparison group (9.2%). The cumulative incidence of DCIS or stage I breast cancer at 6 years was 13.8% (95% CI, 9.1% to 18.5%) in the MRI-screened cohort and 7.2% (95% CI, 4.5% to 9.9%) in the comparison group (P = .01). The cumulative incidence of stages II to IV breast cancers was 1.9% (95% CI, 0.2% to 3.7%) in the MRI-screened cohort and 6.6% (95% CI, 3.8% to 9.3%) in the comparison group (P = .02). The adjusted hazard ratio for the development of stages II to IV breast cancer associated with MRI screening was 0.30 (95% CI, 0.12 to 0.72; P = .008). Conclusion Annual surveillance with MRI is associated with a significant reduction in the incidence of advanced-stage breast cancer in BRCA1 and BRCA2 carriers.

Abstract A recent genome-wide association study found that genetic variants on chromosomes 3, 6, 7, 10, 11, 19 and X were associated with prostate cancer risk. We evaluated the most significant single-nucleotide polymorphisms (SNP) in these loci using a worldwide consortium of 13 groups (PRACTICAL). Blood DNA from 7,370 prostate cancer cases and 5,742 male controls was analyzed by genotyping assays. Odds ratios (OR) associated with each genotype were estimated using unconditional logistic regression. Six of the seven SNPs showed clear evidence of association with prostate cancer (P = 0.0007-P = 10−17). For each of these six SNPs, the estimated per-allele OR was similar to those previously reported and ranged from 1.12 to 1.29. One SNP on 3p12 (rs2660753) showed a weaker association than previously reported [per-allele OR, 1.08 (95% confidence interval, 1.00-1.16; P = 0.06) versus 1.18 (95% confidence interval, 1.06-1.31)]. The combined risks associated with each pair of SNPs were consistent with a multiplicative risk model. Under this model, and in combination with previously reported SNPs on 8q and 17q, these loci explain 16% of the familial risk of the disease, and men in the top 10% of the risk distribution have a 2.1-fold increased risk relative to general population rates. This study provides strong confirmation of these susceptibility loci in multiple populations and shows that they make an important contribution to prostate cancer risk prediction. (Cancer Epidemiol Biomarkers Prev 2008;17(8):2052–61)