Andrew Lee

Breast-Cancer Risk in Families with Mutations in PALB2

BACKGROUND Germline loss-of-function mutations in PALB2 are known to confer a predisposition to breast cancer. However, the lifetime risk of breast cancer that is conferred by such mutations remains unknown. METHODS We analyzed the risk of breast cancer among 362 members of 154 families who had deleterious truncating, splice, or deletion mutations in PALB2. The age-specific breast-cancer risk for mutation carriers was estimated with the use of a modified segregation-analysis approach that allowed for the effects of PALB2 genotype and residual familial aggregation. RESULTS The risk of breast cancer for female PALB2 mutation carriers, as compared with the general population, was eight to nine times as high among those younger than 40 years of age, six to eight times as high among those 40 to 60 years of age, and five times as high among those older than 60 years of age. The estimated cumulative risk of breast cancer among female mutation carriers was 14% (95% confidence interval [CI], 9 to 20) by 50 years of age and 35% (95% CI, 26 to 46) by 70 years of age. Breast-cancer risk was also significantly influenced by birth cohort (P<0.001) and by other familial factors (P=0.04). The absolute breast-cancer risk for PALB2 female mutation carriers by 70 years of age ranged from 33% (95% CI, 25 to 44) for those with no family history of breast cancer to 58% (95% CI, 50 to 66) for those with two or more first-degree relatives with breast cancer at 50 years of age. CONCLUSIONS Loss-of-function mutations in PALB2 are an important cause of hereditary breast cancer, with respect both to the frequency of cancer-predisposing mutations and to the risk associated with them. Our data suggest the breast-cancer risk for PALB2 mutation carriers may overlap with that for BRCA2 mutation carriers. (Funded by the European Research Council and others.).

The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers.

Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.

Age- and Tumor Subtype–Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers

PURPOSE CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. PATIENTS AND METHODS CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. RESULTS Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. CONCLUSION These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.

Evaluation of association methods for analysing modifiers of disease risk in carriers of high-risk mutations.

There is considerable evidence indicating that disease risk in carriers of high‐risk mutations (e.g. BRCA1 and BRCA2) varies by other genetic factors. Such mutations tend to be rare in the population and studies of genetic modifiers of risk have focused on sampling mutation carriers through clinical genetics centres. Genetic testing targets affected individuals from high‐risk families, making ascertainment of mutation carriers non‐random with respect to disease phenotype. Standard analytical methods can lead to biased estimates of associations. Methods proposed to address this problem include a weighted‐cohort (WC) and retrospective likelihood (RL) approach. Their performance has not been evaluated systematically. We evaluate these methods by simulation and extend the RL to analysing associations of two diseases simultaneously (competing risks RL—CRRL). The standard cohort approach (Cox regression) yielded the most biased risk ratio (RR) estimates (relative bias—RB: −25% to −17%) and had the lowest power. The WC and RL approaches provided similar RR estimates, were least biased (RB: −2.6% to 2.5%), and had the lowest mean‐squared errors. The RL method generally had more power than WC. When analysing associations with two diseases, ignoring a potential association with one disease leads to inflated type I errors for inferences with respect to the second disease and biased RR estimates. The CRRL generally gave unbiased RR estimates for both disease risks and had correct nominal type I errors. These methods are illustrated by analyses of genetic modifiers of breast and ovarian cancer risk for BRCA1 and BRCA2 mutation carriers.

Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer

Background: Although high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and MUTYH) account for some familial aggregation of colorectal cancer, their population prevalence and the causes of the remaining familial aggregation are not known. Methods: We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the United States, Canada, and Australia and screened probands for mutations in mismatch repair genes and MUTYH. We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the probands age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of HR for unidentified major gene mutations, and the variance of the residual polygenic component. Results: We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (MLH1 = 1 in 1,946, MSH2 = 1 in 2,841, MSH6 = 1 in 758, PMS2 = 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30% to 50% after allowing for unidentified major genes and decreased from 3.3 for age <40 years to 0.5 for age ≥70 years (equivalent to sibling relative risks of 5.1 to 1.3, respectively). Conclusions: Unidentified major genes might explain one third to one half of the missing heritability of colorectal cancer. Impact: Our findings could aid gene discovery and development of better colorectal cancer risk prediction models. Cancer Epidemiol Biomarkers Prev; 26(3); 404–12. ©2016 AACR.

Ovarian cancer familial relative risks by tumour subtypes and by known ovarian cancer genetic susceptibility variants

Background Family history is one of the most important risk factors for epithelial ovarian cancer (EOC). Little is known, however, on how EOC familial relative risks (FRRs) vary by factors such as tumour subtype or the combined effects of common EOC susceptibility alleles. In addition, no data currently exist on the FRRs associated with EOC after exclusion of BRCA1 or BRCA2 mutation carriers. Methods EOC FRRs were computed from observed EOCs in relatives of 1548 patients with EOC recruited between 1999 and 2010 from a population-based cohort study with known BRCA1 and BRCA2 mutation status and tumour subtype, compared with the number expected in the general population. Results The EOC FRR to all first-degree relatives was estimated to be 2.96 (95% CI 2.35 to 3.72) but there was no evidence of difference in the FRRs for mothers, sisters and daughters. There was significant evidence that the FRR for relatives of patients with EOC diagnosed under age 50 years is higher than that for older patients (4.72 (95% CI 3.21 to 6.95) and 2.53 (95% CI 1.91 to 3.35), p-diff=0.0052) and a suggestion that the FRR in relatives of patients with serous disease is higher than that for non-serous tumours (3.64 (95% CI 2.72 to 4.87) and 2.25 (95% CI 1.56 to 3.26), p-diff=0.0023). The FRR to relatives of cases without a deleterious mutation in BRCA1 or BRCA2 was estimated to be over twice that of the general population (2.24 (95% CI 1.71 to 2.94)). BRCA1 and BRCA2 mutations were estimated to account for about 24% of the EOC FRR to first-degree relatives. FRRs were found to increase with increasing polygenic risk score of the index patient, although the trend was not significant. Conclusions These estimates could be useful in the counselling of relatives of patients with ovarian cancer.

Evaluation of Polygenic Risk Scores for Breast and Ovarian Cancer Risk Prediction in BRCA1 and BRCA2 Mutation Carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]–positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2×10−53). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2×10−20). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management.

Management of cancer-associated thrombosis in patients with thrombocytopenia: guidance from the SSC of the ISTH

B . T . SAMUELSON BANNOW,* A . LEE ,† A. A . KHORANA,‡ J . I . ZWICKER ,§ S . NOBLE , ¶ C. AY** and M. CARR IER†† *Department of Medicine, Division of Hematology, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA; †Division of Hematology, Department of Medicine, University of British Columbia, British Columbia Cancer Agency, Vancouver, British Columbia, Canada; ‡Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH; §Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; ¶Marie Curie Palliative Care Research Centre, Cardiff University, Cardiff, UK; **Department of Medicine I, Clinical Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria; and ††Department of Medicine, Ottawa Hospital Research Institute at the University of Ottawa, Ottawa, Ontario, Canada

The b quark mass from lattice nonrelativistic QCD

We present the first two-loop calculation of the heavy quark e nergy shift in lattice nonrelativistic QCD (NRQCD). This calculation allow us to extract a preliminary prediction of mb(mb, n f = 5) = 4.25(12) GeV for the mass of the b quark from lattice NRQCD simulations performed with a lattice of spacing a = 0.12fm. Our result is an improvement on a previous determination of the b quark mass from unquenched lattice NRQCD simulations, which was limited by the use of one-loop expressions for the energy shift. Our value is in good agreement with recent results of mb(mb) = 4.163(16) GeV from QCD sum rules and mb(mb, n f = 5) = 4.170(25) GeV from realistic lattice simulations using highly-improved stag gered quarks. We employ a mixed strategy to simplify our calculation. Ghost, gluon and counterterm contributions to the energy shift and mass renormalisation are extracted from quenched high-beta simulations whilst fermionic contributions are calculated using automated lattice perturbati on theory. Our results demonstrate the effectiveness of such a strategy.

Evaluation of polygenic risk scores for ovarian cancer risk prediction in a prospective cohort study

Background Genome-wide association studies have identified >30 common SNPs associated with epithelial ovarian cancer (EOC). We evaluated the combined effects of EOC susceptibility SNPs on predicting EOC risk in an independent prospective cohort study. Methods We genotyped ovarian cancer susceptibility single nucleotide polymorphisms (SNPs) in a nested case–control study (750 cases and 1428 controls) from the UK Collaborative Trial of Ovarian Cancer Screening trial. Polygenic risk scores (PRSs) were constructed and their associations with EOC risk were evaluated using logistic regression. The absolute risk of developing ovarian cancer by PRS percentiles was calculated. Results The association between serous PRS and serous EOC (OR 1.43, 95% CI 1.29 to 1.58, p=1.3×10–11) was stronger than the association between overall PRS and overall EOC risk (OR 1.32, 95% CI 1.21 to 1.45, p=5.4×10–10). Women in the top fifth percentile of the PRS had a 3.4-fold increased EOC risk compared with women in the bottom 5% of the PRS, with the absolute EOC risk by age 80 being 2.9% and 0.9%, respectively, for the two groups of women in the population. Conclusion PRSs can be used to predict future risk of developing ovarian cancer for women in the general population. Incorporation of PRSs into risk prediction models for EOC could inform clinical decision-making and health management.