Citations

AbstractThe familial recurrence risk is the probability a person will have disease, given a reported family history. When family histories are obtained as simple counts of disease among family members, as often obtained in cancer registries or surveys, we propose methods to estimate recurrence risks based on truncated binomial distributions. By this approach, we are able to obtain unbiased estimates of risk for a person with at least k‐affected relatives, where k can be specified to determine how risk varies with k. We also derive robust variances of the recurrence risk estimate, to account for correlations within families, such as those induced by shared genes or shared environment, without explicitly modeling the factors that cause familial correlations. Furthermore, we illustrate how mixture models can be used to account for a sample composed of low‐ and high‐risk families. Using simulations, we illustrate the properties of the proposed methods. Application of our methods to a family history survey of prostate cancer shows that the recurrence risk for prostate cancer increased from 16%, when there was at least one affected relative, to 52%, when there was at least five affected relatives.

Abstract Motivation Interpreting genetic variation in noncoding regions of the genome is an important challenge for personal genome analysis. One mechanism by which noncoding single nucleotide variants (SNVs) influence downstream phenotypes is through the regulation of gene expression. Methods to predict whether or not individual SNVs are likely to regulate gene expression would aid interpretation of variants of unknown significance identified in whole-genome sequencing studies. Results We developed FIRE (Functional Inference of Regulators of Expression), a tool to score both noncoding and coding SNVs based on their potential to regulate the expression levels of nearby genes. FIRE consists of 23 random forests trained to recognize SNVs in cis-expression quantitative trait loci (cis-eQTLs) using a set of 92 genomic annotations as predictive features. FIRE scores discriminate cis-eQTL SNVs from non-eQTL SNVs in the training set with a cross-validated area under the receiver operating characteristic curve (AUC) of 0.807, and discriminate cis-eQTL SNVs shared across six populations of different ancestry from non-eQTL SNVs with an AUC of 0.939. FIRE scores are also predictive of cis-eQTL SNVs across a variety of tissue types. Availability and implementation FIRE scores for genome-wide SNVs in hg19/GRCh37 are available for download at https://sites.google.com/site/fireregulatoryvariation/. Supplementary information Supplementary data are available at Bioinformatics online.

75 Background: We investigated the association of germline variation in ten candidate genes important in prostate cancer biology (NKX3-1, JAK2, SLCO2B1, STAT3, CYP19A1, HSD17B4, TRMT11, PRMT3, HSD17B12, NCOA4) with overall survival (OS) in a cohort of metastatic CRPC stage patients. Methods: Patients (N=497) were enrolled at the time of androgen deprivation therapy failure for D2 stage prostate cancer. Candidate genes were selected from the literature and pilot studies. Genes were tagged using SNPs from HapMap with minor allele frequency (MAF) of >5% and r2≥0.8. DNA was extracted from peripheral blood and genotyped using Illumina Veracode platform. The primary endpoint was OS, defined as time from development of CRPC to death. Principle components analysis was used for gene-levels tests. To account for multiple testing we calculated the false discovery rate (FDR). For SNP level results we estimated per allele (ordinal model) hazard ratios (HR) and 95% confidence intervals (CI) using Cox regression and adjusted for age and Gleason score (GS). Results: We successfully genotyped 60 SNPs (from 10 genes) in 497 Caucasian subjects. The median age of the CRPC cohort was 71 years (range 43,93). The GS distribution was 51% subjects with GS≥8; 32% with GS7 and 17% with GS<7. After a median follow up of 2.1 years (IQ range: 1.2-3.6), 297 subjects had died. In unadjusted gene level analyses, NKX3-1 (p=0.04; FDR=0.03) was associated with OS. After adjusting for age and GS the result remained significant (p=0.03). Two of the 5 genotyped SNPs in this gene were associated with OS after adjustment for age and GS: rs10503733 (dominant model p=0.03, HR=0.77; 95 CI=0.60-0.98; A>C; MAF = 0.22) and rs7005368 (dominant model p=0.05, HR=1.38, 95CI=1.0-1.92; G>A; MAF=0.07). Both SNPs are in Hardy Weinberg Equilibrium and in complete LD (D'=1), although r2 is low (r2=0.025) due to different allele frequencies. Conclusions: Variation in the homeobox NKX-1 gene, a prostate specific tumor suppressor gene involved in prostate development and carcinogenesis is significantly associated with OS in CRPC after accounting for age and GS. Further validation is needed to develop these as prognostic biomarkers.

209 Background: Predictive markers of response to AA are not known. In a prior study, we found that 8 single nucleotide polymorphisms (SNPs) from 4 candidate hormone-related genes (JAK2, TRMT11, NKX3-1 and HSD17B12) were associated with response to AA in HSPC in a North American cohort of 519 subjects. We attempt to replicate these findings in a cohort of Portuguese patients. Methods: The Portuguese cohort consisted of 308 HSPC patients, and the primary endpoint was time to AA failure, defined as time from initiating continuous AA to two serial PSA increases over the nadir, initiation of chemotherapy for progressive disease, or clinical or imaging based progression, whichever came first. For each SNP, we calculated hazard ratios (HRs) and 95% confidence intervals (CI) for time to AA failure using a recessive model with adjustment for Gleason score (GS). Results: The median age of the Portuguese cohort was 69 years (range 43, 85). The GS distribution was 35% subjects with GS≥8; 35% with GS=7 and 30% with GS<7. Median time to AA failure for the cohort was 1.8 years (IQ range: 0.3, 3.6). Association of each SNP with time to AA failure is shown in the Table. None of the SNPs replicated. However, there was a suggestive inverse association for rs10503733 (NKX3.1) with time to AA failure (P=0.07). Conclusions: While we were not able to replicate our initial findings, there was an unexpected association with rs10503733 (NKX3.1 gene) that may warrant additional clinical validation. [Table: see text]

PURPOSE: To estimate the efficacy of contralateral prophylactic mastectomy in women with a personal and family history of breast cancer. PATIENTS AND METHODS: We followed the course of 745 women with a first breast cancer and a family history of breast and/or ovarian cancer who underwent contralateral prophylactic mastectomy at the Mayo Clinic between 1960 and 1993. Family history information and cancer follow-up information were obtained from the medical record, a study-specific questionnaire, and telephone follow-up. Life-tables for contralateral breast cancers, which consider age at first breast cancer, current age, and type of family history, were used to calculate the number of breast cancers expected in our cohort had they not had a prophylactic mastectomy. RESULTS: Of the 745 women in our cohort, 388 were premenopausal (age < 50 years) and 357 were post- menopausal. Eight women developed a contralateral breast cancer. Six events were observed among the premenopausal women, compared with 106.2 predicted, resulting in a risk reduction of 94.4% (95% confidence interval [CI], 87.7% to 97.9%). For the 357 postmenopausal women, 50.3 contralateral breast cancers were predicted, whereas only two were observed, representing a 96.0% risk reduction (95% CI, 85.6% to 99.5%). CONCLUSION: The incidence of contralateral breast cancer seems to be reduced significantly after contralateral prophylactic mastectomy in women with a personal and family history of breast cancer.