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BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7 x 10(-8), HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4 x 10(-8), HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4 x 10(-8), HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2 x 10(-4)). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%-50% compared to 81%-100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.
Single Nucleotide Polymorphisms (SNPs) in genes involved in the DNA Base Excision Repair (BER) pathway could be associated with cancer risk in carriers of mutations in the high-penetrance susceptibility genes BRCA1 and BRCA2, given the relation of synthetic lethality that exists between one of the components of the BER pathway, PARP1 (poly ADP ribose polymerase), and both BRCA1 and BRCA2. In the present study, we have performed a comprehensive analysis of 18 genes involved in BER using a tagging SNP approach in a large series of BRCA1 and BRCA2 mutation carriers. 144 SNPs were analyzed in a two stage study involving 23,463 carriers from the CIMBA consortium (the Consortium of Investigators of Modifiers of BRCA1 and BRCA2). Eleven SNPs showed evidence of association with breast and/or ovarian cancer at p<0.05 in the combined analysis. Four of the five genes for which strongest evidence of association was observed were DNA glycosylases. The strongest evidence was for rs1466785 in the NEIL2 (endonuclease VIII-like 2) gene (HR: 1.09, 95% CI (1.03-1.16), p = 2.7x10(-3)) for association with breast cancer risk in BRCA2 mutation carriers, and rs2304277 in the OGG1 (8-guanine DNA glycosylase) gene, with ovarian cancer risk in BRCA1 mutation carriers (HR: 1.12 95% CI: 1.03-1.21, p = 4.8x10(-3)). DNA glycosylases involved in the first steps of the BER pathway may be associated with cancer risk in BRCA1/2 mutation carriers and should be more comprehensively studied.
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04 - 1.15, p = 1.9 x 10\(^{-4}\) (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03 - 1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted p\(_{interaction}\) values > 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients' survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers.
Purpose:
Investigation of a reduced source to target distance to improve organ at risk sparing during stereotactic irradiation (STX).
Methods:
The authors present a planning study with perfectly target-volume adapted collimator compared with multi-leaf collimator (MLC) at reduced source to virtual isocentre distance (SVID) in contrast to normal source to isocentre distance (SID) for stereotactic applications. The role of MLC leaf width and 20–80% penumbra was examined concerning the healthy tissue sparing. Several prescription schemes and target diameters are considered.
Results:
Paddick’s gradient index (GI) as well as comparison of the mean doses to spherical shells at several distances to the target is evaluated. Both emphasize the same results: the healthy tissue sparing in the high dose area around the planning target volume (PTV) is improved at reduced SVID ≤ 70 cm. The effect can be attributed more to steeper penumbra than to finer leaf resolution. Comparing circular collimators at different SVID just as MLC-shaped collimators, always the GI was reduced. Even MLC-shaped collimator at SVID 70 cm had better healthy tissue sparing than an optimal shaped circular collimator at SID 100 cm.
Regarding penumbra changes due to varying SVID, the results of the planning study are underlined by film dosimetry measurements with Agility™ MLC.
Conclusion:
Penumbra requires more attention in comparing studies, especially studies using different planning systems. Reduced SVID probably allows usage of conventional MLC for STX-like irradiations.
Purpose:
The model used to calculate dose distributions in a radiotherapy treatment plan relies on the data entered during beam commissioning. The quality of these data heavily depends on the detector choice made, especially in small fields and in the buildup region. Therefore, it is necessary to identify suitable detectors for measurements in the buildup region of small fields. To aid the understanding of a detector's limitations, several factors that influence the detector signal are to be analyzed, for example, the volume effect due to the detector size, the response to electron contamination, the signal dependence on the polarity used, and the effective point of measurement chosen.
Methods:
We tested the suitability of different small field detectors for measurements of depth dose curves with a special focus on the surface‐near area of dose buildup for fields sized between 10 × 10 and 0.6 × 0.6 cm\(^{2}\). Depth dose curves were measured with 14 different detectors including plane‐parallel chambers, thimble chambers of different types and sizes, shielded and unshielded diodes as well as a diamond detector. Those curves were compared with depth dose curves acquired on Gafchromic film. Additionally, the magnitude of geometric volume corrections was estimated from film profiles in different depths. Furthermore, a lead foil was inserted into the beam to reduce contaminating electrons and to study the resulting changes of the detector response. The role of the effective point of measurement was investigated by quantifying the changes occurring when shifting depth dose curves. Last, measurements for the small ionization chambers taken at opposing biasing voltages were compared to study polarity effects.
Results:
Depth‐dependent correction factors for relative depth dose curves with different detectors were derived. Film, the Farmer chamber FC23, a 0.13 cm\(^{3}\) scanning chamber CC13 and a plane‐parallel chamber PPC05 agree very well in fields sized 4 × 4 and 10 × 10 cm\(^{2}\). For most detectors and in smaller fields, depth dose curves differ from the film. In general, shielded diodes require larger corrections than unshielded diodes. Neither the geometric volume effect nor the electron contamination can account for the detector differences. The biggest uncertainty arises from the positioning of a detector with respect to the water surface and from the choice of the detector's effective point of measurement. Depth dose curves acquired with small ionization chambers differ by over 15% in the buildup region depending on sign of the biasing voltage used.
Conclusions:
A scanning chamber or a PPC40 chamber is suitable for fields larger than 4 × 4 cm\(^{2}\). Below that field size, the microDiamond or small ionization chambers perform best requiring the smallest corrections at depth as well as in the buildup region. Diode response changes considerably between the different types of detectors. The position of the effective point of measurement has a huge effect on the resulting curves, therefore detector specific rather than general shifts of half the inner radius of cylindrical ionization chambers for the effective point of measurement should be used. For small ionization chambers, averaging between both polarities is necessary for data obtained near the surface.