Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10−8) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (PPeer reviewe

IMECE2008-69272 High Speed Micro Holographic PIV Measurements of Microorganisms

ABSTRACT Holographic particle image velocimetry (PIV) is a novel application of holography that allows for tracking of small particle sized objects in a small volume. Whereas regular PIV allows for the two in-plane components of the velocity field to be measured, and stereoscopic PIV allows for the threecomponents of the velocity field to be measured in a thin plane, holographic PIV allows for the three-components of the velocity to be measured for each individual particle present in the measuring volume, thus allowing to fully resolve fluid flows that are inherently 3D in nature. There are many examples of three dimensional flows in nature including turbulence flows, but another very interesting application very well suited for this technique involves tracking living microorganisms in order to study their motion and their means of propulsion. As part of this research a micro organism was tracked in three dimensions using a high speed microscopic holographic imaging method. The ability to track organisms in 3D allows better understanding and characterizing of their behavior including their propulsion methods, their feeding methods and their interaction with each other. The time resolved holograms were reconstructed in Matlab using Fast Fourier Transforms. A laser pointer was used as a source of coherent light, and a high speed PIV camera (Photron APX Ultima) was used to capture the images. A beam expander was used to increase the diameter of the laser beam allowing for a larger tracking area. Results with this system will show the trajectories in 3D of microorganisms as well as the three components of the velocity field showing the interaction of the organisms with their environment

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P&lt;5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P&lt;0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction