Distinct Reproductive Risk Profiles for Intrinsic-Like Breast Cancer Subtypes: Pooled Analysis of Population-Based Studies

Background: Reproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear. Methods: Analyses included up to 23353 cases and 71072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided. Results: Compared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2-like, and HER2-enriched-like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity <. 001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity <. 001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like. Conclusions: This large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction

Breast cancer risk factors and survival by tumor subtype: pooled analyses from the breast cancer association consortium

Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype.Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P-adj > 0.30). The strongest associations were between all-cause mortality and BMI >= 30 versus 18.5-25 kg/m(2) [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age >= 30 years versus 0-= 10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.Surgical oncolog

Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study

Objectives: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics. Methods: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105–377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity. Results: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger). Conclusion: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women

Two truncating variants in FANCC and breast cancer risk

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95% CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.Peer reviewe

Associations of obesity and circulating insulin and glucose with breast cancer risk: a Mendelian randomization analysis.

BACKGROUND: In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. METHODS: We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. RESULTS: All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p  =  5.09  ×  10-4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p  =  4.02  ×  10-4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p  =  5.05  ×  10-19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p  =  9.22  ×  10-6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. CONCLUSIONS: We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer

A joint Fermi-GBM and Swift-BAT analysis of gravitational-wave candidates from the third gravitational-wave observing run

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational-wave (GW) candidate events identified during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Using Fermi-GBM onboard triggers and subthreshold gamma-ray burst (GRB) candidates found in the Fermi-GBM ground analyses, the Targeted Search and the Untargeted Search, we investigate whether there are any coincident GRBs associated with the GWs. We also search the Swift-BAT rate data around the GW times to determine whether a GRB counterpart is present. No counterparts are found. Using both the Fermi-GBM Targeted Search and the Swift-BAT search, we calculate flux upper limits and present joint upper limits on the gamma-ray luminosity of each GW. Given these limits, we constrain theoretical models for the emission of gamma rays from binary black hole mergers

X-ray Study Of Herbaspirilum Seropedicae Glnb Protein Adsorbed On Silicon

GlnB-Hs protein is a globular member of PII-like family involved in the nitrogen control fixation in diazothoph organisms like H. seropedicae. In this work, GlnB-Hs is deposited by spin-coating on Si (in) and its self-assembling is investigated by AFM (atomic force microscopy) and X-ray at grazing incidence angles. GlnB-Hs forms circular 100 nm to 150 nm wide face-up donut shaped protein aggregates on silicon. Reflectivity and diffraction profiles from the protein deposits on Si(111) and Si(100), suggest ordered domains that are stable under the X-ray beam and have d-spacing compatible with protein dimensions already determined by classical protein crystallography. Copyright © 2006 WILEY-VCH Verlag GmbH & Co. KGaA.245-246140146Gray, J., Curr. Opi. in Struct. Biology, 1004 (14), p. 110Sleytr, U., Gyorvary, E., (2003) Progr. in Org. Coating, 47, p. 279Pechkova, E., Nicolini, C., (2004) Trends in Bio, 22, p. 117Pechkova, E., Nicolini, C., (2001) J. of Crystal growth, 231, p. 599Giegé, R., Drenth, J., Ducruix, A., McPherson, A., Saenger, W., (1995) Prog. Cryst. Growth and charact, 30, p. 237Jap, B.K., Zulauf, M., Scheybani, T., Hefti, A., Baumeister, W., Aebi, U., Engel, A., (1992) Ultramicroscopy, 46, p. 45Als-Nielsen, J., Jacquemain, D., Kjaer, K., Leveiller, F., Lahav, M., Leiserowitz, L., (1994) Physics reports, 246, p. 251Samant, M.G., Brown, C.A., Gordon II, J.C., (1991) Langmuir, 7, p. 437Seul, M., Eisenberger, P., McCOnnell, H.M., (1983) PNAS, 80, p. 5795Fenter, P., Eisenberger, P., Li, J., Camillone, N., Bernasek, S., Scoles, G., Ramanarayanan, T.A., Liang, K.S., (1991) Langmuir, 7, p. 2013Salditt, T., Mennicke, U., (2002) Longmuir, 18, p. 8172Verclas, S.A.W., Howes, P.B., Kjaer, K., Wurlitzer, A., Weygand, M., Buldt, G., Dencher, N.A., Lösche, M., (1999) J.M.B, 287, p. 837Lawrence, C.J., Zhou, W., (1991) J. of Non-Newtonian fluid Mech, 39, p. 137Ninfa, A.J., Atkinson, M.R., (2000) Trends Microbiol, 8, p. 172Baldani, V.L.D., Baldani, J.I., Olivares, F., Dobereiner, J., (1992) Symbiosis, 13, p. 65Baldani, J.I., Baldani, V.L.D., Seldin, L., Dobereiner, J., (1986) Int. J. Syst. Bacteriol, 36, p. 86Pimentel, J.P., Olivares, F., Pitard, R.M., Urquiaga, S., Akiba, F., Dobereiner, J., (1991) Plant Soil, 137, p. 61Weber, O.B., Baldani, V.L.D., Teixeira, K.R.S., Kirchhof, C., Baldani, J.I., Doberreiner, J., (1999) Plont Soil, 210, p. 103Benelli, E.M., de Souza, E.M., Funayama, S., Rigo, L.U., Pedrosa, F.O., (1997) J. Bacteriol, 179, p. 4623de Souza, E.M., Pedrosa, F.O., Drummond, M.H., Rigo, L.U., Yates, M.G., (1999) J. Bacteriol, 181, p. 681Benelli, E.M., Buck, M., de Souza, E.M., Yates, M.G., Pedrosa, F.O., (2001) Can. J. Microbiol, 47, p. 309Benelli, E.M., Buck, M., Polikarpov, I., de Souza, E.M., Cruz, L.M., Pedrosa, F.O., (2002) Eur. J. Biochem, 269, p. 3296Hirose, M., Yasaka, T., Takakura, M., Miyazaki, S., (1991) Solid State Technology, p. 43Windt, D.L., (1998) Computers in physics, 12, p. 360Lubambo, A.F., Benelli, E.M., Klein, J., Schreiner, W., de Camargo, P.C., (2006) Cell Bio. and Biophysics, 44, p. 503Guinier, A., (1963) X-Ray Diffraction, p. 121. , Freeman, San FranciscoPechkova, E., Fiodoro, S., Fontani, D., Nicolini, C., (2005) Acta Crysta. D, 61, p. 809Adachi, E., Nagayama, K., (1997) Adv. Biophys, 34, p. 81Kralchevsky, P., Denkov, N.D., (2001) Cur. Opi. In Colloid & Inter. Sci, 6, p. 383Ravelli, R., McSweeneney, S.M., (2000) Structure, 8, p. 315Nave, C., Hill, M.A., (2005) J. Sync. Rad, 12, p. 261Ashley, J.C., (1980) IEEE Trans. on Nucl. Scien, 27, p. 1454M. J. Berger, J. S. Coursey, M. A. Zucker. V 1.2.2., NIST, Gaithersburg, MD, USA 2000Hovington, P., Drouin, D., Gauvin, R., (1997) Scanning, 19, p. 1Murray, J.W., Garman, E.F., Ravelli, R.B.G., (2004) J. of Appl. Cryst, 37, p. 51

Sr, C, and O isotope geochemistry of Ordovician brachiopods: a major isotopic event around the middle-late Ordovician transition

Here we present Sr, C, and O isotope curves for Ordovician marine calcite based on analyses of 206 calcitic brachiopods from 10 localities worldwide. These are the first Ordovician-wide isotope curves that can be placed within the newly emerging global biostratigraphic framework. A total of 182 brachiopods were selected for C and O isotope analysis, and 122 were selected for Sr isotope analysis. Seawater 87Sr/86Sr decreased from 0.7090 to 0.7078 during the Ordovician, with a major, quite rapid fall around the Middle–Late Ordovician transition, most probably caused by a combination of low continental erosion rates and increased submarine hydrothermal exchange rates. Mean δ18O values increase from −10‰ to −3‰ through the Ordovician with an additional short-lived increase of 2 to 3‰ during the latest Ordovician due to glaciation. Although diagenetic alteration may have lowered δ18O in some samples, particularly those from the Lower Ordovician, maximum δ18O values, which are less likely to be altered, increase by more than 3‰ through the Ordovician in both our data and literature data. We consider that this long-term rise in calcite δ18O records the effect of decreasing tropical seawater temperatures across the Middle–Late Ordovician transition superimposed on seawater δ18O that was steadily increasing from ≤−3‰ standard mean ocean water (SMOW). By contrast, δ13C variation seems to have been relatively modest during most of the Ordovician with the exception of the globally documented, but short-lived, latest Ordovician δ13C excursion up to +7‰. Nevertheless, an underlying trend in mean δ13C can be discerned, changing from moderately negative values in the Early Ordovician to moderately positive values by the latest Ordovician. These new isotopic data confirm a major reorganization of ocean chemistry and the surface environment around 465 to 455 Ma. The juxtaposition of the greatest recorded swings in Phanerozoic seawater 87Sr/86Sr and δ18O at the same time as one of the largest marine transgressions in Phanerozoic Earth history suggests a causal link between tectonic and climatic change, and emphasizes an endogenic control on the O isotope budget during the Early Paleozoic. Better isotopic and biostratigraphic constraints are still required if we are to understand the true significance of these changes. We recommend that future work on Ordovician isotope stratigraphy focus on this outstanding Middle–Late Ordovician event

Performance modelling of magnetohydrodynamics codes

Performance modelling is an important tool utilised by the High Performance Computing industry to accurately predict the run-time of science applications on a variety of different architectures. Performance models aid in procurement decisions and help to highlight areas for possible code optimisations. This paper presents a performance model for a magnetohydrodynamics physics application, Lare. We demonstrate that this model is capable of accurately predicting the run-time of Lare across multiple platforms with an accuracy of 90% (for both strong and weak scaled problems). We then utilise this model to evaluate the performance of future optimisations. The model is generated using SST/macro, the machine level component of the Structural Simulation Toolkit (SST) from Sandia National Laboratories, and is validated on both a commodity cluster located at the University of Warwick and a large scale capability resource located at Lawrence Livermore National Laboratory

Genome-wide average DNA methylation is determined in utero

Background Investigating the genetic and environmental causes of variation in genome-wide average DNA methylation (GWAM), a global methylation measure from the HumanMethylation450 array, might give a better understanding of genetic and environmental influences on methylation. Methods We measured GWAM for 2299 individuals aged 0 to 90 years from seven twin and/or family studies. We estimated familial correlations, modelled correlations with cohabitation history and fitted variance components models for GWAM. Results The correlation in GWAM for twin pairs was ∼0.8 at birth, decreased with age during adolescence and was constant at ∼0.4 throughout adulthood, with no evidence that twin pair correlations differed by zygosity. Non-twin first-degree relatives were correlated, from 0.17 [95% confidence interval (CI): 0.05–0.30] to 0.28 (95% CI: 0.08–0.48), except for middle-aged siblings (0.01, 95% CI: −0.10–0.12), and the correlation increased with time living together and decreased with time living apart. Spouse pairs were correlated in all studies, from 0.23 (95% CI: 0.3–0.43) to 0.31 (95% CI: 0.05–0.52), and the correlation increased with time living together. The variance explained by environmental factors shared by twins alone was 90% (95% CI: 74–95%) at birth, decreased in early life and plateaued at 28% (95% CI: 17–39%) in middle age and beyond. There was a cohabitation-related environmental component of variance. Conclusions GWAM is determined in utero by prenatal environmental factors, the effects of which persist throughout life. The variation of GWAM is also influenced by environmental factors shared by family members, as well as by individual-specific environmental factors