Mammographic density and risk of breast cancer by age and tumor characteristics

Introduction: Understanding whether mammographic density (MD) is associated with all breast tumor subtypes and whether the strength of association varies by age is important for utilizing MD in risk models. Methods: Data were pooled from six studies including 3414 women with breast cancer and 7199 without who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2)) status by age (51%) versus average density (11-25%). Women ages 2.1 cm) versus small tumors and positive versus negative lymph node status (P’s < 0.01). For women ages <55 years, there was a stronger association of MD with ER-negative breast cancer than ER-positive tumors compared to women ages 55–64 and ≥65 years (Page-interaction = 0.04). MD was positively associated with both HER2-negative and HER2-positive tumors within each age group. Conclusion: MD is strongly associated with all breast cancer subtypes, but particularly tumors of large size and positive lymph nodes across all ages, and ER-negative status among women ages <55 years, suggesting high MD may play an important role in tumor aggressiveness, especially in younger women

Взаимосвязь показателей кровообращения мышц бедра и плеча с координационной точностью при совершенствовании ударных баллистических движений

В работе была исследована взаимосвязь показателей кровообращения мышц бедра и плеча с координационной точностью при совершенствовании ударных баллистических движений. Для этого было сформировано две группы: в экспериментальной группе в качестве предупреждения травматизма кисти использовались боксерские перчатки (10 унций), а в контрольной - снарядные перчатки. В результате после нанесения одиночного акцентированного прямого удара правой рукой в голову по боксерскому мешку в течение раунда было получено, что в экспериментальной группе происходило увеличение интенсивности кровенаполнения задней поверхности правого бедра и увеличение венозного оттока. Можно предположить, что спортсмены экспериментальной группы больше опираются на правую ногу в заключительной фазе ударного действия, что является более правильно с биомеханической точки зрения нанесения ударов. Интенсивность кровенаполнения и венозного оттока плеча в экспериментальной группе, наоборот, падала. Это позволяет сделать предположение о том, что мышцы плеча при выполнении ударных движений лишь незначительно задействуются спортсменами старших спортивных разрядов в завершающей фазе ударного действия. Данный факт им позволяет наносить удары с большей точностью и эффективностью

Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.ABCFS: The Australian Breast Cancer Family Registry (ABCFR; 1992-1995) was supported by the Australian NHMRC, the New South Wales Cancer Council, and the Victorian Health Promotion Foundation (Australia), and by grant UM1CA164920 from the USA National Cancer Institute. The Genetic Epidemiology Laboratory at the University of Melbourne has also received generous support from Mr B. Hovey and Dr and Mrs R.W. Brown to whom we are most grateful. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Breast Cancer Susceptibility Variants and Mammographic Density 5 Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. BBCC: This study was funded in part by the ELAN-Program of the University Hospital Erlangen; Katharina Heusinger was funded by the ELAN program of the University Hospital Erlangen. BBCC was supported in part by the ELAN program of the Medical Faculty, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg. EPIC-Norfolk: This study was funded by research programme grant funding from Cancer Research UK and the Medical Research Council with additional support from the Stroke Association, British Heart Foundation, Department of Health, Research into Ageing and Academy of Medical Sciences. MCBCS: This study was supported by Public Health Service Grants P50 CA 116201, R01 CA 128931, R01 CA 128931-S01, R01 CA 122340, CCSG P30 CA15083, from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. MCCS: Melissa C. Southey is a National Health and Medical Research Council Senior Research Fellow and a Victorian Breast Cancer Research Consortium Group Leader. The study was supported by the Cancer Council of Victoria and by the Victorian Breast Cancer Research Consortium. MEC: National Cancer Institute: R37CA054281, R01CA063464, R01CA085265, R25CA090956, R01CA132839. MMHS: This work was supported by grants from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. (R01 CA128931, R01 CA 128931-S01, R01 CA97396, P50 CA116201, and Cancer Center Support Grant P30 CA15083). Breast Cancer Susceptibility Variants and Mammographic Density 6 NBCS: This study has been supported with grants from Norwegian Research Council (#183621/S10 and #175240/S10), The Norwegian Cancer Society (PK80108002, PK60287003), and The Radium Hospital Foundation as well as S-02036 from South Eastern Norway Regional Health Authority. NHS: This study was supported by Public Health Service Grants CA131332, CA087969, CA089393, CA049449, CA98233, CA128931, CA 116201, CA 122340 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. OOA study was supported by CA122822 and X01 HG005954 from the NIH; Breast Cancer Research Fund; Elizabeth C. Crosby Research Award, Gladys E. Davis Endowed Fund, and the Office of the Vice President for Research at the University of Michigan. Genotyping services for the OOA study were provided by the Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096. OFBCR: This work was supported by grant UM1 CA164920 from the USA National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. SASBAC: The SASBAC study was supported by Märit and Hans Rausing’s Initiative against Breast Cancer, National Institutes of Health, Susan Komen Foundation and Agency for Science, Technology and Research of Singapore (A*STAR). Breast Cancer Susceptibility Variants and Mammographic Density 7 SIBS: SIBS was supported by program grant C1287/A10118 and project grants from Cancer Research UK (grant numbers C1287/8459). COGS grant: Collaborative Oncological Gene-environment Study (COGS) that enabled the genotyping for this study. Funding for the BCAC component is provided by grants from the EU FP7 programme (COGS) and from Cancer Research UK. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post- Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAMEON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.This is the author accepted manuscript. The final version is available via American Association for Cancer Research at http://cancerres.aacrjournals.org/content/early/2015/04/10/0008-5472.CAN-14-2012.abstract

Breast MRI: guidelines from the European Society of Breast Imaging

The aim of breast MRI is to obtain a reliable evaluation of any lesion within the breast. It is currently always used as an adjunct to the standard diagnostic procedures of the breast, i.e., clinical examination, mammography and ultrasound. Whereas the sensitivity of breast MRI is usually very high, specificity—as in all breast imaging modalities—depends on many factors such as reader expertise, use of adequate techniques and composition of the patient cohorts. Since breast MRI will always yield MR-only visible questionable lesions that require an MR-guided intervention for clarification, MRI should only be offered by institutions that can also offer a MRI-guided breast biopsy or that are in close contact with a site that can perform this type of biopsy for them. Radiologists involved in breast imaging should ensure that they have a thorough knowledge of the MRI techniques that are necessary for breast imaging, that they know how to evaluate a breast MRI using the ACR BI-RADS MRI lexicon, and most important, when to perform breast MRI. This manuscript provides guidelines on the current best practice for the use of breast MRI, and the methods to be used, from the European Society of Breast Imaging (EUSOBI)

Strategies for blocking the fibrogenic actions of connective tissue growth factor (CCN2): From pharmacological inhibition in vitro to targeted siRNA therapy in vivo

Connective tissue growth factor (CCN2) is a major pro-fibrotic factor that frequently acts downstream of transforming growth factor beta (TGF-β)-mediated fibrogenic pathways. Much of our knowledge of CCN2 in fibrosis has come from studies in which its production or activity have been experimentally attenuated. These studies, performed both in vitro and in animal models, have demonstrated the utility of pharmacological inhibitors (e.g. tumor necrosis factor alpha (TNF-α), prostaglandins, peroxisome proliferator-activated receptor-gamma (PPAR-γ) agonists, statins, kinase inhibitors), neutralizing antibodies, antisense oligonucleotides, or small interfering RNA (siRNA) to probe the role of CCN2 in fibrogenic pathways. These investigations have allowed the mechanisms regulating CCN2 production to be more clearly defined, have shown that CCN2 is a rational anti-fibrotic target, and have established a framework for developing effective modalities of therapeutic intervention in vivo

Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression.

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.ajhg.2015.05.002

A Metaheuristic Framework for Bi-level Programming Problems with Multi-disciplinary Applications

Bi-level programming problems arise in situations when the decision maker has to take into account the responses of the users to his decisions. Several problems arising in engineering and economics can be cast within the bi-level programming framework. The bi-level programming model is also known as a Stackleberg or leader-follower game in which the leader chooses his variables so as to optimise his objective function, taking into account the response of the follower(s) who separately optimise their own objectives, treating the leader’s decisions as exogenous. In this chapter, we present a unified framework fully consistent with the Stackleberg paradigm of bi-level programming that allows for the integration of meta-heuristic algorithms with traditional gradient based optimisation algorithms for the solution of bi-level programming problems. In particular we employ Differential Evolution as the main meta-heuristic in our proposal.We subsequently apply the proposed method (DEBLP) to a range of problems from many fields such as transportation systems management, parameter estimation and game theory. It is demonstrated that DEBLP is a robust and powerful search heuristic for this class of problems characterised by non smoothness and non convexity