Perceived Versus Objective Breast Cancer, Breast Cancer Risk in Diverse Women

PubMed Central

Fehniger, Julia; Livaudais-Toman, Jennifer; Karliner, Leah; Kerlikowske, Karla; Tice, Jeffrey A.; Quinn, Jessica; Ozanne, Elissa

2014-01-01

Abstract Background: Prior research suggests that women do not accurately estimate their risk for breast cancer. Estimating and informing women of their risk is essential for tailoring appropriate screening and risk reduction strategies. Methods: Data were collected for BreastCARE, a randomized controlled trial designed to evaluate a PC-tablet based intervention providing multiethnic women and their primary care physicians with tailored information about breast cancer risk. We included women ages 40–74 visiting general internal medicine primary care clinics at one academic practice and one safety net practice who spoke English, Spanish, or Cantonese, and had no personal history of breast cancer. We collected baseline information regarding risk perception and concern. Women were categorized as high risk (vs. average risk) if their family history met criteria for referral to genetic counseling or if they were in the top 5% of risk for their age based on the Gail or Breast Cancer Surveillance Consortium Model (BCSC) breast cancer risk model. Results: Of 1,261 participants, 25% (N=314) were classified as high risk. More average risk than high risk women had correct risk perception (72% vs. 18%); 25% of both average and high risk women reported being very concerned about breast cancer. Average risk women with correct risk perception were less likely to be concerned about breast cancer (odds ratio [OR]=0.3; 95% confidence interval [CI]=0.2–0.4) while high risk women with correct risk perception were more likely to be concerned about breast cancer (OR=5.1; 95%CI=2.7–9.6). Conclusions: Many women did not accurately perceive their risk for breast cancer. Women with accurate risk perception had an appropriate level of concern about breast cancer. Improved methods of assessing and informing women of their breast cancer risk could motivate high risk women to apply appropriate prevention strategies and allay unnecessary concern among average risk women. PMID:24372085

Combining quantitative and qualitative breast density measures to assess breast cancer risk.

PubMed

Kerlikowske, Karla; Ma, Lin; Scott, Christopher G; Mahmoudzadeh, Amir P; Jensen, Matthew R; Sprague, Brian L; Henderson, Louise M; Pankratz, V Shane; Cummings, Steven R; Miglioretti, Diana L; Vachon, Celine M; Shepherd, John A

2017-08-22

Accurately identifying women with dense breasts (Breast Imaging Reporting and Data System [BI-RADS] heterogeneously or extremely dense) who are at high breast cancer risk will facilitate discussions of supplemental imaging and primary prevention. We examined the independent contribution of dense breast volume and BI-RADS breast density to predict invasive breast cancer and whether dense breast volume combined with Breast Cancer Surveillance Consortium (BCSC) risk model factors (age, race/ethnicity, family history of breast cancer, history of breast biopsy, and BI-RADS breast density) improves identifying women with dense breasts at high breast cancer risk. We conducted a case-control study of 1720 women with invasive cancer and 3686 control subjects. We calculated ORs and 95% CIs for the effect of BI-RADS breast density and Volpara™ automated dense breast volume on invasive cancer risk, adjusting for other BCSC risk model factors plus body mass index (BMI), and we compared C-statistics between models. We calculated BCSC 5-year breast cancer risk, incorporating the adjusted ORs associated with dense breast volume. Compared with women with BI-RADS scattered fibroglandular densities and second-quartile dense breast volume, women with BI-RADS extremely dense breasts and third- or fourth-quartile dense breast volume (75% of women with extremely dense breasts) had high breast cancer risk (OR 2.87, 95% CI 1.84-4.47, and OR 2.56, 95% CI 1.87-3.52, respectively), whereas women with extremely dense breasts and first- or second-quartile dense breast volume were not at significantly increased breast cancer risk (OR 1.53, 95% CI 0.75-3.09, and OR 1.50, 95% CI 0.82-2.73, respectively). Adding continuous dense breast volume to a model with BCSC risk model factors and BMI increased discriminatory accuracy compared with a model with only BCSC risk model factors (C-statistic 0.639, 95% CI 0.623-0.654, vs. C-statistic 0.614, 95% CI 0.598-0.630, respectively; P < 0.001). Women

Knocking down cyclin D1b inhibits breast cancer cell growth and suppresses tumor development in a breast cancer model.

PubMed

Wei, Min; Zhu, Li; Li, Yafen; Chen, Weiguo; Han, Baosan; Wang, Zhiwei; He, Jianrong; Yao, Hongliang; Yang, Zhongyin; Zhang, Qing; Liu, Bingya; Gu, Qinlong; Zhu, Zhenggang; Shen, Kunwei

2011-08-01

Cyclin D1 is aberrantly expressed in many types of cancers, including breast cancer. High levels of cyclin D1b, the truncated isoform of cyclin D1, have been reported to be associated with a poor prognosis for breast cancer patients. In the present study, we used siRNA to target cyclin D1b overexpression and assessed its ability to suppress breast cancer growth in nude mice. Cyclin D1b siRNA effectively inhibited overexpression of cyclin D1b. Depletion of cyclin D1b promoted apoptosis of cyclin D1b-overexpressing cells and blocked their proliferation and transformation phenotypes. Notably, cyclin D1b overexpression is correlated with triple-negative basal-like breast cancers, which lack specific therapeutic targets. Administration of cyclin D1b siRNA inhibited breast tumor growth in nude mice and cyclin D1b siRNA synergistically enhanced the cell killing effects of doxorubicin in cell culture, with this combination significantly suppressing tumor growth in the mouse model. In conclusion, the results indicate that cyclin D1b, which is overexpressed in breast cancer, may serve as a novel and effective therapeutic target. More importantly, the present study clearly demonstrated a very promising therapeutic potential for cyclin D1b siRNA in the treatment of cyclin D1b-overexpressing breast cancers, including the very malignant triple-negative breast cancers. © 2011 Japanese Cancer Association.

In vivo models in breast cancer research: progress, challenges and future directions

PubMed Central

Holen, Ingunn; Speirs, Valerie; Morrissey, Bethny

2017-01-01

ABSTRACT Research using animal model systems has been instrumental in delivering improved therapies for breast cancer, as well as in generating new insights into the mechanisms that underpin development of the disease. A large number of different models are now available, reflecting different types and stages of the disease; choosing which one to use depends on the specific research question(s) to be investigated. Based on presentations and discussions from leading experts who attended a recent workshop focused on in vivo models of breast cancer, this article provides a perspective on the many varied uses of these models in breast cancer research, their strengths, associated challenges and future directions. Among the questions discussed were: how well do models represent the different stages of human disease; how can we model the involvement of the human immune system and microenvironment in breast cancer; what are the appropriate models of metastatic disease; can we use models to carry out preclinical drug trials and identify pathways responsible for drug resistance; and what are the limitations of patient-derived xenograft models? We briefly outline the areas where the existing breast cancer models require improvement in light of the increased understanding of the disease process, reflecting the drive towards more personalised therapies and identification of mechanisms of drug resistance. PMID:28381598

Structure, Function, and Applications of the Georgetown-Einstein (GE) Breast Cancer Simulation Model.

PubMed

Schechter, Clyde B; Near, Aimee M; Jayasekera, Jinani; Chandler, Young; Mandelblatt, Jeanne S

2018-04-01

The Georgetown University-Albert Einstein College of Medicine breast cancer simulation model (Model GE) has evolved over time in structure and function to reflect advances in knowledge about breast cancer, improvements in early detection and treatment technology, and progress in computing resources. This article describes the model and provides examples of model applications. The model is a discrete events microsimulation of single-life histories of women from multiple birth cohorts. Events are simulated in the absence of screening and treatment, and interventions are then applied to assess their impact on population breast cancer trends. The model accommodates differences in natural history associated with estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) biomarkers, as well as conventional breast cancer risk factors. The approach for simulating breast cancer natural history is phenomenological, relying on dates, stage, and age of clinical and screen detection for a tumor molecular subtype without explicitly modeling tumor growth. The inputs to the model are regularly updated to reflect current practice. Numerous technical modifications, including the use of object-oriented programming (C++), and more efficient algorithms, along with hardware advances, have increased program efficiency permitting simulations of large samples. The model results consistently match key temporal trends in US breast cancer incidence and mortality. The model has been used in collaboration with other CISNET models to assess cancer control policies and will be applied to evaluate clinical trial design, recurrence risk, and polygenic risk-based screening.

Modelling breast cancer tumour growth for a stable disease population.

PubMed

Isheden, Gabriel; Humphreys, Keith

2017-01-01

Statistical models of breast cancer tumour progression have been used to further our knowledge of the natural history of breast cancer, to evaluate mammography screening in terms of mortality, to estimate overdiagnosis, and to estimate the impact of lead-time bias when comparing survival times between screen detected cancers and cancers found outside of screening programs. Multi-state Markov models have been widely used, but several research groups have proposed other modelling frameworks based on specifying an underlying biological continuous tumour growth process. These continuous models offer some advantages over multi-state models and have been used, for example, to quantify screening sensitivity in terms of mammographic density, and to quantify the effect of body size covariates on tumour growth and time to symptomatic detection. As of yet, however, the continuous tumour growth models are not sufficiently developed and require extensive computing to obtain parameter estimates. In this article, we provide a detailed description of the underlying assumptions of the continuous tumour growth model, derive new theoretical results for the model, and show how these results may help the development of this modelling framework. In illustrating the approach, we develop a model for mammography screening sensitivity, using a sample of 1901 post-menopausal women diagnosed with invasive breast cancer.

Phytoestrogens in menopausal supplements induce ER-dependent cell proliferation and overcome breast cancer treatment in an in vitro breast cancer model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duursen, Majorie B.M. van, E-mail: M.vanDuursen@uu.nl; Smeets, Evelien E.J.W.; Rijk, Jeroen C.W.

Breast cancer treatment by the aromatase inhibitor Letrozole (LET) or Selective Estrogen Receptor Modulator Tamoxifen (TAM) can result in the onset of menopausal symptoms. Women often try to relieve these symptoms by taking menopausal supplements containing high levels of phytoestrogens. However, little is known about the potential interaction between these supplements and breast cancer treatment, especially aromatase inhibitors. In this study, interaction of phytoestrogens with the estrogen receptor alpha and TAM action was determined in an ER-reporter gene assay (BG1Luc4E2 cells) and human breast epithelial tumor cells (MCF-7). Potential interactions with aromatase activity and LET were determined in human adrenocorticocarcinomamore » H295R cells. We also used the previously described H295R/MCF-7 co-culture model to study interactions with steroidogenesis and tumor cell proliferation. In this model, genistein (GEN), 8-prenylnaringenin (8PN) and four commercially available menopausal supplements all induced ER-dependent tumor cell proliferation, which could not be prevented by physiologically relevant LET and 4OH-TAM concentrations. Differences in relative effect potencies between the H295R/MCF-7 co-culture model and ER-activation in BG1Luc4E2 cells, were due to the effects of the phytoestrogens on steroidogenesis. All tested supplements and GEN induced aromatase activity, while 8PN was a strong aromatase inhibitor. Steroidogenic profiles upon GEN and 8PN exposure indicated a strong inhibitory effect on steroidogenesis in H295R cells and H295R/MCF-7 co-cultures. Based on our in vitro data we suggest that menopausal supplement intake during breast cancer treatment should better be avoided, at least until more certainty regarding the safety of supplemental use in breast cancer patients can be provided. - Highlights: • Supplements containing phytoestrogens are commonly used by women with breast cancer. • Phytoestrogens alter steroidogenesis in a co

A conceptual-practice model for occupational therapy to facilitate return to work in breast cancer patients.

PubMed

Désiron, Huguette A M; Donceel, Peter; de Rijk, Angelique; Van Hoof, Elke

2013-12-01

Improved therapies and early detection have significantly increased the number of breast cancers survivors, leading to increasing needs regarding return to work (RTW). Occupational therapy (OT) interventions provide successful RTW assistance for other conditions, but are not validated in breast cancer. This paper aims to identify a theoretical framework for OT intervention by questioning how OT models can be used in OT interventions in RTW of breast cancer patients; criteria to be used to select these models and adaptations that would be necessary to match the OT model(s) to breast cancer patients' needs? Using research specific criteria derived from OT literature (conceptual OT-model, multidisciplinary, referring to the International Classification of functioning (ICF), RTW in breast cancer) a search in 9 electronic databases was conducted to select articles that describe conceptual OT models. A content analysis of those models complying to at least two of the selection criteria was realised. Checking for breast cancer specific issues, results were matched with literature of care-models regarding RTW in breast cancer. From the nine models initially identified, three [Canadian Model of Occupational Performance, Model of Human Occupation (MOHO), Person-Environment-Occupation-Performance model] were selected based on the selection criteria. The MOHO had the highest compliance rate with the criteria. To enhance usability in breast cancer, some adaptations are needed. No OT model to facilitate RTW in breast cancer could be identified, indicating a need to fill this gap. Individual and societal needs of breast cancer patients can be answered by using a MOHO-based OT model, extended with indications for better treatment, work-outcomes and longitudinal process factors.

Genetically Engineered ERα positive breast cancer mouse models

PubMed Central

Dabydeen, Sarah A.; Furth, Priscilla A.

2014-01-01

The majority of human breast cancers are ER+ but this has proven challenging to model in genetically engineered mice. This review summarizes information on twenty-one mouse models that develop ER+ mammary cancer. Where available, information on cancer pathology and gene expression profiles is referenced to assist in understanding which histological subtype of ER+ human cancer each model might represent. Esr1, Ccdn1, prolactin, TGFα, AIB1, Espl1, and Wnt1 over-expression, Pik3ca gain of function, as well as loss of p53 or loss of Stat1 are associated with ER+ mammary cancer. Treatment with the PPARγ agonist efatutazone in a mouse with Brca1 and p53 deficiency and DMBA exposure in combination with an activated myristoylated form of AKT1 also induce ER+ mammary cancer. A spontaneous mutant in nude mice that develops metastatic ER+ mammary cancer is included. Age of cancer development ranges from three to 26 months and the percentages of cancers that are ER+ vary from 21% to 100%. Not all models are characterized as to their estrogen dependency and/or response to anti-hormonal therapy. Strain backgrounds include C57Bl/6, FVB, BALB/c, 129S6/SvEv, CB6F1 and NIH nude. Most models have only been studied on one strain background. In summary while a range of models is available for studies of pathogenesis and therapy of ER+ breast cancers, many could benefit from further characterization and opportunity for development of new models remains. PMID:24481326

The Effect of Breast Cancer Fatalism on Breast Cancer Awareness Among Turkish Women.

PubMed

Altintas, Hulya Kulakci; Ayyildiz, Tulay Kuzlu; Veren, Funda; Topan, Aysel Kose

2017-10-01

The aim of this study was to evaluate the effect of breast cancer fatalism and other factors on breast cancer awareness among Turkish women. This cross-sectional and comparative descriptive study was conducted with 894 women. Data were collected by Personal Information Form, Powe Fatalism Inventory and Champion's Health Belief Model Scale. Seriousness, health motivation, BSE benefits and BSE self-efficacy perceptions of the women were moderate, and susceptibility and BSE barriers perceptions were low. It was determined that awareness of breast cancer of the women was affected by breast cancer fatalism, age, education level, employment status, marital status, family type, economic status, social assurance, menopause status, family history of cancer, family history of breast cancer, knowledge on BSE, source of information on BSE, performing of BSE, frequency of BSE performing, having a problem with breast, having a breast examination in hospital, feeling during breast examination by healthcare professional, sex of healthcare professional for breast examination and their health beliefs (p < .05). The results suggested that awareness of breast cancer of the women was affected by breast cancer fatalism. In providing breast cancer early diagnosis behaviors, it is recommended to evaluate fatalism perceptions and health beliefs of the women and to arrange educational programs for this purpose.

Quantitative analysis of breast cancer diagnosis using a probabilistic modelling approach.

PubMed

Liu, Shuo; Zeng, Jinshu; Gong, Huizhou; Yang, Hongqin; Zhai, Jia; Cao, Yi; Liu, Junxiu; Luo, Yuling; Li, Yuhua; Maguire, Liam; Ding, Xuemei

2018-01-01

Breast cancer is the most prevalent cancer in women in most countries of the world. Many computer-aided diagnostic methods have been proposed, but there are few studies on quantitative discovery of probabilistic dependencies among breast cancer data features and identification of the contribution of each feature to breast cancer diagnosis. This study aims to fill this void by utilizing a Bayesian network (BN) modelling approach. A K2 learning algorithm and statistical computation methods are used to construct BN structure and assess the obtained BN model. The data used in this study were collected from a clinical ultrasound dataset derived from a Chinese local hospital and a fine-needle aspiration cytology (FNAC) dataset from UCI machine learning repository. Our study suggested that, in terms of ultrasound data, cell shape is the most significant feature for breast cancer diagnosis, and the resistance index presents a strong probabilistic dependency on blood signals. With respect to FNAC data, bare nuclei are the most important discriminating feature of malignant and benign breast tumours, and uniformity of both cell size and cell shape are tightly interdependent. The BN modelling approach can support clinicians in making diagnostic decisions based on the significant features identified by the model, especially when some other features are missing for specific patients. The approach is also applicable to other healthcare data analytics and data modelling for disease diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

NSG Mice Provide a Better Spontaneous Model of Breast Cancer Metastasis than Athymic (Nude) Mice

PubMed Central

Puchalapalli, Madhavi; Zeng, Xianke; Mu, Liang; Anderson, Aubree; Hix Glickman, Laura; Zhang, Ming; Sayyad, Megan R.; Mosticone Wangensteen, Sierra; Clevenger, Charles V.; Koblinski, Jennifer E.

2016-01-01

Metastasis is the most common cause of mortality in breast cancer patients worldwide. To identify improved mouse models for breast cancer growth and spontaneous metastasis, we examined growth and metastasis of both estrogen receptor positive (T47D) and negative (MDA-MB-231, SUM1315, and CN34BrM) human breast cancer cells in nude and NSG mice. Both primary tumor growth and spontaneous metastases were increased in NSG mice compared to nude mice. In addition, a pattern of metastasis similar to that observed in human breast cancer patients (metastases to the lungs, liver, bones, brain, and lymph nodes) was found in NSG mice. Furthermore, there was an increase in the metastatic burden in NSG compared to nude mice that were injected with MDA-MB-231 breast cancer cells in an intracardiac experimental metastasis model. This data demonstrates that NSG mice provide a better model for studying human breast cancer metastasis compared to the current nude mouse model. PMID:27662655

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

PubMed

Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

2010-01-01

The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were <1% at eight years for ECRIC (18.9% vs. 19.0%) and WMCIU (17.5% vs. 18.3%) with area under receiver-operator-characteristic curves (AUC) of 0.81 and 0.79 respectively. Differences in breast cancer specific actual and predicted mortality were <1% at eight years for ECRIC (12.9% vs. 13.5%) and <1.5% at eight years for WMCIU (12.2% vs. 13.6%) with AUC of 0.84 and 0.82 respectively. Model calibration was good for both ER positive and negative models although the ER positive model provided better discrimination (AUC 0.82) than ER negative (AUC 0.75). We have developed a prognostication model for early breast cancer based on UK cancer registry data that predicts breast cancer survival following surgery for invasive breast cancer and includes mode of detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

Breast Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer.

PubMed

Tice, Jeffrey A; Miglioretti, Diana L; Li, Chin-Shang; Vachon, Celine M; Gard, Charlotte C; Kerlikowske, Karla

2015-10-01

Women with proliferative breast lesions are candidates for primary prevention, but few risk models incorporate benign findings to assess breast cancer risk. We incorporated benign breast disease (BBD) diagnoses into the Breast Cancer Surveillance Consortium (BCSC) risk model, the only breast cancer risk assessment tool that uses breast density. We developed and validated a competing-risk model using 2000 to 2010 SEER data for breast cancer incidence and 2010 vital statistics to adjust for the competing risk of death. We used Cox proportional hazards regression to estimate the relative hazards for age, race/ethnicity, family history of breast cancer, history of breast biopsy, BBD diagnoses, and breast density in the BCSC. We included 1,135,977 women age 35 to 74 years undergoing mammography with no history of breast cancer; 17% of the women had a prior breast biopsy. During a mean follow-up of 6.9 years, 17,908 women were diagnosed with invasive breast cancer. The BCSC BBD model slightly overpredicted risk (expected-to-observed ratio, 1.04; 95% CI, 1.03 to 1.06) and had modest discriminatory accuracy (area under the receiver operator characteristic curve, 0.665). Among women with proliferative findings, adding BBD to the model increased the proportion of women with an estimated 5-year risk of 3% or higher from 9.3% to 27.8% (P<.001). The BCSC BBD model accurately estimates women's risk for breast cancer using breast density and BBD diagnoses. Greater numbers of high-risk women eligible for primary prevention after BBD diagnosis are identified using the BCSC BBD model. © 2015 by American Society of Clinical Oncology.

Breast Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer

PubMed Central

Tice, Jeffrey A.; Miglioretti, Diana L.; Li, Chin-Shang; Vachon, Celine M.; Gard, Charlotte C.; Kerlikowske, Karla

2015-01-01

Purpose Women with proliferative breast lesions are candidates for primary prevention, but few risk models incorporate benign findings to assess breast cancer risk. We incorporated benign breast disease (BBD) diagnoses into the Breast Cancer Surveillance Consortium (BCSC) risk model, the only breast cancer risk assessment tool that uses breast density. Methods We developed and validated a competing-risk model using 2000 to 2010 SEER data for breast cancer incidence and 2010 vital statistics to adjust for the competing risk of death. We used Cox proportional hazards regression to estimate the relative hazards for age, race/ethnicity, family history of breast cancer, history of breast biopsy, BBD diagnoses, and breast density in the BCSC. Results We included 1,135,977 women age 35 to 74 years undergoing mammography with no history of breast cancer; 17% of the women had a prior breast biopsy. During a mean follow-up of 6.9 years, 17,908 women were diagnosed with invasive breast cancer. The BCSC BBD model slightly overpredicted risk (expected-to-observed ratio, 1.04; 95% CI, 1.03 to 1.06) and had modest discriminatory accuracy (area under the receiver operator characteristic curve, 0.665). Among women with proliferative findings, adding BBD to the model increased the proportion of women with an estimated 5-year risk of 3% or higher from 9.3% to 27.8% (P < .001). Conclusion The BCSC BBD model accurately estimates women's risk for breast cancer using breast density and BBD diagnoses. Greater numbers of high-risk women eligible for primary prevention after BBD diagnosis are identified using the BCSC BBD model. PMID:26282663

Breast cancer literacy and health beliefs related to breast cancer screening among American Indian women.

PubMed

Roh, Soonhee; Burnette, Catherine E; Lee, Yeon-Shim; Jun, Jung Sim; Lee, Hee Yun; Lee, Kyoung Hag

2018-08-01

The purpose of this article is to examine the health beliefs and literacy about breast cancer and their relationship with breast cancer screening among American Indian (AI) women. Using the Health Belief Model (HBM) and hierarchical logistic regression with data from a sample of 286 AI female adults residing in the Northern Plains, we found that greater awareness of breast cancer screening was linked to breast cancer screening practices. However, perceived barriers, one of the HBM constructs, prevented such screening practices. This study suggested that culturally relevant HBM factors should be targeted when developing culturally sensitive breast cancer prevention efforts.

Global Nutrition Research: Nutrition and Breast Cancer Prevention as a Model

PubMed Central

Lelièvre, Sophie A.; Weaver, Connie M.

2013-01-01

The gene-environment interaction is paramount in light of the worldwide rise of incidence of chronic diseases, with cancers in the pole position. Diet is an environmental factor with potential to influence cancer onset by shaping the epigenome (i.e., the genome organization that controls the differential expression of genes). Yet, there is no consensus regarding how diet might help prevent breast cancer, the second most frequent malignancy globally. We propose that the complexity of breast cancers requires working on a global and multidisciplinary scale to further understand the relationship between breast cancer type, diet and the epigenome. This approach is the basis for the International Breast Cancer & Nutrition (IBCN) initiative and related symposia that gather scientists and clinicians from different backgrounds and world regions. A global endeavor will not only bring the diversity necessary to pinpoint important diet-gene relationships, it will also provide momentum to develop the models, detection and assessment tools, and funding and public policy framework necessary to advance primary prevention research for the benefit of all populations affected by breast cancer. This paradigm can be adapted to understanding diet-gene relationships for other chronic diseases. PMID:24447199

Exploring the breast cancer patient journey: do breast cancer survivors need menopause management support?

PubMed

Tanna, Nuttan; Buijs, Helene; Pitkin, Joan

2011-12-01

Breast cancer survivors can be expected to suffer from menopause symptoms with estrogen deprivation due to cancer treatments, in addition to natural menopause-related estrogen loss. To gain an understanding of what support breast cancer patients have when they suffer from menopausal symptoms, and utilize findings to further inform National Health Service (NHS) care provision for breast cancer survivors. Qualitative study with focus group sessions targeting Caucasian and Asian women with breast cancer. Patient stories, with women describing their breast cancer journey and speaking about support received for any menopausal symptoms. Thematic data analysis of transcription. Breast cancer patients were not sure if they had menopausal symptoms or whether this was due to their breast cancer condition or treatment. Patients had an attitude of acceptance of menopausal symptoms and reported trying to cope with these by themselves. This research identifies a need for more information that is culturally sensitive on managing menopause symptoms, both as side-effects of breast cancer treatments as well as for affect on quality of life during the survivorship phase. Our work also gives insight into cultural remedies used for hot flushes by Asian patients, which they consider as 'cooling' foods. Breast cancer patients want to know whether side-effects of cancer treatment persist long term and how these can be managed. There is a need for improved patient support within any new NHS service models that are developed along breast cancer patient pathways, and inclusion of personalized advice for menopause symptoms.

Hpm of Estrogen Model on the Dynamics of Breast Cancer

NASA Astrophysics Data System (ADS)

Govindarajan, A.; Balamuralitharan, S.; Sundaresan, T.

2018-04-01

We enhance a deterministic mathematical model involving universal dynamics on breast cancer with immune response. This is population model so includes Normal cells class, Tumor cells, Immune cells and Estrogen. The eects regarding Estrogen are below incorporated in the model. The effects show to that amount the arrival of greater Estrogen increases the danger over growing breast cancer. Furthermore, approximate solution regarding nonlinear differential equations is arrived by Homotopy Perturbation Method (HPM). Hes HPM is good and correct technique after solve nonlinear differential equation directly. Approximate solution learnt with the support of that method is suitable same as like the actual results in accordance with this models.

Characterizing viscoelastic properties of breast cancer tissue in a mouse model using indentation.

PubMed

Qiu, Suhao; Zhao, Xuefeng; Chen, Jiayao; Zeng, Jianfeng; Chen, Shuangqing; Chen, Lei; Meng, You; Liu, Biao; Shan, Hong; Gao, Mingyuan; Feng, Yuan

2018-03-01

Breast cancer is one of the leading cancer forms affecting females worldwide. Characterizing the mechanical properties of breast cancer tissue is important for diagnosis and uncovering the mechanobiology mechanism. Although most of the studies were based on human cancer tissue, an animal model is still describable for preclinical analysis. Using a custom-build indentation device, we measured the viscoelastic properties of breast cancer tissue from 4T1 and SKBR3 cell lines. A total of 7 samples were tested for each cancer tissue using a mouse model. We observed that a viscoelastic model with 2-term Prony series could best describe the ramp and stress relaxation of the tissue. For long-term responses, the SKBR3 tissues were stiffer in the strain levels of 4-10%, while no significant differences were found for the instantaneous elastic modulus. We also found tissues from both cell lines appeared to be strain-independent for the instantaneous elastic modulus and for the long-term elastic modulus in the strain level of 4-10%. In addition, by inspecting the cellular morphological structure of the two tissues, we found that SKBR3 tissues had a larger volume ratio of nuclei and a smaller volume ratio of extracellular matrix (ECM). Compared with prior cellular mechanics studies, our results indicated that ECM could contribute to the stiffening the tissue-level behavior. The viscoelastic characterization of the breast cancer tissue contributed to the scarce animal model data and provided support for the linear viscoelastic model used for in vivo elastography studies. Results also supplied helpful information for modeling of the breast cancer tissue in the tissue and cellular levels. Copyright © 2018 Elsevier Ltd. All rights reserved.

Breast cancer risk prediction using a clinical risk model and polygenic risk score.

PubMed

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C; Leung, Jessica W T; Tice, Jeffrey A; Vachon, Celine M; Cummings, Steven R; Kerlikowske, Karla; Ziv, Elad

2016-10-01

Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome-wide association studies. We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95 % CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95 % CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95 % CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18 % of cases as high-risk (5-year risk ≥3 %), compared with 7 % using the BCSC model. The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited.

Breast Cancer Risk Prediction Using a Clinical Risk Model and Polygenic Risk Score

PubMed Central

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C.; Leung, Jessica W.T.; Tice, Jeffrey A.; Vachon, Celine M.; Cummings, Steven R.; Kerlikowske, Karla; Ziv, Elad

2016-01-01

Purpose Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome wide association studies. Methods We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Results Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95% CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95% CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95% CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18% of cases as high-risk (5-year risk ≥ 3%), compared with 7% using the BCSC model. Conclusion The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Impact Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited. PMID:27565998

BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface

PubMed Central

Lee, A J; Cunningham, A P; Kuchenbaecker, K B; Mavaddat, N; Easton, D F; Antoniou, A C

2014-01-01

Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction model that is used to compute probabilities of carrying mutations in the high-risk breast and ovarian cancer susceptibility genes BRCA1 and BRCA2, and to estimate the future risks of developing breast or ovarian cancer. In this paper, we describe updates to the BOADICEA model that extend its capabilities, make it easier to use in a clinical setting and yield more accurate predictions. Methods: We describe: (1) updates to the statistical model to include cancer incidences from multiple populations; (2) updates to the distributions of tumour pathology characteristics using new data on BRCA1 and BRCA2 mutation carriers and women with breast cancer from the general population; (3) improvements to the computational efficiency of the algorithm so that risk calculations now run substantially faster; and (4) updates to the model's web interface to accommodate these new features and to make it easier to use in a clinical setting. Results: We present results derived using the updated model, and demonstrate that the changes have a significant impact on risk predictions. Conclusion: All updates have been implemented in a new version of the BOADICEA web interface that is now available for general use: http://ccge.medschl.cam.ac.uk/boadicea/. PMID:24346285

Evidence that breast tissue stiffness is associated with risk of breast cancer.

PubMed

Boyd, Norman F; Li, Qing; Melnichouk, Olga; Huszti, Ella; Martin, Lisa J; Gunasekara, Anoma; Mawdsley, Gord; Yaffe, Martin J; Minkin, Salomon

2014-01-01

Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement.

Evidence That Breast Tissue Stiffness Is Associated with Risk of Breast Cancer

PubMed Central

Boyd, Norman F.; Li, Qing; Melnichouk, Olga; Huszti, Ella; Martin, Lisa J.; Gunasekara, Anoma; Mawdsley, Gord; Yaffe, Martin J.; Minkin, Salomon

2014-01-01

Background Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. Methods Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. Results After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. Conclusion An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement. PMID:25010427

Breast Cancer Biology and Ethnic Disparities in Breast Cancer Mortality in New Zealand: A Cohort Study

PubMed Central

Seneviratne, Sanjeewa; Lawrenson, Ross; Scott, Nina; Kim, Boa; Shirley, Rachel; Campbell, Ian

2015-01-01

Introduction Indigenous Māori women have a 60% higher breast cancer mortality rate compared with European women in New Zealand. We investigated differences in cancer biological characteristics and their impact on breast cancer mortality disparity between Māori and NZ European women. Materials and Methods Data on 2849 women with primary invasive breast cancers diagnosed between 1999 and 2012 were extracted from the Waikato Breast Cancer Register. Differences in distribution of cancer biological characteristics between Māori and NZ European women were explored adjusting for age and socioeconomic deprivation in logistic regression models. Impacts of socioeconomic deprivation, stage and cancer biological characteristics on breast cancer mortality disparity between Māori and NZ European women were explored in Cox regression models. Results Compared with NZ European women (n=2304), Māori women (n=429) had significantly higher rates of advanced and higher grade cancers. Māori women also had non-significantly higher rates of ER/PR negative and HER-2 positive breast cancers. Higher odds of advanced stage and higher grade remained significant for Māori after adjusting for age and deprivation. Māori women had almost a 100% higher age and deprivation adjusted breast cancer mortality hazard compared with NZ European women (HR=1.98, 1.55-2.54). Advanced stage and lower proportion of screen detected cancer in Māori explained a greater portion of the excess breast cancer mortality (HR reduction from 1.98 to 1.38), while the additional contribution through biological differences were minimal (HR reduction from 1.38 to 1.35). Conclusions More advanced cancer stage at diagnosis has the greatest impact while differences in biological characteristics appear to be a minor contributor for inequities in breast cancer mortality between Māori and NZ European women. Strategies aimed at reducing breast cancer mortality in Māori should focus on earlier diagnosis, which will likely

A tissue-engineered humanized xenograft model of human breast cancer metastasis to bone

PubMed Central

Thibaudeau, Laure; Taubenberger, Anna V.; Holzapfel, Boris M.; Quent, Verena M.; Fuehrmann, Tobias; Hesami, Parisa; Brown, Toby D.; Dalton, Paul D.; Power, Carl A.; Hollier, Brett G.; Hutmacher, Dietmar W.

2014-01-01

ABSTRACT The skeleton is a preferred homing site for breast cancer metastasis. To date, treatment options for patients with bone metastases are mostly palliative and the disease is still incurable. Indeed, key mechanisms involved in breast cancer osteotropism are still only partially understood due to the lack of suitable animal models to mimic metastasis of human tumor cells to a human bone microenvironment. In the presented study, we investigate the use of a human tissue-engineered bone construct to develop a humanized xenograft model of breast cancer-induced bone metastasis in a murine host. Primary human osteoblastic cell-seeded melt electrospun scaffolds in combination with recombinant human bone morphogenetic protein 7 were implanted subcutaneously in non-obese diabetic/severe combined immunodeficient mice. The tissue-engineered constructs led to the formation of a morphologically intact ‘organ’ bone incorporating a high amount of mineralized tissue, live osteocytes and bone marrow spaces. The newly formed bone was largely humanized, as indicated by the incorporation of human bone cells and human-derived matrix proteins. After intracardiac injection, the dissemination of luciferase-expressing human breast cancer cell lines to the humanized bone ossicles was detected by bioluminescent imaging. Histological analysis revealed the presence of metastases with clear osteolysis in the newly formed bone. Thus, human tissue-engineered bone constructs can be applied efficiently as a target tissue for human breast cancer cells injected into the blood circulation and replicate the osteolytic phenotype associated with breast cancer-induced bone lesions. In conclusion, we have developed an appropriate model for investigation of species-specific mechanisms of human breast cancer-related bone metastasis in vivo. PMID:24713276

Risk factors for breast cancer in the breast cancer risk model study of Guam and Saipan.

PubMed

Leon Guerrero, Rachael T; Novotny, Rachel; Wilkens, Lynne R; Chong, Marie; White, Kami K; Shvetsov, Yurii B; Buyum, Arielle; Badowski, Grazyna; Blas-Laguaña, Michelle

2017-10-01

Chamorro Pacific Islanders in the Mariana Islands have breast cancer incidence rates similar to, but mortality rates higher than, those of U.S. women. As breast cancer risk factors of women of the Mariana Islands may be unique because of ethnic and cultural differences, we studied established and suspected risk factors for breast cancer in this unstudied population. From 2010-2013, we conducted retrospective case-control study of female breast cancer (104 cases and 185 controls) among women in the Mariana Islands. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each of various lifestyle-related factors from logistic regression of breast cancer, in all women and in pre- and postmenopausal women separately. Tests for interaction of risk factors with ethnicity were based on the Wald statistics for cross-product terms. Of the medical and reproductive factors considered - age at menarche, breastfeeding, number of live births, age at first live birth, hormone use, and menopause - only age at first live birth was confirmed. Age at first live birth, among parous women, was higher among cases (mean 24.9 years) than controls (mean 23.2 years); with increased breast cancer risk (OR=2.53; 95% CI, 1.04-6.19 for age≥30y compared to <20y, P for trend=0.01). Of the lifestyle factors -body mass index, waist circumference, physical activity, alcohol and betel-nut intake, and education - only waist circumference (OR=1.65; 95% CI 0.87-3.14 for the highest tertile group compared to the lowest, P for trend=0.04) was significantly associated with breast cancer risk and only in Filipino women. The association with many other established risk factors, such as BMI, hormone use and physical activity, were in the expected direction but were not significant. Associations for family history of breast cancer and alcohol intake were not evident CONCLUSIONS: The results provide a basis for cancer prevention guidance for women in the Mariana Islands. Copyright © 2017 The

Breast cancer screening

MedlinePlus

Mammogram - breast cancer screening; Breast exam - breast cancer screening; MRI - breast cancer screening ... performed to screen women to detect early breast cancer when it is more likely to be cured. ...

Follistatin is a metastasis suppressor in a mouse model of HER2-positive breast cancer.

PubMed

Seachrist, Darcie D; Sizemore, Steven T; Johnson, Emhonta; Abdul-Karim, Fadi W; Weber Bonk, Kristen L; Keri, Ruth A

2017-06-05

Follistatin (FST) is an intrinsic inhibitor of activin, a member of the transforming growth factor-β superfamily of ligands. The prognostic value of FST and its family members, the follistatin-like (FSTL) proteins, have been studied in various cancers. However, these studies, as well as limited functional analyses of the FSTL proteins, have yielded conflicting results on the role of these proteins in disease progression. Furthermore, very few have been focused on FST itself. We assessed whether FST may be a suppressor of tumorigenesis and/or metastatic progression in breast cancer. Using publicly available gene expression data, we examined the expression patterns of FST and INHBA, a subunit of activin, in normal and cancerous breast tissue and the prognostic value of FST in breast cancer metastases, recurrence-free survival, and overall survival. The functional effects of activin and FST on in vitro proliferation, migration, and invasion of breast cancer cells were also examined. FST overexpression in an autochthonous mouse model of breast cancer was then used to assess the in vivo impact of FST on metastatic progression. Examination of multiple breast cancer datasets revealed that FST expression is reduced in breast cancers compared with normal tissue and that low FST expression predicts increased metastasis and reduced overall survival. FST expression was also reduced in a mouse model of HER2/Neu-induced metastatic breast cancer. We found that FST blocks activin-induced breast epithelial cell migration in vitro, suggesting that its loss may promote breast cancer aggressiveness. To directly determine if FST restoration could inhibit metastatic progression, we transgenically expressed FST in the HER2/Neu model. Although FST had no impact on tumor initiation or growth, it completely blocked the formation of lung metastases. These data indicate that FST is a bona fide metastasis suppressor in this mouse model and support future efforts to develop an FST mimetic to

Overview of Genetically Engineered Mouse Models of Distinct Breast Cancer Subtypes.

PubMed

Usary, Jerry; Darr, David Brian; Pfefferle, Adam D; Perou, Charles M

2016-03-18

Advances in the screening of new therapeutic options have significantly reduced the breast cancer death rate over the last decade. Despite these advances, breast cancer remains the second leading cause of cancer death among women. This is due in part to the complexity of the disease, which is characterized by multiple subtypes that are driven by different genetic mechanisms and that likely arise from different cell types of origin. Because these differences often drive treatment options and outcomes, it is important to select relevant preclinical model systems to study new therapeutic interventions and tumor biology. Described in this unit are the characteristics and applications of validated genetically engineered mouse models (GEMMs) of basal-like, luminal, and claudin-low human subtypes of breast cancer. These different subtypes have different clinical outcomes and require different treatment strategies. These GEMMs can be considered faithful surrogates of their human disease counterparts. They represent alternative preclinical tumor models to cell line and patient-derived xenografts for preclinical drug discovery and tumor biology studies. Copyright © 2016 John Wiley & Sons, Inc.

Radiation-Induced Breast Cancer Incidence and Mortality From Digital Mammography Screening: A Modeling Study.

PubMed

Miglioretti, Diana L; Lange, Jane; van den Broek, Jeroen J; Lee, Christoph I; van Ravesteyn, Nicolien T; Ritley, Dominique; Kerlikowske, Karla; Fenton, Joshua J; Melnikow, Joy; de Koning, Harry J; Hubbard, Rebecca A

2016-02-16

Estimates of risk for radiation-induced breast cancer from mammography screening have not considered variation in dose exposure or diagnostic work-up after abnormal screening results. To estimate distributions of radiation-induced breast cancer incidence and mortality from digital mammography screening while considering exposure from screening and diagnostic mammography and dose variation among women. 2 simulation-modeling approaches. U.S. population. Women aged 40 to 74 years. Annual or biennial digital mammography screening from age 40, 45, or 50 years until age 74 years. Lifetime breast cancer deaths averted (benefits) and radiation-induced breast cancer incidence and mortality (harms) per 100,000 women screened. Annual screening of 100,000 women aged 40 to 74 years was projected to induce 125 breast cancer cases (95% CI, 88 to 178) leading to 16 deaths (CI, 11 to 23), relative to 968 breast cancer deaths averted by early detection from screening. Women exposed at the 95th percentile were projected to develop 246 cases of radiation-induced breast cancer leading to 32 deaths per 100,000 women. Women with large breasts requiring extra views for complete examination (8% of population) were projected to have greater radiation-induced breast cancer risk (266 cancer cases and 35 deaths per 100,000 women) than other women (113 cancer cases and 15 deaths per 100,000 women). Biennial screening starting at age 50 years reduced risk for radiation-induced cancer 5-fold. Life-years lost from radiation-induced breast cancer could not be estimated. Radiation-induced breast cancer incidence and mortality from digital mammography screening are affected by dose variability from screening, resultant diagnostic work-up, initiation age, and screening frequency. Women with large breasts may have a greater risk for radiation-induced breast cancer. Agency for Healthcare Research and Quality, U.S. Preventive Services Task Force, National Cancer Institute.

Epigenome remodelling in breast cancer: insights from an early in vitro model of carcinogenesis.

PubMed

Locke, Warwick J; Clark, Susan J

2012-11-15

Epigenetic gene regulation has influence over a diverse range of cellular functions, including the maintenance of pluripotency, differentiation, and cellular identity, and is deregulated in many diseases, including cancer. Whereas the involvement of epigenetic dysregulation in cancer is well documented, much of the mechanistic detail involved in triggering these changes remains unclear. In the current age of genomics, the development of new sequencing technologies has seen an influx of genomic and epigenomic data and drastic improvements in both resolution and coverage. Studies in cancer cell lines and clinical samples using next-generation sequencing are rapidly delivering spectacular insights into the nature of the cancer genome and epigenome. Despite these improvements in technology, the timing and relationship between genetic and epigenetic changes that occur during the process of carcinogenesis are still unclear. In particular, what changes to the epigenome are playing a driving role during carcinogenesis and what influence the temporal nature of these changes has on cancer progression are not known. Understanding the early epigenetic changes driving breast cancer has the exciting potential to provide a novel set of therapeutic targets or early-disease biomarkers or both. Therefore, it is important to find novel systems that permit the study of initial epigenetic events that potentially occur during the first stages of breast cancer. Non-malignant human mammary epithelial cells (HMECs) provide an exciting in vitro model of very early breast carcinogenesis. When grown in culture, HMECs are able to temporarily escape senescence and acquire a pre-malignant breast cancer-like phenotype (variant HMECs, or vHMECs). Cultured HMECs are composed mainly of cells from the basal breast epithelial layer. Therefore, vHMECs are considered to represent the basal-like subtype of breast cancer. The transition from HMECs to vHMECs in culture recapitulates the epigenomic

Epigenome remodelling in breast cancer: insights from an early in vitro model of carcinogenesis

PubMed Central

2012-01-01

Epigenetic gene regulation has influence over a diverse range of cellular functions, including the maintenance of pluripotency, differentiation, and cellular identity, and is deregulated in many diseases, including cancer. Whereas the involvement of epigenetic dysregulation in cancer is well documented, much of the mechanistic detail involved in triggering these changes remains unclear. In the current age of genomics, the development of new sequencing technologies has seen an influx of genomic and epigenomic data and drastic improvements in both resolution and coverage. Studies in cancer cell lines and clinical samples using next-generation sequencing are rapidly delivering spectacular insights into the nature of the cancer genome and epigenome. Despite these improvements in technology, the timing and relationship between genetic and epigenetic changes that occur during the process of carcinogenesis are still unclear. In particular, what changes to the epigenome are playing a driving role during carcinogenesis and what influence the temporal nature of these changes has on cancer progression are not known. Understanding the early epigenetic changes driving breast cancer has the exciting potential to provide a novel set of therapeutic targets or early-disease biomarkers or both. Therefore, it is important to find novel systems that permit the study of initial epigenetic events that potentially occur during the first stages of breast cancer. Non-malignant human mammary epithelial cells (HMECs) provide an exciting in vitro model of very early breast carcinogenesis. When grown in culture, HMECs are able to temporarily escape senescence and acquire a pre-malignant breast cancer-like phenotype (variant HMECs, or vHMECs). Cultured HMECs are composed mainly of cells from the basal breast epithelial layer. Therefore, vHMECs are considered to represent the basal-like subtype of breast cancer. The transition from HMECs to vHMECs in culture recapitulates the epigenomic

Radiation-Induced Breast Cancer Incidence and Mortality from Digital Mammography Screening: A Modeling Study

PubMed Central

Miglioretti, Diana L.; Lange, Jane; van den Broek, Jeroen J.; Lee, Christoph I.; van Ravesteyn, Nicolien T.; Ritley, Dominique; Kerlikowske, Karla; Fenton, Joshua J.; Melnikow, Joy; de Koning, Harry J.; Hubbard, Rebecca A.

2016-01-01

Background Estimates of radiation-induced breast cancer risk from mammography screening have not previously considered dose exposure variation or diagnostic work-up after abnormal screening. Objective To estimate distributions of radiation-induced breast cancer incidence and mortality from digital mammography screening, considering exposure from screening and diagnostic mammography and dose variation across women. Design Two simulation-modeling approaches using common data on screening mammography from the Breast Cancer Surveillance Consortium and radiation dose from mammography from the Digital Mammographic Imaging Screening Trial. Setting U.S. population. Patients Women aged 40–74 years. Interventions Annual or biennial digital mammography screening from age 40, 45, or 50 until 74. Measurements Lifetime breast cancer deaths averted (benefits) and radiation-induced breast cancer incidence and mortality per 100,000 women screened (harms). Results On average, annual screening of 100,000 women aged 40 to 74 years was projected to induce 125 breast cancers (95% confidence interval [CI]=88–178) leading to 16 deaths (95% CI=11–23) relative to 968 breast cancer deaths averted by early detection from screening. Women exposed at the 95th percentile were projected to develop 246 radiation-induced breast cancers leading to 32 deaths per 100,000 women. Women with large breasts requiring extra views for complete breast examination (8% of population) were projected to have higher radiation-induced breast cancer incidence and mortality (266 cancers, 35 deaths per 100,000 women), compared to women with small or average breasts (113 cancers, 15 deaths per 100,000 women). Biennial screening starting at age 50 reduced risk of radiation-induced cancers 5-fold. Limitations We were unable to estimate years of life lost from radiation-induced breast cancer. Conclusions Radiation-induced breast cancer incidence and mortality from digital mammography screening are impacted by dose

Breast Cancer Overview

MedlinePlus

... are here Home > Types of Cancer > Breast Cancer Breast Cancer This is Cancer.Net’s Guide to Breast Cancer. Use the menu below to choose the Overview/ ... social workers, and patient advocates. Cancer.Net Guide Breast Cancer Introduction Statistics Medical Illustrations Risk Factors and Prevention ...

Breast Camps for Awareness and Early Diagnosis of Breast Cancer in Countries With Limited Resources: A Multidisciplinary Model From Kenya.

PubMed

Sayed, Shahin; Moloo, Zahir; Ngugi, Anthony; Allidina, Amyn; Ndumia, Rose; Mutuiri, Anderson; Wasike, Ronald; Wahome, Charles; Abdihakin, Mohamed; Kasmani, Riaz; Spears, Carol D; Oigara, Raymond; Mwachiro, Elizabeth B; Busarla, Satya V P; Kibor, Kibet; Ahmed, Abdulaziz; Wawire, Jonathan; Sherman, Omar; Saleh, Mansoor; Zujewski, Jo Anne; Dawsey, Sanford M

2016-09-01

Breast cancer is the most common cancer of women in Kenya. There are no national breast cancer early diagnosis programs in Kenya. The objective was to conduct a pilot breast cancer awareness and diagnosis program at three different types of facilities in Kenya. This program was conducted at a not-for-profit private hospital, a faith-based public hospital, and a government public referral hospital. Women aged 15 years and older were invited. Demographic, risk factor, knowledge, attitudes, and screening practice data were collected. Breast health information was delivered, and clinical breast examinations (CBEs) were performed. When appropriate, ultrasound imaging, fine-needle aspirate (FNA) diagnoses, core biopsies, and onward referrals were provided. A total of 1,094 women were enrolled in the three breast camps. Of those, 56% knew the symptoms and signs of breast cancer, 44% knew how breast cancer was diagnosed, 37% performed regular breast self-exams, and 7% had a mammogram or breast ultrasound in the past year. Of the 1,094 women enrolled, 246 (23%) had previously noticed a lump in their breast. A total of 157 participants (14%) had abnormal CBEs, of whom 111 had ultrasound exams, 65 had FNAs, and 18 had core biopsies. A total of 14 invasive breast cancers and 1 malignant phyllodes tumor were diagnosed Conducting a multidisciplinary breast camp awareness and early diagnosis program is feasible in different types of health facilities within a low- and middle-income country setting. This can be a model for breast cancer awareness and point-of-care diagnosis in countries with limited resources like Kenya. This work describes a novel breast cancer awareness and early diagnosis demonstration program in a low- and middle-income country within a limited resource setting. The program includes breast self-awareness and breast cancer education, clinical exams, and point-of-care diagnostics for women in three different types of health facilities in Kenya. This pilot

Breast Cancer -- Male

MedlinePlus

... Home > Types of Cancer > Breast Cancer in Men Breast Cancer in Men This is Cancer.Net’s Guide to Breast Cancer in Men. Use the menu below to choose ... social workers, and patient advocates. Cancer.Net Guide Breast Cancer in Men Introduction Statistics Risk Factors and Prevention ...

Real-world impact of non-breast cancer-specific death on overall survival in resectable breast cancer.

PubMed

Fu, Jianfei; Wu, Lunpo; Jiang, Mengjie; Li, Dan; Jiang, Ting; Fu, Wei; Wang, Liangjing; Du, Jinlin

2017-07-01

The real-world occurrence rate of non-breast cancer-specific death (non-BCSD) and its impact on patients with breast cancer are poorly recognized. Women with resectable breast cancer from 1990 to 2007 in the Surveillance, Epidemiology, and End Results database (n = 199,963) were analyzed. The outcome events of breast cancer were classified as breast cancer-specific death (BCSD), non-BCSD, or survival. Binary logistics was used to estimate the occurrence rates of non-BCSD and BCSD with different clinicopathological factors. The Gray method was used to measure the cumulative incidence of non-BCSD and BCSD. The ratio of non-BCSDs to all causes of death and stacked cumulative incidence function plots were used to present the impact of non-BCSD on overall survival (OS). Models of Cox proportional hazards regression and competing risk regression were compared to highlight the suitable model. There were 12,879 non-BCSDs (6.44%) and 28,784 BCSDs (14.39%). The oldest age group (>62 years), black race, and a single or divorced marital status were associated with more non-BCSDs. With adjustments for age, a hormone receptor-positive (HoR+) status was no longer related to increased non-BCSDs. In patients with grade 1, stage I disease and an HoR+ status as well as the oldest subgroup, a great dilution of non-BCSD on all causes of death could be observed, and this led to incorrect interpretations. The inaccuracy, caused by the commonly used Cox proportional hazards model, could be corrected by a competing risk model. OS was largely impaired by non-BCSD during early breast cancer. For some future clinical trial planning, especially for the oldest patients and those with HoR+ breast cancer, non-BCSD should be considered a competing risk event. Cancer 2017;123:2432-43. © 2017 American Cancer Society. © 2017 American Cancer Society.

Assessing Breast Cancer Risk Estimates Based on the Gail Model and Its Predictors in Qatari Women.

PubMed

Bener, Abdulbari; Çatan, Funda; El Ayoubi, Hanadi R; Acar, Ahmet; Ibrahim, Wanis H

2017-07-01

The Gail model is the most widely used breast cancer risk assessment tool. An accurate assessment of individual's breast cancer risk is very important for prevention of the disease and for the health care providers to make decision on taking chemoprevention for high-risk women in clinical practice in Qatar. To assess the breast cancer risk among Arab women population in Qatar using the Gail model and provide a global comparison of risk assessment. In this cross-sectional study of 1488 women (aged 35 years and older), we used the Gail Risk Assessment Tool to assess the risk of developing breast cancer. Sociodemographic features such as age, lifestyle habits, body mass index, breast-feeding duration, consanguinity among parents, and family history of breast cancer were considered as possible risks. The mean age of the study population was 47.8 ± 10.8 years. Qatari women and Arab women constituted 64.7% and 35.3% of the study population, respectively. The mean 5-year and lifetime breast cancer risks were 1.12 ± 0.52 and 10.57 ± 3.1, respectively. Consanguineous marriage among parents was seen in 30.6% of participants. We found a relationship between the 5-year and lifetime risks of breast cancer and variables such as age, age at menarche, gravidity, parity, body mass index, family history of cancer, menopause age, occupation, and level of education. The linear regression analysis identified the predictors for breast cancer in women such as age, age at menarche, age of first birth, family history and age of menopausal were considered the strong predictors and significant contributing risk factors for breast cancer after adjusting for ethnicity, parity and other variables. The current study is the first to evaluate the performance of the Gail model for Arab women population in the Gulf Cooperation Council. Gail model is an appropriate breast cancer risk assessment tool for female population in Qatar.

Novel modeling of cancer cell signaling pathways enables systematic drug repositioning for distinct breast cancer metastases.

PubMed

Zhao, Hong; Jin, Guangxu; Cui, Kemi; Ren, Ding; Liu, Timothy; Chen, Peikai; Wong, Solomon; Li, Fuhai; Fan, Yubo; Rodriguez, Angel; Chang, Jenny; Wong, Stephen T C

2013-10-15

A new type of signaling network element, called cancer signaling bridges (CSB), has been shown to have the potential for systematic and fast-tracked drug repositioning. On the basis of CSBs, we developed a computational model to derive specific downstream signaling pathways that reveal previously unknown target-disease connections and new mechanisms for specific cancer subtypes. The model enables us to reposition drugs based on available patient gene expression data. We applied this model to repurpose known or shelved drugs for brain, lung, and bone metastases of breast cancer with the hypothesis that cancer subtypes have their own specific signaling mechanisms. To test the hypothesis, we addressed specific CSBs for each metastasis that satisfy (i) CSB proteins are activated by the maximal number of enriched signaling pathways specific to a given metastasis, and (ii) CSB proteins are involved in the most differential expressed coding genes specific to each breast cancer metastasis. The identified signaling networks for the three types of breast cancer metastases contain 31, 15, and 18 proteins and are used to reposition 15, 9, and 2 drug candidates for the brain, lung, and bone metastases. We conducted both in vitro and in vivo preclinical experiments as well as analysis on patient tumor specimens to evaluate the targets and repositioned drugs. Of special note, we found that the Food and Drug Administration-approved drugs, sunitinib and dasatinib, prohibit brain metastases derived from breast cancer, addressing one particularly challenging aspect of this disease. ©2013 AACR.

Cyclooxygenase-2 inhibitor induces apoptosis in breast cancer cells in an in vivo model of spontaneous metastatic breast cancer.

PubMed

Basu, Gargi D; Pathangey, Latha B; Tinder, Teresa L; Lagioia, Michelle; Gendler, Sandra J; Mukherjee, Pinku

2004-11-01

Cyclooxygenase-2 (COX-2) inhibitors are rapidly emerging as a new generation of therapeutic drug in combination with chemotherapy or radiation therapy for the treatment of cancer. The mechanisms underlying its antitumor effects are not fully understood and more thorough preclinical trials are needed to determine if COX-2 inhibition represents a useful approach for prevention and/or treatment of breast cancer. The purpose of this study was to evaluate the growth inhibitory mechanism of a highly selective COX-2 inhibitor, celecoxib, in an in vivo oncogenic mouse model of spontaneous breast cancer that resembles human disease. The oncogenic mice carry the polyoma middle T antigen driven by the mouse mammary tumor virus promoter and develop primary adenocarcinomas of the breast. Results show that oral administration of celecoxib caused significant reduction in mammary tumor burden associated with increased tumor cell apoptosis and decreased proliferation in vivo. In vivo apoptosis correlated with significant decrease in activation of protein kinase B/Akt, a cell survival signaling kinase, with increased expression of the proapoptotic protein Bax and decreased expression of the antiapoptotic protein Bcl-2. In addition, celecoxib treatment reduced levels of proangiogenic factor (vascular endothelial growth factor), suggesting a role of celecoxib in suppression of angiogenesis in this model. Results from these preclinical studies will form the basis for assessing the feasibility of celecoxib therapy alone or in combination with conventional therapies for treatment and/or prevention of breast cancer.

Monitoring breast cancer treatment using a Fourier transform infrared spectroscopy-based computational model.

PubMed

Depciuch, J; Kaznowska, E; Golowski, S; Koziorowska, A; Zawlik, I; Cholewa, M; Szmuc, K; Cebulski, J

2017-09-05

Breast cancer affects one in four women, therefore, the search for new diagnostic technologies and therapeutic approaches is of critical importance. This involves the development of diagnostic tools to facilitate the detection of cancer cells, which is useful for assessing the efficacy of cancer therapies. One of the major challenges for chemotherapy is the lack of tools to monitor efficacy during the course of treatment. Vibrational spectroscopy appears to be a promising tool for such a purpose, as it yields Fourier transformation infrared (FTIR) spectra which can be used to provide information on the chemical composition of the tissue. Previous research by our group has demonstrated significant differences between the infrared spectra of healthy, cancerous and post-chemotherapy breast tissue. Furthermore, the results obtained for three extreme patient cases revealed that the infrared spectra of post-chemotherapy breast tissue closely resembles that of healthy breast tissue when chemotherapy is effective (i.e., a good therapeutic response is achieved), or that of cancerous breast tissue when chemotherapy is ineffective. In the current study, we compared the infrared spectra of healthy, cancerous and post-chemotherapy breast tissue. Characteristic parameters were designated for the obtained spectra, spreading the function of absorbance using the Kramers-Kronig transformation and the best fit procedure to obtain Lorentz functions, which represent components of the bands. The Lorentz function parameters were used to develop a physics-based computational model to verify the efficacy of a given chemotherapy protocol in a given case. The results obtained using this model reflected the actual patient data retrieved from medical records (health improvement or no improvement). Therefore, we propose this model as a useful tool for monitoring the efficacy of chemotherapy in patients with breast cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Transforming growth factor-β signalling controls human breast cancer metastasis in a zebrafish xenograft model.

PubMed

Drabsch, Yvette; He, Shuning; Zhang, Long; Snaar-Jagalska, B Ewa; ten Dijke, Peter

2013-11-07

The transforming growth factor beta (TGF-β) signalling pathway is known to control human breast cancer invasion and metastasis. We demonstrate that the zebrafish xenograft assay is a robust and dependable animal model for examining the role of pharmacological modulators and genetic perturbation of TGF-β signalling in human breast tumour cells. We injected cancer cells into the embryonic circulation (duct of cuvier) and examined their invasion and metastasis into the avascular collagenous tail. Various aspects of the TGF-β signalling pathway were blocked by chemical inhibition, small interfering RNA (siRNA), or small hairpin RNA (shRNA). Analysis was conducted using fluorescent microscopy. Breast cancer cells with different levels of malignancy, according to in vitro and in vivo mouse studies, demonstrated invasive and metastatic properties within the embryonic zebrafish model that nicely correlated with their differential tumourigenicity in mouse models. Interestingly, MCF10A M2 and M4 cells invaded into the caudal hematopoietic tissue and were visible as a cluster of cells, whereas MDA MB 231 cells invaded into the tail fin and were visible as individual cells. Pharmacological inhibition with TGF-β receptor kinase inhibitors or tumour specific Smad4 knockdown disturbed invasion and metastasis in the zebrafish xenograft model and closely mimicked the results we obtained with these cells in a mouse metastasis model. Inhibition of matrix metallo proteinases, which are induced by TGF-β in breast cancer cells, blocked invasion and metastasis of breast cancer cells. The zebrafish-embryonic breast cancer xenograft model is applicable for the mechanistic understanding, screening and development of anti-TGF-β drugs for the treatment of metastatic breast cancer in a timely and cost-effective manner.

Vitamin Supplement Use and Risk for Breast Cancer: The Shanghai Breast Cancer Study.

PubMed Central

Dorjgochoo, Tsogzolmaa; Shrubsole, Martha J.; Shu, Xiao Ou; Lu, Wei; Ruan, Zhixian; Zhen, Ying; Dai, Qi; Gu, Kai; Gao, Yu-Tang; Zheng, Wei

2008-01-01

Objective: The influence of vitamin supplements on risk for breast cancer is unclear. Also the interactive effects of vitamins from dietary and supplemental sources are unknown. This study investigated the association between self-reported vitamin supplement use (A, B, C, E and multivitamin) and breast cancer among urban Chinese women. It also examined the combined effect of vitamin supplements in relation to particular dietary vitamin intakes on breast cancer risk. Methods: Study subjects were identified from The Shanghai Breast Cancer Study (SBCS) and was a population-based case-control study conducted in Shanghai in 1996-1998 (Phase I) and 2002-2004 (Phase II). Participants were aged 25 to 64 and 20 to 70 years for phase I and for phase II, respectively. The analyses included 3,454 incident breast cancer cases and 3,474 controls. Unconditional logistic regression models were used to determine adjusted odds ratios (ORs) for breast cancer risk associated with vitamin supplement use. Results: Overall, the breast cancer risk was not related to intakes of any vitamin supplement. However, an approximately 20% reduction in breast cancer risk was observed with use of vitamin E supplement among women with low-dietary vitamin E intake (OR=0.8; 95% confidence interval (CI), 0.6-0.9) with a significant does-response inverse association (P trend =0.01 for duration). Modest risk reduction was observed among vitamin B supplement users with low dietary intake of the same vitamin (OR=0.9; 95% CI, 0.6-1.0). However, vitamin B supplement was adversely associated with breast cancer risk among those with high dietary vitamin B intake with a significant dose-response effect (P trend =0.04 for duration). Conclusions: This study suggests that vitamins E and B supplement may confer a prevention of breast cancer among women who have low dietary intake of those vitamins. PMID:17917808

Simulation models in population breast cancer screening: A systematic review.

PubMed

Koleva-Kolarova, Rositsa G; Zhan, Zhuozhao; Greuter, Marcel J W; Feenstra, Talitha L; De Bock, Geertruida H

2015-08-01

The aim of this review was to critically evaluate published simulation models for breast cancer screening of the general population and provide a direction for future modeling. A systematic literature search was performed to identify simulation models with more than one application. A framework for qualitative assessment which incorporated model type; input parameters; modeling approach, transparency of input data sources/assumptions, sensitivity analyses and risk of bias; validation, and outcomes was developed. Predicted mortality reduction (MR) and cost-effectiveness (CE) were compared to estimates from meta-analyses of randomized control trials (RCTs) and acceptability thresholds. Seven original simulation models were distinguished, all sharing common input parameters. The modeling approach was based on tumor progression (except one model) with internal and cross validation of the resulting models, but without any external validation. Differences in lead times for invasive or non-invasive tumors, and the option for cancers not to progress were not explicitly modeled. The models tended to overestimate the MR (11-24%) due to screening as compared to optimal RCTs 10% (95% CI - 2-21%) MR. Only recently, potential harms due to regular breast cancer screening were reported. Most scenarios resulted in acceptable cost-effectiveness estimates given current thresholds. The selected models have been repeatedly applied in various settings to inform decision making and the critical analysis revealed high risk of bias in their outcomes. Given the importance of the models, there is a need for externally validated models which use systematical evidence for input data to allow for more critical evaluation of breast cancer screening. Copyright © 2015 Elsevier Ltd. All rights reserved.

Breast Cancer Surgery

MedlinePlus

FACTS FOR LIFE Breast Cancer Surgery The goal of breast cancer surgery is to remove the whole tumor from the breast. Some lymph nodes ... might still be in the body. Types of breast cancer surgery There are two types of breast cancer ...

Mint3 in bone marrow-derived cells promotes lung metastasis in breast cancer model mice.

PubMed

Hara, Toshiro; Murakami, Yoshinori; Seiki, Motoharu; Sakamoto, Takeharu

2017-08-26

Breast cancer is one of the most common cancers in women in the world. Although breast cancer is well treatable at the early stage, patients with distant metastases show a poor prognosis. Data from recent studies using transplantation models indicate that Mint3/APBA3 might promote breast cancer malignancy. However, whether Mint3 indeed contributes to tumor development, progression, or metastasis in vivo remains unclear. To address this, here we examined whether Mint3 depletion affects tumor malignancy in MMTV-PyMT breast cancer model mice. In MMTV-PyMT mice, Mint3 depletion did not affect tumor onset and tumor growth, but attenuated lung metastases. Experimental lung metastasis of breast cancer Met-1 cells derived from MMTV-PyMT mice also decreased in Mint3-depleted mice, indicating that host Mint3 expression affected lung metastasis of MMTV-PyMT-derived breast cancer cells. Further bone marrow transplant experiments revealed that Mint3 in bone marrow-derived cells promoted lung metastasis in MMTV-PyMT mice. Thus, targeting Mint3 in bone marrow-derived cells might be a good strategy for preventing metastasis and improving the prognosis of breast cancer patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Patient-derived Xenograft (PDX) Models In Basic and Translational Breast Cancer Research

PubMed Central

Dobrolecki, Lacey E.; Airhart, Susie D.; Alferez, Denis G.; Aparicio, Samuel; Behbod, Fariba; Bentires-Alj, Mohamed; Brisken, Cathrin; Bult, Carol J.; Cai, Shirong; Clarke, Robert B.; Dowst, Heidi; Ellis, Matthew J.; Gonzalez-Suarez, Eva; Iggo, Richard D.; Kabos, Peter; Li, Shunqiang; Lindeman, Geoffrey J.; Marangoni, Elisabetta; McCoy, Aaron; Meric-Bernstam, Funda; Piwnica-Worms, Helen; Poupon, Marie-France; Reis-Filho, Jorge; Sartorius, Carol A.; Scabia, Valentina; Sflomos, George; Tu, Yizheng; Vaillant, François; Visvader, Jane E.; Welm, Alana; Wicha, Max S.

2017-01-01

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational pre-clinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and “Triple-negative” (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward “credentialing” of PDX models as surrogates to represent individual patients for use in pre-clinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research. PMID:28025748

6 Common Cancers - Breast Cancer

MedlinePlus

... Bar Home Current Issue Past Issues 6 Common Cancers - Breast Cancer Past Issues / Spring 2007 Table of Contents For ... her down. Photo: AP Photo/Brett Flashnick Breast Cancer Breast cancer is a malignant (cancerous) growth that ...

Human Breast Cancer Histoid

PubMed Central

Kaur, Pavinder; Ward, Brenda; Saha, Baisakhi; Young, Lillian; Groshen, Susan; Techy, Geza; Lu, Yani; Atkinson, Roscoe; Taylor, Clive R.; Ingram, Marylou

2011-01-01

Progress in our understanding of heterotypic cellular interaction in the tumor microenvironment, which is recognized to play major roles in cancer progression, has been hampered due to unavailability of an appropriate in vitro co-culture model. The aim of this study was to generate an in vitro 3-dimensional human breast cancer model, which consists of cancer cells and fibroblasts. Breast cancer cells (UACC-893) and fibroblasts at various densities were co-cultured in a rotating suspension culture system to establish co-culture parameters. Subsequently, UACC-893, BT.20, or MDA.MB.453 were co-cultured with fibroblasts for 9 days. Co-cultures resulted in the generation of breast cancer histoid (BCH) with cancer cells showing the invasion of fibroblast spheroids, which were visualized by immunohistochemical (IHC) staining of sections (4 µm thick) of BCH. A reproducible quantitative expression of C-erbB.2 was detected in UACC-893 cancer cells in BCH sections by IHC staining and the Automated Cellular Imaging System. BCH sections also consistently exhibited qualitative expression of pancytokeratins, p53, Ki-67, or E-cadherin in cancer cells and that of vimentin or GSTPi in fibroblasts, fibronectin in the basement membrane and collagen IV in the extracellular matrix. The expression of the protein analytes and cellular architecture of BCH were markedly similar to those of breast cancer tissue. PMID:22034518

Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

PubMed

Nikbakht, Roya; Bahrampour, Abbas

2017-01-01

Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

Breast Camps for Awareness and Early Diagnosis of Breast Cancer in Countries With Limited Resources: A Multidisciplinary Model From Kenya

PubMed Central

Moloo, Zahir; Ngugi, Anthony; Allidina, Amyn; Ndumia, Rose; Mutuiri, Anderson; Wasike, Ronald; Wahome, Charles; Abdihakin, Mohamed; Kasmani, Riaz; Spears, Carol D.; Oigara, Raymond; Mwachiro, Elizabeth B.; Busarla, Satya V.P.; Kibor, Kibet; Ahmed, Abdulaziz; Wawire, Jonathan; Sherman, Omar; Saleh, Mansoor; Zujewski, Jo Anne; Dawsey, Sanford M.

2016-01-01

Background. Breast cancer is the most common cancer of women in Kenya. There are no national breast cancer early diagnosis programs in Kenya. Objective. The objective was to conduct a pilot breast cancer awareness and diagnosis program at three different types of facilities in Kenya. Methods. This program was conducted at a not-for-profit private hospital, a faith-based public hospital, and a government public referral hospital. Women aged 15 years and older were invited. Demographic, risk factor, knowledge, attitudes, and screening practice data were collected. Breast health information was delivered, and clinical breast examinations (CBEs) were performed. When appropriate, ultrasound imaging, fine-needle aspirate (FNA) diagnoses, core biopsies, and onward referrals were provided. Results. A total of 1,094 women were enrolled in the three breast camps. Of those, 56% knew the symptoms and signs of breast cancer, 44% knew how breast cancer was diagnosed, 37% performed regular breast self-exams, and 7% had a mammogram or breast ultrasound in the past year. Of the 1,094 women enrolled, 246 (23%) had previously noticed a lump in their breast. A total of 157 participants (14%) had abnormal CBEs, of whom 111 had ultrasound exams, 65 had FNAs, and 18 had core biopsies. A total of 14 invasive breast cancers and 1 malignant phyllodes tumor were diagnosed Conclusion. Conducting a multidisciplinary breast camp awareness and early diagnosis program is feasible in different types of health facilities within a low- and middle-income country setting. This can be a model for breast cancer awareness and point-of-care diagnosis in countries with limited resources like Kenya. Implications for Practice: This work describes a novel breast cancer awareness and early diagnosis demonstration program in a low- and middle-income country within a limited resource setting. The program includes breast self-awareness and breast cancer education, clinical exams, and point-of-care diagnostics for

Unemployment among breast cancer survivors.

PubMed

Carlsen, Kathrine; Ewertz, Marianne; Dalton, Susanne Oksbjerg; Badsberg, Jens Henrik; Osler, Merete

2014-05-01

Though about 20% of working age breast cancer survivors do not return to work after treatment, few studies have addressed risk factors for unemployment. The majority of studies on occupational consequences of breast cancer focus on non-employment, which is a mixture of sickness absence, unemployment, retirement pensions and other reasons for not working. Unemployment in combination with breast cancer may represent a particular challenge for these women. The aim of the present study is therefore to analyze the risk for unemployment in the years following diagnosis and treatment for breast cancer. This study included 14,750 women diagnosed with breast cancer in Denmark 2001-2009 identified through a population-based clinical database and linked with information from Danish administrative population based registers for information on labour market affiliation, socio-demography and co-morbid conditions. Multivariable analyses were performed by Cox's proportional hazard models. Two years after treatment, 81% of patients were still part of the work force, 10% of which were unemployed. Increasing duration of unemployment before breast cancer was associated with an adjusted HR = 4.37 (95% CI: 3.90-4.90) for unemployment after breast cancer. Other risk factors for unemployment included low socioeconomic status and demography, while adjuvant therapy did not increase the risk of unemployment. Duration of unemployment before breast cancer was the most important determinant of unemployment after breast cancer treatment. This allows identification of a particularly vulnerable group of patients in need of rehabilitation.

A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer

PubMed Central

Goddard, Erica T.; Fischer, Jacob; Schedin, Pepper

2016-01-01

Breast cancer is the leading cause of cancer-related mortality in women worldwide. Liver metastasis is involved in upwards of 30% of cases with breast cancer metastasis, and results in poor outcomes with median survival rates of only 4.8 - 15 months. Current rodent models of breast cancer metastasis, including primary tumor cell xenograft and spontaneous tumor models, rarely metastasize to the liver. Intracardiac and intrasplenic injection models do result in liver metastases, however these models can be confounded by concomitant secondary-site metastasis, or by compromised immunity due to removal of the spleen to avoid tumor growth at the injection site. To address the need for improved liver metastasis models, a murine portal vein injection method that delivers tumor cells firstly and directly to the liver was developed. This model delivers tumor cells to the liver without complications of concurrent metastases in other organs or removal of the spleen. The optimized portal vein protocol employs small injection volumes of 5 - 10 μl, ≥ 32 gauge needles, and hemostatic gauze at the injection site to control for blood loss. The portal vein injection approach in Balb/c female mice using three syngeneic mammary tumor lines of varying metastatic potential was tested; high-metastatic 4T1 cells, moderate-metastatic D2A1 cells, and low-metastatic D2.OR cells. Concentrations of ≤ 10,000 cells/injection results in a latency of ~ 20 - 40 days for development of liver metastases with the higher metastatic 4T1 and D2A1 lines, and > 55 days for the less aggressive D2.OR line. This model represents an important tool to study breast cancer metastasis to the liver, and may be applicable to other cancers that frequently metastasize to the liver including colorectal and pancreatic adenocarcinomas. PMID:28060292

A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer.

PubMed

Goddard, Erica T; Fischer, Jacob; Schedin, Pepper

2016-12-26

Breast cancer is the leading cause of cancer-related mortality in women worldwide. Liver metastasis is involved in upwards of 30% of cases with breast cancer metastasis, and results in poor outcomes with median survival rates of only 4.8 - 15 months. Current rodent models of breast cancer metastasis, including primary tumor cell xenograft and spontaneous tumor models, rarely metastasize to the liver. Intracardiac and intrasplenic injection models do result in liver metastases, however these models can be confounded by concomitant secondary-site metastasis, or by compromised immunity due to removal of the spleen to avoid tumor growth at the injection site. To address the need for improved liver metastasis models, a murine portal vein injection method that delivers tumor cells firstly and directly to the liver was developed. This model delivers tumor cells to the liver without complications of concurrent metastases in other organs or removal of the spleen. The optimized portal vein protocol employs small injection volumes of 5 - 10 μl, ≥ 32 gauge needles, and hemostatic gauze at the injection site to control for blood loss. The portal vein injection approach in Balb/c female mice using three syngeneic mammary tumor lines of varying metastatic potential was tested; high-metastatic 4T1 cells, moderate-metastatic D2A1 cells, and low-metastatic D2.OR cells. Concentrations of ≤ 10,000 cells/injection results in a latency of ~ 20 - 40 days for development of liver metastases with the higher metastatic 4T1 and D2A1 lines, and > 55 days for the less aggressive D2.OR line. This model represents an important tool to study breast cancer metastasis to the liver, and may be applicable to other cancers that frequently metastasize to the liver including colorectal and pancreatic adenocarcinomas.

Prevention of ER-Negative Breast Cancer

PubMed Central

Li, Yuxin

2014-01-01

The successful demonstration that the selective estrogen receptor modulators (SERMs) tamoxifen and raloxifene reduce the risk of breast cancer has stimulated great interest in using drugs to prevent breast cancer in high-risk women. In addition, recent results from breast cancer treatment trials suggest that aromatase inhibitors may be even more effective at preventing breast cancer than are SERMs. However, while SERMs and aromatase inhibitors do prevent the development of many estrogen-receptor (ER)-positive breast cancers, these drugs do not prevent the development of ER-negative breast cancer. Thus, there is an urgent need to identify agents that can prevent ER-negative breast cancer. We have studied the cancer preventative activity of several classes of drugs for their ability to prevent ER-negative breast cancer in preclinical models. Results from these studies demonstrate that rexinoids (analogs of retinoids that bind and activate RXR receptors), tyrosine kinase inhibitors (such as EGFR inhibitors and dual kinase inhibitors that block EGFR and HER2/neu signaling), and cyclo-oxygenase 2 (COX-2) inhibitors all prevent ER-negative breast cancer in transgenic mice that develop ER-negative breast cancer. Other promising agents now under investigation include vitamin D and vitamin D analogs, drugs that activate PPAR-gamma nuclear receptors, and statins. Many of these agents are now being tested in early phase cancer prevention clinical trials to determine whether they will show activity in breast tissue and whether they are safe for use in high-risk women without breast cancer. The current status of these studies will be reviewed. It is anticipated that in the future, drugs that effectively prevent ER-negative breast cancer will be used in combination with hormonal agents such SERMs or aromatase inhibitors to prevent all forms of breast cancer. PMID:19213564

Analysis of survival in breast cancer patients by using different parametric models

NASA Astrophysics Data System (ADS)

Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

2017-09-01

In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

Genomic pathways modulated by Twist in breast cancer.

PubMed

Vesuna, Farhad; Bergman, Yehudit; Raman, Venu

2017-01-13

The basic helix-loop-helix transcription factor TWIST1 (Twist) is involved in embryonic cell lineage determination and mesodermal differentiation. There is evidence to indicate that Twist expression plays a role in breast tumor formation and metastasis, but the role of Twist in dysregulating pathways that drive the metastatic cascade is unclear. Moreover, many of the genes and pathways dysregulated by Twist in cell lines and mouse models have not been validated against data obtained from larger, independant datasets of breast cancer patients. We over-expressed the human Twist gene in non-metastatic MCF-7 breast cancer cells to generate the estrogen-independent metastatic breast cancer cell line MCF-7/Twist. These cells were inoculated in the mammary fat pad of female severe compromised immunodeficient mice, which subsequently formed xenograft tumors that metastasized to the lungs. Microarray data was collected from both in vitro (MCF-7 and MCF-7/Twist cell lines) and in vivo (primary tumors and lung metastases) models of Twist expression. Our data was compared to several gene datasets of various subtypes, classes, and grades of human breast cancers. Our data establishes a Twist over-expressing mouse model of breast cancer, which metastasizes to the lung and replicates some of the ontogeny of human breast cancer progression. Gene profiling data, following Twist expression, exhibited novel metastasis driver genes as well as cellular maintenance genes that were synonymous with the metastatic process. We demonstrated that the genes and pathways altered in the transgenic cell line and metastatic animal models parallel many of the dysregulated gene pathways observed in human breast cancers. Analogous gene expression patterns were observed in both in vitro and in vivo Twist preclinical models of breast cancer metastasis and breast cancer patient datasets supporting the functional role of Twist in promoting breast cancer metastasis. The data suggests that genetic

Metformin and propranolol combination prevents cancer progression and metastasis in different breast cancer models

PubMed Central

Bondarenko, Maryna; Laluce, Nahuel Cesatti; Rozados, Viviana; Nicolas, André; Carré, Manon; Scharovsky, O. Graciela; Márquez, Mauricio Menacho

2017-01-01

Discovery of new drugs for cancer treatment is an expensive and time-consuming process and the percentage of drugs reaching the clinic remains quite low. Drug repositioning refers to the identification and development of new uses for existing drugs and represents an alternative drug development strategy. In this work, we evaluated the antitumor effect of metronomic treatment with a combination of two repositioned drugs, metformin and propranolol, in triple negative breast cancer models. By in vitro studies with five different breast cancer derived cells, we observed that combined treatment decreased proliferation (P < 0.001), mitochondrial activity (P < 0.001), migration (P < 0.001) and invasion (P < 0.001). In vivo studies in immunocompetent mice confirmed the potential of this combination in reducing tumor growth (P < 0.001) and preventing metastasis (P < 0.05). Taken together our results suggest that metformin plus propranolol combined treatment might be beneficial for triple negative breast cancer control, with no symptoms of toxicity. PMID:27926515

Breast Cancer

MedlinePlus

Breast cancer affects one in eight women during their lives. No one knows why some women get breast cancer, but there are many risk factors. Risks that ... who have family members with breast or ovarian cancer may wish to be tested for the genes. ...

Breast Cancer Translational Research Center of Excellence

DTIC Science & Technology

2017-11-01

treating breast diseases and breast cancer. This multidisciplinary model integrates prevention, screening, diagnosis, treatment and continuing care...breast diseases and breast cancer. This approach integrates prevention, screening, diagnosis, treatment and continuing care, incorporation of...mammography and clinical breast examination have a very poor accuracy in the young active duty force in determining which breast abnormalities

Activity of the kinesin spindle protein inhibitor ispinesib (SB-715992) in models of breast cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purcell, James W; Davis, Jefferson; Reddy, Mamatha

2009-06-10

Ispinesib (SB-715992) is a potent inhibitor of kinesin spindle protein (KSP), a kinesin motor protein essential for the formation of a bipolar mitotic spindle and cell cycle progression through mitosis. Clinical studies of ispinesib have demonstrated a 9% response rate in patients with locally advanced or metastatic breast cancer, and a favorable safety profile without significant neurotoxicities, gastrointestinal toxicities or hair loss. To better understand the potential of ispinesib in the treatment of breast cancer we explored the activity of ispinesib alone and in combination several therapies approved for the treatment of breast cancer. We measured the ispinesib sensitivity andmore » pharmacodynamic response of breast cancer cell lines representative of various subtypes in vitro and as xenografts in vivo, and tested the ability of ispinesib to enhance the anti-tumor activity of approved therapies. In vitro, ispinesib displayed broad anti-proliferative activity against a panel of 53 breast cell-lines. In vivo, ispinesib produced regressions in each of five breast cancer models, and tumor free survivors in three of these models. The effects of ispinesib treatment on pharmacodynamic markers of mitosis and apoptosis were examined in vitro and in vivo, revealing a greater increase in both mitotic and apoptotic markers in the MDA-MB-468 model than in the less sensitive BT-474 model. In vivo, ispinesib enhanced the anti-tumor activity of trastuzumab, lapatinib, doxorubicin, and capecitabine, and exhibited activity comparable to paclitaxel and ixabepilone. These findings support further clinical exploration of KSP inhibitors for the treatment of breast cancer.« less

One versus Two Breast Density Measures to Predict 5- and 10-Year Breast Cancer Risk.

PubMed

Kerlikowske, Karla; Gard, Charlotte C; Sprague, Brian L; Tice, Jeffrey A; Miglioretti, Diana L

2015-06-01

One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined whether two BI-RADS density measures improve the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared with one measure. We included 722,654 women of ages 35 to 74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000-2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC, 0.640 vs. 0.635). Of 18.6% of women (134,404 of 722,654) who decreased density categories, 15.4% (20,741 of 134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model. The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. A two-density model should be considered for women whose density decreases when calculating breast cancer risk. ©2015 American Association for Cancer Research.

Cure frailty models for survival data: application to recurrences for breast cancer and to hospital readmissions for colorectal cancer.

PubMed

Rondeau, Virginie; Schaffner, Emmanuel; Corbière, Fabien; Gonzalez, Juan R; Mathoulin-Pélissier, Simone

2013-06-01

Owing to the natural evolution of a disease, several events often arise after a first treatment for the same subject. For example, patients with a primary invasive breast cancer and treated with breast conserving surgery may experience breast cancer recurrences, metastases or death. A certain proportion of subjects in the population who are not expected to experience the events of interest are considered to be 'cured' or non-susceptible. To model correlated failure time data incorporating a surviving fraction, we compare several forms of cure rate frailty models. In the first model already proposed non-susceptible patients are those who are not expected to experience the event of interest over a sufficiently long period of time. The other proposed models account for the possibility of cure after each event. We illustrate the cure frailty models with two data sets. First to analyse time-dependent prognostic factors associated with breast cancer recurrences, metastases, new primary malignancy and death. Second to analyse successive rehospitalizations of patients diagnosed with colorectal cancer. Estimates were obtained by maximization of likelihood using SAS proc NLMIXED for a piecewise constant hazards model. As opposed to the simple frailty model, the proposed methods demonstrate great potential in modelling multivariate survival data with long-term survivors ('cured' individuals).

Multidrug Resistance in Breast Cancer: From In Vitro Models to Clinical Studies

PubMed Central

Wind, N. S.; Holen, I.

2011-01-01

The development of multidrug resistance (MDR) and subsequent relapse on therapy is a widespread problem in breast cancer, but our understanding of the underlying molecular mechanisms is incomplete. Numerous studies have aimed to establish the role of drug transporter pumps in MDR and to link their expression to response to chemotherapy. The ATP-binding cassette (ABC) transporters are central to breast cancer MDR, and increases in ABC expression levels have been shown to correlate with decreases in response to various chemotherapy drugs and a reduction in overall survival. But as there is a large degree of redundancy between different ABC transporters, this correlation has not been seen in all studies. This paper provides an introduction to the key molecules associated with breast cancer MDR and summarises evidence of their potential roles reported from model systems and clinical studies. We provide possible explanations for why despite several decades of research, the precise role of ABC transporters in breast cancer MDR remains elusive. PMID:22332018

Common breast cancer susceptibility loci are associated with triple negative breast cancer

PubMed Central

Stevens, Kristen N.; Vachon, Celine M.; Lee, Adam M.; Slager, Susan; Lesnick, Timothy; Olswold, Curtis; Fasching, Peter A.; Miron, Penelope; Eccles, Diana; Carpenter, Jane E.; Godwin, Andrew K.; Ambrosone, Christine; Winqvist, Robert; Schmidt, Marjanka K.; Cox, Angela; Cross, Simon S.; Sawyer, Elinor; Hartmann, Arndt; Beckmann, Matthias W.; Schulz-Wendtland, Rüdiger; Ekici, Arif B.; Tapper, William J; Gerty, Susan M; Durcan, Lorraine; Graham, Nikki; Hein, Rebecca; Nickels, Stephan; Flesch-Janys, Dieter; Heinz, Judith; Sinn, Hans-Peter; Konstantopoulou, Irene; Fostira, Florentia; Pectasides, Dimitrios; Dimopoulos, Athanasios M.; Fountzilas, George; Clarke, Christine L.; Balleine, Rosemary; Olson, Janet E.; Fredericksen, Zachary; Diasio, Robert B.; Pathak, Harsh; Ross, Eric; Weaver, JoEllen; Rüdiger, Thomas; Försti, Asta; Dünnebier, Thomas; Ademuyiwa, Foluso; Kulkarni, Swati; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Ko, Yon-Dschun; Van Limbergen, Erik; Janssen, Hilde; Peto, Julian; Fletcher, Olivia; Giles, Graham G.; Baglietto, Laura; Verhoef, Senno; Tomlinson, Ian; Kosma, Veli-Matti; Beesley, Jonathan; Greco, Dario; Blomqvist, Carl; Irwanto, Astrid; Liu, Jianjun; Blows, Fiona M.; Dawson, Sarah-Jane; Margolin, Sara; Mannermaa, Arto; Martin, Nicholas G.; Montgomery, Grant W; Lambrechts, Diether; dos Santos Silva, Isabel; Severi, Gianluca; Hamann, Ute; Pharoah, Paul; Easton, Douglas F.; Chang-Claude, Jenny; Yannoukakos, Drakoulis; Nevanlinna, Heli; Wang, Xianshu; Couch, Fergus J.

2012-01-01

Triple negative breast cancers are an aggressive subtype of breast cancer with poor survival, but there remains little known about the etiological factors which promote its initiation and development. Commonly inherited breast cancer risk factors identified through genome wide association studies (GWAS) display heterogeneity of effect among breast cancer subtypes as defined by estrogen receptor (ER) and progesterone receptor (PR) status. In the Triple Negative Breast Cancer Consortium (TNBCC), 22 common breast cancer susceptibility variants were investigated in 2,980 Caucasian women with triple negative breast cancer and 4,978 healthy controls. We identified six single nucleotide polymorphisms (SNPs) significantly associated with risk of triple negative breast cancer, including rs2046210 (ESR1), rs12662670 (ESR1), rs3803662 (TOX3), rs999737 (RAD51L1), rs8170 (19p13.11) and rs8100241 (19p13.11). Together, our results provide convincing evidence of genetic susceptibility for triple negative breast cancer. PMID:21844186

Application of hazard models for patients with breast cancer in Cuba

PubMed Central

Alfonso, Anet Garcia; de Oca, Néstor Arcia Montes

2011-01-01

There has been a rapid development in hazard models and survival analysis in the last decade. This article aims to assess the overall survival time of breast cancer in Cuba, as well as to determine plausible factors that may have a significant impact in the survival time. The data are obtained from the National Cancer Register of Cuba. The data set used in this study relates to 6381 patients diagnosed with breast cancer between January 2000 and December 2002. Follow-up data are available until the end of December 2007, by which time 2167 (33.9%) had died and 4214 (66.1%) were still alive. The adequacy of six parametric models is assessed by using their Akaike information criterion values. Five of the six parametric models (Exponential, Weibull, Log-logistic, Lognormal, and Generalized Gamma) are parameterized by using the accelerated failure-time metric, and the Gompertz model is parameterized by using the proportional hazard metric. The main result in terms of survival is found for the different categories of the clinical stage covariate. The survival time among patients who have been diagnosed at early stage of breast cancer is about 60% higher than the one among patients diagnosed at more advanced stage of the disease. Differences among provinces have not been found. The age is another significant factor, but there is no important difference between patient ages. PMID:21686138

Application of hazard models for patients with breast cancer in Cuba.

PubMed

Alfonso, Anet Garcia; de Oca, Néstor Arcia Montes

2011-01-01

There has been a rapid development in hazard models and survival analysis in the last decade. This article aims to assess the overall survival time of breast cancer in Cuba, as well as to determine plausible factors that may have a significant impact in the survival time. The data are obtained from the National Cancer Register of Cuba. The data set used in this study relates to 6381 patients diagnosed with breast cancer between January 2000 and December 2002. Follow-up data are available until the end of December 2007, by which time 2167 (33.9%) had died and 4214 (66.1%) were still alive. The adequacy of six parametric models is assessed by using their Akaike information criterion values. Five of the six parametric models (Exponential, Weibull, Log-logistic, Lognormal, and Generalized Gamma) are parameterized by using the accelerated failure-time metric, and the Gompertz model is parameterized by using the proportional hazard metric. The main result in terms of survival is found for the different categories of the clinical stage covariate. The survival time among patients who have been diagnosed at early stage of breast cancer is about 60% higher than the one among patients diagnosed at more advanced stage of the disease. Differences among provinces have not been found. The age is another significant factor, but there is no important difference between patient ages.

One vs. Two Breast Density Measures to Predict 5- and 10- Year Breast Cancer Risk

PubMed Central

Kerlikowske, Karla; Gard, Charlotte C.; Sprague, Brian L.; Tice, Jeffrey A.; Miglioretti, Diana L.

2015-01-01

Background One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined if two BI-RADS density measures improves the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared to one measure. Methods We included 722,654 women aged 35–74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000–2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. Results The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC=0.640 vs. 0.635). Of 18.6% of women (134,404/722,654) who decreased density categories, 15.4% (20,741/134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model. Conclusion The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. Impact A two-density model should be considered for women whose density decreases when calculating breast cancer risk. PMID:25824444

Can differences in breast cancer utilities explain disparities in breast cancer care?

PubMed

Schleinitz, Mark D; DePalo, Dina; Blume, Jeffrey; Stein, Michael

2006-12-01

Black, older, and less affluent women are less likely to receive adjuvant breast cancer therapy than their counterparts. Whereas preference contributes to disparities in other health care scenarios, it is unclear if preference explains differential rates of breast cancer care. To ascertain utilities from women of diverse backgrounds for the different stages of, and treatments for, breast cancer and to determine whether a treatment decision modeled from utilities is associated with socio-demographic characteristics. A stratified sample (by age and race) of 156 English-speaking women over 25 years old not currently undergoing breast cancer treatment. We assessed utilities using standard gamble for 5 breast cancer stages, and time-tradeoff for 3 therapeutic modalities. We incorporated each subject's utilities into a Markov model to determine whether her quality-adjusted life expectancy would be maximized with chemotherapy for a hypothetical, current diagnosis of stage II breast cancer. We used logistic regression to determine whether socio-demographic variables were associated with this optimal strategy. Median utilities for the 8 health states were: stage I disease, 0.91 (interquartile range 0.50 to 1.00); stage II, 0.75 (0.26 to 0.99); stage III, 0.51 (0.25 to 0.94); stage IV (estrogen receptor positive), 0.36 (0 to 0.75); stage IV (estrogen receptor negative), 0.40 (0 to 0.79); chemotherapy 0.50 (0 to 0.92); hormonal therapy 0.58 (0 to 1); and radiation therapy 0.83 (0.10 to 1). Utilities for early stage disease and treatment modalities, but not metastatic disease, varied with socio-demographic characteristics. One hundred and twenty-two of 156 subjects had utilities that maximized quality-adjusted life expectancy given stage II breast cancer with chemotherapy. Age over 50, black race, and low household income were associated with at least 5-fold lower odds of maximizing quality-adjusted life expectancy with chemotherapy, whereas women who were married or had a

Detection and Evaluation of Early Breast Cancer via Magnetic Resonance Imaging: Studies of Mouse Models and Clinical Implementation

DTIC Science & Technology

2008-03-01

CONTRACT NUMBER Detection and Evaluation of Early Breast Cancer via Magnetic Resonance Imaging: Studies of Mouse Models and Clinical Implementation...research proposed here can directly lead to clinical improvements in both early breast cancer detection, as well as effective breast cancer therapy. To date... cancer is a major prognostic factor in the management of the disease. In particular, detecting breast cancer in its pre-invasive form as ductal carcinoma

Modeling of electrical impedance tomography to detect breast cancer by finite volume methods

NASA Astrophysics Data System (ADS)

Ain, K.; Wibowo, R. A.; Soelistiono, S.

2017-05-01

The properties of the electrical impedance of tissue are an interesting study, because changes of the electrical impedance of organs are related to physiological and pathological. Both physiological and pathological properties are strongly associated with disease information. Several experiments shown that the breast cancer has a lower impedance than the normal breast tissue. Thus, the imaging based on impedance can be used as an alternative equipment to detect the breast cancer. This research carries out by modelling of Electrical Impedance Tomography to detect the breast cancer by finite volume methods. The research includes development of a mathematical model of the electric potential field by 2D Finite Volume Method, solving the forward problem and inverse problem by linear reconstruction method. The scanning is done by 16 channel electrode with neighbors method to collect data. The scanning is performed at a frequency of 10 kHz and 100 kHz with three objects numeric includes an anomaly at the surface, an anomaly at the depth and an anomaly at the surface and at depth. The simulation has been successfully to reconstruct image of functional anomalies of the breast cancer at the surface position, the depth position or a combination of surface and the depth.

Evaluation of diffusion models in breast cancer.

PubMed

Panek, Rafal; Borri, Marco; Orton, Matthew; O'Flynn, Elizabeth; Morgan, Veronica; Giles, Sharon L; deSouza, Nandita; Leach, Martin O; Schmidt, Maria A

2015-08-01

The purpose of this study is to investigate whether the microvascular pseudodiffusion effects resulting with non-monoexponential behavior are present in breast cancer, taking into account tumor spatial heterogeneity. Additionally, methodological factors affecting the signal in low and high diffusion-sensitizing gradient ranges were explored in phantom studies. The effect of eddy currents and accuracy of b-value determination using a multiple b-value diffusion-weighted MR imaging sequence were investigated in test objects. Diffusion model selection and noise were then investigated in volunteers (n = 5) and breast tumor patients (n = 21) using the Bayesian information criterion. 54.3% of lesion voxels were best fitted by a monoexponential, 26.2% by a stretched-exponential, and 19.5% by a biexponential intravoxel incoherent motion (IVIM) model. High correlation (0.92) was observed between diffusion coefficients calculated using mono- and stretched-exponential models and moderate (0.59) between monoexponential and IVIM (medians: 0.96/0.84/0.72 × 10(-3) mm(2)/s, respectively). Distortion due to eddy currents depended on the direction of the diffusion gradient and displacement varied between 1 and 6 mm for high b-value images. Shift in the apparent diffusion coefficient due to intrinsic field gradients was compensated for by averaging diffusion data obtained from opposite directions. Pseudodiffusion and intravoxel heterogeneity effects were not observed in approximately half of breast cancer and normal tissue voxels. This result indicates that stretched and IVIM models should be utilized in regional analysis rather than global tumor assessment. Cross terms between diffusion-sensitization gradients and other imaging or susceptibility-related gradients are relevant in clinical protocols, supporting the use of geometric averaging of diffusion-weighted images acquired with diffusion-sensitization gradients in opposite directions.

Engineering Breast Cancer Microenvironments and 3D Bioprinting

PubMed Central

Belgodere, Jorge A.; King, Connor T.; Bursavich, Jacob B.; Burow, Matthew E.; Martin, Elizabeth C.; Jung, Jangwook P.

2018-01-01

The extracellular matrix (ECM) is a critical cue to direct tumorigenesis and metastasis. Although two-dimensional (2D) culture models have been widely employed to understand breast cancer microenvironments over the past several decades, the 2D models still exhibit limited success. Overwhelming evidence supports that three dimensional (3D), physiologically relevant culture models are required to better understand cancer progression and develop more effective treatment. Such platforms should include cancer-specific architectures, relevant physicochemical signals, stromal–cancer cell interactions, immune components, vascular components, and cell-ECM interactions found in patient tumors. This review briefly summarizes how cancer microenvironments (stromal component, cell-ECM interactions, and molecular modulators) are defined and what emerging technologies (perfusable scaffold, tumor stiffness, supporting cells within tumors and complex patterning) can be utilized to better mimic native-like breast cancer microenvironments. Furthermore, this review emphasizes biophysical properties that differ between primary tumor ECM and tissue sites of metastatic lesions with a focus on matrix modulation of cancer stem cells, providing a rationale for investigation of underexplored ECM proteins that could alter patient prognosis. To engineer breast cancer microenvironments, we categorized technologies into two groups: (1) biochemical factors modulating breast cancer cell-ECM interactions and (2) 3D bioprinting methods and its applications to model breast cancer microenvironments. Biochemical factors include matrix-associated proteins, soluble factors, ECMs, and synthetic biomaterials. For the application of 3D bioprinting, we discuss the transition of 2D patterning to 3D scaffolding with various bioprinting technologies to implement biophysical cues to model breast cancer microenvironments. PMID:29881724

Breast Cancer Risk Prediction and Mammography Biopsy Decisions

PubMed Central

Armstrong, Katrina; Handorf, Elizabeth A.; Chen, Jinbo; Demeter, Mirar N. Bristol

2012-01-01

Background Controversy continues about screening mammography, in part because of the risk of false-negative and false-positive mammograms. Pre-test breast cancer risk factors may improve the positive and negative predictive value of screening. Purpose To create a model that estimates the potential impact of pre-test risk prediction using clinical and genomic information on the reclassification of women with abnormal mammograms (BI-RADS3 and BI-RADS4 [Breast Imaging-Reporting and Data System]) above and below the threshold for breast biopsy. Methods The current study modeled 1-year breast cancer risk in women with abnormal screening mammograms using existing data on breast cancer risk factors, 12 validated breast cancer single nucleotide polymorphisms (SNPs), and probability of cancer given the BI-RADS category. Examination was made of reclassification of women above and below biopsy thresholds of 1%, 2%, and 3% risk. The Breast Cancer Surveillance Consortium data were collected from 1996 to 2002. Data analysis was conducted in 2010 and 2011. Results Using a biopsy risk threshold of 2% and the standard risk factor model, 5% of women with a BI-RADS3 mammogram had a risk above the threshold, and 3% of women with BIRADS4A mammograms had a risk below the threshold. The addition of 12 SNPs in the model resulted in 8% of women with a BI-RADS3 mammogram above the threshold for biopsy and 7% of women with BI-RADS4A mammograms below the threshold. Conclusions The incorporation of pre-test breast cancer risk factors could change biopsy decisions for a small proportion of women with abnormal mammograms. The greatest impact comes from standard breast cancer risk factors. PMID:23253645

Breast Cancer in Men

MedlinePlus

FACTS FOR LIFE Breast Cancer in Men Do men get breast cancer? Since men have breast tissue, they can get breast cancer, but it’s rare. About 1 percent of ... breast cancer cases in the U.S. occur in men. It may sound like a small number, but ...

Male Breast Cancer

MedlinePlus

... or to other parts of the body. Where breast cancer begins in men Everyone is born with a ... and inflammatory breast cancer. Inherited genes that increase breast cancer risk Some men inherit abnormal (mutated) genes from ...

Risks of Breast Cancer Screening

MedlinePlus

... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Screening (PDQ®)–Patient Version What is screening? Go ... cancer screening: Cancer Screening Overview General Information About Breast Cancer Key Points Breast cancer is a disease in ...

Osthole inhibits bone metastasis of breast cancer

PubMed Central

Guo, Baofeng; Ye, Yiyi; Han, Xianghui; Qin, Yuenong; Liu, Sheng

2017-01-01

Bone is one of the most common sites for breast cancer metastasis, which greatly contributes to patient morbidity and mortality. Osthole, a major extract from Cnidium monnieri (L.), exhibits many biological and pharmacological activities, however, its potential as a therapeutic agent in the treatment of breast cancer bone metastases remain poorly understood. In this study, we set out to investigate whether osthole could inhibit breast cancer metastasis to bone in mice and clarified the potential mechanism of this inhibition. In the murine model of breast cancer osseous metastasis, mice that received osthole developed significantly less bone metastases and displayed decreased tumor burden when compared with mice in the control group. Osthole inhibited breast cancer cell growth, migration, and invasion, and induced apoptosis of breast cancer cells. Additionally, it also regulated OPG/RANKL signals in the interactions between bone cells (osteoblasts and osteoclasts) and cancer cells. Besides, it also inhibited TGF-β/Smads signaling in breast cancer metastasis to bone in MDA-231BO cells. The results of this study suggest that osthole has real potential as a therapeutic candidate in the treatment of breast cancer patients with bone metastases. PMID:28938572

Male Breast Cancer

MedlinePlus

Although breast cancer is much more common in women, men can get it too. It happens most often to men between ... 60 and 70. Breast lumps usually aren't cancer. However, most men with breast cancer have lumps. ...

Melatonin, environmental light, and breast cancer.

PubMed

Srinivasan, V; Spence, D W; Pandi-Perumal, S R; Trakht, I; Esquifino, A I; Cardinali, D P; Maestroni, G J

2008-04-01

Although many factors have been suggested as causes for breast cancer, the increased incidence of the disease seen in women working in night shifts led to the hypothesis that the suppression of melatonin by light or melatonin deficiency plays a major role in cancer development. Studies on the 7,12-dimethylbenz[a]anthracene and N-methyl-N-nitrosourea experimental models of human breast cancer indicate that melatonin is effective in reducing cancer development. In vitro studies in MCF-7 human breast cancer cell line have shown that melatonin exerts its anticarcinogenic actions through a variety of mechanisms, and that it is most effective in estrogen receptor (ER) alpha-positive breast cancer cells. Melatonin suppresses ER gene, modulates several estrogen dependent regulatory proteins and pro-oncogenes, inhibits cell proliferation, and impairs the metastatic capacity of MCF-7 human breast cancer cells. The anticarcinogenic action on MCF-7 cells has been demonstrated at the physiological concentrations of melatonin attained at night, suggesting thereby that melatonin acts like an endogenous antiestrogen. Melatonin also decreases the formation of estrogens from androgens via aromatase inhibition. Circulating melatonin levels are abnormally low in ER-positive breast cancer patients thereby supporting the melatonin hypothesis for breast cancer in shift working women. It has been postulated that enhanced endogenous melatonin secretion is responsible for the beneficial effects of meditation as a form of psychosocial intervention that helps breast cancer patients.

Dose-dependent effect of mammographic breast density on the risk of contralateral breast cancer.

PubMed

Chowdhury, Marzana; Euhus, David; O'Donnell, Maureen; Onega, Tracy; Choudhary, Pankaj K; Biswas, Swati

2018-07-01

Increased mammographic breast density is a significant risk factor for breast cancer. It is not clear if it is also a risk factor for the development of contralateral breast cancer. The data were obtained from Breast Cancer Surveillance Consortium and included women diagnosed with invasive breast cancer or ductal carcinoma in situ between ages 18 and 88 and years 1995 and 2009. Each case of contralateral breast cancer was matched with three controls based on year of first breast cancer diagnosis, race, and length of follow-up. A total of 847 cases and 2541 controls were included. The risk factors included in the study were mammographic breast density, age of first breast cancer diagnosis, family history of breast cancer, anti-estrogen treatment, hormone replacement therapy, menopausal status, and estrogen receptor status, all from the time of first breast cancer diagnosis. Both univariate analysis and multivariate conditional logistic regression analysis were performed. In the final multivariate model, breast density, family history of breast cancer, and anti-estrogen treatment remained significant with p values less than 0.01. Increasing breast density had a dose-dependent effect on the risk of contralateral breast cancer. Relative to 'almost entirely fat' category of breast density, the adjusted odds ratios (and p values) in the multivariate analysis for 'scattered density,' 'heterogeneously dense,' and 'extremely dense' categories were 1.65 (0.036), 2.10 (0.002), and 2.32 (0.001), respectively. Breast density is an independent and significant risk factor for development of contralateral breast cancer. This risk factor should contribute to clinical decision making.

Imaging features of breast cancers on digital breast tomosynthesis according to molecular subtype: association with breast cancer detection.

PubMed

Lee, Su Hyun; Chang, Jung Min; Shin, Sung Ui; Chu, A Jung; Yi, Ann; Cho, Nariya; Moon, Woo Kyung

2017-12-01

To evaluate imaging features of breast cancers on digital breast tomosynthesis (DBT) according to molecular subtype and to determine whether the molecular subtype affects breast cancer detection on DBT. This was an institutional review board--approved study with a waiver of informed consent. DBT findings of 288 invasive breast cancers were reviewed according to Breast Imaging Reporting and Data System lexicon. Detectability of breast cancer was quantified by the number of readers (0-3) who correctly detected the cancer in an independent blinded review. DBT features and the cancer detectability score according to molecular subtype were compared using Fisher's exact test and analysis of variance. Of 288 invasive cancers, 194 were hormone receptor (HR)-positive, 48 were human epidermal growth factor receptor 2 (HER2) positive and 46 were triple negative breast cancers. The most common DBT findings were irregular spiculated masses for HR-positive cancer, fine pleomorphic or linear branching calcifications for HER2 positive cancer and irregular masses with circumscribed margins for triple negative breast cancers (p < 0.001). Cancer detectability on DBT was not significantly different according to molecular subtype (p = 0.213) but rather affected by tumour size, breast density and presence of mass or calcifications. Breast cancers showed different imaging features according to molecular subtype; however, it did not affect the cancer detectability on DBT. Advances in knowledge: DBT showed characteristic imaging features of breast cancers according to molecular subtype. However, cancer detectability on DBT was not affected by molecular subtype of breast cancers.

Persistent breast pain among women with histories of breast conserving surgery for breast cancer compared to women without histories of breast surgery or cancer

PubMed Central

Edmond, Sara N.; Shelby, Rebecca A.; Keefe, Francis J.; Fisher, Hannah M.; Schmidt, John; Soo, Mary Scott; Skinner, Celette Sugg; Ahrendt, Gretchen M.; Manculich, Jessica; Sumkin, Jules H.; Zuley, Margarita L.; Bovbjerg, Dana H.

2016-01-01

Objectives This study compared persistent breast pain among women who received breast-conserving surgery for breast cancer and women without a history of breast cancer. Methods Breast cancer survivors (n=200) were recruited at their first post-surgical surveillance mammogram (6-15 months post-surgery). Women without a breast cancer history (n=150) were recruited at the time of a routine screening mammogram. All women completed measures of breast pain, pain interference with daily activities and intimacy, worry about breast pain, anxiety symptoms, and depression symptoms. Demographic and medical information were also collected. Results Persistent breast pain (duration ≥ 6 months) was reported by 46.5% of breast cancer survivors and 12.7% of women without a breast cancer history (p<0.05). Breast cancer survivors also had significantly higher rates of clinically significant persistent breast pain (pain intensity score ≥3/10), as well as higher average breast pain intensity and unpleasantness scores. Breast cancer survivors with persistent breast pain had significantly higher levels of depressive symptoms, as well as pain worry and interference, compared to survivors without persistent breast pain or women without a breast cancer history. Anxiety symptoms were significantly higher in breast cancer survivors with persistent breast pain compared to women without a breast cancer history. Discussion Results indicate that persistent breast pain negatively impacts women with a history of breast conserving cancer surgery compared to women without that history. Strategies to ameliorate persistent breast pain and to improve adjustment among women with persistent breast pain should be explored for incorporation into standard care for breast cancer survivors. PMID:27922843

A method for using real world data in breast cancer modeling.

PubMed

Pobiruchin, Monika; Bochum, Sylvia; Martens, Uwe M; Kieser, Meinhard; Schramm, Wendelin

2016-04-01

Today, hospitals and other health care-related institutions are accumulating a growing bulk of real world clinical data. Such data offer new possibilities for the generation of disease models for the health economic evaluation. In this article, we propose a new approach to leverage cancer registry data for the development of Markov models. Records of breast cancer patients from a clinical cancer registry were used to construct a real world data driven disease model. We describe a model generation process which maps database structures to disease state definitions based on medical expert knowledge. Software was programmed in Java to automatically derive a model structure and transition probabilities. We illustrate our method with the reconstruction of a published breast cancer reference model derived primarily from clinical study data. In doing so, we exported longitudinal patient data from a clinical cancer registry covering eight years. The patient cohort (n=892) comprised HER2-positive and HER2-negative women treated with or without Trastuzumab. The models generated with this method for the respective patient cohorts were comparable to the reference model in their structure and treatment effects. However, our computed disease models reflect a more detailed picture of the transition probabilities, especially for disease free survival and recurrence. Our work presents an approach to extract Markov models semi-automatically using real world data from a clinical cancer registry. Health care decision makers may benefit from more realistic disease models to improve health care-related planning and actions based on their own data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Circulating microRNA-based screening tool for breast cancer

PubMed Central

Boukerroucha, Meriem; Fasquelle, Corinne; Thiry, Jérôme; Bovy, Nicolas; Struman, Ingrid; Geurts, Pierre; Collignon, Joëlle; Schroeder, Hélène; Kridelka, Frédéric; Lifrange, Eric; Jossa, Véronique

2016-01-01

Circulating microRNAs (miRNAs) are increasingly recognized as powerful biomarkers in several pathologies, including breast cancer. Here, their plasmatic levels were measured to be used as an alternative screening procedure to mammography for breast cancer diagnosis. A plasma miRNA profile was determined by RT-qPCR in a cohort of 378 women. A diagnostic model was designed based on the expression of 8 miRNAs measured first in a profiling cohort composed of 41 primary breast cancers and 45 controls, and further validated in diverse cohorts composed of 108 primary breast cancers, 88 controls, 35 breast cancers in remission, 31 metastatic breast cancers and 30 gynecologic tumors. A receiver operating characteristic curve derived from the 8-miRNA random forest based diagnostic tool exhibited an area under the curve of 0.81. The accuracy of the diagnostic tool remained unchanged considering age and tumor stage. The miRNA signature correctly identified patients with metastatic breast cancer. The use of the classification model on cohorts of patients with breast cancers in remission and with gynecologic cancers yielded prediction distributions similar to that of the control group. Using a multivariate supervised learning method and a set of 8 circulating miRNAs, we designed an accurate, minimally invasive screening tool for breast cancer. PMID:26734993

Breast cancer in men

MedlinePlus

... in situ - male; Intraductal carcinoma - male; Inflammatory breast cancer - male; Paget disease of the nipple - male; Breast cancer - male ... The cause of breast cancer in men is not clear. But there are risk factors that make breast cancer more likely in men: Exposure to ...

Health-Related Quality of Life in a Predictive Model for Mortality in Older Breast Cancer Survivors.

PubMed

DuMontier, Clark; Clough-Gorr, Kerri M; Silliman, Rebecca A; Stuck, Andreas E; Moser, André

2018-03-13

To develop a predictive model and risk score for 10-year mortality using health-related quality of life (HRQOL) in a cohort of older women with early-stage breast cancer. Prospective cohort. Community. U.S. women aged 65 and older diagnosed with Stage I to IIIA primary breast cancer (N=660). We used medical variables (age, comorbidity), HRQOL measures (10-item Physical Function Index and 5-item Mental Health Index from the Medical Outcomes Study (MOS) 36-item Short-Form Survey; 8-item Modified MOS Social Support Survey), and breast cancer variables (stage, surgery, chemotherapy, endocrine therapy) to develop a 10-year mortality risk score using penalized logistic regression models. We assessed model discriminative performance using the area under the receiver operating characteristic curve (AUC), calibration performance using the Hosmer-Lemeshow test, and overall model performance using Nagelkerke R 2 (NR). Compared to a model including only age, comorbidity, and cancer stage and treatment variables, adding HRQOL variables improved discrimination (AUC 0.742 from 0.715) and overall performance (NR 0.221 from 0.190) with good calibration (p=0.96 from HL test). In a cohort of older women with early-stage breast cancer, HRQOL measures predict 10-year mortality independently of traditional breast cancer prognostic variables. These findings suggest that interventions aimed at improving physical function, mental health, and social support might improve both HRQOL and survival. © 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.

Environmental pollutants and breast cancer.

PubMed Central

Brody, Julia Green; Rudel, Ruthann A

2003-01-01

Breast cancer is the most common cancer in women and the leading cause of cancer death among women 35-54 years of age. Rising incidence, increased risk among migrants to higher risk regions, and poor prediction of individual risk have prompted a search for additional modifiable factors. Risk factors for breast cancer include reproductive characteristics associated with estrogen and other hormones, pharmaceutical hormones, and activities such as alcohol use and lack of exercise that affect hormone levels. As a result, investigation of hormonally active compounds in commercial products and pollution is a priority. Compounds that cause mammary tumors in animals are additional priorities. Animal models provide insight into possible mechanisms for effects of environmental pollutants on breast cancer and identify chemical exposures to target in epidemiologic studies. Although few epidemiologic studies have been conducted for chemical exposures, occupational studies show associations between breast cancer and exposure to certain organic solvents and polycyclic aromatic hydrocarbons (PAHs). Population-based studies have been limited to a few organochlorine compounds and PAHs and have been mostly negative. A variety of challenges in studies of breast cancer and the environment may have contributed to negative findings. Lack of exposure assessment tools and few hypothesis-generating toxicologic studies limit the scope of epidemiologic studies. Issues of timing with respect to latency and periods of breast vulnerability, and individual differences in susceptibility pose other challenges. Substantial work is needed in exposure assessment, toxicology, and susceptibility before we can expect a pay-off from large epidemiologic studies of breast cancer and environment. PMID:12826474

A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

PubMed

Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

2012-04-01

A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the

A preclinical mouse model of invasive lobular breast cancer metastasis.

PubMed

Doornebal, Chris W; Klarenbeek, Sjoerd; Braumuller, Tanya M; Klijn, Christiaan N; Ciampricotti, Metamia; Hau, Cheei-Sing; Hollmann, Markus W; Jonkers, Jos; de Visser, Karin E

2013-01-01

Metastatic disease accounts for more than 90% of cancer-related deaths, but the development of effective antimetastatic agents has been hampered by the paucity of clinically relevant preclinical models of human metastatic disease. Here, we report the development of a mouse model of spontaneous breast cancer metastasis, which recapitulates key events in its formation and clinical course. Specifically, using the conditional K14cre;Cdh1(F/F);Trp53(F/F) model of de novo mammary tumor formation, we orthotopically transplanted invasive lobular carcinoma (mILC) fragments into mammary glands of wild-type syngeneic hosts. Once primary tumors were established in recipient mice, we mimicked the clinical course of treatment by conducting a mastectomy. After surgery, recipient mice succumbed to widespread overt metastatic disease in lymph nodes, lungs, and gastrointestinal tract. Genomic profiling of paired mammary tumors and distant metastases showed that our model provides a unique tool to further explore the biology of metastatic disease. Neoadjuvant and adjuvant intervention studies using standard-of-care chemotherapeutics showed the value of this model in determining therapeutic agents that can target early- and late-stage metastatic disease. In obtaining a more accurate preclinical model of metastatic lobular breast cancer, our work offers advances supporting the development of more effective treatment strategies for metastatic disease.

Application of accelerated failure time models for breast cancer patients' survival in Kurdistan Province of Iran.

PubMed

Karimi, Asrin; Delpisheh, Ali; Sayehmiri, Kourosh

2016-01-01

Breast cancer is the most common cancer and the second common cause of cancer-induced mortalities in Iranian women. There has been a rapid development in hazard models and survival analysis in the last decade. The aim of this study was to evaluate the prognostic factors of overall survival (OS) in breast cancer patients using accelerated failure time models (AFT). This was a retrospective-analytic cohort study. About 313 women with a pathologically proven diagnosis of breast cancer who had been treated during a 7-year period (since January 2006 until March 2014) in Sanandaj City, Kurdistan Province of Iran were recruited. Performance among AFT was assessed using the goodness of fit methods. Discrimination among the exponential, Weibull, generalized gamma, log-logistic, and log-normal distributions was done using Akaik information criteria and maximum likelihood. The 5 years OS was 75% (95% CI = 74.57-75.43). The main results in terms of survival were found for the different categories of the clinical stage covariate, tumor metastasis, and relapse of cancer. Survival time in breast cancer patients without tumor metastasis and relapse were 4, 2-fold longer than other patients with metastasis and relapse, respectively. One of the most important undermining prognostic factors in breast cancer is metastasis; hence, knowledge of the mechanisms of metastasis is necessary to prevent it so occurrence and treatment of metastatic breast cancer and ultimately extend the lifetime of patients.

Which strategies reduce breast cancer mortality most? Collaborative modeling of optimal screening, treatment, and obesity prevention.

PubMed

Mandelblatt, Jeanne; van Ravesteyn, Nicolien; Schechter, Clyde; Chang, Yaojen; Huang, An-Tsun; Near, Aimee M; de Koning, Harry; Jemal, Ahmedin

2013-07-15

US breast cancer mortality is declining, but thousands of women still die each year. Two established simulation models examine 6 strategies that include increased screening and/or treatment or elimination of obesity versus continuation of current patterns. The models use common national data on incidence and obesity prevalence, competing causes of death, mammography characteristics, treatment effects, and survival/cure. Parameters are modified based on obesity (defined as BMI  ≥  30 kg/m(2) ). Outcomes are presented for the year 2025 among women aged 25+ and include numbers of cases, deaths, mammograms and false-positives; age-adjusted incidence and mortality; breast cancer mortality reduction and deaths averted; and probability of dying of breast cancer. If current patterns continue, the models project that there would be about 50,100-57,400 (range across models) annual breast cancer deaths in 2025. If 90% of women were screened annually from ages 40 to 54 and biennially from ages 55 to 99 (or death), then 5100-6100 fewer deaths would occur versus current patterns, but incidence, mammograms, and false-positives would increase. If all women received the indicated systemic treatment (with no screening change), then 11,400-14,500 more deaths would be averted versus current patterns, but increased toxicity could occur. If 100% received screening plus indicated therapy, there would be 18,100-20,400 fewer deaths. Eliminating obesity yields 3300-5700 fewer breast cancer deaths versus continuation of current obesity levels. Maximal reductions in breast cancer deaths could be achieved through optimizing treatment use, followed by increasing screening use and obesity prevention. © 2013 American Cancer Society.

Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk.

PubMed

Schonberg, Mara A; Li, Vicky W; Eliassen, A Heather; Davis, Roger B; LaCroix, Andrea Z; McCarthy, Ellen P; Rosner, Bernard A; Chlebowski, Rowan T; Hankinson, Susan E; Marcantonio, Edward R; Ngo, Long H

2016-12-01

Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death. We included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors) and 7 risk factors for non-breast cancer death (comorbidities, functional dependency) and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women's Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years). Within 5 years, 1.8 % of NHS participants were diagnosed with breast cancer (vs. 2.0 % in WHI-ES, p = 0.02), and 6.6 % experienced non-breast cancer death (vs. 5.2 % in WHI-ES, p < 0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model's c-statistic was 0.61 (95 % CI [0.60-0.63]) in NHS and 0.57 (0.55-0.58) in WHI-ES. On average, our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88-0.97]). We developed a novel prediction model that factors in postmenopausal women's individualized competing risks of non-breast cancer death when estimating breast cancer risk.

Adolescent meat intake and breast cancer risk

PubMed Central

Farvid, Maryam S; Cho, Eunyoung; Chen, Wendy Y; Eliassen, A. Heather; Willett, Walter C

2015-01-01

The breast is particularly vulnerable to carcinogenic influences during adolescence due to rapid proliferation of mammary cells and lack of terminal differentiation. We investigated consumption of adolescent red meat and other protein sources in relation to breast cancer risk in the Nurses' Health Study II cohort. We followed prospectively 44,231 women aged 33-52 years who, in 1998, completed a detailed questionnaire about diet during adolescence. Relative risks (RR) and 95% confidence intervals (95%CI) were estimated using Cox proportional hazard regression. We documented 1132 breast cancer cases during 13-year follow-up. In multivariable Cox regression models with major breast cancer risk factors adjustment, greater consumption of adolescent total red meat was significantly associated with higher premenopausal breast cancer risk (highest vs lowest quintiles, RR, 1.42; 95%CI, 1.05-1.94; Ptrend=0.007), but not postmenopausal breast cancer. Adolescent poultry intake was associated with lower risk of breast cancer overall (RR, 0.75; 95%CI, 0.59-0.96; for each serving/day). Adolescent intakes of iron, heme iron, fish, eggs, legumes and nuts were not associated with breast cancer. Replacement of one serving/day of total red meat with one serving of combination of poultry, fish, legumes, and nuts was associated with a 16% lower risk of breast cancer overall (RR, 0.84; 95%CI, 0.74-0.96) and a 24% lower risk of premenopausal breast cancer (RR, 0.76; 95%CI, 0.64-0.92). Higher consumption of red meat during adolescence was associated with premenopausal breast cancer. Substituting other dietary protein sources for red meat in adolescent diet may decrease premenopausal breast cancer risk. PMID:25220168

Breast cancer disparities: high-risk breast cancer and African ancestry.

PubMed

Newman, Lisa A

2014-07-01

African American women have a lower lifetime incidence of breast cancer than white/Caucasian Americans yet have a higher risk of breast cancer mortality. African American women are also more likely to be diagnosed with breast cancer at young ages, and they have higher risk for the biologically more aggressive triple-negative breast cancers. These features are also more common among women from western, sub-Saharan Africa who share ancestry with African Americans, and this prompts questions regarding an association between African ancestry and inherited susceptibility for certain patterns of mammary carcinogenesis. Copyright © 2014 Elsevier Inc. All rights reserved.

Improving Breast Cancer Outcomes among Women in China: Practices, Knowledge, and Attitudes Related to Breast Cancer Screening

PubMed Central

Wu, Tsu-Yin; Liu, Yi-Lan; Chung, Scott

2012-01-01

Background. Breast cancer is a major public health issue and the most commonly diagnosed cancer for women worldwide. Despite lower incidence rates than those living in Western countries, breast cancer incidence among Chinese women has increased dramatically in the past 20 years. Nevertheless, there is a paucity of studies reporting the attitudes toward and practices of breast cancer screening among Chinese women. Methods. This cross-sectional study examined the practices, knowledge, and attitudes toward breast cancer screening (BCS) on a convenience sample of 400 Chinese women. Results. Among study participants, 75% of the women never had a mammogram and the top three barriers reported were low priority, feeling OK, and lack of awareness/knowledge toward breast cancer screening. The results from the logistic regression model showed increased self-efficacy; having performed monthly self-exams, and having had clinical breast exams in the past two years were significant correlates while demographic variables were not correlated with screening behaviors. Conclusion. The findings provide a foundation to better understand beliefs and practices of Chinese women toward BCS and highlight the critical need for general public, health professionals, and the health care system to work collaboratively toward improving the quality of breast cancer care in this population. PMID:23304529

Breast cancer prevention.

PubMed

Euhus, David M; Diaz, Jennifer

2015-01-01

Breast cancer is the most common cancer in women with 232,670 new cases estimated in the USA for 2014. Approaches for reducing breast cancer risk include lifestyle modification, chemoprevention, and prophylactic surgery. Lifestyle modification has a variety of health benefits with few associated risks and is appropriate for all women regardless of breast cancer risk. Chemoprevention options have expanded rapidly, but most are directed at estrogen receptor positive breast cancer and uptake is low. Prophylactic surgery introduces significant additional risks of its own and is generally reserved for the highest risk women. © 2014 Wiley Periodicals, Inc.

[Estimation of individual breast cancer risk: relevance and limits of risk estimation models].

PubMed

De Pauw, A; Stoppa-Lyonnet, D; Andrieu, N; Asselain, B

2009-10-01

Several risk estimation models for breast or ovarian cancers have been developed these last decades. All these models take into account the family history, with different levels of sophistication. Gail model was developed in 1989 taking into account the family history (0, 1 or > or = 2 affected relatives) and several environmental factors. In 1990, Claus model was the first to integrate explicit assumptions about genetic effects, assuming a single gene dominantly inherited occurring with a low frequency in the population. BRCAPRO model, posterior to the identification of BRCA1 and BRCA2, assumes a restricted transmission with only these two dominantly inherited genes. BOADICEA model adds the effect of a polygenic component to the effect of BRCA1 and BRCA2 to explain the residual clustering of breast cancer. At last, IBIS model assumes a third dominantly inherited gene to explain this residual clustering. Moreover, this model incorporates environmental factors. We applied the Claus, BRCAPRO, BOADICEA and IBIS models to four clinical situations, corresponding to more or less heavy family histories, in order to study the consistency of the risk estimates. The three more recent models (BRCAPRO, BOADICEA and IBIS) gave the closer estimations. These estimates could be useful in clinical practice in front of complex analysis of breast and/or ovarian cancers family history.

Cell Culture Models and Pharmacological Perspective for the Study of Breast Cancer Markers

PubMed Central

Tovar, Cristian Layton

2013-01-01

Among the most prevalent neoplasias, breast cancer shows an astonishing tendency. Unfortunately this cancer has a high mortality worldwide, requiring sustained management of all actors involved in public health in order to get an early diagnosis and treatment. The methods associated with conventional cytogenetics and molecular cell culture, besides early detection of gene expression patterns associated with cancer susceptibility, have contributed to identify inherited genes and metabolic disorders related to obesity, which are also involved in breast cancer. In any case, a broad study of the above mentioned factors can give a predictive value to support the design of public health models to determine cancer risk in order to decrease the mortality from this disease. (1) Cell cultures offers a wide range of scientific approach for the study of breast cancer, including the analysis of biological function of several compounds in search of increasingly effective treatments with fewer side effects against this malignancy. (2) PMID:27683438

MMP9 polymorphisms and breast cancer risk: a report from the Shanghai Breast Cancer Genetics Study.

PubMed

Beeghly-Fadiel, Alicia; Lu, Wei; Shu, Xiao-Ou; Long, Jirong; Cai, Qiuyin; Xiang, Yongbin; Gao, Yu-Tang; Zheng, Wei

2011-04-01

In addition to tumor invasion and angiogenesis, matrix metalloproteinase (MMP)9 also contributes to carcinogenesis and tumor growth. Genetic variation that may influence MMP9 expression was evaluated among participants of the Shanghai Breast Cancer Genetics Study (SBCGS) for associations with breast cancer susceptibility. In stage 1, 11 MMP9 single nucleotide polymorphisms (SNPs) were genotyped by the Affymetrix Targeted Genotyping System and/or the Affymetrix Genome-Wide Human SNP Array 6.0 among 4,227 SBCGS participants. One SNP was further genotyped using the Sequenom iPLEX MassARRAY platform among an additional 6,270 SBCGS participants. Associations with breast cancer risk were evaluated by odds ratios (OR) and 95% confidence intervals (CI) from logistic regression models that included adjustment for age, education, and genotyping stage when appropriate. In Stage 1, rare allele homozygotes for a promoter SNP (rs3918241) or a non-synonymous SNP (rs2274756, R668Q) tended to occur more frequently among breast cancer cases (P value = 0.116 and 0.056, respectively). Given their high linkage disequilibrium (D' = 1.0, r (2) = 0.97), one (rs3918241) was selected for additional analysis. An association with breast cancer risk was not supported by additional Stage 2 genotyping. In combined analysis, no elevated risk of breast cancer among homozygotes was found (OR: 1.2, 95% CI: 0.8-1.8). Common genetic variation in MMP9 was not found to be significantly associated with breast cancer susceptibility among participants of the Shanghai Breast Cancer Genetics Study.

Stereotactic Image-Guided Navigation During Breast Reconstruction in Patients With Breast Cancer

ClinicalTrials.gov

2017-04-12

Ductal Breast Carcinoma in Situ; Lobular Breast Carcinoma in Situ; Recurrent Breast Cancer; Stage IA Breast Cancer; Stage IB Breast Cancer; Stage II Breast Cancer; Stage IIIA Breast Cancer; Stage IIIB Breast Cancer; Stage IIIC Breast Cancer; Stage IV Breast Cancer

Childhood growth and breast cancer.

PubMed

De Stavola, B L; dos Santos Silva, I; McCormack, V; Hardy, R J; Kuh, D J; Wadsworth, M E J

2004-04-01

Adult height is known to be positively associated with breast cancer risk. The mechanism underlying this association is complex, since adult height is positively correlated with age at menarche, which in turn is negatively associated with breast cancer risk. The authors used prospective data from a British cohort of 2,547 girls followed from birth in 1946 to the end of 1999 to examine breast cancer risk in relation to childhood growth. As expected, adult height was positively associated with age at menarche and breast cancer. In childhood, cases were taller and leaner, on average, than noncases. Significant predictors of breast cancer risk in models containing all components of growth were height velocity at age 4-7 years (for a one-standard-deviation increase, odds ratio (OR) = 1.54, 95% confidence interval (CI): 1.13, 2.09) and age 11-15 years (OR = 1.29, 95% CI: 0.97, 1.71) and body mass index velocity (weight (kg)/height (m)(2)/year) at age 2-4 years (OR = 0.63, 95% CI: 0.48, 0.83). The effects of these variables were particularly marked in women with early menarche (age <12.5 years). These findings suggest that women who grow faster in childhood and reach an adult height above the average for their menarche category are at particularly increased risk of breast cancer.

Limited fibrosis accompanies triple-negative breast cancer metastasis in multiple model systems and is not a preventive target.

PubMed

Brooks, Danielle; Zimmer, Alexandra; Wakefield, Lalage; Lyle, L Tiffany; Difilippantonio, Simone; Tucci, Fabio C; Illiano, Stephane; Annunziata, Christina M; Steeg, Patricia S

2018-05-04

The lysophosphatidic acid receptor 1 (LPAR1) is mechanistically implicated in both tumor metastasis and tissue fibrosis. Previously, metastasis was increased when fulminant fibrosis was first induced in mice, suggesting a direct connection between these processes. The current report examined the extent of metastasis-induced fibrosis in breast cancer model systems, and tested the metastasis preventive efficacy and fibrosis attenuation of antagonists for LPAR1 and Idiopathic Pulmonary Fibrosis (IPF) in breast and ovarian cancer models. Staining analysis demonstrated only focal, low-moderate levels of fibrosis in lungs from eleven metastasis model systems. Two orally available LPAR1 antagonists, SAR100842 and EPGN9878, significantly inhibited breast cancer motility to LPA in vitro . Both compounds were negative for metastasis prevention and failed to reduce fibrosis in the experimental MDA-MB-231T and spontaneous murine 4T1 in vivo breast cancer metastasis models. SAR100842 demonstrated only occasional reductions in invasive metastases in the SKOV3 and OVCAR5 ovarian cancer experimental metastasis models. Two approved drugs for IPF, nintedanib and pirfenidone, were investigated. Both were ineffective at preventing MDA-MB-231T metastasis, with no attenuation of fibrosis. In summary, metastasis-induced fibrosis is only a minor component of metastasis in untreated progressive breast cancer. LPAR1 antagonists, despite in vitro evidence of specificity and efficacy, were ineffective in vivo as oral agents, as were approved IPF drugs. The data argue against LPAR1 and fibrosis as monotherapy targets for metastasis prevention in triple-negative breast cancer and ovarian cancer.

Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk

PubMed Central

Schonberg, Mara A.; Li, Vicky W.; Eliassen, A. Heather; Davis, Roger B.; LaCroix, Andrea Z.; McCarthy, Ellen P.; Rosner, Bernard A.; Chlebowski, Rowan T.; Hankinson, Susan E.; Marcantonio, Edward R.; Ngo, Long H.

2016-01-01

Purpose Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death. Methods We included 73,066 women who completed the 2004 Nurses’ Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors), 7 risk factors for non-breast cancer death (comorbidities, functional dependency), and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women’s Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years). Results Within 5 years, 1.8% of NHS participants were diagnosed with breast cancer (vs. 2.0% in WHI-ES, p=0.02) and 6.6% experienced non-breast cancer death (vs. 5.2% in WHI-ES, p<0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model’s c-statistic was 0.61 (95% CI [0.60–0.63]) in NHS and 0.57 (0.55–0.58) in WHI-ES. On average our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88–0.97]). Conclusions We developed a novel prediction model that factors in postmenopausal women’s individualized competing risks of non-breast cancer death when estimating breast cancer risk. PMID:27770283

Breast Cancer

MedlinePlus

... the body. Breast cancer is the second most common cancer among women (after skin cancer). The good news is that the rate of death from ... is removed during surgery. Surgery is the most common treatment for breast ... effects on your body. Take good care of yourself. Eat a healthy diet, get ...

Breast density and parenchymal texture measures as potential risk factors for estrogen-receptor positive breast cancer

NASA Astrophysics Data System (ADS)

Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina

2014-03-01

Accurate assessment of a woman's risk to develop specific subtypes of breast cancer is critical for appropriate utilization of chemopreventative measures, such as with tamoxifen in preventing estrogen-receptor positive breast cancer. In this context, we investigate quantitative measures of breast density and parenchymal texture, measures of glandular tissue content and tissue structure, as risk factors for estrogen-receptor positive (ER+) breast cancer. Mediolateral oblique (MLO) view digital mammograms of the contralateral breast from 106 women with unilateral invasive breast cancer were retrospectively analyzed. Breast density and parenchymal texture were analyzed via fully-automated software. Logistic regression with feature selection and was performed to predict ER+ versus ER- cancer status. A combined model considering all imaging measures extracted was compared to baseline models consisting of density-alone and texture-alone features. Area under the curve (AUC) of the receiver operating characteristic (ROC) and Delong's test were used to compare the models' discriminatory capacity for receptor status. The density-alone model had a discriminatory capacity of 0.62 AUC (p=0.05). The texture-alone model had a higher discriminatory capacity of 0.70 AUC (p=0.001), which was not significantly different compared to the density-alone model (p=0.37). In contrast the combined density-texture logistic regression model had a discriminatory capacity of 0.82 AUC (p<0.001), which was statistically significantly higher than both the density-alone (p<0.001) and texture-alone regression models (p=0.04). The combination of breast density and texture measures may have the potential to identify women specifically at risk for estrogen-receptor positive breast cancer and could be useful in triaging women into appropriate risk-reduction strategies.

Exogenous and endogenous hormones and breast cancer

PubMed Central

ChenMD, Wendy Y.

2008-01-01

Exposure to higher levels of both exogenous and endogenous hormone is associated with breast cancer risk. Because of the association between breast cancer and HRT, only the minimal duration of HRT use is recommended for symptom control, and it is not recommended for chronic disease management. Current research issues include the role of progestins, other types of HRT, duration of unopposed estrogen use, and characteristics of cancers that develop on HRT. Circulating sex steroid levels are associated with breast cancer risk, but multiple issues need to be addressed before they are used routinely in clinical practice. Current research issues include measurement of levels for routine clinical practice, integration with standard breast cancer risk models and genetic polymorphism data, and applicability to estrogen-receptor-negative cancers. PMID:18971119

Breast Cancer Knowledge, Perception and Breast Self- Examination Practices among Yemeni Women: an Application of the Health Belief Model.

PubMed

Al-Sakkaf, Khaled Abdulla; Basaleem, Huda Omer

2016-01-01

The incidence of breast cancer is rapidly increasing in Yemen with recent indications of constituting one-third of female cancers. The main problem in Yemen remains very late presentation of breast cancer, most of which should have been easily recognisable. Since stage of disease at diagnosis is the most important prognostic variable, early diagnosis is an important option to be considered for control of breast cancer in low resourced settings like Yemen. In the present study, we aimed at describing breast cancer knowledge, perceptions and breast self-examination (BSE) practices among a sample of Yemeni women. This cross-sectional study covered 400 women attending four reproductive health centres in Aden, Yemen through face-to-face interview using a structured questionnaire during April - July 2014. We collected data on sociodemographic characteristics, knowledge about breast cancer, and screening practices as well as respondents' perceptions based on the five sub scales of the Health Belief Model (HBM): perceived susceptibility; perceived severity; perceived barriers; perceived benefits; and self-efficacy. The response format was a fivepoint Likert scale. Statistical Package for Social Sciences (SPSS 20) was used for statistical analysis. Statistical significance was set at p<0.05. Logistic regression analysis was conducted with BSE as a dependent variable. The mean age of women was 26.5 (S.D=5.6) years. The majority (89.0%) had never ever performed any screening. Two-thirds of respondents had poor knowledge. Perceived BSE benefits and self-efficacy and lower BSE barriers perception were significant independent predictors of BSE practice. Poor knowledge and inadequate BSE practices are prevailing in Yemen. The need for implementing culturally sensitive targeted education measures is mandatory in the effort to improve early detection and reduce the burden of breast cancer.

Prevention of breast cancer.

PubMed

Olver, Ian N

2016-11-21

Modifiable lifestyle factors may reduce the risk of developing breast cancer. Obesity is associated particularly with post-menopausal breast cancer. Diet is important, and exercise equivalent to running for up to 8 hours each week reduces the risk of breast cancer, both in its own right and through reducing obesity. Alcohol consumption may be responsible for 5.8% of breast cancers in Australia and it is recommended to reduce this to two standard drinks per day. Drinking alcohol and smoking increases the risk for breast cancer and, therefore, it is important to quit tobacco smoking. Prolonged use of combined oestrogen and progesterone hormone replacement therapy and oral contraceptives may increase breast cancer risk and this must be factored into individual decisions about their use. Ionising radiation, either from diagnostic or therapeutic radiation or through occupational exposure, is associated with a high incidence of breast cancer and exposure may be reduced in some cases. Tamoxifen chemoprevention may reduce the incidence of oestrogen receptor positive cancer in 51% of women with high risk of breast cancer. Uncommon but serious side effects include thromboembolism and uterine cancer. Raloxifene, which can also reduce osteoporosis, can be used in post-menopausal women and is not associated with the development of uterine cancer. Surgical prophylaxis with bilateral mastectomy and salpingo-oophorectomy can reduce the risk of breast cancer in patients carrying BRCA1 or BRCA2 mutations. For preventive treatments, mammographic screening can identify other women at high risk.

Graphs to estimate an individualized risk of breast cancer.

PubMed

Benichou, J; Gail, M H; Mulvihill, J J

1996-01-01

Clinicians who counsel women about their risk for developing breast cancer need a rapid method to estimate individualized risk (absolute risk), as well as the confidence limits around that point. The Breast Cancer Detection Demonstration Project (BCDDP) model (sometimes called the Gail model) assumes no genetic model and simultaneously incorporates five risk factors, but involves cumbersome calculations and interpolations. This report provides graphs to estimate the absolute risk of breast cancer from the BCDDP model. The BCDDP recruited 280,000 women from 1973 to 1980 who were monitored for 5 years. From this cohort, 2,852 white women developed breast cancer and 3,146 controls were selected, all with complete risk-factor information. The BCDDP model, previously developed from these data, was used to prepare graphs that relate a specific summary relative-risk estimate to the absolute risk of developing breast cancer over intervals of 10, 20, and 30 years. Once a summary relative risk is calculated, the appropriate graph is chosen that shows the 10-, 20-, or 30-year absolute risk of developing breast cancer. A separate graph gives the 95% confidence limits around the point estimate of absolute risk. Once a clinician rules out a single gene trait that predisposes to breast cancer and elicits information on age and four risk factors, the tables and figures permit an estimation of a women's absolute risk of developing breast cancer in the next three decades. These results are intended to be applied to women who undergo regular screening. They should be used only in a formal counseling program to maximize a woman's understanding of the estimates and the proper use of them.

Adherence to cancer prevention guidelines and risk of breast cancer.

PubMed

Catsburg, Chelsea; Miller, Anthony B; Rohan, Thomas E

2014-11-15

Healthy eating patterns and keeping physically active are potentially more important for chronic disease prevention than intake or exclusion of specific food items or nutrients. To this end, many health organizations routinely publish dietary and lifestyle recommendations aimed at preventing chronic disease. Using data from the Canadian National Breast Screening Study, we investigated the association between breast cancer risk and adherence to two sets of guidelines specific for cancer prevention, namely the American Cancer Society (ACS) Guidelines and the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) Recommendations. At baseline, 49,613 women completed dietary and lifestyle questionnaires and height and weight measurements were taken. During a mean follow-up of 16.6 years, 2,503 incident cases of breast cancer were ascertained. Cox proportional hazard models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of meeting each guideline, and number of guidelines met, with breast cancer risk. The two sets of guidelines yielded similar results. Specifically, adherence to all six ACS guidelines was associated with a 31% reduction in breast cancer risk when compared to subjects adhering to at most one guideline (HR=0.69; 95% CI=0.49-0.97); similarly, adherence to six or seven of the WCRF/AICR guidelines was also associated with a 31% reduction in breast cancer risk (HR=0.69; 95% CI=0.47-1.00). Under either classification, meeting each additional guideline was associated with a 4-6% reduction in breast cancer risk. These results suggest that adherence to cancer prevention guidelines is associated with a reduced risk of breast cancer. © 2014 UICC.

Chapter 27 -- Breast Cancer Genomics, Section VI, Pathology and Biological Markers of Invasive Breast Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spellman, Paul T.; Heiser, Laura; Gray, Joe W.

2009-06-18

Breast cancer is predominantly a disease of the genome with cancers arising and progressing through accumulation of aberrations that alter the genome - by changing DNA sequence, copy number, and structure in ways that that contribute to diverse aspects of cancer pathophysiology. Classic examples of genomic events that contribute to breast cancer pathophysiology include inherited mutations in BRCA1, BRCA2, TP53, and CHK2 that contribute to the initiation of breast cancer, amplification of ERBB2 (formerly HER2) and mutations of elements of the PI3-kinase pathway that activate aspects of epidermal growth factor receptor (EGFR) signaling and deletion of CDKN2A/B that contributes tomore » cell cycle deregulation and genome instability. It is now apparent that accumulation of these aberrations is a time-dependent process that accelerates with age. Although American women living to an age of 85 have a 1 in 8 chance of developing breast cancer, the incidence of cancer in women younger than 30 years is uncommon. This is consistent with a multistep cancer progression model whereby mutation and selection drive the tumor's development, analogous to traditional Darwinian evolution. In the case of cancer, the driving events are changes in sequence, copy number, and structure of DNA and alterations in chromatin structure or other epigenetic marks. Our understanding of the genetic, genomic, and epigenomic events that influence the development and progression of breast cancer is increasing at a remarkable rate through application of powerful analysis tools that enable genome-wide analysis of DNA sequence and structure, copy number, allelic loss, and epigenomic modification. Application of these techniques to elucidation of the nature and timing of these events is enriching our understanding of mechanisms that increase breast cancer susceptibility, enable tumor initiation and progression to metastatic disease, and determine therapeutic response or resistance. These studies also

Adolescent meat intake and breast cancer risk.

PubMed

Farvid, Maryam S; Cho, Eunyoung; Chen, Wendy Y; Eliassen, A Heather; Willett, Walter C

2015-04-15

The breast is particularly vulnerable to carcinogenic influences during adolescence due to rapid proliferation of mammary cells and lack of terminal differentiation. We investigated consumption of adolescent red meat and other protein sources in relation to breast cancer risk in the Nurses' Health Study II cohort. We followed prospectively 44,231 women aged 33-52 years who, in 1998, completed a detailed questionnaire about diet during adolescence. Relative risks (RR) and 95% confidence intervals (95%CI) were estimated using Cox proportional hazard regression. We documented 1132 breast cancer cases during 13-year follow-up. In multivariable Cox regression models with major breast cancer risk factors adjustment, greater consumption of total red meat in adolescence was significantly associated with higher premenopausal breast cancer risk (highest vs. lowest quintiles, RR, 1.43; 95%CI, 1.05-1.94; Ptrend  = 0.007), but not postmenopausal breast cancer. Adolescent intake of poultry was associated with lower risk of breast cancer overall (RR, 0.76; 95%CI, 0.60-0.97; for each serving/day). Adolescent intakes of iron, heme iron, fish, eggs, legumes and nuts were not associated with breast cancer. Replacement of one serving/day of total red meat with one serving of combination of poultry, fish, legumes, and nuts was associated with a 15% lower risk of breast cancer overall (RR, 0.85; 95%CI, 0.74-0.96) and a 23% lower risk of premenopausal breast cancer (RR, 0.77; 95%CI, 0.64-0.92). In conclusion, higher consumption of red meat during adolescence was associated with premenopausal breast cancer. Substituting other dietary protein sources for red meat in adolescent diet may decrease premenopausal breast cancer risk. © 2014 UICC.

Comparison of Weibull and Lognormal Cure Models with Cox in the Survival Analysis Of Breast Cancer Patients in Rafsanjan.

PubMed

Hoseini, Mina; Bahrampour, Abbas; Mirzaee, Moghaddameh

2017-02-16

Breast cancer is the most common cancer after lung cancer and the second cause of death. In this study we compared Weibull and Lognormal Cure Models with Cox regression on the survival of breast cancer. A cohort study. The current study retrospective cohort study was conducted on 140 patients referred to Ali Ibn Abitaleb Hospital, Rafsanjan southeastern Iran from 2001 to 2015 suffering from breast cancer. We determined and analyzed the effective survival causes by different models using STATA14. According to AIC, log-normal model was more consistent than Weibull. In the multivariable Lognormal model, the effective factors like smoking, second -hand smoking, drinking herbal tea and the last breast-feeding period were included. In addition, using Cox regression factors of significant were the disease grade, size of tumor and its metastasis (p-value<0.05). As Rafsanjan is surrounded by pistachio orchards and pesticides applied by farmers, people of this city are exposed to agricultural pesticides and its harmful consequences. The effect of the pesticide on breast cancer was studied and the results showed that the effect of pesticides on breast cancer was not in agreement with the models used in this study. Based on different methods for survival analysis, researchers can decide how they can reach a better conclusion. This comparison indicates the result of semi-parametric Cox method is closer to clinical experiences evidences.

Multivitamin and mineral use and breast cancer mortality in older women with invasive breast cancer in the women's health initiative

PubMed Central

McGinn, A. P.; Budrys, N.; Chlebowski, R.; Ho, G. Y.; Johnson, K. C.; Lane, D. S.; Li, W.; Neuhouser, M. L.; Saquib, J.; Shikany, J. M.; Song, Y.; Thomson, C.

2014-01-01

Multivitamin use is common in the United States. It is not known whether multivitamins with minerals supplements (MVM) used by women already diagnosed with invasive breast cancer would affect their breast cancer mortality risk. To determine prospectively the effects of MVM use on breast cancer mortality in postmenopausal women diagnosed with invasive breast cancer, a prospective cohort study was conducted of 7,728 women aged 50–79 at enrollment in the women's health initiative (WHI) in 40 clinical sites across the United States diagnosed with incident invasive breast cancer during WHI and followed for a mean of 7.1 years after breast cancer diagnosis. Use of MVM supplements was assessed at WHI baseline visit and at visit closest to breast cancer diagnosis, obtained from vitamin pill bottles brought to clinic visit. Outcome was breast cancer mortality. Hazard ratios and 95 % confidence intervals (CIs) for breast cancer mortality comparing MVM users to non-users were estimated using Cox proportional hazard regression models. Analyses using propensity to take MVM were done to adjust for potential differences in characteristics of MVM users versus non-users. At baseline, 37.8 % of women reported MVM use. After mean post-diagnosis follow-up of 7.1 ± 4.1 (SD) years, there were 518 (6.7 %) deaths from breast cancer. In adjusted analyses, breast cancer mortality was 30 % lower in MVM users as compared to non-users (HR = 0.70; 95 % CI 0.55, 0.91). This association was highly robust and persisted after multiple adjustments for potential confounding variables and in propensity score matched analysis (HR = 0.76; 95 % CI 0.60–0.96). Postmenopausal women with invasive breast cancer using MVM had lower breast cancer mortality than non-users. The results suggest a possible role for daily MVM use in attenuating breast cancer mortality in women with invasive breast cancer but the findings require confirmation. PMID:24104882

Multivitamin and mineral use and breast cancer mortality in older women with invasive breast cancer in the women's health initiative.

PubMed

Wassertheil-Smoller, S; McGinn, A P; Budrys, N; Chlebowski, R; Ho, G Y; Johnson, K C; Lane, D S; Li, W; Neuhouser, M L; Saquib, J; Shikany, J M; Song, Y; Thomson, C

2013-10-01

Multivitamin use is common in the United States. It is not known whether multivitamins with minerals supplements (MVM) used by women already diagnosed with invasive breast cancer would affect their breast cancer mortality risk. To determine prospectively the effects of MVM use on breast cancer mortality in postmenopausal women diagnosed with invasive breast cancer, a prospective cohort study was conducted of 7,728 women aged 50-79 at enrollment in the women's health initiative (WHI) in 40 clinical sites across the United States diagnosed with incident invasive breast cancer during WHI and followed for a mean of 7.1 years after breast cancer diagnosis. Use of MVM supplements was assessed at WHI baseline visit and at visit closest to breast cancer diagnosis, obtained from vitamin pill bottles brought to clinic visit. Outcome was breast cancer mortality. Hazard ratios and 95 % confidence intervals (CIs) for breast cancer mortality comparing MVM users to non-users were estimated using Cox proportional hazard regression models. Analyses using propensity to take MVM were done to adjust for potential differences in characteristics of MVM users versus non-users. At baseline, 37.8 % of women reported MVM use. After mean post-diagnosis follow-up of 7.1 ± 4.1 (SD) years, there were 518 (6.7 %) deaths from breast cancer. In adjusted analyses, breast cancer mortality was 30 % lower in MVM users as compared to non-users (HR = 0.70; 95 % CI 0.55, 0.91). This association was highly robust and persisted after multiple adjustments for potential confounding variables and in propensity score matched analysis (HR = 0.76; 95 % CI 0.60-0.96). Postmenopausal women with invasive breast cancer using MVM had lower breast cancer mortality than non-users. The results suggest a possible role for daily MVM use in attenuating breast cancer mortality in women with invasive breast cancer but the findings require confirmation.

Breast Cancer Screening in an Era of Personalized Regimens

PubMed Central

Onega, Tracy; Beaber, Elisabeth F.; Sprague, Brian L.; Barlow, William E.; Haas, Jennifer S.; Tosteson, Anna N.A.; Schnall, Mitchell D.; Armstrong, Katrina; Schapira, Marilyn M.; Geller, Berta; Weaver, Donald L.; Conant, Emily F.

2014-01-01

Breast cancer screening holds a prominent place in public health, health care delivery, policy, and women’s health care decisions. Several factors are driving shifts in how population-based breast cancer screening is approached, including advanced imaging technologies, health system performance measures, health care reform, concern for “overdiagnosis,” and improved understanding of risk. Maximizing benefits while minimizing the harms of screening requires moving from a “1-size-fits-all” guideline paradigm to more personalized strategies. A refined conceptual model for breast cancer screening is needed to align women’s risks and preferences with screening regimens. A conceptual model of personalized breast cancer screening is presented herein that emphasizes key domains and transitions throughout the screening process, as well as multilevel perspectives. The key domains of screening awareness, detection, diagnosis, and treatment and survivorship are conceptualized to function at the level of the patient, provider, facility, health care system, and population/policy arena. Personalized breast cancer screening can be assessed across these domains with both process and outcome measures. Identifying, evaluating, and monitoring process measures in screening is a focus of a National Cancer Institute initiative entitled PROSPR (Population-based Research Optimizing Screening through Personalized Regimens), which will provide generalizable evidence for a risk-based model of breast cancer screening, The model presented builds on prior breast cancer screening models and may serve to identify new measures to optimize benefits-to-harms tradeoffs in population-based screening, which is a timely goal in the era of health care reform. PMID:24830599

Estrogen Metabolism and Exposure in a Genotypic-Phenotypic Model for Breast Cancer Risk Prediction

PubMed Central

Crooke, Philip S.; Justenhoven, Christina; Brauch, Hiltrud; Dawling, Sheila; Roodi, Nady; Higginbotham, Kathryn S. P.; Plummer, W. Dale; Schuyler, Peggy A.; Sanders, Melinda E; Page, David L.; Smith, Jeffrey R.; Dupont, William D.; Parl, Fritz F.

2012-01-01

Background Current models of breast cancer risk prediction do not directly reflect mammary estrogen metabolism or genetic variability in exposure to carcinogenic estrogen metabolites. Methods We developed a model that simulates the kinetic effect of genetic variants of the enzymes CYP1A1, CYP1B1, and COMT on the production of the main carcinogenic estrogen metabolite, 4-hydroxyestradiol (4-OHE2), expressed as area under the curve metric (4-OHE2-AUC). The model also incorporates phenotypic factors (age, body mass index, hormone replacement therapy, oral contraceptives, family history), which plausibly influence estrogen metabolism and the production of 4-OHE2. We applied the model to two independent, population-based breast cancer case-control groups, the German GENICA study (967 cases, 971 controls) and the Nashville Breast Cohort (NBC; 465 cases, 885 controls). Results In the GENICA study, premenopausal women at the 90th percentile of 4-OHE2-AUC among control subjects had a risk of breast cancer that was 2.30 times that of women at the 10th control 4-OHE2-AUC percentile (95% CI 1.7 – 3.2, P = 2.9 × 10−7). This relative risk was 1.89 (95% CI 1.5 – 2.4, P = 2.2 × 10−8) in postmenopausal women. In the NBC, this relative risk in postmenopausal women was 1.81 (95% CI 1.3 – 2.6, P = 7.6 × 10−4), which increased to 1.83 (95% CI 1.4 – 2.3, P = 9.5 × 10−7) when a history of proliferative breast disease was included in the model. Conclusions The model combines genotypic and phenotypic factors involved in carcinogenic estrogen metabolite production and cumulative estrogen exposure to predict breast cancer risk. Impact The estrogen carcinogenesis-based model has the potential to provide personalized risk estimates. PMID:21610218

Five-Year Risk of Interval-Invasive Second Breast Cancer

PubMed Central

Buist, Diana S. M.; Houssami, Nehmat; Dowling, Emily C.; Halpern, Elkan F.; Gazelle, G. Scott; Lehman, Constance D.; Henderson, Louise M.; Hubbard, Rebecca A.

2015-01-01

Background: Earlier detection of second breast cancers after primary breast cancer (PBC) treatment improves survival, yet mammography is less accurate in women with prior breast cancer. The purpose of this study was to examine women presenting clinically with second breast cancers after negative surveillance mammography (interval cancers), and to estimate the five-year risk of interval-invasive second cancers for women with varying risk profiles. Methods: We evaluated a prospective cohort of 15 114 women with 47 717 surveillance mammograms diagnosed with stage 0-II unilateral PBC from 1996 through 2008 at facilities in the Breast Cancer Surveillance Consortium. We used discrete time survival models to estimate the association between odds of an interval-invasive second breast cancer and candidate predictors, including demographic, PBC, and imaging characteristics. All statistical tests were two-sided. Results: The cumulative incidence of second breast cancers after five years was 54.4 per 1000 women, with 325 surveillance-detected and 138 interval-invasive second breast cancers. The five-year risk of interval-invasive second cancer for women with referent category characteristics was 0.60%. For women with the most and least favorable profiles, the five-year risk ranged from 0.07% to 6.11%. Multivariable modeling identified grade II PBC (odds ratio [OR] = 1.95, 95% confidence interval [CI] = 1.15 to 3.31), treatment with lumpectomy without radiation (OR = 3.27, 95% CI = 1.91 to 5.62), interval PBC presentation (OR = 2.01, 95% CI 1.28 to 3.16), and heterogeneously dense breasts on mammography (OR = 1.54, 95% CI = 1.01 to 2.36) as independent predictors of interval-invasive second breast cancers. Conclusions: PBC diagnosis and treatment characteristics contribute to variation in subsequent-interval second breast cancer risk. Consideration of these factors may be useful in developing tailored post-treatment imaging surveillance plans. PMID:25904721

SIX1 induces lymphangiogenesis and metastasis via upregulation of VEGF-C in mouse models of breast cancer

PubMed Central

Wang, Chu-An; Jedlicka, Paul; Patrick, Aaron N.; Micalizzi, Douglas S.; Lemmer, Kimberly C.; Deitsch, Erin; Casás-Selves, Matias; Harrell, J. Chuck; Ford, Heide L.

2012-01-01

An association between lymph node metastasis and poor prognosis in breast cancer was observed decades ago. However, the mechanisms by which tumor cells infiltrate the lymphatic system are not completely understood. Recently, it has been proposed that the lymphatic system has an active role in metastatic dissemination and that tumor-secreted growth factors stimulate lymphangiogenesis. We therefore investigated whether SIX1, a homeodomain-containing transcription factor previously associated in breast cancer with lymph node positivity, was involved in lymphangiogenesis and lymphatic metastasis. In a model in which human breast cancer cells were injected into immune-compromised mice, we found that SIX1 expression promoted peritumoral and intratumoral lymphangiogenesis, lymphatic invasion, and distant metastasis of breast cancer cells. SIX1 induced transcription of the prolymphangiogenic factor VEGF-C, and this was required for lymphangiogenesis and lymphatic metastasis. Using a mouse mammary carcinoma model, we found that VEGF-C was not sufficient to mediate all the metastatic effects of SIX1, indicating that SIX1 acts through additional, VEGF-C–independent pathways. Finally, we verified the clinical significance of this prometastatic SIX1/VEGF-C axis by demonstrating coexpression of SIX1 and VEGF-C in human breast cancer. These data define a critical role for SIX1 in lymphatic dissemination of breast cancer cells, providing a direct mechanistic explanation for how VEGF-C expression is upregulated in breast cancer, resulting in lymphangiogenesis and metastasis. PMID:22466647

Combining Gene Signatures Improves Prediction of Breast Cancer Survival

PubMed Central

Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

2011-01-01

Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

[CHEK2-mutation in Dutch breast cancer families: expanding genetic testing for breast cancer].

PubMed

Adank, Muriel A; Hes, Frederik J; van Zelst-Stams, Wendy A G; van den Tol, M Petrousjka; Seynaeve, Caroline; Oosterwijk, Jan C

2015-01-01

In the majority of breast cancer families, DNA testing does not show BRCA1 or BRCA2 mutations and the genetic cause of breast cancer remains unexplained. Routine testing for the CHEK2*1100delC mutation has recently been introduced in breast cancer families in the Netherlands. The 1100delC mutation in the CHEK2-gene may explain the occurrence of breast cancer in about 5% of non-BRCA1/2 families in the Netherlands. In the general population the CHEK2*1100delC mutation confers a slightly increased breast cancer risk, but in a familial breast cancer setting this risk is between 35-55% for first degree female carriers. Female breast cancer patients with the CHEK2*1100delC mutation are at increased risk of contralateral breast cancer and may have a less favourable prognosis. Female heterozygous CHEK2*1100delC mutation carriers are offered annual mammography and specialist breast surveillance between the ages of 35-60 years. Prospective research in CHEK2-positive families is essential in order to develop more specific treatment and screening strategies.

DNA repair variants and breast cancer risk.

PubMed

Grundy, Anne; Richardson, Harriet; Schuetz, Johanna M; Burstyn, Igor; Spinelli, John J; Brooks-Wilson, Angela; Aronson, Kristan J

2016-05-01

A functional DNA repair system has been identified as important in the prevention of tumour development. Previous studies have hypothesized that common polymorphisms in DNA repair genes could play a role in breast cancer risk and also identified the potential for interactions between these polymorphisms and established breast cancer risk factors such as physical activity. Associations with breast cancer risk for 99 single nucleotide polymorphisms (SNPs) from genes in ten DNA repair pathways were examined in a case-control study including both Europeans (644 cases, 809 controls) and East Asians (299 cases, 160 controls). Odds ratios in both additive and dominant genetic models were calculated separately for participants of European and East Asian ancestry using multivariate logistic regression. The impact of multiple comparisons was assessed by correcting for the false discovery rate within each DNA repair pathway. Interactions between several breast cancer risk factors and DNA repair SNPs were also evaluated. One SNP (rs3213282) in the gene XRCC1 was associated with an increased risk of breast cancer in the dominant model of inheritance following adjustment for the false discovery rate (P < 0.05), although no associations were observed for other DNA repair SNPs. Interactions of six SNPs in multiple DNA repair pathways with physical activity were evident prior to correction for FDR, following which there was support for only one of the interaction terms (P < 0.05). No consistent associations between variants in DNA repair genes and breast cancer risk or their modification by breast cancer risk factors were observed. © 2016 Wiley Periodicals, Inc.

Competing risks to breast cancer mortality in Catalonia

PubMed Central

Vilaprinyo, Ester; Gispert, Rosa; Martínez-Alonso, Montserrat; Carles, Misericòrdia; Pla, Roger; Espinàs, Josep-Alfons; Rué, Montserrat

2008-01-01

Background Breast cancer mortality has experienced important changes over the last century. Breast cancer occurs in the presence of other competing risks which can influence breast cancer incidence and mortality trends. The aim of the present work is: 1) to assess the impact of breast cancer deaths among mortality from all causes in Catalonia (Spain), by age and birth cohort and 2) to estimate the risk of death from other causes than breast cancer, one of the inputs needed to model breast cancer mortality reduction due to screening or therapeutic interventions. Methods The multi-decrement life table methodology was used. First, all-cause mortality probabilities were obtained by age and cohort. Then mortality probability for breast cancer was subtracted from the all-cause mortality probabilities to obtain cohort life tables for causes other than breast cancer. These life tables, on one hand, provide an estimate of the risk of dying from competing risks, and on the other hand, permit to assess the impact of breast cancer deaths on all-cause mortality using the ratio of the probability of death for causes other than breast cancer by the all-cause probability of death. Results There was an increasing impact of breast cancer on mortality in the first part of the 20th century, with a peak for cohorts born in 1945–54 in the 40–49 age groups (for which approximately 24% of mortality was due to breast cancer). Even though for cohorts born after 1955 there was only information for women under 50, it is also important to note that the impact of breast cancer on all-cause mortality decreased for those cohorts. Conclusion We have quantified the effect of removing breast cancer mortality in different age groups and birth cohorts. Our results are consistent with US findings. We also have obtained an estimate of the risk of dying from competing-causes mortality, which will be used in the assessment of the effect of mammography screening on breast cancer mortality in Catalonia

Dutch digital breast cancer screening: implications for breast cancer care.

PubMed

Timmers, Johanna M; den Heeten, Gerard J; Adang, Eddy M; Otten, Johannes D; Verbeek, André L; Broeders, Mireille J

2012-12-01

In comparison to other European population-based breast cancer screening programmes, the Dutch programme has a low referral rate, similar breast cancer detection and a high breast cancer mortality reduction. The referral rate in the Netherlands has increased over time and is expected to rise further, mainly following nationwide introduction of digital mammography, completed in 2010. This study explores the consequences of the introduction of digital mammography on the balance between referral rate, detection of breast cancer, diagnostic work-up and associated costs. Detailed information on diagnostic work-up (chart review) was obtained from referred women (n = 988) in 2000-06 (100% analogue mammography) and 2007 (75% digital mammography) in Nijmegen, the Netherlands. The average referral rate increased from 15 (2000-06) to 34 (2007) per 1000 women screened. The number of breast cancers detected increased from 5.5 to 7.8 per 1000 screens, whereas the positive predictive value fell from 37% to 23%. A sharp rise in diagnostic work-up procedures and total diagnostic costs was seen. On the other hand, costs of a single work-up slightly decreased, as less surgical biopsies were performed. Our study shows that a low referral rate in combination with the introduction of digital mammography affects the balance between referral rate and detection rate and can substantially influence breast cancer care and associated costs. Referral rates in the Netherlands are now more comparable to other countries. This effect is therefore of value in countries where implementation of digital breast cancer screening has just started or is still under discussion.

Lifetime and 5 years risk of breast cancer and attributable risk factor according to Gail model in Iranian women

PubMed Central

Mohammadbeigi, Abolfazl; Mohammadsalehi, Narges; Valizadeh, Razieh; Momtaheni, Zeinab; Mokhtari, Mohsen; Ansari, Hossein

2015-01-01

Introduction: Breast cancer is the most commonly diagnosed cancers in women worldwide and in Iran. It is expected to account for 29% of all new cancers in women at 2015. This study aimed to assess the 5 years and lifetime risk of breast cancer according to Gail model, and to evaluate the effect of other additional risk factors on the Gail risk. Materials and Methods: A cross sectional study conducted on 296 women aged more than 34-year-old in Qom, Center of Iran. Breast Cancer Risk Assessment Tool calculated the Gail risk for each subject. Data were analyzed by paired t-test, independent t-test, and analysis of variance in bivariate approach to evaluate the effect of each factor on Gail risk. Multiple linear regression models with stepwise method were used to predict the effect of each variable on the Gail risk. Results: The mean age of the participants was 47.8 ± 8.8-year-old and 47% have Fars ethnicity. The 5 years and lifetime risk was 0.37 ± 0.18 and 4.48 ± 0.925%, respectively. It was lower than the average risk in same race and age women (P < 0.001). Being single, positive family history of breast cancer, positive history of biopsy, and radiotherapy as well as using nonhormonal contraceptives were related to higher lifetime risk (P < 0.05). Moreover, a significant direct correlation observed between lifetime risk and body mass index, age of first live birth, and menarche age. While an inversely correlation observed between lifetimes risk of breast cancer and total month of breast feeding duration and age. Conclusion: Based on our results, the 5 years and lifetime risk of breast cancer according to Gail model was lower than the same race and age. Moreover, by comparison with national epidemiologic indicators about morbidity and mortality of breast cancer, it seems that the Gail model overestimate the risk of breast cancer in Iranian women. PMID:26229355

Toll Like Receptor-9 Mediated Invasion in Breast Cancer

DTIC Science & Technology

2012-07-01

cancer models, but only in triple negative breast cancer cells. In line with these...expression and“dead DNA” are biologically important in triple negative breast cancer . 15. SUBJECT TERMS None provided 16. SECURITY CLASSIFICATION OF...experiments done so far in the Specific Aim # 1: Tumor TLR9 expression has a dramatic effect on prognosis in triple negative breast cancers . The lack

The Effect of Simvastatin on Breast Cancer Cell Growth in Women With Stage I-II Breast Cancer

ClinicalTrials.gov

2018-03-02

Invasive Breast Carcinoma; Stage I Breast Cancer AJCC v7; Stage IA Breast Cancer AJCC v7; Stage IB Breast Cancer AJCC v7; Stage II Breast Cancer AJCC v6 and v7; Stage IIA Breast Cancer AJCC v6 and v7; Stage IIB Breast Cancer AJCC v6 and v7

Joint modelling of longitudinal CEA tumour marker progression and survival data on breast cancer

NASA Astrophysics Data System (ADS)

Borges, Ana; Sousa, Inês; Castro, Luis

2017-06-01

This work proposes the use of Biostatistics methods to study breast cancer in patients of Braga's Hospital Senology Unit, located in Portugal. The primary motivation is to contribute to the understanding of the progression of breast cancer, within the Portuguese population, using a more complex statistical model assumptions than the traditional analysis that take into account a possible existence of a serial correlation structure within a same subject observations. We aim to infer which risk factors aect the survival of Braga's Hospital patients, diagnosed with breast tumour. Whilst analysing risk factors that aect a tumour markers used on the surveillance of disease progression the Carcinoembryonic antigen (CEA). As survival and longitudinal processes may be associated, it is important to model these two processes together. Hence, a joint modelling of these two processes to infer on the association of these was conducted. A data set of 540 patients, along with 50 variables, was collected from medical records of the Hospital. A joint model approach was used to analyse these data. Two dierent joint models were applied to the same data set, with dierent parameterizations which give dierent interpretations to model parameters. These were used by convenience as the ones implemented in R software. Results from the two models were compared. Results from joint models, showed that the longitudinal CEA values were signicantly associated with the survival probability of these patients. A comparison between parameter estimates obtained in this analysis and previous independent survival[4] and longitudinal analysis[5][6], lead us to conclude that independent analysis brings up bias parameter estimates. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary. Results indicate that the longitudinal progression of CEA is signicantly associated with the probability of survival of these patients. Hence, an assumption of

Olaparib In Metastatic Breast Cancer

ClinicalTrials.gov

2018-03-27

Metastatic Breast Cancer; Invasive Breast Cancer; Somatic Mutation Breast Cancer (BRCA1); Somatic Mutation Breast Cancer (BRCA2); CHEK2 Gene Mutation; ATM Gene Mutation; PALB2 Gene Mutation; RAD51 Gene Mutation; BRIP1 Gene Mutation; NBN Gene Mutation

Localized morphea after breast implant for breast cancer: A case report.

PubMed

Moretti, A; Bianchi, F; Abbate, I V; Gherardi, G; Bonavita, M; Passoni, E; Nazzaro, G; Bramati, A; Dazzani, M C; Piva, S; Paternò, E; Frungillo, N; Farina, G; La Verde, N

2018-03-01

Early breast cancer follow-up guidelines for patients who underwent surgery suggest a regular and accurate clinical examination of the breast area, for an early identification of cutaneous or subcutaneous breast cancer relapse. Nonetheless, breast skin lesions arising in patients treated with mastectomy for breast cancer can be caused by several diseases. A series of diagnostic hypotheses should be considered, not only focusing on cutaneous metastasis, but also on dermatologic and systemic diseases. In February 2015, a 37-year-old patient underwent a right subcutaneous mastectomy for stage IIA breast cancer. Five months after beginning adjuvant chemotherapy, she noted hyperpigmentation and thickening of the skin on the right breast. Differential diagnosis included local relapse, skin infection, lymphoma, or primary cutaneous disease, and a skin biopsy was performed. The histopathologic specimen showed full-thickness sclerosis, with features of localized morphea. Therapy with clobetasol was prescribed, with progressive resolution of the thickness. The collaboration between many professionals in a multidisciplinary team (oncologist, dermatologist, plastic surgeon, and pathologist) was crucial to achieving the diagnosis. In the literature, some articles describe correlation between connective tissue diseases and silicone breast implants, but the pathogenetic mechanisms are unknown. We report a rare case of breast morphea after positioning a silicone implant in a patient who had undergone mastectomy. This clinical report represents an interesting model of multidisciplinary management of a patient with breast cancer who developed an uncommon dermatologic disease. Further studies are needed to clarify the association between silicone implants and breast morphea.

Breast cancer statistics, 2011.

PubMed

DeSantis, Carol; Siegel, Rebecca; Bandi, Priti; Jemal, Ahmedin

2011-01-01

In this article, the American Cancer Society provides an overview of female breast cancer statistics in the United States, including trends in incidence, mortality, survival, and screening. Approximately 230,480 new cases of invasive breast cancer and 39,520 breast cancer deaths are expected to occur among US women in 2011. Breast cancer incidence rates were stable among all racial/ethnic groups from 2004 to 2008. Breast cancer death rates have been declining since the early 1990s for all women except American Indians/Alaska Natives, among whom rates have remained stable. Disparities in breast cancer death rates are evident by state, socioeconomic status, and race/ethnicity. While significant declines in mortality rates were observed for 36 states and the District of Columbia over the past 10 years, rates for 14 states remained level. Analyses by county-level poverty rates showed that the decrease in mortality rates began later and was slower among women residing in poor areas. As a result, the highest breast cancer death rates shifted from the affluent areas to the poor areas in the early 1990s. Screening rates continue to be lower in poor women compared with non-poor women, despite much progress in increasing mammography utilization. In 2008, 51.4% of poor women had undergone a screening mammogram in the past 2 years compared with 72.8% of non-poor women. Encouraging patients aged 40 years and older to have annual mammography and a clinical breast examination is the single most important step that clinicians can take to reduce suffering and death from breast cancer. Clinicians should also ensure that patients at high risk of breast cancer are identified and offered appropriate screening and follow-up. Continued progress in the control of breast cancer will require sustained and increased efforts to provide high-quality screening, diagnosis, and treatment to all segments of the population. Copyright © 2011 American Cancer Society, Inc.

Cost-effectiveness of the Norwegian breast cancer screening program.

PubMed

van Luijt, P A; Heijnsdijk, E A M; de Koning, H J

2017-02-15

The Norwegian Breast Cancer Screening Programme (NBCSP) has a nation-wide coverage since 2005. All women aged 50-69 years are invited biennially for mammography screening. We evaluated breast cancer mortality reduction and performed a cost-effectiveness analysis, using our microsimulation model, calibrated to most recent data. The microsimulation model allows for the comparison of mortality and costs between a (hypothetical) situation without screening and a situation with screening. Breast cancer incidence in Norway had a steep increase in the early 1990s. We calibrated the model to simulate this increase and included recent costs for screening, diagnosis and treatment of breast cancer and travel and productivity loss. We estimate a 16% breast cancer mortality reduction for a cohort of women, invited to screening, followed over their complete lifetime. Cost-effectiveness is estimated at NOK 112,162 per QALY gained, when taking only direct medical costs into account (the cost of the buses, examinations, and invitations). We used a 3.5% annual discount rate. Cost-effectiveness estimates are substantially below the threshold of NOK 1,926,366 as recommended by the WHO guidelines. For the Norwegian population, which has been gradually exposed to screening, breast cancer mortality reduction for women exposed to screening is increasing and is estimated to rise to ∼30% in 2020 for women aged 55-80 years. The NBCSP is a highly cost-effective measure to reduce breast cancer specific mortality. We estimate a breast cancer specific mortality reduction of 16-30%, at the cost of 112,162 NOK per QALY gained. © 2016 UICC.

Tailoring Breast Cancer Screening Intervals by Breast Density and Risk for Women Aged 50 Years or Older: Collaborative Modeling of Screening Outcomes.

PubMed

Trentham-Dietz, Amy; Kerlikowske, Karla; Stout, Natasha K; Miglioretti, Diana L; Schechter, Clyde B; Ergun, Mehmet Ali; van den Broek, Jeroen J; Alagoz, Oguzhan; Sprague, Brian L; van Ravesteyn, Nicolien T; Near, Aimee M; Gangnon, Ronald E; Hampton, John M; Chandler, Young; de Koning, Harry J; Mandelblatt, Jeanne S; Tosteson, Anna N A

2016-11-15

Biennial screening is generally recommended for average-risk women aged 50 to 74 years, but tailored screening may provide greater benefits. To estimate outcomes for various screening intervals after age 50 years based on breast density and risk for breast cancer. Collaborative simulation modeling using national incidence, breast density, and screening performance data. United States. Women aged 50 years or older with various combinations of breast density and relative risk (RR) of 1.0, 1.3, 2.0, or 4.0. Annual, biennial, or triennial digital mammography screening from ages 50 to 74 years (vs. no screening) and ages 65 to 74 years (vs. biennial digital mammography from ages 50 to 64 years). Lifetime breast cancer deaths, life expectancy and quality-adjusted life-years (QALYs), false-positive mammograms, benign biopsy results, overdiagnosis, cost-effectiveness, and ratio of false-positive results to breast cancer deaths averted. Screening benefits and overdiagnosis increase with breast density and RR. False-positive mammograms and benign results on biopsy decrease with increasing risk. Among women with fatty breasts or scattered fibroglandular density and an RR of 1.0 or 1.3, breast cancer deaths averted were similar for triennial versus biennial screening for both age groups (50 to 74 years, median of 3.4 to 5.1 vs. 4.1 to 6.5 deaths averted; 65 to 74 years, median of 1.5 to 2.1 vs. 1.8 to 2.6 deaths averted). Breast cancer deaths averted increased with annual versus biennial screening for women aged 50 to 74 years at all levels of breast density and an RR of 4.0, and those aged 65 to 74 years with heterogeneously or extremely dense breasts and an RR of 4.0. However, harms were almost 2-fold higher. Triennial screening for the average-risk subgroup and annual screening for the highest-risk subgroup cost less than $100 000 per QALY gained. Models did not consider women younger than 50 years, those with an RR less than 1, or other imaging methods. Average-risk women

Screening for Breast Cancer.

PubMed

Niell, Bethany L; Freer, Phoebe E; Weinfurtner, Robert Jared; Arleo, Elizabeth Kagan; Drukteinis, Jennifer S

2017-11-01

The goal of screening is to detect breast cancers when still curable to decrease breast cancer-specific mortality. Breast cancer screening in the United States is routinely performed with mammography, supplemental digital breast tomosynthesis, ultrasound, and/or MR imaging. This article aims to review the most commonly used breast imaging modalities for screening, discuss how often and when to begin screening with specific imaging modalities, and examine the pros and cons of screening. By the article's end, the reader will be better equipped to have informed discussions with patients and medical professionals regarding the benefits and disadvantages of breast cancer screening. Copyright © 2017 Elsevier Inc. All rights reserved.

Breast Cancer (For Kids)

MedlinePlus

... Staying Safe Videos for Educators Search English Español Breast Cancer KidsHealth / For Kids / Breast Cancer What's in this ... for it when they are older. What Is Breast Cancer? The human body is made of tiny building ...

Depression and Anxiety Disorders among Hospitalized Women with Breast Cancer.

PubMed

Vin-Raviv, Neomi; Akinyemiju, Tomi F; Galea, Sandro; Bovbjerg, Dana H

2015-01-01

To document the prevalence of depression and anxiety disorders, and their associations with mortality among hospitalized breast cancer patients. We examined the associations between breast cancer diagnosis and the diagnoses of anxiety or depression among 4,164 hospitalized breast cancer cases matched with 4,164 non-breast cancer controls using 2006-2009 inpatient data obtained from the Nationwide Inpatient Sample database. Conditional logistic regression models were used to compute odds ratios (ORs) and 95% confidence intervals (CI) for the associations between breast cancer diagnosis and diagnoses of anxiety or depression. We also used binary logistic regression models to examine the association between diagnoses of depression or anxiety, and in-hospital mortality among breast cancer patients. We observed that breast cancer cases were less likely to have a diagnosis of depression (OR=0.63, 95% CI: 0.52-0.77), and less likely to have a diagnosis of anxiety (OR=0.68, 95% CI: 0.52-0.90) compared with controls. This association remained after controlling for race/ethnicity, residential income, insurance and residential region. Breast cancer patients with a depression diagnosis also had lower mortality (OR=0.69, 95% CI: 0.52-0.89) compared with those without a depression diagnosis, but there was no significant difference in mortality among those with and without anxiety diagnoses. Diagnoses of depression and anxiety in breast cancer patients were less prevalent than expected based on our analysis of hospitalized breast cancer patients and matched non-breast cancer controls identified in the NIS dataset using ICD-9 diagnostic codes. Results suggest that under-diagnosis of mental health problems may be common among hospitalized women with a primary diagnosis of breast cancer. Future work may fruitfully explore reasons for, and consequences of, inappropriate identification of the mental health needs of breast cancer patients.

Depression and Anxiety Disorders among Hospitalized Women with Breast Cancer

PubMed Central

Vin-Raviv, Neomi; Akinyemiju, Tomi F.; Galea, Sandro; Bovbjerg, Dana H.

2015-01-01

Purpose To document the prevalence of depression and anxiety disorders, and their associations with mortality among hospitalized breast cancer patients. Methods We examined the associations between breast cancer diagnosis and the diagnoses of anxiety or depression among 4,164 hospitalized breast cancer cases matched with 4,164 non-breast cancer controls using 2006-2009 inpatient data obtained from the Nationwide Inpatient Sample database. Conditional logistic regression models were used to compute odds ratios (ORs) and 95% confidence intervals (CI) for the associations between breast cancer diagnosis and diagnoses of anxiety or depression. We also used binary logistic regression models to examine the association between diagnoses of depression or anxiety, and in-hospital mortality among breast cancer patients. Results We observed that breast cancer cases were less likely to have a diagnosis of depression (OR=0.63, 95% CI: 0.52-0.77), and less likely to have a diagnosis of anxiety (OR=0.68, 95% CI: 0.52-0.90) compared with controls. This association remained after controlling for race/ethnicity, residential income, insurance and residential region. Breast cancer patients with a depression diagnosis also had lower mortality (OR=0.69, 95% CI: 0.52-0.89) compared with those without a depression diagnosis, but there was no significant difference in mortality among those with and without anxiety diagnoses. Conclusion Diagnoses of depression and anxiety in breast cancer patients were less prevalent than expected based on our analysis of hospitalized breast cancer patients and matched non-breast cancer controls identified in the NIS dataset using ICD-9 diagnostic codes. Results suggest that under-diagnosis of mental health problems may be common among hospitalized women with a primary diagnosis of breast cancer. Future work may fruitfully explore reasons for, and consequences of, inappropriate identification of the mental health needs of breast cancer patients. PMID

Cumulative risk of breast cancer screening outcomes according to the presence of previous benign breast disease and family history of breast cancer: supporting personalised screening.

PubMed

Román, M; Quintana, M J; Ferrer, J; Sala, M; Castells, X

2017-05-23

Our aim was to assess the cumulative risk of false-positive screening results, screen-detected cancer, and interval breast cancer in mammography screening among women with and without a previous benign breast disease and a family history of breast cancer. The cohort included 42 928 women first screened at the age of 50-51 years at three areas of the Spanish Screening Programme (Girona, and two areas in Barcelona) between 1996 and 2011, and followed up until December 2012. We used discrete-time survival models to estimate the cumulative risk of each screening outcome over 10 biennial screening exams. The cumulative risk of false-positive results, screen-detected breast cancer, and interval cancer was 36.6, 5.3, and 1.4 for women with a previous benign breast disease, 24.1, 6.8, and 1.6% for women with a family history of breast cancer, 37.9, 9.0, and 3.2%; for women with both a previous benign breast disease and a family history, and 23.1, 3.2, and 0.9% for women without either of these antecedents, respectively. Women with a benign breast disease or a family history of breast cancer had an increased cumulative risk of favourable and unfavourable screening outcomes than women without these characteristics. A family history of breast cancer did not increase the cumulative risk of false-positive results. Identifying different risk profiles among screening participants provides useful information to stratify women according to their individualised risk when personalised screening strategies are discussed.

Mesenchymal stem cells expressing interleukin-18 inhibit breast cancer in a mouse model.

PubMed

Liu, Xiaoyi; Hu, Jianxia; Li, Yueyun; Cao, Weihong; Wang, Yu; Ma, Zhongliang; Li, Funian

2018-05-01

Development of an improved breast cancer therapy has been an elusive goal of cancer gene therapy for a long period of time. Human mesenchymal stem cells derived from umbilical cord (hUMSCs) genetically modified with the interleukin (IL)-18 gene (hUMSCs/IL-18) were previously demonstrated to be able to suppress the proliferation, migration and invasion of breast cancer cells in vitro . In the present study, the effect of hUMSCs/IL-18 on breast cancer in a mouse model was investigated. A total of 128 mice were divided into 2 studies (the early-effect study and the late-effect study), with 4 groups in each, including the PBS-, hUMSC-, hUMSC/vector- and hUMSC/IL-18-treated groups. All treatments were injected along with 200 µl PBS. Following therapy, the tumor size, histological examination, and expression of lymphocytes, Ki-67, cluster of differentiation 31 and cytokines [interleukin (IL)-18, IL-12, interferon (IFN)-γ and TNF-α] in each group were analyzed. Proliferation of cells (assessed by measuring tumor size and Ki-67 expression) and metastasis, (by determining pulmonary and hepatic metastasis) of breast cancer cells in the hUMSC/IL-18 group were significantly decreased compared with all other groups. hUMSCs/IL-18 suppressed tumor cell proliferation by activating immunocytes and immune cytokines, decreasing the proliferation index of proliferation marker protein Ki-67 of tumor cells and inhibiting tumor angiogenesis. Furthermore, hUMSCs/IL-18 were able to induce a more marked and improved therapeutic effect in the tumor sites, particularly in early tumors. The results of the present study indicate that hUMSCs/IL-18 were able to inhibit the proliferation and metastasis of breast cancer cells in vivo , possibly leading to an approach for a novel antitumor therapy in breast cancer.

Breast reconstruction after mastectomy at a comprehensive cancer center.

PubMed

Connors, Shahnjayla K; Goodman, Melody S; Myckatyn, Terence; Margenthaler, Julie; Gehlert, Sarah

2016-01-01

Breast reconstruction after mastectomy is an integral part of breast cancer treatment that positively impacts quality of life in breast cancer survivors. Although breast reconstruction rates have increased over time, African American women remain less likely to receive breast reconstruction compared to Caucasian women. National Cancer Institute-designated Comprehensive Cancer Centers, specialized institutions with more standardized models of cancer treatment, report higher breast reconstruction rates than primary healthcare facilities. Whether breast reconstruction disparities are reduced for women treated at comprehensive cancer centers is unclear. The purpose of this study was to further investigate breast reconstruction rates and determinants at a comprehensive cancer center in St. Louis, Missouri. Sociodemographic and clinical data were obtained for women who received mastectomy for definitive surgical treatment for breast cancer between 2000 and 2012. Logistic regression was used to identify factors associated with the receipt of breast reconstruction. We found a breast reconstruction rate of 54 % for the study sample. Women who were aged 55 and older, had public insurance, received unilateral mastectomy, and received adjuvant radiation therapy were significantly less likely to receive breast reconstruction. African American women were 30 % less likely to receive breast reconstruction than Caucasian women. These findings suggest that racial disparities in breast reconstruction persist in comprehensive cancer centers. Future research should further delineate the determinants of breast reconstruction disparities across various types of healthcare institutions. Only then can we develop interventions to ensure all eligible women have access to breast reconstruction and the improved quality of life it affords breast cancer survivors.

An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

PubMed

Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

2017-05-22

PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age

Breast cancer and protein biomarkers

PubMed Central

Gam, Lay-Harn

2012-01-01

Breast cancer is a healthcare concern of women worldwide. Despite procedures being available for diagnosis, prognosis and treatment of breast cancer, researchers are working intensively on the disease in order to improve the life quality of breast cancer patients. At present, there is no single treatment known to bring a definite cure for breast cancer. One of the possible solutions for combating breast cancer is through identification of reliable protein biomarkers that can be effectively used for early detection, prognosis and treatments of the cancer. Therefore, the task of identification of biomarkers for breast cancer has become the focus of many researchers worldwide. PMID:24520539

The After Breast Cancer Pooling Project: rationale, methodology, and breast cancer survivor characteristics.

PubMed

Nechuta, Sarah J; Caan, Bette J; Chen, Wendy Y; Flatt, Shirley W; Lu, Wei; Patterson, Ruth E; Poole, Elizabeth M; Kwan, Marilyn L; Chen, Zhi; Weltzien, Erin; Pierce, John P; Shu, Xiao Ou

2011-09-01

The After Breast Cancer Pooling Project was established to examine the role of physical activity, adiposity, dietary factors, supplement use, and quality of life (QOL) in breast cancer prognosis. This paper presents pooled and harmonized data on post-diagnosis lifestyle factors, clinical prognostic factors, and breast cancer outcomes from four prospective cohorts of breast cancer survivors (three US-based and one from Shanghai, China) for 18,314 invasive breast cancer cases diagnosed between 1976 and 2006. Most participants were diagnosed with stage I-II breast cancer (84.7%). About 60% of breast tumors were estrogen receptor (ER)+/progesterone receptor (PR)+; 21% were ER-/PR-. Among 8,118 participants with information on HER-2 tumor status, 74.8% were HER-2- and 18.5% were HER-2+. At 1-2 years post-diagnosis (on average), 17.9% of participants were obese (BMI ≥ 30 kg/m2), 32.6% were overweight (BMI 25-29 kg/m2), and 59.9% met the 2008 Physical Activity Guidelines for Americans (≥ 2.5 h per week of moderate activity). During follow-up (mean = 8.4 years), 3,736 deaths (2,614 from breast cancer) and 3,564 recurrences have been documented. After accounting for differences in year of diagnosis and timing of post-diagnosis enrollment, five-year overall survival estimates were similar across cohorts. This pooling project of 18,000 breast cancer survivors enables the evaluation of associations of post-diagnosis lifestyle factors, QOL, and breast cancer outcomes with an adequate sample size for investigation of heterogeneity by hormone receptor status and other clinical predictors. The project sets the stage for international collaborations for the investigation of modifiable predictors for breast cancer outcomes.

Update on breast cancer risk prediction and prevention.

PubMed

Sestak, Ivana; Cuzick, Jack

2015-02-01

Breast cancer is the most common cancer in women worldwide. This review will focus on current prevention strategies for women at high risk. The identification of women who are at high risk of developing breast cancer is key to breast cancer prevention. Recent findings have shown that the inclusion of breast density and a panel of low-penetrance genetic polymorphisms can improve risk estimation compared with previous models. Preventive therapy with aromatase inhibitors has produced large reductions in breast cancer incidence in postmenopausal women. Tamoxifen confers long-term protection and is the only proven preventive treatment for premenopausal women. Several other agents, including metformin, bisphosphonates, aspirin and statins, have been found to be effective in nonrandomized settings. There are many options for the prevention of oestrogen-positive breast cancer, in postmenopausal women who can be given a selective oestrogen receptor modulator or an aromatase inhibitor. It still remains unclear how to prevent oestrogen-negative breast cancer, which occurs more often in premenopausal women. Identification of women at high risk of the disease is crucial, and the inclusion of breast density and a panel of genetic polymorphisms, which individually have low penetrance, can improve risk assessment.

Educating Normal Breast Mucosa to Prevent Breast Cancer

DTIC Science & Technology

2016-12-01

prevention of breast cancer and the feasibility of translating this approach into preventive breast cancer vaccine setting. 15. SUBJECT TERMS...immunity. Our overall goal is to develop a preventative vaccination strategy to reduce the incidence and mortality from breast cancer based on...thorough understanding of the immunity in breast mucosa will enable the design of appropriate vaccination strategies aimed at generating persistent

Breast cancer in South Asia: a Bangladeshi perspective.

PubMed

Hossain, Mohammad Sorowar; Ferdous, Shameema; Karim-Kos, Henrike E

2014-10-01

South Asian countries are facing a hidden breast cancer epidemic. A significant proportion of the breast cancer cases occur in premenopausal women. Knowledge of the various aspects of breast cancer in different geographical regions is limited in South Asia. In this article, we review the Bangladeshi perspective of the epidemiology, risk factors, pathology, diagnosis and treatment of breast cancer. As in other developing countries, because of the lack of breast cancer awareness in Bangladeshi population and inadequate access to health care, most patients are diagnosed at an advanced stage of the disease. Early detection has a crucial impact on overall treatment outcomes. To battle against breast cancer in resource-limited countries like Bangladesh, it is not feasible to set up a parallel health service system solely dedicated to cancer. Therefore, a cost-effective public health strategy is needed which could reach a large number of women in the country. Considering all these issues, we propose an innovative female-based primary healthcare approach focused on awareness, screening and early detection of breast cancer in Bangladesh. This preventive strategy could be a model for other resource-limited developing countries. Copyright © 2014 Elsevier Ltd. All rights reserved.

Family History and Breast Cancer Risk Among Older Women in the Breast Cancer Surveillance Consortium Cohort.

PubMed

Braithwaite, Dejana; Miglioretti, Diana L; Zhu, Weiwei; Demb, Joshua; Trentham-Dietz, Amy; Sprague, Brian; Tice, Jeffrey A; Onega, Tracy; Henderson, Louise M; Buist, Diana S M; Ziv, Elad; Walter, Louise C; Kerlikowske, Karla

2018-04-01

First-degree family history is a strong risk factor for breast cancer, but controversy exists about the magnitude of the association among older women. To determine whether first-degree family history is associated with increased risk of breast cancer among older women, and identify whether the association varies by breast density. Prospective cohort study between 1996 and 2012 from 7 Breast Cancer Surveillance Consortium (BCSC) registries located in New Hampshire, North Carolina, San Francisco Bay area, western Washington state, New Mexico, Colorado, and Vermont. During a mean (SD) follow-up of 6.3 (3.2) years, 10 929 invasive breast cancers were diagnosed in a cohort of 403 268 women 65 years and older with data from 472 220 mammography examinations. We estimated the 5-year cumulative incidence of invasive breast cancer by first-degree family history, breast density, and age groups. Cox proportional hazards models were fit to estimate the association of first-degree family history with risk of invasive breast cancer (after adjustment for breast density, BCSC registry, race/ethnicity, body mass index, postmenopausal hormone therapy use, and benign breast disease for age groups 65 to 74 years and 75 years and older, separately). Data analyses were performed between June 2016 and June 2017. First-degree family history of breast cancer. Incident breast cancer. In 403 268 women 65 years and older, first-degree family history was associated with an increased risk of breast cancer among women ages 65 to 74 years (hazard ratio [HR], 1.48; 95% CI, 1.35-1.61) and 75 years and older (HR, 1.44; 95% CI, 1.28-1.62). Estimates were similar for women 65 to 74 years with first-degree relative's diagnosis age younger than 50 years (HR, 1.47; 95% CI, 1.25-1.73) vs 50 years and older (HR, 1.33; 95% CI, 1.17-1.51) and for women ages 75 years and older with the relative's diagnosis age younger than 50 years (HR, 1.31; 95% CI, 1.05-1.63) vs 50 years and older (HR, 1.55; 95% CI

Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening

PubMed Central

Autier, Philippe; Sullivan, Richard; Boyle, Peter

2016-01-01

Background The role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates. Patients and Methods The Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk. Results The observed and predicted RR of breast cancer death were 0.72 (0.56–0.94) and 0.98 (0.77–1.24) in the HIP trial, and 0.79 (0.78–1.01) and 0.90 (0.80–1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62–0.87), while the predicted RR was 0.89 (0.75–1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70–0.97) if extra cancers were excluded. Conclusions In breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group. PMID:27100174

Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening.

PubMed

Autier, Philippe; Boniol, Mathieu; Smans, Michel; Sullivan, Richard; Boyle, Peter

2016-01-01

The role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates. The Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk. The observed and predicted RR of breast cancer death were 0.72 (0.56-0.94) and 0.98 (0.77-1.24) in the HIP trial, and 0.79 (0.78-1.01) and 0.90 (0.80-1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62-0.87), while the predicted RR was 0.89 (0.75-1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70-0.97) if extra cancers were excluded. In breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group.

Breast cancer correlates in a cohort of breast screening program participants in Riyadh, KSA.

PubMed

Al-Amri, Fahad A; Saeedi, Mohammed Y; Al-Tahan, Fatina M; Ali, Arwa M; Alomary, Shaker A; Arafa, Mostafa; Ibrahim, Ahmed K; Kassim, Kassim A

2015-06-01

Breast cancer is the first cancer among females in the Kingdom of Saudi Arabia, accounting for 27.4% of all newly diagnosed female cancers in 2010. There are several risk factors affecting the incidence of breast cancer where some factors influence the risk more than the others. We aimed to identify the different risk factors related to breast cancer among females participating in the breast-screening program in Riyadh, KSA. Based on data from phase-I of the breast-screening program, a case-control study was conducted on women living in Riyadh, KSA. A sample of 349 women (58 cases and 290 controls) was recruited to examine the different breast cancer correlates. Multivariate regression model was built to investigate the most important risk factors. The mean age of cases was 48.5±7.1 years. Age at marriage, number of pregnancy, age at menopause, oral contraceptive pills, breast feeding and family history of breast cancer in first-degree relative were identified as the most important correlates among the studied cohort. The findings of the current work suggested that age at marriage, age at menopause ⩾50 years and 1st degree family history of breast cancer were risk factors for breast cancer, while, age at menopause <50 years, number of pregnancies and practicing breast feeding were protective factors against breast cancer. There was no effect of body mass index or physical inactivity. Further studies are needed to explore the hereditary, familial and genetic background risk factors in Saudi population. Copyright © 2015 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

CHEK2*1100delC heterozygosity in women with breast cancer associated with early death, breast cancer-specific death, and increased risk of a second breast cancer.

PubMed

Weischer, Maren; Nordestgaard, Børge G; Pharoah, Paul; Bolla, Manjeet K; Nevanlinna, Heli; Van't Veer, Laura J; Garcia-Closas, Montserrat; Hopper, John L; Hall, Per; Andrulis, Irene L; Devilee, Peter; Fasching, Peter A; Anton-Culver, Hoda; Lambrechts, Diether; Hooning, Maartje; Cox, Angela; Giles, Graham G; Burwinkel, Barbara; Lindblom, Annika; Couch, Fergus J; Mannermaa, Arto; Grenaker Alnæs, Grethe; John, Esther M; Dörk, Thilo; Flyger, Henrik; Dunning, Alison M; Wang, Qin; Muranen, Taru A; van Hien, Richard; Figueroa, Jonine; Southey, Melissa C; Czene, Kamila; Knight, Julia A; Tollenaar, Rob A E M; Beckmann, Matthias W; Ziogas, Argyrios; Christiaens, Marie-Rose; Collée, Johanna Margriet; Reed, Malcolm W R; Severi, Gianluca; Marme, Frederik; Margolin, Sara; Olson, Janet E; Kosma, Veli-Matti; Kristensen, Vessela N; Miron, Alexander; Bogdanova, Natalia; Shah, Mitul; Blomqvist, Carl; Broeks, Annegien; Sherman, Mark; Phillips, Kelly-Anne; Li, Jingmei; Liu, Jianjun; Glendon, Gord; Seynaeve, Caroline; Ekici, Arif B; Leunen, Karin; Kriege, Mieke; Cross, Simon S; Baglietto, Laura; Sohn, Christof; Wang, Xianshu; Kataja, Vesa; Børresen-Dale, Anne-Lise; Meyer, Andreas; Easton, Douglas F; Schmidt, Marjanka K; Bojesen, Stig E

2012-12-10

We tested the hypotheses that CHEK2*1100delC heterozygosity is associated with increased risk of early death, breast cancer-specific death, and risk of a second breast cancer in women with a first breast cancer. From 22 studies participating in the Breast Cancer Association Consortium, 25,571 white women with invasive breast cancer were genotyped for CHEK2*1100delC and observed for up to 20 years (median, 6.6 years). We examined risk of early death and breast cancer-specific death by estrogen receptor status and risk of a second breast cancer after a first breast cancer in prospective studies. CHEK2*1100delC heterozygosity was found in 459 patients (1.8%). In women with estrogen receptor-positive breast cancer, multifactorially adjusted hazard ratios for heterozygotes versus noncarriers were 1.43 (95% CI, 1.12 to 1.82; log-rank P = .004) for early death and 1.63 (95% CI, 1.24 to 2.15; log-rank P < .001) for breast cancer-specific death. In all women, hazard ratio for a second breast cancer was 2.77 (95% CI, 2.00 to 3.83; log-rank P < .001) increasing to 3.52 (95% CI, 2.35 to 5.27; log-rank P < .001) in women with estrogen receptor-positive first breast cancer only. Among women with estrogen receptor-positive breast cancer, CHEK2*1100delC heterozygosity was associated with a 1.4-fold risk of early death, a 1.6-fold risk of breast cancer-specific death, and a 3.5-fold risk of a second breast cancer. This is one of the few examples of a genetic factor that influences long-term prognosis being documented in an extensive series of women with breast cancer.

Family history of cancer other than breast or ovarian cancer in first-degree relatives is associated with poor breast cancer prognosis.

PubMed

Song, Jun-Long; Chen, Chuang; Yuan, Jing-Ping; Li, Juan-Juan; Sun, Sheng-Rong

2017-04-01

Whether a first-degree family history of others cancers (FHOC) than breast or ovarian cancer (BOC) is associated with breast cancer prognosis remains unknown. Thus, the aim of the present study was to clarify this issue. Women who were diagnosed with invasive breast cancer at the Renmin Hospital of Wuhan University from 2010 to 2013 were included in the study. The demographic and clinicopathological characteristics of these patients were extracted. FHOC was considered positive for any patient who had a relative who had been diagnosed with cancer other than BOC. Disease-free survival (DFS) was calculated based on the date of diagnosis. DFS was analyzed using the Cox proportional hazards model. A total of 434 breast cancer patients were included in this study. Among these patients, 61 (14.06%) had a positive FHOC in first-degree relatives. Patients with a positive FHOC tended to have HER2-positive breast cancer (p = 0.03). In the survival analysis, FHOC was associated with poor DFS in both univariate (HR = 2.21 (1.28-3.83), 95% CI: 1.28-3.83, p < 0.01) and multivariate (HR = 2.50, 95% CI: 1.24-5.04, p = 0.01) analyses, especially in patients with luminal A subtypes. The results demonstrated an increased risk of recurrence in breast cancer patients with FHOC, especially in patients with luminal A subtype. Copyright © 2017 Elsevier Ltd. All rights reserved.

Five-year risk of interval-invasive second breast cancer.

PubMed

Lee, Janie M; Buist, Diana S M; Houssami, Nehmat; Dowling, Emily C; Halpern, Elkan F; Gazelle, G Scott; Lehman, Constance D; Henderson, Louise M; Hubbard, Rebecca A

2015-07-01

Earlier detection of second breast cancers after primary breast cancer (PBC) treatment improves survival, yet mammography is less accurate in women with prior breast cancer. The purpose of this study was to examine women presenting clinically with second breast cancers after negative surveillance mammography (interval cancers), and to estimate the five-year risk of interval-invasive second cancers for women with varying risk profiles. We evaluated a prospective cohort of 15 114 women with 47 717 surveillance mammograms diagnosed with stage 0-II unilateral PBC from 1996 through 2008 at facilities in the Breast Cancer Surveillance Consortium. We used discrete time survival models to estimate the association between odds of an interval-invasive second breast cancer and candidate predictors, including demographic, PBC, and imaging characteristics. All statistical tests were two-sided. The cumulative incidence of second breast cancers after five years was 54.4 per 1000 women, with 325 surveillance-detected and 138 interval-invasive second breast cancers. The five-year risk of interval-invasive second cancer for women with referent category characteristics was 0.60%. For women with the most and least favorable profiles, the five-year risk ranged from 0.07% to 6.11%. Multivariable modeling identified grade II PBC (odds ratio [OR] = 1.95, 95% confidence interval [CI] = 1.15 to 3.31), treatment with lumpectomy without radiation (OR = 3.27, 95% CI = 1.91 to 5.62), interval PBC presentation (OR = 2.01, 95% CI 1.28 to 3.16), and heterogeneously dense breasts on mammography (OR = 1.54, 95% CI = 1.01 to 2.36) as independent predictors of interval-invasive second breast cancers. PBC diagnosis and treatment characteristics contribute to variation in subsequent-interval second breast cancer risk. Consideration of these factors may be useful in developing tailored post-treatment imaging surveillance plans. © The Author 2015. Published by Oxford University Press. All rights reserved

Second cancer incidence risk estimates using BEIR VII models for standard and complex external beam radiotherapy for early breast cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donovan, E. M.; James, H.; Bonora, M.

2012-10-15

Purpose: To compare organ specific cancer incidence risks for standard and complex external beam radiotherapy (including cone beam CT verification) following breast conservation surgery for early breast cancer.Method: Doses from breast radiotherapy and kilovoltage cone beam CT (CBCT) exposures were obtained from thermoluminescent dosimeter measurements in an anthropomorphic phantom in which the positions of radiosensitive organs were delineated. Five treatment deliveries were investigated: (i) conventional tangential field whole breast radiotherapy (WBRT), (ii) noncoplanar conformal delivery applicable to accelerated partial beast irradiation (APBI), (iii) two-volume simultaneous integrated boost (SIB) treatment, (iv) forward planned three-volume SIB, and (v) inverse-planned three volume SIB.more » Conformal and intensity modulated radiotherapy methods were used to plan the complex treatments. Techniques spanned the range from simple methods appropriate for patient cohorts with a low cancer recurrence risk to complex plans relevant to cohorts with high recurrence risk. Delineated organs at risk included brain, salivary glands, thyroid, contralateral breast, left and right lung, esophagus, stomach, liver, colon, and bladder. Biological Effects of Ionizing Radiation (BEIR) VII cancer incidence models were applied to the measured mean organ doses to determine lifetime attributable risk (LAR) for ages at exposure from 35 to 80 yr according to radiotherapy techniques, and included dose from the CBCT imaging. Results: All LAR decreased with age at exposure and were lowest for brain, thyroid, liver, and bladder (<0.1%). There was little dependence of LAR on radiotherapy technique for these organs and for colon and stomach. LAR values for the lungs for the three SIB techniques were two to three times those from WBRT and APBI. Uncertainties in the LAR models outweigh any differences in lung LAR between the SIB methods. Constraints in the planning of the SIB methods

Mammographic breast density and breast cancer: evidence of a shared genetic basis.

PubMed

Varghese, Jajini S; Thompson, Deborah J; Michailidou, Kyriaki; Lindström, Sara; Turnbull, Clare; Brown, Judith; Leyland, Jean; Warren, Ruth M L; Luben, Robert N; Loos, Ruth J; Wareham, Nicholas J; Rommens, Johanna; Paterson, Andrew D; Martin, Lisa J; Vachon, Celine M; Scott, Christopher G; Atkinson, Elizabeth J; Couch, Fergus J; Apicella, Carmel; Southey, Melissa C; Stone, Jennifer; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Boyd, Norman F; Hall, Per; Hopper, John L; Tamimi, Rulla M; Rahman, Nazneen; Easton, Douglas F

2012-03-15

Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%-10% representing 5,222-50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08-1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.

Mammographic breast density and breast cancer: evidence of a shared genetic basis

PubMed Central

Varghese, Jajini S; Thompson, Deborah J; Michailidou, Kyriaki; Lindström, Sara; Turnbull, Clare; Brown, Judith; Leyland, Jean; Warren, Ruth ML; Luben, Robert N; Loos, Ruth J; Wareham, Nicholas J; Rommens, Johanna; Paterson, Andrew D; Martin, Lisa J; Vachon, Celine M; Scott, Christopher G; Atkinson, Elizabeth J; Couch, Fergus J; Apicella, Carmel; Southey, Melissa C; Stone, Jennifer; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Boyd, Norman F; Hall, Per; Hopper, John L; Tamimi, Rulla M; Rahman, Nazneen; Easton, Douglas F

2012-01-01

Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3628 breast cancer cases and 5190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of SNPs were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using ten different cut-offs for the most significant density SNPs (1-10% representing 5,222-50,899 SNPs). Permutation analysis was also performed across all 10 cut-offs. The association between risk score and breast cancer was significant for all cut-offs from 3-10% of top density SNPs, being most significant for the 6% (2-sided P=0.002) to 10% (P=0.001) cut-offs (overall permutation P=0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR= 1.31 (95%CI 1.08-1.59)] compared to women in the bottom 10%. Together, our results demonstrate that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants. PMID:22266113

A mathematical model of breast cancer development, local treatment and recurrence.

PubMed

Enderling, Heiko; Chaplain, Mark A J; Anderson, Alexander R A; Vaidya, Jayant S

2007-05-21

Cancer development is a stepwise process through which normal somatic cells acquire mutations which enable them to escape their normal function in the tissue and become self-sufficient in survival. The number of mutations depends on the patient's age, genetic susceptibility and on the exposure of the patient to carcinogens throughout their life. It is believed that in every malignancy 4-6 crucial similar mutations have to occur on cancer-related genes. These genes are classified as oncogenes and tumour suppressor genes (TSGs) which gain or lose their function respectively, after they have received one mutative hit or both of their alleles have been knocked out. With the acquisition of each of the necessary mutations the transformed cell gains a selective advantage over normal cells, and the mutation will spread throughout the tissue via clonal expansion. We present a simplified model of this mutation and expansion process, in which we assume that the loss of two TSGs is sufficient to give rise to a cancer. Our mathematical model of the stepwise development of breast cancer verifies the idea that the normal mutation rate in genes is only sufficient to give rise to a tumour within a clinically observable time if a high number of breast stem cells and TSGs exist or genetic instability is involved as a driving force of the mutation pathway. Furthermore, our model shows that if a mutation occurred in stem cells pre-puberty, and formed a field of cells with this mutation through clonal formation of the breast, it is most likely that a tumour will arise from within this area. We then apply different treatment strategies, namely surgery and adjuvant external beam radiotherapy and targeted intraoperative radiotherapy (TARGIT) and use the model to identify different sources of local recurrence and analyse their prevention.

Benign Breast Disease, Mammographic Breast Density, and the Risk of Breast Cancer

PubMed Central

2013-01-01

Background Benign breast disease and high breast density are prevalent, strong risk factors for breast cancer. Women with both risk factors may be at very high risk. Methods We included 42818 women participating in the Breast Cancer Surveillance Consortium who had no prior diagnosis of breast cancer and had undergone at least one benign breast biopsy and mammogram; 1359 women developed incident breast cancer in 6.1 years of follow-up (78.1% invasive, 21.9% ductal carcinoma in situ). We calculated hazard ratios (HRs) using Cox regression analysis. The referent group was women with nonproliferative changes and average density. All P values are two-sided. Results Benign breast disease and breast density were independently associated with breast cancer. The combination of atypical hyperplasia and very high density was uncommon (0.6% of biopsies) but was associated with the highest risk for breast cancer (HR = 5.34; 95% confidence interval [CI] = 3.52 to 8.09, P < .001). Proliferative disease without atypia (25.6% of biopsies) was associated with elevated risk that varied little across levels of density: average (HR = 1.37; 95% CI = 1.11 to 1.69, P = .003), high (HR = 2.02; 95% CI = 1.68 to 2.44, P < .001), or very high (HR = 2.05; 95% CI = 1.54 to 2.72, P < .001). Low breast density (4.5% of biopsies) was associated with low risk (HRs <1) for all benign pathology diagnoses. Conclusions Women with high breast density and proliferative benign breast disease are at very high risk for future breast cancer. Women with low breast density are at low risk, regardless of their benign pathologic diagnosis. PMID:23744877

Benign breast disease, mammographic breast density, and the risk of breast cancer.

PubMed

Tice, Jeffrey A; O'Meara, Ellen S; Weaver, Donald L; Vachon, Celine; Ballard-Barbash, Rachel; Kerlikowske, Karla

2013-07-17

Benign breast disease and high breast density are prevalent, strong risk factors for breast cancer. Women with both risk factors may be at very high risk. We included 42818 women participating in the Breast Cancer Surveillance Consortium who had no prior diagnosis of breast cancer and had undergone at least one benign breast biopsy and mammogram; 1359 women developed incident breast cancer in 6.1 years of follow-up (78.1% invasive, 21.9% ductal carcinoma in situ). We calculated hazard ratios (HRs) using Cox regression analysis. The referent group was women with nonproliferative changes and average density. All P values are two-sided. Benign breast disease and breast density were independently associated with breast cancer. The combination of atypical hyperplasia and very high density was uncommon (0.6% of biopsies) but was associated with the highest risk for breast cancer (HR = 5.34; 95% confidence interval [CI] = 3.52 to 8.09, P < .001). Proliferative disease without atypia (25.6% of biopsies) was associated with elevated risk that varied little across levels of density: average (HR = 1.37; 95% CI = 1.11 to 1.69, P = .003), high (HR = 2.02; 95% CI = 1.68 to 2.44, P < .001), or very high (HR = 2.05; 95% CI = 1.54 to 2.72, P < .001). Low breast density (4.5% of biopsies) was associated with low risk (HRs <1) for all benign pathology diagnoses. Women with high breast density and proliferative benign breast disease are at very high risk for future breast cancer. Women with low breast density are at low risk, regardless of their benign pathologic diagnosis.

Melatonin: an Inhibitor of Breast Cancer

PubMed Central

Hill, Steven M.; Belancio, Victoria P.; Dauchy, Robert T.; Xiang, Shulin; Brimer, Samantha; Mao, Lulu; Hauch, Adam; Lundberg, Peter W.; Summers, Whitney; Yuan, Lin; Frasch, Tripp; Blask, David E.

2015-01-01

This review discusses recent work on melatonin-mediated circadian regulation and metabolic and molecular signaling mechanisms involved in human breast cancer growth and associated consequences of circadian disruption by exposure to light at night (LEN). The anti-cancer actions of the circadian melatonin signal in human breast cancer cell lines and xenografts heavily involve MT1 receptor-mediated mechanisms. In estrogen receptor alpha (ERα)-positive human breast cancer, melatonin, via the MT1 receptor, suppresses ERα mRNA expression and ERα transcriptional activity. As well, melatonin regulates the transactivation of other members of the nuclear receptor super-family, estrogen metabolizing enzymes, and the expression of core clock and clock-related genes. Furthermore, melatonin also suppresses tumor aerobic metabolism (Warburg effect), and, subsequently, cell-signaling pathways critical to cell proliferation, cell survival, metastasis, and drug resistance. Melatonin demonstrates both cytostatic and cytotoxic activity in breast cancer cells that appears to be cell type specific. Melatonin also possesses anti-invasive/anti-metastatic actions that involve multiple pathways including inhibition of p38 MAPK and repression of epithelial-to-mesenchymal transition. Studies demonstrate that melatonin promotes genomic stability by inhibiting the expression of LINE-1 retrotransposons. Finally, research in animal and human models indicate that LEN induced disruption of the circadian nocturnal melatonin signal promotes the growth, metabolism, and signaling of human breast cancer to drive breast tumors to endocrine and chemotherapeutic resistance. These data provide the strongest understanding and support of the mechanisms underpinning the epidemiologic demonstration of elevated breast cancer risk in night shift workers and other individuals increasingly exposed to LEN. PMID:25876649

Nation-Wide Korean Breast Cancer Data from 2008 Using the Breast Cancer Registration Program

PubMed Central

Na, Kuk Young; Kim, Ku Sang; Ahn, Sei-Hyun; Lee, Soo-Joong; Park, Heung Kyu; Cho, Young Up

2011-01-01

Purpose Since 1996, the Korean Breast Cancer Society has collected nation-wide breast cancer data and analyzed the data using their online registration program biannually. The purpose of this study was to evaluate the characteristics of Korean breast cancer from 2008 and examine chronological based patterns. Methods Data were collected from 38 medical schools (67 hospitals), 20 general hospitals, and 10 private clinics. The data on the total number, gender, and age distribution were collected through a questionnaire as well as other detailed data analyzed via the online registration program. Results In 2008, there were 13,908 patients who were newly diagnosed with breast cancer. The crude incidence rate of female breast cancer was 57.3 among 100,000 and the median age was 49 years. The age distribution had not changed since the initial survey; however the proportion of postmenopausal patients had increased and median age was older than the past. In staging distribution, the proportion of early breast cancer (stage 0, I) was 47.2% with, breast-conserving surgery performed in 58% and mastectomy in 39.5%. Conclusion Compared to past data, the incidence of breast cancer in Korea continues to rise. Furthermore, the proportion of those detected by screening and breast conservation surgery has increased remarkably. To understand the patterns of Korean breast cancer, the nation-wide data should continuously investigated. PMID:22031806

Characterization of IKBKE as a Breast Cancer Oncogene

DTIC Science & Technology

2011-10-01

HMLE -MEKDD cells stably expressing either pWZL or MF-IKKε. Immunoblot analysis by IKKε antibody. (D) IP with an IKK antibody from MCF-7 breast cancer ...summary is presented of research performed during three years of a project to further characterize the breast cancer oncogene IKKε. Two specific aims...constitutive IKKε transgenic mouse model to study the role of IKKε in breast cancer initiation and maintenance. The long term goals of this research

Orthotopic tumorgrafts in nude mice as a model to evaluate calcitriol effects in breast cancer.

PubMed

Fonseca-Filho, V C N; Katayama, M L H; Lyra, E C; Maria, D A; Basso, R A; Nonogaki, S; Guerra, J M; Maistro, S; Góes, J C G S; Folgueira, M A A K

2017-11-01

Calcitriol antiproliferative effects were observed in xenografts of breast cancer cell lines, however they were not yet investigated in tumorgrafts, consisting of freshly collected breast cancer samples xenografted into animals. To establish a tumorgraft model, from freshly collected breast cancer samples, which were directly implanted in nude mice, to study calcitriol effects. Breast cancer samples collected from 12 patients were orthotopically implanted into nude mice. Animals were treated with weekly intratumoral injections of calcitriol 3 μg/Kg, which was previously shown to induce peak serum calcitriol levels in the predicted therapeutic range. Success engraftment rate was 25%. Tumorgrafts were established from aggressive (HER2 positive or histological grade 3) highly proliferative samples and original tumor characteristics were preserved. Calcitriol highly induced its target gene, CYP24A1, indicating that the genomic vitamin D pathway is active in tumorgrafts. However, no differences in the expression of proliferation and apoptosis markers (BrdU incorporation, Ki67, CDKN1A, CDKN1B, BCL2 expression) were observed in these highly proliferative tumor samples. Tumorgrafts seem a promising model to explore other calcitriol doses and regimens, considering the heterogeneity of the disease and microenvironment interactions.

[Hormonotherapy for breast cancer prevention: What about women with genetic predisposition to breast cancer?].

PubMed

Sénéchal, Claire; Reyal, Fabien; Callet, Nasrine; This, Pascale; Noguès, Catherine; Stoppa-Lyonnet, Dominique; Fourme, Emmanuelle

2016-03-01

In France, women carrying BRCA1/2 mutation, at an identified high risk of breast cancer are recommended to undergo breast MRI screening. That screening does not however prevent the risk of developing a breast cancer. The only alternative to breast cancer screening available in France is surgical prevention by prophylactic mastectomy. An interesting option for women who wish to reduce their breast cancer risk, but are unready for prophylactic mastectomy is a preventive hormonal treatment by aromatase inhibitors, or selective estrogens receptor modulators (SERMs). Reliable clinical trials show the efficiency of tamoxifen, raloxifen, exemestane, and anastrozole especially, in reducing breast cancer incidence by 33%, 34%, 65% and 53% respectively. This article tries to sum up the main published trials of breast cancer prevention with hormonal treatment, and presents the latest American and English clinical guidelines concerning hormonal prevention for women at high risk of breast cancer, and starts thinking about the possibilities of hormonoprevention, especially among women carrying a BRCA1/2 mutation in France. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Metabolic Syndrome and Breast Cancer Risk.

PubMed

Wani, Burhan; Aziz, Shiekh Aejaz; Ganaie, Mohammad Ashraf; Mir, Mohammad Hussain

2017-01-01

The study was meant to estimate the prevalence of metabolic syndrome in patients with breast cancer and to establish its role as an independent risk factor on occurrence of breast cancer. Fifty women aged between 40 and 80 years with breast cancer and fifty controls of similar age were assessed for metabolic syndrome prevalence and breast cancer risk factors, including age at menarche, reproductive status, live births, breastfeeding, and family history of breast cancer, age at diagnosis of breast cancer, body mass index, and metabolic syndrome parameters. Metabolic syndrome prevalence was found in 40.0% of breast cancer patients, and 18.0% of those in control group ( P = 0.02). An independent and positive association was seen between metabolic syndrome and breast cancer risk (odds ratio = 3.037; 95% confidence interval 1.214-7.597). Metabolic syndrome is more prevalent in breast cancer patients and is an independent risk factor for breast cancer.

Breast cancer screening in an era of personalized regimens: a conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level.

PubMed

Onega, Tracy; Beaber, Elisabeth F; Sprague, Brian L; Barlow, William E; Haas, Jennifer S; Tosteson, Anna N A; D Schnall, Mitchell; Armstrong, Katrina; Schapira, Marilyn M; Geller, Berta; Weaver, Donald L; Conant, Emily F

2014-10-01

Breast cancer screening holds a prominent place in public health, health care delivery, policy, and women's health care decisions. Several factors are driving shifts in how population-based breast cancer screening is approached, including advanced imaging technologies, health system performance measures, health care reform, concern for "overdiagnosis," and improved understanding of risk. Maximizing benefits while minimizing the harms of screening requires moving from a "1-size-fits-all" guideline paradigm to more personalized strategies. A refined conceptual model for breast cancer screening is needed to align women's risks and preferences with screening regimens. A conceptual model of personalized breast cancer screening is presented herein that emphasizes key domains and transitions throughout the screening process, as well as multilevel perspectives. The key domains of screening awareness, detection, diagnosis, and treatment and survivorship are conceptualized to function at the level of the patient, provider, facility, health care system, and population/policy arena. Personalized breast cancer screening can be assessed across these domains with both process and outcome measures. Identifying, evaluating, and monitoring process measures in screening is a focus of a National Cancer Institute initiative entitled PROSPR (Population-based Research Optimizing Screening through Personalized Regimens), which will provide generalizable evidence for a risk-based model of breast cancer screening, The model presented builds on prior breast cancer screening models and may serve to identify new measures to optimize benefits-to-harms tradeoffs in population-based screening, which is a timely goal in the era of health care reform. © 2014 American Cancer Society.

Effects of education based on the health belief model on screening behavior in high risk women for breast cancer, Tehran, Iran.

PubMed

Hajian, Sepideh; Vakilian, Katayon; Najabadi, Khadijeh Mirzaii; Hosseini, Jalil; Mirzaei, Hamid Reza

2011-01-01

Breast cancer is the most common malignancy in women. Early diagnosis allows efficient treatment and increases survival, but the efficacy of breast self examination (BSE) is not sufficiently well established. The American Cancer Society aims to give women the opportunity to recognize the utility, limitations and adverse effects of breast cancer screening through education models based on psychological theories. With the Health Belief Model, people's health perceptions and attitudes influence their practices, for example with screening. The purpose of this randomized controlled clinical trial was to determine the effect of education based on this model on breast cancer screening in high risk Iranian women. Participants were women with a family history of breast cancer (mother, sister, and daughter). After explanation of the study objectives to participants, they were recruited on obtaining oral consent and each filled out the study questionnaire based on the Health Belief Model. Allocation was into two groups by computerized randomization, control and intervention, receiving education on breast cancer screening. Perceived susceptibility to and seriousness of breast cancer, perceived usefulness of and barriers to BSE, clinical breast examination, and mammography, and self-efficacy in the ability to perform these, were assessed, with comparison of scores for BSE practice before and after education and doing mammography and clinical examination by a physician in intervention and control group. The mean age was 37.8 ± 11.7 (range 19-60). The mean rank in the intervention group significantly differed before and after the education, but except for " perceived threat" and "perceived usefulness of breast self examination", we did not find any significant differences from the control group. After educational sessions, breast self examination and clinical examination practice rates were elevated. Health education based on well known psychological theories for breast cancer

Bazedoxifene exhibits antiestrogenic activity in animal models of tamoxifen-resistant breast cancer: implications for treatment of advanced disease.

PubMed

Wardell, Suzanne E; Nelson, Erik R; Chao, Christina A; McDonnell, Donald P

2013-05-01

There is compelling evidence to suggest that drugs that function as pure estrogen receptor (ER-α) antagonists, or that downregulate the expression of ER-α, would have clinical use in the treatment of advanced tamoxifen- and aromatase-resistant breast cancer. Although such compounds are currently in development, we reasoned, based on our understanding of ER-α pharmacology, that there may already exist among the most recently developed selective estrogen receptor modulators (SERM) compounds that would have usage as breast cancer therapeutics. Thus, our objective was to identify among available SERMs those with unique pharmacologic activities and to evaluate their potential clinical use with predictive models of advanced breast cancer. A validated molecular profiling technology was used to classify clinically relevant SERMs based on their impact on ER-α conformation. The functional consequences of these observed mechanistic differences on (i) gene expression, (ii) receptor stability, and (iii) activity in cellular and animal models of advanced endocrine-resistant breast cancer were assessed. The high-affinity SERM bazedoxifene was shown to function as a pure ER-α antagonist in cellular models of breast cancer and effectively inhibited the growth of both tamoxifen-sensitive and -resistant breast tumor xenografts. Interestingly, bazedoxifene induced a unique conformational change in ER-α that resulted in its proteasomal degradation, although the latter activity was dispensable for its antagonist efficacy. Bazedoxifene was recently approved for use in the European Union for the treatment of osteoporosis and thus may represent a near-term therapeutic option for patients with advanced breast cancer. ©2013 AACR.

Early Diagnosis of Breast Cancer.

PubMed

Wang, Lulu

2017-07-05

Early-stage cancer detection could reduce breast cancer death rates significantly in the long-term. The most critical point for best prognosis is to identify early-stage cancer cells. Investigators have studied many breast diagnostic approaches, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some limitations such as being expensive, time consuming and not suitable for young women. Developing a high-sensitive and rapid early-stage breast cancer diagnostic method is urgent. In recent years, investigators have paid their attention in the development of biosensors to detect breast cancer using different biomarkers. Apart from biosensors and biomarkers, microwave imaging techniques have also been intensely studied as a promising diagnostic tool for rapid and cost-effective early-stage breast cancer detection. This paper aims to provide an overview on recent important achievements in breast screening methods (particularly on microwave imaging) and breast biomarkers along with biosensors for rapidly diagnosing breast cancer.

Relationship Between Mammographic Density and Breast Cancer Death in the Breast Cancer Surveillance Consortium

PubMed Central

2012-01-01

Background Women with elevated mammographic density have an increased risk of developing breast cancer. However, among women diagnosed with breast cancer, it is unclear whether higher density portends reduced survival, independent of other factors. Methods We evaluated relationships between mammographic density and risk of death from breast cancer and all causes within the US Breast Cancer Surveillance Consortium. We studied 9232 women diagnosed with primary invasive breast carcinoma during 1996–2005, with a mean follow-up of 6.6 years. Mammographic density was assessed using the Breast Imaging Reporting and Data System (BI-RADS) density classification. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox proportional hazards regression; women with scattered fibroglandular densities (BI-RADS 2) were the referent group. All statistical tests were two-sided. Results A total of 1795 women died, of whom 889 died of breast cancer. In multivariable analyses (adjusted for site, age at and year of diagnosis, American Joint Committee on Cancer stage, body mass index, mode of detection, treatment, and income), high density (BI-RADS 4) was not related to risk of death from breast cancer (HR = 0.92, 95% CI = 0.71 to 1.19) or death from all causes (HR = 0.83, 95% CI = 0.68 to 1.02). Analyses stratified by stage and other prognostic factors yielded similar results, except for an increased risk of breast cancer death among women with low density (BI-RADS 1) who were either obese (HR = 2.02, 95% CI = 1.37 to 2.97) or had tumors of at least 2.0cm (HR = 1.55, 95% CI = 1.14 to 2.09). Conclusions High mammographic breast density was not associated with risk of death from breast cancer or death from any cause after accounting for other patient and tumor characteristics. Thus, risk factors for the development of breast cancer may not necessarily be the same as factors influencing the risk of death after breast cancer has developed. PMID:22911616

A risk management model for familial breast cancer: A new application using Fuzzy Cognitive Map method.

PubMed

Papageorgiou, Elpiniki I; Jayashree Subramanian; Karmegam, Akila; Papandrianos, Nikolaos

2015-11-01

Breast cancer is the most deadly disease affecting women and thus it is natural for women aged 40-49 years (who have a family history of breast cancer or other related cancers) to assess their personal risk for developing familial breast cancer (FBC). Besides, as each individual woman possesses different levels of risk of developing breast cancer depending on their family history, genetic predispositions and personal medical history, individualized care setting mechanism needs to be identified so that appropriate risk assessment, counseling, screening, and prevention options can be determined by the health care professionals. The presented work aims at developing a soft computing based medical decision support system using Fuzzy Cognitive Map (FCM) that assists health care professionals in deciding the individualized care setting mechanisms based on the FBC risk level of the given women. The FCM based FBC risk management system uses NHL to learn causal weights from 40 patient records and achieves a 95% diagnostic accuracy. The results obtained from the proposed model are in concurrence with the comprehensive risk evaluation tool based on Tyrer-Cuzick model for 38/40 patient cases (95%). Besides, the proposed model identifies high risk women by calculating higher accuracy of prediction than the standard Gail and NSAPB models. The testing accuracy of the proposed model using 10-fold cross validation technique outperforms other standard machine learning based inference engines as well as previous FCM-based risk prediction methods for BC. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Longitudinal in vivo transcutaneous observation of Raman signals from breast cancer during chemotherapy in small animal model

NASA Astrophysics Data System (ADS)

Seong, Myeongsu; Myoung, NoSoung; Yim, Sang-Youp; Kim, Jae G.

2015-02-01

Because mammography, the gold standard of breast cancer screening and monitoring treatment efficacy, has limitations, there is a necessity to have a new method for breast cancer patients. Raman spectroscopy is considered as one of the best alternative approaches due to its ability of visualizing (bio)chemical information of a matter. In this study, we hypothesized that the change of biochemical composition occurs earlier than morphological change in breast cancer during chemotherapy, and attempted to prove it by employing fiber-optic Raman spectroscopy for longitudinal Raman measurement in small animal breast cancer model. To confirm the hypothesis, we measured Raman spectra of a tumor breast and the contralateral breast during chemotherapy for 4 fisher 344 female rats longitudinally. Principal component analysis and Raman spectral differences between breast tumor and contralateral normal breast did not show a clear difference between them which may have been caused by interference from skin. Thus, spatially-offset Raman spectroscopy will be employed in order to acquire the Raman signal directly from tumor while suppressing Raman signal from skin for the future study.

Mediterranean Diet and Breast Cancer Risk

PubMed Central

Carioli, Greta; Ferraroni, Monica; Serraino, Diego; Montella, Maurizio; Giacosa, Attilio; Toffolutti, Federica; Negri, Eva; Levi, Fabio

2018-01-01

The Mediterranean diet has been related to a reduced risk of several common cancers but its role on breast cancer has not been quantified yet. We investigated the association between adherence to the Mediterranean diet and breast cancer risk by means of a hospital-based case-control study conducted in Italy and Switzerland. 3034 breast cancer cases and 3392 controls admitted to the same network of hospitals for acute, non-neoplastic and non-gynaecologic diseases were studied. Adherence to the Mediterranean diet was quantitatively measured through a Mediterranean Diet Score (MDS), summarizing the major characteristics of the Mediterranean dietary pattern and ranging from 0 (lowest adherence) to 9 (highest adherence). We estimated the odds ratios (ORs) of breast cancer for the MDS using multiple logistic regression models, adjusting for several covariates. Compared to a MDS of 0–3, the ORs for breast cancer were 0.86 (95% confidence interval, CI, 0.76–0.98) for a MDS of 4–5 and 0.82 (95% CI, 0.71–0.95) for a MDS of 6–9 (p for trend = 0.008). The exclusion of the ethanol component from the MDS did not materially modify the ORs (e.g., OR = 0.81, 95% CI, 0.70–0.95, for MDS ≥ 6). Results were similar in pre- and post-menopausal women. Adherence to the Mediterranean diet was associated with a reduced breast cancer risk. PMID:29518016

The Obesity-Breast Cancer Conundrum: An Analysis of the Issues

PubMed Central

Matthews, Shawna B.; Thompson, Henry J.

2016-01-01

Breast cancer develops over a timeframe of 2–3 decades prior to clinical detection. Given this prolonged latency, it is somewhat unexpected from a biological perspective that obesity has no effect or reduces the risk for breast cancer in premenopausal women yet increases the risk for breast cancer in postmenopausal women. This conundrum is particularly striking in light of the generally negative effects of obesity on breast cancer outcomes, including larger tumor size at diagnosis and poorer prognosis in both pre- and postmenopausal women. This review and analysis identifies factors that may contribute to this apparent conundrum, issues that merit further investigation, and characteristics of preclinical models for breast cancer and obesity that should be considered if animal models are used to deconstruct the conundrum. PMID:27338371

Characterizing and Targeting Replication Stress Response Defects in Breast Cancer

DTIC Science & Technology

2011-08-01

induced RSR breast cell model, in which cyclin E can be conditionally induced to trigger RSR in normal breast cells. Using this model, we demonstrated...which makes these defects effective targets for both breast cancer prevention and breast cancer treatment. This project is to use cutting-edge...defective RSR; identify drugs that target these defects; and develop RSR-defect-targeting nanoparticles for diagnostic imaging, prevention, and

Risk determination and prevention of breast cancer.

PubMed

Howell, Anthony; Anderson, Annie S; Clarke, Robert B; Duffy, Stephen W; Evans, D Gareth; Garcia-Closas, Montserat; Gescher, Andy J; Key, Timothy J; Saxton, John M; Harvie, Michelle N

2014-09-28

Breast cancer is an increasing public health problem. Substantial advances have been made in the treatment of breast cancer, but the introduction of methods to predict women at elevated risk and prevent the disease has been less successful. Here, we summarize recent data on newer approaches to risk prediction, available approaches to prevention, how new approaches may be made, and the difficult problem of using what we already know to prevent breast cancer in populations. During 2012, the Breast Cancer Campaign facilitated a series of workshops, each covering a specialty area of breast cancer to identify gaps in our knowledge. The risk-and-prevention panel involved in this exercise was asked to expand and update its report and review recent relevant peer-reviewed literature. The enlarged position paper presented here highlights the key gaps in risk-and-prevention research that were identified, together with recommendations for action. The panel estimated from the relevant literature that potentially 50% of breast cancer could be prevented in the subgroup of women at high and moderate risk of breast cancer by using current chemoprevention (tamoxifen, raloxifene, exemestane, and anastrozole) and that, in all women, lifestyle measures, including weight control, exercise, and moderating alcohol intake, could reduce breast cancer risk by about 30%. Risk may be estimated by standard models potentially with the addition of, for example, mammographic density and appropriate single-nucleotide polymorphisms. This review expands on four areas: (a) the prediction of breast cancer risk, (b) the evidence for the effectiveness of preventive therapy and lifestyle approaches to prevention, (c) how understanding the biology of the breast may lead to new targets for prevention, and (d) a summary of published guidelines for preventive approaches and measures required for their implementation. We hope that efforts to fill these and other gaps will lead to considerable advances in our

Interactions of Family History of Breast Cancer with Radiotherapy in Relation to the Risk of Breast Cancer Recurrence.

PubMed

Li, Danmeng; Mai, Volker; Gerke, Travis; Pinney, Susan Mengel; Yaghjyan, Lusine

2017-12-01

We examined associations between a family history of breast cancer and the risk of breast cancer recurrence in women who received or did not receive radiotherapy. Our study included 2,440 women enrolled in the Breast Cancer Registry of Greater Cincinnati. Information on breast cancer risk factors, including detailed family history of breast cancer, characteristics of the primary tumor, treatment received, and recurrence status was collected at baseline and via updates. Associations between a family history of breast cancer and the risk of breast cancer recurrence were examined separately in women treated with and without radiotherapy using survival analysis. Over an average follow-up time of 8.78 years, we found no associations between a family history of breast cancer and the risk of breast cancer recurrence among women with a history of radiotherapy (hazard ratio [HR], 0.96; 95% confidence interval [CI], 0.75-1.23). Among women who did not receive radiotherapy, the total number of relatives with breast cancer was positively associated with the risk of breast cancer recurrence (HR, 1.21; 95% CI, 1.00-1.47). We found no interactions of radiotherapy with family history (p-interaction >0.05). Radiotherapy for a primary breast cancer in women with a family history of breast cancer does not increase risk of breast cancer recurrence. If these findings are replicated in future studies, the results may translate into an important health message for breast cancer survivors with a family history of breast cancer.

The STAT3 inhibitor pyrimethamine displays anti-cancer and immune stimulatory effects in murine models of breast cancer.

PubMed

Khan, Mohammad W; Saadalla, Abdulrahman; Ewida, Ahmed H; Al-Katranji, Khalid; Al-Saoudi, Ghadier; Giaccone, Zachary T; Gounari, Fotini; Zhang, Ming; Frank, David A; Khazaie, Khashayarsha

2018-01-01

The transcription factor signal activator and transducer or transcription (STAT3), which regulates genes controlling proliferation, survival, and invasion, is activated inappropriately in many human cancers, including breast cancer. Activation of STAT3 can lead to both malignant cellular behavior and suppression of immune cell function in the tumor microenvironment. Through a chemical-biology screen, pyrimethamine (PYR), an FDA approved anti-microbial drug, was identified as an inhibitor of STAT3 function at concentrations known to be achieved safely in humans. We report that PYR shows therapeutic activity in two independent mouse models of breast cancer, with both direct tumor inhibitory and immune stimulatory effects. PYR-inhibited STAT3 activity in TUBO and TM40D-MB metastatic breast cancer cells in vitro and inhibited tumor cell proliferation and invasion into Matrigel basement membrane matrix. In tumor-transplanted mice, PYR had both direct and indirect tumor inhibitory effects. Tumor-bearing mice treated with PYR showed reduced STAT3 activation in tumor cells, attenuated tumor growth, and reduced tumor-associated inflammation. In addition, expression of Lamp1 by tumor infiltrating CD8 + T cells was elevated, indicating enhanced release of cytotoxic granules. These findings suggest that PYR may have beneficial effects in the treatment of breast cancer.

Variable selection in semiparametric cure models based on penalized likelihood, with application to breast cancer clinical trials.

PubMed

Liu, Xiang; Peng, Yingwei; Tu, Dongsheng; Liang, Hua

2012-10-30

Survival data with a sizable cure fraction are commonly encountered in cancer research. The semiparametric proportional hazards cure model has been recently used to analyze such data. As seen in the analysis of data from a breast cancer study, a variable selection approach is needed to identify important factors in predicting the cure status and risk of breast cancer recurrence. However, no specific variable selection method for the cure model is available. In this paper, we present a variable selection approach with penalized likelihood for the cure model. The estimation can be implemented easily by combining the computational methods for penalized logistic regression and the penalized Cox proportional hazards models with the expectation-maximization algorithm. We illustrate the proposed approach on data from a breast cancer study. We conducted Monte Carlo simulations to evaluate the performance of the proposed method. We used and compared different penalty functions in the simulation studies. Copyright © 2012 John Wiley & Sons, Ltd.

Mammographic density, breast cancer risk and risk prediction

PubMed Central

Vachon, Celine M; van Gils, Carla H; Sellers, Thomas A; Ghosh, Karthik; Pruthi, Sandhya; Brandt, Kathleen R; Pankratz, V Shane

2007-01-01

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. PMID:18190724

Ex vivo expanded natural killer cells from breast cancer patients and healthy donors are highly cytotoxic against breast cancer cell lines and patient-derived tumours.

PubMed

Shenouda, Mira M; Gillgrass, Amy; Nham, Tina; Hogg, Richard; Lee, Amanda J; Chew, Marianne V; Shafaei, Mahsa; Aarts, Craig; Lee, Dean A; Hassell, John; Bane, Anita; Dhesy-Thind, Sukhbinder; Ashkar, Ali A

2017-07-01

Natural killer (NK) cells play a critical role in cancer immunosurveillance. Recent developments in NK cell ex-vivo expansion makes it possible to generate millions of activated NK cells from a small volume of peripheral blood. We tested the functionality of ex vivo expanded NK cells in vitro against breast cancer cell lines and in vivo using a xenograft mouse model. The study aim was to assess functionality and phenotype of expanded NK cells from breast cancer patients against breast cancer cell lines and autologous primary tumours. We used a well-established NK cell co-culture system to expand NK cells ex vivo from healthy donors and breast cancer patients and examined their surface marker expression. Moreover, we tested the ability of expanded NK cells to lyse the triple negative breast cancer and HER2-positive breast cancer cell lines MDA-MB-231 and MDA-MB-453, respectively. We also tested their ability to prevent tumour growth in vivo using a xenograft mouse model. Finally, we tested the cytotoxicity of expanded NK cells against autologous and allogeneic primary breast cancer tumours in vitro. After 3 weeks of culture we observed over 1000-fold expansion of NK cells isolated from either breast cancer patients or healthy donors. We also showed that the phenotype of expanded NK cells is comparable between those from healthy donors and cancer patients. Moreover, our results confirm the ability of ex vivo expanded NK cells to lyse tumour cell lines in vitro. While the cell lines examined had differential sensitivity to NK cell killing we found this was correlated with level of major histocompatibility complex (MHC) class I expression. In our in vivo model, NK cells prevented tumour establishment and growth in immunocompromised mice. Finally, we showed that NK cells expanded from the peripheral blood of breast cancer patients show high cytotoxicity against allogeneic and autologous patient-derived tumour cells in vitro. NK cells from breast cancer patients can be

How breast cancer presents.

PubMed Central

Devitt, J. E.

1983-01-01

A study of 501 new breast cancers in patients seen in a consulting surgical practice revealed that 87% were in patients 45 years of age or older. The patients had found 83% of the cancers. The distributions of size and stage were the same for the tumours found by the patients and those found by the referring physicians. Two thirds of the cancers had an associated visible clinical sign, demonstrating the importance of inspection in the examination of the breast. Dimpling, sometimes apparent only on manipulation of the tumour, was present with 264 of the cancers and was often associated with "minimal" lesions. Mammography was done for 63 of the breast cancers but it missed 27. Of the physician-found cancers 15 were in patients who had already had breast cancer, 4 were in patients presenting with symptomatic metastases and 14 were in women presenting with other disorders. Of the 52 cancers found by periodic examination 3 were locally advanced and 21 had axillary metastases, while among the 28 "early" cancers 12 were in women who were senile, mentally defective or psychotic. Only four of the cancers found by the physicians were in women under age 45; two were rapidly fatal, one had an axillary metastasis, and the fourth was in a woman who had had cancer of the opposite breast. The remaining 284 lesions found by periodic or routine examination in women under age 45 were benign. Thus, periodic or routine examination for unsuspected breast cancer in women under age 45 seems unjustified except in those who have already had breast cancer. Images FIG. 1 FIG. 2 PMID:6861046

Beta-blocker drug therapy reduces secondary cancer formation in breast cancer and improves cancer specific survival.

PubMed

Powe, Desmond G; Voss, Melanie J; Zänker, Kurt S; Habashy, Hany O; Green, Andrew R; Ellis, Ian O; Entschladen, Frank

2010-11-01

Laboratory models show that the beta-blocker, propranolol, can inhibit norepinephrine-induced breast cancer cell migration. We hypothesised that breast cancer patients receiving beta-blockers for hypertension would show reduced metastasis and improved clinical outcome. Three patient subgroups were identified from the medical records of 466 consecutive female patients (median age 57, range 28-71) with operable breast cancer and follow-up (>10 years). Two subgroups comprised 43 and 49 hypertensive patients treated with beta-blockers or other antihypertensives respectively, prior to cancer diagnosis. 374 patients formed a non-hypertensive control group. Metastasis development, disease free interval, tumour recurrence and hazards risk were statistically compared between groups. Kaplan-Meier plots were used to model survival and DM. Beta-blocker treated patients showed a significant reduction in metastasis development (p=0.026), tumour recurrence (p=0.001), and longer disease free interval (p=0.01). In addition, there was a 57% reduced risk of metastasis (Hazards ratio=0.430; 95% CI=0.200-0.926, p=0.031), and a 71% reduction in breast cancer mortality after 10 years (Hazards ratio=0.291; 95% CI=0.119-0.715, p=0.007). This proof-of-principle study showed beta-blocker therapy significantly reduces distant metastases, cancer recurrence, and cancer-specific mortality in breast cancer patients suggesting a novel role for beta-blocker therapy. A larger epidemiological study leading to randomised clinical trials is needed for breast and other cancer types including colon, prostate and ovary.

Beta-Blocker Drug Therapy Reduces Secondary Cancer Formation in Breast Cancer and Improves Cancer Specific Survival

PubMed Central

Powe, Desmond G.; Voss, Melanie J.; Zänker, Kurt S.; Habashy, Hany O.; Green, Andrew R.; Ellis, Ian O.; Entschladen, Frank

2010-01-01

Laboratory models show that the beta-blocker, propranolol, can inhibit norepinephrine-induced breast cancer cell migration. We hypothesised that breast cancer patients receiving beta-blockers for hypertension would show reduced metastasis and improved clinical outcome. Three patient subgroups were identified from the medical records of 466 consecutive female patients (median age 57, range 28-71) with operable breast cancer and follow-up (>10 years). Two subgroups comprised 43 and 49 hypertensive patients treated with beta-blockers or other antihypertensives respectively, prior to cancer diagnosis. 374 patients formed a non-hypertensive control group. Metastasis development, disease free interval, tumour recurrence and hazards risk were statistically compared between groups. Kaplan-Meier plots were used to model survival and DM. Beta-blocker treated patients showed a significant reduction in metastasis development (p=0.026), tumour recurrence (p=0.001), and longer disease free interval (p=0.01). In addition, there was a 57% reduced risk of metastasis (Hazards ratio=0.430; 95% CI=0.200-0.926, p=0.031), and a 71% reduction in breast cancer mortality after 10 years (Hazards ratio=0.291; 95% CI=0.119-0.715, p=0.007). This proof-of-principle study showed beta-blocker therapy significantly reduces distant metastases, cancer recurrence, and cancer-specific mortality in breast cancer patients suggesting a novel role for beta-blocker therapy. A larger epidemiological study leading to randomised clinical trials is needed for breast and other cancer types including colon, prostate and ovary. PMID:21317458

Myeloid-derived suppressor cells in breast cancer.

PubMed

Markowitz, Joseph; Wesolowski, Robert; Papenfuss, Tracey; Brooks, Taylor R; Carson, William E

2013-07-01

Myeloid-derived suppressor cells (MDSCs) are a population of immature myeloid cells defined by their suppressive actions on immune cells such as T cells, dendritic cells, and natural killer cells. MDSCs typically are positive for the markers CD33 and CD11b but express low levels of HLADR in humans. In mice, MDSCs are typically positive for both CD11b and Gr1. These cells exert their suppressive activity on the immune system via the production of reactive oxygen species, arginase, and cytokines. These factors subsequently inhibit the activity of multiple protein targets such as the T cell receptor, STAT1, and indoleamine-pyrrole 2,3-dioxygenase. The numbers of MDSCs tend to increase with cancer burden while inhibiting MDSCs improves disease outcome in murine models. MDSCs also inhibit immune cancer therapeutics. In light of the poor prognosis of metastatic breast cancer in women and the correlation of increasing levels of MDSCs with increasing disease burden, the purposes of this review are to (1) discuss why MDSCs may be important in breast cancer, (2) describe model systems used to study MDSCs in vitro and in vivo, (3) discuss mechanisms involved in MDSC induction/function in breast cancer, and (4) present pre-clinical and clinical studies that explore modulation of the MDSC-immune system interaction in breast cancer. MDSCs inhibit the host immune response in breast cancer patients and diminishing MDSC actions may improve therapeutic outcomes.

Breast Density and Risk of Breast Cancer in Asian Women: A Meta-analysis of Observational Studies.

PubMed

Bae, Jong-Myon; Kim, Eun Hee

2016-11-01

The established theory that breast density is an independent predictor of breast cancer risk is based on studies targeting white women in the West. More Asian women than Western women have dense breasts, but the incidence of breast cancer is lower among Asian women. This meta-analysis investigated the association between breast density in mammography and breast cancer risk in Asian women. PubMed and Scopus were searched, and the final date of publication was set as December 31, 2015. The effect size in each article was calculated using the interval-collapse method. Summary effect sizes (sESs) and 95% confidence intervals (CIs) were calculated by conducting a meta-analysis applying a random effect model. To investigate the dose-response relationship, random effect dose-response meta-regression (RE-DRMR) was conducted. Six analytical epidemiology studies in total were selected, including one cohort study and five case-control studies. A total of 17 datasets were constructed by type of breast density index and menopausal status. In analyzing the subgroups of premenopausal vs. postmenopausal women, the percent density (PD) index was confirmed to be associated with a significantly elevated risk for breast cancer (sES, 2.21; 95% CI, 1.52 to 3.21; I 2 =50.0%). The RE-DRMR results showed that the risk of breast cancer increased 1.73 times for each 25% increase in PD in postmenopausal women (95% CI, 1.20 to 2.47). In Asian women, breast cancer risk increased with breast density measured using the PD index, regardless of menopausal status. We propose the further development of a breast cancer risk prediction model based on the application of PD in Asian women.

Electromechanical Coupling Factor of Breast Tissue as a Biomarker for Breast Cancer.

PubMed

Park, Kihan; Chen, Wenjin; Chekmareva, Marina A; Foran, David J; Desai, Jaydev P

2018-01-01

This research aims to validate a new biomarker of breast cancer by introducing electromechanical coupling factor of breast tissue samples as a possible additional indicator of breast cancer. Since collagen fibril exhibits a structural organization that gives rise to a piezoelectric effect, the difference in collagen density between normal and cancerous tissue can be captured by identifying the corresponding electromechanical coupling factor. The design of a portable diagnostic tool and a microelectromechanical systems (MEMS)-based biochip, which is integrated with a piezoresistive sensing layer for measuring the reaction force as well as a microheater for temperature control, is introduced. To verify that electromechanical coupling factor can be used as a biomarker for breast cancer, the piezoelectric model for breast tissue is described with preliminary experimental results on five sets of normal and invasive ductal carcinoma (IDC) samples in the 25-45 temperature range. While the stiffness of breast tissues can be captured as a representative mechanical signature which allows one to discriminate among tissue types especially in the higher strain region, the electromechanical coupling factor shows more distinct differences between the normal and IDC groups over the entire strain region than the mechanical signature. From the two-sample -test, the electromechanical coupling factor under compression shows statistically significant differences ( 0.0039) between the two groups. The increase in collagen density in breast tissue is an objective and reproducible characteristic of breast cancer. Although characterization of mechanical tissue property has been shown to be useful for differentiating cancerous tissue from normal tissue, using a single parameter may not be sufficient for practical usage due to inherent variation among biological samples. The portable breast cancer diagnostic tool reported in this manuscript shows the feasibility of measuring multiple

Dose-dependent protective effect of breast-feeding against breast cancer among ever-lactated women in Korea.

PubMed

Kim, Yeonju; Choi, Ji-Yeob; Lee, Kyoung-Mu; Park, Sue Kyung; Ahn, Sei-Hyun; Noh, Dong-Young; Hong, Yun-Chul; Kang, Daehee; Yoo, Keun-Young

2007-04-01

Lactation might have a crucial role in an extraordinary increase in breast cancer incidence in Korea, as the proportion of mothers who practised breast-feeding fell dramatically. This hospital-based case-control analysis has been carried out since 1997 to evaluate whether lactation is associated with breast cancer risk in Korean women. Among the eligible study participants, a total of 753 histologically confirmed incident cases and an equal number of controls were included in the analysis. The risk was estimated using unconditional logistic regression models. Family history, older at menopause, more full-term pregnancies increased the risk of breast cancer. Breast cancer risk decreased according to the total months of breast-feeding (P for trend=0.03). Average duration of breast-feeding of 11-12 months reduced risk of breast cancer by 54% compared with the duration of 1-4 months (odds ratio, 0.46; 95% confidence interval, 0.30-0.70). The decreasing risk trend according to average months of breast-feeding was also statistically significant (P for trend=0.02). Moreover, a reduced risk of breast cancer was apparent when analysis was restricted to the first breast-fed child (P for trend=0.006). This study confirms that lactation has an apparent dose-dependent protective effect against breast cancer in Korean women.

Integrin activation controls metastasis in human breast cancer

NASA Astrophysics Data System (ADS)

Felding-Habermann, Brunhilde; O'Toole, Timothy E.; Smith, Jeffrey W.; Fransvea, Emilia; Ruggeri, Zaverio M.; Ginsberg, Mark H.; Hughes, Paul E.; Pampori, Nisar; Shattil, Sanford J.; Saven, Alan; Mueller, Barbara M.

2001-02-01

Metastasis is the primary cause of death in human breast cancer. Metastasis to bone, lungs, liver, and brain involves dissemination of breast cancer cells via the bloodstream and requires adhesion within the vasculature. Blood cell adhesion within the vasculature depends on integrins, a family of transmembrane adhesion receptors, and is regulated by integrin activation. Here we show that integrin v3 supports breast cancer cell attachment under blood flow conditions in an activation-dependent manner. Integrin v3 was found in two distinct functional states in human breast cancer cells. The activated, but not the nonactivated, state supported tumor cell arrest during blood flow through interaction with platelets. Importantly, activated αvβ3 was expressed by freshly isolated metastatic human breast cancer cells and variants of the MDA-MB 435 human breast cancer cell line, derived from mammary fat pad tumors or distant metastases in severe combined immunodeficient mice. Expression of constitutively activated mutant αvβ3D723R, but not αvβ3WT, in MDA-MB 435 cells strongly promoted metastasis in the mouse model. Thus breast cancer cells can exhibit a platelet-interactive and metastatic phenotype that is controlled by the activation of integrin αvβ3. Consequently, alterations within tumors that lead to the aberrant control of integrin activation are expected to adversely affect the course of human breast cancer.

Correlation of breast image alignment using biomechanical modelling

NASA Astrophysics Data System (ADS)

Lee, Angela; Rajagopal, Vijay; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.

2009-02-01

Breast cancer is one of the most common causes of cancer death among women around the world. Researchers have found that a combination of imaging modalities (such as x-ray mammography, magnetic resonance, and ultrasound) leads to more effective diagnosis and management of breast cancers because each imaging modality displays different information about the breast tissues. In order to aid clinicians in interpreting the breast images from different modalities, we have developed a computational framework for generating individual-specific, 3D, finite element (FE) models of the breast. Medical images are embedded into this model, which is subsequently used to simulate the large deformations that the breasts undergo during different imaging procedures, thus warping the medical images to the deformed views of the breast in the different modalities. In this way, medical images of the breast taken in different geometric configurations (compression, gravity, etc.) can be aligned according to physically feasible transformations. In order to analyse the accuracy of the biomechanical model predictions, squared normalised cross correlation (NCC2) was used to provide both local and global comparisons of the model-warped images with clinical images of the breast subject to different gravity loaded states. The local comparison results were helpful in indicating the areas for improvement in the biomechanical model. To improve the modelling accuracy, we will need to investigate the incorporation of breast tissue heterogeneity into the model and altering the boundary conditions for the breast model. A biomechanical image registration tool of this kind will help radiologists to provide more reliable diagnosis and localisation of breast cancer.

Joint relative risks for estrogen receptor-positive breast cancer from a clinical model, polygenic risk score, and sex hormones.

PubMed

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C; Leung, Jessica W T; Tice, Jeffrey A; Ziv, Elad; Kerlikowske, Karla; Cummings, Steven R

2017-11-01

Models that predict the risk of estrogen receptor (ER)-positive breast cancers may improve our ability to target chemoprevention. We investigated the contributions of sex hormones to the discrimination of the Breast Cancer Surveillance Consortium (BCSC) risk model and a polygenic risk score comprised of 83 single nucleotide polymorphisms. We conducted a nested case-control study of 110 women with ER-positive breast cancers and 214 matched controls within a mammography screening cohort. Participants were postmenopausal and not on hormonal therapy. The associations of estradiol, estrone, testosterone, and sex hormone binding globulin with ER-positive breast cancer were evaluated using conditional logistic regression. We assessed the individual and combined discrimination of estradiol, the BCSC risk score, and polygenic risk score using the area under the receiver operating characteristic curve (AUROC). Of the sex hormones assessed, estradiol (OR 3.64, 95% CI 1.64-8.06 for top vs bottom quartile), and to a lesser degree estrone, was most strongly associated with ER-positive breast cancer in unadjusted analysis. The BCSC risk score (OR 1.32, 95% CI 1.00-1.75 per 1% increase) and polygenic risk score (OR 1.58, 95% CI 1.06-2.36 per standard deviation) were also associated with ER-positive cancers. A model containing the BCSC risk score, polygenic risk score, and estradiol levels showed good discrimination for ER-positive cancers (AUROC 0.72, 95% CI 0.65-0.79), representing a significant improvement over the BCSC risk score (AUROC 0.58, 95% CI 0.50-0.65). Adding estradiol and a polygenic risk score to a clinical risk model improves discrimination for postmenopausal ER-positive breast cancers.

Melatonin: an inhibitor of breast cancer.

PubMed

Hill, Steven M; Belancio, Victoria P; Dauchy, Robert T; Xiang, Shulin; Brimer, Samantha; Mao, Lulu; Hauch, Adam; Lundberg, Peter W; Summers, Whitney; Yuan, Lin; Frasch, Tripp; Blask, David E

2015-06-01

The present review discusses recent work on melatonin-mediated circadian regulation, the metabolic and molecular signaling mechanisms that are involved in human breast cancer growth, and the associated consequences of circadian disruption by exposure to light at night (LEN). The anti-cancer actions of the circadian melatonin signal in human breast cancer cell lines and xenografts heavily involve MT1 receptor-mediated mechanisms. In estrogen receptor alpha (ERα)-positive human breast cancer, melatonin suppresses ERα mRNA expression and ERα transcriptional activity via the MT1 receptor. Melatonin also regulates the transactivation of other members of the nuclear receptor superfamily, estrogen-metabolizing enzymes, and the expression of core clock and clock-related genes. Furthermore, melatonin also suppresses tumor aerobic metabolism (the Warburg effect) and, subsequently, cell-signaling pathways critical to cell proliferation, cell survival, metastasis, and drug resistance. Melatonin demonstrates both cytostatic and cytotoxic activity in breast cancer cells that appears to be cell type-specific. Melatonin also possesses anti-invasive/anti-metastatic actions that involve multiple pathways, including inhibition of p38 MAPK and repression of epithelial-mesenchymal transition (EMT). Studies have demonstrated that melatonin promotes genomic stability by inhibiting the expression of LINE-1 retrotransposons. Finally, research in animal and human models has indicated that LEN-induced disruption of the circadian nocturnal melatonin signal promotes the growth, metabolism, and signaling of human breast cancer and drives breast tumors to endocrine and chemotherapeutic resistance. These data provide the strongest understanding and support of the mechanisms that underpin the epidemiologic demonstration of elevated breast cancer risk in night-shift workers and other individuals who are increasingly exposed to LEN. © 2015 Society for Endocrinology.

Health behaviour models and patient preferences regarding nutrition and physical activity after breast or prostate cancer diagnosis.

PubMed

Green, H J; Steinnagel, G; Morris, C; Laakso, E L

2014-09-01

This study aimed to improve understanding of prostate and breast cancer survivors' physical activity and nutrition and the association of these behaviours with two models. The first model, the Commonsense Self-Regulation Model (CSM), addresses cognitive and emotional perceptions of illness whereas the Transtheoretical Model (TTM) focuses on stage of readiness to engage in a behaviour. Participants who had been diagnosed with either breast (n = 145) or prostate cancer (n = 92) completed measures of demographic and health information, illness representations, stage of change, self-efficacy and preferences regarding health behaviour interventions. Health behaviours in the past seven days were measured via the International Physical Activity Questionnaire and concordance with national dietary guidelines. As hypothesised, TTM variables (stage of change and self-efficacy) demonstrated independent associations with physical activity and nutrition in regression analyses. CSM variables were not independently associated with absolute levels of health behaviours but both TTM and CSM variables were independently associated with self-reported changes in physical activity and nutrition following prostate or breast cancer diagnosis. Many participants reported high interest in receiving lifestyle interventions, particularly soon after diagnosis. Results supported application of the TTM and CSM models for strengthening behaviour change intentions and actions in breast and prostate cancer survivors. © 2014 John Wiley & Sons Ltd.

Breast Cancer-Targeted Nuclear Drug Delivery Overcoming Drug Resistance for Breast Cancer Chemotherapy

DTIC Science & Technology

2011-09-01

breast-cancer-targeted nuclear drug delivery carriers , but we found that the ability of the PEI to disrupt the endosome/lysosome membrane was not...AD_________________ Award Number: W81XWH-09-1-0502 TITLE: Breast Cancer-Targeted Nuclear Drug ...Delivery Overcoming Drug Resistance for Breast Cancer Chemotherapy PRINCIPAL INVESTIGATOR: Youqing Shen, Ph.D

Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer.

PubMed

Duffy, Stephen W; Morrish, Oliver W E; Allgood, Prue C; Black, Richard; Gillan, Maureen G C; Willsher, Paula; Cooke, Julie; Duncan, Karen A; Michell, Michael J; Dobson, Hilary M; Maroni, Roberta; Lim, Yit Y; Purushothaman, Hema N; Suaris, Tamara; Astley, Susan M; Young, Kenneth C; Tucker, Lorraine; Gilbert, Fiona J

2018-01-01

Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer. To assess the association of breast density with presence of cancer by measuring mammographic density visually as a percentage, and with two automated volumetric methods, Quantra™ and VolparaDensity™. The TOMosynthesis with digital MammographY (TOMMY) study of digital breast tomosynthesis in the Breast Screening Programme of the National Health Service (NHS) of the United Kingdom (UK) included 6020 breast screening assessment cases (of whom 1158 had breast cancer) and 1040 screened women with a family history of breast cancer (of whom two had breast cancer). We assessed the association of each measure with breast cancer risk in these populations at enhanced risk, using logistic regression adjusted for age and total breast volume as a surrogate for body mass index (BMI). All density measures showed a positive association with presence of cancer and all declined with age. The strongest effect was seen with Volpara absolute density, with a significant 3% (95% CI 1-5%) increase in risk per 10 cm 3 of dense tissue. The effect of Volpara volumetric density on risk was stronger for large and grade 3 tumours. Automated absolute breast density is a predictor of breast cancer risk in populations at enhanced risk due to either positive mammographic findings or family history. In the screening context, density could be a trigger for more intensive imaging. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identifying Breast Cancer Oncogenes

DTIC Science & Technology

2010-10-01

08-1-0767 TITLE: Identifying Breast Cancer Oncogenes PRINCIPAL INVESTIGATOR: Yashaswi Shrestha... Breast Cancer Oncogenes 5a. CONTRACT NUMBER W81XWH-08-1-0767 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Yashaswi...SUPPLEMENTARY NOTES 14. ABSTRACT Breast cancer is attributed to genetic alterations, the majority of which are yet to be characterized. Oncogenic

Breast cancer staging

MedlinePlus

... this page: //medlineplus.gov/ency/patientinstructions/000911.htm Breast cancer staging To use the sharing features on this ... Once your health care team knows you have breast cancer , they will do more tests to stage it. ...

Biomechanical modelling for breast image registration

NASA Astrophysics Data System (ADS)

Lee, Angela; Rajagopal, Vijay; Chung, Jae-Hoon; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.

2008-03-01

Breast cancer is a leading cause of death in women. Tumours are usually detected by palpation or X-ray mammography followed by further imaging, such as magnetic resonance imaging (MRI) or ultrasound. The aim of this research is to develop a biophysically-based computational tool that will allow accurate collocation of features (such as suspicious lesions) across multiple imaging views and modalities in order to improve clinicians' diagnosis of breast cancer. We have developed a computational framework for generating individual-specific, 3D finite element models of the breast. MR images were obtained of the breast under gravity loading and neutrally buoyant conditions. Neutrally buoyant breast images, obtained whilst immersing the breast in water, were used to estimate the unloaded geometry of the breast (for present purposes, we have assumed that the densities of water and breast tissue are equal). These images were segmented to isolate the breast tissues, and a tricubic Hermite finite element mesh was fitted to the digitised data points in order to produce a customized breast model. The model was deformed, in accordance with finite deformation elasticity theory, to predict the gravity loaded state of the breast in the prone position. The unloaded breast images were embedded into the reference model and warped based on the predicted deformation. In order to analyse the accuracy of the model predictions, the cross-correlation image comparison metric was used to compare the warped, resampled images with the clinical images of the prone gravity loaded state. We believe that a biomechanical image registration tool of this kind will aid radiologists to provide more reliable diagnosis and localisation of breast cancer.

Second cancer risk after 3D-CRT, IMRT and VMAT for breast cancer.

PubMed

Abo-Madyan, Yasser; Aziz, Muhammad Hammad; Aly, Moamen M O M; Schneider, Frank; Sperk, Elena; Clausen, Sven; Giordano, Frank A; Herskind, Carsten; Steil, Volker; Wenz, Frederik; Glatting, Gerhard

2014-03-01

Second cancer risk after breast conserving therapy is becoming more important due to improved long term survival rates. In this study, we estimate the risks for developing a solid second cancer after radiotherapy of breast cancer using the concept of organ equivalent dose (OED). Computer-tomography scans of 10 representative breast cancer patients were selected for this study. Three-dimensional conformal radiotherapy (3D-CRT), tangential intensity modulated radiotherapy (t-IMRT), multibeam intensity modulated radiotherapy (m-IMRT), and volumetric modulated arc therapy (VMAT) were planned to deliver a total dose of 50 Gy in 2 Gy fractions. Differential dose volume histograms (dDVHs) were created and the OEDs calculated. Second cancer risks of ipsilateral, contralateral lung and contralateral breast cancer were estimated using linear, linear-exponential and plateau models for second cancer risk. Compared to 3D-CRT, cumulative excess absolute risks (EAR) for t-IMRT, m-IMRT and VMAT were increased by 2 ± 15%, 131 ± 85%, 123 ± 66% for the linear-exponential risk model, 9 ± 22%, 82 ± 96%, 71 ± 82% for the linear and 3 ± 14%, 123 ± 78%, 113 ± 61% for the plateau model, respectively. Second cancer risk after 3D-CRT or t-IMRT is lower than for m-IMRT or VMAT by about 34% for the linear model and 50% for the linear-exponential and plateau models, respectively. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Targeted Therapy for Breast Cancer Prevention

PubMed Central

den Hollander, Petra; Savage, Michelle I.; Brown, Powel H.

2013-01-01

With a better understanding of the etiology of breast cancer, molecularly targeted drugs have been developed and are being testing for the treatment and prevention of breast cancer. Targeted drugs that inhibit the estrogen receptor (ER) or estrogen-activated pathways include the selective ER modulators (tamoxifen, raloxifene, and lasofoxifene) and aromatase inhibitors (AIs) (anastrozole, letrozole, and exemestane) have been tested in preclinical and clinical studies. Tamoxifen and raloxifene have been shown to reduce the risk of breast cancer and promising results of AIs in breast cancer trials, suggest that AIs might be even more effective in the prevention of ER-positive breast cancer. However, these agents only prevent ER-positive breast cancer. Therefore, current research is focused on identifying preventive therapies for other forms of breast cancer such as human epidermal growth factor receptor 2 (HER2)-positive and triple-negative breast cancer (TNBC, breast cancer that does express ER, progesterone receptor, or HER2). HER2-positive breast cancers are currently treated with anti-HER2 therapies including trastuzumab and lapatinib, and preclinical and clinical studies are now being conducted to test these drugs for the prevention of HER2-positive breast cancers. Several promising agents currently being tested in cancer prevention trials for the prevention of TNBC include poly(ADP-ribose) polymerase inhibitors, vitamin D, and rexinoids, both of which activate nuclear hormone receptors (the vitamin D and retinoid X receptors). This review discusses currently used breast cancer preventive drugs, and describes the progress of research striving to identify and develop more effective preventive agents for all forms of breast cancer. PMID:24069582

Novel Approaches to Breast Cancer Prevention and Inhibition of Metastases

DTIC Science & Technology

2014-10-01

functional characterization of candidate breast cancer genes. The transgenic RNAi library is covering the whole Drosophila genome , giving us an...cancer prevention trials in BRCA1 carriers using RANKL blockade. Using Drosophila modeling of Ras-driven transformation, we performed a near- genome ... Genome wide functional genetics, haploid stem cells, Drosophila cancer modeling, breast cancer prevention, BRCA1 carriers 16. SECURITY

Breast Cancer and Bone Loss

MedlinePlus

... Resource Find an Endocrinologist Search Breast Cancer and Bone Loss July 2010 Download PDFs English Espanol Editors ... What is the link between breast cancer and bone loss? Certain treatments for breast cancer can lead ...

Protective Effect of Perindopril on Tumor Progression and Angiogenesis in Animal Model of Breast Cancer.

PubMed

Patel, Snehal S; Nakka, Surender

2017-01-01

Studies have shown that the renin angiotensin system via angiogenesis is involved in tumor development. Therefore, objective of the present study was to examine the effect of perindopril on tumor growth and angiogenesis in animal models of breast cancer. In the present study, the effect of perindopril on tumor development of mammary gland cancer induced by 7,12-dimethylbenz[a]anthracene, mouse tumor xenograft and corneal micropocket model has been investigated. Anti-angiogenic effect by chick yolk sac membrane assay has also been studied. In the present study, it has been found that perindopril produced a significant inhibition of tumor growth, in DMBA induced breast cancer. Treatment also produced significant suppression of cancer biomarkers such as lactate dehydrogenase, gamma glutamyl transferase and inflammatory markers such as C-reactive protein, erythrocyte sedimentation rate. Histopathological analysis also showed that perindopril was able to inhibit tumor development by the inhibition of hyperplastic lesions. Perindopril produced significant inhibition of tumor growth, in a mouse xenograft model and caused inhibition of neovascularization in the corneal micropocket model. In chick yolk sac membrane assay, perindopril showed inhibition of vascular growth and reduced blood vessel formation. Therefore, perindopril is widely used in clinical practice, may represent a neo-adjuvant therapy for treatment of breast cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Physical Mechanism and Global Quantification of Breast Cancer

PubMed Central

Yu, Chong; Wang, Jin

2016-01-01

Initiation and progression of cancer depend on many factors. Those on the genetic level are often considered crucial. To gain insight into the physical mechanisms of breast cancer, we construct a gene regulatory network (GRN) which reflects both genetic and environmental aspects of breast cancer. The construction of the GRN is based on available experimental data. Three basins of attraction, representing the normal, premalignant and cancer states respectively, were found on the phenotypic landscape. The progression of breast cancer can be seen as switching transitions between different state basins. We quantified the stabilities and kinetic paths of the three state basins to uncover the biological process of breast cancer formation. The gene expression levels at each state were obtained, which can be tested directly in experiments. Furthermore, by performing global sensitivity analysis on the landscape topography, six key genes (HER2, MDM2, TP53, BRCA1, ATM, CDK2) and four regulations (HER2⊣TP53, CDK2⊣BRCA1, ATM→MDM2, TP53→ATM) were identified as being critical for breast cancer. Interestingly, HER2 and MDM2 are the most popular targets for treating breast cancer. BRCA1 and TP53 are the most important oncogene of breast cancer and tumor suppressor gene, respectively. This further validates the feasibility of our model and the reliability of our prediction results. The regulation ATM→MDM2 has been extensive studied on DNA damage but not on breast cancer. We notice the importance of ATM→MDM2 on breast cancer. Previous studies of breast cancer have often focused on individual genes and the anti-cancer drugs are mainly used to target the individual genes. Our results show that the network-based strategy is more effective on treating breast cancer. The landscape approach serves as a new strategy for analyzing breast cancer on both the genetic and epigenetic levels and can help on designing network based medicine for breast cancer. PMID:27410227

Genetics Home Reference: breast cancer

MedlinePlus

... Email Facebook Twitter Home Health Conditions Breast cancer Breast cancer Printable PDF Open All Close All Enable Javascript to view the expand/collapse boxes. Description Breast cancer is a disease in which certain cells in ...

Awareness and current knowledge of breast cancer.

PubMed

Akram, Muhammad; Iqbal, Mehwish; Daniyal, Muhammad; Khan, Asmat Ullah

2017-10-02

Breast cancer remains a worldwide public health dilemma and is currently the most common tumour in the globe. Awareness of breast cancer, public attentiveness, and advancement in breast imaging has made a positive impact on recognition and screening of breast cancer. Breast cancer is life-threatening disease in females and the leading cause of mortality among women population. For the previous two decades, studies related to the breast cancer has guided to astonishing advancement in our understanding of the breast cancer, resulting in further proficient treatments. Amongst all the malignant diseases, breast cancer is considered as one of the leading cause of death in post menopausal women accounting for 23% of all cancer deaths. It is a global issue now, but still it is diagnosed in their advanced stages due to the negligence of women regarding the self inspection and clinical examination of the breast. This review addresses anatomy of the breast, risk factors, epidemiology of breast cancer, pathogenesis of breast cancer, stages of breast cancer, diagnostic investigations and treatment including chemotherapy, surgery, targeted therapies, hormone replacement therapy, radiation therapy, complementary therapies, gene therapy and stem-cell therapy etc for breast cancer.

Loss in working years after a breast cancer diagnosis.

PubMed

Plym, Anna; Bower, Hannah; Fredriksson, Irma; Holmberg, Lars; Lambert, Paul C; Lambe, Mats

2018-03-06

Breast cancer can negatively influence working life, but it is unclear how many working years women with breast cancer can expect to lose. Women diagnosed with breast cancer between 1997 and 2012 were identified in the Breast Cancer Data Base Sweden (N=19 661), together with breast cancer-free comparison women (N=81 303). Using flexible parametric survival modelling, the loss in working years was calculated as the difference in the remaining years in the work force between women with and without breast cancer. Women aged 50 years at diagnosis with stage I disease lost on average 0.5 years (95% CI, 0.2-0.7) of their remaining working time; the corresponding estimates were 0.9 years (0.5-1.2) in stage II, 2.5 years (1.9-3.1) in stage III and 8.1 years (6.5-9.7) in stage IV. Women with in situ breast cancer did not lose any working years. The strongest treatment determinant was axillary lymph node dissection. We found a loss in working years not only in late but also in early-stage breast cancer. Although it is reassuring that some groups had no or only a modest work loss, the economic consequences for society are considerable given the large number of women annually diagnosed with breast cancer.

Coffee consumption modifies risk of estrogen-receptor negative breast cancer

PubMed Central

2011-01-01

Introduction Breast cancer is a complex disease and may be sub-divided into hormone-responsive (estrogen receptor (ER) positive) and non-hormone-responsive subtypes (ER-negative). Some evidence suggests that heterogeneity exists in the associations between coffee consumption and breast cancer risk, according to different estrogen receptor subtypes. We assessed the association between coffee consumption and postmenopausal breast cancer risk in a large population-based study (2,818 cases and 3,111 controls), overall, and stratified by ER tumour subtypes. Methods Odds ratios (OR) and corresponding 95% confidence intervals (CI) were estimated using the multivariate logistic regression models fitted to examine breast cancer risk in a stratified case-control analysis. Heterogeneity among ER subtypes was evaluated in a case-only analysis, by fitting binary logistic regression models, treating ER status as a dependent variable, with coffee consumption included as a covariate. Results In the Swedish study, coffee consumption was associated with a modest decrease in overall breast cancer risk in the age-adjusted model (OR> 5 cups/day compared to OR≤ 1 cup/day: 0.80, 95% CI: 0.64, 0.99, P trend = 0.028). In the stratified case-control analyses, a significant reduction in the risk of ER-negative breast cancer was observed in heavy coffee drinkers (OR> 5 cups/day compared to OR≤ 1 cup/day : 0.43, 95% CI: 0.25, 0.72, P trend = 0.0003) in a multivariate-adjusted model. The breast cancer risk reduction associated with higher coffee consumption was significantly higher for ER-negative compared to ER-positive tumours (P heterogeneity (age-adjusted) = 0.004). Conclusions A high daily intake of coffee was found to be associated with a statistically significant decrease in ER-negative breast cancer among postmenopausal women. PMID:21569535

Breast cancer patterns and lifetime risk of developing breast cancer among Puerto Rican females.

PubMed

Nazario, C M; Figueroa-Vallés, N; Rosario, R V

2000-03-01

The purpose of this study was to evaluate the epidemiologic patterns of breast cancer and to estimate the lifetime risk probability of developing breast cancer among Hispanic females using cancer data from Puerto Rico. The age-adjusted breast cancer incidence rate (per 100,000) in Puerto Rico increased from 15.3 in 1960-1964 to 43.3 in 1985-1989. The age-adjusted breast cancer mortality rate (per 100,000) increased from 5.7 to 10.6 comparing the same two time periods (1960-1964 vs 1985-1989). Nevertheless, in 1985-1989 breast cancer incidence rate was higher in US White females (110.8 per 100,000) compared to Puerto Rican females (51.4 per 100,000; age-adjusted to the 1970 US standard population). The breast cancer mortality rate was also higher in US White females (27.4 per 100,000) than in Puerto Rican females (15.1 per 100,000; age-adjusted to the 1970 US standard population) during 1985-1989. A multiple decrement life table was constructed applying age-specific incidence and mortality rates from cross-sectional data sets (1980-1984 and 1985-1989 data for Puerto Rican females and 1987-1989 SEER data sets for US White and Black females) to a hypothetical cohort of 10,000,000 women. The probability of developing invasive breast cancer was computed for the three groups using the long version of DEVCAN: Probability of DEVeloping CANcer software, version 3.3. The lifetime risk of developing breast cancer was 5.4% for Puerto Rican females, compared to 8.8% for US Black females and 13.0% for US White females. Lifetime risk for Puerto Rican females increased from 4.5% in 1980-1984 to 5.4% in 1985-1989. Lifetime risk of breast cancer appears to be increasing in Puerto Rico, but remains lower than the probability for US White females. Therefore, the application of lifetime probability of developing invasive breast cancer estimated for the US female population will overestimate the risk for the Puerto Rican female population.

Endocrine disruption of the epigenome: a breast cancer link

PubMed Central

Knower, Kevin C; To, Sarah Q; Leung, Yuet-Kin; Ho, Shuk-Mei; Clyne, Colin D

2015-01-01

The heritable component of breast cancer accounts for only a small proportion of total incidences. Environmental and lifestyle factors are therefore considered to among the major influencing components increasing breast cancer risk. Endocrine-disrupting chemicals (EDCs) are ubiquitous in the environment. The estrogenic property of EDCs has thus shown many associations between ongoing exposures and the development of endocrine-related diseases, including breast cancer. The environment consists of a heterogenous population of EDCs and despite many identified modes of action, including that of altering the epigenome, drawing definitive correlations regarding breast cancer has been a point of much discussion. In this review, we describe in detail well-characterized EDCs and their actions in the environment, their ability to disrupt mammary gland formation in animal and human experimental models and their associations with exposure and breast cancer risk. We also highlight the susceptibility of early-life exposure to each EDC to mediate epigenetic alterations, and where possible describe how these epigenome changes influence breast cancer risk. PMID:24532474

Second cancers in patients with male breast cancer: a literature review.

PubMed

Grenader, Tal; Goldberg, Anthony; Shavit, Linda

2008-06-01

The risk of second malignancies among female breast cancer patients has been studied for decades. In contrast, very little is known about second primary tumors in men. Risk factors for breast cancer in men, including genetic, hormonal and environmental factors, provide parallels to the etiology of breast cancer in women. This review considers the literature related to the risk of developing a second cancer in patients with male breast cancer. A systematic review of the literature between 1966 and 2007 was conducted and acceptable articles used for analysis. All retrieved articles were screened to identify any papers that had been missed. Studies were included if they discussed the risk of subsequent malignancy in patients with male breast cancer. Patients with history of male breast cancer have an increased risk of a second ipsilateral, or contralateral breast cancer (standardized incidence ratio 30-110). The risk of subsequent contralateral breast cancer was highest in men under 50 years of age at the time of the diagnosis of the initial cancer. The data on non-breast second primary cancers is diverse. One study has suggested an increased incidence of cancers of the small intestine, prostate, rectum and pancreas, and of non-melanoma skin cancer and myeloid leukaemia. Other investigators did not find an increase in the overall risk of subsequent cancer development in men diagnosed initially with primary breast cancer. Although sarcoma, lung and esophageal cancers are well recognized complications of radiation therapy for female breast cancer, there is no evidence for the association of these cancers following radiation therapy in male breast cancer. Although the incidence of second primary cancer in patients with primary male breast cancer requires further study, male breast cancer survivors should probably undergo periodic screening for the early detection of second breast cancers and other adverse health effects.

The need for supplemental breast cancer screening modalities: a perspective of population-based breast cancer screening programs in Japan.

PubMed

Uematsu, Takayoshi

2017-01-01

This article discusses possible supplemental breast cancer screening modalities for younger women with dense breasts from a perspective of population-based breast cancer screening program in Japan. Supplemental breast cancer screening modalities have been proposed to increase the sensitivity and detection rates of early stage breast cancer in women with dense breasts; however, there are no global guidelines that recommend the use of supplemental breast cancer screening modalities in such women. Also, no criterion standard exists for breast density assessment. Based on the current situation of breast imaging in Japan, the possible supplemental breast cancer screening modalities are ultrasonography, digital breast tomosynthesis, and breast magnetic resonance imaging. An appropriate population-based breast cancer screening program based on the balance between cost and benefit should be a high priority. Further research based on evidence-based medicine is encouraged. It is very important that the ethnicity, workforce, workflow, and resources for breast cancer screening in each country should be considered when considering supplemental breast cancer screening modalities for women with dense breasts.

2'-Hydroxyflavanone: A novel strategy for targeting breast cancer.

PubMed

Singhal, Jyotsana; Nagaprashantha, Lokesh; Chikara, Shireen; Awasthi, Sanjay; Horne, David; Singhal, Sharad S

2017-09-26

Breast cancer is the most common cancer in women that is driven by cross-talk with hormonal and cellular signaling pathways. The natural phytochemicals, due to broad-spectrum anti-inflammatory and anti-cancerous properties, present with novel opportunities for targeting breast cancer. Intake of citrus fruits is known to reduce the risk for incidence of breast cancer. Hence, we tested the efficacy of citrus flavonoid 2'-hydroxyflavanone (2HF) in breast cancer. 2HF inhibited survival, clonogenic ability, cell cycle progression and induced apoptosis in breast cancer cells. 2HF also decreased VEGF levels and inhibited migratory capacity of breast cancer cells. Administration of 2HF led to regression of triple-negative MDA-MB-231 tumors in the mice xenograft model. 2HF decreased the levels of RLIP76 both in vitro studies and in vivo MDA-MB-231 xenograft model of breast cancer. Western blot and histopathological analyses of resected tumors showed a decline in the levels of survival and proliferation markers Ki67, pAkt, survivin, and cell cycle proteins CDK4 and cyclin B1. 2HF treatment led to inhibition of angiogenesis as determined by decreased VEGF levels in vitro and angiogenesis marker CD31 in vivo . 2HF reversed the pro-/anti-apoptotic ratio of BAX/BCL-2 by decreasing anti-apoptotic protein BCL-2 and increasing pro-apoptotic proteins BAX and BIM in vivo . 2HF also decreased the mesenchymal markers vimentin and fibronectin along with causing a parallel increase in pro-differentiation protein E-cadherin. Collectively, the ability of 2HF to decrease RLIP76, VEGF and regulate critical proliferative, apoptotic and differentiation proteins together provides strong rationale to further develop 2HF based interventions for targeting breast cancer.

Population-Attributable Risk Proportion of Clinical Risk Factors for Breast Cancer.

PubMed

Engmann, Natalie J; Golmakani, Marzieh K; Miglioretti, Diana L; Sprague, Brian L; Kerlikowske, Karla

2017-09-01

Many established breast cancer risk factors are used in clinical risk prediction models, although the proportion of breast cancers explained by these factors is unknown. To determine the population-attributable risk proportion (PARP) for breast cancer associated with clinical breast cancer risk factors among premenopausal and postmenopausal women. Case-control study with 1:10 matching on age, year of risk factor assessment, and Breast Cancer Surveillance Consortium (BCSC) registry. Risk factor data were collected prospectively from January 1, 1996, through October 31, 2012, from BCSC community-based breast imaging facilities. A total of 18 437 women with invasive breast cancer or ductal carcinoma in situ were enrolled as cases and matched to 184 309 women without breast cancer, with a total of 58 146 premenopausal and 144 600 postmenopausal women enrolled in the study. Breast Imaging Reporting and Data System (BI-RADS) breast density (heterogeneously or extremely dense vs scattered fibroglandular densities), first-degree family history of breast cancer, body mass index (>25 vs 18.5-25), history of benign breast biopsy, and nulliparity or age at first birth (≥30 years vs <30 years). Population-attributable risk proportion of breast cancer. Of the 18 437 women with breast cancer, the mean (SD) age was 46.3 (3.7) years among premenopausal women and 61.7 (7.2) years among the postmenopausal women. Overall, 4747 (89.8%) premenopausal and 12 502 (95.1%) postmenopausal women with breast cancer had at least 1 breast cancer risk factor. The combined PARP of all risk factors was 52.7% (95% CI, 49.1%-56.3%) among premenopausal women and 54.7% (95% CI, 46.5%-54.7%) among postmenopausal women. Breast density was the most prevalent risk factor for both premenopausal and postmenopausal women and had the largest effect on the PARP; 39.3% (95% CI, 36.6%-42.0%) of premenopausal and 26.2% (95% CI, 24.4%-28.0%) of postmenopausal breast cancers could potentially be

Relationship between preoperative breast MRI and surgical treatment of non-metastatic breast cancer.

PubMed

Onega, Tracy; Weiss, Julie E; Goodrich, Martha E; Zhu, Weiwei; DeMartini, Wendy B; Kerlikowske, Karla; Ozanne, Elissa; Tosteson, Anna N A; Henderson, Louise M; Buist, Diana S M; Wernli, Karen J; Herschorn, Sally D; Hotaling, Elise; O'Donoghue, Cristina; Hubbard, Rebecca

2017-12-01

More extensive surgical treatments for early stage breast cancer are increasing. The patterns of preoperative MRI overall and by stage for this trend has not been well established. Using Breast Cancer Surveillance Consortium registry data from 2010 through 2014, we identified women with an incident non-metastatic breast cancer and determined use of preoperative MRI and initial surgical treatment (mastectomy, with or without contralateral prophylactic mastectomy (CPM), reconstruction, and breast conserving surgery ± radiation). Clinical and sociodemographic covariates were included in multivariable logistic regression models to estimate adjusted odds ratios and 95% confidence intervals. Of the 13 097 women, 2217 (16.9%) had a preoperative MRI. Among the women with MRI, results indicated 32% higher odds of unilateral mastectomy compared to breast conserving surgery and of mastectomy with CPM compared to unilateral mastectomy. Women with preoperative MRI also had 56% higher odds of reconstruction. Preoperative MRI in women with DCIS and early stage invasive breast cancer is associated with more frequent mastectomy, CPM, and reconstruction surgical treatment. Use of more extensive surgical treatment and reconstruction among women with DCIS and early stage invasive cancer whom undergo MRI warrants further investigation. © 2017 Wiley Periodicals, Inc.

A Genetic Interaction Screen for Breast Cancer Progression Driver Genes

DTIC Science & Technology

2013-06-01

analysis of genetic alterations in human breast cancers has revealed that individual tumors accumulate mutations in approximately ninety different genes ...cancer. We performed a screen to test the roles of seventy breast cancer mutated genes in mouse mammary tumorigenesis using the MMTV-PyVT mouse breast...cancer model and piggyBac insertional mutation strains. We found that insertional mutations in 23 genes altered the onset of tumor formation and four

Breast Cancer Basics and You

MedlinePlus

... page please turn JavaScript on. Feature: Screening For Breast Cancer Breast Cancer Basics and You Past Issues / Summer 2014 Table ... more than 232,670 new cases of female breast cancer in the United States in 2014. More than ...

Retrospective observation on contribution and limitations of screening for breast cancer with mammography in Korea: detection rate of breast cancer and incidence rate of interval cancer of the breast.

PubMed

Lee, Kunsei; Kim, Hyeongsu; Lee, Jung Hyun; Jeong, Hyoseon; Shin, Soon Ae; Han, Taehwa; Seo, Young Lan; Yoo, Youngbum; Nam, Sang Eun; Park, Jong Heon; Park, Yoo Mi

2016-11-18

The purpose of this study was to determine the benefits and limitations of screening for breast cancer using mammography. Descriptive design with follow-up was used in the study. Data from breast cancer screening and health insurance claim data were used. The study population consisted of all participants in breast cancer screening from 2009 to 2014. Crude detection rate, positive predictive value and sensitivity and specificity of breast cancer screening and, incidence rate of interval cancer of the breast were calculated. The crude detection rate of breast cancer screening per 100,000 participants increased from 126.3 in 2009 to 182.1 in 2014. The positive predictive value of breast cancer screening per 100,000 positives increased from 741.2 in 2009 to 1,367.9 in 2014. The incidence rate of interval cancer of the breast per 100,000 negatives increased from 51.7 in 2009 to 76.3 in 2014. The sensitivities of screening for breast cancer were 74.6% in 2009 and 75.1% in 2014 and the specificities were 83.1% in 2009 and 85.7% in 2014. To increase the detection rate of breast cancer by breast cancer screening using mammography, the participation rate should be higher and an environment where accurate mammography and reading can be performed and reinforcement of quality control are required. To reduce the incidence rate of interval cancer of the breast, it will be necessary to educate women after their 20s to perform self-examination of the breast once a month regardless of participation in screening for breast cancer.

Breast cancer: updates and advances in 2016.

PubMed

Giordano, Sara B; Gradishar, William

2017-02-01

Approximately 1 in 8 US women (12%) will develop invasive breast cancer over the course of her lifetime. In 2016, an estimated 246,660 new cases of invasive breast cancer are expected to be diagnosed and approximately 40,450 would die as a result of it. The global burden of breast cancer exceeds all other cancers and the incidence is increasing. The heterogeneity of breast cancer makes it a challenging solid tumor to diagnose and treat. This review focuses on the recent advances in breast cancer therapy including hormonal treatment of metastatic breast cancer, targeting cyclin-dependent kinases (CDK) 4/6 in breast cancer, updates in targeting human epidermal growth factor receptor 2 (HER2) positive breast cancer, adaptive randomization trial design and cancer genetic risk assessment. Breast cancer is a heterogeneous disease and targeted therapy is improving the outcomes of women. The use of cyclin-dependent kinase inhibitors (CDK) 4/6 have demonstrated a substantial improvement in progression-free survival in the first line setting of metastatic hormone receptor positive breast cancer. And newer agents directed at HER2 continue to revolutionize HER2-positive breast cancer treatment. This review highlights the recent updates in breast cancer treatment, new concepts in clinical trial design and provides a current overview of cancer genetic risk assessment.

Identifying Breast Cancer Oncogenes

DTIC Science & Technology

2009-10-01

study by Boehm et al. (2007) identified IKBKE as a breast cancer oncogene that cooperates with HMLE -MEKDD to replace the function of myr-AKT in...1-0767 TITLE: Identifying Breast Cancer Oncogenes ~ PRINCIPAL INVESTIGATOR: Yashaswi Shrestha...Identifying Breast Cancer Oncogenes 5a. CONTRACT NUMBER W81XWH-08-1-0767 5b. GRANT NUMBER BC083061 - PreDoc 5c. PROGRAM ELEMENT NUMBER 6

Health Beliefs of Midwifery Students at Istanbul University about Breast Cancer and Breast Self-Examination Acknowledgements.

PubMed

Gençtürk, Nuran; Demirezen, Esma; Ay, Fatma

2017-12-01

Knowing the attitudes and beliefs of midwifery students toward breast cancer and breast self-examination (BSE) practice may reduce breast cancer-related deaths by increasing breast cancer awareness. This study was conducted to examine the attitudes and beliefs of midwifery students toward breast cancer and the BSE practice. The study was conducted with 160 midwifery students at Istanbul University as a descriptive, cross-sectional study. Data were collected by a part of Champion's Health Belief Model Scale and a self-administered questionnaire. The descriptive characteristics were given as frequencies and percentages. The evaluation was done with Kruskal-Wallis test, a non-parametric test. It has been observed 70.0 % among midwifery students have knowledge of breast cancer. 90.0 % of midwifery students know about BSE, however only 14.4 % among them practice BSE regularly every month. The benefit, barrier and confidence sub-dimension scores were positively associated with BSE practice regularity (p ≤ 0.05). It has been determined that more than half of midwifery students have knowledge about breast cancer and BSE, and that only a fraction of those with knowledge about BSE practice BSE regularly every month. The perceived seriousness of breast cancer and knowledge about breast cancer affect the ability of individuals to perform BSE, initiating BSE and continuing to practice BSE for early diagnosis of breast cancer. The results from the study provide the midwifery students awareness of breast cancer and BSE both for themselves and for the women for whom they take responsibility.

The Effect of Treatment Advances on the Mortality Results of Breast Cancer Screening Trials: A Microsimulation Model.

PubMed

Birnbaum, Jeanette; Gadi, Vijayakrishna K; Markowitz, Elan; Etzioni, Ruth

2016-02-16

Mammography trials, which are the primary sources of evidence for screening benefit, were conducted decades ago. Whether advances in systemic therapies have rendered previously observed benefits of screening less significant is unknown. To compare the outcomes of breast cancer screening trials had they been conducted using contemporary systemic treatments with outcomes of trials conducted with previously used treatments. Computer simulation model of 3 virtual screening trials with similar reductions in advanced-stage cancer cases but reflecting treatment patterns in 1975 (prechemotherapy era), 1999, or 2015 (treatment according to receptor status). Meta-analyses of screening and treatment trials; study of dissemination of primary systemic treatments; SEER (Surveillance, Epidemiology, and End Results) registry. U.S. women aged 50 to 74 years. 10 and 25 years. Population. Mammography, chemotherapy, tamoxifen, aromatase inhibitors, and trastuzumab. Breast cancer mortality rate ratio (MRR) and absolute risk reduction (ARR) obtained by the difference in cumulative breast cancer mortality between control and screening groups. At 10 years, screening in a 1975 trial yielded an MRR of 90% and an ARR of 5 deaths per 10,000 women. A 2015 screening trial yielded a 10-year MRR of 90% and an ARR of 3 deaths per 10,000 women. Greater reductions in advanced-stage disease yielded a greater screening effect, but MRRs remained similar across trials. However, ARRs were consistently lower under contemporary treatments. When contemporary treatments were available only for early-stage cases, the MRR was 88%. Disease models simplify reality and cannot capture all breast cancer subtypes. Advances in systemic therapies for breast cancer have not substantively reduced the relative benefits of screening but have likely reduced the absolute benefits because of their positive effect on breast cancer survival. University of Washington and National Cancer Institute.

[Population screening for breast cancer: an interim assessment].

PubMed

van der Maas, P J

2000-06-03

The Dutch national breast cancer programme started in 1989 and ten years later complete coverage of the target population was realised. Screening will save the lives of 27% of all women with screen detected breast cancer. In the other 73% survival will not change, but they will know some years earlier that they have breast cancer. There are 4 lessons from the 12 year experience: (a) mortality reduction due to the present programme can only be identified in individual follow-up data of all women with breast cancer; (b) systematic improvement of the programme's performance can only be based on feedback from a detailed quality and outcome monitoring system; (c) the advice to increase the upper age limit to 75 years was based on the interpretation of trial results for younger age groups and model analysis; (d) breast cancer screening contributed to the systematic improvement of clinical procedures. Current scientific and practical challenges are mortality evaluation, optimising test properties, setting upper and lower age limits, understanding regional differences, developing optimal screening frequencies in women with an elevated breast cancer risk, digital mammography and computer assisted diagnosis.

Theranostics Targeting Metastatic Breast Cancer

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-15-1-0389 TITLE: Theranostics Targeting Metastatic Breast Cancer PRINCIPAL INVESTIGATOR: Kevin Burgess CONTRACTING...ADDRESS. 1. REPORT DATE October 2017 2. REPORT TYPE Annual 3. DATES COVERED 4. TITLE AND SUBTITLE Theranostics Targeting Metastatic Breast Cancer 5a...safe and effective interventions; (ii) elimination of mortality associated with metastatic breast cancer ; and, (iii) distinguishing aggressive breast

Plasma exosome microRNAs are indicative of breast cancer.

PubMed

Hannafon, Bethany N; Trigoso, Yvonne D; Calloway, Cameron L; Zhao, Y Daniel; Lum, David H; Welm, Alana L; Zhao, Zhizhuang J; Blick, Kenneth E; Dooley, William C; Ding, W Q

2016-09-08

microRNAs are promising candidate breast cancer biomarkers due to their cancer-specific expression profiles. However, efforts to develop circulating breast cancer biomarkers are challenged by the heterogeneity of microRNAs in the blood. To overcome this challenge, we aimed to develop a molecular profile of microRNAs specifically secreted from breast cancer cells. Our first step towards this direction relates to capturing and analyzing the contents of exosomes, which are small secretory vesicles that selectively encapsulate microRNAs indicative of their cell of origin. To our knowledge, circulating exosome microRNAs have not been well-evaluated as biomarkers for breast cancer diagnosis or monitoring. Exosomes were collected from the conditioned media of human breast cancer cell lines, mouse plasma of patient-derived orthotopic xenograft models (PDX), and human plasma samples. Exosomes were verified by electron microscopy, nanoparticle tracking analysis, and western blot. Cellular and exosome microRNAs from breast cancer cell lines were profiled by next-generation small RNA sequencing. Plasma exosome microRNA expression was analyzed by qRT-PCR analysis. Small RNA sequencing and qRT-PCR analysis showed that several microRNAs are selectively encapsulated or highly enriched in breast cancer exosomes. Importantly, the selectively enriched exosome microRNA, human miR-1246, was detected at significantly higher levels in exosomes isolated from PDX mouse plasma, indicating that tumor exosome microRNAs are released into the circulation and can serve as plasma biomarkers for breast cancer. This observation was extended to human plasma samples where miR-1246 and miR-21 were detected at significantly higher levels in the plasma exosomes of 16 patients with breast cancer as compared to the plasma exosomes of healthy control subjects. Receiver operating characteristic curve analysis indicated that the combination of plasma exosome miR-1246 and miR-21 is a better indicator of

Seaweed prevents breast cancer?

PubMed

Funahashi, H; Imai, T; Mase, T; Sekiya, M; Yokoi, K; Hayashi, H; Shibata, A; Hayashi, T; Nishikawa, M; Suda, N; Hibi, Y; Mizuno, Y; Tsukamura, K; Hayakawa, A; Tanuma, S