Nurses' Health Study (NHS)
Ontology highlight
ABSTRACT: The Nurses' Health Study is an on-going prospective cohort study of women that was initiated in 1976. This specific study was part of a larger study to advance our knowledge of breast cancer etiology, expand the current knowledge of mammographic density, and clarify the relationship between mammographic density and breast cancer risk. We conducted a nested case control study of breast cancer among women who provided a blood sample. We then targeted our mammogram collection to participants that were selected as part of this nested case-control study (i.e. those who had provided a blood sample). The mammogram closest to the date of blood draw (~1989-1990) was used. We assessed mammographic breast density from digitized film images using a computer assisted thresholding method (Cumulus). The women in this study were genotyped using the Illumina Omni Express Platform.
SECONDARY ACCESSION(S): PRJNA292936PRJNA292935
REPOSITORIES: dbGaP
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Project description:We analyzed gene expression in human peripheral blood mononuclear cells (PBMCs) from breast cancer patients, patients with benign breast abnormalities, healthy cancer-free individuals as well as patients with other types of cancer (gastrointestinal and brain cancers). Peripheral blood mononuclear cell (PBMC) samples were collected from women with a suspect initial mammogram prior to undergoing a diagnostic biopsy procedure to determine whether the detected abnormality was benign or malignant. In total, we collected blood from 57 women with a diagnosis of breast cancer and 37 with a benign diagnosis. We also collected blood from 31 women with normal initial mammograms as negative controls and 15 breast cancer patients following surgery. All breast cancer patient samples were collected at the Duke University Medical Center (DUMC) under an institutional review board (IRB)-approved protocol (Duke eIRB#12025) after obtaining informed consent and were provided by Dr. Jeffrey Marks. PBMC samples from patients with various gastrointestinal cancers (n=15) were colelcted and stored at DUMC under IRB-approved protocols (Duke eIRB#12010 and 12025) and were provided by Dr. Jeffrey Marks. Peripheral blood leukocyte samples from patients with brain tumors (n=7) were provided by Dr. John Sampson and were collected by leukapheresis under Duke eIRB#00003877 and #00009403.
2011-03-01 | E-GEOD-27562 | biostudies-arrayexpress
Project description:Overabundance of circulating RNY transcripts and fragments has been associated with cancer. Here we analyzed the levels of RNYs in plasma collected from women before developing breast cancer and compared the results to matched controls that remained unaffected. Using small RNA-seq, two cohorts were analyzed: a cohort of women carriers of pathogenic variants in BRCA1 and BRCA2, and diagnosed with breast cancer as a first neoplasm within a period of < 12 months after blood test (n = 11), or that provided a blood sample at a similar age and remained unaffected (n = 13); and a cohort from a long-term prospective study, and comprising 8 sporadic breast cancer cases (diagnosed in a period of < 12 months after blood test) and 8 controls matched for individual and epidemiological variables
2023-11-30 | GSE239907 | GEO
Project description:This study evaluates the effects of hydroxytyrosol (HT), a component of olive oil, on mammographic breast density reduction. We explored effects of HT on Wnt β-catenin and other pathways involved in cancer stem cell renewal, DNA repair, cell proliferation and differentiation. Hydroxytyrosol reduced breast density only in women over 60 years, especially in those with high baseline breast density. HT also reduced proliferation and affected Wnt signaling pathway. This study lays the foundation for future larger studies in exploring a natural compound with well tolerability and overall nontoxic profile for chemoprevention of breast cancer.
2025-01-03 | GSE285765 | GEO
Project description:Mufudza2012 - Estrogen effect on the dynamics
of breast cancer
This deterministic model shows the
dynamics of breast cancer with immune response. The effects of
estrogen are incorporated to study its effects as a risk factor for
the disease.
This model is described in the article:
Assessing the effects of
estrogen on the dynamics of breast cancer.
Mufudza C, Sorofa W, Chiyaka
ET.
Comput Math Methods Med 2012; 2012:
473572
Abstract:
Worldwide, breast cancer has become the second most common
cancer in women. The disease has currently been named the most
deadly cancer in women but little is known on what causes the
disease. We present the effects of estrogen as a risk factor on
the dynamics of breast cancer. We develop a deterministic
mathematical model showing general dynamics of breast cancer
with immune response. This is a four-population model that
includes tumor cells, host cells, immune cells, and estrogen.
The effects of estrogen are then incorporated in the model. The
results show that the presence of extra estrogen increases the
risk of developing breast cancer.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000642.
To cite BioModels Database, please use:
BioModels Database:
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quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000642 | BioModels
Project description:The purpose of this study was to improve prediction of patients at high-risk for metastatic disease utilizing a nested case-control design that uniquely enables enrichment for relevant phenotypes. We identified all women diagnosed with primary breast cancer from January 1, 1997, to December 31, 2005, in the Stockholm health care region. Patients developing distant metastatic disease (cases) were selected and controls (free from distant disease) were randomly matched by adjuvant therapy, age and calendar period at diagnosis. The nested case-control study included 768 study subjects with clinical information and gene expression arrays (Human Cancer G110). Study subjects were randomly and equally divided into training set (discovery) or testing (validation) set. Metastatic onset prediction was then compared including either clinical variables only or combining clinical and genetic information. Differentially expressed genes and pathways between cases and controls included a wide-spectrum of well known as well as candidate regulators of the metastatic cascade. The nested case-control study included 768 study subjects corresponding to 623 primary tumor samples. Details concerning case-control status are given in the samples section. Each case and its' matching controls form risk sets, indicated by the setnr variable.
2014-11-03 | E-GEOD-48091 | biostudies-arrayexpress
Project description:Using primary breast tumors from 162 women from the Kaiser Division of Research Pathways Study and the Illumina GoldenGate methylation bead-array platform, we measured CpG loci associated with cancer-related genes 162 tumor specimens from the initial diagnostic biopsy were obtained from the KPNC tumor biorepository for methylation analysis. All tumor specimens were from patients who did not receive neoadjuvant chemotherapy. The Pathways Study is a prospective cohort study of breast cancer survival actively recruiting women diagnosed with invasive breast cancer from the Kaiser Permanente Northern California (KPNC) patient population since January 2006. Further study details are provided in Kwan ML et al. Cancer Causes Control 2008. Written informed consent is obtained from all participants before they are enrolled in the study. The study was approved by the IRB of KPNC and all collaborating sites.
2010-07-28 | E-GEOD-22290 | biostudies-arrayexpress
Project description:Dynamics of Breast Cancer under Different Rates of Chemoradiotherapy.
Mkango SB1, Shaban N1, Mureithi E1, Ngoma T2.
Author information
1
Department of Mathematics, University of Dar es Salaam, P.O. Box 35062, Dar es Salaam, Tanzania.
2
Department of Clinical Oncology, Muhimbili University of Health and Allied Sciences, P.O. Box 65000, Dar es Salaam, Tanzania.
Abstract
A type of cancer which originates from the breast tissue is referred to as breast cancer. Globally, it is the most common cause of death in women. Treatments such as radiotherapy, chemotherapy, hormone therapy, immunotherapy, and gene therapy are the main strategies in the fight against breast cancer. The present study aims at investigating the effects of the combined radiotherapy and chemotherapy as a way to treat breast cancer, and different treatment approaches are incorporated into the model. Also, the model is fitted to data on patients with breast cancer in Tanzania. We determine new treatment strategies, and finally, we show that when sufficient amount of chemotherapy and radiotherapy with a low decay rate is used, the drug will be significantly more effective in combating the disease while health cells remain above the threshold.
Copyright © 2019 Sara B. Mkango et al.
2020-01-20 | MODEL1912120005 | BioModels
Project description:Introduction Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known. Methods Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and generalized regression models were used to assess the independent contribution from different variables to MD. Results SAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified. Conclusions Three UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest among young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer. Gene expression analysis of breast biopsies from 143 women, 79 non-cancer (healthy women with no cancer who had a mammogram taken) and 64 breast cancer.
2010-08-13 | E-GEOD-18672 | biostudies-arrayexpress
Project description:Mammographic breast cancer screening is effective in reducing breast cancer mortality. Nevertheless, several limitations are known. The objective of this study was to identify circulating microRNAs (miRs) ratios associated with BC in women attending mammography screening. A nested case-control study was conducted within the ANDROMEDA cohort (women of age 46-67 attending BC screening in northern Italy), where pre-diagnostic plasma samples, information on life-styles and common BC risk factors were collected. Small RNA sequencing was carried out on plasma samples from 65 cases and 66 controls. miR-ratios associated with BC were selected by two-sample Wilcoxon test and lasso logistic regression. Subsequent assessment by RT-qPCR of the miRs contained in the selected miR-ratios was carried out as a platform validation. Penalized logistic regression was further applied to candidate miR-ratios alone, or in combination with non-molecular factors, to build a diagnostic model.
2023-07-26 | GSE210329 | GEO
Project description:The purpose of this study was to improve prediction of patients at high-risk for metastatic disease utilizing a nested case-control design that uniquely enables enrichment for relevant phenotypes. We identified all women diagnosed with primary breast cancer from January 1, 1997, to December 31, 2005, in the Stockholm health care region. Patients developing distant metastatic disease (cases) were selected and controls (free from distant disease) were randomly matched by adjuvant therapy, age and calendar period at diagnosis. The nested case-control study included 768 study subjects with clinical information and gene expression arrays (Human Cancer G110). Study subjects were randomly and equally divided into training set (discovery) or testing (validation) set. Metastatic onset prediction was then compared including either clinical variables only or combining clinical and genetic information. Differentially expressed genes and pathways between cases and controls included a wide-spectrum of well known as well as candidate regulators of the metastatic cascade.
2015-07-08 | GSE48091 | GEO