Gene expression data from breast ductal cells from women at normal risk or high risk for breast cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE153796 | GEO | 2020/07/05
REPOSITORIES: GEO
Similar Datasets
Project description:Gene expression data from breast ductal cells from women at normal risk or high risk for breast cancer
| PRJNA644115 | ENA
Project description:Detection of breast cancer (BC) in young women is challenging because mammography, the most common tool for detecting BC, is not effective on the dense breast tissue characteristic of young women. In addition to the limited means for detecting their BC, young women face a transient increased risk of pregnancy-associated BC. As a consequence, reproductively active women could benefit significantly from a tool that provides them with accurate risk assessment and early detection of BC. One potential method for detection of BC is biochemical monitoring of proteins and other molecules in bodily fluids such as serum, nipple aspirate, ductal lavage, tear, urine, saliva and breast milk. Of all these fluids, only breast milk provides access to a large volume of breast tissue, in the form of exfoliated epithelial cells, and to the local breast environment, in the form of molecules in the milk. Thus, analysis of breast milk is a non-invasive method with significant potential for assessing BC risk. Here we analyzed human breast milk by mass spectrometry (MS)-based proteomics to build a biomarker signature for early detection of BC. Ten milk samples from 8 women provided 5 paired-groups (cancer versus control) for analysis of differentially expressed proteins: 2 within woman comparisons (milk from a diseased breast versus a healthy breast of the same woman) and 3 across women comparisons (milk from a woman with cancer versus a woman without cancer). Despite a wide range in the time between milk donation and cancer diagnosis (cancer diagnosis occurred from 1 month before to 24 months after milk donation), the levels of some proteins differed significantly between cancer and control in several of the 5 comparison groups. These pilot data are supportive of the idea that molecular analysis of breast milk will identify proteins informative for early detection and accurate assessment of BC risk, and warrant further research.
2017-12-18 | PXD007066 | Pride
Project description:Circulating microRNAs (c-miRNAs) have emerged as measurable biomarkers (liquid biopsies) for cancer detection. The goal of our study was to identify novel biomarkers to predict long-term breast cancer risk in cancer-free women. We evaluated the ability of c-miRNAs to identify women most likely to develop breast cancer by profiling miRNA from serum obtained long before diagnosis. 24 breast cancer cases and controls (matched for risk and age) were identified from women enrolled in the High-Risk Breast Program at the UVM Cancer Center. We used Affymetrix miRNA v4 microarrays to interrogate miRNAs (miRBase v20) in the serum of cancer-free women at high-risk for breast cancer. The 24 cases developed breast cancer at least 6 months (average of 3.2 years) and the 24 controls remain cancer-free.
2018-01-22 | GSE98181 | GEO
Project description:Epigenetic mechanisms such as DNA methylation are important regulators of gene expression and are frequently dysregulated early in breast carcinogenesis. The relationship between DNA methylation aberrations in normal breast tissue and breast cancer risk remains unclear. Disease-free breast tissue cores donated by high-risk (Tyrer-Cuzick lifetime risk ≥20%) and 78 average-risk women were obtained from the Susan G. Komen Tissue Bank and processed for whole methylome and whole transcriptome profiling. We identified 1355 CpGs that were differentially methylated between high- and average-risk breast tissues (ΔZ>0.5, FDR<0.05). Hypomethylated CpGs were overrepresented in high-risk tissue and were found predominantly (68%) in non-coding regions. Hypermethylated CpG sites were found equally in the gene body and non-coding regions. Transcriptomic analysis identified 67 differentially expressed genes (fold change≥2, FDR<0.05, 17 down 50 up), involved in chemokines signaling, metabolism and estrogen biosynthesis. Methylation-expression correlations revealed 6 epigenetically regulated genes in high-risk breast. This is the first gene expression/DNA methylation analysis of normal breasts from women at either high or average risk of breast cancer. Our discovery of epigenetically regulated genes associated with breast cancer risk using a unique resource of normal breast samples opens the doors to a deeper understanding of the process of cancer initiation and provides an opportunity to mechanistically dissect breast cancer susceptibility and risk-associated molecular alterations.
2021-09-30 | GSE164641 | GEO
Project description:Epigenetic mechanisms such as DNA methylation are important regulators of gene expression and are frequently dysregulated early in breast carcinogenesis. The relationship between DNA methylation aberrations in normal breast tissue and breast cancer risk remains unclear. Disease-free breast tissue cores donated by high-risk (Tyrer-Cuzick lifetime risk ≥20%) and 78 average-risk women were obtained from the Susan G. Komen Tissue Bank and processed for whole methylome and whole transcriptome profiling. We identified 1355 CpGs that were differentially methylated between high- and average-risk breast tissues (ΔZ>0.5, FDR<0.05). Hypomethylated CpGs were overrepresented in high-risk tissue and were found predominantly (68%) in non-coding regions. Hypermethylated CpG sites were found equally in the gene body and non-coding regions. Transcriptomic analysis identified 67 differentially expressed genes (fold change≥2, FDR<0.05, 17 down 50 up), involved in chemokines signaling, metabolism and estrogen biosynthesis. Methylation-expression correlations revealed 6 epigenetically regulated genes in high-risk breast. This is the first gene expression/DNA methylation analysis of normal breasts from women at either high or average risk of breast cancer. Our discovery of epigenetically regulated genes associated with breast cancer risk using a unique resource of normal breast samples opens the doors to a deeper understanding of the process of cancer initiation and provides an opportunity to mechanistically dissect breast cancer susceptibility and risk-associated molecular alterations.
2021-09-30 | GSE164640 | 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:
An enhanced, curated and annotated resource for published
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.
2017-07-26 | BIOMD0000000642 | BioModels
Project description:Breast Cancer (BC) is one of the most common cancers and one of the most common causes for cancer- related mortality. Discovery of protein biomarkers associated with cancer, is considered as important for early diagnosis and prediction of the cancer risk. Protein biomarkers could be investigated by large-scale protein investigation or proteomics, using mass spectrometry (MS)- based techniques. Our group applies MS-based proteomics to study the protein pattern in human breast milk from women with BC and controls and investigates the alterations and dysregula-tions of breast milk proteins in comparison pairs of BC versus control. These dysregulated pro-teins might be considered as potential future biomarkers of BC. Identification of potential bi-omarkers in breast milk may benefit young women without BC, but who could collect the milk for future assessment of BC risk. Previously we identified several dysregulated proteins in dif-ferent sets of human breast milk samples from BC patients and controls using gel-based protein separation coupled with MS. Here, we performed two-dimensional polyacrylamide gel electro-phoresis (2D-PAGE) coupled with nano-liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) in a small-scale study on a set of 6 human breast milk samples (3 BC samples vs. 3 controls) and we identified several dysregulated proteins which have potential roles in cancer progression and might be considered as potential BC biomarkers in the future.
2023-10-20 | PXD040188 | Pride
Project description:The underlying biology through which established breast cancer risk factors contribute to disease risk is not well characterized. One key risk factor for breast cancer is age, and age-related DNA methylation alterations may contribute to increased risk of disease. Here we assessed normal breast tissues and tested the relation of DNA methylation with known breast cancer risk factors. Cancer-free women donated breast tissue biopsy specimens through the Susan G. Komen Foundation and provided detailed risk factor data (n=100). Bisulfite modified DNA was profiled for DNA methylation genome-wide using the Infinium 450K DNA methylation array. We tested the relation of known breast cancer risk factors such as age, BMI, parity, and family history of disease with DNA methylation adjusted for variation in cell type proportions using a novel cellular mixture deconvolution algorithm. We identified 787 CpGs that exhibited significant (FDR adjusted, q-value < 0.01) differential DNA methylation associated with subject age, but not with other breast cancer risk factors. We observed an enrichment among the risk factor-related CpGs for Polycomb group target genes (Fisher’s Exact test, P = 1.74E-06), and breast myoepithelial cell enhancer regions (H3K4me1; Fisher’s Exact test, P = 7.1E-20). We validated our risk factor-related findings in two independent populations of normal breast tissue (n=18 and n=97). In addition, age-related CpGs were further deregulated in both pre-invasive (DCIS, n=40) and invasive breast cancers (TCGA, n=731). Overall, our results suggest that the breast cancer risk factor age contributes to epigenetic dysregulation in normal breast tissue that exhibit progressive changes in cancer.
2017-06-20 | GSE88883 | GEO
Project description:Five years of tamoxifen reduces breast cancer risk by nearly 50% but is associated with significant side-effects and toxicities. A better understanding of the direct and indirect effects of tamoxifen in benign breast tissue could elucidate new mechanisms of breast carcinogenesis, suggest novel chemoprevention targets, and provide relevant early response biomarkers for Phase II prevention trials. Seventy-three women at increased risk for breast cancer were randomized to tamoxifen (20 mg daily) or placebo for three months. Blood and breast tissue samples were collected at baseline and post-treatment. Sixty-nine women completed all study activities (37 tamoxifen and 32 placebo). The selected biomarkers focused on estradiol and IGFs in the blood, DNA methylation and cytology in random periareolar fine needle aspirates, and tissue morphometry, proliferation, apoptosis, and gene expression (microarray and RT-PCR) in the tissue core samples. Tamoxifen downregulated ets-oncogene family members ETV4 and ETV5 and reduced breast epithelial cell proliferation independent of CYP2D6 genotypes or effects on estradiol, ESR1 or IGFs. Reduction in proliferation was correlated with downregulation of ETV4 and DNAJC12. Tamoxifen also modulated expression of RAB GTPases, and several genes involved in epithelial-stromal interaction, and reduced tumor suppressor gene methylation. Three months of tamoxifen did not affect breast tissue composition, cytological atypia, preneoplasia or apoptosis. Tamoxifen may durably reduce breast cancer risk through downregulation of ETV4 and ETV5 which could deplete mammary progenitor populations. This pathway has the potential to provide novel targets and early response biomarkers for phase II prevention trials. Randomized prospective double blinded placebo-controlled trial of tamoxifen (20 mg daily) versus placeo in women at increased risk for breast cancer. Gene expression was assessed in whole breast tissue cores obtained at baseline and after three months of treatment for 35 women. Core biopsies were obtained in the late luteal phase (day 28 +/- 2) for premenopausal women (N = 19). Breast lobules from the baseline and post-treatment cores were microdissected for 5 tamoxifen subjects.
2011-07-21 | E-GEOD-29338 | biostudies-arrayexpress
Project description:Worldwide an ever-increasing number of women are prescribed estrogen modulating therapies (EMTs) for the treatment of breast cancer. In parallel, aging of the global population of women will contribute to risk of both breast cancer and Alzheimer’s disease. To address the impact of anti-estrogen therapies on risk of Alzheimer’s and neural function, we conducted medical informatic and molecular pharmacology analyses to determine the impact of EMTs on risk of Alzheimer’s followed by determination of EMT estrogenic mechanisms of action in neurons. In a propensity matched data set of 260,232 women with breast cancer, medical informatic analyses indicated that EMTs were associated with reduced risk of AD which was driven by patients receiving tamoxifen or aromatase inhibitors whereas raloxifene was ineffective independently validating earlier reports. Mechanistically, a comparative analysis of EMTs vs estradiol was conducted to determine whether EMTs exerted estrogenic action in neural cells in-vitro and in brain in-vivo. Outcomes of mechanistic analyses indicated that select EMTs induced estrogenic action and pathways in neural cells including promoting neuronal morphological plasticity, electrophysiological indicators of synaptic connectivity, mitochondrial number and function and induction of transcriptomic pathways consistent with estrogenic outcomes. Collectively, these data provide both clinical and mechanistic data indicating that select EMTs exert estrogenic agonist action in neural tissue that are associated with reduced risk of Alzheimer’s disease while simultaneously acting as effective estrogen receptor antagonists in breast.
2023-11-01 | GSE241054 | GEO