Characterization of Transcriptome Diversity and In Vitro Behavior of Primary Human Breast Cells at Increased Risk for Breast Cancer Development
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE185314 | GEO | 2022/04/22
REPOSITORIES: GEO
Similar Datasets
Project description:Gene expression in histologically normal epithelium from breast cancer patients and cancer-free prophylactic mastectomy patients share a similar profile Introduction: We hypothesized that gene expression in histologically normal epithelium (NlEpi) would differ in breast cancer patients (HN) compared to usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomies from high-risk women (PM), would resemble HN gene expression. Methods: We analyzed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 cases, we used Affymetrix HU133A microarrays to compare gene expression in 18 RM vs 18 age-matched HN (9 ER+, 9 ER-) and 6 PM. Data were validated with qPCR in 31 independent NlEpi samples (8 RM, 17 HN, 6 PM). Results: 98 probesets (86 genes) were differentially expressed between RM and HN samples. Perfoming supervised hierarchical analysis with these 98 probesets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM vs HN, and lower (58%), but more heterogeneous, in RM vs PM. The 86 genes were implicated in many processes including transcription and the MAPK pathway. Conclusion: Gene expression differs between NlEpi of cancer cases and controls. The cancer cases' profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. We determined that 98 probesets significantly differed between reduction mammoplasty and histologically normal epithelium from breast cancer patients. We also found that the histologically normal epithelium from prophylactic mastectomy patients' gene expression was more similar to histologically normal epithelium from breast cancer patients' than to reduction mammoplasty patients' gene expression. These results demonstrate that gene expression differs between NlEpi of cancer cases and controls. The cancer casesâ?? profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. 42 total laser capture microdissected histologically normal breast tissue samples were analyzed with Affymetrix HU133A microarrays. 36 samples were age-matched between reduction mammoplasty (n=18) and histologically normal epithelial samples from breast cancer patients (n=18; 9ER+, 9ER-). 6 histologically normal epithelial samples from prophylactic mastectomy patients were then compared to data generated from the original 36 sample comparison. Sample numbers correspond to individual patient samples.
2010-06-08 | E-GEOD-20437 | biostudies-arrayexpress
Project description:Gene expression in histologically normal epithelium from breast cancer patients and cancer-free prophylactic mastectomy patients share a similar profile Introduction: We hypothesized that gene expression in histologically normal epithelium (NlEpi) would differ in breast cancer patients (HN) compared to usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomies from high-risk women (PM), would resemble HN gene expression. Methods: We analyzed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 cases, we used Affymetrix HU133A microarrays to compare gene expression in 18 RM vs 18 age-matched HN (9 ER+, 9 ER-) and 6 PM. Data were validated with qPCR in 31 independent NlEpi samples (8 RM, 17 HN, 6 PM). Results: 98 probesets (86 genes) were differentially expressed between RM and HN samples. Perfoming supervised hierarchical analysis with these 98 probesets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM vs HN, and lower (58%), but more heterogeneous, in RM vs PM. The 86 genes were implicated in many processes including transcription and the MAPK pathway. Conclusion: Gene expression differs between NlEpi of cancer cases and controls. The cancer cases' profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. We determined that 98 probesets significantly differed between reduction mammoplasty and histologically normal epithelium from breast cancer patients. We also found that the histologically normal epithelium from prophylactic mastectomy patients' gene expression was more similar to histologically normal epithelium from breast cancer patients' than to reduction mammoplasty patients' gene expression. These results demonstrate that gene expression differs between NlEpi of cancer cases and controls. The cancer cases’ profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes.
2010-06-01 | GSE20437 | GEO
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:Breast cancer is the most common cancer in females, affecting one in every eight women and accounting for the majority of cancer-related deaths in women worldwide. Germline mutations in the BRCA1 and BRCA2 genes are significant risk factors for specific subtypes of breast cancer. BRCA1 mutations are associated with basal-like breast cancers, whereas BRCA2 mutations are associated with luminal-like disease. Defects in mammary epithelial cell differentiation have been previously recognized in germline BRCA1/2 mutation carriers even before cancer incidence. However, the underlying mechanism is largely unknown. Here, we employ spatial transcriptomics to investigate defects in mammary epithelial cell differentiation accompanied by distinct microenvironmental alterations in preneoplastic breast tissues from BRCA1/2 mutation carriers and normal breast tissues from non-carrier controls. We uncovered spatially defined receptor-ligand interactions in these tissues for the investigation of autocrine and paracrine signaling. We discovered that β1-integrin-mediated autocrine signaling in BRCA2-deficient mammary epithelial cells may differ from BRCA1-deficient mammary epithelial cells. In addition, we found that the epithelial-to-stromal paracrine signaling in the breast tissues of BRCA1/2 mutation carriers is greater than in control tissues. More integrin-ligand pairs were differentially correlated in BRCA1/2-mutant breast tissues than non-carrier breast tissues with more integrin receptor-expressing stromal cells. Implications: These results suggest alterations in the communication between mammary epithelial cells and the microenvironment in BRCA1 and BRCA2 mutation carriers, laying the foundation for designing innovative breast cancer chemo-prevention strategies for high-risk patients.
2023-10-11 | GSE234017 | 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.
2024-09-02 | BIOMD0000000642 | BioModels
Project description:Human breast cancer tissue samples from 18 patients with high-risk or low-risk MammaPrint breast cancer were analyzed. The membrane fractions were enriched, and the extracted proteins were reduced, alkylated, digested with Lys-C and Trypsin, and labelled with iTRAQ4plex: 114; high risk; 115; low risk. Identification results were filtered at 1% false discovery rate (FDR) thresholds by searching against a randomized decoy database using Mascot at peptide and protein levels.
2016-10-17 | PXD005163 | JPOST Repository
Project description:Most of the breast cancer samples used in clinical research contain multiple cell types other than epithelial cells alone. The non-epithelial cell types have have a substantial effect on the gene expression-profile, which is used to define molecular subtypes of the tumours. The purpose of this data set is to retrieve gene-expression profile within tumour epithelial cells. We collected 9 breast cancer epithelial cell lines and 5 tumour sampes from which epithelial cells were sorted and enriched using BerEp4 antibody coated beads. We profiled the mRNA expression level of these samples and classified probe sets into epithelial genes which were those genes with present calls in at least 50% of the samples. Then we derived an 23-gene signature based on only the epithelial genes to stratify breast cancer.
2010-08-17 | GSE23640 | GEO
Project description:Molecular Determinants of Post-Mastectomy Breast Cancer Recurrence
2018-09-20 | PRJEB28702 | EVA
Project description:Breast cancer develops through the accumulation of genomic changes in the ductal epithelia cells of normal breast tissue. A determination of whether gene expression changes in ductal cells is associated with an increased risk for breast cancer is needed. We sought to determine if the global gene expression profiles of ductal cells of women at high risk for breast cancer or with cytologic ductal epithelial atypia differed from those of women at normal risk or without cytologic atypia. We used microarrays to detail the gene expression profile of breast ductal cells associated with normal risk or high risk for sporadic breast cancer and with or without cytologic epithelial atypia. We did not identify any separation of the sample groups (normal risk vs high-risk, or atypia vs nonatypia) according to expression of subgroups of genes.
2020-07-05 | GSE153796 | GEO
Project description:The aim of our study is to examine the region of tissue surrounding or adjacent to breast tumor in order to detect pre-malignant histological and genetic changes that may be predictive of risk of breast cancer. In this study, histological and gene expression data of breast tissue were obtained from patients that underwent mastectomy at various stages of breast carcinoma. For each patient, samples were obtained from the tumor region and four surrounding zones (1cm, 2cm, 3 cm and 4 cm away from the grossly visible tumor boundary), where possible. We have also breast samples from healthy individuals undergoing breast reduction surgery (mammoplasty). Microarray gene expression profiles of tissue samples (tumor and surrounding tissue, and breast reduction mammoplasty) was performed. In addition pathologist reviewed all slides to provide a details histology of all samples (excluding breast mammoplasty)
2008-04-13 | E-TABM-276 | biostudies-arrayexpress