Circulating miRNA profiles from serum of women at high-risk for breast cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE98181 | GEO | 2018/01/22
REPOSITORIES: GEO
Similar Datasets
Project description:The contralateral unaffected breast of women with unilateral breast cancer (cases) is a good model for defining subtype-specific risk since women with ER-negative index primaries are at high risk for subsequent ER-negative primary cancers. We performed random fine needle aspiration (rFNA) of the unaffected breasts of cases; samples from 30 subjects (15 ER-positive and 15 ER-negative cases matched for age, race and menopausal status), were used for Illumina expression array analysis. In this study, we have examined gene expression profiles in random fine needle aspirate (rFNA) samples from the contralateral breasts of women with new unilateral breast cancer (cases) to seek candidate panels of ER-specific risk biomarkers. On a discovery set of 30 women, we have identified gene expression differences in the contralateral breast that associate with ER+ or ER- index primary tumors.
2013-03-26 | E-GEOD-41400 | biostudies-arrayexpress
Project description:Obesity is a risk factor for postmenopausal ERα (+) breast cancer. The metabolites from serum that contribute to this risk and how these factors affect ERα signaling are not known. Using whole metabolite profiling and a detection panel for proteins, we identified biomarkers that were differentially present in serum from obese vs. non-obese postmenopausal women, and we validated these factors in two separate cohorts of postmenopausal women who either developed breast cancer or those who were obese and lost weight after the onset of menopause. In vitro assays identified free fatty acids (FFAs), in particular oleic acid (OA) as serum factors that correlate with increased proliferation and aggressiveness in ERα(+) breast cancer cells by. FFAs activated both ERα and mTOR pathways and rewired metabolism in breast cancer cells. Pathway preferential estrogen-1 (PaPE-1), which target ERα and mTOR signaling, was able to block changes induced by FFAs. In fact, PaPEs were more effective in the presence of FFAs, suggesting a role for obesity-associated gene and metabolic rewiring in providing new targetable vulnerabilities for ERα-(+) breast cancer in postmenopausal women. Our findings provide a basis for preventing or inhibiting obesity-associated breast cancer by using PaPEs that would reverse these newly appreciated metabolic vulnerabilities of breast tumors in obese postmenopausal women.
2020-01-11 | GSE93510 | GEO
Project description:Obesity is a risk factor for postmenopausal ERα (+) breast cancer. The metabolites from serum that contribute to this risk and how these factors affect ERα signaling are not known. Using whole metabolite profiling and a detection panel for proteins, we identified biomarkers that were differentially present in serum from obese vs. non-obese postmenopausal women, and we validated these factors in two separate cohorts of postmenopausal women who either developed breast cancer or those who were obese and lost weight after the onset of menopause. In vitro assays identified free fatty acids (FFAs), in particular oleic acid (OA) as serum factors that correlate with increased proliferation and aggressiveness in ERα(+) breast cancer cells by. FFAs activated both ERα and mTOR pathways and rewired metabolism in breast cancer cells. Pathway preferential estrogen-1 (PaPE-1), which target ERα and mTOR signaling, was able to block changes induced by FFAs. In fact, PaPEs were more effective in the presence of FFAs, suggesting a role for obesity-associated gene and metabolic rewiring in providing new targetable vulnerabilities for ERα-(+) breast cancer in postmenopausal women. Our findings provide a basis for preventing or inhibiting obesity-associated breast cancer by using PaPEs that would reverse these newly appreciated metabolic vulnerabilities of breast tumors in obese postmenopausal women.
2020-01-11 | GSE93505 | GEO
Project description:Obesity is a risk factor for postmenopausal ERα (+) breast cancer. Molecular mechanisms activated by the factors from serum that contribute to this risk and how these mechanisms affect ERα signaling are yet to be elucidated. To identify such mechanisms, we performed whole metabolite and protein profiling in serum samples, which enabled us to focus on factors that were differentially present in serum from cancer-free vs. breast cancer susceptible and obese vs. non-obese post-menopausal women. These studies combined with in vitro assays identified free fatty acids (FFAs), as serum factors that correlate with increased proliferation and aggressiveness in ERα(+) breast cancer cells by. FFAs activated both ERα and mTOR pathways and rewired metabolism in breast cancer cells. Pathway preferential estrogen-1 (PaPE-1), which target ERα and mTOR signaling, was able to block changes induced by FFAs. In fact, PaPEs were more effective in the presence of FFAs, suggesting a role for obesity-associated gene and metabolic rewiring in providing new targetable vulnerabilities for ERα-(+) breast cancer in postmenopausal women. Our findings provide a basis for preventing or inhibiting obesity-associated breast cancer by using PaPEs that would reverse these newly appreciated metabolic properties of breast tumors in obese postmenopausal women.
2019-05-11 | GSE114372 | GEO
Project description:microRNAs are small, non-coding, single-stranded RNAs between 18-22 nucleotides long that regulate gene expression. Expression of microRNAs is altered in tumor compared to normal tissue; there is some evidence that these changes may be reflected in the serum of cancer cases compared to healthy individuals. This has yet to be examined in a prospective study where samples are collected before diagnosis. We used Affymetrix arrays to examine serum miRNA expression profiles in 410 participants in the Sister Study, a prospective cohort study of 50,884 women. All women in the cohort had never been diagnosed with breast cancer at the time of enrollment. We compared global miRNA expression patterns in 205 women who subsequently developed breast cancer and 205 women who remained breast cancer-free.
2013-05-08 | E-GEOD-44281 | biostudies-arrayexpress
Project description:Introduction: Circulating microRNAs (miRNAs) exhibit remarkable stability and may serve as biomarkers in several clinical cancer settings. The aim of this study was to investigate changes in the levels of specific circulating miRNA following breast cancer surgery and evaluate whether these alterations were also observed in an independent data set. Methods: Global miRNA analysis was performed on prospectively collected serum samples from 24 post-menopausal women with estrogen receptor-positive early-stage breast cancer before surgery and 3 weeks after tumor resection using global LNA-based quantitative real-time PCR (qPCR). Results: Numbers of specific miRNAs detected in the samples ranged from 142 to 161, with 107 miRNAs detectable in all samples. After correction for multiple comparisons, 3 circulating miRNAs (miR-338-3p, miR-223 and miR-148a) exhibited significantly lower, and 1 miRNA (miR-107) higher levels in post-operative vs. pre-operative samples (p<0.05). No miRNAs were consistently undetectable in the post-operative samples compared to the pre-operative samples. Subsequently, our findings were compared to a dataset from a comparable patient population analyzed using similar study design and the same qPCR profiling platform, resulting in limited agreement. Conclusions: A panel of 4 circulating miRNAs exhibited significantly altered levels following radical resection of primary ER+ breast cancers in post-menopausal women. These specific miRNAs may be involved in tumorigenesis and could potentially be used to monitor whether all cancer cells have been removed at surgery and/or, subsequently, whether the patients develop recurrence. 48 serum samples were prospectively collected from 24 patients with early stage breast cancer before and after surgery at Odense University Hospital. Serum was prepared within one hour of sample collection after centrifugation (2000 x g; 10 min at 20 M-BM-:C) and immediately stored at -80 M-BM-:C.
2014-11-01 | E-GEOD-57661 | biostudies-arrayexpress
Project description:Introduction: MicroRNAs (miRNAs) are small, non-coding RNA molecules involved in post-transcriptional gene regulation and have recently been shown to play a role in cancer metastasis. In solid tumors, especially breast cancer, alterations in miRNA expression contribute to cancer pathogenesis, including metastasis. Considering the emerging role of miRNAs in metastasis, the identification of predictive markers is necessary to further understanding of stage-specific breast cancer development. This is a retrospective analysis that aimed to identify molecular biomarkers related to distant breast cancer metastasis development.<br><br>Methods: A retrospective case cohort study was performed in 64 breast cancer patients treated during the period from 1998-2001. The case group (n=29) consisted of patients with a poor prognosis who presented with breast cancer recurrence or metastasis during follow up. The control group (n=35) consisted of a random sample of patients with a good prognosis who did not develop breast cancer recurrence or metastasis. These patient groups were stratified according to TNM clinical stage (CS) I, II and III, and the main clinical features of the patients were homogeneous. miRNA profiling was performed using formalin-fixed, paraffin-embedded tumors. Biomarkers related to metastatic potential were identified independent of clinical stage, and a cutoff point was selected based on the optimal sensitivity and specificity (ROC curve). Finally, a hazard risk analysis of these biomarkers was performed to evaluate their relation to metastatic potential. <br><br>Results: miRNA expression profiling identified several miRNAs that were either specific and shared across all clinical stages (p?0.05). Among these, we identified miRNAs previously associated with cell motility (let-7 family), cell proliferation and invasion (hsa-miR-16 and has-miR-205) and distant metastasis (hsa-miR-21). In addition, hsa-miR-494 and hsa-miR-21 were up-regulated in metastatic cases of CSI and II. Furthermore, the combination of the 3 miRNAs identified for CSII (hsa-miR-494, hsa-miR-183 and hsa-miR-21) was significant and were a more effective risk marker compared to the single miRNAs. <br><br>Conclusions: Women with metastatic breast cancer, especially CSII, presented up-regulated levels of miR-183, miR-494 and miR-21, which were associated with a poor prognosis. These miRNAs therefore represent new risk biomarkers of breast cancer metastasis and may be useful for future targeted therapies.
2013-08-07 | E-MEXP-3947 | biostudies-arrayexpress
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 cancer with most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients versus 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based upon the expression levels of 5 microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the over-expression and down-regulation of proteins differently expressed in the serum of breast cancer patients versus that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a-5p, mir-497-5p, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of mir-125b-5p, miR-29c-3p, mir-16-5p, miR-1260, and miR-451a was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of mir-16-5p with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and use of the predictor here described might be of potential importance for breast cancer prediction.
2020-09-18 | PXD020795 | Pride
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