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
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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.
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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. 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.
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2014-11-01 | E-GEOD-57661 | biostudies-arrayexpress
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2013-08-07 | E-MEXP-3947 | biostudies-arrayexpress
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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
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and identified by:
BIOMD0000000642.
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2024-09-02 | BIOMD0000000642 | BioModels