Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA384216 | ENA |
REPOSITORIES: ENA
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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: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: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: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: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: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:Different miRNA expression profiles between human breast cancer turmors and serum
| PRJNA244080 | ENA