Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA336555 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Expression of oxysterol pathway genes in estrogen positive breast carcinomas-first phase
| PRJNA336554 | ENA
Project description:Expression of oxysterol pathway genes in estrogen positive breast carcinomas
| PRJNA336551 | ENA
Project description:Metabolism of anticancer drugs markedly affects their antitumor effects. The major goal of our study was to investigate associations of gene expression of enzymes metabolizing taxanes and/or anthracyclines with therapy response and survival of breast carcinoma patients The present study investigated differences in transcript levels of key modulators of oxysterol signaling pathway, including oxysterol receptors, metabolic enzymes and transporters in the groups of estrogen receptor positive (ER+) breast carcinomas in comparison to estrogen receptor negative (ER-) ones, and to control non-tumor tissues.
2017-04-06 | GSE85207 | GEO
Project description:Metabolism of anticancer drugs markedly affects their antitumor effects. The major goal of our study was to investigate associations of gene expression of enzymes metabolizing taxanes and/or anthracyclines with therapy response and survival of breast carcinoma patients The present study investigated transcript levels of key modulators of oxysterol signaling pathway, including oxysterol receptors, metabolic enzymes and transporters in the group of hormone-receptor positive breast carcinoma patients to evaluated potential clinical significance of these genes.
2017-04-06 | GSE85206 | GEO
Project description:Definition of clinically distinct molecular subtypes in estrogen receptor positive breast carcinomas using genomic grade
| PRJNA98807 | ENA
Project description:Estrogen-regulated genes predict survival in estrogen receptor and/or progesterone receptor-positive breast cancers
| PRJNA92235 | ENA
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:Cholesterol biosynthesis pathway as a novel mechanism of resistance to estrogen deprivation in estrogen receptor positive breast cancer
| PRJNA305878 | ENA
Project description:Despite extensive research, the genes/proteins and biological pathways responsible for the physiological effects of estrogen remain elusive. In this study, we employed a proteomic method to determine the effect of estrogen on global protein expression in breast cancer MCF7 cells. The expression of 77 cytoplasmic, 74 nuclear, and 81 membrane proteins was significantly altered by 17-β-estradiol (E2). Protein enrichment analyses of the quantified proteins revealed that E2 stimulated cell division primarily by promoting the G1 to S phase transition and advancing the G2/M checkpoint. Functional annotation analyses of the E2-regulated proteins indicated that these proteins promoted cell division primarily through enhancing protein nuclear import, protein translation, reducing mRNA degradation, and increasing protein folding. Interestingly, many of the E2-upregulated proteins contained the HEAT, KH, and RRM domains. The effect of E2 on cell survival was complex, as it could simultaneously enhance and inhibit apoptosis. E2 enhanced apoptosis by promoting cytochrome c release from mitochondria and inhibited apoptosis by activating the PI3K/AKT/mTOR signaling pathway. Treatment of MCF7 cells with E2 and the PI3K inhibitor Ly294002 significantly enhanced apoptosis compared to the cells treated with E2 alone. Our results suggest that combining estrogen with a PI3K inhibitor could be a promising strategy for treating ERα-positive breast cancer.
2025-05-06 | PXD049343 | Pride
Project description:Comparison between Estrogen receptor positive and Estrogen receptor negative breast cancer samples
| PRJNA107971 | ENA