Identification of five cytotoxicity-related genes involved in the progression of breast cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE183947 | GEO | 2021/09/15
REPOSITORIES: GEO
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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.
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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.
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Project description:Identification of five cytotoxicity-related genes involved in the progression of breast cancer
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Project description:Dynamics of Breast Cancer under Different Rates of Chemoradiotherapy.
Mkango SB1, Shaban N1, Mureithi E1, Ngoma T2.
Author information
1
Department of Mathematics, University of Dar es Salaam, P.O. Box 35062, Dar es Salaam, Tanzania.
2
Department of Clinical Oncology, Muhimbili University of Health and Allied Sciences, P.O. Box 65000, Dar es Salaam, Tanzania.
Abstract
A type of cancer which originates from the breast tissue is referred to as breast cancer. Globally, it is the most common cause of death in women. Treatments such as radiotherapy, chemotherapy, hormone therapy, immunotherapy, and gene therapy are the main strategies in the fight against breast cancer. The present study aims at investigating the effects of the combined radiotherapy and chemotherapy as a way to treat breast cancer, and different treatment approaches are incorporated into the model. Also, the model is fitted to data on patients with breast cancer in Tanzania. We determine new treatment strategies, and finally, we show that when sufficient amount of chemotherapy and radiotherapy with a low decay rate is used, the drug will be significantly more effective in combating the disease while health cells remain above the threshold.
Copyright © 2019 Sara B. Mkango et al.
2020-01-20 | MODEL1912120005 | BioModels
Project description:Breast cancer risk continues to increase post menopause. Anti-estrogen therapies are available to prevent postmenopausal breast cancer in high-risk women. However, their adverse effects have reduced acceptability and overall success in cancer prevention. Natural products such as hops (Humulus lupulus) and three pharmacopeial licorice (Glycyrrhiza) species have demonstrated estrogenic and chemopreventive properties, but little is known regarding their effects on aromatase expression and activity as well as pro-proliferation pathways in human breast tissue. We show that Gycyrrhiza inflata (GI) has the highest aromatase inhibition potency among these plant extracts. Moreover, phytoestrogens such as liquiritigenin which is common in all licorice species have potent aromatase inhibitory activity, which is further supported by computational docking of their structures in the binding pocket of aromatase. In addition, GI extract and liquiritigenin suppress aromatase expression in the breast tissue of high-risk postmenopausal women. Although liquiritigenin has estrogenic effects in vitro, with preferential activity through estrogen receptor (ER)-β, it reduces estradiol-induced uterine growth in vivo. It downregulates RNA translation, protein biosynthesis, and metabolism in high-risk women’s breast tissue. Finally, it reduces the rate of MCF-7 cell proliferation, with repeated dosing. Collectively, these data suggest that liquiritigenin has breast cancer prevention potential for high-risk postmenopausal women. We then performed gene expression profiling analysis using data obtained from RNA-seq of 4 different cells at two time points.
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