E-GEOD-32526
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA147827
PROVIDER: E-GEOD-32526 | ExpressionAtlas | 2015-08-17
REPOSITORIES: ExpressionAtlas
Similar Datasets
Project description:Expression data from breast cancer tumor-initiating cells
| PRJNA147827 | ENA
Project description:The application of ketogenic diet (KD) (high fat/low carbohydrate/adequate protein) as an auxiliary cancer therapy is a field of growing attention. KD provides sufficient energy supply for healthy cells, while possibly impairing energy production in highly glycolytic tumor cells. Moreover, KD regulates insulin and tumor related growth factors (like insulin growth factor-1, IGF-1). In order to provide molecular evidence for the proposed additional inhibition of tumor growth when combining chemotherapy with KD, we applied untargeted quantitative metabolome analysis on a spontaneous breast cancer xenograft mouse model, using MDA-MB-468 cells. Healthy mice and mice bearing breast cancer xenografts and receiving cyclophosphamide chemotherapy were compared after treatment with control diet and KD. Metabolomic profiling was performed on plasma samples, applying high-performance liquid chromatography coupled to tandem mass spectrometry. Statistical analysis revealed metabolic fingerprints comprising numerous significantly regulated features in the group of mice bearing breast cancer. This fingerprint disappeared after treatment with KD, resulting in recovery to the metabolic status observed in healthy mice receiving control diet. Moreover, amino acid metabolism as well as fatty acid transport were found to be affected by both the tumor and the applied KD. Our results provide clear evidence of a significant molecular effect of adjuvant KD in the context of tumor growth inhibition and suggest additional mechanisms of tumor suppression beyond the proposed constrain in energy supply of tumor cells.
2020-08-01 | MSV000085879 | GNPS
Project description:The application of ketogenic diet (KD) (high fat/low carbohydrate/adequate protein) as an auxiliary cancer therapy is a field of growing attention. KD provides sufficient energy supply for healthy cells, while possibly impairing energy production in highly glycolytic tumor cells. Moreover, KD regulates insulin and tumor related growth factors (like insulin growth factor-1, IGF-1). In order to provide molecular evidence for the proposed additional inhibition of tumor growth when combining chemotherapy with KD, we applied untargeted quantitative metabolome analysis on a spontaneous breast cancer xenograft mouse model, using MDA-MB-468 cells. Healthy mice and mice bearing breast cancer xenografts and receiving cyclophosphamide chemotherapy were compared after treatment with control diet and KD. Metabolomic profiling was performed on plasma samples, applying high-performance liquid chromatography coupled to tandem mass spectrometry. Statistical analysis revealed metabolic fingerprints comprising numerous significantly regulated features in the group of mice bearing breast cancer. This fingerprint disappeared after treatment with KD, resulting in recovery to the metabolic status observed in healthy mice receiving control diet. Moreover, amino acid metabolism as well as fatty acid transport were found to be affected by both the tumor and the applied KD. Our results provide clear evidence of a significant molecular effect of adjuvant KD in the context of tumor growth inhibition and suggest additional mechanisms of tumor suppression beyond the proposed constrain in energy supply of tumor cells.
2019-10-08 | MTBLS1066 | MetaboLights
Project description:Gene expression profiling of circulating tumor cells in breast cancer
| PRJNA239696 | 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.
2017-07-26 | BIOMD0000000642 | BioModels
Project description:Expression data from breast cancer cells overexpressing NF1-C2
| PRJNA118575 | ENA
Project description:MicroRNA (miRNA/miR) miR526b and miR655 overexpressed tumor cell-free secretions promote breast cancer phenotypes in the tumor microenvironment (TME). However, the mechanisms of miRNA regulating TME have never been investigated. With mass spectrometry analysis of MCF7-miRNA-overexpressed versus miRNA-low MCF7-Mock tumor cell secretomes, we identified 34 novel secretory proteins coded by eight genes YWHAB, TXNDC12, MYL6B, SFN, FN1, PSMB6, PRDX4, and PEA15 those are differentially regulated. We used bioinformatic tools and systems biology approaches to identify these markers’ role in breast cancer. Gene ontology analysis showed that the top functions are related to apoptosis, oxidative stress, membrane transport, and motility, supporting miRNA-induced phenotypes. These secretory markers expression is high in breast tumors, and a strong positive correlation exists between upregulated markers’ mRNA expressions with miRNA cluster expression in luminal A breast tumors. Gene expression of secretome markers is higher in tumor tissues compared to normal samples, and immunohistochemistry data supported gene expression data. Moreover, both up and downregulated marker expressions are associated with breast cancer patient survival. miRNA regulates these marker protein expressions by targeting transcription factors of these genes. Premature miRNA (pri-miR526b and pri-miR655) are established breast cancer blood biomarkers. Here we report novel secretory markers upregulated by miR526b and miR655 (YWHAB, MYL6B, PSMB6, and PEA15) are significantly upregulated in breast cancer patients’ plasma, and are potential breast cancer biomarkers.
2023-05-10 | PXD031771 | Pride
Project description:The SLC22A18 gene, which encodes an orphan transporter, is located at the 11p15.5 imprinted region, an important tumor-suppressor gene region. However, the role of SLC22A18 in tumor suppression remains unclear. Here, we investigated the involvement of SLC22A18 in cell growth, invasion and drug resistance of MCF7 human breast cancer cell line. Western blot analysis indicated that SLC22A18 is predominantly expressed at intracellular organelle membranes. Quantitative proteomics showed that knockdown of SLC22A18 significantly altered the expression of 578 (31.0%) out of 1867 proteins identified, including proteins related to malignancy and poor prognosis of breast cancer.
2019-06-01 | PXD010183 | JPOST Repository
Project description:Cancer cells are known to reprogram their metabolism to adapt to adverse conditions dictated by tumor growth and microenvironment. A subtype of cancer cells with stem-like properties, known as cancer stem cells (CSC), is thought to be responsible for tumor recurrence. In this study, we demonstrated that CSC and chemoresistant cells derived from triple negative breast cancer cells display an enrichment of up- and downregulated proteins from metabolic pathways that suggests their dependence on mitochondria for survival. Here, we selected antibiotics, in particular - linezolid, inhibiting translation of mitoribosomes and inducing mitochondrial dysfunction. We provided the first in vivo evidence demonstrating that linezolid suppressed tumor growth rate, accompanied by increased autophagy. In addition, our results revealed that bactericidal antibiotics used in combination with autophagy blocker decrease tumor growth. This study puts mitochondria in a spotlight for cancer therapy and places antibiotics as effective agents for eliminating CSC and resistant cells.
2019-08-19 | MTBLS678 | MetaboLights