Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-43306
PROVIDER: PRJNA185392 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR645775_1.fastq.gz | Fastqsanger.gz | |||
| SRR645775_2.fastq.gz | Fastqsanger.gz | |||
| SRR645776_1.fastq.gz | Fastqsanger.gz | |||
| SRR645776_2.fastq.gz | Fastqsanger.gz | |||
| SRR645777_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 18 |
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Project description:A mesenchymal rich stroma such as cancer-associated fibroblasts (CAFs) in breast tumors favors the selection of cancer clones with enhanced bone metastatic ability. To determine the cancer cell transcriptomic response to the mesenchymal stroma, we supplemented experimental mammary tumours with or without exogenous mesenchymal cells. We used bone marrow-derived human mesenchymal stem cells (MSCs) as a source of mesenchymal stroma, as MSCs have been shown to undergo CAF-like differentiation. We engineered the cancer cells to express an EGFP-tagged version of ribosomal protein L10a (EGFP-L10a). This allows the retrieval of cancer cell specific transcripts rapidly from whole tumor lysates by translating ribosome affinity purification (TRAP) and direct profiling of cancer cell gene expression patterns when they are in situ. EGFP-10a+ MDA-MB-231 cells were orthotopically injected into the mammary fat pad with or without 1:1 ratio of MSCs. The mammary tumors were retrieved for TRAP-RNAseq profiling after 3 weeks.
2013-11-01 | E-GEOD-43306 | biostudies-arrayexpress
Project description:A mesenchymal rich stroma such as cancer-associated fibroblasts (CAFs) in breast tumors favors the selection of cancer clones with enhanced bone metastatic ability. To determine the cancer cell transcriptomic response to the mesenchymal stroma, we supplemented experimental mammary tumours with or without exogenous mesenchymal cells. We used bone marrow-derived human mesenchymal stem cells (MSCs) as a source of mesenchymal stroma, as MSCs have been shown to undergo CAF-like differentiation. We engineered the cancer cells to express an EGFP-tagged version of ribosomal protein L10a (EGFP-L10a). This allows the retrieval of cancer cell specific transcripts rapidly from whole tumor lysates by translating ribosome affinity purification (TRAP) and direct profiling of cancer cell gene expression patterns when they are in situ.
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Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs.
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Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs. One-condition experment, gene expression of 3A6
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Project description:This model is based on:
Computational Modeling of the Crosstalk Between Macrophage Polarization and Tumor Cell Plasticity in the Tumor Microenvironment.
Abstract:
Tumor microenvironments contain multiple cell types interacting among one another via different signaling pathways. Furthermore, both cancer cells and different immune cells can display phenotypic plasticity in response to these communicating signals, thereby leading to complex spatiotemporal patterns that can impact therapeutic response. Here, we investigate the crosstalk between cancer cells and macrophages in a tumor microenvironment through in silico (computational) co-culture models. In particular, we investigate how macrophages of different polarization (M1 vs. M2) can interact with epithelial-mesenchymal plasticity of cancer cells, and conversely, how cancer cells exhibiting different phenotypes (epithelial vs. mesenchymal) can influence the polarization of macrophages. Based on interactions documented in the literature, an interaction network of cancer cells and macrophages is constructed. The steady states of the network are then analyzed. Various interactions were removed or added into the constructed-network to test the functions of those interactions. Also, parameters in the mathematical models were varied to explore their effects on the steady states of the network. In general, the interactions between cancer cells and macrophages can give rise to multiple stable steady-states for a given set of parameters and each steady state is stable against perturbations. Importantly, we show that the system can often reach one type of stable steady states where cancer cells go extinct. Our results may help inform efficient therapeutic strategies.
2019-09-23 | MODEL1909230002 | BioModels