Hypoxia-mediated translational activation of ITGB3 in breast cancer cells enhances TGF-β signalling and malignant features in vitro and in vivo
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ABSTRACT:
PROVIDER: PRJNA412005 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6068880_1.fastq.gz | Fastqsanger.gz | |||
| SRR6068880_2.fastq.gz | Fastqsanger.gz | |||
| SRR6068890_1.fastq.gz | Fastqsanger.gz | |||
| SRR6068890_2.fastq.gz | Fastqsanger.gz | |||
| SRR6068900_1.fastq.gz | Fastqsanger.gz |
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Project description:We performed a polysomal RNA-Seq screen in non-malignant breast epithelial (MCF10A) and TNBC (MDA-MB-231) cells exposed to normoxic or hypoxic conditions and/or treated with an mTOR pathway inhibitor. Analysis of both the transcriptome and the translatome identified mRNA transcripts translationally activated or repressed by hypoxia in an mTOR-dependent or -independent manner. The mRNA populations of each sample were converted to cDNA libraries using the TruSeq protocol and then sequenced using a HiSeq 2000 machine. Paired-end reads were mapped against the reference human genome (GRCh38) with STAR v2.5.1b (ENCODE parameters for long RNA) and GENCODE v24 annotation. Gene quantification was performed using RSEM v1.2.28 with default parameters. Only protein-coding genes were included in the analysis. Normalization of the count matrix was performed with the TMM method of the edgeR R package. Polysomal RNA (P) and RNA total (T) fold changes across conditions were calculated with edgeR. Significant genes (FDR < 5% for MCF10A cells and FDR < 10% for MDA-MB-231 cells) in polysomes were selected for translational efficiency calculation (log2FC RNA polysomes/log2FC RNA total). Genes with a z-score > 1.5 were considered to have an increased translational efficiency and genes with a z-score < –1.5 were considered to have a decreased translational efficiency. GO enrichment analysis of significant genes was performed with the DAVID database.
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Project description:Cellière2011 - Plasticity of TGF-β Signalling
Transforming growth factor beta (TGF-β) signalling has been implicated as an important regulator of almost all major cell behaviours, including proliferation, differentiation, cell death, and motility. It remains unclear that how the TGF-β signalling pathway accomplishes the flexibility in its responses. What and how many parameters have to be altered for cells to respond differently to perform complex tasks? This canonical response has been explored in this model, by considering the core signalling architecture of TGF-β pathway.
This model is described in the article:
Plasticity of TGF-β signaling
Cellière G, Fengos G, Hervé M, Iber D.
BMC Syst Biol. 2011 Nov 3;5:184.
Abstract:
The family of TGF-β ligands is large and its members are involved in many different signaling processes. These signaling processes strongly differ in type with TGF-β ligands eliciting both sustained or transient responses. Members of the TGF-β family can also act as morphogen and cellular responses would then be expected to provide a direct read-out of the extracellular ligand concentration. A number of different models have been proposed to reconcile these different behaviours. We were interested to define the set of minimal modifications that are required to change the type of signal processing in the TGF-β signaling network.
RESULTS:
To define the key aspects for signaling plasticity we focused on the core of the TGF-β signaling network. With the help of a parameter screen we identified ranges of kinetic parameters and protein concentrations that give rise to transient, sustained, or oscillatory responses to constant stimuli, as well as those parameter ranges that enable a proportional response to time-varying ligand concentrations (as expected in the read-out of morphogens). A combination of a strong negative feedback and fast shuttling to the nucleus biases signaling to a transient rather than a sustained response, while oscillations were obtained if ligand binding to the receptor is weak and the turn-over of the I-Smad is fast. A proportional read-out required inefficient receptor activation in addition to a low affinity of receptor-ligand binding. We find that targeted modification of single parameters suffices to alter the response type. The intensity of a constant signal (i.e. the ligand concentration), on the other hand, affected only the strength but not the type of the response.
CONCLUSIONS:
The architecture of the TGF-β pathway enables the observed signaling plasticity. The observed range of signaling outputs to TGF-β ligand in different cell types and under different conditions can be explained with differences in cellular protein concentrations and with changes in effective rate constants due to cross-talk with other signaling pathways. It will be interesting to uncover the exact cellular differences as well as the details of the cross-talks in future work.
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