Innovative approaches combining regulatory networks and genomic data are needed to extract pertinent biological informations to a better understanding of complex disease such as cancer and improve identi cation of entities leading to potential new therapeutic avenues. In this study, we confronted an automatic generated regulatory network with gene expression pro les (GEP) from a large cohort of patients with multiple myeloma (MM) and normal individuals with a causality reasonning method based of graph coloring to identify keynodes. Due to this causality reasoning, it is possible to infer proteins state from these GEP. Also, our method is able to simulate the impact of the perturbation of a node in this regulatory network to identify therapeutic targets. This method allowed us to nd that JUN/FOS and FOXM1, known in MM, and their inhibition as speci c to large group of patients with MM. Moreover, we associated the inhibition of FOXM1 activity with good prognosis, suggesting the inhibition of FOXM1 activity could be a survival marker. Finally, if JUN/FOS activation seems to be a way to strongly perturb the regulatory network in view of GEP, our result suggests the activation of FOXM1 could be interesting way to perturb some sub-group of profiles.
Logic programming reveals alteration of key transcription factors in multiple myeloma.
Specimen part, Disease, Disease stage
View SamplesWe have analyzed gene expression microarray datasets from four different clinical trials to assess accuracy of gene expression based signature in predicting treatment complete response in patients with multiple myeloma. Two of four datasets were made available via The Intergroupe Francophone du Mylome (IFM) group, and remaining two datasets were downloaded from NCBI GEO portal with accession IDs: GSE19784 (HOVON65/GMMG-HD4 trial) and GSE9782 (APEX/SUMMIT trial). Analysis UUID: datasets_archive--2afcd42a-7e12-11e3-9145-5fcc1e060548--15-Jan-2014-12-23-44-CST.
Gene expression profile alone is inadequate in predicting complete response in multiple myeloma.
No sample metadata fields
View SamplesIn this study we addressed subclonal evolutionary process after treatment and subsequent relapse in multiple myeloma (MM) in a cohort of 24 MM patients treated either with conventional chemotherapy or with the proteasome inhibitor, bortezomib. Because MM is a highly heterogeneous disease coupled with a large number of DNA copy number alterations (CNAs) and loss of heterozygosity (LOH), we focused our study on the secondary genetic events: 1q21 gain, NF-kB activating mutations, RB1 and TP53 deletions, that seem to reflect progression. By using genome-wide high resolution SNP arrays we identified subclones with nonlinear complex evolutionary histories in a third of patients with myeloma, the relapse clone apparently derived from a minor subclone at diagnosis. Such reordering of the spectrum of genetic lesions during therapy is likely to reflect selection of genetically distinct subclones not initially competitive against the dominant population that survived chemotherapy, thrived and acquired new anomalies. In addition we found that emergence of minor subclones at relapse was significantly associated with bortezomib treatment. Altogether, these data support the idea of new strategy of future clinical trials in MM that would combine targeted therapy and subpopulations control to eradicate all myeloma subclones in order to obtain long-term remission.
Minor clone provides a reservoir for relapse in multiple myeloma.
Specimen part, Disease, Cell line, Subject
View SamplesSeries GSE25262 patients on expression side.
Minor clone provides a reservoir for relapse in multiple myeloma.
Specimen part, Disease
View SamplesGene Expression profiling of 170 newly diagnosed Multiple Myeloma patients
A small molecule inhibitor of ubiquitin-specific protease-7 induces apoptosis in multiple myeloma cells and overcomes bortezomib resistance.
Disease
View SamplesWe examined global gene expression patterns in response to PGC-1 expression in cells derived from liver or muscle.
Direct link between metabolic regulation and the heat-shock response through the transcriptional regulator PGC-1α.
Specimen part
View SamplesCell adhesion plays an important role in determining cell shape and function in a variety of physiological and pathophysiological conditions. While links between metabolism and cell adhesion were previously suggested, the exact context and molecular details of such a cross-talk remain incompletely understood.
Inhibition of Adhesion Molecule Gene Expression and Cell Adhesion by the Metabolic Regulator PGC-1α.
Specimen part, Cell line
View SamplesSecreted proteins serve pivotal roles in the development of multicellular organisms, acting as structural matrix, extracellular enzymes and signal molecules. In this study we demonstrate, unexpectedly, that PGC-1, a critical transcriptional co-activator of metabolic gene expression, functions to down-regulate expression of diverse genes encoding secreted molecules and extracellular matrix (ECM) components to modulate the secretome. We show that both endogenous and exogenous PGC-1 down-regulate expression of numerous genes encoding secreted molecules. Mechanistically, results obtained using mRNA stability measurements as well as intronic RNA expression analysis are consistent with a transcriptional effect of PGC-1 on expression of genes encoding secreted proteins. Interestingly, PGC-1 requires the central heat shock response regulator HSF1 to affect some of its targets, and both factors co-reside on several target genes encoding secreted molecules in cells. Finally, using a mass spectrometric analysis of secreted proteins, we demonstrate that PGC-1 modulates the secretome of mouse embryonic fibroblasts (MEFs).
Control of Secreted Protein Gene Expression and the Mammalian Secretome by the Metabolic Regulator PGC-1α.
Specimen part
View SamplesSlow-cycling subpopulations exist in bacteria, yeast, and mammalian systems. In the case of cancer, slow-cycling subpopulations have been proposed to give rise to drug resistance. However, the origin of slow-cycling human cells is poorly studied, in large part due to lack of markers to identify these rare cells. Slow-cycling cells pass through a non-cycling period marked by low CDK2 activity and high p21 levels. Here, we use this knowledge to isolate these naturally slow-cycling cells from a heterogeneous population and perform RNA-sequencing to delineate the transcriptome underlying the slow-cycling state. We show that cellular stress responses – the p53 transcriptional response and the integrated stress response – are the most salient causes of spontaneous entry into the slow-cycling state. Overall design: mRNA profiling of spontaneously quiescent human cells and cells forced into quiescence by four different methods
Spontaneously slow-cycling subpopulations of human cells originate from activation of stress-response pathways.
Cell line, Subject
View SamplesHuman embryonic stem cells (hESCs) have the unique property of immortality, ability to infinitely self-renew and survive in vitro. In contrast to tumor-deribed cells, their immortality are free from any genomic abberations. Instead, they depend on the AKAP-Lbc/Rho signaling cascade. To understand the downstream way, we performed RNA-seq analyses between normal and AKAP-Lbc-depleted hESCs using the doxycyclin-inducible gene silensing strategy. Overall design: We use the genetically modified hESCs in which AKAP-13-targeting shRNA is induced by doxycyclin(dox) treatment. To minimize cell loss during treatment, anti-apoptotic factor Bcl-XL is overexpressed. We collected RNA from dox-treated and untreated cells in biological triplicate. We measured gene expression in these 2 sample groups using RNA-seq (illumina HiSeq) .
Rho-Signaling-Directed YAP/TAZ Activity Underlies the Long-Term Survival and Expansion of Human Embryonic Stem Cells.
No sample metadata fields
View Samples