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accession-icon GSE83503
Key transcription factors altered in multiple myeloma patients revealed by logic programming approach combining gene expression pro ling and regulatory networks
  • organism-icon Homo sapiens
  • sample-icon 602 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

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.

Publication Title

Logic programming reveals alteration of key transcription factors in multiple myeloma.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE58812
Gene-expression molecular subtyping of triple-negative breast cancer tumours: importance of immune response
  • organism-icon Homo sapiens
  • sample-icon 98 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Triple-negative (TN) breast cancers need to be refined in order to identify therapeutic subgroups of patients.

Publication Title

Gene-expression molecular subtyping of triple-negative breast cancer tumours: importance of immune response.

Sample Metadata Fields

Disease

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accession-icon GSE103091
Gene-expression molecular subtyping of triple-negative breast cancer tumors
  • organism-icon Homo sapiens
  • sample-icon 98 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

No associated publication

Sample Metadata Fields

Disease

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accession-icon GSE37469
Minor clone provides a reservoir for relapse in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st), Affymetrix Mapping 250K Nsp SNP Array (mapping250knsp)

Description

In 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.

Publication Title

Minor clone provides a reservoir for relapse in multiple myeloma.

Sample Metadata Fields

Specimen part, Disease, Cell line, Subject

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accession-icon GSE37414
Expression of genetic adaptability of cancer cells under treatment selection pressure in multiple myeloma patients
  • organism-icon Homo sapiens
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Series GSE25262 patients on expression side.

Publication Title

Minor clone provides a reservoir for relapse in multiple myeloma.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE26027
Early dynamic transcriptomic changes as predictors of preoperative radiotherapy efficacy in patients with rectal cancer: a feasibility study.
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

With a view to developing novel biomarkers of the efficacy of radiotherapy in patients with rectal cancer, we measured gene expression profiles on biopsies taken before and during preoperative radiotherapy. Repeat biopsy did not increase toxicity. Radiotherapy induced the expression of genes involved in oxidative stress, signal transduction, apoptosis and immune response.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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