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accession-icon GSE23980
Expression data from human soft tissue sarcomas with complex genomics
  • organism-icon Homo sapiens
  • sample-icon 164 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Differentially expressed genes between 171 human soft tissue sarcomas with complex genomics

Publication Title

From PTEN loss of expression to RICTOR role in smooth muscle differentiation: complex involvement of the mTOR pathway in leiomyosarcomas and pleomorphic sarcomas.

Sample Metadata Fields

Sex, Specimen part, Cell line

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accession-icon GSE71121
Expression data (micro-array and RNA-seq, frozen tumors and FFPE blocks) from various sarcomas
  • organism-icon Homo sapiens
  • sample-icon 259 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

RNA sequencing validation of the Complexity INdex in SARComas prognostic signature.

Sample Metadata Fields

Time

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accession-icon GSE71118
Expression data (micro-array, frozen tumors) from various sarcomas
  • organism-icon Homo sapiens
  • sample-icon 259 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We validated the technological and material transfers of the CINSARC signature.

Publication Title

RNA sequencing validation of the Complexity INdex in SARComas prognostic signature.

Sample Metadata Fields

Time

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accession-icon GSE35306
Combined hepatocellular-cholangiocarcinomas exhibit progenitor features and activation of Wnt and TGFbeta signaling pathways
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Primary liver tumours include hepatocellular carcinomas (HCC), cholangiocarcinomas (CC) and a group of rare tumours exhibiting biliary and hepatocytic differentiation called combined hepatocholangiocarcinomas (cHCC-CC). To better define this latter group, we take advantage of a series of these tumours based on their morphological characteristics and we performed transcriptional analysis allowing thereafter global comparison with published data. We show that most cHCC-CCs express progenitor cell traits, are committed to biliary lineage and are mainly associated to the activation of Wnt/beta-catenin and TGFbeta signalling pathways. Wnt/beta-catenin pathway activation in cHCC-CC is evidenced by the expression of both its direct targets such as LEF1 and EPCAM. In addition, extracellular matrix (ECM) genes and ECM-remodelling genes which are upon the control of TGF profibrotic program were found up-regulated in cHCC-CC. Interestingly, we show that CC and most cHCC-CC share characteristics associated to a subtype of poorly differentiated HCC suggesting that these tumours could originate from a stem/progenitor cell. The plasticity of these cells may explain the phenotypical heterogeneity of these tumors with the maintenance of some hepatocellular differentiation features such as albumin expression. Interestingly, this is shared by at least one third of CC, raising the hypothesis of a potential continuum between CC, cHCC-CC and poorly differentiated HCC.

Publication Title

Combined hepatocellular-cholangiocarcinomas exhibit progenitor features and activation of Wnt and TGFβ signaling pathways.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE58697
Expression data from 128 Desmoids
  • organism-icon Homo sapiens
  • sample-icon 123 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

One of the main problems in managing desmoids tumors is their locoregional aggressiveness and their high ability to recur after initial treatment. In our work, with the goal to identify molecular markers that can predict Progression-Free Survival, gene-expression screening was conducted on 128 available independent untreated primary desmoid tumors using cDNA microarray. By analyzing expression profiles, we have identified, for the first time, a gene expression signature that is able to predict Progression-Free Survival. This molecular signature identified two groups with clearly distinct Progression-Free Survival in the two sets of subjects. Patients in good prognostic group had achieved a progression-free 2-year survival rate of 86% while patients in poor prognostic group had a progression-free 2-year survival rate of 44%.

Publication Title

Gene Expression Profiling of Desmoid Tumors by cDNA Microarrays and Correlation with Progression-Free Survival.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE4188
Drosophila whole testis gene expression
  • organism-icon Drosophila melanogaster
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome Array (drosgenome1)

Description

Whole testes were dissected from adult males. RNA from five or six biological replicates were generated and the expression profiles were determined using Affymetrix Drosophila Genechip 1 arrays. Comparisons between the bgcn- and Os+bgcn- groups allowed for the identification of stem cell genes.

Publication Title

Novel regulators revealed by profiling Drosophila testis stem cells within their niche.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE21050
Expression data from Complex genetics sarcomas (cohort 1 and 2)
  • organism-icon Homo sapiens
  • sample-icon 303 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

For this study, we selected, from the French Sarcoma Group (FSG) database, soft tissue sarcomas with no recurrent chromosomal translocations and for which a frozen tissue of the untreated primary tumor was available. Three hundred and ten sarcomas have been studied. They are split in two cohorts.

Publication Title

Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity.

Sample Metadata Fields

Specimen part, Disease, Time

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accession-icon SRP057793
RNA-seq performed on sarcomas to identify various alterations
  • organism-icon Homo sapiens
  • sample-icon 149 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

No description.

Publication Title

Genomic and transcriptomic comparison of post-radiation versus sporadic sarcomas.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP113755
Transcriptome characterization of radiation-induced sarcomas
  • organism-icon Homo sapiens
  • sample-icon 73 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

No description.

Publication Title

Genomic and transcriptomic comparison of post-radiation versus sporadic sarcomas.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE11732
Runx transcriptional program for control of cell adhesion and survival
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The Runx genes are important in development and cancer, where they can act either as oncogenes or tumour supressors. We compared the effects of ectopic Runx expression in established fibroblasts, where all three genes produce an indistinguishable phenotype entailing epithelioid morphology and increased cell survival under stress conditions. Gene array analysis revealed a strongly overlapping transcriptional signature, with no examples of opposing regulation of the same target gene. A common set of 50 highly regulated genes was identified after further filtering on regulation by inducible RUNX1-ER. This set revealed a strong bias toward genes with annotated roles in cancer and development, and a preponderance of targets encoding extracellular or surface proteins reflecting the marked effects of Runx on cell adhesion.

Publication Title

Gene array analysis reveals a common Runx transcriptional programme controlling cell adhesion and survival.

Sample Metadata Fields

No sample metadata fields

View Samples
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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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Developed by the Childhood Cancer Data Lab

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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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