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accession-icon GSE3167
Classification of carcinoma in situ lesions in human bladder cancer
  • organism-icon Homo sapiens
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The presence of carcinoma in situ (CIS) lesions in the urinary bladder is associated with a high risk of disease progression to a muscle invasive stage. In this study, we used microarray expression profiling to examine the gene expression patterns in superficial transitional cell carcinoma (sTCC) with surrounding CIS (13 patients), without surrounding CIS lesions (15 patients), and in muscle invasive carcinomas (mTCC; 13 patients). Hierarchical cluster analysis separated the sTCC samples according to the presence or absence of CIS in the surrounding urothelium. We identified a few gene clusters that contained genes with similar expression levels in transitional cell carcinoma (TCC) with surrounding CIS and invasive TCC. However, no close relationship between TCC with adjacent CIS and invasive TCC was observed using hierarchical cluster analysis. Expression profiling of a series of biopsies from normal urothelium and urothelium with CIS lesions from the same urinary bladder revealed that the gene expression found in sTCC with surrounding CIS is found also in CIS biopsies as well as in histologically normal samples adjacent to the CIS lesions. Furthermore, we also identified similar gene expression changes in mTCC samples. We used a supervised learning approach to build a 16-gene molecular CIS classifier. The classifier was able to classify sTCC samples according to the presence or absence of surrounding CIS with a high accuracy. This study demonstrates that a CIS gene expression signature is present not only in CIS biopsies but also in sTCC, mTCC, and, remarkably, in histologically normal urothelium from bladders with CIS. Identification of this expression signature could provide guidance for the selection of therapy and follow-up regimen in patients with early stage bladder cancer.

Publication Title

Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE22910
hsa-miR-191, a potential target for Hepatocellular carcinoma therapy
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

hsa-miR-191 is a candidate oncogene target for hepatocellular carcinoma therapy.

Sample Metadata Fields

Cell line, Treatment, Time

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accession-icon GSE22790
Gene expression after treatment with anti-miR-191 or control
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The goal of this experiment was to identify possible genes affected directly or indirectly by anti-miR-191.

Publication Title

hsa-miR-191 is a candidate oncogene target for hepatocellular carcinoma therapy.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE68424
Expression data from glioblastoma stem-like cells
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The objective of this study is to determine how inhibition of microRNA 10b affects gene expression in neurospheres cultures of glioblastoma stem-like cells.

Publication Title

Therapeutic potential of targeting microRNA-10b in established intracranial glioblastoma: first steps toward the clinic.

Sample Metadata Fields

Treatment

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accession-icon GSE30053
Dynamics of two oscillation phenotypes in S. cerevisiae reveal a network of genome-wide transcriptional and cell cycle oscillators.
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 80 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE30052
Dynamics of two oscillation phenotypes in S. cerevisiae [4hr]
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Genetic and environmental factors influence the phenotype of an organism. Time is rarely considered when studying changes in cellular phenotype. Time-resolved microarray data revealed genome-wide transcriptional changes in cells oscillating with ~2 and ~4 h periods. We mapped the global patterns of transcriptional oscillations into a 3-dimensional map to represent different cellular phenotypes of oscillation period. This map shows the dynamic nature of transcripts through time and concentration space, and that they are ordered and coupled to each other. Although cells differed in oscillation periods, transcripts involved in certain processes were conserved in a deterministic way. This ordered timing of biological process may allow cells to grow energetically efficient. Decreased glucose levels in the media were found to increase the redox cycles of yeast strain CEN.PK113-7D. Glucose may have acted as signaling molecules for timing longer catabolic processes in the cell population. As oscillation period lengthened, the peak to trough ratio of transcripts increased and the percent of cells in the unbudded (G0/G1) phase of the cell cycle increased. Gene transcripts appear to be coordinated with metabolic functions and the cell cycle.

Publication Title

Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE30051
Dynamics of two oscillation phenotypes in S. cerevisiae [2hr]
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Genetic and environmental factors influence the phenotype of an organism. Time is rarely considered when studying changes in cellular phenotype. Time-resolved microarray data revealed genome-wide transcriptional changes in cells oscillating with ~2 and ~4 h periods. We mapped the global patterns of transcriptional oscillations into a 3-dimensional map to represent different cellular phenotypes of oscillation period. This map shows the dynamic nature of transcripts through time and concentration space, and that they are ordered and coupled to each other. Although cells differed in oscillation periods, transcripts involved in certain processes were conserved in a deterministic way. This ordered timing of biological process may allow cells to grow energetically efficient. Decreased glucose levels in the media were found to increase the redox cycles of yeast strain CEN.PK113-7D. Glucose may have acted as signaling molecules for timing longer catabolic processes in the cell population. As oscillation period lengthened, the peak to trough ratio of transcripts increased and the percent of cells in the unbudded (G0/G1) phase of the cell cycle increased. Gene transcripts appear to be coordinated with metabolic functions and the cell cycle.

Publication Title

Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE6197
Rat Semi-Circular Canal Duct Gene Expression Studies
  • organism-icon Rattus norvegicus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

The goal was to screen for the expressed genes in Semi-Circular Canal Duct (SCCD) that are related to ion transport and its regulation. The objectives was to discover which genes changed expression levels in response to glucocorticoids.

Publication Title

Ion transport regulation by P2Y receptors, protein kinase C and phosphatidylinositol 3-kinase within the semicircular canal duct epithelium.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE64086
MYC-negative BL frequent in posttransplant patients
  • organism-icon Homo sapiens
  • sample-icon 11 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

Post-transplant molecularly defined Burkitt lymphomas are frequently MYC-negative and characterized by the 11q-gain/loss pattern.

Sample Metadata Fields

Sex, Age, Treatment

View Samples
accession-icon GSE64085
MYC-negative BL frequent in posttransplant patients (expression)
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We performed genomic and transcriptomic analysis of seven cases of molecular Burkitt lymphoma (mBL) developed in immunosuppressed patients who underwent solid organ transplantation. Interestingly, three cases (43%) were MYC-translocation-negative and revealed the 11q-gain/loss aberration recently identified in 3% of mBL developed in immunocompetent hosts.1 Based on array CGH data, minimal gain and loss regions of 11q (MGR/~4Mb and MLR/~13.5Mb, respectively) were defined and integrative genomic and transcriptomic analysis identified 35 differentially expressed genes, when compared with classic BL. All 16 MGR-dysregulated genes were upregulated, including cancer related USP2, CBL and PAFAH1B2. As expected, all 19 MGL-dysregulated genes were downregulated and two of them, TBRG1 and EI24, are potential tumor suppressor genes. Interestingly, the vast majority of dysregulated 11q23-q25 genes are involved in the MYC and TP53 networks. We hypothesize that the 11q-gain/loss aberration represents a molecular variant of t(8q24/MYC) and affects the same pathological pathways as the MYC oncogene.

Publication Title

Post-transplant molecularly defined Burkitt lymphomas are frequently MYC-negative and characterized by the 11q-gain/loss pattern.

Sample Metadata Fields

Sex, Age, Treatment

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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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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