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accession-icon GSE4475
A Biologic Definition of Burkitt's Lymphoma from Transcriptional and Genomic Profiling
  • organism-icon Homo sapiens
  • sample-icon 219 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The distinction between the Burkitt lymphoma and diffuse large B-cell lymphoma is imprecise using current diagnostic criteria. We applied transcriptional and genomic profiling to molecularly define Burkitt lymphoma. Gene expression profiling employing Affymetrix GeneChips (U133A) was performed in 220 mature aggressive B-cell lymphomas, including a core group of eight Burkitt lymphomas, which fulfilled all diagnostic criteria of the WHO classification. A molecular signature of Burkitt lymphoma was generated. Chromosomal abnormalities were detected by interphase fluorescence in-situ hybridization and array comparative genomic hybridization. The molecular Burkitt lymphoma signature identified 44 cases. Fifteen of these cases lacked a morphology typical for Burkitt/Burkitt-like lymphoma. The vast majority (88%) of the 176 lymphomas without the molecular Burkitt lymphoma signature represented diffuse large B-cell lymphomas. In 20% of these cases a MYC break was detectable which was associated with complex chromosomal changes. Our molecular definition of Burkitt lymphoma sharpens and extends the spectrum of Burkitt lymphoma. In mature aggressive B-cell lymphomas without a Burkitt lymphoma signature, a chromosomal break in the MYC locus proved to be associated with adverse clinical outcome.

Publication Title

A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling.

Sample Metadata Fields

Sex, Age

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accession-icon GSE2401
Gene expression in Hypotension
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

Rat kidney in normo- and hypotensive animals.

Publication Title

A physiogenomic approach to study the regulation of blood pressure.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE21266
Effect of Ursodeoxycholic acid on gene expression in the intestial epithelium
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Background & Aims: Ursodeoxycholic acid (UDCA) attenuates chemical and colitis-induced colon carcinogenesis in animal models. We investigated its mechanism of action on normal intestinal cells, in which carcinogenesis- or inflammation-related alterations do not interfere with the result. Methods: Alterations of gene expression were identified in Affymetrix arrays in isolated colon epithelium of mice fed with a diet containing 0.4% UDCA and were confirmed in the normal rat intestinal cell line IEC-6 by RT-PCR. The effect of the insulin receptor substrate 1 (Irs-1) expression and of ERK phosphorylation on proliferation was investigated in vitro by flow cytometry, western blotting, siRNA-mediated gene suppression or by pharmacological inhibition of the kinase activity. The ERK1-effect on Irs-1 transcription was tested in a reporter system. Results: UDCA-treatment in vivo suppressed potential pro-proliferatory genes including Irs-1 and reduced cell proliferation by more than 30%. In vitro it neutralised the proliferatory signals of IGF-1 and EGF and slowed down the cell cycle. Irs-1 transcription was suppressed due to high ERK1 activation. Both Irs-1 suppression and the persistent high ERK activation inhibited proliferation. Conversely, the decrease of phosphorylation of ERK1 (but not ERK2) or of its expression partially abrogated the inhibitory effects of UDCA. Conclusions: UDCA inhibits proliferation of intestinal epithelial cells by acting upon IGF-1 and EGF pathways and targeting ERK1 and, consequently, Irs-1. The inhibition of these pathways adds a new dimension to the physiological and therapeutic action of UDCA and, since both pathways are activated in inflammation and cancer, suggests new applications of UDCA in chemoprevention and chemotherapy.

Publication Title

UDCA slows down intestinal cell proliferation by inducing high and sustained ERK phosphorylation.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE21337
Genome-wide analysis of alternative splicing points to novel leukemia-relevant genes in acute myeloid leukemia.
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Alternative mRNA splicing represents an effective mechanism of regulating gene function and is a key element to increase the coding capacity of the human genome. Today, an increasing number of reports illustrates that aberrant splicing events are common and functionally important for cancer development. However, more comprehensive analyses are warranted to get novel insights into the biology underlying malignancies like e.g. acute myeloid leukemia (AML). Here, we performed a genome-wide screening of splicing events in AML using an exon microarray platform. We analyzed complex karyotype and core binding factor (CBF) AML cases (n=64) in order to evaluate the ability to detect alternative splicing events distinguishing distinct leukemia subgroups. Testing different commercial and open source software tools to compare the respective AML subgroups, we could identify a large number of potentially alternatively spliced transcripts with a certain overlap of the different approaches. Selected candidates were further investigated by PCR and sequence analysis: out of 24 candidate genes studied, we could confirm alternative splice forms in 8 genes of potential pathogenic relevance, such as PRMT1 regulating transcription through histone methylation and participating in DNA damage response, and PTPN6, which encodes for a negative regulator of cell cycle control and apoptosis. In summary, this first large Exon microarray based study demonstrates that transcriptome splicing analysis in AML is feasible but challenging, in particular with regard to the currently available software solutions. Nevertheless, our results show that alternatively spliced candidate genes can be detected, and we provide a guide how to approach such analyses.

Publication Title

A robust estimation of exon expression to identify alternative spliced genes applied to human tissues and cancer samples.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE93611
Time-course expression data from HEK293RAF1:ER cells stimulated with 4OHT, U0126, CYHX, ActD, EGF, FGF, or IGF and labelled with 4SU
  • organism-icon Homo sapiens
  • sample-icon 41 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

An immediate-late gene expression module decodes ERK signal duration.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE4698
Molecular characterization of very early relapsed childhood ALL
  • organism-icon Homo sapiens
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Purpose: In childhood acute lymphoblastic leukemia (ALL), approximately 25% of patients suffer from relapse. In recurrent disease, despite intensified therapy, overall cure rates of 40% remain unsatisfactory and survival rates are particularly poor in certain subgroups. The probability of long-term survival after relapse is predicted from well-established prognostic factors, i. e. time and site of relapse, immunophenotype and minimal residual disease. However, the underlying biological determinants of these prognostic factors remain poorly understood.

Publication Title

No associated publication

Sample Metadata Fields

Sex

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accession-icon GSE18088
Correlation of molecular profiles and clinical outcome of stage UICC II colon cancer patients
  • organism-icon Homo sapiens
  • sample-icon 51 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background Published multi-gene classifiers suggested outcome prediction for patients with stage UICC II colon cancer based on different gene expression signatures. However, there is currently no translation of these classifiers for application in routine diagnostic. Therefore, we aimed at validating own and published gene expression signatures employing methods which enable RNA and protein detection in routine diagnostic specimens. Results Immunohistochemistry was applied to 68 stage UICC II colon cancers to determine the protein expression of five selected previously published classifier genes (CDH17, LAT, CA2, EMR3, and TNFRSF11A). Correlation of protein expression data with clinical outcome within a 5-year post-surgery course failed to separate patients with a disease-free follow-up [Group DF] and relapse [Group R]). In addition, RNA from macrodissected tumor samples from 53 of these 68 patients was profiled on Affymetrix GeneChips (HG-U133 Plus 2.0). Prognostic signatures were generated by Nearest Shrunken Centroids with cross-validation. Although gene expression profiling allowed the identification of differentially expressed genes between the groups DF and R, a stable classification and prognosis signature was not discernable in our data. Furthermore, the application of previously published gene signatures consisting of 22 and 19 genes, respectively, to our gene expression data set using global tests and leave-one-out cross-validation was unable to predict clinical outcome (prediction rate 75.5% and 64.2%; n.s.). T-stage was the only independent prognostic factor for relapse in multivariate analysis with established clinical and pathological parameters including microsatellite status. Conclusions Our protein and gene expression analyses currently do not support application of molecular classifiers for prediction of clinical outcome in routine diagnostic as a basis for patient-orientated therapy in stage UICC II colon cancer. Further studies are needed to develop prognosis signatures applicable in patient care.

Publication Title

Molecular profiles and clinical outcome of stage UICC II colon cancer patients.

Sample Metadata Fields

Sex

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accession-icon GSE72919
Time-course expression data from HEK293RAF1:ER cells stimulated with 4OHT, U0126, CYHX, ActD, EGF, FGF, or IGF
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We integrate experimental data and mathematical modelling to unveil how ERK signal duration is relayed to mRNA dynamics.

Publication Title

An immediate-late gene expression module decodes ERK signal duration.

Sample Metadata Fields

Cell line

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accession-icon GSE77080
Neuroblastoma cells depend on HDAC11 for mitotic cell cycle progression and survival
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The number of long-term survivors of high-risk neuroblastoma remains discouraging, with 10-year survival as low as 20%, despite decades of considerable international efforts to improve outcome. Major obstacles remain and include managing resistance to induction therapy, which causes tumor progression and early death in high-risk patients, and managing chemotherapy-resistant relapses, which can occur years after the initial diagnosis. Identifying and validating novel therapeutic targets is essential to improve treatment. Delineating and deciphering specific functions of single histone deacetylases in neuroblastoma may support development of targeted acetylome-modifying therapeutics for patients with molecularly defined high-risk neuroblastoma profiles. We show here that HDAC11 depletion in MYCN-driven neuroblastoma cell lines strongly induces cell death, mostly mediated by apoptotic programs. Genes necessary for mitotic cell cycle progression and cell division were most prominently enriched in at least two of three time points in whole-genome expression data combined from two cell systems, and all nine genes in these functional categories were strongly repressed, including CENPA, KIF14, KIF23 and RACGAP1. Enforced expression of one selected candidate, RACGAP1, partially rescued the induction of apoptosis caused by HDAC11 depletion. High-level expression of all nine genes in primary neuroblastomas signicantly correlated with unfavorable overall and event-free survival in patients, suggesting a role in mediating the more aggressive biological and clinical phenotype of these tumors. Our study identied a group of cell cycle-promoting genes regulated by HDAC11, being both predictors of unfavorable patient outcome and essential for tumor cell viability. The data indicates a signicant role of HDAC11 for mitotic cell cycle progression and survival of MYCN-amplified neuroblastoma cells, and suggests that HDAC11 could be a valuable drug target.

Publication Title

Neuroblastoma cells depend on HDAC11 for mitotic cell cycle progression and survival.

Sample Metadata Fields

Cell line, Time

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accession-icon GSE75523
Circadian mRNA expression in skeletal muscle of young and aged mice
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Aging animals undergo a variety of changes in molecular processes. Among these, the cellular circadian clock has been shown to change as animals age. Moreover, there is evidence that also core circadian clock proteins could influence the ageing behavior of vertebrates.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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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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