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accession-icon GSE36004
Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma.
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line

View Samples
accession-icon GSE36001
Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma [gene expression]
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

Osteosarcomas are the most common primary malignant tumours of bone, and almost all conventional osteosarcomas are high-grade tumours showing complex genomic aberrations. We have integrated genome-wide genetic and epigenetic profiles from the EuroBoNeT panel of 19 human osteosarcoma cell lines based on microarray technologies. The cell lines showed complex patterns of DNA copy number changes, where copy number gains were significantly associated with gene-rich regions of the genome and losses with gene-poor areas. Integration of the datasets showed that the mRNA levels were regulated by either alterations in DNA copy number or DNA methylation. Using a recurrence threshold of 6/19 (> 30 %) cell lines, 348 genes were identified as having alterations of two data types (gain or hypo-methylation/over-expression, loss or hyper-methylation/under-expression). These genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2-deoxycytidine treatment for all four genes tested. Globally, there was as expected a significant positive association between gain and over-expression, loss and under-expression as well as hyper-methylation and under-expression, but gain was also associated with hyper-methylation and under-expression, suggesting that hyper-methylation may oppose the effects of increased copy number for some genes. Integrative analysis of genome-wide genetic and epigenetic alterations identified mechanistic dependencies and relationships between DNA copy number and DNA methylation in terms of regulating mRNA expression levels in osteosarcomas, contributing to better understanding of osteosarcoma biology.

Publication Title

Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma.

Sample Metadata Fields

Sex, Specimen part, Cell line

View Samples
accession-icon GSE39135
The human AlkB homologue 4 interacts with proteins associated with transcription
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE39127
The human AlkB homologue 4 interacts with proteins associated with transcription (expression)
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

The Fe(II)- and 2-oxoglutarate (2OG)-dependent dioxygenase AlkB from E. coli is a demethylase which repairs alkyl lesions in DNA, as well as RNA, through a direct reversal mechanism. Humans possess nine AlkB homologues (ALKBH1-8 and FTO). ALKBH2 and ALKBH3 display demethylase activities corresponding to that of AlkB, and both ALKBH8 and FTO are RNA modification enzymes. The biochemical functions of the rest of the homologues are still unknown. To increase our knowledge on the functions of ALKBH4 and ALKBH7 we have here performed yeast two-hybrid screens to identify interaction partners of the two proteins. While no high-confidence hits were detected in the case of ALKBH7, several proteins associated with chromatin and/or involved in transcription were found to interact with ALKBH4. For all interaction partners, the regions mediating binding to ALKBH4 comprised domains previously reported to be involved in interaction with DNA or chromatin. Furthermore, some of these partners showed nuclear co-localization with ALKBH4. However, the global gene expression pattern was only marginally altered upon ALKBH4 over-expression, and larger effects were observed in the case of ALKBH7. Although the molecular function of both proteins remains to be revealed, our findings suggest a role for ALKBH4 in regulation of gene expression or chromatin state and support the previous association of ALKBH7 with spermatogenesis.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon E-TABM-707
Transcription profiling of human PEGylated interferon-a2b treatment of one sensitive and two resistant osteosarcoma xenografts established in nude mice
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina_Human-6_V2.0

Description

Gene expression changes as a response to PEGylated interferon-a2b treatment of one sensitive and two resistant osteosarcoma xenografts established in nude mice

Publication Title

Characterization of Treatment Response to Recombinant Interferon-alpha2b in Osteosarcoma Xenografts

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject, Compound

View Samples
accession-icon GSE111260
A multi-component view of the glioma transcriptome identifies unique immune infiltration patterns in primary glioblastomas and patients with inferior prognosis.
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Patients diagnosed with glioblastomas continue to have a dismal prognosis, highlighting the need for a better characterization of these tumors in order to identify more efficient therapies. In this study, we generated genome-wide expression data from normal brain and glioma samples, representing major glioma subtypes, using exon-level microarrays (n=70). A multi-component approach was used to characterize molecular pathways and tumor infiltrate, with particular focus on the poor prognosis primary glioblastomas (pGBM). Two independent, publically available datasets were used for validation of survival data. Grade II glioma and secondary GBM were enriched in cytotoxic lymphocytes, while pGBM exhibited a heterogeneous cell-related immune infiltrate with high infiltration of monocytic cells. Infiltration by cells of monocytic origin predicted poorer prognosis, regardless of the tumor subtype. High TSPYL2 expression was found to be associated with a poor prognosis in pGBM and to correlate with genes involved in tumor invasion. The multi-component transcriptome phenotypes of pGBM introduced in this study add insights into the main pathways associated with aggressiveness, and identified infiltration by cells of monocytic origin as a universal prognostic marker for all glioma subtypes.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Disease

View Samples
accession-icon GSE58887
Drug screening and genomic analyses of HER2 positive breast cancer cell lines reveal predictors for treatment response
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge IconAgilent-014693 Human Genome CGH Microarray 244A (Probe name version), 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

Sex, Cell line

View Samples
accession-icon GSE58700
Drug screening and genomic analyses of HER2 positive breast cancer cell lines reveal predictors for treatment response [Expression profiling]
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Thirteen HER2 positive breast cancer cell lines were screened with 22 commercially available compounds, mainly targeting proteins in the ErbB2 signaling pathway, and the molecular mechanisms related to treatment response were sought. To search for response predictors, genomic and transcriptomic profiling, PIK3CA mutations and PTEN status were associated to the drug responses and several genes involved in the response of the compounds were identified.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Cell line

View Samples
accession-icon GSE6919
Expression Data from Normal and Prostate Tumor Tissues
  • organism-icon Homo sapiens
  • sample-icon 503 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95C Array (hgu95c)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Sample Metadata Fields

Age, Specimen part, Race

View Samples
accession-icon GSE6606
Expression data from Primary Prostate Tumor
  • organism-icon Homo sapiens
  • sample-icon 196 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95B Array (hgu95b)

Description

Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.

Publication Title

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Sample Metadata Fields

Specimen part

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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