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accession-icon GSE71224
Inhibition of 13-cis retinoic acid-induced gene expression of reactive-resistance genes by thalidomide in glioblastoma tumours in vivo
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The cell differentiation potential of 13-cis retinoic acid (RA) has not succeeded in the clinical treatment of glioblastoma (GBM) so far. However, RA may also induce the expression of disistance genes such as HOXB7 which can be suppressed by Thalidomide (THAL). Therefore, we tested if combined treatment with RA+THAL may inhibit growth of glioblastoma in vivo. Treatment with RA+THAL but not RA or THAL alone significantly inhibited tumour growth. The synergistic effect of RA and THAL was corroborated by the effect on proliferation of glioblastoma cell lines in vitro. HOXB7 was not upregulated but microarray analysis validated by real-time PCR identified four potential resistance genes (IL-8, HILDPA, IGFBPA, and ANGPTL4) whose upregulation by RA was suppressed by THAL. Furthermore, genes coding for small nucleolar RNAs (snoRNA) were identified as a target for RA for the first time, and their upregulation was maintained after combined treatment. Pathway analysis showed upregulation of the Ribosome pathway and downregulation of pathways associated with proliferation and inflammation. Combined treatment with RA + THAL delayed growth of GBM xenografts and suppressed putative resistance genes associated with hypoxia and angiogenesis. This encourages further pre-clinical and clinical studies of this drug combination in GBM.

Publication Title

Inhibition of 13-cis retinoic acid-induced gene expression of reactive-resistance genes by thalidomide in glioblastoma tumours in vivo.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE46578
Ectopic expression of AP4 in human colorectal cancer cells DLD-1 for different times
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

To characterize the transcriptome of the transcription factor AP4 DLD-1 cells were infected with AP4 coding viruses for different periods of time. Adenovirus amplification and purification was performed as previously described (He et al., 1998). The minimal amount of virus needed to reach more than 90% infection efficiency was determined by monitoring GFP signals with fluorescence microscopy. DLD-1 cells were infected in serum-free medium with adenovirus for 3 hours. After removal an equal amount of medium containing 20% FBS was added.

Publication Title

AP4 is a mediator of epithelial-mesenchymal transition and metastasis in colorectal cancer.

Sample Metadata Fields

Cell line, Time

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accession-icon SRP185844
Next Generation Sequencing of isolated EGFR+ and HLA-G+ first trimester human trophoblasts
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

The aim of this study was to identify differentially expressed signatures of non-invasive (EGFR+) and invasive (HLA-G+) human trophoblast subtypes. These populations were isolated from single first trimester placentas from 10-12 weeks of gestation. Overall design: We performed RNAseq to analyze the global expression profile of two different trophoblastic subtypes.

Publication Title

Metabolism of cholesterol and progesterone is differentially regulated in primary trophoblastic subtypes and might be disturbed in recurrent miscarriages.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP022054
High-throughput sequencing of matched colorectal normal, tumor and metastasis tissues and proof-of principal bioinformatics modeling of therapeutic consequences of miRNA applications
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are so far hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We identified miRNA-1 as top candidate differentially expressed in tumor and metastasis. Furthermore, miRNA-1 was de-regulated in 16 additional tumor entities underscoring its central role in tumor pathogenesis. Functional analyses showed an additive effect of miRNA-1 with camptothecin treatment. We used a systems-biology simulation of cellular cancer models implemented in PyBios to investigate miRNA-1 function and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options. Overall design: Examination of miRNA expression values by Illumina sequencing of matched benign, tumor and metastasis tissues of 8 colorectal cancer patients. For 4 of these patients all tissues have been resequenced to obtain mRNA expression values.

Publication Title

High-throughput miRNA and mRNA sequencing of paired colorectal normal, tumor and metastasis tissues and bioinformatic modeling of miRNA-1 therapeutic applications.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Subject

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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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