This SuperSeries is composed of the SubSeries listed below.
The miR-96 and RARγ signaling axis governs androgen signaling and prostate cancer progression.
Sex, Specimen part, Cell line, Treatment
View SamplesExpression levels of retinoic acid receptor gamma (NR1B3/RARG, encodes RARG), are commonly reduced in prostate cancer (PCa). Therefore we sought to establish the cellular and gene regulatory consequences of reduced RARG expression, and determine RARG regulatory mechanisms. RARG shRNA approaches in non-malignant (RWPE-1 and HPr1-AR) and malignant (LNCaP) prostate models revealed that reducing RARG levels, rather than adding exogenous retinoid ligand, had the greatest impact on prostate cell viability and gene expression. ChIP-Seq defined the RARG cistrome which was significantly enriched at active enhancers associated with AR binding sites. Reflecting a significant genomic role for RARG to regulate androgen signaling, RARG knockdown in HPr1-AR cells significantly regulated the magnitude of the AR transcriptome. RARG down-regulation was explained by increased miR-96 in PCa cell and mouse models, and TCGA PCa cohorts. Biochemical approaches confirmed that miR-96 directly regulated RARG expression and function. Capture of the miR-96 targetome by biotin-miR96 identified that RARG and a number of RARG interacting co-factors including TACC1 were all targeted by miR-96, and expression of these genes were prominently altered, positively and negatively, in the TCGA-PRAD cohort. Differential gene expression analyses between tumors in the TCGA-PRAD cohort with lower quartile expression levels of RARG and TACC1 and upper quartile miR-96, compared to the reverse, identified a gene network including several RARG target genes (e.g. SOX15) that significantly associated with worse disease free survival (hazard ratio 2.23, 95% CI 1.58 to 2.88, p=0.015). In summary, miR-96 targets a RARG network to govern AR signaling, PCa progression and disease outcome.
The miR-96 and RARγ signaling axis governs androgen signaling and prostate cancer progression.
Sex, Specimen part, Cell line, Treatment
View SamplesExpression levels of retinoic acid receptor gamma (NR1B3/RARG, encodes RARG), are commonly reduced in prostate cancer (PCa). Therefore we sought to establish the cellular and gene regulatory consequences of reduced RARG expression, and determine RARG regulatory mechanisms. RARG shRNA approaches in non-malignant (RWPE-1 and HPr1-AR) and malignant (LNCaP) prostate models revealed that reducing RARG levels, rather than adding exogenous retinoid ligand, had the greatest impact on prostate cell viability and gene expression. ChIP-Seq defined the RARG cistrome which was significantly enriched at active enhancers associated with AR binding sites. Reflecting a significant genomic role for RARG to regulate androgen signaling, RARG knockdown in HPr1-AR cells significantly regulated the magnitude of the AR transcriptome. RARG down-regulation was explained by increased miR-96 in PCa cell and mouse models, and TCGA PCa cohorts. Biochemical approaches confirmed that miR-96 directly regulated RARG expression and function. Capture of the miR-96 targetome by biotin-miR96 identified that RARG and a number of RARG interacting co-factors including TACC1 were all targeted by miR-96, and expression of these genes were prominently altered, positively and negatively, in the TCGA-PRAD cohort. Differential gene expression analyses between tumors in the TCGA-PRAD cohort with lower quartile expression levels of RARG and TACC1 and upper quartile miR-96, compared to the reverse, identified a gene network including several RARG target genes (e.g. SOX15) that significantly associated with worse disease free survival (hazard ratio 2.23, 95% CI 1.58 to 2.88, p=0.015). In summary, miR-96 targets a RARG network to govern AR signaling, PCa progression and disease outcome.
The miR-96 and RARγ signaling axis governs androgen signaling and prostate cancer progression.
Sex, Specimen part, Cell line, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
No associated publication
Specimen part, Cell line, Treatment, Time
View SamplesTo understand the effect of nicotine on sensitivity of cancer cells to radiation or anti-cancer drugs, NCI-H460 human lung large cell carcinoma cells were treated with 6 Gy ionizing radiation or 1 uM cisplatin after exposure to 5 uM nicotine or cigarette smoke extract. Whole genome expression in total RNA extracted from the treated cells was quantified using the GeneChip Human Gene 1.0 ST microarray platform from Affymetrix (Santa Clara, CA).
No associated publication
Specimen part, Cell line, Treatment, Time
View SamplesTime-course and concentration-effect experiments with multiple time points and drug concentrations provide far more valuable information than experiments with just two design-points (treated vs. control), as commonly performed in most microarray studies. Analysis of the data from such complex experiments, however, remains a challenge. Here we present a semi-automated method for fitting time profiles and concentration-effect patterns, simultaneously, to gene expression data. The submodels for time-course included exponential increase and decrease models with parameters such as initial expression level, maximum effect, and rate-constant (or half-time). The submodel for concentration-effect was a 4-parameter Hill model.
Simultaneous modeling of concentration-effect and time-course patterns in gene expression data from microarrays.
No sample metadata fields
View SamplesDendritic cells (DC) arise from a diverse group of hematopoietic progenitors and have marked phenotypic and functional heterogeneity. We have found previously that activation of protein kinase C beta 2 (PRKCB2) by cytokines or phorbol esters drives normal human CD34(+) hematopoietic progenitors and myeloid leukemic blasts (KG1, K562 cell lines, and primary patient blasts) to differentiate into DC, but the genetic program triggered by PRKCB2 activation that results in DC differentiation is only beginning to be characterized. Of the cPKC isoforms, only PRKCB2 was consistently activated by DC differentiation-inducing stimuli in normal and leukemic progenitors. To examine early changes in gene expression following PRKCB2 activation, we employed the following cell lines: (1) the CD34(+) human acute myeloid leukemia derived cell line KG1, which undergoes DC differentiation following phorbol ester treatment; (2) KG1a, a spontaneously arising differentiation-resistant daughter cell line of KG1 that has lost PRKCB2 expression; (3) clones established from KG1a that stably express exogenous PRKCB2-GFP fusion proteins and are once again able to undergo DC differentiation (KG1a-PRKCB2-GFP Clone E9 and Clone E11). We examined changes in gene expression in these cells following treatment with the phorbol ester PMA (phorbol 12-myristate 13-acetate) for 2 hours. Since KG1 and KG1a differ in PRKCB2 expression but have similar expression of the other protein kinase C isoforms, this protocol will allow for the identification of genes regulated by PRKCB2 activation.
Tumor-induced STAT3 signaling in myeloid cells impairs dendritic cell generation by decreasing PKCβII abundance.
Sex, Age, Specimen part, Cell line, Treatment
View SamplesCBL0137 id non-genotoxic DNA binding compounds which directly destabilizes nucleosomes in cells. Effect of different doses of CBL0137 on the abundance of mRNA was studied in two cell types, multiple myeloma MM1.S and cervical carcinoma HeLa cell.
No associated publication
Cell line
View SamplesCompares shFOXO4 vs. Control in LNCaP grown in culture, or in nude mice as primary orthotopic tumors or lymph node metastases
A genome-wide RNAi screen identifies FOXO4 as a metastasis-suppressor through counteracting PI3K/AKT signal pathway in prostate cancer.
Specimen part
View SamplesFACT inhibition, via small molecule or shRNA, lead to reduced growth and viability of all BrCa cells tested. Phenotypic changes were more severe in high FACT cells (death or growth arrest) than in low FACT cells (decreased proliferation). Though inhibition had no effect on the rate of general transcription, expression of individual genes was changed in a cell-specific manner. Initially distinct transcriptional profiles of BrCa cells became almost identical via equalizing FACT expression. We found that in high-FACT cells FACT supports expression of genes involved in the regulation of cell cycle, DNA replication, maintenance of undifferentiated cell state and regulated by the activity of proto-oncogenes, such as Hras, cMyc, E2F family ets. In low-FACT cells presence of FACT reduces expression of genes coding enzymes of steroid metabolism characteristic for the differentiated mammary epithelia. Inhibition of FACT leads to the shift from more aggressive transcriptional program to more benign, accompanied with similar type of phenotypical changes. Thus we propose FACT as a marker to predict aggressiveness of BrCa and as a target to either kill aggressive BrCa cells or to convert them to a less aggressive phenotype.
No associated publication
Cell line
View Samples