E-GEOD-58966
Ontology highlight
ABSTRACT:
PROVIDER: E-GEOD-58966 | ExpressionAtlas | 2019-05-14
REPOSITORIES: ExpressionAtlas
Dataset's files
primary
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| E-GEOD-58966-analysis-methods.tsv | Tabular | |||
| E-GEOD-58966-analytics.tsv | Tabular | |||
| E-GEOD-58966-analytics.tsv.undecorated | Tabular | |||
| E-GEOD-58966-analytics.tsv.undecorated.unrounded | Tabular | |||
| E-GEOD-58966-analytics.tsv.unrounded | Tabular |
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Project description:EZH2 is frequently over-expressed in aggressive and metastatic solid tumors, including castration resistant prostate cancer (CRPC). We sought to determine EZH2-dependent gene expression programmes in prostate cancer progression, and found an intriguing functional switch of EZH2 from a repressor to an activator during CRPC development. We used microarrays to detail the global profiling of gene expression that are differentially regulated upon EZH2 depletion in two different prostate cancer cell lines. The androgen-dependent prostate cancer cell line LNCaP and the LNCaP-derived androgen-independent cell line LNCaP-abl (abl) were used for this study, as their transcription profiles strongly resemble that of clinical androgen-dependent and castration resistant prostate tumors, respectively. EZH2 was silenced by specific siRNAs in both cell lines, and total RNA was extracted and hybridized on Affymetrix microarrays.
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Project description:High-throughput profiling of human castration-resistant prostate cancer cell lines
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Project description:Background: Despite the significant global loss of DNA hydroxymethylation marks in prostate cancer tissues, the locus-specific role of hydroxymethylation in prostate tumorigenesis is unknown. We characterized hydroxymethylation and methylation marks by performing whole-genome next generation sequencing in representative normal and prostate cancer-derived cell lines in order to determine functional pathways and key genes regulated by these epigenomic modifications in cancer. Results: Our cell line model shows disruption of hydroxymethylation distribution in cancer, with global loss and highly specific gain in promoter and CpG island regions. Significantly, we observed locus-specific retention of hydroxymethylation marks in specific intronic and intergenic regions which may play a novel role in the regulation of gene expression in critical functional pathways, such as BARD1 signaling and steroid hormone receptor signaling in cancer. We confirm a modest correlation of hydroxymethylation with expression in intragenic regions in prostate cancer, while identifying an original role for intergenic hydroxymethylation in differentially expressed regulatory pathways in cancer. We also demonstrate a successful strategy for the identification and validation of key candidate genes from differentially regulated biological pathways in prostate cancer. Conclusion: Our results indicate a distinct function for aberrant hydroxymethylation within each genomic feature in cancer, suggesting a specific and complex role for the deregulation of hydroxymethylation in tumorigenesis, similar to methylation. Subsequently, our characterization of key cellular pathways exhibiting dynamic enrichment patterns for methylation and hydroxymethylation marks may allow us to identify differentially epigenetically modified target genes implicated in prostate cancer tumorigenesis. Methylation profiles of representative normal prostate cell line RWPE-1 and prostate adenocarcinoma cell line 22Rv1 were generated by MBD capture followed by high-throughput sequencing on the HiSeq 2500 (Illumina), in triplicate. Hydroxymethylation profiles of RWPE-1 and 22Rv1 were generated by hMeSeal followed by high-throughput sequencing on the HiSeq 2500 (one replicate each). Additional hydroxymethylation profiling for RWPE-1 was generated by hMeDIP followed by high-throughput sequencing on the HiSeq 2000 (Illumina).
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Project description:Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression.Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR.Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis.Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases.
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Project description:In the developed world, prostate cancer is the most common cancer diagnosis in men. Although prostate cancer initially presents as a non life-threatening disease, 90% of patients will develop castration resistant prostate cancer (CRPC), which preludes distant metastasis and is largely accountable for prostate cancer associated deaths. This is because as yet, there are no viable molecular therapeutic targets for effective treatment of CRPC. It is now widely accepted that cancer cells can alter their metabolic profile during the course of tumourgenesis and metastasis such that they are able to survive in oxygen and nutrient-poor environments. This work was aimed towards gaining greater mechanistic understanding of how such 'stresses' in the tumour microenvironment impact on both androgen sensitive (LNCaP) and androgen independent (LNCaP-abl and LNCaP-abl-Hof) prostate cancer cell lines. Here we have applied technically robust and reproducible label-free liquid chromatography mass spectrometry analysis for comprehensive proteomic profiling of prostate cancer cell lines under nutrient deficient (low glucose) conditions. This led to the identification of approximately 4,000 proteins - one of the largest protein datasets for prostate cancer cell lines established to date. The biological and clinical significance of proteins showing a significant change in expression as result of low glucose conditions was established. Novel, intuitive workflows were subsequently implemented to ensure the verification of selected proteins of interest in a robust, reproducible and high throughput manner. Overall, these data suggest that this strategy supports identification of protein biomarkers of prostate cancer progression and potential therapeutic targets for CRPC.
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Project description:Approximately one in six men are diagnosed with Prostate Cancer every year in the Western world. Although it can be well managed and non-life threatening in the early stages, over time many patients cease to respond to treatment and develop castrate resistant prostate cancer (CRPC). CRPC represents a clinically challenging and lethal form of prostate cancer. Progression of CRPC is, in part, driven by the ability of cancer cells to alter their metabolic profile during the course of tumourgenesis and metastasis so that they can survive in oxygen and nutrient-poor environments and even withstand treatment. This work was carried out as a continuation of a study aimed towards gaining greater mechanistic understanding of how conditions within the tumour microenvironment impact on both androgen sensitive (LNCaP) and androgen independent (LNCaP-abl and LNCaP-abl-Hof) prostate cancer cell lines. Here we have applied technically robust and reproducible label-free liquid chromatography mass spectrometry analysis for comprehensive proteomic profiling of prostate cancer cell lines under hypoxic conditions. This led to the identification of over 4,000 proteins - one of the largest protein datasets for prostate cancer cell lines established to date. The biological and clinical significance of proteins showing a significant change in expression as result of hypoxic conditions was established. Novel, intuitive workflows were subsequently implemented to enable robust, reproducible and high throughput verification of selected proteins of interest. Overall, these data suggest that this strategy supports identification of protein biomarkers of prostate cancer progression and potential therapeutic targets for CRPC.
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Project description:BACKGROUND: High throughput sequencing-by-synthesis is an emerging technology that allows the rapid production of millions of bases of data. Although the sequence reads are short, they can readily be used for re-sequencing. By re-sequencing the mRNA products of a cell, one may rapidly discover polymorphisms and splice variants particular to that cell. RESULTS: We present the utility of massively parallel sequencing by synthesis for profiling the transcriptome of a human prostate cancer cell-line, LNCaP, that has been treated with the synthetic androgen, R1881. Through the generation of approximately 20 megabases (MB) of EST data, we detect transcription from over 10,000 gene loci, 25 previously undescribed alternative splicing events involving known exons, and over 1,500 high quality single nucleotide discrepancies with the reference human sequence. Further, we map nearly 10,000 ESTs to positions on the genome where no transcription is currently predicted to occur. We also characterize various obstacles with using sequencing by synthesis for transcriptome analysis and propose solutions to these problems. CONCLUSION: The use of high-throughput sequencing-by-synthesis methods for transcript profiling allows the specific and sensitive detection of many of a cell's transcripts, and also allows the discovery of high quality base discrepancies, and alternative splice variants. Thus, this technology may provide an effective means of understanding various disease states, discovering novel targets for disease treatment, and discovery of novel transcripts.
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Project description:High-throughput chromatin accessibility profiling of human castration-resistant prostate cancer cell lines
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