Transcriptional Characterization of Glioma Neural Stem Cells Diva ...

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7.5 Glioblastoma Pathway Analysis Results Figure 7.9 displays a simplified and condensed version of the integrated GBM pathway of figure 7.8 that is focused on the pathways most frequently affected in glioblastoma, meant to highlight that we did capture some of the most com- mon alterations in glioblastoma with the GNS/NS comparison. Such changes include up-regulation of EGFR and down-regulation of the tumour suppressor PTEN [326]. Similarly to the complete pathway in figure 7.8, the colour gradient of the condensed pathway in figure 7.9 is taken from the same colour gradients defined in the qRT-PCR heatmap of figure 6.13 and the tumour expression correlation heatmap of figure 7.4. Figure 7.9: Affected p53, RB1 and PTEN/PI3K pathways. Genes are represented by circles coloured according to the expression FC measured between GNS and NS cell lines by Tag-seq. Given the high heterogeneity typical of glioblastoma tumours, we envisioned another application for our GBM integrated pathway. Since every cell line originated from a separate patient (for the exception of G144ED and G144) 192
7.5 Glioblastoma Pathway Analysis Results and the heterogeneity of the tumour has recently been emphasised further by signature microarray studies like those of Verhaak et al [511] and Phillips et al [390], we mapped the Tag-seq measured expression levels for every GNS cell line on our GBM integrated pathway to try and visualise differences poten- tially unique to any GNS cell line and, therefore, to the tumour it originated from (single pathways in Appendix D.2). Figure 7.10 highlights the genes in our GBM pathway that are expressed in each individual GNS cell line, as measured via Tag-seq. The green nodes reflect the genes that have been measured and the intensity of the green colour correlates with the level of expression ob- served, where lighter greens signify smaller expression values and darker greens signify higher expression values (normalised digital tag counts range from 0 to 16,500) (Fig 7.10). For a clearer view of each of these pathways refer to Ap- pendix D.2 Pathway Images. By having the GNS cell line-specific GBM pathways next to each other in figure 7.10, it is possible to observe differences as well as commonalities in gene expression patterns. For example, in each GNS cell line, tumour suppressor PTEN is not expressed (blue shaded boxes) and the antigen presentation- related genes light up with different intensities, highlighting a more highly activated antigen presentation process at the transcriptional level in cell line G144 than in cell lines G166 and G179 (red shaded boxes). Also, since the CDKN2A-CDKN2B tumour suppressor locus is deleted in cell line G179 but retained in cell lines G144 and G166 - possibly in response to an oncogenic signal - the expression of its CDKN2A, CDKN2A:ARF and CDKN2B genes is very low (darker green nodes) in the G179 pathway and much higher (lighter green nodes) in the G144 and G166 pathways (green shaded boxes). Finally, we can see that the orphan nuclear receptor NR0B1, which is known to be up-regulated and drive tumour growth in Ewing’s sarcoma [158], is also highly expressed (lighter green nodes) in our G179 pathway as opposed to the G144 and G166 pathways (yellow shaded boxes). The PARP3 and PARP12 genes, located below NR0B1 in the pathways and included within the yellow shaded box of figure 7.10, are highly expressed across all GNS pathways, consistent with the potential therapeutic role of these genes in GNS cells as inhibitors of their homolog PARP1, for which characteristic they are now being studied in brain tumour clinical trials [270]. In order to consider other sources of expression data that could highlight interesting patterns when compared to our Tag-seq dataset, we overlaid the exon and microarray expression data from the TCGA and HGG datasets (described in Methods section 5.9; all genes overlaid 193
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Transcriptional Characterization of
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This dissertation is my own work an
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Acknowledgements I would like to th
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5.9 External Dataset Expression Cor
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Introduction 1
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1.1 Glial Cells in the Central Nerv
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1.2 Glioblastoma Multiforme Introdu
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1.3 Primary and Secondary Glioblast
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1.4 Pathways Involved in Glioblasto
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1.5 Pathway Crosstalk Introduction
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Chapter 2 Neurogenesis Contents 2.1
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2.1 Radial Glia Introduction VZ adj
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2.2 Neural Stem Cells Introduction
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Chapter 3 Brain Cancer Stem Cells C
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3.1 The Cancer Stem Cell Hypothesis
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3.1 The Cancer Stem Cell Hypothesis
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3.2 Brain Cancer Stem Cells Introdu
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3.3 Glioma Culture Systems Introduc
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Chapter 4 The Non-Coding RNA World
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4.1 MicroRNA regulation Introductio
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4.1 MicroRNA regulation Introductio
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4.2 Target Prediction and Validatio
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Methods 93
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5.1 Tag-sequencing Data Processing
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5.1 Tag-sequencing Data Processing
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5.2 Array Comparative Genomic Hybri
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5.4 Quantitative Real Time-PCR Vali
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5.5 Literature Mining Methods Figur
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5.5 Literature Mining Methods How m
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5.6 Differential Isoform Expression
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5.9 External Dataset Expression Cor
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5.10 Glioblastoma Pathway Construct
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5.11 MicroRNA Target Prediction Ana
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Results 119
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6.2 Tag mapping Results Table 6.1:
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6.2 Tag mapping Results 123 Figure
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6.3 Copy Number Aberrations Results
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6.3 Copy Number Aberrations Results
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6.4 Core Differentially Expressed G
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6.5 Large-scale qRT-PCR Validation
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6.5 Large-scale qRT-PCR Validation
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A.1 Differential Expression Appendi
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A.2 Classified Differential Express
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A.3 Quantitative RT-PCR Appendix Ta
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A.3 Quantitative RT-PCR Appendix We
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A.3 Quantitative RT-PCR Appendix Ta
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A.3 Quantitative RT-PCR Appendix We
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A.4 Tag-seq vs qRT-PCR Correlation
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Appendix "BEX5", "DIAPH2", "GBP3",
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End Select End If End Sub Appendix
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If NameStr.ToLower().Equals("query"
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Appendix C Long ncRNAs We detected
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C. Long ncRNAs Appendix Tag Accessi
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D.1 Pathway Interactions Appendix F
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D.2 Pathway Images Appendix Figure
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D.2 Pathway Images Appendix Figure
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E. Exon Array Data Appendix Average
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F. MicroRNA Array Data Appendix Tab
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F. MicroRNA Array Data Appendix GNS
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F. MicroRNA Array Data Appendix GNS
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Ln Natural logarithm LOH Loss of He
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3.3 Schematisation of cell cycle ph
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8.3 Workflows at the core of the pr
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7.1 Selected Gene Ontology terms an
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