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Transcriptional characterization of glioma stem cells using high-throughput tag sequencing

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A recent advance in the study of glioblastoma multiforme (GBM) is the establishment of glioma-derived neural stem (GNS) cells that may represent the glioma cell of origin. These exhibit many similarities to normal neural stem (NS) cells and are propagated as a uniform, adherent monolayer culture to effectively suppress differentiation. GNS cells to give rise to authentic glioma tumors when xenografted in immunocompromised NOD /SCID mice, yet both normal and diseased counterparts are morphologically and immunohistologically indistinguishable. 

To characterize the transcriptome of GNS cells and identify transcriptional differences between GNS and NS that may underlie tumorigenesis, we carried out high-throughput sequencing of mRNA tags (Tag-Seq) on GNS lines from three histologically distinct gliomas and on two normal NS lines. Technical reproducibility of cell line establishment and tag sequencing was high, as demonstrated by comparison of Tag-Seq results for two independently established GNS lines from the same parental tumor. Applying stringent criteria, we identified a set of 80 genes consistently up- or down-regulated among the GNS lines relative to the NS lines by a factor of two of more. This set contains known glioma-related genes, e.g. PTEN , as well as novel candidates, several with known regulatory functions in other contexts. 

In addition to mRNA expression, we detected differential expression of a number of noncoding RNA transcripts between GNS and NS lines, including several from loci neighboring known regulatory genes, e.g. the HOXA cluster. We also mapped chromosomal aberrations in the GNS lines by array comparative genomic hybridization (aCGH). On a global level we see a correlation between chromosomal aberrations and expression levels, but this trend was modest, suggesting that regulatory changes and post-transcriptional factors not related to the cancer genome architecture play a major role in shaping the GNS transcriptome. 

This talk is part of the Seminars on Quantitative Biology @ CRUK Cambridge Institute series.

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