Poster Presentation 25th Lorne Cancer Conference 2013

The Transcriptome of Glioblastoma Stem Cells. (#126)

Daniel V Brown 1 , Giovanna D'Abaco 2 , Nicole Kountouri 2 , Andrew Lonie 3 , Andrew Morokoff 2 , Theo Mantamadiotis 1
  1. Pathology, University of Melbourne, Melbourne, VIC, Australia
  2. Surgery, Royal Melbourne Hospital, Melbourne, VIC, Australia
  3. Victorian Life Sciences Computation Initiative, Melbourne, VIC, Australia

Glioblastoma multiforme (GBM) is an aggressive cancer of the brain with a median survival of 14 months. GBM has been shown to be initiated and maintained by a subpopulation of cells termed glioma initiating cells (GICs) (1). GICs have enhanced resistance to chemotherapy and radiotherapy compared to the tumour bulk (2). Characterisation of GICs at the molecular level will enable development of better biomarkers and new opportunities for therapeutic targeting of this subpopulation to improve the current prognosis of this cancer.

The transcriptome of a panel of human GIC samples will be measured by RNA sequencing (RNA-seq) and quantitative reverse transcription PCR (qRT-PCR) to compare groups that differ in survival. The data will be integrated with clinical information and classification analysis will be performed to discover transcripts associated with survival and response to therapy. The resulting gene signature will be cross-validated using public GBM data from the Cancer Genome Atlas database.

GICs have been successfully isolated and purified from clinical GBM samples. qRT-PCR has validated these cells as being enriched for stem cell markers.  A pilot RNA-seq experiment measuring the transcriptome of a stemness enriched and stemness depleted GIC clone was performed. The data was processed and analysed for differential transcript expression using a variety of software packages. 200 genes were determined to be differentially expressed along with 159 isoforms. Gene set enrichment analysis revealed cell migration, vascular remodeling and proliferation categories to be over-represented in the differentially expressed gene list. Protein network analysis showed growth factor signaling and developmental pathways to be signaling hubs in stem cell enriched GICs.

The addition of biological replicates and greater read depth will enable more in-depth analyses to be performed.