Optimising single cell RNAseq for the analysis of paired primary and recurrent Glioblastoma. (31st January 2018) - Rippaus, Nora; Morton, Ruth; Taylor, Claire; Bruns, Alexander-Francisco; Wurdak, Heiko; Chakrabarty, Aruna; Ismail, Azzam; Short, Susan; Stead, Lucy
Abstract: Glioblastoma (GBM) brain tumours are notoriously heterogeneous, constituting numerous subpopulations of cells with distinct genotypes and/or phenotypes. This level of heterogeneity is likely to facilitate Darwinian selection of treatment-resistant subpopulations during standard therapy and, thus, contribute to the inevitable recurrence of GBM tumours. In order to identify and characterise such treatment-resistant cells, with the aim of finding more effective ways of killing them, we are working on optimising the analysis of paired GBM tumours (before and after standard therapy) at single cell resolution using RNAseq.This is challenging for two reasons: 1) it is not possible to know, once a primary GBM is operated on, whether that patient's recurrence will also be surgically removed, 2) archival pairs of tumours tend to be stored in snap frozen or paraffin-embedded form, thus hindering single cell analysis. To overcome this, we have altered the way that primary GBM tissue is processed in Leeds. Storing single cells of primary GBM tissue in lysis buffer enables subsequent continuation of our optimised single cell RNAseq workflow, if the recurrent tumour is operated on. We have also inspected several routes for performing single cell analysis on archival, paired tumours and found that our workflow can be applied to nuclei extracted from frozen material. Preliminary results show the feasibility of obtaining transcriptome profiling from RNA extracted from the isolated nuclei. Therefore, our research has a strong potential to reveal the cellular subpopulation dynamics promoting treatment resistance during GBM recurrence.