High-resolution RNA-seq profiling of glioblastoma residual invasive cells isolated by a novel 5-ALA fluorescence based method

INTRODUCTION: Malignant brain cancer Glioblastoma (GBM) kills 3500 people per year in the UK with an average survival of 6 months. The intra-tumour heterogeneity of GBM has meant tailored therapies based on the genetic... [ view full abstract ]

INTRODUCTION: Malignant brain cancer Glioblastoma (GBM) kills 3500 people per year in the UK with an average survival of 6 months. The intra-tumour heterogeneity of GBM has meant tailored therapies based on the genetic mutations within the cancer cells have so far failed to replicate in vitro promise in clinical trials. Previous research has focused on the core of the tumour; however this is removed by surgery and doesn’t reflect the residual cancer cells left in the patient’s brain. The aim of this study is to generate new potential targets from looking at the expression of those residual cancer cells left behind after surgery that ultimately lead to tumour recurrence. METHOD: 5-aminolevulinic acid (5-ALA) is a clinically used drug that makes cancer cells glow (fluoresce) pink, allowing more complete removal of brain tumours. 10 Tumour samples were dissociated and fluorescent activated cell sorting (FACS) was used to separate the residual fluorescent cancer cells (1%) from normal brain at the tumour’s edge. Samples from 3 distinct tumour regions, core, rim and invasive margin without FACS sorting from the same patients were also included for comparison to the FACS samples. Gene expression was analysed by RNA-seq and validated by qPCR. RESULTS: High-resolution RNA-seq profiles were generated for distinct tumour regions and the fluorescently isolated invasive cell population, allowing potential targetable abnormalities to be identified and validated. CONCLUSION: This study shows that pure tumour cells can be separated from normal cells using fluorescence generated from tumour metabolism of 5-ALA. Further optimisation of FACS is required to increase RNA yield from FACS sorted samples. Our approach gives hope that we can interrogate the true residual disease, and for the first time gain insight into the source of tumour recurrence.