Unravelling glioblastoma heterogeneity by single-cell RNA sequencing

Abstract

Glioblastoma (GBM) is an extremely aggressive brain cancer that accounts for almost 50% of all primary malignant brain tumors. Despite extensive efforts, challenges such as intratumoral and intertumoral heterogeneity continue to impact the prognosis and survival rate. To address this, single-cell RNA-sequencing (scRNA-seq) of 2 tumor data sets was used to precisely determine the gene expression of GBM cell populations. Results revealed the striking molecular heterogeneity present in individual tumor specimens and the complexity of tumor-infiltrating cells, confirming the diversity of genes present in GBM tumors. There have been a number of previous studies that each analyzed GBM tumor heterogeneity for individual application purposes, but there has not yet been an analysis of multiple samples using the same set of markers. Therefore, my results across multiple tumor data sets provide helpful information for GBM tumor heterogeneity, which can be applied to patient classification, and highlight potential therapeutical gene targets to advance current therapies and treatments.