Single-cell RNA sequencing reveals the impact of chromosomal instability on glioblastoma cancer stem cells

Intra-tumor genetic heterogeneity comes from whole chromosome and/or focal copy number variations (CNVs). We investigated the impact of whole chromosome CNVs on gene expression by performing single-cell RNA sequencing on a chromosomally unstable glioblastoma cancer stem cell (CSC) line and a control normal, diploid neural stem cell (NSC) line. From the gene expression data, we computationally inferred large-scale CNVs in single cells. We find that gene expression across large genomic regions scales proportionally to whole chromosome copy number in chromosomally unstable CSCs. Also, we find that the differential expression of most genes between normal NSCs and glioblastoma CSCs is largely accounted for by copy number alterations. However, we identify 269 genes whose differential expression in glioblastoma CSCs relative to normal NSCs is independent of copy number. Moreover, a gene signature derived from the subset of genes that are differential expressed independent of copy number in glioblastoma CSCs correlates with tumor grade and is prognostic for patient survival. In conclusion, this study demonstrates the utility of single-cell RNA sequencing when analyzing chromosomally unstable cells. Overall design: Single-cell RNA sequencing of normal neural stem cells and glioblastoma cancer stem cells using C1 Single Cell Auto Prep system from Fluidigm and Illumina Nextera XT library sequencing as C1- protocol.