Single-cell RNA sequencing reveals the impact of chromosomal instability on glioblastoma cancer stem cells.
Yanding Zhao, Robert Carter, Sivaraman Natarajan, Frederick S Varn, Duane A Compton, Charles Gawad, Chao Cheng, Kristina M Godek
Author Information
Yanding Zhao: Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Robert Carter: Departments of Oncology and Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Sivaraman Natarajan: Departments of Oncology and Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Frederick S Varn: Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Duane A Compton: Department of Biochemistry and Cell Biology, HB7200, Geisel School of Medicine at Dartmouth, Hanover, NH, 03755, USA.
Charles Gawad: Departments of Oncology and Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Chao Cheng: Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA. chao.cheng@bcm.edu.
Kristina M Godek: Department of Biochemistry and Cell Biology, HB7200, Geisel School of Medicine at Dartmouth, Hanover, NH, 03755, USA. Kristina.M.Godek@dartmouth.edu. ORCID
BACKGROUND: Intra-tumor heterogeneity stems from genetic, epigenetic, functional, and environmental differences among tumor cells. A major source of genetic heterogeneity comes from DNA sequence differences and/or whole chromosome and focal copy number variations (CNVs). Whole chromosome CNVs are caused by chromosomal instability (CIN) that is defined by a persistently high rate of chromosome mis-segregation. Accordingly, CIN causes constantly changing karyotypes that result in extensive cell-to-cell genetic heterogeneity. How the genetic heterogeneity caused by CIN influences gene expression in individual cells remains unknown. METHODS: We performed single-cell RNA sequencing on a chromosomally unstable glioblastoma cancer stem cell (CSC) line and a control normal, diploid neural stem cell (NSC) line to investigate the impact of CNV due to CIN on gene expression. From the gene expression data, we computationally inferred large-scale CNVs in single cells. Also, we performed copy number adjusted differential gene expression analysis between NSCs and glioblastoma CSCs to identify copy number dependent and independent differentially expressed genes. RESULTS: Here, we demonstrate that gene expression across large genomic regions scales proportionally to whole chromosome copy number in chromosomally unstable CSCs. Also, we show 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. CONCLUSIONS: These results demonstrate that CIN is directly responsible for gene expression changes and contributes to both genetic and transcriptional heterogeneity among glioblastoma CSCs. These results also demonstrate that the expression of some genes is buffered against changes in copy number, thus preserving some consistency in gene expression levels from cell-to-cell despite the continuous change in karyotype driven by CIN. Importantly, a gene signature derived from the subset of genes whose expression is buffered against copy number alterations correlates with tumor grade and is prognostic for patient survival that could facilitate patient diagnosis and treatment.
