Single-cell landscapes of primary glioblastomas and matched explants and cell lines show variable retention of inter- and intratumor heterogeneity

Cancer Cell. 2022 Apr 11;40(4):379-392.e9. doi: 10.1016/j.ccell.2022.02.016. | PubMed

Véronique G LeBlanc¹, Diane L Trinh¹, Shaghayegh Aslanpour², Martha Hughes², Dorothea Livingstone², Dan Jin¹, Bo Young Ahn³, Michael D Blough³, J Gregory Cairncross², Jennifer A Chan⁴, John J P Kelly², Marco A Marra⁵

1. Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, V5Z 4S6 BC, Canada.
2. Department of Clinical Neurosciences, University of Calgary, Calgary, T2N 2T9 AB, Canada; Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, T2N 4Z6 AB, Canada.
3. Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, T2N 4Z6 AB, Canada.
4. Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, T2N 4Z6 AB, Canada; Department of Pathology & Laboratory Medicine, University of Calgary, Calgary, T2L 2K8 AB, Canada.
5. Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, V5Z 4S6 BC, Canada; Department of Medical Genetics, University of British Columbia, Vancouver, V6H 3N1 BC, Canada. Electronic address: mmarra@bcgsc.ca.

Abstract

Glioblastomas (GBMs) are aggressive brain tumors characterized by extensive inter- and intratumor heterogeneity. Patient-derived models, such as organoids and explants, have recently emerged as useful models to study such heterogeneity, although the extent to which they can recapitulate GBM genomic features remains unclear. Here, we analyze bulk exome and single-cell genome and transcriptome profiles of 12 IDH wild-type GBMs, including two recurrent tumors, and of patient-derived explants (PDEs) and gliomasphere (GS) lines derived from these tumors. We find that PDEs are genetically similar to, and variably retain gene expression characteristics of, their parent tumors. Notably, PDEs appear to exhibit similar levels of transcriptional heterogeneity compared with their parent tumors, whereas GS lines tend to be enriched for cells in a more uniform transcriptional state. The approaches and datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived models, especially in the context of studying cellular heterogeneity.

Presented By Véronique LeBlanc | ORCID iD