Surveying brain tumor heterogeneity by single-cell RNA-sequencing of multi-sector biopsies - Yu, Kai; Hu, Yuqiong; Wu, Fan; Guo, Qiufang; Qian, Zenghui; Hu, Waner; Chen, Jing; Wang, Kuanyu; Fan, Xiaoying; Wu, Xinglong; Rasko, John EJ; Fan, Xiaolong; et al. (National science review, 2020)
Abstract Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multi-sector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred copy number variations and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single-cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This study provides the first spatial-level analysis of the cellular states that characterize human gliomas. It also presents an initial molecular map of the cross-talks between glioma cells and the surrounding microenvironment with single-cell resolution.