Surveying brain tumor heterogeneity by single-cell RNA-sequencing of multi-sector biopsies

• Published in: National science review Vol. 7; no. 8; pp. 1306 - 1318
• Main Authors: 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, Iavarone, Antonio, Jiang, Tao, Tang, Fuchou, Su, Xiao-Dong
• Format: Journal Article
• Language: English
• Published: Oxford University Press 01.08.2020
• Subjects: Neuroscience; glioma; single-cell RNA-seq; multi-sector biopsy; heterogeneity
• ISSN: 2095-5138; 2053-714X; 2053-714X
• DOI: 10.1093/nsr/nwaa099

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.