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

TLDR

Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. The study combined single‑cell RNA‑seq with multi‑sector biopsies of 13 Chinese glioma patients, generating spatial and temporal landscapes of invasion patterns and using inferred copy‑number variations and pseudotime trajectories to identify key branches driving tumor progression. The analysis revealed that multi‑region biopsy data allowed unprecedented spatial deconvolution of core versus periphery transcriptomic features, characterized chemokine/chemokine‑receptor interactions among tumor and non‑tumor cells, and provided the first spatial‑level map of cellular states and cross‑talks in human gliomas.

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.