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 ofgliomas from 13 Chinese patients.After classifying individual cells,we generated a spatial and temporal landscape ofglioma that revealed the pattes 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.