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Single-cell RNA-sequencing (scRNA-seq) is becoming a ubiquitous method in profiling the cellular transcriptomes of both malignant and non-malignant cells from the human brain. Here, we present a protocol to isolate viable tumor cells from human ex vivo glioblastoma cultures for single-cell transcriptomic analysis. We describe steps including surgical tissue collection, sectioning, culturing, primary tumor cells inoculation, growth tracking, fluorescence-based cell sorting, and population-enriched scRNA-seq. This comprehensive methodology empowers in-depth understanding of brain tumor biology at the single-cell level. For complete details on the use and execution of this protocol, please refer to Ravi et al. 1 ., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies. The source of dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapts to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with reactive transcriptional programs, confirming that environmental stress gives rise to selection pressure. A model of glioblastoma stem cells implanted into human and rodent neocortical tissue mimicking various environments confirmed that transcriptional states originate from dynamic adaptation to various environments., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)