生物
胶质母细胞瘤
计算生物学
寄主(生物学)
癌症研究
计算机科学
遗传学
作者
Vidhya M. Ravi,Paulina Will,Jan Kueckelhaus,Na Sun,Kevin Joseph,Henrike Salié,Lea Vollmer,Ugnė Kuliešiūtė,Jasmin von Ehr,Jasim Kada Benotmane,Nicolas Neidert,Marie Follo,Florian Scherer,Jonathan M. Goeldner,Simon P. Behringer,Pamela Franco,Mohammed Khiat,Junyi Zhang,Ulrich Hofmann,Christian Fung
出处
期刊:Cancer Cell
[Cell Press]
日期:2022-06-01
卷期号:40 (6): 639-655.e13
被引量:328
标识
DOI:10.1016/j.ccell.2022.05.009
摘要
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.
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