Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma

  • Vidhya M Ravi (Geteilte/r Erstautor/in)
  • Paulina Will (Geteilte/r Erstautor/in)
  • Jan Kueckelhaus (Geteilte/r Erstautor/in)
  • Na Sun
  • Kevin Joseph
  • Henrike Salié
  • Lea Vollmer
  • Ugne Kuliesiute
  • Jasmin von Ehr
  • Jasim K Benotmane
  • Nicolas Neidert
  • Marie Follo
  • Florian Scherer
  • Jonathan M Goeldner
  • Simon P Behringer
  • Pamela Franco
  • Mohammed Khiat
  • Junyi Zhang
  • Ulrich G Hofmann
  • Christian Fung
  • Franz L Ricklefs
  • Katrin Lamszus
  • Melanie Boerries
  • Manching Ku
  • Jürgen Beck
  • Roman Sankowski
  • Marius Schwabenland
  • Marco Prinz
  • Ulrich Schüller
  • Saskia Killmer
  • Bertram Bengsch
  • Axel K Walch
  • Daniel Delev
  • Oliver Schnell
  • Dieter Henrik Heiland

Abstract

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.

Bibliografische Daten

OriginalspracheEnglisch
ISSN1535-6108
DOIs
StatusVeröffentlicht - 13.06.2022

Anmerkungen des Dekanats

Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.

PubMed 35700707