Data from: Spatiotemporal modeling reveals high-resolution invasion states in glioblastoma

Diffuse invasion of glioblastoma cells through normal brain tissue is a
key contributor to tumor aggressiveness, resistance to conventional
therapies, and dismal prognosis in patients. A deeper understanding of how
components of the tumor microenvironment (TME) contribute to overall tumor
organization and to programs of invasion may reveal opportunities for
improved therapeutic strategies. Towards this goal, we applied a novel
computational workflow to a spatiotemporally profiled GBM xenograft
cohort, leveraging the ability to distinguish human tumor from mouse TME
to overcome previous limitations in analysis of diffuse invasion. Our
analytic approach, based on unsupervised deconvolution, performs
reference-free discovery of cell types and cell activities within the
complete GBM ecosystem. We present a comprehensive catalogue of 15 tumor
cell programs set within the spatiotemporal context of 90 mouse brain and
TME cell types, cell activities, and anatomic structures. Distinct tumor
programs related to invasion were aligned with routes of perivascular,
white matter, and parenchymal invasion. Furthermore, sub-modules of genes
serving as program hubs were highly prognostic in GBM patients. The
compendium of programs presented here provides a basis for rational
targeting of tumor and/or TME components. We anticipate that our approach
will facilitate an ecosystem-level understanding of immediate and
long-term consequences of such perturbations, including identification of
compensatory programs that will inform improved combinatorial therapies.