Spatiotemporal modeling reveals high-resolution invasion states in glioblastoma.

ABSTRACT:

Background

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.

Results

Towards this goal, we apply 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 the analysis of diffuse invasion. Our analytic approach, based on unsupervised deconvolution, performs reference-free discovery of cell types and cell activitie

SUBMITTER: Manoharan VT 

PROVIDER: S-EPMC11465563 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature