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 prog..., The dataset includes 10x Genomics Visium spatial transcriptomic profiles of 23 GBM xenograft samples established from six brain tumor initiating cell lines (BTIC) derived from four patients (BT143, BT238, BT134 and BT161). BTIC lines from two patients (BT143 and BT238) were established from samples obtained from the tumor core (x), the contrast-enhancing highly vascularized tumor margin (y), and the highly diffuse leading edge of the tumor (z) through pre-operative MRI-guided resections. Upon implantation, early, mid, and late timepoints of growth are sampled based on known time to endpoint. Biological replicates of these mouse brain sections are obtained 30-40um apart. Raw spatial transcriptomic data were processed using the SpaceRanger software (v1.3.1) to generate FASTQ files. Sequences were aligned to the hybrid genome reference sequence GRCh38-mm10-2020-A and barcode/UMI counting was performed using Space Ranger pipeline’s default settings and all samples were aggregated using the ..., , # **Spatiotemporal modeling reveals high-resolution invasion states in glioblastoma**

The dataset includes 10x Genomics Visium spatial transcriptomic profiles of 23 GBM xenograft samples established from six brain tumor initiating cell lines (BTIC) derived from four patients (BT143, BT238, BT134 and BT161). BTIC lines from two patients (BT143 and BT238) were established from samples obtained from the tumor core (x), the contrast-enhancing highly vascularized tumor margin (y), and the highly diffuse leading edge of the tumor (z) through pre-operative MRI-guided resections. Upon implantation, early, mid, and late timepoints of growth are sampled based on known time to endpoint. Biological replicates of these mouse brain sections are obtained 30-40um apart. Raw spatial transcriptomic data were processed using the SpaceRanger software (v1.3.1) to generate FASTQ files. Sequences were aligned to the hybrid genome reference sequence GRCh38-mm10-2020-A and barcode/UMI counting was performed ...