Vamsi Mangena

Abstract Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical owing to the complexity of in vivo models. Here we introduce an in vivo barcoding strategy that is capable of determining the metastatic potential of human cancer cell lines in mouse xenografts at scale. We validated the robustness, scalability and reproducibility of the method and applied it to 500 cell lines 1,2 spanning 21 types of solid tumour. We created a first-generation metastasis map (MetMap) that reveals organ-specific patterns of metastasis, enabling these patterns to be associated with clinical and genomic features. We demonstrate the utility of MetMap by investigating the molecular basis of breast cancers capable of metastasizing to the brain—a principal cause of death in patients with this type of cancer. Breast cancers capable of metastasizing to the brain showed evidence of altered lipid metabolism. Perturbation of lipid metabolism in these cells curbed brain metastasis development, suggesting a therapeutic strategy to combat the disease and demonstrating the utility of MetMap as a resource to support metastasis research.

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

Glioblastoma (GBM) is characterized by heterogeneous malignant cells that are functionally integrated within the neuroglial microenvironment. In this study, we model this ecosystem by growing GBM into long-term cultured human cortical organoids that contain the major neuroglial cell types found in the cerebral cortex. Single-cell RNA sequencing analysis suggests that, compared with matched gliomasphere models, GBM cortical organoids more faithfully recapitulate the diversity and expression programs of malignant cell states found in patient tumors. Additionally, we observe widespread transfer of GBM transcripts and GFP to nonmalignant cells in the organoids. Mechanistically, this transfer involves extracellular vesicles and is biased toward defined GBM cell states and astroglia cell types. These results extend previous GBM organoid modeling efforts and suggest widespread intercellular transfer in the GBM neuroglial microenvironment. Significance: Models that recapitulate intercellular communications in GBM are limited. In this study, we leverage GBM cortical organoids to characterize widespread mRNA and GFP transfer from malignant to nonmalignant cells in the GBM neuroglial microenvironment. This transfer involves extracellular vesicles, may contribute to reprogramming the microenvironment, and may extend to other cancer types. See related commentary by Shakya et al., p. 261.