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Spatial analysis of recurrent glioblastoma reveals perivascular niche organization
Ugoma Onubogu, Chandler D. Gatenbee, Sandhya Prabhakaran, Kelsey L. Wolfe, Benjamin Oakes, Roberto Salatino, Rachael Vaubel, Oszkar Szentirmai, Alexander R.A. Anderson, Michalina Janiszewska
Ugoma Onubogu, Chandler D. Gatenbee, Sandhya Prabhakaran, Kelsey L. Wolfe, Benjamin Oakes, Roberto Salatino, Rachael Vaubel, Oszkar Szentirmai, Alexander R.A. Anderson, Michalina Janiszewska
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Research Article Oncology

Spatial analysis of recurrent glioblastoma reveals perivascular niche organization

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Abstract

Tumor evolution is driven by genetic variation; however, it is the tumor microenvironment (TME) that provides the selective pressure contributing to evolution in cancer. Despite high histopathological heterogeneity within glioblastoma (GBM), the most aggressive brain tumor, the interactions between the genetically distinct GBM cells and the surrounding TME are not fully understood. To address this, we analyzed matched primary and recurrent GBM archival tumor tissues with imaging-based techniques aimed to simultaneously evaluate tumor tissues for the presence of hypoxic, angiogenic, and inflammatory niches, extracellular matrix (ECM) organization, TERT promoter mutational status, and several oncogenic amplifications on the same slide and location. We found that the relationships between genetic and TME diversity are different in primary and matched recurrent tumors. Interestingly, the texture of the ECM, identified by label-free reflectance imaging, was predictive of single-cell genetic traits present in the tissue. Moreover, reflectance of ECM revealed structured organization of the perivascular niche in recurrent GBM, enriched in immunosuppressive macrophages. Single-cell spatial transcriptomics further confirmed the presence of the niche-specific macrophage populations and identified interactions between endothelial cells, perivascular fibroblasts, and immunosuppressive macrophages. Our results underscore the importance of GBM tissue organization in tumor evolution and highlight genetic and spatial dependencies.

Authors

Ugoma Onubogu, Chandler D. Gatenbee, Sandhya Prabhakaran, Kelsey L. Wolfe, Benjamin Oakes, Roberto Salatino, Rachael Vaubel, Oszkar Szentirmai, Alexander R.A. Anderson, Michalina Janiszewska

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Figure 5

Spatial profiling of perivascular regions in primary and recurrent GBM.

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Spatial profiling of perivascular regions in primary and recurrent GBM.
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(A) Representative images highlighting selected vascular regions of recurrent GBM samples. Reflectance imaging showing hyperintense signal around vessel lumen (left) and immunostaining for CD163 and CD8α of peripheral cells (right). Scale bars: 40 μm. (B) Trichrome staining of perivascular collagen in recurrent GBM of adjacent section of the tumor region imaged in panel A. Scale bar: 40 μm. (C) Quantification of collagen rim around blood vessels in FOVs containing vasculature for primary and recurrent samples. Color scale represents number of cases. (D) Semisupervised clustering generated from normalized gene expression of 52,588 cells (4 GBM tumors). (E) Top differentially expressed markers of cellular groups. Columns represent cell types and rows represent genes. Scaled expression data represented as z scores. (F) UMAP plot grouped by tissue of origin. Primary (top) or recurrent (bottom) tissues. (G) Cell type composition of primary and recurrent samples. (H) Representative images of linked IHC (top), cell type spatial plots (middle), and niche spatial plots (bottom) in primary and recurrent samples. IHC images represent matched tissue sample locations to spatial plots at serial section not more than 12 μm away. Scale bars: 120 μm. (I) Distribution of percentage of cell types present within TME niches. Yellow cells indicate highly represented outliers computed at α = 0.001 before normalization. (J) Niche composition of primary and recurrent tumor.

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