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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 4

Reflectance imaging–based patterns of tissue organization predictive of cellular composition of the tumor.

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Reflectance imaging–based patterns of tissue organization predictive of ...
(A) Representative images of reflectance microscopy–based extracellular matrix textures: string-like, spotty, and mossy. Scale bars: 40 μm. (B) Representative images of mixed reflectance textures and their manual annotation. SL, string-like texture; SP, spotty texture; MO, mossy texture. Scale bars: 40 μm. (C) Influence of cell type on reflectance niche. Mean non-zero influences estimated from correctly classified quadrats (quadrat width and height = 199), weighted by the frequency at which each feature had a non-zero influence per class. Error bars indicate the 95% confidence intervals. n reps = 100, mean correctly classified quadrats per rep = 690.49, median ROC-AUC = 0.784.

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ISSN 2379-3708

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