Spatial transcriptomics reveals segregation of tumor cell states in glioblastoma and marked immunosuppression within the perinecrotic niche

Abstract

Glioblastoma (GBM) remains an untreatable malignant tumor with poor patient outcomes, characterized by palisading necrosis and microvascular proliferation. While single-cell technology made it possible to characterize different lineage of glioma cells into neural progenitor-like (NPC-like), oligodendrocyte-progenitor-like (OPC-like), astrocyte-like (AC-like) and mesenchymal like (MES-like) states, it does not capture the spatial localization of these tumor cell states. Spatial transcriptomics empowers the study of the spatial organization of different cell types and tumor cell states and allows for the selection of regions of interest to investigate region-specific and cell-type-specific pathways. Here, we obtained paired 10x Chromium single-nuclei RNA-sequencing (snRNA-seq) and 10x Visium spatial transcriptomics data from three GBM patients to interrogate the GBM microenvironment. Integration of the snRNA-seq and spatial transcriptomics data reveals patterns of segregation of tumor cell states. For instance, OPC-like tumor and NPC-like tumor significantly segregate in two of the three samples. Our differentially expressed gene and pathway analyses uncovered significant pathways in functionally relevant niches. Specifically, perinecrotic regions were more immunosuppressive than the endogenous GBM microenvironment, and perivascular regions were more pro-inflammatory. Our gradient analysis suggests that OPC-like tumor cells tend to reside in areas closer to the tumor vasculature compared to tumor necrosis, which may reflect increased oxygen requirements for OPC-like cells. In summary, we characterized the localization of cell types and tumor cell states, the gene expression patterns, and pathways in different niches within the GBM microenvironment. Our results provide further evidence of the segregation of tumor cell states and highlight the immunosuppressive nature of the necrotic and perinecrotic niches in GBM.

Keywords: Glioblastoma; Perinecrotic niche; Perivascular niche; Single-cell sequencing; Spatial transcriptomics; Tumor microenvironment.

Fig. 1

a Workflow of the study. From each GBM brain, both snRNA-seq and Visium spatial transcriptomics data were generated as paired samples. The single nuclei data and spatial data were processed separately, then integrated for downstream analysis. b Combined snRNA-seq data from three GBMs with annotation of cell types and tumor cell states. c Combined inferCNV results from three GBMs. Chromosome 7 gain and 10 loss was observed in all samples, and each sample had distinct copy number variations (CNV), demonstrating heterogeneity in CNV

Fig. 2

a–c Deconvolution results from RCTD for samples 18-0282, 19-0142, and 19-0341, respectively, showing localization of each cell type. “Neuron” refers to cells expressing both excitatory and inhibitory neuron markers. d–k Correlation between cell type pairs, calculated with cor.test() in R. Complete correlation plots in Additional file 6: Fig. S6

Fig. 3

Plot for samples 18-0282 and 19-0142, logFC of gene expression in palisading necrosis niche compared to the generic tumor region, cell type adjusted. Whether the logFC of the gene is significant is shown in the legend. Adjusted p values < 0.05 were labeled as significant

Fig. 4

a, b Heatmaps showing the top DEGs (top) and localizations of cell types or tumor cell states (bottom) in each of the eight annotated regions, cell type adjusted, for samples 18-0282 and 19-0142, respectively. Each column represents a spot in the corresponding region. If a gene is differentially expressed in multiple regions, it’s only shown once (See Additional file 21: Table S4 for the full DEGs)