Glioblastoma (GBM) is a typical heterogeneous tumor and the most fatal primary malignant tumor of the central nervous system (CNS). The conventional treatment for GBM is surgical resection followed by radiotherapy, combined with temozolomide chemotherapy; however the treatment effect is still not ideal. Intratumoral heterogeneity and redundancy of signaling pathways may explain why traditional and targeted therapies cannot achieve long-term remission. Therefore, new therapies are urgently needed to improve the prognosis of glioma patients. At present, cancer immunotherapy is a great breakthrough, with immune checkpoint inhibitors leading the way. Different immune checkpoints have different mechanisms in cancer immunotherapy. Unlike the cytotoxic effects of chemotherapy, immune checkpoints regulate the immune system and induce cancer cell death. With the development of single-cell RNA sequencing (scRNA-seq), our understanding of diseases at the genetic level has increased to the single cell levels, Recently, scRNA-seq has revealed differences between blood-derived tumor-associated macrophages (TAMs) and microglial TAMs, cellular state of malignant cells, and their plasticity and gene-driven regulation in GBM. Nevertheless, scRNA-seq datasets lack spatial location information and cannot reveal cell states. Therefore, we introduced spatial transcriptomics (ST), which combines histological imaging and RNA-Seq by retaining the positional information for each transcript through spatially immobilized and barcoded cDNA synthesis primers. 

Here, we revealed the expression of immune checkpoints in GBM and intratumoral heterogeneity via snRNA-seq and ST. We profiled the transcriptome of 32 328 single cells from GBM and paracancerous samples, and produced an atlas of the spatial tumor microenvironment inside GBM tissues. Our study will improve our understanding of the mechanism of GBM progression, and may be potentially valuable in identifying novel targets for GBM.We generated a single-cell spatial transcriptome map using snRNA-seq and ST to reveal the landscape of the microenvironment in GBM, summarized the expression profiles of common immune checkpoints in GBM and observed that TIM-3, VISTA, PSGL-1, and VSIG-3 were the most highly expressed in GBM at single-cell and spatial levels. We demonstrated that the expression patterns of TIM-3, VISTA, and PSGL-1 were almost the same, showing a significant positive correlation, mainly expressed in microglia, whereas VSIG-3 was highly expressed in neoplastic cells. In this study, we demonstrated that VSIR_IGSF11 was extensively involved in intercellular communication. Taken together, our GBM transcription map provided a framework for understanding the TME and characterizes tumor-associated subsets. Moreover, we described the immunosuppressive state of GBM in several aspects, which are potential targets for the development of immunotherapy for GBM and other cancers. The combination of single-cell data with spatial information allowed us to summarize spatial and cellular information in GBM. Finally, although we have obtained key interaction networks in the GBM tumor microenvironment through bioinformatics analysis, further functional experiments are needed to explore the biological consequences and potential mechanisms.