Heterogeneity Analysis of Glioblastoma Tumor Cell Population Based on Single-Cell Rna Sequencing Data Analysis

Gliomas are lethal cancers that originate in the central nervous system. Glioblastoma multiforme (GBM) is the most aggressive and commonly occurring malignant brain glioma, accounting for just under 50% of all cases of malignant brain tumours in adults. In this paper, glioblastoma tumour cell single-cell RNA sequencing data were analyzed with Seurat, and cell groups were identified by employing various marker genes. Diverse populations of cell types were revealed, including tumour-associated macrophages, microglia, monocytes, t-cells, oligodendrocytes, glioblastoma stem cells, and other progenitor cells. Glioblastoma heterogeneity was also observed, as different samples of glioblastoma possessed distinct cellular compositions. Analysis of phagocytic cell clusters revealed the presence of microglia-like cells that resulted from monocyte differentiation. The upregulation of TIGIT and STAT3 in t-cell clusters was observed in cases with especially low t-cell counts, which demonstrates glioblastoma's immunosuppressive abilities. Furthermore, stem cell count was shown to be exceedingly low in cases of recurrent glioblastoma in comparison to cases of newly-diagnosed glioblastoma. Presumably, tumour recurrence should be caused by stem cells, but the exceptionally low stem cell count in cases of recurrent glioblastoma proves otherwise. This reveals that treatment or surgery should target stem cells in cases of newly developed glioblastoma but should target other factors in cases of recurrent glioblastoma-examples of which include the tumour microenvironment. These results can be used to help create more innovative and effective treatments for glioblastoma multiforme.