In this study, through in-depth single-cell RNA sequencing analysis, we have unveiled the complex heterogeneity of glioma, particularly at the level of malignant cells and macrophages/monocytes within the tumor microenvironment. Our findings not only confirm previous studies on the diversity of immune cells within the glioma microenvironment but also, through developmental trajectory analysis, propose potential origins and differentiation pathways for malignant cells, offering new insights into the biological behavior of glioma.
The malignant cell subpopulations and macrophage/monocyte subtypes we identified demonstrate the high heterogeneity of cellular subpopulations within the glioma microenvironment. Notably, the discovery of the NB-like Malignant cell population suggests its potential initiating role in tumorigenesis. This finding aligns with the cancer stem cell theory, which posits that tumor-initiating cells play a key role in the initiation, development, and therapeutic resistance of tumors23. Furthermore, our developmental trajectory analysis has shed light on the differentiation pathways of malignant cells, consistent with the study by Verhaak et al., which revealed the molecular subtypes of glioma through large-scale genomic analysis24.
Cell-cell communication analysis has revealed the complex interactions between macrophages/monocytes and malignant cells. In particular, the discovery of the MIF and SPP1 signaling pathways provides new targets for glioma treatment. The immunomodulatory role of MIF in various tumors has been extensively studied, and our study further emphasizes its critical role within the glioma microenvironment25,26. SPP1, as an important extracellular matrix protein, has been shown to play a role in the adhesion, migration, and invasion of tumor cells27,28.
Our analysis of GRNs has identified multiple transcription factors, such as IKZF1 and HDAC2, that may play a key role in the development of glioma. The abnormal activity of these transcription factors is closely related to the proliferation, survival, and invasion of tumor cells. Therefore, they may serve as potential targets for glioma treatment.
Unsupervised consensus clustering analysis has divided glioma into two subgroups with significant differences in survival. The high infiltration levels of immune cells and enhanced immune treatment response in the C2 subgroup suggest that this subgroup may be more sensitive to immunotherapy. This finding is consistent with the study by Economopoulou et al., which highlighted the important role of the immune microenvironment in tumor immune evasion and response to immunotherapy29.
Finally, the prognostic model we constructed has demonstrated high accuracy and robust performance in predicting the survival of glioma patients. The development of this model not only provides a new tool for the clinical management of glioma but also, through the inclusion of genes, offers potential targets for future mechanistic research and drug development. The abnormal expression of these genes is closely related to the invasiveness, therapeutic resistance, and prognosis of glioma30,31,32,33,34,35. The negative correlation between high-risk scores and immune checkpoints and immune cell infiltration levels indicates the important role of the immune microenvironment in glioma prognosis. This finding is in line with the concept of immune editing, which suggests that tumors may evade immune surveillance by modulating the immune microenvironment36. Additionally, the expression of immune checkpoint molecules may predict patient responsiveness to immunotherapy, providing potential biomarkers for personalized treatment.
Despite the new insights our study provides into the heterogeneity of glioma and the interactions within the microenvironment, there are some limitations. For example, the sample size in our study is still limited, and future studies need to validate our findings with a larger number of samples and across a broader range of ethnicities and geographic regions. Moreover, our results need to be further validated in prospective clinical trials. Future research should also explore the interactions between malignant cell subpopulations and macrophage/monocyte subtypes and how these interactions affect the development and treatment response of glioma.
In summary, our study, through single-cell RNA sequencing and comprehensive analysis, has revealed the complex interplay between malignant cells and immune cells within the glioma microenvironment. The prognostic model we constructed and our analysis of cell-cell communication and gene regulatory networks provide new strategies for personalized treatment of glioma. These findings not only enhance our understanding of glioma heterogeneity but also provide valuable information for future research and treatment. Of course, our research has the following limitations: (1) The size of the datasets used in this study was limited. While we have attempted to draw meaningful conclusions from the available data, a larger dataset would likely provide more robust and generalizable results; (2) This study lacks external validation. The findings presented have not been corroborated by additional independent studies, which may impact the strength and reliability of the conclusions drawn; (3) The results of this study may not be generalizable to broader populations due to the specific characteristics of the dataset. Further research with more diverse samples is required to confirm the applicability of these findings across different contexts.