Integrative analysis of single-cell and bulk transcriptome data reveals age-related immune cell alterations in primary glioblastoma associated with prognosis.

BACKGROUND: Glioblastoma (GBM) is the most malignant and highly recurrent brain tumor. Although over half of the GBM patients are elderly patients, the understanding of how aging affects GBM progression remains limited. METHODS: Clinical and genomic variation data of GBM patients from TCGA and CGGA databases were used for prognostic analysis. We collected single-cell transcriptome data of 88,908 cells from 13 primary GBM (pGBM) and 12 recurrent GBM (rGBM) patients. Age-related immune cells were identified through cell-cell communication and trajectory analysis. The results were validated by projecting the single-cell transcriptome profiles onto bulk data. Finally, we experimentally validated the results on syngeneic orthotopic models of younger and older mice. RESULTS: Prognostic analysis indicated the effect of age in pGBM patients is stronger than that in rGBM patients. Moreover, the mutational signatures in pGBM does not affect prognosis. Single-cell RNA sequencing analysis revealed age-related differences in immune cells between pGBM and rGBM, and identified microglia underwent significant cell state changes with aging only in pGBM patients. Next, we validated that high expression of HSPB1 in microglia from older pGBM patients is associated with poor prognosis. Finally, the syngeneic orthotopic model for aged mice exhibited more tumor invasion, with a shorter median survival time. Furthermore, the microglia within the tumor microenvironment (TME) of aged mice showed markedly high expression level of HSPB1. CONCLUSIONS: Our study highlights the crucial role of microglial aging in pGBM, reveals distinct age-related changes of immune cells in the TME between pGBM and rGBM, and offers valuable insights into clinical treatment strategies targeting elderly GBM patients.