Expression of key unfolded protein response genes predicts patient survival and an immunosuppressive microenvironment in glioblastoma

Abstract

Abstract Background Dysregulation of cellular processes related to protein folding and trafficking leads to the accumulation of misfolded proteins in the endoplasmic reticulum (ER), triggering ER stress. Cells cope with ER stress by activating the unfolded protein response (UPR), a signaling pathway that has been implicated in a variety of diseases, including cancer. However, the role of the UPR in cancer initiation and progression is still unclear. Methods Here we used bulk and single cell RNA sequencing data to investigate ER stress-related gene expression in glioblastoma, as well as the impact key UPR genes have on patient survival. Results ER stress-related genes are highly expressed in both cancer cells and tumor-associated macrophages, with evidence of high intra- and inter-tumor heterogeneity. High expression of the UPR-related genes HSPA5, P4HB, and PDIA4 was identified as risk factors while high MAPK8 (JNK1) expression was identified as a protective factor in glioblastoma patients, indicating UPR genes have prognostic potential in this cancer type. Finally, expression of XBP1 and MAPK8, two key downstream targets of the ER sentinel IRE1α, correlates with the presence of immune cell types associated with immunosuppression and a worse patient outcome. This suggests that the expression of these genes is associated with an immunosuppressive tumor microenvironment and uncover a potential link between stress response pathways, tumor microenvironment and glioblastoma patient survival. Conclusions We performed a comprehensive transcriptional characterization of the unfolded protein response in glioblastoma patients and identified UPR-related genes associated with glioblastoma patient survival, providing potential prognostic and predictive biomarkers as well as promising targets for developing new therapeutic interventions in glioblastoma treatment.

Keywords

• Glioblastoma
• Unfolded protein response
• Endoplasmic reticulum stress
• Transcriptomics
• Single cell RNA-sequencing