Background: Glioblastoma (GBM), one of the most aggressive tumors of the brain, has no effective or sufficient therapies. Identifying robust biomarkers for the response to immune checkpoint blockade (ICB) therapy, a promising treatment option for GBM patients, is urgently needed.
Methods: We comprehensively evaluated lncRNA m6A modification patterns in m6A-sequencing (m6A-seq) data for GBM tissues and systematically investigated the immune and stromal regulators of these m6A-regulated lncRNAs. We used the single-sample gene-set enrichment analysis (ssGSEA) algorithm to investigate the difference in enriched tumor microenvironment (TME) infiltrating cells and the functional annotation of HSPA7 in individual GBM samples. Further, we validated that HSPA7 promoted the recruitment of macrophages into GBM TME in vitro, as well as in our GBM tissue section. We also explored its impact on the efficacy of ICB therapy using the patient-derived glioblastoma organoid (GBO) model.
Results: Here, we depicted the first transcriptome-wide m6A methylation profile of lncRNAs in GBM, revealing highly distinct lncRNA m6A modification patterns compared to those in normal brain tissues. We identified the m6A-modified pseudogene HSPA7 as a novel prognostic risk factor in GBM patients, with crucial roles in immunophenotype determination, stromal activation, and carcinogenic pathway activation. We confirmed that HSPA7 promoted macrophage infiltration and SPP1 expression via upregulating the YAP1 and LOX expression of glioblastoma stem cells (GSCs) in vitro and in our clinical GBM tumor samples. We also confirmed that knockdown of HSPA7 might increase the efficiency of anti-PD1 therapy utilizing the GBO model, highlighting its potential as a novel target for immunotherapy.
Conclusions: Our results indicated that HSPA7 could be a novel immunotherapy target for GBM patients.
Keywords: HSPA7; N6-methyladenosine; glioblastoma; immune checkpoint blockade; tumor microenvironment.
Copyright © 2021 Zhao, Li, Zhang, He, Pan, Guo, Qiu, Qi, Zhao, Wang, Chen, Zhang, Guo, Xue and Li.