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In a study published in Neurology, investigators from China identified a local immune signature predictive of outcomes in glioblastoma (GBM) compared to lower grade glioma (LGG).
By examining immune phenotypes from 297 cases of glioma taken from the Chinese Glioma Genome Atlas (CGGA) database, Wen Cheng, MD, PhD, of the First Hospital of China Medical University, and colleagues were able to identify 8 genes that showed the highest association to outcomes. According to hazard ratios (HR), 3 of the genes (FOX03, ZBTB16, AIMP1) were designated as conferring increased protection, while the other 5 (IL6, IL10, CCL18, AIMP1, FCGR2B, MMP9) were designated as conferring increased risk (P<.01). The researchers created a combined signature of the immune-related risk for a poor outcome.
The glioma data profiles were then segregated according to histological grade: 170 were rated as LGG (grades II and III), and 127 as GBM. Different immune phenotypes were evident between the 2 groups based on immune-gene set enrichment analysis (GSEA), demonstrating a higher intensity in the high-risk group.
Immune-risk signature was also effective in identifying unfavorable outcomes in GBM across two molecular markers (IDH1 and MGMT), and regardless of whether patients received chemotherapy or radiation treatment. All of the results were validated using The Cancer Genome Atlas (TCGA) database, which supported the finding that the local immune signature represented an independent risk factor for overall survival (OS).
The authors pointed out that LGG cases also showed immune signature responses that were predictive of outcomes, suggesting similar immune mechanisms to both forms of glioma. The main limitations to their study, they concluded, were that it is retrospective, and the full accuracy of the immune-signature they created needs to be tested in clinical environments.
The importance of this study was examined in an editorial by Rifaat Bashir, MD and Nimish Mohile, MD, who commended the authors for expanding discussion of the potential role of the immune system in the pathogenesis of GBM. Immune signatures in GBM have applications in the identification of pathways for development of new therapies, as well as in the selection of patients most likely to respond to immunologic-based treatments.
