Gliomas, as the most lethal and malignant brain tumours in adults, remain a major challenge worldwide. DNA damage and repair-related genes (DDRRGs) appear to play a significant role in gliomas, but the studies of DDRRGs are still insufficient. Herein, we systematically explored and analysed 1547 DDRRGs in 938 glioma samples from TCGA and CGGA datasets. Using least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we identified a 16-DDRRG signature, characterized by high-risk and low-risk patterns. This risk model harbours robust predictive capability for overall survival of glioma patients. We found the high-risk score is strongly associated with well-known malignant features of gliomas, such as the mesenchymal subtype, IDH-wildtype, 1p/19q non-codeletion and MGMT promoter unmethylated status. In addition, we found that the high-risk score is also linked with multiple oncogenic pathways and therapeutic resistance. Significantly, we found the high-risk group has higher enrichment of immunosuppressive cells (M2-type macrophages, Tregs and MDSCs) and immune inhibition biomarkers (PD-1, PD-L1 and CTLA-4). Lastly, we proved that SMC4, which has the highest positive regression coefficient in our risk model, is strongly linked with malignant progression and TMZ resistance of gliomas in a E2F1-dependent manner.
Keywords: gliomas; immunosuppressive status; prognostic prediction; risk stratification; the DDRRGs signature.
© 2022 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.