A Prognostic DNA Damage Repair Genes Signature and Its Impact on Immune Cell Infiltration in Glioma - Wang, Guohui; Zhou, Huandi; Tian, Lei; Yan, Tianfang; Han, Xuetao; Chen, Pengyu; Li, Haonan; Wang, Wenyan; Xiao, Zhiqing; Hou, Liubing; Xue, Xiaoying (Frontiers in Oncology, 2021)
Objective: Glioma is the most frequent type of malignant cerebral tumors. DNA damage repair genes (DDRGs) play a crucial role in the development of cancer. In this study, we constructed a DDRGs signature and investigated the potential mechanisms involved in this disease. Methods: RNA sequence data, microarray data, and corresponding clinical information of gliomas were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO). Subsequently, we identified candidate genes by differential analysis and Cox regression analysis. The least absolute shrinkage and selection operator Cox regression model was utilized to construct a DDRGs signature using TCGA training dataset. According to this signature, patients with glioma were divided into low- and high-risk groups. The predictive ability of the signature was validated by prognostic analysis, receiver operating characteristic curves, principal component analysis, and stratification analysis in TCGA testing and CGGA verification datasets. CIBERSORT and single-sample gene set enrichment analysis were used to evaluate the immune microenvironment of glioma. Moreover, we conducted GSEA to determine the functions and pathways in the low- and high-risk groups. Finally, a nomogram was constructed by combining the signature and other clinical features. Results: A total of 1,431 samples of glioma (592 from TCGA, 686 from the CGGA, and 153 from the GEO) and 23 samples of normal brain tissue from the GEO were analyzed in this study. There were 51 prognostic differentially expressed DDRGs. Additionally, five DDRGs (CDK4,HMGB2,WEE1,SMC3, and GADD45G) were selected to construct a DDRGs signature for glioma, stratifying patients into low- and high-risk groups. The survival analysis showed that the DDRGs signature could differentiate the outcome of the low- and high-risk groups, showing that high-risk gliomas were associated with shorter overall survival. The immune microenvironment analysis revealed that more immunosuppressive cells, such as tumor associated macrophages and regulatory T cells, were recruited in the high-risk group. GSEA also showed that high-risk glioma was correlated with the immune and extracellular matrix pathways. Conclusion: The five DDRGs signature and its impact on the infiltration of immunosuppressive cells could precisely predict the prognosis and provide guidance on the treatment of glioma.