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A novel tailored immune gene pairs signature for overall survival prediction in lower-grade gliomas
Authors:Xuyan Pan  Zhaopeng Wang  Fang Liu  Feihui Zou  Qijun Xie  Yizhuo Guo  Liang Shen
Institution:aDepartment of Neurosurgery, Huzhou Cent Hospital, Affiliated Cent Hospital Huzhou University, 1558 Third Ring North Road, Huzhou, Zhejiang 313000, China;bDepartment of Neurosurgery, The affiliated Changzhou No.2 People''s Hospital of Nanjing Medical University, 68 Gehu Road, Changzhou, Jiangsu 213000, China
Abstract:Lower-grade gliomas (LGGs) have a good prognosis with a wide range of overall survival (OS) outcomes. An accurate prognostic system can better predict survival time. An RNA-Sequencing (RNA-seq) prognostic signature showed a better predictive power than clinical predictor models. A signature constructed using gene pairs can transcend changes from biological heterogeneity, technical biases, and different measurement platforms. RNA-seq coupled with corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Immune-related gene pairs (IRGPs) were used to establish a prognostic signature through univariate and multivariate Cox proportional hazards regression. Weighted gene co-expression network analysis (WGCNA) was used to evaluate module eigengenes correlating with immune cell infiltration and to construct gene co-expression networks. Samples in the training and testing cohorts were dichotomized into high- and low-risk groups. Risk score was identified as an independent predictor, and exhibited a closed relationship with prognosis. WGCNA presented a gene set that was positively correlated with age, WHO grade, isocitrate dehydrogenase (IDH) mutation status, 1p/19 codeletion, risk score, and immune cell infiltrations (CD4 T cells, B cells, dendritic cells, and macrophages). A nomogram comprising of age, WHO grade, 1p/19q codeletion, and three gene pairs (BIRC5|SSTR2, BMP2|TNFRSF12A, and NRG3|TGFB2) was established as a tool for predicting OS. The IPGPs signature, which is associated with immune cell infiltration, is a novel tailored tool for individual-level prediction.
Keywords:Lower-grade gliomas  Immune  Weighted gene co-expression network analysis  Nomogram  Prognosis
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