A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma

作者:Lin, Tao; Cheng, Hao; Liu, Da; Wen, Lei; Kang, Junlin; Xu, Longwen; Shan, Changguo; Chen, Zhijie; Li, Hainan; Lai, Mingyao; Zhou, Zhaoming; Hong, Weiping; Hu, Qingjun; Li, Shaoqun; Zhou, Cheng; Geng, Jiwu*; Jin, Xin*
来源:Frontiers in Genetics, 2021, 12: 698284.
DOI:10.3389/fgene.2021.698284

摘要

Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and risk signature in LGG. Therefore, we identified six autophagy-related genes (BAG1, PTK6, EEF2, PEA15, ITGA6, and MAP1LC3C) to build in the training cohort (n = 305 patients) and verify the prognostic model in the validation cohort (n = 128) and the whole cohort (n = 433), based on the data from The Cancer Genome Atlas (TCGA). The six-gene risk signature could divide LGG patients into high- and low-risk groups with distinct overall survival in multiple cohorts (all p < 0.001). The prognostic effect was assessed by area under the time-dependent ROC (t-ROC) analysis in the training, validation, and whole cohorts, in which the AUC value at the survival time of 5 years was 0.837, 0.755, and 0.803, respectively. Cox regression analysis demonstrated that the risk model was an independent risk predictor of OS (HR > 1, p < 0.05). A nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its robust predictive capacity. KM analysis revealed a significant difference in the subgroup analyses' survival. Functional enrichment analysis revealed that these autophagy-related signatures were mainly involved in the phagosome and immune-related pathways. Besides, we also found significant differences in immune cell infiltration and immunotherapy targets between risk groups. In conclusion, we built a powerful predictive signature and explored immune components (including immune cells and emerging immunotherapy targets) in LGG.

  • 单位
    1; 南方医科大学; 西安交通大学; 广东省人民医院; 兰州大学