Zhao Songyun, Chi Hao, Ji Wei, He Qisheng, Lai Guichuan, Peng Gaoge, Zhao Xiaoyu, Cheng Chao
Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi 214000, China.
Clinical Medicine College, Southwest Medical University, Luzhou 646000, China.
Brain Sci. 2022 Oct 5;12(10):1349. doi: 10.3390/brainsci12101349.
Low-grade glioma (LGG) is a highly aggressive disease in the skull. On the other hand, anoikis, a specific form of cell death induced by the loss of cell contact with the extracellular matrix, plays a key role in cancer metastasis. In this study, anoikis-related genes (ANRGs) were used to identify LGG subtypes and to construct a prognostic model for LGG patients. In addition, we explored the immune microenvironment and enrichment pathways between different subtypes. We constructed an anoikis-related gene signature using the TCGA (The Cancer Genome Atlas) cohort and investigated the differences between different risk groups in clinical features, mutational landscape, immune cell infiltration (ICI), etc. Kaplan-Meier analysis showed that the characteristics of ANRGs in the high-risk group were associated with poor prognosis in LGG patients. The risk score was identified as an independent prognostic factor. The high-risk group had higher ICI, tumor mutation load (TMB), immune checkpoint gene expression, and therapeutic response to immune checkpoint blockers (ICB). Functional analysis showed that these high-risk and low-risk groups had different immune statuses and drug sensitivity. Risk scores were used together with LGG clinicopathological features to construct a nomogram, and Decision Curve Analysis (DCA) showed that the model could enable patients to benefit from clinical treatment strategies.
低级别胶质瘤（LGG）是一种发生于颅骨的侵袭性很强的疾病。另一方面，失巢凋亡是一种因细胞与细胞外基质失去接触而诱导的特定形式的细胞死亡，在癌症转移中起关键作用。在本研究中，利用失巢凋亡相关基因（ANRGs）来识别LGG亚型并构建LGG患者的预后模型。此外，我们还探究了不同亚型之间的免疫微环境和富集通路。我们使用癌症基因组图谱（TCGA）队列构建了一个失巢凋亡相关基因特征，并研究了不同风险组在临床特征、突变图谱、免疫细胞浸润（ICI）等方面的差异。Kaplan-Meier分析表明，高危组中ANRGs的特征与LGG患者的不良预后相关。风险评分被确定为一个独立的预后因素。高危组具有更高的ICI、肿瘤突变负荷（TMB）、免疫检查点基因表达以及对免疫检查点阻断剂（ICB）的治疗反应。功能分析表明，这些高危组和低危组具有不同的免疫状态和药物敏感性。将风险评分与LGG临床病理特征结合起来构建了一个列线图，决策曲线分析（DCA）表明该模型能够使患者从临床治疗策略中获益。
