Li Wenxia, Ling Ling, Xiang Lei, Ding Peng, Yue Wei
Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China.
Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China.
Front Cell Neurosci. 2023 Feb 28;17:1146686. doi: 10.3389/fncel.2023.1146686. eCollection 2023.
Lower-grade glioma (LGG) is one of the most common malignant tumors in the central nervous system (CNS). Accumulating evidence have demonstrated that tryptophan metabolism is significant in tumor. Therefore, this study aims to comprehensively clarify the relationship between tryptophan metabolism-related genes (TRGs) and LGGs.
The expression level of TRGs in LGG and normal tissues was first analyzed. Next, the key TRGs with prognostic value and differential expression in LGGs were identified using the least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, a risk model was constructed and Consensus clustering analysis was conducted based on the expression level of key TRGs. Then, the prognostic value, clinicopathological factors, and tumor immune microenvironment (TIME) characteristics between different risk groups and molecular subtypes were analyzed. Finally, the expression, prognosis, and TIME of each key TRGs were analyzed separately in LGG patients.
A total of 510 patients with LGG from The Cancer Genome Atlas (TCGA) dataset and 1,152 normal tissues from the Genotype-Tissue Expression (GTEx) dataset were included to evaluate the expression level of TRGs. After LASSO regression analysis, we identified six key TRGs and constructed a TRGs risk model. The survival analysis revealed that the risk model was the independent predictor in LGG patients. And the nomogram containing risk scores and independent clinicopathological factors could accurately predict the prognosis of LGG patients. In addition, the results of the Consensus cluster analysis based on the expression of the six TRGs showed that it could classify the LGG patients into two distinct clusters, with significant differences in prognosis, clinicopathological factors and TIME between these two clusters. Finally, we validated the expression, prognosis and immune infiltration of six key TRGs in patients with LGG.
This study demonstrated that tryptophan metabolism plays an important role in the progression of LGG. In addition, the risk model and the molecular subtypes we constructed not only could be used as an indicator to predict the prognosis of LGG patients but also were closely related to the clinicopathological factors and TIME of LGG patients. Overall, our study provides theoretical support for the ultimate realization of precision treatment for patients with LGG.
低级别胶质瘤（LGG）是中枢神经系统（CNS）最常见的恶性肿瘤之一。越来越多的证据表明色氨酸代谢在肿瘤中具有重要意义。因此，本研究旨在全面阐明色氨酸代谢相关基因（TRGs）与LGG之间的关系。
首先分析LGG组织和正常组织中TRGs的表达水平。接下来，使用最小绝对收缩和选择算子（LASSO）回归分析确定在LGG中具有预后价值和差异表达的关键TRGs。随后，基于关键TRGs的表达水平构建风险模型并进行一致性聚类分析。然后，分析不同风险组和分子亚型之间的预后价值、临床病理因素和肿瘤免疫微环境（TIME）特征。最后，分别分析LGG患者中每个关键TRG的表达、预后和TIME。
纳入来自癌症基因组图谱（TCGA）数据集的510例LGG患者和来自基因型-组织表达（GTEx）数据集的1152例正常组织，以评估TRGs的表达水平。经过LASSO回归分析，我们确定了6个关键TRGs并构建了一个TRGs风险模型。生存分析显示该风险模型是LGG患者的独立预测因子。并且包含风险评分和独立临床病理因素的列线图可以准确预测LGG患者的预后。此外，基于6个TRGs表达的一致性聚类分析结果表明，它可以将LGG患者分为两个不同的聚类，这两个聚类在预后、临床病理因素和TIME方面存在显著差异。最后，我们验证了LGG患者中6个关键TRGs的表达、预后和免疫浸润情况。
本研究表明色氨酸代谢在LGG的进展中起重要作用。此外，我们构建的风险模型和分子亚型不仅可以作为预测LGG患者预后的指标，而且与LGG患者的临床病理因素和TIME密切相关。总体而言，我们的研究为最终实现LGG患者的精准治疗提供了理论支持。
