Table_2_Identification of tryptophan metabolic gene-related subtypes, development of prognostic models, and characterization of tumor microenvironment infiltration in gliomas.XLS

BackgroundEpigenetic regulation and immunotherapy of tumor microenvironment (TME) is a hot topic in recent years. However, the potential value of tryptophan metabolism genes in regulating TME and immunotherapy is still unclear.Materials and methodsA comprehensive study of glioma patients was carried out based on 40 tryptophan metabolic genes. Subsequently, these prognostic tryptophan metabolic genes are systematically associated with immunological characteristics and immunotherapy. A risk score model was constructed and verified in the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) cohorts to provide guidance for prognosis prediction and immunotherapy of glioma patients.ResultsWe described the changes of tryptophan metabolism genes in 966 glioma samples from genetic and transcriptional fields and evaluated their expression patterns from two independent data sets. We identified two different molecular subtypes and found that two subtypes were associated with clinicopathological features, prognosis, TME cell infiltration, and immune checkpoint blockers (ICBs). Then, four genes (IL4I1, CYP1A1, OGDHL, and ASMT) were screened out by univariate and multivariate cox regression analysis of tryptophan metabolism genes, and a risk score model for predicting the overall survival (OS) of glioma patients was constructed. And its predictive ability is verified using the CGGA database. At the same time, we verified the expression of IL4I1, CYP1A1, OGDHL, and ASMT four genes in glioma specimens and cell lines in GES4260 and GES15824. Therefore, we constructed a nomogram to improve the clinical applicability of the risk assessment model. The high risk score group, characterized by increased TMB and immune cell infiltration, was also sensitive to temozolomide immunotherapy. Our comprehensive analysis of tryptophan metabolic genes in gliomas shows that they play a potential role in tumor immune stromal microenvironment, clinicopathological features, and prognosis.ConclusionTryptophan metabolism genes play an indispensable role in the complexity, diversity, and prognosis of TME. This risk score model based on tryptophan metabolism gene is a new predictor of clinical prognosis and immunotherapy response of glioma, and guides a more appropriate immunotherapy strategy for glioma patients.

近年来，肿瘤微环境（TME）的表观遗传调控与免疫治疗成为研究热点。然而，色氨酸代谢基因在调控TME及免疫治疗中的潜在价值尚不明确。本研究基于40个色氨酸代谢基因，对胶质瘤患者进行了全面研究。随后，这些预测性色氨酸代谢基因与免疫学特征及免疫治疗进行了系统性关联。构建并验证了一个风险评分模型，用于Cancer Genome Atlas（TCGA）和Chinese Glioma Genome Atlas（CGGA）队列中的预后预测和免疫治疗指导。研究结果显示，我们从遗传和转录层面描述了966个胶质瘤样本中色氨酸代谢基因的变化，并从两个独立数据集中评估了其表达模式。我们识别出两种不同的分子亚型，并发现这两种亚型与临床病理特征、预后、TME细胞浸润及免疫检查点抑制剂（ICBs）相关。通过单变量和多变量Cox回归分析筛选出四个基因（IL4I1、CYP1A1、OGDHL和ASMT），并构建了一个预测胶质瘤患者总生存期（OS）的风险评分模型。该模型的预测能力在CGGA数据库中得到验证。同时，我们验证了IL4I1、CYP1A1、OGDHL和ASMT四个基因在胶质瘤标本和GES4260、GES15824细胞系中的表达。因此，我们构建了一个诺模图，以提高风险评估模型的临床应用性。高风险评分组，其特征为肿瘤突变负荷（TMB）增加和免疫细胞浸润，对替莫唑胺免疫治疗敏感。我们对胶质瘤中色氨酸代谢基因的全面分析表明，它们在肿瘤免疫基质微环境、临床病理特征及预后中发挥着潜在的作用。结论指出，色氨酸代谢基因在TME的复杂性、多样性和预后中发挥着不可或缺的作用。基于色氨酸代谢基因构建的风险评分模型是胶质瘤临床预后和免疫治疗反应的新预测因子，并指导制定更合适的胶质瘤患者免疫治疗策略。