Department of Physiology, School of Medicine, Jeju National University, Jeju, Republic of Korea.
Department of Physiology and Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV, USA.
J Int Med Res. 2022 Jul;50(7):3000605221113911. doi: 10.1177/03000605221113911.
To undertake a comprehensive analysis of the differential expression of the G protein-coupled receptor () genes in order to construct a gene signature for human glioma prognosis.
This current study investigated several glioma transcriptomic datasets and identified the genes potentially associated with glioma severity.
A gene signature comprising 13 genes (nine upregulated and four downregulated genes in high-grade glioma) was developed. The predictive power of the 13-gene signature was tested in two validation cohorts and a strong positive correlation (Spearman's rank correlation test: =0.649 for the Validation1 cohort; 0.693 for the Validation2 cohort) was observed between the glioma grade and 13-gene based severity score in both cohorts. The 13-gene signature was also predictive of glioma prognosis based on Kaplan-Meier survival curve analyses and Cox proportional hazard regression analysis in four cohorts of patients with glioma.
Knowledge of gene expression in glioma may help researchers gain a better understanding of the pathogenesis of high-grade glioma. Further studies are needed to validate the association between these genes and glioma pathogenesis.
全面分析 G 蛋白偶联受体（GPCR）基因的差异表达，构建用于预测人胶质瘤预后的基因特征。
本研究分析了多个胶质瘤转录组数据集，确定了与胶质瘤严重程度相关的潜在基因。
构建了一个由 13 个基因组成的基因特征（高级别胶质瘤中上调 9 个基因，下调 4 个基因）。在两个验证队列中测试了 13 个基因特征的预测能力，并观察到在两个队列中，胶质瘤分级与基于 13 个基因的严重程度评分之间存在很强的正相关性（验证 1 队列的 Spearman 等级相关检验：=0.649；验证 2 队列：=0.693）。基于 Kaplan-Meier 生存曲线分析和 Cox 比例风险回归分析，该基因特征在四个胶质瘤患者队列中也可预测胶质瘤的预后。
了解胶质瘤中 GPCR 基因的表达可能有助于研究人员更好地理解高级别胶质瘤的发病机制。需要进一步的研究来验证这些基因与胶质瘤发病机制之间的关联。
