Department of Information Sciences, Faculty of Science and Technology, Tokyo University of Science, Chiba, Japan
Department of Information Sciences, Faculty of Science and Technology, Tokyo University of Science, Chiba, Japan.
Anticancer Res. 2020 May;40(5):2777-2785. doi: 10.21873/anticanres.14250.
BACKGROUND/AIM: Understanding of the molecular events associated with progression and survival differences in patients with lower-grade gliomas (LGGs) is still unclear. The comparison of findings across studies using different datasets and methods is essential for a new molecular-based classification system. The aim of the study was to identify biomarkers for prognostic classification of patients with LGGs, and furthermore to lay a foundation for future development of targeted therapies for LGGs.
Using information-theoretic and statistical approaches, we analyzed mRNA expression data for 18,413 genes from LGG samples in order to identify candidate biomarkers for survival. The candidate genes were then evaluated for their potential as prognostic biomarkers using multivariable Cox regression analyses that adjusted for the effects of age and grade.
WEE1, EMP3, E2F7, CD58 and NSUN7 genes were identified as candidate biomarkers of LGGs and their high expression was associated with significantly shorter survival. The hazard ratios for mortality were 5.02 (95% CI=3.40-7.40) for WEE1, 5.45 (95% CI=3.63-8.18) for EMP3, 4.49 (95% CI=3.03-6.66) for E2F7, 4.77 (95% CI=3.22-7.06) for CD58 and 4.38 (95% CI=2.97-6.47) for NSUN7. In addition, the expression pattern of these genes, associated with shorter survival in LGGs, was also observed in glioblastoma multiforme.
Identification of genes associated with poor outcomes will provide insights into novel biological mechanisms that may lead to improvement in progression and survival for patients with LGGs.
背景/目的:对于低级别胶质瘤(LGG)患者进展和生存差异相关的分子事件的理解仍不清楚。使用不同数据集和方法进行的研究结果的比较对于新的基于分子的分类系统至关重要。本研究的目的是确定 LGG 患者预后分类的生物标志物,并为 LGG 的靶向治疗的未来发展奠定基础。
使用信息论和统计方法,我们分析了来自 LGG 样本的 18413 个基因的 mRNA 表达数据,以鉴定与生存相关的候选生物标志物。然后使用多变量 Cox 回归分析评估候选基因作为预后生物标志物的潜力,该分析调整了年龄和分级的影响。
WEE1、EMP3、E2F7、CD58 和 NSUN7 基因被确定为 LGG 的候选生物标志物,其高表达与明显较短的生存相关。死亡率的危险比分别为:WEE1 为 5.02(95%可信区间为 3.40-7.40),EMP3 为 5.45(95%可信区间为 3.63-8.18),E2F7 为 4.49(95%可信区间为 3.03-6.66),CD58 为 4.77(95%可信区间为 3.22-7.06),NSUN7 为 4.38(95%可信区间为 2.97-6.47)。此外,这些基因的表达模式与 LGG 中较短的生存相关,也在多形性胶质母细胞瘤中观察到。
鉴定与不良预后相关的基因将为新的生物学机制提供深入了解,这些机制可能导致 LGG 患者的进展和生存得到改善。