Five Genes Associated With Survival in Patients With Lower-grade Gliomas Were Identified by Information-theoretical Analysis
Five Genes Associated With Survival in Patients With Lower-grade Gliomas Were Identified by Information-theoretical Analysis
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DOI：
10.21873/anticanres.14250
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发表时间：
2020-05-01
影响因子：
2
通讯作者：
Akimoto, Kazunori
中科院分区：
文献类型：
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作者：
Sato, Keiko;Tahata, Kouji;Akimoto, Kazunori
背景/目的：对低级别胶质瘤(LGG)患者进展和生存差异的分子事件的了解尚不清楚。使用不同的数据集和方法比较不同研究的结果对于新的基于分子的分类系统是至关重要的。本研究的目的是找出LGGs患者预后分类的生物标志物，并进一步为未来LGGs靶向治疗的发展奠定基础。患者和方法：利用信息论和统计学方法，我们分析了来自LGG样本的18,413个基因的mRNA表达数据，以确定影响生存的候选生物标记物。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记物的潜力，该回归分析调整了年龄和年级的影响。结果：Wee1、EMP3、E2F7、CD58和NSUN7基因是LGGs的候选标志物，其高表达与生存期显著缩短相关。WEE1、EMP3、E2F7、CD58和NSUN7的死亡风险比分别为5.02(95%CI=3.40~7.40)、5.45(95%CI=3.63~8.18)、4.49(95%CI=3.03~6.66)、4.77(95%CI=3.22~7.06)和4.38(95%CI=2.97~6.47)。此外，在多形性胶质母细胞瘤中也观察到了这些基因的表达模式，这些基因与LGG中的生存时间较短有关。结论：识别与不良预后相关的基因将为改善LGGS患者的进展和生存提供新的生物学机制的洞察力。
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. Patients and Methods: 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. Results: 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. Conclusion: 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.