Kondo Toru
Division of Stem Cell Biology, Institute for Genetic Medicine, Hokkaido University, Kita-15, Nishi-7, Kita-ku, Sapporo, 060-0815, Japan.
Brain Tumor Pathol. 2017 Jan;34(1):1-7. doi: 10.1007/s10014-017-0278-8. Epub 2017 Jan 23.
The application of molecular parameters in the World Health Organization classification of central nervous system tumors has advanced remarkably in this field. Large-scale genomic DNA analyses, including gene expression profiling, genome-wide association studies, and single-nucleotide polymorphism analysis, have revealed differences between tumors with the same pathological features. Because mutated genes and their signaling pathways can be targets for therapy, categorizing tumors by molecular parameters facilitates the selection of optimal therapeutic methods. Many genes are either oncogenes or tumor suppressor genes, and many of them are also involved in normal development, such as neural stem cell maintenance and neural differentiation. Moreover, genetic engineering has enabled the generation of tumors that phenocopy human tumors in mice. Here, I will discuss key molecular parameters, mechanisms of neural differentiation, isocitrate dehydrogenases, 1p36/19q13, and p53 in gliomagenesis. Because future therapeutic methods will be determined by the molecular mechanisms of tumors, identification of new parameters is still needed for further classification of glioma.
分子参数在世界卫生组织中枢神经系统肿瘤分类中的应用在该领域取得了显著进展。大规模基因组DNA分析,包括基因表达谱分析、全基因组关联研究和单核苷酸多态性分析,揭示了具有相同病理特征的肿瘤之间的差异。由于突变基因及其信号通路可作为治疗靶点,通过分子参数对肿瘤进行分类有助于选择最佳治疗方法。许多基因要么是癌基因,要么是肿瘤抑制基因,其中许多还参与正常发育,如神经干细胞维持和神经分化。此外,基因工程已能够在小鼠中生成模拟人类肿瘤的肿瘤。在此,我将讨论胶质瘤发生过程中的关键分子参数、神经分化机制、异柠檬酸脱氢酶、1p36/19q13和p53。由于未来的治疗方法将由肿瘤的分子机制决定,因此仍需要鉴定新的参数以进一步对胶质瘤进行分类。