Department of Radiation Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Tex, USA.
Brain Pathol. 2011 Jan;21(1):88-95. doi: 10.1111/j.1750-3639.2010.00456.x.
The diffuse gliomas are a heterogeneous group of malignancies with highly variable outcomes and diagnosis is largely based on the histological appearance of the tumors. Tumor classification according to cello type and grade provides some prognostic information. However, the diversity of gliomas, within tumor type and grade categories, has made prognostic determinations based purely on clinicopathologic variables difficult. There is an increasing body of data suggesting a significant amount of molecular diversity accounts for the heterogeneity of clinical observations, such as response to treatment and time to progression. The last decade has witnessed an explosive advance in our knowledge of the molecular genetics of brain tumors, due in large part to the availability of high-throughput profiling techniques, including new sequencing methodologies as well as multidimensional profiling by the Cancer Genome Atlas project. The large amount of data generated by these efforts has enabled the identification of prognostic and predictive factors and helping to identify pathways that are driving tumor growth. Identification of biomarkers, especially when coupled to clinical trials of newer targeted therapies, will enable better patient stratification and individualization of treatment.
弥漫性神经胶质瘤是一组异质性恶性肿瘤，其预后差异很大，诊断主要基于肿瘤的组织学表现。根据细胞类型和分级对肿瘤进行分类可以提供一些预后信息。然而，神经胶质瘤在肿瘤类型和分级内的多样性，使得仅基于临床病理变量进行预后判断变得困难。越来越多的数据表明，大量的分子多样性解释了临床观察结果的异质性，例如对治疗的反应和进展时间。过去十年中，由于高通量分析技术的出现，包括新的测序方法以及癌症基因组图谱项目的多维分析，我们对脑肿瘤的分子遗传学有了突飞猛进的了解。这些努力产生的大量数据使我们能够识别预后和预测因素，并有助于确定驱动肿瘤生长的途径。生物标志物的识别，特别是与新的靶向治疗临床试验相结合，将能够更好地对患者进行分层和个体化治疗。
