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新兴分子技术在多形性胶质母细胞瘤中的应用。

Applications of emerging molecular technologies in glioblastoma multiforme.

作者信息

Kumar Hari R, Zhong Xiaoling, Sandoval John A, Hickey Robert J, Malkas Linda H

机构信息

Department of Surgery, Indiana University School of Medicine, 545 Barnhill Drive, Emerson Hall Room 202, Indianapolis, IN 46202, USA.

出版信息

Expert Rev Neurother. 2008 Oct;8(10):1497-506. doi: 10.1586/14737175.8.10.1497.

Abstract

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. Median survival from the time of diagnosis is less than a year, with less than 5% of patients surviving 5 years. These tumors are thought to arise through two different pathways. Primary GBMs represent de novo tumors, while secondary GBMs represent the malignant progression of lower-grade astrocytomas. Moreover, despite improvements in deciphering the complex biology of these tumors, the overall prognosis has not changed in the past three decades. The hope for improving the outlook for these glial-based malignancies is centered on the successful clinical application of current high-throughput technologies. For example, the complete sequencing of the human genome has brought both genomics and proteomics to the forefront of cancer research as a powerful approach to systematically identify large volumes of data that can be utilized to study the molecular and cellular basis of oncology. The organization of these data into a comprehensive view of tumor growth and progression translates into a unique opportunity to diagnose and treat cancer patients. In this review, we summarize current genomic and proteomic alterations associated with GBM and how these modalities may ultimately impact treatment and survival.

摘要

多形性胶质母细胞瘤(GBM)是成人中最常见的原发性脑肿瘤。从诊断时起的中位生存期不到一年,不到5%的患者能存活5年。这些肿瘤被认为通过两种不同的途径产生。原发性GBM代表新发肿瘤,而继发性GBM代表低级别星形细胞瘤的恶性进展。此外,尽管在解读这些肿瘤的复杂生物学方面有所进展,但在过去三十年中总体预后并未改变。改善这些基于胶质细胞的恶性肿瘤预后的希望集中在当前高通量技术的成功临床应用上。例如,人类基因组的完整测序已将基因组学和蛋白质组学作为一种强大的方法推到癌症研究的前沿,该方法可系统地识别大量数据,用于研究肿瘤学的分子和细胞基础。将这些数据整理成肿瘤生长和进展的全面视图转化为诊断和治疗癌症患者的独特机会。在本综述中,我们总结了与GBM相关的当前基因组和蛋白质组改变,以及这些模式最终可能如何影响治疗和生存。

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