Department of Neurology and Neuro-Oncology Program, University of California, Los Angeles, California 90095; email:
Annu Rev Pathol. 2014;9:1-25. doi: 10.1146/annurev-pathol-011110-130324. Epub 2013 Aug 5.
Glioblastoma (GBM) is one of the most lethal human cancers. Genomic analyses are defining the molecular architecture of GBM, uncovering relevant subsets of patients whose disease may require different treatments. Many pharmacological targets have been revealed, promising to transform patient care through targeted therapies. However, for most patients, clinical responses to targeted inhibitors are either not apparent or not durable. In this review, we address the challenge of developing more effective, molecularly guided approaches for the treatment of GBM patients. We summarize the current state of knowledge regarding molecular classifiers and examine their benefit for stratifying patients for treatment. We survey the molecular landscape of the disease, discussing the challenges raised by acquired drug resistance. Furthermore, we analyze the biochemical features of GBM, suggesting a next generation of drug targets, and we examine the contribution of tumor heterogeneity and its implications. We conclude with an analysis of the experimental approaches and their potential benefit to patients.
胶质母细胞瘤（GBM）是最致命的人类癌症之一。基因组分析正在定义 GBM 的分子结构，揭示了一些相关的患者亚群，他们的疾病可能需要不同的治疗方法。已经发现了许多药理学靶点，有望通过靶向治疗来改变患者的治疗效果。然而，对于大多数患者来说，针对这些靶点的抑制剂的临床疗效要么不明显，要么不持久。在这篇综述中，我们探讨了为 GBM 患者开发更有效、更具分子指导作用的治疗方法的挑战。我们总结了目前关于分子分类器的知识状态，并研究了它们在为治疗分层患者方面的益处。我们调查了疾病的分子图谱，讨论了获得性耐药所带来的挑战。此外，我们分析了 GBM 的生化特征，提出了下一代药物靶点，并研究了肿瘤异质性及其影响。最后，我们对实验方法进行了分析，并探讨了其对患者的潜在益处。
