Department of Neurology, David Geffen UCLA School of Medicine, Los Angeles, California 90095-1732, USA.
Clin Cancer Res. 2011 Jan 1;17(1):6-11. doi: 10.1158/1078-0432.CCR-09-2268.
Cancer is a molecularly complex, genomically unstable disease. Selection for drug-resistant mutations, activation of feedback loops, and upregulation of cross-talk pathways provide escape routes by which cancer cells maintain signal flux through critical downstream effectors to promote therapeutic resistance. Attempts to target signal transduction pathways in cancer may therefore require investigators to aim at a moving target. We need to anticipate the routes of resistance to guide the selection of drugs that will lead to durable therapeutic response. In this New Strategies article, we discuss the challenges imposed by the complexity and adaptive capacity of cancer and suggest potential new diagnostic strategies to more effectively guide targeted cancer therapy. We focus on glioblastoma, the most common malignant primary brain tumor of adults. Glioblastoma is a model for a pathway-driven, molecularly heterogeneous cancer for which new genomic insights obtained through The Cancer Genome Atlas are ripe for integration with functional biology and incorporation into new molecular diagnostic assays.
癌症是一种分子结构复杂、基因组不稳定的疾病。药物耐药性突变的选择、反馈回路的激活以及交叉对话途径的上调,为癌细胞通过关键下游效应物维持信号流提供了逃逸途径,从而促进了治疗耐药性。因此,靶向癌症信号转导途径的尝试可能需要研究人员将目标瞄准移动的目标。我们需要预测耐药途径,以指导选择能够导致持久治疗反应的药物。在这篇新策略文章中,我们讨论了癌症的复杂性和适应能力所带来的挑战,并提出了潜在的新诊断策略,以更有效地指导靶向癌症治疗。我们专注于胶质母细胞瘤,这是成人中最常见的恶性原发性脑肿瘤。胶质母细胞瘤是一种通路驱动的、分子异质性的癌症模型,通过癌症基因组图谱获得的新基因组见解已经成熟,可以与功能生物学相结合,并纳入新的分子诊断检测。