Shrestha Gajendra, MacNeil Shelley M, McQuerry Jasmine A, Jenkins David F, Sharma Sunil, Bild Andrea H
Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA.
Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA.
Semin Cell Dev Biol. 2016 Oct;58:108-17. doi: 10.1016/j.semcdb.2016.06.012. Epub 2016 Jun 20.
The rise in genomic knowledge over the past decade has revealed the molecular etiology of many diseases, and has identified intricate signaling network activity in human cancers. Genomics provides the opportunity to determine genome structure and capture the activity of thousands of molecular events concurrently, which is important for deciphering highly complex genetic diseases such as cancer. In this review, we focus on genomic efforts directed towards one of cancer's most frequently mutated networks, the RAS pathway. Genomic tools such as gene expression signatures and assessment of mutations across the RAS network enable the capture of RAS signaling complexity. Due to this high level of interaction and cross-talk within the network, efforts to target RAS signaling in the clinic have generally failed, and we currently lack the ability to directly inhibit the RAS protein with high efficacy. We propose that the use of gene expression data can identify effective treatments that broadly inhibit the RAS network as this approach measures pathway activity independent of mutation status or any single mechanism of activation. Here, we review the genomic studies that map the complexity of the RAS network in cancer, and that show how genomic measurements of RAS pathway activation can identify effective RAS inhibition strategies. We also address the challenges and future directions for treating RAS-driven tumors. In summary, genomic assessment of RAS signaling provides a level of complexity necessary to accurately map the network that matches the intricacy of RAS pathway interactions in cancer.
在过去十年中,基因组学知识的增长揭示了许多疾病的分子病因,并确定了人类癌症中复杂的信号网络活动。基因组学为确定基因组结构和同时捕捉数千个分子事件的活动提供了机会,这对于解读像癌症这样高度复杂的遗传疾病至关重要。在本综述中,我们聚焦于针对癌症中最常发生突变的网络之一——RAS 通路的基因组学研究。诸如基因表达特征和对整个 RAS 网络突变情况的评估等基因组学工具,能够捕捉 RAS 信号传导的复杂性。由于该网络内部存在高度的相互作用和信号串扰,临床上针对 RAS 信号传导的靶向治疗努力通常以失败告终,而且我们目前还缺乏高效直接抑制 RAS 蛋白的能力。我们提出,利用基因表达数据能够识别出可广泛抑制 RAS 网络的有效治疗方法,因为这种方法测量的是通路活性,而不依赖于突变状态或任何单一的激活机制。在此,我们综述了描绘癌症中 RAS 网络复杂性的基因组学研究,以及展示 RAS 通路激活的基因组学测量如何能够识别有效 RAS 抑制策略方面的研究。我们还探讨了治疗 RAS 驱动型肿瘤所面临的挑战和未来方向。总之,对 RAS 信号传导的基因组学评估提供了准确描绘该网络所需的复杂性水平,这与癌症中 RAS 通路相互作用的复杂性相匹配。