I.M. Sechenov First Moscow State Medical University, Moscow, Russia; Omicsway Corp., Walnut, CA, USA; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.
I.M. Sechenov First Moscow State Medical University, Moscow, Russia.
Semin Cancer Biol. 2018 Dec;53:110-124. doi: 10.1016/j.semcancer.2018.06.003. Epub 2018 Jun 20.
Anticancer target drugs (ATDs) specifically bind and inhibit molecular targets that play important roles in cancer development and progression, being deeply implicated in intracellular signaling pathways. To date, hundreds of different ATDs were approved for clinical use in the different countries. Compared to previous chemotherapy treatments, ATDs often demonstrate reduced side effects and increased efficiency, but also have higher costs. However, the efficiency of ATDs for the advanced stage tumors is still insufficient. Different ATDs have different mechanisms of action and are effective in different cohorts of patients. Personalized approaches are therefore needed to select the best ATD candidates for the individual patients. In this review, we focus on a new generation of biomarkers - molecular pathway activation - and on their applications for predicting individual tumor response to ATDs. The success in high throughput gene expression profiling and emergence of novel bioinformatic tools reinforced quick development of pathway related field of molecular biomedicine. The ability to quantitatively measure degree of a pathway activation using gene expression data has revolutionized this field and made the corresponding analysis quick, robust and inexpensive. This success was further enhanced by using machine learning algorithms for selection of the best biomarkers. We review here the current progress in translating these studies to clinical oncology and patient-oriented adjustment of cancer therapy.
抗癌靶标药物（ATDs）特异性结合并抑制在癌症发展和进展中起重要作用的分子靶标，这些靶标与细胞内信号通路密切相关。迄今为止，已有数百种不同的 ATD 在不同国家获得批准用于临床应用。与以前的化疗治疗相比，ATDs 通常表现出较低的副作用和较高的效率，但成本也更高。然而，ATDs 对晚期肿瘤的疗效仍然不足。不同的 ATD 具有不同的作用机制，对不同患者群体有效。因此，需要采用个性化方法为个体患者选择最佳的 ATD 候选药物。在这篇综述中，我们重点介绍了新一代生物标志物——分子通路激活——及其在预测个体肿瘤对 ATD 反应方面的应用。高通量基因表达谱分析的成功以及新型生物信息学工具的出现，推动了分子生物医学领域相关领域的快速发展。使用基因表达数据定量测量通路激活程度的能力彻底改变了这一领域，使相应的分析变得快速、稳健和廉价。通过使用机器学习算法选择最佳生物标志物，这一成功进一步得到了增强。我们在这里回顾了将这些研究转化为临床肿瘤学以及面向患者的癌症治疗调整的最新进展。
