Kotelnikova Ekaterina A, Pyatnitskiy Mikhail, Paleeva Anna, Kremenetskaya Olga, Vinogradov Dmitriy
Personal Biomedicine, Moscow, Russia.
A. A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia.
Oncotarget. 2016 Aug 9;7(32):52493-52516. doi: 10.18632/oncotarget.9370.
Nowadays, the personalized approach to health care and cancer care in particular is becoming more and more popular and is taking an important place in the translational medicine paradigm. In some cases, detection of the patient-specific individual mutations that point to a targeted therapy has already become a routine practice for clinical oncologists. Wider panels of genetic markers are also on the market which cover a greater number of possible oncogenes including those with lower reliability of resulting medical conclusions. In light of the large availability of high-throughput technologies, it is very tempting to use complete patient-specific New Generation Sequencing (NGS) or other "omics" data for cancer treatment guidance. However, there are still no gold standard methods and protocols to evaluate them. Here we will discuss the clinical utility of each of the data types and describe a systems biology approach adapted for single patient measurements. We will try to summarize the current state of the field focusing on the clinically relevant case-studies and practical aspects of data processing.
如今,个性化医疗保健方法,尤其是癌症护理,正变得越来越流行,并在转化医学范式中占据重要地位。在某些情况下,检测指向靶向治疗的患者特异性个体突变已成为临床肿瘤学家的常规做法。市面上也有更广泛的基因标记物检测板,其涵盖了更多可能的致癌基因,包括那些得出医学结论可靠性较低的基因。鉴于高通量技术的广泛应用,利用完整的患者特异性新一代测序(NGS)或其他“组学”数据来指导癌症治疗极具吸引力。然而,目前仍没有评估这些数据的金标准方法和方案。在此,我们将讨论每种数据类型的临床效用,并描述一种适用于单患者测量的系统生物学方法。我们将尝试总结该领域的现状,重点关注临床相关的案例研究和数据处理的实际方面。