Van Neste Leander, Van Criekinge Wim
Department of Pathology, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands,
Cell Oncol (Dordr). 2015 Feb;38(1):29-37. doi: 10.1007/s13402-014-0195-3. Epub 2014 Sep 10.
The medical landscape is evolving at a rapid pace, creating the opportunity for more personalized patient treatment and shifting the way healthcare is approached and thought about. With the availability of (epi)genome-wide, transcriptomic and proteogenomic profiling techniques detailed characterization of a disease at the level of the individual is now possible, offering the opportunity for truly tailored approaches for treatment and patient care. While improvements are still expected, the techniques and the basic analytical tools have reached a state that these can be efficiently deployed in both routine research and clinical practice. Still, some major challenges remain. Notably, holistic approaches, integrating data from several sources, e.g. genomic and epigenomic, will increase the understanding of the underlying biological concepts and provide insight into the causes, effects and effective solutions. However, creating and validating such a knowledge base, potentially for different levels of expertise, and integrating several data points into meaningful information is not trivial.
医学领域正在迅速发展,为更个性化的患者治疗创造了机会,并改变了医疗保健的方式和人们对其的思考方式。随着全基因组、转录组和蛋白质基因组分析技术的出现,现在有可能在个体层面上对疾病进行详细表征,从而为真正量身定制的治疗方法和患者护理提供了机会。虽然仍有望取得改进,但这些技术和基本分析工具已经发展到可以在常规研究和临床实践中有效应用的阶段。然而,一些重大挑战仍然存在。值得注意的是,整合来自多个来源(如基因组和表观基因组)的数据的整体方法,将增进对潜在生物学概念的理解,并深入了解病因、影响和有效解决方案。然而,创建和验证这样一个知识库(可能针对不同专业水平),并将多个数据点整合为有意义的信息并非易事。