Centre for Individualized Medicine, Department of Pediatrics, Faculty of Health Sciences, Linköping University, Linköping, Sweden.
J Intern Med. 2016 Mar;279(3):229-40. doi: 10.1111/joim.12412. Epub 2015 Aug 19.
Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide a brief introduction to systems medicine and discuss how it may contribute to the clinical implementation of individualized treatment, using clinically relevant examples.
许多常见疾病患者对治疗没有反应。这是现代医疗保健面临的一个关键挑战,它不仅给患者带来痛苦,还造成巨大的经济负担。治疗反应缺乏的一个重要原因是,常见疾病与数千个基因之间相互作用的改变有关,而这些改变在对特定治疗有反应和无反应的患者亚组之间存在组合差异。最近在哮喘、糖尿病、自身免疫性疾病和癌症中已经描述了这种亚组,甚至是不同的疾病实体。高通量技术(组学)允许识别和描述这些亚组或实体。这可能具有重要的临床意义,例如确定个体化医学的诊断标志物,以及为那些对现有药物没有反应的患者确定新的治疗靶点。例如,全基因组测序可以更准确地指导神经发育疾病的治疗,或者确定专门针对癌症中突变基因的药物。2015 年发表的一项研究表明,28%的肝细胞癌含有潜在可被美国食品和药物管理局批准的药物靶向的突变基因。一项详细描述的转化研究表明,如何通过综合组学、计算、功能和临床研究,在过敏中鉴定和验证新的诊断和治疗候选基因。另一个重要的临床意义是确定预测性和预防性医学的潜在诊断标志物和治疗靶点。通过结合计算和实验方法,可以鉴定早期疾病调节剂,并有可能在疾病出现症状之前用于预测和治疗疾病。系统医学是一个新兴学科,它可以通过将组学与计算、功能和临床研究相结合,为这些发展做出贡献。本文的目的是简要介绍系统医学,并讨论如何使用临床相关实例为个体化治疗的临床实施做出贡献。