VIB Center for Inflammation Research, Ghent, Belgium.
Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium.
Cell Death Differ. 2019 Jan;26(1):83-98. doi: 10.1038/s41418-018-0196-2. Epub 2018 Sep 10.
Current clinical diagnosis is typically based on a combination of approaches including clinical examination of the patient, clinical experience, physiologic and/or genetic parameters, high-tech diagnostic medical imaging, and an extended list of laboratory values mostly determined in biofluids such as blood and urine. One could consider this as precision medicine v1.0. However, recent advances in technology and better understanding of molecular mechanisms underlying disease will allow us to better characterize patients in the future. These improvements will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses. Treatments will be able to be chosen more "precisely", resulting in more appropriate therapy, precision medicine v2.0. In this review, we will reflect on the potential added value of recent advances in technology and a better molecular understanding of necrosis and inflammation for improving diagnosis and treatment of critically ill patients. We give a brief overview on the mutual interplay between necrosis and inflammation, which are two crucial detrimental factors in organ and/or systemic dysfunction. One of the challenges for the future will thus be the cellular and molecular profiling of necroinflammation in biofluids. The huge amount of data generated by profiling biomolecules and single cells through, for example, different omic-approaches is needed for data mining methods to allow patient-clustering and identify novel biomarkers. The real-time monitoring of biomarkers will allow continuous (re)evaluation of treatment strategies using machine learning models. Ultimately, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics.
目前的临床诊断通常基于多种方法的结合,包括对患者的临床检查、临床经验、生理和/或遗传参数、高科技诊断医学成像以及大多数在生物流体(如血液和尿液)中确定的实验室值的扩展列表。人们可以将其视为 1.0 版精准医学。然而,技术的最新进展和对疾病潜在分子机制的更好理解将使我们能够在未来更好地对患者进行特征描述。这些改进将使我们能够区分具有相似临床表现但具有不同细胞和分子反应的患者。治疗将能够更“精确”地选择,从而实现更合适的治疗,即 2.0 版精准医学。在这篇综述中,我们将反思技术最新进展和对坏死和炎症的更好分子理解为改善危重病患者诊断和治疗带来的潜在附加值。我们简要概述了坏死和炎症之间的相互作用,这两者是器官和/或全身功能障碍的两个关键有害因素。因此,未来的挑战之一将是在生物流体中对坏死炎症进行细胞和分子分析。通过不同的组学方法对生物分子和单细胞进行分析所产生的大量数据需要数据挖掘方法来允许患者聚类并识别新的生物标志物。对生物标志物的实时监测将允许使用机器学习模型对治疗策略进行持续(重新)评估。最终,我们也许能够提供专门针对个体患者分子构成的精准治疗,这在癌症治疗中已经开始实施。