Latosinska Agnieszka, Frantzi Maria, Vlahou Antonia, Merseburger Axel S, Mischak Harald
Mosaiques Diagnostics GmbH, Hannover, Germany.
Biotechnology Division, Biomedical Research Foundation, Academy of Athens, Athens, Greece.
Proteomics Clin Appl. 2018 Mar;12(2). doi: 10.1002/prca.201700074. Epub 2017 Oct 25.
Precision medicine can improve patient management by guiding therapeutic decision based on molecular characteristics. The concept has been extensively addressed through the application of -omics-based approaches. Proteomics attract high interest, as proteins reflect a "real-time" dynamic molecular phenotype. Focusing on proteomics applications for personalized medicine, a literature search was conducted to cover: a) disease prevention, b) monitoring/ prediction of treatment response, c) stratification to guide intervention, and d) identification of drug targets. The review indicates the potential of proteomics for personalized medicine by also highlighting multiple challenges to be addressed prior to actual implementation. In oncology, particularly bladder cancer, application of precision medicine appears especially promising. The high heterogeneity and recurrence rates together with the limited treatment options, suggest that earlier and more efficient intervention, continuous monitoring, and the development of alternative therapies could be accomplished by applying proteomics-guided personalized approaches. This notion is backed by studies presenting biomarkers that are of value in patient stratification and prognosis, and by recent studies demonstrating the identification of promising therapeutic targets. Herein, we aim to present an approach whereby combining the knowledge on biomarkers and therapeutic targets in bladder cancer could serve as basis towards proteomics-guided personalized patient management.
精准医学可以通过基于分子特征指导治疗决策来改善患者管理。这一概念已通过基于组学方法的应用得到广泛探讨。蛋白质组学备受关注，因为蛋白质反映了一种“实时”动态分子表型。围绕蛋白质组学在个性化医疗中的应用，我们进行了文献检索，涵盖以下方面：a）疾病预防，b）治疗反应的监测/预测，c）指导干预的分层，以及d）药物靶点的识别。该综述通过强调在实际实施之前需要解决的多重挑战，表明了蛋白质组学在个性化医疗中的潜力。在肿瘤学领域，尤其是膀胱癌，精准医学的应用似乎特别有前景。高度的异质性和复发率以及有限的治疗选择表明，应用蛋白质组学指导的个性化方法可以实现更早、更有效的干预、持续监测以及替代疗法的开发。这一观点得到了一些研究的支持，这些研究提出了在患者分层和预后方面有价值的生物标志物，以及最近一些证明识别出有前景的治疗靶点的研究。在此，我们旨在提出一种方法，即结合膀胱癌生物标志物和治疗靶点的知识，可为蛋白质组学指导的个性化患者管理奠定基础。
