Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I of Rome, Rome, Italy.
Institute for System Analysis and Computer Science (IASI), National Research Council, Rome, Italy.
NPJ Syst Biol Appl. 2020 May 7;6(1):13. doi: 10.1038/s41540-020-0133-0.
Up to date, screening for prostate cancer (PCa) remains one of the most appealing but also a very controversial topics in the urological community. PCa is the second most common cancer in men worldwide and it is universally acknowledged as a complex disease, with a multi-factorial etiology. The pathway of PCa diagnosis has changed dramatically in the last few years, with the multiparametric magnetic resonance (mpMRI) playing a starring role with the introduction of the "MRI Pathway". In this scenario the basic tenet of network medicine (NM) that sees the disease as perturbation of a network of interconnected molecules and pathways, seems to fit perfectly with the challenges that PCa early detection must face to advance towards a more reliable technique. Integration of tests on body fluids, tissue samples, grading/staging classification, physiological parameters, MR multiparametric imaging and molecular profiling technologies must be integrated in a broader vision of "disease" and its complexity with a focus on early signs. PCa screening research can greatly benefit from NM vision since it provides a sound interpretation of data and a common language, facilitating exchange of ideas between clinicians and data analysts for exploring new research pathways in a rational, highly reliable, and reproducible way.
目前,前列腺癌(PCa)的筛查仍然是泌尿外科领域最引人关注但也极具争议的话题之一。PCa 是全球男性第二大常见癌症,被普遍认为是一种复杂的疾病,具有多因素的病因。PCa 的诊断途径在过去几年发生了巨大变化,随着“MRI 路径”的引入,多参数磁共振(mpMRI)发挥了重要作用。在这种情况下,网络医学(NM)的基本原则认为疾病是相互关联的分子和途径网络的扰动,这似乎与 PCa 早期检测必须面对的挑战非常吻合,以推进更可靠的技术。必须将体液检测、组织样本、分级/分期分类、生理参数、MR 多参数成像和分子分析技术整合到“疾病”及其复杂性的更广泛视野中,并关注早期迹象。PCa 筛查研究可以从 NM 视角中受益,因为它为数据提供了合理的解释和通用语言,促进了临床医生和数据分析人员之间的思想交流,以合理、高度可靠和可重复的方式探索新的研究途径。