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膀胱癌精准医学的蛋白质组学分析:忙碌的泌尿科医生的综述。

Proteomic profiling of bladder cancer for precision medicine in the clinical setting: A review for the busy urologist.

机构信息

Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA.

出版信息

Investig Clin Urol. 2020 Nov;61(6):539-554. doi: 10.4111/icu.20200317.

Abstract

At present, proteomic methods have successfully identified potential biomarkers of urological malignancies, such as prostate cancer (PC), bladder cancer (BC), and renal cell carcinoma (RCC), reflecting different numbers of key cellular processes, including extracellular environment modification, invasion and metastasis, chemotaxis, differentiation, metabolite transport, and apoptosis. The potential application of proteomics in the detection of clinical markers of urological malignancies can help improve patient assessment through early cancer detection, prognosis, and treatment response prediction. A variety of proteomic studies have already been carried out to find prognostic BC biomarkers, and a large number of potential biomarkers have been reported. It is worth noting that proteomics research has not been applied to the study of predictive markers; this may be due to the incompatibility between the number of measured variables and the available sample size, which has become particularly evident in the study of therapeutic response. On the contrary, prognostic correlation is more common, which is also reflected in existing research. We are now entering an era of clinical proteomics. Driven by proteomic-based workflows, computing tools, and the applicability of cross-correlation of proteomic data, it is now feasible to use proteomic analysis to support personalized medicine. In this paper, we will summarize the current emerging technologies for advanced discovery, targeted proteomics, and proteomic applications in BC, particularly in discovery of human-based biomarkers.

摘要

目前,蛋白质组学方法已成功鉴定出泌尿外科恶性肿瘤(如前列腺癌(PC)、膀胱癌(BC)和肾细胞癌(RCC))的潜在生物标志物,反映了不同数量的关键细胞过程,包括细胞外环境修饰、侵袭和转移、趋化作用、分化、代谢物转运和细胞凋亡。蛋白质组学在泌尿外科恶性肿瘤临床标志物检测中的潜在应用有助于通过早期癌症检测、预后和治疗反应预测来改善患者评估。已经进行了各种蛋白质组学研究来寻找膀胱癌的预后生物标志物,并且已经报道了大量潜在的生物标志物。值得注意的是,蛋白质组学研究尚未应用于预测标志物的研究;这可能是由于测量变量的数量与可用样本量之间的不兼容所致,在治疗反应的研究中尤其明显。相反,预后相关性更为常见,这也反映在现有的研究中。我们现在正进入临床蛋白质组学时代。受基于蛋白质组学的工作流程、计算工具以及蛋白质组学数据交叉相关性的适用性的推动,现在可以使用蛋白质组学分析来支持个性化医疗。本文将总结 BC 中先进发现、靶向蛋白质组学和蛋白质组学应用的新兴技术,特别是在基于人类的生物标志物的发现方面。

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