Bhawal Ruchika, Oberg Ann L, Zhang Sheng, Kohli Manish
Proteomics and Metabolomics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY 14853, USA.
Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.
Cancers (Basel). 2020 Aug 27;12(9):2428. doi: 10.3390/cancers12092428.
Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.
血液是一种易于获取的生物流体，含有大量重要的蛋白质、核酸和代谢物，可作为包括癌症在内的疾病的临床诊断工具。与目前利用液体活检检测循环游离细胞和基于细胞的肿瘤核酸来发现癌症生物标志物的努力一样，循环蛋白质组在临床癌症生物标志物应用方面尚未得到充分探索。对人血清/血浆进行全面的蛋白质组分析，获得高质量的数据并进行有说服力的解读，尽管需要应对一些挑战，但有可能为理解疾病机制提供机会。血清/血浆蛋白质组生物标志物的丰度极低，而且由于癌症的异质性，涉及的复杂性很高，因此迫切需要开发灵敏且特异的蛋白质组学技术和分析平台。迄今为止，基于液相色谱质谱（LC-MS）的定量蛋白质组学一直是在血清/血浆中发现新的潜在癌症生物标志物的主要分析流程。本综述将总结血清蛋白质组学在临床应用中的机会；血清/血浆中新型生物标志物发现面临的挑战；以及癌症研究中当前的蛋白质组学策略，这些策略将血清/血浆蛋白质组学应用于临床预后、预测和诊断应用，以及监测治疗后的微小残留病。我们将重点介绍基于质谱的蛋白质组学技术在适当的样本采集、处理一致性、研究设计和数据分析方面的一些最新进展，重点关注这些综合流程如何识别用于临床应用的新型潜在癌症生物标志物。
