Suppr超能文献

肿瘤蛋白质组学:当前趋势与未来展望。

Oncoproteomics: current trends and future perspectives.

作者信息

Cho William C S, Cheng Christopher H K

机构信息

Queen Elizabeth Hospital, Department of Clinical Oncology, Kowloon, Hong Kong SAR, PR China.

出版信息

Expert Rev Proteomics. 2007 Jun;4(3):401-10. doi: 10.1586/14789450.4.3.401.

Abstract

Oncoproteomics is the application of proteomics technologies in oncology. Functional proteomics is a promising technique for the rational identification of biomarkers and novel therapeutic targets for cancers. Recent progress in proteomics has opened new avenues for tumor-associated biomarker discovery. With the advent of new and improved proteomics technologies, such as the development of quantitative proteomic methods, high-resolution, -speed and -sensitivity mass spectrometry and protein arrays, as well as advanced bioinformatics for data handling and interpretation, it is now possible to discover biomarkers that can reliably and accurately predict outcomes during cancer management and treatment. However, there are several difficulties in the study of proteins/peptides that are not inherent in the study of nucleic acids. New challenges arise in large-scale proteomic profiling when dealing with complex biological mixtures. Nevertheless, oncoproteomics offers great promise for unveiling the complex molecular events of tumorigenesis, as well as those that control clinically important tumor behaviors, such as metastasis, invasion and resistance to therapy. In this review, the development and advancement of oncoproteomics technologies for cancer research in recent years are expounded.

摘要

肿瘤蛋白质组学是蛋白质组学技术在肿瘤学中的应用。功能蛋白质组学是一种很有前景的技术,可用于合理鉴定癌症的生物标志物和新型治疗靶点。蛋白质组学的最新进展为肿瘤相关生物标志物的发现开辟了新途径。随着新的和改进的蛋白质组学技术的出现,如定量蛋白质组学方法的发展、高分辨率、高速度和高灵敏度的质谱分析以及蛋白质阵列,以及用于数据处理和解释的先进生物信息学,现在有可能发现能够可靠且准确地预测癌症管理和治疗过程中结果的生物标志物。然而,蛋白质/肽的研究存在一些核酸研究中不存在的困难。在处理复杂生物混合物时,大规模蛋白质组分析会出现新的挑战。尽管如此,肿瘤蛋白质组学在揭示肿瘤发生的复杂分子事件以及控制临床重要肿瘤行为(如转移、侵袭和对治疗的抗性)方面具有巨大潜力。在这篇综述中,阐述了近年来用于癌症研究的肿瘤蛋白质组学技术的发展和进步。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验