通过质谱分析、蛋白质组学和当前生物信息学工具加速乳腺癌生物标志物的发现

Maritess D Cation, Maria Cristina Ramos
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引用次数: 1

摘要

在全球范围内,我们可以继续观察到乳腺癌患病率的上升。世界卫生组织在2021年登记了60万例乳腺癌死亡病例,并估计在未来10年,每8名妇女中就有1名被诊断患有乳腺癌。研究已经发现了蛋白质在影响乳腺癌的途径中的作用,但还没有发现一种潜在的生物标志物,对所有类型的乳腺癌都有效,尤其是对三阴性乳腺癌。检测和治疗乳腺癌仍然是一项挑战,特别是如果在晚期无法治愈的阶段发现。因此,蛋白质组学成为筛选乳腺癌诊断、治疗和疾病控制的新蛋白质生物标志物的实用方法。蛋白质组学涵盖了整个蛋白质的研究,通过质谱法和各种生物信息学工具的进步,蛋白质组学的修饰一直引领着乳腺癌生物标志物发现的竞争。这两种方法的结合为深入、全面和高吞吐量的研究提供了最快但最简单的方法。这篇综述文章将概述这些蛋白质组学研究的趋势在线工具,同时引用它们与已知临床乳腺癌生物标志物的应用实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accelerating Breast Cancer Biomarker Discovery by Mass Spectrometry Proteomics and Current Bioinformatics Tools
Across the globe, we can continue to observe a rise in the prevalence of breast cancer. The World Health Organization registered 600,000 cases of death due to breast cancer in 2021 and estimated that there would be 1 in every 8 women diagnosed with breast cancer in the next 10 years. Studies have discovered the role of proteins in the pathways that affect breast cancer but have not found a potential biomarker effective for all types, especially for triple-negative breast cancer. It remains a challenge to detect and treat breast cancer, especially if found in the later uncurable stage. With this, proteomics becomes a practical approach to screening new protein biomarkers for breast cancer diagnosis, therapy, and disease control. Proteomics covers the study of the entire protein, and its modification has been leading the race in breast cancer biomarker discovery made possible through the advancement of mass spectrometry and various bioinformatics tools. The combination has brought novel information being the fastest yet simplest approach for deep, comprehensive, and high throughput approach. This review article will give an overview of these trending online tools for proteomics research while citing examples of their utility with known clinical breast cancer biomarkers.
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