Introduction: Discovery proteomics for cancer research generates complex datasets of diagnostic, prognostic, and therapeutic significance in human cancer. With the advent of high-resolution mass spectrometers, able to identify thousands of proteins in complex biological samples, only the application of bioinformatics can lead to the interpretation of data which can be relevant for cancer research.

Areas covered: Here, we give an overview of the current bioinformatic tools used in cancer proteomics. Moreover, we describe their applications in cancer proteomics studies of cell lines, serum, and tissues, highlighting recent results and critically evaluating their outcomes.

Expert opinion: The use of bioinformatic tools is a fundamental step in order to manage the large amount of proteins (from hundreds to thousands) that can be identified and quantified in a cancer biological samples by proteomics. To handle this challenge and obtain useful data for translational medicine, it is important the combined use of different bioinformatic tools. Moreover, a particular attention to the global experimental design, and the integration of multidisciplinary skills are essential for best setting of tool parameters and best interpretation of bioinformatics output.

简介：用于癌症研究的发现蛋白质组学生成了对人类癌症具有诊断，预后和治疗意义的复杂数据集。随着高分辨率质谱仪的出现，能够识别复杂生物样品中的数千种蛋白质，只有生物信息学的应用才能导致对可能与癌症研究相关的数据进行解释。

涵盖的领域：在这里，我们概述了癌症蛋白质组学中使用的当前生物信息学工具。此外，我们描述了它们在细胞系，血清和组织的癌症蛋白质组学研究中的应用，重点介绍了最近的结果并严格评估了它们的结果。

专家意见：使用生物信息学工具是管理蛋白质组学可以识别和定量的大量蛋白质（数百种至数千种）的基本步骤。为了应对这一挑战并获得转化医学的有用数据，重要的是结合使用不同的生物信息学工具。此外，对全局实验设计的特别关注以及多学科技能的整合对于最佳设置工具参数和最佳解释生物信息学输出至关重要。