The prominent characteristics of mitochondria are highly dynamic and regulatory, which have crucial roles in cell metabolism, biosynthetic, senescence, apoptosis, and signaling pathways. Mitochondrial dysfunction might lead to multiple serious diseases, including cancer. Therefore, identification of mitochondrial proteins in cancer could provide a global view of tumorigenesis and progression. Mass spectrometry‐based quantitative mitochondrial proteomics fulfils this task by enabling systems‐wide, accurate, and quantitative analysis of mitochondrial protein abundance, and mitochondrial protein posttranslational modifications (PTMs). Multiple quantitative proteomics techniques, including isotope‐coded affinity tag, stable isotope labeling with amino acids in cell culture, isobaric tags for relative and absolute quantification, tandem mass tags, and label‐free quantification, in combination with different PTM‐peptide enrichment methods such as TiO₂ enrichment of tryptic phosphopeptides and antibody enrichment of other PTM‐peptides, increase flexibility for researchers to study mitochondrial proteomes. This article reviews isolation and purification of mitochondria, quantitative mitochondrial proteomics, quantitative mitochondrial phosphoproteomics, mitochondrial protein‐involved signaling pathway networks, mitochondrial phosphoprotein‐involved signaling pathway networks, integration of mitochondrial proteomic and phosphoproteomic data with whole tissue proteomic and transcriptomic data and clinical information in ovarian cancers (OC) to in‐depth understand its molecular mechanisms, and discover effective mitochondrial biomarkers and therapeutic targets for predictive, preventive, and personalized treatment of OC. This proof‐of‐principle model about OC mitochondrial proteomics is easily implementable to other cancer types. © 2020 John Wiley & Sons Ltd. Mass Spec Rev

中文翻译：

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人类卵巢癌中基于质谱的线粒体蛋白质组学。

线粒体的突出特点是高度动态和调节，在细胞代谢、生物合成、衰老、凋亡和信号通路中起着至关重要的作用。线粒体功能障碍可能导致多种严重疾病，包括癌症。因此，癌症中线粒体蛋白的鉴定可以提供肿瘤发生和进展的全局视图。基于质谱的定量线粒体蛋白质组学通过对线粒体蛋白质丰度和线粒体蛋白质翻译后修饰 (PTM) 进行全系统、准确和定量分析来完成这项任务。多种定量蛋白质组学技术，包括同位素编码的亲和标记、细胞培养中氨基酸的稳定同位素标记、用于相对和绝对定量的同量异位标记、串联质量标记、₂胰蛋白酶磷酸肽的富集和其他 PTM 肽的抗体富集，增加了研究人员研究线粒体蛋白质组的灵活性。本文综述了线粒体的分离和纯化、定量线粒体蛋白质组学、定量线粒体磷酸化蛋白质组学、线粒体蛋白相关信号通路网络、线粒体磷蛋白相关信号通路网络、线粒体蛋白质组学和磷酸化蛋白质组学数据与全组织蛋白质组学和临床信息转录组学数据的整合在卵巢癌 (OC) 中深入了解其分子机制，并发现有效的线粒体生物标志物和治疗靶点，用于 OC 的预测、预防和个性化治疗。这种关于 OC 线粒体蛋白质组学的原理验证模型很容易应用于其他癌症类型。© 2020 John Wiley & Sons Ltd. 质谱修订版