Introduction: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior.

Areas covered: This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with ‘ovarian cancer’ including ‘proteomics’, ‘proteogenomic’, ‘reverse-phase protein array’, ‘mass spectrometry’, and ‘adaptive response’, were used to search PubMed.

Expert opinion: Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes.

简介：由于相对较低的突变率和较高的拷贝数变异频率，寻找可操作的高级浆液性癌（HGSC）遗传驱动因素是一项艰巨的任务。此外，新兴的研究表明，遗传改变通常在蛋白质水平上表现不佳，从而增加了一层复杂性。随着大规模蛋白质组学技术的改进，蛋白质组学研究有潜力对导致高HGSC行为的途径进行可靠的分析。

涵盖的领域：这篇综述总结了在适当大小的卵巢癌样本集中最新的大规模蛋白质组学发现。使用关键词与“卵巢癌”结合，包括“蛋白质组学”，“蛋白质组学”，“反相蛋白质阵列”，“质谱”和“适应性反应”，来搜索PubMed。

专家意见：HGSC的蛋白质组学分析及其对治疗的适应性反应可以发现新的治疗缺陷，从而减少耐药性的产生并可能改善患者预后。迫切需要更好地了解卵巢癌固有的基因组和表观基因组异质性如何在蛋白质水平上反映出来，以及如何利用这些信息来改善患者的预后。