Ku Xin, Cai Chunlin, Xu Yan, Chen Su, Zhou Zhenhua, Xiao Jianru, Yan Wei
Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China.
Department of Orthopedic Oncology, Shanghai Changzheng Hospital, The Second Military Medical University, Shanghai 200003, China.
Transl Cancer Res. 2020 Apr;9(4):2390-2401. doi: 10.21037/tcr.2020.03.41.
Bone metastasis is the third most common metastatic cancers worldwide. It is a group of highly heterogeneous diseases with various potential cancer primaries. Among them, one third was diagnosed as bone metastasis of unknown primary (BMUP) due to lack of indication for the primary tumor even after comprehensive examinations. Thus, the prognosis of BMUP is often very poor since the treatment was largely empirical and untargeted. To assist identification of the primary tumor, a series of molecular markers including traditional tissue-specific histochemistry as well as gene and mRNA markers were developed with moderate to good sensitivity and specificity.
In this paper, we carried out a comprehensive expression profiling for fresh-frozen tissue samples of bone metastasis from lung, prostate and liver cancers using high resolution, data-independent-acquisition mass spectrometry (DIA-MS). The proteome variation was analyzed and protein classifiers were prioritized.
Over 6,000 proteins were quantified from 18 samples, which, to the best of our knowledge, was never achieved before. Further statistical analysis and bioinformatics data mining revealed 4 significant proteins (RFIP1, CK15, ESYT2, and MAL2) with excellent discriminating capabilities with AUCs higher than 0.8.
The comprehensive proteome map of bone metastases will complement available genomic and transcriptomic data. Newly discovered protein classifiers will expand current diagnostic arsenal for tissue of origin studies in BMUP. Furthermore, the proteome map generated in this study by DIA-MS allows future data re-mining as our knowledge advances to assist investigation of bone metastasis and progression of tumors as well as the development of diagnostic tools and prognosis management for BMUPs.
骨转移是全球第三常见的转移性癌症。它是一组高度异质性疾病，有多种潜在的原发癌症。其中，三分之一被诊断为原发灶不明的骨转移（BMUP），因为即使经过全面检查也缺乏原发肿瘤的指征。因此，BMUP的预后通常很差，因为治疗很大程度上是经验性的且无针对性。为了辅助识别原发肿瘤，开发了一系列分子标志物，包括传统的组织特异性组织化学以及基因和mRNA标志物，其敏感性和特异性从中等到良好。
在本文中，我们使用高分辨率、数据非依赖采集质谱（DIA-MS）对来自肺癌、前列腺癌和肝癌的骨转移新鲜冷冻组织样本进行了全面的表达谱分析。分析了蛋白质组变异并对蛋白质分类器进行了优先排序。
从18个样本中定量了超过6000种蛋白质，据我们所知，这是以前从未实现过的。进一步的统计分析和生物信息学数据挖掘揭示了4种具有优异鉴别能力的显著蛋白质（RFIP1、CK15、ESYT2和MAL2），其曲线下面积（AUC）高于0.8。
骨转移的全面蛋白质组图谱将补充现有的基因组和转录组数据。新发现的蛋白质分类器将扩大当前用于BMUP起源组织研究的诊断手段。此外，本研究通过DIA-MS生成的蛋白质组图谱允许随着我们知识的进步进行未来的数据重新挖掘，以辅助研究骨转移和肿瘤进展以及BMUP的诊断工具开发和预后管理。
