Phosphorylation regulates the functions of proteins and aberrant phosphorylation often leads to a variety of diseases, including cancers. Extracellular vesicles (EVs) are important messengers in the microenvironment and their proteome contributes to cancer genesis and metastasis, while the kinases that driving EVs proteins' phosphorylation are less known. Clinical tissue samples from 13 patients with non-small-cell lung cancer (NSCLC) were utilized to isolate cancer EVs and adjacent normal EVs. Through quantitative phosphoproteomics analysis, 2473 phosphorylation sites on 1567 proteins were successfully identified and quantified. Accordingly, 152 kinases were identified, and 25 of them were differentially expressed. Based on Tied Diffusion through Interacting Events (TieDIE) algorithm, we integrated genomic and transcriptomic data sets of NSCLC from TCGA with our phosphoproteome data set to construct signaling networks. Through database integration and multiomics enrichment analysis, a compact network of 234 nodes with 1599 edges was constructed, which consisted of 34 transcription factors, 33 kinases, 63 aberrant genes, and 172 linking proteins. Rarely studied phosphorylation sites were specifically enriched. Key phosphoproteins of network nodes were validated in patients' EVs, including MAPK6^S189, IKBKE^S172, SRC^Y530, CDK7^S164, and CDK1^T14. These networks depict intrinsic signal-regulation derived from EVs' phosphoproteins, providing a comprehensive and pathway-based strategy for in-depth lung cancer research.

中文翻译：

---

细胞外囊泡磷酸化蛋白质组学与多组学分析相结合揭示了肺癌的新型激酶网络

磷酸化调节蛋白质的功能，异常的磷酸化通常会导致多种疾病，包括癌症。细胞外囊泡 (EVs) 是微环境中的重要信使，它们的蛋白质组有助于癌症的发生和转移，而驱动 EVs 蛋白磷酸化的激酶则鲜为人知。来自 13 名非小细胞肺癌 (NSCLC) 患者的临床组织样本被用于分离癌症 EV 和邻近的正常 EV。通过定量磷酸化蛋白质组学分析，成功鉴定和量化了 1567 种蛋白质上的 2473 个磷酸化位点。因此，鉴定了 152 种激酶，其中 25 种表达差异。基于交互事件绑定扩散（TieDIE）算法，我们将来自 TCGA 的 NSCLC 的基因组和转录组数据集与我们的磷酸化蛋白质组数据集相结合，以构建信号网络。通过数据库整合和多组学富集分析，构建了一个由34个转录因子、33个激酶、63个异常基因和172个连接蛋白组成的234个节点、1599条边的紧凑网络。很少研究的磷酸化位点特别丰富。网络节点的关键磷蛋白在患者的 EV 中得到验证，包括 MAPK6 很少研究的磷酸化位点特别丰富。网络节点的关键磷蛋白在患者的 EV 中得到验证，包括 MAPK6 很少研究的磷酸化位点特别丰富。网络节点的关键磷蛋白在患者的 EV 中得到验证，包括 MAPK6^S189、IKBKE ^S172、SRC ^Y530、CDK7 ^S164和 CDK1 ^T14。这些网络描绘了源自 EV 磷蛋白的内在信号调节，为深入的肺癌研究提供了全面的基于通路的策略。