Dong Qun, Shen Danqing, Ye Jiachen, Chen Jiaxin, Li Jing
Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
iScience. 2024 Sep 27;27(11):111060. doi: 10.1016/j.isci.2024.111060. eCollection 2024 Nov 15.
Protein phosphorylation is a crucial post-translational modification implicated in cancer pathogenesis, offering potential diagnostic and therapeutic targets. Here, we developed PhosCancer, a user-friendly database for extracting biologically and clinically relevant insights from phosphoproteomics data. Leveraging data from the CNHPP and CPTAC, PhosCancer encompasses 174,587 phosphosites from 14 datasets spanning 12 cancer types. Through extensive statistical analyses and integration of annotations from external resources, PhosCancer serves as a convenient one-stop platform facilitating the exploration of phosphorylation profiles across different cancer types. Not only does PhosCancer encompass basic information, 3D structure, functional domains, and upstream kinases, but also provides quantitative associations with nine clinical features, and the relevance with hallmarks in both cancer-specific and pan-cancer views. PhosCancer is a valuable resource for cancer researchers and clinicians, promoting the identification of clinically actionable biomarkers and further facilitating the clinical applications of phosphoproteomic data.
蛋白质磷酸化是一种关键的翻译后修饰，与癌症发病机制相关，提供了潜在的诊断和治疗靶点。在此，我们开发了PhosCancer，这是一个用户友好的数据库，用于从磷酸化蛋白质组学数据中提取生物学和临床相关见解。利用来自CNHPP和CPTAC的数据，PhosCancer涵盖了来自12种癌症类型的14个数据集的174,587个磷酸化位点。通过广泛的统计分析和整合来自外部资源的注释，PhosCancer作为一个便捷的一站式平台，有助于探索不同癌症类型的磷酸化谱。PhosCancer不仅包含基本信息、三维结构、功能域和上游激酶，还提供与九种临床特征的定量关联，以及在癌症特异性和泛癌视角下与癌症特征的相关性。PhosCancer是癌症研究人员和临床医生的宝贵资源，促进了临床可操作生物标志物的识别，并进一步推动了磷酸化蛋白质组学数据的临床应用。
