Ahn Benjamin, Chou Charissa, Chou Caden, Chen Jennifer, Zug Amelia, Baykara Yigit, Claus Jessica, Hacking Sean M, Uzun Alper, Gamsiz Uzun Ece D
Department of Pathology and Laboratory Medicine, The Warren Alpert Medical School of Brown University, 593 Eddy Street, Providence, RI 02903, USA.
Department of Pathology and Laboratory Medicine, Rhode Island Hospital, 593 Eddy Street, Providence, RI 02903, USA.
NAR Cancer. 2025 Jan 15;7(1):zcae047. doi: 10.1093/narcan/zcae047. eCollection 2025 Mar.
Cancer is a complex disease with heterogeneous mutational and gene expression patterns. Subgroups of patients who share a phenotype might share a specific genetic architecture including protein-protein interactions (PPIs). We developed the Atlas of Protein-Protein Interactions in Cancer (APPIC), an interactive webtool that provides PPI subnetworks of 10 cancer types and their subtypes shared by cohorts of patients. To achieve this, we analyzed publicly available RNA sequencing data from patients and identified PPIs specific to 26 distinct cancer subtypes. APPIC compiles biological and clinical information from various databases, including the Human Protein Atlas, Hugo Gene Nomenclature Committee, g:Profiler, cBioPortal and Clue.io. The user-friendly interface allows for both 2D and 3D PPI network visualizations, enhancing the usability and interpretability of complex data. For advanced users seeking greater customization, APPIC conveniently provides all output files for further analysis and visualization on other platforms or tools. By offering comprehensive insights into PPIs and their role in cancer, APPIC aims to support the discovery of tumor subtype-specific novel targeted therapeutics and drug repurposing. APPIC is freely available at https://appic.brown.edu.
癌症是一种具有异质性突变和基因表达模式的复杂疾病。具有相同表型的患者亚组可能共享特定的遗传结构,包括蛋白质-蛋白质相互作用(PPI)。我们开发了癌症蛋白质-蛋白质相互作用图谱(APPIC),这是一个交互式网络工具,可提供10种癌症类型及其患者队列共享的亚型的PPI子网。为实现这一目标,我们分析了来自患者的公开可用RNA测序数据,并确定了26种不同癌症亚型特有的PPI。APPIC整合了来自多个数据库的生物学和临床信息,包括人类蛋白质图谱、Hugo基因命名委员会、g:Profiler、cBioPortal和Clue.io。用户友好的界面允许进行二维和三维PPI网络可视化,增强了复杂数据的可用性和可解释性。对于寻求更大定制性的高级用户,APPIC方便地提供所有输出文件,以便在其他平台或工具上进行进一步分析和可视化。通过全面洞察PPI及其在癌症中的作用,APPIC旨在支持发现肿瘤亚型特异性新型靶向疗法和药物再利用。可在https://appic.brown.edu免费获取APPIC。