美国斯隆凯特林研究所Gabriela Chiosis 和Mark P.S. Dunphy课题组合作，建立了针对大型蛋白复合体（epichaperome）治疗癌症的精准医学方法。相关论文10月24日在线发表于国际学术期刊《癌细胞》。

研究人员利用成像探针选择动力学特性来可视化并测量epichaperome，这是一种病理性蛋白与蛋白相互作用网络。通过使用针对病人肿瘤单一病灶的抑制剂，研究人员可以实时分析和影像化癌症中大型蛋白复合体网络及其功能。研究人员还证明了单个肿瘤水平上的定量评估可用于优化剂量和时间选择。因此，该研究为靶向蛋白质网络异常的精准医学提供了临床前和临床证据。

据了解，蛋白质与蛋白质相互作用网络的改变是肿瘤恶性转化的标志，但目前尚未有针对蛋白质互作网络的诊断工具。

附：英文原文

Title: Paradigms for Precision Medicine in Epichaperome Cancer Therapy

Author: Nagavarakishore Pillarsetty, Komal Jhaveri, Tony Taldone, Eloisi Caldas-Lopes, Blesida Punzalan, Suhasini Joshi, Alexander Bolaender, Mohammad M. Uddin, Anna Rodina, Pengrong Yan, Anson Ku, Thomas Ku, Smit K. Shah, Serge Lyashchenko, Eva Burnazi, Tai Wang, Nicolas Lecomte, Yelena Janjigian, Anas Younes, Connie W. Batlevi, Monica L. Guzman, Gail J. Roboz, Jacek Koziorowski, Pat Zanzonico, Mary L. Alpaugh, Adriana Corben, Shanu Modi, Larry Norton, Steven M. Larson, Jason S. Lewis, Gabriela Chiosis, John F. Gerecitano, Mark P.S. Dunphy

Issue&Volume: 2019/10/24

Abstract: Alterations in protein-protein interaction networks are at the core of malignant transformation but have yet to be translated into appropriate diagnostic tools. We make use of the kinetic selectivity properties of an imaging probe to visualize and measure the epichaperome, a pathologic protein-protein interaction network. We are able to assay and image epichaperome networks in cancer and their engagement by inhibitor in patients' tumors at single-lesion resolution in real time, and demonstrate that quantitative evaluation at the level of individual tumors can be used to optimize dose and schedule selection. We thus provide preclinical and clinical evidence in the use of this theranostic platform for precision medicine targeting of the aberrant properties of protein networks.

DOI: 10.1016/j.ccell.2019.09.007

Source: https://www.cell.com/cancer-cell/fulltext/S1535-6108(19)30427-1