Wrobel John A, Xie Ling, Wang Li, Liu Cui, Rashid Naim, Gallagher Kristalyn K, Xiong Yan, Konze Kyle D, Jin Jian, Gatza Michael L, Chen Xian
Department of Biochemistry & Biophysics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Department of Biochemistry & Biophysics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
iScience. 2019 Jul 26;17:359-378. doi: 10.1016/j.isci.2019.07.001. Epub 2019 Jul 4.
Proliferative and invasive breast tumors evolve heterogeneously in individual patients, posing significant challenges in identifying new druggable targets for precision, effective therapy. Here we present a functional multi-omics method, interaction-Correlated Multi-omic Aberration Patterning (iC-MAP), which dissects intra-tumor heterogeneity and identifies in situ the oncogenic consequences of multi-omics aberrations that drive proliferative and invasive tumors. First, we perform chromatin activity-based chemoproteomics (ChaC) experiments on breast cancer (BC) patient tissues to identify genetic/transcriptomic alterations that manifest as oncogenically active proteins. ChaC employs a biotinylated small molecule probe that specifically binds to the oncogenically active histone methyltransferase G9a, enabling sorting/enrichment of a G9a-interacting protein complex that represents the predominant BC subtype in a tissue. Second, using patient transcriptomic/genomic data, we retrospectively identified some G9a interactor-encoding genes that showed individualized iC-MAP. Our iC-MAP findings represent both new diagnostic/prognostic markers to identify patient subsets with incurable metastatic disease and targets to create individualized therapeutic strategies.
增殖性和侵袭性乳腺肿瘤在个体患者中异质性地演变，这给识别用于精准、有效治疗的新的可药物作用靶点带来了重大挑战。在此，我们提出一种功能性多组学方法——相互作用相关多组学畸变模式分析（iC-MAP），该方法剖析肿瘤内异质性，并原位识别驱动增殖性和侵袭性肿瘤的多组学畸变的致癌后果。首先，我们对乳腺癌（BC）患者组织进行基于染色质活性的化学蛋白质组学（ChaC）实验，以识别表现为致癌活性蛋白的遗传/转录组改变。ChaC使用一种生物素化小分子探针，该探针特异性结合致癌活性组蛋白甲基转移酶G9a，从而能够分选/富集代表组织中主要BC亚型的G9a相互作用蛋白复合物。其次，利用患者转录组/基因组数据，我们回顾性地鉴定了一些显示个体化iC-MAP的G9a相互作用因子编码基因。我们的iC-MAP研究结果既代表了用于识别患有无法治愈的转移性疾病患者亚组的新诊断/预后标志物，也代表了用于制定个体化治疗策略的靶点。
