Department of Molecular and Systems Biology, Dartmouth College, Hanover, New Hampshire.
Department of Medicine, Baylor College of Medicine, Houston, Texas.
Mol Cancer Res. 2021 Mar;19(3):414-428. doi: 10.1158/1541-7786.MCR-20-0526. Epub 2020 Nov 24.
c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type-specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant. IMPLICATIONS: By using cancer type-specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.
c-MYC（MYC）在超过 50%的所有癌症中失调。虽然 MYC 扩增是最常见的 MYC 失调事件，但许多其他改变也可以增加 MYC 的活性。因此，我们系统地研究了不同肿瘤类型中的 MYC 途径活性。我们使用逻辑回归框架，建立了基于转录组的肿瘤类型特异性 MYC 活性评分，可以准确捕捉 MYC 活性。我们表明，MYC 活性评分反映了多种调节 MYC 的机制，包括 MYCL 和/或 MYCN 扩增、MYC 启动子甲基化、MYC mRNA 表达、lncRNA PVT1 表达、MYC 突变和 MYC 基因座附近的病毒整合。我们的 MYC 活性评分整合了所有这些机制，与几种癌症类型中的 MYC 扩增状态、MYC 启动子甲基化和 MYC mRNA 表达相比，能更好地进行预后预测。此外，我们表明肿瘤增殖和免疫逃避可能是导致这种生存降低的原因。最后，我们开发了一种用于液体肿瘤的 MYC 活性特征，其中经常观察到 MYC 易位，这表明我们的方法可应用于不同类型的基因组改变。总之，我们开发了一种捕捉 MYC 途径活性且具有临床相关性的 MYC 活性评分。意义：通过使用肿瘤类型特异性的 MYC 活性谱，我们能够评估比以前研究更多的肿瘤类型中的 MYC 活性。我们的 MYC 活性评分所捕获的不同 MYC 相关改变的范围可用于促进未来 MYC 抑制剂的应用，并帮助医生为靶向治疗选择合适的患者。
