Davies Alexander E, Pargett Michael, Siebert Stefan, Gillies Taryn E, Choi Yongin, Tobin Savannah J, Ram Abhineet R, Murthy Vaibhav, Juliano Celina, Quon Gerald, Bissell Mina J, Albeck John G
Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA; Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA.
Cell Syst. 2020 Aug 26;11(2):161-175.e5. doi: 10.1016/j.cels.2020.07.004. Epub 2020 Jul 28.
Intratumoral heterogeneity is associated with aggressive tumor behavior, therapy resistance, and poor patient outcomes. Such heterogeneity is thought to be dynamic, shifting over periods of minutes to hours in response to signaling inputs from the tumor microenvironment. However, models of this process have been inferred from indirect or post-hoc measurements of cell state, leaving the temporal details of signaling-driven heterogeneity undefined. Here, we developed a live-cell model system in which microenvironment-driven signaling dynamics can be directly observed and linked to variation in gene expression. Our analysis reveals that paracrine signaling between two cell types is sufficient to drive continual diversification of gene expression programs. This diversification emerges from systems-level properties of the EGFR-RAS-ERK signaling cascade, including intracellular amplification of amphiregulin-mediated paracrine signals and differential kinetic filtering by target genes including Fra-1, c-Myc, and Egr1. Our data enable more precise modeling of paracrine-driven transcriptional variation as a generator of gene expression heterogeneity. A record of this paper's transparent peer review process is included in the Supplemental Information.
肿瘤内异质性与侵袭性肿瘤行为、治疗抗性及患者不良预后相关。这种异质性被认为是动态的，会在数分钟到数小时的时间内，响应肿瘤微环境的信号输入而发生变化。然而，该过程的模型是从细胞状态的间接或事后测量中推断出来的，信号驱动的异质性的时间细节仍不明确。在此，我们开发了一种活细胞模型系统，在该系统中可以直接观察微环境驱动的信号动态，并将其与基因表达的变化联系起来。我们的分析表明，两种细胞类型之间的旁分泌信号足以驱动基因表达程序的持续多样化。这种多样化源自EGFR-RAS-ERK信号级联的系统水平特性，包括双调蛋白介导的旁分泌信号的细胞内放大以及包括Fra-1、c-Myc和Egr1在内的靶基因的差异动力学过滤。我们的数据能够更精确地模拟旁分泌驱动的转录变异，将其作为基因表达异质性的一个成因。本文透明的同行评审过程记录包含在补充信息中。
