University of Oxford, Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford OX3 9DS, United Kingdom.
University of Oxford, Weatherall Institute of Molecular Medicine, MRC Human Immunology Unit, Radcliffe Department of Medicine, Oxford OX3 9DS, United Kingdom.
Dis Model Mech. 2018 Apr 6;11(4):dmm030056. doi: 10.1242/dmm.030056.
A complex network of inflammatory genes is closely linked to somatic cell transformation and malignant disease. Immune cells and their associated molecules are responsible for detecting and eliminating cancer cells as they establish themselves as the precursors of a tumour. By the time a patient has a detectable solid tumour, cancer cells have escaped the initial immune response mechanisms. Here, we describe the development of a double binary zebrafish model that enables regulatory programming of the myeloid cells as they respond to oncogene-activated melanocytes to be explored, focussing on the initial phase when cells become the precursors of cancer. A hormone-inducible binary system allows for temporal control of expression of different Ras oncogenes (, and ) in melanocytes, leading to proliferation and changes in morphology of the melanocytes. This model was coupled to binary cell-specific biotagging models allowing biotinylation and subsequent isolation of macrophage or neutrophil nuclei for regulatory profiling of their active transcriptomes. Nuclear transcriptional profiling of neutrophils, performed as they respond to the earliest precursors of melanoma , revealed an intricate landscape of regulatory factors that may promote progression to melanoma, including Serpinb1l4, Fgf1, Fgf6, Cathepsin H, Galectin 1 and Galectin 3. The model presented here provides a powerful platform to study the myeloid response to the earliest precursors of melanoma.
一个复杂的炎症基因网络与体细胞转化和恶性疾病密切相关。免疫细胞及其相关分子负责检测和消除癌细胞，因为它们是肿瘤前体。当患者出现可检测的实体瘤时，癌细胞已经逃脱了最初的免疫反应机制。在这里，我们描述了一种双二元斑马鱼模型的开发，该模型能够探索髓样细胞对致癌基因激活的黑素细胞的反应的调节编程，重点关注细胞成为癌症前体的初始阶段。激素诱导的双元系统允许在黑素细胞中时空控制不同 Ras 癌基因（NRAS、HRAS 和 KRAS）的表达，导致黑素细胞的增殖和形态变化。该模型与二元细胞特异性生物标记模型相结合，允许生物素化和随后分离巨噬细胞或中性粒细胞核，以对其活跃转录组进行调节分析。在对黑色素瘤最早前体做出反应时，对中性粒细胞进行核转录组分析，揭示了可能促进黑色素瘤进展的复杂调节因子景观，包括 Serpinb1l4、Fgf1、Fgf6、组织蛋白酶 H、半乳糖凝集素 1 和半乳糖凝集素 3。本文提出的模型为研究髓样细胞对黑色素瘤最早前体的反应提供了一个强大的平台。
