Generation of a double binary transgenic zebrafish model to study myeloid gene regulation in response to oncogene activation in melanocytes

• Main Authors: Amy Kenyon (Author), Daria Gavriouchkina (Author), Jernej Zorman (Author), Vanessa Chong-Morrison (Author), Giorgio Napolitani (Author), Vincenzo Cerundolo (Author), Tatjana Sauka-Spengler (Author)
• Format: Book
• Published: The Company of Biologists, 2018-04-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1754-8403; 1754-8411; 10.1242/dmm.030056
• Keywords: Biotagging; Macrophage; Melanocyte; Neutrophil; Oncogene; Zebrafish; Medicine; R; Pathology; RB1-214
• Source: Disease Models & Mechanisms, Vol 11, Iss 4 (2018)

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 (NRasQ61K, HRasG12V and KRasG12V) in melanocytes, leading to proliferation and changes in morphology of the melanocytes. This model was coupled to binary cell-specific biotagging models allowing in vivo 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 in vivo, 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.